Protein Nutritional Status and Frailty: A Mendelian Randomization Study

Development and Validation of a Nomogram for Predicting Nutritional Risk Based on Frailty Scores in Older Stroke Patients

BACKGROUND

In older stroke patients with frailty, nutritional deficiencies can amplify their susceptibility, delay recovery, and deteriorate prognosis. A precise predictive model is crucial to assess their nutritional risk, enabling targeted interventions for improved clinical outcomes.

OBJECTIVE

To develop and externally validate a nutritional risk prediction model integrating general demographics, physical parameters, psychological indicators, and biochemical markers. The aim is to facilitate the early identification of older stroke patients requiring nutritional intervention.

METHODS

This was a multicenter cross-sectional study. A total of 570 stroke patients were included, 434 as the modeling set and 136 as the external validation set. The least absolute shrinkage selection operator (LASSO) regression analysis was used to select the predictor variables. Internal validation was performed using Bootstrap resampling (1000 iterations). The nomogram was constructed based on the results of logistic regression. The performance assessment relied on the receiver operating characteristic curve (ROC), Hosmer--Lemeshow test, calibration curves, Brier score, and decision curve analysis (DCA).

RESULTS

The predictive nomogram encompassed seven pivotal variables: Activities of Daily Living (ADL), NIHSS score, diabetes, Body Mass Index (BMI), grip strength, serum albumin levels, and depression. Together, these variables comprehensively evaluate the overall health and nutritional status of elderly stroke patients, facilitating accurate assessment of their nutritional risk. The model exhibited excellent accuracy in both the development and external validation sets, evidenced by AUC values of 0.934 and 0.887, respectively. Such performance highlights its efficacy in pinpointing elderly stroke patients who require nutritional intervention. Moreover, the model showed robust goodness of fit and practical applicability, providing essential clinical insights to improve recovery and prognosis for patients prone to malnutrition.

CONCLUSIONS

Elderly individuals recovering from stroke often experience significant nutritional deficiencies. The nomogram we devised accurately assesses this risk by combining physiological, psychological, and biochemical metrics. It equips healthcare providers with the means to actively screen for and manage the nutritional care of these patients. This tool is instrumental in swiftly identifying those in urgent need of targeted nutritional support, which is essential for optimizing their recovery and managing their nutrition more effectively.

Plant-Based Diet Indices and Their Association with Frailty in Older Adults: A CLHLS-Based Cohort Study

Within the realm of aging, the nexus between diet and health has garnered considerable attention. However, only select studies have amalgamated insights into the correlation between plant and animal food consumption and frailty. Our aim was to appraise the connections between the overall plant-based diet index (PDI), healthful plant-based diet index (hPDI), and unhealthful plant-based diet index (uPDI) and frailty in the elderly, utilizing data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). This cohort study drew upon CLHLS data spanning from 2008 to 2018. The PDI, hPDI, and uPDI were gauged using a simplified food frequency questionnaire (FFQ). A frailty index, encompassing 35 variables across major health domains, was formulated. Cox proportional hazard models were employed to scrutinize the associations between the three plant-based dietary indices and frailty in older adults, including an exploration of gender disparities in these associations. A cohort of 2883 study participants was encompassed, with 1987 (68.9%) observed to be either frail or in the pre-frail stage. The Cox model with penalized spline exhibited linear associations of PDI, hPDI, and uPDI with the frailty index. Following covariate adjustments, it was discerned that older adults situated in the highest quartiles of PDI (HR = 0.86, 95% CI: 0.77-0.95) and hPDI (HR = 0.83, 95% CI: 0.74-0.93) experienced a 14% and 17% diminished risk of frailty compared to those in the lowest quartiles of PDI and hPDI, respectively. Conversely, when contrasted with those in the lowest quartile of uPDI, older adults adhering to the highest tertile of uPDI exhibited a 21% elevated risk of frailty (HR = 1.21, 95% CI: 1.08-1.36), with both associations achieving statistical significance (p < 0.01). Moreover, additional subgroup analyses revealed that the protective effects of PDI and hPDI against frailty and the deleterious effects of uPDI were more conspicuous in men compared to women. To forestall or decelerate the progression of frailty in the elderly, tailored dietary interventions are imperative, particularly targeting male seniors.

Genetic predisposition to white blood cells in relation to the risk of frailty

BACKGROUND

Observational studies have suggested an association between white blood cells (WBCs) and frailty, but considering the susceptibility to reverse causality and confounding, the causal direction and magnitude of this association remain ambiguous. Our aim was to investigate the causal effect of WBCs on frailty by means of a Mendelian randomization (MR) analysis.

METHODS

Based on the genome-wide association study (GWAS) summary statistics data provided by the European Bioinformatics Institute (EBI), we carried out a two-sample MR study. We applied the genetically predicted independent WBCs from GWAS as a measure of exposure data. The Rockwood Frailty Index (FI) was used as outcome measure, which was derived from a meta-analysis from GWAS in UK Biobank European ancestry participants and Swedish TwinGene participants. Our study applied inverse variance weighted (IVW), weighted median, Mendelian randomization-Egger (MR-Egger) and outlier test (MR-PRESSO) methods to explore relationships between various WBCs and frailty.

RESULTS

In our study, a possible causal relationship between eosinophil levels and frailty was demonstrated by two-sample MR analysis. Eosinophils were associated with FI (beta:0.0609; 95% CI 0.0382, 0.0836; P = 1.38E-07). Our results suggest that as the level of eosinophils increases, so does the risk of frailty. No meaningful causal relationship between neutrophils, lymphocytes, monocytes or basophils and FI was found in the MR results (P > 0.05).

CONCLUSIONS

According to this MR study, higher eosinophil counts are related to an increased risk of frailty. To validate these findings and investigate the mechanisms underlying these connections, future studies are warranted.

Unraveling the metabolic underpinnings of frailty using multicohort observational and Mendelian randomization analyses

Identifying metabolic biomarkers of frailty, an age-related state of physiological decline, is important for understanding its metabolic underpinnings and developing preventive strategies. Here, we systematically examined 168 nuclear magnetic resonance-based metabolomic biomarkers and 32 clinical biomarkers for their associations with frailty. In up to 90,573 UK Biobank participants, we identified 59 biomarkers robustly and independently associated with the frailty index (FI). Of these, 34 associations were replicated in the Swedish TwinGene study (n = 11,025) and the Finnish Health 2000 Survey (n = 6073). Using two-sample Mendelian randomization, we showed that the genetically predicted level of glycoprotein acetyls, an inflammatory marker, was statistically significantly associated with an increased FI (β per SD increase = 0.37%, 95% confidence interval: 0.12-0.61). Creatinine and several lipoprotein lipids were also associated with increased FI, yet their effects were mostly driven by kidney and cardiometabolic diseases, respectively. Our findings provide new insights into the causal effects of metabolites on frailty and highlight the role of chronic inflammation underlying frailty development.