The brain insulin receptor gene network and associations with frailty index.

OBJECTIVE: To investigate longitudinal associations between variations in the co-expression-based brain insulin receptor polygenic risk score and frailty, as well as change in frailty across follow-up. METHODS: This longitudinal study included 1605 participants from the Helsinki Birth Cohort Study. Biologically informed expression-based polygenic risk scores for the insulin receptor gene network, which measure genetic variation in the function of the insulin receptor, were calculated for the hippocampal (hePRS-IR) and the mesocorticolimbic (mePRS-IR) regions. Frailty was assessed in at baseline in 2001-2004, 2011-2013 and 2017-2018 by applying a deficit accumulation-based frailty index. Analyses were carried out by applying linear mixed models and logistical regression models adjusted for adult socioeconomic status, birthweight, smoking and their interactions with age. RESULTS: The FI levels of women were 1.19%-points (95% CI 0.12-2.26, P = 0.029) higher than in men. Both categorical and continuous hePRS-IR in women were associated with higher FI levels than in men at baseline (P < 0.05). In women with high hePRS-IR, the rate of change was steeper with increasing age compared to those with low or moderate hePRS-IR (P < 0.05). No associations were detected between mePRS-IR and frailty at baseline, nor between mePRS-IR and the increase in mean FI levels per year in either sex (P > 0.43). CONCLUSIONS: Higher variation in the function of the insulin receptor gene network in the hippocampus is associated with increasing frailty in women. This could potentially offer novel targets for future drug development aimed at frailty and ageing.

The impact of frailty and cognitive impairment on quality of life: employment and social context matter.

ABSTRACTBackground:How cognitive impairment and frailty combine to impact on older adults' Quality of Life (QoL) is little studied, but their inter-relationships are important given how often they co-occur. We sought to examine how frailty and cognitive impairment, as well as changes in frailty and cognition, are associated with QoL and how these relationships differ based on employment status and social circumstances. METHODS: Using the Survey of Health, Ageing, and Retirement in Europe data, we employed moderated regression, followed by simple slopes analysis, to examine how the relationships between levels of health (i.e., of frailty and cognition) and QoL varied as a function of sex, age, education, social vulnerability, and employment status. We used the same analysis to test whether the relationships between changes in health (over two years) and QoL varied based on these same moderators. RESULTS: Worse frailty (b = -1.61, p < .001) and cognitive impairment (b = -0.08, p < .05) were each associated with lower QoL. Increase in frailty (b = -2.17, p < .001) and cognitive impairment (b = -0.25, p < .001) were associated with lower QoL. The strength of these relationships varied depending on interactions with age, sex, education, social vulnerability, and employment status. Higher social vulnerability was consistently associated with lower QoL in analyses examining both static health (b = -3.16, p < .001) and change in health (b = -0.66, p < .001). CONCLUSIONS: Many predictors of QoL are modifiable, providing potential targets to improve older adults' QoL. Even so, the relationships between health, cognition, and social circumstances that shape QoL in older adults are complex, highlighting the importance for individualized interventions.

Utilizing multimodal approach to identify candidate pathways and biomarkers and predicting frailty syndrome in individuals from UK Biobank.

Frailty, a prevalent clinical syndrome in aging adults, is characterized by poor health outcomes, represented via a standardized frailty-phenotype (FP), and Frailty Index (FI). While the relevance of the syndrome is gaining awareness, much remains unclear about its underlying biology. Further elucidation of the genetic determinants and possible underlying mechanisms may help improve patients' outcomes allowing healthy aging.Genotype, clinical and demographic data of subjects (aged 60-73 years) from UK Biobank were utilized. FP was defined on Fried's criteria. FI was calculated using electronic-health-records. Genome-wide-association-studies (GWAS) were conducted and polygenic-risk-scores (PRS) were calculated for both FP and FI. Functional analysis provided interpretations of underlying biology. Finally, machine-learning (ML) models were trained using clinical, demographic and PRS towards identifying frail from non-frail individuals.Thirty-one loci were significantly associated with FI accounting for 12% heritability. Seventeen of those were known associations for body-mass-index, coronary diseases, cholesterol-levels, and longevity, while the rest were novel. Significant genes CDKN2B and APOE, previously implicated in aging, were reported to be enriched in lipoprotein-particle-remodeling. Linkage-disequilibrium-regression identified specific regulation in limbic-system, associated with long-term memory and cognitive-function. XGboost was established as the best performing ML model with area-under-curve as 85%, sensitivity and specificity as 0.75 and 0.8, respectively.This study provides novel insights into increased vulnerability and risk stratification of frailty syndrome via a multi-modal approach. The findings suggest frailty as a highly polygenic-trait, enriched in cholesterol-remodeling and metabolism and to be genetically associated with cognitive abilities. ML models utilizing FP and FI + PRS were established that identified frailty-syndrome patients with high accuracy.

Frailty index and risk of cardiovascular diseases: a mendelian randomization study.

Background: Previous epidemiological evidence has suggested that frailty status might be associated with cardiovascular diseases (CVDs). However, the exact causality remains unestablished. In this study, we employed Mendelian randomization and sought to investigate the potential causality in association of frailty index (FI) with cardiovascular outcomes [coronary artery disease (CAD), myocardial infarction (MI), atrial fibrillation (AF), and heart failure (HF)]. Methods: Independent single nucleotide polymorphisms (SNPs) at genome-wide significance for FI were obtained from a recent genome-wide association study (GWAS) meta-analysis of European descent (n=175,226). The association of these SNPs with CVDs was examined in summary statistics from corresponding GWASs of European descent (CAD: 184,305 cases and 60,801 controls; MI: 184,305 cases and 43,676 controls; AF: 1,030,836 cases and 60,620 controls; and HF: 977,323 cases and 47,309 controls). Replication analyses were performed using GWAS datasets from FinnGen. Results: In the meta-analysis of inverse-variance weighted estimates from different data sources, genetically determined higher FI conferred an odds ratio (OR) of 1.46 [95% confidence interval (CI): 1.13 to 1.87; P=0.003] for CAD, 1.62 (95% CI: 1.21 to 2.17, P=0.001) for MI, and 1.46 (95% CI: 1.24 to 1.72; P=4.89×10-6) for HF. However, FI failed to be potentially influential on AF risk (OR, 1.43; 95% CI: 0.93 to 1.66; P=0.107). Several complementary analyses also received broadly concordant results. Conclusions: We have provided genetic evidence of a causal association between FI and the risk of CAD, MI, and HF. Further studies are warranted to clarify whether FI is causally related to AF risk.

A quantile frailty index without dichotomization.

measures of health quantify the aging process of individuals. They should be interpretable, associated with future adverse outcomes, and straightforward to assemble. We use the rank-ordering of risk within a population to construct a quantile frailty index (QFI) that avoids dichotomization, is convenient and interpretable, and is associated with adverse outcomes. We show that the QFI outperforms previous frailty index (FI) measures on cross-sectional laboratory data (NHANES, CSHA, and ELSA). We construct the QFI by ranking the risk of individuals with respect to a reference population. Sex-specific reference populations narrow male-female FI differences as a function of age, and improve predictive performance. With a fixed reference population of 80-85 year olds, our QFI appears similar to earlier FI measures. With an age-matched reference population for each individual, we obtain a QFI that contains very little age information and that has similar predictive performance as other age-controlled FI measures. Adding age as an auxiliary variable leads to significantly better performance. We conclude that age should be controlled for when evaluating the predictive performance of summary measures of health. This is straight-forward to do with the QFI.

Frailty in Relation to the Risk of Alzheimer's Disease, Dementia, and Death in Older Chinese Adults: A Seven-Year Prospective Study.

OBJECTIVES: To explore the relationship of general health decline assessed by frailty and risk of dementia and Alzheimer's disease (AD). DESIGN: A seven-year prospective cohort study. SETTING: Secondary analysis of data from the Beijing Longitudinal Study on Aging. PARTICIPANTS: Urban and rural community-dwelling people aged 60 and older at baseline. MEASUREMENTS: Frailty was quantified using the deficit accumulation-based frailty index (FI), constructed from 40 health deficits at baseline. Dementia was diagnosed by DSM-IIIR. AD and vascular dementia (VaD) were diagnosed by NINCDS-ADRDA and NINDS-AIREN. The relationships between frailty and the risk of dementia, AD and death were evaluated through multivariable models. RESULTS: Of 2788 participants at baseline (1997), 171 (11.1%) reported a history of dementia. In seven years, 351 people developed dementia (13%: 223 AD and 128 other types of dementia) and 813 died (29%). After adjustment for age, sex, education, and baseline cognition, baseline frailty status significantly associated with Alzheimer's disease and dementia and death. For each deficit accumulated, the odds ratio of death increased by 5.7%, and the odds ratio of dementia increased by 2.9% (p < 0.001). CONCLUSION: Frailty was associated with Alzheimer's disease and dementia over a seven years period. Frailty index might facilitate the identification of older adults at high risk of dementia for the application of the most effective, targeted prevention strategies.