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Use of >100,000 NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium whole genome sequences improves imputation quality and detection of rare variant associations in admixed African and Hispanic/Latino populations.

ABSTRACT: Most genome-wide association and fine-mapping studies to date have been conducted in individuals of European descent, and genetic studies of populations of Hispanic/Latino and African ancestry are limited. In addition, these populations have more complex linkage disequilibrium structure. In order to better define the genetic architecture of these understudied populations, we leveraged >100,000 phased sequences available from deep-coverage whole genome sequencing through the multi-ethnic NHLBI Trans-Omics for Precision Medicine (TOPMed) program to impute genotypes into admixed African and Hispanic/Latino samples with genome-wide genotyping array data. We demonstrated that using TOPMed sequencing data as the imputation reference panel improves genotype imputation quality in these populations, which subsequently enhanced gene-mapping power for complex traits. For rare variants with minor allele frequency (MAF) < 0.5%, we observed a 2.3- to 6.1-fold increase in the number of well-imputed variants, with 11-34% improvement in average imputation quality, compared to the state-of-the-art 1000 Genomes Project Phase 3 and Haplotype Reference Consortium reference panels. Impressively, even for extremely rare variants with minor allele count <10 (including singletons) in the imputation target samples, average information content rescued was >86%. Subsequent association analyses of TOPMed reference panel-imputed genotype data with hematological traits (hemoglobin (HGB), hematocrit (HCT), and white blood cell count (WBC)) in ~21,600 African-ancestry and ~21,700 Hispanic/Latino individuals identified associations with two rare variants in the HBB gene (rs33930165 with higher WBC [p = 8.8x10-15] in African populations, rs11549407 with lower HGB [p = 1.5x10-12] and HCT [p = 8.8x10-10] in Hispanics/Latinos). By comparison, neither variant would have been genome-wide significant if either 1000 Genomes Project Phase 3 or Haplotype Reference Consortium reference panels had been used for imputation. Our findings highlight the utility of the TOPMed imputation reference panel for identification of novel rare variant associations not previously detected in similarly sized genome-wide studies of under-represented African and Hispanic/Latino populations.

SUBMITTER: Kowalski MH

PROVIDER: S-EPMC6953885 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Use of >100,000 NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium whole genome sequences improves imputation quality and detection of rare variant associations in admixed African and Hispanic/Latino populations.

Kowalski Madeline H MH Qian Huijun H Hou Ziyi Z Rosen Jonathan D JD Tapia Amanda L AL Shan Yue Y Jain Deepti D Argos Maria M Arnett Donna K DK Avery Christy C Barnes Kathleen C KC Becker Lewis C LC Bien Stephanie A SA Bis Joshua C JC Blangero John J Boerwinkle Eric E Bowden Donald W DW Buyske Steve S Cai Jianwen J Cho Michael H MH Choi Seung Hoan SH Choquet Hélène H Cupples L Adrienne LA Cushman Mary M Daya Michelle M de Vries Paul S PS Ellinor Patrick T PT Faraday Nauder N Fornage Myriam M Gabriel Stacey S Ganesh Santhi K SK Graff Misa M Gupta Namrata N He Jiang J Heckbert Susan R SR Hidalgo Bertha B Hodonsky Chani J CJ Irvin Marguerite R MR Johnson Andrew D AD Jorgenson Eric E Kaplan Robert R Kardia Sharon L R SLR Kelly Tanika N TN Kooperberg Charles C Lasky-Su Jessica A JA Loos Ruth J F RJF Lubitz Steven A SA Mathias Rasika A RA McHugh Caitlin P CP Montgomery Courtney C Moon Jee-Young JY Morrison Alanna C AC Palmer Nicholette D ND Pankratz Nathan N Papanicolaou George J GJ Peralta Juan M JM Peyser Patricia A PA Rich Stephen S SS Rotter Jerome I JI Silverman Edwin K EK Smith Jennifer A JA Smith Nicholas L NL Taylor Kent D KD Thornton Timothy A TA Tiwari Hemant K HK Tracy Russell P RP Wang Tao T Weiss Scott T ST Weng Lu-Chen LC Wiggins Kerri L KL Wilson James G JG Yanek Lisa R LR Zöllner Sebastian S North Kari E KE Auer Paul L PL Raffield Laura M LM Reiner Alexander P AP Li Yun Y

PLoS genetics 20191223 12

Most genome-wide association and fine-mapping studies to date have been conducted in individuals of European descent, and genetic studies of populations of Hispanic/Latino and African ancestry are limited. In addition, these populations have more complex linkage disequilibrium structure. In order to better define the genetic architecture of these understudied populations, we leveraged >100,000 phased sequences available from deep-coverage whole genome sequencing through the multi-ethnic NHLBI Tr ...[more]

PMID: 31869403

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Project description:Aims/hypothesisThe Latino population has been systematically underrepresented in large-scale genetic analyses, and previous studies have relied on the imputation of ungenotyped variants based on the 1000 Genomes (1000G) imputation panel, which results in suboptimal capture of low-frequency or Latino-enriched variants. The National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) released the largest multi-ancestry genotype reference panel representing a unique opportunity to analyse rare genetic variations in the Latino population. We hypothesise that a more comprehensive analysis of low/rare variation using the TOPMed panel would improve our knowledge of the genetics of type 2 diabetes in the Latino population.MethodsWe evaluated the TOPMed imputation performance using genotyping array and whole-exome sequence data in six Latino cohorts. To evaluate the ability of TOPMed imputation to increase the number of identified loci, we performed a Latino type 2 diabetes genome-wide association study (GWAS) meta-analysis in 8150 individuals with type 2 diabetes and 10,735 control individuals and replicated the results in six additional cohorts including whole-genome sequence data from the All of Us cohort.ResultsCompared with imputation with 1000G, the TOPMed panel improved the identification of rare and low-frequency variants. We identified 26 genome-wide significant signals including a novel variant (minor allele frequency 1.7%; OR 1.37, p=3.4 × 10-9). A Latino-tailored polygenic score constructed from our data and GWAS data from East Asian and European populations improved the prediction accuracy in a Latino target dataset, explaining up to 7.6% of the type 2 diabetes risk variance.Conclusions/interpretationOur results demonstrate the utility of TOPMed imputation for identifying low-frequency variants in understudied populations, leading to the discovery of novel disease associations and the improvement of polygenic scores.Data availabilityFull summary statistics are available through the Common Metabolic Diseases Knowledge Portal ( https://t2d.hugeamp.org/downloads.html ) and through the GWAS catalog ( https://www.ebi.ac.uk/gwas/ , accession ID: GCST90255648). Polygenic score (PS) weights for each ancestry are available via the PGS catalog ( https://www.pgscatalog.org , publication ID: PGP000445, scores IDs: PGS003443, PGS003444 and PGS003445).

Project description:Colorectal cancer contributes to cancer-related deaths and health disparities in the Hispanic and Latino community. To probe both the biological and genetic bases of the disparities, we characterized features of colorectal cancer in terms of somatic alterations and genetic similarity. Specifically, we conducted a comprehensive genome-scale analysis of 67 Hispanic and Latino samples. We performed DNA exome sequencing for somatic mutations, somatic copy number alterations, and genetic similarity. We also performed RNA sequencing for differential gene expression, cellular pathways, and gene fusions. We analyzed all samples for 22 important CRC gene mutations, 8 gene amplifications, and 25 CRC gene fusions. Then, we compared our data from the Hispanic and Latino samples to publicly available, Non-Hispanic White (NHW) cohorts. According to our analyses, twenty-four percent of colorectal carcinomas were hypermutated when patients were of Peruvians-from-Lima-like (1KG-PEL-like) genetic similarity population from the 1000 genome project. Moreover, most of these cases occurred in patients who were less than fiay years old age at diagnosis. Excluding hypermutated tumors, approximately 55% of colon cancers and 58% of rectum cancers exhibited two similar features: 1) the paderns of genomic alterations; 2) percentage of 1KG-PEL-like. We analyzed all samples -- which had a median 1KG-PEL-like proportion of 55% -- for 22 important CRC gene mutations, 8 gene amplifications, and 25 CRC gene fusions. One notable example of a frequently observed gene mutation was SMAD4. Samples with SMAD4 alterations, which are known to support tumor growth and progression, had the highest 1KG-PEL-like proportion (63%). According to our results from risk association analyses and differential gene expression, SMAD4 alterations were significant when we compared Hispanic and Latino samples to NHW cohorts. Of the 8 drug-targetable amplifications, PIK3CA and PI3K exhibited an average 1KG-PEL-like of over 55%. Of the 25 relevant CRC gene fusions, targetable genes included ALK, FGFR1, RAF1, and PTPRK; PTPRK was observed in a sample with the highest 1KG-PEL-like proportion (95%). Using Integrative analysis, we also detected recurrent alterations in the WNT, TGFB, TP53, IGF2/PI3K, and RTK/RAS pathways. Importantly, these alterations mostly occurred in young patients with high 1KG-PEL-like. These findings highlight the potential for tailoring precision medicine therapeutics to an underrepresented population. Our study advances the molecular profiling of CRC in Hispanics and Latinos. In toto, genetic similarity appears to be an important component in understanding colorectal carcinogenesis and has the potential to advance cancer health disparities research.

Dataset Information

Use of >100,000 NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium whole genome sequences improves imputation quality and detection of rare variant associations in admixed African and Hispanic/Latino populations.

Publications

Use of >100,000 NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium whole genome sequences improves imputation quality and detection of rare variant associations in admixed African and Hispanic/Latino populations.

Similar Datasets

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