ArticleMechanisms of ageing and development2020
Derivation of a measure of physiological multisystem dysregulation: Results from WHAS and health ABC.
Article in Mechanisms of ageing and development, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 16 citations in OpenAlex.
- Multiomics strategy-based obesity biomarkers discovery for precision medicine.International journal of obesity (2005) · 2026Review
- The vitality domain of intrinsic capacity: A scoping review of conceptual frameworks and measurements.The Journal of frailty & aging · 2025Article
- Characterization of Dynamic Adaptation to Stressors Using Multisystem Stimulus-Response Data: The Study of Physical Resilience in Aging Pilot.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025Article
- Applications of multi-omics analysis in human diseases.MedComm · 2023Review
- Efficient representations of binarized health deficit data: the frailty index and beyond.GeroScience · 2023Article
- Intercorrelated variability in blood and hemodynamic biomarkers reveals physiological network in hemodialysis patients.Scientific reports · 2023Article
- Serum Metabolomic Profiling in Aging Mice Using Liquid Chromatography-Mass Spectrometry.Biomolecules · 2022Article
- Longitudinal phenotypic aging metrics in the Baltimore Longitudinal Study of Aging.Nature aging · 2022Article
- Integrated Multi-Omics for Novel Aging Biomarkers and Antiaging Targets.Biomolecules · 2021Review
- Physiological Dysregulation, Frailty, and Impacts on Adverse Health and Functional Outcomes.Frontiers in medicine · 2021Article
- Validation of Two Intrinsic Capacity Scales and Its Relationship with Frailty and Other Outcomes in Mexican Community-Dwelling Older Adults.The journal of nutrition, health & aging · 2021Article
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Authors and funding
10 authors at 4 institutions in 1 country.
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Abstract
introductionMultifactorial 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.
methodsWe 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.
resultsA 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. DISCUSSION: 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.
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