129 research outputs found

    Development of admixture mapping panels for African Americans from commercial high-density SNP arrays

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    <p>Abstract</p> <p>Background</p> <p>Admixture mapping is a powerful approach for identifying genetic variants involved in human disease that exploits the unique genomic structure in recently admixed populations. To use existing published panels of ancestry-informative markers (AIMs) for admixture mapping, markers have to be genotyped <it>de novo </it>for each admixed study sample and samples representing the ancestral parental populations. The increased availability of dense marker data on commercial chips has made it feasible to develop panels wherein the markers need not be predetermined.</p> <p>Results</p> <p>We developed two panels of AIMs (~2,000 markers each) based on the Affymetrix Genome-Wide Human SNP Array 6.0 for admixture mapping with African American samples. These two AIM panels had good map power that was higher than that of a denser panel of ~20,000 random markers as well as other published panels of AIMs. As a test case, we applied the panels in an admixture mapping study of hypertension in African Americans in the Washington, D.C. metropolitan area.</p> <p>Conclusions</p> <p>Developing marker panels for admixture mapping from existing genome-wide genotype data offers two major advantages: (1) no <it>de novo </it>genotyping needs to be done, thereby saving costs, and (2) markers can be filtered for various quality measures and replacement markers (to minimize gaps) can be selected at no additional cost. Panels of carefully selected AIMs have two major advantages over panels of random markers: (1) the map power from sparser panels of AIMs is higher than that of ~10-fold denser panels of random markers, and (2) clusters can be labeled based on information from the parental populations. With current technology, chip-based genome-wide genotyping is less expensive than genotyping ~20,000 random markers. The major advantage of using random markers is the absence of ascertainment effects resulting from the process of selecting markers. The ability to develop marker panels informative for ancestry from SNP chip genotype data provides a fresh opportunity to conduct admixture mapping for disease genes in admixed populations when genome-wide association data exist or are planned.</p

    Genome-wide association study of type 2 diabetes in Africa

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    Abstract: Aims/hypothesis: Genome-wide association studies (GWAS) for type 2 diabetes have uncovered >400 risk loci, primarily in populations of European and Asian ancestry. Here, we aimed to discover additional type 2 diabetes risk loci (including African-specific variants) and fine-map association signals by performing genetic analysis in African populations. Methods: We conducted two type 2 diabetes genome-wide association studies in 4347 Africans from South Africa, Nigeria, Ghana and Kenya and meta-analysed both studies together. Likely causal variants were identified using fine-mapping approaches. Results: The most significantly associated variants mapped to the widely replicated type 2 diabetes risk locus near TCF7L2 (p = 5.3 × 10−13). Fine-mapping of the TCF7L2 locus suggested one type 2 diabetes association signal shared between Europeans and Africans (indexed by rs7903146) and a distinct African-specific signal (indexed by rs17746147). We also detected one novel signal, rs73284431, near AGMO (p = 5.2 × 10−9, minor allele frequency [MAF] = 0.095; monomorphic in most non-African populations), distinct from previously reported signals in the region. In analyses focused on 100 published type 2 diabetes risk loci, we identified 21 with shared causal variants in African and non-African populations. Conclusions/interpretation: These results demonstrate the value of performing GWAS in Africans, provide a resource to larger consortia for further discovery and fine-mapping and indicate that additional large-scale efforts in Africa are warranted to gain further insight in to the genetic architecture of type 2 diabetes

    Refining the impact of TCF7L2 gene variants on type 2 diabetes and adaptive evolution

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    To access publisher full text version of this article. Please click on the hyperlink in Additional Links fieldWe recently described an association between risk of type 2diabetes and variants in the transcription factor 7-like 2 gene (TCF7L2; formerly TCF4), with a population attributable risk (PAR) of 17%-28% in three populations of European ancestry. Here, we refine the definition of the TCF7L2 type 2diabetes risk variant, HapB(T2D), to the ancestral T allele of a SNP, rs7903146, through replication in West African and Danish type 2 diabetes case-control studies and an expanded Icelandic study. We also identify another variant of the same gene, HapA, that shows evidence of positive selection in East Asian, European and West African populations. Notably, HapA shows a suggestive association with body mass index and altered concentrations of the hunger-satiety hormones ghrelin and leptin in males, indicating that the selective advantage of HapA may have been mediated through effects on energy metabolism

    The African Genome Variation Project shapes medical genetics in Africa.

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    Given the importance of Africa to studies of human origins and disease susceptibility, detailed characterization of African genetic diversity is needed. The African Genome Variation Project provides a resource with which to design, implement and interpret genomic studies in sub-Saharan Africa and worldwide. The African Genome Variation Project represents dense genotypes from 1,481 individuals and whole-genome sequences from 320 individuals across sub-Saharan Africa. Using this resource, we find novel evidence of complex, regionally distinct hunter-gatherer and Eurasian admixture across sub-Saharan Africa. We identify new loci under selection, including loci related to malaria susceptibility and hypertension. We show that modern imputation panels (sets of reference genotypes from which unobserved or missing genotypes in study sets can be inferred) can identify association signals at highly differentiated loci across populations in sub-Saharan Africa. Using whole-genome sequencing, we demonstrate further improvements in imputation accuracy, strengthening the case for large-scale sequencing efforts of diverse African haplotypes. Finally, we present an efficient genotype array design capturing common genetic variation in Africa

    Uganda Genome Resource Enables Insights into Population History and Genomic Discovery in Africa.

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    Genomic studies in African populations provide unique opportunities to understand disease etiology, human diversity, and population history. In the largest study of its kind, comprising genome-wide data from 6,400 individuals and whole-genome sequences from 1,978 individuals from rural Uganda, we find evidence of geographically correlated fine-scale population substructure. Historically, the ancestry of modern Ugandans was best represented by a mixture of ancient East African pastoralists. We demonstrate the value of the largest sequence panel from Africa to date as an imputation resource. Examining 34 cardiometabolic traits, we show systematic differences in trait heritability between European and African populations, probably reflecting the differential impact of genes and environment. In a multi-trait pan-African GWAS of up to 14,126 individuals, we identify novel loci associated with anthropometric, hematological, lipid, and glycemic traits. We find that several functionally important signals are driven by Africa-specific variants, highlighting the value of studying diverse populations across the region.Main funding: This work was funded by the Wellcome Trust, The Wellcome Sanger Institute (WT098051), the U.K. Medical Research Council (G0901213-92157, G0801566, and MR/K013491/1), and the Medical Research Council/Uganda Virus Research Institute Uganda Research Unit on AIDS core funding

    UGT1A1 is a major locus influencing bilirubin levels in African Americans

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    Total serum bilirubin is associated with several clinical outcomes, including cardiovascular disease, diabetes and drug metabolism. We conducted a genome-wide association study in 619 healthy unrelated African Americans in an attempt to replicate reported findings in Europeans and Asians and to identify novel loci influencing total serum bilirubin levels. We analyzed a dense panel of over two million genotyped and imputed SNPs in additive genetic models adjusting for age, sex, and the first two significant principal components from the sample covariance matrix of genotypes. Thirty-nine SNPs spanning a 78 kb region within the UGT1A1 displayed P-values <5 × 10−8. The lowest P-value was 1.7 × 10−22 for SNP rs887829. None of SNPs in the UGT1A1 remained statistically significant in conditional association analyses that adjusted for rs887829. In addition, SNP rs10929302 located in phenobarbital response enhancer module was significantly associated with bilirubin level with a P-value of 1.37 × 10−11; this enhancer module is believed to have a critical role in phenobarbital treatment of hyperbilirubinemia. Interestingly, the lead SNP, rs887829, is in strong linkage disequilibrium (LD) (r2≥0.74) with rs10929302. Taking advantage of the lower LD and shorter haplotypes in African-ancestry populations, we identified rs887829 as a more refined proxy for the causative variant influencing bilirubin levels. Also, we replicated the reported association between variants in SEMA3C and bilirubin levels. In summary, UGT1A1 is a major locus influencing bilirubin levels and the results of this study promise to contribute to understanding of the etiology and treatment of hyperbilirubinaemia in African-ancestry populations
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