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Transancestral fine-mapping of four type 2 diabetes susceptibility loci highlights potential causal regulatory mechanisms.

ABSTRACT: To gain insight into potential regulatory mechanisms through which the effects of variants at four established type 2 diabetes (T2D) susceptibility loci (CDKAL1, CDKN2A-B, IGF2BP2 and KCNQ1) are mediated, we undertook transancestral fine-mapping in 22 086 cases and 42 539 controls of East Asian, European, South Asian, African American and Mexican American descent. Through high-density imputation and conditional analyses, we identified seven distinct association signals at these four loci, each with allelic effects on T2D susceptibility that were homogenous across ancestry groups. By leveraging differences in the structure of linkage disequilibrium between diverse populations, and increased sample size, we localised the variants most likely to drive each distinct association signal. We demonstrated that integration of these genetic fine-mapping data with genomic annotation can highlight potential causal regulatory elements in T2D-relevant tissues. These analyses provide insight into the mechanisms through which T2D association signals are mediated, and suggest future routes to understanding the biology of specific disease susceptibility loci.

SUBMITTER: Horikoshi M

PROVIDER: S-EPMC5062576 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

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Transancestral fine-mapping of four type 2 diabetes susceptibility loci highlights potential causal regulatory mechanisms.

Horikoshi Momoko M Pasquali Lorenzo L Wiltshire Steven S Huyghe Jeroen R JR Mahajan Anubha A Asimit Jennifer L JL Ferreira Teresa T Locke Adam E AE Robertson Neil R NR Wang Xu X Sim Xueling X Fujita Hayato H Hara Kazuo K Young Robin R Zhang Weihua W Choi Sungkyoung S Chen Han H Kaur Ismeet I Takeuchi Fumihiko F Fontanillas Pierre P Thuillier Dorothée D Yengo Loic L Below Jennifer E JE Tam Claudia H T CH Wu Ying Y Abecasis Gonçalo G Altshuler David D Bell Graeme I GI Blangero John J Burtt Noél P NP Duggirala Ravindranath R Florez Jose C JC Hanis Craig L CL Seielstad Mark M Atzmon Gil G Chan Juliana C N JC Ma Ronald C W RC Froguel Philippe P Wilson James G JG Bharadwaj Dwaipayan D Dupuis Josee J Meigs James B JB Cho Yoon Shin YS Park Taesung T Kooner Jaspal S JS Chambers John C JC Saleheen Danish D Kadowaki Takashi T Tai E Shyong ES Mohlke Karen L KL Cox Nancy J NJ Ferrer Jorge J Zeggini Eleftheria E Kato Norihiro N Teo Yik Ying YY Boehnke Michael M McCarthy Mark I MI Morris Andrew P AP

Human molecular genetics 20160223 10

To gain insight into potential regulatory mechanisms through which the effects of variants at four established type 2 diabetes (T2D) susceptibility loci (CDKAL1, CDKN2A-B, IGF2BP2 and KCNQ1) are mediated, we undertook transancestral fine-mapping in 22 086 cases and 42 539 controls of East Asian, European, South Asian, African American and Mexican American descent. Through high-density imputation and conditional analyses, we identified seven distinct association signals at these four loci, each w ...[more]

PMID: 26911676

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Project description:Heritable diseases often manifest in a highly tissue-specific manner, with different disease loci mediated by genes in distinct tissues or cell types. We propose Tissue-Gene Fine-Mapping (TGFM), a fine-mapping method that infers the posterior probability (PIP) for each gene-tissue pair to mediate a disease locus by analyzing GWAS summary statistics (and in-sample LD) and leveraging eQTL data from diverse tissues to build cis-predicted expression models; TGFM also assigns PIPs to causal variants that are not mediated by gene expression in assayed genes and tissues. TGFM accounts for both co-regulation across genes and tissues and LD between SNPs (generalizing existing fine-mapping methods), and incorporates genome-wide estimates of each tissue's contribution to disease as tissue-level priors. TGFM was well-calibrated and moderately well-powered in simulations; unlike previous methods, TGFM was able to attain correct calibration by modeling uncertainty in cis-predicted expression models. We applied TGFM to 45 UK Biobank diseases/traits (average N=316K) using eQTL data from 38 GTEx tissues. TGFM identified an average of 147 PIP > 0.5 causal genetic elements per disease/trait, of which 11% were gene-tissue pairs. Implicated gene-tissue pairs were concentrated in known disease-critical tissues, and causal genes were strongly enriched in disease-relevant gene sets. Causal gene-tissue pairs identified by TGFM recapitulated known biology (e.g., TPO-thyroid for Hypothyroidism), but also included biologically plausible novel findings (e.g., SLC20A2-artery aorta for Diastolic blood pressure). Further application of TGFM to single-cell eQTL data from 9 cell types in peripheral blood mononuclear cells (PBMC), analyzed jointly with GTEx tissues, identified 30 additional causal gene-PBMC cell type pairs at PIP > 0.5-primarily for autoimmune disease and blood cell traits, including the well-established role of CTLA4 in CD8+ T cells for All autoimmune disease. In conclusion, TGFM is a robust and powerful method for fine-mapping causal tissues and genes at disease-associated loci.

Project description:Coronary artery disease (CAD) is the leading cause of mortality and morbidity driven by both genetic and environmental risk factors. Meta-analyses of genome-wide association studies (GWAS) have identified multiple single nucleotide polymorphisms (SNPs) associated with CAD and myocardial infarction (MI) susceptibility in multi-ethnic populations. The majority of these variants reside in non-coding regulatory regions and are co-inherited with hundreds of candidate regulatory SNPs. Herein, we use integrative genomic, epigenomic, and transcriptomic fine-mapping in human coronary artery smooth muscle cells (HCASMC) and tissues to identify causal regulatory variation and mechanisms responsible for CAD associations. Using these genome-wide maps we prioritize 65 candidate variants and perform allele-specific binding and expression analyses on 7 top candidates. We validate our findings in two independent cohorts of diseased human arterial expression quantitative trait loci (eQTL), which together demonstrate fundamental links between CAD associations and regulatory function in the appropriate disease context. We performed ATAC-seq, ChIP-seq, and RNA-seq on human coronary artery smooth muscle cells grown in SmGM-2 Smooth Muscle Growth Medium-2 including hEGF, insulin, hFGF-B and FBS, but without antibiotics (Lonza, #CC-3182). For ATAC-seq and RNA-seq we performed stimulations with growth factors (TGF-B1, PDGF-BB, PDGF-DD) versus serum-free control. We conducted two biological replicates for each condition using independent donors. For ATAC-seq experiments, sequencing was completed on an Illumina Hiseq 2500, paired-end 50bp reads. For ChIP-seq we performed immunoprecipitations using H3K27ac (Abcam ab4729). We conducted two biological replicates using HCASMC from independent donors, and also did an IgG control for these studies. For RNA-seq we also conducted two replicates using HCASMC from independent donors. For both ChIP-seq and RNA-seq experiments, sequencing was completed on an Illumina HiSeq 2500, paired-end 100bp reads. We also performed ex-vivo ATAC-seq on frozen tissues (isolated media) from normal and atherosclerotic human coronary arteries, using three independent donors for each. Sequencing was also completed on an Illumina HiSeq 2500, paired end 50bp reads.

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Transancestral fine-mapping of four type 2 diabetes susceptibility loci highlights potential causal regulatory mechanisms.

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Transancestral fine-mapping of four type 2 diabetes susceptibility loci highlights potential causal regulatory mechanisms.

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