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

Authors: Bridget M Lin; Kelsey E Grinde; Jennifer A Brody; Charles E Breeze; Laura M Raffield; Josyf C Mychaleckyj; Timothy A Thornton; +67 Authors

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

Abstract

Genetic factors that influence kidney traits have been understudied for low frequency and ancestry-specific variants.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.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.This study highlights challenges in studying variants influencing kidney traits that are low frequency in populations and more common in non-European ancestry.

Countries
United States, Germany
Keywords

Male, Medicine (General), Epidemiology, Clinical Sciences, 610, Clinical sciences, Polymorphism, Single Nucleotide, Ancestry-specific variants, Quantitative Trait, R5-920, Quantitative Trait, Heritable, Gene Frequency, Health Sciences, and Blood Institute (U.S.), Genetics, 2.1 Biological and endogenous factors, Humans, Genetic Predisposition to Disease, Public Health Surveillance, Aetiology, Polymorphism, Precision Medicine, Lung, Heritable, Kidney traits, Alleles, Whole Genome Sequencing, Human Genome, R, Rare variants, National Heart, Single Nucleotide, Genomics, United States, Good Health and Well Being, Whole genome sequencing, Public Health and Health Services, Medicine, National Heart, Lung, and Blood Institute (U.S.), Biotechnology, Research Paper, Genome-Wide Association Study, Glomerular Filtration Rate

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    Top 10%
    influence
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
23
Top 10%
Average
Top 10%
Green
gold