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. 2023 Jul 26;45(6):3187–3209. doi: 10.1007/s11357-023-00878-3

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© The Author(s) 2023

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 4 — Gene set enrichment analysis of aging effects in primates. The genome region based enrichment analysis was carried using GREAT [25] where the statistical background was defined by the probes on the mammalian methylation array in Hg19 assembly. The CpGs are annotated with adjacent genes with gene regulation domain: 5.0 kb upstream, 1.0 kb downstream, plus Distal: up to 50 kb. We extracted up to top 500 CpGs based on p value of association per direction of change as input for the enrichment analysis. The p values are calculated by genomic region based hypergeometric test with the following ontologies: gene ontology, mouse phenotypes, promoter motifs, and MsigDB Perturbation, which includes the expression signatures of genetic perturbations curated in GSEA database. The results were filtered for significance at p < 10^–5 and only the top terms for each EWAS are reported