Neighborhood-level Social Vulnerability and Prevalence of Cardiovascular Risk Factors and Coronary Heart Disease.

Social determinants of health are implicated in the geographic variation in cardiovascular diseases (CVDs). The social vulnerability index (SVI) is an estimate of a neighborhood's potential for deleterious outcomes when faced with natural disasters or disease outbreaks. We sought to investigate the association of the SVI with cardiovascular risk factors and the prevalence of coronary heart disease (CHD) in the United States at the census tract level. We linked census tract SVI with prevalence of census tract CVD risk factors (smoking, high cholesterol, diabetes, high blood pressure, low physical activity and obesity), and prevalence of CHD obtained from the behavioral risk factor surveillance system. We evaluated the association between SVI, its sub-scales, CVD risk factors and CHD prevalence using linear regression. Among 72,173 census tracts, prevalence of all cardiovascular risk factors increased linearly with SVI. A higher SVI was associated with a higher CHD prevalence (R2 = 0.17, P < 0.0001). The relationship between SVI and CHD was stronger when accounting for census-tract median age (R2 = 0.57, P < 0.0001). A multivariable linear regression model including 4 SVI themes separately explained considerably more variation in CHD prevalence than the composite SVI alone (50.0% vs 17.3%). Socioeconomic status and household composition and disability were the SVI themes most closely associated with cardiovascular risk factors and CHD prevalence. In the United States, social vulnerability can explain significant portion of geographic variation in CHD, and its risk factors. Neighborhoods with high social vulnerability are at disproportionately increased risk of CHD and its risk factors. Social determinants of health are implicated in the geographic variation in cardiovascular diseases (CVDs). We investigated the association of social vulnerability index (SVI) with cardiovascular risk factors and the prevalence of coronary heart disease (CHD) in the United States at the census tract level. We show that cardiovascular risk factors and CHD were more common with higher SVI. A multivariable linear regression model including 4 SVI themes separately explained considerably more variation in CHD prevalence than the composite SVI alone (50.0% vs 17.3%). Socioeconomic status and household composition and/or disability were the SVI themes most closely associated with cardiovascular risk factors and CHD prevalence.

Soluble Tumor Necrosis Factor Receptor 1 is Associated With Cardiovascular Risk in Persons With Coronary Artery Calcium Score of Zero.

BACKGROUND: A coronary artery calcium (CAC) score of zero confers a low but nonzero risk of atherosclerotic cardiovascular events (CVD) in asymptomatic patient populations, and additional risk stratification is needed to guide preventive interventions. Soluble tumor necrosis factor receptors (sTNFR-1 and sTNFR-2) are shed in the context of TNF-alpha signaling and systemic inflammation, which play a role in atherosclerosis and plaque instability. We hypothesized that serum sTNFR-1 concentrations may aid in cardiovascular risk stratification among asymptomatic patients with a CAC score of zero. METHODS: We included all participants with CAC=0 and baseline sTNFR-1 measurements from the prospective cohort Multi-Ethnic Study of Atherosclerosis (MESA). The primary outcome was a composite CVD event (myocardial infarction, stroke, coronary revascularization, cardiovascular death). RESULTS: The study included 1471 participants (mean age 57.6 years, 64% female), with measured baseline sTNFR-1 ranging from 603 pg/mL to 5544 pg/mL (mean 1294 pg/mL ±378.8 pg/mL). Over a median follow-up of 8.5 years, 37 participants (2.5%) experienced a CVD event. In multivariable analyses adjusted for Framingham Score, doubling of sTNFR-1 was associated with a 3-fold increase in the hazards of CVD (HR 3.0, 95% CI: 1.48-6.09, P = 0.002), which remained significant after adjusting for traditional CVD risk factors individually (HR 2.29; 95% CI: 1.04-5.06, P=0.04). Doubling of sTNFR-1 was also associated with progression of CAC >100, adjusted for age (OR 2.84, 95% CI: 1.33-6.03, P=0.007). CONCLUSIONS: sTNFR-1 concentrations are associated with more CVD events in participants with a CAC score of zero. Utilizing sTNFR-1 measurements may improve cardiovascular risk stratification and guide primary prevention in otherwise low-risk individuals.

Evidence-Based Medical Management of Peripheral Artery Disease.

Peripheral artery disease is an atherosclerotic disease of the lower extremities associated with high cardiovascular mortality. Management of this condition may include lifestyle modifications, medical management, endovascular repair, or surgery. The medical approach to peripheral artery disease is multifaceted and includes cholesterol reduction, antiplatelet therapy, anticoagulation, peripheral vasodilators, blood pressure management, exercise therapy, and smoking cessation. Adherence to this regimen can reduce limb-related complications like critical limb ischemia and amputation, as well as systemic complications of atherosclerosis like stroke and myocardial infarction. Relative to coronary artery disease, peripheral artery disease is an undertreated condition. In this article, we explore the evidence behind medical therapies for the management of peripheral artery disease.

Predicting time to castration resistance in hormone sensitive prostate cancer by a personalization algorithm based on a mechanistic model integrating patient data.

BACKGROUND: Prostate cancer (PCa) is a leading cause of cancer death of men worldwide. In hormone-sensitive prostate cancer (HSPC), androgen deprivation therapy (ADT) is widely used, but an eventual failure on ADT heralds the passage to the castration-resistant prostate cancer (CRPC) stage. Because predicting time to failure on ADT would allow improved planning of personal treatment strategy, we aimed to develop a predictive personalization algorithm for ADT efficacy in HSPC patients. METHODS: A mathematical mechanistic model for HSPC progression and treatment was developed based on the underlying disease dynamics (represented by prostate-specific antigen; PSA) as affected by ADT. Following fine-tuning by a dataset of ADT-treated HSPC patients, the model was embedded in an algorithm, which predicts the patient's time to biochemical failure (BF) based on clinical metrics obtained before or early in-treatment. RESULTS: The mechanistic model, including a tumor growth law with a dynamic power and an elaborate ADT-resistance mechanism, successfully retrieved individual time-courses of PSA (R(2) = 0.783). Using the personal Gleason score (GS) and PSA at diagnosis, as well as PSA dynamics from 6 months after ADT onset, and given the full ADT regimen, the personalization algorithm accurately predicted the individual time to BF of ADT in 90% of patients in the retrospective cohort (R(2) = 0.98). CONCLUSIONS: The algorithm we have developed, predicting biochemical failure based on routine clinical tests, could be especially useful for patients destined for short-lived ADT responses and quick progression to CRPC. Prospective studies must validate the utility of the algorithm for clinical decision-making.

Whole blood defensin mRNA expression is a predictive biomarker of docetaxel response in castration-resistant prostate cancer.

This study tested the potential of circulating RNA-based signals as predictive biomarkers for docetaxel response in patients with metastatic castration-resistant prostate cancer (CRPC). RNA was analyzed in blood from six CRPC patients by whole-transcriptome sequencing (total RNA-sequencing) before and after docetaxel treatment using the Illumina's HiSeq platform. Targeted RNA capture and sequencing was performed in an independent cohort of ten patients with CRPC matching the discovery cohort to confirm differential expression of the genes. Response to docetaxel was defined on the basis of prostate-specific antigen levels and imaging criteria. Two-way analysis of variance was used to compare differential gene expression in patients classified as responders versus nonresponders before and after docetaxel treatment. Thirty-four genes with two-fold differentially expressed transcripts in responders versus nonresponders were selected from total RNA-sequencing for further validation. Targeted RNA capture and sequencing showed that 13/34 genes were differentially expressed in responders. Alpha defensin genes DEFA1, DEFA1B, and DEFA3 exhibited significantly higher expression in responder patients compared with nonresponder patients before administration of chemotherapy (fold change >2.5). In addition, post-docetaxel treatment significantly increased transcript levels of these defensin genes in responders (fold change >2.8). Our results reveal that patients with higher defensin RNA transcripts in blood respond well to docetaxel therapy. We suggest that monitoring DEFA1, DEFA1B, and DEFA3 RNA transcripts in blood prior to treatment will be helpful to determine which patients are better candidates to receive docetaxel chemotherapy.

Exosomal miR-1290 and miR-375 as prognostic markers in castration-resistant prostate cancer.

BACKGROUND: Extracellular microRNAs (miRNAs) embedded in circulating exosomes may serves as prognostic biomarkers in cancer. OBJECTIVE: To identify and evaluate plasma exosomal miRNAs for prognosis in castration-resistant prostate cancer (CRPC). DESIGN, SETTING, AND PARTICIPANTS: RNA sequencing was performed to identify candidate exosomal miRNAs associated with overall survival in a screening cohort of 23 CRPC patients. Candidate miRNAs were further evaluated for prognosis using quantitative real-time polymerase chain reaction in a follow-up cohort of 100 CRPC patients. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Cox regression and Kaplan-Meier survival analyses were used to evaluate survival association using candidate miRNAs along with clinical prognostic factors. RESULTS AND LIMITATIONS: RNA sequencing in screening cohort generated approximately 6.80 million mappable reads per patient. Of those with normalized read counts ≥ 5, 43% were mapped to miRNAs for a total of 375 known and 57 novel miRNAs. Cox regression analysis identified an association of miR-1290, -1246, and -375 with overall survival (false discover rate < 0.05). Of those, higher levels of miR-1290 and -375 were significantly associated with poor overall survival (p < 0.004) in the follow-up cohort. Incorporation of miR-1290/-375 into putative clinical prognostic factors-based models in CRPC stage significantly improved predictive performance with a time-dependent area under the curve increase from 0.66 to 0.73 (p = 6.57 × 10(-6)). CONCLUSIONS: Plasma exosomal miR-1290 and miR-375 are promising prognostic biomarkers for CRPC patients. Prospective validation is needed for further evaluation of these candidate miRNAs. PATIENT SUMMARY: In this study, we evaluated whether small RNAs circulating in blood could be used to predict clinical outcomes in late-stage prostate cancer patients. We identified two blood-based small RNAs whose levels showed significant association with survival. Our results warrant further investigation because the noninvasive blood-based test has great potential in the management of late-stage prostate cancer.