A neuroimaging biomarker for Individual Brain-Related Abnormalities In Neurodegeneration (IBRAIN): a cross-sectional study.
A neuroimaging biomarker for Individual Brain-Related Abnormalities In Neurodegeneration (IBRAIN): a cross-sectional study.
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DOI：
10.1016/j.eclinm.2023.102276
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发表时间：
2023-11
影响因子：
15.1
通讯作者：
Liu, Yong
中科院分区：
文献类型：
--
作者：
Zhao, Kun;Chen, Pindong;Alexander-Bloch, Aaron;Wei, Yongbin;Dyrba, Martin;Yang, Fan;Kang, Xiaopeng;Wang, Dawei;Fan, Dongsheng;Ye, Shan;Tang, Yi;Yao, Hongxiang;Zhou, Bo;Lu, Jie;Yu, Chunshui;Wang, Pan;Liao, Zhengluan;Chen, Yan;Huang, Longjian;Zhang, Xi;Han, Ying;Li, Shuyu;Liu, Yong
阿尔茨海默病(AD)是一种普遍存在的神经退行性疾病，对全球公共卫生构成挑战。神经成像生物标记物将显著改善早期诊断和干预，最终提高受影响个人的生活质量，并减轻医疗系统的负担。本研究使用了来自12个独立数据集的横断面和纵向数据(10,099名参与者，13,380次扫描)(该研究在2021年9月1日至2023年2月15日之间进行)。个体脑相关神经变性异常(IBrain)评分是在基于结构性MRI数据的集成机器学习模型下，通过基于区域和网络的综合措施制定的。我们系统地评估了iBrain是否可以作为AD的神经成像生物标记物。IBrain准确地将AD患者与NCS(AUC=0.92)和其他神经退行性疾病区分开来，包括额颞部痴呆(FTD)、帕金森病(PD)、血管性痴呆(VAD)和肌萎缩侧索硬化症(ALS)(AUC=60.92)。IBrain与临床指标和基因表达显著相关，在免疫过程和蛋白质代谢中丰富。IBrain评分对前驱AD(即轻度认知功能障碍)的进展有显著的预测作用(危险比=66.52[95%CI：4.42∼9.62]，p<0.05)；1×10−16)，与脑脊液Aβ(HR=33.78[95%CI：2.63∼5.43]，p=92.13×10−14)和脑脊液Tau(HR=377[95%CI：2.64∼5.39]，p=95.53[95%CI：2.63∼5.39]，p=95.53[95%CI：2.64−5.39])相似。值得注意的是，iBrain在捕捉转换为AD的个人的纵向变化方面表现出类似的敏感度(Beta=−0.70，p<sup<；p<sup>1×10</sup>−16)与csf Aβ(p<sup>−</sup>=0.26<sup>−</sup>)和csf Tau(p<sup>0</sup>=0<sup>−</sup>−9)和csf Tau(p<sup>0</sup>=0·12，p<sup>10</sup>−5)。我们的发现表明，iBrain是一种生物学上相关的、特异的、敏感的神经成像生物标志物，可以作为一种临床手段来揭示先兆AD的进展。它在未来的临床实践和治疗试验中具有很强的应用潜力。、和人才创业基金。
Alzheimer's disease (AD) is a prevalent neurodegenerative disorder that poses a worldwide public health challenge. A neuroimaging biomarker would significantly improve early diagnosis and intervention, ultimately enhancing the quality of life for affected individuals and reducing the burden on healthcare systems. Cross-sectional and longitudinal data (10,099 participants with 13,380 scans) from 12 independent datasets were used in the present study (this study was performed between September 1, 2021 and February 15, 2023). The Individual Brain-Related Abnormalities In Neurodegeneration (IBRAIN) score was developed via integrated regional- and network-based measures under an ensemble machine learning model based on structural MRI data. We systematically assessed whether IBRAIN could be a neuroimaging biomarker for AD. IBRAIN accurately differentiated individuals with AD from NCs (AUC = 0.92) and other neurodegenerative diseases, including Frontotemporal dementia (FTD), Parkinson's disease (PD), Vascular dementia (VaD) and Amyotrophic Lateral Sclerosis (ALS) (AUC = 0.92). IBRAIN was significantly correlated to clinical measures and gene expression, enriched in immune process and protein metabolism. The IBRAIN score exhibited a significant ability to reveal the distinct progression of prodromal AD (i.e., Mild cognitive impairment, MCI) (Hazard Ratio (HR) = 6.52 [95% CI: 4.42∼9.62], p < 1 × 10−16), which offers similar powerful performance with Cerebrospinal Fluid (CSF) Aβ (HR = 3.78 [95% CI: 2.63∼5.43], p = 2.13 × 10−14) and CSF Tau (HR = 3.77 [95% CI: 2.64∼5.39], p = 9.53 × 10−15) based on the COX and Log-rank test. Notably, the IBRAIN shows comparable sensitivity (beta = −0.70, p < 1 × 10−16) in capturing longitudinal changes in individuals with conversion to AD than CSF Aβ (beta = −0.26, p = 4.40 × 10−9) and CSF Tau (beta = 0.12, p = 1.02 × 10−5). Our findings suggested that IBRAIN is a biologically relevant, specific, and sensitive neuroimaging biomarker that can serve as a clinical measure to uncover prodromal AD progression. It has strong potential for application in future clinical practice and treatment trials. , the , , the for the , and the Startup Funds for Talents at .
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影响因子：
16.6
作者：
Jones D;Lowe V;Graff-Radford J;Botha H;Barnard L;Wiepert D;Murphy MC;Murray M;Senjem M;Gunter J;Wiste H;Boeve B;Knopman D;Petersen R;Jack C
通讯作者：
Jack C
人脑网络组图谱：基于连接架构的新大脑图谱
DOI：
10.1093/cercor/bhw157
发表时间：
2016-08
期刊：
Cerebral cortex (New York, N.Y. : 1991)
影响因子：
--
作者：
Fan L;Li H;Zhuo J;Zhang Y;Wang J;Chen L;Yang Z;Chu C;Xie S;Laird AR;Fox PT;Eickhoff SB;Yu C;Jiang T
通讯作者：
Jiang T
影响因子：
64.8
作者：
Marek S;Tervo-Clemmens B;Calabro FJ;Montez DF;Kay BP;Hatoum AS;Donohue MR;Foran W;Miller RL;Hendrickson TJ;Malone SM;Kandala S;Feczko E;Miranda-Dominguez O;Graham AM;Earl EA;Perrone AJ;Cordova M;Doyle O;Moore LA;Conan GM;Uriarte J;Snider K;Lynch BJ;Wilgenbusch JC;Pengo T;Tam A;Chen J;Newbold DJ;Zheng A;Seider NA;Van AN;Metoki A;Chauvin RJ;Laumann TO;Greene DJ;Petersen SE;Garavan H;Thompson WK;Nichols TE;Yeo BTT;Barch DM;Luna B;Fair DA;Dosenbach NUF
通讯作者：
Dosenbach NUF
DOI：
10.1109/tpami.2018.2889096
发表时间：
2020-04-01
影响因子：
23.6
作者：
Lian, Chunfeng;Liu, Mingxia;Shen, Dinggang
通讯作者：
Shen, Dinggang
DOI：
10.1038/s43587-020-00003-5
发表时间：
2021-01-01
期刊：
NATURE AGING
影响因子：
--
作者：
Cullen, Nicholas C.;Leuzy, Antoine;Hansson, Oskar
通讯作者：
Hansson, Oskar