Dataset Information

The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes.

ABSTRACT:

Aims/hypothesis

The 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.

Methods

We 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.

Results

Compared 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/interpretation

Our 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 availability

Full 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).

SUBMITTER: Huerta-Chagoya A

PROVIDER: S-EPMC10244266 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

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Publications

The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes.

Huerta-Chagoya Alicia A Schroeder Philip P Mandla Ravi R Deutsch Aaron J AJ Zhu Wanying W Petty Lauren L Yi Xiaoyan X Cole Joanne B JB Udler Miriam S MS Dornbos Peter P Porneala Bianca B DiCorpo Daniel D Liu Ching-Ti CT Li Josephine H JH Szczerbiński Lukasz L Kaur Varinderpal V Kim Joohyun J Lu Yingchang Y Martin Alicia A Eizirik Decio L DL Marchetti Piero P Marselli Lorella L Chen Ling L Srinivasan Shylaja S Todd Jennifer J Flannick Jason J Gubitosi-Klug Rose R Levitsky Lynne L Shah Rachana R Kelsey Megan M Burke Brian B Dabelea Dana M DM Divers Jasmin J Marcovina Santica S Stalbow Lauren L Loos Ruth J F RJF Darst Burcu F BF Kooperberg Charles C Raffield Laura M LM Haiman Christopher C Sun Quan Q McCormick Joseph B JB Fisher-Hoch Susan P SP Ordoñez Maria L ML Meigs James J Baier Leslie J LJ González-Villalpando Clicerio C González-Villalpando Maria Elena ME Orozco Lorena L García-García Lourdes L Moreno-Estrada Andrés A Aguilar-Salinas Carlos A CA Tusié Teresa T Dupuis Josée J Ng Maggie C Y MCY Manning Alisa A Highland Heather M HM Cnop Miriam M Hanson Robert R Below Jennifer J Florez Jose C JC Leong Aaron A Mercader Josep M JM

Diabetologia 20230506 7

<h4>Aims/hypothesis</h4>The 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 ...[more]

PMID: 37148359

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Project description: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.

Project description:BackgroundThe epilepsies are highly heritable conditions that commonly follow complex inheritance. While monogenic causes have been identified in rare familial epilepsies, most familial epilepsies remain unsolved. We aimed to determine (1) whether common genetic variation contributes to familial epilepsy risk, and (2) whether that genetic risk is enriched in familial compared with non-familial (sporadic) epilepsies.MethodsUsing common variants derived from the largest epilepsy genome-wide association study, we calculated polygenic risk scores (PRS) for patients with familial epilepsy (n = 1,818 from 1,181 families), their unaffected relatives (n = 771), sporadic patients (n = 1,182), and population controls (n = 15,929). We also calculated separate PRS for genetic generalised epilepsy (GGE) and focal epilepsy. Statistical analyses used mixed-effects regression models to account for familial relatedness, sex, and ancestry.FindingsPatients with familial epilepsies had higher epilepsy PRS compared to population controls (OR 1·20, padj = 5×10-9), sporadic patients (OR 1·11, padj = 0.008), and their own unaffected relatives (OR 1·12, padj = 0.01). The top 1% of the PRS distribution was enriched 3.8-fold for individuals with familial epilepsy when compared to the lowest decile (padj = 5×10-11). Familial PRS enrichment was consistent across epilepsy type; overall, polygenic risk was greatest for the GGE clinical group. There was no significant PRS difference in familial cases with established rare variant genetic etiologies compared to unsolved familial cases.InterpretationThe aggregate effects of common genetic variants, measured as polygenic risk scores, play an important role in explaining why some families develop epilepsy, why specific family members are affected while their relatives are not, and why families manifest specific epilepsy types. Polygenic risk contributes to the complex inheritance of the epilepsies, including in individuals with a known genetic etiology.FundingNational Health and Medical Research Council of Australia, National Institutes of Health, American Academy of Neurology, Thomas B and Jeannette E Laws McCabe Fund, Mirowski Family Foundation.

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Dataset Information

The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes.

Aims/hypothesis

Methods

Results

Conclusions/interpretation

Data availability

Publications

The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes.

Similar Datasets

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