{"title":"血浆蛋白质组学确定了大脑衰老的生物标志物和起伏变化。","authors":"Wei-Shi Liu, Jia You, Shi-Dong Chen, Yi Zhang, Jian-Feng Feng, Yu-Ming Xu, Jin-Tai Yu, Wei Cheng","doi":"10.1038/s43587-024-00753-6","DOIUrl":null,"url":null,"abstract":"Proteomics enables the characterization of brain aging biomarkers and discernment of changes during brain aging. We leveraged multimodal brain imaging data from 10,949 healthy adults to estimate brain age gap (BAG), an indicator of brain aging. Proteome-wide association analysis across 4,696 participants of 2,922 proteins identified 13 significantly associated with BAG, implicating stress, regeneration and inflammation. Brevican (BCAN) (β = −0.838, P = 2.63 × 10−10) and growth differentiation factor 15 (β = 0.825, P = 3.48 × 10−11) showed the most significant, and multiple, associations with dementia, stroke and movement functions. Dysregulation of BCAN affected multiple cortical and subcortical structures. Mendelian randomization supported the causal association between BCAN and BAG. We revealed undulating changes in the plasma proteome across brain aging, and profiled brain age-related change peaks at 57, 70 and 78 years, implicating distinct biological pathways during brain aging. Our findings revealed the plasma proteomic landscape of brain aging and pinpointed biomarkers for brain disorders. Using proteomics and imaging data from UK Biobank, the authors identified multiple circulating proteins associated with brain aging and discovered undulating age-related changes in the plasma proteome, with peaks occurring at 57, 70 and 78 years of age.","PeriodicalId":94150,"journal":{"name":"Nature aging","volume":"5 1","pages":"99-112"},"PeriodicalIF":17.0000,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Plasma proteomics identify biomarkers and undulating changes of brain aging\",\"authors\":\"Wei-Shi Liu, Jia You, Shi-Dong Chen, Yi Zhang, Jian-Feng Feng, Yu-Ming Xu, Jin-Tai Yu, Wei Cheng\",\"doi\":\"10.1038/s43587-024-00753-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Proteomics enables the characterization of brain aging biomarkers and discernment of changes during brain aging. We leveraged multimodal brain imaging data from 10,949 healthy adults to estimate brain age gap (BAG), an indicator of brain aging. Proteome-wide association analysis across 4,696 participants of 2,922 proteins identified 13 significantly associated with BAG, implicating stress, regeneration and inflammation. Brevican (BCAN) (β = −0.838, P = 2.63 × 10−10) and growth differentiation factor 15 (β = 0.825, P = 3.48 × 10−11) showed the most significant, and multiple, associations with dementia, stroke and movement functions. Dysregulation of BCAN affected multiple cortical and subcortical structures. Mendelian randomization supported the causal association between BCAN and BAG. We revealed undulating changes in the plasma proteome across brain aging, and profiled brain age-related change peaks at 57, 70 and 78 years, implicating distinct biological pathways during brain aging. Our findings revealed the plasma proteomic landscape of brain aging and pinpointed biomarkers for brain disorders. Using proteomics and imaging data from UK Biobank, the authors identified multiple circulating proteins associated with brain aging and discovered undulating age-related changes in the plasma proteome, with peaks occurring at 57, 70 and 78 years of age.\",\"PeriodicalId\":94150,\"journal\":{\"name\":\"Nature aging\",\"volume\":\"5 1\",\"pages\":\"99-112\"},\"PeriodicalIF\":17.0000,\"publicationDate\":\"2024-12-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature aging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.nature.com/articles/s43587-024-00753-6\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CELL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature aging","FirstCategoryId":"1085","ListUrlMain":"https://www.nature.com/articles/s43587-024-00753-6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
蛋白质组学能够表征脑老化生物标志物和识别脑老化过程中的变化。我们利用10949名健康成年人的多模态脑成像数据来估计脑年龄差距(BAG),这是脑衰老的一个指标。对4,696名参与者的2,922种蛋白质进行全蛋白质组关联分析,发现13种与BAG显著相关,涉及应激、再生和炎症。Brevican (BCAN) (β = -0.838, P = 2.63 × 10-10)和生长分化因子15 (β = 0.825, P = 3.48 × 10-11)与痴呆、脑卒中和运动功能的相关性最显著,且多重相关。BCAN的失调影响多个皮层和皮层下结构。孟德尔随机化支持BCAN和BAG之间的因果关系。我们揭示了血浆蛋白质组在大脑衰老过程中的波动变化,并描绘了与大脑年龄相关的变化在57岁、70岁和78岁时达到峰值,这暗示了大脑衰老过程中不同的生物学途径。我们的发现揭示了大脑衰老的血浆蛋白质组学图景,并确定了大脑疾病的生物标志物。
Plasma proteomics identify biomarkers and undulating changes of brain aging
Proteomics enables the characterization of brain aging biomarkers and discernment of changes during brain aging. We leveraged multimodal brain imaging data from 10,949 healthy adults to estimate brain age gap (BAG), an indicator of brain aging. Proteome-wide association analysis across 4,696 participants of 2,922 proteins identified 13 significantly associated with BAG, implicating stress, regeneration and inflammation. Brevican (BCAN) (β = −0.838, P = 2.63 × 10−10) and growth differentiation factor 15 (β = 0.825, P = 3.48 × 10−11) showed the most significant, and multiple, associations with dementia, stroke and movement functions. Dysregulation of BCAN affected multiple cortical and subcortical structures. Mendelian randomization supported the causal association between BCAN and BAG. We revealed undulating changes in the plasma proteome across brain aging, and profiled brain age-related change peaks at 57, 70 and 78 years, implicating distinct biological pathways during brain aging. Our findings revealed the plasma proteomic landscape of brain aging and pinpointed biomarkers for brain disorders. Using proteomics and imaging data from UK Biobank, the authors identified multiple circulating proteins associated with brain aging and discovered undulating age-related changes in the plasma proteome, with peaks occurring at 57, 70 and 78 years of age.