TY - JOUR
T1 - Composite Measure of Physiological Dysregulation as a Predictor of Mortality
T2 - The Long Life Family Study
AU - Long Life Family Study
AU - Arbeev, Konstantin G.
AU - Bagley, Olivia
AU - Ukraintseva, Svetlana V.
AU - Duan, Hongzhe
AU - Kulminski, Alexander M.
AU - Stallard, Eric
AU - Wu, Deqing
AU - Christensen, Kaare
AU - Feitosa, Mary F.
AU - Thyagarajan, Bharat
AU - Zmuda, Joseph M.
AU - Yashin, Anatoliy I.
N1 - Publisher Copyright:
© Copyright © 2020 Arbeev, Bagley, Ukraintseva, Duan, Kulminski, Stallard, Wu, Christensen, Feitosa, Thyagarajan, Zmuda and Yashin.
PY - 2020/3/6
Y1 - 2020/3/6
N2 - Biological aging results in changes in an organism that accumulate over age in a complex fashion across different regulatory systems, and their cumulative effect manifests in increased physiological dysregulation (PD) and declining robustness and resilience that increase risks of health disorders and death. Several composite measures involving multiple biomarkers that capture complex effects of aging have been proposed. We applied one such approach, the Mahalanobis distance (DM), to baseline measurements of various biomarkers (inflammation, hematological, diabetes-associated, lipids, endocrine, renal) in 3,279 participants from the Long Life Family Study (LLFS) with complete biomarker data. We used DM to estimate the level of PD by summarizing information about multiple deviations of biomarkers from specified “norms” in the reference population (here, LLFS participants younger than 60 years at baseline). An increase in DM was associated with significantly higher mortality risk (hazard ratio per standard deviation of DM: 1.42; 95% confidence interval: [1.3, 1.54]), even after adjustment for a composite measure summarizing 85 health-related deficits (disabilities, diseases, less severe symptoms), age, and other covariates. Such composite measures significantly improved mortality predictions especially in the subsample of participants from families enriched for exceptional longevity (the areas under the receiver operating characteristic curves are 0.88 vs. 0.85, in models with and without the composite measures, p = 2.9 × 10−5). Sensitivity analyses confirmed that our conclusions are not sensitive to different aspects of computational procedures. Our findings provide the first evidence of association of PD with mortality and its predictive performance in a unique sample selected for exceptional familial longevity.
AB - Biological aging results in changes in an organism that accumulate over age in a complex fashion across different regulatory systems, and their cumulative effect manifests in increased physiological dysregulation (PD) and declining robustness and resilience that increase risks of health disorders and death. Several composite measures involving multiple biomarkers that capture complex effects of aging have been proposed. We applied one such approach, the Mahalanobis distance (DM), to baseline measurements of various biomarkers (inflammation, hematological, diabetes-associated, lipids, endocrine, renal) in 3,279 participants from the Long Life Family Study (LLFS) with complete biomarker data. We used DM to estimate the level of PD by summarizing information about multiple deviations of biomarkers from specified “norms” in the reference population (here, LLFS participants younger than 60 years at baseline). An increase in DM was associated with significantly higher mortality risk (hazard ratio per standard deviation of DM: 1.42; 95% confidence interval: [1.3, 1.54]), even after adjustment for a composite measure summarizing 85 health-related deficits (disabilities, diseases, less severe symptoms), age, and other covariates. Such composite measures significantly improved mortality predictions especially in the subsample of participants from families enriched for exceptional longevity (the areas under the receiver operating characteristic curves are 0.88 vs. 0.85, in models with and without the composite measures, p = 2.9 × 10−5). Sensitivity analyses confirmed that our conclusions are not sensitive to different aspects of computational procedures. Our findings provide the first evidence of association of PD with mortality and its predictive performance in a unique sample selected for exceptional familial longevity.
KW - Long Life Family Study
KW - aging
KW - deficits index
KW - mortality
KW - physiological dysregulation
KW - prediction
KW - statistical distance
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U2 - 10.3389/fpubh.2020.00056
DO - 10.3389/fpubh.2020.00056
M3 - Article
AN - SCOPUS:85082701674
SN - 2296-2565
VL - 8
JO - Frontiers in Public Health
JF - Frontiers in Public Health
M1 - 56
ER -