PuSH - Publikationsserver des Helmholtz Zentrums München

Southam, L.* ; Gilly, A.* ; Süveges, D.* ; Farmaki, A.E.* ; Schwartzentruber, J.* ; Tachmazidou, I.* ; Matchan, A.* ; Rayner, N.W.* ; Tsafantakis, E.* ; Karaleftheri, M.* ; Xue, Y.* ; Dedoussis, G.* ; Zeggini, E.

Whole genome sequencing and imputation in isolated populations identify genetic associations with medically-relevant complex traits.

Nat. Commun. 8:15606 (2017)
Verlagsversion DOI
Creative Commons Lizenzvertrag
Next-generation association studies can be empowered by sequence-based imputation and by studying founder populations. Here we report ∼9.5 million variants from whole-genome sequencing (WGS) of a Cretan-isolated population, and show enrichment of rare and low-frequency variants with predicted functional consequences. We use a WGS-based imputation approach utilizing 10,422 reference haplotypes to perform genome-wide association analyses and observe 17 genome-wide significant, independent signals, including replicating evidence for association at eight novel low-frequency variant signals. Two novel cardiometabolic associations are at lead variants unique to the founder population sequences: chr16:70790626 (high-density lipoprotein levels beta -1.71 (SE 0.25), P=1.57 × 10-11, effect allele frequency (EAF) 0.006); and rs145556679 (triglycerides levels beta -1.13 (SE 0.17), P=2.53 × 10-11, EAF 0.013). Our findings add empirical support to the contribution of low-frequency variants in complex traits, demonstrate the advantage of including population-specific sequences in imputation panels and exemplify the power gains afforded by population isolates.
Weitere Metriken?
Zusatzinfos bearbeiten [➜Einloggen]
Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
ISSN (print) / ISBN 2041-1723
e-ISSN 2041-1723
Zeitschrift Nature Communications
Quellenangaben Band: 8, Heft: , Seiten: , Artikelnummer: 15606 Supplement: ,
Verlag Nature Publishing Group
Verlagsort London
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Translational Genomics (ITG)