Browsing by Author "Diao, Lixia"

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    Comprehensive characterization of the transcriptional landscape in Alzheimer’s disease (AD) brains
    (American Association for the Advancement of Science, 2025) Chen, Chengxuan; Zhang, Zhao; Liu, Yuan; Hong, Wei; Karahan, Hande; Wang, Jun; Li, Wenbo; Diao, Lixia; Yu, Meichen; Saykin, Andrew J.; Nho, Kwangsik; Kim, Jungsu; Han, Leng; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public Health
    Alzheimer's disease (AD) is the leading dementia among the elderly with complex origins. Despite extensive investigation into the AD-associated protein-coding genes, the involvement of noncoding RNAs (ncRNAs) and posttranscriptional modification (PTM) in AD pathogenesis remains unclear. Here, we comprehensively characterized the landscape of ncRNAs and PTM events in 1460 samples across six brain regions sourced from the Mount Sinai/JJ Peters VA Medical Center Brain Bank Study and Mayo cohorts, encompassing 33,321 long ncRNAs, 92,897 enhancer RNAs, 53,763 alternative polyadenylation events, and 900,221 A-to-I RNA editing events. We additionally identified 25,351 aberrantly expressed ncRNAs and altered PTM events associated with AD traits and further identified the corresponding protein-coding genes to construct regulatory networks. Furthermore, we developed a user-friendly data portal, ADatlas, facilitating users in exploring our results. Our study aims to establish a comprehensive data platform for ncRNAs and PTMs in AD to advance related research.
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    PancanQTLv2.0: a comprehensive resource for expression quantitative trait loci across human cancers
    (Oxford University Press, 2024) Chen, Chengxuan; Liu, Yuan; Luo, Mei; Yang, Jingwen; Chen, Yamei; Wang, Runhao; Zhou, Joseph; Zang, Yong; Diao, Lixia; Han, Leng; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public Health
    Expression quantitative trait locus (eQTL) analysis is a powerful tool used to investigate genetic variations in complex diseases, including cancer. We previously developed a comprehensive database, PancanQTL, to characterize cancer eQTLs using The Cancer Genome Atlas (TCGA) dataset, and linked eQTLs with patient survival and GWAS risk variants. Here, we present an updated version, PancanQTLv2.0 (https://hanlaboratory.com/PancanQTLv2/), with advancements in fine-mapping causal variants for eQTLs, updating eQTLs overlapping with GWAS linkage disequilibrium regions and identifying eQTLs associated with drug response and immune infiltration. Through fine-mapping analysis, we identified 58 747 fine-mapped eQTLs credible sets, providing mechanic insights of gene regulation in cancer. We further integrated the latest GWAS Catalog and identified a total of 84 592 135 linkage associations between eQTLs and the existing GWAS loci, which represents a remarkable ∼50-fold increase compared to the previous version. Additionally, PancanQTLv2.0 uncovered 659516 associations between eQTLs and drug response and identified 146948 associations between eQTLs and immune cell abundance, providing potentially clinical utility of eQTLs in cancer therapy. PancanQTLv2.0 expanded the resources available for investigating gene expression regulation in human cancers, leading to advancements in cancer research and precision oncology.