Cockayne syndrome (CS) is a disorder characterized by a variety of clinical features including cachectic dwarfism, severe neurological manifestations including microcephaly and cognitive deficits, pigmentary retinopathy, cataracts, sensorineural deafness, and ambulatory and feeding difficulties, leading to death by 12 years of age on average. It is an autosomal recessive disorder, with a prevalence of approximately 2.5 per million. There are several phenotypes (1, 2 and 3) and complementation groups (CSA and CSB), and overlaps with xeroderma pigmentosum (XP). It has been considered a progeria, and many of the clinical features resemble accelerated aging. As such, the study of CS affords an opportunity to better understand the underlying mechanisms of aging. The molecular basis of CS has traditionally been considered to be due to defects in transcription and transcription-coupled nucleotide excision repair (TC-NER). However, recent work suggests that defects in base excision DNA repair and mitochondrial functions may also play key roles. This opens up the possibility of molecular interventions in CS, and by extrapolation, possibly in aging.
Over the past three decades, considerable effort has been dedicated to quantifying the pace of ageing yet identifying the most essential metrics of ageing remains challenging due to lack of comprehensive measurements and heterogeneity of the ageing processes. Most of the previously proposed metrics of ageing have been emerged from cross‐sectional associations with chronological age and predictive accuracy of mortality, thus lacking a conceptual model of functional or phenotypic domains. Further, such models may be biased by selective attrition and are unable to address underlying biological constructs contributing to functional markers of age‐related decline. Using longitudinal data from the Baltimore Longitudinal Study of Aging (BLSA), we propose a conceptual framework to identify metrics of ageing that may capture the hierarchical and temporal relationships between functional ageing, phenotypic ageing and biological ageing based on four hypothesized domains: body composition, energy regulation, homeostatic mechanisms and neurodegeneration/neuroplasticity. We explored the longitudinal trajectories of key variables within these phenotypes using linear mixed‐effects models and more than 10 years of data. Understanding the longitudinal trajectories across these domains in the BLSA provides a reference for researchers, informs future refinement of the phenotypic ageing framework and establishes a solid foundation for future models of biological ageing.
To define metrics of phenotypic aging, it is essential to identify biological and environmental factors that influence the pace of aging. Previous attempts to develop aging metrics were hampered by cross-sectional designs and/or focused on younger populations. In the Baltimore Longitudinal Study of Aging (BLSA), we collected longitudinally across the adult age range a comprehensive list of phenotypes within four domains (body composition, energetics, homeostatic mechanisms and neurodegeneration/neuroplasticity) and functional outcomes. We integrated individual deviations from population trajectories into a global longitudinal phenotypic metric of aging and demonstrate that accelerated longitudinal phenotypic aging is associated with faster physical and cognitive decline, faster accumulation of multimorbidity and shorter survival. These associations are more robust compared with the use of phenotypic and epigenetic measurements at a single time point. Estimation of these metrics required repeated measures of multiple phenotypes over time but may uniquely facilitate the identification of mechanisms driving phenotypic aging and subsequent age-related functional decline.
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