@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 {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} }