Browsing by Author "Kim, Sang Yun"

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    Aberrant GAP43 Gene Expression Is Alzheimer Disease Pathology-Specific
    (Wiley, 2023) Pyun, Jung-Min; Park, Young Ho; Wang, Jiebiao; Bice, Paula J.; Bennett, David A.; Kim, Sang Yun; Saykin, Andrew J.; Nho, Kwangsik; Radiology and Imaging Sciences, School of Medicine
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    miR-129-5p as a biomarker for pathology and cognitive decline in Alzheimer’s disease
    (Springer Nature, 2024-01-09) Han, Sang‑Won; Pyun, Jung‑Min; Bice, Paula J.; Bennett, David A.; Saykin, Andrew J.; Kim, Sang Yun; Park, Young Ho; Nho, Kwangsik; Radiology and Imaging Sciences, School of Medicine
    Background: Alzheimer's dementia (AD) pathogenesis involves complex mechanisms, including microRNA (miRNA) dysregulation. Integrative network and machine learning analysis of miRNA can provide insights into AD pathology and prognostic/diagnostic biomarkers. Methods: We performed co-expression network analysis to identify network modules associated with AD, its neuropathology markers, and cognition using brain tissue miRNA profiles from the Religious Orders Study and Rush Memory and Aging Project (ROS/MAP) (N = 702) as a discovery dataset. We performed association analysis of hub miRNAs with AD, its neuropathology markers, and cognition. After selecting target genes of the hub miRNAs, we performed association analysis of the hub miRNAs with their target genes and then performed pathway-based enrichment analysis. For replication, we performed a consensus miRNA co-expression network analysis using the ROS/MAP dataset and an independent dataset (N = 16) from the Gene Expression Omnibus (GEO). Furthermore, we performed a machine learning approach to assess the performance of hub miRNAs for AD classification. Results: Network analysis identified a glucose metabolism pathway-enriched module (M3) as significantly associated with AD and cognition. Five hub miRNAs (miR-129-5p, miR-433, miR-1260, miR-200a, and miR-221) of M3 had significant associations with AD clinical and/or pathologic traits, with miR129-5p by far the strongest across all phenotypes. Gene-set enrichment analysis of target genes associated with their corresponding hub miRNAs identified significantly enriched biological pathways including ErbB, AMPK, MAPK, and mTOR signaling pathways. Consensus network analysis identified two AD-associated consensus network modules and two hub miRNAs (miR-129-5p and miR-221). Machine learning analysis showed that the AD classification performance (area under the curve (AUC) = 0.807) of age, sex, and APOE ε4 carrier status was significantly improved by 6.3% with inclusion of five AD-associated hub miRNAs. Conclusions: Integrative network and machine learning analysis identified miRNA signatures, especially miR-129-5p, as associated with AD, its neuropathology markers, and cognition, enhancing our understanding of AD pathogenesis and leading to better performance of AD classification as potential diagnostic/prognostic biomarkers.
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    Transcriptome analysis of early‐ and late‐onset Alzheimer's disease in Korean cohorts
    (Wiley, 2025) Han, Sang-Won; Hwang, Jiyun; Park, Tamina; Pyun, Jung-Min; Lee, Joo-Yeon; Park, Jeong Su; Bice, Paula J.; Liu, Shiwei; Yun, Sunmin; Jeong, Jibin; Risacher, Shannon L.; Saykin, Andrew J.; Byun, Min Soo; Yi, Dahyun; Sung, Joohon; Lee, Dong Young; Kim, Sang Yun; Nho, Kwangsik; Park, Young Ho; Radiology and Imaging Sciences, School of Medicine
    Introduction: The molecular mechanisms underlying early-onset Alzheimer's disease (EOAD) and late-onset Alzheimer's disease (LOAD) remain incompletely understood, particularly in Asian populations. Methods: RNA-sequencing was carried out on blood samples from 248 participants in the Seoul National University Bundang Hospital cohort to perform differential gene expression (DGE) and weighted gene co-expression network analysis. Findings were replicated in an independent Korean cohort (N = 275). Results: DGE analysis identified 18 and 88 dysregulated genes in EOAD and LOAD, respectively. Network analysis identified a LOAD-associated module showing a significant enrichment in pathways related to mitophagy, 5' adenosine monophosphate-activated protein kinase signaling, and ubiquitin-mediated proteolysis. In the replication cohort, downregulation of SMOX and PLVAP in LOAD was replicated, and the LOAD-associated module was highly preserved. In addition, SMOX and PLVAP were associated with brain amyloid beta deposition. Discussion: Our findings suggest distinct molecular signatures for EOAD and LOAD in a Korean population, providing deeper understanding of their diagnostic potential and molecular mechanisms. Highlights: Analysis identified 18 and 88 dysregulated genes in early-onset Alzheimer's disease (EOAD) and late-onset Alzheimer's disease (LOAD), respectively. Expression levels of SMOX and PLVAP were downregulated in LOAD. Expression levels of SMOX and PLVAP were associated with brain amyloid beta deposition. Pathways including mitophagy and 5' adenosine monophosphate-activated protein kinase signaling were enriched in a LOAD module. A LOAD module was highly preserved across two independent cohorts.