Taking Cardiovascular Genetic Association Studies to the Next Level

Genetic information is beginning to have a direct impact on patient care and it is important that cardiologists appreciate the value and approaches to associating genetic variation and health outcomes. Genetic associations should be based on compelling genetic and biological hypotheses and should be statistically sound so as to reduce the possibility of “false discovery” in the setting of testing multiple hypotheses. Study designs should clearly define cases and controls and measurement of phenotypes. Finally, findings should be replicated in at least 1 independent cohort. Consideration of these principles should provide insight into disease biology based on genetic findings and encourage their meaningful adoption into clinical practice

Searching for epistatic interactions in nuclear families using conditional linkage analysis

BACKGROUND: Genomic screens generally employ a single-locus strategy for linkage analysis, but this may have low power in the presence of epistasis. Ordered subsets analysis (OSA) is a method for conditional linkage analysis using continuous covariates. METHODS: We used OSA to evaluate two-locus interactions in the simulated Genetic Analysis Workshop 14 dataset. We used all nuclear families ascertained by Aipotu, Karangar, and Danacaa. Using the single-nucleotide polymorphism map, multipoint affected-sibling-pair (ASP) linkage analysis was performed on all 100 replicates for each chromosome using SIBLINK. OSA was used to examine linkage on each chromosome using LOD scores at each 3-cM location on every other chromosome as covariates. Two methods were used to identify positive results: one searching across the entire covariate chromosome, the other conditioning on location of known disease loci. RESULTS: Single-locus linkage analysis revealed very high LOD scores for disease loci D1 through D4, with mean LOD scores over 100 replicates ranging from 4.0 to 7.8. Although OSA did not obscure this linkage evidence, it did not detect the simulated interactions between any of the locus pairs. We found inflated type I error rates using the first OSA method, highlighting the need to correct for multiple comparisons. Therefore, using "null chromosome pairs" without simulated disease loci, we calculated a corrected alpha-level. CONCLUSION: We were unable to detect two-locus interactions using OSA. This may have been due to lack of incorporation of phenotypic subgroups, or because linkage evidence as summarized by LOD scores performs poorly as an OSA covariate. We found inflated type I error rates, but were able to calculate a corrected alpha-level for future analyses employing this strategy to search for two-locus interactions

Risk factors for 1-year mortality after thoracic endovascular aortic repair

ObjectiveThoracic endovascular aortic repair, although physiologically well tolerated, may fail to confer significant survival benefit in some high-risk patients. In an effort to identify patients most likely to benefit from intervention, the present study sought to determine the risk factors for 1-year mortality after thoracic endovascular aortic repair.MethodsA retrospective review was performed on prospectively collected data from all patients undergoing thoracic endovascular aortic repair from 2002 to 2010 at a single institution. Univariate analysis and multivariate Cox proportional hazards regression analysis were used to identify risk factors associated with mortality within 1 year after thoracic endovascular aortic repair.ResultsDuring the study period, 282 patients underwent at least 1 thoracic endovascular aortic repair; index procedures included descending aortic repair (n = 189), hybrid arch repair (n = 55), and hybrid thoracoabdominal repair (n = 38). The 30-day/in-hospital mortality was 7.4% (n = 21) and the overall 1-year mortality was 19% (n = 54). Cardiopulmonary pathologies were the most common cause of nonperioperative 1-year mortality (22%, n = 12). Multivariate modeling demonstrated 3 variables independently associated with 1-year mortality: age older than 75 years (hazard ratio, 2.26; P = .005), aortic diameter greater than 6.5 cm (hazard ratio, 2.20; P = .007), and American Society of Anesthesiologists class 4 (hazard ratio, 1.85; P = .049). A baseline creatinine greater than 1.5 mg/dL (hazard ratio, 1.79; P = .05) and congestive heart failure (hazard ratio, 1.87; P = .08) were also retained in the final model. These 5 variables explained a large proportion of the risk of 1-year mortality (C statistic = 0.74).ConclusionsAge older than 75 years, aortic diameter greater than 6.5 cm, and American Society of Anesthesiologists class 4 are independently associated with 1-year mortality after thoracic endovascular aortic repair. These clinical characteristics may help risk-stratify patients undergoing thoracic endovascular aortic repair and identify those unlikely to derive a long-term survival benefit from the procedure

Inverse association of general joint hypermobility with hand and knee osteoarthritis and serum cartilage oligomeric matrix protein levels

Extensive joint hypermobility, lower serum cartilage oligomeric matrix protein (COMP), and early-onset osteoarthritis (OA) are phenotypes of inherited pseudoachondroplasia (PSACH) and multiple epiphyseal dysplasia (MED). However, few studies have evaluated the association between articular hypermobility and primary OA. Therefore, we evaluated this association and tested the hypothesis that COMP level is associated with hypermobility in OA and non-OA individuals

Potential Impact and Study Considerations of Metabolomics in Cardiovascular Health and Disease: A Scientific Statement From the American Heart Association.

Through the measure of thousands of small-molecule metabolites in diverse biological systems, metabolomics now offers the potential for new insights into the factors that contribute to complex human diseases such as cardiovascular disease. Targeted metabolomics methods have already identified new molecular markers and metabolomic signatures of cardiovascular disease risk (including branched-chain amino acids, select unsaturated lipid species, and trimethylamine-N-oxide), thus in effect linking diverse exposures such as those from dietary intake and the microbiota with cardiometabolic traits. As technologies for metabolomics continue to evolve, the depth and breadth of small-molecule metabolite profiling in complex systems continue to advance rapidly, along with prospects for ongoing discovery. Current challenges facing the field of metabolomics include scaling throughput and technical capacity for metabolomics approaches, bioinformatic and chemoinformatic tools for handling large-scale metabolomics data, methods for elucidating the biochemical structure and function of novel metabolites, and strategies for determining the true clinical relevance of metabolites observed in association with cardiovascular disease outcomes. Progress made in addressing these challenges will allow metabolomics the potential to substantially affect diagnostics and therapeutics in cardiovascular medicine

Creatine and creatinine quantified using nuclear magnetic resonance:A method validation study and clinical associations between circulating creatine and fatigue in kidney transplant recipients

Background: A potential contributor to fatigue in kidney transplant recipients (KTR) may be impaired creatine homeostasis. We developed and validated a high-throughput NMR assay allowing for simultaneous measurement of circulating creatine and creatinine, and determined plasma creatine and estimated intramuscular creatine concentrations in KTRs, delineated their determinants and explored their associations with self-reported fatigue.Methods: An NMR assay was developed and validated for measurement of circulating creatinine and creatine concentrations. Plasma creatine and creatinine concentrations were measured in 618 KTR. Fatigue was assessed using the checklist individual strength. Associations of creatine parameters with fatigue was assessed using linear mixed effect models.Results: The NMR-based assay had good sensitivity, precision and demonstrated linearity across a large range of values. Among KTR, the mean age was 56 ± 13 years, 62% were men and eGFR was 54 ± 18 ml/min/1.73 m2. Plasma creatine concentration was 27 [19–39] µmol/L. Estimated intramuscular creatine concentration was 27 ± 7 mmol/kg. Higher plasma creatine concentration and higher estimated intramuscular creatine concentration were independently associated with a lower total fatigue score and less motivation problems.Conclusion: An NMR method for measurement of circulating creatine and creatinine which offers the potential for accurate and efficient quantification was developed. The found associations suggest that improving creatine status may play a beneficial role in mitigating fatigue.</p

Epigenetic regulation of COL15A1 in smooth muscle cell replicative aging and atherosclerosis

Smooth muscle cell (SMC) proliferation is a hallmark of vascular injury and disease. Global hypomethylation occurs during SMC proliferation in culture and in vivo during neointimal formation. Regardless of the programmed or stochastic nature of hypomethylation, identifying these changes is important in understanding vascular disease, as maintenance of a cells' epigenetic profile is essential for maintaining cellular phenotype. Global hypomethylation of proliferating aortic SMCs and concomitant decrease of DNMT1 expression were identified in culture during passage. An epigenome screen identified regions of the genome that were hypomethylated during proliferation and a region containing Collagen, type XV, alpha 1 (COL15A1) was selected by ‘genomic convergence' for characterization. COL15A1 transcript and protein levels increased with passage-dependent decreases in DNA methylation and the transcript was sensitive to treatment with 5-Aza-2′-deoxycytidine, suggesting DNA methylation-mediated gene expression. Phenotypically, knockdown of COL15A1 increased SMC migration and decreased proliferation and Col15a1 expression was induced in an atherosclerotic lesion and localized to the atherosclerotic cap. A sequence variant in COL15A1 that is significantly associated with atherosclerosis (rs4142986, P = 0.017, OR = 1.434) was methylated and methylation of the risk allele correlated with decreased gene expression and increased atherosclerosis in human aorta. In summary, hypomethylation of COL15A1 occurs during SMC proliferation and the consequent increased gene expression may impact SMC phenotype and atherosclerosis formation. Hypomethylated genes, such as COL15A1, provide evidence for concomitant epigenetic regulation and genetic susceptibility, and define a class of causal targets that sit at the intersection of genetic and epigenetic predisposition in the etiology of complex diseas

Atherogenic Lipoprotein Determinants of Cardiovascular Disease and Residual Risk Among Individuals With Low Low‐Density Lipoprotein Cholesterol

Background: Levels of LDL (low‐density lipoprotein) cholesterol in the population are declining, and increasing attention is being focused on residual lipid‐related pathways of atherosclerotic cardiovascular disease risk beyond LDL cholesterol. Among individuals with low (<130 mg/dL) LDL cholesterol, we undertook detailed profiling of circulating atherogenic lipoproteins in relation to incident cardiovascular disease in 2 populations. Methods and Results: We performed proton nuclear magnetic resonance spectroscopy to quantify concentrations of LDL and VLDL (very low‐density lipoprotein) particle subclasses in 11 984 JUPITER trial participants (NCT00239681). Adjusted Cox models examined cardiovascular disease risk associated with lipoprotein measures according to treatment allocation. Risk (adjusted hazard ratio [95%CI] per SD increment) among placebo‐allocated participants was associated with total LDL particles (1.19 [1.02, 1.38]) and total VLDL particles (1.21 [1.04, 1.41]), as well as apolipoprotein B, non–high‐density lipoprotein cholesterol, and triglycerides, but not LDL‐c. Rosuvastatin reduced LDL measures but had variable effects on triglyceride and VLDL measures. On‐statin levels of the smallest VLDL particle subclass were associated with a 68% per‐SD (adjusted hazard ratio 1.68 [1.28, 2.22]) increase in residual risk—this risk was related to VLDL cholesterol and not triglyceride or larger VLDL particles. There was evidence that residual risk prediction during statin therapy could be significantly improved through the inclusion of key VLDL measures (Harrell C‐index 0.780 versus 0.712; P<0.0001). In an independent, prospective cohort of 4721 individuals referred for cardiac catheterization (CATHGEN), similar patterns of lipoprotein‐related risk were observed. Conclusions: Atherogenic lipoprotein particle concentrations were associated with cardiovascular disease risk when LDL cholesterol was low. VLDL lipoproteins, particularly the smallest remnant subclass, may represent unused targets for risk prediction and potential therapeutic intervention for reducing residual risk. Clinical Trial Registration URL: http://www.clinicaltrials.gov. Unique identifier: NCT00239681

Fine mapping of a linkage peak with integration of lipid traits identifies novel coronary artery disease genes on chromosome 5

Coronary artery disease (CAD), and one of its intermediate risk factors, dyslipidemia, possess a demonstrable genetic component, although the genetic architecture is incompletely defined. We previously reported a linkage peak on chromosome 5q31-33 for early-onset CAD where the strength of evidence for linkage was increased in families with higher mean low density lipoprotein-cholesterol (LDL-C). Therefore, we sought to fine-map the peak using association mapping of LDL-C as an intermediate disease-related trait to further define the etiology of this linkage peak. The study populations consisted of 1908 individuals from the CATHGEN biorepository of patients undergoing cardiac catheterization; 254 families (N = 827 individuals) from the GENECARD familial study of early-onset CAD; and 162 aorta samples harvested from deceased donors. Linkage disequilibrium-tagged SNPs were selected with an average of one SNP per 20 kb for 126.6-160.2 MB (region of highest linkage) and less dense spacing (one SNP per 50 kb) for the flanking regions (117.7-126.6 and 160.2-167.5 MB) and genotyped on all samples using a custom Illumina array. Association analysis of each SNP with LDL-C was performed using multivariable linear regression (CATHGEN) and the quantitative trait transmission disequilibrium test (QTDT; GENECARD). SNPs associated with the intermediate quantitative trait, LDL-C, were then assessed for association with CAD (i.e., a qualitative phenotype) using linkage and association in the presence of linkage (APL; GENECARD) and logistic regression (CATHGEN and aortas)

Integrative Genomics Reveals Novel Molecular Pathways and Gene Networks for Coronary Artery Disease

The majority of the heritability of coronary artery disease (CAD) remains unexplained, despite recent successes of genome-wide association studies (GWAS) in identifying novel susceptibility loci. Integrating functional genomic data from a variety of sources with a large-scale meta-analysis of CAD GWAS may facilitate the identification of novel biological processes and genes involved in CAD, as well as clarify the causal relationships of established processes. Towards this end, we integrated 14 GWAS from the CARDIoGRAM Consortium and two additional GWAS from the Ottawa Heart Institute (25,491 cases and 66,819 controls) with 1) genetics of gene expression studies of CAD-relevant tissues in humans, 2) metabolic and signaling pathways from public databases, and 3) data-driven, tissue-specific gene networks from a multitude of human and mouse experiments. We not only detected CAD-associated gene networks of lipid metabolism, coagulation, immunity, and additional networks with no clear functional annotation, but also revealed key driver genes for each CAD network based on the topology of the gene regulatory networks. In particular, we found a gene network involved in antigen processing to be strongly associated with CAD. The key driver genes of this network included glyoxalase I (GLO1) and peptidylprolyl isomerase I (PPIL1), which we verified as regulatory by siRNA experiments in human aortic endothelial cells. Our results suggest genetic influences on a diverse set of both known and novel biological processes that contribute to CAD risk. The key driver genes for these networks highlight potential novel targets for further mechanistic studies and therapeutic interventions