Whole-genome sequencing analysis identifies rare, large-effect noncoding variants and regulatory regions associated with circulating protein levels

The contribution of rare noncoding genetic variation to common phenotypes is largely unknown, as a result of a historical lack of population-scale whole-genome sequencing data and the difficulty of categorizing noncoding variants into functionally similar groups. To begin addressing these challenges, we performed a cis association analysis using whole-genome sequencing data, consisting of 1.1 billion variants, 123 million noncoding aggregate-based tests and 2,907 circulating protein levels in ~50,000 UK Biobank participants. We identified 604 independent rare noncoding single-variant associations with circulating protein levels. Unlike protein-coding variation, rare noncoding genetic variation was almost as likely to increase or decrease protein levels. Rare noncoding aggregate testing identified 357 conditionally independent associated regions. Of these, 74 (21%) were not detectable by single-variant testing alone. Our findings have important implications for the identification, and role, of rare noncoding genetic variation associated with common human phenotypes, including the importance of testing aggregates of noncoding variants.

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Publication Details

Journal
Nature Genetics
Published
2025-02-24
DOI
https://doi.org/10.1038/s41588-025-02095-4
Citations
12
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
21.81

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article

Whole-genome sequencing analysis identifies rare, large-effect noncoding variants and regulatory regions associated with circulating protein levels

V. Kartik Chundru, Timothy M. Frayling, Andrew R. Wood, Anna Murray et al.
12 citations
Nature Genetics
Genetic Associations and Epidemiology
21.81
article

Whole-genome sequencing analysis identifies rare, large-effect noncoding variants and regulatory regions associated with circulating protein levels

V. Kartik Chundru, Timothy M. Frayling, Andrew R. Wood, Anna Murray, Caroline F. Wright, Robin N. Beaumont, Leigh Jackson, Gareth Hawkes, Kashyap Patel, Michael N. Weedon
article en
12 citations

Abstract

The contribution of rare noncoding genetic variation to common phenotypes is largely unknown, as a result of a historical lack of population-scale whole-genome sequencing data and the difficulty of categorizing noncoding variants into functionally similar groups. To begin addressing these challenges, we performed a cis association analysis using whole-genome sequencing data, consisting of 1.1 billion variants, 123 million noncoding aggregate-based tests and 2,907 circulating protein levels in ~50,000 UK Biobank participants. We identified 604 independent rare noncoding single-variant associations with circulating protein levels. Unlike protein-coding variation, rare noncoding genetic variation was almost as likely to increase or decrease protein levels. Rare noncoding aggregate testing identified 357 conditionally independent associated regions. Of these, 74 (21%) were not detectable by single-variant testing alone. Our findings have important implications for the identification, and role, of rare noncoding genetic variation associated with common human phenotypes, including the importance of testing aggregates of noncoding variants.

Nature GeneticsVol. 57(3)
University of Geneva (CH), University of Exeter (GB)
Wellcome Trust, European Federation of Pharmaceutical Industries and Associations, National Institute for Health and Care Research, British Heart Foundation, Department of Health and Social Care, Diabetes UK, University of Exeter, European Commission, Medical Research Council, Biotechnology and Biological Sciences Research Council
Openalex Percentile: Top 0%
Genetic Associations and Epidemiology
21.81
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