21 research outputs found
Homeostatic dysregulation proceeds in parallel in multiple physiological systems
Abstract: An increasing number of aging researchers believes that multisystem physiological dysregulation may be a key biological mechanism of aging, but evidence of this has been sparse. Here, we used biomarker data on nearly 33 000 individuals from four large datasets to test for the presence of multi-system dysregulation. We grouped 37 biomarkers into six a priori groupings representing physiological systems (lipids, immune, oxygen transport, liver function, vitamins, and electrolytes), then calculated dysregulation scores for each system in each individual using statistical distance. Correlations among dysregulation levels across systems were generally weak but significant. Comparison of these results to dysregulation in arbitrary ‘systems’ generated by random grouping of biomarkers showed that a priori knowledge effectively distinguished the true systems in which dysregulation proceeds most independently. In other words, correlations among dysregulation levels were higher using arbitrary systems, indicating that only a priori systems identified distinct dysregulation processes. Additionally, dysregulation of most systems increased with age and significantly predicted multiple health outcomes including mortality, frailty, diabetes, heart disease, and number of chronic diseases. The six systems differed in how well their dysregulation scores predicted health outcomes and age. These findings present the first unequivocal demonstration of integrated multi-system physiological dysregulation during aging, demonstrating that physiological dysregulation proceeds neither as a single global process nor as a completely independent process in different systems, but rather as a set of system-specific processes likely linked through weak feedback effects. These processes – probably many more than the six measured here – are implicated in aging
Detection of a novel, integrative aging process suggests complex physiological integration
Abstract: Many studies of aging examine biomarkers one at a time, but complex systems theory and
network theory suggest that interpretations of individual markers may be context-dependent.
Here, we attempted to detect underlying processes governing the levels ofmany biomarkers
simultaneously by applying principal components analysis to 43 common clinical biomarkers
measured longitudinally in 3694 humans from three longitudinal cohort studies on two continents
(Women’s Health and Aging I & II, InCHIANTI, and the Baltimore Longitudinal Study on
Aging). The first axis was associated with anemia, inflammation, and low levels of calcium
and albumin. The axis structure was precisely reproduced in all three populations and in all
demographic sub-populations (by sex, race, etc.); we call the process represented by the
axis “integrated albunemia.” Integrated albunemia increases and accelerates with age in all
populations, and predicts mortality and frailty – but not chronic disease – even after controlling
for age. This suggests a role in the aging process, though causality is not yet clear.
Integrated albunemia behaves more stably across populations than its component biomarkers,
and thus appears to represent a higher-order physiological process emerging from the
structure of underlying regulatory networks. If this is correct, detection of this process has
substantial implications for physiological organizationmore generally