> Detailanzeige

Lin, Bridget M [VerfasserIn]; Grinde, Kelsey E [VerfasserIn]; Köttgen, Anna [VerfasserIn]; Franceschini, Nora [VerfasserIn]

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

Literatur-
verwaltung

Zur
Merkliste

Lösche von
Merkliste

Per Whatsapp teilen

Schließen

Merkliste



Sie können Bookmarks mittels Listen verwalten, loggen Sie sich dafür bitte in Ihr SLUB Benutzerkonto ein.
  • Medientyp: E-Book; Sonderdruck
  • Titel: Whole genome sequence analyses of eGFR in 23,732 people representing multiple ancestries in the NHLBI trans-omics for precision medicine (TOPMed) consortium
  • Beteiligte: Lin, Bridget M [VerfasserIn]; Grinde, Kelsey E [VerfasserIn]; Köttgen, Anna [VerfasserIn]; Franceschini, Nora [VerfasserIn]
  • Erschienen: Amsterdam [u.a.]: Elsevier, 2021
  • Erschienen in: EBioMedicine ; 63 (2021), 103157
  • Umfang: 1 Online-Ressource (12 Seiten); Diagramme; Supplementary materials (1 ZIP-Datei: 1 .xlsx-Datei, 1 .docx-Datei)
  • Sprache: Englisch
  • DOI: 10.1016/j.ebiom.2020.103157
  • ISSN: 2352-3964
  • Identifikator:
  • Entstehung:
  • Anmerkungen:
  • Beschreibung: Abstract: Background<br>Genetic factors that influence kidney traits have been understudied for low frequency and ancestry-specific variants.<br><br>Methods<br>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.<br><br>Findings<br>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.<br><br>Interpretation<br>This study highlights challenges in studying variants influencing kidney traits that are low frequency in populations and more common in non-European ancestry
  • Zugangsstatus: Freier Zugang