03141nas a2200685 4500008004100000022001400041245018100055210006900236260001300305300001100318490000700329520115600336653001001492653000901502653002201511653001201533653003001545653001101575653003801586653003401624653001301658653001101671653000901682653001701691653001601708653002201724653000901746653001701755100002701772700002501799700002201824700002101846700002201867700001501889700001901904700002301923700002401946700002301970700002401993700002002017700002502037700001902062700002302081700001502104700002102119700002002140700001802160700002402178700002602202700001902228700002202247700002302269700002302292700001902315700001902334700002202353700002302375700002102398856003602419 2012 eng d a1939-327X00aConsistent directions of effect for established type 2 diabetes risk variants across populations: the population architecture using Genomics and Epidemiology (PAGE) Consortium.0 aConsistent directions of effect for established type 2 diabetes c2012 Jun a1642-70 v613 a
Common genetic risk variants for type 2 diabetes (T2D) have primarily been identified in populations of European and Asian ancestry. We tested whether the direction of association with 20 T2D risk variants generalizes across six major racial/ethnic groups in the U.S. as part of the Population Architecture using Genomics and Epidemiology Consortium (16,235 diabetes case and 46,122 control subjects of European American, African American, Hispanic, East Asian, American Indian, and Native Hawaiian ancestry). The percentage of positive (odds ratio [OR] >1 for putative risk allele) associations ranged from 69% in American Indians to 100% in European Americans. Of the nine variants where we observed significant heterogeneity of effect by racial/ethnic group (P(heterogeneity) < 0.05), eight were positively associated with risk (OR >1) in at least five groups. The marked directional consistency of association observed for most genetic variants across populations implies a shared functional common variant in each region. Fine-mapping of all loci will be required to reveal markers of risk that are important within and across populations.
10aAdult10aAged10aAged, 80 and over10aAlleles10aDiabetes Mellitus, Type 210aFemale10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aGenotype10aHumans10aMale10aMetagenomics10aMiddle Aged10aPopulation Groups10aRisk10aRisk Factors1 aHaiman, Christopher, A1 aFesinmeyer, Megan, D1 aSpencer, Kylee, L1 aBůzková, Petra1 aVoruganti, Saroja1 aWan, Peggy1 aHaessler, Jeff1 aFranceschini, Nora1 aMonroe, Kristine, R1 aHoward, Barbara, V1 aJackson, Rebecca, D1 aFlorez, Jose, C1 aKolonel, Laurence, N1 aBuyske, Steven1 aGoodloe, Robert, J1 aLiu, Simin1 aManson, JoAnn, E1 aMeigs, James, B1 aWaters, Kevin1 aMukamal, Kenneth, J1 aPendergrass, Sarah, A1 aShrader, Peter1 aWilkens, Lynne, R1 aHindorff, Lucia, A1 aAmbite, Jose, Luis1 aNorth, Kari, E1 aPeters, Ulrike1 aCrawford, Dana, C1 aLe Marchand, Loïc1 aPankow, James, S uhttps://chs-nhlbi.org/node/663302941nas a2200517 4500008004100000022001400041245009800055210006900153260001300222300001100235490000700246520147300253653000901726653002101735653001501756653002501771653004001796653002401836653003201860653001701892653003801909653002201947653001101969653001401980653000901994653001602003653001402019653003602033653000902069100002002078700002302098700002102121700001902142700002402161700002002185700002202205700002202227700002802249700001702277700001802294700001902312700001902331700001702350700002002367856003602387 2013 eng d a1533-712X00aGenetic analysis of a population heavy drinking phenotype identifies risk variants in whites.0 aGenetic analysis of a population heavy drinking phenotype identi c2013 Apr a206-100 v333 aGenetic association studies thus far have used detailed diagnoses of alcoholism to identify loci associated with risk. This proof-of-concept analysis examined whether population data of lifetime heaviest alcohol consumption may be used to identify genetic loci that modulate risk. We conducted a genetic association study in European Americans between variants in approximately 2100 genes and alcohol consumption as part of the Candidate gene Association Resource project. We defined cases as individuals with a history of drinking 5 or more drinks per day almost every day of the week and controls as current light drinkers (1-5 drinks per week). We cross-validated identified single nucleotide polymorphisms in a meta-analysis of 2 cohorts of unrelated individuals--Atherosclerosis Risk in Communities (ARIC) and Cardiovascular Health Study (CHS)--and in a separate cohort of related individuals--Framingham Heart Study (FHS). The most significant variant in the meta-analysis of ARIC and CHS was rs6933598 in methylenetetrahydrofolate dehydrogenase (P = 7.46 × 10(-05)) with a P value in FHS of 0.042. The top variants in FHS were rs12249562 in cubulin (P = 3.03 × 10(-05)) and rs9839267 near cholecystokinin (P = 3.05 × 10(-05)) with a P value of 0.019 for rs9839267 in CHS. We have here shown feasibility in evaluating lifetime incidence of heavy alcohol drinking from population-based studies for the purpose of conducting genetic association analyses.
10aAged10aAlcohol Drinking10aAlcoholism10aCase-Control Studies10aEuropean Continental Ancestry Group10aFeasibility Studies10aGenetic Association Studies10aGenetic Loci10aGenetic Predisposition to Disease10aGenetic Variation10aHumans10aIncidence10aMale10aMiddle Aged10aPhenotype10aPolymorphism, Single Nucleotide10aRisk1 aHamidovic, Ajna1 aGoodloe, Robert, J1 aYoung, Taylor, R1 aStyn, Mindi, A1 aMukamal, Kenneth, J1 aChoquet, Helene1 aKasberger, Jay, L1 aBuxbaum, Sarah, G1 aPapanicolaou, George, J1 aWhite, Wendy1 aVolcik, Kelly1 aSpring, Bonnie1 aHitsman, Brian1 aLevy, Daniel1 aJorgenson, Eric uhttps://chs-nhlbi.org/node/162002686nas a2200697 4500008004100000022001400041245012800055210006900183260001300252300001200265490000800277520066900285653002100954653002100975653001900996653001801015653001101033653001901044653003301063653002501096653003401121653001101155653002101166653000901187653003601196653001501232653001201247653001801259653001601277100002201293700001901315700002301334700002301357700002101380700002101401700002801422700002201450700002301472700002101495700001901516700002101535700002401556700001601580700002201596700002201618700002201640700002601662700002301688700002101711700002101732700002301753700002201776700002301798700002701821700001901848700002401867700001901891700002001910700002201930856003601952 2013 eng d a1432-120300aNo evidence of interaction between known lipid-associated genetic variants and smoking in the multi-ethnic PAGE population.0 aNo evidence of interaction between known lipidassociated genetic c2013 Dec a1427-310 v1323 aGenome-wide association studies (GWAS) have identified many variants that influence high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and/or triglycerides. However, environmental modifiers, such as smoking, of these known genotype-phenotype associations are just recently emerging in the literature. We have tested for interactions between smoking and 49 GWAS-identified variants in over 41,000 racially/ethnically diverse samples with lipid levels from the Population Architecture Using Genomics and Epidemiology (PAGE) study. Despite their biological plausibility, we were unable to detect significant SNP × smoking interactions.
10aCholesterol, HDL10aCholesterol, LDL10aCohort Studies10aEthnic Groups10aFemale10aGene Frequency10aGene-Environment Interaction10aGenetics, Population10aGenome-Wide Association Study10aHumans10aLipid Metabolism10aMale10aPolymorphism, Single Nucleotide10aPrevalence10aSmoking10aTriglycerides10aYoung Adult1 aDumitrescu, Logan1 aCarty, Cara, L1 aFranceschini, Nora1 aHindorff, Lucia, A1 aCole, Shelley, A1 aBůzková, Petra1 aSchumacher, Fredrick, R1 aEaton, Charles, B1 aGoodloe, Robert, J1 aDuggan, David, J1 aHaessler, Jeff1 aCochran, Barbara1 aHenderson, Brian, E1 aCheng, Iona1 aJohnson, Karen, C1 aCarlson, Chris, S1 aLove, Shelly-Anne1 aBrown-Gentry, Kristin1 aNato, Alejandro, Q1 aQuibrera, Miguel1 aShohet, Ralph, V1 aAmbite, Jose, Luis1 aWilkens, Lynne, R1 aLe Marchand, Loïc1 aHaiman, Christopher, A1 aBuyske, Steven1 aKooperberg, Charles1 aNorth, Kari, E1 aFornage, Myriam1 aCrawford, Dana, C uhttps://chs-nhlbi.org/node/629203380nas a2200673 4500008004100000022001400041245020100055210006900256260001300325300001100338490000700349520133800356653001001694653000901704653004001713653001101753653003201764653003401796653001101830653001101841653000901852653001601861653003601877653002801913653003401941653001701975100002201992700001902014700002302033700002302056700002102079700002102100700002802121700002202149700002302171700002102194700001902215700002102234700002402255700001602279700002202295700002202317700002102339700002602360700002302386700002102409700002102430700002102451700002302472700002202495700002202517700002702539700001902566700002402585700001902609700002002628700002202648856003602670 2013 eng d a1469-180900aPost-genome-wide association study challenges for lipid traits: describing age as a modifier of gene-lipid associations in the Population Architecture using Genomics and Epidemiology (PAGE) study.0 aPostgenomewide association study challenges for lipid traits des c2013 Sep a416-250 v773 aNumerous common genetic variants that influence plasma high-density lipoprotein cholesterol, low-density lipoprotein cholesterol (LDL-C), and triglyceride distributions have been identified via genome-wide association studies (GWAS). However, whether or not these associations are age-dependent has largely been overlooked. We conducted an association study and meta-analysis in more than 22,000 European Americans between 49 previously identified GWAS variants and the three lipid traits, stratified by age (males: <50 or ≥50 years of age; females: pre- or postmenopausal). For each variant, a test of heterogeneity was performed between the two age strata and significant Phet values were used as evidence of age-specific genetic effects. We identified seven associations in females and eight in males that displayed suggestive heterogeneity by age (Phet < 0.05). The association between rs174547 (FADS1) and LDL-C in males displayed the most evidence for heterogeneity between age groups (Phet = 1.74E-03, I(2) = 89.8), with a significant association in older males (P = 1.39E-06) but not younger males (P = 0.99). However, none of the suggestive modifying effects survived adjustment for multiple testing, highlighting the challenges of identifying modifiers of modest SNP-trait associations despite large sample sizes.
10aAdult10aAged10aEuropean Continental Ancestry Group10aFemale10aGenetic Association Studies10aGenome-Wide Association Study10aHumans10aLipids10aMale10aMiddle Aged10aPolymorphism, Single Nucleotide10aQuantitative Trait Loci10aQuantitative Trait, Heritable10aRisk Factors1 aDumitrescu, Logan1 aCarty, Cara, L1 aFranceschini, Nora1 aHindorff, Lucia, A1 aCole, Shelley, A1 aBůzková, Petra1 aSchumacher, Fredrick, R1 aEaton, Charles, B1 aGoodloe, Robert, J1 aDuggan, David, J1 aHaessler, Jeff1 aCochran, Barbara1 aHenderson, Brian, E1 aCheng, Iona1 aJohnson, Karen, C1 aCarlson, Chris, S1 aLove, Shelly-Ann1 aBrown-Gentry, Kristin1 aNato, Alejandro, Q1 aQuibrera, Miguel1 aAnderson, Garnet1 aShohet, Ralph, V1 aAmbite, Jose, Luis1 aWilkens, Lynne, R1 aLe Marchand, Loic1 aHaiman, Christopher, A1 aBuyske, Steven1 aKooperberg, Charles1 aNorth, Kari, E1 aFornage, Myriam1 aCrawford, Dana, C uhttps://chs-nhlbi.org/node/6111