Circulating mitokines GDF-15 and FGF21 are associated with frailty, sarcopenia, and malnutrition in older adults: Evidence from the FRASNET study

Description

Rationale: To identify circulating biomarkers of fraily. Participants were eligible if they were ≥65 years old, able to walk >500 m without assistance, and had a life expectancy >6 months. Exclusion criteria included severe cognitive impairment (Mini-Mental State Examination [MMSE] <18), inability to provide informed consent, or severe health conditions such as uncontrolled hypertension, recent fractures of the upper or lower extremities, or myocardial infarction within the previous year. For this analysis, individuals recruited in nursing homes and those with missing data required to compute frailty or body composition were excluded. Data were collected at baseline (2017) and follow-up (2024). Frailty was assessed using three instruments: the Frailty Index (FI), the modified Frailty Phenotype (FP), and the Clinical Frailty Scale (CFS). Nutritional status was evaluated with the Mini Nutritional Assessment–Short Form (MNA-SF) and categorized as malnourished (≤7), at risk (8–11), or well-nourished (12–14). Sarcopenia was screened using the SARC-F questionnaire and confirmed according to EWGSOP2 criteria. Muscle strength was assessed using the SPPB chair-stand test (>15 s indicating reduced strength). Muscle mass was measured by bioelectrical impedance analysis (BIA), with cut-offs <32.9 % in men and <23.9 % in women. Sarcopenic obesity was defined according to ESPEN/EASO criteria as the coexistence of reduced muscle strength, low muscle mass, and excess fat mass (≥30 % in men and ≥42 % in women). Physical activity was assessed with the Physical Activity Scale for the Elderly (PASE; <76 indicating low activity). Cognitive function was measured using the MMSE (≤24 indicating impairment), and depressive symptoms using the Geriatric Depression Scale (GDS-15). Functional status was evaluated through Activities of Daily Living (ADL) and Instrumental ADL (IADL), and fall risk using the Tinetti scale. Biomarker analyses were performed in plasma samples from 52 of 228 participants due to assay costs and sample availability. Participants were randomly selected among those reassessed at follow-up and were representative of the overall cohort. Blood samples were collected in EDTA tubes from non-fasting subjects, processed within 24 h, aliquoted, and stored at −80 °C. Biomarker concentrations were measured using the ELLA™ automated immunoassay system (Bio-Techne, USA). Continuous variables were reported as mean ± SD or median (IQR), and categorical variables as frequencies (%). Baseline and follow-up comparisons used paired t-tests or Wilcoxon tests. Associations between biomarkers and clinical outcomes were examined using regression models adjusted for age and sex. GDF-15 and FGF-21 concentrations were log-transformed. ROC analyses evaluated the ability of baseline biomarkers to discriminate adverse outcomes at follow-up. Optimal thresholds were determined using the Youden index. Analyses were performed using IBM SPSS Statistics version 25.

Steps to reproduce

Participants were eligible if they were ≥65 years old, able to walk >500 m without assistance, and had a life expectancy >6 months. Exclusion criteria included severe cognitive impairment (Mini-Mental State Examination [MMSE] <18), inability to provide informed consent, or severe health conditions such as uncontrolled hypertension, recent fractures of the upper or lower extremities, or myocardial infarction within the previous year. For this analysis, individuals recruited in nursing homes and those with missing data required to compute frailty or body composition were excluded. Data were collected at baseline (2017) and follow-up (2024). Frailty was assessed using three instruments: the Frailty Index (FI), the modified Frailty Phenotype (FP), and the Clinical Frailty Scale (CFS). Nutritional status was evaluated with the Mini Nutritional Assessment–Short Form (MNA-SF) and categorized as malnourished (≤7), at risk (8–11), or well-nourished (12–14). Sarcopenia was screened using the SARC-F questionnaire and confirmed according to EWGSOP2 criteria. Muscle strength was assessed using the SPPB chair-stand test (>15 s indicating reduced strength). Muscle mass was measured by bioelectrical impedance analysis (BIA), with cut-offs <32.9 % in men and <23.9 % in women. Sarcopenic obesity was defined according to ESPEN/EASO criteria as the coexistence of reduced muscle strength, low muscle mass, and excess fat mass (≥30 % in men and ≥42 % in women). Physical activity was assessed with the Physical Activity Scale for the Elderly (PASE; <76 indicating low activity). Cognitive function was measured using the MMSE (≤24 indicating impairment), and depressive symptoms using the Geriatric Depression Scale (GDS-15). Functional status was evaluated through Activities of Daily Living (ADL) and Instrumental ADL (IADL), and fall risk using the Tinetti scale. Biomarker analyses were performed in plasma samples from 52 of 228 participants due to assay costs and sample availability. Participants were randomly selected among those reassessed at follow-up and were representative of the overall cohort. Blood samples were collected in EDTA tubes from non-fasting subjects, processed within 24 h, aliquoted, and stored at −80 °C. Biomarker concentrations were measured using the ELLA™ automated immunoassay system (Bio-Techne, USA). Continuous variables were reported as mean ± SD or median (IQR), and categorical variables as frequencies (%). Baseline and follow-up comparisons used paired t-tests or Wilcoxon tests. Associations between biomarkers and clinical outcomes were examined using regression models adjusted for age and sex. GDF-15 and FGF-21 concentrations were log-transformed. ROC analyses evaluated the ability of baseline biomarkers to discriminate adverse outcomes at follow-up. Optimal thresholds were determined using the Youden index. Analyses were performed using IBM SPSS Statistics version 25.

Institutions

• IRCCS Ospedale San Raffaele

  Lombardy, Milan

Categories

Funders

• European Union - Next Generation EU - NRRP M6C2 - Investment 2.1 Enhancement and strengthening of biomedical research in the NHS.

  Grant ID: PNRR-MAD-2022-12376672, CUP C43C22001310007

Related Links

Licence