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Thalida Em Arpawong on Muck Rack

Thalida Em Arpawong

As seen in: Nature, Wiley Online Library, Taylor & Francis Online, BioRxiv, medRxiv
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Articles

Assessing Metabolic Ageing via DNA Methylation Surrogate Markers: A Multicohort Study in Britain, Ireland and the USA

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By Kexin Xu, Belinda Hernandez, Thalida Em Arpawong, Stephane Camuzeaux
| Wiley Online Library Verified
1 Introduction With lifespan increasing faster than health span for the last two centuries, prolonging disease-free years has become a focus of ageing research (Garmany, Yamada, and Terzic 2021). Ageing, a time-dependent decline in physiological function and stress resistance, underlies most chronic diseases, including cancer, diabetes, neurodegeneration and cardiovascular disease (CVD) (Rutledge, Oh, and Wyss-Coray 2022; López-Otín et al. 2013).
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Development of a novel transcriptomic measure of aging: Transcriptomic Mortality-risk Age (TraMA)

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By Eric Klopack, Thalida Em Arpawong, Steve Cole, Gokul Seshadri
| medRxiv
The authors have declared no competing interest. Research reported in this study was supported by the National Institute on Aging of the National Institutes of Health under Award Numbers U01AG05849906, T32AG000037, R01AG060110 and P30AG017265. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
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Blood Omics Models for System-Specific Mortality Risk Estimation

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By Matias Fuentealba Verified, Thalida Em Arpawong, Kevin Schneider, Eileen M. Crimmins
| BioRxiv
Abstract Traditional blood-based aging clocks provide an estimate of a person's overall biological age. However, physiological systems and organs age at different rates in an individual, and anti-aging interventions often target specific physiological systems. Therefore, there is a growing need for methods capable of assessing biological age at the level of specific physiological systems.
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