한빛사논문
- 조회547
Jung-Min Pyun 1, Young Ho Park 2, Jiebiao Wang 3, David A Bennett 4, Paula J Bice 5, Jun Pyo Kim 5, SangYun Kim 2, Andrew J Saykin 5,6, Kwangsik Nho 5,7
1Department of Neurology, Soonchunhyang University Seoul Hospital, Soonchunhyang University College of Medicine, Yongsan-gu, Seoul, Republic of Korea.
2Department of Neurology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, Republic of Korea.
3Department of Biostatistics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
4Department of Neurological Science, Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA.
5Department of Radiology and Imaging Sciences, and the Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, Indiana, USA.
6Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA.
7Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Health Information and Translational Science Building, Indianapolis, Indiana, USA.
CORRESPONDING AUTHORS : Young Ho Park, Kwangsik Nho
Abstract
Introduction: Our previously developed blood-based transcriptional risk scores (TRS) showed associations with diagnosis and neuroimaging biomarkers for Alzheimer's disease (AD). Here, we developed brain-based TRS.
Methods: We integrated AD genome-wide association study summary and expression quantitative trait locus data to prioritize target genes using Mendelian randomization. We calculated TRS using brain transcriptome data of two independent cohorts (N = 878) and performed association analysis of TRS with diagnosis, amyloidopathy, tauopathy, and cognition. We compared AD classification performance of TRS with polygenic risk scores (PRS).
Results: Higher TRS values were significantly associated with AD, amyloidopathy, tauopathy, worse cognition, and faster cognitive decline, which were replicated in an independent cohort. The AD classification performance of PRS was increased with the inclusion of TRS up to 16% with the area under the curve value of 0.850.
Discussion: Our results suggest brain-based TRS improves the AD classification of PRS and may be a potential AD biomarker.
Highlights: Transcriptional risk score (TRS) is developed using brain RNA-Seq data. Higher TRS values are shown in Alzheimer's disease (AD). TRS improves the AD classification power of PRS up to 16%. TRS is associated with AD pathology presence. TRS is associated with worse cognitive performance and faster cognitive decline.
논문정보
- Research article
- 2023년 08월 (BRIC 등록일 2023-08-14)
- 국내(교신)+국외 연구진
- 의약학 > 신경의학
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