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| Status |
Public on Feb 26, 2019 |
| Title |
Risk prediction models for dementia constructed by supervised principal component analysis using miRNA expression data |
| Organism |
Homo sapiens |
| Experiment type |
Non-coding RNA profiling by array
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| Summary |
Alzheimer’s disease (AD) is the most common subtype of dementia, followed by Vascular Dementia (VaD), and Dementia with Lewy Bodies (DLB). Recently, microRNAs (miRNAs) have received a lot of attention as the novel biomarkers for dementia. Here, using serum miRNA expression of 1,601 Japanese individuals, we investigated potential miRNA bio- markers and constructed risk prediction models, based on a supervised principal component analysis (PCA) logistic regression method, according to the subtype of dementia. The final risk prediction model achieved a high accuracy of 0.873 on a validation cohort in AD, when using 78 miRNAs: Accuracy = 0.836 with 86 miRNAs in VaD; Accuracy = 0.825 with 110 miRNAs in DLB. To our knowledge, this is the first report applying miRNA-based risk pre- diction models to a dementia prospective cohort. Our study demonstrates our models to be effective in prospective disease risk prediction; and with further improvement may contribute to practical clinical use in dementia.
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| Overall design |
1,601 serum samples (1,021 AD cases, 91 VaD cases, 169 DLB cases, 32 Mild Cognitive Impairment: MCI, and 288 NC).
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| Contributor(s) |
Shigemizu D, Akiyama S, Asanomi Y, Boroevich KA, Sharma A, Tsunoda T, Matsukuma K, Ichikawa M, Sudo H, Takizawa S, Sakurai T, Ochiya T, Ozaki K, Niida S |
| Citation(s) |
30820472, 31666070, 34686734 |
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| Submission date |
Sep 27, 2018 |
| Last update date |
Nov 03, 2021 |
| 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 (1601)
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| Relations |
| BioProject |
PRJNA493639 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE120584_RAW.tar |
99.0 Mb |
(http)(custom) |
TAR (of TXT) |
| Processed data included within Sample table |
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