
대규모 바이오뱅크 데이터와 유전체 연관 연구 요약 통계를 활용하여, 알츠하이머병 발병 위험 요인과 내부 표현형 간의 복잡한 관계를 규명하였다.


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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 1,738 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. Further, 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.

### Competing Interest Statement

The authors have declared no competing interest.

Biobank-wide association scan identifies risk factors for late-onset Alzheimer’s disease and endophenotypes

알츠하이머병-발병-위험-요인-및-내부-표현형에-대한-바이오뱅크-전체-연관-분석


알츠하이머병 발병 위험 요인 및 내부 표현형에 대한 바이오뱅크 전체 연관 분석
