Whole-genome sequencing in 333,100 individuals reveals rare non-coding single variant and aggregate associations with height

The role of rare non-coding variation in complex human phenotypes is still largely unknown. To elucidate the impact of rare variants in regulatory elements, we performed a whole-genome sequencing association analysis for height using 333,100 individuals from three datasets: UK Biobank (N = 200,003), TOPMed (N = 87,652) and All of Us (N = 45,445). We performed rare ( < 0.1% minor-allele-frequency) single-variant and aggregate testing of non-coding variants in regulatory regions based on proximal-regulatory, intergenic-regulatory and deep-intronic annotation. We observed 29 independent variants associated with height at P < <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mn>6</mml:mn> <mml:mo>×</mml:mo> <mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow> <mml:mrow><mml:mo>-</mml:mo> <mml:mn>10</mml:mn></mml:mrow> </mml:msup> </mml:math> after conditioning on previously reported variants, with effect sizes ranging from -7cm to +4.7 cm. We also identified and replicated non-coding aggregate-based associations proximal to HMGA1 containing variants associated with a 5 cm taller height and of highly-conserved variants in MIR497HG on chromosome 17. We have developed an approach for identifying non-coding rare variants in regulatory regions with large effects from whole-genome sequencing data associated with complex traits.

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Publication Details

Journal
Nature Communications
Published
2024-10-03
DOI
https://doi.org/10.1038/s41467-024-52579-w
Citations
28
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
15.41

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article

Whole-genome sequencing in 333,100 individuals reveals rare non-coding single variant and aggregate associations with height

Bruce M. Psaty, Charles Kooperberg, Take Naseri, Kathleen C. Barnes et al.
28 citations
Nature Communications
Genetic Associations and Epidemiology
15.41
article

Whole-genome sequencing in 333,100 individuals reveals rare non-coding single variant and aggregate associations with height

Bruce M. Psaty, Charles Kooperberg, Take Naseri, Kathleen C. Barnes, Aneel A. Ashrani, Victor R. Gordeuk, Ruth J. F. Loos, Chii‐Min Hwu, Timothy M. Frayling, Andrew R. Wood, Braxton D. Mitchell, Xihong Lin, Dawood Darbar, Satupaitea Viali, Edwin K. Silverman, Alisa K. Manning, Joanne M. Murabito, Rita Rastogi Kalyani, Steven A. Lubitz, Anna Murray, Christine M. Albert, M. Benjamin Shoemaker, Nathalie Chami, Caroline F. Wright, Robert C. Kaplan, Nick Owens, Marilyn J. Telen, Allison E. Ashley‐Koch, Anne E. Justice, Kari E. North, Jonathan M. Locke, Hufeng Zhou, Lisa R. Yanek, Ryan L. Minster, Jennifer A. Brody, Patrick T. Ellinor, Scott T. Weiss, Robin N. Beaumont, April P. Carson, Ching‐Ti Liu, Mina K. Chung, Xiuqing Guo, Yii‐Der Ida Chen, Joanne E. Curran, Xihao Li, Gareth Hawkes, Kashyap Patel, Ravi Mandla, Jiang He, Zilin Li, Susan Redline, Eric Boerwinkle, Michael N. Weedon, Donna K. Arnett, Sharon Kardia, Myrian Fornage
article en
28 citations

Abstract

The role of rare non-coding variation in complex human phenotypes is still largely unknown. To elucidate the impact of rare variants in regulatory elements, we performed a whole-genome sequencing association analysis for height using 333,100 individuals from three datasets: UK Biobank (N = 200,003), TOPMed (N = 87,652) and All of Us (N = 45,445). We performed rare ( < 0.1% minor-allele-frequency) single-variant and aggregate testing of non-coding variants in regulatory regions based on proximal-regulatory, intergenic-regulatory and deep-intronic annotation. We observed 29 independent variants associated with height at P < <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mn>6</mml:mn> <mml:mo>×</mml:mo> <mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow> <mml:mrow><mml:mo>-</mml:mo> <mml:mn>10</mml:mn></mml:mrow> </mml:msup> </mml:math> after conditioning on previously reported variants, with effect sizes ranging from -7cm to +4.7 cm. We also identified and replicated non-coding aggregate-based associations proximal to HMGA1 containing variants associated with a 5 cm taller height and of highly-conserved variants in MIR497HG on chromosome 17. We have developed an approach for identifying non-coding rare variants in regulatory regions with large effects from whole-genome sequencing data associated with complex traits.

Nature CommunicationsVol. 15(1)
Broad Institute (US), Boston University (US), University of North Carolina at Chapel Hill (US), Tulane University (US), University of Copenhagen (DK), University of Maryland, Baltimore (US), Cedars-Sinai Medical Center (US), Brigham and Women's Hospital (US), Albert Einstein College of Medicine (US), Mayo Clinic (US), Harvard University (US), Johns Hopkins University (US), University of South Carolina (US), University of Pittsburgh (US), Duke University (US), University of Washington (US), University of Exeter (GB), National University of Samoa (WS), Brown University (US), University of Michigan (US), Johns Hopkins Medicine (US), Novo Nordisk Foundation (DK), UCLA Medical Center (US), The University of Texas Rio Grande Valley (US), Jackson Memorial Hospital (US), Taipei Veterans General Hospital (TW), University of Mississippi Medical Center (US), Yale University (US), University of Illinois Chicago (US), Massachusetts General Hospital (US), Fred Hutch Cancer Center (US), National Heart, Lung, and Blood Institute (US), Framingham Heart Study (US), Duke Medical Center (US), Circadian (United States) (US), Cedars-Sinai Smidt Heart Institute (US), Orthopedic Institute (US), Harbor–UCLA Medical Center (US), Wake Forest University (US), University of Colorado Anschutz Medical Campus (US), Geisinger Health System (US), Vanderbilt University Medical Center (US), The University of Texas Health Science Center at Houston (US), University of Colorado Denver (US), Icahn School of Medicine at Mount Sinai (US)
European Federation of Pharmaceutical Industries and Associations, European Commission, Innovative Medicines Initiative, Medical Research Council, Biotechnology and Biological Sciences Research Council
Openalex Percentile: Top 1%
Genetic Associations and Epidemiology
15.41
DOIOpen Access PDFOpenAlex
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