Genetics of frailty: A longevity perspective

Frailty and biological age. Which best describes our aging and longevity?

Frailty and Biological Age are two closely related concepts; however, frailty is a multisystem geriatric syndrome that applies to elderly subjects, whereas biological age is a gerontologic way to describe the rate of aging of each individual, which can be used from the beginning of the aging process, in adulthood. If frailty reaches less consensus on the definition, it is a term much more widely used than this of biological age, which shows a clearer definition but is scarcely employed in social and medical fields. In this review, we suggest that this Biological Age is the best to describe how we are aging and determine our longevity, and several examples support our proposal.

Genetic and phenotypic associations of frailty with cardiovascular indicators and behavioral characteristics

INTRODUCTION

Frailty Index (FI) is a common measure of frailty, which has been advocated as a routine clinical test by many guidelines. The genetic and phenotypic relationships of FI with cardiovascular indicators (CIs) and behavioral characteristics (BCs) are unclear, which has hampered ability to monitor FI using easily collected data.

OBJECTIVES

This study is designed to investigate the genetic and phenotypic associations of frailty with CIs and BCs, and further to construct a model to predict FI.

METHOD

Genetic relationships of FI with 288 CIs and 90 BCs were assessed by the cross-trait LD score regression (LDSC) and Mendelian randomization (MR). The phenotypic data of these CIs and BCs were integrated with a machine-learning model to predict FI of individuals in UK-biobank. The relationships of the predicted FI with risks of type 2 diabetes (T2D) and neurodegenerative diseases were tested by the Kaplan-Meier estimator and Cox proportional hazards model.

RESULTS

MR revealed putative causal effects of seven CIs and eight BCs on FI. These CIs and BCs were integrated to establish a model for predicting FI. The predicted FI is significantly correlated with the observed FI (Pearson correlation coefficient = 0.660, P-value = 4.96 × 10-62). The prediction model indicated "usual walking pace" contributes the most to prediction. Patients who were predicted with high FI are in significantly higher risk of T2D (HR = 2.635, P < 2 × 10-16) and neurodegenerative diseases (HR = 2.307, P = 1.62 × 10-3) than other patients.

CONCLUSION

This study supports associations of FI with CIs and BCs from genetic and phenotypic perspectives. The model that is developed by integrating easily collected CIs and BCs data in predicting FI has the potential to monitor disease risk.

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.

The epigenetics of frailty

The conceptual change of frailty, from a physical to a biopsychosocial phenotype, expanded the field of frailty, including social and behavioral domains with critical interaction between different frailty models. Environmental exposures - including physical exercise, psychosocial factors and diet - may play a role in the frailty pathophysiology. Complex underlying mechanisms involve the progressive interactions of genetics with epigenetics and of multimorbidity with environmental factors. Here we review the literature on possible mechanisms explaining the association between epigenetic hallmarks (i.e., global DNA methylation, DNA methylation age acceleration and microRNAs) and frailty, considered as biomarkers of aging. Frailty could be considered the result of environmental epigenetic factors on biological aging, caused by conflicting DNA methylation age and chronological age.

To Be Frail or Not to Be Frail: This Is the Question-A Critical Narrative Review of Frailty

Many factors have contributed to rendering frailty an emerging, relevant, and very popular concept. First, many pandemics that have affected humanity in history, including COVID-19, most recently, have had more severe effects on frail people compared to non-frail ones. Second, the increase in human life expectancy observed in many developed countries, including Italy has led to a rise in the percentage of the older population that is more likely to be frail, which is why frailty is much a more common concern among geriatricians compared to other the various health-care professionals. Third, the stratification of people according to the occurrence and the degree of frailty allows healthcare decision makers to adequately plan for the allocation of available human professional and economic resources. Since frailty is considered to be fully preventable, there are relevant consequences in terms of potential benefits both in terms of the clinical outcome and healthcare costs. Frailty is becoming a popular, pervasive, and almost omnipresent concept in many different contexts, including clinical medicine, physical health, lifestyle behavior, mental health, health policy, and socio-economic planning sciences. The emergence of the new "science of frailty" has been recently acknowledged. However, there is still debate on the exact definition of frailty, the pathogenic mechanisms involved, the most appropriate method to assess frailty, and consequently, who should be considered frail. This narrative review aims to analyze frailty from many different aspects and points of view, with a special focus on the proposed pathogenic mechanisms, the various factors that have been considered in the assessment of frailty, and the emerging role of biomarkers in the early recognition of frailty, particularly on the role of mitochondria. According to the extensive literature on this topic, it is clear that frailty is a very complex syndrome, involving many different domains and affecting multiple physiological systems. Therefore, its management should be directed towards a comprehensive and multifaceted holistic approach and a personalized intervention strategy to slow down its progression or even to completely reverse the course of this condition.

Multivariate genome-wide analysis of aging-related traits identifies novel loci and new drug targets for healthy aging

The concept of aging is complex, including many related phenotypes such as healthspan, lifespan, extreme longevity, frailty and epigenetic aging, suggesting shared biological underpinnings; however, aging-related endpoints have been primarily assessed individually. Using data from these traits and multivariate genome-wide association study methods, we modeled their underlying genetic factor ('mvAge'). mvAge (effective n = ~1.9 million participants of European ancestry) identified 52 independent variants in 38 genomic loci. Twenty variants were novel (not reported in input genome-wide association studies). Transcriptomic imputation identified age-relevant genes, including VEGFA and PHB1. Drug-target Mendelian randomization with metformin target genes showed a beneficial impact on mvAge (P value = 8.41 × 10-5). Similarly, genetically proxied thiazolidinediones (P value = 3.50 × 10-10), proprotein convertase subtilisin/kexin 9 inhibition (P value = 1.62 × 10-6), angiopoietin-like protein 4, beta blockers and calcium channel blockers also had beneficial Mendelian randomization estimates. Extending the drug-target Mendelian randomization framework to 3,947 protein-coding genes prioritized 122 targets. Together, these findings will inform future studies aimed at improving healthy aging.

A genome-wide association study of frailty identifies significant genetic correlation with neuropsychiatric, cardiovascular, and inflammation pathways

Frailty is an aging-related clinical phenotype defined as a state in which there is an increase in a person's vulnerability for dependency and/or mortality when exposed to a stressor. While underlying mechanisms leading to the occurrence of frailty are complex, the importance of genetic factors has not been fully investigated. We conducted a large-scale genome-wide association study (GWAS) of frailty, as defined by the five criteria (weight loss, exhaustion, physical activity, walking speed, and grip strength) captured in the Fried Frailty Score (FFS), in 386,565 European descent participants enrolled in the UK Biobank (mean age 57 [SD 8] years, 208,481 [54%] females). We identified 37 independent, novel loci associated with the FFS (p < 5 × 10-8), including seven loci without prior described associations with other traits. The variants associated with FFS were significantly enriched in brain tissues as well as aging-related pathways. Our post-GWAS bioinformatic analyses revealed significant genetic correlations between FFS and cardiovascular-, neurological-, and inflammation-related diseases/traits, and subsequent Mendelian Randomization analyses identified causal associations with chronic pain, obesity, diabetes, education-related traits, joint disorders, and depressive/neurological, metabolic, and respiratory diseases. The GWAS signals were replicated in the Health and Retirement Study (HRS, n = 9,720, mean age 73 [SD 7], 5,582 [57%] females), where the polygenic risk score built from UKB GWAS was significantly associated with the FFS in HRS individuals (OR per SD of the score 1.27, 95% CI 1.22-1.31, p = 1.3 × 10-11). These results provide new insight into the biology of frailty by comprehensively evaluating its genetic architecture.

Leisure Activities, Genetic Risk, and Frailty: Evidence from the Chinese Adults Aged 80 Years or Older

INTRODUCTION

About half of adults aged ≥80 years suffer from frailty. Exercise is considered effective in preventing frailty but may be inapplicable to adults aged ≥80 years due to physical limitations. As an alternative, we aimed to explore the association of leisure activities with frailty and identify potential interaction with established polygenic risk score (PRS) among adults aged ≥80 years.

METHODS

Analyses were performed in a prospective cohort study of 7,471 community-living older adults aged ≥80 years who were recruited between 2002 and 2014 from 23 provinces in China. Leisure activity was assessed using a seven-question leisure activity index and frailty was defined as a frailty index ≥0.25 using a validated 39-item health-related scale. The PRS was constructed using 59 single-nucleotide polymorphisms associated with frailty in a subsample of 2,541 older adults. Cox proportional hazards models were used to explore the associations of leisure activities, PRS with frailty.

RESULTS

The mean age of participants was 89.4 ± 6.6 years (range: 80-116). In total, 2,930 cases of frailty were identified during 42,216 person-years of follow-up. Each 1 unit increase in the leisure activity index was associated with 12% lower risk of frailty (hazard ratio: 0.88 [95% confidence interval, 0.85-0.91]). Participants with high genetic risk (PRS >2.47 × 10-4) suffered from 26% higher risk of frailty. Interaction between leisure activity and genetic risk was not observed.

CONCLUSION

Evidence is presented for the independent association of leisure activities and genetic risk with frailty. Engagement in leisure activities is suggested to be associated with lower risk of frailty across all levels of genetic risk among adults aged ≥80 years.

Cross-cultural adaptation and validation of the geriatric 8 screening tool in Chinese hospitalized older adults with cancer

OBJECTIVES

To translate, cross-culturally adapt, and validate the Geriatric 8 (G8) questionnaire in Chinese hospitalized older adults with cancer.

METHODS

The Chinese version of the G8 (C-G8) was produced following Brislin's guidelines. The psychometric properties of the C-G8 were evaluated among 296 eligible patients.

RESULTS

The content validity index of the C-G8 was 0.8∼1 at the item level and 0.975 at the scale level. The C-G8 identified more frail individuals among these older (>75 years) participants compared to their younger (65∼75 years) counterparts (frailty prevalence: 87.1% vs. 70.9%, P=0.010). The convergent validity of the C-G8 was tested by correlating it with the FRAIL scale (r=-0.592, P<0.001). The C-G8 had a lower internal consistency (Cronbach's α coefficient=0.501) but higher test-retest reliability and inter-rater reliability (intraclass correlation coefficient=0.913 and 0.993, respectively, P<0.001).

CONCLUSIONS

The C-G8 questionnaire presented acceptable validity and reliability and could be used in Chinese hospitalized older adults with cancer.

Cognitive frailty and 5-year adverse health-related outcomes for the Malaysian elders longitudinal research (MELoR) study

PURPOSE

To determine the risk of adverse outcomes among prefrail and frail individuals with and without cognitive impairment as well as those with isolated cognitive impairment compared to robust individuals without cognitive impairment.

METHODS

Data from the Malaysian elders longitudinal research (MELoR) study were utilised. Baseline data were obtained from home-based computer-assisted interviews and hospital-based health-checks from 2013 to 2015. Protocol of MELoR study has been described in previous study (Lim in PLoS One 12(3):e0173466, 2017). Follow-up interviews were conducted in 2019 during which data on the adverse outcomes of falls, sarcopenia, hospitalization, and memory worsening were obtained. Sarcopenia at follow-up was determined using the strength, assistance with walking, rising from a chair, climbing stairs, and falls (SARC-F) questionnaire.

RESULTS

Follow-up data was available for 776 participants, mean (SD) age 68.1 (7.1) years and 57.1% women. At baseline, 37.1% were robust, 12.8% had isolated cognitive impairment, 24.1% were prefrail, 1.0% were frail, 20.2% were prefrail with cognitive impairment, and 4.8% had CF. Differences in age, ethnicity, quality of life, psychological status, function and comorbidities were observed across groups. The association between CF with hospitalisation and falls compared to robust individuals was attenuated by ethnic differences. Pre-frail individuals were at increased risk of memory worsening compared robust individuals [aOR(95%CI) = 1.69 (1.09-2.60)]. Frail [7.70 (1.55-38.20)], prefrail with cognitive impairment [3.35 (1.76-6.39)] and CF [6.15 (2.35-16.11)] were significantly more likely to be sarcopenic at 5-year follow-up compared to the robust group.

CONCLUSIONS

Cognitive frailty was an independently predictor of sarcopenia at 5-year follow-up. The relationship between CF with falls and hospitalization, however, appeared to be accounted for by ethnic disparities. Future studies should seek to unravel the potential genetic and lifestyle variations between ethnic groups to identify potential interventions to reduce the adverse outcomes associated with CF.

Frailty, sarcopenia and diabetic kidney disease: where do we stand?

The aim of this narrative non-systematic review was to investigate the potential interplay among frailty syndrome, sarcopenia and diabetic kidney disease (DKD) in type 2 diabetes mellitus (T2DM) patients. Data derived from a limited number of studies underline that DKD is a significant risk factor for frailty. On the other hand, frailty syndrome poses a higher risk for end-stage renal disease (ESRD) in subjects with DKD. In addition, frailty seems to affect the cognitive function and social life of DKD individuals, whilst as DKD deteriorates, there is a higher prevalence of sarcopenia which is a fundamental frailty factor. As a result, it is shown that a bidirectional relation is established between these entities, as diabetes mellitus (DM) affects the components of frailty and sarcopenia and vice versa. This vicious cycle is created through multiple pathophysiologic mechanisms, including the anabolic role of insulin, low-grade inflammation, cytokines and endothelial function, prompting further investigation in this area. Specific nutritional and exercise interventions are imperative to be established in order to ameliorate potential adverse outcomes, concerning these entities.

Biomarkers of Frailty: miRNAs as Common Signatures of Impairment in Cognitive and Physical Domains

The past years have seen an increasing concern about frailty, owing to the growing number of elderly people and the major impact of this syndrome on health and social care. The identification of frail people passes through the use of different tests and biomarkers, whose concerted analysis helps to stratify the populations of patients according to their risk profile. However, their efficiency in prognosis and their capability to reflect the multisystemic impairment of frailty is discussed. Recent works propose the use of miRNAs as biological hallmarks of physiological impairment in different organismal districts. Changes in miRNAs expression have been described in biological processes associated with phenotypic outcomes of frailty, opening intriguing possibilities for their use as biomarkers of fragility. Here, with the aim of finding reliable biomarkers of frailty, while considering its complex nature, we revised the current literature on the field, for uncovering miRNAs shared across physical and cognitive frailty domains. By applying in silico analyses, we retrieved the top-ranked shared miRNAs and their targets, finally prioritizing the most significant ones. From this analysis, ten miRNAs emerged which converge into two main biological processes: inflammation and energy homeostasis. Such markers, if validated, may offer promising capabilities for early diagnosis of frailty in the elderly population.

Can a biomarker for oxidative stress and antioxidant reserves identify frailty in geriatric trauma patients?

OBJECTIVE

Frailty is a state of systematic physiologic decline and reduced ability to recover from illness. There are no rapid quantitative biological measures to assess frailty. The study objective was to determine whether oxidation-reduction potential (ORP) is correlated with frailty score.

METHODS

This prospective, observational cohort study was performed using plasma samples of geriatric trauma patients (≥65 years) admitted to a level I trauma center. Frailty was measured with the Canadian Study of Health and Aging (CSHA) Clinical Frailty Scale (7-point scale; 1 = robust health and 7 = severely frail). Plasma ORP was determined using the RedoxSYS™ system to measure static ORP (aggregate measure of oxidative stress) and capacity ORP (antioxidant reserves; log transformed). Spearman rank correlation (presented as r_s) and ordinal logistic regression (presented as adjusted odds ratios, AOR) were used to examine the unadjusted and adjusted relationship between frailty score and ORP values.

RESULTS

There were 93 geriatric trauma patients in our study. The majority (86%) had frailty scores 1-5, 11% were moderately frail and 3% were severely frail. There was a u-shaped relationship between ORP and frailty scale that became monotonic for scores 1-5. Each increase in frailty score demonstrated significant decreases in antioxidant reserves (log cORP r_s = -0.26, p = 0.02) and nonsignificant increases in oxidative stress (sORP r_s = 0.17, p = 0.15). After adjustment, variables significantly associated with frailty included log cORP (e.g., fewer antioxidant reserves, AOR: 0.70), age (AOR: 1.82), injury severity score (AOR: 0.50), admission lactate ≥2.5 mMol (AOR: 4.31), and alcohol use (AOR: 0.34).

CONCLUSIONS

The amount of antioxidant reserves (cORP) appears to be a quantitative marker to differentiate the degree of frailty ranging from robust health to mild frailty in geriatric trauma patients. We propose that direct quantification of frailty by way of a biomarker for oxidative reserves could have application in emergent trauma situations.

The degree of frailty as a translational measure of health in aging

Frailty is a multiply determined, age-related state of increased risk for adverse health outcomes. We review how the degree of frailty conditions the development of late-life diseases and modifies their expression. The risks for frailty range from subcellular damage to social determinants. These risks are often synergistic-circumstances that favor damage also make repair less likely. We explore how age-related damage and decline in repair result in cellular and molecular deficits that scale up to tissue, organ and system levels, where they are jointly expressed as frailty. The degree of frailty can help to explain the distinction between carrying damage and expressing its usual clinical manifestations. Studying people-and animals-who live with frailty, including them in clinical trials and measuring the impact of the degree of frailty are ways to better understand the diseases of old age and to establish best practices for the care of older adults.

Trajectories of frailty in aging: Prospective cohort study

Background

Emerging evidence suggests that there is significant variability in the progression of frailty in aging. We aimed to identify latent subpopulations of frailty trajectories, and examine their clinical and biological correlates.

Methods

We characterized frailty using a 41-item cumulative deficit score at baseline and annual visits up to 12 years in 681 older adults (55% women, mean age 74·6 years). Clinical risk profile and walking while talking performance as a clinical marker of trajectories were examined. Mortality risk associated with trajectories was evaluated using Cox regression adjusted for established survival predictors, and reported as hazard ratios (HR). Proteome-wide analysis was done.

Findings

Latent class modeling identified 4 distinct frailty trajectories: relatively stable (34·4%) as well as mild (36·1%), moderate (24·1%) and severely frail (5·4%). Four distinct classes of frailty trajectories were also shown in an independent sample of 515 older adults (60% women, 68% White, 26% Black). The stable group took a median of 31 months to accumulate one additional deficit compared to 20 months in the severely frail group. The worst trajectories were associated with modifiable risk factors such as low education, living alone, obesity, and physical inactivity as well as slower walking while talking speed. In the pooled sample, mild (HR 2·33, 95% CI 1·30–4·18), moderate (HR 2·49, 95% CI 1·33–4·66), and severely frail trajectories (HR 5·28, 95% CI 2·68–10·41) had higher mortality compared to the stable group. Proteomic analysis showed 11 proteins in lipid metabolism and growth factor pathways associated with frailty trajectories.

Conclusion

Frailty shows both stable and accelerated patterns in aging, which can be distinguished clinically and biologically.

Frailty assessment and postoperative complications in urologic oncology operations

Major urologic oncology procedures such as radical cystectomy (RC), radical prostatectomy (RP), radical nephroureterectomy (RNU) and radical or partial nephrectomy are the gold standard operations for the treatment of urological malignancies not suitable to be dealt with using minimal invasive procedures such as transurethral resection or other conservative approaches. However, these surgical procedures carry significant risk of complications, especially in elderly and frail patients. The purpose of this review is to highlight the use of a wide variety of preoperative frailty and health status indexes and calculators. Recent data from large population based studies confirm that these calculators can assist physicians and urologists to predict the postoperative morbidity of patients undergoing major operations. Moreover, these frailty calculators can help urologists choose the most suitable and safe treatment for every individual patient. However, the absence of widely accepted specific urologic oncology calculators to predict the association between frailty and postoperative complications emphasizes the necessity for the use of a combination of calculators.