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巴西老年人群样本中与年龄相关的DNA甲基化变化。

Age-related changes in DNA methylation in a sample of elderly Brazilians.

作者信息

Welsh Hayley, Batalha Caio M P F, Li Weili, Souza-Pinto Nadja C, Duarte Yeda A O, Naslavsky Michel S, Parra Esteban J

机构信息

Department of Anthropology, University of Toronto at Mississauga, Mississauga, Canada.

Department of Biochemistry, University of São Paulo, São Paulo, Brazil.

出版信息

Clin Epigenetics. 2025 Feb 5;17(1):17. doi: 10.1186/s13148-025-01821-3.


DOI:10.1186/s13148-025-01821-3
PMID:39910411
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11796210/
Abstract

BACKGROUND: Age-related changes in DNA methylation (DNAm) play a critical role in regulating gene expression. However, most epigenome-wide association studies have predominantly focused on individuals of European descent. This study aims to characterize longitudinal changes in DNAm patterns in a cohort of elderly Brazilian participants. METHODS: DNAm profiles were collected approximately nine years apart from 23 elderly Brazilian individuals using the Illumina Infinium MethyationEPIC BeadChip. Using mixed-effects models, we examined changes in DNAm patterns using both quantitative age and binary timepoint (e.g., baseline vs. follow-up) as predictors of interest to identify differentially methylated positions (DMPs). Significant DMPs were compared with a list of previously identified age-related DMPs. Differentially methylated regions (DMRs) were also identified using DMRcate. Gene ontology (GO) pathway enrichment analyses were performed to explore the functional significance of identified DMPs and DMRs. RESULTS: Of the 586,229 autosomal probes included in the differential methylation analyses, 2768 significant (FDR < 0.05) age-associated DMPs (aDMPs) and 2757 significant (FDR < 0.05) timepoint-associated DMPs (tpDMPs) were identified. Of the 2768 aDMPs, 1471 were replicated from previous studies. Of the 1297 non-replicated CpGs, 77.4% were exclusive to the EPIC array. The DMR analyses identified 305 age-associated DMRs (aDMRs) and 372 timepoint-associated DMRs (tpDMRs). Both aDMPs and aDMRs exhibited age-related hypermethylation within CpG islands and promoter regions of the genome, whereas hypomethylation predominantly occurred in interCGI and intergenic regions and introns. The GO enrichment analyses identified several neurological and cognition-related pathways enriched for hypermethylated CpG islands, many of which were mapped near transcription start sites and first exon regions. CONCLUSIONS: This longitudinal study identified age-associated and timepoint-associated DMPs and DMRs in a sample of elderly Brazilians. Most of the non-replicated CpGs were found to be on the new EPIC array, suggesting that more age-related studies using the EPIC array are required to validate these CpGs. The GO pathway enrichment analyses identified age-related enrichment of several gene sets related to cognitive and physical decline in elderly populations. The enrichment of these sites could provide evidence for age-related neurodegeneration and cognitive decline in elderly populations.

摘要

背景:DNA甲基化(DNAm)的年龄相关变化在调节基因表达中起关键作用。然而,大多数全表观基因组关联研究主要集中在欧洲血统的个体上。本研究旨在描述一组巴西老年参与者DNAm模式的纵向变化。 方法:使用Illumina Infinium MethyationEPIC BeadChip对23名巴西老年个体相隔约九年收集DNAm谱。使用混合效应模型,我们以定量年龄和二元时间点(例如,基线与随访)作为感兴趣的预测因子来检查DNAm模式的变化,以识别差异甲基化位点(DMP)。将显著的DMP与先前确定的与年龄相关的DMP列表进行比较。还使用DMRcate识别差异甲基化区域(DMR)。进行基因本体(GO)通路富集分析以探索已识别的DMP和DMR的功能意义。 结果:在差异甲基化分析中包含的586,229个常染色体探针中,识别出2768个显著(FDR < 0.05)的与年龄相关的DMP(aDMP)和2757个显著(FDR < 0.05)的与时间点相关的DMP(tpDMP)。在2768个aDMP中,1471个是从先前研究中复制而来的。在1297个未复制的CpG中,77.4%是EPIC阵列特有的。DMR分析识别出305个与年龄相关的DMR(aDMR)和372个与时间点相关的DMR(tpDMR)。aDMP和aDMR在基因组的CpG岛和启动子区域内均表现出与年龄相关的高甲基化,而低甲基化主要发生在CpG岛间和基因间区域以及内含子中。GO富集分析识别出几个神经学和认知相关通路在高甲基化的CpG岛中富集,其中许多位于转录起始位点和第一外显子区域附近。 结论:这项纵向研究在一组巴西老年人样本中识别出与年龄相关和与时间点相关的DMP和DMR。发现大多数未复制的CpG位于新的EPIC阵列上,这表明需要更多使用EPIC阵列的与年龄相关的研究来验证这些CpG。GO通路富集分析识别出与老年人群认知和身体衰退相关的几个基因集的年龄相关富集。这些位点的富集可为老年人群中与年龄相关的神经退行性变和认知衰退提供证据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1c0/11796210/4d367396c2a5/13148_2025_1821_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1c0/11796210/ef1fbc1d9b9b/13148_2025_1821_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1c0/11796210/4d367396c2a5/13148_2025_1821_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1c0/11796210/ef1fbc1d9b9b/13148_2025_1821_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1c0/11796210/4d367396c2a5/13148_2025_1821_Fig2_HTML.jpg

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本文引用的文献

[1]
Characterizing hedgehog pathway features in senescence associated osteoarthritis through Integrative multi-omics and machine learning analysis.

Front Genet. 2024-2-20

[2]
Longitudinal changes and variation in human DNA methylation analysed with the Illumina MethylationEPIC BeadChip assay and their implications on forensic age prediction.

Sci Rep. 2023-12-8

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Integrative Approaches of DNA Methylation Patterns According to Age, Sex and Longitudinal Changes.

Curr Genomics. 2023-2-14

[4]
A systematic evaluation of normalization methods and probe replicability using infinium EPIC methylation data.

Clin Epigenetics. 2023-3-11

[5]
Local CpG density affects the trajectory and variance of age-associated DNA methylation changes.

Genome Biol. 2022-10-17

[6]
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Genome Med. 2022-7-6

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Mech Ageing Dev. 2022-9

[8]
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Nat Genet. 2022-6

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Whole-genome sequencing of 1,171 elderly admixed individuals from São Paulo, Brazil.

Nat Commun. 2022-3-4

[10]
Longitudinal DNA methylation dynamics as a practical indicator in clinical epigenetics.

Clin Epigenetics. 2021-12-13

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