Aging and Allostasis: Using Bayesian Network Analytics to Explore and Evaluate Allostatic Markers in the Context of Aging

Victor Kallen (Corresponding author), Muhammad Tahir, Andrew Bedard, Bart Bongers, Natal van Riel, Nico van Meeteren

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Allostatic load reflects the cumulative strain on organic functions that may gradually evolve into overt disease. Our aim was to evaluate the allostatic parameters in the context of aging, and identify the parameters that may be suitable for an allostatic load index for elderly people (>60 years). From previously published studies, 11 allostatic (bio)markers could be identified that sustain sufficient variability with aging to capture meaningful changes in health status. Based on reported statistics (prevalence of a biomarker and its associated outcome, and/or an odds/risk ratio relating these two), seven of these could be adopted in a Bayesian Belief Network (BBN), providing the probability of "disturbed" allostasis in any given elder. Additional statistical analyses showed that changes in IL-6 and BMI contributed the most to a "disturbed" allostasis, indicating their prognostic potential in relation to deteriorating health in otherwise generally healthy elderly. In this way, and despite the natural decline in variance that irrevocably alters the prognostic relevance of most allostatic (bio)markers with aging, it appeared possible to outline an allostatic load index specifically for the elderly. The allostatic parameters here identified might consequently be considered a useful basis for future quantitative modelling in the context of (healthy) aging.

Original languageEnglish
Article number157
Number of pages18
JournalDiagnostics
Volume11
Issue number2
DOIs
Publication statusPublished - 21 Jan 2021

Keywords

  • allostasis
  • allostatic load
  • allostatic load index
  • aging
  • biomarkers
  • Bayesian belief network
  • elderly
  • IL-6
  • BMI

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