Genetic predisposition to smoking in relation to the risk of frailty in ageing

Causal relationship between neuroticism and frailty: A bidirectional Mendelian randomization study

BACKGROUND

Observational studies have shown that neuroticism is associated with frailty, but the causal relationship between them remains unclear.

METHODS

A two-sample Mendelian randomization (MR) study was conducted to explore the bidirectional causal relationship between neuroticism (n = 380,506 for the primary analysis, n = 79,004 for the validation) and frailty (n = 175,226) using publicly available genome-wide association study data. The inverse variance weighted (IVW), weighted median, and MR-Egger were used to obtain the causal estimates. Findings were verified through extensive sensitivity analyses and validated using another dataset. Multivariable MR (MVMR) analysis was performed to estimate the direct causal effects with adjustment of potential confounders. Two-step MR technique was then conducted to explore the mediators in the causal effects of neuroticism on frailty.

RESULTS

Genetically-predicted higher neuroticism score was significantly correlated with higher frailty index (IVW beta: 0.53, 95%CI: 0.48 to 0.59, P = 9.3E-83), and genetically-determined higher frailty index was significantly associated with higher neuroticism score (IVW beta: 0.28, 95%CI: 0.21 to 0.35, P = 1.3E-16). These results remained robust across sensitivity analyses and were reproducible using another dataset. The MVMR analysis indicated that the causal relationships remained significant after adjusting for the potential confounding factors. Mediation analysis revealed that depression, years of schooling, and smoking were significantly mediated the causal effects of neuroticism on frailty.

CONCLUSIONS

A bidirectional causal relationship existed between neuroticism and frailty. Our findings suggested that early intervention and behavioral changes might be helpful to reduce the neuroticism levels and prevent the development of frailty.

Pre-frailty after blood or marrow transplantation and the risk of subsequent mortality

We examined the prevalence, risk factors, and association between pre-frailty and subsequent mortality after blood or marrow transplantation (BMT). Study participants were drawn from the BMT Survivor Study (BMTSS) and included 3346 individuals who underwent BMT between 1974 and 2014 at one of three transplant centers and survived ≥2 years post-BMT. Participants completed the BMTSS survey at a median of 9 years from BMT and were followed for subsequent mortality for a median of 5 years after survey completion. Closest-age and same-sex biological siblings also completed the survey. Previously published self-reported indices (exhaustion, weakness, low energy expenditure, slowness, unintentional weight loss) classified participants as non-frail (0-1 indices) or pre-frail (2 indices). National Death Index was used to determine vital status and cause of death. Overall, 626 (18.7%) BMT survivors were pre-frail. BMT survivors had a 3.2-fold higher odds of being pre-frail (95% CI = 1.9-5.3) compared to siblings. Compared to non-frail survivors, pre-frail survivors had higher hazards of all-cause mortality (adjusted hazard ratio [aHR] = 1.6, 95% CI = 1.4-2.0). Female sex, pre-BMT radiation, smoking, lack of exercise, anxiety, and severe/life-threatening chronic health conditions were associated with pre-frailty. The novel association between pre-frailty and subsequent mortality provides evidence for interventions as pre-frail individuals may transition back to their robust state.

The Association Between an Electronic Health Record (EHR)-Embedded Frailty Index and Patient-Reported Outcomes Among Patients with Metastatic Non-Small-Cell Lung Cancer on Immunotherapy: A Brief Report

Background: While frailty is a well-established predictor of overall mortality among patients with metastatic non-small cell lung cancer (mNSCLC), its association with patient-reported outcomes is not well-characterized. The goal of this study was to examine the association between an electronic frailty index (eFI) score and patient-reported outcome measures along with prognostic awareness among patients with mNSCLC receiving immunotherapy. Methods: In a cross-sectional study, patients with mNSCLC who were on immunotherapy completed the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC-QLQ-C30) and the National Cancer Institute Patient Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE). We utilized bivariate analyses to compare quality of life, symptoms, supportive services, and prognostic awareness among 3 groups defined by e-frailty status. Results: Sixty patients (mean age 62.5 years, 75% Caucasian, 60% women) participated. Most patients were pre-frail (68%), with 13% being frail and 18% non-frail. Pre-frail and frail patients had significantly lower physical function scores (mean 83.9 fit vs 74.8 pre-frail vs 60.0 frail, P = .04) and higher rates of self-reported pain (75% frail vs 41.5% pre-frail vs 18.2% fit; P = .04) compared to non-frail patients. We found no differences in palliative referral rates. Conclusion: Pre-frail and frail mNSCLC patients identified by the eFI have higher rates of pain and physical functional impairments than non-frail patients. These findings highlight the importance of emphasizing preventive interventions targeting social needs, functional limitations, and pain management, especially among pre-frail patients to reduce further decline.

Sex differences in frailty among older adults

By definition, aging is a natural, gradual and continuous process. On the other hand, frailty reflects the increase in vulnerability to stressors and shortens the time without disease (health span) while longevity refers to the length of life (lifespan). The average life expectancy has significantly increased during the last few decades. A longer lifespan has been accompanied by an increase in frailty and decreased independence in older adults, with major differences existing between men and women. For example, women tend to live longer than men but also experience higher rates of frailty and disability. Sex differences prevent optimization of lifestyle interventions and therapies to effectively prevent frailty. Sex differences in frailty and aging are rooted in a complex interplay between uncontrollable (genetic, epigenetic, physiological), and controllable factors (psychosocial and lifestyle factors). Thus, understanding the underlying causes of sex differences in frailty and aging is essential for developing personalized interventions to promote healthy aging and improve quality of life in older men and women. In this review, we have discussed the key contributors and knowledge gaps related to sex differences in aging and frailty.