{"title":"通过单核转录组学分析确定健康大脑衰老的临界点。","authors":"Peiru Wu, Xuyu Zhao, Zixin Chen, Jingying Huang, Tengteng Dai, Jianxin Zhou, Luyao Xiao, Luonan Chen, Robert Chunhua Zhao, Jiao Wang","doi":"10.1002/advs.202505779","DOIUrl":null,"url":null,"abstract":"<p><p>Brain aging significantly impairs cognitive and behavioral functions. While some nonlinear aging studies have identified age-specific aging peaks at certain ages, the influence of different cell types on brain aging fluctuations across the lifespan remains unclear. This study, approaching from the interdisciplinary perspective of brain aging and systems dynamics, extends the nonlinear aging analysis to the cellular level, using single-cell transcriptomic data to analyze 45 healthy elderly brain samples aged 29-94 years. Describing cellular and molecular differences in the aging process, neuron proportion is downregulated but relatively stable with low variability after aging, while glial cells are significantly upregulated and highly unstable. Notably, peaks in nonlinear molecular fluctuations are observed in aging at ages 60, 70, and 79. The nonlinear features prompted the introduction of a dynamic network biomarker and the identification of 56-60 years as the tipping point in the brain's healthy aging process, then suggesting that glia predominantly mediate this process and exploring the underlying features and mechanisms. This work investigates the tipping point of aging at single-cell resolution and provides new research strategies for early diagnosis and intervention of aging-related neurological diseases.</p>","PeriodicalId":117,"journal":{"name":"Advanced Science","volume":" ","pages":"e05779"},"PeriodicalIF":14.1000,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identifying Tipping Points during Healthy Brain Aging through Single-Nucleus Transcriptomic Analysis.\",\"authors\":\"Peiru Wu, Xuyu Zhao, Zixin Chen, Jingying Huang, Tengteng Dai, Jianxin Zhou, Luyao Xiao, Luonan Chen, Robert Chunhua Zhao, Jiao Wang\",\"doi\":\"10.1002/advs.202505779\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Brain aging significantly impairs cognitive and behavioral functions. While some nonlinear aging studies have identified age-specific aging peaks at certain ages, the influence of different cell types on brain aging fluctuations across the lifespan remains unclear. This study, approaching from the interdisciplinary perspective of brain aging and systems dynamics, extends the nonlinear aging analysis to the cellular level, using single-cell transcriptomic data to analyze 45 healthy elderly brain samples aged 29-94 years. Describing cellular and molecular differences in the aging process, neuron proportion is downregulated but relatively stable with low variability after aging, while glial cells are significantly upregulated and highly unstable. Notably, peaks in nonlinear molecular fluctuations are observed in aging at ages 60, 70, and 79. The nonlinear features prompted the introduction of a dynamic network biomarker and the identification of 56-60 years as the tipping point in the brain's healthy aging process, then suggesting that glia predominantly mediate this process and exploring the underlying features and mechanisms. This work investigates the tipping point of aging at single-cell resolution and provides new research strategies for early diagnosis and intervention of aging-related neurological diseases.</p>\",\"PeriodicalId\":117,\"journal\":{\"name\":\"Advanced Science\",\"volume\":\" \",\"pages\":\"e05779\"},\"PeriodicalIF\":14.1000,\"publicationDate\":\"2025-08-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advanced Science\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.1002/advs.202505779\",\"RegionNum\":1,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Science","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1002/advs.202505779","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Identifying Tipping Points during Healthy Brain Aging through Single-Nucleus Transcriptomic Analysis.
Brain aging significantly impairs cognitive and behavioral functions. While some nonlinear aging studies have identified age-specific aging peaks at certain ages, the influence of different cell types on brain aging fluctuations across the lifespan remains unclear. This study, approaching from the interdisciplinary perspective of brain aging and systems dynamics, extends the nonlinear aging analysis to the cellular level, using single-cell transcriptomic data to analyze 45 healthy elderly brain samples aged 29-94 years. Describing cellular and molecular differences in the aging process, neuron proportion is downregulated but relatively stable with low variability after aging, while glial cells are significantly upregulated and highly unstable. Notably, peaks in nonlinear molecular fluctuations are observed in aging at ages 60, 70, and 79. The nonlinear features prompted the introduction of a dynamic network biomarker and the identification of 56-60 years as the tipping point in the brain's healthy aging process, then suggesting that glia predominantly mediate this process and exploring the underlying features and mechanisms. This work investigates the tipping point of aging at single-cell resolution and provides new research strategies for early diagnosis and intervention of aging-related neurological diseases.
期刊介绍:
Advanced Science is a prestigious open access journal that focuses on interdisciplinary research in materials science, physics, chemistry, medical and life sciences, and engineering. The journal aims to promote cutting-edge research by employing a rigorous and impartial review process. It is committed to presenting research articles with the highest quality production standards, ensuring maximum accessibility of top scientific findings. With its vibrant and innovative publication platform, Advanced Science seeks to revolutionize the dissemination and organization of scientific knowledge.