Browsing by Subject "trajectory"

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    GIT2 Acts as a Systems-Level Coordinator of Neurometabolic Activity and Pathophysiological Aging.
    (Front Endocrinol (Lausanne), 2015) Martin, Bronwen; Chadwick, Wayne; Janssens, Jonathan; Premont, Richard T; Schmalzigaug, Robert; Becker, Kevin G; Lehrmann, Elin; Wood, William H; Zhang, Yongqing; Siddiqui, Sana; Park, Sung-Soo; Cong, Wei-Na; Daimon, Caitlin M; Maudsley, Stuart
    Aging represents one of the most complicated and highly integrated somatic processes. Healthy aging is suggested to rely upon the coherent regulation of hormonal and neuronal communication between the central nervous system and peripheral tissues. The hypothalamus is one of the main structures in the body responsible for sustaining an efficient interaction between energy balance and neurological activity and therefore likely coordinates multiple systems in the aging process. We previously identified, in hypothalamic and peripheral tissues, the G protein-coupled receptor kinase interacting protein 2 (GIT2) as a stress response and aging regulator. As metabolic status profoundly affects aging trajectories, we investigated the role of GIT2 in regulating metabolic activity. We found that genomic deletion of GIT2 alters hypothalamic transcriptomic signatures related to diabetes and metabolic pathways. Deletion of GIT2 reduced whole animal respiratory exchange ratios away from those related to primary glucose usage for energy homeostasis. GIT2 knockout (GIT2KO) mice demonstrated lower insulin secretion levels, disruption of pancreatic islet beta cell mass, elevated plasma glucose, and insulin resistance. High-dimensionality transcriptomic signatures from islets isolated from GIT2KO mice indicated a disruption of beta cell development. Additionally, GIT2 expression was prematurely elevated in pancreatic and hypothalamic tissues from diabetic-state mice (db/db), compared to age-matched wild type (WT) controls, further supporting the role of GIT2 in metabolic regulation and aging. We also found that the physical interaction of pancreatic GIT2 with the insulin receptor and insulin receptor substrate 2 was diminished in db/db mice compared to WT mice. Therefore, GIT2 appears to exert a multidimensional "keystone" role in regulating the aging process by coordinating somatic responses to energy deficits.
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    Joint Analyses of Longitudinal and Time-to-Event Data in Research on Aging: Implications for Predicting Health and Survival.
    (Front Public Health, 2014) Arbeev, Konstantin G; Akushevich, Igor; Kulminski, Alexander M; Ukraintseva, Svetlana V; Yashin, Anatoliy I
    Longitudinal data on aging, health, and longevity provide a wealth of information to investigate different aspects of the processes of aging and development of diseases leading to death. Statistical methods aimed at analyses of time-to-event data jointly with longitudinal measurements became known as the "joint models" (JM). An important point to consider in analyses of such data in the context of studies on aging, health, and longevity is how to incorporate knowledge and theories about mechanisms and regularities of aging-related changes that accumulate in the research field into respective analytic approaches. In the absence of specific observations of longitudinal dynamics of relevant biomarkers manifesting such mechanisms and regularities, traditional approaches have a rather limited utility to estimate respective parameters that can be meaningfully interpreted from the biological point of view. A conceptual analytic framework for these purposes, the stochastic process model of aging (SPM), has been recently developed in the biodemographic literature. It incorporates available knowledge about mechanisms of aging-related changes, which may be hidden in the individual longitudinal trajectories of physiological variables and this allows for analyzing their indirect impact on risks of diseases and death. Despite, essentially, serving similar purposes, JM and SPM developed in parallel in different disciplines with very limited cross-referencing. Although there were several publications separately reviewing these two approaches, there were no publications presenting both these approaches in some detail. Here, we overview both approaches jointly and provide some new modifications of SPM. We discuss the use of stochastic processes to capture biological variation and heterogeneity in longitudinal patterns and important and promising (but still largely underused) applications of JM and SPM to predictions of individual and population mortality and health-related outcomes.