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| Status |
Public on Nov 11, 2020 |
| Title |
Prognosis prediction model for Alzheimer’s disease conversion from mild cognitive impairment by integrative analysis of multi-omics data |
| Organism |
Homo sapiens |
| Experiment type |
Non-coding RNA profiling by array
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| Summary |
Mild cognitive impairment (MCI) is a clinical precursor of Alzheimer’s disease (AD). Many MCI subjects convert to AD, although others remain stable as MCI or sometimes return to cognitive normal. Currently, there are no curative treatments for patients who are already in AD, and therefore biomarkers for early detection of high risk MCI-to-AD conversion subjects are rapidly required. Here, we investigated potential biomarkers from blood-based miRNA (miR) expression profiles and genomic data of 197 Japanese MCI patients. Using the candidate biomarkers, we constructed a prognosis prediction model based on a Cox proportional hazard model. The final prediction model, composed of 24 miR-eQTLs (i.e. SNP-miRNA pairs) and three clinical factors (age, sex and ApoE ε4 carriers), successfully classified MCI patients into two groups, low and high, in terms of risk of MCI-to-AD conversion (log-rank trend test P=3.44×10^(-4)), and achieved a concordance index of 0.702 on an independent test set. Network-based meta-analysis using target genes of the miR-eQTLs further revealed four important hub genes (SHC1, FOXO1, GSK3B, and PTEN) associated with the pathogenesis of AD. Statistically significant differences were observed in PTEN expression between MCI and AD and SHC1 expression between cognitively normal elder subjects (CN) and AD when examining RNA-seq data from 610 blood samples (PTEN, P=0.023; SHC1, P=0.049), although FOXO1 and GSK3B showed low levels of expression in blood. Accurate prediction of MCI-to-AD conversion enables earlier appropriate intervention for those MCI patients and can lead to a reduction of MCI patients that convert to AD with high risk. We believe that further investigation with larger sample sizes will contribute to practical clinical use of our approach in MCI-to-AD conversion in the near future.
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| Overall design |
197 serum Mild Cognitive Impairment (MCI) samples (83 MCI converters: MCI-C and 114 MCI non-converters: MCI-NC)
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| Web link |
https://pubmed.ncbi.nlm.nih.gov/33172501/
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| Contributor(s) |
Shigemizu D, Akiyama S, Higaki S, Sugimoto T, Sakurai T, Boroevich KA, Sharma A, Tsunoda T, Ochiya T, Niida S, Ozaki K |
| Citation(s) |
33172501 |
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| Submission date |
May 15, 2020 |
| Last update date |
Nov 13, 2020 |
| Contact name |
Daichi Shigemizu |
| E-mail(s) |
d.shigemizu@gmail.com
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| Organization name |
National Center for Geriatrics and Gerontology
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| Street address |
7-430 Morioka-cho
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| City |
Obu |
| State/province |
Aichi |
| ZIP/Postal code |
474-8511 |
| Country |
Japan |
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| Platforms (1) |
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| Samples (197)
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| Relations |
| BioProject |
PRJNA633163 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE150693_RAW.tar |
12.2 Mb |
(http)(custom) |
TAR (of TXT) |
| Processed data included within Sample table |
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