Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits. - Evangelou, Evangelos; Warren, Helen R; Mosen-Ansorena, David; Mifsud, Borbala; Pazoki, Raha; Gao, He; Ntritsos, Georgios; Dimou, Niki; Cabrera, Claudia P; Karaman, Ibrahim; Ng, Fu Liang; Evangelou, Marina; et al. (Nat Genet, 2018)
High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits (systolic, diastolic and pulse pressure) to date in over 1 million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also highlight shared genetic architecture between blood pressure and lifestyle exposures. Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future.

Rare and low-frequency coding variants alter human adult height. - Marouli, Eirini; Graff, Mariaelisa; Medina-Gomez, Carolina; Lo, Ken Sin; Wood, Andrew R; Kjaer, Troels R; Fine, Rebecca S; Lu, Yingchang; Schurmann, Claudia; Highland, Heather M; Rüeger, Sina; Thorleifsson, Gudmar; et al. (Nature, 2017)
Height is a highly heritable, classic polygenic trait with approximately 700 common associated variants identified through genome-wide association studies so far. Here, we report 83 height-associated coding variants with lower minor-allele frequencies (in the range of 0.1-4.8%) and effects of up to 2 centimetres per allele (such as those in IHH, STC2, AR and CRISPLD2), greater than ten times the average effect of common variants. In functional follow-up studies, rare height-increasing alleles of STC2 (giving an increase of 1-2 centimetres per allele) compromised proteolytic inhibition of PAPP-A and increased cleavage of IGFBP-4 in vitro, resulting in higher bioavailability of insulin-like growth factors. These 83 height-associated variants overlap genes that are mutated in monogenic growth disorders and highlight new biological candidates (such as ADAMTS3, IL11RA and NOX4) and pathways (such as proteoglycan and glycosaminoglycan synthesis) involved in growth. Our results demonstrate that sufficiently large sample sizes can uncover rare and low-frequency variants of moderate-to-large effect associated with polygenic human phenotypes, and that these variants implicate relevant genes and pathways.
Keywords: ADAMTS Proteins; Adult; Alleles; Body Height; Cell Adhesion Molecules; Female; Gene Frequency; Genetic Variation; Genome, Human; Glycoproteins; Glycosaminoglycans; Hedgehog Proteins; Humans; Intercellular Signaling Peptides and Proteins; Interferon Regulatory Factors; Interleukin-11 Receptor alpha Subunit; Male; Multifactorial Inheritance; NADPH Oxidase 4; NADPH Oxidases; Phenotype; Pregnancy-Associated Plasma Protein-A; Procollagen N-Endopeptidase; Proteoglycans; Proteolysis; Receptors, Androgen; Somatomedins

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