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

Genetic studies of body mass index yield new insights for obesity biology. - Locke, Adam E; Kahali, Bratati; Berndt, Sonja I; Justice, Anne E; Pers, Tune H; Day, Felix R; Powell, Corey; Vedantam, Sailaja; Buchkovich, Martin L; Yang, Jian; Croteau-Chonka, Damien C; Esko, Tõnu; et al. (Nature, 2015)
Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.
Keywords: Adipogenesis; Adiposity; Age Factors; Body Mass Index; Continental Population Groups; Energy Metabolism; Europe; Female; Genetic Predisposition to Disease; Genome-Wide Association Study; Glutamic Acid; Humans; Insulin; Male; Obesity; Polymorphism, Single Nucleotide; Quantitative Trait Loci; Synapses

New genetic loci link adipose and insulin biology to body fat distribution. - Shungin, Dmitry; Winkler, Thomas W; Croteau-Chonka, Damien C; Ferreira, Teresa; Locke, Adam E; Mägi, Reedik; Strawbridge, Rona J; Pers, Tune H; Fischer, Krista; Justice, Anne E; Workalemahu, Tsegaselassie; Wu, Joseph M W; et al. (Nature, 2015)
Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.
Keywords: Adipocytes; Adipogenesis; Adipose Tissue; Age Factors; Body Fat Distribution; Body Mass Index; Continental Population Groups; Epigenesis, Genetic; Europe; Female; Genome, Human; Genome-Wide Association Study; Humans; Insulin; Insulin Resistance; Male; Models, Biological; Neovascularization, Physiologic; Obesity; Polymorphism, Single Nucleotide; Quantitative Trait Loci; Sex Characteristics; Transcription, Genetic; Waist-Hip Ratio

Population genetic differentiation of height and body mass index across Europe. - Robinson, Matthew R; Hemani, Gibran; Medina-Gomez, Carolina; Mezzavilla, Massimo; Esko, Tõnu; Shakhbazov, Konstantin; Powell, Joseph E; Vinkhuyzen, Anna; Berndt, Sonja I; Gustafsson, Stefan; Justice, Anne E; Kahali, Bratati; et al. (Nat Genet, 2015)
Across-nation differences in the mean values for complex traits are common, but the reasons for these differences are unknown. Here we find that many independent loci contribute to population genetic differences in height and body mass index (BMI) in 9,416 individuals across 14 European countries. Using discovery data on over 250,000 individuals and unbiased effect size estimates from 17,500 sibling pairs, we estimate that 24% (95% credible interval (CI) = 9%, 41%) and 8% (95% CI = 4%, 16%) of the captured additive genetic variance for height and BMI, respectively, reflect population genetic differences. Population genetic divergence differed significantly from that in a null model (height, P < 3.94 × 10(-8); BMI, P < 5.95 × 10(-4)), and we find an among-population genetic correlation for tall and slender individuals (r = -0.80, 95% CI = -0.95, -0.60), consistent with correlated selection for both phenotypes. Observed differences in height among populations reflected the predicted genetic means (r = 0.51; P < 0.001), but environmental differences across Europe masked genetic differentiation for BMI (P < 0.58).