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1.
Aging (Albany NY) ; 12(3): 2952-2973, 2020 02 08.
Article in English | MEDLINE | ID: mdl-32039831

ABSTRACT

We conducted a cross-sectional study investigating community-dwelling older population to determine association between immunoscenescence marker, inflammatory cytokines and frailty. Frailty status was classified with 33-item modified frailty index and latent class analysis was applied to explore the latent classes (subtypes) of frailty. In multivariable analysis, higher Tfh2 cells were associated with a higher risk of frailty [1.13(1.03-1.25)] in females, but a lower risk of cognitive and functional frail [0.92(0.86-0.99)] and physiological frail [0.92(0.87-0.98)]. Additionally, a greater risk of multi-frail and physiological frail correlated with low Tfh1 [0.77(0.60-0.99); 0.87(0.79-0.96)] and Tfh17 cells [0.79(0.65-0.96); 0.86(0.78-0.94)], respectively. Higher B cells were associated with decreased frailty/pre-frailty both in females [0.89(0.81-0.98)] and males [0.82(0.71-0.96)], but did not correlate with frailty subtypes. Regarding inflammatory markers, participants in the TGF-ß 2nd quartile showed a decreased risk of pre-frailty/frailty in females [0.39(0.17-0.89)] and psychological frail [0.37(0.16-0.88)], compared with those in the top tertile. Moreover, we found participants in the 2nd tertile for IL-12 levels showed a decreased risk of physiological frail [0.40 (0.17-0.97)]. Our study highlights the importance of Tfh cell subsets and inflammatory markers in frailty in a sex-specific manner, particularly in terms of frailty subtype.


Subject(s)
Frailty/blood , Aged , Aged, 80 and over , Biomarkers/blood , Cross-Sectional Studies , Cytokines/blood , Cytokines/genetics , Cytokines/metabolism , Female , Gene Expression Regulation , Humans , Male , Middle Aged , Sex Factors
2.
Aging (Albany NY) ; 12(2): 1128-1140, 2020 01 16.
Article in English | MEDLINE | ID: mdl-31951595

ABSTRACT

In order to explore frailty subtypes and find their associated risk factors, we conducted cross-sectional surveys of 5,341 seniors aged 60 and over in China using the Frailty Index (FI) scale. We identified four frailty subtypes, namely multi-frail, cognitive and functionally frail, psychologically frail and physiologically frail. Old age and low education level were the common risk factors among the four subtypes. Being widowed, divorced or unmarried was a risk factor for multi-frail, cognitive and functionally frail and psychologically frail, and male sex was a protective factor against cognitive and functionally frail and psychologically frail subtypes. Having a harmonious relationship with family was a protective factor against multi-frail, and fewer visits to the elderly by their children was a risk factor for psychologically frail. Dissatisfaction with their housing was a risk factor for cognitive and functionally frail, psychologically frail and physiologically frail, and a pension being the main source of income was a risk factor for cognitive and functionally frail and psychologically frail. Exercising every day was a protective factor against multi-frail and cognitive and functionally frail, and a lower level of physical activity was a risk factor for all four frailty subtypes. Our findings confirm the heterogeneity of frailty and suggest that different frail elderly individuals need more targeted care interventions.


Subject(s)
Frail Elderly , Frailty , Geriatric Assessment , Aged , Aged, 80 and over , Cross-Sectional Studies , Female , Health Status , Humans , Independent Living , Male , Middle Aged , Odds Ratio , Population Surveillance , Risk Factors
3.
PLoS One ; 8(3): e59421, 2013.
Article in English | MEDLINE | ID: mdl-23527193

ABSTRACT

OBJECTIVE: A meta-analysis was applied to evaluate the associations between tumor necrosis factor-α (TNF-α) -308G>A (rs1800629) polymorphism and type 2 diabetes mellitus (T2DM). METHODS: Hardy-Weinberg equilibrium (HWE) was employed to test genetic equilibrium among the genotypes of the selected literature. Power analysis was performed with the Power and Sample Size Calculation (PS) program. A fixed or random effect model was used on the basis of heterogeneity. Publication bias was quantified and examined with the Begg's funnel plot test and Egger's linear regression test. The meta-analysis was performed with Review Manager 5.1 and Stata 11.0. RESULTS: There were 10 studies including 1425 T2DM patients and 1116 healthy control subjects involved in this meta-analysis. No significant publication bias was found in the studies. The pooled ORs (95% CIs) for TNF-α -308G>A of A vs. G allele and GA+AA vs. GG genotype were 1.63 (1.17-2.25) and 1.47 (1.17-1.85), respectively. CONCLUSION: This meta-analysis result suggested that TNF-α -308G>A polymorphism was strongly associated with T2DM risk, and A allele at this locus might be a susceptibility allele for the development of T2DM in Han Chinese population.


Subject(s)
Asian People/genetics , Diabetes Mellitus, Type 2/genetics , Polymorphism, Single Nucleotide/genetics , Tumor Necrosis Factor-alpha/genetics , Genetic Association Studies , Genotype , Humans , Linear Models , Models, Genetic , Odds Ratio , Publication Bias
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