Santhi K. Ganesh

Genome-wide association study of blood pressure and hypertension

Blood pressure is a major cardiovascular disease risk factor. To date, few variants associated with interindividual blood pressure variation have been identified and replicated. Here we report results of a genome-wide association study of systolic (SBP) and diastolic (DBP) blood pressure and hypertension in the CHARGE Consortium (n = 29,136), identifying 13 SNPs for SBP, 20 for DBP and 10 for hypertension at P < 4 × 10−7. The top ten loci for SBP and DBP were incorporated into a risk score; mean BP and prevalence of hypertension increased in relation to the number of risk alleles carried. When ten CHARGE SNPs for each trait were included in a joint meta-analysis with the Global BPgen Consortium (n = 34,433), four CHARGE loci attained genome-wide significance (P < 5 × 10−8) for SBP (ATP2B1, CYP17A1, PLEKHA7, SH2B3), six for DBP (ATP2B1, CACNB2, CSK-ULK3, SH2B3, TBX3-TBX5, ULK4) and one for hypertension (ATP2B1). Identifying genes associated with blood pressure advances our understanding of blood pressure regulation and highlights potential drug targets for the prevention or treatment of hypertension.

Multiple loci influence erythrocyte phenotypes in the CHARGE Consortium

Measurements of erythrocytes within the blood are important clinical traits and can indicate various hematological disorders. We report here genome-wide association studies (GWAS) for six erythrocyte traits, including hemoglobin concentration (Hb), hematocrit (Hct), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC) and red blood cell count (RBC). We performed an initial GWAS in cohorts of the CHARGE Consortium totaling 24,167 individuals of European ancestry and replication in additional independent cohorts of the HaemGen Consortium totaling 9,456 individuals. We identified 23 loci significantly associated with these traits in a meta-analysis of the discovery and replication cohorts (combined P values ranging from 5 × 10−8 to 7 × 10−86). Our findings include loci previously associated with these traits (HBS1L-MYB, HFE, TMPRSS6, TFR2, SPTA1) as well as new associations (EPO, TFRC, SH2B3 and 15 other loci). This study has identified new determinants of erythrocyte traits, offering insight into common variants underlying variation in erythrocyte measures.

A farnesyltransferase inhibitor prevents both the onset and late progression of cardiovascular disease in a progeria mouse model

Hutchinson-Gilford progeria syndrome (HGPS) is the most dramatic form of human premature aging. Death occurs at a mean age of 13 years, usually from heart attack or stroke. Almost all cases of HGPS are caused by a de novo point mutation in the lamin A (LMNA) gene that results in production of a mutant lamin A protein termed progerin. This protein is permanently modified by a lipid farnesyl group, and acts as a dominant negative, disrupting nuclear structure. Treatment with farnesyltransferase inhibitors (FTIs) has been shown to prevent and even reverse this nuclear abnormality in cultured HGPS fibroblasts. We have previously created a mouse model of HGPS that shows progressive loss of vascular smooth muscle cells in the media of the large arteries, in a pattern that is strikingly similar to the cardiovascular disease seen in patients with HGPS. Here we show that the dose-dependent administration of the FTI tipifarnib (R115777, Zarnestra) to this HGPS mouse model can significantly prevent both the onset of the cardiovascular phenotype as well as the late progression of existing cardiovascular disease. These observations provide encouraging evidence for the current clinical trial of FTIs for this rare and devastating disease.

Genetics and Genomics for the Prevention and Treatment of Cardiovascular Disease: Update A Scientific Statement From the American Heart Association

Cardiovascular diseases (CVDs) are a major source of morbidity and mortality worldwide. Despite a decline of ≈30% over the past decade, heart disease remains the leading killer of Americans.1 For rare and familial forms of CVD, we are increasingly recognizing single-gene mutations that impart relatively large effects on individual phenotype. Examples include inherited forms of cardiomyopathy, arrhythmias, and aortic diseases. However, the prevalence of monogenic disorders typically accounts for a small proportion of the total CVD observed in the population. CVDs in the general population are complex diseases, with several contributing genetic and environmental factors. Although recent progress in monogenic disorders has occurred, we have seen a period of intense investigation to identify the genetic architecture of more common forms of CVD and related traits.nnGenomics serves several roles in cardiovascular health and disease, including disease prediction, discovery of genetic loci influencing CVD, functional evaluation of these genetic loci to understand mechanisms, and identification of therapeutic targets. For single-gene CVDs, progress has led to several clinically useful diagnostic tests, extending our ability to inform the management of afflicted patients and their family members. However, there has been little progress in developing genetic testing for complex CVD because individual common variants have only a modest impact on risk. The study of the genomics of complex CVDs is further challenged by the influence of environmental variables, phenotypic heterogeneity, and pathogenic complexity. Characterization of the clinical phenotype requires consideration of the clinical details of the diseases and traits under study.nnThis update expands the prior scientific statement on the relevance of genetics and genomics for the prevention and treatment of CVDs.2 In the earlier report, we focused on the current status of the field, which consisted of predominantly family-based linkage studies and single-gene or mendelian mutations of relatively large phenotypic effect …

Rationale and study design of the CardioGene Study: genomics of in-stent restenosis

BACKGROUND AND AIMSnin-stent restenosis is a major limitation of stent therapy for atherosclerosis coronary artery disease. The CardioGene Study is an ongoing study of restenosis in bare mental stents (BMS) for the treatment of coronary artery disease. The overall goal is to understand the genetic determinants of the responses to vascular injury that result in the development of restenosis in some patients but not in others. Gene expression profiling at transcriptional and translational levels provides global assessment of gene activity after vascular injury and mechanistic insight. Furthermore, the delineation of genetic biomarkers would be of value in the clinical setting of risk-stratify patients prior to stent therapy. Prospective risk stratification would allow for the rational selection of specialized treatments against the development of in-stent restenosis (ISR), such as drug-eluting stents.nnnSETTINGnPatients are enrolled at two sites in the US with high-volume cardiac catheterization facilities: the William Beaumont Hospital in Royal Oak, MI, USA, and the Mayo Clinic in Rochester, MN, USA.nnnSTUDY DESIGNnTwo complementary study designs are used to understand the molecular mechanisms of restenosis and the genetic biomarkers predictive of restenosis. First, 350 patients are enrolled prospectively at the time of stent implantation. Blood is sampled prior to stent placement and afterwards at 2 weeks and 6 months. The clinical outcome of restenosis is determined 6 and 12 months after stent placement. The primary outcome is clinical restenosis at 6 months. The major secondary outcome is clinical restenosis at 12 months. Second, a corollary case-control analysis will be carried out with the enrollment of an additional 250 cases with a history of recurrent restenosis after treatment with BMS. Controls for this analysis are derived from the prospective cohort.nnnPATIENTS AND METHODSnConsecutive patients presenting to the cardiac catheterization laboratory are screened, informed about the study and enrolled after signing the consent form. Enrollment has been completed for the prospective cohort, and enrollment of the additional group is ongoing. A standardized questionnaire is used to collect clinical data primarily through direct patient interview to assess medical history, medication use, functional status, family history, environmental factors, and social history. Further data are abstracted from the medical charts and catheterization reports. A total of 276 clinical variables are collected per individual at baseline, and 49 variables are collected at each of the 6- and 12-month follow-up visits. A Clinical Events Committee adjudicates clinical outcomes. Blood samples are processed at each clinical enrollment site using standardized operating procedures. From each blood sample, several aliquots are prepared and stored of peripheral blood mononuclear cells, granulocytes, platelets, serum, and plasma. Additionally, a portion of each patients leukocytes is cryopreserved for future cell-line creation. Samples are frozen and shipped to the National Heart, Lung and Blood Institute (NHLBI). Additional materials generated in the analysis of the samples at the NHLBI are frozen and stored, including isolated genomic DNA, total RNA, reverse transcribed cDNA libraries and labeled RNA hybridization mixtures used in microarray analysis. Per individual in the prospective cohort, high-quality transcript profiles of peripheral blood mononuclear cells at each time of blood sampling are obtained using Affymetrix U133A microarrays (Affymetrix, Santa Clara, CA, USA). Per chip, this yields 495,930 features per individual per time of sampling. This represents expression levels for 22,283 genes per patients oer time of blood sampling, including 14,500 well-characterized human genes. Proteomics of plasma is performed with multidimensional liquid chromatography and tandem mass spectrometry. Protein expression is examined similarly to mRNA expression as a measure of gene expression. Genotyping is performed in two manners. First, those genes showing differential expression at the levels of mRNA and protein are investigated using a candidate gene approach. Specific variants in known gene regulatory regions, such as promoters, are sought initially, as those variants may explain differences in expression level. Second, a genome-wide scan is used to identify genetic loci that are associated with ISR. Those regions identified are further examined for genes that show differential expression in the mRNA microarray profiling or proteomics investigations. These genes are finely investigated for candidate SNPs and other gene variants. Complementary genomic and proteomic approaches are expected to be robust. Integration of data sets is accomplished using a variety of informatics tools, organization of gene expression into functional pathways, and investigation of physical maps of up- and downregulated sets of genes.nnnCONCLUSIONSnThe CardioGene Study is designed to understand ISR. Global gene and protein expression profiling define molecular phenotypes of patients. Well-defined clinical phenotypes will be paired with genomic data to define analyses aimed to achieve several goals. These include determining blood gene and protein expression in patients with ISR, investigating the genetic basis of ISR, developing predictive gene and protein biomarkers, and the identification of new targets for treatment.

Anti-atherosclerotic effects of statins: lessons from prevention trials.

Statins are best-known for their lipid-lowering effects and have been shown to significantly impact the natural progression of coronary atherosclerosis. The mechanism through which they exert this effect is thought to be primarily due to their ability to reduce low-density lipoprotein cholesterol levels. However, there is increasing evidence that statins exert a myriad of other beneficial effects on the vascular wall, thus altering the course of atherosclerotic disease. This article will review the prevention trial literature as it pertains to the effects of statin therapy on atherosclerosis. J Cardiovasc Risk 10:155-159

Detection of Venous Thromboembolism by Proteomic Serum Biomarkers

Background Available blood assays for venous thromboembolism (VTE) suffer from diminished specificity. Compared with single marker tests, such as D-dimer, a multi-marker strategy may improve diagnostic ability. We used direct mass spectrometry (MS) analysis of serum from patients with VTE to determine whether protein expression profiles would predict diagnosis. Methods and Results We developed a direct MS and computational approach to the proteomic analysis of serum. Using this new method, we analyzed serum from inpatients undergoing radiographic evaluation for VTE. In a balanced cohort of 76 patients, a neural network-based prediction model was built using a training subset of the cohort to first identify proteomic patterns of VTE. The proteomic patterns were then validated in a separate group of patients within the cohort. The model yielded a sensitivity of 68% and specificity of 89%, which exceeded the specificity of D-dimer assay tested by latex agglutination, ELISA, and immunoturbimetric methods (sensitivity/specificity of 63.2%/60.5%, 97.4%/21.1%, 97.4%/15.8%, respectively). We validated differences in protein expression between patients with and without VTE using more traditional gel-based analysis of the same serum samples. Conclusion Protein expression analysis of serum using direct MS demonstrates potential diagnostic utility for VTE. This pilot study is the first such direct MS study to be applied to a cardiovascular disease. Differences in protein expression were identified and subsequently validated in a separate group of patients. The findings in this initial cohort can be evaluated in other independent cohorts, including patients with inflammatory conditions and chronic (but not acute) VTE, for the diagnosis of VTE.

Time course analysis of gene expression identifies multiple genes with differential expression in patients with in-stent restenosis

BackgroundThe vascular disease in-stent restenosis (ISR) is characterized by formation of neointima and adverse inward remodeling of the artery after injury by coronary stent implantation. We hypothesized that the analysis of gene expression in peripheral blood mononuclear cells (PBMCs) would demonstrate differences in transcript expression between individuals who develop ISR and those who do not.Methods and ResultsWe determined and investigated PBMC gene expression of 358 patients undergoing an index procedure to treat in de novo coronary artery lesions with bare metallic stents, using a novel time-varying intercept model to optimally assess the time course of gene expression across a time course of blood samples. Validation analyses were conducted in an independent sample of 97 patients with similar time-course blood sampling and gene expression data. We identified 47 probesets with differential expression, of which 36 were validated upon independent replication testing. The genes identified have varied functions, including some related to cellular growth and metabolism, such as the NAB2 and LAMP genes.ConclusionsIn a study of patients undergoing bare metallic stent implantation, we have identified and replicated differential gene expression in peripheral blood mononuclear cells, studied across a time series of blood samples. The genes identified suggest alterations in cellular growth and metabolism pathways, and these results provide the basis for further specific functional hypothesis generation and testing of the mechanisms of ISR.

On Averaging Power for Genetic Association and Linkage Studies

A power calculation is crucial in planning genetic studies. In genetic association studies, the power is often calculated using the expected number of individuals with each genotype calculated from an assumed allele frequency under Hardy-Weinberg equilibrium. Since the allele frequency is often unknown, the number of individuals with each genotype is random and so a power calculation assuming a known allele frequency may be incorrect. Ambrosius et al. [1] recently showed that the power ignoring this randomness may lead to studies with insufficient power and proposed averaging the power due to the randomness. We extend the method of averaging power in two directions. First, for testing association in case-control studies, we use the Cochran-Armitage trend test and find that the time needed for calculating the averaged power is much reduced compared to the chi-square test with two degrees of freedom studied by Ambrosius et al. [1]. A real study is used for illustration of the method. Second, we extend the method to linkage analysis, where the number of identical-by-descent alleles shared by siblings is random. The distribution of identical-by-descent numbers depends on the underlying genetic model rather than the allele frequency. The robust test for linkage analysis is also examined using the averaged powers. We also recommend a sensitivity analysis when the true allele frequency or the number of identical-by-descent alleles is unknown.

Genomics of In-Stent Restenosis Early Insights Into a Complex Disease

Inflammation is a key component of atherosclerosis. Abundant preclinical data support the hypothesis that atherosclerosis is a chronic inflammatory disorder.1,2 Indeed, clinical trial data now provide evidence that inflammation, as reflected in serum markers such as C-reactive protein and interleukin-6, is a strong risk factor for the development and progression of atherosclerosis.3,4 The role of genetic factors in determining a predisposition or susceptibility to inflammation that exacerbates atherosclerosis is not fully known.nnArticle p 2417 nnIn-stent restenosis occurs after the deployment of an intravascular stent within an atherosclerotic lesion. The fibroproliferative response to this vascular “injury” typically develops within the first 9 months postprocedure. The response to injury follows a continuum in human arteries; some degree of cell proliferation occurs in all patients and can be thought of as a wound-healing process. In some individuals, however, the wound healing becomes excessive, leading to exuberant vascular smooth muscle cell growth and extracellular matrix synthesis, and encroachment on the arterial lumen, and resulting in a recurrence of clinical symptoms. Molecular and genetic studies suggest that cell cycle proteins, growth factors, and inflammatory cytokines regulate this process.5 Drug-eluting stents have dramatically reduced the prevalence of in-stent restenosis because of the local treatment of the fibroproliferation with 2 drugs, sirolimus and paclitaxel, which have antiproliferative and antiinflammatory properties.6,7 What is not known, however, is whether there is a genetic susceptibility that determines a patient’s response to stent deployment …