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1.
Nat Commun ; 11(1): 4912, 2020 09 30.
Artigo em Inglês | MEDLINE | ID: mdl-32999275

RESUMO

Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, key tissues and cell-types required for functional inference are absent from large-scale resources. Here we explore the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using data from 420 donors. We find: (a) 7741 cis-eQTLs in islets with a replication rate across 44 GTEx tissues between 40% and 73%; (b) marked overlap between islet cis-eQTL signals and active regulatory sequences in islets, with reduced eQTL effect size observed in the stretch enhancers most strongly implicated in GWAS signal location; (c) enrichment of islet cis-eQTL signals with T2D risk variants identified in genome-wide association studies; and (d) colocalization between 47 islet cis-eQTLs and variants influencing T2D or glycemic traits, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in disease relevant tissues.


Assuntos
Glicemia/genética , Diabetes Mellitus Tipo 2/genética , Predisposição Genética para Doença , Ilhotas Pancreáticas/metabolismo , Locos de Características Quantitativas , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Animais , Glicemia/metabolismo , Linhagem Celular Tumoral , Estudos de Coortes , Diabetes Mellitus Tipo 2/sangue , Diacilglicerol Quinase/genética , Diacilglicerol Quinase/metabolismo , Elementos Facilitadores Genéticos , Feminino , Regulação da Expressão Gênica , Estudo de Associação Genômica Ampla , Humanos , Masculino , Camundongos , Pessoa de Meia-Idade , Polimorfismo de Nucleotídeo Único , RNA-Seq , Análise de Sequência de DNA , Proteína 2 Semelhante ao Fator 7 de Transcrição/genética , Proteína 2 Semelhante ao Fator 7 de Transcrição/metabolismo , Adulto Jovem
2.
PLoS Genet ; 16(9): e1009019, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32915782

RESUMO

Loci identified in genome-wide association studies (GWAS) can include multiple distinct association signals. We sought to identify the molecular basis of multiple association signals for adiponectin, a hormone involved in glucose regulation secreted almost exclusively from adipose tissue, identified in the Metabolic Syndrome in Men (METSIM) study. With GWAS data for 9,262 men, four loci were significantly associated with adiponectin: ADIPOQ, CDH13, IRS1, and PBRM1. We performed stepwise conditional analyses to identify distinct association signals, a subset of which are also nearly independent (lead variant pairwise r2<0.01). Two loci exhibited allelic heterogeneity, ADIPOQ and CDH13. Of seven association signals at the ADIPOQ locus, two signals colocalized with adipose tissue expression quantitative trait loci (eQTLs) for three transcripts: trait-increasing alleles at one signal were associated with increased ADIPOQ and LINC02043, while trait-increasing alleles at the other signal were associated with decreased ADIPOQ-AS1. In reporter assays, adiponectin-increasing alleles at two signals showed corresponding directions of effect on transcriptional activity. Putative mechanisms for the seven ADIPOQ signals include a missense variant (ADIPOQ G90S), a splice variant, a promoter variant, and four enhancer variants. Of two association signals at the CDH13 locus, the first signal consisted of promoter variants, including the lead adipose tissue eQTL variant for CDH13, while a second signal included a distal intron 1 enhancer variant that showed ~2-fold allelic differences in transcriptional reporter activity. Fine-mapping and experimental validation demonstrated that multiple, distinct association signals at these loci can influence multiple transcripts through multiple molecular mechanisms.

3.
Genet Epidemiol ; 44(6): 579-588, 2020 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-32511788

RESUMO

Multiple linear regression is commonly used to test for association between genetic variants and continuous traits and estimate genetic effect sizes. Confounding variables are controlled for by including them as additional covariates. An alternative technique that is increasingly used is to regress out covariates from the raw trait and then perform regression analysis with only the genetic variants included as predictors. In the case of single-variant analysis, this adjusted trait regression (ATR) technique is known to be less powerful than the traditional technique when the genetic variant is correlated with the covariates We extend previous results for single-variant tests by deriving exact relationships between the single-variant score, Wald, likelihood-ratio, and F test statistics and their ATR analogs. We also derive the asymptotic power of ATR analogs of the multiple-variant score and burden tests. We show that the maximum power loss of the ATR analog of the multiple-variant score test is completely characterized by the canonical correlations between the set of genetic variants and the set of covariates. Further, we show that for both single- and multiple-variant tests, the power loss for ATR analogs increases with increasing stringency of Type 1 error control ( α ) and increasing correlation (or canonical correlations) between the genetic variant (or multiple variants) and covariates. We recommend using ATR only when maximum canonical correlation between variants and covariates is low, as is typically true.

4.
Genet Epidemiol ; 44(6): 537-549, 2020 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-32519380

RESUMO

A key aim for current genome-wide association studies (GWAS) is to interrogate the full spectrum of genetic variation underlying human traits, including rare variants, across populations. Deep whole-genome sequencing is the gold standard to fully capture genetic variation, but remains prohibitively expensive for large sample sizes. Array genotyping interrogates a sparser set of variants, which can be used as a scaffold for genotype imputation to capture a wider set of variants. However, imputation quality depends crucially on reference panel size and genetic distance from the target population. Here, we consider sequencing a subset of GWAS participants and imputing the rest using a reference panel that includes both sequenced GWAS participants and an external reference panel. We investigate how imputation quality and GWAS power are affected by the number of participants sequenced for admixed populations (African and Latino Americans) and European population isolates (Sardinians and Finns), and identify powerful, cost-effective GWAS designs given current sequencing and array costs. For populations that are well-represented in existing reference panels, we find that array genotyping alone is cost-effective and well-powered to detect common- and rare-variant associations. For poorly represented populations, sequencing a subset of participants is often most cost-effective, and can substantially increase imputation quality and GWAS power.

5.
Nature ; 582(7811): 240-245, 2020 06.
Artigo em Inglês | MEDLINE | ID: mdl-32499647

RESUMO

Meta-analyses of genome-wide association studies (GWAS) have identified more than 240 loci that are associated with type 2 diabetes (T2D)1,2; however, most of these loci have been identified in analyses of individuals with European ancestry. Here, to examine T2D risk in East Asian individuals, we carried out a meta-analysis of GWAS data from 77,418 individuals with T2D and 356,122 healthy control individuals. In the main analysis, we identified 301 distinct association signals at 183 loci, and across T2D association models with and without consideration of body mass index and sex, we identified 61 loci that are newly implicated in predisposition to T2D. Common variants associated with T2D in both East Asian and European populations exhibited strongly correlated effect sizes. Previously undescribed associations include signals in or near GDAP1, PTF1A, SIX3, ALDH2, a microRNA cluster, and genes that affect the differentiation of muscle and adipose cells3. At another locus, expression quantitative trait loci at two overlapping T2D signals affect two genes-NKX6-3 and ANK1-in different tissues4-6. Association studies in diverse populations identify additional loci and elucidate disease-associated genes, biology, and pathways.


Assuntos
Grupo com Ancestrais do Continente Asiático/genética , Diabetes Mellitus Tipo 2/genética , Predisposição Genética para Doença , Aldeído-Desidrogenase Mitocondrial/genética , Alelos , Anquirinas/genética , Índice de Massa Corporal , Estudos de Casos e Controles , Europa (Continente)/etnologia , Proteínas do Olho/genética , Extremo Oriente/etnologia , Feminino , Estudo de Associação Genômica Ampla , Proteínas de Homeodomínio/genética , Humanos , Masculino , Proteínas do Tecido Nervoso/genética , RNA Mensageiro/análise , Fatores de Transcrição/genética , Transcrição Genética
7.
Nature ; 582(7813): 577-581, 2020 06.
Artigo em Inglês | MEDLINE | ID: mdl-32499649

RESUMO

Many common illnesses, for reasons that have not been identified, differentially affect men and women. For instance, the autoimmune diseases systemic lupus erythematosus (SLE) and Sjögren's syndrome affect nine times more women than men1, whereas schizophrenia affects men with greater frequency and severity relative to women2. All three illnesses have their strongest common genetic associations in the major histocompatibility complex (MHC) locus, an association that in SLE and Sjögren's syndrome has long been thought to arise from alleles of the human leukocyte antigen (HLA) genes at that locus3-6. Here we show that variation of the complement component 4 (C4) genes C4A and C4B, which are also at the MHC locus and have been linked to increased risk for schizophrenia7, generates 7-fold variation in risk for SLE and 16-fold variation in risk for Sjögren's syndrome among individuals with common C4 genotypes, with C4A protecting more strongly than C4B in both illnesses. The same alleles that increase risk for schizophrenia greatly reduce risk for SLE and Sjögren's syndrome. In all three illnesses, C4 alleles act more strongly in men than in women: common combinations of C4A and C4B generated 14-fold variation in risk for SLE, 31-fold variation in risk for Sjögren's syndrome, and 1.7-fold variation in schizophrenia risk among men (versus 6-fold, 15-fold and 1.26-fold variation in risk among women, respectively). At a protein level, both C4 and its effector C3 were present at higher levels in cerebrospinal fluid and plasma8,9 in men than in women among adults aged between 20 and 50 years, corresponding to the ages of differential disease vulnerability. Sex differences in complement protein levels may help to explain the more potent effects of C4 alleles in men, women's greater risk of SLE and Sjögren's syndrome and men's greater vulnerability to schizophrenia. These results implicate the complement system as a source of sexual dimorphism in vulnerability to diverse illnesses.


Assuntos
Complemento C3/genética , Complemento C4/genética , Lúpus Eritematoso Sistêmico/genética , Caracteres Sexuais , Síndrome de Sjogren/genética , Adulto , Alelos , Complemento C3/análise , Complemento C3/líquido cefalorraquidiano , Complemento C4/análise , Complemento C4/líquido cefalorraquidiano , Feminino , Predisposição Genética para Doença , Antígenos HLA/genética , Haplótipos , Humanos , Lúpus Eritematoso Sistêmico/sangue , Lúpus Eritematoso Sistêmico/líquido cefalorraquidiano , Complexo Principal de Histocompatibilidade/genética , Masculino , Pessoa de Meia-Idade , Síndrome de Sjogren/sangue , Síndrome de Sjogren/líquido cefalorraquidiano , Adulto Jovem
8.
Genes (Basel) ; 11(5)2020 05 25.
Artigo em Inglês | MEDLINE | ID: mdl-32466134

RESUMO

There is great interest in understanding the impact of rare variants in human diseases using large sequence datasets. In deep sequence datasets of >10,000 samples, ~10% of the variant sites are observed to be multi-allelic. Many of the multi-allelic variants have been shown to be functional and disease-relevant. Proper analysis of multi-allelic variants is critical to the success of a sequencing study, but existing methods do not properly handle multi-allelic variants and can produce highly misleading association results. We discuss practical issues and methods to encode multi-allelic sites, conduct single-variant and gene-level association analyses, and perform meta-analysis for multi-allelic variants. We evaluated these methods through extensive simulations and the study of a large meta-analysis of ~18,000 samples on the cigarettes-per-day phenotype. We showed that our joint modeling approach provided an unbiased estimate of genetic effects, greatly improved the power of single-variant association tests among methods that can properly estimate allele effects, and enhanced gene-level tests over existing approaches. Software packages implementing these methods are available online.

9.
Genome Res ; 30(2): 185-194, 2020 02.
Artigo em Inglês | MEDLINE | ID: mdl-31980570

RESUMO

Detecting and estimating DNA sample contamination are important steps to ensure high-quality genotype calls and reliable downstream analysis. Existing methods rely on population allele frequency information for accurate estimation of contamination rates. Correctly specifying population allele frequencies for each individual in early stage of sequence analysis is impractical or even impossible for large-scale sequencing centers that simultaneously process samples from multiple studies across diverse populations. On the other hand, incorrectly specified allele frequencies may result in substantial bias in estimated contamination rates. For example, we observed that existing methods often fail to identify 10% contaminated samples at a typical 3% contamination exclusion threshold when genetic ancestry is misspecified. Such an incomplete screening of contaminated samples substantially inflates the estimated rate of genotyping errors even in deeply sequenced genomes and exomes. We propose a robust statistical method that accurately estimates DNA contamination and is agnostic to genetic ancestry of the intended or contaminating sample. Our method integrates the estimation of genetic ancestry and DNA contamination in a unified likelihood framework by leveraging individual-specific allele frequencies projected from reference genotypes onto principal component coordinates. Our method can also be used for estimating genetic ancestries, similar to LASER or TRACE, but simultaneously accounting for potential contamination. We demonstrate that our method robustly estimates contamination rates and genetic ancestries across populations and contamination scenarios. We further demonstrate that, in the presence of contamination, genetic ancestry inference can be substantially biased with existing methods that ignore contamination, while our method corrects for such biases.

10.
Genet Epidemiol ; 44(1): 41-51, 2020 01.
Artigo em Inglês | MEDLINE | ID: mdl-31520493

RESUMO

Individual sequencing studies often have limited sample sizes and so limited power to detect trait associations with rare variants. A common strategy is to aggregate data from multiple studies. For studying rare variants, jointly calling all samples together is the gold standard strategy but can be difficult to implement due to privacy restrictions and computational burden. Here, we compare joint calling to the alternative of single-study calling in terms of variant detection sensitivity and genotype accuracy as a function of sequencing coverage and assess their impact on downstream association analysis. To do so, we analyze deep-coverage (~82×) exome and low-coverage (~5×) genome sequence data on 2,250 individuals from the Genetics of Type 2 Diabetes study jointly and separately within five geographic cohorts. For rare single nucleotide variants (SNVs): (a) ≥97% of discovered SNVs are found by both calling strategies; (b) nonreference concordance with a set of highly accurate genotypes is ≥99% for both calling strategies; (c) meta-analysis has similar power to joint analysis in deep-coverage sequence data but can be less powerful in low-coverage sequence data. Given similar data processing and quality control steps, we recommend single-study calling as a viable alternative to joint calling for analyzing SNVs of all minor allele frequency in deep-coverage data.


Assuntos
Diabetes Mellitus Tipo 2/genética , Frequência do Gene/genética , Polimorfismo de Nucleotídeo Único/genética , Exoma/genética , Genótipo , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Humanos
11.
Biostatistics ; 2019 Dec 28.
Artigo em Inglês | MEDLINE | ID: mdl-31883325

RESUMO

Trans-ethnic meta-analysis is a powerful tool for detecting novel loci in genetic association studies. However, in the presence of heterogeneity among different populations, existing gene-/region-based rare variants meta-analysis methods may be unsatisfactory because they do not consider genetic similarity or dissimilarity among different populations. In response, we propose a score test under the modified random effects model for gene-/region-based rare variants associations. We adapt the kernel regression framework to construct the model and incorporate genetic similarities across populations into modeling the heterogeneity structure of the genetic effect coefficients. We use a resampling-based copula method to approximate asymptotic distribution of the test statistic, enabling efficient estimation of p-values. Simulation studies show that our proposed method controls type I error rates and increases power over existing approaches in the presence of heterogeneity. We illustrate our method by analyzing T2D-GENES consortium exome sequence data to explore rare variant associations with several traits.

12.
Hum Mol Genet ; 28(24): 4161-4172, 2019 12 15.
Artigo em Inglês | MEDLINE | ID: mdl-31691812

RESUMO

Integration of genome-wide association study (GWAS) signals with expression quantitative trait loci (eQTL) studies enables identification of candidate genes. However, evaluating whether nearby signals may share causal variants, termed colocalization, is affected by the presence of allelic heterogeneity, different variants at the same locus impacting the same phenotype. We previously identified eQTL in subcutaneous adipose tissue from 770 participants in the Metabolic Syndrome in Men (METSIM) study and detected 15 eQTL signals that colocalized with GWAS signals for waist-hip ratio adjusted for body mass index (WHRadjBMI) from the Genetic Investigation of Anthropometric Traits consortium. Here, we reevaluated evidence of colocalization using two approaches, conditional analysis and the Bayesian test COLOC, and show that providing COLOC with approximate conditional summary statistics at multi-signal GWAS loci can reconcile disagreements in colocalization classification between the two tests. Next, we performed conditional analysis on the METSIM subcutaneous adipose tissue data to identify conditionally distinct or secondary eQTL signals. We used the two approaches to test for colocalization with WHRadjBMI GWAS signals and evaluated the differences in colocalization classification between the two tests. Through these analyses, we identified four GWAS signals colocalized with secondary eQTL signals for FAM13A, SSR3, GRB14 and FMO1. Thus, at loci with multiple eQTL and/or GWAS signals, analyzing each signal independently enabled additional candidate genes to be identified.

14.
Am J Hum Genet ; 105(4): 773-787, 2019 10 03.
Artigo em Inglês | MEDLINE | ID: mdl-31564431

RESUMO

Genome-wide association studies (GWASs) have identified thousands of genetic loci associated with cardiometabolic traits including type 2 diabetes (T2D), lipid levels, body fat distribution, and adiposity, although most causal genes remain unknown. We used subcutaneous adipose tissue RNA-seq data from 434 Finnish men from the METSIM study to identify 9,687 primary and 2,785 secondary cis-expression quantitative trait loci (eQTL; <1 Mb from TSS, FDR < 1%). Compared to primary eQTL signals, secondary eQTL signals were located further from transcription start sites, had smaller effect sizes, and were less enriched in adipose tissue regulatory elements compared to primary signals. Among 2,843 cardiometabolic GWAS signals, 262 colocalized by LD and conditional analysis with 318 transcripts as primary and conditionally distinct secondary cis-eQTLs, including some across ancestries. Of cardiometabolic traits examined for adipose tissue eQTL colocalizations, waist-hip ratio (WHR) and circulating lipid traits had the highest percentage of colocalized eQTLs (15% and 14%, respectively). Among alleles associated with increased cardiometabolic GWAS risk, approximately half (53%) were associated with decreased gene expression level. Mediation analyses of colocalized genes and cardiometabolic traits within the 434 individuals provided further evidence that gene expression influences variant-trait associations. These results identify hundreds of candidate genes that may act in adipose tissue to influence cardiometabolic traits.


Assuntos
Tecido Adiposo/metabolismo , Diabetes Mellitus Tipo 2/genética , Expressão Gênica , Obesidade/genética , Alelos , Índice de Massa Corporal , Finlândia , Estudo de Associação Genômica Ampla , Humanos , Masculino , Locos de Características Quantitativas , Relação Cintura-Quadril
16.
Nature ; 572(7769): 323-328, 2019 08.
Artigo em Inglês | MEDLINE | ID: mdl-31367044

RESUMO

Exome-sequencing studies have generally been underpowered to identify deleterious alleles with a large effect on complex traits as such alleles are mostly rare. Because the population of northern and eastern Finland has expanded considerably and in isolation following a series of bottlenecks, individuals of these populations have numerous deleterious alleles at a relatively high frequency. Here, using exome sequencing of nearly 20,000 individuals from these regions, we investigate the role of rare coding variants in clinically relevant quantitative cardiometabolic traits. Exome-wide association studies for 64 quantitative traits identified 26 newly associated deleterious alleles. Of these 26 alleles, 19 are either unique to or more than 20 times more frequent in Finnish individuals than in other Europeans and show geographical clustering comparable to Mendelian disease mutations that are characteristic of the Finnish population. We estimate that sequencing studies of populations without this unique history would require hundreds of thousands to millions of participants to achieve comparable association power.


Assuntos
Estudos de Associação Genética/métodos , Predisposição Genética para Doença/genética , Variação Genética/genética , Locos de Características Quantitativas/genética , Sequenciamento Completo do Exoma , Alelos , HDL-Colesterol/genética , Análise por Conglomerados , Determinação de Ponto Final , Finlândia , Mapeamento Geográfico , Humanos , Herança Multifatorial/genética , Reprodutibilidade dos Testes
17.
Nat Genet ; 51(6): 957-972, 2019 06.
Artigo em Inglês | MEDLINE | ID: mdl-31152163

RESUMO

Chronic kidney disease (CKD) is responsible for a public health burden with multi-systemic complications. Through trans-ancestry meta-analysis of genome-wide association studies of estimated glomerular filtration rate (eGFR) and independent replication (n = 1,046,070), we identified 264 associated loci (166 new). Of these, 147 were likely to be relevant for kidney function on the basis of associations with the alternative kidney function marker blood urea nitrogen (n = 416,178). Pathway and enrichment analyses, including mouse models with renal phenotypes, support the kidney as the main target organ. A genetic risk score for lower eGFR was associated with clinically diagnosed CKD in 452,264 independent individuals. Colocalization analyses of associations with eGFR among 783,978 European-ancestry individuals and gene expression across 46 human tissues, including tubulo-interstitial and glomerular kidney compartments, identified 17 genes differentially expressed in kidney. Fine-mapping highlighted missense driver variants in 11 genes and kidney-specific regulatory variants. These results provide a comprehensive priority list of molecular targets for translational research.


Assuntos
Estudos de Associação Genética/métodos , Predisposição Genética para Doença , Locos de Características Quantitativas , Característica Quantitativa Herdável , Insuficiência Renal Crônica/genética , Insuficiência Renal Crônica/fisiopatologia , Mapeamento Cromossômico , Grupo com Ancestrais do Continente Europeu , Estudo de Associação Genômica Ampla , Taxa de Filtração Glomerular , Humanos , Padrões de Herança , Testes de Função Renal , Fenótipo , Polimorfismo de Nucleotídeo Único , Insuficiência Renal Crônica/urina , Uromodulina/urina
19.
Am J Hum Genet ; 105(1): 15-28, 2019 07 03.
Artigo em Inglês | MEDLINE | ID: mdl-31178129

RESUMO

Circulating levels of adiponectin, an adipocyte-secreted protein associated with cardiovascular and metabolic risk, are highly heritable. To gain insights into the biology that regulates adiponectin levels, we performed an exome array meta-analysis of 265,780 genetic variants in 67,739 individuals of European, Hispanic, African American, and East Asian ancestry. We identified 20 loci associated with adiponectin, including 11 that had been reported previously (p < 2 × 10-7). Comparison of exome array variants to regional linkage disequilibrium (LD) patterns and prior genome-wide association study (GWAS) results detected candidate variants (r2 > .60) spanning as much as 900 kb. To identify potential genes and mechanisms through which the previously unreported association signals act to affect adiponectin levels, we assessed cross-trait associations, expression quantitative trait loci in subcutaneous adipose, and biological pathways of nearby genes. Eight of the nine loci were also associated (p < 1 × 10-4) with at least one obesity or lipid trait. Candidate genes include PRKAR2A, PTH1R, and HDAC9, which have been suggested to play roles in adipocyte differentiation or bone marrow adipose tissue. Taken together, these findings provide further insights into the processes that influence circulating adiponectin levels.


Assuntos
Adiponectina/genética , Tecido Adiposo/patologia , Exoma/genética , Predisposição Genética para Doença , Lipídeos/análise , Obesidade/etiologia , Polimorfismo de Nucleotídeo Único , Tecido Adiposo/metabolismo , Adolescente , Adulto , Afro-Americanos/genética , Idoso , Idoso de 80 Anos ou mais , Grupo com Ancestrais do Continente Europeu/genética , Feminino , Hispano-Americanos/genética , Humanos , Masculino , Pessoa de Meia-Idade , Obesidade/patologia , Fenótipo , Locos de Características Quantitativas , Adulto Jovem
20.
J Am Heart Assoc ; 8(10): e011922, 2019 05 21.
Artigo em Inglês | MEDLINE | ID: mdl-31070104

RESUMO

Background Recent studies have revealed sexually dimorphic associations between the carbamoyl-phosphate synthase 1 locus, intermediates of the metabolic pathway leading from choline to urea, and risk of coronary artery disease ( CAD ) in women. Based on evidence from the literature, the atheroprotective association with carbamoyl-phosphate synthase 1 could be mediated by the strong genetic effect of this locus on increased circulating glycine levels. Methods and Results We sought to identify additional genetic determinants of circulating glycine levels by carrying out a meta-analysis of genome-wide association study data in up to 30 118 subjects of European ancestry. Mendelian randomization and other analytical approaches were used to determine whether glycine-associated variants were associated with CAD and traditional risk factors. Twelve loci were significantly associated with circulating glycine levels, 7 of which were not previously known to be involved in glycine metabolism ( ACADM , PHGDH , COX 18- ADAMTS 3, PSPH , TRIB 1, PTPRD , and ABO ). Glycine-raising alleles at several loci individually exhibited directionally consistent associations with decreased risk of CAD . However, these effects could not be attributed directly to glycine because of associations with other CAD -related traits. By comparison, genetic models that only included the 2 variants directly involved in glycine degradation and for which there were no other pleiotropic associations were not associated with risk of CAD or blood pressure, lipid levels, and obesity-related traits. Conclusions These results provide additional insight into the genetic architecture of glycine metabolism, but do not yield conclusive evidence for a causal relationship between circulating levels of this amino acid and risk of CAD in humans.

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