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Measuring Frailty in HIV-infected Individuals. Identification of Frail Patients is the First Step to Amelioration and Reversal of Frailty
Published on: July 24, 2013
Frailty-related plasma metabolomic signatures predict long-term mortality risk and implicate systemic aging pathways:
Xiru Zhang1,2, Xin Feng1, Wenchao Liu1
1Neurosurgery Center, Department of Cerebrovascular Surgery, The Engineering Technology Research Center of Education Ministry of China on Diagnosis and Treatment of Cerebrovascular Disease, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
None:
Frailty is a common geriatric syndrome associated with increased mortality, yet its underlying biological mechanisms and potential value for early risk stratification remain inadequately understood. In this large prospective cohort of more than 260,000 UK Biobank participants with plasma metabolomic profiling, we identified and validated metabolomic signatures of physical frailty and a 49-item frailty index using 50-times repeated 10-fold cross-validated elastic-net regression. The signatures demonstrated strong internal stability and geographic reproducibility and reflected coordinated alterations across lipid, amino acid, energy, and inflammatory pathways. Higher signature levels were significantly associated with increased risks of all-cause and cause-specific mortality, including cancer, cardiovascular, respiratory, and digestive deaths. Individuals in the highest-risk tertile had more than 2.5-fold higher risks of cardiovascular, respiratory, and digestive mortality. At age 60, individuals above the median signature level were estimated to have 4.1 fewer years of life expectancy. Mediation analyses indicated that the metabolomic signatures statistically explained up to 35% of the observed frailty-mortality association. Associations were stronger among younger individuals and differed by sex and BMI. These findings suggest that frailty-related plasma metabolomic signatures capture systemic metabolic correlates of biological aging and may support early mortality risk prediction and personalized prevention strategies in aging populations.
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