Multiomics and artificial intelligence enabled peripheral blood-based prediction of amnestic mild cognitive impairment - 03/02/23

Doi : 10.1016/j.retram.2022.103367

Yota Tatara ^a, Hiromi Yamazaki ^a, Fumiki Katsuoka ^b, Mitsuru Chiba ^c, Daisuke Saigusa ^b, Shuya Kasai ^a, Tomohiro Nakamura ^d, Jin Inoue ^b, Yuichi Aoki ^b, Miho Shoji ^e, Ikuko N. Motoike ^b, Yoshinori Tamada ^f, Katsuhito Hashizume ^e, Mikio Shoji ^g,^h,^k, Kengo Kinoshita ^b,^i,^j, Koichi Murashita ^k, Shigeyuki Nakaji ^l, Masayuki Yamamoto ^b,^m, Ken Itoh ^a,^⁎
^a Department of Stress Response Science, Center for Advanced Medical Research, Graduate School of Medicine, Hirosaki University, 5 Zaifu-cho, Hirosaki, Aomori 036-8562, Japan
^b Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-Machi, Aoba-ku, Sendai, Miyagi 980-8573, Japan
^c Department of Bioscience and Laboratory Medicine, Hirosaki University Graduate School of Health Sciences, 66-1 Hon-cho, Hirosaki, Aomori 036-8564, Japan
^d Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, Division of Personalized Prevention and Epidemiology, 2-1 Seiryo-Machi, Aoba-ku, Sendai, Miyagi 980-8573, Japan
^e Human Metabolome Technologies, Inc., 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata 997-0052, Japan
^f Innovation Center for Health Promotion, Graduate School of Medicine, Hirosaki University, 5 Zaifu-cho, Hirosaki, Aomori 036-8562, Japan
^g Department of Neurology, Gunma University Hospital, 3-39-15 Showamachi, Maebashi, Gunma 371-8511, Japan
^h Department of Neurology, Dementia Research Center, Geriatrics Research Institute and Hospital, 3-26-8 Ootomo-machi, Maebashi, Gunma 371-0847 Japan
ⁱ Department of Applied Information Sciences, Graduate School of Information Sciences, Tohoku University, 6-6-05 Aramaki Aza Aoba, Aoba-ku, Sendai, Miyagi 980-8579, Japan
^j Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi 980-8573, Japan
^k COI Research Initiatives Organization, Hirosaki University, 5 Zaifu-cho, Hirosaki, Aomori 036-8216, Japan
^l Department of Social Medicine, Hirosaki University Graduate School of Medicine, 5 Zaifu-cho, Hirosaki, Aomori 036-8216, Japan
^m Department of Medical Biochemistry, Graduate School of Medicine, Tohoku University, 2-1 Seiryo-Machi, Aoba-ku, Sendai, Miyagi 980-8575, Japan

^⁎Corresponding author.

Abstract

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.

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Keywords : Mild cognitive impairment, Alzheimer's disease with dementia, Transcriptome, Proteome, Metabolome, Cohort, Biomarker, miRNA, Regulatory T cells

Abbreviations : MCI, AD, LOAD, NIA-AA, IHPP, MMSE, LMII, OLD, CDR, WMS-R, APOE, JPSC-AD, MRM, ROC, PCA, OPLS-DA, ISR, TCR, AUC, BBB, IPA

Mappa

Introduction

Materials and methods

Design, participants, and ethics

Blood collection and preparation

Microarray analysis of miRNA

Overview of omics data

Multiomics information of peripheral blood suggests the involvement of the GCN1-mediated integrated stress response pathway and immune cell alteration

aMCI biomarker model building with AI

Discussion

Data sharing statement

CRediT authorship contribution statement

Esportazione

Vol 71 - N° 1

Articolo 103367- gennaio 2023 Ritorno al numero

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Multiomics and artificial intelligence enabled peripheral blood-based prediction of amnestic mild cognitive impairment - 03/02/23

Abstract

Background

Methods

Findings

Interpretation

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