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.

We have performed a metabolite quantitative trait locus (mQTL) study of the (1)H nuclear magnetic resonance spectroscopy ((1)H NMR) metabolome in humans, building on recent targeted knowledge of genetic drivers of metabolic regulation. Urine and plasma samples were collected from two cohorts of individuals of European descent, with one cohort comprised of female twins donating samples longitudinally. Sample metabolite concentrations were quantified by (1)H NMR and tested for association with genome-wide single-nucleotide polymorphisms (SNPs). Four metabolites' concentrations exhibited significant, replicable association with SNP variation (8.6×10(-11)<p<2.8×10(-23)). Three of these-trimethylamine, 3-amino-isobutyrate, and an N-acetylated compound-were measured in urine. The other-dimethylamine-was measured in plasma. Trimethylamine and dimethylamine mapped to a single genetic region (hence we report a total of three implicated genomic regions). Two of the three hit regions lie within haplotype blocks (at 2p13.1 and 10q24.2) that carry the genetic signature of strong, recent, positive selection in European populations. Genes NAT8 and PYROXD2, both with relatively uncharacterized functional roles, are good candidates for mediating the corresponding mQTL associations. The study's longitudinal twin design allowed detailed variance-components analysis of the sources of population variation in metabolite levels. The mQTLs explained 40%-64% of biological population variation in the corresponding metabolites' concentrations. These effect sizes are stronger than those reported in a recent, targeted mQTL study of metabolites in serum using the targeted-metabolomics Biocrates platform. By re-analysing our plasma samples using the Biocrates platform, we replicated the mQTL findings of the previous study and discovered a previously uncharacterized yet substantial familial component of variation in metabolite levels in addition to the heritability contribution from the corresponding mQTL effects.

BACKGROUND: Genome-wide association (GWA) studies have identified several susceptibility loci for metabolic syndrome (MetS) component traits, but have had variable success in identifying susceptibility loci to the syndrome as an entity. We conducted a GWA study on MetS and its component traits in 4 Finnish cohorts consisting of 2637 MetS cases and 7927 controls, both free of diabetes, and followed the top loci in an independent sample with transcriptome and nuclear magnetic resonance-based metabonomics data. Furthermore, we tested for loci associated with multiple MetS component traits using factor analysis, and built a genetic risk score for MetS. METHODS AND RESULTS: A previously known lipid locus, APOA1/C3/A4/A5 gene cluster region (SNP rs964184), was associated with MetS in all 4 study samples (P=7.23×10(-9) in meta-analysis). The association was further supported by serum metabolite analysis, where rs964184 was associated with various very low density lipoprotein, triglyceride, and high-density lipoprotein metabolites (P=0.024-1.88×10(-5)). Twenty-two previously identified susceptibility loci for individual MetS component traits were replicated in our GWA and factor analysis. Most of these were associated with lipid phenotypes, and none with 2 or more uncorrelated MetS components. A genetic risk score, calculated as the number of risk alleles in loci associated with individual MetS traits, was strongly associated with MetS status. CONCLUSIONS: Our findings suggest that genes from lipid metabolism pathways have the key role in the genetic background of MetS. We found little evidence for pleiotropy linking dyslipidemia and obesity to the other MetS component traits, such as hypertension and glucose intolerance.

Genome-wide association studies (GWAS) have identified many risk loci for complex diseases, but effect sizes are typically small and information on the underlying biological processes is often lacking. Associations with metabolic traits as functional intermediates can overcome these problems and potentially inform individualized therapy. Here we report a comprehensive analysis of genotype-dependent metabolic phenotypes using a GWAS with non-targeted metabolomics. We identified 37 genetic loci associated with blood metabolite concentrations, of which 25 show effect sizes that are unusually high for GWAS and account for 10-60% differences in metabolite levels per allele copy. Our associations provide new functional insights for many disease-related associations that have been reported in previous studies, including those for cardiovascular and kidney disorders, type 2 diabetes, cancer, gout, venous thromboembolism and Crohn's disease. The study advances our knowledge of the genetic basis of metabolic individuality in humans and generates many new hypotheses for biomedical and pharmaceutical research.

Previous studies using SAGE (the Study of Addiction: Genetics and Environment) and COGA (the Collaborative Study on the Genetics of Alcoholism) genome-wide association study (GWAS) data sets reported several risk loci for alcohol dependence (AD), which have not yet been well replicated independently or confirmed by functional studies. We combined these two data sets, now publicly available, to increase the study power, in order to identify replicable, functional, and significant risk regions for AD. A total of 4116 subjects (1409 European-American (EA) cases with AD, 1518 EA controls, 681 African-American (AA) cases, and 508 AA controls) underwent association analysis. An additional 443 subjects underwent expression quantitative trait locus (eQTL) analysis. Genome-wide association analysis was performed in EAs to identify significant risk genes. All available markers in the genome-wide significant risk genes were tested in AAs for associations with AD, and in six HapMap populations and two European samples for associations with gene expression levels. We identified a unique genome-wide significant gene--KIAA0040--that was enriched with many replicable risk SNPs for AD, all of which had significant cis-acting regulatory effects. The distributions of -log(p) values for SNP-disease and SNP-expression associations for all markers in the TNN-KIAA0040 region were consistent across EAs, AAs, and five HapMap populations (0.369 ≤ r ≤ 0.824; 2.8 × 10⁻⁹ ≤ p ≤ 0.032). The most significant SNPs in these populations were in high LD, concentrating in KIAA0040. Finally, expression of KIAA0040 was significantly (1.2 × 10⁻¹¹ ≤ p ≤1 .5 × 10⁻⁶) associated with the expression of numerous genes in the neurotransmitter systems or metabolic pathways previously associated with AD. We concluded that KIAA0040 might harbor a causal variant for AD and thus might directly contribute to risk for this disorder. KIAA0040 might also contribute to the risk of AD via neurotransmitter systems or metabolic pathways that have previously been implicated in the pathophysiology of AD. Alternatively, KIAA0040 might regulate the risk via some interactions with flanking genes TNN and TNR. TNN is involved in neurite outgrowth and cell migration in hippocampal explants, and TNR is an extracellular matrix protein expressed primarily in the central nervous system.

Recent genome-wide association (GWA) studies described 95 loci controlling serum lipid levels. These common variants explain ∼25% of the heritability of the phenotypes. To date, no unbiased screen for gene-environment interactions for circulating lipids has been reported. We screened for variants that modify the relationship between known epidemiological risk factors and circulating lipid levels in a meta-analysis of genome-wide association (GWA) data from 18 population-based cohorts with European ancestry (maximum N = 32,225). We collected 8 further cohorts (N = 17,102) for replication, and rs6448771 on 4p15 demonstrated genome-wide significant interaction with waist-to-hip-ratio (WHR) on total cholesterol (TC) with a combined P-value of 4.79×10(-9). There were two potential candidate genes in the region, PCDH7 and CCKAR, with differential expression levels for rs6448771 genotypes in adipose tissue. The effect of WHR on TC was strongest for individuals carrying two copies of G allele, for whom a one standard deviation (sd) difference in WHR corresponds to 0.19 sd difference in TC concentration, while for A allele homozygous the difference was 0.12 sd. Our findings may open up possibilities for targeted intervention strategies for people characterized by specific genomic profiles. However, more refined measures of both body-fat distribution and metabolic measures are needed to understand how their joint dynamics are modified by the newly found locus.

Carotid intima media thickness (cIMT) and plaque determined by ultrasonography are established measures of subclinical atherosclerosis that each predicts future cardiovascular disease events. We conducted a meta-analysis of genome-wide association data in 31,211 participants of European ancestry from nine large studies in the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. We then sought additional evidence to support our findings among 11,273 individuals using data from seven additional studies. In the combined meta-analysis, we identified three genomic regions associated with common carotid intima media thickness and two different regions associated with the presence of carotid plaque (P < 5 × 10(-8)). The associated SNPs mapped in or near genes related to cellular signaling, lipid metabolism and blood pressure homeostasis, and two of the regions were associated with coronary artery disease (P < 0.006) in the Coronary Artery Disease Genome-Wide Replication and Meta-Analysis (CARDIoGRAM) consortium. Our findings may provide new insight into pathways leading to subclinical atherosclerosis and subsequent cardiovascular events.

We carried out a genome-wide association study of serum aspartate aminotransferase (AST) activity in 866 Amish participants of the Heredity and Phenotype Intervention Heart Study and identified significant association of AST activity with a cluster of single nucleotide polymorphisms located on chromosome 10q24.1 (peak association was rs17109512; P=2.80E-14), in the vicinity of GOT1, the gene encoding cytosolic AST (cAST). Sequencing of GOT1 revealed an in-frame deletion of three nucleic acids encoding asparagine at position 389 c.1165_1167delAAC (p.Asn389del) in the gene. Deletion carriers had significantly lower AST activity levels compared with homozygotes for the common allele (mean±s.d.: 10.0±2.8 versus 18.8±5.2 U l(-1); P=2.80E-14). Further genotyping of the deletion in other Amish samples (n=1932) identified an additional 20 carriers (minor allele frequency (MAF)=0.0052). The deletion was not detected in 647 outbred Caucasians. Asn at codon 389 is conserved among known mammalian cASTs. In vitro transient transfection of wild-type and mutant cAST indicated that mutant cAST protein was barely detectable in the cells. Furthermore, even after correction for cAST expression, mutant cAST had markedly diminished enzymatic activity. Remarkably, we did not find any association between the deletion and metabolic traits including serum fasting glucose or insulin, fasting and post-meal lipids, inflammatory markers, or sub-clinical markers of cardiovascular disease. In conclusion, we discovered a rare in-frame deletion in GOT1 gene, which inactivates cAST enzyme in the Old Order Amish. This finding will help us to understand structure and function of the enzyme and would be useful for predicting serum AST levels.

Serum butyrylcholinesterase (BCHE) activity is associated with obesity, blood pressure and biomarkers of cardiovascular and diabetes risk. We have conducted a genome-wide association scan to discover genetic variants affecting BCHE activity, and to clarify whether the associations between BCHE activity and cardiometabolic risk factors are caused by variation in BCHE or whether BCHE variation is secondary to the metabolic abnormalities. We measured serum BCHE in adolescents and adults from three cohorts of Australian twin and family studies. The genotypes from ∼2.4 million single-nucleotide polymorphisms (SNPs) were available in 8791 participants with BCHE measurements. We detected significant associations with BCHE activity at three independent groups of SNPs at the BCHE locus (P = 5.8 × 10(-262), 7.8 × 10(-47), 2.9 × 10(-12)) and at four other loci: RNPEP (P = 9.4 × 10(-16)), RAPH1-ABI2 (P = 4.1 × 10(-18)), UGT1A1 (P = 4.0 × 10(-8)) and an intergenic region on chromosome 8 (P = 1.4 × 10(-8)). These loci affecting BCHE activity were not associated with metabolic risk factors. On the other hand, SNPs in genes previously associated with metabolic risk had effects on BCHE activity more often than can be explained by chance. In particular, SNPs within FTO and GCKR were associated with BCHE activity, but their effects were partly mediated by body mass index and triglycerides, respectively. We conclude that variation in BCHE activity is due to multiple variants across the spectrum from uncommon/large effect to common/small effect, and partly results from (rather than causes) metabolic abnormalities.

We report the first genome-wide association study of habitual caffeine intake. We included 47,341 individuals of European descent based on five population-based studies within the United States. In a meta-analysis adjusted for age, sex, smoking, and eigenvectors of population variation, two loci achieved genome-wide significance: 7p21 (P = 2.4 × 10(-19)), near AHR, and 15q24 (P = 5.2 × 10(-14)), between CYP1A1 and CYP1A2. Both the AHR and CYP1A2 genes are biologically plausible candidates as CYP1A2 metabolizes caffeine and AHR regulates CYP1A2.