Dataset Information

Whole genome sequence analyses of eGFR in 23,732 people representing multiple ancestries in the NHLBI trans-omics for precision medicine (TOPMed) consortium.

ABSTRACT:

Background

Genetic factors that influence kidney traits have been understudied for low frequency and ancestry-specific variants.

Methods

We combined whole genome sequencing (WGS) data from 23,732 participants from 10 NHLBI Trans-Omics for Precision Medicine (TOPMed) Program multi-ethnic studies to identify novel loci for estimated glomerular filtration rate (eGFR). Participants included European, African, East Asian, and Hispanic ancestries. We applied linear mixed models using a genetic relationship matrix estimated from the WGS data and adjusted for age, sex, study, and ethnicity.

Findings

When testing single variants, we identified three novel loci driven by low frequency variants more commonly observed in non-European ancestry (PRKAA2, rs180996919, minor allele frequency [MAF] 0.04%, P = 6.1 × 10^-11; METTL8, rs116951054, MAF 0.09%, P = 4.5 × 10^-9; and MATK, rs539182790, MAF 0.05%, P = 3.4 × 10^-9). We also replicated two known loci for common variants (rs2461702, MAF=0.49, P = 1.2 × 10^-9, nearest gene GATM, and rs71147340, MAF=0.34, P = 3.3 × 10^-9, CDK12). Testing aggregated variants within a gene identified the MAF gene. A statistical approach based on local ancestry helped to identify replication samples for ancestry-specific variants.

Interpretation

This study highlights challenges in studying variants influencing kidney traits that are low frequency in populations and more common in non-European ancestry.

SUBMITTER: Lin BM

PROVIDER: S-EPMC7804602 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Publications

Whole genome sequence analyses of eGFR in 23,732 people representing multiple ancestries in the NHLBI trans-omics for precision medicine (TOPMed) consortium.

Lin Bridget M BM Grinde Kelsey E KE Brody Jennifer A JA Breeze Charles E CE Raffield Laura M LM Mychaleckyj Josyf C JC Thornton Timothy A TA Perry James A JA Baier Leslie J LJ de las Fuentes Lisa L Guo Xiuqing X Heavner Benjamin D BD Hanson Robert L RL Hung Yi-Jen YJ Qian Huijun H Hsiung Chao A CA Hwang Shih-Jen SJ Irvin Margaret R MR Jain Deepti D Kelly Tanika N TN Kobes Sayuko S Lange Leslie L Lash James P JP Li Yun Y Liu Xiaoming X Mi Xuenan X Musani Solomon K SK Papanicolaou George J GJ Parsa Afshin A Reiner Alex P AP Salimi Shabnam S Sheu Wayne H-H WH Shuldiner Alan R AR Taylor Kent D KD Smith Albert V AV Smith Jennifer A JA Tin Adrienne A Vaidya Dhananjay D Wallace Robert B RB Yamamoto Kenichi K Sakaue Saori S Matsuda Koichi K Kamatani Yoichiro Y Momozawa Yukihide Y Yanek Lisa R LR Young Betsi A BA Zhao Wei W Okada Yukinori Y Abecasis Gonzalo G Psaty Bruce M BM Arnett Donna K DK Boerwinkle Eric E Cai Jianwen J Yii-Der Chen Ida I Correa Adolfo A Cupples L Adrienne LA He Jiang J Kardia Sharon Lr SL Kooperberg Charles C Mathias Rasika A RA Mitchell Braxton D BD Nickerson Deborah A DA Turner Steve T ST Vasan Ramachandran S RS Rotter Jerome I JI Levy Daniel D Kramer Holly J HJ Köttgen Anna A Nhlbi Trans-Omics For Precision Medicine TOPMed Consortium TOPMed Kidney Working Group Rich Stephen S SS Lin Dan-Yu DY Browning Sharon R SR Franceschini Nora N

EBioMedicine 20210106

<h4>Background</h4>Genetic factors that influence kidney traits have been understudied for low frequency and ancestry-specific variants.<h4>Methods</h4>We combined whole genome sequencing (WGS) data from 23,732 participants from 10 NHLBI Trans-Omics for Precision Medicine (TOPMed) Program multi-ethnic studies to identify novel loci for estimated glomerular filtration rate (eGFR). Participants included European, African, East Asian, and Hispanic ancestries. We applied linear mixed models using a ...[more]

PMID: 33418499

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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:BackgroundMitochondria support critical cellular functions, such as energy production through oxidative phosphorylation, regulation of reactive oxygen species, apoptosis, and calcium homeostasis.ObjectiveGiven the heightened level of cellular activity in patients with asthma, we sought to determine whether mitochondrial DNA (mtDNA) copy number measured in peripheral blood differed between individuals with and without asthma.MethodsWhole genome sequence data was generated as part of the Trans-Omics for Precision Medicine (TOPMed) Program on participants from the Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-ethnicity (SAPPHIRE) and the Study of African Americans, Asthma, Genes, & Environment II (SAGE II). We restricted our analysis to individuals who self-identified as African American (3,651 asthma cases and 1,344 controls). Mitochondrial copy number was estimated using the sequencing read depth ratio for the mitochondrial and nuclear genomes. Respiratory complex expression was assessed using RNA-sequencing.ResultsAverage mitochondrial copy number was significantly higher among individuals with asthma when compared with controls (SAPPHIRE: 218.60 vs. 200.47, P<0.001; SAGE II: 235.99 vs. 223.07, P<0.001). Asthma status was significantly associated with mitochondrial copy number after accounting for potential explanatory variables, such as participant age, sex, leukocyte counts, and mitochondrial haplogroup. Despite the consistent relationship between asthma status and mitochondrial copy number, the latter was not associated with time-to-exacerbation or patient-reported asthma control. Mitochondrial respiratory complex gene expression was disproportionately lower in individuals with asthma when compared with individuals without asthma and other protein-encoding genes.ConclusionsWe observed a robust association between asthma and higher mitochondrial copy number. Asthma having an effect on mitochondria function was also supported by lower respiratory complex gene expression in this group.

Project description:BackgroundRisk for venous thromboembolism has a strong genetic component. Whole genome sequencing from the TOPMed program (Trans-Omics for Precision Medicine) allowed us to look for new associations, particularly rare variants missed by standard genome-wide association studies.MethodsThe 3793 cases and 7834 controls (11.6% of cases were individuals of African, Hispanic/Latino, or Asian ancestry) were analyzed using a single variant approach and an aggregate gene-based approach using our primary filter (included only loss-of-function and missense variants predicted to be deleterious) and our secondary filter (included all missense variants).ResultsSingle variant analyses identified associations at 5 known loci. Aggregate gene-based analyses identified only PROC (odds ratio, 6.2 for carriers of rare variants; P=7.4×10-14) when using our primary filter. Employing our secondary variant filter led to a smaller effect size at PROC (odds ratio, 3.8; P=1.6×10-14), while excluding variants found only in rare isoforms led to a larger one (odds ratio, 7.5). Different filtering strategies improved the signal for 2 other known genes: PROS1 became significant (minimum P=1.8×10-6 with the secondary filter), while SERPINC1 did not (minimum P=4.4×10-5 with minor allele frequency <0.0005). Results were largely the same when restricting the analyses to include only unprovoked cases; however, one novel gene, MS4A1, became significant (P=4.4×10-7 using all missense variants with minor allele frequency <0.0005).ConclusionsHere, we have demonstrated the importance of using multiple variant filtering strategies, as we detected additional genes when filtering variants based on their predicted deleteriousness, frequency, and presence on the most expressed isoforms. Our primary analyses did not identify new candidate loci; thus larger follow-up studies are needed to replicate the novel MS4A1 locus and to identify additional rare variation associated with venous thromboembolism.

Dataset Information

Whole genome sequence analyses of eGFR in 23,732 people representing multiple ancestries in the NHLBI trans-omics for precision medicine (TOPMed) consortium.

Background

Methods

Findings

Interpretation

Publications

Whole genome sequence analyses of eGFR in 23,732 people representing multiple ancestries in the NHLBI trans-omics for precision medicine (TOPMed) consortium.

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