Genome Analyses of >200,000 Individuals Identify 58 Loci for Chronic Inflammation and Highlight Pathways that Link Inflammation and Complex Disorders. - Ligthart, Symen; Vaez, Ahmad; Võsa, Urmo; Stathopoulou, Maria G; de Vries, Paul S; Prins, Bram P; van der Most, Peter J; Tanaka, Toshiko; Naderi, Elnaz; Rose, Lynda M; Wu, Ying; Karlsson, Robert; et al. (Am J Hum Genet, 2018)
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). 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.

Whole-Genome Sequencing Coupled to Imputation Discovers Genetic Signals for Anthropometric Traits. - Tachmazidou, Ioanna; Süveges, Dániel; Min, Josine L; Ritchie, Graham R S; Steinberg, Julia; Walter, Klaudia; Iotchkova, Valentina; Schwartzentruber, Jeremy; Huang, Jie; Memari, Yasin; McCarthy, Shane; Crawford, Andrew A; et al. (Am J Hum Genet, 2017)
Deep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the broader allelic architecture of 12 anthropometric traits associated with height, body mass, and fat distribution in up to 267,616 individuals. We report 106 genome-wide significant signals that have not been previously identified, including 9 low-frequency variants pointing to functional candidates. Of the 106 signals, 6 are in genomic regions that have not been implicated with related traits before, 28 are independent signals at previously reported regions, and 72 represent previously reported signals for a different anthropometric trait. 71% of signals reside within genes and fine mapping resolves 23 signals to one or two likely causal variants. We confirm genetic overlap between human monogenic and polygenic anthropometric traits and find signal enrichment in cis expression QTLs in relevant tissues. Our results highlight the potential of WGS strategies to enhance biologically relevant discoveries across the frequency spectrum.
Keywords: Anthropometry; Body Height; Cohort Studies; Databases, Genetic; DNA Methylation; Female; Genetic Variation; Genome, Human; Genome-Wide Association Study; Humans; Lipodystrophy; Male; Meta-Analysis as Topic; Obesity; Physical Chromosome Mapping; Quantitative Trait Loci; Sequence Analysis, DNA; Sex Characteristics; Syndrome; United Kingdom

A reference panel of 64,976 haplotypes for genotype imputation. - McCarthy, Shane; Das, Sayantan; Kretzschmar, Warren; Delaneau, Olivier; Wood, Andrew R; Teumer, Alexander; Kang, Hyun Min; Fuchsberger, Christian; Danecek, Petr; Sharp, Kevin; Luo, Yang; Sidore, Carlo; et al. (Nat Genet, 2016)
We describe a reference panel of 64,976 human haplotypes at 39,235,157 SNPs constructed using whole-genome sequence data from 20 studies of predominantly European ancestry. Using this resource leads to accurate genotype imputation at minor allele frequencies as low as 0.1% and a large increase in the number of SNPs tested in association studies, and it can help to discover and refine causal loci. We describe remote server resources that allow researchers to carry out imputation and phasing consistently and efficiently.

Genome sequencing elucidates Sardinian genetic architecture and augments association analyses for lipid and blood inflammatory markers. - Sidore, Carlo; Busonero, Fabio; Maschio, Andrea; Porcu, Eleonora; Naitza, Silvia; Zoledziewska, Magdalena; Mulas, Antonella; Pistis, Giorgio; Steri, Maristella; Danjou, Fabrice; Kwong, Alan; Ortega Del Vecchyo, Vicente Diego; et al. (Nat Genet, 2015)
We report ∼17.6 million genetic variants from whole-genome sequencing of 2,120 Sardinians; 22% are absent from previous sequencing-based compilations and are enriched for predicted functional consequences. Furthermore, ∼76,000 variants common in our sample (frequency >5%) are rare elsewhere (<0.5% in the 1000 Genomes Project). We assessed the impact of these variants on circulating lipid levels and five inflammatory biomarkers. We observe 14 signals, including 2 major new loci, for lipid levels and 19 signals, including 2 new loci, for inflammatory markers. The new associations would have been missed in analyses based on 1000 Genomes Project data, underlining the advantages of large-scale sequencing in this founder population.