| Item type |
リポジトリ登録用アイテムタイプ（シンプル）(1) |
| 公開日 |
2025-03-25 |
| タイトル |
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|
タイトル |
Multiomics and artificial intelligence enabled peripheral blood-based prediction of amnestic mild cognitive impairment |
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言語 |
en |
| 言語 |
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|
言語 |
eng |
| キーワード |
|
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言語 |
en |
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主題Scheme |
Other |
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主題 |
Mild cognitive impairment |
| キーワード |
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言語 |
en |
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主題Scheme |
Other |
|
主題 |
Alzheimer's disease with dementia |
| キーワード |
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言語 |
en |
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主題Scheme |
Other |
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主題 |
Transcriptome |
| キーワード |
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言語 |
en |
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主題Scheme |
Other |
|
主題 |
Proteome |
| キーワード |
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言語 |
en |
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主題Scheme |
Other |
|
主題 |
Metabolome |
| キーワード |
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言語 |
en |
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主題Scheme |
Other |
|
主題 |
Cohort |
| キーワード |
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言語 |
en |
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主題Scheme |
Other |
|
主題 |
Biomarker |
| キーワード |
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言語 |
en |
|
主題Scheme |
Other |
|
主題 |
miRNA |
| キーワード |
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|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Regulatory T cells |
| 資源タイプ |
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資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
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資源タイプ |
journal article |
| アクセス権 |
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アクセス権 |
open access |
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アクセス権URI |
http://purl.org/coar/access_right/c_abf2 |
| 著者 |
Tatara, Yota
Yamazaki, Hiromi
Katsuoka, Fumiki
Chiba, Mitsuru
Saigusa, Daisuke
Kasai, Shuya
Nakamura, Tomohiro
Inoue, Jin
Aoki, Yuichi
Shoji, Miho
Motoike, N. Ikuko
Tamada, Yoshinori
Hashizume, Katsuhito
Shoji, Mikio
Kinoshita, Kengo
Murashita, Koichi
Nakaji, Shigeyuki
Yamamoto, Masayuki
Itoh, Ken
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| 抄録 |
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内容記述タイプ |
Abstract |
|
内容記述 |
Background: Since dementia is preventable with early interventions, biomarkers that assist in diagnosing early stages of dementia, such as mild cognitive impairment (MCI), are urgently needed.
Methods: Multiomics analysis of amnestic MCI (aMCI) peripheral blood (n = 25) was performed covering the transcriptome, microRNA, proteome, and metabolome. Validation analysis for microRNAs was conducted in an independent cohort (n = 12). Artificial intelligence was used to identify the most important features for predicting aMCI.
Findings: We found that hsa-miR-4455 is the best biomarker in all omics analyses. The diagnostic index taking a ratio of hsa-miR-4455 to hsa-let-7b-3p predicted aMCI patients against healthy subjects with 97% overall accuracy. An integrated review of multiomics data suggested that a subset of T cells and the GCN (general control nonderepressible) pathway are associated with aMCI.
Interpretation: The multiomics approach has enabled aMCI biomarkers with high specificity and illuminated the accompanying changes in peripheral blood. Future large-scale studies are necessary to validate candidate biomarkers for clinical use. |
|
言語 |
en |
| 書誌情報 |
en : Current Research in Translational Medicine
巻 71,
号 1,
p. 103367
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| ISSN |
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収録物識別子タイプ |
EISSN |
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収録物識別子 |
2452-3186 |
| DOI |
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関連タイプ |
isIdenticalTo |
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識別子タイプ |
DOI |
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関連識別子 |
https://doi.org/10.1016/j.retram.2022.103367 |
| 権利情報 |
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言語 |
en |
|
権利情報 |
© 2022 The Author(s). Published by Elsevier Masson SAS. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
| 出版タイプ |
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出版タイプ |
VoR |
|
出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| 関連情報 |
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関連タイプ |
isIdenticalTo |
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識別子タイプ |
URI |
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関連識別子 |
https://www.sciencedirect.com/science/article/pii/S2452318622000356?via%3Dihub |
1-s2.0-S2452318622000356-main.pdf (1.5 MB)
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