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Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution

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Abstract

Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥5%) and nine low-frequency or rare (MAF <5%) coding novel variants. Pathway/gene set enrichment analyses identified lipid particle, adiponectin, abnormal white adipose tissue physiology and bone development and morphology as important contributors to fat distribution, while cross-trait associations highlight cardiometabolic traits. In functional follow-up analyses, specifically in Drosophila RNAi-knockdowns, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). We implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants.

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Fig. 1: Summary of meta-analysis study design and workflow.
Fig. 2: Minor allele frequency compared to estimated effect.
Fig. 3: Regional association plots for known loci with novel coding signals identified by conditional analyses.
Fig. 4: Heat maps showing DEPICT gene set enrichment results from the stage 1 all ancestry sex-combined individuals (N = 344,369).

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Data availability

Summary statistics of all analyses are available at https://portals.broadinstitute.org/collaboration/giant/index.php/GIANT_consortium_data_files.

Change history

  • 07 March 2019

    In the HTML version of the article originally published, the link for Supplementary Data 5 returned the file for Supplementary Data 7. The error has been corrected in the HTML version of the article.

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Acknowledgements

This work was primarily supported through funding from the National Institute of Health (NIH): 1K99HL130580, R01-DK089256, 2R01HD057194, U01HG007416, R01DK101855, T32 HL007055, KL2TR001109; and the American Heart Association (AHA): 13POST16500011 and 13GRNT16490017. Co-author Y. Jia recently passed away while this work was in process. This study was completed as part of the Genetic Investigation of ANtropometric Traits (GIANT) Consortium. This research has been conducted using the UK Biobank resource. A full list of acknowledgements is provided in the Supplementary Data 18.

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