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dc.contributor.author | Kondo, Takayuki | en |
dc.contributor.author | Yada, Yuichiro | en |
dc.contributor.author | Ikeuchi, Takeshi | en |
dc.contributor.author | Inoue, Haruhisa | en |
dc.contributor.alternative | 近藤, 孝之 | ja |
dc.contributor.alternative | 矢田, 祐一郎 | ja |
dc.contributor.alternative | 井上, 治久 | ja |
dc.date.accessioned | 2023-09-14T07:32:25Z | - |
dc.date.available | 2023-09-14T07:32:25Z | - |
dc.date.issued | 2023-03 | - |
dc.identifier.uri | http://hdl.handle.net/2433/285098 | - |
dc.description.abstract | Alzheimer’s disease (AD) is a neurodegenerative disease that causes cognitive impairment for which neither treatable nor preventable approaches have been confirmed. Although genetic factors are considered to contribute to sporadic AD, for the majority of AD patients, the exact causes of AD aren’t fully understood. For AD genetics, we developed cellular dissection of polygenicity (CDiP) technology to identify the smallest unit of AD, i.e., genetic factors at a cellular level. By CDiP, we found potential therapeutic targets, a rare variant for disease stratification, and polygenes to predict real-world AD by using the real-world data of AD cohort studies (Alzheimer’s Disease Neuroimaging Initiative: ADNI and Japanese Alzheimer’s Disease Neuroimaging Initiative: J-ADNI). In this review, we describe the components and results of CDiP in AD, induced pluripotent stem cell (iPSC) cohort, a cell genome-wide association study (cell GWAS), and machine learning. And finally, we discuss the future perspectives of CDiP technology for reverse engineering of sporadic AD toward AD eradication. | en |
dc.language.iso | eng | - |
dc.publisher | Springer Nature | en |
dc.rights | © The Author(s) 2022 | en |
dc.rights | This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. | en |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | - |
dc.subject | Alzheimer's disease | en |
dc.subject | Genome-wide association studies | en |
dc.subject | Induced pluripotent stem cells | en |
dc.title | CDiP technology for reverse engineering of sporadic Alzheimer’s disease | en |
dc.type | journal article | - |
dc.type.niitype | Journal Article | - |
dc.identifier.jtitle | Journal of Human Genetics | en |
dc.identifier.volume | 68 | - |
dc.identifier.issue | 3 | - |
dc.identifier.spage | 231 | - |
dc.identifier.epage | 235 | - |
dc.relation.doi | 10.1038/s10038-022-01047-8 | - |
dc.textversion | publisher | - |
dc.identifier.pmid | 35680997 | - |
dcterms.accessRights | open access | - |
datacite.awardNumber | 21H02807 | - |
datacite.awardNumber | 17K16121 | - |
datacite.awardNumber | 20K16599 | - |
datacite.awardNumber | 18K18452 | - |
datacite.awardNumber.uri | https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-21H02807/ | - |
datacite.awardNumber.uri | https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-17K16121/ | - |
datacite.awardNumber.uri | https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-20K16599/ | - |
datacite.awardNumber.uri | https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-18K18452/ | - |
dc.identifier.pissn | 1434-5161 | - |
dc.identifier.eissn | 1435-232X | - |
jpcoar.funderName | 日本学術振興会 | ja |
jpcoar.funderName | 日本学術振興会 | ja |
jpcoar.funderName | 日本学術振興会 | ja |
jpcoar.funderName | 日本学術振興会 | ja |
jpcoar.awardTitle | 点鼻タウワクチンによる脳内免疫応答の解明とナノ粒子のベクター利用 | ja |
jpcoar.awardTitle | 疾患特異的iPS細胞を用いた3次元創薬プラットフォームの構築 | ja |
jpcoar.awardTitle | 患者アストロサイトを用いたアルツハイマー病病態の解明 | ja |
jpcoar.awardTitle | Deep learningによる神経変性画像解析の研究 | ja |
出現コレクション: | 学術雑誌掲載論文等 |

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