Genotype Imputation of <scp>M</scp>etabochip<scp>SNPs</scp> Using a Study‐Specific Reference Panel of ∼4,000 Haplotypes in <scp>A</scp>frican <scp>A</scp>mericans From the Women's Health Initiative

Liu, Eric Yi; Buyske, Steven; Aragaki, Aaron K.; Peters, Ulrike; Boerwinkle, Eric; Carlson, Chris; Carty, Cara L.; Crawford, Dana C.; Haessler, Jeff; Hindorff, Lucia A.; Marchand, Loı̈c Le; Manolio, Teri A.; Matise, Tara C.; Wang, Wei; Kooperberg, Charles; North, Kari E.; Li, Yun

doi:10.1002/gepi.21603

Cited by 61 publications

(70 citation statements)

References 41 publications

(49 reference statements)

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“…This corroborated the value of admixture mapping as a complementary approach to association mapping in admixed populations, which may uncover associations not detectable by SNP association tests alone [27]. The chromosome 6 local ancestry segment associated with asthma (after correcting for multiple tests) harbors the TCF21 gene which is differentially expressed in the bronchial tissues of asthmatics and nonasthmatics [22]. Because no SAPPHIRE controls were typed on the ADPC, asthmatic cases from SAPPHIRE were not included in the admixture mapping tests for association.…”

Section: Admixture Mappingsupporting

confidence: 57%

“…Genes falling in this segment include the Transcription Factor 21 (TCF21) and TATA-Box Binding Protein Like 1 (TBPL1) genes. The TCF21 gene has been shown to be differentially expressed in bronchial biopsies of asthmatics compared to controls [22].…”

Section: Admixture Mappingmentioning

confidence: 99%

“…http://dx.doi.org/10.1101/112953 doi: bioRxiv preprint first posted online Mar. 2, 2017; correlation between imputed allele dosages and true unknown genotypes (Rsq) [22]. SNPs with MAF ≤ 0.005 were excluded if Rsq ≤ 0.5 and SNPs with MAF > 0.005 were excluded if Rsq ≤ 0.3.…”

Section: Merging and Imputation Of Gwas And Adpc Datasetsmentioning

confidence: 99%

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Genome-wide association study of asthma in individuals of African ancestry reveals novel asthma susceptibility loci

Adegnika

Arinola

Ateba-Ngoa

et al. 2017

Preprint

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BACKGROUND:Asthma is a complex disease with striking disparities across racial and ethnic groups, which may be partly attributable to genetic factors. One of the main goals of the Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA) is to discover genes conferring risk to asthma in populations of African descent. METHODS:We performed a genome-wide meta-analysis of asthma across 11 CAAPA datasets (4,827 asthma cases and 5,397 controls), genotyped on the African Diaspora Power Chip (ADPC) and including existing GWAS array data. The genotype data were imputed up to a whole genome sequence reference panel from n=880 African ancestry individuals for a total of 61,904,576 SNPs. Statistical models appropriate to each study design were used to test for association, and results were combined using the weighted Z-score method. We also used admixture mapping as a complementary approach to identify loci involved in asthma pathogenesis in subjects of African ancestry. RESULTS: SNPs rs787160 and rs17834780 on chromosome 2q22.3 were significantly associated with asthma (p=6.57 × 10 -9 and 2.97 × 10 -8 , respectively). These SNPs lie in the intergenic region between the Rho GTPase Activating Protein 15 (ARHGAP15) and Glycosyltransferase Like Domain Containing 1 (GTDC1) genes. Four low frequency variants on chromosome 1q21.3, which may be involved in the "atopic march" and which are not polymorphic in Europeans, also showed evidence for association with asthma (1.18 ×10 -6 ≤ p ≤ 3.06 ×10 -6 ). SNP rs11264909 on chromosome 1q23.1, close to a region previously identified by the EVE asthma meta-analysis as having a putative African ancestry specific effect, only showed differences in counts in subjects homozygous for alleles of African ancestry. Admixture mapping also identified a significantly associated region on chromosome 6q23.2, which includes the Transcription Factor 21 (TCF21) gene, previously shown to be differentially expressed in bronchial tissues of asthmatics and non-asthmatics. CONCLUSIONS:We have identified a number of novel asthma association signals warranting further investigation.

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Section: Admixture Mappingsupporting

confidence: 57%

Section: Admixture Mappingmentioning

confidence: 99%

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Genome-wide association study of asthma in individuals of African ancestry reveals novel asthma susceptibility loci

Adegnika

Arinola

Ateba-Ngoa

et al. 2017

Preprint

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“…Genotyping on the MetaboChip was performed according to the manufacturer's protocol (Illumina). A portion of WHI African Americans had both MetaboChip and the Affymetrix 6.0 genotype data available from the SNP Health Association Resource (SHARe); this was used to impute MetaboChip SNPs in the remaining SHARe participants with only Affymetrix 6.0 GWAS (30). Samples of BioMe TM participants were genotyped using the Illumina HumanOmniExpressþ v1.1 and then imputed using haplotypes from the 1000 Genomes Project (31).…”

Section: Genotypingmentioning

confidence: 99%

Fine-mapping of lipid regions in global populations discovers ethnic-specific signals and refines previously identified lipid loci

Zubair

Graff²,

Ambite

et al. 2016

Human Molecular Genetics

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Genome-wide association studies have identified over 150 loci associated with lipid traits, however, no large-scale studies exist for Hispanics and other minority populations. Additionally, the genetic architecture of lipid-influencing loci remains largely unknown. We performed one of the most racially/ethnically diverse fine-mapping genetic studies of HDL-C, LDL-C, and triglycerides to-date using SNPs on the MetaboChip array on 54,119 individuals: 21,304 African Americans, 19,829 Hispanic Americans, 12,456 Asians, and 530 American Indians. The majority of signals found in these groups generalize to European Americans. While we uncovered signals unique to racial/ethnic populations, we also observed systematically consistent lipid associations across these groups. In African Americans, we identified three novel signals associated with HDL-C (LPL, APOA5, LCAT) and two associated with LDL-C (ABCG8, DHODH). In addition, using this population, we refined the location for 16 out of the 58 known MetaboChip lipid loci. These results can guide tailored screening efforts, reveal population-specific responses to lipid-lowering medications, and aid in the development of new targeted drug therapies.

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“…For example, a subset of the WHI African Americans was genotyped on Metabochip (28) and used as the reference panel to impute Metabochip variants for the remaining African Americans with GWAS data (29). In addition, the GWAS genotyping arrays can be replaced by the Metabochip (28) or the Exomechip (30), which can then be imputed against sequencing data (28).…”

Section: Discussionmentioning

confidence: 99%

Integrative analysis of sequencing and array genotype data for discovering disease associations with rare mutations

Auer

et al. 2015

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

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In the large cohorts that have been used for genome-wide association studies (GWAS), it is prohibitively expensive to sequence all cohort members. A cost-effective strategy is to sequence subjects with extreme values of quantitative traits or those with specific diseases. By imputing the sequencing data from the GWAS data for the cohort members who are not selected for sequencing, one can dramatically increase the number of subjects with information on rare variants. However, ignoring the uncertainties of imputed rare variants in downstream association analysis will inflate the type I error when sequenced subjects are not a random subset of the GWAS subjects. In this article, we provide a valid and efficient approach to combining observed and imputed data on rare variants. We consider commonly used gene-level association tests, all of which are constructed from the score statistic for assessing the effects of individual variants on the trait of interest. We show that the score statistic based on the observed genotypes for sequenced subjects and the imputed genotypes for nonsequenced subjects is unbiased. We derive a robust variance estimator that reflects the true variability of the score statistic regardless of the sampling scheme and imputation quality, such that the corresponding association tests always have correct type I error. We demonstrate through extensive simulation studies that the proposed tests are substantially more powerful than the use of accurately imputed variants only and the use of sequencing data alone. We provide an application to the Women's Health Initiative. The relevant software is freely available. data integration | gene-level association tests | genotype imputation | linkage disequilibrium | whole-exome sequencing R ecent technological advances have made it possible to conduct high-throughput DNA sequencing studies on rare variants, which have a stronger impact on complex diseases and traits than common variants (1). However, it is still economically infeasible to sequence all subjects in a large cohort, and, therefore, only a subset of cohort members can be selected for sequencing. A cost-effective sampling strategy is to preferentially select subjects in the extremes of a quantitative trait distribution or those with a specific disease (2, 3). For case−control studies, an equal number of cases and controls provides more power than other case−control ratios. For quantitative traits, the power increases as more extreme values are sampled (2).Trait-dependent sampling has been adopted in many sequencing studies, including the National Heart, Lung, and Blood Institute (NHLBI) Exome Sequencing Project (ESP) and the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) resequencing project. The NHLBI ESP consists of three studies that sequenced subjects with the largest and smallest values of body mass index (BMI), low-density lipoprotein, and blood pressure, one case−control study on myocardial infarction, and one case-only study on stroke (2). The CHARGE resequencing pr...

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Genotype Imputation of MetabochipSNPs Using a Study‐Specific Reference Panel of ∼4,000 Haplotypes in African Americans From the Women's Health Initiative

Cited by 61 publications

References 41 publications

Genome-wide association study of asthma in individuals of African ancestry reveals novel asthma susceptibility loci

Genome-wide association study of asthma in individuals of African ancestry reveals novel asthma susceptibility loci

Fine-mapping of lipid regions in global populations discovers ethnic-specific signals and refines previously identified lipid loci

Integrative analysis of sequencing and array genotype data for discovering disease associations with rare mutations

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