Biological Age Predictors: The Status Quo and Future Trends

Erema, Veronika V.; Yakovchik, Anna Y.; Kashtanova, Daria A.; Bochkaeva, Zanda V.; Иванов, М. В.; Sosin, Dmitry V.; Matkava, Lorena R.; Yudin, Vladimir S.; Makarov, Valentin V.; Keskinov, Anton A.; Kraevoy, Sergey A.; Yudin, S. M.

doi:10.3390/ijms232315103

Cited by 14 publications

(4 citation statements)

References 70 publications

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“…We discovered that the probabilities of ICU admission, usage of a ventilator, prolonged hospital stays, and mortality cluster together after extracting principal components using SVD from the data. Interestingly, med-co-administration-derived clustering is unrelated to BMI, but high MEWS and aging are moderately correlated with the other four COVID-19-related targets and consistent with previous publications [18][19][20][21] . MEWS is a useful method for quickly assessing COVID-19 patients.…”

Section: Discussionsupporting

confidence: 91%

Mining medicine prescriptions to enhance predictive management of COVID-19 patients in the UAE

AlBataineh,

Ruta,

Salameh

et al. 2023

Preprint

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Data mining is becoming more popular in the healthcare industry to enhance decision-making and patient outcomes. In this study, we examined medication patterns in over 10,000 COVID-19 patients spanning over three years from the UAE. Prescriptions digitization enabled their utility as data evidence for analytical and predictive modeling tools including machine learning (ML). In this work, we attempt to utilize digitized free-text prescriptions associated with 10k + COVID-19-positive hospitalized cases, to first extract a three-layered hierarchy of administered medicines and then use them as data features to understand their administration patterns, reveal the impacts on and associations with patients' treatment to improve the performance of predicting the key treatment outcomes. We determined higher frequencies of certain medications during different stages of the pandemic and discovered correlations between medication co-administration habits and patient outcomes such as ICU admission, ventilator usage, prolonged hospital stays, and mortality. Next, we train ML models for forecasting targeted variables and found that MEWS and Age are associated with increased risk for ICU admission, ventilator use, lengthy hospital stays, and mortality. A singleton micro-predictor of the selected feature targets in connection with the likelihood of death reveals that VENTILATOR_USE and IS_SEPTIC feature elevates the likelihood of death to 60%. Remarkably, the use of ANTISPASMODIC and ANTIFUNGAL have high mortality rates and support (PX 0.151,0.055, P DEATH/X 0.379, 0.641, respectively). Underscoring the importance of data-driven approaches to inform clinical decision-making. The application of clustering and co-administration patterns generated from graph theory may offer cutting-edge pandemic control techniques in preparation for the next pandemic.

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Section: Discussionsupporting

confidence: 91%

Mining medicine prescriptions to enhance predictive management of COVID-19 patients in the UAE

AlBataineh,

Ruta,

Salameh

et al. 2023

Preprint

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“…Individually, most clinical biomarkers are insufficiently sensitive to measure the pace of aging and biological age. Studies, however, have shown that certain combinations of biomarkers are more reliable predictors of biological age or mortality [114]. Given robust correlation of EpiAge with key physiological, behavioral, and metabolic metrics underlying functional decline with age (and not the metrics of overt pathologies such as cancer, neurodegeneration, cardiovascular disfunction) we posit that EpiAge could be used as a single and personalized biomarker of functional age.…”

Section: Discussionmentioning

confidence: 99%

ImAge: an imaging approach to quantitate aging and rejuvenation

Rodriguez¹,

Fiengo²,

Alvarez-Kuglen³

et al. 2022

Preprint

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Predictive biomarkers of functional or biological age are key for evaluating interventions aimed at increas-ing healthspan and / or lifespan in humans. Currently, cardiovascular performance, blood analytes, frailty indices (e.g. gait speed), and DNA methylation clocks are used to provide such estimates; each technique has its own challenges and limitations. We have developed a novel approach, microscopic imaging of bio-logical age (miBioAge), which computes multiparametric signatures based on the patterns of epigenetic landscape in single nuclei. We demonstrated that such miBioAge readouts can robustly distinguish young and old cells from multiple tissues, reveal aging progression in peripheral blood (e.g. CD3+ T cells), and reflect changes of epigenetic signatures consistent with expected slowdown or acceleration of biological age in chronologically identical mice treated with caloric restriction or chemotherapy. Because miBioAge readouts are computed from individual samples without applying linear regression, we posit that this novel biomarker may provide personalized assessment of functional aging.

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“…Epigenome has ushered a new era of molecular research in the field of aging ( Erema et al, 2022 ) as DNA methylation (DNAm) has emerged as one of the most powerful strategies to predict chronological age ( Horvath and Raj, 2018 ; Oblak et al, 2021 ; Simpson and Chandra, 2021 ). The precision of this instrument is astonishing, to the point to be used for forensic purposes to estimate chronological age in burned and defaced corpses or in biological specimens ( Freire-Aradas et al, 2022 ).…”

Section: Epigenetic Clocksmentioning

confidence: 99%

Epigenetic clocks and female fertility timeline: A new approach to an old issue?

Piani

Viganò

Somigliana

2023

Front. Cell Dev. Biol.

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Worldwide increase in life expectancy has boosted research on aging. Overcoming the concept of chronological age, higher attention has been addressed to biological age, which reflects a person’s real health state, and which may be the resulting combination of both intrinsic and environmental factors. As epigenetics may exert a pivotal role in the biological aging, epigenetic clocks were developed. They are based on mathematical models aimed at identifying DNA methylation patterns that can define the biological age and that can be adopted for different clinical scopes (i.e., estimation of the risks of developing age-related disorders or predicting lifespan). Recently, epigenetic clocks have gained a peculiar attention in the fertility research field, in particular in the female counterpart. The insight into the possible relations between epigenetic aging and women’s infertility might glean additional information about certain conditions that are still not completely understood. Moreover, they could disclose significant implications for health promotion programs in infertile women. Of relevance here is that the impact of biological age and epigenetics may not be limited to fertility status but could translate into pregnancy issues. Indeed, epigenetic alterations of the mother may transfer into the offspring, and pregnancy itself as well as related complications could contribute to epigenetic modifications in both the mother and newborn. However, even if the growing interest has culminated in the conspicuous production of studies on these topics, a global overview and the availability of validated instruments for diagnosis is still missing. The present narrative review aims to explore the possible bonds between epigenetic aging and fertility timeline. In the “infertility” section, we will discuss the advances on epigenetic clocks focusing on the different tissues examined (endometrium, peripheral blood, ovaries). In the “pregnancy” section, we will discuss the results obtained from placenta, umbilical cord and peripheral blood. The possible role of epigenetic aging on infertility mechanisms and pregnancy outcomes represents a question that may configure epigenetic clock as a bond between two apparently opposite worlds: infertility and pregnancy.

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Biological Age Predictors: The Status Quo and Future Trends

Cited by 14 publications

References 70 publications

Mining medicine prescriptions to enhance predictive management of COVID-19 patients in the UAE

Mining medicine prescriptions to enhance predictive management of COVID-19 patients in the UAE

ImAge: an imaging approach to quantitate aging and rejuvenation

Epigenetic clocks and female fertility timeline: A new approach to an old issue?

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