Longevity & Aging Series (S2, E1): Dr. Irina Conboy and Serafina Mei | Aging-US
Channel: Aging (Aging-US)
Date: 22/04/2024

In the season 2 premiere episode of the Longevity & Aging Series, Dr. Irina Conboy and Xiaoyue (Serafina) Mei from the Department of Bioengineering and QB3 at the University of California, Berkeley, discuss a priority research paper they co-authored that was published in Volume 15, Issue 17, of Aging (Aging-US), entitled, “Fail-tests of DNA methylation clocks, and development of a noise barometer for measuring epigenetic pressure of aging and disease.” @BerkeleyNews 
#aging #longevity #webinar #authorinterview #interview #presentation #dnamethylation #epigenetics #dna #research #researchpaper #openaccess #openscience #peerreview #journal #publication #publishing

DOI - https://doi.org/10.18632/aging.205046

Corresponding Author - Irina M. Conboy - iconboy@berkeley.edu

Video transcript - https://aging-us.net/2024/04/22/longevity-aging-series-s2-e1-dr-irina-conboy-and-xiaoyue-serafina-mei/

Abstract

This study shows that Elastic Net (EN) DNA methylation (DNAme) clocks have low accuracy of predictions for individuals of the same age and a low resolution between healthy and disease cohorts; caveats inherent in applying linear model to non-linear processes. We found that change in methylation of cytosines with age is, interestingly, not the determinant for their selection into the clocks. Moreover, an EN clock’s selected cytosines change when non-clock cytosines are removed from the training data; as expected from optimization in a machine learning (ML) context, but inconsistently with the identification of health markers in a biological context. To address these limitations, we moved from predictions to measurement of biological age, focusing on the cytosines that on average remain invariable in their methylation through lifespan, postulated to be homeostatically vital. We established that dysregulation of such cytosines, measured as the sums of standard deviations of their methylation values, quantifies biological noise, which in our hypothesis is a biomarker of aging and disease. We term this approach a “noise barometer” - the pressure of aging and disease on an organism. These noise-detecting cytosines are particularly important as sums of SD on the entire 450K DNAme array data yield a random pattern through chronology. Testing how many cytosines of the 450K arrays become noisier with age, we found that the paradigm of DNAme noise as a biomarker of aging and disease remarkably manifests in ~1/4 of the total. In that large set even the cytosines that have on average constant methylation through age show increased SDs and can be used as noise detectors of the barometer.

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Keywords - aging, DNA methylation, epigenetics, clocks’ fail-test, biological noise

About Longevity & Aging Series

In its second season, the Longevity & Aging Series is a video series that features esteemed researchers discussing the latest in aging research with a focus on their studies published by Aging (Aging-US).

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Aging publishes research papers in all fields of aging research including but not limited, aging from yeast to mammals, cellular senescence, age-related diseases such as cancer and Alzheimer’s diseases and their prevention and treatment, anti-aging strategies and drug development and especially the role of signal transduction pathways such as mTOR in aging and potential approaches to modulate these signaling pathways to extend lifespan. The journal aims to promote treatment of age-related diseases by slowing down aging, validation of anti-aging drugs by treating age-related diseases, prevention of cancer by inhibiting aging. Cancer and COVID-19 are age-related diseases.

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