Derivation of a measure of physiological multisystem dysregulation: Results from WHAS and health ABC.
Biomarkers
Frailty
Psychometrics
Journal
Mechanisms of ageing and development
ISSN: 1872-6216
Titre abrégé: Mech Ageing Dev
Pays: Ireland
ID NLM: 0347227
Informations de publication
Date de publication:
06 2020
06 2020
Historique:
received:
26
02
2020
revised:
23
04
2020
accepted:
30
04
2020
pubmed:
20
5
2020
medline:
28
9
2021
entrez:
20
5
2020
Statut:
ppublish
Résumé
Multifactorial biological processes underpin dysregulation over several individual physiological systems. However, it is challenging to characterize and model this multisystemic dysregulation and its relationship with individual physiologic systems. We operationalized a theory-driven measure of multisystem dysregulation and empirically tested for measurement differences by key characteristics. We used the Women's Health and Aging Studies (WHAS) I and II (N = 649), and the Health ABC study (N = 1515). Twelve biomarkers representing multiple systems including stress response (e.g., inflammation), endocrine system, and energy regulation were identified. A series of confirmatory factor analyses (CFA) were conducted to evaluate the interplay between physiological systems and underlying multisystem dysregulation. We evaluated convergent criterion validity of a score for multisystem dysregulation against the physical frailty phenotype, and predictive criterion validity with incidence of walking difficulty and mortality. A bifactor CFA, a model in which dysregulation of individual systems proceeds independently of generalized dysregulation, fit data well in WHAS (RMSEA: 0.019; CFI: 0.977; TLI: 0.961) and Health ABC (RMSEA: 0.047; CFI: 0.874; TLI: 0.787). The general dysregulation factor was associated with frailty (OR: 2.2, 95 % CI: 1.4, 3.5), and elevated risk of incident walking difficulty and mortality. Findings were replicated in Health ABC. Biomarker data from two epidemiologic studies support the construct of multisystem physiological dysregulation. Results further suggest system-specific and system-wide processes have unique and non-overlapping contributions to dysregulation in biological markers.
Identifiants
pubmed: 32423871
pii: S0047-6374(20)30054-3
doi: 10.1016/j.mad.2020.111258
pmc: PMC7375911
mid: NIHMS1596679
pii:
doi:
Substances chimiques
Biomarkers
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, N.I.H., Intramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
111258Subventions
Organisme : NIA NIH HHS
ID : R01 AG011703
Pays : United States
Organisme : NIA NIH HHS
ID : N1AG62101A
Pays : United States
Organisme : NIA NIH HHS
ID : K01 AG050699
Pays : United States
Organisme : NIA NIH HHS
ID : R37 AG019905
Pays : United States
Organisme : NIA NIH HHS
ID : K01 AG064040
Pays : United States
Organisme : NIA NIH HHS
ID : P30 AG021334
Pays : United States
Organisme : NINR NIH HHS
ID : R01 NR012459
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG055781
Pays : United States
Organisme : NIA NIH HHS
ID : N1AG62103A
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG028050
Pays : United States
Organisme : NIA NIH HHS
ID : N01 AG012112
Pays : United States
Organisme : NCI NIH HHS
ID : P30 CA006973
Pays : United States
Informations de copyright
Copyright © 2020 Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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