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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.


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]

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