Age dynamics of DNA damage and CpG methylation in the peripheral blood leukocytes of mice

Biological Age Predictors: The Status Quo and Future Trends

There is no single universal biomarker yet to estimate overall health status and longevity prospects. Moreover, a consensual approach to the very concept of aging and the means of its assessment are yet to be developed. Markers of aging could facilitate effective health control, more accurate life expectancy estimates, and improved health and quality of life. Clinicians routinely use several indicators that could be biomarkers of aging. Duly validated in a large cohort, models based on a combination of these markers could provide a highly accurate assessment of biological age and the pace of aging. Biological aging is a complex characteristic of chronological age (usually), health-to-age concordance, and medically estimated life expectancy. This study is a review of the most promising techniques that could soon be used in routine clinical practice. Two main selection criteria were applied: a sufficient sample size and reliability based on validation. The selected biological age calculators were grouped according to the type of biomarker used: (1) standard clinical and laboratory markers; (2) molecular markers; and (3) epigenetic markers. The most accurate were the calculators, which factored in a variety of biomarkers. Despite their demonstrated effectiveness, most of them require further improvement and cannot yet be considered for use in standard clinical practice. To illustrate their clinical application, we reviewed their use during the COVID-19 pandemic.

Human Variation in DNA Repair, Immune Function, and Cancer Risk

DNA damage constantly threatens genome integrity, and DNA repair deficiency is associated with increased cancer risk. An intuitive and widely accepted explanation for this relationship is that unrepaired DNA damage leads to carcinogenesis due to the accumulation of mutations in somatic cells. But DNA repair also plays key roles in the function of immune cells, and immunodeficiency is an important risk factor for many cancers. Thus, it is possible that emerging links between inter-individual variation in DNA repair capacity and cancer risk are driven, at least in part, by variation in immune function, but this idea is underexplored. In this review we present an overview of the current understanding of the links between cancer risk and both inter-individual variation in DNA repair capacity and inter-individual variation in immune function. We discuss factors that play a role in both types of variability, including age, lifestyle, and environmental exposures. In conclusion, we propose a research paradigm that incorporates functional studies of both genome integrity and the immune system to predict cancer risk and lay the groundwork for personalized prevention.

Cell cycle involvement in cancer therapy; WEE1 kinase, a potential target as therapeutic strategy

Mitosis is the process of cell division and is regulated by checkpoints in the cell cycle. G1-S, S, and G2-M are the three main checkpoints that prevent initiation of the next phase of the cell cycle phase until previous phase has completed. DNA damage leads to activation of the G2-M checkpoint, which can trigger a downstream DNA damage response (DDR) pathway to induce cell cycle arrest while the damage is repaired. If the DNA damage cannot be repaired, the replication stress response (RSR) pathway finally leads to cell death by apoptosis, in this case called mitotic catastrophe. Many cancer treatments (chemotherapy and radiotherapy) cause DNA damages based on SSBs (single strand breaks) or DSBs (double strand breaks), which cause cell death through mitotic catastrophe. However, damaged cells can activate WEE1 kinase (as a part of the DDR and RSR pathways), which prevents apoptosis and cell death by inducing cell cycle arrest at G2 phase. Therefore, inhibition of WEE1 kinase could sensitize cancer cells to chemotherapeutic drugs. This review focuses on the role of WEE1 kinase (as a biological macromolecule which has a molecular mass of 96 kDa) in the cell cycle, and its interactions with other regulatory pathways. In addition, we discuss the potential of WEE1 inhibition as a new therapeutic approach in the treatment of various cancers, such as melanoma, breast cancer, pancreatic cancer, cervical cancer, etc.

Markers of arterial health could serve as accurate non-invasive predictors of human biological and chronological age

The decline in functional capacity is unavoidable consequence of the process of aging. While many anti-aging interventions have been proposed, clinical investigations into anti-aging medicine are limited by lack of reliable techniques for evaluating the rate of ageing. Here we present simple, accurate and cost-efficient techniques for estimation of human biological age, Male and Female Arterial Indices. We started with developing a model which accurately predicts chronological age. Using machine learning, we arrived on a set of four predictors, all of which reflect the functioning of the cardiovascular system. In Arterial Indices models, results of carotid artery duplex scan that show the thickness of the intima media complex and quantitatively describe the degree of stenosis are combined with pulse wave velocity and augmentation index measurements performed by applanation tonometry. In our cohort, the age of men was determined with MAE = 6.91 years (adjusted R-squared = 0.55), and the age of women with MAE = 5.87 years (adjusted R² = 0.69). The Epsilon-accuracies of age-predicting models were at 86.5% and 80% for women and men, respectively. Substantially higher differences between the predicted age and the calendar age were noted for patients with Type 2 Diabetes Mellitus (T2D) as compared to non-T2D controls, indicating that the model could serve as a good approximation for an elusive biological age. Notably, in females with chronological and biological ages mismatching by 5 or more years, significant increases in in Framingham CVD scores and lower levels of IGF-1 were observed.

Proposed Male and Female Arterial Indices derive biological age from the results of functional tests which do not require specialized laboratory equipment and, therefore, could be performed in hospitals and community health clinics.

Age-Specific Gene Expression Profiles of Rhesus Monkey Ovaries Detected by Microarray Analysis

The biological function of human ovaries declines with age. To identify the potential molecular changes in ovarian aging, we performed genome-wide gene expression analysis by microarray of ovaries from young, middle-aged, and old rhesus monkeys. Microarray data was validated by quantitative real-time PCR. Results showed that a total of 503 (60 upregulated, 443 downregulated) and 84 (downregulated) genes were differentially expressed in old ovaries compared to young and middle-aged groups, respectively. No difference in gene expression was found between middle-aged and young groups. Differentially expressed genes were mainly enriched in cell and organelle, cellular and physiological process, binding, and catalytic activity. These genes were primarily associated with KEGG pathways of cell cycle, DNA replication and repair, oocyte meiosis and maturation, MAPK, TGF-beta, and p53 signaling pathway. Genes upregulated were involved in aging, defense response, oxidation reduction, and negative regulation of cellular process; genes downregulated have functions in reproduction, cell cycle, DNA and RNA process, macromolecular complex assembly, and positive regulation of macromolecule metabolic process. These findings show that monkey ovary undergoes substantial change in global transcription with age. Gene expression profiles are useful in understanding the mechanisms underlying ovarian aging and age-associated infertility in primates.