Composite Measure of Physiological Dysregulation as a Predictor of Mortality: The Long Life Family Study

Long Life Family Study

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Abstract

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.

Original languageEnglish (US)
Article number56
JournalFrontiers in Public Health
Volume8
DOIs
StatePublished - Mar 6 2020

Bibliographical note

Funding Information:
Research reported in this publication was supported by the National Institute on Aging of the National Institutes of Health (NIA/NIH) under Award Numbers U01AG023712 and U19AG063893. This work of KA, OB, SU, HD, AK, ES, DW, and AY was also partly supported by the NIA/NIH grant P01AG043352. This work of KA, OB, SU, HD, DW, and AY was also partly supported by the NIA/NIH grant R01AG062623. This content was solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Keywords

  • Long Life Family Study
  • aging
  • deficits index
  • mortality
  • physiological dysregulation
  • prediction
  • statistical distance

PubMed: MeSH publication types

  • Journal Article

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