@article {6301, title = {Lower estimated GFR and higher albuminuria are associated with adverse kidney outcomes. A collaborative meta-analysis of general and high-risk population cohorts.}, journal = {Kidney Int}, volume = {80}, year = {2011}, month = {2011 Jul}, pages = {93-104}, abstract = {

Both a low estimated glomerular filtration rate (eGFR) and albuminuria are known risk factors for end-stage renal disease (ESRD). To determine their joint contribution to ESRD and other kidney outcomes, we performed a meta-analysis of nine general population cohorts with 845,125 participants and an additional eight cohorts with 173,892 patients, the latter selected because of their high risk for chronic kidney disease (CKD). In the general population, the risk for ESRD was unrelated to eGFR at values between 75 and 105 ml/min per 1.73 m(2) but increased exponentially at lower levels. Hazard ratios for eGFRs averaging 60, 45, and 15 were 4, 29, and 454, respectively, compared with an eGFR of 95, after adjustment for albuminuria and cardiovascular risk factors. Log albuminuria was linearly associated with log ESRD risk without thresholds. Adjusted hazard ratios at albumin-to-creatinine ratios of 30, 300, and 1000 mg/g were 5, 13, and 28, respectively, compared with an albumin-to-creatinine ratio of 5. Albuminuria and eGFR were associated with ESRD, without evidence for multiplicative interaction. Similar associations were found for acute kidney injury and progressive CKD. In high-risk cohorts, the findings were generally comparable. Thus, lower eGFR and higher albuminuria are risk factors for ESRD, acute kidney injury and progressive CKD in both general and high-risk populations, independent of each other and of cardiovascular risk factors.

}, keywords = {Aged, Albuminuria, Cohort Studies, Creatinine, Female, Glomerular Filtration Rate, Humans, Kidney Failure, Chronic, Male, Middle Aged, Prognosis, Proportional Hazards Models, Risk Factors}, issn = {1523-1755}, doi = {10.1038/ki.2010.531}, author = {Gansevoort, Ron T and Matsushita, Kunihiro and van der Velde, Marije and Astor, Brad C and Woodward, Mark and Levey, Andrew S and de Jong, Paul E and Coresh, Josef} } @article {1563, title = {Separate and combined associations of body-mass index and abdominal adiposity with cardiovascular disease: collaborative analysis of 58 prospective studies.}, journal = {Lancet}, volume = {377}, year = {2011}, month = {2011 Mar 26}, pages = {1085-95}, abstract = {

BACKGROUND: Guidelines differ about the value of assessment of adiposity measures for cardiovascular disease risk prediction when information is available for other risk factors. We studied the separate and combined associations of body-mass index (BMI), waist circumference, and waist-to-hip ratio with risk of first-onset cardiovascular disease.

METHODS: We used individual records from 58 cohorts to calculate hazard ratios (HRs) per 1 SD higher baseline values (4.56 kg/m(2) higher BMI, 12.6 cm higher waist circumference, and 0.083 higher waist-to-hip ratio) and measures of risk discrimination and reclassification. Serial adiposity assessments were used to calculate regression dilution ratios.

RESULTS: Individual records were available for 221,934 people in 17 countries (14,297 incident cardiovascular disease outcomes; 1.87 million person-years at risk). Serial adiposity assessments were made in up to 63,821 people (mean interval 5.7 years [SD 3.9]). In people with BMI of 20 kg/m(2) or higher, HRs for cardiovascular disease were 1.23 (95\% CI 1.17-1.29) with BMI, 1.27 (1.20-1.33) with waist circumference, and 1.25 (1.19-1.31) with waist-to-hip ratio, after adjustment for age, sex, and smoking status. After further adjustment for baseline systolic blood pressure, history of diabetes, and total and HDL cholesterol, corresponding HRs were 1.07 (1.03-1.11) with BMI, 1.10 (1.05-1.14) with waist circumference, and 1.12 (1.08-1.15) with waist-to-hip ratio. Addition of information on BMI, waist circumference, or waist-to-hip ratio to a cardiovascular disease risk prediction model containing conventional risk factors did not importantly improve risk discrimination (C-index changes of -0.0001, -0.0001, and 0.0008, respectively), nor classification of participants to categories of predicted 10-year risk (net reclassification improvement -0.19\%, -0.05\%, and -0.05\%, respectively). Findings were similar when adiposity measures were considered in combination. Reproducibility was greater for BMI (regression dilution ratio 0.95, 95\% CI 0.93-0.97) than for waist circumference (0.86, 0.83-0.89) or waist-to-hip ratio (0.63, 0.57-0.70).

INTERPRETATION: BMI, waist circumference, and waist-to-hip ratio, whether assessed singly or in combination, do not importantly improve cardiovascular disease risk prediction in people in developed countries when additional information is available for systolic blood pressure, history of diabetes, and lipids.

FUNDING: British Heart Foundation and UK Medical Research Council.

}, keywords = {Age Factors, Blood Pressure, Body Mass Index, Cardiovascular Diseases, Cholesterol, Cholesterol, HDL, Diabetes Mellitus, Female, Humans, Male, Middle Aged, Obesity, Abdominal, Proportional Hazards Models, Prospective Studies, Risk Assessment, Sex Factors, Smoking, Systole, Waist Circumference, Waist-Hip Ratio}, issn = {1474-547X}, doi = {10.1016/S0140-6736(11)60105-0}, author = {Wormser, David and Kaptoge, Stephen and Di Angelantonio, Emanuele and Wood, Angela M and Pennells, Lisa and Thompson, Alex and Sarwar, Nadeem and Kizer, Jorge R and Lawlor, Debbie A and Nordestgaard, B{\o}rge G and Ridker, Paul and Salomaa, Veikko and Stevens, June and Woodward, Mark and Sattar, Naveed and Collins, Rory and Thompson, Simon G and Whitlock, Gary and Danesh, John} } @article {6086, title = {Associations of kidney disease measures with mortality and end-stage renal disease in individuals with and without diabetes: a meta-analysis.}, journal = {Lancet}, volume = {380}, year = {2012}, month = {2012 Nov 10}, pages = {1662-73}, abstract = {

BACKGROUND: Chronic kidney disease is characterised by low estimated glomerular filtration rate (eGFR) and high albuminuria, and is associated with adverse outcomes. Whether these risks are modified by diabetes is unknown.

METHODS: We did a meta-analysis of studies selected according to Chronic Kidney Disease Prognosis Consortium criteria. Data transfer and analyses were done between March, 2011, and June, 2012. We used Cox proportional hazards models to estimate the hazard ratios (HR) of mortality and end-stage renal disease (ESRD) associated with eGFR and albuminuria in individuals with and without diabetes.

FINDINGS: We analysed data for 1,024,977 participants (128,505 with diabetes) from 30 general population and high-risk cardiovascular cohorts and 13 chronic kidney disease cohorts. In the combined general population and high-risk cohorts with data for all-cause mortality, 75,306 deaths occurred during a mean follow-up of 8{\textperiodcentered}5 years (SD 5{\textperiodcentered}0). In the 23 studies with data for cardiovascular mortality, 21,237 deaths occurred from cardiovascular disease during a mean follow-up of 9{\textperiodcentered}2 years (SD 4{\textperiodcentered}9). In the general and high-risk cohorts, mortality risks were 1{\textperiodcentered}2-1{\textperiodcentered}9 times higher for participants with diabetes than for those without diabetes across the ranges of eGFR and albumin-to-creatinine ratio (ACR). With fixed eGFR and ACR reference points in the diabetes and no diabetes groups, HR of mortality outcomes according to lower eGFR and higher ACR were much the same in participants with and without diabetes (eg, for all-cause mortality at eGFR 45 mL/min per 1{\textperiodcentered}73 m(2) [vs 95 mL/min per 1{\textperiodcentered}73 m(2)], HR 1{\textperiodcentered}35; 95\% CI 1{\textperiodcentered}18-1{\textperiodcentered}55; vs 1{\textperiodcentered}33; 1{\textperiodcentered}19-1{\textperiodcentered}48 and at ACR 30 mg/g [vs 5 mg/g], 1{\textperiodcentered}50; 1{\textperiodcentered}35-1{\textperiodcentered}65 vs 1{\textperiodcentered}52; 1{\textperiodcentered}38-1{\textperiodcentered}67). The overall interactions were not significant. We identified much the same findings for ESRD in the chronic kidney disease cohorts.

INTERPRETATION: Despite higher risks for mortality and ESRD in diabetes, the relative risks of these outcomes by eGFR and ACR are much the same irrespective of the presence or absence of diabetes, emphasising the importance of kidney disease as a predictor of clinical outcomes.

FUNDING: US National Kidney Foundation.

}, keywords = {Aged, Albuminuria, Cardiovascular Diseases, Cause of Death, Diabetic Nephropathies, Female, Glomerular Filtration Rate, Humans, Kidney Failure, Chronic, Male, Middle Aged, Risk Factors}, issn = {1474-547X}, doi = {10.1016/S0140-6736(12)61350-6}, author = {Fox, Caroline S and Matsushita, Kunihiro and Woodward, Mark and Bilo, Henk J G and Chalmers, John and Heerspink, Hiddo J Lambers and Lee, Brian J and Perkins, Robert M and Rossing, Peter and Sairenchi, Toshimi and Tonelli, Marcello and Vassalotti, Joseph A and Yamagishi, Kazumasa and Coresh, Josef and de Jong, Paul E and Wen, Chi-Pang and Nelson, Robert G} } @article {1385, title = {Comparison of risk prediction using the CKD-EPI equation and the MDRD study equation for estimated glomerular filtration rate.}, journal = {JAMA}, volume = {307}, year = {2012}, month = {2012 May 09}, pages = {1941-51}, abstract = {

CONTEXT: The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation more accurately estimates glomerular filtration rate (GFR) than the Modification of Diet in Renal Disease (MDRD) Study equation using the same variables, especially at higher GFR, but definitive evidence of its risk implications in diverse settings is lacking.

OBJECTIVE: To evaluate risk implications of estimated GFR using the CKD-EPI equation compared with the MDRD Study equation in populations with a broad range of demographic and clinical characteristics.

DESIGN, SETTING, AND PARTICIPANTS: A meta-analysis of data from 1.1 million adults (aged >= 18 years) from 25 general population cohorts, 7 high-risk cohorts (of vascular disease), and 13 CKD cohorts. Data transfer and analyses were conducted between March 2011 and March 2012.

MAIN OUTCOME MEASURES: All-cause mortality (84,482 deaths from 40 cohorts), cardiovascular mortality (22,176 events from 28 cohorts), and end-stage renal disease (ESRD) (7644 events from 21 cohorts) during 9.4 million person-years of follow-up; the median of mean follow-up time across cohorts was 7.4 years (interquartile range, 4.2-10.5 years).

RESULTS: Estimated GFR was classified into 6 categories (>=90, 60-89, 45-59, 30-44, 15-29, and <15 mL/min/1.73 m(2)) by both equations. Compared with the MDRD Study equation, 24.4\% and 0.6\% of participants from general population cohorts were reclassified to a higher and lower estimated GFR category, respectively, by the CKD-EPI equation, and the prevalence of CKD stages 3 to 5 (estimated GFR <60 mL/min/1.73 m(2)) was reduced from 8.7\% to 6.3\%. In estimated GFR of 45 to 59 mL/min/1.73 m(2) by the MDRD Study equation, 34.7\% of participants were reclassified to estimated GFR of 60 to 89 mL/min/1.73 m(2) by the CKD-EPI equation and had lower incidence rates (per 1000 person-years) for the outcomes of interest (9.9 vs 34.5 for all-cause mortality, 2.7 vs 13.0 for cardiovascular mortality, and 0.5 vs 0.8 for ESRD) compared with those not reclassified. The corresponding adjusted hazard ratios were 0.80 (95\% CI, 0.74-0.86) for all-cause mortality, 0.73 (95\% CI, 0.65-0.82) for cardiovascular mortality, and 0.49 (95\% CI, 0.27-0.88) for ESRD. Similar findings were observed in other estimated GFR categories by the MDRD Study equation. Net reclassification improvement based on estimated GFR categories was significantly positive for all outcomes (range, 0.06-0.13; all P < .001). Net reclassification improvement was similarly positive in most subgroups defined by age (<65 years and >=65 years), sex, race/ethnicity (white, Asian, and black), and presence or absence of diabetes and hypertension. The results in the high-risk and CKD cohorts were largely consistent with the general population cohorts.

CONCLUSION: The CKD-EPI equation classified fewer individuals as having CKD and more accurately categorized the risk for mortality and ESRD than did the MDRD Study equation across a broad range of populations.

}, keywords = {African Continental Ancestry Group, Aged, Algorithms, Asian Continental Ancestry Group, Cardiovascular Diseases, Cohort Studies, Decision Support Techniques, European Continental Ancestry Group, Female, Glomerular Filtration Rate, Humans, Kidney Failure, Chronic, Male, Middle Aged, Models, Theoretical, Risk Assessment, Sex Factors}, issn = {1538-3598}, doi = {10.1001/jama.2012.3954}, author = {Matsushita, Kunihiro and Mahmoodi, Bakhtawar K and Woodward, Mark and Emberson, Jonathan R and Jafar, Tazeen H and Jee, Sun Ha and Polkinghorne, Kevan R and Shankar, Anoop and Smith, David H and Tonelli, Marcello and Warnock, David G and Wen, Chi-Pang and Coresh, Josef and Gansevoort, Ron T and Hemmelgarn, Brenda R and Levey, Andrew S} } @article {6424, title = {Association of kidney disease measures with ischemic versus hemorrhagic strokes: pooled analyses of 4 prospective community-based cohorts.}, journal = {Stroke}, volume = {45}, year = {2014}, month = {2014 Jul}, pages = {1925-31}, abstract = {

BACKGROUND AND PURPOSE: Although low glomerular filtration rate (GFR) and albuminuria are associated with increased risk of stroke, few studies compared their contribution to risk of ischemic versus hemorrhagic stroke separately. We contrasted the association of these kidney measures with ischemic versus hemorrhagic stroke.

METHODS: We pooled individual participant data from 4 community-based cohorts: 3 from the United States and 1 from The Netherlands. GFR was estimated using both creatinine and cystatin C, and albuminuria was quantified by urinary albumin-to-creatinine ratio (ACR). Associations of estimated GFR and ACR were compared for each stroke type (ischemic versus intraparenchymal hemorrhagic) using study-stratified Cox regression.

RESULTS: Among 29,595 participants (mean age, 61 [SD 12.5] years; 46\% men; 17\% black), 1261 developed stroke (12\% hemorrhagic) during 280,549 person-years. Low estimated GFR was significantly associated with increased risk of ischemic stroke, but not hemorrhagic stroke, whereas high ACR was associated with both stroke types. Adjusted hazard ratios for ischemic and hemorrhagic stroke at estimated GFR of 45 (versus 95) mL/min per 1.73 m2 were 1.30 (95\% confidence interval, 1.01-1.68) and 0.92 (0.47-1.81), respectively. In contrast, the corresponding hazard ratios for ACR of 300 (versus 5) mg/g were 1.62 (1.27-2.07) for ischemic and 2.57 (1.37-4.83) for hemorrhagic stroke, with significantly stronger association with hemorrhagic stroke (P=0.04). For hemorrhagic stroke, the association of elevated ACR was of similar magnitude as that of elevated systolic blood pressure.

CONCLUSIONS: Whereas albuminuria showed significant association with both stroke types, the association of decreased estimated GFR was only significant for ischemic stroke. The strong association of albuminuria with both stroke types warrants clinical attention and further investigations.

}, keywords = {Aged, Albuminuria, Brain Ischemia, Comorbidity, Female, Glomerular Filtration Rate, Humans, Intracranial Hemorrhages, Kidney Diseases, Male, Middle Aged, Netherlands, Proportional Hazards Models, Prospective Studies, Risk Factors, Stroke, United States}, issn = {1524-4628}, doi = {10.1161/STROKEAHA.114.004900}, author = {Mahmoodi, Bakhtawar K and Yatsuya, Hiroshi and Matsushita, Kunihiro and Sang, Yinying and Gottesman, Rebecca F and Astor, Brad C and Woodward, Mark and Longstreth, W T and Psaty, Bruce M and Shlipak, Michael G and Folsom, Aaron R and Gansevoort, Ron T and Coresh, Josef} } @article {6811, title = {Association of Cardiometabolic Multimorbidity With Mortality.}, journal = {JAMA}, volume = {314}, year = {2015}, month = {2015 Jul 7}, pages = {52-60}, abstract = {

IMPORTANCE: The prevalence of cardiometabolic multimorbidity is increasing.

OBJECTIVE: To estimate reductions in life expectancy associated with cardiometabolic multimorbidity.

DESIGN, SETTING, AND PARTICIPANTS: Age- and sex-adjusted mortality rates and hazard ratios (HRs) were calculated using individual participant data from the Emerging Risk Factors Collaboration (689,300 participants; 91 cohorts; years of baseline surveys: 1960-2007; latest mortality follow-up: April 2013; 128,843 deaths). The HRs from the Emerging Risk Factors Collaboration were compared with those from the UK Biobank (499,808 participants; years of baseline surveys: 2006-2010; latest mortality follow-up: November 2013; 7995 deaths). Cumulative survival was estimated by applying calculated age-specific HRs for mortality to contemporary US age-specific death rates.

EXPOSURES: A history of 2 or more of the following: diabetes mellitus, stroke, myocardial infarction (MI).

MAIN OUTCOMES AND MEASURES: All-cause mortality and estimated reductions in life expectancy.

RESULTS: In participants in the Emerging Risk Factors Collaboration without a history of diabetes, stroke, or MI at baseline (reference group), the all-cause mortality rate adjusted to the age of 60 years was 6.8 per 1000 person-years. Mortality rates per 1000 person-years were 15.6 in participants with a history of diabetes, 16.1 in those with stroke, 16.8 in those with MI, 32.0 in those with both diabetes and MI, 32.5 in those with both diabetes and stroke, 32.8 in those with both stroke and MI, and 59.5 in those with diabetes, stroke, and MI. Compared with the reference group, the HRs for all-cause mortality were 1.9 (95\% CI, 1.8-2.0) in participants with a history of diabetes, 2.1 (95\% CI, 2.0-2.2) in those with stroke, 2.0 (95\% CI, 1.9-2.2) in those with MI, 3.7 (95\% CI, 3.3-4.1) in those with both diabetes and MI, 3.8 (95\% CI, 3.5-4.2) in those with both diabetes and stroke, 3.5 (95\% CI, 3.1-4.0) in those with both stroke and MI, and 6.9 (95\% CI, 5.7-8.3) in those with diabetes, stroke, and MI. The HRs from the Emerging Risk Factors Collaboration were similar to those from the more recently recruited UK Biobank. The HRs were little changed after further adjustment for markers of established intermediate pathways (eg, levels of lipids and blood pressure) and lifestyle factors (eg, smoking, diet). At the age of 60 years, a history of any 2 of these conditions was associated with 12 years of reduced life expectancy and a history of all 3 of these conditions was associated with 15 years of reduced life expectancy.

CONCLUSIONS AND RELEVANCE: Mortality associated with a history of diabetes, stroke, or MI was similar for each condition. Because any combination of these conditions was associated with multiplicative mortality risk, life expectancy was substantially lower in people with multimorbidity.

}, keywords = {Adult, Aged, Comorbidity, Diabetes Mellitus, Female, Humans, Life Expectancy, Male, Middle Aged, Mortality, Myocardial Infarction, Risk Factors, Stroke}, issn = {1538-3598}, doi = {10.1001/jama.2015.7008}, author = {Di Angelantonio, Emanuele and Kaptoge, Stephen and Wormser, David and Willeit, Peter and Butterworth, Adam S and Bansal, Narinder and O{\textquoteright}Keeffe, Linda M and Gao, Pei and Wood, Angela M and Burgess, Stephen and Freitag, Daniel F and Pennells, Lisa and Peters, Sanne A and Hart, Carole L and H{\r a}heim, Lise Lund and Gillum, Richard F and Nordestgaard, B{\o}rge G and Psaty, Bruce M and Yeap, Bu B and Knuiman, Matthew W and Nietert, Paul J and Kauhanen, Jussi and Salonen, Jukka T and Kuller, Lewis H and Simons, Leon A and van der Schouw, Yvonne T and Barrett-Connor, Elizabeth and Selmer, Randi and Crespo, Carlos J and Rodriguez, Beatriz and Verschuren, W M Monique and Salomaa, Veikko and Sv{\"a}rdsudd, Kurt and van der Harst, Pim and Bj{\"o}rkelund, Cecilia and Wilhelmsen, Lars and Wallace, Robert B and Brenner, Hermann and Amouyel, Philippe and Barr, Elizabeth L M and Iso, Hiroyasu and Onat, Altan and Trevisan, Maurizio and D{\textquoteright}Agostino, Ralph B and Cooper, Cyrus and Kavousi, Maryam and Welin, Lennart and Roussel, Ronan and Hu, Frank B and Sato, Shinichi and Davidson, Karina W and Howard, Barbara V and Leening, Maarten J G and Leening, Maarten and Rosengren, Annika and D{\"o}rr, Marcus and Deeg, Dorly J H and Kiechl, Stefan and Stehouwer, Coen D A and Nissinen, Aulikki and Giampaoli, Simona and Donfrancesco, Chiara and Kromhout, Daan and Price, Jackie F and Peters, Annette and Meade, Tom W and Casiglia, Edoardo and Lawlor, Debbie A and Gallacher, John and Nagel, Dorothea and Franco, Oscar H and Assmann, Gerd and Dagenais, Gilles R and Jukema, J Wouter and Sundstr{\"o}m, Johan and Woodward, Mark and Brunner, Eric J and Khaw, Kay-Tee and Wareham, Nicholas J and Whitsel, Eric A and Nj{\o}lstad, Inger and Hedblad, Bo and Wassertheil-Smoller, Sylvia and Engstr{\"o}m, Gunnar and Rosamond, Wayne D and Selvin, Elizabeth and Sattar, Naveed and Thompson, Simon G and Danesh, John} } @article {6796, title = {A Meta-analysis of the Association of Estimated GFR, Albuminuria, Diabetes Mellitus, and Hypertension With Acute Kidney Injury.}, journal = {Am J Kidney Dis}, volume = {66}, year = {2015}, month = {2015 Oct}, pages = {602-12}, abstract = {

BACKGROUND: Diabetes mellitus and hypertension are risk factors for acute kidney injury (AKI). Whether estimated glomerular filtration rate (eGFR) and urine albumin-creatinine ratio (ACR) remain risk factors for AKI in the presence and absence of these conditions is uncertain.

STUDY DESIGN: Meta-analysis of cohort studies.

SETTING \& POPULATION: 8 general-population (1,285,045 participants) and 5 chronic kidney disease (CKD; 79,519 participants) cohorts.

SELECTION CRITERIA FOR STUDIES: Cohorts participating in the CKD Prognosis Consortium.

PREDICTORS: Diabetes and hypertension status, eGFR by the 2009 CKD Epidemiology Collaboration creatinine equation, urine ACR, and interactions.

OUTCOME: Hospitalization with AKI, using Cox proportional hazards models to estimate HRs of AKI and random-effects meta-analysis to pool results.

RESULTS: During a mean follow-up of 4 years, there were 16,480 episodes of AKI in the general-population and 2,087 episodes in the CKD cohorts. Low eGFRs and high ACRs were associated with higher risks of AKI in individuals with or without diabetes and with or without hypertension. When compared to a common reference of eGFR of 80mL/min/1.73m(2) in nondiabetic patients, HRs for AKI were generally higher in diabetic patients at any level of eGFR. The same was true for diabetic patients at all levels of ACR compared with nondiabetic patients. The risk gradient for AKI with lower eGFRs was greater in those without diabetes than with diabetes, but similar with higher ACRs in those without versus with diabetes. Those with hypertension had a higher risk of AKI at eGFRs>60mL/min/1.73m(2) than those without hypertension. However, risk gradients for AKI with both lower eGFRs and higher ACRs were greater for those without than with hypertension.

LIMITATIONS: AKI identified by diagnostic code.

CONCLUSIONS: Lower eGFRs and higher ACRs are associated with higher risks of AKI among individuals with or without either diabetes or hypertension.

}, keywords = {Acute Kidney Injury, Adult, Aged, Comorbidity, Diabetes Mellitus, Disease Progression, Female, Glomerular Filtration Rate, Humans, Hypertension, Incidence, Kidney Failure, Chronic, Male, Middle Aged, Prognosis, Renal Insufficiency, Chronic}, issn = {1523-6838}, doi = {10.1053/j.ajkd.2015.02.338}, author = {James, Matthew T and Grams, Morgan E and Woodward, Mark and Elley, C Raina and Green, Jamie A and Wheeler, David C and de Jong, Paul and Gansevoort, Ron T and Levey, Andrew S and Warnock, David G and Sarnak, Mark J} } @article {7575, title = {Measures of chronic kidney disease and risk of incident peripheral artery disease: a collaborative meta-analysis of individual participant data.}, journal = {Lancet Diabetes Endocrinol}, volume = {5}, year = {2017}, month = {2017 Sep}, pages = {718-728}, abstract = {

BACKGROUND: Some evidence suggests that chronic kidney disease is a risk factor for lower-extremity peripheral artery disease. We aimed to quantify the independent and joint associations of two measures of chronic kidney disease (estimated glomerular filtration rate [eGFR] and albuminuria) with the incidence of peripheral artery disease.

METHODS: In this collaborative meta-analysis of international cohorts included in the Chronic Kidney Disease Prognosis Consortium (baseline measurements obtained between 1972 and 2014) with baseline measurements of eGFR and albuminuria, at least 1000 participants (this criterion not applied to cohorts exclusively enrolling patients with chronic kidney disease), and at least 50 peripheral artery disease events, we analysed adult participants without peripheral artery disease at baseline at the individual patient level with Cox proportional hazards models to quantify associations of creatinine-based eGFR, urine albumin-to-creatinine ratio (ACR), and dipstick proteinuria with the incidence of peripheral artery disease (including hospitalisation with a diagnosis of peripheral artery disease, intermittent claudication, leg revascularisation, and leg amputation). We assessed discrimination improvement through c-statistics.

FINDINGS: We analysed 817 084 individuals without a history of peripheral artery disease at baseline from 21 cohorts. 18 261 cases of peripheral artery disease were recorded during follow-up across cohorts (median follow-up was 7{\textperiodcentered}4 years [IQR 5{\textperiodcentered}7-8{\textperiodcentered}9], range 2{\textperiodcentered}0-15{\textperiodcentered}8 years across cohorts). Both chronic kidney disease measures were independently associated with the incidence of peripheral artery disease. Compared with an eGFR of 95 mL/min per 1{\textperiodcentered}73 m2, adjusted hazard ratios (HRs) for incident study-specific peripheral artery disease was 1{\textperiodcentered}22 (95\% CI 1{\textperiodcentered}14-1{\textperiodcentered}30) at an eGFR of 45 mL/min per 1{\textperiodcentered}73 m2 and 2{\textperiodcentered}06 (1{\textperiodcentered}70-2{\textperiodcentered}48) at an eGFR of 15 mL/min per 1{\textperiodcentered}73 m2. Compared with an ACR of 5 mg/g, the adjusted HR for incident study-specific peripheral artery disease was 1{\textperiodcentered}50 (1{\textperiodcentered}41-1{\textperiodcentered}59) at an ACR of 30 mg/g and 2{\textperiodcentered}28 (2{\textperiodcentered}12-2{\textperiodcentered}44) at an ACR of 300 mg/g. The adjusted HR at an ACR of 300 mg/g versus 5 mg/g was 3{\textperiodcentered}68 (95\% CI 3{\textperiodcentered}00-4{\textperiodcentered}52) for leg amputation. eGFR and albuminuria contributed multiplicatively (eg, adjusted HR 5{\textperiodcentered}76 [4{\textperiodcentered}90-6{\textperiodcentered}77] for incident peripheral artery disease and 10{\textperiodcentered}61 [5{\textperiodcentered}70-19{\textperiodcentered}77] for amputation in eGFR <30 mL/min per 1{\textperiodcentered}73 m2 plus ACR >=300 mg/g or dipstick proteinuria 2+ or higher vs eGFR >=90 mL/min per 1{\textperiodcentered}73 m2 plus ACR <10 mg/g or dipstick proteinuria negative). Both eGFR and ACR significantly improved peripheral artery disease risk discrimination beyond traditional predictors, with a substantial improvement prediction of amputation with ACR (difference in c-statistic 0{\textperiodcentered}058, 95\% CI 0{\textperiodcentered}045-0{\textperiodcentered}070). Patterns were consistent across clinical subgroups.

INTERPRETATION: Even mild-to-moderate chronic kidney disease conferred increased risk of incident peripheral artery disease, with a strong association between albuminuria and amputation. Clinical attention should be paid to the development of peripheral artery disease symptoms and signs in people with any stage of chronic kidney disease.

FUNDING: American Heart Association, US National Kidney Foundation, and US National Institute of Diabetes and Digestive and Kidney Diseases.

}, issn = {2213-8595}, doi = {10.1016/S2213-8587(17)30183-3}, author = {Matsushita, Kunihiro and Ballew, Shoshana H and Coresh, Josef and Arima, Hisatomi and Arnl{\"o}v, Johan and Cirillo, Massimo and Ebert, Natalie and Hiramoto, Jade S and Kimm, Heejin and Shlipak, Michael G and Visseren, Frank L J and Gansevoort, Ron T and Kovesdy, Csaba P and Shalev, Varda and Woodward, Mark and Kronenberg, Florian} } @article {7923, title = {Equalization of four cardiovascular risk algorithms after systematic recalibration: individual-participant meta-analysis of 86 prospective studies.}, journal = {Eur Heart J}, year = {2018}, month = {2018 Nov 22}, abstract = {

Aims: There is debate about the optimum algorithm for cardiovascular disease (CVD) risk estimation. We conducted head-to-head comparisons of four algorithms recommended by primary prevention guidelines, before and after {\textquoteright}recalibration{\textquoteright}, a method that adapts risk algorithms to take account of differences in the risk characteristics of the populations being studied.

Methods and results: Using individual-participant data on 360 737 participants without CVD at baseline in 86 prospective studies from 22 countries, we compared the Framingham risk score (FRS), Systematic COronary Risk Evaluation (SCORE), pooled cohort equations (PCE), and Reynolds risk score (RRS). We calculated measures of risk discrimination and calibration, and modelled clinical implications of initiating statin therapy in people judged to be at {\textquoteright}high{\textquoteright} 10 year CVD risk. Original risk algorithms were recalibrated using the risk factor profile and CVD incidence of target populations. The four algorithms had similar risk discrimination. Before recalibration, FRS, SCORE, and PCE over-predicted CVD risk on average by 10\%, 52\%, and 41\%, respectively, whereas RRS under-predicted by 10\%. Original versions of algorithms classified 29-39\% of individuals aged >=40 years as high risk. By contrast, recalibration reduced this proportion to 22-24\% for every algorithm. We estimated that to prevent one CVD event, it would be necessary to initiate statin therapy in 44-51 such individuals using original algorithms, in contrast to 37-39 individuals with recalibrated algorithms.

Conclusion: Before recalibration, the clinical performance of four widely used CVD risk algorithms varied substantially. By contrast, simple recalibration nearly equalized their performance and improved modelled targeting of preventive action to clinical need.

}, issn = {1522-9645}, doi = {10.1093/eurheartj/ehy653}, author = {Pennells, Lisa and Kaptoge, Stephen and Wood, Angela and Sweeting, Mike and Zhao, Xiaohui and White, Ian and Burgess, Stephen and Willeit, Peter and Bolton, Thomas and Moons, Karel G M and van der Schouw, Yvonne T and Selmer, Randi and Khaw, Kay-Tee and Gudnason, Vilmundur and Assmann, Gerd and Amouyel, Philippe and Salomaa, Veikko and Kivimaki, Mika and Nordestgaard, B{\o}rge G and Blaha, Michael J and Kuller, Lewis H and Brenner, Hermann and Gillum, Richard F and Meisinger, Christa and Ford, Ian and Knuiman, Matthew W and Rosengren, Annika and Lawlor, Debbie A and V{\"o}lzke, Henry and Cooper, Cyrus and Mar{\'\i}n Iba{\~n}ez, Alejandro and Casiglia, Edoardo and Kauhanen, Jussi and Cooper, Jackie A and Rodriguez, Beatriz and Sundstr{\"o}m, Johan and Barrett-Connor, Elizabeth and Dankner, Rachel and Nietert, Paul J and Davidson, Karina W and Wallace, Robert B and Blazer, Dan G and Bj{\"o}rkelund, Cecilia and Donfrancesco, Chiara and Krumholz, Harlan M and Nissinen, Aulikki and Davis, Barry R and Coady, Sean and Whincup, Peter H and J{\o}rgensen, Torben and Ducimetiere, Pierre and Trevisan, Maurizio and Engstr{\"o}m, Gunnar and Crespo, Carlos J and Meade, Tom W and Visser, Marjolein and Kromhout, Daan and Kiechl, Stefan and Daimon, Makoto and Price, Jackie F and G{\'o}mez de la C{\'a}mara, Agustin and Wouter Jukema, J and Lamarche, Beno{\^\i}t and Onat, Altan and Simons, Leon A and Kavousi, Maryam and Ben-Shlomo, Yoav and Gallacher, John and Dekker, Jacqueline M and Arima, Hisatomi and Shara, Nawar and Tipping, Robert W and Roussel, Ronan and Brunner, Eric J and Koenig, Wolfgang and Sakurai, Masaru and Pavlovic, Jelena and Gansevoort, Ron T and Nagel, Dorothea and Goldbourt, Uri and Barr, Elizabeth L M and Palmieri, Luigi and Nj{\o}lstad, Inger and Sato, Shinichi and Monique Verschuren, W M and Varghese, Cherian V and Graham, Ian and Onuma, Oyere and Greenland, Philip and Woodward, Mark and Ezzati, Majid and Psaty, Bruce M and Sattar, Naveed and Jackson, Rod and Ridker, Paul M and Cook, Nancy R and D{\textquoteright}Agostino, Ralph B and Thompson, Simon G and Danesh, John and Di Angelantonio, Emanuele} } @article {7915, title = {Relationship of Estimated GFR and Albuminuria to Concurrent Laboratory Abnormalities: An Individual Participant Data Meta-analysis in a Global Consortium.}, journal = {Am J Kidney Dis}, year = {2018}, month = {2018 Oct 19}, abstract = {

RATIONALE \& OBJECTIVE: Chronic kidney disease (CKD) is complicated by abnormalities that reflect disruption in filtration, tubular, and endocrine functions of the kidney. Our aim was to explore the relationship of specific laboratory result abnormalities and hypertension with the estimated glomerular filtration rate (eGFR) and albuminuria CKD staging framework.

STUDY DESIGN: Cross-sectional individual participant-level analyses in a global consortium.

SETTING \& STUDY POPULATIONS: 17 CKD and 38 general population and high-risk cohorts.

SELECTION CRITERIA FOR STUDIES: Cohorts in the CKD Prognosis Consortium with data for eGFR and albuminuria, as well as a measurement of hemoglobin, bicarbonate, phosphorus, parathyroid hormone, potassium, or calcium, or hypertension.

DATA EXTRACTION: Data were obtained and analyzed between July 2015 and January~2018.

ANALYTICAL APPROACH: We modeled the association of eGFR and albuminuria with hemoglobin, bicarbonate, phosphorus, parathyroid hormone, potassium, and calcium values using linear regression and with hypertension and categorical definitions of each abnormality using logistic regression. Results were pooled using random-effects meta-analyses.

RESULTS: The CKD cohorts (n=254,666 participants) were 27\% women and 10\% black, with a mean age of 69 (SD, 12) years. The general population/high-risk cohorts (n=1,758,334) were 50\% women and 2\% black, with a mean age of 50 (16) years. There was a strong graded association between lower eGFR and all laboratory result abnormalities (ORs ranging from 3.27 [95\% CI, 2.68-3.97] to 8.91 [95\% CI, 7.22-10.99] comparing eGFRs of 15 to 29 with eGFRs of 45 to 59mL/min/1.73m), whereas albuminuria had equivocal or weak associations with abnormalities (ORs ranging from 0.77 [95\% CI, 0.60-0.99] to 1.92 [95\% CI, 1.65-2.24] comparing urinary albumin-creatinine ratio > 300 vs~< 30mg/g).

LIMITATIONS: Variations in study era, health care delivery system, typical diet, and laboratory assays.

CONCLUSIONS: Lower eGFR was strongly associated with higher odds of multiple laboratory result abnormalities. Knowledge of risk associations might help guide management in the heterogeneous group of patients with CKD.

}, issn = {1523-6838}, doi = {10.1053/j.ajkd.2018.08.013}, author = {Inker, Lesley A and Grams, Morgan E and Levey, Andrew S and Coresh, Josef and Cirillo, Massimo and Collins, John F and Gansevoort, Ron T and Gutierrez, Orlando M and Hamano, Takayuki and Heine, Gunnar H and Ishikawa, Shizukiyo and Jee, Sun Ha and Kronenberg, Florian and Landray, Martin J and Miura, Katsuyuki and Nadkarni, Girish N and Peralta, Carmen A and Rothenbacher, Dietrich and Schaeffner, Elke and Sedaghat, Sanaz and Shlipak, Michael G and Zhang, Luxia and van Zuilen, Arjan D and Hallan, Stein I and Kovesdy, Csaba P and Woodward, Mark and Levin, Adeera} } @article {7664, title = {Risk thresholds for alcohol consumption: combined analysis of individual-participant data for 599 912 current drinkers in 83 prospective studies.}, journal = {Lancet}, volume = {391}, year = {2018}, month = {2018 04 14}, pages = {1513-1523}, abstract = {

BACKGROUND: Low-risk limits recommended for alcohol consumption vary substantially across different national guidelines. To define thresholds associated with lowest risk for all-cause mortality and cardiovascular disease, we studied individual-participant data from 599 912 current drinkers without previous cardiovascular disease.

METHODS: We did a combined analysis of individual-participant data from three large-scale data sources in 19 high-income countries (the Emerging Risk Factors Collaboration, EPIC-CVD, and the UK Biobank). We characterised dose-response associations and calculated hazard ratios (HRs) per 100 g per week of alcohol (12{\textperiodcentered}5 units per week) across 83 prospective studies, adjusting at least for study or centre, age, sex, smoking, and diabetes. To be eligible for the analysis, participants had to have information recorded about their alcohol consumption amount and status (ie, non-drinker vs current drinker), plus age, sex, history of diabetes and smoking status, at least 1 year of follow-up after baseline, and no baseline history of cardiovascular disease. The main analyses focused on current drinkers, whose baseline alcohol consumption was categorised into eight predefined groups according to the amount in grams consumed per week. We assessed alcohol consumption in relation to all-cause mortality, total cardiovascular disease, and several cardiovascular disease subtypes. We corrected HRs for estimated long-term variability in alcohol consumption using 152 640 serial alcohol assessments obtained some years apart (median interval 5{\textperiodcentered}6 years [5th-95th percentile 1{\textperiodcentered}04-13{\textperiodcentered}5]) from 71 011 participants from 37 studies.

FINDINGS: In the 599 912 current drinkers included in the analysis, we recorded 40 310 deaths and 39 018 incident cardiovascular disease events during 5{\textperiodcentered}4 million person-years of follow-up. For all-cause mortality, we recorded a positive and curvilinear association with the level of alcohol consumption, with the minimum mortality risk around or below 100 g per week. Alcohol consumption was roughly linearly associated with a higher risk of stroke (HR per 100 g per week higher consumption 1{\textperiodcentered}14, 95\% CI, 1{\textperiodcentered}10-1{\textperiodcentered}17), coronary disease excluding myocardial infarction (1{\textperiodcentered}06, 1{\textperiodcentered}00-1{\textperiodcentered}11), heart failure (1{\textperiodcentered}09, 1{\textperiodcentered}03-1{\textperiodcentered}15), fatal hypertensive disease (1{\textperiodcentered}24, 1{\textperiodcentered}15-1{\textperiodcentered}33); and fatal aortic aneurysm (1{\textperiodcentered}15, 1{\textperiodcentered}03-1{\textperiodcentered}28). By contrast, increased alcohol consumption was log-linearly associated with a lower risk of myocardial infarction (HR 0{\textperiodcentered}94, 0{\textperiodcentered}91-0{\textperiodcentered}97). In comparison to those who reported drinking >0-<=100 g per week, those who reported drinking >100-<=200 g per week, >200-<=350 g per week, or >350 g per week had lower life expectancy at age 40 years of approximately 6 months, 1-2 years, or 4-5 years, respectively.

INTERPRETATION: In current drinkers of alcohol in high-income countries, the threshold for lowest risk of all-cause mortality was about 100 g/week. For cardiovascular disease subtypes other than myocardial infarction, there were no clear risk thresholds below which lower alcohol consumption stopped being associated with lower disease risk. These data support limits for alcohol consumption that are lower than those recommended in most current guidelines.

FUNDING: UK Medical Research Council, British Heart Foundation, National Institute for Health Research, European Union Framework 7, and European Research Council.

}, issn = {1474-547X}, doi = {10.1016/S0140-6736(18)30134-X}, author = {Wood, Angela M and Kaptoge, Stephen and Butterworth, Adam S and Willeit, Peter and Warnakula, Samantha and Bolton, Thomas and Paige, Ellie and Paul, Dirk S and Sweeting, Michael and Burgess, Stephen and Bell, Steven and Astle, William and Stevens, David and Koulman, Albert and Selmer, Randi M and Verschuren, W M Monique and Sato, Shinichi and Nj{\o}lstad, Inger and Woodward, Mark and Salomaa, Veikko and Nordestgaard, B{\o}rge G and Yeap, Bu B and Fletcher, Astrid and Melander, Olle and Kuller, Lewis H and Balkau, Beverley and Marmot, Michael and Koenig, Wolfgang and Casiglia, Edoardo and Cooper, Cyrus and Arndt, Volker and Franco, Oscar H and Wennberg, Patrik and Gallacher, John and de la C{\'a}mara, Agustin G{\'o}mez and V{\"o}lzke, Henry and Dahm, Christina C and Dale, Caroline E and Bergmann, Manuela M and Crespo, Carlos J and van der Schouw, Yvonne T and Kaaks, Rudolf and Simons, Leon A and Lagiou, Pagona and Schoufour, Josje D and Boer, Jolanda M A and Key, Timothy J and Rodriguez, Beatriz and Moreno-Iribas, Conchi and Davidson, Karina W and Taylor, James O and Sacerdote, Carlotta and Wallace, Robert B and Quiros, J Ramon and Tumino, Rosario and Blazer, Dan G and Linneberg, Allan and Daimon, Makoto and Panico, Salvatore and Howard, Barbara and Skeie, Guri and Strandberg, Timo and Weiderpass, Elisabete and Nietert, Paul J and Psaty, Bruce M and Kromhout, Daan and Salamanca-Fernandez, Elena and Kiechl, Stefan and Krumholz, Harlan M and Grioni, Sara and Palli, Domenico and Huerta, Jos{\'e} M and Price, Jackie and Sundstr{\"o}m, Johan and Arriola, Larraitz and Arima, Hisatomi and Travis, Ruth C and Panagiotakos, Demosthenes B and Karakatsani, Anna and Trichopoulou, Antonia and K{\"u}hn, Tilman and Grobbee, Diederick E and Barrett-Connor, Elizabeth and van Schoor, Natasja and Boeing, Heiner and Overvad, Kim and Kauhanen, Jussi and Wareham, Nick and Langenberg, Claudia and Forouhi, Nita and Wennberg, Maria and Despr{\'e}s, Jean-Pierre and Cushman, Mary and Cooper, Jackie A and Rodriguez, Carlos J and Sakurai, Masaru and Shaw, Jonathan E and Knuiman, Matthew and Voortman, Trudy and Meisinger, Christa and Tj{\o}nneland, Anne and Brenner, Hermann and Palmieri, Luigi and Dallongeville, Jean and Brunner, Eric J and Assmann, Gerd and Trevisan, Maurizio and Gillum, Richard F and Ford, Ian and Sattar, Naveed and Lazo, Mariana and Thompson, Simon G and Ferrari, Pietro and Leon, David A and Smith, George Davey and Peto, Richard and Jackson, Rod and Banks, Emily and Di Angelantonio, Emanuele and Danesh, John} } @article {8047, title = {Biomarkers of Dietary Omega-6 Fatty Acids and Incident Cardiovascular Disease and Mortality.}, journal = {Circulation}, volume = {139}, year = {2019}, month = {2019 May 21}, pages = {2422-2436}, abstract = {

BACKGROUND: Global dietary recommendations for and cardiovascular effects of linoleic acid, the major dietary omega-6 fatty acid, and its major metabolite, arachidonic acid, remain controversial. To address this uncertainty and inform international recommendations, we evaluated how in vivo circulating and tissue levels of linoleic acid (LA) and arachidonic acid (AA) relate to incident cardiovascular disease (CVD) across multiple international studies.

METHODS: We performed harmonized, de novo, individual-level analyses in a global consortium of 30 prospective observational studies from 13 countries. Multivariable-adjusted associations of circulating and adipose tissue LA and AA biomarkers with incident total CVD and subtypes (coronary heart disease, ischemic stroke, cardiovascular mortality) were investigated according to a prespecified analytic plan. Levels of LA and AA, measured as the percentage of total fatty acids, were evaluated linearly according to their interquintile range (ie, the range between the midpoint of the first and fifth quintiles), and categorically by quintiles. Study-specific results were pooled using inverse-variance-weighted meta-analysis. Heterogeneity was explored by age, sex, race, diabetes mellitus, statin use, aspirin use, omega-3 levels, and fatty acid desaturase 1 genotype (when available).

RESULTS: In 30 prospective studies with medians of follow-up ranging 2.5 to 31.9 years, 15 198 incident cardiovascular events occurred among 68 659 participants. Higher levels of LA were significantly associated with lower risks of total CVD, cardiovascular mortality, and ischemic stroke, with hazard ratios per interquintile range of 0.93 (95\% CI, 0.88-0.99), 0.78 (0.70-0.85), and 0.88 (0.79-0.98), respectively, and nonsignificantly with lower coronary heart disease risk (0.94; 0.88-1.00). Relationships were similar for LA evaluated across quintiles. AA levels were not associated with higher risk of cardiovascular outcomes; in a comparison of extreme quintiles, higher levels were associated with lower risk of total CVD (0.92; 0.86-0.99). No consistent heterogeneity by population subgroups was identified in the observed relationships.

CONCLUSIONS: In pooled global analyses, higher in vivo circulating and tissue levels of LA and possibly AA were associated with lower risk of major cardiovascular events. These results support a favorable role for LA in CVD prevention.

}, issn = {1524-4539}, doi = {10.1161/CIRCULATIONAHA.118.038908}, author = {Marklund, Matti and Wu, Jason H Y and Imamura, Fumiaki and Del Gobbo, Liana C and Fretts, Amanda and de Goede, Janette and Shi, Peilin and Tintle, Nathan and Wennberg, Maria and Aslibekyan, Stella and Chen, Tzu-An and de Oliveira Otto, Marcia C and Hirakawa, Yoichiro and Eriksen, Helle H{\o}jmark and Kr{\"o}ger, Janine and Laguzzi, Federica and Lankinen, Maria and Murphy, Rachel A and Prem, Kiesha and Samieri, Cecilia and Virtanen, Jyrki and Wood, Alexis C and Wong, Kerry and Yang, Wei-Sin and Zhou, Xia and Baylin, Ana and Boer, Jolanda M A and Brouwer, Ingeborg A and Campos, Hannia and Chaves, Paulo H M and Chien, Kuo-Liong and de Faire, Ulf and Djouss{\'e}, Luc and Eiriksdottir, Gudny and El-Abbadi, Naglaa and Forouhi, Nita G and Michael Gaziano, J and Geleijnse, Johanna M and Gigante, Bruna and Giles, Graham and Guallar, Eliseo and Gudnason, Vilmundur and Harris, Tamara and Harris, William S and Helmer, Catherine and Hellenius, Mai-Lis and Hodge, Allison and Hu, Frank B and Jacques, Paul F and Jansson, Jan-H{\r a}kan and Kalsbeek, Anya and Khaw, Kay-Tee and Koh, Woon-Puay and Laakso, Markku and Leander, Karin and Lin, Hung-Ju and Lind, Lars and Luben, Robert and Luo, Juhua and McKnight, Barbara and Mursu, Jaakko and Ninomiya, Toshiharu and Overvad, Kim and Psaty, Bruce M and Rimm, Eric and Schulze, Matthias B and Siscovick, David and Skjelbo Nielsen, Michael and Smith, Albert V and Steffen, Brian T and Steffen, Lyn and Sun, Qi and Sundstr{\"o}m, Johan and Tsai, Michael Y and Tunstall-Pedoe, Hugh and Uusitupa, Matti I J and van Dam, Rob M and Veenstra, Jenna and Monique Verschuren, W M and Wareham, Nick and Willett, Walter and Woodward, Mark and Yuan, Jian-Min and Micha, Renata and Lemaitre, Rozenn N and Mozaffarian, Dariush and Riserus, Ulf} } @article {8624, title = {Meta-analysis uncovers genome-wide significant variants for rapid kidney function decline.}, journal = {Kidney Int}, year = {2020}, month = {2020 Oct 30}, abstract = {

Rapid decline of glomerular filtration rate estimated from creatinine (eGFRcrea) is associated with severe clinical endpoints. In contrast to cross-sectionally assessed eGFRcrea, the genetic basis for rapid eGFRcrea decline is largely unknown. To help define this, we meta-analyzed 42 genome-wide association studies from the Chronic Kidney Diseases Genetics Consortium and United Kingdom Biobank to identify genetic loci for rapid eGFRcrea decline. Two definitions of eGFRcrea decline were used: 3 mL/min/1.73m/year or more ("Rapid3"; encompassing 34,874 cases, 107,090 controls) and eGFRcrea decline 25\% or more and eGFRcrea under 60 mL/min/1.73m at follow-up among those with eGFRcrea 60 mL/min/1.73m or more at baseline ("CKDi25"; encompassing 19,901 cases, 175,244 controls). Seven independent variants were identified across six loci for Rapid3 and/or CKDi25: consisting of five variants at four loci with genome-wide significance (near UMOD-PDILT (2), PRKAG2, WDR72, OR2S2) and two variants among 265 known eGFRcrea variants (near GATM, LARP4B). All these loci were novel for Rapid3 and/or CKDi25 and our bioinformatic follow-up prioritized variants and genes underneath these loci. The OR2S2 locus is novel for any eGFRcrea trait including interesting candidates. For the five genome-wide significant lead variants, we found supporting effects for annual change in blood urea nitrogen or cystatin-based eGFR, but not for GATM or LARP4B. Individuals at high compared to those at low genetic risk (8-14 vs 0-5 adverse alleles) had a 1.20-fold increased risk of acute kidney injury (95\% confidence interval 1.08-1.33). Thus, our identified loci for rapid kidney function decline may help prioritize therapeutic targets and identify mechanisms and individuals at risk for sustained deterioration of kidney function.

}, issn = {1523-1755}, doi = {10.1016/j.kint.2020.09.030}, author = {Gorski, Mathias and Jung, Bettina and Li, Yong and Matias-Garcia, Pamela R and Wuttke, Matthias and Coassin, Stefan and Thio, Chris H L and Kleber, Marcus E and Winkler, Thomas W and Wanner, Veronika and Chai, Jin-Fang and Chu, Audrey Y and Cocca, Massimiliano and Feitosa, Mary F and Ghasemi, Sahar and Hoppmann, Anselm and Horn, Katrin and Li, Man and Nutile, Teresa and Scholz, Markus and Sieber, Karsten B and Teumer, Alexander and Tin, Adrienne and Wang, Judy and Tayo, Bamidele O and Ahluwalia, Tarunveer S and Almgren, Peter and Bakker, Stephan J L and Banas, Bernhard and Bansal, Nisha and Biggs, Mary L and Boerwinkle, Eric and Bottinger, Erwin P and Brenner, Hermann and Carroll, Robert J and Chalmers, John and Chee, Miao-Li and Chee, Miao-Ling and Cheng, Ching-Yu and Coresh, Josef and de Borst, Martin H and Degenhardt, Frauke and Eckardt, Kai-Uwe and Endlich, Karlhans and Franke, Andre and Freitag-Wolf, Sandra and Gampawar, Piyush and Gansevoort, Ron T and Ghanbari, Mohsen and Gieger, Christian and Hamet, Pavel and Ho, Kevin and Hofer, Edith and Holleczek, Bernd and Xian Foo, Valencia Hui and Hutri-K{\"a}h{\"o}nen, Nina and Hwang, Shih-Jen and Ikram, M Arfan and Josyula, Navya Shilpa and K{\"a}h{\"o}nen, Mika and Khor, Chiea-Chuen and Koenig, Wolfgang and Kramer, Holly and Kr{\"a}mer, Bernhard K and Kuhnel, Brigitte and Lange, Leslie A and Lehtim{\"a}ki, Terho and Lieb, Wolfgang and Loos, Ruth J F and Lukas, Mary Ann and Lyytik{\"a}inen, Leo-Pekka and Meisinger, Christa and Meitinger, Thomas and Melander, Olle and Milaneschi, Yuri and Mishra, Pashupati P and Mononen, Nina and Mychaleckyj, Josyf C and Nadkarni, Girish N and Nauck, Matthias and Nikus, Kjell and Ning, Boting and Nolte, Ilja M and O{\textquoteright}Donoghue, Michelle L and Orho-Melander, Marju and Pendergrass, Sarah A and Penninx, Brenda W J H and Preuss, Michael H and Psaty, Bruce M and Raffield, Laura M and Raitakari, Olli T and Rettig, Rainer and Rheinberger, Myriam and Rice, Kenneth M and Rosenkranz, Alexander R and Rossing, Peter and Rotter, Jerome I and Sabanayagam, Charumathi and Schmidt, Helena and Schmidt, Reinhold and Sch{\"o}ttker, Ben and Schulz, Christina-Alexandra and Sedaghat, Sanaz and Shaffer, Christian M and Strauch, Konstantin and Szymczak, Silke and Taylor, Kent D and Tremblay, Johanne and Chaker, Layal and van der Harst, Pim and van der Most, Peter J and Verweij, Niek and V{\"o}lker, Uwe and Waldenberger, Melanie and Wallentin, Lars and Waterworth, Dawn M and White, Harvey D and Wilson, James G and Wong, Tien-Yin and Woodward, Mark and Yang, Qiong and Yasuda, Masayuki and Yerges-Armstrong, Laura M and Zhang, Yan and Snieder, Harold and Wanner, Christoph and B{\"o}ger, Carsten A and K{\"o}ttgen, Anna and Kronenberg, Florian and Pattaro, Cristian and Heid, Iris M} } @article {9093, title = {Genetic loci and prioritization of genes for kidney function decline derived from a meta-analysis of 62 longitudinal genome-wide association studies.}, journal = {Kidney Int}, year = {2022}, month = {2022 Jun 16}, abstract = {

Estimated glomerular filtration rate (eGFR) reflects kidney function. Progressive eGFR-decline can lead to kidney failure, necessitating dialysis or transplantation. Hundreds of loci from genome-wide association studies (GWAS) for eGFR help explain population cross section variability. Since the contribution of these or other loci to eGFR-decline remains largely unknown, we derived GWAS for annual eGFR-decline and meta-analyzed 62 longitudinal studies with eGFR assessed twice over time in all 343,339 individuals and in high-risk groups. We also explored different covariate adjustment. Twelve genome-wide significant independent variants for eGFR-decline unadjusted or adjusted for eGFR-baseline (11 novel, one known for this phenotype), including nine variants robustly associated across models were identified. All loci for eGFR-decline were known for cross-sectional eGFR and thus distinguished a subgroup of eGFR loci. Seven of the nine variants showed variant-by-age interaction on eGFR cross section (further about 350,000 individuals), which linked genetic associations for eGFR-decline with age-dependency of genetic cross-section associations. Clinically important were two to four-fold greater genetic effects on eGFR-decline in high-risk subgroups. Five variants associated also with chronic kidney disease progression mapped to genes with functional in-silico evidence (UMOD, SPATA7, GALNTL5, TPPP). An unfavorable versus favorable nine-variant genetic profile showed increased risk odds ratios of 1.35 for kidney failure (95\% confidence intervals 1.03-1.77) and 1.27 for acute kidney injury (95\% confidence intervals 1.08-1.50) in over 2000 cases each, with matched controls). Thus, we provide a large data resource, genetic loci, and prioritized genes for kidney function decline, which help inform drug development pipelines revealing important insights into the age-dependency of kidney function genetics.

}, issn = {1523-1755}, doi = {10.1016/j.kint.2022.05.021}, author = {Gorski, Mathias and Rasheed, Humaira and Teumer, Alexander and Thomas, Laurent F and Graham, Sarah E and Sveinbjornsson, Gardar and Winkler, Thomas W and G{\"u}nther, Felix and Stark, Klaus J and Chai, Jin-Fang and Tayo, Bamidele O and Wuttke, Matthias and Li, Yong and Tin, Adrienne and Ahluwalia, Tarunveer S and Arnl{\"o}v, Johan and {\r A}svold, Bj{\o}rn Olav and Bakker, Stephan J L and Banas, Bernhard and Bansal, Nisha and Biggs, Mary L and Biino, Ginevra and B{\"o}hnke, Michael and Boerwinkle, Eric and Bottinger, Erwin P and Brenner, Hermann and Brumpton, Ben and Carroll, Robert J and Chaker, Layal and Chalmers, John and Chee, Miao-Li and Chee, Miao-Ling and Cheng, Ching-Yu and Chu, Audrey Y and Ciullo, Marina and Cocca, Massimiliano and Cook, James P and Coresh, Josef and Cusi, Daniele and de Borst, Martin H and Degenhardt, Frauke and Eckardt, Kai-Uwe and Endlich, Karlhans and Evans, Michele K and Feitosa, Mary F and Franke, Andre and Freitag-Wolf, Sandra and Fuchsberger, Christian and Gampawar, Piyush and Gansevoort, Ron T and Ghanbari, Mohsen and Ghasemi, Sahar and Giedraitis, Vilmantas and Gieger, Christian and Gudbjartsson, Daniel F and Hallan, Stein and Hamet, Pavel and Hishida, Asahi and Ho, Kevin and Hofer, Edith and Holleczek, Bernd and Holm, Hilma and Hoppmann, Anselm and Horn, Katrin and Hutri-K{\"a}h{\"o}nen, Nina and Hveem, Kristian and Hwang, Shih-Jen and Ikram, M Arfan and Josyula, Navya Shilpa and Jung, Bettina and K{\"a}h{\"o}nen, Mika and Karabegovi{\'c}, Irma and Khor, Chiea-Chuen and Koenig, Wolfgang and Kramer, Holly and Kr{\"a}mer, Bernhard K and Kuhnel, Brigitte and Kuusisto, Johanna and Laakso, Markku and Lange, Leslie A and Lehtim{\"a}ki, Terho and Li, Man and Lieb, Wolfgang and Lind, Lars and Lindgren, Cecilia M and Loos, Ruth J F and Lukas, Mary Ann and Lyytik{\"a}inen, Leo-Pekka and Mahajan, Anubha and Matias-Garcia, Pamela R and Meisinger, Christa and Meitinger, Thomas and Melander, Olle and Milaneschi, Yuri and Mishra, Pashupati P and Mononen, Nina and Morris, Andrew P and Mychaleckyj, Josyf C and Nadkarni, Girish N and Naito, Mariko and Nakatochi, Masahiro and Nalls, Mike A and Nauck, Matthias and Nikus, Kjell and Ning, Boting and Nolte, Ilja M and Nutile, Teresa and O{\textquoteright}Donoghue, Michelle L and O{\textquoteright}Connell, Jeffrey and Olafsson, Isleifur and Orho-Melander, Marju and Parsa, Afshin and Pendergrass, Sarah A and Penninx, Brenda W J H and Pirastu, Mario and Preuss, Michael H and Psaty, Bruce M and Raffield, Laura M and Raitakari, Olli T and Rheinberger, Myriam and Rice, Kenneth M and Rizzi, Federica and Rosenkranz, Alexander R and Rossing, Peter and Rotter, Jerome I and Ruggiero, Daniela and Ryan, Kathleen A and Sabanayagam, Charumathi and Salvi, Erika and Schmidt, Helena and Schmidt, Reinhold and Scholz, Markus and Sch{\"o}ttker, Ben and Schulz, Christina-Alexandra and Sedaghat, Sanaz and Shaffer, Christian M and Sieber, Karsten B and Sim, Xueling and Sims, Mario and Snieder, Harold and Stanzick, Kira J and Thorsteinsdottir, Unnur and Stocker, Hannah and Strauch, Konstantin and Stringham, Heather M and Sulem, Patrick and Szymczak, Silke and Taylor, Kent D and Thio, Chris H L and Tremblay, Johanne and Vaccargiu, Simona and van der Harst, Pim and van der Most, Peter J and Verweij, Niek and V{\"o}lker, Uwe and Wakai, Kenji and Waldenberger, Melanie and Wallentin, Lars and Wallner, Stefan and Wang, Judy and Waterworth, Dawn M and White, Harvey D and Willer, Cristen J and Wong, Tien-Yin and Woodward, Mark and Yang, Qiong and Yerges-Armstrong, Laura M and Zimmermann, Martina and Zonderman, Alan B and Bergler, Tobias and Stefansson, Kari and B{\"o}ger, Carsten A and Pattaro, Cristian and K{\"o}ttgen, Anna and Kronenberg, Florian and Heid, Iris M} } @article {9579, title = {X-chromosome and kidney function: evidence from a multi-trait genetic analysis of 908,697 individuals reveals sex-specific and sex-differential findings in genes regulated by androgen response elements.}, journal = {Nat Commun}, volume = {15}, year = {2024}, month = {2024 Jan 18}, pages = {586}, abstract = {

X-chromosomal genetic variants are understudied but can yield valuable insights into sexually dimorphic human traits and diseases. We performed a sex-stratified cross-ancestry X-chromosome-wide association meta-analysis of seven kidney-related traits (n = 908,697), identifying 23 loci genome-wide significantly associated with two of the traits: 7 for uric acid and 16 for estimated glomerular filtration rate (eGFR), including four novel eGFR loci containing the functionally plausible prioritized genes ACSL4, CLDN2, TSPAN6 and the female-specific DRP2. Further, we identified five novel sex-interactions, comprising male-specific effects at FAM9B and AR/EDA2R, and three sex-differential findings with larger genetic effect sizes in males at DCAF12L1 and MST4 and larger effect sizes in females at HPRT1. All prioritized genes in loci showing significant sex-interactions were located next to androgen response elements (ARE). Five ARE genes showed sex-differential expressions. This study contributes new insights into sex-dimorphisms of kidney traits along with new prioritized gene targets for further molecular research.

}, keywords = {Androgens, Chromosomes, Human, X, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Kidney, Male, Polymorphism, Single Nucleotide, Response Elements, Tetraspanins}, issn = {2041-1723}, doi = {10.1038/s41467-024-44709-1}, author = {Scholz, Markus and Horn, Katrin and Pott, Janne and Wuttke, Matthias and K{\"u}hnapfel, Andreas and Nasr, M Kamal and Kirsten, Holger and Li, Yong and Hoppmann, Anselm and Gorski, Mathias and Ghasemi, Sahar and Li, Man and Tin, Adrienne and Chai, Jin-Fang and Cocca, Massimiliano and Wang, Judy and Nutile, Teresa and Akiyama, Masato and {\r A}svold, Bj{\o}rn Olav and Bansal, Nisha and Biggs, Mary L and Boutin, Thibaud and Brenner, Hermann and Brumpton, Ben and Burkhardt, Ralph and Cai, Jianwen and Campbell, Archie and Campbell, Harry and Chalmers, John and Chasman, Daniel I and Chee, Miao Ling and Chee, Miao Li and Chen, Xu and Cheng, Ching-Yu and Cifkova, Renata and Daviglus, Martha and Delgado, Graciela and Dittrich, Katalin and Edwards, Todd L and Endlich, Karlhans and Michael Gaziano, J and Giri, Ayush and Giulianini, Franco and Gordon, Scott D and Gudbjartsson, Daniel F and Hallan, Stein and Hamet, Pavel and Hartman, Catharina A and Hayward, Caroline and Heid, Iris M and Hellwege, Jacklyn N and Holleczek, Bernd and Holm, Hilma and Hutri-K{\"a}h{\"o}nen, Nina and Hveem, Kristian and Isermann, Berend and Jonas, Jost B and Joshi, Peter K and Kamatani, Yoichiro and Kanai, Masahiro and Kastarinen, Mika and Khor, Chiea Chuen and Kiess, Wieland and Kleber, Marcus E and K{\"o}rner, Antje and Kovacs, Peter and Krajcoviechova, Alena and Kramer, Holly and Kr{\"a}mer, Bernhard K and Kuokkanen, Mikko and K{\"a}h{\"o}nen, Mika and Lange, Leslie A and Lash, James P and Lehtim{\"a}ki, Terho and Li, Hengtong and Lin, Bridget M and Liu, Jianjun and Loeffler, Markus and Lyytik{\"a}inen, Leo-Pekka and Magnusson, Patrik K E and Martin, Nicholas G and Matsuda, Koichi and Milaneschi, Yuri and Mishra, Pashupati P and Mononen, Nina and Montgomery, Grant W and Mook-Kanamori, Dennis O and Mychaleckyj, Josyf C and M{\"a}rz, Winfried and Nauck, Matthias and Nikus, Kjell and Nolte, Ilja M and Noordam, Raymond and Okada, Yukinori and Olafsson, Isleifur and Oldehinkel, Albertine J and Penninx, Brenda W J H and Perola, Markus and Pirastu, Nicola and Polasek, Ozren and Porteous, David J and Poulain, Tanja and Psaty, Bruce M and Rabelink, Ton J and Raffield, Laura M and Raitakari, Olli T and Rasheed, Humaira and Reilly, Dermot F and Rice, Kenneth M and Richmond, Anne and Ridker, Paul M and Rotter, Jerome I and Rudan, Igor and Sabanayagam, Charumathi and Salomaa, Veikko and Schneiderman, Neil and Sch{\"o}ttker, Ben and Sims, Mario and Snieder, Harold and Stark, Klaus J and Stefansson, Kari and Stocker, Hannah and Stumvoll, Michael and Sulem, Patrick and Sveinbjornsson, Gardar and Svensson, Per O and Tai, E-Shyong and Taylor, Kent D and Tayo, Bamidele O and Teren, Andrej and Tham, Yih-Chung and Thiery, Joachim and Thio, Chris H L and Thomas, Laurent F and Tremblay, Johanne and T{\"o}njes, Anke and van der Most, Peter J and Vitart, Veronique and V{\"o}lker, Uwe and Wang, Ya Xing and Wang, Chaolong and Wei, Wen Bin and Whitfield, John B and Wild, Sarah H and Wilson, James F and Winkler, Thomas W and Wong, Tien-Yin and Woodward, Mark and Sim, Xueling and Chu, Audrey Y and Feitosa, Mary F and Thorsteinsdottir, Unnur and Hung, Adriana M and Teumer, Alexander and Franceschini, Nora and Parsa, Afshin and K{\"o}ttgen, Anna and Schlosser, Pascal and Pattaro, Cristian} }