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

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.

Directional dominance on stature and cognition in diverse human populations. - Joshi, Peter K; Esko, Tõnu; Mattsson, Hannele; Eklund, Niina; Gandin, Ilaria; Nutile, Teresa; Jackson, Anne U; Schurmann, Claudia; Smith, Albert V; Zhang, Weihua; Okada, Yukinori; Stančáková, Alena; et al. (Nature, 2015)
Homozygosity has long been associated with rare, often devastating, Mendelian disorders, and Darwin was one of the first to recognize that inbreeding reduces evolutionary fitness. However, the effect of the more distant parental relatedness that is common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power. Here we use runs of homozygosity to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts, and find statistically significant associations between summed runs of homozygosity and four complex traits: height, forced expiratory lung volume in one second, general cognitive ability and educational attainment (P < 1 × 10(-300), 2.1 × 10(-6), 2.5 × 10(-10) and 1.8 × 10(-10), respectively). In each case, increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months' less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing evidence that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.
Keywords: Biological Evolution; Blood Pressure; Body Height; Cholesterol, LDL; Cognition; Cohort Studies; Educational Status; Female; Forced Expiratory Volume; Genome, Human; Homozygote; Humans; Lung Volume Measurements; Male; Phenotype