03528nas a2200721 4500008004100000022001400041245014600055210006900201260000900270300001100279490000600290520139200296653002201688653002801710653004001738653002101778653002101799653002301820653001901843653001901862653003401881653001301915653001101928653002301939653003601962653002801998100001902026700001302045700001902058700001602077700002902093700002202122700002302144700002202167700002302189700002102212700002102233700002202254700002102276700001802297700002202315700002502337700002302362700002202385700001702407700002002424700002402444700001202468700002302480700002002503700002602523700002202549700002802571700002402599700001802623700002102641700002102662700002702683700001902710700002202729700001902751856003602770 2012 eng d a1932-620300aEvaluation of the metabochip genotyping array in African Americans and implications for fine mapping of GWAS-identified loci: the PAGE study.0 aEvaluation of the metabochip genotyping array in African America c2012 ae356510 v73 a
The Metabochip is a custom genotyping array designed for replication and fine mapping of metabolic, cardiovascular, and anthropometric trait loci and includes low frequency variation content identified from the 1000 Genomes Project. It has 196,725 SNPs concentrated in 257 genomic regions. We evaluated the Metabochip in 5,863 African Americans; 89% of all SNPs passed rigorous quality control with a call rate of 99.9%. Two examples illustrate the value of fine mapping with the Metabochip in African-ancestry populations. At CELSR2/PSRC1/SORT1, we found the strongest associated SNP for LDL-C to be rs12740374 (p = 3.5 × 10(-11)), a SNP indistinguishable from multiple SNPs in European ancestry samples due to high correlation. Its distinct signal supports functional studies elsewhere suggesting a causal role in LDL-C. At CETP we found rs17231520, with risk allele frequency 0.07 in African Americans, to be associated with HDL-C (p = 7.2 × 10(-36)). This variant is very rare in Europeans and not tagged in common GWAS arrays, but was identified as associated with HDL-C in African Americans in a single-gene study. Our results, one narrowing the risk interval and the other revealing an associated variant not found in Europeans, demonstrate the advantages of high-density genotyping of common and rare variation for fine mapping of trait loci in African American samples.
10aAfrican Americans10aCardiovascular Diseases10aCholesterol Ester Transfer Proteins10aCholesterol, HDL10aCholesterol, LDL10aChromosomes, Human10aCohort Studies10aGene Frequency10aGenome-Wide Association Study10aGenotype10aHumans10aMetabolic Diseases10aPolymorphism, Single Nucleotide10aQuantitative Trait Loci1 aBuyske, Steven1 aWu, Ying1 aCarty, Cara, L1 aCheng, Iona1 aAssimes, Themistocles, L1 aDumitrescu, Logan1 aHindorff, Lucia, A1 aMitchell, Sabrina1 aAmbite, Jose, Luis1 aBoerwinkle, Eric1 aBůzková, Petra1 aCarlson, Chris, S1 aCochran, Barbara1 aDuggan, David1 aEaton, Charles, B1 aFesinmeyer, Megan, D1 aFranceschini, Nora1 aHaessler, Jeffrey1 aJenny, Nancy1 aKang, Hyun, Min1 aKooperberg, Charles1 aLin, Yi1 aLe Marchand, Loïc1 aMatise, Tara, C1 aRobinson, Jennifer, G1 aRodriguez, Carlos1 aSchumacher, Fredrick, R1 aVoight, Benjamin, F1 aYoung, Alicia1 aManolio, Teri, A1 aMohlke, Karen, L1 aHaiman, Christopher, A1 aPeters, Ulrike1 aCrawford, Dana, C1 aNorth, Kari, E uhttps://chs-nhlbi.org/node/663404096nas a2200901 4500008004100000022001400041245007000055210006900125260001500194300001100209490000700220520164400227653001001871653002201881653000901903653002201912653002001934653001101954653001701965653003801982653001802020653003402038653001302072653001102085653002702096653000902123653001602132653001202148653003602160653001602196100001502212700002502227700001502252700002302267700001902290700001902309700002802328700002102356700002102377700002002398700001702418700002102435700002102456700002502477700002002502700001702522700001602539700002002555700002502575700002102600700001602621700002102637700001602658700001902674700001802693700001902711700001702730700002602747700002002773700002202793700002102815700002002836700002402856700001502880700002002895700001602915700003002931700002202961700002102983700002403004700002003028700002303048700002203071700002703093700001903120700001903139856003603158 2013 eng d a1537-660500aFine Mapping and Identification of BMI Loci in African Americans.0 aFine Mapping and Identification of BMI Loci in African Americans c2013 Oct 3 a661-710 v933 aGenome-wide association studies (GWASs) primarily performed in European-ancestry (EA) populations have identified numerous loci associated with body mass index (BMI). However, it is still unclear whether these GWAS loci can be generalized to other ethnic groups, such as African Americans (AAs). Furthermore, the putative functional variant or variants in these loci mostly remain under investigation. The overall lower linkage disequilibrium in AA compared to EA populations provides the opportunity to narrow in or fine-map these BMI-related loci. Therefore, we used the Metabochip to densely genotype and evaluate 21 BMI GWAS loci identified in EA studies in 29,151 AAs from the Population Architecture using Genomics and Epidemiology (PAGE) study. Eight of the 21 loci (SEC16B, TMEM18, ETV5, GNPDA2, TFAP2B, BDNF, FTO, and MC4R) were found to be associated with BMI in AAs at 5.8 × 10(-5). Within seven out of these eight loci, we found that, on average, a substantially smaller number of variants was correlated (r(2) > 0.5) with the most significant SNP in AA than in EA populations (16 versus 55). Conditional analyses revealed GNPDA2 harboring a potential additional independent signal. Moreover, Metabochip-wide discovery analyses revealed two BMI-related loci, BRE (rs116612809, p = 3.6 × 10(-8)) and DHX34 (rs4802349, p = 1.2 × 10(-7)), which were significant when adjustment was made for the total number of SNPs tested across the chip. These results demonstrate that fine mapping in AAs is a powerful approach for both narrowing in on the underlying causal variants in known loci and discovering BMI-related loci.
10aAdult10aAfrican Americans10aAged10aAged, 80 and over10aBody Mass Index10aFemale10aGenetic Loci10aGenetic Predisposition to Disease10aGenome, Human10aGenome-Wide Association Study10aGenotype10aHumans10aLinkage Disequilibrium10aMale10aMiddle Aged10aObesity10aPolymorphism, Single Nucleotide10aYoung Adult1 aGong, Jian1 aSchumacher, Fredrick1 aLim, Unhee1 aHindorff, Lucia, A1 aHaessler, Jeff1 aBuyske, Steven1 aCarlson, Christopher, S1 aRosse, Stephanie1 aBůzková, Petra1 aFornage, Myriam1 aGross, Myron1 aPankratz, Nathan1 aPankow, James, S1 aSchreiner, Pamela, J1 aCooper, Richard1 aEhret, Georg1 aGu, Charles1 aHouston, Denise1 aIrvin, Marguerite, R1 aJackson, Rebecca1 aKuller, Lew1 aHenderson, Brian1 aCheng, Iona1 aWilkens, Lynne1 aLeppert, Mark1 aLewis, Cora, E1 aLi, Rongling1 aNguyen, Khanh-Dung, H1 aGoodloe, Robert1 aFarber-Eger, Eric1 aBoston, Jonathan1 aDilks, Holli, H1 aRitchie, Marylyn, D1 aFowke, Jay1 aPooler, Loreall1 aGraff, Misa1 aFernandez-Rhodes, Lindsay1 aCochrane, Barbara1 aBoerwinkle, Eric1 aKooperberg, Charles1 aMatise, Tara, C1 aLe Marchand, Loïc1 aCrawford, Dana, C1 aHaiman, Christopher, A1 aNorth, Kari, E1 aPeters, Ulrike uhttps://chs-nhlbi.org/node/662603673nas a2200601 4500008004100000022001400041245015800055210006900213260000900282300000700291490000700298520191500305653001102220653002602231653001802257653003402275653001102309653001102320653000902331653003602340653002202376100002002398700001902418700002202437700002102459700002102480700002002501700002402521700002202545700002102567700002102588700002202609700002402631700001902655700002302674700002202697700002102719700002102740700001602761700002202777700002602799700002102825700002302846700002402869700002302893700002402916700002202940700001902962700001902981700002003000710001503020856003603035 2013 eng d a1471-215600aInvestigation of gene-by-sex interactions for lipid traits in diverse populations from the population architecture using genomics and epidemiology study.0 aInvestigation of genebysex interactions for lipid traits in dive c2013 a330 v143 aBACKGROUND: High-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels are influenced by both genes and the environment. Genome-wide association studies (GWAS) have identified ~100 common genetic variants associated with HDL-C, LDL-C, and/or TG levels, mostly in populations of European descent, but little is known about the modifiers of these associations. Here, we investigated whether GWAS-identified SNPs for lipid traits exhibited heterogeneity by sex in the Population Architecture using Genomics and Epidemiology (PAGE) study.
RESULTS: A sex-stratified meta-analysis was performed for 49 GWAS-identified SNPs for fasting HDL-C, LDL-C, and ln(TG) levels among adults self-identified as European American (25,013). Heterogeneity by sex was established when phet < 0.001. There was evidence for heterogeneity by sex for two SNPs for ln(TG) in the APOA1/C3/A4/A5/BUD13 gene cluster: rs28927680 (p(het) = 7.4 x 10(-7)) and rs3135506 (p(het) = 4.3 x 10(-4)one SNP in PLTP for HDL levels (rs7679; p(het) = 9.9 x 10(-4)), and one in HMGCR for LDL levels (rs12654264; p(het) = 3.1 x 10(-5)). We replicated heterogeneity by sex in five of seventeen loci previously reported by genome-wide studies (binomial p = 0.0009). We also present results for other racial/ethnic groups in the supplementary materials, to provide a resource for future meta-analyses.
CONCLUSIONS: We provide further evidence for sex-specific effects of SNPs in the APOA1/C3/A4/A5/BUD13 gene cluster, PLTP, and HMGCR on fasting triglyceride levels in European Americans from the PAGE study. Our findings emphasize the need for considering context-specific effects when interpreting genetic associations emerging from GWAS, and also highlight the difficulties in replicating interaction effects across studies and across racial/ethnic groups.
10aFemale10aGenetic Heterogeneity10aGenome, Human10aGenome-Wide Association Study10aHumans10aLipids10aMale10aPolymorphism, Single Nucleotide10aPopulation Groups1 aTaylor, Kira, C1 aCarty, Cara, L1 aDumitrescu, Logan1 aBůzková, Petra1 aCole, Shelley, A1 aHindorff, Lucia1 aSchumacher, Fred, R1 aWilkens, Lynne, R1 aShohet, Ralph, V1 aQuibrera, Miguel1 aJohnson, Karen, C1 aHenderson, Brian, E1 aHaessler, Jeff1 aFranceschini, Nora1 aEaton, Charles, B1 aDuggan, David, J1 aCochran, Barbara1 aCheng, Iona1 aCarlson, Chris, S1 aBrown-Gentry, Kristin1 aAnderson, Garnet1 aAmbite, Jose, Luis1 aHaiman, Christopher1 aLe Marchand, Loïc1 aKooperberg, Charles1 aCrawford, Dana, C1 aBuyske, Steven1 aNorth, Kari, E1 aFornage, Myriam1 aPAGE Study uhttps://chs-nhlbi.org/node/662702686nas 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/611104247nas a2200757 4500008004100000022001400041245023300055210006900288260000900357300001300366490000600379520199400385653004102379653001002420653002202430653000902452653002202461653001202483653002002495653002302515653003402538653004002572653001102612653003802623653003402661653001102695653002702706653000902733653001702742653001602759653001202775653001302787100001902800700001902819700002402838700001802862700001902880700001502899700002502914700002402939700001902963700002502982700001503007700001603022700002103038700001903059700001703078700001603095700001703111700002603128700002003154700001903174700001803193700002503211700001603236700002003252700002103272700002103293700002003314700002303334700002303357700002203380700002703402700002403429856003603453 2013 eng d a1553-740400aA systematic mapping approach of 16q12.2/FTO and BMI in more than 20,000 African Americans narrows in on the underlying functional variation: results from the Population Architecture using Genomics and Epidemiology (PAGE) study.0 asystematic mapping approach of 16q122FTO and BMI in more than 20 c2013 ae10031710 v93 aGenetic variants in intron 1 of the fat mass- and obesity-associated (FTO) gene have been consistently associated with body mass index (BMI) in Europeans. However, follow-up studies in African Americans (AA) have shown no support for some of the most consistently BMI-associated FTO index single nucleotide polymorphisms (SNPs). This is most likely explained by different race-specific linkage disequilibrium (LD) patterns and lower correlation overall in AA, which provides the opportunity to fine-map this region and narrow in on the functional variant. To comprehensively explore the 16q12.2/FTO locus and to search for second independent signals in the broader region, we fine-mapped a 646-kb region, encompassing the large FTO gene and the flanking gene RPGRIP1L by investigating a total of 3,756 variants (1,529 genotyped and 2,227 imputed variants) in 20,488 AAs across five studies. We observed associations between BMI and variants in the known FTO intron 1 locus: the SNP with the most significant p-value, rs56137030 (8.3 × 10(-6)) had not been highlighted in previous studies. While rs56137030was correlated at r(2)>0.5 with 103 SNPs in Europeans (including the GWAS index SNPs), this number was reduced to 28 SNPs in AA. Among rs56137030 and the 28 correlated SNPs, six were located within candidate intronic regulatory elements, including rs1421085, for which we predicted allele-specific binding affinity for the transcription factor CUX1, which has recently been implicated in the regulation of FTO. We did not find strong evidence for a second independent signal in the broader region. In summary, this large fine-mapping study in AA has substantially reduced the number of common alleles that are likely to be functional candidates of the known FTO locus. Importantly our study demonstrated that comprehensive fine-mapping in AA provides a powerful approach to narrow in on the functional candidate(s) underlying the initial GWAS findings in European populations.
10aAdaptor Proteins, Signal Transducing10aAdult10aAfrican Americans10aAged10aAged, 80 and over10aAlleles10aBody Mass Index10aChromosome Mapping10aContinental Population Groups10aEuropean Continental Ancestry Group10aFemale10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aHumans10aLinkage Disequilibrium10aMale10aMetagenomics10aMiddle Aged10aObesity10aProteins1 aPeters, Ulrike1 aNorth, Kari, E1 aSethupathy, Praveen1 aBuyske, Steve1 aHaessler, Jeff1 aJiao, Shuo1 aFesinmeyer, Megan, D1 aJackson, Rebecca, D1 aKuller, Lew, H1 aRajkovic, Aleksandar1 aLim, Unhee1 aCheng, Iona1 aSchumacher, Fred1 aWilkens, Lynne1 aLi, Rongling1 aMonda, Keri1 aEhret, Georg1 aNguyen, Khanh-Dung, H1 aCooper, Richard1 aLewis, Cora, E1 aLeppert, Mark1 aIrvin, Marguerite, R1 aGu, Charles1 aHouston, Denise1 aBůzková, Petra1 aRitchie, Marylyn1 aMatise, Tara, C1 aLe Marchand, Loïc1 aHindorff, Lucia, A1 aCrawford, Dana, C1 aHaiman, Christopher, A1 aKooperberg, Charles uhttps://chs-nhlbi.org/node/662805266nas a2201201 4500008004100000022001400041245015400055210006900209260001300278300001300291490000600304520181500310653002202125653002202147653002102169653002102190653004002211653003402251653001102285653002202296653002202318653002702340653002602367653001802393100001302411700002202424700002102446700002102467700001902488700001802507700002102525700002102546700002502567700001902592700001602611700002102627700003002648700002202678700002202700700002302722700001702745700002402762700002302786700001402809700002002823700002202843700001802865700002302883700001202906700002202918700002802940700002502968700001902993700002603012700002103038700002503059700002003084700001703104700001803121700002003139700001903159700001903178700002103197700002003218700002803238700002103266700002603287700002403313700001803337700002103355700001703376700001703393700002003410700002003430700002303450700002603473700002203499700001903521700001903540700001403559700002103573700002003594700002003614700002103634700001903655700002403674700002103698700002203719700002003741700002303761700002003784700002003804700002103824700002703845700002103872700002403893700002903917700002203946700002003968700001903988700002104007856003604028 2013 eng d a1553-740400aTrans-ethnic fine-mapping of lipid loci identifies population-specific signals and allelic heterogeneity that increases the trait variance explained.0 aTransethnic finemapping of lipid loci identifies populationspeci c2013 Mar ae10033790 v93 aGenome-wide association studies (GWAS) have identified ~100 loci associated with blood lipid levels, but much of the trait heritability remains unexplained, and at most loci the identities of the trait-influencing variants remain unknown. We conducted a trans-ethnic fine-mapping study at 18, 22, and 18 GWAS loci on the Metabochip for their association with triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C), respectively, in individuals of African American (n = 6,832), East Asian (n = 9,449), and European (n = 10,829) ancestry. We aimed to identify the variants with strongest association at each locus, identify additional and population-specific signals, refine association signals, and assess the relative significance of previously described functional variants. Among the 58 loci, 33 exhibited evidence of association at P<1 × 10(-4) in at least one ancestry group. Sequential conditional analyses revealed that ten, nine, and four loci in African Americans, Europeans, and East Asians, respectively, exhibited two or more signals. At these loci, accounting for all signals led to a 1.3- to 1.8-fold increase in the explained phenotypic variance compared to the strongest signals. Distinct signals across ancestry groups were identified at PCSK9 and APOA5. Trans-ethnic analyses narrowed the signals to smaller sets of variants at GCKR, PPP1R3B, ABO, LCAT, and ABCA1. Of 27 variants reported previously to have functional effects, 74% exhibited the strongest association at the respective signal. In conclusion, trans-ethnic high-density genotyping and analysis confirm the presence of allelic heterogeneity, allow the identification of population-specific variants, and limit the number of candidate SNPs for functional studies.
10aAfrican Americans10aApolipoproteins A10aCholesterol, HDL10aCholesterol, LDL10aEuropean Continental Ancestry Group10aGenome-Wide Association Study10aHumans10aLipoproteins, HDL10aLipoproteins, LDL10aProprotein Convertases10aSerine Endopeptidases10aTriglycerides1 aWu, Ying1 aWaite, Lindsay, L1 aJackson, Anne, U1 aSheu, Wayne, H-H1 aBuyske, Steven1 aAbsher, Devin1 aArnett, Donna, K1 aBoerwinkle, Eric1 aBonnycastle, Lori, L1 aCarty, Cara, L1 aCheng, Iona1 aCochran, Barbara1 aCroteau-Chonka, Damien, C1 aDumitrescu, Logan1 aEaton, Charles, B1 aFranceschini, Nora1 aGuo, Xiuqing1 aHenderson, Brian, E1 aHindorff, Lucia, A1 aKim, Eric1 aKinnunen, Leena1 aKomulainen, Pirjo1 aLee, Wen-Jane1 aLe Marchand, Loïc1 aLin, Yi1 aLindström, Jaana1 aLingaas-Holmen, Oddgeir1 aMitchell, Sabrina, L1 aNarisu, Narisu1 aRobinson, Jennifer, G1 aSchumacher, Fred1 aStančáková, Alena1 aSundvall, Jouko1 aSung, Yun-Ju1 aSwift, Amy, J1 aWang, Wen-Chang1 aWilkens, Lynne1 aWilsgaard, Tom1 aYoung, Alicia, M1 aAdair, Linda, S1 aBallantyne, Christie, M1 aBůzková, Petra1 aChakravarti, Aravinda1 aCollins, Francis, S1 aDuggan, David1 aFeranil, Alan, B1 aHo, Low-Tone1 aHung, Yi-Jen1 aHunt, Steven, C1 aHveem, Kristian1 aJuang, Jyh-Ming, J1 aKesäniemi, Antero, Y1 aKuusisto, Johanna1 aLaakso, Markku1 aLakka, Timo, A1 aLee, I-Te1 aLeppert, Mark, F1 aMatise, Tara, C1 aMoilanen, Leena1 aNjølstad, Inger1 aPeters, Ulrike1 aQuertermous, Thomas1 aRauramaa, Rainer1 aRotter, Jerome, I1 aSaramies, Jouko1 aTuomilehto, Jaakko1 aUusitupa, Matti1 aWang, Tzung-Dau1 aBoehnke, Michael1 aHaiman, Christopher, A1 aChen, Yii-der, I1 aKooperberg, Charles1 aAssimes, Themistocles, L1 aCrawford, Dana, C1 aHsiung, Chao, A1 aNorth, Kari, E1 aMohlke, Karen, L uhttps://chs-nhlbi.org/node/662904252nas a2200745 4500008004100000022001400041245016200055210006900217260001300286300001100299490000600310520207600316653001002392653003902402653000902441653003702450653002302487653001102510653002202521653003402543653002302577653001102600653002802611653001702639653000902656653001602665653003602681653001802717653001602735100002602751700002602777700001902803700002102822700002802843700001602871700001702887700002302904700001702927700001902944700001502963700002602978700002003004700002603024700001803050700001803068700002103086700002103107700002103128700002203149700002103171700002303192700002003215700002203235700002703257700002503284700002003309700001603329700002103345700002303366700002303389700002203412700001703434700001903451856003603470 2014 eng d a1942-326800aMultiancestral analysis of inflammation-related genetic variants and C-reactive protein in the population architecture using genomics and epidemiology study.0 aMultiancestral analysis of inflammationrelated genetic variants c2014 Apr a178-880 v73 aBACKGROUND: C-reactive protein (CRP) is a biomarker of inflammation. Genome-wide association studies (GWAS) have identified single-nucleotide polymorphisms (SNPs) associated with CRP concentrations and inflammation-related traits such as cardiovascular disease, type 2 diabetes mellitus, and obesity. We aimed to replicate previous CRP-SNP associations, assess whether these associations generalize to additional race/ethnicity groups, and evaluate inflammation-related SNPs for a potentially pleiotropic association with CRP.
METHODS AND RESULTS: We selected and analyzed 16 CRP-associated and 250 inflammation-related GWAS SNPs among 40 473 African American, American Indian, Asian/Pacific Islander, European American, and Hispanic participants from 7 studies collaborating in the Population Architecture using Genomics and Epidemiology (PAGE) study. Fixed-effect meta-analyses combined study-specific race/ethnicity-stratified linear regression estimates to evaluate the association between each SNP and high-sensitivity CRP. Overall, 18 SNPs in 8 loci were significantly associated with CRP (Bonferroni-corrected P<3.1×10(-3) for replication, P<2.0×10(-4) for pleiotropy): Seven of these were specific to European Americans, while 9 additionally generalized to African Americans (1), Hispanics (5), or both (3); 1 SNP was seen only in African Americans and Hispanics. Two SNPs in the CELSR2/PSRC1/SORT1 locus showed a potentially novel association with CRP: rs599839 (P=2.0×10(-6)) and rs646776 (P=3.1×10(-5)).
CONCLUSIONS: We replicated 16 SNP-CRP associations, 10 of which generalized to African Americans and/or Hispanics. We also identified potentially novel pleiotropic associations with CRP for two SNPs previously associated with coronary artery disease and/or low-density lipoprotein-cholesterol. These findings demonstrate the benefit of evaluating genotype-phenotype associations in multiple race/ethnicity groups and looking for pleiotropic relationships among SNPs previously associated with related phenotypes.
10aAdult10aAfrican Continental Ancestry Group10aAged10aAsian Continental Ancestry Group10aC-Reactive Protein10aFemale10aGenetic Variation10aGenome-Wide Association Study10aHispanic Americans10aHumans10aIndians, North American10aInflammation10aMale10aMiddle Aged10aPolymorphism, Single Nucleotide10aUnited States10aYoung Adult1 aKocarnik, Jonathan, M1 aPendergrass, Sarah, A1 aCarty, Cara, L1 aPankow, James, S1 aSchumacher, Fredrick, R1 aCheng, Iona1 aDurda, Peter1 aAmbite, Jose, Luis1 aDeelman, Ewa1 aCook, Nancy, R1 aLiu, Simin1 aWactawski-Wende, Jean1 aHutter, Carolyn1 aBrown-Gentry, Kristin1 aWilson, Sarah1 aBest, Lyle, G1 aPankratz, Nathan1 aHong, Ching-Ping1 aCole, Shelley, A1 aVoruganti, Saroja1 aBůzková, Petra1 aJorgensen, Neal, W1 aJenny, Nancy, S1 aWilkens, Lynne, R1 aHaiman, Christopher, A1 aKolonel, Laurence, N1 aLaCroix, Andrea1 aNorth, Kari1 aJackson, Rebecca1 aLe Marchand, Loïc1 aHindorff, Lucia, A1 aCrawford, Dana, C1 aGross, Myron1 aPeters, Ulrike uhttps://chs-nhlbi.org/node/636003689nas a2200553 4500008004100000022001400041245023400055210006900289260001600358300001400374490000700388520195100395100002602346700002102372700001602393700002202409700002002431700001902451700001902470700002502489700002202514700002802536700002302564700002902587700001902616700002102635700001802656700001302674700001902687700002502706700002402731700003002755700001902785700002102804700002102825700001802846700002302864700001602887700002202903700002302925700002002948700001902968700001902987700002703006700001903033700002303052700002403075856003603099 2018 eng d a1460-208300aDiscovery, fine-mapping, and conditional analyses of genetic variants associated with C-reactive protein in multiethnic populations using the Metabochip in the Population Architecture using Genomics and Epidemiology (PAGE) study.0 aDiscovery finemapping and conditional analyses of genetic varian c2018 Aug 15 a2940-29530 v273 aC-reactive protein (CRP) is a circulating biomarker indicative of systemic inflammation. We aimed to evaluate genetic associations with CRP levels among non-European-ancestry populations through discovery, fine-mapping and conditional analyses. A total of 30 503 non-European-ancestry participants from 6 studies participating in the Population Architecture using Genomics and Epidemiology study had serum high-sensitivity CRP measurements and ∼200 000 single nucleotide polymorphisms (SNPs) genotyped on the Metabochip. We evaluated the association between each SNP and log-transformed CRP levels using multivariate linear regression, with additive genetic models adjusted for age, sex, the first four principal components of genetic ancestry, and study-specific factors. Differential linkage disequilibrium patterns between race/ethnicity groups were used to fine-map regions associated with CRP levels. Conditional analyses evaluated for multiple independent signals within genetic regions. One hundred and sixty-three unique variants in 12 loci in overall or race/ethnicity-stratified Metabochip-wide scans reached a Bonferroni-corrected P-value <2.5E-7. Three loci have no (HACL1, OLFML2B) or only limited (PLA2G6) previous associations with CRP levels. Six loci had different top hits in race/ethnicity-specific versus overall analyses. Fine-mapping refined the signal in six loci, particularly in HNF1A. Conditional analyses provided evidence for secondary signals in LEPR, IL1RN and HNF1A, and for multiple independent signals in CRP and APOE. We identified novel variants and loci associated with CRP levels, generalized known CRP associations to a multiethnic study population, refined association signals at several loci and found evidence for multiple independent signals at several well-known loci. This study demonstrates the benefit of conducting inclusive genetic association studies in large multiethnic populations.
1 aKocarnik, Jonathan, M1 aRichard, Melissa1 aGraff, Misa1 aHaessler, Jeffrey1 aBien, Stephanie1 aCarlson, Chris1 aCarty, Cara, L1 aReiner, Alexander, P1 aAvery, Christy, L1 aBallantyne, Christie, M1 aLaCroix, Andrea, Z1 aAssimes, Themistocles, L1 aBarbalic, Maja1 aPankratz, Nathan1 aTang, Weihong1 aTao, Ran1 aChen, Dongquan1 aTalavera, Gregory, A1 aDaviglus, Martha, L1 aChirinos-Medina, Diana, A1 aPereira, Rocio1 aNishimura, Katie1 aBůzková, Petra1 aBest, Lyle, G1 aAmbite, Jose, Luis1 aCheng, Iona1 aCrawford, Dana, C1 aHindorff, Lucia, A1 aFornage, Myriam1 aHeiss, Gerardo1 aNorth, Kari, E1 aHaiman, Christopher, A1 aPeters, Ulrike1 aLe Marchand, Loïc1 aKooperberg, Charles uhttps://chs-nhlbi.org/node/7798