期刊
BMC GERIATRICS
卷 22, 期 1, 页码 -出版社
BMC
DOI: 10.1186/s12877-022-03720-1
关键词
Phenotypic aging marker; Phenotypic age acceleration; HIV/AIDS; Frailty; Aging; Comorbidities; Thailand
资金
- Thai government through the National Research Council of Thailand
- Chulalongkorn University
- Office of the Higher Education Commission (Health Cluster) [GRB_APS_04_16_30_03, GRB_APS_12_58_30_09, GRB_APS_04_59_30_03]
- Ratchadapiseksompotch Fund, Faculty of Medicine, Chulalongkorn University [RA61/008]
- National Research University (NRU), Health Cluster [NRU59-014-HR]
In this study, predictors of novel aging markers PhenoAge and PAA in people living with HIV were evaluated, with male sex, smoking, diabetes, hypertension, frailty, and high IL-6 levels independently associated with higher PAA. The PhenoAge marker showed better discrimination for frailty compared to chronological age alone, indicating its potential usefulness in identifying high-risk PLWH within a similar chronological age group.
Background: Aging characteristics in people living with HIV (PLWH) are heterogeneous, and the identification of risk factors associated with aging-related comorbidities such as neurocognitive impairment (NCI) and frailty is important. We evaluated predictors of novel aging markers, phenotypic age (PhenoAge) and phenotypic age acceleration (PAA) and their association with comorbidities, frailty, and NCI. Methods: In a cohort of PLWH and age- and sex-matched HIV-negative controls, we calculated PhenoAge using chronological age and 9 biomarkers from complete blood counts, inflammatory, metabolic-, liver- and kidney-related parameters. PAA was calculated as the difference between chronological age and PhenoAge. Multivariate logistic regression models were used to identify the factors associated with higher (> median) PAA. Area under the receiver operating characteristics curve (AUROC) was used to assess model discrimination for frailty. Results: Among 333 PLWH and 102 HIV-negative controls (38% female), the median phenotypic age (49.4 vs. 48.5 years, p = 0.54) and PAA (- 6.7 vs. -7.5, p = 0.24) was slightly higher and PAA slightly less in PLWH although this did not reach statistical significance. In multivariate analysis, male sex (adjusted odds ratio = 1.68 [95%CI = 1.03-2.73]), current smoking (2.74 [1.30-5.79]), diabetes mellitus (2.97 [1.48-5.99]), hypertension (1.67 [1.02-2.72]), frailty (3.82 [1.33-10.93]), and higher IL-6 levels (1.09 [1.04-1.15]), but not HIV status and NCI, were independently associated with higher PAA. PhenoAge marker discriminated frailty better than chronological age alone (AUROC: 0.75 [0.66-0.85] vs. 0.65 [0.55-0.77], p = 0.04). In the analysis restricted to PLWH, PhenoAge alone predicted frailty better than chronological age alone (AUROC: 0.7412 vs. 0.6499, P = 0.09) and VACS index (AUROC: 0.7412 vs. 0.6811, P = 0.34) despite not statistically significant. Conclusions: While PLWH did not appear to have accelerated aging in our cohort, the phenotypic aging marker was significantly associated with systemic inflammation, frailty, and cardiovascular disease risk factors. This simple aging marker could be useful to identify high-risk PLWH within a similar chronological age group.
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