@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 {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 {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 {7549, title = {Predictors and outcomes of heart failure with mid-range ejection fraction.}, journal = {Eur J Heart Fail}, year = {2017}, month = {2017 Dec 11}, abstract = {

AIMS: While heart failure with preserved (HFpEF) and reduced ejection fraction (HFrEF) are well described, determinants and outcomes of heart failure with mid-range ejection fraction (HFmrEF) remain unclear. We sought to examine clinical and biochemical predictors of incident HFmrEF in the community.

METHODS AND RESULTS: We pooled data from four community-based longitudinal cohorts, with ascertainment of new heart failure (HF) classified into HFmrEF [ejection fraction (EF) 41-49\%], HFpEF (EF >=50\%), and HFrEF (EF <=40\%). Predictors of incident HF subtypes were assessed using multivariable Cox models. Among 28 820 participants free of HF followed for a median of 12 years, there were 200 new HFmrEF cases, compared with 811 HFpEF and 1048 HFrEF. Clinical predictors of HFmrEF included age, male sex, systolic blood pressure, diabetes mellitus, and prior myocardial infarction (multivariable adjusted P~<= 0.003 for all). Biomarkers that predicted HFmrEF included natriuretic peptides, cystatin-C, and high-sensitivity troponin (P~<= 0.0004 for all). Natriuretic peptides were stronger predictors of HFrEF [hazard ratio (HR) 2.00 per 1 standard deviation increase, 95\% confidence interval (CI) 1.81-2.20] than of HFmrEF (HR 1.51, 95\% CI 1.20-1.90, P~= 0.01 for difference), and did not differ in their association with incident HFmrEF and HFpEF (HR 1.56, 95\% CI 1.41-1.73, P~= 0.68 for difference). All-cause mortality following the onset of HFmrEF was worse than that of HFpEF (50 vs. 39 events per 1000 person-years, P~= 0.02), but comparable to that of HFrEF (46 events per 1000 person-years, P~= 0.78).

CONCLUSIONS: We found overlap in predictors of incident HFmrEF with other HF subtypes. In contrast, mortality risk after HFmrEF was worse than HFpEF, and similar to HFrEF.

}, issn = {1879-0844}, doi = {10.1002/ejhf.1091}, author = {Bhambhani, Vijeta and Kizer, Jorge R and Lima, Jo{\~a}o A C and van der Harst, Pim and Bahrami, Hossein and Nayor, Matthew and de Filippi, Christopher R and Enserro, Danielle and Blaha, Michael J and Cushman, Mary and Wang, Thomas J and Gansevoort, Ron T and Fox, Caroline S and Gaggin, Hanna K and Kop, Willem J and Liu, Kiang and Vasan, Ramachandran S and Psaty, Bruce M and Lee, Douglas S and Brouwers, Frank P and Hillege, Hans L and Bartz, Traci M and Benjamin, Emelia J and Chan, Cheeling and Allison, Matthew and Gardin, Julius M and Januzzi, James L and Levy, Daniel and Herrington, David M and van Gilst, Wiek H and Bertoni, Alain G and Larson, Martin G and de Boer, Rudolf A and Gottdiener, John S and Shah, Sanjiv J and Ho, Jennifer E} } @article {7603, title = {Association of Cardiovascular Biomarkers With Incident Heart Failure With Preserved and Reduced Ejection Fraction.}, journal = {JAMA Cardiol}, year = {2018}, month = {2018 Jan 10}, abstract = {

Importance: Nearly half of all patients with heart failure have preserved ejection fraction (HFpEF) as opposed to reduced ejection fraction (HFrEF), yet associations of biomarkers with future heart failure subtype are incompletely understood.

Objective: To evaluate the associations of 12 cardiovascular biomarkers with incident HFpEF vs HFrEF among adults from the general population.

Design, Setting, and Participants: This study included 4 longitudinal community-based cohorts: the Cardiovascular Health Study (1989-1990; 1992-1993 for supplemental African-American cohort), the Framingham Heart Study (1995-1998), the Multi-Ethnic Study of Atherosclerosis (2000-2002), and the Prevention of Renal and Vascular End-stage Disease study (1997-1998). Each cohort had prospective ascertainment of incident HFpEF and HFrEF. Data analysis was performed from June 25, 2015, to November 9, 2017.

Exposures: The following biomarkers were examined: N-terminal pro B-type natriuretic peptide or brain natriuretic peptide, high-sensitivity troponin T or I, C-reactive protein (CRP), urinary albumin to creatinine ratio (UACR), renin to aldosterone ratio, D-dimer, fibrinogen, soluble suppressor of tumorigenicity, galectin-3, cystatin C, plasminogen activator inhibitor 1, and interleukin 6.

Main Outcomes and Measures: Development of incident HFpEF and incident HFrEF.

Results: Among the 22 756 participants in these 4 cohorts (12 087 women and 10 669 men; mean [SD] age, 60 [13] years) in the study, during a median follow-up of 12 years, 633 participants developed incident HFpEF, and 841 developed HFrEF. In models adjusted for clinical risk factors of heart failure, 2 biomarkers were significantly associated with incident HFpEF: UACR (hazard ratio [HR], 1.33; 95\% CI, 1.20-1.48; P < .001) and natriuretic peptides (HR, 1.27; 95\% CI, 1.16-1.40; P < .001), with suggestive associations for high-sensitivity troponin (HR, 1.11; 95\% CI, 1.03-1.19; P = .008), plasminogen activator inhibitor 1 (HR, 1.22; 95\% CI, 1.03-1.45; P = .02), and fibrinogen (HR, 1.12; 95\% CI, 1.03-1.22; P = .01). By contrast, 6 biomarkers were associated with incident HFrEF: natriuretic peptides (HR, 1.54; 95\% CI, 1.41-1.68; P < .001), UACR (HR, 1.21; 95\% CI, 1.11-1.32; P < .001), high-sensitivity troponin (HR, 1.37; 95\% CI, 1.29-1.46; P < .001), cystatin C (HR, 1.19; 95\% CI, 1.11-1.27; P < .001), D-dimer (HR, 1.22; 95\% CI, 1.11-1.35; P < .001), and CRP (HR, 1.19; 95\% CI, 1.11-1.28; P < .001). When directly compared, natriuretic peptides, high-sensitivity troponin, and CRP were more strongly associated with HFrEF compared with HFpEF.

Conclusions and Relevance: Biomarkers of renal dysfunction, endothelial dysfunction, and inflammation were associated with incident HFrEF. By contrast, only natriuretic peptides and UACR were associated with HFpEF. These findings highlight the need for future studies focused on identifying novel biomarkers of the risk of HFpEF.

}, issn = {2380-6591}, doi = {10.1001/jamacardio.2017.4987}, author = {de Boer, Rudolf A and Nayor, Matthew and deFilippi, Christopher R and Enserro, Danielle and Bhambhani, Vijeta and Kizer, Jorge R and Blaha, Michael J and Brouwers, Frank P and Cushman, Mary and Lima, Jo{\~a}o A C and Bahrami, Hossein and van der Harst, Pim and Wang, Thomas J and Gansevoort, Ron T and Fox, Caroline S and Gaggin, Hanna K and Kop, Willem J and Liu, Kiang and Vasan, Ramachandran S and Psaty, Bruce M and Lee, Douglas S and Hillege, Hans L and Bartz, Traci M and Benjamin, Emelia J and Chan, Cheeling and Allison, Matthew and Gardin, Julius M and Januzzi, James L and Shah, Sanjiv J and Levy, Daniel and Herrington, David M and Larson, Martin G and van Gilst, Wiek H and Gottdiener, John S and Bertoni, Alain G and Ho, Jennifer E} } @article {7668, title = {Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes.}, journal = {Nat Genet}, volume = {50}, year = {2018}, month = {2018 Apr}, pages = {559-571}, abstract = {

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 {\texttimes} 10); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio <=1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent {\textquoteright}false leads{\textquoteright} with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.

}, issn = {1546-1718}, doi = {10.1038/s41588-018-0084-1}, author = {Mahajan, Anubha and Wessel, Jennifer and Willems, Sara M and Zhao, Wei and Robertson, Neil R and Chu, Audrey Y and Gan, Wei and Kitajima, Hidetoshi and Taliun, Daniel and Rayner, N William and Guo, Xiuqing and Lu, Yingchang and Li, Man and Jensen, Richard A and Hu, Yao and Huo, Shaofeng and Lohman, Kurt K and Zhang, Weihua and Cook, James P and Prins, Bram Peter and Flannick, Jason and Grarup, Niels and Trubetskoy, Vassily Vladimirovich and Kravic, Jasmina and Kim, Young Jin and Rybin, Denis V and Yaghootkar, Hanieh and M{\"u}ller-Nurasyid, Martina and Meidtner, Karina and Li-Gao, Ruifang and Varga, Tibor V and Marten, Jonathan and Li, Jin and Smith, Albert Vernon and An, Ping and Ligthart, Symen and Gustafsson, Stefan and Malerba, Giovanni and Demirkan, Ayse and Tajes, Juan Fernandez and Steinthorsdottir, Valgerdur and Wuttke, Matthias and Lecoeur, C{\'e}cile and Preuss, Michael and Bielak, Lawrence F and Graff, Marielisa and Highland, Heather M and Justice, Anne E and Liu, Dajiang J and Marouli, Eirini and Peloso, Gina Marie and Warren, Helen R and Afaq, Saima and Afzal, Shoaib and Ahlqvist, Emma and Almgren, Peter and Amin, Najaf and Bang, Lia B and Bertoni, Alain G and Bombieri, Cristina and Bork-Jensen, Jette and Brandslund, Ivan and Brody, Jennifer A and Burtt, Noel P and Canouil, Micka{\"e}l and Chen, Yii-Der Ida and Cho, Yoon Shin and Christensen, Cramer and Eastwood, Sophie V and Eckardt, Kai-Uwe and Fischer, Krista and Gambaro, Giovanni and Giedraitis, Vilmantas and Grove, Megan L and de Haan, Hugoline G and Hackinger, Sophie and Hai, Yang and Han, Sohee and Tybj{\ae}rg-Hansen, Anne and Hivert, Marie-France and Isomaa, Bo and J{\"a}ger, Susanne and J{\o}rgensen, Marit E and J{\o}rgensen, Torben and K{\"a}r{\"a}j{\"a}m{\"a}ki, AnneMari and Kim, Bong-Jo and Kim, Sung Soo and Koistinen, Heikki A and Kovacs, Peter and Kriebel, Jennifer and Kronenberg, Florian and L{\"a}ll, Kristi and Lange, Leslie A and Lee, Jung-Jin and Lehne, Benjamin and Li, Huaixing and Lin, Keng-Hung and Linneberg, Allan and Liu, Ching-Ti and Liu, Jun and Loh, Marie and M{\"a}gi, Reedik and Mamakou, Vasiliki and McKean-Cowdin, Roberta and Nadkarni, Girish and Neville, Matt and Nielsen, Sune F and Ntalla, Ioanna and Peyser, Patricia A and Rathmann, Wolfgang and Rice, Kenneth and Rich, Stephen S and Rode, Line and Rolandsson, Olov and Sch{\"o}nherr, Sebastian and Selvin, Elizabeth and Small, Kerrin S and Stan{\v c}{\'a}kov{\'a}, Alena and Surendran, Praveen and Taylor, Kent D and Teslovich, Tanya M and Thorand, Barbara and Thorleifsson, Gudmar and Tin, Adrienne and T{\"o}njes, Anke and Varbo, Anette and Witte, Daniel R and Wood, Andrew R and Yajnik, Pranav and Yao, Jie and Yengo, Loic and Young, Robin and Amouyel, Philippe and Boeing, Heiner and Boerwinkle, Eric and Bottinger, Erwin P and Chowdhury, Rajiv and Collins, Francis S and Dedoussis, George and Dehghan, Abbas and Deloukas, Panos and Ferrario, Marco M and Ferrieres, Jean and Florez, Jose C and Frossard, Philippe and Gudnason, Vilmundur and Harris, Tamara B and Heckbert, Susan R and Howson, Joanna M M and Ingelsson, Martin and Kathiresan, Sekar and Kee, Frank and Kuusisto, Johanna and Langenberg, Claudia and Launer, Lenore J and Lindgren, Cecilia M and M{\"a}nnist{\"o}, Satu and Meitinger, Thomas and Melander, Olle and Mohlke, Karen L and Moitry, Marie and Morris, Andrew D and Murray, Alison D and de Mutsert, Ren{\'e}e and Orho-Melander, Marju and Owen, Katharine R and Perola, Markus and Peters, Annette and Province, Michael A and Rasheed, Asif and Ridker, Paul M and Rivadineira, Fernando and Rosendaal, Frits R and Rosengren, Anders H and Salomaa, Veikko and Sheu, Wayne H-H and Sladek, Rob and Smith, Blair H and Strauch, Konstantin and Uitterlinden, Andr{\'e} G and Varma, Rohit and Willer, Cristen J and Bl{\"u}her, Matthias and Butterworth, Adam S and Chambers, John Campbell and Chasman, Daniel I and Danesh, John and van Duijn, Cornelia and Dupuis, Jos{\'e}e and Franco, Oscar H and Franks, Paul W and Froguel, Philippe and Grallert, Harald and Groop, Leif and Han, Bok-Ghee and Hansen, Torben and Hattersley, Andrew T and Hayward, Caroline and Ingelsson, Erik and Kardia, Sharon L R and Karpe, Fredrik and Kooner, Jaspal Singh and K{\"o}ttgen, Anna and Kuulasmaa, Kari and Laakso, Markku and Lin, Xu and Lind, Lars and Liu, Yongmei and Loos, Ruth J F and Marchini, Jonathan and Metspalu, Andres and Mook-Kanamori, Dennis and Nordestgaard, B{\o}rge G and Palmer, Colin N A and Pankow, James S and Pedersen, Oluf and Psaty, Bruce M and Rauramaa, Rainer and Sattar, Naveed and Schulze, Matthias B and Soranzo, Nicole and Spector, Timothy D and Stefansson, Kari and Stumvoll, Michael and Thorsteinsdottir, Unnur and Tuomi, Tiinamaija and Tuomilehto, Jaakko and Wareham, Nicholas J and Wilson, James G and Zeggini, Eleftheria and Scott, Robert A and Barroso, In{\^e}s and Frayling, Timothy M and Goodarzi, Mark O and Meigs, James B and Boehnke, Michael and Saleheen, Danish and Morris, Andrew P and Rotter, Jerome I and McCarthy, Mark I} } @article {7925, title = {Abnormal Fasting Glucose Increases Risk of Unrecognized Myocardial Infarctions in an Elderly Cohort.}, journal = {J Am Geriatr Soc}, volume = {67}, year = {2019}, month = {2019 Jan}, pages = {43-49}, abstract = {

OBJECTIVES: To investigate glucose levels as a risk factor for unrecognized myocardial infarctions (UMIs).

DESIGN: Cohort SETTING: Cardiovascular Health Study.

PARTICIPANTS: Individuals aged 65 and older with fasting glucose measurements (N=4,355; normal fasting glucose (NFG), n = 2,041; impaired fasting glucose (IFG), n = 1,706; DM: n = 608; 40\% male, 84\% white, mean age 72.4 {\textpm} 5.6).

MEASUREMENTS: The relationship between glucose levels and UMI was examined. Participants with prior coronary heart disease (CHD) or UMI on initial electrocardiography were excluded. Using Minnesota codes, UMI was identified according to the presence of pathological Q-waves or minor Q-waves with ST-T abnormalities. Crude and adjusted hazard ratios (HRs) were calculated. Analyses were adjusted for age, sex, body mass index (BMI), hypertension, antihypertensive and lipid-lowering medication use, total cholesterol, high-density lipoprotein cholesterol, and smoking status.

RESULTS: Over a mean follow-up of 6 years, there were 459 incident UMIs (NFG, n=202; IFG, n=183; DM, n=74). Participants with IFG were slightly more likely than those with NFG to experience a UMI (hazard ratio (HR)=1.11, 95\% confidence interval (CI)=0.91-1.36, p = .30), and those with DM were more likely than those with NFG to experience a UMI (HR=1.65, 95\% CI=1.25-2.13, p < .001). After adjustment HR for UMI in IFG those with IFG were no more likely than those with NFG to experience a UMI (HR=1.01, 95\% CI=0.82-1.24, p = .93), whereas those with DM were more likely than those with NFG to experience a UMI (HR=1.37, 95\% CI=1.02-1.81, p = .03). The 2-hour oral glucose tolerance test was not statistically significantly associated with UMI.

CONCLUSION: Fasting glucose status, particularly in the diabetic range, forecasted UMI during 6 years of follow-up in elderly adults. Further studies are needed to clarify the level of glucose at which risk is greater. J Am Geriatr Soc 67:43-49, 2019.

}, issn = {1532-5415}, doi = {10.1111/jgs.15604}, author = {Stacey, Richard Brandon and Zgibor, Janice and Leaverton, Paul E and Schocken, Douglas D and Peregoy, Jennifer A and Lyles, Mary F and Bertoni, Alain G and Burke, Gregory L} } @article {8488, title = {Sex-Specific Associations of Cardiovascular Risk Factors and Biomarkers With Incident Heart~Failure.}, journal = {J Am Coll Cardiol}, volume = {76}, year = {2020}, month = {2020 Sep 22}, pages = {1455-1465}, abstract = {

BACKGROUND: Whether cardiovascular (CV) disease risk factors and biomarkers associate differentially with heart failure (HF) risk in men and women is unclear.

OBJECTIVES: The purpose of this study was to evaluate sex-specific associations of CV risk factors and biomarkers with incident HF.

METHODS: The analysis was performed using data from 4 community-based cohorts with 12.5 years of follow-up. Participants (recruited between 1989 and 2002) were free of HF at baseline. Biomarker measurements included natriuretic peptides, cardiac troponins, plasminogen activator inhibitor-1, D-dimer, fibrinogen, C-reactive protein, sST2, galectin-3, cystatin-C, and urinary albumin-to-creatinine ratio.

RESULTS: Among 22,756 participants (mean age 60 {\textpm} 13 years, 53\% women), HF occurred in 2,095 participants (47\% women). Age, smoking, type 2 diabetes mellitus, hypertension, body mass index, atrial fibrillation, myocardial infarction, left ventricular hypertrophy, and left bundle branch block were strongly associated with HF in both sexes (p~<~0.001), and the combined clinical model had good discrimination in men (C-statistic~=~0.80) and in women (C-statistic~=~0.83). The majority of biomarkers were strongly and similarly associated with HF in both sexes. The clinical model improved modestly after adding natriuretic peptides in men (ΔC-statistic~=~0.006; likelihood ratio chi-square~=~146; p~<~0.001), and after adding cardiac troponins in women (ΔC-statistic~=~0.003; likelihood ratio chi-square~=~73; p~<~0.001).

CONCLUSIONS: CV risk factors are strongly and similarly associated with incident HF in both sexes, highlighting the similar importance of risk factor control in reducing HF risk in the community. There are subtle sex-related differences in the predictive value of individual biomarkers, but the overall improvement in HF risk estimation when included in~a~clinical HF risk prediction model is limited in both sexes.

}, issn = {1558-3597}, doi = {10.1016/j.jacc.2020.07.044}, author = {Suthahar, Navin and Lau, Emily S and Blaha, Michael J and Paniagua, Samantha M and Larson, Martin G and Psaty, Bruce M and Benjamin, Emelia J and Allison, Matthew A and Bartz, Traci M and Januzzi, James L and Levy, Daniel and Meems, Laura M G and Bakker, Stephan J L and Lima, Jo{\~a}o A C and Cushman, Mary and Lee, Douglas S and Wang, Thomas J and deFilippi, Christopher R and Herrington, David M and Nayor, Matthew and Vasan, Ramachandran S and Gardin, Julius M and Kizer, Jorge R and Bertoni, Alain G and Allen, Norrina B and Gansevoort, Ron T and Shah, Sanjiv J and Gottdiener, John S and Ho, Jennifer E and de Boer, Rudolf A} } @article {9160, title = {Lung function impairment and risk of incident heart failure: the NHLBI Pooled Cohorts Study.}, journal = {Eur Heart J}, volume = {43}, year = {2022}, month = {2022 06 14}, pages = {2196-2208}, abstract = {

AIMS: The aim is to evaluate associations of lung function impairment with risk of incident heart failure (HF).

METHODS AND RESULTS: Data were pooled across eight US population-based cohorts that enrolled participants from 1987 to 2004. Participants with self-reported baseline cardiovascular disease were excluded. Spirometry was used to define obstructive [forced expiratory volume in 1 s/forced vital capacity (FEV1/FVC) <0.70] or restrictive (FEV1/FVC >=0.70, FVC <80\%) lung physiology. The incident HF was defined as hospitalization or death caused by HF. In a sub-set, HF events were sub-classified as HF with reduced ejection fraction (HFrEF; EF <50\%) or preserved EF (HFpEF; EF >=50\%). The Fine-Gray proportional sub-distribution hazards models were adjusted for sociodemographic factors, smoking, and cardiovascular risk factors. In models of incident HF sub-types, HFrEF, HFpEF, and non-HF mortality were treated as competing risks. Among 31 677 adults, there were 3344 incident HF events over a median follow-up of 21.0 years. Of 2066 classifiable HF events, 1030 were classified as HFrEF and 1036 as HFpEF. Obstructive [adjusted hazard ratio (HR) 1.17, 95\% confidence interval (CI) 1.07-1.27] and restrictive physiology (adjusted HR 1.43, 95\% CI 1.27-1.62) were associated with incident HF. Obstructive and restrictive ventilatory defects were associated with HFpEF but not HFrEF. The magnitude of the association between restrictive physiology and HFpEF was similar to associations with hypertension, diabetes, and smoking.

CONCLUSION: Lung function impairment was associated with increased risk of incident HF, and particularly incident HFpEF, independent of and to a similar extent as major known cardiovascular risk factors.

}, keywords = {Adult, Heart Failure, Hospitalization, Humans, Lung, National Heart, Lung, and Blood Institute (U.S.), Prognosis, Risk Factors, Stroke Volume, United States}, issn = {1522-9645}, doi = {10.1093/eurheartj/ehac205}, author = {Eckhardt, Christina M and Balte, Pallavi P and Barr, Robert Graham and Bertoni, Alain G and Bhatt, Surya P and Cuttica, Michael and Cassano, Patricia A and Chaves, Paolo and Couper, David and Jacobs, David R and Kalhan, Ravi and Kronmal, Richard and Lange, Leslie and Loehr, Laura and London, Stephanie J and O{\textquoteright}Connor, George T and Rosamond, Wayne and Sanders, Jason and Schwartz, Joseph E and Shah, Amil and Shah, Sanjiv J and Smith, Lewis and White, Wendy and Yende, Sachin and Oelsner, Elizabeth C} } @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} }