Objective:To investigate the correlation of mitochondrial respiration function and oxidative phosphorylation of peripheral blood mononuclear cells(PBMCs)with grip strength and muscle mass in the elderly, and to identify potential biomarkers for the diagnosis of sarcopenia.Methods:A total of 65 patients admitted to our hospital from June 2019 to August 2020 were enrolled in this study.PBMCs were extracted from subjects.Mitochondrial oxidative respiration function was assessed via the Seahorse XF24 analyzer.Grip strength was measured using a hydraulic dynamometer, and appendicular skeletal muscle mass(ASM)was estimated by dual-energy X-ray absorptiometry(DXA). Multivariate analysis was conducted by using partial correlation analysis and multiple linear regression, in order to evaluate the correlation of mitochondrial oxidative respiration function with grip strength and ASM.Results:After adjustment for gender and body mass index(BMI), partial correlation analysis showed that grip strength and ASM had a negative correlation with age( r=-0.537 and -0.390, both P<0.001); and basal respiration, maximal respiration, ATP production and spare respiratory capacity of mitochondria in PBMCs were negatively correlated with age( r=-0.558, -0.614, -0.526 and -0.582, all P<0.001), whereas grip strength and ASM were positively correlated with basal respiration, maximal respiration, ATP production, spare respiratory capacity and proton leak of mitochondria in PBMCs(grip strength: r=0.414, 0.451, 0.362, 0.420 and 0.425, P=0.002, 0.001, 0.008, 0.002 and 0.002; ASM: r=0.319, 0.368, 0.299, 0.352 and 0.279, P=0.019, 0.006, 0.028, 0.009 and 0.041). Multiple linear regression analysis showed that grip strength and ASM were positively correlated with basal respiration, maximal respiration, ATP production, spare respiratory capacity and proton leak of mitochondria in PBMCs(grip: β=0.503, 0.548, 0.452, 0.519 and 0.532, t=3.248, 3.604, 2.774, 3.301 and 3.350, P=0.002, 0.001, 0.008, 0.002 and 0.002; ASM: β=0.302, 0.355, 0.289, 0.346 and 0.271, t=2.427, 2.856, 2.263, 2.716 and 2.091, P=0.019, 0.006, 0.028, 0.009 and 0.041). Age was negatively correlated with basal respiration, maximal respiration, ATP production and spare respiratory capacity of mitochondria in PBMCs( β=-0.581, -0.654, -0.558 and -0.640, t=-4.285, -5.157, -3.938 and -4.863, all P<0.001). Multiple linear regression analysis showed that ASM and grip strength had no significant correlation with basal respiration, maximal respiration, ATP production, spare respiratory capacity or proton leak of mitochondria in PBMCs. Conclusions:Age-related mitochondrial oxidative respiration in PBMCs can reflect changes in muscle strength and muscle mass and, combined with grip strength and ASM, may be considered as a biomarker for the evaluation of sarcopenia in the elderly.

Objective:To investigate the correlation between depression risk and the test time for dual-task timed up-and-go(TUG)test in the elderly.Methods:A total of 193 elderly volunteers aged 60 years and over who lived in the Nanjing community of Jiangsu Province were recruited.The Geriatric Depression Scale(GDS)was used to screen for geriatric depression.The single-task TUG(TUG-single), TUG with additional operational tasks(TUG-manual)and TUG with additional cognitive tasks(TUG-cognitive)were tested in all subjects.The differences in test times taken to complete TUG-single, TUG-manual and TUG-cognitive tests were analyzed by ANOVA.The correlation of GDS scores with test time for TUG-single, TUG-manual, TUG-cognitive was analyzed by using Pearson's correlation.Results:The average test times for TUG-cognitive and TUG-manual tests were longer than that for TUG-single test( P<0.0001). The higher the GDS score, the longer the TUG-single test time, with a significantly positive correlation between GDS and the test time for TUG-single( r=0.2261, P=0.0016). Similarly, GDS score showed significantly positive correlations with the test time for TUG-manual( r=0.2359, P=0.0010)and the TUG-cognitive test time( r=0.1946, P=0.0067). Conclusions:The increase of depression risk is significantly and positively correlated with the prolongation of the TUG test time in the elderly.The TUG test can be used to assess the functional mobility in elderly patients with depression.

Objective:To evaluate insulin sensitivity(IS)and pancreatic β-cell secretion function in the elderly, analyze the influencing factors, and compare these parameters with those observed in adults.Methods:A total of 301 participants were selected from the health examination population at the Geriatrics Endocrinology Department of Jiangsu Provincial People's Hospital, all of whom had no history of diabetes, between December 2018 and June 2021.Participants were categorized into elderly and adult groups based on age.Personal and medical histories were recorded, and various measurements, including height, weight, waist circumference, hip circumference, blood lipids, and nutritional metabolic indicators, were obtained.Body composition was assessed using dual-emission X-ray absorptiometry(DXA).The oral minimal model(OMM)method was utilized to derive the insulin sensitivity index(ISI), dynamic insulin secretion(Φd), static insulin secretion(Φs), total insulin secretion(Φt), and disposition index(DI).Participants were grouped according to the results of oral glucose tolerance tests.Finally, the factors influencing IS and pancreatic β-cell function were analyzed in both elderly and adult populations, as well as to identify any differences between the two groups.Results:Following adjustments for gender and body mass index(BMI), partial correlation analysis indicated a decrease in Φd, DI-Φd, and DI-Φt with advancing age( r=-0.219, -0.210, -0.187; P=0.005, 0.015, 0.017).In contrast, ISI, Φs, Φt, and DI-Φs showed no significant correlation with age.Although ISI levels were comparable between the elderly and adult groups, individuals newly diagnosed with diabetes in the elderly cohort exhibited higher DI-Φd, DI-Φs, and DI-Φt compared to those in the adult group after ISI correction.When incorporating age, high-density lipoprotein cholesterol(HDL-C), total muscle mass, the android to gynoid ratio(A/G), and fat mass index(FMI)into a binary Logistic regression model, the findings underscored FMI as a common risk factor for both elderly and adult cohorts concerning the ISI( OR=2.324, 1.773; P=0.032, 0.005).The A/G ratio was identified as a risk factor for DI-Φd in both age groups( OR=69 252.464, 407.653; P=0.012, 0.001).Furthermore, HDL-C was recognized as a protective factor for ISI( OR=0.024, P=0.012)in the elderly, while advancing age( OR=1.454, P=0.039)was found to be a risk factor for DI-Φs in this demographic.Total muscle mass and the A/G ratio were also acknowledged as risk factors for ISI( OR=1.054, 15.725; P=0.021, 0.026), with FMI serving as a risk factor for DI-Φs in the adult cohort( OR=1.826, P=0.035). Conclusions:The secretion function of pancreatic β-cells declines with age, whereas ISI remains unchanged.The factors affecting ISI, DI-Φd, and DI-Φs in elderly and adult populations show notable differences.This indicates that implementing targeted lifestyle interventions for distinct age groups may be more effective in preserving both ISI and pancreatic β-cell function.

Objective:To investigate the correlation of peripheral blood relative mitochondrial DNA copy number(mtDNAcn)with intrinsic capacity and body composition, and to identify potential biomarkers for healthy aging.Methods:Clinical data of 416 patients admitted to our hospital from September 2019 to June 2021 were consecutively collected.MtDNA was extracted from peripheral blood of these subjects, and mtDNAcn was determined by a real-time fluoresence quantitative reverse transcription-polymerase chain reaction(qRT-PCR). Intrinsic capacity assessment included 5 aspects that were exercise[Morse Fall Scale(MFS), Physiological Frailty Phenotype(PFP), Sarcopenia Questionnaire(SARC-CALF), Short Physical Performance Battery(SPPB), Time Up and Go Test(TUG)]; vitality[Mini Nutritional Assessment(MNA), Multidimensional Prognostic Index(MPI)]; cognition[Mini-Mental State Examination(MMSE)scale]; psychology[Geriatric Depression Scale(GDS), Self-rating Anxiety Scale(SAS)]; sensory capacities[Cumulative Illness Rating Scale-the Comorbidity Index(CIRS-CI)]. To assess body composition, dual-energy X-ray absorptiometry was used to measure body fat, including trunk fat, total body fat, fat in the abdominal region, fat in the buttock region, and then to calculate fat index(FMI)and limb skeletal muscle mass index(ASMI).Results:Spearman correlation analysis showed that mtDNAcn had a negatively correlation with age( r=-0.176, P<0.05). After adjustment for gender and body mass index, partial correlation analysis showed mtDNAcn were still negatively correlated with age( r=-0.144, P<0.05). Furthermore, mtDNAcn was significantly correlated with 4 m gait speed, the scores of SARC-CalF, MFS, MNA, MMSE, MPI and its sub-scale's Activities of Daily Living(ADL)and Short Portable Mental Status Questionnaire(SPMSQ)( r=0.171, -0.207, -0.163, 0.221, 0.184, -0.210, 0.241, -0.269, all P<0.05). After adjustment for age, gender and body mass index, partial correlation analysis showed mtDNAcn still had a significant correlation with gait speed, the scores of MFS, MNA, MPI and SPMSQ( r=0.170, -0.170, 0.148, -0.242, -0.188, all P<0.05). In addition, the Spearman correlation analysis showed that mtDNAcn was positively correlated with FMI, trunk fat, total body fat, abdominal fat and fat in the buttock region( r=0.168, 0.143, 0.175, 0.116, 0.199, all P<0.05). However, after adjustment for age and gender, mtDNAcn was only correlated with FMI, total body fat, fat in the buttock region( r=0.126, 0.131, 0.127, all P<0.05). On the other hand, multiple linear regression analysis showed that mtDNAcn was significantly correlated with age, gait speed, FMI, total body fat, fat in the buttock region, the scores of MFS, PFP, MNA and MPI( β=-0.191, 0.156, 0.126, 0.131, 0.125, -0.119, -0.145, 0.151, -0.171, all P<0.05). Conclusions:MtDNAcn is correlated with physical function, frailty, nutrition, falling, cognition and body composition, and may be considered as a biomarker for the evaluation of the locomotion and vitality of human intrinsic capacity.

Objective:To analyze the factors influencing sarcopenia in older patients with chronic diseases, both in community settings and hospitals, and to develop a risk prediction model for sarcopenia.Methods:We recruited a total of 403 older adults with chronic diseases, consisting of 251 individuals from a community in Nanjing, Jiangsu Province, and 152 hospitalized patients from the Department of Geriatrics at Jiangsu Province Hospital.Assessments were conducted using a general information questionnaire, serum sample collection, the mini nutritional assessment-short form(MNA-SF), the mini-mental state examination(MMSE), and the geriatric depression scale(GDS).Binary Logistic regression analysis was employed to identify influencing factors and to construct a risk prediction model for sarcopenia, which was illustrated using a nomogram.The model's discrimination was evaluated using the receiver operating characteristic(ROC)curve and the area under the curve(AUC).Results:The prevalence of sarcopenia among community-dwelling older adults with chronic conditions was found to be 4.0%(10/251).In contrast, the prevalence in hospitalized older adults with chronic conditions was significantly higher at 36.2%(55/152).Binary Logistic regression analysis identified several independent risk factors for sarcopenia, including hospitalization( OR=14.391、95% CI: 6.284-32.955、 P<0.001), male gender( OR=3.321、95% CI: 1.587-6.950、 P=0.001), lower low-density lipoprotein cholesterol(LDL-C)levels( OR=2.542、95% CI: 1.160-5.572、 P=0.020), cognitive impairment( OR=2.654、95% CI: 1.269-5.550、 P=0.010), and the use of four or more types of medication( OR=2.328、95% CI: 1.952-5.689、 P=0.044).Based on these risk factors, a nomogram was developed as a predictive model for assessing sarcopenia risk.The AUC for this prediction model was 0.860(95% CI: 0.815-0.912), indicating a sensitivity of 0.831 and a specificity of 0.760. Conclusions:The incidence of sarcopenia is notably high among older patients with chronic diseases.A risk prediction model that incorporates factors such as hospitalization history, gender, LDL-C levels, cognitive function, and types of medication demonstrates significant potential for predicting sarcopenia.This model serves as a valuable foundation for the early screening and intervention of sarcopenia.