Association between allostatic load and breast cancer risk: a cohort study.

BACKGROUND: Allostatic load (AL) reflects the collective load of chronic stress during lifetime. Previous studies have shown that higher AL is associated with poor clinical outcomes among breast cancer patients. However, the relationship between AL and breast cancer risk is still unclear. METHODS: To fill the gap, we analyzed the association between AL and the development of breast cancer in 181,455 women identified from the UK Biobank. RESULTS: During the follow-up from 2006 to 2020, 5,701 women were diagnosed with incident breast cancer. Significantly higher AL was observed among incident breast cancer cases than all study participants (mean: 2.77 vs. 2.63, P < 0.01). Univariate Cox regression analysis indicated the risk of breast cancer was increased by 5% per one AL unit increase (hazard ratio (HR) = 1.05, 95% confidence interval (CI) 1.04, 1.07). In multivariate analyses, after adjusting demographics, family history of breast cancer, reproductive factors, socioeconomic status, lifestyle factors, and breast cancer polygenic risk score (PRS), the significant association remained (HR = 1.05, 95%CI 1.03, 1.07). The significant relationship was further confirmed in the categorical analysis. Compared with women in the low AL group (AL: 0 ~ 2), those in the high AL group (AL: 3 ~ 11) had a 1.17-fold increased risk of breast cancer (HR = 1.17, 95%CI 1.11, 1.24). Finally, in the stratified analysis, joint effects on the risk of breast cancer were observed between the AL and selected known breast cancer risk factors, including age, family history of breast cancer, PRS, income, physical activity, and alcohol consumption. CONCLUSION: In summary, those findings have demonstrated that higher AL was associated with an increased breast cancer risk in women. This association is likely independent of known breast cancer risk factors. Thus, the AL could be a valuable biomarker to help breast cancer risk prediction and stratification.

Association of Allostatic Load and All Cancer Risk in the SWAN Cohort.

Elevated chronic stress is thought to increase cancer risk, though the results so far have been inconsistent. In this study, we assessed the relationship between allostatic load (AL), a biological indicator of chronic stress, and overall cancer risk in 3015 women who participated in the Study of Women's Health Across the Nation (SWAN). Based on the distribution of AL, the study population was categorized into four groups, from the lowest (1st category) to the highest AL group (4th category). At baseline, African American and Hispanic women were more likely to be in the higher AL categories than White women (p < 0.001). In addition, women who smoked regularly, drank alcohol regularly, had no leisure physical activity, and had restless sleep were also more likely to be in the higher AL categories than their relative counterparts (p < 0.001). We also observed that women in the lower-income category with no health insurance were more likely to be in the higher AL category (p < 0.001). The study then found that women in the 4th category of AL (the highest AL group) had a 1.64-fold increased risk of overall cancer (Hazard ratio (HR): 1.64, 95% confidence interval (CI): 1.04, 2.59). The risk association was further strengthened after adjusting demographics, healthy behaviors, and socioeconomic factors with an HR of 2.08. In further analysis of individual biomarkers of AL score, we found that higher levels of triglyceride and CRP were associated with increased risk of cancer, highlighting the role of metabolic dysfunction and inflammation in the etiology of cancer development. In summary, we report that higher AL is associated with increased cancer risk.

Differences in molecular phenotype in mouse and human hypertrophic cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is characterized by phenotypic heterogeneity. We investigated the molecular basis of the cardiac phenotype in two mouse models at established disease stage (mouse-HCM), and human myectomy tissue (human-HCM). We analyzed the transcriptome in 2 mouse models with non-obstructive HCM (R403Q-MyHC, R92W-TnT)/littermate-control hearts at 24 weeks of age, and in myectomy tissue of patients with obstructive HCM/control hearts (GSE36961, GSE36946). Additionally, we examined myocyte redox, cardiac mitochondrial DNA copy number (mtDNA-CN), mt-respiration, mt-ROS generation/scavenging and mt-Ca2+ handling in mice. We identified distinct allele-specific gene expression in mouse-HCM, and marked differences between mouse-HCM and human-HCM. Only two genes (CASQ1, GPT1) were similarly dysregulated in both mutant mice and human-HCM. No signaling pathway or transcription factor was predicted to be similarly dysregulated (by Ingenuity Pathway Analysis) in both mutant mice and human-HCM. Losartan was a predicted therapy only in TnT-mutant mice. KEGG pathway analysis revealed enrichment for several metabolic pathways, but only pyruvate metabolism was enriched in both mutant mice and human-HCM. Both mutant mouse myocytes demonstrated evidence of an oxidized redox environment. Mitochondrial complex I RCR was lower in both mutant mice compared to controls. MyHC-mutant mice had similar mtDNA-CN and mt-Ca2+ handling, but TnT-mutant mice exhibited lower mtDNA-CN and impaired mt-Ca2+ handling, compared to littermate-controls. Molecular profiling reveals differences in gene expression, transcriptional regulation, intracellular signaling and mt-number/function in 2 mouse models at established disease stage. Further studies are needed to confirm differences in gene expression between mouse and human-HCM, and to examine whether cardiac phenotype, genotype and/or species differences underlie the divergence in molecular profiles.

Machine Learning Methods for Identifying Atrial Fibrillation Cases and Their Predictors in Patients With Hypertrophic Cardiomyopathy: The HCM-AF-Risk Model.

BACKGROUND: Hypertrophic cardiomyopathy (HCM) patients have a high incidence of atrial fibrillation (AF) and increased stroke risk, even with low CHA2DS2-VASc (congestive heart failure, hypertension, age diabetes, previous stroke/transient ischemic attack) scores. Hence, there is a need to understand the pathophysiology of AF/stroke in HCM. In this retrospective study, we develop and apply a data-driven, machine learning-based method to identify AF cases, and clinical/imaging features associated with AF, using electronic health record data. METHODS: HCM patients with documented paroxysmal/persistent/permanent AF (n = 191) were considered AF cases, and the remaining patients in sinus rhythm (n = 640) were tagged as No-AF. We evaluated 93 clinical variables; the most informative variables useful for distinguishing AF from No-AF cases were selected based on the 2-sample t test and the information gain criterion. RESULTS: We identified 18 highly informative variables that are positively (n = 11) and negatively (n = 7) correlated with AF in HCM. Next, patient records were represented via these 18 variables. Data imbalance resulting from the relatively low number of AF cases was addressed via a combination of oversampling and undersampling strategies. We trained and tested multiple classifiers under this sampling approach, showing effective classification. Specifically, an ensemble of logistic regression and naïve Bayes classifiers, trained based on the 18 variables and corrected for data imbalance, proved most effective for separating AF from No-AF cases (sensitivity = 0.74, specificity = 0.70, C-index = 0.80). CONCLUSIONS: Our model (HCM-AF-Risk Model) is the first machine learning-based method for identification of AF cases in HCM. This model demonstrates good performance, addresses data imbalance, and suggests that AF is associated with a more severe cardiac HCM phenotype.

INTRODUCTION: Les patients atteints d'une cardiomyopathie hypertrophique (CMH) présentent une forte incidence de fibrillation auriculaire (FA) et un risque accru d'accident vasculaire cérébral (AVC), malgré des scores CHA2DS2-VASc (congestive heart failure, hypertension, age diabetes, previous stroke/transient ischemic attack, c'est-à-dire : insuffisance cardiaque congestive, hypertension, âge, diabète, AVC ou accident ischémique transitoire antérieur) faibles. Par conséquent, il est nécessaire de comprendre la physiopathologie de la FA et de l'AVC en présence d'une CMH. Dans la présente étude rétrospective, nous avons élaboré et appliqué une méthode d'apprentissage automatique dirigée sur les données pour déterminer les cas de FA, et les caractéristiques cliniques/d'imagerie associées à la FA, à l'aide des données des dossiers de santé électroniques. MÉTHODES: Nous avons considéré les patients atteints d'une CMH qui ont une FA paroxystique/persistante/permanente documentée (n = 191) comme des cas de FA, et avons étiqueté les autres patients en rythme sinusal (n = 640) comme des cas sans FA. Nous avons évalué 93 variables cliniques; nous avons sélectionné les variables les plus informatives qui sont utiles pour distinguer les cas de FA des cas sans FA en fonction du test t pour deux échantillons et du critère de gain d'information. RÉSULTATS: Nous avons relevé 18 variables hautement informatives qui ont une corrélation positive (n = 11) et une corrélation négative (n = 7) avec la FA en présence d'une CMH. Ensuite, nous avons représenté les dossiers des patients au moyen de ces 18 variables. Nous avons remédié au déséquilibre des données, qui résulte du nombre relativement faible de cas de FA, grâce à une combinaison de stratégies de suréchantillonnage et de sous-échantillonnage. Nous avons formé et testé de nombreux classificateurs selon cette approche d'échantillonnage, qui montre une classification efficace. Particulièrement, un ensemble de régression logistique et de classificateurs bayésiens naïfs formés en fonction des 18 variables et corrigés en fonction du déséquilibre des données s'est révélé le plus efficace pour séparer les cas de FA des cas sans FA (sensibilité = 0,74, spécificité = 0,70, indice C = 0,80). CONCLUSIONS: Notre modèle (modèle de risque de CMH-FA) est la première méthode d'apprentissage automatique qui sert à déterminer les cas de FA en présence de CMH. Ce modèle permet de démontrer une bonne performance, de remédier au déséquilibre des données, et de croire que la FA est associée à un phénotype grave de CMH.

Identifying Ventricular Arrhythmias and Their Predictors by Applying Machine Learning Methods to Electronic Health Records in Patients With Hypertrophic Cardiomyopathy (HCM-VAr-Risk Model).

Clinical risk stratification for sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HC) employs rules derived from American College of Cardiology Foundation/American Heart Association (ACCF/AHA) guidelines or the HCM Risk-SCD model (C-index ∼0.69), which utilize a few clinical variables. We assessed whether data-driven machine learning methods that consider a wider range of variables can effectively identify HC patients with ventricular arrhythmias (VAr) that lead to SCD. We scanned the electronic health records of 711 HC patients for sustained ventricular tachycardia or ventricular fibrillation. Patients with ventricular tachycardia or ventricular fibrillation (n = 61) were tagged as VAr cases and the remaining (n = 650) as non-VAr. The 2-sample ttest and information gain criterion were used to identify the most informative clinical variables that distinguish VAr from non-VAr; patient records were reduced to include only these variables. Data imbalance stemming from low number of VAr cases was addressed by applying a combination of over- and undersampling strategies. We trained and tested multiple classifiers under this sampling approach, showing effective classification. We evaluated 93 clinical variables, of which 22 proved predictive of VAr. The ensemble of logistic regression and naïve Bayes classifiers, trained based on these 22 variables and corrected for data imbalance, was most effective in separating VAr from non-VAr cases (sensitivity = 0.73, specificity = 0.76, C-index = 0.83). Our method (HCM-VAr-Risk Model) identified 12 new predictors of VAr, in addition to 10 established SCD predictors. In conclusion, this is the first application of machine learning for identifying HC patients with VAr, using clinical attributes. Our model demonstrates good performance (C-index) compared with currently employed SCD prediction algorithms, while addressing imbalance inherent in clinical data.

Differences in microRNA-29 and Pro-fibrotic Gene Expression in Mouse and Human Hypertrophic Cardiomyopathy.

Background: Hypertrophic cardiomyopathy (HCM) is characterized by myocyte hypertrophy and fibrosis. Studies in two mouse models (R92W-TnT/R403Q-MyHC) at early HCM stage revealed upregulation of endothelin (ET1) signaling in both mutants, but TGFß signaling only in TnT mutants. Dysregulation of miR-29 expression has been implicated in cardiac fibrosis. But it is unknown whether expression of miR-29a/b/c and profibrotic genes is commonly regulated in mouse and human HCM. Methods: In order to understand mechanisms underlying fibrosis in HCM, and examine similarities/differences in expression of miR-29a/b/c and several profibrotic genes in mouse and human HCM, we performed parallel studies in rat cardiac myocyte/fibroblast cultures, examined gene expression in two mouse models of (non-obstructive) HCM (R92W-TnT, R403Q-MyHC)/controls at early (5 weeks) and established (24 weeks) disease stage, and analyzed publicly available mRNA/miRNA expression data from obstructive-HCM patients undergoing septal myectomy/controls (unused donor hearts). Results: Myocyte cultures: ET1 increased superoxide/H2O2, stimulated TGFß expression/secretion, and suppressed miR-29a expression in myocytes. The effect of ET1 on miR-29 and TGFß expression/secretion was antagonized by N-acetyl-cysteine, a reactive oxygen species scavenger. Fibroblast cultures: ET1 had no effect on pro-fibrotic gene expression in fibroblasts. TGFß1/TGFß2 suppressed miR-29a and increased collagen expression, which was abolished by miR-29a overexpression. Mouse and human HCM: Expression of miR-29a/b/c was lower, and TGFB1/collagen gene expression was higher in TnT mutant-LV at 5 and 24 weeks; no difference was observed in expression of these genes in MyHC mutant-LV and in human myectomy tissue. TGFB2 expression was higher in LV of both mutant mice and human myectomy tissue. ACE2, a negative regulator of the renin-angiotensin-aldosterone system, was the most upregulated transcript in human myectomy tissue. Pathway analysis predicted upregulation of the anti-hypertrophic/anti-fibrotic liver X receptor/retinoid X receptor (LXR/RXR) pathway only in human myectomy tissue. Conclusions: Our in vitro studies suggest that activation of ET1 signaling in cardiac myocytes increases reactive oxygen species and stimulates TGFß secretion, which downregulates miR-29a and increases collagen in fibroblasts, thus contributing to fibrosis. Our gene expression studies in mouse and human HCM reveal allele-specific differences in miR-29 family/profibrotic gene expression in mouse HCM, and activation of anti-hypertrophic/anti-fibrotic genes and pathways in human HCM.

Allele-specific differences in transcriptome, miRNome, and mitochondrial function in two hypertrophic cardiomyopathy mouse models.

Hypertrophic cardiomyopathy (HCM) stems from mutations in sarcomeric proteins that elicit distinct biophysical sequelae, which in turn may yield radically different intracellular signaling and molecular pathologic profiles. These signaling events remain largely unaddressed by clinical trials that have selected patients based on clinical HCM diagnosis, irrespective of genotype. In this study, we determined how two mouse models of HCM differ, with respect to cellular/mitochondrial function and molecular biosignatures, at an early stage of disease. We show that hearts from young R92W-TnT and R403Q-αMyHC mutation-bearing mice differ in their transcriptome, miRNome, intracellular redox environment, mitochondrial antioxidant defense mechanisms, and susceptibility to mitochondrial permeability transition pore opening. Pathway analysis of mRNA-sequencing data and microRNA profiles indicate that R92W-TnT mutants exhibit a biosignature consistent with activation of profibrotic TGF-ß signaling. Our results suggest that the oxidative environment and mitochondrial impairment in young R92W-TnT mice promote activation of TGF-ß signaling that foreshadows a pernicious phenotype in young individuals. Of the two mutations, R92W-TnT is more likely to benefit from anti-TGF-ß signaling effects conferred by angiotensin receptor blockers and may be responsive to mitochondrial antioxidant strategies in the early stage of disease. Molecular and functional profiling may therefore serve as aids to guide precision therapy for HCM.

Cardiosphere-Derived Cells Demonstrate Metabolic Flexibility That Is Influenced by Adhesion Status.

Adult stem cells demonstrate metabolic flexibility that is regulated by cell adhesion status. The authors demonstrate that adherent cells primarily utilize glycolysis, whereas suspended cells rely on oxidative phosphorylation for their ATP needs. Akt phosphorylation transduces adhesion-mediated regulation of energy metabolism, by regulating translocation of glucose transporters (GLUT1) to the cell membrane and thus, cellular glucose uptake and glycolysis. Cell dissociation, a pre-requisite for cell transplantation, leads to energetic stress, which is mediated by Akt dephosphorylation, downregulation of glucose uptake, and glycolysis. They designed hydrogels that promote rapid cell adhesion of encapsulated cells, Akt phosphorylation, restore glycolysis, and cellular ATP levels.

Relation of Heavy Alcohol Consumption to QTc Interval Prolongation.

Until now, few studies have examined QT intervals in subjects who consume alcohol. We performed this study to evaluate the associations between alcohol consumption and the QTc interval based on a general population. A total of 11,269 adults were examined using a multistage cluster sampling method to select a representative sample of subjects aged ≥35 years. Participants were asked to provide information about their alcohol consumption, and all participants received electrocardiograms and echocardiograms. A prolonged QTc interval was defined according to the national guidelines, which specify thresholds of ≥460 ms in women and ≥450 ms in men. Patients were divided into 3 categories, based on the amount of alcohol they consumed: heavy drinkers (>15 g/day for women and >30 g/day for men), moderate drinkers (≤15 g/day for women and ≤30 g/day for men), and nondrinkers (0 g/day). The results showed that the heavy drinkers had longer QTc intervals than did the nondrinkers. Multivariate logistic regression analyses revealed that men who were heavy drinkers had approximately 1.4-fold higher odds of having a prolonged QTc interval (odds ratio 1.431, 95% confidence interval [CI] 1.033 to 1.982, p = 0.031) than nondrinkers; in women, heavy drinkers had ∼2.3-fold higher odds of having a prolonged QTc interval (odds ratio 2.344, 95% CI 1.202 to 4.571, p = 0.012) than nondrinkers. Neither men nor women who were moderate drinkers exhibited a significant increase in risk for prolonged QTc interval. In conclusion, heavy alcohol consumption was found to be a risk factor for a prolonged QTc interval.

The Association Between Alcohol Consumption and Left Ventricular Ejection Fraction: An Observational Study on a General Population.

The results of previous studies on the relation between alcohol consumption and heart failure (HF) have been inconsistent. This study aimed to evaluate the association between alcohol consumption and left ventricular ejection fraction (LVEF) in a general population.A total of 10,824 adults were examined using a multistage cluster sampling method to select a representative sample of individuals who were at least 35-years old. The participants were asked to provide information about their alcohol consumption. Echocardiograms were obtained, and LVEF was calculated using modified Simpson's rule.Of the 10,824 participants included in the present study, 46.1% were males, and the mean participant age was 54 years; age ranged from 35 to 93 years. The overall prevalence of LVEF< 0.50 and LVEF < 0.40 in the studied population was 11.6% and 2.9%, respectively. The prevalence of LVEF < 0.5 and LVEF < 0.04 was higher in both the moderate and heavy drinker groups than in the nondrinker group (P <0.05). Multivariate logistic regression analyses corrected according to the different levels of alcohol consumption showed that moderate and heavy drinkers had an -1.3-fold and 1.2-fold higher risk of LVEF <0.5, respectively, than nondrinkers (OR: 1.381, 95% CI: 1.115-1.711, P = 0.003 for moderate drinkers; OR: 1.246, 95% CI: 1.064-1.460, P = 0.006 for heavy drinkers). Heavy drinkers had an ∼1.5-fold higher risk of decreased LVEF < 0.4 than nondrinkers (OR: 1.482, 95% CI: 1.117-1.965, P = 0.006). Moderate drinkers did not show a risk of decreased LVEF < 0.4 that was significantly higher than that of nondrinkers (OR: 1.183, 95% CI: 0.774-1.808, P = 0.437).According to these results, we concluded that increased alcohol consumption was associated with decreased LVEF compared with no alcohol consumption in this general population.

Common miR-590 Variant rs6971711 Present Only in African Americans Reduces miR-590 Biogenesis.

MicroRNAs (miRNAs) are recognized as important regulators of cardiac development, hypertrophy and fibrosis. Recent studies have demonstrated that genetic variations which cause alterations in miRNA:target interactions can lead to disease. We hypothesized that genetic variations in miRNAs that regulate cardiac hypertrophy/fibrosis might be involved in generation of the cardiac phenotype in patients diagnosed with hypertrophic cardiomyopathy (HCM). To investigate this question, we Sanger sequenced 18 miRNA genes previously implicated in myocyte hypertrophy/fibrosis and apoptosis, using genomic DNA isolated from the leukocytes of 199 HCM patients. We identified a single nucleotide polymorphism (rs6971711, C57T SNP) at the 17th position of mature miR-590-3p (= 57th position of pre-miR-590) that is common in individuals of African ancestry. SNP frequency was higher in African American HCM patients (n = 55) than ethnically-matched controls (n = 100), but the difference was not statistically significant (8.2% vs. 6.5%; p = 0.5). Using a cell culture system, we discovered that presence of this SNP resulted in markedly lower levels of mature miR-590-5p (39 ± 16%, p<0.003) and miR-590-3p (20 ± 2%, p<0.003), when compared with wild-type (WT) miR-590, without affecting levels of pri-miR-590 and pre-miR-590. Consistent with this finding, the SNP resulted in reduced target suppression when compared to WT miR-590 (71% suppression by WT vs 60% suppression by SNP, p<0.03). Since miR-590 can regulate TGF-ß, Activin A and Akt signaling, SNP-induced reduction in miR-590 biogenesis could influence cardiac phenotype by de-repression of these signaling pathways. Since the SNP is only present in African Americans, population studies in this patient population would be valuable to investigate effects of this SNP on myocyte function and cardiac physiology.