@article {585, title = {Relationship of plasmin generation to cardiovascular disease risk factors in elderly men and women.}, journal = {Arterioscler Thromb Vasc Biol}, volume = {19}, year = {1999}, month = {1999 Mar}, pages = {499-504}, abstract = {

Plasmin-alpha2-antiplasmin complex (PAP) marks plasmin generation and fibrinolytic balance. We recently observed that elevated levels of PAP predict acute myocardial infarction in the elderly, yet little is known about the correlates of PAP. We measured PAP in 800 elderly subjects who were free of clinical cardiovascular disease in 2 cohort studies: the Cardiovascular Health Study and the Honolulu Heart Program. Median PAP levels did not differ between the Cardiovascular Health Study (6.05+/-1.46 nmol/L) and the Honolulu Heart Program (6.11+/-1.44 nmol/L), and correlates of PAP were similar in both cohorts. In CHS, PAP levels increased with age (r=0. 30), procoagulant factors (eg, factor VIIc, r=0.15), thrombin activity (prothrombin fragment F1+2, r=0.29), and inflammation-sensitive proteins (eg, fibrinogen, r=0.44; factor VIIIc, r=0.37). PAP was associated with increased atherosclerosis as measured by the ankle-arm index (AAI) (P for trend, }, keywords = {Aged, Aged, 80 and over, alpha-2-Antiplasmin, Antifibrinolytic Agents, Asian Continental Ancestry Group, Cohort Studies, Coronary Disease, Diabetes Mellitus, Type 2, European Continental Ancestry Group, Female, Fibrinolysin, Fibrinolysis, Humans, Insulin Resistance, Male, Multivariate Analysis, Myocardial Infarction, Plasminogen Activator Inhibitor 1, Risk Factors}, issn = {1079-5642}, doi = {10.1161/01.atv.19.3.499}, author = {Sakkinen, P A and Cushman, M and Psaty, B M and Rodriguez, B and Boineau, R and Kuller, L H and Tracy, R P} } @article {611, title = {Diabetes mellitus: subclinical cardiovascular disease and risk of incident cardiovascular disease and all-cause mortality.}, journal = {Arterioscler Thromb Vasc Biol}, volume = {20}, year = {2000}, month = {2000 Mar}, pages = {823-9}, abstract = {

Previously diagnosed diabetes mellitus, newly diagnosed diabetes mellitus, and impaired glucose tolerance are important determinants of the risk of clinical cardiovascular disease (CVD). We have evaluated the relation of patients with subclinical CVD, diabetes, and impaired glucose tolerance and "normal" subjects and the risk of clinical CVD in the Cardiovascular Health Study. Diabetes (1343), impaired glucose tolerance (1433), and normal (2421) were defined by World Health Organization criteria at baseline in 1989 to 1990. The average follow-up was 6.4 years (mean age 73 years). Diabetics had a higher prevalence of clinical and subclinical CVD at baseline. Compared with diabetes in the absence of subclinical disease, the presence of subclinical CVD and diabetes was associated with significant increased adjusted relative risk of death (1.5, CI 0.93 to 2.41), relative risk of incident coronary heart disease (1.99, CI 1.25 to 3.19), and incident myocardial infarction (1.93, CI 0.96 to 3.91). The risk of clinical events was greater for participants with a history of diabetes compared with newly diagnosed diabetics at baseline. Compared with nondiabetic nonhypertensive subjects without subclinical disease, patients with a combination of diabetes, hypertension, and subclinical disease had a 12-fold increased risk of stroke. Fasting blood glucose levels were a weak predictor of incident coronary heart disease as were most other risk factors. Subclinical CVD was the primary determinant of clinical CVD among diabetics in the Cardiovascular Health Study.

}, keywords = {Aged, Arteriosclerosis, Coronary Disease, Diabetes Mellitus, Type 1, Diabetes Mellitus, Type 2, Diabetic Angiopathies, Female, Humans, Incidence, Male, Multivariate Analysis, Myocardial Infarction, Prevalence, Proportional Hazards Models, Risk Factors, Sex Distribution, Stroke}, issn = {1079-5642}, doi = {10.1161/01.atv.20.3.823}, author = {Kuller, L H and Velentgas, P and Barzilay, J and Beauchamp, N J and O{\textquoteright}Leary, D H and Savage, P J} } @article {606, title = {Evidence of islet cell autoimmunity in elderly patients with type 2 diabetes.}, journal = {Diabetes}, volume = {49}, year = {2000}, month = {2000 Jan}, pages = {32-8}, abstract = {

In light of an occurring growth of elderly people affected by type 2 diabetes and recent observations indicating that type 2 diabetes may be a disease of the innate immune system, we evaluated whether signs of islet cell autoimmunity are associated with an abnormal glucose control, the presence of insulin requirement, or an activation of the acute-phase response in older individuals with type 2 diabetes. GAD65 and IA-2 autoantibodies along with the acute-phase response markers fibrinogen and C-reactive protein were tested in 196 serum samples from patients with type 2 diabetes and in 94 nondiabetic control subjects over the age of 65 years from the Pittsburgh cohort of the Cardiovascular Health Study. Of the diabetic patients, 12\% (24 of 196) had autoantibodies against GAD65 and/or IA-2, a prevalence significantly higher than that found in nondiabetic individuals (1 of 94, 1.1\%; P = 0.001). Type 2 diabetic patients who were positive for GAD65 and/or IA-2 autoantibodies (Ab+), as compared with those negative for these autoantibodies (Ab-), had an abnormal oral glucose tolerance test (OGTT) (P = 0.03) before and a higher frequency of oral hypoglycemic treatment (P = 0.003) at the time of autoantibody testing. No differences were seen in the percentage of insulin requirement in the two groups. Moreover, a statistically significant increase in fibrinogen (P = 0.005) and C-reactive protein levels (P = 0.025) was found in type 2 diabetic patients with high levels of GAD65 and/or IA-2 autoantibodies as compared with Ab-patients and control subjects. In conclusion, in type 2 diabetic subjects > or =65 years old, the presence of islet cell autoimmunity is associated with an impairment of the acute-phase insulin secretion, as revealed by an OGTT. A pronounced activation of the acute-phase response, found to be associated with islet cell autoimmunity, may in part explain this defect in insulin secretion. These findings not only have direct implications for adequate classification and treatment of diabetes in the elderly, but also for understanding the autoimmune/inflammatory mechanisms involved in the pathogenesis of hyperglycemia.

}, keywords = {Aged, Aged, 80 and over, Aging, Autoantibodies, Autoantigens, Autoimmunity, Blood Glucose, C-Reactive Protein, Diabetes Mellitus, Type 2, Female, Fibrinogen, Glucose Tolerance Test, Glutamate Decarboxylase, Humans, Islets of Langerhans, Male, Membrane Proteins, Protein Tyrosine Phosphatases, Receptor-Like Protein Tyrosine Phosphatases, Class 8}, issn = {0012-1797}, doi = {10.2337/diabetes.49.1.32}, author = {Pietropaolo, M and Barinas-Mitchell, E and Pietropaolo, S L and Kuller, L H and Trucco, M} } @article {652, title = {Prevalence of clinical and isolated subclinical cardiovascular disease in older adults with glucose disorders: the Cardiovascular Health Study.}, journal = {Diabetes Care}, volume = {24}, year = {2001}, month = {2001 Jul}, pages = {1233-9}, abstract = {

OBJECTIVE: Clinical cardiovascular disease (CVD) is highly prevalent among people with diabetes. However, there is little information regarding the prevalence of subclinical CVD and its relation to clinical CVD in diabetes and in the glucose disorders that precede diabetes.

RESEARCH DESIGN AND METHODS: Participants in the Cardiovascular Health Study, aged > or = 65 years (n = 5,888), underwent vascular and metabolic testing. Individuals with known disease in the coronary, cerebral, or peripheral circulations were considered to have clinical disease. Those without any clinical disease in whom CVD was detected by ultrasonography, electrocardiography, or ankle arm index in any of the three vascular beds were considered to have isolated subclinical disease.

RESULTS: Approximately 30\% of the cohort had clinical disease, and approximately 60\% of the remainder had isolated subclinical disease. In those with normal glucose status, isolated subclinical disease made up most of the total CVD. With increasing glucose severity, the proportion of total CVD that was clinical disease increased; 75\% of men and 66\% of women with normal fasting glucose status had either clinical or subclinical CVD. Among those with known diabetes, the prevalence was approximately 88\% (odds ratio [OR] 2.46 for men and 4.22 for women, P < 0.0001). There were intermediate prevalences and ORs for those with impaired fasting glucose status and newly diagnosed diabetes.

CONCLUSIONS: Isolated subclinical CVD is common among older adults. Glucose disorders are associated with an increased prevalence of total CVD and an increased proportion of clinical disease relative to subclinical disease.

}, keywords = {Aged, Angina Pectoris, Cardiovascular Diseases, Cerebrovascular Disorders, Cohort Studies, Diabetes Mellitus, Diabetes Mellitus, Type 1, Diabetes Mellitus, Type 2, Electrocardiography, Female, Glucose Intolerance, Heart Diseases, Humans, Male, Peripheral Vascular Diseases, Prevalence, United States}, issn = {0149-5992}, doi = {10.2337/diacare.24.7.1233}, author = {Barzilay, J I and Spiekerman, C F and Kuller, L H and Burke, G L and Bittner, V and Gottdiener, J S and Brancati, F L and Orchard, T J and O{\textquoteright}Leary, D H and Savage, P J} } @article {674, title = {The relation of atherosclerotic cardiovascular disease to retinopathy in people with diabetes in the Cardiovascular Health Study.}, journal = {Br J Ophthalmol}, volume = {86}, year = {2002}, month = {2002 Jan}, pages = {84-90}, abstract = {

AIMS: To describe the association of retinopathy with atherosclerosis and atherosclerotic risk factors in people with diabetes.

METHODS: 296 of the 558 people classified as having diabetes by the American Diabetes Association criteria, from a population based cohort of adults (ranging in age from 69 to 102 years) living in four United States communities (Allegheny County, Pennsylvania; Forsyth County, North Carolina; Sacramento County, California; and Washington County, Maryland) were studied from 1997 to 1998. Lesions typical of diabetic retinopathy were determined by grading a 45 degrees colour fundus photograph of one eye of each participant, using a modification of the Airlie House classification system.

RESULTS: Retinopathy was present in 20\% of the diabetic cohort, with the lowest prevalence (16\%), in those 80 years of age or older. Retinopathy was detected in 20.3\% of the 296 people with diabetes; 2.7\% of the 296 had signs of proliferative retinopathy and 2.1\% had signs of macular oedema. The prevalence of diabetic retinopathy was higher in black people (35.4\%) than white (16.0\%). Controlling for age, sex, and blood glucose, retinopathy was more frequent in black people than white (odds ratio (OR) 2.26, 95\% confidence interval (CI) 1.01, 5.05), in those with longer duration of diabetes (OR (per 5 years of diabetes) 1.42, 95\% CI 1.18, 1.70), in those with subclinical cardiovascular disease (OR 1.49, 95\% CI 0.51, 4.31), or coronary heart disease or stroke (OR 3.23, 95\% CI 1.09, 9.56) than those without those diseases, in those with higher plasma low density lipoprotein (LDL) cholesterol (OR (per 10 mg/dl of LDL cholesterol) 1.12, 95\% CI 1.02, 1.23), and in those with gross proteinuria (OR 4.76, 95\% CI 1.53, 14.86).

CONCLUSION: Data from this population based study suggest a higher prevalence of retinopathy in black people than white people with diabetes and the association of cardiovascular disease, elevated plasma LDL cholesterol, and gross proteinuria with diabetic retinopathy. However, any conclusions or explanations regarding associations described here must be made with caution because only about one half of those with diabetes mellitus were evaluated.

}, keywords = {Age of Onset, Aged, Aged, 80 and over, Arteriosclerosis, Black People, Blood Pressure, Cohort Studies, Diabetes Mellitus, Type 2, Diabetic Retinopathy, Female, Humans, Longitudinal Studies, Male, Odds Ratio, Prospective Studies, Regression Analysis, Risk Factors, Time Factors, White People}, issn = {0007-1161}, doi = {10.1136/bjo.86.1.84}, author = {Klein, Ronald and Marino, Emily K and Kuller, Lewis H and Polak, Joseph F and Tracy, Russell P and Gottdiener, John S and Burke, Gregory L and Hubbard, Larry D and Boineau, Robin} } @article {725, title = {The 6-min walk test: a quick measure of functional status in elderly adults.}, journal = {Chest}, volume = {123}, year = {2003}, month = {2003 Feb}, pages = {387-98}, abstract = {

OBJECTIVES: To determine the correlates of the total 6-min walk distance (6MWD) in a population sample of adults > or = 68 years old.

METHODS: The standardized 6-min walk test (6MWT) was administered to the Cardiovascular Health Study cohort during their seventh annual examination.

RESULTS: Of the 3,333 participants with a clinic visit, 2,281 subjects (68\%) performed the 6MWT. There were no untoward events. The mean 6MWD was 344 m (SD, 88 m). Independent general correlates of a shorter 6MWD in linear regression models in women and men included the following: older age, higher weight, larger waist, weaker grip strength, symptoms of depression, and decreased mental status. Independent disease or risk factor correlates of a shorter 6MWD included the following: a low ankle BP, use of angiotensin-converting enzyme inhibitors, and arthritis in men and women; higher C-reactive protein, diastolic hypertension, and lower FEV(1) in women; and the use of digitalis in men. Approximately 30\% of the variance in 6MWD was explained by the linear regression models. Newly described bivariate associations of a shorter 6MWD included impaired activities of daily living; self-reported poor health; less education; nonwhite race; a history of coronary heart disease, transient ischemic attacks, stroke, or diabetes; and higher levels of C-reactive protein, fibrinogen, or WBC count.

CONCLUSIONS: Most community-dwelling elderly persons can quickly and safely perform this functional status test in the outpatient clinic setting. The test may be used clinically to measure the impact of multiple comorbidities, including cardiovascular disease, lung disease, arthritis, diabetes, and cognitive dysfunction and depression, on exercise capacity and endurance in older adults. Expected values should be adjusted for the patient{\textquoteright}s age, gender, height, and weight.

}, keywords = {Activities of Daily Living, Aged, Aged, 80 and over, Cardiovascular Diseases, Cohort Studies, Coronary Disease, Cross-Sectional Studies, Diabetes Mellitus, Type 2, Exercise Test, Female, Humans, Ischemic Attack, Transient, Linear Models, Male, Mass Screening, Sensitivity and Specificity, Stroke, United States, Walking}, issn = {0012-3692}, doi = {10.1378/chest.123.2.387}, author = {Enright, Paul L and McBurnie, Mary Ann and Bittner, Vera and Tracy, Russell P and McNamara, Robert and Arnold, Alice and Newman, Anne B} } @article {800, title = {Sleep-disordered breathing, glucose intolerance, and insulin resistance: the Sleep Heart Health Study.}, journal = {Am J Epidemiol}, volume = {160}, year = {2004}, month = {2004 Sep 15}, pages = {521-30}, abstract = {

Clinic-based studies suggest that sleep-disordered breathing (SDB) is associated with glucose intolerance and insulin resistance. However, in the available studies, researchers have not rigorously controlled for confounding variables to assess the independent relation between SDB and impaired glucose metabolism. The objective of this study was to determine whether SDB was associated with glucose intolerance and insulin resistance among community-dwelling subjects (n=2,656) participating in the Sleep Heart Health Study (1994-1999). SDB was characterized with the respiratory disturbance index and measurements of oxygen saturation during sleep. Fasting and 2-hour glucose levels measured during an oral glucose tolerance test were used to assess glycemic status. Relative to subjects with a respiratory disturbance index of less than 5.0 events/hour (the reference category), subjects with mild SDB (5.0-14.9 events/hour) and moderate to severe SDB (> or =15 events/hour) had adjusted odds ratios of 1.27 (95\% confidence interval: 0.98, 1.64) and 1.46 (95\% confidence interval: 1.09, 1.97), respectively, for fasting glucose intolerance (p for trend < 0.01). Sleep-related hypoxemia was also associated with glucose intolerance independently of age, gender, body mass index, and waist circumference. The results of this study suggest that SDB is independently associated with glucose intolerance and insulin resistance and may lead to type 2 diabetes mellitus.

}, keywords = {Aged, Blood Gas Analysis, Body Constitution, Body Mass Index, Cohort Studies, Confounding Factors, Epidemiologic, Cross-Sectional Studies, Diabetes Mellitus, Type 2, Fasting, Female, Glucose Intolerance, Glucose Tolerance Test, Humans, Insulin Resistance, Linear Models, Male, Middle Aged, Multivariate Analysis, Oxyhemoglobins, Polysomnography, Research Design, Risk Factors, Severity of Illness Index, Sleep Apnea Syndromes}, issn = {0002-9262}, doi = {10.1093/aje/kwh261}, author = {Punjabi, Naresh M and Shahar, Eyal and Redline, Susan and Gottlieb, Daniel J and Givelber, Rachel and Resnick, Helaine E} } @article {898, title = {The prevalence of the 65-kilodalton isoform of glutamic acid decarboxylase autoantibodies by glucose tolerance status in elderly patients from the cardiovascular health study.}, journal = {J Clin Endocrinol Metab}, volume = {91}, year = {2006}, month = {2006 Aug}, pages = {2871-7}, abstract = {

CONTEXT: Autoantibodies (AA) to glutamic acid decarboxylase (GAD65), a determinant of risk for autoimmune diabetes, have been found in up to 10\% of patients with type 2 diabetes. In older adults, this marker may also serve as a determinant of risk for autoimmune diabetes and enhance diabetes classification.

OBJECTIVE: The objective of this study was to evaluate the relationship between GAD65AA and glucose tolerance status, current diabetes treatment, and clinical measures in older adults.

DESIGN: GAD65AA were measured at baseline in 3318 participants from the Cardiovascular Health Study, a cohort study of 5888 individuals 65 or older.

SETTING: The population-based cohort was recruited from four U.S. sites.

PATIENTS: Patients included all Cardiovascular Health Study participants with known diabetes, newly diagnosed diabetes, impaired fasting glucose, impaired glucose tolerance, and a sample of normal glucose-tolerant participants.

MAIN OUTCOME MEASURES: GAD65AA, body mass index, fasting glucose and insulin levels, blood pressure, lipid levels, and diabetes treatment at baseline were measured.

RESULTS: The prevalence of GAD65AA increased with decreasing glucose tolerance in both Blacks (n = 560) and Whites (n = 2730), being more pronounced in known diabetic individuals. GAD65AA were found in 2.3, 5.8, 7.8, and 8.3\% of diabetic participants, reporting use of no diabetes medication, oral hypoglycemic agents, insulin only, and both oral hypoglycemic agents and insulin, respectively (P = 0.02, linear trend). Among diabetic participants, GAD65AA positivity was associated with diabetes treatment, higher fasting glucose, and lower body mass index.

CONCLUSIONS: Even among older individuals with diabetes, GAD65AA may be a useful marker in identifying a subgroup of autoimmune diabetes, serve as a marker of insulin requirement, and remain stable over years.

}, keywords = {Aged, Aging, Autoantibodies, Blood Glucose, Blood Pressure, Cardiovascular Diseases, Cohort Studies, Diabetes Mellitus, Type 2, Fasting, Female, Glucose Intolerance, Glutamate Decarboxylase, Humans, Insulin, Isoenzymes, Lipids, Logistic Models, Male, Nutrition Surveys}, issn = {0021-972X}, doi = {10.1210/jc.2005-2667}, author = {Barinas-Mitchell, Emma and Kuller, Lewis H and Pietropaolo, Susan and Zhang, Ying-Jian and Henderson, Tyona and Pietropaolo, Massimo} } @article {971, title = {Alcohol consumption and type 2 diabetes among older adults: the Cardiovascular Health Study.}, journal = {Obesity (Silver Spring)}, volume = {15}, year = {2007}, month = {2007 Jul}, pages = {1758-65}, abstract = {

OBJECTIVE: The objective was to examine the role of total and beverage-specific alcohol consumption on the incidence of type 2 diabetes mellitus (DM) among elderly men and women.

RESEARCH METHODS AND PROCEDURES: We studied prospectively 4655 participants of the Cardiovascular Health Study who were free of DM at baseline. Alcohol consumption was obtained at baseline and during follow-up examinations. DM was defined using fasting glucose and/or use of hypoglycemic medications. We used Cox proportional hazard models to estimate adjusted relative risks of diabetes across alcohol categories.

RESULTS: During a mean follow-up of 6.3 years, 234 incident cases of DM were documented. Compared with never drinkers, hazard ratios [95\% confidence interval (CI)] for DM were 0.7 (0.3 to 1.4), 0.5 (0.3 to 0.9), 0.6 (0.4 to 1.1), and 0.8 (0.4 to 1.3) for former drinkers and current drinkers of <1, 1 to 6, and 7+ drinks per week, respectively, for men after adjustment for age, BMI, education, and smoking. Corresponding values for women were 1.2 (0.6 to 2.3), 0.7 (0.4 to 1.1), 0.6 (0.3 to 1.1), and 0.4 (0.2 to 1.0), respectively. A reduced risk of DM was observed with all types of beverage consumed. Similar findings were observed when we repeated the above analyses using simple or weighted cumulative alcohol update and covariates over time.

DISCUSSION: Light to moderate alcohol consumption was associated with a lower incidence of DM among elderly people, irrespective of the type of beverage consumed.

}, keywords = {Aged, Aged, 80 and over, Alcohol Drinking, Diabetes Mellitus, Type 2, Female, Follow-Up Studies, Humans, Incidence, Longitudinal Studies, Male, Medicare, Middle Aged, Risk, Smoking, Temperance, United States}, issn = {1930-7381}, doi = {10.1038/oby.2007.209}, author = {Djouss{\'e}, Luc and Biggs, Mary L and Mukamal, Kenneth J and Siscovick, David S} } @article {961, title = {Longitudinal association between depressive symptoms and incident type 2 diabetes mellitus in older adults: the cardiovascular health study.}, journal = {Arch Intern Med}, volume = {167}, year = {2007}, month = {2007 Apr 23}, pages = {802-7}, abstract = {

BACKGROUND: Prospective studies indicate that a single self-report of high depressive symptoms is associated with an increased risk of developing type 2 diabetes mellitus.

METHODS: We tested whether a single report of high depressive symptoms, an increase in depressive symptoms, or persistently high depressive symptoms over time were associated with the development of diabetes in adults 65 years and older. Participants from the Cardiovascular Health Study completed the 10-item Center for Epidemiological Studies-Depression Scale (CES-D) annually from 1989 to 1999. A single report of high depressive symptoms (CES-D score, >/=8), an increase in symptoms during follow-up (>/=5 from baseline), and persistently high symptoms (2 consecutive scores >/=8) were each studied in relation to incident diabetes, defined by initiation of diabetes control medications among participants who were free from diabetes at baseline (n = 4681).

RESULTS: The mean CES-D score at baseline was 4.5 (SD, 4.5). The incidence rate of diabetes was 4.4 per 1000 person-years. Following adjustment for baseline demographic characteristics and measures of physical activity, smoking, alcohol intake, body mass index, and C-reactive protein during follow-up, each measure of depressive symptoms was significantly associated with incident diabetes (high baseline CES-D score: hazard ratio, 1.6 [95\% confidence interval, 1.1-2.3]; CES-D score increase: hazard ratio, 1.5 [95\% confidence interval, 1.1-2.2]; and persistently high symptoms: hazard ratio, 1.5 [95\% confidence interval, 1.1-2.3]).

CONCLUSION: Older adults who reported higher depressive symptoms were more likely to develop diabetes than their counterparts; this association was not fully explained by risk factors for diabetes.

}, keywords = {Aged, Body Mass Index, C-Reactive Protein, Depression, Diabetes Mellitus, Type 2, Drinking, Female, Humans, Longitudinal Studies, Male, Smoking}, issn = {0003-9926}, doi = {10.1001/archinte.167.8.802}, author = {Carnethon, Mercedes R and Biggs, Mary L and Barzilay, Joshua I and Smith, Nicholas L and Vaccarino, Viola and Bertoni, Alain G and Arnold, Alice and Siscovick, David} } @article {1009, title = {Enhanced risk for Alzheimer disease in persons with type 2 diabetes and APOE epsilon4: the Cardiovascular Health Study Cognition Study.}, journal = {Arch Neurol}, volume = {65}, year = {2008}, month = {2008 Jan}, pages = {89-93}, abstract = {

BACKGROUND: Diabetes and the apolipoprotein E epsilon4 allele (APOE epsilon4) increase the risk for Alzheimer disease (AD). We hypothesize that APOE epsilon4 may modify the risk for AD in individuals with diabetes.

OBJECTIVE: To examine the joint effect of type 2 diabetes and APOE epsilon4 on the risk of AD, AD with vascular dementia (mixed AD), and vascular dementia without AD.

DESIGN: The Cardiovascular Health Study (CHS) Cognition Study (1992-2000) is a prospective study designed to identify all existing and new cases of dementia among study participants. Diagnoses were made according to international criteria for dementia and subtypes. There were 2547 dementia-free participants in the CHS Cognition Study cohort with complete information on APOE epsilon4 and type 2 diabetes status; among these, 411 new cases of dementia developed. Risk of dementia was estimated with a Cox proportional hazard model adjusted for age and other demographic and cardiovascular risk factors.

RESULTS: Compared with those who had neither type 2 diabetes nor APOE epsilon4, those with both factors had a significantly higher risk of AD (hazard ratio, 4.58; 95\% confidence interval, 2.18-9.65) and mixed AD (hazard ratio, 3.89; 95\% confidence interval, 1.46-10.40).

CONCLUSION: These data suggest that having both diabetes and APOE epsilon4 increases the risk of dementia, especially for AD and mixed AD.

}, keywords = {African Americans, Age Factors, Aged, Alzheimer Disease, Apolipoprotein E4, Cognition, Cohort Studies, Confidence Intervals, Dementia, Vascular, Diabetes Mellitus, Type 2, European Continental Ancestry Group, Female, Genotype, Humans, Longitudinal Studies, Male, Neuropsychological Tests, Proportional Hazards Models, Prospective Studies, Risk Factors, Sex Factors}, issn = {0003-9942}, doi = {10.1001/archneurol.2007.29}, author = {Irie, Fumiko and Fitzpatrick, Annette L and Lopez, Oscar L and Kuller, Lewis H and Peila, Rita and Newman, Anne B and Launer, Lenore J} } @article {1043, title = {Fasting glycemia in sleep disordered breathing: lowering the threshold on oxyhemoglobin desaturation.}, journal = {Sleep}, volume = {31}, year = {2008}, month = {2008 Jul}, pages = {1018-24}, abstract = {

STUDY OBJECTIVES: Commonly used definitions of sleep-disordered breathing (SDB) are based on identifying discrete events of breathing abnormalities during sleep that are accompanied by an oxyhemoglobin desaturation (delta SaO2) of at least 4\%. However, it is not known whether disordered breathing events with oxyhemoglobin desaturation less than 4\% are associated with clinical sequelae such as abnormalities in fasting glycemia.

DESIGN: Cross-sectional study.

SUBJECTS AND SETTING: Participants from the Sleep Heart Health Study (SHHS) with a fasting glucose measurement made within a year of the baseline polysomnogram.

MEASUREMENTS AND RESULTS: SDB severity was defined using the apnea-hypopnea index (AHI) and the hypopnea index (HI) by counting events with different levels of oxyhemoglobin desaturation (0.0\%-1.9\%, 2.0\%-2.9\%, 3.0\%-3.9\%, > or = 4.0\%). Fasting glucose levels were used to classify individuals into normal (<100 mg/dL), impaired (100-125 mg/dL), and diabetic (> or = 126 mg/dL) groups. Ordinal logistic regression was used to determine the adjusted relative odds of an abnormal glucose value across quartiles of the hypopnea index, independent of factors such as age, body mass index, waist circumference, and usual sleep duration. The prevalence of impaired and diabetic fasting glucose in the analytical sample was 32.9\% and 5.8\%, respectively. The covariate-adjusted relative odds of impaired or diabetic fasting glucose in the highest versus the lowest AHI quartile was 1.35 (95\% CI: 1.04-1.76) for events with a delta SaO2 > or = 4.0\%, 1.72 (95\% CI: 1.20-2.48) for events with a delta SaO2 between 3.0\%-3.9\%, 1.41 (95\% CI: 1.07-1.86) for events with a delta SaO2 between 2.0\%-2.9\%, and 1.07 (95\% CI: 0.84-1.37) for events with a delta SaO2 between 0.0\%-1.9\%. The corresponding odds ratios for the HI were 1.47 (95\% CI: 1.13-1.92), 2.25 (95\% CI: 1.59-3.19), 1.44 (95\% CI: 1.09-1.90), and 1.15 (95\% CI: 0.90-1.47), respectively.

CONCLUSIONS: The results of this study indicate that SDB events accompanied by oxyhemoglobin desaturation of between 2\% to 4\% are associated with fasting hyperglycemia. These findings suggest that milder degrees of SDB may predispose to adverse metabolic outcomes.

}, keywords = {Aged, Blood Glucose, Body Mass Index, Cohort Studies, Cross-Sectional Studies, Diabetes Mellitus, Type 2, Fasting, Female, Humans, Male, Middle Aged, Odds Ratio, Oxygen, Oxyhemoglobins, Polysomnography, Reference Values, Sleep Apnea, Obstructive}, issn = {0161-8105}, author = {Stamatakis, Katherine and Sanders, Mark H and Caffo, Brian and Resnick, Helaine E and Gottlieb, Dan J and Mehra, Reena and Punjabi, Naresh M} } @article {1095, title = {Lifestyle risk factors and new-onset diabetes mellitus in older adults: the cardiovascular health study.}, journal = {Arch Intern Med}, volume = {169}, year = {2009}, month = {2009 Apr 27}, pages = {798-807}, abstract = {

BACKGROUND: The combined impact of lifestyle factors on incidence of diabetes mellitus later in life is not well established. The objective of this study was to determine how lifestyle factors, assessed in combination, relate to new-onset diabetes in a broad and relatively unselected population of older adults.

METHODS: We prospectively examined associations of lifestyle factors, measured using repeated assessments later in life, with incident diabetes mellitus during a 10-year period (1989-1998) among 4883 men and women 65 years or older (mean [SD] age at baseline, 73 [6] years) enrolled in the Cardiovascular Health Study. Low-risk lifestyle groups were defined by physical activity level (leisure-time activity and walking pace) above the median; dietary score (higher fiber intake and polyunsaturated to saturated fat ratio, lower trans-fat intake and lower mean glycemic index) in the top 2 quintiles; never smoked or former smoker more than 20 years ago or for fewer than 5 pack-years; alcohol use (predominantly light or moderate); body mass index less than 25 (calculated as weight in kilograms divided by height in meters squared); and waist circumference of 88 cm for women or 92 cm for men. The main outcome measure was incident diabetes defined annually by new use of insulin or oral hypoglycemic medications. We also evaluated fasting and 2-hour postchallenge glucose levels.

RESULTS: During 34,539 person-years, 337 new cases of drug-treated diabetes mellitus occurred (9.8 per 1000 person-years). After adjustment for age, sex, race, educational level, and annual income, each lifestyle factor was independently associated with incident diabetes. Overall, the rate of incident diabetes was 35\% lower (relative risk, 0.65; 95\% confidence interval, 0.59-0.71) for each 1 additional lifestyle factor in the low-risk group. Participants whose physical activity level and dietary, smoking, and alcohol habits were all in the low-risk group had an 82\% lower incidence of diabetes (relative risk, 0.18; 95\% confidence interval, 0.06-0.56) compared with all other participants. When absence of adiposity (either body mass index <25 or waist circumference < or =88/92 cm for women/men) was added to the other 4 low-risk lifestyle factors, incidence of diabetes was 89\% lower (relative risk, 0.11; 95\% confidence interval, 0.01-0.76). Overall, 9 of 10 new cases of diabetes appeared to be attributable to these 5 lifestyle factors. Associations were slightly attenuated, but still highly significant, for incident diabetes defined by medication use or glucose level.

CONCLUSION: Even later in life, combined lifestyle factors are associated with a markedly lower incidence of new-onset diabetes mellitus.

}, keywords = {Age of Onset, Aged, Aged, 80 and over, Diabetes Mellitus, Type 2, Female, Humans, Incidence, Life Style, Male, National Heart, Lung, and Blood Institute (U.S.), Prospective Studies, Risk Factors, United States}, issn = {1538-3679}, doi = {10.1001/archinternmed.2009.21}, author = {Mozaffarian, Dariush and Kamineni, Aruna and Carnethon, Mercedes and Djouss{\'e}, Luc and Mukamal, Kenneth J and Siscovick, David} } @article {1210, title = {Association between adiposity in midlife and older age and risk of diabetes in older adults.}, journal = {JAMA}, volume = {303}, year = {2010}, month = {2010 Jun 23}, pages = {2504-12}, abstract = {

CONTEXT: Adiposity is a well-recognized risk factor for type 2 diabetes among young and middle-aged adults, but the relationship between body composition and type 2 diabetes is not well described among older adults.

OBJECTIVE: To examine the relationship between adiposity, changes in adiposity, and risk of incident type 2 diabetes in adults 65 years of age and older.

DESIGN, SETTING, AND PARTICIPANTS: Prospective cohort study (1989-2007) of 4193 men and women 65 years of age and older in the Cardiovascular Health Study. Measures of adiposity were derived from anthropometry and bioelectrical impedance data at baseline and anthropometry repeated 3 years later.

MAIN OUTCOME MEASURE: Incident diabetes was ascertained based on use of antidiabetic medication or a fasting glucose level of 126 mg/dL or greater.

RESULTS: Over median follow-up of 12.4 years (range, 0.9-17.8 years), 339 cases of incident diabetes were ascertained (7.1/1000 person-years). The adjusted hazard ratio (HR) (95\% confidence interval [CI]) of type 2 diabetes for participants in the highest quintile of baseline measures compared with those in the lowest was 4.3 (95\% CI, 2.9-6.5) for body mass index (BMI [calculated as weight in kilograms divided by height in meters squared]), 3.0 (95\% CI, 2.0-4.3) for BMI at 50 years of age, 4.2 (95\% CI, 2.8-6.4) for weight, 4.0 (95\% CI, 2.6-6.0) for fat mass, 4.2 (95\% CI, 2.8-6.2) for waist circumference, 2.4 (95\% CI, 1.6-3.5) for waist-hip ratio, and 3.8 (95\% CI, 2.6-5.5) for waist-height ratio. However, when stratified by age, participants 75 years of age and older had HRs approximately half as large as those 65 to 74 years of age. Compared with weight-stable participants (+/-2 kg), those who gained the most weight from 50 years of age to baseline (> or = 9 kg), and from baseline to the third follow-up visit (> or = 6 kg), had HRs for type 2 diabetes of 2.8 (95\% CI, 1.9-4.3) and 2.0 (95\% CI, 1.1-3.7), respectively. Participants with a greater than 10-cm increase in waist size from baseline to the third follow-up visit had an HR of type 2 diabetes of 1.7 (95\% CI, 1.1-2.8) compared with those who gained or lost 2 cm or less.

CONCLUSION: Among older adults, overall and central adiposity, and weight gain during middle age and after the age of 65 years are associated with risk of diabetes.

}, keywords = {Adiposity, Age Factors, Aged, Body Mass Index, Diabetes Mellitus, Type 2, Female, Humans, Incidence, Male, Prospective Studies, Risk Factors, United States, Weight Gain}, issn = {1538-3598}, doi = {10.1001/jama.2010.843}, author = {Biggs, Mary L and Mukamal, Kenneth J and Luchsinger, Jos{\'e} A and Ix, Joachim H and Carnethon, Mercedes R and Newman, Anne B and de Boer, Ian H and Strotmeyer, Elsa S and Mozaffarian, Dariush and Siscovick, David S} } @article {1120, title = {Brain structure and obesity.}, journal = {Hum Brain Mapp}, volume = {31}, year = {2010}, month = {2010 Mar}, pages = {353-64}, abstract = {

Obesity is associated with increased risk for cardiovascular health problems including diabetes, hypertension, and stroke. These cardiovascular afflictions increase risk for cognitive decline and dementia, but it is unknown whether these factors, specifically obesity and Type II diabetes, are associated with specific patterns of brain atrophy. We used tensor-based morphometry (TBM) to examine gray matter (GM) and white matter (WM) volume differences in 94 elderly subjects who remained cognitively normal for at least 5 years after their scan. Bivariate analyses with corrections for multiple comparisons strongly linked body mass index (BMI), fasting plasma insulin (FPI) levels, and Type II Diabetes Mellitus (DM2) with atrophy in frontal, temporal, and subcortical brain regions. A multiple regression model, also correcting for multiple comparisons, revealed that BMI was still negatively correlated with brain atrophy (FDR <5\%), while DM2 and FPI were no longer associated with any volume differences. In an Analysis of Covariance (ANCOVA) model controlling for age, gender, and race, obese subjects with a high BMI (BMI > 30) showed atrophy in the frontal lobes, anterior cingulate gyrus, hippocampus, and thalamus compared with individuals with a normal BMI (18.5-25). Overweight subjects (BMI: 25-30) had atrophy in the basal ganglia and corona radiata of the WM. Overall brain volume did not differ between overweight and obese persons. Higher BMI was associated with lower brain volumes in overweight and obese elderly subjects. Obesity is therefore associated with detectable brain volume deficits in cognitively normal elderly subjects.

}, keywords = {Age Factors, Aged, Analysis of Variance, Body Mass Index, Brain, Continental Population Groups, Diabetes Mellitus, Type 2, Fasting, Female, Humans, Insulin, Magnetic Resonance Imaging, Male, Nerve Fibers, Myelinated, Nerve Fibers, Unmyelinated, Obesity, Organ Size, Regression Analysis, Sex Factors}, issn = {1097-0193}, doi = {10.1002/hbm.20870}, author = {Raji, Cyrus A and Ho, April J and Parikshak, Neelroop N and Becker, James T and Lopez, Oscar L and Kuller, Lewis H and Hua, Xue and Leow, Alex D and Toga, Arthur W and Thompson, Paul M} } @article {1207, title = {Diabetes and coronary heart disease as risk factors for mortality in older adults.}, journal = {Am J Med}, volume = {123}, year = {2010}, month = {2010 Jun}, pages = {556.e1-9}, abstract = {

BACKGROUND: Type 2 diabetes has been described as a coronary heart disease (CHD) "risk equivalent." We tested whether cardiovascular and all-cause mortality rates were similar between participants with prevalent CHD vs diabetes in an older adult population in whom both glucose disorders and preexisting atherosclerosis are common.

METHODS: The Cardiovascular Health Study is a longitudinal study of men and women (n=5784) aged > or =65 years at baseline who were followed from baseline (1989/1992-1993) through 2005 for mortality. Diabetes was defined by fasting plasma glucose > or =7.0 mmol/L or use of diabetes control medications. Prevalent CHD was determined by confirmed history of myocardial infarction, angina, or coronary revascularization.

RESULTS: Following multivariable adjustment for other cardiovascular disease risk factors and subclinical atherosclerosis, CHD mortality risk was similar between participants with CHD alone vs diabetes alone (hazard ratio [HR] 1.04, 95\% confidence interval [CI], 0.83-1.30). The proportion of mortality attributable to prevalent diabetes (population-attributable risk percent=8.4\%) and prevalent CHD (6.7\%) was similar in women, but the proportion of mortality attributable to CHD (16.5\%) as compared with diabetes (6.4\%) was markedly higher in men. Patterns were similar for cardiovascular disease mortality. By contrast, the adjusted relative hazard of total mortality was lower among participants with CHD alone (HR 0.85, 95\% CI, 0.75-0.96) as compared with those who had diabetes alone.

CONCLUSIONS: Among older adults, diabetes alone confers a risk for cardiovascular mortality similar to that from established clinical CHD. The public health burden of both diabetes and CHD is substantial, particularly among women.

}, keywords = {Aged, Coronary Disease, Diabetes Mellitus, Type 2, Female, Follow-Up Studies, Humans, Male, Prevalence, Risk Factors, Sex Distribution, Survival Rate, Time Factors, United States}, issn = {1555-7162}, doi = {10.1016/j.amjmed.2009.11.023}, author = {Carnethon, Mercedes R and Biggs, Mary L and Barzilay, Joshua and Kuller, Lewis H and Mozaffarian, Dariush and Mukamal, Kenneth and Smith, Nicholas L and Siscovick, David} } @article {1240, title = {Differential white blood cell count and type 2 diabetes: systematic review and meta-analysis of cross-sectional and prospective studies.}, journal = {PLoS One}, volume = {5}, year = {2010}, month = {2010 Oct 18}, pages = {e13405}, abstract = {

OBJECTIVE: Biological evidence suggests that inflammation might induce type 2 diabetes (T2D), and epidemiological studies have shown an association between higher white blood cell count (WBC) and T2D. However, the association has not been systematically investigated.

RESEARCH DESIGN AND METHODS: Studies were identified through computer-based and manual searches. Previously unreported studies were sought through correspondence. 20 studies were identified (8,647 T2D cases and 85,040 non-cases). Estimates of the association of WBC with T2D were combined using random effects meta-analysis; sources of heterogeneity as well as presence of publication bias were explored.

RESULTS: The combined relative risk (RR) comparing the top to bottom tertile of the WBC count was 1.61 (95\% CI: 1.45; 1.79, p = 1.5*10(-18)). Substantial heterogeneity was present (I(2) = 83\%). For granulocytes the RR was 1.38 (95\% CI: 1.17; 1.64, p = 1.5*10(-4)), for lymphocytes 1.26 (95\% CI: 1.02; 1.56, p = 0.029), and for monocytes 0.93 (95\% CI: 0.68; 1.28, p = 0.67) comparing top to bottom tertile. In cross-sectional studies, RR was 1.74 (95\% CI: 1.49; 2.02, p = 7.7*10(-13)), while in cohort studies it was 1.48 (95\% CI: 1.22; 1.79, p = 7.7*10(-5)). We assessed the impact of confounding in EPIC-Norfolk study and found that the age and sex adjusted HR of 2.19 (95\% CI: 1.74; 2.75) was attenuated to 1.82 (95\% CI: 1.45; 2.29) after further accounting for smoking, T2D family history, physical activity, education, BMI and waist circumference.

CONCLUSIONS: A raised WBC is associated with higher risk of T2D. The presence of publication bias and failure to control for all potential confounders in all studies means the observed association is likely an overestimate.

}, keywords = {Adult, Aged, Cross-Sectional Studies, Diabetes Mellitus, Type 2, Female, Humans, Leukocyte Count, Male, Middle Aged, Prospective Studies}, issn = {1932-6203}, doi = {10.1371/journal.pone.0013405}, author = {Gkrania-Klotsas, Effrossyni and Ye, Zheng and Cooper, Andrew J and Sharp, Stephen J and Luben, Robert and Biggs, Mary L and Chen, Liang-Kung and Gokulakrishnan, Kuppan and Hanefeld, Markolf and Ingelsson, Erik and Lai, Wen-An and Lin, Shih-Yi and Lind, Lars and Lohsoonthorn, Vitool and Mohan, Viswanathan and Muscari, Antonio and Nilsson, Goran and Ohrvik, John and Chao Qiang, Jiang and Jenny, Nancy Swords and Tamakoshi, Koji and Temelkova-Kurktschiev, Theodora and Wang, Ya-Yu and Yajnik, Chittaranjan Sakerlal and Zoli, Marco and Khaw, Kay-Tee and Forouhi, Nita G and Wareham, Nicholas J and Langenberg, Claudia} } @article {1203, title = {Egg consumption and risk of type 2 diabetes in older adults.}, journal = {Am J Clin Nutr}, volume = {92}, year = {2010}, month = {2010 Aug}, pages = {422-7}, abstract = {

BACKGROUND: Type 2 diabetes (T2D) remains an important public health issue in the United States. There are limited and inconsistent data on the association between egg consumption and fasting glucose or incident diabetes.

OBJECTIVES: We assessed the association between egg intake and incident diabetes in older adults.

DESIGN: In this prospective study of 3898 men and women from the Cardiovascular Health Study (1989-2007), we assessed egg consumption by using a picture-sorted food questionnaire and ascertained incident T2D annually by using information on hypoglycemic agents and plasma glucose. We used Cox proportional hazards models to estimate adjusted relative risks.

RESULTS: During a mean follow-up of 11.3 y, 313 new cases of T2D occurred. Crude incidence rates of T2D were 7.39, 6.83, 7.00, 6.72, and 12.20 per 1000 person-years in people who reported egg consumption of never, <1 egg/mo, 1-3 eggs/mo, 1-4 eggs/wk, and almost daily, respectively. In multivariable-adjusted models, there was no association between egg consumption and increased risk of T2D in either sex and overall. In a secondary analysis, dietary cholesterol was not associated with incident diabetes (P for trend = 0.47). In addition, egg consumption was not associated with clinically meaningful differences in fasting glucose, fasting insulin, or measures of insulin resistance despite small absolute analytic differences that were significant.

CONCLUSION: In this cohort of older adults with limited egg intake, there was no association between egg consumption or dietary cholesterol and increased risk of incident T2D.

}, keywords = {Aged, Blood Glucose, Cholesterol, Dietary, Diabetes Mellitus, Type 2, Diet, Diet Surveys, Eggs, Feeding Behavior, Female, Humans, Insulin, Insulin Resistance, Male, Proportional Hazards Models, Prospective Studies, Risk Factors, Surveys and Questionnaires}, issn = {1938-3207}, doi = {10.3945/ajcn.2010.29406}, author = {Djouss{\'e}, Luc and Kamineni, Aruna and Nelson, Tracy L and Carnethon, Mercedes and Mozaffarian, Dariush and Siscovick, David and Mukamal, Kenneth J} } @article {1160, title = {New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.}, journal = {Nat Genet}, volume = {42}, year = {2010}, month = {2010 Feb}, pages = {105-16}, abstract = {

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes.

}, keywords = {Adolescent, Adult, Alleles, Blood Glucose, Child, Databases, Genetic, Diabetes Mellitus, Type 2, DNA Copy Number Variations, Fasting, Gene Expression Regulation, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Homeostasis, Humans, Meta-Analysis as Topic, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Quantitative Trait, Heritable, Reproducibility of Results}, issn = {1546-1718}, doi = {10.1038/ng.520}, author = {Dupuis, Jos{\'e}e and Langenberg, Claudia and Prokopenko, Inga and Saxena, Richa and Soranzo, Nicole and Jackson, Anne U and Wheeler, Eleanor and Glazer, Nicole L and Bouatia-Naji, Nabila and Gloyn, Anna L and Lindgren, Cecilia M and M{\"a}gi, Reedik and Morris, Andrew P and Randall, Joshua and Johnson, Toby and Elliott, Paul and Rybin, Denis and Thorleifsson, Gudmar and Steinthorsdottir, Valgerdur and Henneman, Peter and Grallert, Harald and Dehghan, Abbas and Hottenga, Jouke Jan and Franklin, Christopher S and Navarro, Pau and Song, Kijoung and Goel, Anuj and Perry, John R B and Egan, Josephine M and Lajunen, Taina and Grarup, Niels and Spars{\o}, Thomas and Doney, Alex and Voight, Benjamin F and Stringham, Heather M and Li, Man and Kanoni, Stavroula and Shrader, Peter and Cavalcanti-Proen{\c c}a, Christine and Kumari, Meena and Qi, Lu and Timpson, Nicholas J and Gieger, Christian and Zabena, Carina and Rocheleau, Ghislain and Ingelsson, Erik and An, Ping and O{\textquoteright}Connell, Jeffrey and Luan, Jian{\textquoteright}an and Elliott, Amanda and McCarroll, Steven A and Payne, Felicity and Roccasecca, Rosa Maria and Pattou, Fran{\c c}ois and Sethupathy, Praveen and Ardlie, Kristin and Ariyurek, Yavuz and Balkau, Beverley and Barter, Philip and Beilby, John P and Ben-Shlomo, Yoav and Benediktsson, Rafn and Bennett, Amanda J and Bergmann, Sven and Bochud, Murielle and Boerwinkle, Eric and Bonnefond, Am{\'e}lie and Bonnycastle, Lori L and Borch-Johnsen, Knut and B{\"o}ttcher, Yvonne and Brunner, Eric and Bumpstead, Suzannah J and Charpentier, Guillaume and Chen, Yii-Der Ida and Chines, Peter and Clarke, Robert and Coin, Lachlan J M and Cooper, Matthew N and Cornelis, Marilyn and Crawford, Gabe and Crisponi, Laura and Day, Ian N M and de Geus, Eco J C and Delplanque, Jerome and Dina, Christian and Erdos, Michael R and Fedson, Annette C and Fischer-Rosinsky, Antje and Forouhi, Nita G and Fox, Caroline S and Frants, Rune and Franzosi, Maria Grazia and Galan, Pilar and Goodarzi, Mark O and Graessler, J{\"u}rgen and Groves, Christopher J and Grundy, Scott and Gwilliam, Rhian and Gyllensten, Ulf and Hadjadj, Samy and Hallmans, G{\"o}ran and Hammond, Naomi and Han, Xijing and Hartikainen, Anna-Liisa and Hassanali, Neelam and Hayward, Caroline and Heath, Simon C and Hercberg, Serge and Herder, Christian and Hicks, Andrew A and Hillman, David R and Hingorani, Aroon D and Hofman, Albert and Hui, Jennie and Hung, Joe and Isomaa, Bo and Johnson, Paul R V and J{\o}rgensen, Torben and Jula, Antti and Kaakinen, Marika and Kaprio, Jaakko and Kesaniemi, Y Antero and Kivimaki, Mika and Knight, Beatrice and Koskinen, Seppo and Kovacs, Peter and Kyvik, Kirsten Ohm and Lathrop, G Mark and Lawlor, Debbie A and Le Bacquer, Olivier and Lecoeur, C{\'e}cile and Li, Yun and Lyssenko, Valeriya and Mahley, Robert and Mangino, Massimo and Manning, Alisa K and Mart{\'\i}nez-Larrad, Mar{\'\i}a Teresa and McAteer, Jarred B and McCulloch, Laura J and McPherson, Ruth and Meisinger, Christa and Melzer, David and Meyre, David and Mitchell, Braxton D and Morken, Mario A and Mukherjee, Sutapa and Naitza, Silvia and Narisu, Narisu and Neville, Matthew J and Oostra, Ben A and Orr{\`u}, Marco and Pakyz, Ruth and Palmer, Colin N A and Paolisso, Giuseppe and Pattaro, Cristian and Pearson, Daniel and Peden, John F and Pedersen, Nancy L and Perola, Markus and Pfeiffer, Andreas F H and Pichler, Irene and Polasek, Ozren and Posthuma, Danielle and Potter, Simon C and Pouta, Anneli and Province, Michael A and Psaty, Bruce M and Rathmann, Wolfgang and Rayner, Nigel W and Rice, Kenneth and Ripatti, Samuli and Rivadeneira, Fernando and Roden, Michael and Rolandsson, Olov and Sandbaek, Annelli and Sandhu, Manjinder and Sanna, Serena and Sayer, Avan Aihie and Scheet, Paul and Scott, Laura J and Seedorf, Udo and Sharp, Stephen J and Shields, Beverley and Sigurethsson, Gunnar and Sijbrands, Eric J G and Silveira, Angela and Simpson, Laila and Singleton, Andrew and Smith, Nicholas L and Sovio, Ulla and Swift, Amy and Syddall, Holly and Syv{\"a}nen, Ann-Christine and Tanaka, Toshiko and Thorand, Barbara and Tichet, Jean and T{\"o}njes, Anke and Tuomi, Tiinamaija and Uitterlinden, Andr{\'e} G and van Dijk, Ko Willems and van Hoek, Mandy and Varma, Dhiraj and Visvikis-Siest, Sophie and Vitart, Veronique and Vogelzangs, Nicole and Waeber, G{\'e}rard and Wagner, Peter J and Walley, Andrew and Walters, G Bragi and Ward, Kim L and Watkins, Hugh and Weedon, Michael N and Wild, Sarah H and Willemsen, Gonneke and Witteman, Jaqueline C M and Yarnell, John W G and Zeggini, Eleftheria and Zelenika, Diana and Zethelius, Bj{\"o}rn and Zhai, Guangju and Zhao, Jing Hua and Zillikens, M Carola and Borecki, Ingrid B and Loos, Ruth J F and Meneton, Pierre and Magnusson, Patrik K E and Nathan, David M and Williams, Gordon H and Hattersley, Andrew T and Silander, Kaisa and Salomaa, Veikko and Smith, George Davey and Bornstein, Stefan R and Schwarz, Peter and Spranger, Joachim and Karpe, Fredrik and Shuldiner, Alan R and Cooper, Cyrus and Dedoussis, George V and Serrano-R{\'\i}os, Manuel and Morris, Andrew D and Lind, Lars and Palmer, Lyle J and Hu, Frank B and Franks, Paul W and Ebrahim, Shah and Marmot, Michael and Kao, W H Linda and Pankow, James S and Sampson, Michael J and Kuusisto, Johanna and Laakso, Markku and Hansen, Torben and Pedersen, Oluf and Pramstaller, Peter Paul and Wichmann, H Erich and Illig, Thomas and Rudan, Igor and Wright, Alan F and Stumvoll, Michael and Campbell, Harry and Wilson, James F and Bergman, Richard N and Buchanan, Thomas A and Collins, Francis S and Mohlke, Karen L and Tuomilehto, Jaakko and Valle, Timo T and Altshuler, David and Rotter, Jerome I and Siscovick, David S and Penninx, Brenda W J H and Boomsma, Dorret I and Deloukas, Panos and Spector, Timothy D and Frayling, Timothy M and Ferrucci, Luigi and Kong, Augustine and Thorsteinsdottir, Unnur and Stefansson, Kari and van Duijn, Cornelia M and Aulchenko, Yurii S and Cao, Antonio and Scuteri, Angelo and Schlessinger, David and Uda, Manuela and Ruokonen, Aimo and Jarvelin, Marjo-Riitta and Waterworth, Dawn M and Vollenweider, Peter and Peltonen, Leena and Mooser, Vincent and Abecasis, Goncalo R and Wareham, Nicholas J and Sladek, Robert and Froguel, Philippe and Watanabe, Richard M and Meigs, James B and Groop, Leif and Boehnke, Michael and McCarthy, Mark I and Florez, Jose C and Barroso, In{\^e}s} } @article {1257, title = {Trans-palmitoleic acid, metabolic risk factors, and new-onset diabetes in U.S. adults: a cohort study.}, journal = {Ann Intern Med}, volume = {153}, year = {2010}, month = {2010 Dec 21}, pages = {790-9}, abstract = {

BACKGROUND: Palmitoleic acid (cis-16:1n-7), which is produced by endogenous fat synthesis, has been linked to both beneficial and deleterious metabolic effects, potentially confounded by diverse determinants and tissue sources of endogenous production. Trans-palmitoleate (trans-16:1n-7) represents a distinctly exogenous source of 16:1n-7, unconfounded by endogenous synthesis or its determinants, that may be uniquely informative.

OBJECTIVE: To investigate whether circulating trans-palmitoleate is independently related to lower metabolic risk and incident type 2 diabetes.

DESIGN: Prospective cohort study from 1992 to 2006.

SETTING: Four U.S. communities.

PATIENTS: 3736 adults in the Cardiovascular Health Study.

MEASUREMENTS: Anthropometric characteristics and levels of plasma phospholipid fatty acids, blood lipids, inflammatory markers, and glucose-insulin measured at baseline in 1992 and dietary habits measured 3 years earlier. Multivariate-adjusted models were used to investigate how demographic, clinical, and lifestyle factors independently related to plasma phospholipid trans-palmitoleate; how trans-palmitoleate related to major metabolic risk factors; and how trans-palmitoleate related to new-onset diabetes (304 incident cases). Findings were validated for metabolic risk factors in an independent cohort of 327 women.

RESULTS: In multivariate analyses, whole-fat dairy consumption was most strongly associated with higher trans-palmitoleate levels. Higher trans-palmitoleate levels were associated with slightly lower adiposity and, independently, with higher high-density lipoprotein cholesterol levels (1.9\% across quintiles; P = 0.040), lower triglyceride levels (-19.0\%; P < 0.001), a lower total cholesterol-HDL cholesterol ratio (-4.7\%; P < 0.001), lower C-reactive protein levels (-13.8\%; P = 0.05), and lower insulin resistance (-16.7\%, P < 0.001). Trans-palmitoleate was also associated with a substantially lower incidence of diabetes, with multivariate hazard ratios of 0.41 (95\% CI, 0.27 to 0.64) and 0.38 (CI, 0.24 to 0.62) in quintiles 4 and 5 versus quintile 1 (P for trend < 0.001). Findings were independent of estimated dairy consumption or other fatty acid dairy biomarkers. Protective associations with metabolic risk factors were confirmed in the validation cohort.

LIMITATION: Results could be affected by measurement error or residual confounding.

CONCLUSION: Circulating trans-palmitoleate is associated with lower insulin resistance, presence of atherogenic dyslipidemia, and incident diabetes. Our findings may explain previously observed metabolic benefits of dairy consumption and support the need for detailed further experimental and clinical investigation.

PRIMARY FUNDING SOURCE: National Heart, Lung, and Blood Institute and National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health.

}, keywords = {Adiposity, Aged, C-Reactive Protein, Cholesterol, Cholesterol, HDL, Dairy Products, Diabetes Mellitus, Type 2, Fatty Acids, Monounsaturated, Feeding Behavior, Female, Humans, Incidence, Insulin Resistance, Male, Prospective Studies, Risk Factors, Triglycerides, United States}, issn = {1539-3704}, doi = {10.7326/0003-4819-153-12-201012210-00005}, author = {Mozaffarian, Dariush and Cao, Haiming and King, Irena B and Lemaitre, Rozenn N and Song, Xiaoling and Siscovick, David S and Hotamisligil, G{\"o}khan S} } @article {1567, title = {Candidate gene association study for diabetic retinopathy in persons with type 2 diabetes: the Candidate gene Association Resource (CARe).}, journal = {Invest Ophthalmol Vis Sci}, volume = {52}, year = {2011}, month = {2011 Sep 29}, pages = {7593-602}, abstract = {

PURPOSE: To investigate whether variants in cardiovascular candidate genes, some of which have been previously associated with type 2 diabetes (T2D), diabetic retinopathy (DR), and diabetic nephropathy (DN), are associated with DR in the Candidate gene Association Resource (CARe).

METHODS: Persons with T2D who were enrolled in the study (n = 2691) had fundus photography and genotyping of single nucleotide polymorphisms (SNPs) in 2000 candidate genes. Two case definitions were investigated: Early Treatment Diabetic Retinopathy Study (ETDRS) grades >= 14 and >= 30. The χ{\texttwosuperior} analyses for each CARe cohort were combined by Cochran-Mantel-Haenszel (CMH) pooling of odds ratios (ORs) and corrected for multiple hypothesis testing. Logistic regression was performed with adjustment for other DR risk factors. Results from replication in independent cohorts were analyzed with CMH meta-analysis methods.

RESULTS: Among 39 genes previously associated with DR, DN, or T2D, three SNPs in P-selectin (SELP) were associated with DR. The strongest association was to rs6128 (OR = 0.43, P = 0.0001, after Bonferroni correction). These associations remained significant after adjustment for DR risk factors. Among other genes examined, several variants were associated with DR with significant P values, including rs6856425 tagging α-l-iduronidase (IDUA) (P = 2.1 {\texttimes} 10(-5), after Bonferroni correction). However, replication in independent cohorts did not reveal study-wide significant effects. The P values after replication were 0.55 and 0.10 for rs6128 and rs6856425, respectively.

CONCLUSIONS: Genes associated with DN, T2D, and vascular diseases do not appear to be consistently associated with DR. A few genetic variants associated with DR, particularly those in SELP and near IDUA, should be investigated in additional DR cohorts.

}, keywords = {Cardiovascular Diseases, Diabetes Mellitus, Type 2, Diabetic Nephropathies, Diabetic Retinopathy, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Iduronidase, Odds Ratio, P-Selectin, Polymorphism, Single Nucleotide, Risk Factors}, issn = {1552-5783}, doi = {10.1167/iovs.11-7510}, author = {Sobrin, Lucia and Green, Todd and Sim, Xueling and Jensen, Richard A and Tai, E Shyong and Tay, Wan Ting and Wang, Jie Jin and Mitchell, Paul and Sandholm, Niina and Liu, Yiyuan and Hietala, Kustaa and Iyengar, Sudha K and Brooks, Matthew and Buraczynska, Monika and Van Zuydam, Natalie and Smith, Albert V and Gudnason, Vilmundur and Doney, Alex S F and Morris, Andrew D and Leese, Graham P and Palmer, Colin N A and Swaroop, Anand and Taylor, Herman A and Wilson, James G and Penman, Alan and Chen, Ching J and Groop, Per-Henrik and Saw, Seang-Mei and Aung, Tin and Klein, Barbara E and Rotter, Jerome I and Siscovick, David S and Cotch, Mary Frances and Klein, Ronald and Daly, Mark J and Wong, Tien Y} } @article {1288, title = {Enhanced statistical tests for GWAS in admixed populations: assessment using African Americans from CARe and a Breast Cancer Consortium.}, journal = {PLoS Genet}, volume = {7}, year = {2011}, month = {2011 Apr}, pages = {e1001371}, abstract = {

While genome-wide association studies (GWAS) have primarily examined populations of European ancestry, more recent studies often involve additional populations, including admixed populations such as African Americans and Latinos. In admixed populations, linkage disequilibrium (LD) exists both at a fine scale in ancestral populations and at a coarse scale (admixture-LD) due to chromosomal segments of distinct ancestry. Disease association statistics in admixed populations have previously considered SNP association (LD mapping) or admixture association (mapping by admixture-LD), but not both. Here, we introduce a new statistical framework for combining SNP and admixture association in case-control studies, as well as methods for local ancestry-aware imputation. We illustrate the gain in statistical power achieved by these methods by analyzing data of 6,209 unrelated African Americans from the CARe project genotyped on the Affymetrix 6.0 chip, in conjunction with both simulated and real phenotypes, as well as by analyzing the FGFR2 locus using breast cancer GWAS data from 5,761 African-American women. We show that, at typed SNPs, our method yields an 8\% increase in statistical power for finding disease risk loci compared to the power achieved by standard methods in case-control studies. At imputed SNPs, we observe an 11\% increase in statistical power for mapping disease loci when our local ancestry-aware imputation framework and the new scoring statistic are jointly employed. Finally, we show that our method increases statistical power in regions harboring the causal SNP in the case when the causal SNP is untyped and cannot be imputed. Our methods and our publicly available software are broadly applicable to GWAS in admixed populations.

}, keywords = {African Americans, Algorithms, Breast Neoplasms, Chromosome Mapping, Coronary Disease, Diabetes Mellitus, Type 2, Female, Gene Frequency, Genetic Variation, Genetics, Population, Genome, Human, Genome-Wide Association Study, Genotype, Humans, Linkage Disequilibrium, Male, Odds Ratio, Phenotype, Polymorphism, Single Nucleotide, Principal Component Analysis, Receptor, Fibroblast Growth Factor, Type 2, Software}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1001371}, author = {Pasaniuc, Bogdan and Zaitlen, Noah and Lettre, Guillaume and Chen, Gary K and Tandon, Arti and Kao, W H Linda and Ruczinski, Ingo and Fornage, Myriam and Siscovick, David S and Zhu, Xiaofeng and Larkin, Emma and Lange, Leslie A and Cupples, L Adrienne and Yang, Qiong and Akylbekova, Ermeg L and Musani, Solomon K and Divers, Jasmin and Mychaleckyj, Joe and Li, Mingyao and Papanicolaou, George J and Millikan, Robert C and Ambrosone, Christine B and John, Esther M and Bernstein, Leslie and Zheng, Wei and Hu, Jennifer J and Ziegler, Regina G and Nyante, Sarah J and Bandera, Elisa V and Ingles, Sue A and Press, Michael F and Chanock, Stephen J and Deming, Sandra L and Rodriguez-Gil, Jorge L and Palmer, Cameron D and Buxbaum, Sarah and Ekunwe, Lynette and Hirschhorn, Joel N and Henderson, Brian E and Myers, Simon and Haiman, Christopher A and Reich, David and Patterson, Nick and Wilson, James G and Price, Alkes L} } @article {1250, title = {Lipoprotein-associated phospholipase A(2) and future risk of subclinical disease and cardiovascular events in individuals with type 2 diabetes: the Cardiovascular Health Study.}, journal = {Diabetologia}, volume = {54}, year = {2011}, month = {2011 Feb}, pages = {329-33}, abstract = {

AIMS/HYPOTHESIS: Type 2 diabetes is an established risk factor for cardiovascular disease (CVD). This increased risk may be due in part to the increased levels of inflammatory factors associated with diabetes. Lipoprotein-associated phospholipase A(2) (Lp-PLA(2)) is a risk marker for CVD and has pro-inflammatory effects in atherosclerotic plaques. We therefore sought to determine whether Lp-PLA(2) levels partially explain the greater prevalence of subclinical CVD and greater incidence of CVD outcomes associated with type 2 diabetes in the Cardiovascular Health Study.

METHODS: We conducted a cross-sectional and prospective study of 4,062 men and women without previous CVD from the Cardiovascular Health Study (1989 to 2007). Lp-PLA(2) mass and activity were measured in baseline plasma. Subclinical disease was determined at baseline and incident CVD was ascertained annually. We used logistic regression for cross-sectional analyses and Cox proportional hazards models for incident analyses.

RESULTS: At baseline, Lp-PLA(2) mass did not differ significantly by type 2 diabetes status; however, Lp-PLA(2) activity was significantly higher among type 2 diabetic individuals. Baseline subclinical disease was significantly associated with baseline diabetes and this association was similar in models unadjusted or adjusted for Lp-PLA(2) (OR 1.68 [95\% CI 1.31-2.15] vs OR 1.67 [95\% CI 1.30-2.13]). Baseline type 2 diabetes was also significantly associated with incident CVD events, including fatal CHD, fatal myocardial infarction (MI) and non-fatal MI in multivariable analyses. There were no differences in these estimates after further adjustment for Lp-PLA(2) activity.

CONCLUSIONS/INTERPRETATION: In this older cohort, differences in Lp-PLA(2) activity did not explain any of the excess risk for subclinical disease or CVD outcomes related to diabetes.

}, keywords = {1-Alkyl-2-acetylglycerophosphocholine Esterase, Aged, Cardiovascular Diseases, Cross-Sectional Studies, Diabetes Mellitus, Type 2, Female, Humans, Male, Proportional Hazards Models, Prospective Studies, Risk Factors}, issn = {1432-0428}, doi = {10.1007/s00125-010-1969-4}, author = {Nelson, T L and Kamineni, A and Psaty, B and Cushman, M and Jenny, N S and Hokanson, J and Furberg, C and Mukamal, K J} } @article {1258, title = {Meta-analysis of gene-environment interaction: joint estimation of SNP and SNP {\texttimes} environment regression coefficients.}, journal = {Genet Epidemiol}, volume = {35}, year = {2011}, month = {2011 Jan}, pages = {11-8}, abstract = {

INTRODUCTION: Genetic discoveries are validated through the meta-analysis of genome-wide association scans in large international consortia. Because environmental variables may interact with genetic factors, investigation of differing genetic effects for distinct levels of an environmental exposure in these large consortia may yield additional susceptibility loci undetected by main effects analysis. We describe a method of joint meta-analysis (JMA) of SNP and SNP by Environment (SNP {\texttimes} E) regression coefficients for use in gene-environment interaction studies.

METHODS: In testing SNP {\texttimes} E interactions, one approach uses a two degree of freedom test to identify genetic variants that influence the trait of interest. This approach detects both main and interaction effects between the trait and the SNP. We propose a method to jointly meta-analyze the SNP and SNP {\texttimes} E coefficients using multivariate generalized least squares. This approach provides confidence intervals of the two estimates, a joint significance test for SNP and SNP {\texttimes} E terms, and a test of homogeneity across samples.

RESULTS: We present a simulation study comparing this method to four other methods of meta-analysis and demonstrate that the JMA performs better than the others when both main and interaction effects are present. Additionally, we implemented our methods in a meta-analysis of the association between SNPs from the type 2 diabetes-associated gene PPARG and log-transformed fasting insulin levels and interaction by body mass index in a combined sample of 19,466 individuals from five cohorts.

}, keywords = {Adult, Aged, Body Mass Index, Confidence Intervals, Diabetes Mellitus, Type 2, Environment, Fasting, Female, Genome, Human, Genome-Wide Association Study, Genotype, Humans, Insulin, Least-Squares Analysis, Male, Mathematical Computing, Meta-Analysis as Topic, Middle Aged, Polymorphism, Single Nucleotide, PPAR gamma}, issn = {1098-2272}, doi = {10.1002/gepi.20546}, author = {Manning, Alisa K and LaValley, Michael and Liu, Ching-Ti and Rice, Kenneth and An, Ping and Liu, Yongmei and Miljkovic, Iva and Rasmussen-Torvik, Laura and Harris, Tamara B and Province, Michael A and Borecki, Ingrid B and Florez, Jose C and Meigs, James B and Cupples, L Adrienne and Dupuis, Jos{\'e}e} } @article {1380, title = {Association of fetuin-a with incident diabetes mellitus in community-living older adults: the cardiovascular health study.}, journal = {Circulation}, volume = {125}, year = {2012}, month = {2012 May 15}, pages = {2316-22}, abstract = {

BACKGROUND: The liver-secreted protein fetuin-A induces peripheral insulin resistance in vitro. In a pilot study, we observed that higher fetuin-A levels were associated with diabetes mellitus in older persons. However, this finding has not been confirmed in large cohorts. We sought to confirm the association of fetuin-A with incident diabetes mellitus in older persons and to determine whether the association differs by age, sex, and race and among persons with cardiovascular disease (CVD).

METHODS AND RESULTS: Among 3710 community-living individuals >= 65 years of age without diabetes mellitus at baseline, fetuin-A was measured in serum collected in 1992 to 1993. Participants were followed up for 10.6 years (median) for incident diabetes mellitus. Cox regression models evaluated the association of fetuin-A with incident diabetes mellitus. Interaction terms evaluated heterogeneity by age, sex, race, and CVD. Mean age was 75 years; 60 were female; 15 were black; and 16 had CVD. Mean fetuin-A concentrations were 0.47 {\textpm} 0.10 g/L. During follow-up, 305 incident diabetes cases occurred. Each 0.10-g/L (SD)-greater fetuin-A was associated with 19 higher risk of diabetes mellitus (hazard ratio, 1.19; 95 confidence interval, 1.06-1.33) after adjustment for demographics, lifestyle factors, albumin, kidney function, and CVD. Further adjustment for potential mediators (body mass index, waist circumference, hypertension, lipids, and C-reactive protein) moderately attenuated the association (hazard ratio, 1.13; 95 confidence interval, 1.00-1.28). Results were similar by sex, race, and CVD status but were stronger in persons <75 years old (P for interaction=0.01).

CONCLUSIONS: Higher fetuin-A is associated with incident diabetes mellitus in older persons regardless of sex, race, or prevalent CVD status. The association may be attenuated in those >= 75 years of age.

}, keywords = {African Continental Ancestry Group, Age Distribution, Aged, Aged, 80 and over, alpha-2-HS-Glycoprotein, Body Mass Index, C-Reactive Protein, Cardiovascular Diseases, Diabetes Mellitus, Type 2, European Continental Ancestry Group, Female, Humans, Incidence, Life Style, Lipids, Male, Pilot Projects, Prevalence, Proportional Hazards Models, Residence Characteristics, Risk Factors, Sex Distribution}, issn = {1524-4539}, doi = {10.1161/CIRCULATIONAHA.111.072751}, author = {Ix, Joachim H and Biggs, Mary L and Mukamal, Kenneth J and Kizer, Jorge R and Zieman, Susan J and Siscovick, David S and Mozzaffarian, Dariush and Jensen, Majken K and Nelson, Lauren and Ruderman, Neil and Djouss{\'e}, Luc} } @article {1402, title = {Association of weight status with mortality in adults with incident diabetes.}, journal = {JAMA}, volume = {308}, year = {2012}, month = {2012 Aug 08}, pages = {581-90}, abstract = {

CONTEXT: Type 2 diabetes in normal-weight adults (body mass index [BMI] <25) is a representation of the metabolically obese normal-weight phenotype with unknown mortality consequences.

OBJECTIVE: To test the association of weight status with mortality in adults with new-onset diabetes in order to minimize the influence of diabetes duration and voluntary weight loss on mortality.

DESIGN, SETTING, AND PARTICIPANTS: Pooled analysis of 5 longitudinal cohort studies: Atherosclerosis Risk in Communities study, 1990-2006; Cardiovascular Health Study, 1992-2008; Coronary Artery Risk Development in Young Adults, 1987-2011; Framingham Offspring Study, 1979-2007; and Multi-Ethnic Study of Atherosclerosis, 2002-2011. A total of 2625 participants with incident diabetes contributed 27,125 person-years of follow-up. Included were men and women (age >40 years) who developed incident diabetes based on fasting glucose 126 mg/dL or greater or newly initiated diabetes medication and who had concurrent measurements of BMI. Participants were classified as normal weight if their BMI was 18.5 to 24.99 or overweight/obese if BMI was 25 or greater.

MAIN OUTCOME MEASURES: Total, cardiovascular, and noncardiovascular mortality.

RESULTS: The proportion of adults who were normal weight at the time of incident diabetes ranged from 9\% to 21\% (overall 12\%). During follow-up, 449 participants died: 178 from cardiovascular causes and 253 from noncardiovascular causes (18 were not classified). The rates of total, cardiovascular, and noncardiovascular mortality were higher in normal-weight participants (284.8, 99.8, and 198.1 per 10,000 person-years, respectively) than in overweight/obese participants (152.1, 67.8, and 87.9 per 10,000 person-years, respectively). After adjustment for demographic characteristics and blood pressure, lipid levels, waist circumference, and smoking status, hazard ratios comparing normal-weight participants with overweight/obese participants for total, cardiovascular, and noncardiovascular mortality were 2.08 (95\% CI, 1.52-2.85), 1.52 (95\% CI, 0.89-2.58), and 2.32 (95\% CI, 1.55-3.48), respectively.

CONCLUSION: Adults who were normal weight at the time of incident diabetes had higher mortality than adults who are overweight or obese.

}, keywords = {Adult, Aged, Aged, 80 and over, Body Mass Index, Body Weight, Cardiovascular Diseases, Cause of Death, Diabetes Mellitus, Type 2, Female, Humans, Longitudinal Studies, Male, Middle Aged, Obesity, Overweight, United States}, issn = {1538-3598}, doi = {10.1001/jama.2012.9282}, author = {Carnethon, Mercedes R and De Chavez, Peter John D and Biggs, Mary L and Lewis, Cora E and Pankow, James S and Bertoni, Alain G and Golden, Sherita H and Liu, Kiang and Mukamal, Kenneth J and Campbell-Jenkins, Brenda and Dyer, Alan R} } @article {1561, title = {Common genetic variants differentially influence the transition from clinically defined states of fasting glucose metabolism.}, journal = {Diabetologia}, volume = {55}, year = {2012}, month = {2012 Feb}, pages = {331-9}, abstract = {

AIMS/HYPOTHESIS: Common genetic variants have been associated with type 2 diabetes. We hypothesised that a subset of these variants may have different effects on the transition from normal fasting glucose (NFG) to impaired fasting glucose (IFG) than on that from IFG to diabetes.

METHODS: We identified 16 type 2 diabetes risk variants from the Illumina Broad Candidate-gene Association Resource (CARe) array genotyped in 26,576 CARe participants. Participants were categorised at baseline as NFG, IFG or type 2 diabetic (n = 16,465, 8,017 or 2,291, respectively). Using Cox proportional hazards and likelihood ratio tests (LRTs), we compared rates of progression by genotype for 4,909 (NFG to IFG) and 1,518 (IFG to type 2 diabetes) individuals, respectively. We then performed multinomial regression analyses at baseline, comparing the risk of assignment to the NFG, IFG or diabetes groups by genotype.

RESULTS: The rate of progression from NFG to IFG was significantly greater in participants carrying the risk allele at MTNR1B (p = 1 {\texttimes} 10(-4)), nominally greater at GCK and SLC30A8 (p < 0.05) and nominally smaller at IGF2BP2 (p = 0.01) than the rate of progression from IFG to diabetes by the LRT. Results of the baseline, multinomial regression model were consistent with these findings.

CONCLUSIONS/INTERPRETATION: Common genetic risk variants at GCK, SLC30A8, IGF2BP2 and MTNR1B influence to different extents the development of IFG and the transition from IFG to type 2 diabetes. Our findings may have implications for understanding the genetic contribution of these variants to the development of IFG and type 2 diabetes.

}, keywords = {Adult, Aged, Blood Glucose, Cohort Studies, Diabetes Mellitus, Type 2, Disease Progression, Fasting, Female, Genetic Variation, Genotype, Humans, Male, Middle Aged, Models, Genetic, Polymorphism, Single Nucleotide, Proportional Hazards Models, Regression Analysis, Risk}, issn = {1432-0428}, doi = {10.1007/s00125-011-2353-8}, author = {Walford, G A and Green, T and Neale, B and Isakova, T and Rotter, J I and Grant, S F A and Fox, C S and Pankow, J S and Wilson, J G and Meigs, J B and Siscovick, D S and Bowden, D W and Daly, M J and Florez, J C} } @article {6633, title = {Consistent directions of effect for established type 2 diabetes risk variants across populations: the population architecture using Genomics and Epidemiology (PAGE) Consortium.}, journal = {Diabetes}, volume = {61}, year = {2012}, month = {2012 Jun}, pages = {1642-7}, abstract = {

Common genetic risk variants for type 2 diabetes (T2D) have primarily been identified in populations of European and Asian ancestry. We tested whether the direction of association with 20 T2D risk variants generalizes across six major racial/ethnic groups in the U.S. as part of the Population Architecture using Genomics and Epidemiology Consortium (16,235 diabetes case and 46,122 control subjects of European American, African American, Hispanic, East Asian, American Indian, and Native Hawaiian ancestry). The percentage of positive (odds ratio [OR] >1 for putative risk allele) associations ranged from 69\% in American Indians to 100\% in European Americans. Of the nine variants where we observed significant heterogeneity of effect by racial/ethnic group (P(heterogeneity) < 0.05), eight were positively associated with risk (OR >1) in at least five groups. The marked directional consistency of association observed for most genetic variants across populations implies a shared functional common variant in each region. Fine-mapping of all loci will be required to reveal markers of risk that are important within and across populations.

}, keywords = {Adult, Aged, Aged, 80 and over, Alleles, Diabetes Mellitus, Type 2, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Male, Metagenomics, Middle Aged, Population Groups, Risk, Risk Factors}, issn = {1939-327X}, doi = {10.2337/db11-1296}, author = {Haiman, Christopher A and Fesinmeyer, Megan D and Spencer, Kylee L and B{\r u}zkov{\'a}, Petra and Voruganti, V Saroja and Wan, Peggy and Haessler, Jeff and Franceschini, Nora and Monroe, Kristine R and Howard, Barbara V and Jackson, Rebecca D and Florez, Jose C and Kolonel, Laurence N and Buyske, Steven and Goodloe, Robert J and Liu, Simin and Manson, JoAnn E and Meigs, James B and Waters, Kevin and Mukamal, Kenneth J and Pendergrass, Sarah A and Shrader, Peter and Wilkens, Lynne R and Hindorff, Lucia A and Ambite, Jose Luis and North, Kari E and Peters, Ulrike and Crawford, Dana C and Le Marchand, Lo{\"\i}c and Pankow, James S} } @article {6089, title = {Genome-wide association study for circulating levels of PAI-1 provides novel insights into its regulation.}, journal = {Blood}, volume = {120}, year = {2012}, month = {2012 Dec 06}, pages = {4873-81}, abstract = {

We conducted a genome-wide association study to identify novel associations between genetic variants and circulating plasminogen activator inhibitor-1 (PAI-1) concentration, and examined functional implications of variants and genes that were discovered. A discovery meta-analysis was performed in 19 599 subjects, followed by replication analysis of genome-wide significant (P < 5 {\texttimes} 10(-8)) single nucleotide polymorphisms (SNPs) in 10 796 independent samples. We further examined associations with type 2 diabetes and coronary artery disease, assessed the functional significance of the SNPs for gene expression in human tissues, and conducted RNA-silencing experiments for one novel association. We confirmed the association of the 4G/5G proxy SNP rs2227631 in the promoter region of SERPINE1 (7q22.1) and discovered genome-wide significant associations at 3 additional loci: chromosome 7q22.1 close to SERPINE1 (rs6976053, discovery P = 3.4 {\texttimes} 10(-10)); chromosome 11p15.2 within ARNTL (rs6486122, discovery P = 3.0 {\texttimes} 10(-8)); and chromosome 3p25.2 within PPARG (rs11128603, discovery P = 2.9 {\texttimes} 10(-8)). Replication was achieved for the 7q22.1 and 11p15.2 loci. There was nominal association with type 2 diabetes and coronary artery disease at ARNTL (P < .05). Functional studies identified MUC3 as a candidate gene for the second association signal on 7q22.1. In summary, SNPs in SERPINE1 and ARNTL and an SNP associated with the expression of MUC3 were robustly associated with circulating levels of PAI-1.

}, keywords = {Adaptor Proteins, Signal Transducing, ARNTL Transcription Factors, ATPases Associated with Diverse Cellular Activities, Cell Line, Cell Line, Tumor, Cohort Studies, Coronary Artery Disease, Diabetes Mellitus, Type 2, Gene Expression Profiling, Gene Expression Regulation, Gene Frequency, Genome-Wide Association Study, Genotype, Humans, LIM Domain Proteins, Meta-Analysis as Topic, Monocytes, Mucin-3, Plasminogen Activator Inhibitor 1, Polymorphism, Single Nucleotide, PPAR gamma, Proteasome Endopeptidase Complex, RNA Interference, Transcription Factors}, issn = {1528-0020}, doi = {10.1182/blood-2012-06-436188}, author = {Huang, Jie and Sabater-Lleal, Maria and Asselbergs, Folkert W and Tregouet, David and Shin, So-Youn and Ding, Jingzhong and Baumert, Jens and Oudot-Mellakh, Tiphaine and Folkersen, Lasse and Johnson, Andrew D and Smith, Nicholas L and Williams, Scott M and Ikram, Mohammad A and Kleber, Marcus E and Becker, Diane M and Truong, Vinh and Mychaleckyj, Josyf C and Tang, Weihong and Yang, Qiong and Sennblad, Bengt and Moore, Jason H and Williams, Frances M K and Dehghan, Abbas and Silbernagel, G{\"u}nther and Schrijvers, Elisabeth M C and Smith, Shelly and Karakas, Mahir and Tofler, Geoffrey H and Silveira, Angela and Navis, Gerjan J and Lohman, Kurt and Chen, Ming-Huei and Peters, Annette and Goel, Anuj and Hopewell, Jemma C and Chambers, John C and Saleheen, Danish and Lundmark, Per and Psaty, Bruce M and Strawbridge, Rona J and Boehm, Bernhard O and Carter, Angela M and Meisinger, Christa and Peden, John F and Bis, Joshua C and McKnight, Barbara and Ohrvik, John and Taylor, Kent and Franzosi, Maria Grazia and Seedorf, Udo and Collins, Rory and Franco-Cereceda, Anders and Syv{\"a}nen, Ann-Christine and Goodall, Alison H and Yanek, Lisa R and Cushman, Mary and M{\"u}ller-Nurasyid, Martina and Folsom, Aaron R and Basu, Saonli and Matijevic, Nena and van Gilst, Wiek H and Kooner, Jaspal S and Hofman, Albert and Danesh, John and Clarke, Robert and Meigs, James B and Kathiresan, Sekar and Reilly, Muredach P and Klopp, Norman and Harris, Tamara B and Winkelmann, Bernhard R and Grant, Peter J and Hillege, Hans L and Watkins, Hugh and Spector, Timothy D and Becker, Lewis C and Tracy, Russell P and M{\"a}rz, Winfried and Uitterlinden, Andr{\'e} G and Eriksson, Per and Cambien, Francois and Morange, Pierre-Emmanuel and Koenig, Wolfgang and Soranzo, Nicole and van der Harst, Pim and Liu, Yongmei and O{\textquoteright}Donnell, Christopher J and Hamsten, Anders} } @article {1370, title = {Insulin resistance and incident peripheral artery disease in the Cardiovascular Health Study.}, journal = {Vasc Med}, volume = {17}, year = {2012}, month = {2012 Apr}, pages = {85-93}, abstract = {

Type 2 diabetes is a risk factor for peripheral artery disease (PAD), and insulin resistance is a key feature of diabetes and pre-diabetes. No longitudinal epidemiological study has examined the relation between insulin resistance and PAD. Our study analyzed the association of quartiles of the homeostatic model of insulin resistance (HOMA-IR) and the development of PAD defined by two methods. PAD was first defined as the development of an abnormal ankle-brachial index (ABI) (dichotomous outcome) after 6 years of follow-up. PAD was alternatively defined as the development of clinical PAD (time-to-event analysis). The study samples included adults over the age of 65 years who were enrolled in the Cardiovascular Health Study, had fasting measurements of insulin and glucose, had ABI measurements, and were not receiving treatment for diabetes. Multivariable models were adjusted for potential confounders, including age, sex, field center and cohort, body mass index (BMI), smoking status, alcohol use, and exercise intensity. Additional models adjusted for potential mediators, including blood pressure, lipids, kidney function, and prevalent vascular disease. In the ABI analysis (n = 2108), multivariable adjusted models demonstrated a positive relation between HOMA-IR and incident PAD (odds ratio = 1.80 comparing the 4th versus 1st quartile of HOMA-IR, 95\% confidence interval [CI] 1.20-2.71). In the clinical PAD analysis (n = 4208), we found a similar relation (hazard ratio = 2.30 comparing the 4th versus 1st quartile of HOMA-IR, 95\% CI 1.15-4.58). As expected, further adjustment for potential mediators led to some attenuation of effect estimates. In conclusion, insulin resistance is associated with a higher risk of PAD in older adults.

}, keywords = {Aged, Ankle Brachial Index, Biomarkers, Blood Glucose, Diabetes Mellitus, Type 2, Diabetic Angiopathies, Fasting, Female, Health Surveys, Humans, Incidence, Insulin, Insulin Resistance, Logistic Models, Longitudinal Studies, Male, Odds Ratio, Peripheral Arterial Disease, Predictive Value of Tests, Proportional Hazards Models, Prospective Studies, Risk Assessment, Risk Factors, Time Factors, United States}, issn = {1477-0377}, doi = {10.1177/1358863X11436195}, author = {Britton, Kathryn A and Mukamal, Kenneth J and Ix, Joachim H and Siscovick, David S and Newman, Anne B and de Boer, Ian H and Thacker, Evan L and Biggs, Mary L and Gaziano, J Michael and Djouss{\'e}, Luc} } @article {1369, title = {Lipoprotein-associated phospholipase A2 (Lp-PLA2) and future risk of type 2 diabetes: results from the Cardiovascular Health Study.}, journal = {J Clin Endocrinol Metab}, volume = {97}, year = {2012}, month = {2012 May}, pages = {1695-701}, abstract = {

INTRODUCTION: Lipoprotein-associated phospholipase A2 (Lp-PLA(2)) has been consistently associated with cardiovascular disease (CVD) risk factors and predictive of CVD outcomes; furthermore, it is consistently higher among type 2 diabetics than nondiabetics. However, the relationships of circulating Lp-PLA(2) mass and activity with incident type 2 diabetes mellitus have not been examined. Therefore, the purpose of this study was to determine the association of Lp-PLA(2) mass and activity with type 2 diabetes among older adults.

METHODS: We conducted analyses of Lp-PLA(2) and prevalent and incident diabetes among 5474 men and women from the Cardiovascular Health Study (1989-2007). Lp-PLA(2) mass and activity were measured in baseline plasma. Diabetes status was ascertained annually with medication inventories and repeated blood glucose measurements. Generalized linear and Cox proportional hazards models were used to adjust for confounding factors including body mass index and inflammation.

RESULTS: At baseline, the top two quintiles of Lp-PLA(2) activity were significantly associated with prevalent type 2 diabetes with a multivariable relative risk = 1.35 [95\% confidence interval (CI) = 1.11-1.63] for quintile 4, and relative risk = 1.33 (95\% CI = 1.07-1.66) for quintile 5. Among participants free of diabetes at baseline, we found a significant positive association with both the homeostatic model assessment for insulin resistance and β-cell function per SD increase in Lp-PLA(2) activity (P values for both <0.01). In prospective analyses, the risk of incident type 2 diabetes was significantly higher among those in the highest quintile of Lp-PLA(2) activity [multivariable hazard ratio = 1.45 (95\% CI = 1.01-2.07)] compared with the lowest quintile. Lp-PLA(2) mass was not significantly associated with incident type 2 diabetes.

DISCUSSION: Lp-PLA(2) activity is positively associated with insulin resistance and predicts incident type 2 diabetes among older adults independent of multiple factors associated with diabetes pathogenesis.

}, keywords = {1-Alkyl-2-acetylglycerophosphocholine Esterase, Aged, Aged, 80 and over, Cardiovascular Diseases, Diabetes Mellitus, Type 2, Female, Humans, Incidence, Insulin Resistance, Male, Middle Aged, Predictive Value of Tests, Prevalence, Prospective Studies, Risk, Risk Factors}, issn = {1945-7197}, doi = {10.1210/jc.2011-3026}, author = {Nelson, T L and Biggs, M L and Kizer, J R and Cushman, M and Hokanson, J E and Furberg, C D and Mukamal, K J} } @article {1378, title = {Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals.}, journal = {PLoS Genet}, volume = {8}, year = {2012}, month = {2012}, pages = {e1002607}, abstract = {

Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5{\texttimes}10(-8)-1.2{\texttimes}10(-43)). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3{\texttimes}10(-4)). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3{\texttimes}10(-3), n = 22,044), increased triglycerides (p = 2.6{\texttimes}10(-14), n = 93,440), increased waist-to-hip ratio (p = 1.8{\texttimes}10(-5), n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4{\texttimes}10(-3), n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDL-cholesterol concentrations (p = 4.5{\texttimes}10(-13), n = 96,748) and decreased BMI (p = 1.4{\texttimes}10(-4), n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.

}, keywords = {Adiponectin, African Americans, Asian Continental Ancestry Group, Cholesterol, HDL, Diabetes Mellitus, Type 2, European Continental Ancestry Group, Female, Gene Expression, Genetic Predisposition to Disease, Genome-Wide Association Study, Glucose Tolerance Test, Humans, Insulin Resistance, Male, Metabolic Networks and Pathways, Polymorphism, Single Nucleotide, Waist-Hip Ratio}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1002607}, author = {Dastani, Zari and Hivert, Marie-France and Timpson, Nicholas and Perry, John R B and Yuan, Xin and Scott, Robert A and Henneman, Peter and Heid, Iris M and Kizer, Jorge R and Lyytik{\"a}inen, Leo-Pekka and Fuchsberger, Christian and Tanaka, Toshiko and Morris, Andrew P and Small, Kerrin and Isaacs, Aaron and Beekman, Marian and Coassin, Stefan and Lohman, Kurt and Qi, Lu and Kanoni, Stavroula and Pankow, James S and Uh, Hae-Won and Wu, Ying and Bidulescu, Aurelian and Rasmussen-Torvik, Laura J and Greenwood, Celia M T and Ladouceur, Martin and Grimsby, Jonna and Manning, Alisa K and Liu, Ching-Ti and Kooner, Jaspal and Mooser, Vincent E and Vollenweider, Peter and Kapur, Karen A and Chambers, John and Wareham, Nicholas J and Langenberg, Claudia and Frants, Rune and Willems-Vandijk, Ko and Oostra, Ben A and Willems, Sara M and Lamina, Claudia and Winkler, Thomas W and Psaty, Bruce M and Tracy, Russell P and Brody, Jennifer and Chen, Ida and Viikari, Jorma and K{\"a}h{\"o}nen, Mika and Pramstaller, Peter P and Evans, David M and St Pourcain, Beate and Sattar, Naveed and Wood, Andrew R and Bandinelli, Stefania and Carlson, Olga D and Egan, Josephine M and B{\"o}hringer, Stefan and van Heemst, Diana and Kedenko, Lyudmyla and Kristiansson, Kati and Nuotio, Marja-Liisa and Loo, Britt-Marie and Harris, Tamara and Garcia, Melissa and Kanaya, Alka and Haun, Margot and Klopp, Norman and Wichmann, H-Erich and Deloukas, Panos and Katsareli, Efi and Couper, David J and Duncan, Bruce B and Kloppenburg, Margreet and Adair, Linda S and Borja, Judith B and Wilson, James G and Musani, Solomon and Guo, Xiuqing and Johnson, Toby and Semple, Robert and Teslovich, Tanya M and Allison, Matthew A and Redline, Susan and Buxbaum, Sarah G and Mohlke, Karen L and Meulenbelt, Ingrid and Ballantyne, Christie M and Dedoussis, George V and Hu, Frank B and Liu, Yongmei and Paulweber, Bernhard and Spector, Timothy D and Slagboom, P Eline and Ferrucci, Luigi and Jula, Antti and Perola, Markus and Raitakari, Olli and Florez, Jose C and Salomaa, Veikko and Eriksson, Johan G and Frayling, Timothy M and Hicks, Andrew A and Lehtim{\"a}ki, Terho and Smith, George Davey and Siscovick, David S and Kronenberg, Florian and van Duijn, Cornelia and Loos, Ruth J F and Waterworth, Dawn M and Meigs, James B and Dupuis, Jos{\'e}e and Richards, J Brent and Voight, Benjamin F and Scott, Laura J and Steinthorsdottir, Valgerdur and Dina, Christian and Welch, Ryan P and Zeggini, Eleftheria and Huth, Cornelia and Aulchenko, Yurii S and Thorleifsson, Gudmar and McCulloch, Laura J and Ferreira, Teresa and Grallert, Harald and Amin, Najaf and Wu, Guanming and Willer, Cristen J and Raychaudhuri, Soumya and McCarroll, Steve A and Hofmann, Oliver M and Segr{\`e}, Ayellet V and van Hoek, Mandy and Navarro, Pau and Ardlie, Kristin and Balkau, Beverley and Benediktsson, Rafn and Bennett, Amanda J and Blagieva, Roza and Boerwinkle, Eric and Bonnycastle, Lori L and Bostr{\"o}m, Kristina Bengtsson and Bravenboer, Bert and Bumpstead, Suzannah and Burtt, Noel P and Charpentier, Guillaume and Chines, Peter S and Cornelis, Marilyn and Crawford, Gabe and Doney, Alex S F and Elliott, Katherine S and Elliott, Amanda L and Erdos, Michael R and Fox, Caroline S and Franklin, Christopher S and Ganser, Martha and Gieger, Christian and Grarup, Niels and Green, Todd and Griffin, Simon and Groves, Christopher J and Guiducci, Candace and Hadjadj, Samy and Hassanali, Neelam and Herder, Christian and Isomaa, Bo and Jackson, Anne U and Johnson, Paul R V and J{\o}rgensen, Torben and Kao, Wen H L and Kong, Augustine and Kraft, Peter and Kuusisto, Johanna and Lauritzen, Torsten and Li, Man and Lieverse, Aloysius and Lindgren, Cecilia M and Lyssenko, Valeriya and Marre, Michel and Meitinger, Thomas and Midthjell, Kristian and Morken, Mario A and Narisu, Narisu and Nilsson, Peter and Owen, Katharine R and Payne, Felicity and Petersen, Ann-Kristin and Platou, Carl and Proen{\c c}a, Christine and Prokopenko, Inga and Rathmann, Wolfgang and Rayner, N William and Robertson, Neil R and Rocheleau, Ghislain and Roden, Michael and Sampson, Michael J and Saxena, Richa and Shields, Beverley M and Shrader, Peter and Sigurdsson, Gunnar and Spars{\o}, Thomas and Strassburger, Klaus and Stringham, Heather M and Sun, Qi and Swift, Amy J and Thorand, Barbara and Tichet, Jean and Tuomi, Tiinamaija and van Dam, Rob M and van Haeften, Timon W and van Herpt, Thijs and van Vliet-Ostaptchouk, Jana V and Walters, G Bragi and Weedon, Michael N and Wijmenga, Cisca and Witteman, Jacqueline and Bergman, Richard N and Cauchi, Stephane and Collins, Francis S and Gloyn, Anna L and Gyllensten, Ulf and Hansen, Torben and Hide, Winston A and Hitman, Graham A and Hofman, Albert and Hunter, David J and Hveem, Kristian and Laakso, Markku and Morris, Andrew D and Palmer, Colin N A and Rudan, Igor and Sijbrands, Eric and Stein, Lincoln D and Tuomilehto, Jaakko and Uitterlinden, Andre and Walker, Mark and Watanabe, Richard M and Abecasis, Goncalo R and Boehm, Bernhard O and Campbell, Harry and Daly, Mark J and Hattersley, Andrew T and Pedersen, Oluf and Barroso, In{\^e}s and Groop, Leif and Sladek, Rob and Thorsteinsdottir, Unnur and Wilson, James F and Illig, Thomas and Froguel, Philippe and van Duijn, Cornelia M and Stefansson, Kari and Altshuler, David and Boehnke, Michael and McCarthy, Mark I and Soranzo, Nicole and Wheeler, Eleanor and Glazer, Nicole L and Bouatia-Naji, Nabila and M{\"a}gi, Reedik and Randall, Joshua and Elliott, Paul and Rybin, Denis and Dehghan, Abbas and Hottenga, Jouke Jan and Song, Kijoung and Goel, Anuj and Lajunen, Taina and Doney, Alex and Cavalcanti-Proen{\c c}a, Christine and Kumari, Meena and Timpson, Nicholas J and Zabena, Carina and Ingelsson, Erik and An, Ping and O{\textquoteright}Connell, Jeffrey and Luan, Jian{\textquoteright}an and Elliott, Amanda and McCarroll, Steven A and Roccasecca, Rosa Maria and Pattou, Fran{\c c}ois and Sethupathy, Praveen and Ariyurek, Yavuz and Barter, Philip and Beilby, John P and Ben-Shlomo, Yoav and Bergmann, Sven and Bochud, Murielle and Bonnefond, Am{\'e}lie and Borch-Johnsen, Knut and B{\"o}ttcher, Yvonne and Brunner, Eric and Bumpstead, Suzannah J and Chen, Yii-Der Ida and Chines, Peter and Clarke, Robert and Coin, Lachlan J M and Cooper, Matthew N and Crisponi, Laura and Day, Ian N M and de Geus, Eco J C and Delplanque, Jerome and Fedson, Annette C and Fischer-Rosinsky, Antje and Forouhi, Nita G and Franzosi, Maria Grazia and Galan, Pilar and Goodarzi, Mark O and Graessler, J{\"u}rgen and Grundy, Scott and Gwilliam, Rhian and Hallmans, G{\"o}ran and Hammond, Naomi and Han, Xijing and Hartikainen, Anna-Liisa and Hayward, Caroline and Heath, Simon C and Hercberg, Serge and Hillman, David R and Hingorani, Aroon D and Hui, Jennie and Hung, Joe and Kaakinen, Marika and Kaprio, Jaakko and Kesaniemi, Y Antero and Kivimaki, Mika and Knight, Beatrice and Koskinen, Seppo and Kovacs, Peter and Kyvik, Kirsten Ohm and Lathrop, G Mark and Lawlor, Debbie A and Le Bacquer, Olivier and Lecoeur, C{\'e}cile and Li, Yun and Mahley, Robert and Mangino, Massimo and Mart{\'\i}nez-Larrad, Mar{\'\i}a Teresa and McAteer, Jarred B and McPherson, Ruth and Meisinger, Christa and Melzer, David and Meyre, David and Mitchell, Braxton D and Mukherjee, Sutapa and Naitza, Silvia and Neville, Matthew J and Orr{\`u}, Marco and Pakyz, Ruth and Paolisso, Giuseppe and Pattaro, Cristian and Pearson, Daniel and Peden, John F and Pedersen, Nancy L and Pfeiffer, Andreas F H and Pichler, Irene and Polasek, Ozren and Posthuma, Danielle and Potter, Simon C and Pouta, Anneli and Province, Michael A and Rayner, Nigel W and Rice, Kenneth and Ripatti, Samuli and Rivadeneira, Fernando and Rolandsson, Olov and Sandbaek, Annelli and Sandhu, Manjinder and Sanna, Serena and Sayer, Avan Aihie and Scheet, Paul and Seedorf, Udo and Sharp, Stephen J and Shields, Beverley and Sigur{\dh}sson, Gunnar and Sijbrands, Eric J G and Silveira, Angela and Simpson, Laila and Singleton, Andrew and Smith, Nicholas L and Sovio, Ulla and Swift, Amy and Syddall, Holly and Syv{\"a}nen, Ann-Christine and T{\"o}njes, Anke and Uitterlinden, Andr{\'e} G and van Dijk, Ko Willems and Varma, Dhiraj and Visvikis-Siest, Sophie and Vitart, Veronique and Vogelzangs, Nicole and Waeber, G{\'e}rard and Wagner, Peter J and Walley, Andrew and Ward, Kim L and Watkins, Hugh and Wild, Sarah H and Willemsen, Gonneke and Witteman, Jaqueline C M and Yarnell, John W G and Zelenika, Diana and Zethelius, Bj{\"o}rn and Zhai, Guangju and Zhao, Jing Hua and Zillikens, M Carola and Borecki, Ingrid B and Meneton, Pierre and Magnusson, Patrik K E and Nathan, David M and Williams, Gordon H and Silander, Kaisa and Bornstein, Stefan R and Schwarz, Peter and Spranger, Joachim and Karpe, Fredrik and Shuldiner, Alan R and Cooper, Cyrus and Serrano-R{\'\i}os, Manuel and Lind, Lars and Palmer, Lyle J and Hu, Frank B and Franks, Paul W and Ebrahim, Shah and Marmot, Michael and Kao, W H Linda and Pramstaller, Peter Paul and Wright, Alan F and Stumvoll, Michael and Hamsten, Anders and Buchanan, Thomas A and Valle, Timo T and Rotter, Jerome I and Penninx, Brenda W J H and Boomsma, Dorret I and Cao, Antonio and Scuteri, Angelo and Schlessinger, David and Uda, Manuela and Ruokonen, Aimo and Jarvelin, Marjo-Riitta and Peltonen, Leena and Mooser, Vincent and Sladek, Robert and Musunuru, Kiran and Smith, Albert V and Edmondson, Andrew C and Stylianou, Ioannis M and Koseki, Masahiro and Pirruccello, James P and Chasman, Daniel I and Johansen, Christopher T and Fouchier, Sigrid W and Peloso, Gina M and Barbalic, Maja and Ricketts, Sally L and Bis, Joshua C and Feitosa, Mary F and Orho-Melander, Marju and Melander, Olle and Li, Xiaohui and Li, Mingyao and Cho, Yoon Shin and Go, Min Jin and Kim, Young Jin and Lee, Jong-Young and Park, Taesung and Kim, Kyunga and Sim, Xueling and Ong, Rick Twee-Hee and Croteau-Chonka, Damien C and Lange, Leslie A and Smith, Joshua D and Ziegler, Andreas and Zhang, Weihua and Zee, Robert Y L and Whitfield, John B and Thompson, John R and Surakka, Ida and Spector, Tim D and Smit, Johannes H and Sinisalo, Juha and Scott, James and Saharinen, Juha and Sabatti, Chiara and Rose, Lynda M and Roberts, Robert and Rieder, Mark and Parker, Alex N and Par{\'e}, Guillaume and O{\textquoteright}Donnell, Christopher J and Nieminen, Markku S and Nickerson, Deborah A and Montgomery, Grant W and McArdle, Wendy and Masson, David and Martin, Nicholas G and Marroni, Fabio and Lucas, Gavin and Luben, Robert and Lokki, Marja-Liisa and Lettre, Guillaume and Launer, Lenore J and Lakatta, Edward G and Laaksonen, Reijo and Kyvik, Kirsten O and K{\"o}nig, Inke R and Khaw, Kay-Tee and Kaplan, Lee M and Johansson, Asa and Janssens, A Cecile J W and Igl, Wilmar and Hovingh, G Kees and Hengstenberg, Christian and Havulinna, Aki S and Hastie, Nicholas D and Harris, Tamara B and Haritunians, Talin and Hall, Alistair S and Groop, Leif C and Gonzalez, Elena and Freimer, Nelson B and Erdmann, Jeanette and Ejebe, Kenechi G and D{\"o}ring, Angela and Dominiczak, Anna F and Demissie, Serkalem and Deloukas, Panagiotis and de Faire, Ulf and Crawford, Gabriel and Chen, Yii-der I and Caulfield, Mark J and Boekholdt, S Matthijs and Assimes, Themistocles L and Quertermous, Thomas and Seielstad, Mark and Wong, Tien Y and Tai, E-Shyong and Feranil, Alan B and Kuzawa, Christopher W and Taylor, Herman A and Gabriel, Stacey B and Holm, Hilma and Gudnason, Vilmundur and Krauss, Ronald M and Ordovas, Jose M and Munroe, Patricia B and Kooner, Jaspal S and Tall, Alan R and Hegele, Robert A and Kastelein, John J P and Schadt, Eric E and Strachan, David P and Reilly, Muredach P and Samani, Nilesh J and Schunkert, Heribert and Cupples, L Adrienne and Sandhu, Manjinder S and Ridker, Paul M and Rader, Daniel J and Kathiresan, Sekar} } @article {1379, title = {Plasma free fatty acids and risk of atrial fibrillation (from the Cardiovascular Health Study).}, journal = {Am J Cardiol}, volume = {110}, year = {2012}, month = {2012 Jul 15}, pages = {212-6}, abstract = {

Atrial fibrillation (AF) is a highly prevalent cardiac arrhythmia in clinical practice, affecting approximately 2.3 million residents of the United States and 4.5 million residents of the European Union. It is unclear whether plasma free fatty acids (FFAs) influence the risk of AF in older adults. The aim of this study was to prospectively examine the association between plasma FFAs and incident AF in a prospective cohort of 4,175 men and women >=65 years old from the Cardiovascular Health Study. Plasma concentrations of FFAs were measured 2 times during the 1992 to 1993 examination. Incident AF was ascertained based on study electrocardiographic and hospitalization records during follow-up. We used Cox regression to estimate relative risks of AF. Average age at baseline was 74.6 {\textpm} 5.1 years. During a mean follow-up of 10.0 years, 1,041 new cases of AF occurred. Crude incidence rates of AF were 23.7, 23.3, 23.9, and 29.7 cases/1,000 person-years across consecutive quartiles of plasma FFAs. There was a positive association between plasma FFAs and risk of AF. Multivariable adjusted hazard ratios (95\% confidence intervals) for incident AF were 1.00 (referent), 1.02 (0.85 to 1.21), 1.05 (0.88 to 1.26), and 1.29 (1.08 to 1.55) from the lowest to highest quartiles of FFAs, respectively. In a secondary analysis restricted to the first 5 years of follow-up, this association persisted. In conclusion, our data show an increased risk of AF with higher plasma FFAs in community-dwelling older adults.

}, keywords = {Aged, Atrial Fibrillation, C-Reactive Protein, Diabetes Mellitus, Type 2, Fatty Acids, Nonesterified, Female, Follow-Up Studies, Humans, Hypertension, Incidence, Lipoproteins, HDL, Lipoproteins, LDL, Male, Natriuretic Peptide, Brain, Obesity, Peptide Fragments, Prospective Studies, Sex Factors, Triglycerides, United States}, issn = {1879-1913}, doi = {10.1016/j.amjcard.2012.03.010}, author = {Khawaja, Owais and Bartz, Traci M and Ix, Joachim H and Heckbert, Susan R and Kizer, Jorge R and Zieman, Susan J and Mukamal, Kenneth J and Tracy, Russell P and Siscovick, David S and Djouss{\'e}, Luc} } @article {1552, title = {Fetuin-A, type 2 diabetes, and risk of cardiovascular disease in older adults: the cardiovascular health study.}, journal = {Diabetes Care}, volume = {36}, year = {2013}, month = {2013 May}, pages = {1222-8}, abstract = {

OBJECTIVE: Fetuin-A, a hepatic secretory protein that simultaneously inhibits arterial calcification and insulin action, is associated with type 2 diabetes, but its association with cardiovascular disease (CVD) is uncertain. Preliminary studies suggest that the association of fetuin-A with CVD might differ among individuals with or without type 2 diabetes.

RESEARCH DESIGN AND METHODS: This was a prospective study of 3,810 community-living individuals older than 65 years (511 with type 2 diabetes) and free of CVD in 1992 when fetuin-A levels were measured. Participants were followed-up for incident CVD through June 2008.

RESULTS: Mean age was 75 years, and 61\% were women; 1,456 participants had an incident CVD event (248 among individuals with type 2 diabetes). The association of fetuin-A with CVD was modified by type 2 diabetes (P interaction = 0.02). Higher fetuin-A was associated with lower CVD risk among persons without type 2 diabetes [hazard ratio per SD 0.1 g/L higher fetuin-A, 0.93 (95\% CI, 0.88-0.99)], whereas a trend in the opposite direction was observed among individuals with type 2 diabetes, although it was not statistically significant [1.07 (0.93-1.22)]. Among individuals without type 2 diabetes, similar effect modification was observed by obesity and insulin resistance. Consistently, higher fetuin-A was associated with lower CVD risk only in the subgroups without obesity or with HOMA-IR below the median [0.91 (0.85-0.97) and 0.87 (0.79-0.95), respectively].

CONCLUSIONS: The association of fetuin-A with risk of CVD differs among elderly individuals with and without insulin resistance or type 2 diabetes.

}, keywords = {Aged, Aged, 80 and over, Cardiovascular Diseases, Diabetes Mellitus, Type 2, Female, Fetuins, Humans, Incidence, Longitudinal Studies, Male, Risk Factors}, issn = {1935-5548}, doi = {10.2337/dc12-1591}, author = {Jensen, Majken K and Bartz, Traci M and Mukamal, Kenneth J and Djouss{\'e}, Luc and Kizer, Jorge R and Tracy, Russell P and Zieman, Susan J and Rimm, Eric B and Siscovick, David S and Shlipak, Michael and Ix, Joachim H} } @article {6289, title = {Generalization and dilution of association results from European GWAS in populations of non-European ancestry: the PAGE study.}, journal = {PLoS Biol}, volume = {11}, year = {2013}, month = {2013 Sep}, pages = {e1001661}, abstract = {

The vast majority of genome-wide association study (GWAS) findings reported to date are from populations with European Ancestry (EA), and it is not yet clear how broadly the genetic associations described will generalize to populations of diverse ancestry. The Population Architecture Using Genomics and Epidemiology (PAGE) study is a consortium of multi-ancestry, population-based studies formed with the objective of refining our understanding of the genetic architecture of common traits emerging from GWAS. In the present analysis of five common diseases and traits, including body mass index, type 2 diabetes, and lipid levels, we compare direction and magnitude of effects for GWAS-identified variants in multiple non-EA populations against EA findings. We demonstrate that, in all populations analyzed, a significant majority of GWAS-identified variants have allelic associations in the same direction as in EA, with none showing a statistically significant effect in the opposite direction, after adjustment for multiple testing. However, 25\% of tagSNPs identified in EA GWAS have significantly different effect sizes in at least one non-EA population, and these differential effects were most frequent in African Americans where all differential effects were diluted toward the null. We demonstrate that differential LD between tagSNPs and functional variants within populations contributes significantly to dilute effect sizes in this population. Although most variants identified from GWAS in EA populations generalize to all non-EA populations assessed, genetic models derived from GWAS findings in EA may generate spurious results in non-EA populations due to differential effect sizes. Regardless of the origin of the differential effects, caution should be exercised in applying any genetic risk prediction model based on tagSNPs outside of the ancestry group in which it was derived. Models based directly on functional variation may generalize more robustly, but the identification of functional variants remains challenging.

}, keywords = {African Americans, Asian Americans, Body Mass Index, Diabetes Mellitus, Type 2, European Continental Ancestry Group, Gene Frequency, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Hispanic Americans, Humans, Indians, North American, Lipids, Metagenomics, Oceanic Ancestry Group, Polymorphism, Single Nucleotide}, issn = {1545-7885}, doi = {10.1371/journal.pbio.1001661}, author = {Carlson, Christopher S and Matise, Tara C and North, Kari E and Haiman, Christopher A and Fesinmeyer, Megan D and Buyske, Steven and Schumacher, Fredrick R and Peters, Ulrike and Franceschini, Nora and Ritchie, Marylyn D and Duggan, David J and Spencer, Kylee L and Dumitrescu, Logan and Eaton, Charles B and Thomas, Fridtjof and Young, Alicia and Carty, Cara and Heiss, Gerardo and Le Marchand, Lo{\"\i}c and Crawford, Dana C and Hindorff, Lucia A and Kooperberg, Charles L} } @article {6290, title = {Genetic variants associated with fasting glucose and insulin concentrations in an ethnically diverse population: results from the Population Architecture using Genomics and Epidemiology (PAGE) study.}, journal = {BMC Med Genet}, volume = {14}, year = {2013}, month = {2013 Sep 25}, pages = {98}, abstract = {

BACKGROUND: Multiple genome-wide association studies (GWAS) within European populations have implicated common genetic variants associated with insulin and glucose concentrations. In contrast, few studies have been conducted within minority groups, which carry the highest burden of impaired glucose homeostasis and type 2 diabetes in the U.S.

METHODS: As part of the {\textquoteright}Population Architecture using Genomics and Epidemiology (PAGE) Consortium, we investigated the association of up to 10 GWAS-identified single nucleotide polymorphisms (SNPs) in 8 genetic regions with glucose or insulin concentrations in up to 36,579 non-diabetic subjects including 23,323 European Americans (EA) and 7,526 African Americans (AA), 3,140 Hispanics, 1,779 American Indians (AI), and 811 Asians. We estimated the association between each SNP and fasting glucose or log-transformed fasting insulin, followed by meta-analysis to combine results across PAGE sites.

RESULTS: Overall, our results show that 9/9 GWAS SNPs are associated with glucose in EA (p = 0.04 to 9 {\texttimes} 10-15), versus 3/9 in AA (p= 0.03 to 6 {\texttimes} 10-5), 3/4 SNPs in Hispanics, 2/4 SNPs in AI, and 1/2 SNPs in Asians. For insulin we observed a significant association with rs780094/GCKR in EA, Hispanics and AI only.

CONCLUSIONS: Generalization of results across multiple racial/ethnic groups helps confirm the relevance of some of these loci for glucose and insulin metabolism. Lack of association in non-EA groups may be due to insufficient power, or to unique patterns of linkage disequilibrium.

}, keywords = {Adaptor Proteins, Signal Transducing, Adult, African Americans, Aged, Alleles, Asian Continental Ancestry Group, Blood Glucose, Diabetes Mellitus, Type 2, European Continental Ancestry Group, Female, Gene Frequency, Genetic Loci, Genome-Wide Association Study, Genomics, Hispanic Americans, Humans, Indians, North American, Insulin, Male, Middle Aged, Polymorphism, Single Nucleotide, Transcription Factor 7-Like 2 Protein}, issn = {1471-2350}, doi = {10.1186/1471-2350-14-98}, author = {Fesinmeyer, Megan D and Meigs, James B and North, Kari E and Schumacher, Fredrick R and B{\r u}zkov{\'a}, Petra and Franceschini, Nora and Haessler, Jeffrey and Goodloe, Robert and Spencer, Kylee L and Voruganti, Venkata Saroja and Howard, Barbara V and Jackson, Rebecca and Kolonel, Laurence N and Liu, Simin and Manson, JoAnn E and Monroe, Kristine R and Mukamal, Kenneth and Dilks, Holli H and Pendergrass, Sarah A and Nato, Andrew and Wan, Peggy and Wilkens, Lynne R and Le Marchand, Lo{\"\i}c and Ambite, Jose Luis and Buyske, Steven and Florez, Jose C and Crawford, Dana C and Hindorff, Lucia A and Haiman, Christopher A and Peters, Ulrike and Pankow, James S} } @article {5995, title = {Genetically elevated fetuin-A levels, fasting glucose levels, and risk of type 2 diabetes: the cardiovascular health study.}, journal = {Diabetes Care}, volume = {36}, year = {2013}, month = {2013 Oct}, pages = {3121-7}, abstract = {

OBJECTIVE: Fetuin-A levels are associated with higher risk of type 2 diabetes, but it is unknown if the association is causal. We investigated common (>5\%) genetic variants in the fetuin-A gene (AHSG) fetuin-A levels, fasting glucose, and risk of type 2 diabetes.

RESEARCH DESIGN AND METHODS: Genetic variation, fetuin-A levels, and fasting glucose were assessed in 2,893 Caucasian and 542 African American community-living individuals 65 years of age or older in 1992-1993.

RESULTS: Common AHSG variants (rs4917 and rs2248690) were strongly associated with fetuin-A concentrations (P<0.0001). In analyses of 259 incident cases of type 2 diabetes, the single nucleotide polymorphisms (SNPs) were not associated with diabetes risk during follow-up and similar null associations were observed when 579 prevalent cases were included. As expected, higher fetuin-A levels were associated with higher fasting glucose concentrations (1.9 mg/dL [95\% CI, 1.2-2.7] higher per SD in Caucasians), but Mendelian randomization analyses using both SNPs as unbiased proxies for measured fetuin-A did not support an association between genetically predicted fetuin-A levels and fasting glucose (-0.3 mg/dL [95\% CI, -1.9 to 1.3] lower per SD in Caucasians). The difference between the associations of fasting glucose with actual and genetically predicted fetuin-A level was statistically significant (P=0.001). Results among the smaller sample of African Americans trended in similar directions but were statistically insignificant.

CONCLUSIONS: Common variants in the AHSG gene are strongly associated with plasma fetuin-A concentrations, but not with risk of type 2 diabetes or glucose concentrations, raising the possibility that the association between fetuin-A and type 2 diabetes may not be causal.

}, keywords = {alpha-2-HS-Glycoprotein, Blood Glucose, Diabetes Mellitus, Type 2, Fasting, Female, Genotype, Humans, Male, Polymorphism, Single Nucleotide}, issn = {1935-5548}, doi = {10.2337/dc12-2323}, author = {Jensen, Majken K and Bartz, Traci M and Djouss{\'e}, Luc and Kizer, Jorge R and Zieman, Susan J and Rimm, Eric B and Siscovick, David S and Psaty, Bruce M and Ix, Joachim H and Mukamal, Kenneth J} } @article {5880, title = {Genome-wide association study identifies novel loci associated with concentrations of four plasma phospholipid fatty acids in the de novo lipogenesis pathway: results from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortiu}, journal = {Circ Cardiovasc Genet}, volume = {6}, year = {2013}, month = {2013 Apr}, pages = {171-83}, abstract = {

BACKGROUND- Palmitic acid (16:0), stearic acid (18:0), palmitoleic acid (16:1n-7), and oleic acid (18:1n-9) are major saturated and monounsaturated fatty acids that affect cellular signaling and metabolic pathways. They are synthesized via de novo lipogenesis and are the main saturated and monounsaturated fatty acids in the diet. Levels of these fatty acids have been linked to diseases including type 2 diabetes mellitus and coronary heart disease. METHODS AND RESULTS- Genome-wide association studies were conducted in 5 population-based cohorts comprising 8961 participants of European ancestry to investigate the association of common genetic variation with plasma levels of these 4 fatty acids. We identified polymorphisms in 7 novel loci associated with circulating levels of >=1 of these fatty acids. ALG14 (asparagine-linked glycosylation 14 homolog) polymorphisms were associated with higher 16:0 (P=2.7{\texttimes}10(-11)) and lower 18:0 (P=2.2{\texttimes}10(-18)). FADS1 and FADS2 (desaturases) polymorphisms were associated with higher 16:1n-7 (P=6.6{\texttimes}10(-13)) and 18:1n-9 (P=2.2{\texttimes}10(-32)) and lower 18:0 (P=1.3{\texttimes}10(-20)). LPGAT1 (lysophosphatidylglycerol acyltransferase) polymorphisms were associated with lower 18:0 (P=2.8{\texttimes}10(-9)). GCKR (glucokinase regulator; P=9.8{\texttimes}10(-10)) and HIF1AN (factor inhibiting hypoxia-inducible factor-1; P=5.7{\texttimes}10(-9)) polymorphisms were associated with higher 16:1n-7, whereas PKD2L1 (polycystic kidney disease 2-like 1; P=5.7{\texttimes}10(-15)) and a locus on chromosome 2 (not near known genes) were associated with lower 16:1n-7 (P=4.1{\texttimes}10(-8)). CONCLUSIONS- Our findings provide novel evidence that common variations in genes with diverse functions, including protein-glycosylation, polyunsaturated fatty acid metabolism, phospholipid modeling, and glucose- and oxygen-sensing pathways, are associated with circulating levels of 4 fatty acids in the de novo lipogenesis pathway. These results expand our knowledge of genetic factors relevant to de novo lipogenesis and fatty acid biology.

}, keywords = {Adult, Aged, Chromosomes, Human, Pair 2, Cohort Studies, Coronary Disease, Diabetes Mellitus, Type 2, Fatty Acids, Monounsaturated, Female, Genetic Loci, Genome-Wide Association Study, Genotype, Humans, Linkage Disequilibrium, Lipogenesis, Male, Middle Aged, Oleic Acid, Palmitic Acid, Polymorphism, Single Nucleotide, Stearic Acids}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.112.964619}, author = {Wu, Jason H Y and Lemaitre, Rozenn N and Manichaikul, Ani and Guan, Weihua and Tanaka, Toshiko and Foy, Millennia and Kabagambe, Edmond K and Djouss{\'e}, Luc and Siscovick, David and Fretts, Amanda M and Johnson, Catherine and King, Irena B and Psaty, Bruce M and McKnight, Barbara and Rich, Stephen S and Chen, Yii-der I and Nettleton, Jennifer A and Tang, Weihong and Bandinelli, Stefania and Jacobs, David R and Browning, Brian L and Laurie, Cathy C and Gu, Xiangjun and Tsai, Michael Y and Steffen, Lyn M and Ferrucci, Luigi and Fornage, Myriam and Mozaffarian, Dariush} } @article {5994, title = {Risk factors for type 2 diabetes mellitus preceded by β-cell dysfunction, insulin resistance, or both in older adults: the Cardiovascular Health Study.}, journal = {Am J Epidemiol}, volume = {177}, year = {2013}, month = {2013 Jun 15}, pages = {1418-29}, chapter = {1418}, abstract = {

Insulin resistance (IR) and pancreatic β-cell dysfunction lead to type 2 diabetes mellitus (DM). We tested whether risk factors would differ for DM that was preceded predominantly by IR, β-cell dysfunction, or both among 4,384 older adults (mean age, 72.7 (standard deviation, 5.6) years) in the Cardiovascular Health Study, which was conducted in North Carolina, California, Maryland, and Pennsylvania (1989-2007). When evaluating established risk factors, we found older age, greater adiposity, higher systolic blood pressure, a lower high-density lipoprotein cholesterol level, a higher triglyceride level, and a lower alcohol intake to be independently associated with greater IR but, conversely, with better β-cell function (P < 0.001). The prospective associations between some risk factors and incident DM varied significantly depending on whether DM was preceded predominantly by IR, β-cell dysfunction, or both. For example, obesity and lower high-density lipoprotein cholesterol levels were positively associated with DM preceded predominantly by IR (hazard ratio (HR) = 5.02, 95\% confidence interval (CI): 2.81, 9.00; and HR = 1.97, 95\% CI: 1.32, 2.93, respectively), with a significant association with and an insignificant trend toward a lower risk of DM preceded predominantly by β-cell dysfunction (HR = 0.33, 95\% CI: 0.14, 0.80; and HR = 0.78, 95\% CI: 0.43, 1.39, respectively). In conclusion, among older adults, DM risk factors were differentially associated with DM preceded predominantly by IR or β-cell dysfunction. Biologic and clinical implications of putative subtypes of DM require further investigation.

}, keywords = {Adiposity, Age Factors, Aged, Aged, 80 and over, Aging, Alcohol Drinking, Blood Pressure, Cross-Sectional Studies, Diabetes Mellitus, Type 2, Female, Humans, Incidence, Insulin Resistance, Insulin-Secreting Cells, Lipids, Male, Prospective Studies, Risk Factors, Socioeconomic Factors, United States}, issn = {1476-6256}, doi = {10.1093/aje/kws440}, author = {Imamura, Fumiaki and Mukamal, Kenneth J and Meigs, James B and Luchsinger, Jos{\'e} A and Ix, Joachim H and Siscovick, David S and Mozaffarian, Dariush} } @article {6555, title = {Association of levels of fasting glucose and insulin with rare variants at the chromosome 11p11.2-MADD locus: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study.}, journal = {Circ Cardiovasc Genet}, volume = {7}, year = {2014}, month = {2014 Jun}, pages = {374-382}, abstract = {

BACKGROUND: Common variation at the 11p11.2 locus, encompassing MADD, ACP2, NR1H3, MYBPC3, and SPI1, has been associated in genome-wide association studies with fasting glucose and insulin (FI). In the Cohorts for Heart and Aging Research in Genomic Epidemiology Targeted Sequencing Study, we sequenced 5 gene regions at 11p11.2 to identify rare, potentially functional variants influencing fasting glucose or FI levels.

METHODS AND RESULTS: Sequencing (mean depth, 38{\texttimes}) across 16.1 kb in 3566 individuals without diabetes mellitus identified 653 variants, 79.9\% of which were rare (minor allele frequency <1\%) and novel. We analyzed rare variants in 5 gene regions with FI or fasting glucose using the sequence kernel association test. At NR1H3, 53 rare variants were jointly associated with FI (P=2.73{\texttimes}10(-3)); of these, 7 were predicted to have regulatory function and showed association with FI (P=1.28{\texttimes}10(-3)). Conditioning on 2 previously associated variants at MADD (rs7944584, rs10838687) did not attenuate this association, suggesting that there are >2 independent signals at 11p11.2. One predicted regulatory variant, chr11:47227430 (hg18; minor allele frequency=0.00068), contributed 20.6\% to the overall sequence kernel association test score at NR1H3, lies in intron 2 of NR1H3, and is a predicted binding site for forkhead box A1 (FOXA1), a transcription factor associated with insulin regulation. In human HepG2 hepatoma cells, the rare chr11:47227430 A allele disrupted FOXA1 binding and reduced FOXA1-dependent transcriptional activity.

CONCLUSIONS: Sequencing at 11p11.2-NR1H3 identified rare variation associated with FI. One variant, chr11:47227430, seems to be functional, with the rare A allele reducing transcription factor FOXA1 binding and FOXA1-dependent transcriptional activity.

}, keywords = {Aged, Aged, 80 and over, Aging, Blood Glucose, Chromosomes, Human, Pair 11, Cohort Studies, Death Domain Receptor Signaling Adaptor Proteins, Diabetes Mellitus, Type 2, Fasting, Female, Gene Frequency, Genetic Variation, Genome-Wide Association Study, Genomics, Guanine Nucleotide Exchange Factors, Heart Diseases, Humans, Insulin, Male, Middle Aged, Polymorphism, Single Nucleotide, Sequence Analysis, DNA}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.113.000169}, author = {Cornes, Belinda K and Brody, Jennifer A and Nikpoor, Naghmeh and Morrison, Alanna C and Chu, Huan and Ahn, Byung Soo and Wang, Shuai and Dauriz, Marco and Barzilay, Joshua I and Dupuis, Jos{\'e}e and Florez, Jose C and Coresh, Josef and Gibbs, Richard A and Kao, W H Linda and Liu, Ching-Ti and McKnight, Barbara and Muzny, Donna and Pankow, James S and Reid, Jeffrey G and White, Charles C and Johnson, Andrew D and Wong, Tien Y and Psaty, Bruce M and Boerwinkle, Eric and Rotter, Jerome I and Siscovick, David S and Sladek, Robert and Meigs, James B} } @article {6585, title = {Meta-analysis of genome-wide association studies in African Americans provides insights into the genetic architecture of type 2 diabetes.}, journal = {PLoS Genet}, volume = {10}, year = {2014}, month = {2014 Aug}, pages = {e1004517}, abstract = {

Type 2 diabetes (T2D) is more prevalent in African Americans than in Europeans. However, little is known about the genetic risk in African Americans despite the recent identification of more than 70 T2D loci primarily by genome-wide association studies (GWAS) in individuals of European ancestry. In order to investigate the genetic architecture of T2D in African Americans, the MEta-analysis of type 2 DIabetes in African Americans (MEDIA) Consortium examined 17 GWAS on T2D comprising 8,284 cases and 15,543 controls in African Americans in stage 1 analysis. Single nucleotide polymorphisms (SNPs) association analysis was conducted in each study under the additive model after adjustment for age, sex, study site, and principal components. Meta-analysis of approximately 2.6 million genotyped and imputed SNPs in all studies was conducted using an inverse variance-weighted fixed effect model. Replications were performed to follow up 21 loci in up to 6,061 cases and 5,483 controls in African Americans, and 8,130 cases and 38,987 controls of European ancestry. We identified three known loci (TCF7L2, HMGA2 and KCNQ1) and two novel loci (HLA-B and INS-IGF2) at genome-wide significance (4.15 {\texttimes} 10(-94)}, keywords = {African Americans, Diabetes Mellitus, Type 2, Genome-Wide Association Study, HLA-B27 Antigen, HMGA2 Protein, Humans, KCNQ1 Potassium Channel, Mutant Chimeric Proteins, Polymorphism, Single Nucleotide, Transcription Factor 7-Like 2 Protein}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1004517}, author = {Ng, Maggie C Y and Shriner, Daniel and Chen, Brian H and Li, Jiang and Chen, Wei-Min and Guo, Xiuqing and Liu, Jiankang and Bielinski, Suzette J and Yanek, Lisa R and Nalls, Michael A and Comeau, Mary E and Rasmussen-Torvik, Laura J and Jensen, Richard A and Evans, Daniel S and Sun, Yan V and An, Ping and Patel, Sanjay R and Lu, Yingchang and Long, Jirong and Armstrong, Loren L and Wagenknecht, Lynne and Yang, Lingyao and Snively, Beverly M and Palmer, Nicholette D and Mudgal, Poorva and Langefeld, Carl D and Keene, Keith L and Freedman, Barry I and Mychaleckyj, Josyf C and Nayak, Uma and Raffel, Leslie J and Goodarzi, Mark O and Chen, Y-D Ida and Taylor, Herman A and Correa, Adolfo and Sims, Mario and Couper, David and Pankow, James S and Boerwinkle, Eric and Adeyemo, Adebowale and Doumatey, Ayo and Chen, Guanjie and Mathias, Rasika A and Vaidya, Dhananjay and Singleton, Andrew B and Zonderman, Alan B and Igo, Robert P and Sedor, John R and Kabagambe, Edmond K and Siscovick, David S and McKnight, Barbara and Rice, Kenneth and Liu, Yongmei and Hsueh, Wen-Chi and Zhao, Wei and Bielak, Lawrence F and Kraja, Aldi and Province, Michael A and Bottinger, Erwin P and Gottesman, Omri and Cai, Qiuyin and Zheng, Wei and Blot, William J and Lowe, William L and Pacheco, Jennifer A and Crawford, Dana C and Grundberg, Elin and Rich, Stephen S and Hayes, M Geoffrey and Shu, Xiao-Ou and Loos, Ruth J F and Borecki, Ingrid B and Peyser, Patricia A and Cummings, Steven R and Psaty, Bruce M and Fornage, Myriam and Iyengar, Sudha K and Evans, Michele K and Becker, Diane M and Kao, W H Linda and Wilson, James G and Rotter, Jerome I and Sale, Mich{\`e}le M and Liu, Simin and Rotimi, Charles N and Bowden, Donald W} } @article {6270, title = {Sleep duration does not mediate or modify association of common genetic variants with type 2 diabetes.}, journal = {Diabetologia}, volume = {57}, year = {2014}, month = {2014 Feb}, pages = {339-46}, abstract = {

AIMS/HYPOTHESIS: Short and long sleep duration are associated with increased risk of type 2 diabetes. We aimed to investigate whether genetic variants for fasting glucose or type 2 diabetes associate with short or long sleep duration and whether sleep duration modifies the association of genetic variants with these traits.

METHODS: We examined the cross-sectional relationship between self-reported habitual sleep duration and prevalence of type 2 diabetes in individuals of European descent participating in five studies included in the Candidate Gene Association Resource (CARe), totalling 1,474 cases and 8,323 controls. We tested for association of 16 fasting glucose-associated variants, 27 type 2 diabetes-associated variants and aggregate genetic risk scores with continuous and dichotomised (<=5~h or >=9~h) sleep duration using regression models adjusted for age, sex and BMI. Finally, we tested whether a gene {\texttimes} behaviour interaction of variants with sleep duration had an impact on fasting glucose or type 2 diabetes risk.

RESULTS: Short sleep duration was significantly associated with type 2 diabetes in CARe (OR 1.32; 95\% CI 1.08, 1.61; p = 0.008). Variants previously associated with fasting glucose or type 2 diabetes and genetic risk scores were not associated with sleep duration. Furthermore, no study-wide significant interaction was observed between sleep duration and these variants on glycaemic traits. Nominal interactions were observed for sleep duration and PPARG rs1801282, CRY2 rs7943320 and HNF1B rs4430796 in influencing risk of type 2 diabetes (p < 0.05).

CONCLUSIONS/INTERPRETATION: Our findings suggest that differences in habitual sleep duration do not mediate or modify the relationship between common variants underlying glycaemic traits (including in circadian rhythm genes) and diabetes.

}, keywords = {Blood Glucose, Body Composition, Body Mass Index, Cross-Sectional Studies, Diabetes Mellitus, Type 2, European Continental Ancestry Group, Fasting, Female, Genetic Predisposition to Disease, Genetic Variation, Genotype, Glucose Intolerance, Glycated Hemoglobin A, Humans, Insulin Resistance, Male, Middle Aged, Polymorphism, Single Nucleotide, Risk Factors, Sleep, Surveys and Questionnaires, Time Factors, United States}, issn = {1432-0428}, doi = {10.1007/s00125-013-3110-y}, author = {Tare, Archana and Lane, Jacqueline M and Cade, Brian E and Grant, Struan F A and Chen, Ting-Hsu and Punjabi, Naresh M and Lauderdale, Diane S and Zee, Phyllis C and Gharib, Sina A and Gottlieb, Daniel J and Scheer, Frank A J L and Redline, Susan and Saxena, Richa} } @article {6679, title = {Atherosclerotic cardiovascular disease in older adults with diabetes mellitus.}, journal = {Clin Geriatr Med}, volume = {31}, year = {2015}, month = {2015 Feb}, pages = {29-39, vii}, abstract = {

Diabetes mellitus exerts a strong effect on atherosclerotic cardiovascular disease risk into older age (beyond ages 70-74 years). This effect is particularly noticeable with regard to coronary artery disease and cerebral microvascular disease. Thus, diabetes mellitus in older adults deserves the same careful medical attention as it does in middle age.

}, keywords = {Age Factors, Aged, Coronary Artery Disease, Diabetes Mellitus, Type 2, Female, Humans, Male, Risk Factors, Survival Rate}, issn = {1879-8853}, doi = {10.1016/j.cger.2014.09.001}, author = {Barzilay, Joshua I and Mukamal, Kenneth J and Kizer, Jorge R} } @article {6737, title = {Changes in insulin-like growth factor-I and its binding proteins are associated with diabetes mellitus in older adults.}, journal = {J Am Geriatr Soc}, volume = {63}, year = {2015}, month = {2015 May}, pages = {902-9}, abstract = {

OBJECTIVES: To determine whether changes in insulin-like growth factor (IGF) protein levels are greater in participants with type 2 diabetes mellitus or worsening glycemia than in normoglycemic individuals over a 9-year follow-up period.

DESIGN: Retrospective analysis of a cohort study.

SETTING: Participants were recruited from North Carolina, California, Maryland, and Pennsylvania.

PARTICIPANTS: Cardiovascular Health Study All Stars participants, a cohort study of community-dwelling adults aged 65 and older (N=897).

MEASUREMENTS: Plasma IGF-I, IGF binding protein (IGFBP)-1, and IGFBP-3 levels were assessed and American Diabetes Association cut-points for impaired glucose tolerance (IGT), impaired fasting glucose (IFG), and diabetes mellitus were used to classify participants at baseline (1996-97) and follow-up (2005-06).

RESULTS: At baseline, mean age was 76.3{\textpm}3.6, and 18.5\% had diabetes mellitus. Participants with IFG alone and IGT plus IFG had higher IGF-I levels and lower IGFBP-1 levels than those with normoglycemia or diabetes mellitus. The greatest percentage change in IGF levels occurred in those who had diabetes mellitus at baseline (9-year changes: -9.3\% for IGF-I, 59.7\% for IGFBP-1, -13.4\% for IGFBP-3), the smallest in individuals who remained normoglycemic at follow-up (9-year changes: -3.7\% for IGF-I, 25.6\% for IGFBP-1, -6.4\% for IGFBP-3), and intermediate in those who were normoglycemic but developed IFG at follow-up.

CONCLUSION: Degrees of glycemic impairment are associated with varying degrees of change in IGF protein levels. The changes observed in the diabetes mellitus group have been previously shown to be associated with heart failure, cancer, and noncancer mortality.

}, keywords = {Aged, Blood Glucose, Cohort Studies, Diabetes Mellitus, Type 2, Female, Humans, Insulin-Like Growth Factor Binding Protein 1, Insulin-Like Growth Factor Binding Protein 3, Insulin-Like Growth Factor I, Male, Retrospective Studies}, issn = {1532-5415}, doi = {10.1111/jgs.13390}, author = {Aneke-Nash, Chino S and Parrinello, Christina M and Rajpathak, Swapnil N and Rohan, Thomas E and Strotmeyer, Elsa S and Kritchevsky, Stephen B and Psaty, Bruce M and B{\r u}zkov{\'a}, Petra and Kizer, Jorge R and Newman, Anne B and Strickler, Howard D and Kaplan, Robert C} } @article {6664, title = {Circulating and dietary trans fatty acids and incident type 2 diabetes in older adults: the Cardiovascular Health Study.}, journal = {Diabetes Care}, volume = {38}, year = {2015}, month = {2015 Jun}, pages = {1099-107}, abstract = {

OBJECTIVE: To investigate the effects of trans fatty acids (TFAs) on type 2 diabetes mellitus (DM) by specific TFA subtype or method of assessment.

RESEARCH DESIGN AND METHODS: In the Cardiovascular Health Study, plasma phospholipid trans (t)-16:1n9, t-18:1, and cis (c)/t-, t/c-, and t/t-18:2 were measured in blood drawn from 2,919 adults aged 74 {\textpm} 5 years and free of prevalent DM in 1992. Dietary TFA was estimated among 4,207 adults free of prevalent DM when dietary questionnaires were initially administered in 1989 or 1996. Incident DM was defined through 2010 by medication use or blood glucose levels. Risks were assessed by Cox proportional hazards.

RESULTS: In biomarker analyses, 287 DM cases occurred during 30,825 person-years. Both t-16:1n9 (extreme quartile hazard ratio 1.59 [95\% CI 1.04-2.42], P-trend = 0.04) and t-18:1 (1.91 [1.20-3.03], P-trend = 0.01) levels were associated with higher incident DM after adjustment for de novo lipogenesis fatty acids. In dietary analyses, 407 DM cases occurred during 50,105 person-years. Incident DM was positively associated with consumption of total TFAs (1.38 [1.03-1.86], P-trend = 0.02), t-18:1 (1.32 [1.00-1.76], P-trend = 0.04), and t-18:2 (1.41 [1.05-1.89], P-trend = 0.02). After further adjustment for other dietary habits, however, the associations of estimated dietary TFA with DM were attenuated, and only nonsignificant positive trends remained.

CONCLUSIONS: Among older adults, plasma phospholipid t-16:1n9 and t-18:1 levels were positively related to DM after adjustment for de novo lipogenesis fatty acids. Estimated dietary TFA was not significantly associated with DM. These findings highlight the need for further observational, interventional, and experimental studies of the effects TFA on DM.

}, keywords = {Aged, Biomarkers, Diabetes Mellitus, Type 2, Diabetic Angiopathies, Dietary Fats, Unsaturated, Epidemiologic Methods, Female, Food Habits, Humans, Male, Phospholipids, Trans Fatty Acids}, issn = {1935-5548}, doi = {10.2337/dc14-2101}, author = {Wang, Qianyi and Imamura, Fumiaki and Ma, Wenjie and Wang, Molin and Lemaitre, Rozenn N and King, Irena B and Song, Xiaoling and Biggs, Mary L and Delaney, Joseph A and Mukamal, Kenneth J and Djouss{\'e}, Luc and Siscovick, David S and Mozaffarian, Dariush} } @article {6927, title = {Gene-Environment Interactions of Circadian-Related Genes for Cardiometabolic Traits.}, journal = {Diabetes Care}, volume = {38}, year = {2015}, month = {2015 Aug}, pages = {1456-66}, abstract = {

OBJECTIVE: Common circadian-related gene variants associate with increased risk for metabolic alterations including type 2 diabetes. However, little is known about whether diet and sleep could modify associations between circadian-related variants (CLOCK-rs1801260, CRY2-rs11605924, MTNR1B-rs1387153, MTNR1B-rs10830963, NR1D1-rs2314339) and cardiometabolic traits (fasting glucose [FG], HOMA-insulin resistance, BMI, waist circumference, and HDL-cholesterol) to facilitate personalized recommendations.

RESEARCH DESIGN AND METHODS: We conducted inverse-variance weighted, fixed-effect meta-analyses of results of adjusted associations and interactions between dietary intake/sleep duration and selected variants on cardiometabolic traits from 15 cohort studies including up to 28,190 participants of European descent from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium.

RESULTS: We observed significant associations between relative macronutrient intakes and glycemic traits and short sleep duration (<7 h) and higher FG and replicated known MTNR1B associations with glycemic traits. No interactions were evident after accounting for multiple comparisons. However, we observed nominally significant interactions (all P < 0.01) between carbohydrate intake and MTNR1B-rs1387153 for FG with a 0.003 mmol/L higher FG with each additional 1\% carbohydrate intake in the presence of the T allele, between sleep duration and CRY2-rs11605924 for HDL-cholesterol with a 0.010 mmol/L higher HDL-cholesterol with each additional hour of sleep in the presence of the A allele, and between long sleep duration (>=9 h) and MTNR1B-rs1387153 for BMI with a 0.60 kg/m(2) higher BMI with long sleep duration in the presence of the T allele relative to normal sleep duration (>=7 to <9 h).

CONCLUSIONS: Our results suggest that lower carbohydrate intake and normal sleep duration may ameliorate cardiometabolic abnormalities conferred by common circadian-related genetic variants. Until further mechanistic examination of the nominally significant interactions is conducted, recommendations applicable to the general population regarding diet{\textemdash}specifically higher carbohydrate and lower fat composition{\textemdash}and normal sleep duration should continue to be emphasized among individuals with the investigated circadian-related gene variants.

}, keywords = {Adult, Alleles, Blood Glucose, Circadian Rhythm Signaling Peptides and Proteins, Cohort Studies, Diabetes Mellitus, Type 2, Diet, Fat-Restricted, European Continental Ancestry Group, Fasting, Female, Gene-Environment Interaction, Humans, Insulin Resistance, Male, Middle Aged, Multicenter Studies as Topic, Observational Studies as Topic, Phenotype, Polymorphism, Single Nucleotide, Sleep, Waist Circumference}, issn = {1935-5548}, doi = {10.2337/dc14-2709}, author = {Dashti, Hassan S and Follis, Jack L and Smith, Caren E and Tanaka, Toshiko and Garaulet, Marta and Gottlieb, Daniel J and Hruby, Adela and Jacques, Paul F and Kiefte-de Jong, Jessica C and Lamon-Fava, Stefania and Scheer, Frank A J L and Bartz, Traci M and Kovanen, Leena and Wojczynski, Mary K and Frazier-Wood, Alexis C and Ahluwalia, Tarunveer S and Per{\"a}l{\"a}, Mia-Maria and Jonsson, Anna and Muka, Taulant and Kalafati, Ioanna P and Mikkil{\"a}, Vera and Ordovas, Jose M} } @article {6863, title = {HMG-coenzyme A reductase inhibition, type 2 diabetes, and bodyweight: evidence from genetic analysis and randomised trials.}, journal = {Lancet}, volume = {385}, year = {2015}, month = {2015 Jan 24}, pages = {351-61}, abstract = {

BACKGROUND: Statins increase the risk of new-onset type 2 diabetes mellitus. We aimed to assess whether this increase in risk is a consequence of inhibition of 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), the intended drug target.

METHODS: We used single nucleotide polymorphisms in the HMGCR gene, rs17238484 (for the main analysis) and rs12916 (for a subsidiary analysis) as proxies for HMGCR inhibition by statins. We examined associations of these variants with plasma lipid, glucose, and insulin concentrations; bodyweight; waist circumference; and prevalent and incident type 2 diabetes. Study-specific effect estimates per copy of each LDL-lowering allele were pooled by meta-analysis. These findings were compared with a meta-analysis of new-onset type 2 diabetes and bodyweight change data from randomised trials of statin drugs. The effects of statins in each randomised trial were assessed using meta-analysis.

FINDINGS: Data were available for up to 223 463 individuals from 43 genetic studies. Each additional rs17238484-G allele was associated with a mean 0{\textperiodcentered}06 mmol/L (95\% CI 0{\textperiodcentered}05-0{\textperiodcentered}07) lower LDL cholesterol and higher body weight (0{\textperiodcentered}30 kg, 0{\textperiodcentered}18-0{\textperiodcentered}43), waist circumference (0{\textperiodcentered}32 cm, 0{\textperiodcentered}16-0{\textperiodcentered}47), plasma insulin concentration (1{\textperiodcentered}62\%, 0{\textperiodcentered}53-2{\textperiodcentered}72), and plasma glucose concentration (0{\textperiodcentered}23\%, 0{\textperiodcentered}02-0{\textperiodcentered}44). The rs12916 SNP had similar effects on LDL cholesterol, bodyweight, and waist circumference. The rs17238484-G allele seemed to be associated with higher risk of type 2 diabetes (odds ratio [OR] per allele 1{\textperiodcentered}02, 95\% CI 1{\textperiodcentered}00-1{\textperiodcentered}05); the rs12916-T allele association was consistent (1{\textperiodcentered}06, 1{\textperiodcentered}03-1{\textperiodcentered}09). In 129 170 individuals in randomised trials, statins lowered LDL cholesterol by 0{\textperiodcentered}92 mmol/L (95\% CI 0{\textperiodcentered}18-1{\textperiodcentered}67) at 1-year of follow-up, increased bodyweight by 0{\textperiodcentered}24 kg (95\% CI 0{\textperiodcentered}10-0{\textperiodcentered}38 in all trials; 0{\textperiodcentered}33 kg, 95\% CI 0{\textperiodcentered}24-0{\textperiodcentered}42 in placebo or standard care controlled trials and -0{\textperiodcentered}15 kg, 95\% CI -0{\textperiodcentered}39 to 0{\textperiodcentered}08 in intensive-dose vs moderate-dose trials) at a mean of 4{\textperiodcentered}2 years (range 1{\textperiodcentered}9-6{\textperiodcentered}7) of follow-up, and increased the odds of new-onset type 2 diabetes (OR 1{\textperiodcentered}12, 95\% CI 1{\textperiodcentered}06-1{\textperiodcentered}18 in all trials; 1{\textperiodcentered}11, 95\% CI 1{\textperiodcentered}03-1{\textperiodcentered}20 in placebo or standard care controlled trials and 1{\textperiodcentered}12, 95\% CI 1{\textperiodcentered}04-1{\textperiodcentered}22 in intensive-dose vs moderate dose trials).

INTERPRETATION: The increased risk of type 2 diabetes noted with statins is at least partially explained by HMGCR inhibition.

FUNDING: The funding sources are cited at the end of the paper.

}, keywords = {Aged, Body Mass Index, Body Weight, Cholesterol, HDL, Cholesterol, LDL, Diabetes Mellitus, Type 2, Female, Genetic Testing, Humans, Hydroxymethylglutaryl CoA Reductases, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Male, Middle Aged, Polymorphism, Single Nucleotide, Randomized Controlled Trials as Topic, Risk Factors}, issn = {1474-547X}, doi = {10.1016/S0140-6736(14)61183-1}, author = {Swerdlow, Daniel I and Preiss, David and Kuchenbaecker, Karoline B and Holmes, Michael V and Engmann, Jorgen E L and Shah, Tina and Sofat, Reecha and Stender, Stefan and Johnson, Paul C D and Scott, Robert A and Leusink, Maarten and Verweij, Niek and Sharp, Stephen J and Guo, Yiran and Giambartolomei, Claudia and Chung, Christina and Peasey, Anne and Amuzu, Antoinette and Li, KaWah and Palmen, Jutta and Howard, Philip and Cooper, Jackie A and Drenos, Fotios and Li, Yun R and Lowe, Gordon and Gallacher, John and Stewart, Marlene C W and Tzoulaki, Ioanna and Buxbaum, Sarah G and van der A, Daphne L and Forouhi, Nita G and Onland-Moret, N Charlotte and van der Schouw, Yvonne T and Schnabel, Renate B and Hubacek, Jaroslav A and Kubinova, Ruzena and Baceviciene, Migle and Tamosiunas, Abdonas and Pajak, Andrzej and Topor-Madry, Roman and Stepaniak, Urszula and Malyutina, Sofia and Baldassarre, Damiano and Sennblad, Bengt and Tremoli, Elena and de Faire, Ulf and Veglia, Fabrizio and Ford, Ian and Jukema, J Wouter and Westendorp, Rudi G J and de Borst, Gert Jan and de Jong, Pim A and Algra, Ale and Spiering, Wilko and Maitland-van der Zee, Anke H and Klungel, Olaf H and de Boer, Anthonius and Doevendans, Pieter A and Eaton, Charles B and Robinson, Jennifer G and Duggan, David and Kjekshus, John and Downs, John R and Gotto, Antonio M and Keech, Anthony C and Marchioli, Roberto and Tognoni, Gianni and Sever, Peter S and Poulter, Neil R and Waters, David D and Pedersen, Terje R and Amarenco, Pierre and Nakamura, Haruo and McMurray, John J V and Lewsey, James D and Chasman, Daniel I and Ridker, Paul M and Maggioni, Aldo P and Tavazzi, Luigi and Ray, Kausik K and Seshasai, Sreenivasa Rao Kondapally and Manson, JoAnn E and Price, Jackie F and Whincup, Peter H and Morris, Richard W and Lawlor, Debbie A and Smith, George Davey and Ben-Shlomo, Yoav and Schreiner, Pamela J and Fornage, Myriam and Siscovick, David S and Cushman, Mary and Kumari, Meena and Wareham, Nick J and Verschuren, W M Monique and Redline, Susan and Patel, Sanjay R and Whittaker, John C and Hamsten, Anders and Delaney, Joseph A and Dale, Caroline and Gaunt, Tom R and Wong, Andrew and Kuh, Diana and Hardy, Rebecca and Kathiresan, Sekar and Castillo, Berta A and van der Harst, Pim and Brunner, Eric J and Tybjaerg-Hansen, Anne and Marmot, Michael G and Krauss, Ronald M and Tsai, Michael and Coresh, Josef and Hoogeveen, Ronald C and Psaty, Bruce M and Lange, Leslie A and Hakonarson, Hakon and Dudbridge, Frank and Humphries, Steve E and Talmud, Philippa J and Kivimaki, Mika and Timpson, Nicholas J and Langenberg, Claudia and Asselbergs, Folkert W and Voevoda, Mikhail and Bobak, Martin and Pikhart, Hynek and Wilson, James G and Reiner, Alex P and Keating, Brendan J and Hingorani, Aroon D and Sattar, Naveed} } @article {6686, title = {Low-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility.}, journal = {Nat Commun}, volume = {6}, year = {2015}, month = {2015}, pages = {5897}, abstract = {

Fasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF=1.4\%) with lower FG (β=-0.09{\textpm}0.01 mmol l(-1), P=3.4 {\texttimes} 10(-12)), T2D risk (OR[95\%CI]=0.86[0.76-0.96], P=0.010), early insulin secretion (β=-0.07{\textpm}0.035 pmolinsulin mmolglucose(-1), P=0.048), but higher 2-h glucose (β=0.16{\textpm}0.05 mmol l(-1), P=4.3 {\texttimes} 10(-4)). We identify a gene-based association with FG at G6PC2 (pSKAT=6.8 {\texttimes} 10(-6)) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF=20\%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (β=0.02{\textpm}0.004 mmol l(-1), P=1.3 {\texttimes} 10(-8)). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.

}, keywords = {African Continental Ancestry Group, Blood Glucose, Diabetes Mellitus, Type 2, European Continental Ancestry Group, Exome, Fasting, Genetic Association Studies, Genetic Loci, Genetic Predisposition to Disease, Genetic Variation, Glucagon-Like Peptide-1 Receptor, Glucose-6-Phosphatase, Humans, Insulin, Mutation Rate, Oligonucleotide Array Sequence Analysis, Polymorphism, Single Nucleotide}, issn = {2041-1723}, doi = {10.1038/ncomms6897}, author = {Wessel, Jennifer and Chu, Audrey Y and Willems, Sara M and Wang, Shuai and Yaghootkar, Hanieh and Brody, Jennifer A and Dauriz, Marco and Hivert, Marie-France and Raghavan, Sridharan and Lipovich, Leonard and Hidalgo, Bertha and Fox, Keolu and Huffman, Jennifer E and An, Ping and Lu, Yingchang and Rasmussen-Torvik, Laura J and Grarup, Niels and Ehm, Margaret G and Li, Li and Baldridge, Abigail S and Stan{\v c}{\'a}kov{\'a}, Alena and Abrol, Ravinder and Besse, C{\'e}line and Boland, Anne and Bork-Jensen, Jette and Fornage, Myriam and Freitag, Daniel F and Garcia, Melissa E and Guo, Xiuqing and Hara, Kazuo and Isaacs, Aaron and Jakobsdottir, Johanna and Lange, Leslie A and Layton, Jill C and Li, Man and Hua Zhao, Jing and Meidtner, Karina and Morrison, Alanna C and Nalls, Mike A and Peters, Marjolein J and Sabater-Lleal, Maria and Schurmann, Claudia and Silveira, Angela and Smith, Albert V and Southam, Lorraine and Stoiber, Marcus H and Strawbridge, Rona J and Taylor, Kent D and Varga, Tibor V and Allin, Kristine H and Amin, Najaf and Aponte, Jennifer L and Aung, Tin and Barbieri, Caterina and Bihlmeyer, Nathan A and Boehnke, Michael and Bombieri, Cristina and Bowden, Donald W and Burns, Sean M and Chen, Yuning and Chen, Yii-DerI and Cheng, Ching-Yu and Correa, Adolfo and Czajkowski, Jacek and Dehghan, Abbas and Ehret, Georg B and Eiriksdottir, Gudny and Escher, Stefan A and Farmaki, Aliki-Eleni and Fr{\r a}nberg, Mattias and Gambaro, Giovanni and Giulianini, Franco and Goddard, William A and Goel, Anuj and Gottesman, Omri and Grove, Megan L and Gustafsson, Stefan and Hai, Yang and Hallmans, G{\"o}ran and Heo, Jiyoung and Hoffmann, Per and Ikram, Mohammad K and Jensen, Richard A and J{\o}rgensen, Marit E and J{\o}rgensen, Torben and Karaleftheri, Maria and Khor, Chiea C and Kirkpatrick, Andrea and Kraja, Aldi T and Kuusisto, Johanna and Lange, Ethan M and Lee, I T and Lee, Wen-Jane and Leong, Aaron and Liao, Jiemin and Liu, Chunyu and Liu, Yongmei and Lindgren, Cecilia M and Linneberg, Allan and Malerba, Giovanni and Mamakou, Vasiliki and Marouli, Eirini and Maruthur, Nisa M and Matchan, Angela and McKean-Cowdin, Roberta and McLeod, Olga and Metcalf, Ginger A and Mohlke, Karen L and Muzny, Donna M and Ntalla, Ioanna and Palmer, Nicholette D and Pasko, Dorota and Peter, Andreas and Rayner, Nigel W and Renstrom, Frida and Rice, Ken and Sala, Cinzia F and Sennblad, Bengt and Serafetinidis, Ioannis and Smith, Jennifer A and Soranzo, Nicole and Speliotes, Elizabeth K and Stahl, Eli A and Stirrups, Kathleen and Tentolouris, Nikos and Thanopoulou, Anastasia and Torres, Mina and Traglia, Michela and Tsafantakis, Emmanouil and Javad, Sundas and Yanek, Lisa R and Zengini, Eleni and Becker, Diane M and Bis, Joshua C and Brown, James B and Cupples, L Adrienne and Hansen, Torben and Ingelsson, Erik and Karter, Andrew J and Lorenzo, Carlos and Mathias, Rasika A and Norris, Jill M and Peloso, Gina M and Sheu, Wayne H-H and Toniolo, Daniela and Vaidya, Dhananjay and Varma, Rohit and Wagenknecht, Lynne E and Boeing, Heiner and Bottinger, Erwin P and Dedoussis, George and Deloukas, Panos and Ferrannini, Ele and Franco, Oscar H and Franks, Paul W and Gibbs, Richard A and Gudnason, Vilmundur and Hamsten, Anders and Harris, Tamara B and Hattersley, Andrew T and Hayward, Caroline and Hofman, Albert and Jansson, Jan-H{\r a}kan and Langenberg, Claudia and Launer, Lenore J and Levy, Daniel and Oostra, Ben A and O{\textquoteright}Donnell, Christopher J and O{\textquoteright}Rahilly, Stephen and Padmanabhan, Sandosh and Pankow, James S and Polasek, Ozren and Province, Michael A and Rich, Stephen S and Ridker, Paul M and Rudan, Igor and Schulze, Matthias B and Smith, Blair H and Uitterlinden, Andr{\'e} G and Walker, Mark and Watkins, Hugh and Wong, Tien Y and Zeggini, Eleftheria and Laakso, Markku and Borecki, Ingrid B and Chasman, Daniel I and Pedersen, Oluf and Psaty, Bruce M and Tai, E Shyong and van Duijn, Cornelia M and Wareham, Nicholas J and Waterworth, Dawn M and Boerwinkle, Eric and Kao, W H Linda and Florez, Jose C and Loos, Ruth J F and Wilson, James G and Frayling, Timothy M and Siscovick, David S and Dupuis, Jos{\'e}e and Rotter, Jerome I and Meigs, James B and Scott, Robert A and Goodarzi, Mark O} } @article {6616, title = {Prospective association of fatty acids in the de novo lipogenesis pathway with risk of type 2 diabetes: the Cardiovascular Health Study.}, journal = {Am J Clin Nutr}, volume = {101}, year = {2015}, month = {2015 Jan}, pages = {153-63}, abstract = {

BACKGROUND: Experimental evidence suggests that hepatic de novo lipogenesis (DNL) affects insulin homeostasis via synthesis of saturated fatty acids (SFAs) and monounsaturated fatty acids (MUFAs). Few prospective studies have used fatty acid biomarkers to assess associations with type 2 diabetes.

OBJECTIVES: We investigated associations of major circulating SFAs [palmitic acid (16:0) and stearic acid (18:0)] and MUFA [oleic acid (18:1n-9)] in the DNL pathway with metabolic risk factors and incident diabetes in community-based older U.S. adults in the Cardiovascular Health Study. We secondarily assessed other DNL fatty acid biomarkers [myristic acid (14:0), palmitoleic acid (16:1n-7), 7-hexadecenoic acid (16:1n-9), and vaccenic acid (18:1n-7)] and estimated dietary SFAs and MUFAs.

DESIGN: In 3004 participants free of diabetes, plasma phospholipid fatty acids were measured in 1992, and incident diabetes was identified by medication use and blood glucose. Usual diets were assessed by using repeated food-frequency questionnaires. Multivariable linear and Cox regression were used to assess associations with metabolic risk factors and incident diabetes, respectively.

RESULTS: At baseline, circulating palmitic acid and stearic acid were positively associated with adiposity, triglycerides, inflammation biomarkers, and insulin resistance (P-trend < 0.01 each), whereas oleic acid showed generally beneficial associations (P-trend < 0.001 each). During 30,763 person-years, 297 incident diabetes cases occurred. With adjustment for demographics and lifestyle, palmitic acid (extreme-quintile HR: 1.89; 95\% CI: 1.27, 2.83; P-trend = 0.001) and stearic acid (HR: 1.62; 95\% CI: 1.09, 2.41; P-trend = 0.006) were associated with higher diabetes risk, whereas oleic acid was not significantly associated. In secondary analyses, vaccenic acid was inversely associated with diabetes (HR: 0.56; 95\% CI: 0.38, 0.83; P-trend = 0.005). Other fatty acid biomarkers and estimated dietary SFAs or MUFAs were not significantly associated with incident diabetes.

CONCLUSIONS: In this large prospective cohort, circulating palmitic acid and stearic acid were associated with higher diabetes risk, and vaccenic acid was associated with lower diabetes risk. These results indicate a need for additional investigation of biological mechanisms linking specific fatty acids in the DNL pathway to the pathogenesis of diabetes.

}, keywords = {Aged, Biomarkers, Cohort Studies, Cross-Sectional Studies, Diabetes Mellitus, Type 2, Female, Follow-Up Studies, Humans, Incidence, Lipogenesis, Liver, Male, Palmitic Acid, Phospholipids, Prevalence, Proportional Hazards Models, Risk Factors, Stearic Acids, United States, Up-Regulation}, issn = {1938-3207}, doi = {10.3945/ajcn.114.092601}, author = {Ma, Wenjie and Wu, Jason H Y and Wang, Qianyi and Lemaitre, Rozenn N and Mukamal, Kenneth J and Djouss{\'e}, Luc and King, Irena B and Song, Xiaoling and Biggs, Mary L and Delaney, Joseph A and Kizer, Jorge R and Siscovick, David S and Mozaffarian, Dariush} } @article {6854, title = {Sleep Disturbances and Glucose Metabolism in Older Adults: The Cardiovascular Health Study.}, journal = {Diabetes Care}, volume = {38}, year = {2015}, month = {2015 Nov}, pages = {2050-8}, abstract = {

OBJECTIVE: We examined the associations of symptoms of sleep-disordered breathing (SDB), which was defined as loud snoring, stopping breathing for a while during sleep, and daytime sleepiness, and insomnia with glucose metabolism and incident type 2 diabetes in older adults.

RESEARCH DESIGN AND METHODS: Between 1989 and 1993, the Cardiovascular Health Study recruited 5,888 participants >=65 years of age from four U.S. communities. Participants reported SDB and insomnia symptoms yearly through 1989-1994. In 1989-1990, participants underwent an oral glucose tolerance test, from which insulin secretion and insulin sensitivity were estimated. Fasting glucose levels were measured in 1989-1990 and again in 1992-1993, 1994-1995, 1996-1997, and 1998-1999, and medication use was ascertained yearly. We determined the cross-sectional associations of sleep symptoms with fasting glucose levels, 2-h glucose levels, insulin sensitivity, and insulin secretion using generalized estimated equations and linear regression models. We determined the associations of updated and averaged sleep symptoms with incident diabetes in Cox proportional hazards models. We adjusted for sociodemographics, lifestyle factors, and medical history.

RESULTS: Observed apnea, snoring, and daytime sleepiness were associated with higher fasting glucose levels, higher 2-h glucose levels, lower insulin sensitivity, and higher insulin secretion. The risk of the development of type 2 diabetes was positively associated with observed apnea (hazard ratio [HR] 1.84 [95\% CI 1.19-2.86]), snoring (HR 1.27 [95\% CI 0.95-1.71]), and daytime sleepiness (HR 1.54 [95\% CI 1.13-2.12]). In contrast, we did not find consistent associations between insomnia symptoms and glucose metabolism or incident type 2 diabetes.

CONCLUSIONS: Easily collected symptoms of SDB are strongly associated with insulin resistance and the incidence of type 2 diabetes in older adults. Monitoring glucose metabolism in such patients may prove useful in identifying candidates for lifestyle or pharmacological therapy. Further studies are needed to determine whether insomnia symptoms affect the risk of diabetes in younger adults.

}, keywords = {Adult, Aged, Blood Glucose, Cardiovascular System, Cross-Sectional Studies, Diabetes Mellitus, Type 2, Fasting, Female, Glucose Tolerance Test, Humans, Incidence, Insulin, Insulin Resistance, Male, Middle Aged, Sleep Apnea Syndromes, Sleep Initiation and Maintenance Disorders, Snoring, United States}, issn = {1935-5548}, doi = {10.2337/dc15-0137}, author = {Strand, Linn Beate and Carnethon, Mercedes and Biggs, Mary Lou and Djouss{\'e}, Luc and Kaplan, Robert C and Siscovick, David S and Robbins, John A and Redline, Susan and Patel, Sanjay R and Janszky, Imre and Mukamal, Kenneth J} } @article {7573, title = {Exome-wide association study of plasma lipids in >300,000 individuals.}, journal = {Nat Genet}, volume = {49}, year = {2017}, month = {2017 Dec}, pages = {1758-1766}, abstract = {

We screened variants on an exome-focused genotyping array in >300,000 participants (replication in >280,000 participants) and identified 444 independent variants in 250 loci significantly associated with total cholesterol (TC), high-density-lipoprotein cholesterol (HDL-C), low-density-lipoprotein cholesterol (LDL-C), and/or triglycerides (TG). At two loci (JAK2 and A1CF), experimental analysis in mice showed lipid changes consistent with the human data. We also found that: (i) beta-thalassemia trait carriers displayed lower TC and were protected from coronary artery disease (CAD); (ii) excluding the CETP locus, there was not a predictable relationship between plasma HDL-C and risk for age-related macular degeneration; (iii) only some mechanisms of lowering LDL-C appeared to increase risk for type 2 diabetes (T2D); and (iv) TG-lowering alleles involved in hepatic production of TG-rich lipoproteins (TM6SF2 and PNPLA3) tracked with higher liver fat, higher risk for T2D, and lower risk for CAD, whereas TG-lowering alleles involved in peripheral lipolysis (LPL and ANGPTL4) had no effect on liver fat but decreased risks for both T2D and CAD.

}, keywords = {Coronary Artery Disease, Diabetes Mellitus, Type 2, Exome, Genetic Association Studies, Genetic Predisposition to Disease, Genetic Variation, Genotype, Humans, Lipids, Macular Degeneration, Phenotype, Risk Factors}, issn = {1546-1718}, doi = {10.1038/ng.3977}, author = {Liu, Dajiang J and Peloso, Gina M and Yu, Haojie and Butterworth, Adam S and Wang, Xiao and Mahajan, Anubha and Saleheen, Danish and Emdin, Connor and Alam, Dewan and Alves, Alexessander Couto and Amouyel, Philippe and Di Angelantonio, Emanuele and Arveiler, Dominique and Assimes, Themistocles L and Auer, Paul L and Baber, Usman and Ballantyne, Christie M and Bang, Lia E and Benn, Marianne and Bis, Joshua C and Boehnke, Michael and Boerwinkle, Eric and Bork-Jensen, Jette and Bottinger, Erwin P and Brandslund, Ivan and Brown, Morris and Busonero, Fabio and Caulfield, Mark J and Chambers, John C and Chasman, Daniel I and Chen, Y Eugene and Chen, Yii-Der Ida and Chowdhury, Rajiv and Christensen, Cramer and Chu, Audrey Y and Connell, John M and Cucca, Francesco and Cupples, L Adrienne and Damrauer, Scott M and Davies, Gail and Deary, Ian J and Dedoussis, George and Denny, Joshua C and Dominiczak, Anna and Dub{\'e}, Marie-Pierre and Ebeling, Tapani and Eiriksdottir, Gudny and Esko, T{\~o}nu and Farmaki, Aliki-Eleni and Feitosa, Mary F and Ferrario, Marco and Ferrieres, Jean and Ford, Ian and Fornage, Myriam and Franks, Paul W and Frayling, Timothy M and Frikke-Schmidt, Ruth and Fritsche, Lars G and Frossard, Philippe and Fuster, Valentin and Ganesh, Santhi K and Gao, Wei and Garcia, Melissa E and Gieger, Christian and Giulianini, Franco and Goodarzi, Mark O and Grallert, Harald and Grarup, Niels and Groop, Leif and Grove, Megan L and Gudnason, Vilmundur and Hansen, Torben and Harris, Tamara B and Hayward, Caroline and Hirschhorn, Joel N and Holmen, Oddgeir L and Huffman, Jennifer and Huo, Yong and Hveem, Kristian and Jabeen, Sehrish and Jackson, Anne U and Jakobsdottir, Johanna and Jarvelin, Marjo-Riitta and Jensen, Gorm B and J{\o}rgensen, Marit E and Jukema, J Wouter and Justesen, Johanne M and Kamstrup, Pia R and Kanoni, Stavroula and Karpe, Fredrik and Kee, Frank and Khera, Amit V and Klarin, Derek and Koistinen, Heikki A and Kooner, Jaspal S and Kooperberg, Charles and Kuulasmaa, Kari and Kuusisto, Johanna and Laakso, Markku and Lakka, Timo and Langenberg, Claudia and Langsted, Anne and Launer, Lenore J and Lauritzen, Torsten and Liewald, David C M and Lin, Li An and Linneberg, Allan and Loos, Ruth J F and Lu, Yingchang and Lu, Xiangfeng and M{\"a}gi, Reedik and M{\"a}larstig, Anders and Manichaikul, Ani and Manning, Alisa K and M{\"a}ntyselk{\"a}, Pekka and Marouli, Eirini and Masca, Nicholas G D and Maschio, Andrea and Meigs, James B and Melander, Olle and Metspalu, Andres and Morris, Andrew P and Morrison, Alanna C and Mulas, Antonella and M{\"u}ller-Nurasyid, Martina and Munroe, Patricia B and Neville, Matt J and Nielsen, Jonas B and Nielsen, Sune F and Nordestgaard, B{\o}rge G and Ordovas, Jose M and Mehran, Roxana and O{\textquoteright}Donnell, Christoper J and Orho-Melander, Marju and Molony, Cliona M and Muntendam, Pieter and Padmanabhan, Sandosh and Palmer, Colin N A and Pasko, Dorota and Patel, Aniruddh P and Pedersen, Oluf and Perola, Markus and Peters, Annette and Pisinger, Charlotta and Pistis, Giorgio and Polasek, Ozren and Poulter, Neil and Psaty, Bruce M and Rader, Daniel J and Rasheed, Asif and Rauramaa, Rainer and Reilly, Dermot F and Reiner, Alex P and Renstrom, Frida and Rich, Stephen S and Ridker, Paul M and Rioux, John D and Robertson, Neil R and Roden, Dan M and Rotter, Jerome I and Rudan, Igor and Salomaa, Veikko and Samani, Nilesh J and Sanna, Serena and Sattar, Naveed and Schmidt, Ellen M and Scott, Robert A and Sever, Peter and Sevilla, Raquel S and Shaffer, Christian M and Sim, Xueling and Sivapalaratnam, Suthesh and Small, Kerrin S and Smith, Albert V and Smith, Blair H and Somayajula, Sangeetha and Southam, Lorraine and Spector, Timothy D and Speliotes, Elizabeth K and Starr, John M and Stirrups, Kathleen E and Stitziel, Nathan and Strauch, Konstantin and Stringham, Heather M and Surendran, Praveen and Tada, Hayato and Tall, Alan R and Tang, Hua and Tardif, Jean-Claude and Taylor, Kent D and Trompet, Stella and Tsao, Philip S and Tuomilehto, Jaakko and Tybjaerg-Hansen, Anne and van Zuydam, Natalie R and Varbo, Anette and Varga, Tibor V and Virtamo, Jarmo and Waldenberger, Melanie and Wang, Nan and Wareham, Nick J and Warren, Helen R and Weeke, Peter E and Weinstock, Joshua and Wessel, Jennifer and Wilson, James G and Wilson, Peter W F and Xu, Ming and Yaghootkar, Hanieh and Young, Robin and Zeggini, Eleftheria and Zhang, He and Zheng, Neil S and Zhang, Weihua and Zhang, Yan and Zhou, Wei and Zhou, Yanhua and Zoledziewska, Magdalena and Howson, Joanna M M and Danesh, John and McCarthy, Mark I and Cowan, Chad A and Abecasis, Goncalo and Deloukas, Panos and Musunuru, Kiran and Willer, Cristen J and Kathiresan, Sekar} } @article {7596, title = {Impact of common genetic determinants of Hemoglobin A1c on type 2 diabetes risk and diagnosis in ancestrally diverse populations: A transethnic genome-wide meta-analysis.}, journal = {PLoS Med}, volume = {14}, year = {2017}, month = {2017 Sep}, pages = {e1002383}, abstract = {

BACKGROUND: Glycated hemoglobin (HbA1c) is used to diagnose type 2 diabetes (T2D) and assess glycemic control in patients with diabetes. Previous genome-wide association studies (GWAS) have identified 18 HbA1c-associated genetic variants. These variants proved to be classifiable by their likely biological action as erythrocytic (also associated with erythrocyte traits) or glycemic (associated with other glucose-related traits). In this study, we tested the hypotheses that, in a very large scale GWAS, we would identify more genetic variants associated with HbA1c and that HbA1c variants implicated in erythrocytic biology would affect the diagnostic accuracy of HbA1c. We therefore expanded the number of HbA1c-associated loci and tested the effect of genetic risk-scores comprised of erythrocytic or glycemic variants on incident diabetes prediction and on prevalent diabetes screening performance. Throughout this multiancestry study, we kept a focus on interancestry differences in HbA1c genetics performance that might influence race-ancestry differences in health outcomes.

METHODS \& FINDINGS: Using genome-wide association meta-analyses in up to 159,940 individuals from 82 cohorts of European, African, East Asian, and South Asian ancestry, we identified 60 common genetic variants associated with HbA1c. We classified variants as implicated in glycemic, erythrocytic, or unclassified biology and tested whether additive genetic scores of erythrocytic variants (GS-E) or glycemic variants (GS-G) were associated with higher T2D incidence in multiethnic longitudinal cohorts (N = 33,241). Nineteen glycemic and 22 erythrocytic variants were associated with HbA1c at genome-wide significance. GS-G was associated with higher T2D risk (incidence OR = 1.05, 95\% CI 1.04-1.06, per HbA1c-raising allele, p = 3 {\texttimes} 10-29); whereas GS-E was not (OR = 1.00, 95\% CI 0.99-1.01, p = 0.60). In Europeans and Asians, erythrocytic variants in aggregate had only modest effects on the diagnostic accuracy of HbA1c. Yet, in African Americans, the X-linked G6PD G202A variant (T-allele frequency 11\%) was associated with an absolute decrease in HbA1c of 0.81\%-units (95\% CI 0.66-0.96) per allele in hemizygous men, and 0.68\%-units (95\% CI 0.38-0.97) in homozygous women. The G6PD variant may cause approximately 2\% (N = 0.65 million, 95\% CI 0.55-0.74) of African American adults with T2D to remain undiagnosed when screened with HbA1c. Limitations include the smaller sample sizes for non-European ancestries and the inability to classify approximately one-third of the variants. Further studies in large multiethnic cohorts with HbA1c, glycemic, and erythrocytic traits are required to better determine the biological action of the unclassified variants.

CONCLUSIONS: As G6PD deficiency can be clinically silent until illness strikes, we recommend investigation of the possible benefits of screening for the G6PD genotype along with using HbA1c to diagnose T2D in populations of African ancestry or groups where G6PD deficiency is common. Screening with direct glucose measurements, or genetically-informed HbA1c diagnostic thresholds in people with G6PD deficiency, may be required to avoid missed or delayed diagnoses.

}, keywords = {Diabetes Mellitus, Type 2, Genetic Variation, Genome-Wide Association Study, Glycated Hemoglobin A, Humans, Phenotype, Risk}, issn = {1549-1676}, doi = {10.1371/journal.pmed.1002383}, author = {Wheeler, Eleanor and Leong, Aaron and Liu, Ching-Ti and Hivert, Marie-France and Strawbridge, Rona J and Podmore, Clara and Li, Man and Yao, Jie and Sim, Xueling and Hong, Jaeyoung and Chu, Audrey Y and Zhang, Weihua and Wang, Xu and Chen, Peng and Maruthur, Nisa M and Porneala, Bianca C and Sharp, Stephen J and Jia, Yucheng and Kabagambe, Edmond K and Chang, Li-Ching and Chen, Wei-Min and Elks, Cathy E and Evans, Daniel S and Fan, Qiao and Giulianini, Franco and Go, Min Jin and Hottenga, Jouke-Jan and Hu, Yao and Jackson, Anne U and Kanoni, Stavroula and Kim, Young Jin and Kleber, Marcus E and Ladenvall, Claes and Lecoeur, C{\'e}cile and Lim, Sing-Hui and Lu, Yingchang and Mahajan, Anubha and Marzi, Carola and Nalls, Mike A and Navarro, Pau and Nolte, Ilja M and Rose, Lynda M and Rybin, Denis V and Sanna, Serena and Shi, Yuan and Stram, Daniel O and Takeuchi, Fumihiko and Tan, Shu Pei and van der Most, Peter J and van Vliet-Ostaptchouk, Jana V and Wong, Andrew and Yengo, Loic and Zhao, Wanting and Goel, Anuj and Martinez Larrad, Maria Teresa and Radke, D{\"o}rte and Salo, Perttu and Tanaka, Toshiko and van Iperen, Erik P A and Abecasis, Goncalo and Afaq, Saima and Alizadeh, Behrooz Z and Bertoni, Alain G and Bonnefond, Am{\'e}lie and B{\"o}ttcher, Yvonne and Bottinger, Erwin P and Campbell, Harry and Carlson, Olga D and Chen, Chien-Hsiun and Cho, Yoon Shin and Garvey, W Timothy and Gieger, Christian and Goodarzi, Mark O and Grallert, Harald and Hamsten, Anders and Hartman, Catharina A and Herder, Christian and Hsiung, Chao Agnes and Huang, Jie and Igase, Michiya and Isono, Masato and Katsuya, Tomohiro and Khor, Chiea-Chuen and Kiess, Wieland and Kohara, Katsuhiko and Kovacs, Peter and Lee, Juyoung and Lee, Wen-Jane and Lehne, Benjamin and Li, Huaixing and Liu, Jianjun and Lobbens, Stephane and Luan, Jian{\textquoteright}an and Lyssenko, Valeriya and Meitinger, Thomas and Miki, Tetsuro and Miljkovic, Iva and Moon, Sanghoon and Mulas, Antonella and M{\"u}ller, Gabriele and M{\"u}ller-Nurasyid, Martina and Nagaraja, Ramaiah and Nauck, Matthias and Pankow, James S and Polasek, Ozren and Prokopenko, Inga and Ramos, Paula S and Rasmussen-Torvik, Laura and Rathmann, Wolfgang and Rich, Stephen S and Robertson, Neil R and Roden, Michael and Roussel, Ronan and Rudan, Igor and Scott, Robert A and Scott, William R and Sennblad, Bengt and Siscovick, David S and Strauch, Konstantin and Sun, Liang and Swertz, Morris and Tajuddin, Salman M and Taylor, Kent D and Teo, Yik-Ying and Tham, Yih Chung and T{\"o}njes, Anke and Wareham, Nicholas J and Willemsen, Gonneke and Wilsgaard, Tom and Hingorani, Aroon D and Egan, Josephine and Ferrucci, Luigi and Hovingh, G Kees and Jula, Antti and Kivimaki, Mika and Kumari, Meena and Nj{\o}lstad, Inger and Palmer, Colin N A and Serrano R{\'\i}os, Manuel and Stumvoll, Michael and Watkins, Hugh and Aung, Tin and Bl{\"u}her, Matthias and Boehnke, Michael and Boomsma, Dorret I and Bornstein, Stefan R and Chambers, John C and Chasman, Daniel I and Chen, Yii-Der Ida and Chen, Yduan-Tsong and Cheng, Ching-Yu and Cucca, Francesco and de Geus, Eco J C and Deloukas, Panos and Evans, Michele K and Fornage, Myriam and Friedlander, Yechiel and Froguel, Philippe and Groop, Leif and Gross, Myron D and Harris, Tamara B and Hayward, Caroline and Heng, Chew-Kiat and Ingelsson, Erik and Kato, Norihiro and Kim, Bong-Jo and Koh, Woon-Puay and Kooner, Jaspal S and K{\"o}rner, Antje and Kuh, Diana and Kuusisto, Johanna and Laakso, Markku and Lin, Xu and Liu, Yongmei and Loos, Ruth J F and Magnusson, Patrik K E and M{\"a}rz, Winfried and McCarthy, Mark I and Oldehinkel, Albertine J and Ong, Ken K and Pedersen, Nancy L and Pereira, Mark A and Peters, Annette and Ridker, Paul M and Sabanayagam, Charumathi and Sale, Michele and Saleheen, Danish and Saltevo, Juha and Schwarz, Peter Eh and Sheu, Wayne H H and Snieder, Harold and Spector, Timothy D and Tabara, Yasuharu and Tuomilehto, Jaakko and van Dam, Rob M and Wilson, James G and Wilson, James F and Wolffenbuttel, Bruce H R and Wong, Tien Yin and Wu, Jer-Yuarn and Yuan, Jian-Min and Zonderman, Alan B and Soranzo, Nicole and Guo, Xiuqing and Roberts, David J and Florez, Jose C and Sladek, Robert and Dupuis, Jos{\'e}e and Morris, Andrew P and Tai, E-Shyong and Selvin, Elizabeth and Rotter, Jerome I and Langenberg, Claudia and Barroso, In{\^e}s and Meigs, James B} } @article {8041, title = {Fatty acid biomarkers of dairy fat consumption and incidence of type 2 diabetes: A pooled analysis of prospective cohort studies.}, journal = {PLoS Med}, volume = {15}, year = {2018}, month = {2018 10}, pages = {e1002670}, abstract = {

BACKGROUND: We aimed to investigate prospective associations of circulating or adipose tissue odd-chain fatty acids 15:0 and 17:0 and trans-palmitoleic acid, t16:1n-7, as potential biomarkers of dairy fat intake, with incident type 2 diabetes (T2D).

METHODS AND FINDINGS: Sixteen prospective cohorts from 12 countries (7 from the United States, 7 from Europe, 1 from Australia, 1 from Taiwan) performed new harmonised individual-level analysis for the prospective associations according to a standardised plan. In total, 63,682 participants with a broad range of baseline ages and BMIs and 15,180 incident cases of T2D over the average of 9 years of follow-up were evaluated. Study-specific results were pooled using inverse-variance-weighted meta-analysis. Prespecified interactions by age, sex, BMI, and race/ethnicity were explored in each cohort and were meta-analysed. Potential heterogeneity by cohort-specific characteristics (regions, lipid compartments used for fatty acid assays) was assessed with metaregression. After adjustment for potential confounders, including measures of adiposity (BMI, waist circumference) and lipogenesis (levels of palmitate, triglycerides), higher levels of 15:0, 17:0, and t16:1n-7 were associated with lower incidence of T2D. In the most adjusted model, the hazard ratio (95\% CI) for incident T2D per cohort-specific 10th to 90th percentile range of 15:0 was 0.80 (0.73-0.87); of 17:0, 0.65 (0.59-0.72); of t16:1n7, 0.82 (0.70-0.96); and of their sum, 0.71 (0.63-0.79). In exploratory analyses, similar associations for 15:0, 17:0, and the sum of all three fatty acids were present in both genders but stronger in women than in men (pinteraction < 0.001). Whereas studying associations with biomarkers has several advantages, as limitations, the biomarkers do not distinguish between different food sources of dairy fat (e.g., cheese, yogurt, milk), and residual confounding by unmeasured or imprecisely measured confounders may exist.

CONCLUSIONS: In a large meta-analysis that pooled the findings from 16 prospective cohort studies, higher levels of 15:0, 17:0, and t16:1n-7 were associated with a lower risk of T2D.

}, keywords = {Aged, Australia, Biomarkers, Dairy Products, Diabetes Mellitus, Type 2, Dietary Fats, Europe, Fatty Acids, Fatty Acids, Monounsaturated, Female, Humans, Incidence, Male, Middle Aged, Prospective Studies, Sex Factors, Taiwan, United States}, issn = {1549-1676}, doi = {10.1371/journal.pmed.1002670}, author = {Imamura, Fumiaki and Fretts, Amanda and Marklund, Matti and Ardisson Korat, Andres V and Yang, Wei-Sin and Lankinen, Maria and Qureshi, Waqas and Helmer, Catherine and Chen, Tzu-An and Wong, Kerry and Bassett, Julie K and Murphy, Rachel and Tintle, Nathan and Yu, Chaoyu Ian and Brouwer, Ingeborg A and Chien, Kuo-Liong and Frazier-Wood, Alexis C and Del Gobbo, Liana C and Djouss{\'e}, Luc and Geleijnse, Johanna M and Giles, Graham G and de Goede, Janette and Gudnason, Vilmundur and Harris, William S and Hodge, Allison and Hu, Frank and Koulman, Albert and Laakso, Markku and Lind, Lars and Lin, Hung-Ju and McKnight, Barbara and Rajaobelina, Kalina and Riserus, Ulf and Robinson, Jennifer G and Samieri, Cecilia and Siscovick, David S and Soedamah-Muthu, Sabita S and Sotoodehnia, Nona and Sun, Qi and Tsai, Michael Y and Uusitupa, Matti and Wagenknecht, Lynne E and Wareham, Nick J and Wu, Jason HY and Micha, Renata and Forouhi, Nita G and Lemaitre, Rozenn N and Mozaffarian, Dariush} } @article {8258, title = {Comment on Davis et al. Development and Validation of a Simple Hip Fracture Risk Prediction Tool for Type 2 Diabetes: The Fremantle Diabetes Study Phase I. Diabetes Care 2018;42:102-109.}, journal = {Diabetes Care}, volume = {42}, year = {2019}, month = {2019 06}, pages = {e100}, keywords = {Diabetes Mellitus, Type 2, Hip Fractures, Humans}, issn = {1935-5548}, doi = {10.2337/dc19-0204}, author = {B{\r u}zkov{\'a}, Petra and Barzilay, Joshua I} } @article {8774, title = {Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes.}, journal = {Nat Commun}, volume = {12}, year = {2021}, month = {2021 06 09}, pages = {3505}, abstract = {

Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier develops the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we apply clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias display effect sizes significantly larger than the top 1\% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers average 60\% or lower for most conditions. We assess epidemiologic and genetic factors contributing to risk prediction in monogenic variant carriers, demonstrating that inclusion of polygenic variation significantly improves biomarker estimation for two monogenic dyslipidemias.

}, keywords = {Adult, Biological Variation, Population, Biomarkers, Diabetes Mellitus, Type 2, Dyslipidemias, Exome, Genetic Predisposition to Disease, Genotype, Humans, Multifactorial Inheritance, Penetrance, Risk Assessment}, issn = {2041-1723}, doi = {10.1038/s41467-021-23556-4}, author = {Goodrich, Julia K and Singer-Berk, Moriel and Son, Rachel and Sveden, Abigail and Wood, Jordan and England, Eleina and Cole, Joanne B and Weisburd, Ben and Watts, Nick and Caulkins, Lizz and Dornbos, Peter and Koesterer, Ryan and Zappala, Zachary and Zhang, Haichen and Maloney, Kristin A and Dahl, Andy and Aguilar-Salinas, Carlos A and Atzmon, Gil and Barajas-Olmos, Francisco and Barzilai, Nir and Blangero, John and Boerwinkle, Eric and Bonnycastle, Lori L and Bottinger, Erwin and Bowden, Donald W and Centeno-Cruz, Federico and Chambers, John C and Chami, Nathalie and Chan, Edmund and Chan, Juliana and Cheng, Ching-Yu and Cho, Yoon Shin and Contreras-Cubas, Cecilia and C{\'o}rdova, Emilio and Correa, Adolfo and DeFronzo, Ralph A and Duggirala, Ravindranath and Dupuis, Jos{\'e}e and Garay-Sevilla, Ma Eugenia and Garc{\'\i}a-Ortiz, Humberto and Gieger, Christian and Glaser, Benjamin and Gonz{\'a}lez-Villalpando, Clicerio and Gonzalez, Ma Elena and Grarup, Niels and Groop, Leif and Gross, Myron and Haiman, Christopher and Han, Sohee and Hanis, Craig L and Hansen, Torben and Heard-Costa, Nancy L and Henderson, Brian E and Hernandez, Juan Manuel Malacara and Hwang, Mi Yeong and Islas-Andrade, Sergio and J{\o}rgensen, Marit E and Kang, Hyun Min and Kim, Bong-Jo and Kim, Young Jin and Koistinen, Heikki A and Kooner, Jaspal Singh and Kuusisto, Johanna and Kwak, Soo-Heon and Laakso, Markku and Lange, Leslie and Lee, Jong-Young and Lee, Juyoung and Lehman, Donna M and Linneberg, Allan and Liu, Jianjun and Loos, Ruth J F and Lyssenko, Valeriya and Ma, Ronald C W and Mart{\'\i}nez-Hern{\'a}ndez, Ang{\'e}lica and Meigs, James B and Meitinger, Thomas and Mendoza-Caamal, Elvia and Mohlke, Karen L and Morris, Andrew D and Morrison, Alanna C and Ng, Maggie C Y and Nilsson, Peter M and O{\textquoteright}Donnell, Christopher J and Orozco, Lorena and Palmer, Colin N A and Park, Kyong Soo and Post, Wendy S and Pedersen, Oluf and Preuss, Michael and Psaty, Bruce M and Reiner, Alexander P and Revilla-Monsalve, Cristina and Rich, Stephen S and Rotter, Jerome I and Saleheen, Danish and Schurmann, Claudia and Sim, Xueling and Sladek, Rob and Small, Kerrin S and So, Wing Yee and Spector, Timothy D and Strauch, Konstantin and Strom, Tim M and Tai, E Shyong and Tam, Claudia H T and Teo, Yik Ying and Thameem, Farook and Tomlinson, Brian and Tracy, Russell P and Tuomi, Tiinamaija and Tuomilehto, Jaakko and Tusi{\'e}-Luna, Teresa and van Dam, Rob M and Vasan, Ramachandran S and Wilson, James G and Witte, Daniel R and Wong, Tien-Yin and Burtt, Noel P and Zaitlen, Noah and McCarthy, Mark I and Boehnke, Michael and Pollin, Toni I and Flannick, Jason and Mercader, Josep M and O{\textquoteright}Donnell-Luria, Anne and Baxter, Samantha and Florez, Jose C and MacArthur, Daniel G and Udler, Miriam S} } @article {8921, title = {Egg consumption, overall diet quality, and risk of type 2 diabetes and coronary heart disease: A pooling project of US prospective cohorts.}, journal = {Clin Nutr}, volume = {40}, year = {2021}, month = {2021 05}, pages = {2475-2482}, abstract = {

BACKGROUND AND AIMS: Data on the relation of egg consumption with risk of type 2 diabetes (T2D) and coronary heart disease (CHD) are limited and inconsistent. Few studies have controlled for overall dietary patterns in egg-T2D or egg-CHD analyses, and it is unclear whether any observed elevated risks of T2D and CHD with frequent egg consumption is real or due to confounding by dietary habits. We tested the hypothesis that frequent egg consumption is associated with a higher risk of T2D and CHD risk after adjustment for overall dietary patterns among adults.

DESIGN: We used prospective cohort design to complete time-to-event analyses.

METHODS: We pooled de novo, harmonized, individual-level analyses from nine US cohorts (n~=~103,811). Cox regression was used to estimate hazard ratios separately in each cohort adjusting for age, ethnicity, body mass index (BMI), exercise, smoking, alcohol intake, and dietary patterns. We pooled cohort-specific results using an inverse-variance weighted method to estimate summary relative risks.

RESULTS: Median age ranged from 25 to 72 years. Median egg consumption was 1 egg per week in most of the cohorts. While egg consumption up to one per week was not associated with T2D risk, consumption of >=2 eggs per week was associated with elevated risk [27\% elevated risk of T2D comparing 7+ eggs/week with none (95\% CI: 16\%-37\%)]. There was little evidence for heterogeneity across cohorts and we observed similar conclusions when stratified by BMI. Overall, egg consumption was not associated with the risk of CHD. However, in a sensitivity analysis, there was a 30\% higher risk of CHD (95\% CI: 3\%-56\%) restricted to older adults consuming 5-6 eggs/week.

CONCLUSIONS: Our data showed an elevated risk of T2D with egg consumption of >=2 eggs per week but not with <2 eggs/week. While there was no overall association of egg consumption with CHD risk, the elevated CHD observed with consumption of 5-6 eggs/week in older cohorts merits further investigation.

}, keywords = {Adult, Aged, Cohort Studies, Coronary Disease, Diabetes Mellitus, Type 2, Diet, Eggs, Humans, Middle Aged, Prospective Studies, Risk Factors, United States}, issn = {1532-1983}, doi = {10.1016/j.clnu.2021.03.003}, author = {Djouss{\'e}, Luc and Zhou, Guohai and McClelland, Robyn L and Ma, Nanxun and Zhou, Xia and Kabagambe, Edmond K and Talegawkar, Sameera A and Judd, Suzanne E and Biggs, Mary L and Fitzpatrick, Annette L and Clark, Cheryl R and Gagnon, David R and Steffen, Lyn M and Gaziano, J Michael and Lee, I-Min and Buring, Julie E and Manson, JoAnn E} } @article {9295, title = {Fasting and Postload Nonesterified Fatty Acids and Glucose Dysregulation in Older Adults.}, journal = {Am J Epidemiol}, volume = {191}, year = {2022}, month = {2022 Jun 27}, pages = {1235-1247}, abstract = {

To evaluate the association of nonesterified fatty acids (NEFA) with dysglycemia in older adults, NEFA levels were measured among participants in the Cardiovascular Health Study (United States; enrolled 1989-1993). Associations with insulin sensitivity and pancreatic β-cell function, and with incident type 2 diabetes mellitus (DM), were examined. The sample comprised 2,144 participants (aged 77.9 (standard deviation, 4.5) years). Participant data from the Cardiovascular Health Study visit in 1996-1997 was used with prospective follow-up through 2010. Fasting and postload NEFA showed significant associations with lower insulin sensitivity and pancreatic β-cell function, individually and on concurrent adjustment. Over median follow-up of 9.7 years, 236 cases of DM occurred. Postload NEFA were associated with risk of DM (per standard deviation, hazard ratio~= 1.18, 95\% confidence interval: 1.08, 1.29), but fasting NEFA were not (hazard ratio~= 1.12, 95\% confidence interval: 0.97, 1.29). The association for postload NEFA persisted after adjustment for putative intermediates, and after adjustment for fasting NEFA. Sex and body mass index modified these associations, which were stronger for fasting NEFA with DM in men but were accentuated for postload NEFA in women and among leaner individuals. Fasting and postload NEFA were related to lower insulin sensitivity and pancreatic β-cell function, but only postload NEFA were associated with increased DM. Additional study into NEFA metabolism could uncover novel potential targets for diabetes prevention in elders.

}, keywords = {Aged, Blood Glucose, Diabetes Mellitus, Type 2, Fasting, Fatty Acids, Nonesterified, Female, Glucose, Humans, Insulin, Insulin Resistance, Male, Prospective Studies}, issn = {1476-6256}, doi = {10.1093/aje/kwac044}, author = {Shitole, Sanyog G and Biggs, Mary L and Ix, Joachim H and Fretts, Amanda M and Tracy, Russell P and Siscovick, David S and Djouss{\'e}, Luc and Mukamal, Kenneth J and Kizer, Jorge R} } @article {9104, title = {Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation.}, journal = {Nat Genet}, volume = {54}, year = {2022}, month = {2022 May}, pages = {560-572}, abstract = {

We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9\% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 {\texttimes} 10), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4\% of T2D associations to a single variant with >50\% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.

}, keywords = {Diabetes Mellitus, Type 2, Ethnicity, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Risk Factors}, issn = {1546-1718}, doi = {10.1038/s41588-022-01058-3}, author = {Mahajan, Anubha and Spracklen, Cassandra N and Zhang, Weihua and Ng, Maggie C Y and Petty, Lauren E and Kitajima, Hidetoshi and Yu, Grace Z and R{\"u}eger, Sina and Speidel, Leo and Kim, Young Jin and Horikoshi, Momoko and Mercader, Josep M and Taliun, Daniel and Moon, Sanghoon and Kwak, Soo-Heon and Robertson, Neil R and Rayner, Nigel W and Loh, Marie and Kim, Bong-Jo and Chiou, Joshua and Miguel-Escalada, Irene and Della Briotta Parolo, Pietro and Lin, Kuang and Bragg, Fiona and Preuss, Michael H and Takeuchi, Fumihiko and Nano, Jana and Guo, Xiuqing and Lamri, Amel and Nakatochi, Masahiro and Scott, Robert A and Lee, Jung-Jin and Huerta-Chagoya, Alicia and Graff, Mariaelisa and Chai, Jin-Fang and Parra, Esteban J and Yao, Jie and Bielak, Lawrence F and Tabara, Yasuharu and Hai, Yang and Steinthorsdottir, Valgerdur and Cook, James P and Kals, Mart and Grarup, Niels and Schmidt, Ellen M and Pan, Ian and Sofer, Tamar and Wuttke, Matthias and Sarnowski, Chloe and Gieger, Christian and Nousome, Darryl and Trompet, Stella and Long, Jirong and Sun, Meng and Tong, Lin and Chen, Wei-Min and Ahmad, Meraj and Noordam, Raymond and Lim, Victor J Y and Tam, Claudia H T and Joo, Yoonjung Yoonie and Chen, Chien-Hsiun and Raffield, Laura M and Lecoeur, C{\'e}cile and Prins, Bram Peter and Nicolas, Aude and Yanek, Lisa R and Chen, Guanjie and Jensen, Richard A and Tajuddin, Salman and Kabagambe, Edmond K and An, Ping and Xiang, Anny H and Choi, Hyeok Sun and Cade, Brian E and Tan, Jingyi and Flanagan, Jack and Abaitua, Fernando and Adair, Linda S and Adeyemo, Adebowale and Aguilar-Salinas, Carlos A and Akiyama, Masato and Anand, Sonia S and Bertoni, Alain and Bian, Zheng and Bork-Jensen, Jette and Brandslund, Ivan and Brody, Jennifer A and Brummett, Chad M and Buchanan, Thomas A and Canouil, Micka{\"e}l and Chan, Juliana C N and Chang, Li-Ching and Chee, Miao-Li and Chen, Ji and Chen, Shyh-Huei and Chen, Yuan-Tsong and Chen, Zhengming and Chuang, Lee-Ming and Cushman, Mary and Das, Swapan K and de Silva, H Janaka and Dedoussis, George and Dimitrov, Latchezar and Doumatey, Ayo P and Du, Shufa and Duan, Qing and Eckardt, Kai-Uwe and Emery, Leslie S and Evans, Daniel S and Evans, Michele K and Fischer, Krista and Floyd, James S and Ford, Ian and Fornage, Myriam and Franco, Oscar H and Frayling, Timothy M and Freedman, Barry I and Fuchsberger, Christian and Genter, Pauline and Gerstein, Hertzel C and Giedraitis, Vilmantas and Gonz{\'a}lez-Villalpando, Clicerio and Gonzalez-Villalpando, Maria Elena and Goodarzi, Mark O and Gordon-Larsen, Penny and Gorkin, David and Gross, Myron and Guo, Yu and Hackinger, Sophie and Han, Sohee and Hattersley, Andrew T and Herder, Christian and Howard, Annie-Green and Hsueh, Willa and Huang, Mengna and Huang, Wei and Hung, Yi-Jen and Hwang, Mi Yeong and Hwu, Chii-Min and Ichihara, Sahoko and Ikram, Mohammad Arfan and Ingelsson, Martin and Islam, Md Tariqul and Isono, Masato and Jang, Hye-Mi and Jasmine, Farzana and Jiang, Guozhi and Jonas, Jost B and J{\o}rgensen, Marit E and J{\o}rgensen, Torben and Kamatani, Yoichiro and Kandeel, Fouad R and Kasturiratne, Anuradhani and Katsuya, Tomohiro and Kaur, Varinderpal and Kawaguchi, Takahisa and Keaton, Jacob M and Kho, Abel N and Khor, Chiea-Chuen and Kibriya, Muhammad G and Kim, Duk-Hwan and Kohara, Katsuhiko and Kriebel, Jennifer and Kronenberg, Florian and Kuusisto, Johanna and L{\"a}ll, Kristi and Lange, Leslie A and Lee, Myung-Shik and Lee, Nanette R and Leong, Aaron and Li, Liming and Li, Yun and Li-Gao, Ruifang and Ligthart, Symen and Lindgren, Cecilia M and Linneberg, Allan and Liu, Ching-Ti and Liu, Jianjun and Locke, Adam E and Louie, Tin and Luan, Jian{\textquoteright}an and Luk, Andrea O and Luo, Xi and Lv, Jun and Lyssenko, Valeriya and Mamakou, Vasiliki and Mani, K Radha and Meitinger, Thomas and Metspalu, Andres and Morris, Andrew D and Nadkarni, Girish N and Nadler, Jerry L and Nalls, Michael A and Nayak, Uma and Nongmaithem, Suraj S and Ntalla, Ioanna and Okada, Yukinori and Orozco, Lorena and Patel, Sanjay R and Pereira, Mark A and Peters, Annette and Pirie, Fraser J and Porneala, Bianca and Prasad, Gauri and Preissl, Sebastian and Rasmussen-Torvik, Laura J and Reiner, Alexander P and Roden, Michael and Rohde, Rebecca and Roll, Kathryn and Sabanayagam, Charumathi and Sander, Maike and Sandow, Kevin and Sattar, Naveed and Sch{\"o}nherr, Sebastian and Schurmann, Claudia and Shahriar, Mohammad and Shi, Jinxiu and Shin, Dong Mun and Shriner, Daniel and Smith, Jennifer A and So, Wing Yee and Stan{\v c}{\'a}kov{\'a}, Alena and Stilp, Adrienne M and Strauch, Konstantin and Suzuki, Ken and Takahashi, Atsushi and Taylor, Kent D and Thorand, Barbara and Thorleifsson, Gudmar and Thorsteinsdottir, Unnur and Tomlinson, Brian and Torres, Jason M and Tsai, Fuu-Jen and Tuomilehto, Jaakko and Tusi{\'e}-Luna, Teresa and Udler, Miriam S and Valladares-Salgado, Adan and van Dam, Rob M and van Klinken, Jan B and Varma, Rohit and Vujkovic, Marijana and Wacher-Rodarte, Niels and Wheeler, Eleanor and Whitsel, Eric A and Wickremasinghe, Ananda R and van Dijk, Ko Willems and Witte, Daniel R and Yajnik, Chittaranjan S and Yamamoto, Ken and Yamauchi, Toshimasa and Yengo, Loic and Yoon, Kyungheon and Yu, Canqing and Yuan, Jian-Min and Yusuf, Salim and Zhang, Liang and Zheng, Wei and Raffel, Leslie J and Igase, Michiya and Ipp, Eli and Redline, Susan and Cho, Yoon Shin and Lind, Lars and Province, Michael A and Hanis, Craig L and Peyser, Patricia A and Ingelsson, Erik and Zonderman, Alan B and Psaty, Bruce M and Wang, Ya-Xing and Rotimi, Charles N and Becker, Diane M and Matsuda, Fumihiko and Liu, Yongmei and Zeggini, Eleftheria and Yokota, Mitsuhiro and Rich, Stephen S and Kooperberg, Charles and Pankow, James S and Engert, James C and Chen, Yii-Der Ida and Froguel, Philippe and Wilson, James G and Sheu, Wayne H H and Kardia, Sharon L R and Wu, Jer-Yuarn and Hayes, M Geoffrey and Ma, Ronald C W and Wong, Tien-Yin and Groop, Leif and Mook-Kanamori, Dennis O and Chandak, Giriraj R and Collins, Francis S and Bharadwaj, Dwaipayan and Par{\'e}, Guillaume and Sale, Mich{\`e}le M and Ahsan, Habibul and Motala, Ayesha A and Shu, Xiao-Ou and Park, Kyong-Soo and Jukema, J Wouter and Cruz, Miguel and McKean-Cowdin, Roberta and Grallert, Harald and Cheng, Ching-Yu and Bottinger, Erwin P and Dehghan, Abbas and Tai, E-Shyong and Dupuis, Jos{\'e}e and Kato, Norihiro and Laakso, Markku and K{\"o}ttgen, Anna and Koh, Woon-Puay and Palmer, Colin N A and Liu, Simin and Abecasis, Goncalo and Kooner, Jaspal S and Loos, Ruth J F and North, Kari E and Haiman, Christopher A and Florez, Jose C and Saleheen, Danish and Hansen, Torben and Pedersen, Oluf and M{\"a}gi, Reedik and Langenberg, Claudia and Wareham, Nicholas J and Maeda, Shiro and Kadowaki, Takashi and Lee, Juyoung and Millwood, Iona Y and Walters, Robin G and Stefansson, Kari and Myers, Simon R and Ferrer, Jorge and Gaulton, Kyle J and Meigs, James B and Mohlke, Karen L and Gloyn, Anna L and Bowden, Donald W and Below, Jennifer E and Chambers, John C and Sim, Xueling and Boehnke, Michael and Rotter, Jerome I and McCarthy, Mark I and Morris, Andrew P} } @article {9100, title = {A multi-ethnic polygenic risk score is associated with hypertension prevalence and progression throughout adulthood.}, journal = {Nat Commun}, volume = {13}, year = {2022}, month = {2022 Jun 21}, pages = {3549}, abstract = {

In a multi-stage analysis of 52,436 individuals aged 17-90 across diverse cohorts and biobanks, we train, test, and evaluate a polygenic risk score (PRS) for hypertension risk and progression. The PRS is trained using genome-wide association studies (GWAS) for systolic, diastolic blood pressure, and hypertension, respectively. For each trait, PRS is selected by optimizing the coefficient of variation (CV) across estimated effect sizes from multiple potential PRS using the same GWAS, after which the 3 trait-specific PRSs are combined via an unweighted sum called "PRSsum", forming the HTN-PRS. The HTN-PRS is associated with both prevalent and incident hypertension at 4-6 years of follow up. This association is further confirmed in age-stratified analysis. In an independent biobank of 40,201 individuals, the HTN-PRS is confirmed to be predictive of increased risk for coronary artery disease, ischemic stroke, type 2 diabetes, and chronic kidney disease.

}, keywords = {Adult, Diabetes Mellitus, Type 2, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Hypertension, Multifactorial Inheritance, Prevalence, Risk Factors}, issn = {2041-1723}, doi = {10.1038/s41467-022-31080-2}, author = {Kurniansyah, Nuzulul and Goodman, Matthew O and Kelly, Tanika N and Elfassy, Tali and Wiggins, Kerri L and Bis, Joshua C and Guo, Xiuqing and Palmas, Walter and Taylor, Kent D and Lin, Henry J and Haessler, Jeffrey and Gao, Yan and Shimbo, Daichi and Smith, Jennifer A and Yu, Bing and Feofanova, Elena V and Smit, Roelof A J and Wang, Zhe and Hwang, Shih-Jen and Liu, Simin and Wassertheil-Smoller, Sylvia and Manson, JoAnn E and Lloyd-Jones, Donald M and Rich, Stephen S and Loos, Ruth J F and Redline, Susan and Correa, Adolfo and Kooperberg, Charles and Fornage, Myriam and Kaplan, Robert C and Psaty, Bruce M and Rotter, Jerome I and Arnett, Donna K and Morrison, Alanna C and Franceschini, Nora and Levy, Daniel and Sofer, Tamar} } @article {9171, title = {Plasma epoxyeicosatrienoic acids and diabetes-related cardiovascular disease: The cardiovascular health study.}, journal = {EBioMedicine}, volume = {83}, year = {2022}, month = {2022 Sep}, pages = {104189}, abstract = {

BACKGROUND: Epoxyeicosatrienoic acids (EETs) are metabolites of arachidonic acid that may impact atherosclerosis, and animal experimental studies suggest EETs protect cardiac function. Plasma EETs are mostly esterified to phospholipids and part of an active pool. To address the limited information about EETs and CVD in humans, we conducted a prospective study of total plasma EETs (free~+~esterified) and diabetes-related CVD in the Cardiovascular Health Study (CHS).

METHODS: We measured 4 EET species and their metabolites, dihydroxyepoxyeicosatrienoic acids (DHETs), in plasma samples from 892 CHS participants with type 2 diabetes. We determined the association of EETs and DHETs with incident myocardial infarction (MI) and ischemic stroke using Cox regression.

FINDINGS: During follow-up (median 7.5 years), we identified 150 MI and 134 ischemic strokes. In primary, multivariable analyses, elevated levels of each EET species were associated with non-significant lower risk of incident MI (for example, hazard ratio for 1 SD higher 14,15-EET: 0.86, 95\% CI: 0.72-1.02; p=0.08). The EETs-MI associations became significant in analyses further adjusted for DHETs (hazard ratio for 1 SD higher 14,15-EET adjusted for 14,15-DHET: 0.76, 95\% CI: 0.63-0.91; p=0.004). Elevated EET levels were associated with higher risk of ischemic stroke in primary but not secondary analyses. Three DHET species were associated with higher risk of ischemic stroke in all analyses.

INTERPRETATION: Findings from this prospective study complement the extensive studies in animal models showing EETs protect cardiac function and provide new information in humans. Replication is needed to confirm the associations.

FUNDING: US National Institutes of Health.

}, keywords = {Animals, Arachidonic Acids, Cardiovascular Diseases, Diabetes Mellitus, Type 2, Eicosanoids, Humans, Ischemic Stroke, Prospective Studies}, issn = {2352-3964}, doi = {10.1016/j.ebiom.2022.104189}, author = {Lemaitre, Rozenn N and Jensen, Paul N and Zeigler, Maxwell and Fretts, Amanda M and Umans, Jason G and Howard, Barbara V and Sitlani, Colleen M and McKnight, Barbara and Gharib, Sina A and King, Irena B and Siscovick, David S and Psaty, Bruce M and Sotoodehnia, Nona and Totah, Rheem A} } @article {8975, title = {Rare coding variants in 35 genes associate with circulating lipid levels-A multi-ancestry analysis of 170,000 exomes.}, journal = {Am J Hum Genet}, volume = {109}, year = {2022}, month = {2022 01 06}, pages = {81-96}, abstract = {

Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1\%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples. We prioritize 32 genes in array-based genome-wide association study (GWAS) loci based on aggregations of rare coding variants; three (EVI5, SH2B3, and PLIN1) had no prior association of rare coding variants with lipid levels. Most of our associated genes showed evidence of association among multiple ancestries. Finally, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes and for genes closest to GWAS index single-nucleotide polymorphisms (SNPs). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels.

}, keywords = {Alleles, Blood Glucose, Case-Control Studies, Computational Biology, Databases, Genetic, Diabetes Mellitus, Type 2, Exome, Genetic Predisposition to Disease, Genetic Variation, Genetics, Population, Genome-Wide Association Study, Humans, Lipid Metabolism, Lipids, Liver, Molecular Sequence Annotation, Multifactorial Inheritance, Open Reading Frames, Phenotype, Polymorphism, Single Nucleotide}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2021.11.021}, author = {Hindy, George and Dornbos, Peter and Chaffin, Mark D and Liu, Dajiang J and Wang, Minxian and Selvaraj, Margaret Sunitha and Zhang, David and Park, Joseph and Aguilar-Salinas, Carlos A and Antonacci-Fulton, Lucinda and Ardissino, Diego and Arnett, Donna K and Aslibekyan, Stella and Atzmon, Gil and Ballantyne, Christie M and Barajas-Olmos, Francisco and Barzilai, Nir and Becker, Lewis C and Bielak, Lawrence F and Bis, Joshua C and Blangero, John and Boerwinkle, Eric and Bonnycastle, Lori L and Bottinger, Erwin and Bowden, Donald W and Bown, Matthew J and Brody, Jennifer A and Broome, Jai G and Burtt, Noel P and Cade, Brian E and Centeno-Cruz, Federico and Chan, Edmund and Chang, Yi-Cheng and Chen, Yii-der I and Cheng, Ching-Yu and Choi, Won Jung and Chowdhury, Rajiv and Contreras-Cubas, Cecilia and C{\'o}rdova, Emilio J and Correa, Adolfo and Cupples, L Adrienne and Curran, Joanne E and Danesh, John and de Vries, Paul S and DeFronzo, Ralph A and Doddapaneni, Harsha and Duggirala, Ravindranath and Dutcher, Susan K and Ellinor, Patrick T and Emery, Leslie S and Florez, Jose C and Fornage, Myriam and Freedman, Barry I and Fuster, Valentin and Garay-Sevilla, Ma Eugenia and Garc{\'\i}a-Ortiz, Humberto and Germer, Soren and Gibbs, Richard A and Gieger, Christian and Glaser, Benjamin and Gonzalez, Clicerio and Gonzalez-Villalpando, Maria Elena and Graff, Mariaelisa and Graham, Sarah E and Grarup, Niels and Groop, Leif C and Guo, Xiuqing and Gupta, Namrata and Han, Sohee and Hanis, Craig L and Hansen, Torben and He, Jiang and Heard-Costa, Nancy L and Hung, Yi-Jen and Hwang, Mi Yeong and Irvin, Marguerite R and Islas-Andrade, Sergio and Jarvik, Gail P and Kang, Hyun Min and Kardia, Sharon L R and Kelly, Tanika and Kenny, Eimear E and Khan, Alyna T and Kim, Bong-Jo and Kim, Ryan W and Kim, Young Jin and Koistinen, Heikki A and Kooperberg, Charles and Kuusisto, Johanna and Kwak, Soo Heon and Laakso, Markku and Lange, Leslie A and Lee, Jiwon and Lee, Juyoung and Lee, Seonwook and Lehman, Donna M and Lemaitre, Rozenn N and Linneberg, Allan and Liu, Jianjun and Loos, Ruth J F and Lubitz, Steven A and Lyssenko, Valeriya and Ma, Ronald C W and Martin, Lisa Warsinger and Mart{\'\i}nez-Hern{\'a}ndez, Ang{\'e}lica and Mathias, Rasika A and McGarvey, Stephen T and McPherson, Ruth and Meigs, James B and Meitinger, Thomas and Melander, Olle and Mendoza-Caamal, Elvia and Metcalf, Ginger A and Mi, Xuenan and Mohlke, Karen L and Montasser, May E and Moon, Jee-Young and Moreno-Macias, Hortensia and Morrison, Alanna C and Muzny, Donna M and Nelson, Sarah C and Nilsson, Peter M and O{\textquoteright}Connell, Jeffrey R and Orho-Melander, Marju and Orozco, Lorena and Palmer, Colin N A and Palmer, Nicholette D and Park, Cheol Joo and Park, Kyong Soo and Pedersen, Oluf and Peralta, Juan M and Peyser, Patricia A and Post, Wendy S and Preuss, Michael and Psaty, Bruce M and Qi, Qibin and Rao, D C and Redline, Susan and Reiner, Alexander P and Revilla-Monsalve, Cristina and Rich, Stephen S and Samani, Nilesh and Schunkert, Heribert and Schurmann, Claudia and Seo, Daekwan and Seo, Jeong-Sun and Sim, Xueling and Sladek, Rob and Small, Kerrin S and So, Wing Yee and Stilp, Adrienne M and Tai, E Shyong and Tam, Claudia H T and Taylor, Kent D and Teo, Yik Ying and Thameem, Farook and Tomlinson, Brian and Tsai, Michael Y and Tuomi, Tiinamaija and Tuomilehto, Jaakko and Tusi{\'e}-Luna, Teresa and Udler, Miriam S and van Dam, Rob M and Vasan, Ramachandran S and Viaud Martinez, Karine A and Wang, Fei Fei and Wang, Xuzhi and Watkins, Hugh and Weeks, Daniel E and Wilson, James G and Witte, Daniel R and Wong, Tien-Yin and Yanek, Lisa R and Kathiresan, Sekar and Rader, Daniel J and Rotter, Jerome I and Boehnke, Michael and McCarthy, Mark I and Willer, Cristen J and Natarajan, Pradeep and Flannick, Jason A and Khera, Amit V and Peloso, Gina M} } @article {9158, title = {Whole genome sequence association analysis of fasting glucose and fasting insulin levels in diverse cohorts from the NHLBI TOPMed program.}, journal = {Commun Biol}, volume = {5}, year = {2022}, month = {2022 07 28}, pages = {756}, abstract = {

The genetic determinants of fasting glucose (FG) and fasting insulin (FI) have been studied mostly through genome arrays, resulting in over 100 associated variants. We extended this work with high-coverage whole genome sequencing analyses from fifteen cohorts in NHLBI{\textquoteright}s Trans-Omics for Precision Medicine (TOPMed) program. Over 23,000 non-diabetic individuals from five race-ethnicities/populations (African, Asian, European, Hispanic and Samoan) were included. Eight variants were significantly associated with FG or FI across previously identified regions MTNR1B, G6PC2, GCK, GCKR and FOXA2. We additionally characterize suggestive associations with FG or FI near previously identified SLC30A8, TCF7L2, and ADCY5 regions as well as APOB, PTPRT, and ROBO1. Functional annotation resources including the Diabetes Epigenome Atlas were compiled for each signal (chromatin states, annotation principal components, and others) to elucidate variant-to-function hypotheses. We provide a catalog of nucleotide-resolution genomic variation spanning intergenic and intronic regions creating a foundation for future sequencing-based investigations of glycemic traits.

}, keywords = {Diabetes Mellitus, Type 2, Fasting, Glucose, Humans, Insulin, National Heart, Lung, and Blood Institute (U.S.), Nerve Tissue Proteins, Polymorphism, Single Nucleotide, Precision Medicine, Receptors, Immunologic, United States}, issn = {2399-3642}, doi = {10.1038/s42003-022-03702-4}, author = {DiCorpo, Daniel and Gaynor, Sheila M and Russell, Emily M and Westerman, Kenneth E and Raffield, Laura M and Majarian, Timothy D and Wu, Peitao and Sarnowski, Chloe and Highland, Heather M and Jackson, Anne and Hasbani, Natalie R and de Vries, Paul S and Brody, Jennifer A and Hidalgo, Bertha and Guo, Xiuqing and Perry, James A and O{\textquoteright}Connell, Jeffrey R and Lent, Samantha and Montasser, May E and Cade, Brian E and Jain, Deepti and Wang, Heming and D{\textquoteright}Oliveira Albanus, Ricardo and Varshney, Arushi and Yanek, Lisa R and Lange, Leslie and Palmer, Nicholette D and Almeida, Marcio and Peralta, Juan M and Aslibekyan, Stella and Baldridge, Abigail S and Bertoni, Alain G and Bielak, Lawrence F and Chen, Chung-Shiuan and Chen, Yii-Der Ida and Choi, Won Jung and Goodarzi, Mark O and Floyd, James S and Irvin, Marguerite R and Kalyani, Rita R and Kelly, Tanika N and Lee, Seonwook and Liu, Ching-Ti and Loesch, Douglas and Manson, JoAnn E and Minster, Ryan L and Naseri, Take and Pankow, James S and Rasmussen-Torvik, Laura J and Reiner, Alexander P and Reupena, Muagututi{\textquoteright}a Sefuiva and Selvin, Elizabeth and Smith, Jennifer A and Weeks, Daniel E and Xu, Huichun and Yao, Jie and Zhao, Wei and Parker, Stephen and Alonso, Alvaro and Arnett, Donna K and Blangero, John and Boerwinkle, Eric and Correa, Adolfo and Cupples, L Adrienne and Curran, Joanne E and Duggirala, Ravindranath and He, Jiang and Heckbert, Susan R and Kardia, Sharon L R and Kim, Ryan W and Kooperberg, Charles and Liu, Simin and Mathias, Rasika A and McGarvey, Stephen T and Mitchell, Braxton D and Morrison, Alanna C and Peyser, Patricia A and Psaty, Bruce M and Redline, Susan and Shuldiner, Alan R and Taylor, Kent D and Vasan, Ramachandran S and Viaud-Martinez, Karine A and Florez, Jose C and Wilson, James G and Sladek, Robert and Rich, Stephen S and Rotter, Jerome I and Lin, Xihong and Dupuis, Jos{\'e}e and Meigs, James B and Wessel, Jennifer and Manning, Alisa K} }