Fast Principal-Component Analysis Reveals Convergent Evolution of ADH1B in Europe and East Asia

Galinsky, Kevin; Bhatia, Gaurav; Loh, Po−Ru; Georgiev, Stoyan; Mukherjee, Sayan; Patterson, Nick; Price, Alkes L.

doi:10.1016/j.ajhg.2015.12.022

Cited by 366 publications

(414 citation statements)

References 104 publications

(158 reference statements)

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“…We performed a PCA (40,41) in the sample using GCTA-PCA (27) on all common autosomal SNPs after QC and projected the PCs to the subjects from the 1000G (42). Our study subjects were stratified along PC1 (SI Appendix, Fig.…”

Section: Methodsmentioning

confidence: 99%

Genetic signatures of high-altitude adaptation in Tibetans

Yang

Jin

Chen

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

179

174

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Indigenous Tibetan people have lived on the Tibetan Plateau for millennia. There is a long-standing question about the genetic basis of high-altitude adaptation in Tibetans. We conduct a genome-wide study of 7.3 million genotyped and imputed SNPs of 3,008 Tibetans and 7,287 non-Tibetan individuals of Eastern Asian ancestry. Using this large dataset, we detect signals of high-altitude adaptation at nine genomic loci, of which seven are unique. The alleles under natural selection at two of these loci [methylenetetrahydrofolate reductase (MTHFR) and EPAS1] are strongly associated with blood-related phenotypes, such as hemoglobin, homocysteine, and folate in Tibetans. The folate-increasing allele of rs1801133 at the MTHFR locus has an increased frequency in Tibetans more than expected under a drift model, which is probably a consequence of adaptation to high UV radiation. These findings provide important insights into understanding the genomic consequences of high-altitude adaptation in Tibetans.high-altitude adaptation | Tibetans | genome-wide association study | mixed linear model | polygenic selection G enetic adaptation to a novel environment is a fundamental process for the survival and adaptation of a species. In humans, one of the most recent examples is adaptation to high altitude, such as the Tibetan highlands. The Tibetan Plateau (TP; also known as the Qinghai-Tibet Plateau in China) has an average elevation of ∼4,000 m above sea level, where the oxygen concentration is ∼40% lower (1) and UV radiation is ∼30% stronger (2) than at sea level. The indigenous Tibetan people have developed a distinctive set of physiological characteristics to adapt to the extreme environmental conditions in the highlands (1). Previous population-based genetic studies have reported evidence that genetic variants at the EPAS1 and EGLN1 loci have been under positive natural selection (3-7). These genetic variants are associated with phenotypic variation of hemoglobin concentration (HGB) in Tibetans (3-5). The EPAS1 gene, which encodes the hypoxia inducible factor-2α (HIF-2α) subunit of HIF complex, is a transcription factor involved in body response to hypoxia (8, 9). EGLN1 encodes PHD2, which is a major oxygen-dependent negative regulator of HIFs (10, 11). Apart from these two known genes that have biological relevance to hypoxia adaptation (3-7, 12), several other candidate gene loci (e.g., PPARA and HBB) have been highlighted in recent studies (3,4,(13)(14)(15). Genetic adaptation to high altitude, however, is likely to be a complex process, with a large number of genes involved in response to not only hypoxia but also, other extreme environmental conditions, such as low temperature, high UV radiation, and insufficient food supply. If the strength of natural selection at these gene loci has been small to moderate, these loci would not be detected in previous studies (3-7) of small sample size (typically n < 150). In this study, we perform a largescale genome-wide study to detect genetic signals of high-altitude adaptation in 3...

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Section: Methodsmentioning

confidence: 99%

Genetic signatures of high-altitude adaptation in Tibetans

Yang

Jin

Chen

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

179

174

View full text Add to dashboard Cite

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“…Similarly, ALDH rs672 is negatively associated with alcohol use behaviors in Asian populations (this variant is very rare or absent in non-Asian populations) (Quillen et al, 2014) and it causes a complete or nearcomplete lack of acetaldehyde metabolism activity via this pathway (Peng et al, 2014), producing an accumulation of acetaldehyde and consequently its aversive symptoms. It is also recognized that the ADH1B locus is under strong selection in East Asians and a recent study hypothesized an independent evolution of the same locus also in Europeans (Galinsky et al, 2016). For smoking behaviors, the most recognized risk locus is the CHRNA3-CHRNA5-CHRNB4 gene cluster, and risk alleles in this region (rs8034191, rs1051730, rs12914385, rs2036527, and rs16969968) are associated with smoking behaviors including nicotine dependence and smoking quantity (The Tobacco and Genetics Consortium, 2010;David et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Phenome-Wide Association Study for Alcohol and Nicotine Risk Alleles in 26394 Women

Polimanti

Kranzler

2016

Neuropsychopharmacol

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To identify novel traits associated with alleles known to predispose to alcohol and nicotine use, we conducted a phenome-wide association study (PheWAS) in a large multi-population cohort. We investigated 7688 African-Americans, 1133 Asian-Americans, 14 081 EuropeanAmericans, and 3492 Hispanic-Americans from the Women's Health Initiative, analyzing alleles at the CHRNA3-CHRNA5 locus, ADH1B, and ALDH2 with respect to phenotypic traits related to anthropometric characteristics, dietary habits, social status, psychological traits, reproductive history, health conditions, and nicotine/alcohol use. In ADH1B trans-population meta-analysis and population-specific analysis, we replicated prior associations with drinking behaviors and identified multiple novel phenome-wide significant and suggestive findings related to psychological traits, socioeconomic status, vascular/metabolic conditions, and reproductive health. We then applied Bayesian network learning algorithms to provide insight into the causative relationships of the novel ADH1B associations: ADH1B appears to affect phenotypic traits via both alcohol-mediated and alcohol-independent effects. In an independent sample of 2379 subjects, we also replicated the novel ADH1B associations related to socioeconomic status (household gross income and highest grade finished in school). For CHRNA3-CHRNA5 risk alleles, we replicated association with smoking behaviors, lung cancer, and asthma. There were also novel suggestive CHRNA3-CHRNA5 findings with respect to high-cholesterol-medication use and distrustful attitude. In conclusion, the genetics of alcohol and tobacco use potentially has broader implications on physical and mental health than is currently recognized. In particular, ADH1B may be a gene relevant for the human phenome via both alcohol metabolism-related mechanisms and other alcohol metabolismindependent mechanisms.

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“…To perform PCA, we focused on a previously described subset of 54,734 unrelated individuals of European ancestry 6 . We chose this data set as our reference panel for computation of PC loadings based on its large sample size and through representation of individuals of diverse European ancestry.…”

Section: Gera Datasetmentioning

confidence: 99%

“…To assess the validity of PC loading regression as a tool for correction for population stratification, we performed simulations using real genotypes from the GERA data set 7 , a data set of 54,000 European American individuals of diverse European ancestry 6 (see Methods) genotyped at 608k SNPs after QC. We split this data set into two partitions (n=27k each), and computed 16 PCs-four SNP PCs and four haploSNP PCs from each of the MAF ranges [10 -4 ,10 -3 ), [10 -3 ,0.005) and [0.005, 0.01)-in each partition.…”

Section: Assessing Correction Effectiveness Using Out-of-sample Pcsmentioning

confidence: 99%

“…We chose this data set as our reference panel for computation of PC loadings based on its large sample size and through representation of individuals of diverse European ancestry. PCA was performed on an LD pruned set of 162,335 SNPs using the fast principal component analysis feature of EIGENSOFT 4,6 and loadings for the top four PCs were estimated on the full set of 608,981 post-QC SNPs. Separately, we computed loadings for haploSNP CRM PCs that were computed from rare haploSNPs in three bins: [0.0001-0.001),[0.001-0.005),[0.005-0.01).…”

Section: Gera Datasetmentioning

confidence: 99%

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Correcting subtle stratification in summary association statistics

Bhatia

Furlotte

Loh

et al. 2016

Preprint

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Population stratification is a well-documented confounder in GWASes, and is often addressed by including principal component (PC) covariates computed from common SNPs (SNP-PCs). In our analyses of summary statistics from 36 GWASes (mean n=88k), including 20 GWASes using 23andMe data that included SNP-PC covariates, we observed a significantly inflated LD score regression (LDSC) intercept for several traits-suggesting that residual stratification remains a concern, even when SNP-PC covariates are included.Here we propose a new method, PC loading regression, to correct for stratification in summary statistics by leveraging SNP loadings for PCs computed in a large reference panel. In addition to SNP-PCs, the method can be applied to haploSNP-PCs, i.e. PCs computed from a larger number of rare haplotype variants that better capture subtle structure. Using simulations based on real genotypes from 54,000 individuals of diverse European ancestry from the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort, we show that PC loading regression effectively corrects for stratification along top PCs.We applied PC loading regression to several traits with inflated LDSC intercepts. Correcting for the top four SNP-PCs in GERA data, we observe a significant reduction in LDSC intercept height summary statistics from the Genetic Investigation of ANthropometric Traits (GIANT) consortium, but not for 23andMe summary statistics, which already included SNP-PC covariates. However, when correcting for additional haploSNP-PCs in 23andMe GWASes, inflation in the LDSC intercept was eliminated for eye color, hair color, and skin color and substantially reduced for height (1.41 to 1.16; n=430k). Correcting for haploSNP-PCs in GIANT height summary statistics eliminated inflation in the LDSC intercept (from 1.35 to 1.00; n=250k), eliminating 27 significant association signals including one at the LCT locus, which is highly differentiated among European populations and widely known to produce spurious signals. Overall, our results suggest that uncorrected population stratification is a concern in GWASes of large sample size and that PC loading regression can correct for this stratification.

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Fast Principal-Component Analysis Reveals Convergent Evolution of ADH1B in Europe and East Asia

Cited by 366 publications

References 104 publications

Genetic signatures of high-altitude adaptation in Tibetans

Genetic signatures of high-altitude adaptation in Tibetans

Phenome-Wide Association Study for Alcohol and Nicotine Risk Alleles in 26394 Women

Correcting subtle stratification in summary association statistics

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