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Biochemical Markers in Ophthalmology
Published in Ching-Yu Cheng, Tien Yin Wong, Ophthalmic Epidemiology, 2022
Abdus Samad Ansari, Pirro G. Hysi
A large proportion of the age-related epigenetic changes are related to the constant adaptive DNAm changes in response to exposure to a variety of environmental stimuli during the life course [96]. The cumulative methylation changes observed with age have led to the notion of the “epigenetic clock,” in which the epigenetic age of the DNA is correlated with both chronological and biological age. Accelerated age, i.e., when the epigenetic age is higher than the chronological one, is associated with risk for several diseases [97] and decreased longevity [98]. However, not even age-related changes are completely irreversible and the cell preserves a pluripotency memory and age of somatic cells can be reprogrammed or fully reset, through manipulation of the expression of the Yamanaka factors [99, 100].
Breast cancer epigenetic targets for precision medicine
Published in Debmalya Barh, Precision Medicine in Cancers and Non-Communicable Diseases, 2018
Recent studies linked the “epigenetic clock,” or the DNA methylation-based markers of ageing, to the risk of cancer development. In order to identify possible epigenetics biomarkers for breast cancer susceptibility and risk stratification, a new study conducted a DNA methylome analysis in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort using the Illumina HumanMethylation 450K BeadChip arrays. It was found that higher CpG islands’ DNA methylation is significantly associated with postmenopausal breast cancer susceptibility, suggesting that accelerated epigenetic ageing increases risk of breast cancer development (Ambatipudi et al., 2017).
The Role of Mathematical Modeling in Understanding Aging
Published in Shamim I. Ahmad, Aging: Exploring a Complex Phenomenon, 2017
Mark Mc Auley, Amy Morgan, Kathleen Mooney
The process of growing old and aging has intrigued and troubled scholars, philosophers, and scientists from the beginning of civilization. The question of why we age is challenging, however thanks to the contributions of many eminent scientists this conundrum has largely been resolved. Mathematical models have been to the forefront in helping to unravel this puzzle and in this chapter we discuss the contribution they have made to biogerontology [1,2]. In order for mathematical models to be successfully applied to unraveling why aging occurs it was necessary to understand aging from an evolutionary perspective. The first scientist to seriously consider aging through the lens of evolution was the brilliant German biologist August Weismann. In 1881, a mere 22 years after Darwin published On The Origin of Species by Means of Natural Selection [3], Weisman outlined a purely adaptive theory to explain aging [4]. He reasoned that senescence is the result of an evolved limitation to the division potential of somatic cells and argued this limitation evolved because it is beneficial to eliminate old individuals from a population, thus freeing up resources for younger individuals. This theory resonated with much of the evolutionary and social demographic thinking of the nineteenth century as Weismann hypothesized senescence or “programmed death” as it became known was an evolved trait and its utility was to remove decrepit individuals from a population. As a theory it remains controversial for a number of reasons; first, if a trait was to be selected for by evolution, for example, “programmed aging/death” it would have been necessary for it to manifest itself in such a way as to have a bearing on the survival of the organism; and as aging is rarely witnessed in the wild due to high rates of extrinsic mortality, there would have been limited selection pressure for “programmed death” to have evolved. It is uncertain if Weismann recognized this limitation but he did go on to propose a second nonadaptive theory that considered old individuals as neutral and the evolution of aging as a “panmixia,” where neutral characters decline during evolution [5]. Thus, Weismann's original idea of “programmed aging” has been in the main consigned to the annals of history. Although the idea of “programmed aging” still has its advocacy recently, Mitteldorf argued for a form of programmed aging by postulating that aging is regulated by an epigenetic clock [6].
Maintaining a ‘fit’ immune system: the role of vaccines
Published in Expert Review of Vaccines, 2023
Béatrice Laupèze, T. Mark Doherty
These DNA methylation levels can be used as markers of ‘bioaging’ and are sometimes referred to as an ‘epigenetic clock.’ The accumulation of such markers can be accelerated, or slowed, or even possibly reversed by given factors, although research is only beginning in this field. However, in general, the impact of external or environmental factors on the ‘epigenetic clock’ increases as individuals age. The outcome of these external factors may not always be negative, theoretically making the ‘epigenetic clock’ amenable to positive intervention to maintain immune health for longer. It appears that the ‘epigenetic clock’ can be accelerated by some chronic infections such as cytomegalovirus (CMV) and human immunodeficiency virus (HIV) infections [56]. The ‘epigenetic clock’ can be slowed down, perhaps predictably, by a healthy diet and physical exercise [57–59].
Investigational drugs and nutrients for human longevity. Recent clinical trials registered in ClinicalTrials.gov and clinicaltrialsregister.eu
Published in Expert Opinion on Investigational Drugs, 2021
The CENTRAL MRI trial [93] showed that lifestyle weight-loss intervention may attenuate DNA methylation age. The use of epigenetic clocks is opening the way to measure ‘biological age’ as alternative to the chronological age, that is, ‘aging’ as alternative of ‘longevity’ [94,95].