A trans-acting locus regulates an anti-viral expression network and type 1 diabetes risk.

Combined analyses of gene networks and DNA sequence variation can provide new insights into the aetiology of common diseases that may not be apparent from genome-wide association studies alone. Recent advances in rat genomics are facilitating systems-genetics approaches. Here we report the use of integrated genome-wide approaches across seven rat tissues to identify gene networks and the loci underlying their regulation. We defined an interferon regulatory factor 7 (IRF7)-driven inflammatory network (IDIN) enriched for viral response genes, which represents a molecular biomarker for macrophages and which was regulated in multiple tissues by a locus on rat chromosome 15q25. We show that Epstein-Barr virus induced gene 2 (Ebi2, also known as Gpr183), which lies at this locus and controls B lymphocyte migration, is expressed in macrophages and regulates the IDIN. The human orthologous locus on chromosome 13q32 controlled the human equivalent of the IDIN, which was conserved in monocytes. IDIN genes were more likely to associate with susceptibility to type 1 diabetes (T1D)-a macrophage-associated autoimmune disease-than randomly selected immune response genes (P = 8.85 × 10(-6)). The human locus controlling the IDIN was associated with the risk of T1D at single nucleotide polymorphism rs9585056 (P = 7.0 × 10(-10); odds ratio, 1.15), which was one of five single nucleotide polymorphisms in this region associated with EBI2 (GPR183) expression. These data implicate IRF7 network genes and their regulatory locus in the pathogenesis of T1D.

Genome-wide haplotype analysis of cis expression quantitative trait loci in monocytes.

In order to assess whether gene expression variability could be influenced by several SNPs acting in cis, either through additive or more complex haplotype effects, a systematic genome-wide search for cis haplotype expression quantitative trait loci (eQTL) was conducted in a sample of 758 individuals, part of the Cardiogenics Transcriptomic Study, for which genome-wide monocyte expression and GWAS data were available. 19,805 RNA probes were assessed for cis haplotypic regulation through investigation of ~2,1 × 10(9) haplotypic combinations. 2,650 probes demonstrated haplotypic p-values >10(4)-fold smaller than the best single SNP p-value. Replication of significant haplotype effects were tested for 412 probes for which SNPs (or proxies) that defined the detected haplotypes were available in the Gutenberg Health Study composed of 1,374 individuals. At the Bonferroni correction level of 1.2 × 10(-4) (~0.05/412), 193 haplotypic signals replicated. 1000 G imputation was then conducted, and 105 haplotypic signals still remained more informative than imputed SNPs. In-depth analysis of these 105 cis eQTL revealed that at 76 loci genetic associations were compatible with additive effects of several SNPs, while for the 29 remaining regions data could be compatible with a more complex haplotypic pattern. As 24 of the 105 cis eQTL have previously been reported to be disease-associated loci, this work highlights the need for conducting haplotype-based and 1000 G imputed cis eQTL analysis before commencing functional studies at disease-associated loci.

GUESS-ing polygenic associations with multiple phenotypes using a GPU-based evolutionary stochastic search algorithm.

Genome-wide association studies (GWAS) yielded significant advances in defining the genetic architecture of complex traits and disease. Still, a major hurdle of GWAS is narrowing down multiple genetic associations to a few causal variants for functional studies. This becomes critical in multi-phenotype GWAS where detection and interpretability of complex SNP(s)-trait(s) associations are complicated by complex Linkage Disequilibrium patterns between SNPs and correlation between traits. Here we propose a computationally efficient algorithm (GUESS) to explore complex genetic-association models and maximize genetic variant detection. We integrated our algorithm with a new Bayesian strategy for multi-phenotype analysis to identify the specific contribution of each SNP to different trait combinations and study genetic regulation of lipid metabolism in the Gutenberg Health Study (GHS). Despite the relatively small size of GHS (n  =  3,175), when compared with the largest published meta-GWAS (n > 100,000), GUESS recovered most of the major associations and was better at refining multi-trait associations than alternative methods. Amongst the new findings provided by GUESS, we revealed a strong association of SORT1 with TG-APOB and LIPC with TG-HDL phenotypic groups, which were overlooked in the larger meta-GWAS and not revealed by competing approaches, associations that we replicated in two independent cohorts. Moreover, we demonstrated the increased power of GUESS over alternative multi-phenotype approaches, both Bayesian and non-Bayesian, in a simulation study that mimics real-case scenarios. We showed that our parallel implementation based on Graphics Processing Units outperforms alternative multi-phenotype methods. Beyond multivariate modelling of multi-phenotypes, our Bayesian model employs a flexible hierarchical prior structure for genetic effects that adapts to any correlation structure of the predictors and increases the power to identify associated variants. This provides a powerful tool for the analysis of diverse genomic features, for instance including gene expression and exome sequencing data, where complex dependencies are present in the predictor space.

Statistical colocalization of monocyte gene expression and genetic risk variants for type 1 diabetes.

One mechanism by which disease-associated DNA variation can alter disease risk is altering gene expression. However, linkage disequilibrium (LD) between variants, mostly single-nucleotide polymorphisms (SNPs), means it is not sufficient to show that a particular variant associates with both disease and expression, as there could be two distinct causal variants in LD. Here, we describe a formal statistical test of colocalization and apply it to type 1 diabetes (T1D)-associated regions identified mostly through genome-wide association studies and expression quantitative trait loci (eQTLs) discovered in a recently determined large monocyte expression data set from the Gutenberg Health Study (1370 individuals), with confirmation sought in an additional data set from the Cardiogenics Transcriptome Study (558 individuals). We excluded 39 out of 60 overlapping eQTLs in 49 T1D regions from possible colocalization and identified 21 coincident eQTLs, representing 21 genes in 14 distinct T1D regions. Our results reflect the importance of monocyte (and their derivatives, macrophage and dendritic cell) gene expression in human T1D and support the candidacy of several genes as causal factors in autoimmune pancreatic beta-cell destruction, including AFF3, CD226, CLECL1, DEXI, FKRP, PRKD2, RNLS, SMARCE1 and SUOX, in addition to the recently described GPR183 (EBI2) gene.

Integrating genome-wide genetic variations and monocyte expression data reveals trans-regulated gene modules in humans.

One major expectation from the transcriptome in humans is to characterize the biological basis of associations identified by genome-wide association studies. So far, few cis expression quantitative trait loci (eQTLs) have been reliably related to disease susceptibility. Trans-regulating mechanisms may play a more prominent role in disease susceptibility. We analyzed 12,808 genes detected in at least 5% of circulating monocyte samples from a population-based sample of 1,490 European unrelated subjects. We applied a method of extraction of expression patterns-independent component analysis-to identify sets of co-regulated genes. These patterns were then related to 675,350 SNPs to identify major trans-acting regulators. We detected three genomic regions significantly associated with co-regulated gene modules. Association of these loci with multiple expression traits was replicated in Cardiogenics, an independent study in which expression profiles of monocytes were available in 758 subjects. The locus 12q13 (lead SNP rs11171739), previously identified as a type 1 diabetes locus, was associated with a pattern including two cis eQTLs, RPS26 and SUOX, and 5 trans eQTLs, one of which (MADCAM1) is a potential candidate for mediating T1D susceptibility. The locus 12q24 (lead SNP rs653178), which has demonstrated extensive disease pleiotropy, including type 1 diabetes, hypertension, and celiac disease, was associated to a pattern strongly correlating to blood pressure level. The strongest trans eQTL in this pattern was CRIP1, a known marker of cellular proliferation in cancer. The locus 12q15 (lead SNP rs11177644) was associated with a pattern driven by two cis eQTLs, LYZ and YEATS4, and including 34 trans eQTLs, several of them tumor-related genes. This study shows that a method exploiting the structure of co-expressions among genes can help identify genomic regions involved in trans regulation of sets of genes and can provide clues for understanding the mechanisms linking genome-wide association loci to disease.

A follow-up study of a genome-wide association scan identifies a susceptibility locus for venous thrombosis on chromosome 6p24.1.

To identify genetic susceptibility factors conferring increased risk of venous thrombosis (VT), we conducted a multistage study, following results of a previously published GWAS that failed to detect loci for developing VT. Using a collection of 5862 cases with VT and 7112 healthy controls, we identified the HIVEP1 locus on chromosome 6p24.1 as a susceptibility locus for VT. Indeed, the HIVEP1 rs169713C allele was associated with an increased risk for VT, with an odds ratio of 1.20 (95% confidence interval 1.13-1.27, p = 2.86 x 10(-9)). HIVEP1 codes for a protein that participates in the transcriptional regulation of inflammatory target genes by binding specific DNA sequences in their promoter and enhancer regions. The current results provide the identification of a locus involved in VT susceptibility that lies outside the traditional coagulation/fibrinolysis pathway.

Genetic association study identifies HSPB7 as a risk gene for idiopathic dilated cardiomyopathy.

Dilated cardiomyopathy (DCM) is a structural heart disease with strong genetic background. Monogenic forms of DCM are observed in families with mutations located mostly in genes encoding structural and sarcomeric proteins. However, strong evidence suggests that genetic factors also affect the susceptibility to idiopathic DCM. To identify risk alleles for non-familial forms of DCM, we carried out a case-control association study, genotyping 664 DCM cases and 1,874 population-based healthy controls from Germany using a 50K human cardiovascular disease bead chip covering more than 2,000 genes pre-selected for cardiovascular relevance. After quality control, 30,920 single nucleotide polymorphisms (SNP) were tested for association with the disease by logistic regression adjusted for gender, and results were genomic-control corrected. The analysis revealed a significant association between a SNP in HSPB7 gene (rs1739843, minor allele frequency 39%) and idiopathic DCM (p = 1.06 × 10⁻6, OR  = 0.67 [95% CI 0.57-0.79] for the minor allele T). Three more SNPs showed p < 2.21 × 10⁻5. De novo genotyping of these four SNPs was done in three independent case-control studies of idiopathic DCM. Association between SNP rs1739843 and DCM was significant in all replication samples: Germany (n =564, n = 981 controls, p = 2.07 × 10⁻³, OR = 0.79 [95% CI 0.67-0.92]), France 1 (n = 433 cases, n = 395 controls, p =3.73 × 10⁻³, OR  = 0.74 [95% CI 0.60-0.91]), and France 2 (n = 249 cases, n = 380 controls, p = 2.26 × 10⁻4, OR  = 0.63 [95% CI 0.50-0.81]). The combined analysis of all four studies including a total of n = 1,910 cases and n = 3,630 controls showed highly significant evidence for association between rs1739843 and idiopathic DCM (p = 5.28 × 10⁻¹³, OR= 0.72 [95% CI 0.65-0.78]). None of the other three SNPs showed significant results in the replication stage.This finding of the HSPB7 gene from a genetic search for idiopathic DCM using a large SNP panel underscores the influence of common polymorphisms on DCM susceptibility.

Sensitive troponin I assay in early diagnosis of acute myocardial infarction.

BACKGROUND: Cardiac troponin testing is central to the diagnosis of acute myocardial infarction. We evaluated a sensitive troponin I assay for the early diagnosis and risk stratification of myocardial infarction. METHODS: In a multicenter study, we determined levels of troponin I as assessed by a sensitive assay, troponin T, and traditional myocardial necrosis markers in 1818 consecutive patients with suspected acute myocardial infarction, on admission and 3 hours and 6 hours after admission. RESULTS: For samples obtained on admission, the diagnostic accuracy was highest with the sensitive troponin I assay (area under the receiver-operating-characteristic curve [AUC], 0.96), as compared with the troponin T assay (AUC, 0.85) and traditional myocardial necrosis markers. With the use of the sensitive troponin I assay (cutoff value, 0.04 ng per milliliter) on admission, the clinical sensitivity was 90.7%, and the specificity was 90.2%. The diagnostic accuracy was virtually identical in baseline and serial samples, regardless of the time of chest-pain onset. In patients presenting within 3 hours after chest-pain onset, a single sensitive troponin I assay had a negative predictive value of 84.1% and a positive predictive value of 86.7%; these findings predicted a 30% rise in the troponin I level within 6 hours. A troponin I level of more than 0.04 ng per milliliter was independently associated with an increased risk of an adverse outcome at 30 days (hazard ratio, 1.96; 95% confidence interval, 1.27 to 3.05; P=0.003). CONCLUSIONS: The use of a sensitive assay for troponin I improves early diagnosis of acute myocardial infarction and risk stratification, regardless of the time of chest-pain onset.

ESS++: a C++ objected-oriented algorithm for Bayesian stochastic search model exploration.

SUMMARY: ESS++ is a C++ implementation of a fully Bayesian variable selection approach for single and multiple response linear regression. ESS++ works well both when the number of observations is larger than the number of predictors and in the 'large p, small n' case. In the current version, ESS++ can handle several hundred observations, thousands of predictors and a few responses simultaneously. The core engine of ESS++ for the selection of relevant predictors is based on Evolutionary Monte Carlo. Our implementation is open source, allowing community-based alterations and improvements. AVAILABILITY: C++ source code and documentation including compilation instructions are available under GNU licence at http://bgx.org.uk/software/ESS.html.

Midregional proadrenomedullin for prediction of cardiovascular events in coronary artery disease: results from the AtheroGene study.

BACKGROUND: Midregional proadrenomedullin (MR-proADM) is a newly identified prognostic marker in heart failure. We evaluated the prognostic impact of MR-proADM in a cohort of patients with symptomatic coronary artery disease according to their clinical presentation. METHODS: We measured baseline MR-proADM concentrations in 2240 individuals from the prospective AtheroGene study and evaluated the prognostic impact on future fatal and nonfatal cardiovascular events during a follow-up period of 3.6 (1.6) years. RESULTS: The sample comprised 1355 individuals with stable angina pectoris (SAP) and 885 with acute coronary syndrome (ACS). A cardiovascular event occurred in 192 people. Individuals presenting with SAP had only slightly lower plasma MR-proADM concentrations than those with ACS (0.53 vs 0.55 nmol/L, P=0.006). MR-proADM showed a moderate association with age, serum N-terminal pro-B-type natriuretic peptide (NT-proBNP), glomerular filtration rate, serum C-reactive protein, hypertension, diabetes, and prevalent multivessel disease (all P<0.0005). Individuals suffering from a cardiovascular event had higher MR-proADM concentrations at baseline in both groups (SAP 0.63 vs 0.53 nmol/L and ACS 0.65 nmol/L vs 0.55 nmol/L, both P<0.0005). Cox regression analysis incorporating various variables of cardiovascular risk and NT-proBNP revealed a hazard ratio of 1.4 (95% CI 1.2-1.6; P<0.0005) per increment of MR-proADM by 1SD. In risk models for secondary prevention, MR-proADM provided information comparable to that of NT-proBNP. CONCLUSIONS: MR-proADM is an independent predictor for future cardiovascular events in patients with symptomatic coronary artery disease, providing information comparable to NT-proBNP for secondary risk stratification.

C4BPB/C4BPA is a new susceptibility locus for venous thrombosis with unknown protein S-independent mechanism: results from genome-wide association and gene expression analyses followed by case-control studies.

Through its binding with protein S (PS), a key element of the coagulation/fibrinolysis cascade, the C4b-binding protein (C4BP) has been hypothesized to be involved in the susceptibility to venous thrombosis (VT). To identify genetic factors that may influence the plasma levels of the 3 C4BP existing isoforms, alpha(7)beta(1), alpha(6)beta(1), and alpha(7)beta(0), we conducted a genome-wide association study by analyzing 283 437 single nucleotide polymorphisms (SNPs) in the Genetic Analysis of Idiopathic Thrombophilia (GAIT) study composed of 352 persons. Three SNPs at the C4BPB/C4BPA locus were found genome-wide significantly associated with alpha(7)beta(0) levels. One of these SNPs was further found to explain approximately 11% of the variability of mRNA C4BPA expression in the Gutenberg Heart Study composed of 1490 persons, with no effect on C4BPB mRNA expression. The allele associated with increased alpha(7)beta(0) plasma levels and increased C4BPA expression was further found associated with increased risk of VT (odds ratio [OR] = 1.24 [1.03-1.53]) in 2 independent case-control studies (MARseille THrombosis Association study [MARTHA] and FActeurs de RIsque et de récidives de la maladie thromboembolique VEineuse [FARIVE]) gathering 1706 cases and 1379 controls. This SNP was not associated with free PS or total PS. In conclusion, we observed strong evidence that the C4BPB/C4BPA locus is a new susceptibility locus for VT through a PS-independent mechanism that remains to be elucidated.

A genome-wide association study identifies two loci associated with heart failure due to dilated cardiomyopathy.

AIMS: Dilated cardiomyopathy (DCM) is a major cause of heart failure with a high familial recurrence risk. So far, the genetics of DCM remains largely unresolved. We conducted the first genome-wide association study (GWAS) to identify loci contributing to sporadic DCM. METHODS AND RESULTS: One thousand one hundred and seventy-nine DCM patients and 1108 controls contributed to the discovery phase. Pools of DNA stratified on disease status, population, age, and gender were constituted and used for testing association of DCM with 517 382 single nucleotide polymorphisms (SNPs). Three DCM-associated SNPs were confirmed by individual genotyping (P < 5.0 10(-7)), and two of them, rs10927875 and rs2234962, were replicated in independent samples (1165 DCM patients and 1302 controls), with P-values of 0.002 and 0.009, respectively. rs10927875 maps to a region on chromosome 1p36.13 which encompasses several genes among which HSPB7 has been formerly suggested to be implicated in DCM. The second identified locus involves rs2234962, a non-synonymous SNP (c.T757C, p. C151R) located within the sequence of BAG3 on chromosome 10q26. To assess whether coding mutations of BAG3 might cause monogenic forms of the disease, we sequenced BAG3 exons in 168 independent index cases diagnosed with familial DCM and identified four truncating and two missense mutations. Each mutation was heterozygous, present in all genotyped relatives affected by the disease and absent in a control group of 347 healthy individuals, strongly suggesting that these mutations are causing the disease. CONCLUSION: This GWAS identified two loci involved in sporadic DCM, one of them probably implicates BAG3. Our results show that rare mutations in BAG3 contribute to monogenic forms of the disease, while common variant(s) in the same gene are implicated in sporadic DCM.

Influence of sex and genetic variability on expression of X-linked genes in human monocytes.

In humans, the fraction of X-linked genes with higher expression in females has been estimated to be 5% from microarray studies, a proportion lower than the 25% of genes thought to escape X inactivation. We analyzed 715 X-linked transcripts in circulating monocytes from 1,467 subjects and found an excess of female-biased transcripts on the X compared to autosomes (9.4% vs 5.5%, p<2×10(-5)). Among the genes not previously known to escape inactivation, the most significant one was EFHC2 whose 20% of variability was explained by sex. We also investigated cis expression quantitative trait loci (eQTLs) by analyzing 15,703 X-linked SNPs. The frequency and magnitude of X-linked cis eQTLs were quite similar in males and females. Few genes exhibited a stronger genetic effect in females than in males (ARSD, DCX, POLA1 and ITM2A). These genes would deserve further investigation since they may contribute to sex pathophysiological differences.

Contribution of 30 biomarkers to 10-year cardiovascular risk estimation in 2 population cohorts: the MONICA, risk, genetics, archiving, and monograph (MORGAM) biomarker project.

BACKGROUND: Cardiovascular risk estimation by novel biomarkers needs assessment in disease-free population cohorts, followed up for incident cardiovascular events, assaying the serum and plasma archived at baseline. We report results from 2 cohorts in such a continuing study. METHODS AND RESULTS: Thirty novel biomarkers from different pathophysiological pathways were evaluated in 7915 men and women of the FINRISK97 population cohort with 538 incident cardiovascular events at 10 years (fatal or nonfatal coronary or stroke events), from which a biomarker score was developed and then validated in the 2551 men of the Belfast Prospective Epidemiological Study of Myocardial Infarction (PRIME) cohort (260 events). No single biomarker consistently improved risk estimation in FINRISK97 men and FINRISK97 women and the Belfast PRIME Men cohort after allowing for confounding factors; however, the strongest associations (with hazard ratio per SD in FINRISK97 men) were found for N-terminal pro-brain natriuretic peptide (1.23), C-reactive protein (1.23), B-type natriuretic peptide (1.19), and sensitive troponin I (1.18). A biomarker score was developed from the FINRISK97 cohort with the use of regression coefficients and lasso methods, with selection of troponin I, C-reactive protein, and N-terminal pro-brain natriuretic peptide. Adding this score to a conventional risk factor model in the Belfast PRIME Men cohort validated it by improved c-statistics (P=0.004) and integrated discrimination (P<0.0001) and led to significant reclassification of individuals into risk categories (P=0.0008). CONCLUSIONS: The addition of a biomarker score including N-terminal pro-brain natriuretic peptide, C-reactive protein, and sensitive troponin I to a conventional risk model improved 10-year risk estimation for cardiovascular events in 2 middle-aged European populations. Further validation is needed in other populations and age groups.

Common susceptibility alleles are unlikely to contribute as strongly as the FV and ABO loci to VTE risk: results from a GWAS approach.

Venous thromboembolism (VTE) is a complex disease that has a major genetic component of risk. To identify genetic factors that may modify the risk of VTE, we conducted a genome-wide association study by analyzing approximately 317 000 single nucleotide polymorphisms (SNPs) in 453 VTE cases and 1327 controls. Only 3 SNPs located in the FV and ABO blood group genes were found associated with VTE at a genome-wide significant level of 1.7 x 10(-7). Detailed analysis of these SNPs in additional cohorts of more than 1700 cases and 1400 controls revealed that the association observed at the FV locus was the result of the increased risk mediated by the FV Leiden mutation, whereas O and A2 blood groups were found to be at lower risk for VTE. Apart from the FV and ABO loci, no other locus was found strongly associated with VTE. However, using this large cohort of subjects, we were able to replicate the mild effects of 2 nonsynonymous SNPs, rs1613662 in GP6 and rs13146272 in CYP4V2, recently suspected to be associated with VTE.

Multiple marker approach to risk stratification in patients with stable coronary artery disease.

AIMS: multimarker approaches for risk prediction in coronary artery disease have remained inconsistent. We assessed multiple biomarkers representing distinct pathophysiological pathways in relation to cardiovascular events in stable angina. METHODS AND RESULTS: we investigated 12 biomarkers reflecting inflammation [C-reactive protein, growth-differentiation factor (GDF)-15, neopterin], lipid metabolism (apolipoproteins AI, B100), renal function (cystatin C, serum creatinine), and cardiovascular function and remodelling [copeptin, C-terminal-pro-endothelin-1, mid-regional-pro-adrenomedullin (MR-proADM), mid-regional-pro-atrial natriuretic peptide (MR-proANP), N-terminal-pro-B-type natriuretic peptide (Nt-proBNP)] in 1781 stable angina patients in relation to non-fatal myocardial infarction and cardiovascular death (n = 137) over 3.6 years. Using Cox proportional hazards models and C-indices, the strongest association with outcome for log-transformed biomarkers in multivariable-adjusted analyses was observed for Nt-proBNP [hazard ratio (HR) for one standard deviation increase 1.65, 95% confidence interval (CI) 1.28-2.13, C-index 0.686], GDF-15 (HR 1.59, 95% CI 1.25-2.02, C-index 0.681), MR-proANP (HR 1.46, 95% CI 1.14-1.87, C-index 0.673), cystatin C (HR 1.39, 95% CI 1.10-1.75, C-index 0.671), and MR-proADM (HR 1.63, 95% CI 1.21-2.20, C-index 0.668). Each of these top single markers and their combination (C-index 0.690) added predictive information beyond the baseline model consisting of the classical risk factors assessed by C-index and led to substantial reclassification (P-integrated discrimination improvement <0.05). CONCLUSION: comparative analysis of 12 biomarkers revealed Nt-proBNP, GDF-15, MR-proANP, cystatin C, and MR-proADM as the strongest predictors of cardiovascular outcome in stable angina. All five biomarkers taken separately offered incremental predictive ability over established risk factors. Combination of the single markers slightly improved model fit but did not enhance risk prediction from a clinical perspective.

The impact of newly identified loci on coronary heart disease, stroke and total mortality in the MORGAM prospective cohorts.

Recently, genome wide association studies (GWAS) have identified a number of single nucleotide polymorphisms (SNPs) as being associated with coronary heart disease (CHD). We estimated the effect of these SNPs on incident CHD, stroke and total mortality in the prospective cohorts of the MORGAM Project. We studied cohorts from Finland, Sweden, France and Northern Ireland (total N=33,282, including 1,436 incident CHD events and 571 incident stroke events). The lead SNPs at seven loci identified thus far and additional SNPs (in total 42) were genotyped using a case-cohort design. We estimated the effect of the SNPs on disease history at baseline, disease events during follow-up and classic risk factors. Multiple testing was taken into account using false discovery rate (FDR) analysis. SNP rs1333049 on chromosome 9p21.3 was associated with both CHD and stroke (HR=1.20, 95% CI 1.08-1.34 for incident CHD events and 1.15, 0.99-1.34 for incident stroke). SNP rs11670734 (19q12) was associated with total mortality and stroke. SNP rs2146807 (10q11.21) showed some association with the fatality of acute coronary event. SNP rs2943634 (2q36.3) was associated with high density lipoprotein (HDL) cholesterol and SNPs rs599839, rs4970834 (1p13.3) and rs17228212 (15q22.23) were associated with non-HDL cholesterol. SNPs rs2943634 (2q36.3) and rs12525353 (6q25.1) were associated with blood pressure. These findings underline the need for replication studies in prospective settings and confirm the candidacy of several SNPs that may play a role in the etiology of cardiovascular disease.

Molecular genetic analysis of a human insulin-like growth factor 1 promoter P1 variation.

Insulin-like growth factor 1 (IGF1) exerts important endocrine and paracrine functions in the cardiovascular system. We identified the common variant -1411C>T in the IGF1 upstream promoter P1, located within several overlapping transcription factor binding sites. Using transient transfection assays, we identified this site as a functional enhancer. The T allele-carrying enhancer, compared with the C allelic portion, exerts significantly reduced or even abrogated activity, respectively, in SaOs-2 and HepG2 (all P<0.0001) as well as in differentiated THP-1 macrophages. Electrophoretic mobility shift assay and subsequent supershift experiments in HepG2 identified c-Jun as the binding partner exclusively to the T allele, whereas CCAAT/enhancer-binding protein delta and interferon consensus site-binding protein/interferon-regulating factor 8 interacted only with the C allelic promoter portion. Furthermore, genotyping in a case-control study for essential hypertension (n=745 hypertensive patients; n=769 normotensive control subjects) for this variant revealed an odds ratio for hypertension of 0.73 (95% confidence interval 0.58-0.91, P=0.006) associated with the T allele, and normotensive subjects carrying the protective T allele displayed a significant decrease in diastolic (P=0.036) and systolic (P=0.024) blood pressure levels. We here report detection of a functional enhancer module in the upstream IGF1 promoter region, which might play a key role in local IGF1 bioavailability. Whether -1411C>T is also associated with other IGF1-related disease phenotypes should be evaluated further in population studies.

Cystatin C and cardiovascular mortality in patients with coronary artery disease and normal or mildly reduced kidney function: results from the AtheroGene study.

AIMS: Chronic kidney disease is associated with increased risk of cardiovascular disease. Cystatin C is a promising marker to reliably mirror renal function. The role of cystatin C in patients with coronary artery disease (CAD) and normal or mildly reduced kidney function is the subject of current investigation. METHODS AND RESULTS: In 2162 patients, over the whole spectrum of CAD, baseline cystatin C concentrations were measured. Patients with an estimated glomerular filtration rate of < or =60 mL/min per 1.73 m(2) (n = 295) were excluded. In patients with complete follow-up information (n = 1827), 66 cardiovascular deaths were registered during a median follow-up of 3.65 years. Logarithmically transformed, standardized cystatin C was associated with cardiovascular death [hazard ratio: 1.94, 95% confidence interval (CI): 1.59-2.37, P < 0.001]. A potential threshold effect was observed; patients in the upper quartile had a 3.87-fold (95% CI: 2.33-6.42; P < 0.001) risk of mortality compared with the pooled lower quartiles. This risk association remained robust after adjustment for potential confounders including classical risk factors and N-terminal pro B-type natriuretic peptide. Serum creatinine was not associated with the outcome in this group of patients with normal renal function. CONCLUSION: Results of this prospective study show that cystatin C is a potent predictor of cardiovascular mortality beyond classical risk factors in patients with CAD and normal or mildly reduced kidney function.

Correction: Exome-wide association study reveals novel susceptibility genes to sporadic dilated cardiomyopathy.

[This corrects the article DOI: 10.1371/journal.pone.0172995.].