Sudden cardiac death (SCD) remains a major cause of death in Western Countries. It has a heritable component, but previous molecular studies have mainly focused on common genetic variants. We studied the prevalence, clinical phenotypes, and risk of SCD presented by ten rare mutations previously associated with arrhythmogenic right ventricular cardiomyopathy, long QT syndrome, or catecholaminergic polymorphic ventricular tachycardia.
The occurrence of ten arrhythmia-associated mutations was determined in four large prospective population cohorts (FINRISK 1992, 1997, 2002, and Health 2000, n = 28,465) and two series of forensic autopsies (The Helsinki Sudden Death Study and The Tampere Autopsy Study, n = 825). Follow-up data was collected from national registries.
The ten mutations showed a combined prevalence of 79 per 10,000 individuals in Finland and six of them showed remarkable geographic clustering. Of a total of 715 SCD cases, seven (1.0%) carried one of the ten mutations assayed: three carried KCNH2 R176W, one KCNH2 L552S, two PKP2 Q59L, and one RYR2 R3570W.
Arrhythmia-associated mutations are prevalent in the general Finnish population but do not seem to present a major risk factor for SCD, at least during a mean of 10-year follow-up of a random adult population sample.
Arrhythmia; Genetic epidemiology; Genetics; Mutation; Sudden cardiac death
T-peak to T-end (TPE) interval on the electrocardiogram (ECG) is a measure of myocardial dispersion of repolarization and is associated with increased risk of ventricular arrhythmias. The genetic factors affecting the TPE interval are largely unknown.
We sought to identify common genetic variants that affect the TPE-interval duration in the general population.
We performed a genome-wide association study on 1 870 individuals of Finnish origin participating in the Health 2000 Study. TPE interval was measured from T-peak to T-wave end in leads II, V2 and V5 on resting ECGs and the mean of these TPE intervals was adjusted for age, sex and Cornell voltage-duration product. We sought replication for a genome-wide significant result in the 3 745 subjects from the Framingham Heart Study.
We identified a locus on 17q24 that was associated with the TPE interval. The minor allele of the common variant rs7219669 was associated with a 1.8-ms shortening of the TPE interval (P=1.1×10−10). The association was replicated in the Framingham Heart Study (−1.5 ms, P=1.3×10−4).The overall effect estimate of rs7219669 in the two studies was −1.7 ms (P=5.7×10−14). The common variant rs7219669 maps downstream of KCNJ2 gene, in which rare mutations cause congenital Long- and Short-QT syndromes.
The common variant rs7219669 is associated with the TPE interval and is thus a candidate to modify repolarization-related arrhythmia susceptibility in individuals carrying the major allele of this polymorphism.
Electrocardiography; Repolarization; T wave; Epidemiology; Genetics; Polymorphism
Economic variables such as income, education, and occupation are known to affect mortality and morbidity, such as cardiovascular disease, and have also been shown to be partly heritable. However, very little is known about which genes influence economic variables, although these genes may have both a direct and an indirect effect on health. We report results from the first large-scale collaboration that studies the molecular genetic architecture of an economic variable–entrepreneurship–that was operationalized using self-employment, a widely-available proxy. Our results suggest that common SNPs when considered jointly explain about half of the narrow-sense heritability of self-employment estimated in twin data (σg2/σP2 = 25%, h2 = 55%). However, a meta-analysis of genome-wide association studies across sixteen studies comprising 50,627 participants did not identify genome-wide significant SNPs. 58 SNPs with p<10−5 were tested in a replication sample (n = 3,271), but none replicated. Furthermore, a gene-based test shows that none of the genes that were previously suggested in the literature to influence entrepreneurship reveal significant associations. Finally, SNP-based genetic scores that use results from the meta-analysis capture less than 0.2% of the variance in self-employment in an independent sample (p≥0.039). Our results are consistent with a highly polygenic molecular genetic architecture of self-employment, with many genetic variants of small effect. Although self-employment is a multi-faceted, heavily environmentally influenced, and biologically distal trait, our results are similar to those for other genetically complex and biologically more proximate outcomes, such as height, intelligence, personality, and several diseases.
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.
Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have raised the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional follow-up of these newly discovered loci will further improve our understanding of glycemic control.
Biobanks can have a pivotal role in elucidating disease etiology, translation, and
advancing public health. However, meeting these challenges hinges on a critical shift in
the way science is conducted and requires biobank harmonization. There is growing
recognition that a common strategy is imperative to develop biobanking globally and
effectively. To help guide this strategy, we articulate key principles, goals, and
priorities underpinning a roadmap for global biobanking to accelerate health science,
patient care, and public health. The need to manage and share very large amounts of data
has driven innovations on many fronts. Although technological solutions are allowing
biobanks to reach new levels of integration, increasingly powerful data-collection tools,
analytical techniques, and the results they generate raise new ethical and legal issues
and challenges, necessitating a reconsideration of previous policies, practices, and
ethical norms. These manifold advances and the investments that support them are also
fueling opportunities for biobanks to ultimately become integral parts of health-care
systems in many countries. International harmonization to increase interoperability and
sustainability are two strategic priorities for biobanking. Tackling these issues requires
an environment favorably inclined toward scientific funding and equipped to address
socio-ethical challenges. Cooperation and collaboration must extend beyond systems to
enable the exchange of data and samples to strategic alliances between many organizations,
including governmental bodies, funding agencies, public and private science enterprises,
and other stakeholders, including patients. A common vision is required and we articulate
the essential basis of such a vision herein.
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 four 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 NMR-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 four study samples (P=7.23×10−9 in meta-analysis). The association was further supported by serum metabolite analysis, where rs964184 associated with various VLDL, TG, and HDL 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 associated with lipid phenotypes and none with two or more uncorrelated MetS components. A genetic risk score, calculated as the number of alleles in loci associated with individual MetS traits, was strongly associated with MetS status.
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.
metabolic syndrome; risk factors; genome-wide association study; meta-analysis; lipids
Association testing of multiple correlated phenotypes offers better power than univariate analysis of single traits. We analyzed 6,600 individuals from two population-based cohorts with both genome-wide SNP data and serum metabolomic profiles. From the observed correlation structure of 130 metabolites measured by nuclear magnetic resonance, we identified 11 metabolic networks and performed a multivariate genome-wide association analysis. We identified 34 genomic loci at genome-wide significance, of which 7 are novel. In comparison to univariate tests, multivariate association analysis identified nearly twice as many significant associations in total. Multi-tissue gene expression studies identified variants in our top loci, SERPINA1 and AQP9, as eQTLs and showed that SERPINA1 and AQP9 expression in human blood was associated with metabolites from their corresponding metabolic networks. Finally, liver expression of AQP9 was associated with atherosclerotic lesion area in mice, and in human arterial tissue both SERPINA1 and AQP9 were shown to be upregulated (6.3-fold and 4.6-fold, respectively) in atherosclerotic plaques. Our study illustrates the power of multi-phenotype GWAS and highlights candidate genes for atherosclerosis.
In this study, we aim to identify novel genetic variants for metabolism, characterize their effects on nearby genes, and show that the nearby genes are associated with metabolism and atherosclerosis. To discover new genetic variants, we use an alternative approach to traditional genome-wide association studies: we leverage the information in phenotype covariance to increase our statistical power. We identify variants at seven novel loci and then show that our top signals drive expression of nearby genes AQP9 and SERPINA1 in multiple tissues. We demonstrate that AQP9 and SERPINA1 gene expression, in turn, is associated with metabolite levels. Finally, we show that the genes are associated with atherosclerosis using mouse atherosclerotic lesion size (AQP9) as well as tissue from healthy human arteries and atherosclerotic plaques (AQP9 and SERPINA1). This study illustrates that multivariate analysis of correlated metabolites can boost power for gene discovery substantially. Further functional work will need to be performed to elucidate the biological role of SERPINA1 and AQP9 in atherosclerosis.
Genetic effects contribute to individual differences in smoking behavior. Persistence to smoke despite known harmful health effects is mostly driven by nicotine addiction. As the physiological effects of nicotine are mediated by nicotinic acetylcholine receptors (nAChRs), we aimed at examining whether single nucleotide polymorphisms (SNPs) residing in nAChR subunit (CHRN) genes, other than CHRNA3/CHRNA5/CHRNB4 gene cluster previously showing association in our sample, are associated with smoking quantity or serum cotinine levels.
The study sample consisted of 485 Finnish adult daily smokers (age 30–75 years, 59% men) assessed for the number of cigarettes smoked per day (CPD) and serum cotinine level. We first studied SNPs residing on selected nAChR subunit genes (CHRNA2, CHRNA4, CHRNA6/CHRNB3, CHRNA7, CHRNA9, CHRNA10, CHRNB2, CHRNG/CHRND) genotyped within a genome-wide association study for single SNP and multiple SNP associations by ordinal regression. Next, we explored individual haplotype associations using sliding window technique.
At one of the 8 loci studied, CHRNG/CHRND (chr2), single SNP (rs1190452), multiple SNP, and 2-SNP haplotype analyses (SNPs rs4973539–rs1190452) all showed statistically significant association with cotinine level. The median cotinine levels varied between the 2-SNP haplotypes from 220 ng/ml (AA haplotype) to 249 ng/ml (AG haplotype). We did not observe significant associations with CPD.
These results provide further evidence that the γ−δ nAChR subunit gene region is associated with cotinine levels but not with the number of CPD, illustrating the usefulness of biomarkers in genetic analyses.
IgA nephropathy (IgAN), major cause of kidney failure worldwide, is common in Asians, moderately prevalent in Europeans, and rare in Africans. It is not known if these differences represent variation in genes, environment, or ascertainment. In a recent GWAS, we localized five IgAN susceptibility loci on Chr.6p21 (HLA-DQB1/DRB1, PSMB9/TAP1, and DPA1/DPB2 loci), Chr.1q32 (CFHR3/R1 locus), and Chr.22q12 (HORMAD2 locus). These IgAN loci are associated with risk of other immune-mediated disorders such as type I diabetes, multiple sclerosis, or inflammatory bowel disease. We tested association of these loci in eight new independent cohorts of Asian, European, and African-American ancestry (N = 4,789), followed by meta-analysis with risk-score modeling in 12 cohorts (N = 10,755) and geospatial analysis in 85 world populations. Four susceptibility loci robustly replicated and all five loci were genome-wide significant in the combined cohort (P = 5×10−32–3×10−10), with heterogeneity detected only at the PSMB9/TAP1 locus (I2 = 0.60). Conditional analyses identified two new independent risk alleles within the HLA-DQB1/DRB1 locus, defining multiple risk and protective haplotypes within this interval. We also detected a significant genetic interaction, whereby the odds ratio for the HORMAD2 protective allele was reversed in homozygotes for a CFHR3/R1 deletion (P = 2.5×10−4). A seven–SNP genetic risk score, which explained 4.7% of overall IgAN risk, increased sharply with Eastward and Northward distance from Africa (r = 0.30, P = 3×10−128). This model paralleled the known East–West gradient in disease risk. Moreover, the prediction of a South–North axis was confirmed by registry data showing that the prevalence of IgAN–attributable kidney failure is increased in Northern Europe, similar to multiple sclerosis and type I diabetes. Variation at IgAN susceptibility loci correlates with differences in disease prevalence among world populations. These findings inform genetic, biological, and epidemiological investigations of IgAN and permit cross-comparison with other complex traits that share genetic risk loci and geographic patterns with IgAN.
IgA nephropathy (IgAN) is the most common cause of kidney failure in Asia, has lower prevalence in Europe, and is very infrequent among populations of African ancestry. A long-standing question in the field is whether these differences represent variation in genes, environment, or ascertainment. In a recent genome-wide association study of 5,966 individuals, we identified five susceptibility loci for this trait. In this paper, we study the largest IgAN case-control cohort reported to date, composed of 10,775 individuals of European, Asian, and African-American ancestry. We confirm that all five loci are significant contributors to disease risk across this multi-ethnic cohort. In addition, we identify two novel independent susceptibility alleles within the HLA-DQB1/DRB1 locus and a new genetic interaction between loci on Chr.1p36 and Chr.22q22. We develop a seven–SNP genetic risk score that explains nearly 5% of variation in disease risk. In geospatial analysis of 85 world populations, the genetic risk score closely parallels worldwide patterns of disease prevalence. The genetic risk score also predicts an unsuspected Northward risk gradient in Europe. This genetic prediction is verified by examination of registry data demonstrating, similarly to other immune-mediated diseases such as multiple sclerosis and type I diabetes, a previously unrecognized increase in IgAN–attributable kidney failure in Northern European countries.
Although sudden cardiac death (SCD) is heritable, its genetic underpinnings are poorly characterized. The QT interval appears to have a graded relationship to SCD and 35–45% of its variation is heritable. We examined the relationship among recently reported common genetic variants, QT interval and SCD.
Methods and Results
We genotyped 15 common (minor allele frequency >1%) candidate SNPs, based on association to the QT interval in prior studies, in individuals in 2 cohort studies (Health 2000, n=6,597; Mini-Finland, n=801). After exclusions, we identified 116 incident SCDs from the remaining sample (n=6,808). We constructed a QT genotype score (QTscore) using the allele copy number and previously reported effect estimates for each SNP. Cox proportional hazards models adjusting for age, sex, and geographical area were used time to SCD analyses. The QTscore was a continuous independent predictor of the heart rate-corrected QT interval (P<10−107). Comparing the top to the bottom quintile of QTscore, there was a 15.6 msec higher group mean QT interval (P<10−84). A 10 msec increase in the observed QT was associated with an increased risk of SCD (HR 1.19, 95% CI 1.07–1.32, P=0.002). There was no linear relationship between QTscore and SCD risk; although, in post-hoc secondary analysis there was increased risk in the top compared with the middle QTscore quintile (HR of 1.92, 95% CI 1.05–3.58, P=0.04).
Our study strongly replicates the relationship between common genetic variants and the QT interval, confirms the relationship between the QT interval and SCD, but does not show evidence for a linear relationship between QTscore and SCD risk.
death; sudden; genetics; QT interval; electrocardiography; mortality; electrophysiology
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 (nFIN = 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 (pFIN = 3.01E-05, pICBP-GWAS = 0.0007, pALL = 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.
When multiple genes or genetic regions contribute to the inherited risk of a disease, it is referred to as a complex disease. Genome-wide association studies (GWAS) aim to detect common genetic variations that associate with complex traits or diseases. Although GWAS have been successful in identifying strongly associated genetic loci, they lack the means to point out true, but less strong, associations. Studying conditions that are related to the disease of interest can help sort out less strong associations. Intracranial aneurysms (IA) are berry-like dilations in cerebral arteries. Most IAs do not give symptoms until they bleed, causing a highly fatal form of stroke. Half of the people who suffer bleeding of an IA die. IA is a complex disease. Both inherited risk and environmental factors contribute to the risk of developing IA. Women, smokers, those with high alcohol intake or high blood pressure are more prone to develop IA and bleeding. GWAS found 19 genetic regions increasing the risk of IA. Here we show that one of these loci, on the long arm of chromosome 5, in addition to raising IA risk also increases systolic blood pressure. We speculate that the cause is modified vascular wall structure.
Although complex diseases and traits are thought to have multifactorial genetic basis, the common methods in genome-wide association analyses test each variant for association independent of the others. This computational simplification may lead to reduced power to identify variants with small effect sizes and requires correcting for multiple hypothesis tests with complex relationships. However, advances in computational methods and increase in computational resources are enabling the computation of models that adhere more closely to the theory of multifactorial inheritance. Here, a Bayesian variable selection and model averaging approach is formulated for searching for additive and dominant genetic effects. The approach considers simultaneously all available variants for inclusion as predictors in a linear genotype-phenotype mapping and averages over the uncertainty in the variable selection. This leads to naturally interpretable summary quantities on the significances of the variants and their contribution to the genetic basis of the studied trait. We first characterize the behavior of the approach in simulations. The results indicate a gain in the causal variant identification performance when additive and dominant variation are simulated, with a negligible loss of power in purely additive case. An application to the analysis of high- and low-density lipoprotein cholesterol levels in a dataset of 3895 Finns is then presented, demonstrating the feasibility of the approach at the current scale of single-nucleotide polymorphism data. We describe a Markov chain Monte Carlo algorithm for the computation and give suggestions on the specification of prior parameters using commonly available prior information. An open-source software implementing the method is available at http://www.lce.hut.fi/research/mm/bmagwa/ and https://github.com/to-mi/.
Common genetic variants have been shown to explain a fraction of the inherited variation for many common diseases and quantitative traits, including height, a classic polygenic trait. The extent to which common variation determines the phenotype of highly heritable traits such as height is uncertain, as is the extent to which common variation is relevant to individuals with more extreme phenotypes. To address these questions, we studied 1,214 individuals from the top and bottom extremes of the height distribution (tallest and shortest ∼1.5%), drawn from ∼78,000 individuals from the HUNT and FINRISK cohorts. We found that common variants still influence height at the extremes of the distribution: common variants (49/141) were nominally associated with height in the expected direction more often than is expected by chance (p<5×10−28), and the odds ratios in the extreme samples were consistent with the effects estimated previously in population-based data. To examine more closely whether the common variants have the expected effects, we calculated a weighted allele score (WAS), which is a weighted prediction of height for each individual based on the previously estimated effect sizes of the common variants in the overall population. The average WAS is consistent with expectation in the tall individuals, but was not as extreme as expected in the shortest individuals (p<0.006), indicating that some of the short stature is explained by factors other than common genetic variation. The discrepancy was more pronounced (p<10−6) in the most extreme individuals (height<0.25 percentile). The results at the extreme short tails are consistent with a large number of models incorporating either rare genetic non-additive or rare non-genetic factors that decrease height. We conclude that common genetic variants are associated with height at the extremes as well as across the population, but that additional factors become more prominent at the shorter extreme.
Although there are many loci in the human genome that have been discovered to be significantly associated with height, it is unclear if these loci have similar effects in extremely tall and short individuals. Here, we examine hundreds of extremely tall and short individuals in two population-based cohorts to see if these known height determining loci are as predictive as expected in these individuals. We found that these loci are generally as predictive of height as expected in these individuals but that they begin to be less predictive in the most extremely short individuals. We showed that this result is consistent with models that not only include the common variants but also multiple low frequency genetic variants that substantially decrease height. However, this result is also consistent with non-additive genetic effects or rare non-genetic factors that substantially decrease height. This finding suggests the possibility of a major role of low frequency variants, particularly in individuals with extreme phenotypes, and has implications on whole-genome or whole-exome sequencing efforts to discover rare genetic variation associated with complex traits.
USF1 is a ubiquitous transcription factor governing the expression of numerous genes of lipid and glucose metabolism. APOA5 is a well-established candidate gene regulating triglyceride (TG) levels and has been identified as a downstream target of upstream stimulatory factor. No detailed studies about the effect of APOA5 on atherosclerotic lesion formation have been conducted, nor has its potential interaction with USF1 been examined.
Methods and Results
We analyzed allelic variants of USF1 and APOA5 in families (n=516) ascertained for atherogenic dyslipidemia and in an autopsy series of middle-aged men (n=300) with precise quantitative measurements of atherosclerotic lesions. The impact of previously associated APOA5 variants on TGs was observed in the dyslipidemic families, and variant rs3135506 was associated with size of fibrotic aortic lesions in the autopsy series. The USF1 variant rs2516839, associated previously with atherosclerotic lesions, showed an effect on TGs in members of the dyslipidemic families with documented coronary artery disease. We provide preliminary evidence of gene-gene interaction between these variants in an autopsy series with a fibrotic lesion area in the abdominal aorta (P=0.0028), with TGs in dyslipidemic coronary artery disease subjects (P=0.03), and with high-density lipoprotein cholesterol (P=0.008) in a large population cohort of coronary artery disease patients (n=1065) in which the interaction for TGs was not replicated.
Our findings in these unique samples reinforce the roles of APOA5 and USF1 variants on cardiovascular phenotypes and suggest that both genes contribute to lipid levels and aortic atherosclerosis individually and possibly through epistatic effects.
genes; USF1; APOA5; lipids; atherosclerosis; epistasis
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.
Circulating serum lipids contribute greatly to the global health by affecting the risk for cardiovascular diseases. Serum lipid levels are partly inherited, and already 95 loci affecting high- and low-density lipoprotein cholesterol, total cholesterol, and triglycerides have been found. Serum lipids are also known to be affected by multiple epidemiological risk factors like body composition, lifestyle, and sex. It has been hypothesized that there are loci modifying the effects between risk factors and serum lipids, but to date only candidate gene studies for interactions have been reported. We conducted a genome-wide screen with meta-analysis approach to identify loci having interactions with epidemiological risk factors on serum lipids with over 30,000 population-based samples. When combining results from our initial datasets and 8 additional replication cohorts (maximum N = 17,102), we found a genome-wide significant locus in chromosome 4p15 with a joint P-value of 4.79×10−9 modifying the effect of waist-to-hip ratio on total cholesterol. In the area surrounding this genetic variant, there were two genes having association between the genotypes and the gene expression in adipose tissue, and we also found enrichment of association in genes belonging to lipid metabolism related functions.
We used the Tampere Autopsy Study (TASTY) series (n = 603, age 0-97 yrs), representing an unselected population outside institutions, to investigate the pathogenic involvement of inflammation in Alzheimer's disease-related lesions.
We studied senile plaque (SP), neurofibrillary tangles (NFT) and SP phenotype associations with 6 reported haplotype tagging single nucleotide polymorphisms (SNPs) in the CRP gene. CRP and Aβ immunohistochemistry was assessed using brain tissue microarrays.
In multivariate analyses (age- and APOE-adjusted), non-neuritic SP were associated with the high-CRP TA-genotype (3.0% prevalence) of rs3091244 and CA-genotype (10.8%) of rs3093075 compared to common genotypes. Conversely, the low-CRP C allele (39.3%) of rs2794521 reduced the risk of harbouring early non-neuritic SP, compared to the TT genotype. CRP haplotype TAGCC (high) associated with non-neuritic SP, whereas haplotype CCGCC offered protection. TT genotypes (high) of rs3091244 and rs1130864 were associated with CRP staining. There were no associations between SNPs or haplotypes and NFT. CRP staining of the hippocampal CA1/2 region correlated with Aβ staining.
CRP gene variation affects early SP development in prodromal Alzheimer's disease, independent of APOE genotype.
The integrated analysis of genotypic and expression data for association with complex traits could identify novel genetic pathways involved in complex traits. We profiled 19,573 expression probes in Epstein-Barr virus-transformed lymphoblastoid cell lines (LCLs) from 299 twins and correlated these with 44 quantitative traits (QTs). For 939 expressed probes correlating with more than one QT, we investigated the presence of eQTL associations in three datasets of 57 CEU HapMap founders and 86 unrelated twins. Genome-wide association analysis of these probes with 2.2 m SNPs revealed 131 potential eQTLs (1,989 eQTL SNPs) overlapping between the HapMap datasets, five of which were in cis (58 eQTL SNPs). We then tested 535 SNPs tagging the eQTL SNPs, for association with the relevant QT in 2,905 twins. We identified nine potential SNP-QT associations (P<0.01) but none significantly replicated in five large consortia of 1,097–16,129 subjects. We also failed to replicate previous reported eQTL associations with body mass index, plasma low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides levels derived from lymphocytes, adipose and liver tissue. Our results and additional power calculations suggest that proponents may have been overoptimistic in the power of LCLs in eQTL approaches to elucidate regulatory genetic effects on complex traits using the small datasets generated to date. Nevertheless, larger tissue-specific expression data sets relevant to specific traits are becoming available, and should enable the adoption of similar integrated analyses in the near future.
Restless legs syndrome (RLS) is a sensorimotor disorder with an age-dependent prevalence of up to 10% in the general population above 65 years of age. Affected individuals suffer from uncomfortable sensations and an urge to move in the lower limbs that occurs mainly in resting situations during the evening or at night. Moving the legs or walking leads to an improvement of symptoms. Concomitantly, patients report sleep disturbances with consequences such as reduced daytime functioning. We conducted a genome-wide association study (GWA) for RLS in 922 cases and 1,526 controls (using 301,406 SNPs) followed by a replication of 76 candidate SNPs in 3,935 cases and 5,754 controls, all of European ancestry. Herein, we identified six RLS susceptibility loci of genome-wide significance, two of them novel: an intergenic region on chromosome 2p14 (rs6747972, P = 9.03 × 10−11, OR = 1.23) and a locus on 16q12.1 (rs3104767, P = 9.4 × 10−19, OR = 1.35) in a linkage disequilibrium block of 140 kb containing the 5′-end of TOX3 and the adjacent non-coding RNA BC034767.
Restless legs syndrome (RLS) is one of the most common neurological disorders. Patients with RLS suffer from an urge to move the legs and unpleasant sensations located mostly deep in the calf. Symptoms mainly occur in resting situations in the evening or at night. As a consequence, initiation and maintenance of sleep become defective. Here, we performed a genome-wide association study to identify common genetic variants increasing the risk for disease. The genome-wide phase included 922 cases and 1,526 controls, and candidate SNPs were replicated in 3,935 cases and 5,754 controls, all of European ancestry. We identified two new RLS–associated loci: an intergenic region on chromosome 2p14 and a locus on 16q12.1 in a linkage disequilibrium block containing the 5′-end of TOX3 and the adjacent non-coding RNA BC034767. TOX3 has been implicated in the development of breast cancer. The physiologic role of TOX3 and BC034767 in the central nervous system and a possible involvement of these two genes in RLS pathogenesis remain to be established.
The lipid–leukocyte (LL) module is associated with, and reactive to, a wide variety of serum metabolites.The LL module appears to be a link between metabolism, adiposity, and inflammation.Serum metabolite concentrations themselves determine the connectedness of LL module.
Comprehensive characterization of human tissues promises novel insights into the biological architecture of human diseases and traits. We assessed metabonomic, transcriptomic, and genomic variation for a large population-based cohort from the capital region of Finland. Network analyses identified a set of highly correlated genes, the lipid–leukocyte (LL) module, as having a prominent role in over 80 serum metabolites (of 134 measures quantified), including lipoprotein subclasses, lipids, and amino acids. Concurrent association with immune response markers suggested the LL module as a possible link between inflammation, metabolism, and adiposity. Further, genomic variation was used to generate a directed network and infer LL module's largely reactive nature to metabolites. Finally, gene co-expression in circulating leukocytes was shown to be dependent on serum metabolite concentrations, providing evidence for the hypothesis that the coherence of molecular networks themselves is conditional on environmental factors. These findings show the importance and opportunity of systematic molecular investigation of human population samples. To facilitate and encourage this investigation, the metabonomic, transcriptomic, and genomic data used in this study have been made available as a resource for the research community.
bioinformatics; biological networks; integrative genomics; metabonomics; transcriptomics
Comparison of patients with coronary heart disease and controls in genome-wide association studies has revealed several single nucleotide polymorphisms (SNPs) associated with coronary heart disease. We aimed to establish the external validity of these findings and to obtain more precise risk estimates using a prospective cohort design.
We tested 13 recently discovered SNPs for association with coronary heart disease in a case-control design including participants differing from those in the discovery samples (3829 participants with prevalent coronary heart disease and 48 897 controls free of the disease) and a prospective cohort design including 30 725 participants free of cardiovascular disease from Finland and Sweden. We modelled the 13 SNPs as a multilocus genetic risk score and used Cox proportional hazards models to estimate the association of genetic risk score with incident coronary heart disease. For case-control analyses we analysed associations between individual SNPs and quintiles of genetic risk score using logistic regression.
In prospective cohort analyses, 1264 participants had a first coronary heart disease event during a median 10·7 years' follow-up (IQR 6·7–13·6). Genetic risk score was associated with a first coronary heart disease event. When compared with the bottom quintile of genetic risk score, participants in the top quintile were at 1·66-times increased risk of coronary heart disease in a model adjusting for traditional risk factors (95% CI 1·35–2·04, p value for linear trend=7·3×10−10). Adjustment for family history did not change these estimates. Genetic risk score did not improve C index over traditional risk factors and family history (p=0·19), nor did it have a significant effect on net reclassification improvement (2·2%, p=0·18); however, it did have a small effect on integrated discrimination index (0·004, p=0·0006). Results of the case-control analyses were similar to those of the prospective cohort analyses.
Using a genetic risk score based on 13 SNPs associated with coronary heart disease, we can identify the 20% of individuals of European ancestry who are at roughly 70% increased risk of a first coronary heart disease event. The potential clinical use of this panel of SNPs remains to be defined.
The Wellcome Trust; Academy of Finland Center of Excellence for Complex Disease Genetics; US National Institutes of Health; the Donovan Family Foundation.
A cluster of three nicotinic acetylcholine receptor genes on chromosome 15 (CHRNA5/CHRNA3/CHRNB4) has been shown to be associated with nicotine dependence and smoking quantity. The aim of this study was to clarify whether the variation at this locus regulates nicotine intake among smokers by using the level of a metabolite of nicotine, cotinine, as an outcome. The number of cigarettes smoked per day (CPD) and immune-reactive serum cotinine level were determined in 516 daily smokers (age 30–75 years, 303 males) from the population-based Health2000 study. Association of 21 SNPs from a 100 kb region of chromosome 15 with cotinine and CPD was examined. SNP rs1051730 showed the strongest association to both measures. However, this SNP accounted for nearly a five-fold larger proportion of variance in cotinine levels than in CPD (R2 4.3% versus 0.9%). The effect size of the SNP was 0.30 for cotinine level, whereas it was 0.13 for CPD. Variation at CHRNA5/CHRNA3/CHRNB4 cluster influences nicotine level, measured as cotinine, more strongly than smoking quantity, measured by CPD, and appears thus to be involved in regulation of nicotine levels among smokers.
While recent scans for genetic variation associated with human disease have been immensely successful in uncovering large numbers of loci, far fewer studies have focused on the underlying pathways of disease pathogenesis. Many loci which are associated with disease and complex phenotypes map to non-coding, regulatory regions of the genome, indicating that modulation of gene transcription plays a key role. Thus, this study generated genome-wide profiles of both genetic and transcriptional variation from the total blood extracts of over 500 randomly-selected, unrelated individuals. Using measurements of blood lipids, key players in the progression of atherosclerosis, three levels of biological information are integrated in order to investigate the interactions between circulating leukocytes and proximal lipid compounds. Pair-wise correlations between gene expression and lipid concentration indicate a prominent role for basophil granulocytes and mast cells, cell types central to powerful allergic and inflammatory responses. Network analysis of gene co-expression showed that the top associations function as part of a single, previously unknown gene module, the Lipid Leukocyte (LL) module. This module replicated in T cells from an independent cohort while also displaying potential tissue specificity. Further, genetic variation driving LL module expression included the single nucleotide polymorphism (SNP) most strongly associated with serum immunoglobulin E (IgE) levels, a key antibody in allergy. Structural Equation Modeling (SEM) indicated that LL module is at least partially reactive to blood lipid levels. Taken together, this study uncovers a gene network linking blood lipids and circulating cell types and offers insight into the hypothesis that the inflammatory response plays a prominent role in metabolism and the potential control of atherogenesis.
Circulating lipid concentrations are important predictors of coronary artery disease. The main pathology of coronary artery disease is atherosclerosis, a cycle of lipid adherence to the walls of arteries and an inflammatory response resulting in more adhesion. To investigate the link between lipids and immune cells in circulation, we have generated both genomic and whole blood gene expression profiles for a population-based collection of individuals from the capital region of Finland. Key mediators of inflammation and allergy were shown to be correlated with lipid levels. Further, the expressions of these genes operated in such a highly coordinated fashion that they appeared to function as part of a single pathway, which itself was both highly correlated with and reactive to lipid levels. Our findings offer insight into how lipids activate circulating immune cells, potentially contributing to the pathogenesis of coronary artery disease.