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C-reactive protein (CRP) is a sensitive biomarker of chronic low-grade inflammation and is associated with multiple complex diseases. The genetic determinants of chronic inflammation remain largely unknown, and the causal role of CRP in several clinical outcomes is debated. We performed two genome-wide association studies (GWASs), on HapMap and 1000 Genomes imputed data, of circulating amounts of CRP by using data from 88 studies comprising 204,402 European individuals. Additionally, we performed in silico functional analyses and Mendelian randomization analyses with several clinical outcomes. The GWAS meta-analyses of CRP revealed 58 distinct genetic loci (p < 5 × 10-8). After adjustment for body mass index in the regression analysis, the associations at all except three loci remained. The lead variants at the distinct loci explained up to 7.0% of the variance in circulating amounts of CRP. We identified 66 gene sets that were organized in two substantially correlated clusters, one mainly composed of immune pathways and the other characterized by metabolic pathways in the liver. Mendelian randomization analyses revealed a causal protective effect of CRP on schizophrenia and a risk-increasing effect on bipolar disorder. Our findings provide further insights into the biology of inflammation and could lead to interventions for treating inflammation and its clinical consequences.

Original publication

DOI

10.1016/j.ajhg.2018.09.009

Type

Journal article

Journal

American journal of human genetics

Publication Date

11/2018

Volume

103

Pages

691 - 706

Addresses

Department of Epidemiology, Erasmus University Medical Center, Rotterdam 3000 CA, the Netherlands.

Keywords

LifeLines Cohort Study, CHARGE Inflammation Working Group, Liver, Humans, Inflammation, C-Reactive Protein, Body Mass Index, Bipolar Disorder, Schizophrenia, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, Child, Female, Male, Metabolic Networks and Pathways, Genome-Wide Association Study, Young Adult, Genetic Loci, Mendelian Randomization Analysis, Biomarkers