Biobank-wide association scan identifies risk factors for late-onset Alzheimer’s disease and endophenotypes
| Title: | Biobank-wide association scan identifies risk factors for late-onset Alzheimer’s disease and endophenotypes |
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| Authors: | Donghui Yan, Bowen Hu, Burcu F Darst, Shubhabrata Mukherjee, Brian W Kunkle, Yuetiva Deming, Logan Dumitrescu, Yunling Wang, Adam Naj, Amanda Kuzma, Yi Zhao, Hyunseung Kang, Sterling C Johnson, Cruchaga Carlos, Timothy J Hohman, Paul K Crane, Corinne D Engelman, Alzheimer’s Disease Genetics Consortium (ADGC), Qiongshi Lu |
| Source: | eLife, Vol 12 (2024) |
| Publisher Information: | eLife Sciences Publications Ltd, 2024. |
| Publication Year: | 2024 |
| Collection: | LCC:Medicine LCC:Science LCC:Biology (General) |
| Subject Terms: | Alzheimer's disease, GWAS, UK-biobank, Medicine, Science, Biology (General), QH301-705.5 |
| More Details: | Rich data from large biobanks, coupled with increasingly accessible association statistics from genome-wide association studies (GWAS), provide great opportunities to dissect the complex relationships among human traits and diseases. We introduce BADGERS, a powerful method to perform polygenic score-based biobank-wide association scans. Compared to traditional approaches, BADGERS uses GWAS summary statistics as input and does not require multiple traits to be measured in the same cohort. We applied BADGERS to two independent datasets for late-onset Alzheimer’s disease (AD; n=61,212). Among 1738 traits in the UK biobank, we identified 48 significant associations for AD. Family history, high cholesterol, and numerous traits related to intelligence and education showed strong and independent associations with AD. Furthermore, we identified 41 significant associations for a variety of AD endophenotypes. While family history and high cholesterol were strongly associated with AD subgroups and pathologies, only intelligence and education-related traits predicted pre-clinical cognitive phenotypes. These results provide novel insights into the distinct biological processes underlying various risk factors for AD. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 2050-084X |
| Relation: | https://elifesciences.org/articles/91360; https://doaj.org/toc/2050-084X |
| DOI: | 10.7554/eLife.91360 |
| Access URL: | https://doaj.org/article/70e5d04b97aa44e69655821a17499202 |
| Accession Number: | edsdoj.70e5d04b97aa44e69655821a17499202 |
| Database: | Directory of Open Access Journals |
| ISSN: | 2050084X |
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| DOI: | 10.7554/eLife.91360 |
| Published in: | eLife |
| Language: | English |