Derivation of a measure of physiological multisystem dysregulation: Results from WHAS and health ABC. (June 2020)

• Record Type: Journal Article
• Authors: Gross, Alden L.; Carlson, Michelle C.; Chu, Nadia M.; McAdams-DeMarco, Mara A.; Mungas, Dan; Simonsick, Eleanor M.; Varadhan, Ravi; Xue, Qian-Li; Walston, Jeremy; Bandeen-Roche, Karen
• Is Part Of: Mechanisms of ageing and development. Volume 188(2020)
• Publication Date: 2020-06
• Subjects: Biomarkers -- Frailty -- Psychometrics; Aging -- Periodicals; Developmental biology -- Periodicals; Aging -- Periodicals; Developmental Biology -- Periodicals; Vieillissement -- Périodiques; Biologie du développement -- Périodiques; Aging; Developmental biology; Periodicals; 612.67
• DOI: 10.1016/j.mad.2020.111258
• Languages: English
• ISSNs: 0047-6374

Abstract

Highlights: It is challenging to model multisystemic biological dysregulation and its relationship with individual systems. We developed a theory-driven measure of multisystem dysregulation by fitting alternate theory-driven models to biomarkers. Findings suggest system-specific and system-wide processes drive biomarker dysregulation in unique, non-overlapping ways. The multisystem dysregulation factor is associated with frailty and elevated hazards of mobility difficulty and death. Abstract: Introduction: 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. Methods: 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. Results: 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. 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.