{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T03:09:32Z","timestamp":1793502572459,"version":"4.5.0"},"reference-count":51,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100016958","name":"Office of Research Infrastructure Programs, National Institutes of Health","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100016958","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Aging Neurosci."],"abstract":"<jats:p>Aging is a major risk factor for late-onset Alzheimer\u2019s disease (LOAD). How aging contributes to the development of LOAD remains elusive. In this study, we examined multiple large-scale transcriptomic datasets from both normal aging and LOAD brains to understand the molecular interconnection between aging and LOAD. We found that shared gene expression changes between aging and LOAD are mostly seen in the hippocampal and several cortical regions. In the hippocampus, the expression of phosphoprotein, alternative splicing and cytoskeleton genes are commonly changed in both aging and AD, while synapse, ion transport, and synaptic vesicle genes are commonly down-regulated. Aging-specific changes are associated with acetylation and methylation, while LOAD-specific changes are more related to glycoprotein (both up- and down-regulations), inflammatory response (up-regulation), myelin sheath and lipoprotein (down-regulation). We also found that normal aging brain transcriptomes from relatively young donors (45\u201370 years old) clustered into several subgroups and some subgroups showed gene expression changes highly similar to those seen in LOAD brains. Using brain transcriptomic datasets from another cohort of older individuals (&amp;gt;70 years), we found that samples from cognitively normal older individuals clustered with the \u201chealthy aging\u201d subgroup while AD samples mainly clustered with the \u201cAD similar\u201d subgroups. This may imply that individuals in the healthy aging subgroup will likely remain cognitively normal when they become older and vice versa. In summary, our results suggest that on the transcriptome level, aging and LOAD have strong interconnections in some brain regions in a subpopulation of cognitively normal aging individuals. This supports the theory that the initiation of LOAD occurs decades earlier than the manifestation of clinical phenotype and it may be essential to closely study the \u201cnormal brain aging\u201d to identify the very early molecular events that may lead to LOAD development.<\/jats:p>","DOI":"10.3389\/fnagi.2021.711524","type":"journal-article","created":{"date-parts":[[2021,12,2]],"date-time":"2021-12-02T07:21:56Z","timestamp":1638429716000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":27,"title":["Transcriptomic Changes Highly Similar to Alzheimer\u2019s Disease Are Observed in a Subpopulation of Individuals During Normal Brain Aging"],"prefix":"10.3389","volume":"13","author":[{"given":"Shouneng","family":"Peng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lu","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jean-Vianney","family":"Haure-Mirande","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Minghui","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Derek M.","family":"Huffman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vahram","family":"Haroutunian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michelle E.","family":"Ehrlich","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhidong","family":"Tu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2021,12,1]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"327","DOI":"10.1002\/alz.12328","article-title":"2021 Alzheimer\u2019s disease facts and figures.","volume":"17","year":"2021","journal-title":"Alzheimers Dement."},{"key":"B2","doi-asserted-by":"publisher","first-page":"4282","DOI":"10.1038\/s41598-018-22701-2","article-title":"Whole transcriptome profiling of Late-Onset Alzheimer\u2019s disease patients provides insights into the molecular changes involved in the disease.","volume":"8","author":"Annese","year":"2018","journal-title":"Sci. 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