Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci

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 withP <5 x 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 x 10(-8)) in the discovery samples. Ten novel SNVs, including rs12616219 nearTMEM182, were followed-up and five of them (rs462779 inREV3L, rs12780116 inCNNM2, rs1190736 inGPR101, rs11539157 inPJA1, and rs12616219 nearTMEM182) replicated at a Bonferroni significance threshold (P <4.5 x 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, inCCDC141and two low-frequency SNVs inCEP350andHDGFRP2. Functional follow-up implied that decreased expression ofREV3Lmay 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.Peer reviewe

Exome Chip Meta-analysis Fine Maps Causal Variants and Elucidates the Genetic Architecture of Rare Coding Variants in Smoking and Alcohol Use

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 to contribute to disease risk. METHODS: We analyzed similar to 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-variant tests, and gene-based burden tests of nonsynonymous/loss-of-function coding variants. We performed a novel fine-mapping analysis to winnow the number of putative causal variants within associated loci. RESULTS: Meta-analytic sample sizes ranged from 152,348 to 433,216, depending on the phenotype. Rare coding variation explained 1.1% to 2.2% of phenotypic variance, reflecting 11% to 18% of the total single nucleotide polymorphism heritability of these phenotypes. We identified 171 genome-wide associated loci across all phenotypes. Fine mapping identified putative causal variants with double base-pair resolution at 24 of these loci, and between three and 10 variants for 65 loci. Twenty loci contained rare coding variants in the 95% credible intervals. CONCLUSIONS: Rare coding variation significantly contributes to the heritability of smoking and alcohol use. Fine-mapping genome-wide association study loci identifies specific variants contributing to the biological etiology of substance use behavior.Peer reviewe

Rare and low-frequency coding variants alter human adult height

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 frequenc ies ( range of 0.1 - 4.8% ) and effects of up to 2 16 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) compromise d proteolytic inhibition of PAPP - A and increased cleavage of IGFBP - 4 in vitro , resulting in higher bioavailability of insulin - like growth factors . The se 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

Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci

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 &lt; 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 &lt; 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 &lt; 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