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Riveros-McKay, F.* ; Oliver-Williams, C.* ; Karthikeyan, S.* ; Walter, K.* ; Kundu, K.* ; Ouwehand, W.H.* ; Roberts, D.* ; Soranzo, N.* ; Wheeler, E.* ; Zeggini, E. ; Barroso, I.*

The influence of rare variants in circulating metabolic biomarkers.

PLoS Genet. 16:e1008605 (2020)

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Author summaryCardiovascular diseases (CVD) are the number one cause of death globally. Various metabolic biomarkers including lipid and lipoprotein particles have been implicated as risk factors for the development of CVD. Understanding how these biomarkers are regulated can lead to increased understanding of CVD aetiology and the potential identification of drug targets. Here we take advantage of high resolution measurements on a large cohort of 7,142 healthy blood donors with whole-exome and whole-genome sequencing data to explore the influence of rare variation on circulating metabolic biomarker levels. Using a novel approach leveraging the information gained from various measurements on the same participants we are able to identify a novel biological pathway involved in the regulation of intermediate-density and low-density lipoproteins as well as circulating cholesterol, confirm various established gene associations and identify potential novel gene associations that merit further replication. This work highlights the advantages that can be gained by combining high resolution genotypic and phenotypic measurements in one large cohort.Circulating metabolite levels are biomarkers for cardiovascular disease (CVD). Here we studied, association of rare variants and 226 serum lipoproteins, lipids and amino acids in 7,142 (discovery plus follow-up) healthy participants. We leveraged the information from multiple metabolite measurements on the same participants to improve discovery in rare variant association analyses for gene-based and gene-set tests by incorporating correlated metabolites as covariates in the validation stage. Gene-based analysis corrected for the effective number of tests performed, confirmed established associations at APOB, APOC3, PAH, HAL and PCSK (p<1.32x10(-7)) and identified novel gene-trait associations at a lower stringency threshold with ACSL1, MYCN, FBXO36 and B4GALNT3 (p<2.5x10(-6)). Regulation of the pyruvate dehydrogenase (PDH) complex was associated for the first time, in gene-set analyses also corrected for effective number of tests, with IDL and LDL parameters, as well as circulating cholesterol (p(METASKAT)<2.41x10(-6)). In conclusion, using an approach that leverages metabolite measurements obtained in the same participants, we identified novel loci and pathways involved in the regulation of these important metabolic biomarkers. As large-scale biobanks continue to amass sequencing and phenotypic information, analytical approaches such as ours will be useful to fully exploit the copious amounts of biological data generated in these efforts.

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