Antti-Pekka Sarin

Genome-wide association study identifies multiple loci influencing human serum metabolite levels

Nuclear magnetic resonance assays allow for measurement of a wide range of metabolic phenotypes. We report here the results of a GWAS on 8,330 Finnish individuals genotyped and imputed at 7.7 million SNPs for a range of 216 serum metabolic phenotypes assessed by NMR of serum samples. We identified significant associations (P < 2.31 × 10−10) at 31 loci, including 11 for which there have not been previous reports of associations to a metabolic trait or disorder. Analyses of Finnish twin pairs suggested that the metabolic measures reported here show higher heritability than comparable conventional metabolic phenotypes. In accordance with our expectations, SNPs at the 31 loci associated with individual metabolites account for a greater proportion of the genetic component of trait variance (up to 40%) than is typically observed for conventional serum metabolic phenotypes. The identification of such associations may provide substantial insight into cardiometabolic disorders.

The impact of low-frequency and rare variants on lipid levels

Using a genome-wide screen of 9.6 million genetic variants achieved through 1000 Genomes Project imputation in 62,166 samples, we identify association to lipid traits in 93 loci, including 79 previously identified loci with new lead SNPs and 10 new loci, 15 loci with a low-frequency lead SNP and 10 loci with a missense lead SNP, and 2 loci with an accumulation of rare variants. In six loci, SNPs with established function in lipid genetics (CELSR2, GCKR, LIPC and APOE) or candidate missense mutations with predicted damaging function (CD300LG and TM6SF2) explained the locus associations. The low-frequency variants increased the proportion of variance explained, particularly for low-density lipoprotein cholesterol and total cholesterol. Altogether, our results highlight the impact of low-frequency variants in complex traits and show that imputation offers a cost-effective alternative to resequencing.

Genome-wide study for circulating metabolites identifies 62 loci and reveals novel systemic effects of LPA

Genome-wide association studies have identified numerous loci linked with complex diseases, for which the molecular mechanisms remain largely unclear. Comprehensive molecular profiling of circulating metabolites captures highly heritable traits, which can help to uncover metabolic pathophysiology underlying established disease variants. We conduct an extended genome-wide association study of genetic influences on 123 circulating metabolic traits quantified by nuclear magnetic resonance metabolomics from up to 24,925 individuals and identify eight novel loci for amino acids, pyruvate and fatty acids. The LPA locus link with cardiovascular risk exemplifies how detailed metabolic profiling may inform underlying aetiology via extensive associations with very-low-density lipoprotein and triglyceride metabolism. Genetic fine mapping and Mendelian randomization uncover wide-spread causal effects of lipoprotein(a) on overall lipoprotein metabolism and we assess potential pleiotropic consequences of genetically elevated lipoprotein(a) on diverse morbidities via electronic health-care records. Our findings strengthen the argument for safe LPA-targeted intervention to reduce cardiovascular risk.

Detailed metabolic and genetic characterization reveals new associations for 30 known lipid loci

Almost 100 genetic loci are known to affect serum cholesterol and triglyceride levels. For many of these loci, the biological function and causal variants remain unknown. We performed an association analysis of the reported 95 lipid loci against 216 metabolite measures, including 95 measurements on lipids and lipoprotein subclasses, obtained via serum nuclear magnetic resonance metabolomics and four enzymatic lipid traits in 8330 individuals from Finland. The genetic variation in the loci was investigated using a dense set of 440 807 directly genotyped and imputed variants around the previously identified lead single nucleotide polymorphisms (SNPs). For 30 of the 95 loci, we identified new metabolic or genetic associations (P < 5 × 10(-8)). In the majority of the loci, the strongest association was to a more specific metabolite measure than the enzymatic lipids. In four loci, the smallest high-density lipoprotein measures showed effects opposite to the larger ones, and 14 loci had associations beyond the individual lipoprotein measures. In 27 loci, we identified SNPs with a stronger association than the previously reported markers and 12 loci harboured multiple, statistically independent variants. Our data show considerable diversity in association patterns between the loci originally identified through associations with enzymatic lipid measures and reveal association profiles of far greater detail than from routine clinical lipid measures. Additionally, a dense marker set and a homogeneous population allow for detailed characterization of the genetic association signals to a resolution exceeding that achieved so far. Further understanding of the rich variability in genetic effects on metabolites provides insights into the biological processes modifying lipid levels.

Analysis of Detailed Phenotype Profiles Reveals CHRNA5-CHRNA3-CHRNB4 Gene Cluster Association With Several Nicotine Dependence Traits

INTRODUCTION The role of the nicotinic acetylcholine receptor gene cluster on chromosome 15q24-25 in the etiology of nicotine dependence (ND) is still being defined. In this study, we included all 15 tagging single nucleotide polymorphisms (SNPs) within the CHRNA5-CHRNA3-CHRNB4 cluster and tested associations with 30 smoking-related phenotypes. METHODS The study sample was ascertained from the Finnish Twin Cohort study. Twin pairs born 1938-1957 and concordant for a history of cigarette smoking were recruited along with their family members (mainly siblings), as part of the Nicotine Addiction Genetics consortium. The study sample consisted of 1,428 individuals (59% males) from 735 families, with mean age 55.6 years. RESULTS We detected multiple novel associations for ND. DSM-IV ND symptoms associated significantly with the proxy SNP Locus 1 (rs2036527, p = .000009) and Locus 2 (rs578776, p = .0001) and tolerance factor of the Nicotine Dependence Syndrome Scale (NDSS) showed suggestive association to rs11636753 (p = .0059), rs11634351 (p = .0069), and rs1948 (p = .0071) in CHRNB4. Furthermore, we report significant association with DSM-IV ND diagnosis (rs2036527, p = .0003) for the first time in a Caucasian population. Several SNPs indicated suggestive association for traits related to ages at smoking initiation. Also, rs11636753 in CHRNB4 showed suggestive association with regular drinking (p = .0029) and the comorbidity of depression and ND (p = .0034). CONCLUSIONS We demonstrate novel associations of DSM-IV ND symptoms and the NDSS tolerance subscale. Our results confirm and extend association findings for other ND measures. We show pleiotropic effects of this gene cluster on multiple measures of ND and also regular drinking and the comorbidity of ND and depression.

Adiposity as a cause of cardiovascular disease: a Mendelian randomization study

BACKGROUND Adiposity, as indicated by body mass index (BMI), has been associated with risk of cardiovascular diseases in epidemiological studies. We aimed to investigate if these associations are causal, using Mendelian randomization (MR) methods. METHODS The associations of BMI with cardiovascular outcomes [coronary heart disease (CHD), heart failure and ischaemic stroke], and associations of a genetic score (32 BMI single nucleotide polymorphisms) with BMI and cardiovascular outcomes were examined in up to 22,193 individuals with 3062 incident cardiovascular events from nine prospective follow-up studies within the ENGAGE consortium. We used random-effects meta-analysis in an MR framework to provide causal estimates of the effect of adiposity on cardiovascular outcomes. RESULTS There was a strong association between BMI and incident CHD (HR = 1.20 per SD-increase of BMI, 95% CI, 1.12-1.28, P = 1.9.10(-7)), heart failure (HR = 1.47, 95% CI, 1.35-1.60, P = 9.10(-19)) and ischaemic stroke (HR = 1.15, 95% CI, 1.06-1.24, P = 0.0008) in observational analyses. The genetic score was robustly associated with BMI (β = 0.030 SD-increase of BMI per additional allele, 95% CI, 0.028-0.033, P = 3.10(-107)). Analyses indicated a causal effect of adiposity on development of heart failure (HR = 1.93 per SD-increase of BMI, 95% CI, 1.12-3.30, P = 0.017) and ischaemic stroke (HR = 1.83, 95% CI, 1.05-3.20, P = 0.034). Additional cross-sectional analyses using both ENGAGE and CARDIoGRAMplusC4D data showed a causal effect of adiposity on CHD. CONCLUSIONS Using MR methods, we provide support for the hypothesis that adiposity causes CHD, heart failure and, previously not demonstrated, ischaemic stroke.

A Genome-Wide Association Study of a Biomarker of Nicotine Metabolism

Individuals with fast nicotine metabolism typically smoke more and thus have a greater risk for smoking-induced diseases. Further, the efficacy of smoking cessation pharmacotherapy is dependent on the rate of nicotine metabolism. Our objective was to use nicotine metabolite ratio (NMR), an established biomarker of nicotine metabolism rate, in a genome-wide association study (GWAS) to identify novel genetic variants influencing nicotine metabolism. A heritability estimate of 0.81 (95% CI 0.70–0.88) was obtained for NMR using monozygotic and dizygotic twins of the FinnTwin cohort. We performed a GWAS in cotinine-verified current smokers of three Finnish cohorts (FinnTwin, Young Finns Study, FINRISK2007), followed by a meta-analysis of 1518 subjects, and annotated the genome-wide significant SNPs with methylation quantitative loci (meQTL) analyses. We detected association on 19q13 with 719 SNPs exceeding genome-wide significance within a 4.2 Mb region. The strongest evidence for association emerged for CYP2A6 (min p = 5.77E-86, in intron 4), the main metabolic enzyme for nicotine. Other interesting genes with genome-wide significant signals included CYP2B6, CYP2A7, EGLN2, and NUMBL. Conditional analyses revealed three independent signals on 19q13, all located within or in the immediate vicinity of CYP2A6. A genetic risk score constructed using the independent signals showed association with smoking quantity (p = 0.0019) in two independent Finnish samples. Our meQTL results showed that methylation values of 16 CpG sites within the region are affected by genotypes of the genome-wide significant SNPs, and according to causal inference test, for some of the SNPs the effect on NMR is mediated through methylation. To our knowledge, this is the first GWAS on NMR. Our results enclose three independent novel signals on 19q13.2. The detected CYP2A6 variants explain a strikingly large fraction of variance (up to 31%) in NMR in these study samples. Further, we provide evidence for plausible epigenetic mechanisms influencing NMR.

Genome-wide association study on detailed profiles of smoking behavior and nicotine dependence in a twin sample

Smoking is a major risk factor for several somatic diseases and is also emerging as a causal factor for neuropsychiatric disorders. Genome-wide association (GWA) and candidate gene studies for smoking behavior and nicotine dependence (ND) have disclosed too few predisposing variants to account for the high estimated heritability. Previous large-scale GWA studies have had very limited phenotypic definitions of relevance to smoking-related behavior, which has likely impeded the discovery of genetic effects. We performed GWA analyses on 1114 adult twins ascertained for ever smoking from the population-based Finnish Twin Cohort study. The availability of 17 smoking-related phenotypes allowed us to comprehensively portray the dimensions of smoking behavior, clustered into the domains of smoking initiation, amount smoked and ND. Our results highlight a locus on 16p12.3, with several single-nucleotide polymorphisms (SNPs) in the vicinity of CLEC19A showing association (P<1 × 10−6) with smoking quantity. Interestingly, CLEC19A is located close to a previously reported attention-deficit hyperactivity disorder (ADHD) linkage locus and an evident link between ADHD and smoking has been established. Intriguing preliminary association (P<1 × 10−5) was detected between DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, 4th edition) ND diagnosis and several SNPs in ERBB4, coding for a Neuregulin receptor, on 2q33. The association between ERBB4 and DSM-IV ND diagnosis was replicated in an independent Australian sample. Recently, a significant increase in ErbB4 and Neuregulin 3 (Nrg3) expression was revealed following chronic nicotine exposure and withdrawal in mice and an association between NRG3 SNPs and smoking cessation success was detected in a clinical trial. ERBB4 has previously been associated with schizophrenia; further, it is located within an established schizophrenia linkage locus and within a linkage locus for a smoker phenotype identified in this sample. In conclusion, we disclose novel tentative evidence for the involvement of ERBB4 in ND, suggesting the involvement of the Neuregulin/ErbB signalling pathway in addictions and providing a plausible link between the high co-morbidity of schizophrenia and ND.

Discovery and fine-mapping of glycaemic and obesity-related trait loci using high-density imputation

Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI) at genome-wide significance, and two for fasting glucose (FG), none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3) and FG (GCK and G6PC2). The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated.

Chromosome X-Wide Association Study Identifies Loci for Fasting Insulin and Height and Evidence for Incomplete Dosage Compensation

The X chromosome (chrX) represents one potential source for the “missing heritability” for complex phenotypes, which thus far has remained underanalyzed in genome-wide association studies (GWAS). Here we demonstrate the benefits of including chrX in GWAS by assessing the contribution of 404,862 chrX SNPs to levels of twelve commonly studied cardiometabolic and anthropometric traits in 19,697 Finnish and Swedish individuals with replication data on 5,032 additional Finns. By using a linear mixed model, we estimate that on average 2.6% of the additive genetic variance in these twelve traits is attributable to chrX, this being in proportion to the number of SNPs in the chromosome. In a chrX-wide association analysis, we identify three novel loci: two for height (rs182838724 near FGF16/ATRX/MAGT1, joint P-value = 2.71×10−9, and rs1751138 near ITM2A, P-value = 3.03×10−10) and one for fasting insulin (rs139163435 in Xq23, P-value = 5.18×10−9). Further, we find that effect sizes for variants near ITM2A, a gene implicated in cartilage development, show evidence for a lack of dosage compensation. This observation is further supported by a sex-difference in ITM2A expression in whole blood (P-value = 0.00251), and is also in agreement with a previous report showing ITM2A escapes from X chromosome inactivation (XCI) in the majority of women. Hence, our results show one of the first links between phenotypic variation in a population sample and an XCI-escaping locus and pinpoint ITM2A as a potential contributor to the sexual dimorphism in height. In conclusion, our study provides a clear motivation for including chrX in large-scale genetic studies of complex diseases and traits.