Background: Late-onset Alzheimer's disease (AD) is a complex multifactorial affliction, the pathogenesis of which is thought to involve gene-environment interactions that might be captured in the epigenome. The present study investigated epigenome-wide patterns of DNA methylation (5-methylcytosine, 5mC) and hydroxymethylation (5-hydroxymethylcytosine, 5hmC), as well as the abundance of unmodified cytosine (UC), in relation to AD.
Results: We identified epigenetic differences in AD patients (n = 45) as compared to age-matched controls (n = 35) in the middle temporal gyrus, pertaining to genomic regions close to or overlapping with genes such as OXT (- 3.76% 5mC, p = 1.07E-06), CHRNB1 (+ 1.46% 5hmC, p = 4.01E-04), RHBDF2 (- 3.45% UC, p = 4.85E-06), and C3 (- 1.20% UC, p = 1.57E-03). In parallel, in an independent cohort, we compared the blood methylome of converters to AD dementia (n = 54) and non-converters (n = 42), at a preclinical stage. DNA methylation in the same region of the OXT promoter as found in the brain was found to be associated with subsequent conversion to AD dementia in the blood of elderly, non-demented individuals (+ 3.43% 5mC, p = 7.14E-04).
Conclusions: The implication of genome-wide significant differential methylation of OXT, encoding oxytocin, in two independent cohorts indicates it is a promising target for future studies on early biomarkers and novel therapeutic strategies in AD.
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http://dx.doi.org/10.1186/s13148-019-0755-5 | DOI Listing |
Aging (Albany NY)
January 2025
Department of Public Health Sciences, University of Chicago, Chicago, IL 60615, USA.
Background: DNA methylation (DNAm) data from human samples has been leveraged to develop "epigenetic clock" algorithms that predict age and other aging-related phenotypes. Some DNAm clocks were trained using DNAm obtained from blood cells, while other clocks were trained using data from diverse tissue/cell types. To assess how DNAm clocks perform across non-blood tissue types, we applied DNAm algorithms to DNAm data generated from 9 different human tissue types.
View Article and Find Full Text PDFBMC Mol Cell Biol
January 2025
Epigenetics Programme, Babraham Institute, Cambridge, CB22 3AT, UK.
Background: During the latter stages of their development, mammalian oocytes under dramatic chromatin reconfiguration, transitioning from a non-surrounded nucleolus (NSN) to a surrounded nucleolus (SN) stage, and concomitant transcriptional silencing. Although the NSN-SN transition is known to be essential for developmental competence of the oocyte, less is known about the accompanying molecular changes. Here we examine the changes in the transcriptome and DNA methylation during the NSN to SN transition in mouse oocytes.
View Article and Find Full Text PDFMol Psychiatry
January 2025
Institute of Biomedicine, Integrative Physiology and Pharmacology Unit, University of Turku, Turku, Finland.
Childhood maltreatment exposure (CME) increases the risk of adverse long-term health consequences for the exposed individual. Animal studies suggest that CME may also influence the health and behaviour in the next generation offspring through CME-driven epigenetic changes in the germ line. Here we investigated the associated between early life stress on the epigenome of sperm in humans with history of CME.
View Article and Find Full Text PDFSci Rep
January 2025
Jiangxi Key Laboratory of Molecular Medicine, Jiangxi Medical College, The Second Affiliated Hospital of Nanchang University, Nanchang University, Nanchang, 330006, China.
SMAD3, a protein-coding gene, assumes a pivotal role within the transforming growth factor-beta (TGF-β) signaling pathway. Notably, aberrant SMAD3 expression has been linked to various malignancies. Nevertheless, an extensive examination of the comprehensive pan-cancer impact on SMAD3's diagnostic, prognostic, and immunological predictive utility has yet to be undertaken.
View Article and Find Full Text PDFNat Commun
January 2025
Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
We have developed the regionalpcs method, an approach for summarizing gene-level methylation. regionalpcs addresses the challenge of deciphering complex epigenetic mechanisms in diseases like Alzheimer's disease. In contrast to averaging, regionalpcs uses principal components analysis to capture complex methylation patterns across gene regions.
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