Epidemiological studies have shown that short or insufficient sleep is associated with increased risk for metabolic diseases and mortality. To elucidate mechanisms behind this connection, we aimed to identify genes and pathways affected by experimentally induced, partial sleep restriction and to verify their connection to insufficient sleep at population level. The experimental design simulated sleep restriction during a working week: sleep of healthy men (N = 9) was restricted to 4 h/night for five nights. The control subjects (N = 4) spent 8 h/night in bed. Leukocyte RNA expression was analyzed at baseline, after sleep restriction, and after recovery using whole genome microarrays complemented with pathway and transcription factor analysis. Expression levels of the ten most up-regulated and ten most down-regulated transcripts were correlated with subjective assessment of insufficient sleep in a population cohort (N = 472). Experimental sleep restriction altered the expression of 117 genes. Eight of the 25 most up-regulated transcripts were related to immune function. Accordingly, fifteen of the 25 most up-regulated Gene Ontology pathways were also related to immune function, including those for B cell activation, interleukin 8 production, and NF-κB signaling (P<0.005). Of the ten most up-regulated genes, expression of STX16 correlated negatively with self-reported insufficient sleep in a population sample, while three other genes showed tendency for positive correlation. Of the ten most down-regulated genes, TBX21 and LGR6 correlated negatively and TGFBR3 positively with insufficient sleep. Partial sleep restriction affects the regulation of signaling pathways related to the immune system. Some of these changes appear to be long-lasting and may at least partly explain how prolonged sleep restriction can contribute to inflammation-associated pathological states, such as cardiometabolic diseases.
Exploring genetic pleiotropy can provide clues to a mechanism underlying the observed epidemiological association between type 2 diabetes and heightened fracture risk. We examined genetic variants associated with bone mineral density (BMD) for association with type 2 diabetes and glycemic traits in large well-phenotyped and -genotyped consortia. We undertook follow-up analysis in ∼19,000 individuals and assessed gene expression. We queried single nucleotide polymorphisms (SNPs) associated with BMD at levels of genome-wide significance, variants in linkage disequilibrium (r2 > 0.5), and BMD candidate genes. SNP rs6867040, at the ITGA1 locus, was associated with a 0.0166 mmol/L (0.004) increase in fasting glucose per C allele in the combined analysis. Genetic variants in the ITGA1 locus were associated with its expression in the liver but not in adipose tissue. ITGA1 variants appeared among the top loci associated with type 2 diabetes, fasting insulin, β-cell function by homeostasis model assessment, and 2-h post–oral glucose tolerance test glucose and insulin levels. ITGA1 has demonstrated genetic pleiotropy in prior studies, and its suggested role in liver fibrosis, insulin secretion, and bone healing lends credence to its contribution to both osteoporosis and type 2 diabetes. These findings further underscore the link between skeletal and glucose metabolism and highlight a locus to direct future investigations.
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
The role of the nicotinic acetylcholine receptor gene cluster on chromosome 15q24-25 in the etiology of nicotine dependence (ND) is still being defined. In this study, we included all 15 tagging single nucleotide polymorphisms (SNPs) within the CHRNA5-CHRNA3-CHRNB4 cluster and tested associations with 30 smoking-related phenotypes.
The study sample was ascertained from the Finnish Twin Cohort study. Twin pairs born 1938–1957 and concordant for a history of cigarette smoking were recruited along with their family members (mainly siblings), as part of the Nicotine Addiction Genetics consortium. The study sample consisted of 1,428 individuals (59% males) from 735 families, with mean age 55.6 years.
We detected multiple novel associations for ND. DSM-IV ND symptoms associated significantly with the proxy SNP Locus 1 (rs2036527, p = .000009) and Locus 2 (rs578776, p = .0001) and tolerance factor of the Nicotine Dependence Syndrome Scale (NDSS) showed suggestive association to rs11636753 (p = .0059), rs11634351 (p = .0069), and rs1948 (p = .0071) in CHRNB4. Furthermore, we report significant association with DSM-IV ND diagnosis (rs2036527, p = .0003) for the first time in a Caucasian population. Several SNPs indicated suggestive association for traits related to ages at smoking initiation. Also, rs11636753 in CHRNB4 showed suggestive association with regular drinking (p = .0029) and the comorbidity of depression and ND (p = .0034).
We demonstrate novel associations of DSM-IV ND symptoms and the NDSS tolerance subscale. Our results confirm and extend association findings for other ND measures. We show pleiotropic effects of this gene cluster on multiple measures of ND and also regular drinking and the comorbidity of ND and depression.
Metabolite associations with insulin resistance were studied in 7,098 young Finns (age 31 ± 3 years; 52% women) to elucidate underlying metabolic pathways. Insulin resistance was assessed by the homeostasis model (HOMA-IR) and circulating metabolites quantified by high-throughput nuclear magnetic resonance spectroscopy in two population-based cohorts. Associations were analyzed using regression models adjusted for age, waist, and standard lipids. Branched-chain and aromatic amino acids, gluconeogenesis intermediates, ketone bodies, and fatty acid composition and saturation were associated with HOMA-IR (P < 0.0005 for 20 metabolite measures). Leu, Ile, Val, and Tyr displayed sex- and obesity-dependent interactions, with associations being significant for women only if they were abdominally obese. Origins of fasting metabolite levels were studied with dietary and physical activity data. Here, protein energy intake was associated with Val, Phe, Tyr, and Gln but not insulin resistance index. We further tested if 12 genetic variants regulating the metabolites also contributed to insulin resistance. The genetic determinants of metabolite levels were not associated with HOMA-IR, with the exception of a variant in GCKR associated with 12 metabolites, including amino acids (P < 0.0005). Nonetheless, metabolic signatures extending beyond obesity and lipid abnormalities reflected the degree of insulin resistance evidenced in young, normoglycemic adults with sex-specific fingerprints.
Early pubertal onset in females is associated with increased risk for adult obesity and cardiovascular disease, but whether this relationship is independent of preceding childhood growth events is unclear. Furthermore, the association between male puberty and adult disease remains unknown. To clarify the link between puberty and adult health, we evaluated the relationship between pubertal timing and risk factors for type 2 diabetes and cardiovascular disease in both males and females from a large, prospective, and randomly ascertained birth cohort from Northern Finland.
RESEARCH DESIGN AND METHODS
Pubertal timing was estimated based on pubertal height growth in 5,058 subjects (2,417 males and 2,641 females), and the relationship between puberty and body weight, glucose and lipid homeostasis, and blood pressure at age 31 years was evaluated with linear regression modeling.
Earlier pubertal timing associated with higher adult BMI, fasting insulin, diastolic blood pressure, and decreased HDL cholesterol in both sexes (P < 0.002) and with higher total serum cholesterol, LDL cholesterol, and triglycerides in males. The association with BMI and diastolic blood pressure remained statistically significant in both sexes, as did the association with insulin levels and HDL cholesterol concentrations in males after adjusting for covariates reflecting both fetal and childhood growth including childhood BMI.
We demonstrate independent association between earlier pubertal timing and adult metabolic syndrome-related derangements both in males and females. The connection emphasizes that the mechanisms advancing puberty may also contribute to adult metabolic disorders.
During the past ten years the field of human disease genetics has made major leaps, including the completion of the Human Genome Project, the HapMap Project, the development of the genome-wide association (GWA) studies to identify common disease-predisposing variants and the introduction of large-scale whole-genome and whole-exome sequencing studies. The introduction of new technologies has enabled researchers to utilize novel study designs to tackle previously unexplored research questions in human genomics. These new types of studies typically need large sample sizes to overcome the multiple testing challenges caused by the huge number of interrogated genetic variants. As a consequence, large consortia-studies are at present the default in disease genetics research. The systematic planning of the GWA-studies was a key element in the success of the approach. Similar planning and rigor in statistical inferences will probably be beneficial also to future sequencing studies. Already today, the next-generation exome sequencing has led to the identification of several genes underlying Mendelian diseases. In spite of the clear benefits, the method has proven to be more challenging than anticipated. In the case of complex diseases, next-generation sequencing aims to identify disease-associated low-frequency alleles. However, their robust detection will require very large study samples, even larger than in the case of the GWA-studies. This has stimulated study designs that capitalize on enriching sets of low-frequency alleles, for example, studies focusing on population isolates such as Finland or Iceland. One example is the collaborative SISu Project (Sequencing Initiative Suomi) that aims to provide near complete genome variation information from Finnish study samples and pave the way for large, nationwide genome health initiative studies.
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.
Several studies examined the fine-scale structure of human genetic variation in Europe. However, the European sets analyzed represent mainly northern, western, central, and southern Europe. Here, we report an analysis of approximately 166,000 single nucleotide polymorphisms in populations from eastern (northeastern) Europe: four Russian populations from European Russia, and three populations from the northernmost Finno-Ugric ethnicities (Veps and two contrast groups of Komi people). These were compared with several reference European samples, including Finns, Estonians, Latvians, Poles, Czechs, Germans, and Italians. The results obtained demonstrated genetic heterogeneity of populations living in the region studied. Russians from the central part of European Russia (Tver, Murom, and Kursk) exhibited similarities with populations from central–eastern Europe, and were distant from Russian sample from the northern Russia (Mezen district, Archangelsk region). Komi samples, especially Izhemski Komi, were significantly different from all other populations studied. These can be considered as a second pole of genetic diversity in northern Europe (in addition to the pole, occupied by Finns), as they had a distinct ancestry component. Russians from Mezen and the Finnic-speaking Veps were positioned between the two poles, but differed from each other in the proportions of Komi and Finnic ancestries. In general, our data provides a more complete genetic map of Europe accounting for the diversity in its most eastern (northeastern) populations.
Clinical relevance of a genetic predisposition to elevated blood pressure was quantified during the transition from childhood to adulthood in a population-based Finnish cohort (N=2,357). Blood pressure was measured at baseline in 1980 (age 3–18 years) and in follow-ups in 1983, 1986, 2001 and 2007. Thirteen single nucleotide polymorphisms associated with blood pressure were genotyped and three genetic risk scores associated with systolic and diastolic blood pressure and their combination were derived for all participants. Effects of the genetic risk score were 0.47 mmHg for systolic and 0.53 mmHg for diastolic blood pressure (both p<0.01). The combination genetic risk score was associated with diastolic blood pressure from age 9 onwards (β=0.68 mmHg, p=0.015). Replications in 1194 participants of the Bogalusa Heart Study showed essentially similar results. The participants in the highest quintile of the combination genetic risk score had a 1.82-fold risk of hypertension in adulthood (p<0.0001) compared with the lowest quintile, independent of a family history of premature hypertension. These findings show that genetic variants are associated with preclinical blood pressure traits in childhood, individuals with several susceptibility alleles have on average a 0.5 mmHg higher blood pressure and this trajectory continues from childhood to adulthood.
Epidemiological study; Genetic risk score; Blood Pressure; Cardiovascular disease
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.
High plasma HDL cholesterol is associated with reduced risk of myocardial infarction, but whether this association is causal is unclear. Exploiting the fact that genotypes are randomly assigned at meiosis, are independent of non-genetic confounding, and are unmodified by disease processes, mendelian randomisation can be used to test the hypothesis that the association of a plasma biomarker with disease is causal.
We performed two mendelian randomisation analyses. First, we used as an instrument a single nucleotide polymorphism (SNP) in the endothelial lipase gene (LIPG Asn396Ser) and tested this SNP in 20 studies (20 913 myocardial infarction cases, 95 407 controls). Second, we used as an instrument a genetic score consisting of 14 common SNPs that exclusively associate with HDL cholesterol and tested this score in up to 12 482 cases of myocardial infarction and 41 331 controls. As a positive control, we also tested a genetic score of 13 common SNPs exclusively associated with LDL cholesterol.
Carriers of the LIPG 396Ser allele (2·6% frequency) had higher HDL cholesterol (0·14 mmol/L higher, p=8×10−13) but similar levels of other lipid and non-lipid risk factors for myocardial infarction compared with non-carriers. This difference in HDL cholesterol is expected to decrease risk of myocardial infarction by 13% (odds ratio [OR] 0·87, 95% CI 0·84–0·91). However, we noted that the 396Ser allele was not associated with risk of myocardial infarction (OR 0·99, 95% CI 0·88–1·11, p=0·85). From observational epidemiology, an increase of 1 SD in HDL cholesterol was associated with reduced risk of myocardial infarction (OR 0·62, 95% CI 0·58–0·66). However, a 1 SD increase in HDL cholesterol due to genetic score was not associated with risk of myocardial infarction (OR 0·93, 95% CI 0·68–1·26, p=0·63). For LDL cholesterol, the estimate from observational epidemiology (a 1 SD increase in LDL cholesterol associated with OR 1·54, 95% CI 1·45–1·63) was concordant with that from genetic score (OR 2·13, 95% CI 1·69–2·69, p=2×10−10).
Some genetic mechanisms that raise plasma HDL cholesterol do not seem to lower risk of myocardial infarction. These data challenge the concept that raising of plasma HDL cholesterol will uniformly translate into reductions in risk of myocardial infarction.
US National Institutes of Health, The Wellcome Trust, European Union, British Heart Foundation, and the German Federal Ministry of Education and Research.
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.
Psychological stress is suggested to accelerate the rate of biological aging. We investigated whether work-related exhaustion, an indicator of prolonged work stress, is associated with accelerated biological aging, as indicated by shorter leukocyte telomeres, that is, the DNA-protein complexes that cap chromosomal ends in cells.
We used data from a representative sample of the Finnish working-age population, the Health 2000 Study. Our sample consisted of 2911 men and women aged 30–64. Work-related exhaustion was assessed using the Maslach Burnout Inventory - General Survey. We determined relative leukocyte telomere length using a quantitative real-time polymerase chain reaction (PCR) -based method.
After adjustment for age and sex, individuals with severe exhaustion had leukocyte telomeres on average 0.043 relative units shorter (standard error of the mean 0.016) than those with no exhaustion (p = 0.009). The association between exhaustion and relative telomere length remained significant after additional adjustment for marital and socioeconomic status, smoking, body mass index, and morbidities (adjusted difference 0.044 relative units, standard error of the mean 0.017, p = 0.008).
These data suggest that work-related exhaustion is related to the acceleration of the rate of biological aging. This hypothesis awaits confirmation in a prospective study measuring changes in relative telomere length over time.
Phenotype mining is a novel approach for elucidating the genetic basis of complex phenotypic variation. It involves a search of rich phenotype databases for measures correlated with genetic variation, as identified in genome-wide genotyping or sequencing studies. An initial implementation of phenotype mining in a prospective unselected population cohort, the Northern Finland 1966 Birth Cohort (NFBC1966), identifies neurodevelopment-related traits—intellectual deficits, poor school performance and hearing abnormalities—which are more frequent among individuals with large (>500 kb) deletions than among other cohort members. Observation of extensive shared single nucleotide polymorphism haplotypes around deletions suggests an opportunity to expand phenotype mining from cohort samples to the populations from which they derive.
To get insight into molecular mechanisms underlying insulin resistance, we compared acute in vivo effects of insulin on adipose tissue transcriptional profiles between obese insulin-resistant and lean insulin-sensitive women.
Subcutaneous adipose tissue biopsies were obtained before and after 3 and 6 hours of intravenously maintained euglycemic hyperinsulinemia from 9 insulin-resistant and 11 insulin-sensitive females. Gene expression was measured using Affymetrix HG U133 Plus 2 microarrays and qRT-PCR. Microarray data and pathway analyses were performed with Chipster v1.4.2 and by using in-house developed nonparametric pathway analysis software.
The most prominent difference in gene expression of the insulin-resistant group during hyperinsulinemia was reduced transcription of nuclear genes involved in mitochondrial respiration (mitochondrial respiratory chain, GO:0001934). Inflammatory pathways with complement components (inflammatory response, GO:0006954) and cytokines (chemotaxis, GO:0042330) were strongly up-regulated in insulin-resistant as compared to insulin-sensitive subjects both before and during hyperinsulinemia. Furthermore, differences were observed in genes contributing to fatty acid, cholesterol and triglyceride metabolism (FATP2, ELOVL6, PNPLA3, SREBF1) and in genes involved in regulating lipolysis (ANGPTL4) between the insulin-resistant and -sensitive subjects especially during hyperinsulinemia.
The major finding of this study was lower expression of mitochondrial respiratory pathway and defective induction of lipid metabolism pathways by insulin in insulin-resistant subjects. Moreover, the study reveals several novel genes whose aberrant regulation is associated with the obese insulin-resistant phenotype.
Rationale: Genomic loci are associated with FEV1 or the ratio of FEV1 to FVC in population samples, but their association with chronic obstructive pulmonary disease (COPD) has not yet been proven, nor have their combined effects on lung function and COPD been studied.
Objectives: To test association with COPD of variants at five loci (TNS1, GSTCD, HTR4, AGER, and THSD4) and to evaluate joint effects on lung function and COPD of these single-nucleotide polymorphisms (SNPs), and variants at the previously reported locus near HHIP.
Methods: By sampling from 12 population-based studies (n = 31,422), we obtained genotype data on 3,284 COPD case subjects and 17,538 control subjects for sentinel SNPs in TNS1, GSTCD, HTR4, AGER, and THSD4. In 24,648 individuals (including 2,890 COPD case subjects and 13,862 control subjects), we additionally obtained genotypes for rs12504628 near HHIP. Each allele associated with lung function decline at these six SNPs contributed to a risk score. We studied the association of the risk score to lung function and COPD.
Measurements and Main Results: Association with COPD was significant for three loci (TNS1, GSTCD, and HTR4) and the previously reported HHIP locus, and suggestive and directionally consistent for AGER and TSHD4. Compared with the baseline group (7 risk alleles), carrying 10–12 risk alleles was associated with a reduction in FEV1 (β = –72.21 ml, P = 3.90 × 10−4) and FEV1/FVC (β = –1.53%, P = 6.35 × 10−6), and with COPD (odds ratio = 1.63, P = 1.46 × 10−5).
Conclusions: Variants in TNS1, GSTCD, and HTR4 are associated with COPD. Our highest risk score category was associated with a 1.6-fold higher COPD risk than the population average score.
FEV1; FVC; genome-wide association study; modeling risk
Attrition in longitudinal studies can lead to biased results. The study is motivated by the unexpected observation that alcohol consumption decreased despite of increased availability, which may be due to sample attrition of heavy drinkers. Several imputation methods have been proposed, but rarely compared in longitudinal studies of alcohol consumption. The imputation of consumption level measurements is computationally particularly challenging due to alcohol consumption being a semi-continuous variable (dichotomous drinking status and continuous volume among drinkers), and the non-normality of data in the continuous part. Data come from a longitudinal study in Denmark with four waves (2003–2006) and 1771 individuals at baseline. Five techniques for missing data are compared: Last value carried forward (LVCF) was used as a single, and Hotdeck, Heckman modelling, multivariate imputation by chained equations (MICE), and a Bayesian approach as multiple imputation methods. Predictive mean matching was used to account for non-normality, where instead of imputing regression estimates, “real” observed values from similar cases are imputed. Methods were also compared by means of a simulated dataset. The simulation showed that the Bayesian approach yielded the most unbiased estimates for imputation. The finding of no increase in consumption levels despite a higher availability remained unaltered.
panel surveys; missing data; multiple imputation; Bayesian models; alcohol consumption
Genome-wide association studies (GWASs) have identified a large number of variants (SNPs) associating with an increased risk of coronary artery disease (CAD). Recently, the CARDIoGRAM consortium published a GWAS based on the largest study population so far. They successfully replicated twelve already known associations and discovered thirteen new SNPs associating with CAD. We examined whether the genetic profiling of these variants improves prediction of subclinical atherosclerosis – i.e., carotid intima-media thickness (CIMT) and carotid artery elasticity (CAE) – beyond classical risk factors.
Subjects and Methods
We genotyped 24 variants found in a population of European ancestry and measured CIMT and CAE in 2001 and 2007 from 2,081, and 2,015 subjects (aged 30–45 years in 2007) respectively, participating in the Cardiovascular Risk in Young Finns Study (YFS). The Bogalusa Heart Study (BHS; n = 1179) was used as a replication cohort (mean age of 37.5). For additional replication, a sub-sample of 5 SNPs was genotyped for 1,291 individuals aged 46–76 years participating in the Health 2000 population survey. We tested the impact of genetic risk score (GRS24SNP/CAD) calculated as a weighted (by allelic odds ratios for CAD) sum of CAD risk alleles from the studied 24 variants on CIMT, CAE, the incidence of carotid atherosclerosis and the progression of CIMT and CAE during a 6-year follow-up.
CIMT or CAE did not significantly associate with GRS24SNP/CAD before or after adjusting for classical CAD risk factors (p>0.05 for all) in YFS or in the BHS. CIMT and CAE associated with only one SNP each in the YFS. The findings were not replicated in the replication cohorts. In the meta-analysis CIMT or CAE did not associate with any of the SNPs.
Genetic profiling, by using known CAD risk variants, should not improve risk stratification for subclinical atherosclerosis beyond conventional risk factors among healthy young adults.
A cost-efficient way to increase power in a genetic association study is to pool controls from different sources. The genotyping effort can then be directed to large case series. The Nordic Control database, NordicDB, has been set up as a unique resource in the Nordic area and the data are available for authorized users through the web portal (http://www.nordicdb.org). The current version of NordicDB pools together high-density genome-wide SNP information from ∼5000 controls originating from Finnish, Swedish and Danish studies and shows country-specific allele frequencies for SNP markers. The genetic homogeneity of the samples was investigated using multidimensional scaling (MDS) analysis and pairwise allele frequency differences between the studies. The plot of the first two MDS components showed excellent resemblance to the geographical placement of the samples, with a clear NW–SE gradient. We advise researchers to assess the impact of population structure when incorporating NordicDB controls in association studies. This harmonized Nordic database presents a unique genome-wide resource for future genetic association studies in the Nordic countries.
common controls; genome-wide data; Nordic Control Database; population stratification
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
Patterns of genetic diversity have previously been shown to mirror geography on a global scale and within continents and individual countries. Using genome-wide SNP data on 5174 Swedes with extensive geographical coverage, we analyzed the genetic structure of the Swedish population. We observed strong differences between the far northern counties and the remaining counties. The population of Dalarna county, in north middle Sweden, which borders southern Norway, also appears to differ markedly from other counties, possibly due to this county having more individuals with remote Finnish or Norwegian ancestry than other counties. An analysis of genetic differentiation (based on pairwise Fst) indicated that the population of Sweden's southernmost counties are genetically closer to the HapMap CEU samples of Northern European ancestry than to the populations of Sweden's northernmost counties. In a comparison of extended homozygous segments, we detected a clear divide between southern and northern Sweden with small differences between the southern counties and considerably more segments in northern Sweden. Both the increased degree of homozygosity in the north and the large genetic differences between the south and the north may have arisen due to a small population in the north and the vast geographical distances between towns and villages in the north, in contrast to the more densely settled southern parts of Sweden. Our findings have implications for future genome-wide association studies (GWAS) with respect to the matching of cases and controls and the need for within-county matching. We have shown that genetic differences within a single country may be substantial, even when viewed on a European scale. Thus, population stratification needs to be accounted for, even within a country like Sweden, which is often perceived to be relatively homogenous and a favourable resource for genetic mapping, otherwise inferences based on genetic data may lead to false conclusions.
C-reactive protein (CRP) is a heritable marker of chronic inflammation that is strongly associated with cardiovascular disease. We aimed to identify genetic variants that are associated with CRP levels.
Methods and Results
We performed a genome wide association (GWA) analysis of CRP in 66,185 participants from 15 population-based studies. We sought replication for the genome wide significant and suggestive loci in a replication panel comprising 16,540 individuals from ten independent studies. We found 18 genome-wide significant loci and we provided evidence of replication for eight of them. Our results confirm seven previously known loci and introduce 11 novel loci that are implicated in pathways related to the metabolic syndrome (APOC1, HNF1A, LEPR, GCKR, HNF4A, and PTPN2), immune system (CRP, IL6R, NLRP3, IL1F10, and IRF1), or that reside in regions previously not known to play a role in chronic inflammation (PPP1R3B, SALL1, PABPC4, ASCL1, RORA, and BCL7B). We found significant interaction of body mass index (BMI) with LEPR (p<2.9×10−6). A weighted genetic risk score that was developed to summarize the effect of risk alleles was strongly associated with CRP levels and explained approximately 5% of the trait variance; however, there was no evidence for these genetic variants explaining the association of CRP with coronary heart disease.
We identified 18 loci that were associated with CRP levels. Our study highlights immune response and metabolic regulatory pathways involved in the regulation of chronic inflammation.
genome-wide association; C-reactive protein; inflammation; epidemiology; coronary heart disease