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

Lorraine Southam, Arthur Gilly, Dániel Süveges, Aliki-Eleni Farmaki, Jeremy Schwartzentruber, Ioanna Tachmazidou, Angela Matchan, Nigel W. Rayner, Emmanouil Tsafantakis, Maria Karaleftheri, Yali Xue, George Dedoussis and Eleftheria Zeggini ()
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Lorraine Southam: Wellcome Trust Sanger Institute
Arthur Gilly: Wellcome Trust Sanger Institute
Dániel Süveges: Wellcome Trust Sanger Institute
Aliki-Eleni Farmaki: School of Health Science and Education, Harokopio University
Jeremy Schwartzentruber: Wellcome Trust Sanger Institute
Ioanna Tachmazidou: Wellcome Trust Sanger Institute
Angela Matchan: Wellcome Trust Sanger Institute
Nigel W. Rayner: Wellcome Trust Sanger Institute
Emmanouil Tsafantakis: Anogia Medical Centre
Maria Karaleftheri: Echinos Medical Centre, Echinos
Yali Xue: Wellcome Trust Sanger Institute
George Dedoussis: School of Health Science and Education, Harokopio University
Eleftheria Zeggini: Wellcome Trust Sanger Institute

Nature Communications, 2017, vol. 8, issue 1, 1-11

Abstract: Abstract 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.

Date: 2017
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DOI: 10.1038/ncomms15606

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