Summary Height is a highly heritable, classic polygenic trait with ∼700 common associated variants identified so far through genome-wide association studies. Here, we report 83 height-associated coding variants with lower minor allele frequencies (range of 0.1-4.8%) and effects of up to 2 cm/allele (e.g. in IHH, STC2, AR and CRISPLD2), >10 times the average effect of common variants. In functional follow-up studies, rare height-increasing alleles of STC2 (+1-2 cm/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 mutated in monogenic growth disorders and highlight new biological candidates (e.g. ADAMTS3, IL11RA, NOX4) and pathways (e.g. proteoglycan/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.

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, non-coding variants from which pinpointing causal genes remains challenging. Here, we combined data from 718,734 individuals to discover rare and low-frequency (MAF<5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which eight in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2, ZNF169) newly implicated in human obesity, two (MC4R, KSR2) previously observed in extreme obesity, and two variants in GIPR. Effect sizes of rare variants are ~10 times larger than of common variants, with the largest effect observed in carriers of an MC4R stop-codon (p.Tyr35Ter, MAF=0.01%), weighing ~7kg more than non-carriers. Pathway analyses confirmed enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically-supported therapeutic targets to treat obesity.

Hematological traits are important clinical parameters. To test the role of rare and low-frequency coding variants on hematological traits, we analyzed hemoglobin, hematocrit, white blood cell (WBC) and platelet count in 31,340 individuals genotyped on an exome array. We identified several missense variants of CXCR2 associated with reduced WBC count (gene-based P=2.6×10−13). In a separate family-based re-sequencing study, we identified a novel loss-of-function CXCR2 frameshift mutation in a pedigree with congenital neutropenia that abolished ligand-induced CXCR2 signal transduction and chemotaxis. We also identified novel missense or splice site variants in key hematopoiesis regulators (EPO, TRF2, HBB, TUBB1, SH2B3) associated with blood cell traits. Finally, we were able to detect associations between the rare somatic JAK2 p.Val617Phe mutation and platelet count (P=3.9×10−22) as well as hemoglobin (P=0.002), hematocrit (P=9.5×10−7) and WBC (P=3.1×10−5). In conclusion, exome arrays complement GWAS in identifying new variants that contribute to complex human traits.

Smoking is a major heritable and modifiable risk factor for many diseases, including cancer, common respiratory disorders and cardiovascular diseases. Fourteen genetic loci have previously been associated with smoking behaviour-related traits. We tested up to 235,116 single nucleotide variants (SNVs) on the exome-array for association with smoking initiation, cigarettes per day, pack-years, and smoking cessation in a fixed effects meta-analysis of up to 61 studies (up to 346,813 participants). In a subset of 112,811 participants, a further one million SNVs were also genotyped and tested for association with the four smoking behaviour traits. SNV-trait associations with P < 5 × 10 −8 in either analysis were taken forward for replication in up to 275,596 independent participants from UK Biobank. Lastly, a meta-analysis of the discovery and replication studies was performed. Sixteen SNVs were associated with at least one of the smoking behaviour traits (P < 5 × 10 −8) in the discovery samples. Ten novel SNVs, including rs12616219 near TMEM182, were followed-up and five of them (rs462779 in REV3L, rs12780116 in CNNM2, rs1190736 in GPR101, rs11539157 in PJA1, and rs12616219 near TMEM182) replicated at a Bonferroni significance threshold (P < 4.5 × 10 −3) with consistent direction of effect. A further 35 SNVs were associated with smoking behaviour traits in the discovery plus replication meta-analysis (up to 622,409 participants) including a rare SNV, rs150493199, in CCDC141 and two low-frequency SNVs in CEP350 and HDGFRP2. Functional follow-up implied that decreased expression of REV3L may lower the probability of smoking initiation. The novel loci will facilitate understanding the genetic aetiology of smoking behaviour and may lead to the identification of potential drug targets for smoking prevention and/or cessation.

BackgroundEpigenetic mechanisms may be involved in the regulation of genes found to be differentially expressed in the visceral adipose tissue (VAT) of severely obese subjects with (MetS+) versus without (MetS-) metabolic syndrome (MetS). Long interspersed nuclear element 1 (LINE-1) elements DNA methylation levels (%meth) in blood, a marker of global DNA methylation, have recently been associated with fasting glucose, blood lipids, heart diseases and stroke.AimTo test whether LINE-1%meth levels in VAT are associated with MetS phenotypes and whether they can predict MetS risk in severely obese individuals.MethodsDNA was extracted from VAT of 34 men (MetS-: n = 14, MetS+: n = 20) and 152 premenopausal women (MetS-: n = 84; MetS+: n = 68) undergoing biliopancreatic diversion for the treatment of obesity. LINE-1%meth levels were assessed by pyrosequencing of sodium bisulfite-treated DNA.ResultsThe mean LINE-1%meth in VAT was of 75.8% (SD = 3.0%). Multiple linear regression analyses revealed that LINE-1%meth was negatively associated with fasting glucose levels (β = -0.04; P = 0.03), diastolic blood pressure (β =  -0.65; P = 0.03) and MetS status (β = -0.04; P = 0.004) after adjustments for the effects of age, sex, waist circumference (except for MetS status) and smoking. While dividing subjects into quartiles based on their LINE-1%meth (Q1 to Q4: lower %meth to higher %meth levels), greater risk were observed in the first (Q1: odds ratio (OR) = 4.37, P = 0.004) and the second (Q2: OR = 4.76, P = 0.002) quartiles compared to Q4 (1.00) when adjusting for age, sex and smoking.ConclusionsThese results suggest that lower global DNA methylation, assessed by LINE-1 repetitive elements methylation analysis, would be associated with a greater risk for MetS in the presence of obesity.

Severely obese subjects with the metabolic syndrome (MS) have higher dipeptidyl peptidase‐4 (DPP4) expression in their visceral adipose tissue (VAT) compared to obese individuals without MS. We tested the hypothesis that methylation level of CpG sites in the DPP4 promoter CpG island in VAT was genotype‐dependent and associated with DPP4 mRNA abundance and MS‐related phenotypes. The VAT DNA was extracted in 92 severely obese premenopausal women undergoing biliopancreatic derivation for the treatment of obesity. Women were nondiabetic and none of them used medication to treat MS features. Cytosine methylation rates (%) of 102 CpG sites in the DPP4 CpG island were assessed by pyrosequencing of sodium bisulfite‐treated DNA. Methylation rates were >10% for CpG sites 94–102. Their mean methylation rate (%Meth94–102) was different between genotypes for DPP4 polymorphisms rs13015258 (P = 0.001), rs17848915 (P = 0.0004), and c.1926 G>A (P = 0.001). The %Meth94–102 correlated negatively with DPP4 mRNA abundance (r = −0.25, P < 0.05) and positively with plasma high‐density lipoprotein (HDL) cholesterol concentrations (r = 0.22, P < 0.05), whereas DPP4 mRNA abundance correlated positively with plasma total‐/HDL‐cholesterol ratio (r = 0.25; P < 0.05). In the VAT of nondiabetic severely obese women, genotype‐dependent methylation levels of specific CpG sites in the DPP4 promoter CpG island were associated with DPP4 gene expression and variability in the plasma lipid profile. Higher DPP4 gene expression in VAT and its relationship with the plasma lipid profile may be explained by actually unknown DPP4 biological effect or, to another extent, may also be a marker of VAT inflammation known to be associated with metabolic disturbances.

Rapid postnatal growth is associated with increased risk of childhood adiposity. The aim of this study was to establish whether this pathway is mediated by altered DNA methylation and gene expression. Two distinct cohorts, one preterm (n = 121) and one term born (n = 6,990), were studied. Exploratory analyses were performed using microarrays to identify differentially expressed genes in whole blood from children defined as “slow” (n = 10) compared with “rapid” (n = 10) postnatal (term to 12 weeks corrected age) growers. Methylation within the identified TACSTD2 gene was measured in both cohorts, and rs61779296 genotype was determined by Pyrosequencing or imputation and analyzed in relation to body composition at 9–15 years of age. In cohort 1, TACSTD2 expression was inversely correlated with methylation (P = 0.016), and both measures were associated with fat mass (expression, P = 0.049; methylation, P = 0.037). Although associated with gene expression (cohort 1, P = 0.008) and methylation (cohort 1, P = 2.98 × 10−11; cohort 2, P = 3.43 × 10−15), rs61779296 was not associated with postnatal growth or fat mass in either cohort following multiple regression analysis. Hence, the lack of association between fat mass and a methylation proxy SNP suggests that reverse causation or confounding may explain the initial association between fat mass and gene regulation. Noncausal methylation patterns may still be useful predictors of later adiposity.

Brazel, D. M. et al. (2019) Exome chip meta-analysis fine maps causal variants and elucidates the genetic architecture of rare coding variants in smoking and alcohol use. Number of words in abstract: 249Number of words in main text: 3676 Abstract: Background: Smoking and alcohol use have been associated with common genetic variants in multiple loci. Rare variants within these loci hold promise in the identification of biological mechanisms in substance use. Exome arrays and genotype imputation can now efficiently genotype rare nonsynonymous and loss of function variants. Such variants are expected to have deleterious functional consequences, and contribute to disease risk. Methods: We analyzed ~250,000 rare variants from 16 independent studies genotyped with exome arrays and augmented this dataset with imputed data from the UK Biobank. Associations were tested for five phenotypes: cigarettes per day, pack years, smoking initiation, age of smoking initiation, and alcoholic drinks per week. We conducted stratified heritability analyses, single-