Blood Leukocyte DNA Methylation Predicts Risk of Future Myocardial Infarction and Coronary Heart Disease.

BACKGROUND: DNA methylation is implicated in coronary heart disease (CHD), but current evidence is based on small, cross-sectional studies. We examined blood DNA methylation in relation to incident CHD across multiple prospective cohorts. METHODS: Nine population-based cohorts from the United States and Europe profiled epigenome-wide blood leukocyte DNA methylation using the Illumina Infinium 450k microarray, and prospectively ascertained CHD events including coronary insufficiency/unstable angina, recognized myocardial infarction, coronary revascularization, and coronary death. Cohorts conducted race-specific analyses adjusted for age, sex, smoking, education, body mass index, blood cell type proportions, and technical variables. We conducted fixed-effect meta-analyses across cohorts. RESULTS: Among 11 461 individuals (mean age 64 years, 67% women, 35% African American) free of CHD at baseline, 1895 developed CHD during a mean follow-up of 11.2 years. Methylation levels at 52 CpG (cytosine-phosphate-guanine) sites were associated with incident CHD or myocardial infarction (false discovery rate<0.05). These CpGs map to genes with key roles in calcium regulation (ATP2B2, CASR, GUCA1B, HPCAL1), and genes identified in genome- and epigenome-wide studies of serum calcium (CASR), serum calcium-related risk of CHD (CASR), coronary artery calcified plaque (PTPRN2), and kidney function (CDH23, HPCAL1), among others. Mendelian randomization analyses supported a causal effect of DNA methylation on incident CHD; these CpGs map to active regulatory regions proximal to long non-coding RNA transcripts. CONCLUSION: Methylation of blood-derived DNA is associated with risk of future CHD across diverse populations and may serve as an informative tool for gaining further insight on the development of CHD.

Inflammation-related genes are associated with epigenetic aging in HIV.

Chronic inflammation is characteristic of both HIV and aging ("inflammaging") and may contribute to the accelerated aging observed in people living with HIV (PLWH). We examined whether three inflammation-related single-nucleotide polymorphisms (SNPs) were risk factors for accelerated aging and HIV-associated, non-AIDS (HANA) conditions among PLWH. We examined 155 postmortem cases with HIV (mean age = 47.3, 81% male, 68% self-reported White) from the National NeuroAIDS Tissue Consortium who had pre-mortem neurobehavioral/medical/virologic data and epigenomic data from occipital cortex tissue. Accelerated aging was measured according to the Epigenetic Clock; an aging biomarker based on DNA methylation levels. Past or current age-associated HANA conditions including cerebrovascular, liver and kidney disease, chronic obstructive pulmonary disease, cancer, and diabetes were determined via self-report. Epigenetic Aging Z-scores and likelihood of past/current HANA conditions were compared between major allele homozygotes and minor allele carriers for each SNP (IL-6 - 174G>C, IL-10 - 592C>A, TNF-α - 308 G>A) separately. Analyses were adjusted for relevant demographic/clinical factors. Epigenetic aging (e.g., higher Z-scores) was significantly greater in IL-6 C allele carriers (p = .002) and IL-10 CC homozygotes (p = .02) compared to other genotype groups. The likelihood of any past/current HANA condition did not differ by IL-10 genotype but was 3.36 times greater in IL-6 C allele carriers versus others (OR = 3.36, 95%CI = 1.09-10.34, p = .03). TNF-α genotype was not associated with epigenetic aging or HANA conditions. IL-6 and IL-10 SNPs may help to identify PLWH who are at high risk for accelerated aging. These insights into pathophysiological pathways may inform interventional approaches to treat rapid aging among PLWH.

A systematic approach to multifactorial cardiovascular disease: causal analysis.

The combination of systems biology and large data sets offers new approaches to the study of cardiovascular diseases. These new approaches are especially important for the common cardiovascular diseases that have long been described as multifactorial. This promise is undermined by biologists' skepticism of the spider web-like network diagrams required to analyze these large data sets. Although these spider webs resemble composites of the familiar biochemical pathway diagrams, the complexity of the webs is overwhelming. As a result, biologists collaborate with data analysts whose mathematical methods seem much like those of experts using Ouija boards. To make matters worse, it is not evident how to design experiments when the network implies that many molecules must be part of the disease process. Our goal is to remove some of this mystery and suggest a simple experimental approach to the design of experiments appropriate for such analysis. We will attempt to explain how combinations of data sets that include all possible variables, graphical diagrams, complementation of different data sets, and Bayesian analyses now make it possible to determine the causes of multifactorial cardiovascular disease. We will describe this approach using the term causal analysis. Finally, we will describe how causal analysis is already being used to decipher the interactions among cytokines as causes of cardiovascular disease.

Biomarkers to predict antidepressant response.

During the past several years, we have achieved a deeper understanding of the etiology/pathophysiology of major depressive disorder (MDD). However, this improved understanding has not translated to improved treatment outcome. Treatment often results in symptomatic improvement, but not full recovery. Clinical approaches are largely trial-and-error, and when the first treatment does not result in recovery for the patient, there is little proven scientific basis for choosing the next. One approach to enhancing treatment outcomes in MDD has been the use of standardized sequential treatment algorithms and measurement-based care. Such treatment algorithms stand in contrast to the personalized medicine approach, in which biomarkers would guide decision making. Incorporation of biomarker measurements into treatment algorithms could speed recovery from MDD by shortening or eliminating lengthy and ineffective trials. Recent research results suggest several classes of physiologic biomarkers may be useful for predicting response. These include brain structural or functional findings, as well as genomic, proteomic, and metabolomic measures. Recent data indicate that such measures, at baseline or early in the course of treatment, may constitute useful predictors of treatment outcome. Once such biomarkers are validated, they could form the basis of new paradigms for antidepressant treatment selection.

Reg IV: a promising marker of hormone refractory metastatic prostate cancer.

The diagnosis and management of prostate cancer is hampered by the absence of markers capable of identifying patients with metastatic disease. In order to identify potential new markers for prostate cancer, we compared gene expression signatures of matched androgen-dependent and hormone refractory prostate cancer xenografts. One candidate gene overexpressed in a hormone refractory xenograft was homologous to the regenerating protein gene family, a group of secreted proteins expressed in the gastrointestinal tract and overexpressed in inflammatory bowel disease and cancer. This gene, Reg IV, was confirmed to be differentially expressed in the LAPC-9 hormone refractory xenograft. Consistent with its up-regulation in a hormone refractory xenograft, it is expressed in several prostate tumors after neoadjuvant hormone ablation therapy. As predicted by its sequence homology, it is secreted from transiently transfected cells. It is also expressed strongly in a majority of hormone refractory metastases represented on two high-density tissue microarrays. In comparison, it is not expressed by any normal prostate specimens and only at low levels in approximately 40% of primary tumors. These data support Reg IV as a candidate marker for hormone refractory metastatic prostate cancer.

Epithelial cell adhesion molecule (KSA) expression: pathobiology and its role as an independent predictor of survival in renal cell carcinoma.

PURPOSE: Epithelial cell adhesion molecule (EpCAM) is a widely expressed adhesion molecule in epithelial cancers. The purpose of this study is to determine the protein expression patterns of EpCAM in renal cell carcinoma (RCC) using tissue arrays linked to a clinicopathological database to evaluate both its predictive power in patient stratification and its suitability as a potential target for immunotherapeutic treatment strategies. EXPERIMENTAL DESIGN: The University of California, Los Angeles kidney cancer tissue microarray contains specimens from 417 patients treated with nephrectomy. EpCAM protein expression in tumors and matched morphologically normal renal tissues was evaluated using anti-EpCAM immunohistochemistry. The resultant expression reactivity was correlated with clinicopathological variables. RESULTS: EpCAM is consistently expressed in the distal nephron on normal renal epithelium. Clear cell RCCs show minimal and infrequent EpCAM expression, whereas chromophobe and collecting duct RCCs both demonstrate intense and frequent expression. Of 318 clear cell carcinomas used in the analysis, 10% were EpCAM positive in > or = 50% of cells, and 8% of patients would be considered candidates for EpCAM-based therapy, based on high expression [> or = moderate intensity and frequent (> or = 50%) expression] and the need for systemic treatment. EpCAM expression was an independent prognostic factor for improved disease-specific survival, with a multivariate hazard ratio of 0.63 (P = 0.017; 95% confidence interval, 0.43-0.92). CONCLUSIONS: EpCAM is a novel prognostic molecular marker in RCC patients, and its positive expression is an independent predictor associated with improved survival. However, high expression in morphologically normal renal tissues and minimal or absent expression in clear cell carcinomas will likely limit the utility of this epithelial marker in targeted treatments of this most common RCC type.

Population differences in cardiovascular reactivity to the cold pressor test.

The interaction of race and climatic adaptation on patterns of cardiovascular reactivity among young adult males was examined. Malay and Chinese subjects living in a tropical climate in the Orient and Caucasians living in a sub-tropical climate in North America were investigated. The cold pressor test with hand immersion in cold water was used as the stressor. Systolic and diastolic blood pressures, cardiac frequency, cardiac output, and stroke volume were measured. The results provided limited evidence for absence of differences in cardiac reactivity among racial groups and for greater vascular reactivity in the Caucasians. Cold immersion also elicited differential responses which could be partially attributed to differences in acclimatizations status. © 1995 Wiley-Liss, Inc.

Postprandial lipemia detects the effect of soy protein on cardiovascular disease risk compared with the fasting lipid profile.

Studies examining the effect of soy protein on cardiovascular disease (CVD) risk factors have not taken advantage of the postprandial state as an adjunct to the fasting lipid profile. The American Heart Association has acknowledged the efficacy of soy protein in reducing CVD risk factors to be limited. We hypothesized that the postprandial state would be more sensitive to any favorable changes associated with consuming soy protein compared with the fasting lipid profile. Furthermore, the presence of isoflavones in soy would enhance this effect. Thirty sedentary males aged 18-30 years were randomly assigned to milk protein (Milk), isoflavone-poor soy (Soy-), or isoflavone-rich soy (Soy+). Usual diets were supplemented with 25 g/day of protein for 28 days. Serum samples were collected before and after supplementation in a fasted state and postprandially at 30, 60, 120, 240, and 360 min after a high-fat, 1,000 kcal shake. Triacylglycerol (TAG), total cholesterol, non-esterified fatty acids, apolipoproteins B-100 and A-I and glucose concentrations were quantified. Fasting concentrations were not different after any protein supplementation. Postprandial TAG and TAG AUC increased after Soy-consumption supporting the postprandial state as a more sensitive indicator of soy ingestion effects on CVD risk factors compared with the fasting lipid profile. Furthermore, the absence of isoflavones in soy protein may have deleterious consequences on purported cardio-protective effects.

Monoclonal antibody targeting of N-cadherin inhibits prostate cancer growth, metastasis and castration resistance.

The transition from androgen-dependent to castration-resistant prostate cancer (CRPC) is a lethal event of uncertain molecular etiology. Comparing gene expression in isogenic androgen-dependent and CRPC xenografts, we found a reproducible increase in N-cadherin expression, which was also elevated in primary and metastatic tumors of individuals with CRPC. Ectopic expression of N-cadherin in nonmetastatic, androgen-dependent prostate cancer models caused castration resistance, invasion and metastasis. Monoclonal antibodies against the ectodomain of N-cadherin reduced proliferation, adhesion and invasion of prostate cancer cells in vitro. In vivo, these antibodies slowed the growth of multiple established CRPC xenografts, blocked local invasion and metastasis and, at higher doses, led to complete regression. N-cadherin-specific antibodies markedly delayed the time to emergence of castration resistance, markedly affected tumor histology and angiogenesis, and reduced both AKT serine-threonine kinase activity and serum interleukin-8 (IL-8) secretion. These data indicate that N-cadherin is a major cause of both prostate cancer metastasis and castration resistance. Therapeutic targeting of this factor with monoclonal antibodies may have considerable clinical benefit.

NMR analysis of lipoprotein particle size does not increase sensitivity to the effect of soy protein on CVD risk when compared with the traditional lipid profile.

The traditional lipid profile compared with nuclear magnetic resonance (NMR) may underestimate the risk for cardiovascular disease and may explain some of the discrepancies in results between studies analyzing the salubrious effects of soy. Our purpose was to compare the traditional lipid profile with NMR quantification of the number of lipoprotein particles, subclasses, and diameters or sizes in 30 sedentary males, between 18 and 30 years of age, consuming 1 of the following 3 supplements daily for 28 days: milk protein (Milk), isoflavone-poor soy protein (Soy-), or isoflavone-rich soy protein (Soy+). The study used a double-blind, parallel-arm design with random assignment to 1 of the 3 protein supplement groups. Fasting EDTA blood samples were collected at baseline and after 28 days of supplementation and analyzed for the number and size of very low-density lipoprotein (VLDL), low-density lipoprotein (LDL), and high-density lipoprotein (HDL) particles, respectively. Fasting serum samples were analyzed for concentrations of total cholesterol (TC), LDL cholesterol (LDL-C), total HDL cholesterol (HDL-C), HDL(2)-C, HDL(3)-C, triglycerides (TGs), free fatty acids (FFAs), and glucose. Fasting heparin blood samples were collected at baseline and after supplementation and analyzed for apolipoproteins A-I, A-II, B, C-II, C-III, and E, as well as hepatic and lipoprotein lipase concentrations. HDL3-C increased by 47.2% after Soy+ supplementation and hepatic lipase decreased 19.2% after Soy- supplementation (p < 0.05). HDL-C and apolipoproteins A-I and A-II were found to increase in all 3 groups (p < 0.05). Results support that NMR analysis of lipoprotein particle number and size are not more sensitive to the effect of soy protein on CVD risk compared with the traditional lipid profile. Furthermore, the lack of isoflavones in soy protein seems to have a deleterious effect on hepatic lipase.