Trending With Impact: PCBrainAge in the Context of Alzheimer’s Disease



August 2, 2022

Aging-US published this trending research paper as the cover for Volume 14, Issue 14, entitled, "Aging the brain: multi-region methylation principal component based clock in the context of Alzheimer’s disease" by researchers from Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT; Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL; Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, CA; Department of Biostatistics, Fielding School of Public Health, UCLA, Los Angeles, CA; Department of Psychiatry, Yale University School of Medicine, New Haven, CT; Alzheimer’s Disease Research Center, Yale University School of Medicine, New Haven, CT; VA Connecticut Healthcare System, West Haven, CT; Department of Pathology, Yale University School of Medicine, New Haven, CT; Altos Labs, San Diego Institute of Science, San Diego, CA. DOI - Corresponding authors - Albert T. Higgins-Chen -, and Morgan E. Levine - Abstract Alzheimer’s disease (AD) risk increases exponentially with age and is associated with multiple molecular hallmarks of aging, one of which is epigenetic alterations. Epigenetic age predictors based on 5’ cytosine methylation (DNAm), or epigenetic clocks, have previously suggested that epigenetic age acceleration may occur in AD brain tissue. Epigenetic clocks are promising tools for the quantification of biological aging, yet we hypothesize that investigation of brain aging in AD will be assisted by the development of brain-specific epigenetic clocks. Therefore, we generated a novel age predictor termed PCBrainAge that was trained solely in cortical samples. This predictor utilizes a combination of principal components analysis and regularized regression, which reduces technical noise and greatly improves test-retest reliability. To characterize the scope of PCBrainAge’s utility, we generated DNAm data from multiple brain regions in a sample from the Religious Orders Study and Rush Memory and Aging Project. PCBrainAge captures meaningful heterogeneity of aging: Its acceleration demonstrates stronger associations with clinical AD dementia, pathologic AD, and APOE ε4 carrier status compared to extant epigenetic age predictors. It further does so across multiple cortical and subcortical regions. Overall, PCBrainAge’s increased reliability and specificity makes it a particularly promising tool for investigating heterogeneity in brain aging, as well as epigenetic alterations underlying AD risk and resilience. Sign up for free Altmetric alerts about this article - Press release - Keywords - aging, epigenetic clocks, unsupervised machine learning, brain, Alzheimer’s, age acceleration About Aging-US Launched in 2009, Aging-US publishes papers of general interest and biological significance in all fields of aging research and age-related diseases, including cancer—and now, with a special focus on COVID-19 vulnerability as an age-dependent syndrome. Topics in Aging-US go beyond traditional gerontology, including, but not limited to, cellular and molecular biology, human age-related diseases, pathology in model organisms, signal transduction pathways (e.g., p53, sirtuins, and PI-3K/AKT/mTOR, among others), and approaches to modulating these signaling pathways. Please visit our website at​​ and connect with us: SoundCloud - Facebook - Twitter - Instagram - YouTube -​ LinkedIn - Pinterest - Media Contact 18009220957 MEDIA@IMPACTJOURNALS.COM

Analytical TechniquesDiagnosticsMolecular BiologyNeuroscience

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