2
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Generating synthetic aging trajectories with a weighted network model using cross-sectional data

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          We develop a computational model of human aging that generates individual health trajectories with a set of observed health attributes. Our model consists of a network of interacting health attributes that stochastically damage with age to form health deficits, leading to eventual mortality. We train and test the model for two different cross-sectional observational aging studies that include simple binarized clinical indicators of health. In both studies, we find that cohorts of simulated individuals generated from the model resemble the observed cross-sectional data in both health characteristics and mortality. We can generate large numbers of synthetic individual aging trajectories with our weighted network model. Predicted average health trajectories and survival probabilities agree well with the observed data.

          Related collections

          Most cited references39

          • Record: found
          • Abstract: found
          • Article: found

          The Hallmarks of Aging

          Aging is characterized by a progressive loss of physiological integrity, leading to impaired function and increased vulnerability to death. This deterioration is the primary risk factor for major human pathologies, including cancer, diabetes, cardiovascular disorders, and neurodegenerative diseases. Aging research has experienced an unprecedented advance over recent years, particularly with the discovery that the rate of aging is controlled, at least to some extent, by genetic pathways and biochemical processes conserved in evolution. This Review enumerates nine tentative hallmarks that represent common denominators of aging in different organisms, with special emphasis on mammalian aging. These hallmarks are: genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, and altered intercellular communication. A major challenge is to dissect the interconnectedness between the candidate hallmarks and their relative contributions to aging, with the final goal of identifying pharmaceutical targets to improve human health during aging, with minimal side effects. Copyright © 2013 Elsevier Inc. All rights reserved.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Frailty in Older Adults: Evidence for a Phenotype

              Bookmark
              • Record: found
              • Abstract: found
              • Article: found

              Frailty in elderly people

              Frailty is the most problematic expression of population ageing. It is a state of vulnerability to poor resolution of homoeostasis after a stressor event and is a consequence of cumulative decline in many physiological systems during a lifetime. This cumulative decline depletes homoeostatic reserves until minor stressor events trigger disproportionate changes in health status. In landmark studies, investigators have developed valid models of frailty and these models have allowed epidemiological investigations that show the association between frailty and adverse health outcomes. We need to develop more efficient methods to detect frailty and measure its severity in routine clinical practice, especially methods that are useful for primary care. Such progress would greatly inform the appropriate selection of elderly people for invasive procedures or drug treatments and would be the basis for a shift in the care of frail elderly people towards more appropriate goal-directed care. Copyright © 2013 Elsevier Ltd. All rights reserved.
                Bookmark

                Author and article information

                Contributors
                spencer.farrell@dal.ca
                andrew.rutenberg@dal.ca
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                16 November 2020
                16 November 2020
                2020
                : 10
                : 19833
                Affiliations
                [1 ]GRID grid.55602.34, ISNI 0000 0004 1936 8200, Department of Physics and Atmospheric Science, , Dalhousie University, ; Halifax, NS Canada
                [2 ]GRID grid.55602.34, ISNI 0000 0004 1936 8200, Division of Geriatric Medicine, , Dalhousie University, ; Halifax, NS Canada
                Article
                76827
                10.1038/s41598-020-76827-3
                7670406
                33199733
                6346e89d-4267-47ad-9648-51a7feb461ec
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 7 May 2020
                : 2 November 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000024, Canadian Institutes of Health Research;
                Award ID: PJT-156114
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000038, Natural Sciences and Engineering Research Council of Canada;
                Award ID: RGPIN 2019-05888
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                geriatrics,numerical simulations,stochastic modelling,computational models,predictive medicine,ageing

                Comments

                Comment on this article