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1.  Association of Functional Polymorphism rs2231142 (Q141K) in the ABCG2 Gene With Serum Uric Acid and Gout in 4 US Populations 
American Journal of Epidemiology  2013;177(9):923-932.
A loss-of-function mutation (Q141K, rs2231142) in the ATP-binding cassette, subfamily G, member 2 gene (ABCG2) has been shown to be associated with serum uric acid levels and gout in Asians, Europeans, and European and African Americans; however, less is known about these associations in other populations. Rs2231142 was genotyped in 22,734 European Americans, 9,720 African Americans, 3,849 Mexican Americans, and 3,550 American Indians in the Population Architecture using Genomics and Epidemiology (PAGE) Study (2008–2012). Rs2231142 was significantly associated with serum uric acid levels (P = 2.37 × 10−67, P = 3.98 × 10−5, P = 6.97 × 10−9, and P = 5.33 × 10−4 in European Americans, African Americans, Mexican Americans, and American Indians, respectively) and gout (P = 2.83 × 10−10, P = 0.01, and P = 0.01 in European Americans, African Americans, and Mexican Americans, respectively). Overall, the T allele was associated with a 0.24-mg/dL increase in serum uric acid level (P = 1.37 × 10−80) and a 1.75-fold increase in the odds of gout (P = 1.09 × 10−12). The association between rs2231142 and serum uric acid was significantly stronger in men, postmenopausal women, and hormone therapy users compared with their counterparts. The association with gout was also significantly stronger in men than in women. These results highlight a possible role of sex hormones in the regulation of ABCG2 urate transporter and its potential implications for the prevention, diagnosis, and treatment of hyperuricemia and gout.
PMCID: PMC4023295  PMID: 23552988
ABCG2 protein, human; genetic association studies; gout; meta-analysis; polymorphism, single nucleotide; urate transporter; uric acid
2.  Does Genetic Ancestry Explain Higher Values of Glycated Hemoglobin in African Americans? 
Diabetes  2011;60(9):2434-2438.
Glycated hemoglobin (HbA1c) values are higher in African Americans than whites, raising the question of whether classification of diabetes status by HbA1c should differ for African Americans. We investigated the relative contribution of genetic ancestry and nongenetic factors to HbA1c values and the effect of genetic ancestry on diabetes classification by HbA1c in African Americans.
We performed a cross-sectional analysis of data from the community-based Atherosclerosis Risk in Communities (ARIC) Study. We estimated percentage of European genetic ancestry (PEA) for each of the 2,294 African Americans without known diabetes using 1,350 ancestry-informative markers. HbA1c was measured from whole-blood samples and categorized using American Diabetes Association diagnostic cut points (<5.7, 5.7–6.4, and ≥6.5%).
PEA was inversely correlated with HbA1c (adjusted r = −0.07; P < 0.001) but explained <1% of its variance. Age and socioeconomic and metabolic factors, including fasting glucose, explained 13.8% of HbA1c variability. Eleven percent of participants were classified as having diabetes; adjustment for fasting glucose decreased this to 4.4%. Additional adjustment for PEA did not significantly reclassify diabetes status (net reclassification index = 0.034; P = 0.94) nor did further adjustment for demographic, socioeconomic, and metabolic risk factors.
The relative contribution of demographic and metabolic factors far outweighs the contribution of genetic ancestry to HbA1c values in African Americans. Moreover, the impact of adjusting for genetic ancestry when classifying diabetes by HbA1c is minimal after taking into account fasting glucose levels, thus supporting the use of currently recommended HbA1c categories for diagnosis of diabetes in African Americans.
PMCID: PMC3161314  PMID: 21788574
3.  Pleiotropic genes for metabolic syndrome and inflammation 
Molecular genetics and metabolism  2014;112(4):317-338.
Metabolic syndrome (MetS) has become a health and financial burden worldwide. The MetS definition captures clustering of risk factors that predict higher risk for diabetes mellitus and cardiovascular disease. Our study hypothesis is that additional to genes influencing individual MetS risk factors, genetic variants exist that influence MetS and inflammatory markers forming a predisposing MetS genetic network. To test this hypothesis a staged approach was undertaken. (a) We analyzed 17 metabolic and inflammatory traits in more than 85,500 participants from 14 large epidemiological studies within the Cross Consortia Pleiotropy Group. Individuals classified with MetS (NCEP definition), versus those without, showed on average significantly different levels for most inflammatory markers studied. (b) Paired average correlations between 8 metabolic traits and 9 inflammatory markers from the same studies as above, estimated with two methods, and factor analyses on large simulated data, helped in identifying 8 combinations of traits for follow-up in meta-analyses, out of 130,305 possible combinations between metabolic traits and inflammatory markers studied. (c) We performed correlated meta-analyses for 8 metabolic traits and 6 inflammatory markers by using existing GWAS published genetic summary results, with about 2.5 million SNPs from twelve predominantly largest GWAS consortia. These analyses yielded 130 unique SNPs/genes with pleiotropic associations (a SNP/gene associating at least one metabolic trait and one inflammatory marker). Of them twenty-five variants (seven loci newly reported) are proposed as MetS candidates. They map to genes MACF1, KIAA0754, GCKR, GRB14, COBLL1, LOC646736-IRS1, SLC39A8, NELFE, SKIV2L, STK19, TFAP2B, BAZ1B, BCL7B, TBL2, MLXIPL, LPL, TRIB1, ATXN2, HECTD4, PTPN11, ZNF664, PDXDC1, FTO, MC4R and TOMM40. Based on large data evidence, we conclude that inflammation is a feature of MetS and several gene variants show pleiotropic genetic associations across phenotypes and might explain a part of MetS correlated genetic architecture. These findings warrant further functional investigation.
PMCID: PMC4122618  PMID: 24981077
4.  Rationale and design for the Predictors of Arrhythmic and Cardiovascular Risk in End Stage Renal Disease (PACE) study 
BMC Nephrology  2015;16:63.
Sudden cardiac death occurs commonly in the end-stage renal disease population receiving dialysis, with 25% dying of sudden cardiac death over 5 years. Despite this high risk, surprisingly few prospective studies have studied clinical- and dialysis-related risk factors for sudden cardiac death and arrhythmic precursors of sudden cardiac death in end-stage renal disease.
We present a brief summary of the risk factors for arrhythmias and sudden cardiac death in persons with end-stage renal disease as the rationale for the Predictors of Arrhythmic and Cardiovascular Risk in End Stage Renal Disease (PACE) study, a prospective cohort study of patients recently initiated on chronic hemodialysis, with the overall goal to understand arrhythmic and sudden cardiac death risk. Participants were screened for eligibility and excluded if they already had a pacemaker or an automatic implantable cardioverter defibrillator. We describe the study aims, design, and data collection of 574 incident hemodialysis participants from the Baltimore region in Maryland, U.S.A.. Participants were recruited from 27 hemodialysis units and underwent detailed clinical, dialysis and cardiovascular evaluation at baseline and follow-up. Cardiovascular phenotyping was conducted on nondialysis days with signal averaged electrocardiogram, echocardiogram, pulse wave velocity, ankle, brachial index, and cardiac computed tomography and angiography conducted at baseline. Participants were followed annually with study visits including electrocardiogram, pulse wave velocity, and ankle brachial index up to 4 years. A biorepository of serum, plasma, DNA, RNA, and nails were collected to study genetic and serologic factors associated with disease.
Studies of modifiable risk factors for sudden cardiac death will help set the stage for clinical trials to test therapies to prevent sudden cardiac death in this high-risk population.
PMCID: PMC4434806  PMID: 25903746
Dialysis; Hemodialysis; Mortality; Sudden death; Sudden cardiac death; Arrhythmia; End stage renal disease
5.  Genome-wide association study identifies common loci influencing circulating glycated hemoglobin (HbA1c) levels in non-diabetic subjects: the Long Life Family Study (LLFS) 
Glycated hemoglobin (HbA1c) is a stable index of chronic glycemic status and hyperglycemia associated with progressive development of insulin resistance and frank diabetes. It is also associated with premature aging and increased mortality. To uncover novel loci for HbA1c that are associated with healthy aging, we conducted a genome-wide association study (GWAS) using non-diabetic participants in the Long Life Family Study (LLFS), a study with familial clustering of exceptional longevity in the US and Denmark.
A total of 4,088 non-diabetic subjects from the LLFS were used for GWAS discoveries, and a total of 8,231 non-diabetic subjects from the Atherosclerosis Risk in Communities Study (ARIC, in the MAGIC Consortium) and the Health, Aging, and Body Composition Study (HABC) were used for GWAS replications. HbA1c was adjusted for age, sex, centers, 20 principal components, without and with BMI. A linear mixed effects model was used for association testing.
Two known loci at GCK rs730497 (or rs2908282) and HK1 rs17476364 were confirmed (p < 5e–8). Of 25 suggestive (5e–8 < p < 1e–5) loci, one known (G6PC2 rs560887, replication p = 5e–5) and one novel (OR10R3P/SPTA1- rs12041363, replication p = 1e–17) loci were replicated (p < 0.0019). Similar findings resulted when HbA1c was further adjusted for BMI. Further validations are crucial for the remaining suggestive loci including the emerged variant near OR10R3P/SPTA1.
The analysis reconfirmed two known GWAS loci (GCK, HK1) and identified 25 suggestive loci including one reconfirmed variant in G6PC2 and one replicated variant near OR10R3P/SPTA1. Future focused survey of sequence elements containing mainly functional and regulatory variants may yield additional findings.
PMCID: PMC3965585  PMID: 24405752
Genome-wide association study; Non-enzymatic glycation; Glucose, insulin resistance and diabetes; Premature aging processes
6.  Modulation of Genetic Associations with Serum Urate Levels by Body-Mass-Index in Humans 
Huffman, Jennifer E. | Albrecht, Eva | Teumer, Alexander | Mangino, Massimo | Kapur, Karen | Johnson, Toby | Kutalik, Zoltán | Pirastu, Nicola | Pistis, Giorgio | Lopez, Lorna M. | Haller, Toomas | Salo, Perttu | Goel, Anuj | Li, Man | Tanaka, Toshiko | Dehghan, Abbas | Ruggiero, Daniela | Malerba, Giovanni | Smith, Albert V. | Nolte, Ilja M. | Portas, Laura | Phipps-Green, Amanda | Boteva, Lora | Navarro, Pau | Johansson, Asa | Hicks, Andrew A. | Polasek, Ozren | Esko, Tõnu | Peden, John F. | Harris, Sarah E. | Murgia, Federico | Wild, Sarah H. | Tenesa, Albert | Tin, Adrienne | Mihailov, Evelin | Grotevendt, Anne | Gislason, Gauti K. | Coresh, Josef | D'Adamo, Pio | Ulivi, Sheila | Vollenweider, Peter | Waeber, Gerard | Campbell, Susan | Kolcic, Ivana | Fisher, Krista | Viigimaa, Margus | Metter, Jeffrey E. | Masciullo, Corrado | Trabetti, Elisabetta | Bombieri, Cristina | Sorice, Rossella | Döring, Angela | Reischl, Eva | Strauch, Konstantin | Hofman, Albert | Uitterlinden, Andre G. | Waldenberger, Melanie | Wichmann, H-Erich | Davies, Gail | Gow, Alan J. | Dalbeth, Nicola | Stamp, Lisa | Smit, Johannes H. | Kirin, Mirna | Nagaraja, Ramaiah | Nauck, Matthias | Schurmann, Claudia | Budde, Kathrin | Farrington, Susan M. | Theodoratou, Evropi | Jula, Antti | Salomaa, Veikko | Sala, Cinzia | Hengstenberg, Christian | Burnier, Michel | Mägi, Reedik | Klopp, Norman | Kloiber, Stefan | Schipf, Sabine | Ripatti, Samuli | Cabras, Stefano | Soranzo, Nicole | Homuth, Georg | Nutile, Teresa | Munroe, Patricia B. | Hastie, Nicholas | Campbell, Harry | Rudan, Igor | Cabrera, Claudia | Haley, Chris | Franco, Oscar H. | Merriman, Tony R. | Gudnason, Vilmundur | Pirastu, Mario | Penninx, Brenda W. | Snieder, Harold | Metspalu, Andres | Ciullo, Marina | Pramstaller, Peter P. | van Duijn, Cornelia M. | Ferrucci, Luigi | Gambaro, Giovanni | Deary, Ian J. | Dunlop, Malcolm G. | Wilson, James F. | Gasparini, Paolo | Gyllensten, Ulf | Spector, Tim D. | Wright, Alan F. | Hayward, Caroline | Watkins, Hugh | Perola, Markus | Bochud, Murielle | Kao, W. H. Linda | Caulfield, Mark | Toniolo, Daniela | Völzke, Henry | Gieger, Christian | Köttgen, Anna | Vitart, Veronique
PLoS ONE  2015;10(3):e0119752.
We tested for interactions between body mass index (BMI) and common genetic variants affecting serum urate levels, genome-wide, in up to 42569 participants. Both stratified genome-wide association (GWAS) analyses, in lean, overweight and obese individuals, and regression-type analyses in a non BMI-stratified overall sample were performed. The former did not uncover any novel locus with a major main effect, but supported modulation of effects for some known and potentially new urate loci. The latter highlighted a SNP at RBFOX3 reaching genome-wide significant level (effect size 0.014, 95% CI 0.008-0.02, Pinter= 2.6 x 10-8). Two top loci in interaction term analyses, RBFOX3 and ERO1LB-EDARADD, also displayed suggestive differences in main effect size between the lean and obese strata. All top ranking loci for urate effect differences between BMI categories were novel and most had small magnitude but opposite direction effects between strata. They include the locus RBMS1-TANK (men, Pdifflean-overweight= 4.7 x 10-8), a region that has been associated with several obesity related traits, and TSPYL5 (men, Pdifflean-overweight= 9.1 x 10-8), regulating adipocytes-produced estradiol. The top-ranking known urate loci was ABCG2, the strongest known gout risk locus, with an effect halved in obese compared to lean men (Pdifflean-obese= 2 x 10-4). Finally, pathway analysis suggested a role for N-glycan biosynthesis as a prominent urate-associated pathway in the lean stratum. These results illustrate a potentially powerful way to monitor changes occurring in obesogenic environment.
PMCID: PMC4374966  PMID: 25811787
7.  The Pharmacogenetics of Type 2 Diabetes: A Systematic Review 
Diabetes Care  2014;37(3):876-886.
We performed a systematic review to identify which genetic variants predict response to diabetes medications.
We performed a search of electronic databases (PubMed, EMBASE, and Cochrane Database) and a manual search to identify original, longitudinal studies of the effect of diabetes medications on incident diabetes, HbA1c, fasting glucose, and postprandial glucose in prediabetes or type 2 diabetes by genetic variation. Two investigators reviewed titles, abstracts, and articles independently. Two investigators abstracted data sequentially and evaluated study quality independently. Quality evaluations were based on the Strengthening the Reporting of Genetic Association Studies guidelines and Human Genome Epidemiology Network guidance.
Of 7,279 citations, we included 34 articles (N = 10,407) evaluating metformin (n = 14), sulfonylureas (n = 4), repaglinide (n = 8), pioglitazone (n = 3), rosiglitazone (n = 4), and acarbose (n = 4). Studies were not standalone randomized controlled trials, and most evaluated patients with diabetes. Significant medication–gene interactions for glycemic outcomes included 1) metformin and the SLC22A1, SLC22A2, SLC47A1, PRKAB2, PRKAA2, PRKAA1, and STK11 loci; 2) sulfonylureas and the CYP2C9 and TCF7L2 loci; 3) repaglinide and the KCNJ11, SLC30A8, NEUROD1/BETA2, UCP2, and PAX4 loci; 4) pioglitazone and the PPARG2 and PTPRD loci; 5) rosiglitazone and the KCNQ1 and RBP4 loci; and 5) acarbose and the PPARA, HNF4A, LIPC, and PPARGC1A loci. Data were insufficient for meta-analysis.
We found evidence of pharmacogenetic interactions for metformin, sulfonylureas, repaglinide, thiazolidinediones, and acarbose consistent with their pharmacokinetics and pharmacodynamics. While high-quality controlled studies with prespecified analyses are still lacking, our results bring the promise of personalized medicine in diabetes one step closer to fruition.
PMCID: PMC3931386  PMID: 24558078
8.  Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization 
Arking, Dan E. | Pulit, Sara L. | Crotti, Lia | van der Harst, Pim | Munroe, Patricia B. | Koopmann, Tamara T. | Sotoodehnia, Nona | Rossin, Elizabeth J. | Morley, Michael | Wang, Xinchen | Johnson, Andrew D. | Lundby, Alicia | Gudbjartsson, Daníel F. | Noseworthy, Peter A. | Eijgelsheim, Mark | Bradford, Yuki | Tarasov, Kirill V. | Dörr, Marcus | Müller-Nurasyid, Martina | Lahtinen, Annukka M. | Nolte, Ilja M. | Smith, Albert Vernon | Bis, Joshua C. | Isaacs, Aaron | Newhouse, Stephen J. | Evans, Daniel S. | Post, Wendy S. | Waggott, Daryl | Lyytikäinen, Leo-Pekka | Hicks, Andrew A. | Eisele, Lewin | Ellinghaus, David | Hayward, Caroline | Navarro, Pau | Ulivi, Sheila | Tanaka, Toshiko | Tester, David J. | Chatel, Stéphanie | Gustafsson, Stefan | Kumari, Meena | Morris, Richard W. | Naluai, Åsa T. | Padmanabhan, Sandosh | Kluttig, Alexander | Strohmer, Bernhard | Panayiotou, Andrie G. | Torres, Maria | Knoflach, Michael | Hubacek, Jaroslav A. | Slowikowski, Kamil | Raychaudhuri, Soumya | Kumar, Runjun D. | Harris, Tamara B. | Launer, Lenore J. | Shuldiner, Alan R. | Alonso, Alvaro | Bader, Joel S. | Ehret, Georg | Huang, Hailiang | Kao, W.H. Linda | Strait, James B. | Macfarlane, Peter W. | Brown, Morris | Caulfield, Mark J. | Samani, Nilesh J. | Kronenberg, Florian | Willeit, Johann | Smith, J. Gustav | Greiser, Karin H. | zu Schwabedissen, Henriette Meyer | Werdan, Karl | Carella, Massimo | Zelante, Leopoldo | Heckbert, Susan R. | Psaty, Bruce M. | Rotter, Jerome I. | Kolcic, Ivana | Polašek, Ozren | Wright, Alan F. | Griffin, Maura | Daly, Mark J. | Arnar, David O. | Hólm, Hilma | Thorsteinsdottir, Unnur | Denny, Joshua C. | Roden, Dan M. | Zuvich, Rebecca L. | Emilsson, Valur | Plump, Andrew S. | Larson, Martin G. | O'Donnell, Christopher J. | Yin, Xiaoyan | Bobbo, Marco | D'Adamo, Adamo P. | Iorio, Annamaria | Sinagra, Gianfranco | Carracedo, Angel | Cummings, Steven R. | Nalls, Michael A. | Jula, Antti | Kontula, Kimmo K. | Marjamaa, Annukka | Oikarinen, Lasse | Perola, Markus | Porthan, Kimmo | Erbel, Raimund | Hoffmann, Per | Jöckel, Karl-Heinz | Kälsch, Hagen | Nöthen, Markus M. | consortium, HRGEN | den Hoed, Marcel | Loos, Ruth J.F. | Thelle, Dag S. | Gieger, Christian | Meitinger, Thomas | Perz, Siegfried | Peters, Annette | Prucha, Hanna | Sinner, Moritz F. | Waldenberger, Melanie | de Boer, Rudolf A. | Franke, Lude | van der Vleuten, Pieter A. | Beckmann, Britt Maria | Martens, Eimo | Bardai, Abdennasser | Hofman, Nynke | Wilde, Arthur A.M. | Behr, Elijah R. | Dalageorgou, Chrysoula | Giudicessi, John R. | Medeiros-Domingo, Argelia | Barc, Julien | Kyndt, Florence | Probst, Vincent | Ghidoni, Alice | Insolia, Roberto | Hamilton, Robert M. | Scherer, Stephen W. | Brandimarto, Jeffrey | Margulies, Kenneth | Moravec, Christine E. | Fabiola Del, Greco M. | Fuchsberger, Christian | O'Connell, Jeffrey R. | Lee, Wai K. | Watt, Graham C.M. | Campbell, Harry | Wild, Sarah H. | El Mokhtari, Nour E. | Frey, Norbert | Asselbergs, Folkert W. | Leach, Irene Mateo | Navis, Gerjan | van den Berg, Maarten P. | van Veldhuisen, Dirk J. | Kellis, Manolis | Krijthe, Bouwe P. | Franco, Oscar H. | Hofman, Albert | Kors, Jan A. | Uitterlinden, André G. | Witteman, Jacqueline C.M. | Kedenko, Lyudmyla | Lamina, Claudia | Oostra, Ben A. | Abecasis, Gonçalo R. | Lakatta, Edward G. | Mulas, Antonella | Orrú, Marco | Schlessinger, David | Uda, Manuela | Markus, Marcello R.P. | Völker, Uwe | Snieder, Harold | Spector, Timothy D. | Ärnlöv, Johan | Lind, Lars | Sundström, Johan | Syvänen, Ann-Christine | Kivimaki, Mika | Kähönen, Mika | Mononen, Nina | Raitakari, Olli T. | Viikari, Jorma S. | Adamkova, Vera | Kiechl, Stefan | Brion, Maria | Nicolaides, Andrew N. | Paulweber, Bernhard | Haerting, Johannes | Dominiczak, Anna F. | Nyberg, Fredrik | Whincup, Peter H. | Hingorani, Aroon | Schott, Jean-Jacques | Bezzina, Connie R. | Ingelsson, Erik | Ferrucci, Luigi | Gasparini, Paolo | Wilson, James F. | Rudan, Igor | Franke, Andre | Mühleisen, Thomas W. | Pramstaller, Peter P. | Lehtimäki, Terho J. | Paterson, Andrew D. | Parsa, Afshin | Liu, Yongmei | van Duijn, Cornelia | Siscovick, David S. | Gudnason, Vilmundur | Jamshidi, Yalda | Salomaa, Veikko | Felix, Stephan B. | Sanna, Serena | Ritchie, Marylyn D. | Stricker, Bruno H. | Stefansson, Kari | Boyer, Laurie A. | Cappola, Thomas P. | Olsen, Jesper V. | Lage, Kasper | Schwartz, Peter J. | Kääb, Stefan | Chakravarti, Aravinda | Ackerman, Michael J. | Pfeufer, Arne | de Bakker, Paul I.W. | Newton-Cheh, Christopher
Nature genetics  2014;46(8):826-836.
The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal Mendelian Long QT Syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals we identified 35 common variant QT interval loci, that collectively explain ∼8-10% of QT variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 novel QT loci in 298 unrelated LQTS probands identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode for proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies novel candidate genes for ventricular arrhythmias, LQTS,and SCD.
PMCID: PMC4124521  PMID: 24952745
genome-wide association study; QT interval; Long QT Syndrome; sudden cardiac death; myocardial repolarization; arrhythmias
9.  Association of a Cystatin C Gene Variant With Cystatin C Levels, CKD, and Risk of Incident Cardiovascular Disease and Mortality 
Carriers of the T allele of the single-nucleotide polymorphism rs13038305 tend to have lower cystatin C levels and higher cystatin C-based estimated glomerular filtration rate (eGFRcys). Adjusting for this genetic effect on cystatin C concentrations may improve GFR estimation, reclassify cases of CKD, and strengthen risk estimates for cardiovascular disease (CVD) and mortality.
Study Design
Setting & Population
Four population-based cohorts: Atherosclerosis Risk in Communities (ARIC), Cardiovascular Health (CHS), Framingham Heart (FHS), and Health, Aging, and Body Compostion (Health ABC) studies.
We estimated the association of rs13038305 with eGFRcys and eGFRcr, and performed longitudinal analyses of the associations of eGFRcys with mortality and cardiovascular events following adjustment for rs13038305.
We assessed reclassification by genotype-adjusted eGFRcys across CKD categories: <45, 45–59, 60–89, and ≥90 mL/min/1.73 m2. We compared mortality and CVD outcomes in those reclassified to a worse eGFRcys category with those unaffected. Results were combined using fixed-effect inverse-variance meta-analysis.
In 14,645 participants, each copy of the T allele of rs13038305 (frequency, 21%), was associated with 6.4% lower cystatin C concentration, 5.5 mL/min/1.73 m2 higher eGFRcys, and 36% [95% CI, 29%–41%] lower odds of CKD. Associations with CVD (HR, 1.17; 95% CI, 1.14–1.20) and mortality (HR, 1.22; 95% CI, 1.19–1.24) per 10- ml/min/1.73 m2 lower eGFRcys were similar with or without rs13038305 adjustment. In total, 1134 participants (7.7%) were reclassified to a worse CKD category following rs13038305 adjustment, and rates of CVD and mortality were higher in individuals who were reclassified. However, the overall net reclassification index was not significant for either outcome, at 0.009 (95% CI, −0.003 to 0.022) for mortality and 0.014 (95% CI, 0.0 to 0.028) for CVD.
rs13038305 only explains a small proportion of cystatin C variation.
Statistical adjustment can correct a genetic bias in GFR estimates based on cystatin C in carriers of the T allele of rs13038305 and result in changes in disease classification. However, on a population level, the effects on overall reclassification of CKD status are modest.
PMCID: PMC3872167  PMID: 23932088
Cystatin C; chronic kidney disease; genetics; single nucleotide polymorphism; net reclassification improvement
10.  Association of Levels of Fasting Glucose and Insulin with Rare Variants at the Chromosome 11p11.2-MADD Locus: the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Targeted Sequencing Study 
Common variation at the 11p11.2 locus, encompassing MADD, ACP2, NR1H3, MYBPC3 and SPI1, has been associated in genome-wide association studies with fasting glucose (FG) and insulin (FI). In the Cohorts for Heart and Aging Research in Genomic Epidemiology Targeted Sequencing Study, we sequenced five gene regions at 11p11.2 to identify rare, potentially functional variants influencing FG or FI levels.
Method & Results
Sequencing (mean depth 38×) across 16.1kb in 3,566 non-diabetic individuals identified 653 variants, 79.9% of which were rare (MAF <1%) and novel. We analyzed rare variants in five gene regions with FI or FG using the Sequence Kernel Association Test (SKAT). At NR1H3, 53 rare variants were jointly associated with FI (p=2.73 × 10−3); of these, seven were predicted to have regulatory function and showed association with FI (p=1.28 × 10−3). Conditioning on two previously associated variants at MADD (rs7944584, rs10838687) did not attenuate this association, suggesting that there are more than two independent signals at 11p11.2. One predicted regulatory variant, chr11:47227430 (hg18; MAF 0.00068), contributed 20.6% to the overall SKAT score at NR1H3, lies in intron 2 of NR1H3 and is a predicted binding site for FOXA1, a transcription factor associated with insulin regulation. In human HepG2 hepatoma cells, the rare chr11:47227430 A allele disrupted FOXA1 binding and reduced FOXA1-dependent transcriptional activity.
Sequencing at 11p11.2- NR1H3 identified rare variation associated with FI. One variant, chr11:47227430, appears to be functional, with the rare A allele reducing transcription factor FOXA1 binding and FOXA1-dependent transcriptional activity.
PMCID: PMC4066205  PMID: 24951664
fasting glucose; fasting insulin; chr11p11.2; target sequencing; next-generation sequencing
11.  Meta-Analysis of Genome-Wide Association Studies in African Americans Provides Insights into the Genetic Architecture of Type 2 Diabetes 
Ng, Maggie C. Y. | Shriner, Daniel | Chen, Brian H. | Li, Jiang | Chen, Wei-Min | Guo, Xiuqing | Liu, Jiankang | Bielinski, Suzette J. | Yanek, Lisa R. | Nalls, Michael A. | Comeau, Mary E. | Rasmussen-Torvik, Laura J. | Jensen, Richard A. | Evans, Daniel S. | Sun, Yan V. | An, Ping | Patel, Sanjay R. | Lu, Yingchang | Long, Jirong | Armstrong, Loren L. | Wagenknecht, Lynne | Yang, Lingyao | Snively, Beverly M. | Palmer, Nicholette D. | Mudgal, Poorva | Langefeld, Carl D. | Keene, Keith L. | Freedman, Barry I. | Mychaleckyj, Josyf C. | Nayak, Uma | Raffel, Leslie J. | Goodarzi, Mark O. | Chen, Y-D Ida | Taylor, Herman A. | Correa, Adolfo | Sims, Mario | Couper, David | Pankow, James S. | Boerwinkle, Eric | Adeyemo, Adebowale | Doumatey, Ayo | Chen, Guanjie | Mathias, Rasika A. | Vaidya, Dhananjay | Singleton, Andrew B. | Zonderman, Alan B. | Igo, Robert P. | Sedor, John R. | Kabagambe, Edmond K. | Siscovick, David S. | McKnight, Barbara | Rice, Kenneth | Liu, Yongmei | Hsueh, Wen-Chi | Zhao, Wei | Bielak, Lawrence F. | Kraja, Aldi | Province, Michael A. | Bottinger, Erwin P. | Gottesman, Omri | Cai, Qiuyin | Zheng, Wei | Blot, William J. | Lowe, William L. | Pacheco, Jennifer A. | Crawford, Dana C. | Grundberg, Elin | Rich, Stephen S. | Hayes, M. Geoffrey | Shu, Xiao-Ou | Loos, Ruth J. F. | Borecki, Ingrid B. | Peyser, Patricia A. | Cummings, Steven R. | Psaty, Bruce M. | Fornage, Myriam | Iyengar, Sudha K. | Evans, Michele K. | Becker, Diane M. | Kao, W. H. Linda | Wilson, James G. | Rotter, Jerome I. | Sale, Michèle M. | Liu, Simin | Rotimi, Charles N. | Bowden, Donald W.
PLoS Genetics  2014;10(8):e1004517.
Type 2 diabetes (T2D) is more prevalent in African Americans than in Europeans. However, little is known about the genetic risk in African Americans despite the recent identification of more than 70 T2D loci primarily by genome-wide association studies (GWAS) in individuals of European ancestry. In order to investigate the genetic architecture of T2D in African Americans, the MEta-analysis of type 2 DIabetes in African Americans (MEDIA) Consortium examined 17 GWAS on T2D comprising 8,284 cases and 15,543 controls in African Americans in stage 1 analysis. Single nucleotide polymorphisms (SNPs) association analysis was conducted in each study under the additive model after adjustment for age, sex, study site, and principal components. Meta-analysis of approximately 2.6 million genotyped and imputed SNPs in all studies was conducted using an inverse variance-weighted fixed effect model. Replications were performed to follow up 21 loci in up to 6,061 cases and 5,483 controls in African Americans, and 8,130 cases and 38,987 controls of European ancestry. We identified three known loci (TCF7L2, HMGA2 and KCNQ1) and two novel loci (HLA-B and INS-IGF2) at genome-wide significance (4.15×10−94
Author Summary
Despite the higher prevalence of type 2 diabetes (T2D) in African Americans than in Europeans, recent genome-wide association studies (GWAS) were examined primarily in individuals of European ancestry. In this study, we performed meta-analysis of 17 GWAS in 8,284 cases and 15,543 controls to explore the genetic architecture of T2D in African Americans. Following replication in additional 6,061 cases and 5,483 controls in African Americans, and 8,130 cases and 38,987 controls of European ancestry, we identified two novel and three previous reported T2D loci reaching genome-wide significance. We also examined 158 loci previously reported to be associated with T2D or regulating glucose homeostasis. While 56% of these loci were shared between African Americans and the other populations, the strongest associations in African Americans are often found in nearby single nucleotide polymorphisms (SNPs) instead of the original SNPs reported in other populations due to differential genetic architecture across populations. Our results highlight the importance of performing genetic studies in non-European populations to fine map the causal genetic variants.
PMCID: PMC4125087  PMID: 25102180
The New England journal of medicine  2013;369(23):2183-2196.
Among patients in the United States with chronic kidney disease, black patients are at increased risk for end-stage renal disease, as compared with white patients.
In two studies, we examined the effects of variants in the gene encoding apolipoprotein L1 (APOL1) on the progression of chronic kidney disease. In the African American Study of Kidney Disease and Hypertension (AASK), we evaluated 693 black patients with chronic kidney disease attributed to hypertension. In the Chronic Renal Insufficiency Cohort (CRIC) study, we evaluated 2955 white patients and black patients with chronic kidney disease (46% of whom had diabetes) according to whether they had 2 copies of high-risk APOL1 variants (APOL1 high-risk group) or 0 or 1 copy (APOL1 low-risk group). In the AASK study, the primary outcome was a composite of end-stage renal disease or a doubling of the serum creatinine level. In the CRIC study, the primary outcomes were the slope in the estimated glomerular filtration rate (eGFR) and the composite of end-stage renal disease or a reduction of 50% in the eGFR from baseline.
In the AASK study, the primary outcome occurred in 58.1% of the patients in the APOL1 high-risk group and in 36.6% of those in the APOL1 low-risk group (hazard ratio in the high-risk group, 1.88; P<0.001). There was no interaction between APOL1 status and trial interventions or the presence of baseline proteinuria. In the CRIC study, black patients in the APOL1 high-risk group had a more rapid decline in the eGFR and a higher risk of the composite renal outcome than did white patients, among those with diabetes and those without diabetes (P<0.001 for all comparisons).
Renal risk variants in APOL1 were associated with the higher rates of end-stage renal disease and progression of chronic kidney disease that were observed in black patients as compared with white patients, regardless of diabetes status. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases and others.)
PMCID: PMC3969022  PMID: 24206458
Chronic kidney disease is associated with cardiovascular disease. We tested for evidence of a shared genetic basis to these traits.
Study Design
We conducted two targeted analyses. First, we examined whether known single nucleotide polymorphisms (SNPs) underpinning kidney traits were associated with a series of vascular phenotypes. Additionally, we tested whether vascular SNPs were associated with markers of kidney damage. Significance was set to 1.5 × 10-4 (0.05/325 tests).
Setting & Participants
Vascular outcomes were analyzed in participants from the AortaGen (20,634), CARDIoGRAM (86,995), CHARGE Eye (15,358), CHARGE IMT (31,181), ICBP (69,395) and NeuroCHARGE (12,385) consortia. Tests for kidney outcomes were conducted in up to 67,093 participants from the CKDGen consortium.
We used 19 kidney SNPs and 64 vascular SNPs.
Outcomes & Measurements
Vascular outcomes tested were blood pressure, coronary artery disease, carotid intima-media thickness, pulse wave velocity, retinal venular caliber and brain white matter lesions. Kidney outcomes were estimated glomerular filtration rate and albuminuria.
In general, we found that kidney disease variants were not associated with vascular phenotypes (127 of 133 tests were non-significant). The one exception was rs653178 near SH2B3 (SH2B adaptor protein 3), which showed direction-consistent association with systolic (p=9.3E-10) and diastolic (p=1.6E-14) blood pressure and coronary artery disease (p=2.2E-6), all previously reported. Similarly, the 64 SNPs associated with vascular phenotypes were not associated with kidney phenotypes (187 of 192 tests were non-significant), with the exception of 2 high-correlated SNPs at the SH2B3 locus (p=1.06E-07 and p=7.05E-08).
Combined effect size of the SNPs for kidney and vascular outcomes may be too low to detect shared genetic associations.
Overall, although we confirmed one locus (SH2B3) as associated with both kidney and cardiovascular disease, our primary findings suggest that there is little overlap between kidney and cardiovascular disease risk variants in the overall population. The reciprocal risks of kidney and cardiovascular disease may not be genetically mediated, but rather a function of the disease milieu itself.
PMCID: PMC3660426  PMID: 23474010
Nephrology Dialysis Transplantation  2013;28(6):1497-1504.
Beta-trace protein (BTP), measured in serum or plasma, has potential as a novel biomarker for kidney function. Little is known about the genes influencing BTP levels.
We conducted a genome-wide association study of log-transformed plasma BTP levels in 6720 European Americans (EAs) and replicated the significant associations in 1734 African Americans (AAs) from the Atherosclerosis Risk in Communities (ARIC) study.
We identified a genome-wide significant locus in EA upstream of Prostaglandin D2 synthase (PTGDS), the gene encoding BTP. Each copy of the A allele at rs57024841 was associated with 5% higher BTP levels (P = 1.2 × 10−23). The association at PTGDS was confirmed in AAs (6% higher BTP for each A allele at rs57024841, P = 1.9 × 10−7). The index single nucleotide polymorphisms (SNPs) in EAs and AAs explained ∼1.1% of the log(BTP) variance within each population and explained over 30% of the difference in log(BTP) levels between EAs and AAs. The index SNPs at the PTGDS locus in the two populations were not associated with the estimated glomerular filtration rate (eGFR) or the urine albumin creatinine ratio (P > 0.05). We further tested for the associations of BTP with 16 known loci of the eGFR in EA, and BTP was associated with 3 of 16 tested.
The identification of a novel BTP-specific (non-renal related) locus and the confirmation of several genetic loci of the eGFR with BTP extend our understanding of the metabolism of BTP and inform its use as a kidney filtration biomarker.
PMCID: PMC3685304  PMID: 23328707
chronic kidney disease; genome-wide association study; glomerular filtration rate; GWAS; kidney function biomarker
Kidney international  2013;84(4):834-840.
Proteinuria is associated with adverse clinical outcomes in HIV infection. Here we evaluated whether APOL1 risk alleles, previously associated with advanced kidney disease, is independently associated with proteinuria in HIV infection in a cross-sectional study of HIV-infected women in the Women’s Interagency HIV Study. We estimated the percent difference in urine protein excretion and odds of proteinuria (200 mg/g and higher) associated with two versus one or no APOL1 risk allele using linear and logistic regression, respectively. Of 1285 women successfully genotyped, 379 carried one and 80 carried two risk alleles. Proteinuria was present in 124 women; 78 of whom had proteinuria confirmed on a second sample. In women without prior AIDS, two risk alleles were independently associated with a 69% higher urine protein excretion (95% CI: 36%, 108%) and 5-fold higher odds of proteinuria (95% CI: 2.45, 10.37) versus one or no risk allele. No association was found in women with prior AIDS. Analyses in which women with impaired kidney function were excluded and proteinuria was confirmed by a second urine sample yielded similar estimates. Thus, APOL1 risk alleles are associated with significant proteinuria in HIV-infected persons without prior clinical AIDS, independent of clinical factors traditionally associated with proteinuria. Trials are needed to determine whether APOL1 genotyping identifies individuals who could benefit from earlier intervention to prevent overt renal disease.
PMCID: PMC3788838  PMID: 23715117
Carcinogenesis  2012;34(1):86-92.
The hypothesis that germ-line polymorphisms in DNA repair genes influence cancer risk has previously been tested primarily on a cancer site-specific basis. The purpose of this study was to test the hypothesis that DNA repair gene allelic variants contribute to globally elevated cancer risk by measuring associations with risk of all cancers that occurred within a population-based cohort. In the CLUE II cohort study established in 1989 in Washington County, MD, this study was comprised of all 3619 cancer cases ascertained through 2007 compared with a sample of 2296 with no cancer. Associations were measured between 759 DNA repair gene single nucleotide polymorphisms (SNPs) and risk of all cancers. A SNP in O6-methylguanine-DNA methyltransferase, MGMT, (rs2296675) was significantly associated with overall cancer risk [per minor allele odds ratio (OR) 1.30, 95% confidence interval (CI) 1.19–1.43 and P-value: 4.1 × 10−8]. The association between rs2296675 and cancer risk was stronger among those aged ≤54 years old than those who were ≥55 years at baseline (P-for-interaction = 0.021). OR were in the direction of increased risk for all 15 categories of malignancies studied (P < 0.0001), ranging from 1.22 (P = 0.42) for ovarian cancer to 2.01 (P = 0.008) for urinary tract cancers; the smallest P-value was for breast cancer (OR 1.45, P = 0.0002). The results indicate that the minor allele of MGMT SNP rs2296675, a common genetic marker with 37% carriers, was significantly associated with increased risk of cancer across multiple tissues. Replication is needed to more definitively determine the scientific and public health significance of this observed association.
PMCID: PMC3534189  PMID: 23027618
PLoS ONE  2013;8(12):e81888.
Estimated glomerular filtration rate (eGFR), a measure of kidney function, is heritable, suggesting that genes influence renal function. Genes that influence eGFR have been identified through genome-wide association studies. However, family-based linkage approaches may identify loci that explain a larger proportion of the heritability. This study used genome-wide linkage and association scans to identify quantitative trait loci (QTL) that influence eGFR.
Genome-wide linkage and sparse association scans of eGFR were performed in families ascertained by probands with advanced diabetic nephropathy (DN) from the multi-ethnic Family Investigation of Nephropathy and Diabetes (FIND) study. This study included 954 African Americans (AA), 781 American Indians (AI), 614 European Americans (EA) and 1,611 Mexican Americans (MA). A total of 3,960 FIND participants were genotyped for 6,000 single nucleotide polymorphisms (SNPs) using the Illumina Linkage IVb panel. GFR was estimated by the Modification of Diet in Renal Disease (MDRD) formula.
The non-parametric linkage analysis, accounting for the effects of diabetes duration and BMI, identified the strongest evidence for linkage of eGFR on chromosome 20q11 (log of the odds [LOD] = 3.34; P = 4.4×10−5) in MA and chromosome 15q12 (LOD = 2.84; P = 1.5×10−4) in EA. In all subjects, the strongest linkage signal for eGFR was detected on chromosome 10p12 (P = 5.5×10−4) at 44 cM near marker rs1339048. A subsequent association scan in both ancestry-specific groups and the entire population identified several SNPs significantly associated with eGFR across the genome.
The present study describes the localization of QTL influencing eGFR on 20q11 in MA, 15q21 in EA and 10p12 in the combined ethnic groups participating in the FIND study. Identification of causal genes/variants influencing eGFR, within these linkage and association loci, will open new avenues for functional analyses and development of novel diagnostic markers for DN.
PMCID: PMC3866106  PMID: 24358131
Chasman, Daniel I. | Fuchsberger, Christian | Pattaro, Cristian | Teumer, Alexander | Böger, Carsten A. | Endlich, Karlhans | Olden, Matthias | Chen, Ming-Huei | Tin, Adrienne | Taliun, Daniel | Li, Man | Gao, Xiaoyi | Gorski, Mathias | Yang, Qiong | Hundertmark, Claudia | Foster, Meredith C. | O'Seaghdha, Conall M. | Glazer, Nicole | Isaacs, Aaron | Liu, Ching-Ti | Smith, Albert V. | O'Connell, Jeffrey R. | Struchalin, Maksim | Tanaka, Toshiko | Li, Guo | Johnson, Andrew D. | Gierman, Hinco J. | Feitosa, Mary F. | Hwang, Shih-Jen | Atkinson, Elizabeth J. | Lohman, Kurt | Cornelis, Marilyn C. | Johansson, Åsa | Tönjes, Anke | Dehghan, Abbas | Lambert, Jean-Charles | Holliday, Elizabeth G. | Sorice, Rossella | Kutalik, Zoltan | Lehtimäki, Terho | Esko, Tõnu | Deshmukh, Harshal | Ulivi, Sheila | Chu, Audrey Y. | Murgia, Federico | Trompet, Stella | Imboden, Medea | Coassin, Stefan | Pistis, Giorgio | Harris, Tamara B. | Launer, Lenore J. | Aspelund, Thor | Eiriksdottir, Gudny | Mitchell, Braxton D. | Boerwinkle, Eric | Schmidt, Helena | Cavalieri, Margherita | Rao, Madhumathi | Hu, Frank | Demirkan, Ayse | Oostra, Ben A. | de Andrade, Mariza | Turner, Stephen T. | Ding, Jingzhong | Andrews, Jeanette S. | Freedman, Barry I. | Giulianini, Franco | Koenig, Wolfgang | Illig, Thomas | Meisinger, Christa | Gieger, Christian | Zgaga, Lina | Zemunik, Tatijana | Boban, Mladen | Minelli, Cosetta | Wheeler, Heather E. | Igl, Wilmar | Zaboli, Ghazal | Wild, Sarah H. | Wright, Alan F. | Campbell, Harry | Ellinghaus, David | Nöthlings, Ute | Jacobs, Gunnar | Biffar, Reiner | Ernst, Florian | Homuth, Georg | Kroemer, Heyo K. | Nauck, Matthias | Stracke, Sylvia | Völker, Uwe | Völzke, Henry | Kovacs, Peter | Stumvoll, Michael | Mägi, Reedik | Hofman, Albert | Uitterlinden, Andre G. | Rivadeneira, Fernando | Aulchenko, Yurii S. | Polasek, Ozren | Hastie, Nick | Vitart, Veronique | Helmer, Catherine | Wang, Jie Jin | Stengel, Bénédicte | Ruggiero, Daniela | Bergmann, Sven | Kähönen, Mika | Viikari, Jorma | Nikopensius, Tiit | Province, Michael | Ketkar, Shamika | Colhoun, Helen | Doney, Alex | Robino, Antonietta | Krämer, Bernhard K. | Portas, Laura | Ford, Ian | Buckley, Brendan M. | Adam, Martin | Thun, Gian-Andri | Paulweber, Bernhard | Haun, Margot | Sala, Cinzia | Mitchell, Paul | Ciullo, Marina | Kim, Stuart K. | Vollenweider, Peter | Raitakari, Olli | Metspalu, Andres | Palmer, Colin | Gasparini, Paolo | Pirastu, Mario | Jukema, J. Wouter | Probst-Hensch, Nicole M. | Kronenberg, Florian | Toniolo, Daniela | Gudnason, Vilmundur | Shuldiner, Alan R. | Coresh, Josef | Schmidt, Reinhold | Ferrucci, Luigi | Siscovick, David S. | van Duijn, Cornelia M. | Borecki, Ingrid B. | Kardia, Sharon L.R. | Liu, Yongmei | Curhan, Gary C. | Rudan, Igor | Gyllensten, Ulf | Wilson, James F. | Franke, Andre | Pramstaller, Peter P. | Rettig, Rainer | Prokopenko, Inga | Witteman, Jacqueline | Hayward, Caroline | Ridker, Paul M | Parsa, Afshin | Bochud, Murielle | Heid, Iris M. | Kao, W.H. Linda | Fox, Caroline S. | Köttgen, Anna
Human Molecular Genetics  2012;21(24):5329-5343.
In conducting genome-wide association studies (GWAS), analytical approaches leveraging biological information may further understanding of the pathophysiology of clinical traits. To discover novel associations with estimated glomerular filtration rate (eGFR), a measure of kidney function, we developed a strategy for integrating prior biological knowledge into the existing GWAS data for eGFR from the CKDGen Consortium. Our strategy focuses on single nucleotide polymorphism (SNPs) in genes that are connected by functional evidence, determined by literature mining and gene ontology (GO) hierarchies, to genes near previously validated eGFR associations. It then requires association thresholds consistent with multiple testing, and finally evaluates novel candidates by independent replication. Among the samples of European ancestry, we identified a genome-wide significant SNP in FBXL20 (P = 5.6 × 10−9) in meta-analysis of all available data, and additional SNPs at the INHBC, LRP2, PLEKHA1, SLC3A2 and SLC7A6 genes meeting multiple-testing corrected significance for replication and overall P-values of 4.5 × 10−4–2.2 × 10−7. Neither the novel PLEKHA1 nor FBXL20 associations, both further supported by association with eGFR among African Americans and with transcript abundance, would have been implicated by eGFR candidate gene approaches. LRP2, encoding the megalin receptor, was identified through connection with the previously known eGFR gene DAB2 and extends understanding of the megalin system in kidney function. These findings highlight integration of existing genome-wide association data with independent biological knowledge to uncover novel candidate eGFR associations, including candidates lacking known connections to kidney-specific pathways. The strategy may also be applicable to other clinical phenotypes, although more testing will be needed to assess its potential for discovery in general.
PMCID: PMC3607468  PMID: 22962313
The SNP rs11628722 in the SERPINA9 gene was previously associated with incident ischemic stroke in the Atherosclerosis Risk in Communities (ARIC) study. Centerin, the protein encoded by SERPINA9, is involved in maturation and maintenance of naïve B cells, which play a role in atherogenesis. We investigated whether 21 tag SNPs in the SERPINA9 gene are associated with features of carotid artery atherosclerotic plaque measured by magnetic resonance imaging (MRI). Carotid MRI data were obtained from 1,282 European Americans and 341 African Americans of the ARIC Carotid MRI study, which recruited participants from ARIC by a stratified sampling plan that over-sampled participants with carotid intima-media thickening. Five MRI measures, focused on carotid wall volume, wall thickness, and lipid core, were analyzed. Genetic associations between the MRI measurements and each of the 21 SNPs were analyzed in linear regression models with adjustment for sample weights and traditional risk factors. Rs11628722 was tested a priori. In African Americans, rs11628722 was significantly associated with carotid wall volume (p < 0.05). Among the other 20 SNPs, adjusted for multiple testing, rs4905204, which encodes an Ala to Val amino acid change, was significantly associated with maximum wall thickness (p < 0.000625) and suggestively associated with total wall volume (p < 0.0026) in European Americans. In conclusion, SNPs in the SERPINA9 gene showed race-specific associations with characteristics of carotid atherosclerotic plaques. Replications in other populations are needed to validate findings of this study and to establish the SERPINA9 gene as a candidate in the etiology of carotid atherosclerosis.
PMCID: PMC3852645  PMID: 24319541
SERPINA9 gene; carotid atherosclerosis; MRI; genetic association
Cancer epidemiology  2012;36(5):e288-e293.
A personal history of basal cell carcinoma (BCC) is associated with increased risk of other malignancies, but the reason is unknown. The hedgehog pathway is critical to the etiology of BCC, and is also believed to contribute to susceptibility to other cancers. This study tested the hypothesis that hedgehog pathway and pathway-related gene variants contribute to the increased risk of subsequent cancers among those with a history of BCC.
The study was nested within the ongoing CLUE II cohort study, established in 1989 in Washington County, Maryland, USA. The study consisted of a cancer-free control group (n=2,296) compared to three different groups of cancer cases ascertained through 2007, those diagnosed with: 1) Other (non-BCC) cancer only (n=2,349); 2) BCC only (n=534); and 3) BCC plus other cancer (n=446). The frequencies of variant alleles were compared among these four groups for 20 single nucleotide polymorphisms (SNPs) in 6 hedgehog pathway genes (SHH, IHH, PTCH2, SMO, GLI1, SUFU), and also 22 SNPs in VDR and 8 SNPs in FAS, which have cross-talk with the hedgehog pathway.
Comparing those with both BCC and other cancer versus those with no cancer, no significant associations were observed for any of the hedgehog pathway SNPs, or for the FAS SNPs. One VDR SNP was nominally significantly associated with the BCC cancer-prone phenotype, rs11574085 [per minor allele odds ratio (OR) 1.38, 95% confidence interval (CI) 1.05–1.82; p-value=0.02].
The hedgehog pathway gene SNPs studied, along with the VDR and FAS SNPs studied, are not strongly associated with the BCC cancer-prone phenotype.
PMCID: PMC3438291  PMID: 22677152
skin cancer; genetics; polymorphisms; hedgehog; vitamin D receptor; fas
O'Seaghdha, Conall M. | Wu, Hongsheng | Yang, Qiong | Kapur, Karen | Guessous, Idris | Zuber, Annie Mercier | Köttgen, Anna | Stoudmann, Candice | Teumer, Alexander | Kutalik, Zoltán | Mangino, Massimo | Dehghan, Abbas | Zhang, Weihua | Eiriksdottir, Gudny | Li, Guo | Tanaka, Toshiko | Portas, Laura | Lopez, Lorna M. | Hayward, Caroline | Lohman, Kurt | Matsuda, Koichi | Padmanabhan, Sandosh | Firsov, Dmitri | Sorice, Rossella | Ulivi, Sheila | Brockhaus, A. Catharina | Kleber, Marcus E. | Mahajan, Anubha | Ernst, Florian D. | Gudnason, Vilmundur | Launer, Lenore J. | Mace, Aurelien | Boerwinckle, Eric | Arking, Dan E. | Tanikawa, Chizu | Nakamura, Yusuke | Brown, Morris J. | Gaspoz, Jean-Michel | Theler, Jean-Marc | Siscovick, David S. | Psaty, Bruce M. | Bergmann, Sven | Vollenweider, Peter | Vitart, Veronique | Wright, Alan F. | Zemunik, Tatijana | Boban, Mladen | Kolcic, Ivana | Navarro, Pau | Brown, Edward M. | Estrada, Karol | Ding, Jingzhong | Harris, Tamara B. | Bandinelli, Stefania | Hernandez, Dena | Singleton, Andrew B. | Girotto, Giorgia | Ruggiero, Daniela | d'Adamo, Adamo Pio | Robino, Antonietta | Meitinger, Thomas | Meisinger, Christa | Davies, Gail | Starr, John M. | Chambers, John C. | Boehm, Bernhard O. | Winkelmann, Bernhard R. | Huang, Jie | Murgia, Federico | Wild, Sarah H. | Campbell, Harry | Morris, Andrew P. | Franco, Oscar H. | Hofman, Albert | Uitterlinden, Andre G. | Rivadeneira, Fernando | Völker, Uwe | Hannemann, Anke | Biffar, Reiner | Hoffmann, Wolfgang | Shin, So–Youn | Lescuyer, Pierre | Henry, Hughes | Schurmann, Claudia | Munroe, Patricia B. | Gasparini, Paolo | Pirastu, Nicola | Ciullo, Marina | Gieger, Christian | März, Winfried | Lind, Lars | Spector, Tim D. | Smith, Albert V. | Rudan, Igor | Wilson, James F. | Polasek, Ozren | Deary, Ian J. | Pirastu, Mario | Ferrucci, Luigi | Liu, Yongmei | Kestenbaum, Bryan | Kooner, Jaspal S. | Witteman, Jacqueline C. M. | Nauck, Matthias | Kao, W. H. Linda | Wallaschofski, Henri | Bonny, Olivier | Fox, Caroline S. | Bochud, Murielle
PLoS Genetics  2013;9(9):e1003796.
Calcium is vital to the normal functioning of multiple organ systems and its serum concentration is tightly regulated. Apart from CASR, the genes associated with serum calcium are largely unknown. We conducted a genome-wide association meta-analysis of 39,400 individuals from 17 population-based cohorts and investigated the 14 most strongly associated loci in ≤21,679 additional individuals. Seven loci (six new regions) in association with serum calcium were identified and replicated. Rs1570669 near CYP24A1 (P = 9.1E-12), rs10491003 upstream of GATA3 (P = 4.8E-09) and rs7481584 in CARS (P = 1.2E-10) implicate regions involved in Mendelian calcemic disorders: Rs1550532 in DGKD (P = 8.2E-11), also associated with bone density, and rs7336933 near DGKH/KIAA0564 (P = 9.1E-10) are near genes that encode distinct isoforms of diacylglycerol kinase. Rs780094 is in GCKR. We characterized the expression of these genes in gut, kidney, and bone, and demonstrate modulation of gene expression in bone in response to dietary calcium in mice. Our results shed new light on the genetics of calcium homeostasis.
Author Summary
Calcium is vital to many biological processes and its serum concentration is tightly regulated. Family studies have shown that serum calcium is under strong genetic control. Apart from CASR, the genes associated with serum calcium are largely unknown. We conducted a genome-wide association meta-analysis of 39,400 individuals from 17 population-based cohorts and investigated the 14 most strongly associated loci in ≤21,679 additional individuals. We identified seven loci (six new regions) as being robustly associated with serum calcium. Three loci implicate regions involved in rare monogenic diseases including disturbances of serum calcium levels. Several of the newly identified loci harbor genes linked to the hormonal control of serum calcium. In mice experiments, we characterized the expression of these genes in gut, kidney, and bone, and explored the influence of dietary calcium intake on the expression of these genes in these organs. Our results shed new light on the genetics of calcium homeostasis and suggest a role for dietary calcium intake in bone-specific gene expression.
PMCID: PMC3778004  PMID: 24068962
Carcinogenesis  2012;33(9):1692-1698.
For unknown reasons, non-melanoma skin cancer (NMSC) is associated with increased risk of other malignancies. Focusing solely on DNA repair or DNA repair-related genes, this study tested the hypothesis that DNA repair gene variants contribute to the increased cancer risk associated with a personal history of NMSC. From the parent CLUE II cohort study, established in 1989 in Washington County, MD, the study consisted of a cancer-free control group (n 5 2296) compared with three mutually exclusive groups of cancer cases ascertained through 2007: (i) Other (non-NMSC) cancer only (n 5 2349); (ii) NMSC only (n 5 694) and (iii) NMSC plus other cancer (n 5 577). The frequency of minor alleles in 759 DNA repair gene single nucleotide polymorphisms (SNPs) was compared in these four groups. Comparing those with both NMSC and other cancer versus those with no cancer, 10 SNPs had allelic trend P-values <0.01. The two top-ranked SNPs were both within the thymine DNA glycosylase gene (TDG). One was a non-synonymous coding SNP (rs2888805) [per allele odds ratio (OR) 1.40, 95% confidence interval (CI) 1.16–1.70; P-value 5 0.0006] and the other was an intronic SNP in high linkage disequilibrium with rs2888805 (rs4135150). None of the associations had a P-value <6.6310−5, the threshold for statistical significance after correcting for multiple comparisons. The results pinpoint DNA repair genes most likely to contribute to the NMSC cancer-prone phenotype. A promising lead is genetic variants in TDG, important not only in base excision repair but also in regulating the epigenome and gene expression, which may contribute to the NMSC-associated increase in overall cancer risk.
PMCID: PMC3514896  PMID: 22581838
Köttgen, Anna | Albrecht, Eva | Teumer, Alexander | Vitart, Veronique | Krumsiek, Jan | Hundertmark, Claudia | Pistis, Giorgio | Ruggiero, Daniela | O’Seaghdha, Conall M | Haller, Toomas | Yang, Qiong | Tanaka, Toshiko | Johnson, Andrew D | Kutalik, Zoltán | Smith, Albert V | Shi, Julia | Struchalin, Maksim | Middelberg, Rita P S | Brown, Morris J | Gaffo, Angelo L | Pirastu, Nicola | Li, Guo | Hayward, Caroline | Zemunik, Tatijana | Huffman, Jennifer | Yengo, Loic | Zhao, Jing Hua | Demirkan, Ayse | Feitosa, Mary F | Liu, Xuan | Malerba, Giovanni | Lopez, Lorna M | van der Harst, Pim | Li, Xinzhong | Kleber, Marcus E | Hicks, Andrew A | Nolte, Ilja M | Johansson, Asa | Murgia, Federico | Wild, Sarah H | Bakker, Stephan J L | Peden, John F | Dehghan, Abbas | Steri, Maristella | Tenesa, Albert | Lagou, Vasiliki | Salo, Perttu | Mangino, Massimo | Rose, Lynda M | Lehtimäki, Terho | Woodward, Owen M | Okada, Yukinori | Tin, Adrienne | Müller, Christian | Oldmeadow, Christopher | Putku, Margus | Czamara, Darina | Kraft, Peter | Frogheri, Laura | Thun, Gian Andri | Grotevendt, Anne | Gislason, Gauti Kjartan | Harris, Tamara B | Launer, Lenore J | McArdle, Patrick | Shuldiner, Alan R | Boerwinkle, Eric | Coresh, Josef | Schmidt, Helena | Schallert, Michael | Martin, Nicholas G | Montgomery, Grant W | Kubo, Michiaki | Nakamura, Yusuke | Tanaka, Toshihiro | Munroe, Patricia B | Samani, Nilesh J | Jacobs, David R | Liu, Kiang | D’Adamo, Pio | Ulivi, Sheila | Rotter, Jerome I | Psaty, Bruce M | Vollenweider, Peter | Waeber, Gerard | Campbell, Susan | Devuyst, Olivier | Navarro, Pau | Kolcic, Ivana | Hastie, Nicholas | Balkau, Beverley | Froguel, Philippe | Esko, Tõnu | Salumets, Andres | Khaw, Kay Tee | Langenberg, Claudia | Wareham, Nicholas J | Isaacs, Aaron | Kraja, Aldi | Zhang, Qunyuan | Wild, Philipp S | Scott, Rodney J | Holliday, Elizabeth G | Org, Elin | Viigimaa, Margus | Bandinelli, Stefania | Metter, Jeffrey E | Lupo, Antonio | Trabetti, Elisabetta | Sorice, Rossella | Döring, Angela | Lattka, Eva | Strauch, Konstantin | Theis, Fabian | Waldenberger, Melanie | Wichmann, H-Erich | Davies, Gail | Gow, Alan J | Bruinenberg, Marcel | Study, LifeLines Cohort | Stolk, Ronald P | Kooner, Jaspal S | Zhang, Weihua | Winkelmann, Bernhard R | Boehm, Bernhard O | Lucae, Susanne | Penninx, Brenda W | Smit, Johannes H | Curhan, Gary | Mudgal, Poorva | Plenge, Robert M | Portas, Laura | Persico, Ivana | Kirin, Mirna | Wilson, James F | Leach, Irene Mateo | van Gilst, Wiek H | Goel, Anuj | Ongen, Halit | Hofman, Albert | Rivadeneira, Fernando | Uitterlinden, Andre G | Imboden, Medea | von Eckardstein, Arnold | Cucca, Francesco | Nagaraja, Ramaiah | Piras, Maria Grazia | Nauck, Matthias | Schurmann, Claudia | Budde, Kathrin | Ernst, Florian | Farrington, Susan M | Theodoratou, Evropi | Prokopenko, Inga | Stumvoll, Michael | Jula, Antti | Perola, Markus | Salomaa, Veikko | Shin, So-Youn | Spector, Tim D | Sala, Cinzia | Ridker, Paul M | Kähönen, Mika | Viikari, Jorma | Hengstenberg, Christian | Nelson, Christopher P | Consortium, CARDIoGRAM | Consortium, DIAGRAM | Consortium, ICBP | Consortium, MAGIC | Meschia, James F | Nalls, Michael A | Sharma, Pankaj | Singleton, Andrew B | Kamatani, Naoyuki | Zeller, Tanja | Burnier, Michel | Attia, John | Laan, Maris | Klopp, Norman | Hillege, Hans L | Kloiber, Stefan | Choi, Hyon | Pirastu, Mario | Tore, Silvia | Probst-Hensch, Nicole M | Völzke, Henry | Gudnason, Vilmundur | Parsa, Afshin | Schmidt, Reinhold | Whitfield, John B | Fornage, Myriam | Gasparini, Paolo | Siscovick, David S | Polašek, Ozren | Campbell, Harry | Rudan, Igor | Bouatia-Naji, Nabila | Metspalu, Andres | Loos, Ruth J F | van Duijn, Cornelia M | Borecki, Ingrid B | Ferrucci, Luigi | Gambaro, Giovanni | Deary, Ian J | Wolffenbuttel, Bruce H R | Chambers, John C | März, Winfried | Pramstaller, Peter P | Snieder, Harold | Gyllensten, Ulf | Wright, Alan F | Navis, Gerjan | Watkins, Hugh | Witteman, Jacqueline C M | Sanna, Serena | Schipf, Sabine | Dunlop, Malcolm G | Tönjes, Anke | Ripatti, Samuli | Soranzo, Nicole | Toniolo, Daniela | Chasman, Daniel I | Raitakari, Olli | Kao, W H Linda | Ciullo, Marina | Fox, Caroline S | Caulfield, Mark | Bochud, Murielle | Gieger, Christian
Nature genetics  2012;45(2):145-154.
Elevated serum urate concentrations can cause gout, a prevalent and painful inflammatory arthritis. By combining data from >140,000 individuals of European ancestry within the Global Urate Genetics Consortium (GUGC), we identified and replicated 28 genome-wide significant loci in association with serum urate concentrations (18 new regions in or near TRIM46, INHBB, SFMBT1, TMEM171, VEGFA, BAZ1B, PRKAG2, STC1, HNF4G, A1CF, ATXN2, UBE2Q2, IGF1R, NFAT5, MAF, HLF, ACVR1B-ACVRL1 and B3GNT4). Associations for many of the loci were of similar magnitude in individuals of non-European ancestry. We further characterized these loci for associations with gout, transcript expression and the fractional excretion of urate. Network analyses implicate the inhibins-activins signaling pathways and glucose metabolism in systemic urate control. New candidate genes for serum urate concentration highlight the importance of metabolic control of urate production and excretion, which may have implications for the treatment and prevention of gout.
PMCID: PMC3663712  PMID: 23263486
Kidney international  2012;83(1):114-120.
Despite intensive anti-hypertensive therapy there was a high incidence of renal end-points in participants of the African American Study of Kidney Disease and Hypertension (AASK) cohort. To better understand this, coding variants in the apolipoprotein L1 (APOL1) and the non-muscle myosin heavy chain 9 (MYH9) genes were evaluated for an association with hypertension-attributed nephropathy and clinical outcomes in a case-control study. Clinical data and DNA were available for 675 AASK participant cases and 618 African American non-nephropathy control individuals. APOL1 G1 and G2, and MYH9 E1 variants along with 44 ancestry informative markers were genotyped with allele frequency differences between cases and controls analyzed by logistic regression multivariable models adjusting for ancestry, age, and gender. In recessive models, APOL1 risk variants were significantly associated with kidney disease in all cases compared to controls with an odds ratio of 2.57. In AASK cases with more advanced disease, such as a baseline urine protein to creatinine ratio over 0.6 g/g or a serum creatinine over 3 mg/dL during follow-up, the association was strengthened with odds ratios of 6.29 and 4.61, respectively. APOL1 risk variants were consistently associated with renal disease progression across medication classes and blood pressure targets. Thus, kidney disease in AASK participants was strongly associated with APOL1 renal risk variants.
PMCID: PMC3484228  PMID: 22832513
Scott, Robert A. | Chu, Audrey Y. | Grarup, Niels | Manning, Alisa K. | Hivert, Marie-France | Shungin, Dmitry | Tönjes, Anke | Yesupriya, Ajay | Barnes, Daniel | Bouatia-Naji, Nabila | Glazer, Nicole L. | Jackson, Anne U. | Kutalik, Zoltán | Lagou, Vasiliki | Marek, Diana | Rasmussen-Torvik, Laura J. | Stringham, Heather M. | Tanaka, Toshiko | Aadahl, Mette | Arking, Dan E. | Bergmann, Sven | Boerwinkle, Eric | Bonnycastle, Lori L. | Bornstein, Stefan R. | Brunner, Eric | Bumpstead, Suzannah J. | Brage, Soren | Carlson, Olga D. | Chen, Han | Chen, Yii-Der Ida | Chines, Peter S. | Collins, Francis S. | Couper, David J. | Dennison, Elaine M. | Dowling, Nicole F. | Egan, Josephine S. | Ekelund, Ulf | Erdos, Michael R. | Forouhi, Nita G. | Fox, Caroline S. | Goodarzi, Mark O. | Grässler, Jürgen | Gustafsson, Stefan | Hallmans, Göran | Hansen, Torben | Hingorani, Aroon | Holloway, John W. | Hu, Frank B. | Isomaa, Bo | Jameson, Karen A. | Johansson, Ingegerd | Jonsson, Anna | Jørgensen, Torben | Kivimaki, Mika | Kovacs, Peter | Kumari, Meena | Kuusisto, Johanna | Laakso, Markku | Lecoeur, Cécile | Lévy-Marchal, Claire | Li, Guo | Loos, Ruth J.F. | Lyssenko, Valeri | Marmot, Michael | Marques-Vidal, Pedro | Morken, Mario A. | Müller, Gabriele | North, Kari E. | Pankow, James S. | Payne, Felicity | Prokopenko, Inga | Psaty, Bruce M. | Renström, Frida | Rice, Ken | Rotter, Jerome I. | Rybin, Denis | Sandholt, Camilla H. | Sayer, Avan A. | Shrader, Peter | Schwarz, Peter E.H. | Siscovick, David S. | Stančáková, Alena | Stumvoll, Michael | Teslovich, Tanya M. | Waeber, Gérard | Williams, Gordon H. | Witte, Daniel R. | Wood, Andrew R. | Xie, Weijia | Boehnke, Michael | Cooper, Cyrus | Ferrucci, Luigi | Froguel, Philippe | Groop, Leif | Kao, W.H. Linda | Vollenweider, Peter | Walker, Mark | Watanabe, Richard M. | Pedersen, Oluf | Meigs, James B. | Ingelsson, Erik | Barroso, Inês | Florez, Jose C. | Franks, Paul W. | Dupuis, Josée | Wareham, Nicholas J. | Langenberg, Claudia
Diabetes  2012;61(5):1291-1296.
Gene–lifestyle interactions have been suggested to contribute to the development of type 2 diabetes. Glucose levels 2 h after a standard 75-g glucose challenge are used to diagnose diabetes and are associated with both genetic and lifestyle factors. However, whether these factors interact to determine 2-h glucose levels is unknown. We meta-analyzed single nucleotide polymorphism (SNP) × BMI and SNP × physical activity (PA) interaction regression models for five SNPs previously associated with 2-h glucose levels from up to 22 studies comprising 54,884 individuals without diabetes. PA levels were dichotomized, with individuals below the first quintile classified as inactive (20%) and the remainder as active (80%). BMI was considered a continuous trait. Inactive individuals had higher 2-h glucose levels than active individuals (β = 0.22 mmol/L [95% CI 0.13–0.31], P = 1.63 × 10−6). All SNPs were associated with 2-h glucose (β = 0.06–0.12 mmol/allele, P ≤ 1.53 × 10−7), but no significant interactions were found with PA (P > 0.18) or BMI (P ≥ 0.04). In this large study of gene–lifestyle interaction, we observed no interactions between genetic and lifestyle factors, both of which were associated with 2-h glucose. It is perhaps unlikely that top loci from genome-wide association studies will exhibit strong subgroup-specific effects, and may not, therefore, make the best candidates for the study of interactions.
PMCID: PMC3331745  PMID: 22415877

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