轻度认知障碍和阿尔茨海默病的纵向加速脑年龄。

IF 4.1 2区 医学 Q2 GERIATRICS & GERONTOLOGY Frontiers in Aging Neuroscience Pub Date : 2024-10-22 eCollection Date: 2024-01-01 DOI:10.3389/fnagi.2024.1433426
Maria Ly, Gary Yu, Sang Joon Son, Tharick Pascoal, Helmet T Karim
{"title":"轻度认知障碍和阿尔茨海默病的纵向加速脑年龄。","authors":"Maria Ly, Gary Yu, Sang Joon Son, Tharick Pascoal, Helmet T Karim","doi":"10.3389/fnagi.2024.1433426","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Brain age is a machine learning-derived estimate that captures lower brain volume. Previous studies have found that brain age is significantly higher in mild cognitive impairment and Alzheimer's disease (AD) compared to healthy controls. Few studies have investigated changes in brain age longitudinally in MCI and AD. We hypothesized that individuals with MCI and AD would show heightened brain age over time and across the lifespan. We also hypothesized that both MCI and AD would show faster rates of brain aging (higher slopes) over time compared to healthy controls.</p><p><strong>Methods: </strong>We utilized data from an archival dataset, mainly Alzheimer's disease Neuroimaging Initiative (ADNI) 1 with 3Tesla (3 T) data which totaled 677 scans from 183 participants. This constitutes a secondary data analysis on existing data. We included control participants (healthy controls or HC), individuals with MCI, and individuals with AD. We predicted brain age using a pre-trained model and tested for accuracy. We investigated cross-sectional differences in brain age by group [healthy controls or HC, mild cognitive impairment (MCI), and AD]. We conducted longitudinal modeling of age and brain age by group using time from baseline in one model and chronological age in another model.</p><p><strong>Results: </strong>We predicted brain age with a mean absolute error (MAE) < 5 years. Brain age was associated with age across the study and individuals with MCI and AD had greater brain age on average. We found that the MCI group had significantly higher rates of change in brain age over time compared to the HC group regardless of individual chronologic age, while the AD group did not differ in rate of brain age change.</p><p><strong>Discussion: </strong>We replicated past studies that showed that MCI and AD had greater brain age than HC. We additionally found that this was true over time, both groups showed higher brain age longitudinally. Contrary to our hypothesis, we found that the MCI, but not the AD group, showed faster rates of brain aging. We essentially found that while the MCI group was actively experiencing faster rates of brain aging, the AD group may have already experienced this acceleration (as they show higher brain age). Individuals with MCI may experience higher rates of brain aging than AD and controls. AD may represent a homeostatic endpoint after significant neurodegeneration. Future work may focus on individuals with MCI as one potential therapeutic option is to alter rates of brain aging, which ultimately may slow cognitive decline in the long-term.</p>","PeriodicalId":12450,"journal":{"name":"Frontiers in Aging Neuroscience","volume":"16 ","pages":"1433426"},"PeriodicalIF":4.1000,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11534682/pdf/","citationCount":"0","resultStr":"{\"title\":\"Longitudinal accelerated brain age in mild cognitive impairment and Alzheimer's disease.\",\"authors\":\"Maria Ly, Gary Yu, Sang Joon Son, Tharick Pascoal, Helmet T Karim\",\"doi\":\"10.3389/fnagi.2024.1433426\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Brain age is a machine learning-derived estimate that captures lower brain volume. Previous studies have found that brain age is significantly higher in mild cognitive impairment and Alzheimer's disease (AD) compared to healthy controls. Few studies have investigated changes in brain age longitudinally in MCI and AD. We hypothesized that individuals with MCI and AD would show heightened brain age over time and across the lifespan. We also hypothesized that both MCI and AD would show faster rates of brain aging (higher slopes) over time compared to healthy controls.</p><p><strong>Methods: </strong>We utilized data from an archival dataset, mainly Alzheimer's disease Neuroimaging Initiative (ADNI) 1 with 3Tesla (3 T) data which totaled 677 scans from 183 participants. This constitutes a secondary data analysis on existing data. We included control participants (healthy controls or HC), individuals with MCI, and individuals with AD. We predicted brain age using a pre-trained model and tested for accuracy. We investigated cross-sectional differences in brain age by group [healthy controls or HC, mild cognitive impairment (MCI), and AD]. We conducted longitudinal modeling of age and brain age by group using time from baseline in one model and chronological age in another model.</p><p><strong>Results: </strong>We predicted brain age with a mean absolute error (MAE) < 5 years. Brain age was associated with age across the study and individuals with MCI and AD had greater brain age on average. We found that the MCI group had significantly higher rates of change in brain age over time compared to the HC group regardless of individual chronologic age, while the AD group did not differ in rate of brain age change.</p><p><strong>Discussion: </strong>We replicated past studies that showed that MCI and AD had greater brain age than HC. We additionally found that this was true over time, both groups showed higher brain age longitudinally. Contrary to our hypothesis, we found that the MCI, but not the AD group, showed faster rates of brain aging. We essentially found that while the MCI group was actively experiencing faster rates of brain aging, the AD group may have already experienced this acceleration (as they show higher brain age). Individuals with MCI may experience higher rates of brain aging than AD and controls. AD may represent a homeostatic endpoint after significant neurodegeneration. Future work may focus on individuals with MCI as one potential therapeutic option is to alter rates of brain aging, which ultimately may slow cognitive decline in the long-term.</p>\",\"PeriodicalId\":12450,\"journal\":{\"name\":\"Frontiers in Aging Neuroscience\",\"volume\":\"16 \",\"pages\":\"1433426\"},\"PeriodicalIF\":4.1000,\"publicationDate\":\"2024-10-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11534682/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers in Aging Neuroscience\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.3389/fnagi.2024.1433426\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"GERIATRICS & GERONTOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Aging Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fnagi.2024.1433426","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"GERIATRICS & GERONTOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

简介脑年龄是一种通过机器学习得出的估计值,可捕捉较低的脑容量。以往的研究发现,与健康对照组相比,轻度认知障碍和阿尔茨海默病(AD)患者的脑年龄明显偏高。很少有研究对 MCI 和 AD 患者的脑年龄变化进行纵向调查。我们假设 MCI 和 AD 患者的脑年龄会随着时间的推移和寿命的延长而增加。我们还假设,与健康对照组相比,随着时间的推移,MCI 和 AD 患者的大脑老化速度更快(斜率更高):我们利用了一个档案数据集的数据,主要是阿尔茨海默病神经成像倡议(ADNI)1的3特斯拉(3 T)数据,该数据集共有183名参与者的677次扫描。这是对现有数据的二次数据分析。我们纳入了对照组参与者(健康对照组或 HC)、MCI 患者和 AD 患者。我们使用预先训练好的模型预测大脑年龄,并测试其准确性。我们调查了各组(健康对照组或 HC、轻度认知障碍(MCI)和注意力缺失症)脑年龄的横断面差异。我们在一个模型中使用从基线算起的时间,在另一个模型中使用年代年龄,按组别对年龄和脑年龄进行了纵向建模:结果:我们以平均绝对误差(MAE)预测了脑年龄:我们重复了过去的研究,这些研究表明 MCI 和 AD 的脑龄大于 HC。此外,我们还发现,随着时间的推移,这一点也是正确的,两组人的脑年龄纵向都较高。与我们的假设相反,我们发现 MCI 组的大脑老化速度更快,而 AD 组则不然。我们基本上发现,虽然 MCI 组正在积极经历更快的大脑衰老速度,但注意力缺失症组可能已经经历了这种加速(因为他们显示出更高的大脑年龄)。与注意力缺失症患者和对照组相比,MCI 患者的大脑衰老速度可能更快。注意力缺失症可能是神经退化显著后的一个平衡终点。未来的工作可能会侧重于 MCI 患者,因为一个潜在的治疗方案是改变大脑的衰老速度,这最终可能会减缓认知能力的长期衰退。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Longitudinal accelerated brain age in mild cognitive impairment and Alzheimer's disease.

Introduction: Brain age is a machine learning-derived estimate that captures lower brain volume. Previous studies have found that brain age is significantly higher in mild cognitive impairment and Alzheimer's disease (AD) compared to healthy controls. Few studies have investigated changes in brain age longitudinally in MCI and AD. We hypothesized that individuals with MCI and AD would show heightened brain age over time and across the lifespan. We also hypothesized that both MCI and AD would show faster rates of brain aging (higher slopes) over time compared to healthy controls.

Methods: We utilized data from an archival dataset, mainly Alzheimer's disease Neuroimaging Initiative (ADNI) 1 with 3Tesla (3 T) data which totaled 677 scans from 183 participants. This constitutes a secondary data analysis on existing data. We included control participants (healthy controls or HC), individuals with MCI, and individuals with AD. We predicted brain age using a pre-trained model and tested for accuracy. We investigated cross-sectional differences in brain age by group [healthy controls or HC, mild cognitive impairment (MCI), and AD]. We conducted longitudinal modeling of age and brain age by group using time from baseline in one model and chronological age in another model.

Results: We predicted brain age with a mean absolute error (MAE) < 5 years. Brain age was associated with age across the study and individuals with MCI and AD had greater brain age on average. We found that the MCI group had significantly higher rates of change in brain age over time compared to the HC group regardless of individual chronologic age, while the AD group did not differ in rate of brain age change.

Discussion: We replicated past studies that showed that MCI and AD had greater brain age than HC. We additionally found that this was true over time, both groups showed higher brain age longitudinally. Contrary to our hypothesis, we found that the MCI, but not the AD group, showed faster rates of brain aging. We essentially found that while the MCI group was actively experiencing faster rates of brain aging, the AD group may have already experienced this acceleration (as they show higher brain age). Individuals with MCI may experience higher rates of brain aging than AD and controls. AD may represent a homeostatic endpoint after significant neurodegeneration. Future work may focus on individuals with MCI as one potential therapeutic option is to alter rates of brain aging, which ultimately may slow cognitive decline in the long-term.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Frontiers in Aging Neuroscience
Frontiers in Aging Neuroscience GERIATRICS & GERONTOLOGY-NEUROSCIENCES
CiteScore
6.30
自引率
8.30%
发文量
1426
期刊介绍: Frontiers in Aging Neuroscience is a leading journal in its field, publishing rigorously peer-reviewed research that advances our understanding of the mechanisms of Central Nervous System aging and age-related neural diseases. Specialty Chief Editor Thomas Wisniewski at the New York University School of Medicine is supported by an outstanding Editorial Board of international researchers. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, clinicians and the public worldwide.
期刊最新文献
Association between exercise habits in adolescence and old age and the risk of mild cognitive impairment: the Bunkyo health study. Effects of traditional Chinese exercises or their integration with medical treatments on cognitive impairment: a network meta-analysis based on randomized controlled trials. Efficacy of acupuncture in ameliorating anxiety in Parkinson's disease: a systematic review and meta-analysis with trial sequential analysis. Specific gut microbiome signatures predict the risk of acute ischemic stroke. The impact of body position on neurofluid dynamics: present insights and advancements in imaging.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1