Multivariate Genome-wide Association Analysis of a Cytokine Network Reveals Variants with Widespread Immune, Haematological, and Cardiometabolic Pleiotropy.

Cytokines are essential regulatory components of the immune system, and their aberrant levels have been linked to many disease states. Despite increasing evidence that cytokines operate in concert, many of the physiological interactions between cytokines, and the shared genetic architecture that underlies them, remain unknown. Here, we aimed to identify and characterize genetic variants with pleiotropic effects on cytokines. Using three population-based cohorts (n = 9,263), we performed multivariate genome-wide association studies (GWAS) for a correlation network of 11 circulating cytokines, then combined our results in meta-analysis. We identified a total of eight loci significantly associated with the cytokine network, of which two (PDGFRB and ABO) had not been detected previously. In addition, conditional analyses revealed a further four secondary signals at three known cytokine loci. Integration, through the use of Bayesian colocalization analysis, of publicly available GWAS summary statistics with the cytokine network associations revealed shared causal variants between the eight cytokine loci and other traits; in particular, cytokine network variants at the ABO, SERPINE2, and ZFPM2 loci showed pleiotropic effects on the production of immune-related proteins, on metabolic traits such as lipoprotein and lipid levels, on blood-cell-related traits such as platelet count, and on disease traits such as coronary artery disease and type 2 diabetes.

Haplotype Sharing Provides Insights into Fine-Scale Population History and Disease in Finland.

Finland provides unique opportunities to investigate population and medical genomics because of its adoption of unified national electronic health records, detailed historical and birth records, and serial population bottlenecks. We assembled a comprehensive view of recent population history (≤100 generations), the timespan during which most rare-disease-causing alleles arose, by comparing pairwise haplotype sharing from 43,254 Finns to that of 16,060 Swedes, Estonians, Russians, and Hungarians from geographically and linguistically adjacent countries with different population histories. We find much more extensive sharing in Finns, with at least one ≥ 5 cM tract on average between pairs of unrelated individuals. By coupling haplotype sharing with fine-scale birth records from more than 25,000 individuals, we find that although haplotype sharing broadly decays with geographical distance, there are pockets of excess haplotype sharing; individuals from northeast Finland typically share several-fold more of their genome in identity-by-descent segments than individuals from southwest regions. We estimate recent effective population-size changes through time across regions of Finland, and we find that there was more continuous gene flow as Finns migrated from southwest to northeast between the early- and late-settlement regions than was dichotomously described previously. Lastly, we show that haplotype sharing is locally enriched by an order of magnitude among pairs of individuals sharing rare alleles and especially among pairs sharing rare disease-causing variants. Our work provides a general framework for using haplotype sharing to reconstruct an integrative view of recent population history and gain insight into the evolutionary origins of rare variants contributing to disease.

Genome-wide Association Study Identifies 27 Loci Influencing Concentrations of Circulating Cytokines and Growth Factors.

Circulating cytokines and growth factors are regulators of inflammation and have been implicated in autoimmune and metabolic diseases. In this genome-wide association study (GWAS) of up to 8,293 Finns we identified 27 genome-widely significant loci (p < 1.2 × 10-9) for one or more cytokines. Fifteen of the associated variants had expression quantitative trait loci in whole blood. We provide genetic instruments to clarify the causal roles of cytokine signaling and upstream inflammation in immune-related and other chronic diseases. We further link inflammatory markers with variants previously associated with autoimmune diseases such as Crohn disease, multiple sclerosis, and ulcerative colitis and hereby elucidate the molecular mechanisms underpinning these diseases and suggest potential drug targets.

The Contribution of GWAS Loci in Familial Dyslipidemias.

Familial combined hyperlipidemia (FCH) is a complex and common familial dyslipidemia characterized by elevated total cholesterol and/or triglyceride levels with over five-fold risk of coronary heart disease. The genetic architecture and contribution of rare Mendelian and common variants to FCH susceptibility is unknown. In 53 Finnish FCH families, we genotyped and imputed nine million variants in 715 family members with DNA available. We studied the enrichment of variants previously implicated with monogenic dyslipidemias and/or lipid levels in the general population by comparing allele frequencies between the FCH families and population samples. We also constructed weighted polygenic scores using 212 lipid-associated SNPs and estimated the relative contributions of Mendelian variants and polygenic scores to the risk of FCH in the families. We identified, across the whole allele frequency spectrum, an enrichment of variants known to elevate, and a deficiency of variants known to lower LDL-C and/or TG levels among both probands and affected FCH individuals. The score based on TG associated SNPs was particularly high among affected individuals compared to non-affected family members. Out of 234 affected FCH individuals across the families, seven (3%) carried Mendelian variants and 83 (35%) showed high accumulation of either known LDL-C or TG elevating variants by having either polygenic score over the 90th percentile in the population. The positive predictive value of high score was much higher for affected FCH individuals than for similar sporadic cases in the population. FCH is highly polygenic, supporting the hypothesis that variants across the whole allele frequency spectrum contribute to this complex familial trait. Polygenic SNP panels improve identification of individuals affected with FCH, but their clinical utility remains to be defined.

Genome-wide association study and meta-analysis in Northern European populations replicate multiple colorectal cancer risk loci.

Genome-wide association studies have been successful in elucidating the genetic basis of colorectal cancer (CRC), but there remains unexplained variability in genetic risk. To identify new risk variants and to confirm reported associations, we conducted a genome-wide association study in 1,701 CRC cases and 14,082 cancer-free controls from the Finnish population. A total of 9,068,015 genetic variants were imputed and tested, and 30 promising variants were studied in additional 11,647 cases and 12,356 controls of European ancestry. The previously reported association between the single-nucleotide polymorphism (SNP) rs992157 (2q35) and CRC was independently replicated (p = 2.08 × 10-4 ; OR, 1.14; 95% CI, 1.06-1.23), and it was genome-wide significant in combined analysis (p = 1.50 × 10-9 ; OR, 1.12; 95% CI, 1.08-1.16). Variants at 2q35, 6p21.2, 8q23.3, 8q24.21, 10q22.3, 10q24.2, 11q13.4, 11q23.1, 14q22.2, 15q13.3, 18q21.1, 20p12.3 and 20q13.33 were associated with CRC in the Finnish population (false discovery rate < 0.1), but new risk loci were not found. These results replicate the effects of multiple loci on the risk of CRC and identify shared risk alleles between the Finnish population isolate and outbred populations.

Variation at 2q35 (PNKD and TMBIM1) influences colorectal cancer risk and identifies a pleiotropic effect with inflammatory bowel disease.

To identify new risk loci for colorectal cancer (CRC), we conducted a meta-analysis of seven genome-wide association studies (GWAS) with independent replication, totalling 13 656 CRC cases and 21 667 controls of European ancestry. The combined analysis identified a new risk association for CRC at 2q35 marked by rs992157 (P = 3.15 × 10-8, odds ratio = 1.10, 95% confidence interval = 1.06-1.13), which is intronic to PNKD (paroxysmal non-kinesigenic dyskinesia) and TMBIM1 (transmembrane BAX inhibitor motif containing 1). Intriguingly this susceptibility single-nucleotide polymorphism (SNP) is in strong linkage disequilibrium (r2 = 0.90, D' = 0.96) with the previously discovered GWAS SNP rs2382817 for inflammatory bowel disease (IBD). Following on from this observation we examined for pleiotropy, or shared genetic susceptibility, between CRC and the 200 established IBD risk loci, identifying an additional 11 significant associations (false discovery rate [FDR]) < 0.05). Our findings provide further insight into the biological basis of inherited genetic susceptibility to CRC, and identify risk factors that may influence the development of both CRC and IBD.

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.

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.

MicroRNA-192* impairs adipocyte triglyceride storage.

We investigated the expression of miR-192* (miR-192-3p) in the visceral adipose tissue (VAT) of obese subjects and its function in cultured human adipocytes. This miRNA is a 3' arm derived from the same pre-miRNA as miR-192 (miR-192-5p) implicated in type 2 diabetes, liver disease and cancers, and is predicted to target key genes in lipid metabolism. In morbidly obese subjects undergoing bariatric surgery preceded by a very low calorie diet, miR-192* in VAT correlated negatively (r=-0.387; p=0.046) with serum triglyceride (TG) and positively with high-density lipoprotein (HDL) concentration (r=0.396; p=0.041). In a less obese patient cohort, the miRNA correlated negatively with the body mass index (r=-0.537; p=0.026). To characterize the function of miR-192*, we overexpressed it in cultured adipocytes and analyzed the expression of adipogenic differentiation markers as well as cellular TG content. Reduced TG and expression of the adipocyte marker proteins aP2 (adipocyte protein 2) and perilipin 1 were observed. The function of miR-192* was further investigated by transcriptomic profiling of adipocytes expressing this miRNA, revealing impacts on key lipogenic genes. A number of the mRNA alterations were validated by qPCR. Western analysis confirmed a marked reduction of the lipogenic enzyme SCD (stearoyl coenzyme A desaturase-1), the fatty aldehyde dehydrogenase ALDH3A2 (aldehyde dehydrogenase 3 family member A2) and the high-density lipoprotein receptor SCARB1 (scavenger receptor B, type I). SCD and ALDH3A2 were demonstrated to be direct targets of miR-192*. To conclude, the present data identify miR-192* as a novel controller of adipocyte differentiation and lipid homeostasis.

Mendelian randomisation implicates hyperlipidaemia as a risk factor for colorectal cancer.

While elevated blood cholesterol has been associated with an increased risk of colorectal cancer (CRC) in observational studies, causality is uncertain. Here we apply a Mendelian randomisation (MR) analysis to examine the potential causal relationship between lipid traits and CRC risk. We used single nucleotide polymorphisms (SNPs) associated with blood levels of total cholesterol (TC), triglyceride (TG), low-density lipoprotein (LDL), and high-density lipoprotein (HDL) as instrumental variables (IV). We calculated MR estimates for each risk factor with CRC using SNP-CRC associations from 9,254 cases and 18,386 controls. Genetically predicted higher TC was associated with an elevated risk of CRC (odds ratios (OR) per unit SD increase = 1.46, 95% confidence interval [CI]: 1.20-1.79, p = 1.68 × 10-4 ). The pooled ORs for LDL, HDL, and TG were 1.05 (95% CI: 0.92-1.18, p = 0.49), 0.94 (95% CI: 0.84-1.05, p = 0.27), and 0.98 (95% CI: 0.85-1.12, p = 0.75) respectively. A genetic risk score for 3-hydoxy-3-methylglutaryl-coenzyme A reductase (HMGCR) to mimic the effects of statin therapy was associated with a reduced CRC risk (OR = 0.69, 95% CI: 0.49-0.99, p = 0.046). This study supports a causal relationship between higher levels of TC with CRC risk, and a further rationale for implementing public health strategies to reduce the prevalence of hyperlipidaemia.

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.

Genetic support for the causal role of insulin in coronary heart disease.

AIMS/HYPOTHESIS: Epidemiological studies have identified several traits associated with CHD, but few of these have been shown to be causal risk factors and thus suitable targets for treatment. Our aim was to evaluate the causal role of a large set of known CHD risk factors using single-nucleotide polymorphisms (SNPs) as instrumental variables. METHODS: Based on published genome-wide association studies (GWASs), we estimated the associations between the established risk factors (blood lipids, obesity, glycaemic traits and BP) and CHD with two complementary approaches: (1) using summary statistics from GWASs to analyse the accordance of SNP effects on risk factors and on CHD; and (2) individual-level analysis where we constructed genetic risk scores (GRSs) in a large Finnish dataset (N = 26,554, CHD events n = 4016). We used a weighted regression-based method for summary-level data to evaluate the causality of risk factors. The associations between the GRSs and CHD in the Finnish dataset were evaluated with logistic and conditional logistic regression models. RESULTS: The summary-level data analysis revealed causal effects between glycaemic traits (insulin and glucose) and CHD. The individual-level data analysis supported the causal role of insulin, but not of glucose, on CHD. The GRS for insulin was associated with CHD in the Finnish cohort (OR 1.06 per SD in GRS, 95% CI 1.02, 1.10, p = 0.002). CONCLUSIONS/INTERPRETATION: These results support the causal role of insulin in the pathogenesis of CHD. Efficient treatment and prevention of insulin resistance is essential to prevent future CHD events.

Hierarchical Bayesian model for rare variant association analysis integrating genotype uncertainty in human sequence data.

Next-generation sequencing (NGS) has led to the study of rare genetic variants, which possibly explain the missing heritability for complex diseases. Most existing methods for rare variant (RV) association detection do not account for the common presence of sequencing errors in NGS data. The errors can largely affect the power and perturb the accuracy of association tests due to rare observations of minor alleles. We developed a hierarchical Bayesian approach to estimate the association between RVs and complex diseases. Our integrated framework combines the misclassification probability with shrinkage-based Bayesian variable selection. It allows for flexibility in handling neutral and protective RVs with measurement error, and is robust enough for detecting causal RVs with a wide spectrum of minor allele frequency (MAF). Imputation uncertainty and MAF are incorporated into the integrated framework to achieve the optimal statistical power. We demonstrate that sequencing error does significantly affect the findings, and our proposed model can take advantage of it to improve statistical power in both simulated and real data. We further show that our model outperforms existing methods, such as sequence kernel association test (SKAT). Finally, we illustrate the behavior of the proposed method using a Finnish low-density lipoprotein cholesterol study, and show that it identifies an RV known as FH North Karelia in LDLR gene with three carriers in 1,155 individuals, which is missed by both SKAT and Granvil.

Mendelian randomisation analysis strongly implicates adiposity with risk of developing colorectal cancer.

BACKGROUND: Observational studies have associated adiposity with an increased risk of colorectal cancer (CRC). However, such studies do not establish a causal relationship. To minimise bias from confounding we performed a Mendelian randomisation (MR) analysis to examine the relationship between adiposity and CRC. METHODS: We used SNPs associated with adult body mass index (BMI), waist-hip ratio (WHR), childhood obesity and birth weight as instrumental variables in a MR analysis of 9254 CRC cases and 18 386 controls. RESULTS: In the MR analysis, the odds ratios (ORs) of CRC risk per unit increase in BMI, WHR and childhood obesity were 1.23 (95% CI: 1.02-1.49, P=0.033), 1.59 (95% CI: 1.08-2.34, P=0.019) and 1.07 (95% CI: 1.03-1.13, P=0.018), respectively. There was no evidence for association between birth weight and CRC (OR=1.22, 95% CI: 0.89-1.67, P=0.22). Combining these data with a concurrent MR-based analysis for BMI and WHR with CRC risk (totalling to 18 190 cases, 27 617 controls) provided increased support, ORs for BMI and WHR were 1.26 (95% CI: 1.10-1.44, P=7.7 × 10(-4)) and 1.40 (95% CI: 1.14-1.72, P=1.2 × 10(-3)), respectively. CONCLUSIONS: These data provide further evidence for a strong causal relationship between adiposity and the risk of developing CRC highlighting the urgent need for prevention and treatment of adiposity.

Assessing multivariate gene-metabolome associations with rare variants using Bayesian reduced rank regression.

MOTIVATION: A typical genome-wide association study searches for associations between single nucleotide polymorphisms (SNPs) and a univariate phenotype. However, there is a growing interest to investigate associations between genomics data and multivariate phenotypes, for example, in gene expression or metabolomics studies. A common approach is to perform a univariate test between each genotype-phenotype pair, and then to apply a stringent significance cutoff to account for the large number of tests performed. However, this approach has limited ability to uncover dependencies involving multiple variables. Another trend in the current genetics is the investigation of the impact of rare variants on the phenotype, where the standard methods often fail owing to lack of power when the minor allele is present in only a limited number of individuals. RESULTS: We propose a new statistical approach based on Bayesian reduced rank regression to assess the impact of multiple SNPs on a high-dimensional phenotype. Because of the method's ability to combine information over multiple SNPs and phenotypes, it is particularly suitable for detecting associations involving rare variants. We demonstrate the potential of our method and compare it with alternatives using the Northern Finland Birth Cohort with 4702 individuals, for whom genome-wide SNP data along with lipoprotein profiles comprising 74 traits are available. We discovered two genes (XRCC4 and MTHFD2L) without previously reported associations, which replicated in a combined analysis of two additional cohorts: 2390 individuals from the Cardiovascular Risk in Young Finns study and 3659 individuals from the FINRISK study. AVAILABILITY AND IMPLEMENTATION: R-code freely available for download at http://users.ics.aalto.fi/pemartti/gene_metabolome/.

Intracranial aneurysm risk locus 5q23.2 is associated with elevated systolic blood pressure.

Although genome-wide association studies (GWAS) have identified hundreds of complex trait loci, the pathomechanisms of most remain elusive. Studying the genetics of risk factors predisposing to disease is an attractive approach to identify targets for functional studies. Intracranial aneurysms (IA) are rupture-prone pouches at cerebral artery branching sites. IA is a complex disease for which GWAS have identified five loci with strong association and a further 14 loci with suggestive association. To decipher potential underlying disease mechanisms, we tested whether there are IA loci that convey their effect through elevating blood pressure (BP), a strong risk factor of IA. We performed a meta-analysis of four population-based Finnish cohorts (n(FIN)  =  11 266) not selected for IA, to assess the association of previously identified IA candidate loci (n  =  19) with BP. We defined systolic BP (SBP), diastolic BP, mean arterial pressure, and pulse pressure as quantitative outcome variables. The most significant result was further tested for association in the ICBP-GWAS cohort of 200 000 individuals. We found that the suggestive IA locus at 5q23.2 in PRDM6 was significantly associated with SBP in individuals of European descent (p(FIN)  =  3.01E-05, p(ICBP-GWAS)  =  0.0007, p(ALL)  =  8.13E-07). The risk allele of IA was associated with higher SBP. PRDM6 encodes a protein predominantly expressed in vascular smooth muscle cells. Our study connects a complex disease (IA) locus with a common risk factor for the disease (SBP). We hypothesize that common variants in PRDM6 can contribute to altered vascular wall structure, hence increasing SBP and predisposing to IA. True positive associations often fail to reach genome-wide significance in GWAS. Our findings show that analysis of traditional risk factors as intermediate phenotypes is an effective tool for deciphering hidden heritability. Further, we demonstrate that common disease loci identified in a population isolate may bear wider significance.

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.

Genomic, transcriptomic, and lipidomic profiling highlights the role of inflammation in individuals with low high-density lipoprotein cholesterol.

OBJECTIVE: Low high-density lipoprotein cholesterol (HDL-C) is associated with cardiometabolic pathologies. In this study, we investigate the biological pathways and individual genes behind low HDL-C by integrating results from 3 high-throughput data sources: adipose tissue transcriptomics, HDL lipidomics, and dense marker genotypes from Finnish individuals with low or high HDL-C (n=450). APPROACH AND RESULTS: In the pathway analysis of genetic data, we demonstrate that genetic variants within inflammatory pathways were enriched among low HDL-C associated single-nucleotide polymorphisms, and the expression of these pathways upregulated in the adipose tissue of low HDL-C subjects. The lipidomic analysis highlighted the change in HDL particle quality toward putatively more inflammatory and less vasoprotective state in subjects with low HDL-C, as evidenced by their decreased antioxidative plasmalogen contents. We show that the focal point of these inflammatory pathways seems to be the HLA region with its low HDL-associated alleles also associating with more abundant local transcript levels in adipose tissue, increased plasma vascular cell adhesion molecule 1 (VCAM1) levels, and decreased HDL particle plasmalogen contents, markers of adipose tissue inflammation, vascular inflammation, and HDL antioxidative potential, respectively. In a population-based look-up of the inflammatory pathway single-nucleotide polymorphisms in a large Finnish cohorts (n=11 211), no association of the HLA region was detected for HDL-C as quantitative trait, but with extreme HDL-C phenotypes, implying the presence of low or high HDL genes in addition to the population-genomewide association studies-identified HDL genes. CONCLUSIONS: Our study highlights the role of inflammation with a genetic component in subjects with low HDL-C and identifies novel cis-expression quantitative trait loci (cis-eQTL) variants in HLA region to be associated with low HDL-C.

A genome-wide screen for interactions reveals a new locus on 4p15 modifying the effect of waist-to-hip ratio on total cholesterol.

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.

The role of adiposity in cardiometabolic traits: a Mendelian randomization analysis.

BACKGROUND: The association between adiposity and cardiometabolic traits is well known from epidemiological studies. Whilst the causal relationship is clear for some of these traits, for others it is not. We aimed to determine whether adiposity is causally related to various cardiometabolic traits using the Mendelian randomization approach. METHODS AND FINDINGS: We used the adiposity-associated variant rs9939609 at the FTO locus as an instrumental variable (IV) for body mass index (BMI) in a Mendelian randomization design. Thirty-six population-based studies of individuals of European descent contributed to the analyses. Age- and sex-adjusted regression models were fitted to test for association between (i) rs9939609 and BMI (n  =  198,502), (ii) rs9939609 and 24 traits, and (iii) BMI and 24 traits. The causal effect of BMI on the outcome measures was quantified by IV estimators. The estimators were compared to the BMI-trait associations derived from the same individuals. In the IV analysis, we demonstrated novel evidence for a causal relationship between adiposity and incident heart failure (hazard ratio, 1.19 per BMI-unit increase; 95% CI, 1.03-1.39) and replicated earlier reports of a causal association with type 2 diabetes, metabolic syndrome, dyslipidemia, and hypertension (odds ratio for IV estimator, 1.1-1.4; all p < 0.05). For quantitative traits, our results provide novel evidence for a causal effect of adiposity on the liver enzymes alanine aminotransferase and gamma-glutamyl transferase and confirm previous reports of a causal effect of adiposity on systolic and diastolic blood pressure, fasting insulin, 2-h post-load glucose from the oral glucose tolerance test, C-reactive protein, triglycerides, and high-density lipoprotein cholesterol levels (all p < 0.05). The estimated causal effects were in agreement with traditional observational measures in all instances except for type 2 diabetes, where the causal estimate was larger than the observational estimate (p  =  0.001). CONCLUSIONS: We provide novel evidence for a causal relationship between adiposity and heart failure as well as between adiposity and increased liver enzymes.