Serum cholesterol levels and the risk of brain natriuretic peptide-diagnosed heart failure in postmenopausal women: a population-based prospective cohort study

Biobanks in chronic disease management: A comprehensive review of strategies, challenges, and future directions

Biobanks, through the collection and storage of patient blood, tissue, genomic, and other biological samples, provide unique and rich resources for the research and management of chronic diseases such as cardiovascular diseases, diabetes, and cancer. These samples contain valuable cellular and molecular level information that can be utilized to decipher the pathogenesis of diseases, guide the development of novel diagnostic technologies, treatment methods, and personalized medical strategies. This article first outlines the historical evolution of biobanks, their classification, and the impact of technological advancements. Subsequently, it elaborates on the significant role of biobanks in revealing molecular biomarkers of chronic diseases, promoting the translation of basic research to clinical applications, and achieving individualized treatment and management. Additionally, challenges such as standardization of sample processing, information privacy, and security are discussed. Finally, from the perspectives of policy support, regulatory improvement, and public participation, this article provides a forecast on the future development directions of biobanks and strategies to address challenges, aiming to safeguard and enhance their unique advantages in supporting chronic disease prevention and treatment.

Pregnancy, Reproductive Factors, and Female Heart Failure Risk and Outcomes

PURPOSE OF REVIEW

The purpose of this review is to provide an overview of recent evidence on female-specific risk factors related to reproductive status or pregnancy.

RECENT FINDINGS

Pregnancy-related factors, including hypertensive disorders and gestational diabetes, increase the risk of heart failure in women, while breastfeeding and hormone therapy may offer protection. Hypertensive disorders of pregnancy, gestational diabetes, polycystic ovarian syndrome, placental abruption, younger maternal age at first live birth, younger maternal age at last live birth, number of stillbirths, number of pregnancies, onset of menstruation before 12 years of age, shorter reproductive age, ovariectomy, and prolonged absence of ovarian hormones may increase the risk of heart failure in women. Conversely, breastfeeding status and hormone therapy (for menopause or contraception) may serve as protective factors, while fertility treatments have no discernible effect on the risk of heart failure.

Causal relationship between nutritional assessment phenotypes and heart failure: A Mendelian randomization study

Introduction

Malnutrition is strongly associated with heart failure (HF); however, the causal link remains unclear. We used Mendelian randomization (MR) to infer causal associations between different nutritional assessment phenotypes and HF and to analyze whether these associations were mediated by common HF risk factors.

Methods

Two-sample bidirectional MR was used to infer causal associations between nutritional assessment phenotypes and HF. Mutual influences between different nutritional assessment phenotypes and potential correlations were estimated using multivariate MR methods. Two-step MR was used to quantify the mediating effects of common HF risk factors on the causal associations.

Results

Three phenotypes were positively associated with the development of HF: waist circumference (WC) (odds ratio [OR] = 1.74; 95% confidence interval [CI], 1.60-1.90; P = 3.95 × 10-39), body mass index (BMI) (OR = 1.70; 95%CI, 1.60-1.80; P = 1.35 × 10-73), and whole body fat mass (WBFM) (OR = 1.54; 95%CI, 1.44-1.65; P = 4.82 × 10-37). Multivariate MR indicated that WBFM remained positively associated with HF after conditioning on BMI and WC (OR = 2.05; 95%CI, 1.27-3.31; P = 0.003). Three phenotypes were negatively correlated with the development of HF: usual walking pace (UWP) (OR = 0.40; 95%CI, 0.27-0.60; P = 8.41 × 10-6), educational attainment (EA) (OR = 0.73; 95%CI, 0.67-0.79; P = 2.27 × 10-13), and total cholesterol (TC) (OR = 0.90; 95%CI, 0.84-0.96; P = 4.22 × 10-3). There was a bidirectional causality between HF and UWP (Effect estimate = -0.03; 95%CI, -0.05 to -0.01; P = 1.95 × 10-3). Mediation analysis showed that common risk factors for HF (hypertension, coronary artery disease, cardiomyopathy, and valvular heart disease) mediated these causal associations (all P < 0.05).

Conclusions

BMI, WC, and WBFM are potential risk factors for HF, and the correlation between WBFM and HF was significantly stronger than that between BMI and WC, and HF. EA, UWP, and TC are potential protective factors against HF. Common risk factors for HF mediate these causal pathways. Early identification of potential risk or protective factors for HF patients from the dimension of nutritional status is expected to further improve patient outcomes.