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DOI	10.1016/j.neurobiolaging.2022.06.008
	Predicting future cognitive decline from non-brain and multimodal brain imaging data in healthy and pathological aging
	Vieira, Bruno Hebling; Liem, Franziskus; Dadi, Kamalaker; Engemann, Denis A.; Gramfort, Alexandre; Bellec, Pierre; Craddock, Richard Cameron; Damoiseaux, Jessica S.; Steele, Christopher J.; Yarkoni, Tal; Langer, Nicolas; Margulies, Daniel S.; Varoquaux, Gael
通讯作者	Vieira, BH
来源期刊	NEUROBIOLOGY OF AGING
ISSN	0197-4580
EISSN	1558-1497
出版年	2022
卷号	118 页码:55-65
英文摘要	Previous literature has focused on predicting a diagnostic label from structural brain imaging. Since subtle changes in the brain precede a cognitive decline in healthy and pathological aging, our study predicts fu-ture decline as a continuous trajectory instead. Here, we tested whether baseline multimodal neuroimag-ing data improve the prediction of future cognitive decline in healthy and pathological aging. Nonbrain data (demographics, clinical, and neuropsychological scores), structural MRI, and functional connectivity data from OASIS-3 (N = 662; age = 46-96 years) were entered into cross-validated multitarget random forest models to predict future cognitive decline (measured by CDR and MMSE), on average 5.8 years into the future. The analysis was preregistered, and all analysis code is publicly available. Combining non-brain with structural data improved the continuous prediction of future cognitive decline (best test -set performance: R2 = 0.42). Cognitive performance, daily functioning, and subcortical volume drove the performance of our model. Including functional connectivity did not improve predictive accuracy. In the future, the prognosis of age-related cognitive decline may enable earlier and more effective individualized cognitive, pharmacological, and behavioral interventions. (c) 2022 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )
英文关键词	Biomarker Machine learning Predictive modeling Open science Cross-validation
类型	Article
语种	英语
开放获取类型	Green Submitted, hybrid, Green Published, Green Accepted
收录类别	SCI-E
WOS记录号	WOS:000874880700001
WOS关键词	DATA SET UDS ; ALZHEIMERS-DISEASE ; CLASSIFICATION ; BIOMARKERS ; HIPPOCAMPUS ; VALIDATION ; REGRESSION ; DEMENTIA ; CAPTURES ; SCORES
WOS类目	Geriatrics & Gerontology ; Neurosciences
WOS研究方向	Geriatrics & Gerontology ; Neurosciences & Neurology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/393860
推荐引用方式 GB/T 7714	Vieira, Bruno Hebling,Liem, Franziskus,Dadi, Kamalaker,et al. Predicting future cognitive decline from non-brain and multimodal brain imaging data in healthy and pathological aging[J],2022,118:55-65.
APA	Vieira, Bruno Hebling.,Liem, Franziskus.,Dadi, Kamalaker.,Engemann, Denis A..,Gramfort, Alexandre.,...&Varoquaux, Gael.(2022).Predicting future cognitive decline from non-brain and multimodal brain imaging data in healthy and pathological aging.NEUROBIOLOGY OF AGING,118,55-65.
MLA	Vieira, Bruno Hebling,et al."Predicting future cognitive decline from non-brain and multimodal brain imaging data in healthy and pathological aging".NEUROBIOLOGY OF AGING 118(2022):55-65.