{"title":"Beyond hallmarks of aging - biological age and emergence of aging networks.","authors":"S Michal Jazwinski, Sangkyu Kim, Jessica Fuselier","doi":"10.31491/APT.2025.03.166","DOIUrl":"10.31491/APT.2025.03.166","url":null,"abstract":"<p><p>The hallmarks of aging have contributed immensely to the systematization of research on aging and have influenced the emergence of geroscience. The developments that led to the concepts of the hallmarks and geroscience were first marked by the proliferation of 'theories' of aging, mostly based on the experimental predilections of practitioners of aging research. Deeper consideration of the concepts of hallmarks of aging and geroscience leads to the quandary of whether a biological aging process exists beyond disease itself. To address this difficulty, a metric of biological age as opposed to calendar age is necessary. Several examples of biological age measured using similar assumptions, but different methods, exist. One of these, the frailty index was the first to successfully characterize aging in terms of loss of integrated function, and it is simpler than and superior to other constructs for measuring biological age. Though relatively simple in construction, the frailty index is rich conceptually, however, pointing to a network model of the aging organism. This network functions as a nonlinear complex system that is governed by stochastic thermodynamics, in which loss of integration leads to increasing entropy. Its structure transcends all levels of biological organization, such that its parts form hierarchies that are self-similar (fractal). The hallmarks of aging are simply nodes in the aging network, which can be found repetitively in various locations of the network. Stochastic thermodynamics implies that the aging system with higher entropy can exist in a multitude of possible microstates that are tantamount to high disorder with a high probability to assume a certain state. This explains the observed variability among aging individuals.</p>","PeriodicalId":520009,"journal":{"name":"Aging pathobiology and therapeutics","volume":"7 1","pages":"44-55"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12094518/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144121945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Resilience to aging drives personalized intervention strategies for Alzheimer's disease.","authors":"Jackson Wezeman, Addison Keely, Warren Ladiges","doi":"10.31491/apt.2023.12.127","DOIUrl":"10.31491/apt.2023.12.127","url":null,"abstract":"<p><p>There has been little progress in reducing the incidence and mortality of Alzheimer's disease (AD). Prevention of onset, more accurate diagnostic tools, and prediction of health outcomes have all been identified as critical issues, but more and better basic research approaches are needed. The single greatest risk factor associated with AD is aging. It follows that if aging can be delayed, there should be an equivalent delay or even prevention of the onset of AD neuropathology. Therefore, targeting multiple pathways of aging would be a powerful way to enhance resilience to aging and slow or prevent the onset of AD neuropathology and dementia in a personalized manner. More effective and predictive animal models, such as the aging pet cat that spontaneously develops neuropathology similar to human AD patients, are necessary to help validate noninvasive and inexpensive biomarkers for identifying individuals at risk. Resilience to aging and its ability to delay or prevent the onset of age-related diseases should be the focus for preventing brain aging and enhancing resistance to AD.</p>","PeriodicalId":520009,"journal":{"name":"Aging pathobiology and therapeutics","volume":"5 4","pages":"151-153"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11299896/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141895146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}