STEMM Institute Press
Science, Technology, Engineering, Management and Medicine
Research Progress on the Correlation Between Multi-Dimensional Serum Biomarkers and Frailty in the Elderly
DOI: https://doi.org/10.62517/jmhs.202605125
Author(s)
Yaqing Cui1,#, Jiao Zhou1,#, Hua Lin2, Juntao Li1, Zhengyan Shi1, Xuyang Li1, Zhixin Wu1, Jinlei Dong1, Kun Zhu1,*
Affiliation(s)
1Surgical Department, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, China 2Nursing Department, Baoji Central Hospital, Baoji, Shaanxi, China #Co-First Author *Corresponding Author
Abstract
With the accelerated aging process in China, frailty has become an important geriatric syndrome that threatens the health of the elderly. Frailty is characterized by decreased physiological reserve and increased physical vulnerability, often leads to adverse health outcomes. Recently, serum factors have received widespread attention as potential biomarkers for early identification and risk assessment of frailty. In terms of chronic inflammation, levels of interleukin-6 (IL-6), C-reactive protein (CRP), and procalcitonin (PCT) are significantly elevated in frail individuals, showing a positive correlation with frailty phenotype; homocysteine (Hcy), as a metabolism-related factor, is closely associated with cognitive frailty; 25-hydroxyvitamin D (25(OH)D) and Klotho protein exhibit a protective effect against frailty, and their decreased levels are associated with an increased risk of frailty. Predictive models based on multi-markers have higher diagnostic performance than single markers, and proteomic studies also show the revealed protein signature associated with frailty. However, currently there is a lack of standardized serum factor’s evaluation Protocol. This review provides a scientific basis for early clinical identification and intervention of frailty and the future research directions need focusing on the optimization and application validation of multi-marker combined models.
Keywords
Frailty; Serum Factor; Biomarker; Chronic Disease; Predictive Model
References
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