Browsing by Author "Kim, Bo-Hyun"

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    Genome-wide association study identifies susceptibility loci of brain atrophy to NFIA and ST18 in Alzheimer's disease
    (Elsevier, 2021-06) Kim, Bo-Hyun; Nho, Kwangsik; Lee, Jong-Min; Alzheimer's Disease Neuroimaging Initiative; Radiology & Imaging Sciences, School of Medicine
    To identify genetic variants influencing cortical atrophy in Alzheimer's disease (AD), we performed genome-wide association studies (GWAS) of mean cortical thicknesses in 17 AD-related brain. In this study, we used neuroimaging and genetic data of 919 participants from the Alzheimer's Disease Neuroimaging Initiative cohort, which include 268 cognitively normal controls, 488 mild cognitive impairment, 163 AD individuals. We performed GWAS with 3,041,429 single nucleotide polymorphisms (SNPs) for cortical thickness. The results of GWAS indicated that rs10109716 in ST18 (ST18 C2H2C-type zinc finger transcription factor) and rs661526 in NFIA (nuclear factor I A) genes are significantly associated with mean cortical thicknesses of the left inferior frontal gyrus and left parahippocampal gyrus, respectively. The rs661526 regulates the expression levels of NFIA in the substantia nigra and frontal cortex and rs10109716 regulates the expression levels of ST18 in the thalamus. These results suggest a crucial role of identified genes for cortical atrophy and could provide further insights into the genetic basis of AD.
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    Identification of Novel Genes Associated with Cortical Thickness in Alzheimer’s Disease: Systems Biology Approach to Neuroimaging Endophenotype
    (IOS Press, 2020) Kim, Bo-Hyun; Choi, Yong-Ho; Yang, Jin-Ju; Kim, SangYun; Nho, Kwangsik; Lee, Jong-Min; Radiology and Imaging Sciences, School of Medicine
    Alzheimer’s disease (AD) is a common neurodegenerative disorder characterized by a heterogeneous distribution of pathological changes in the brain. Cortical thickness is one of the most sensitive imaging biomarkers for AD representing structural atrophy. The purpose of this study is to identify novel genes associated with cortical thickness. We measured the whole-brain mean cortical thickness from magnetic resonance imaging (MRI) scans in 919 subjects from the Alzheimer’s Disease Neuroimaging Initiative cohort, including 163 AD patients, 488 mild cognitive impairment patients, and 268 cognitively normal participants. Based on the single-nucleotide polymorphism (SNP)-based genome-wide association study, we performed gene-based association analysis for mean cortical thickness. Furthermore, we performed expression quantitative trait loci, protein-protein interaction network, and pathway analysis to identify biologically functional information. We identified four genes (B4GALNT1, RAB44, LOC101927583, and SLC26A10), two pathways (cyclin-dependent protein kinase holoenzyme complex and nuclear cyclin-dependent protein kinase holoenzyme complex), and one protein-protein interaction (B4GALNT1 and GALNT8 pair). These genes are involved in protein degradation, GTPase activity, neuronal loss, and apoptosis. The identified pathways are involved in the cellular processes and neuronal differentiation, which contribute to neuronal loss that is responsible for AD. Furthermore, the most significant SNP (rs12320537) in B4GALNT1 is associated with expression levels of B4GALNT1 in several brain regions. Thus, the identified genes and pathways provide deeper mechanistic insight into the molecular basis of brain atrophy in AD.
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    Integrative analysis of DNA methylation and gene expression identifies genes associated with biological aging in Alzheimer's disease
    (Wiley, 2022-09-20) Kim, Bo-Hyun; Vasanthakumar, Aparna; Li, Qingqin S.; Nudelman, Kelly N.H.; Risacher, Shannon L.; Davis, Justin W.; Idler, Kenneth; Lee, Jong-Min; Seo, Sang Won; Waring, Jeffrey F.; Saykin, Andrew J.; Nho, Kwangsik; Alzheimer’s Disease Neuroimaging Initiative (ADNI); Radiology and Imaging Sciences, School of Medicine
    Introduction: The acceleration of biological aging is a risk factor for Alzheimer's disease (AD). Here, we performed weighted gene co-expression network analysis (WGCNA) to identify modules and dysregulated genes involved in biological aging in AD. Methods: We performed WGCNA to identify modules associated with biological clocks and hub genes of the module with the highest module significance. In addition, we performed differential expression analysis and association analysis with AD biomarkers. Results: WGCNA identified five modules associated with biological clocks, with the module designated as "purple" showing the strongest association. Functional enrichment analysis revealed that the purple module was related to cell migration and death. Ten genes were identified as hub genes in purple modules, of which CX3CR1 was downregulated in AD and low levels of CX3CR1 expression were associated with AD biomarkers. Conclusion: Network analysis identified genes associated with biological clocks, which suggests the genetic architecture underlying biological aging in AD. Highlights: Examine links between Alzheimer's disease (AD) peripheral transcriptome and biological aging changes. Weighted gene co-expression network analysis (WGCNA) found five modules related to biological aging. Among the hub genes of the module, CX3CR1 was downregulated in AD. The CX3CR1 expression level was associated with cognitive performance and brain atrophy.
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    Integrative Co-methylation Network Analysis Identifies Novel DNA Methylation Signatures and Their Target Genes in Alzheimer's Disease
    (Elsevier, 2023) Kim, Jun Pyo; Kim, Bo-Hyun; Bice, Paula J.; Seo, Sang Won; Bennett, David A.; Saykin, Andrew J.; Nho, Kwangsik; Radiology and Imaging Sciences, School of Medicine
    Background: DNA methylation is a key epigenetic marker, and its alternations may be involved in Alzheimer's disease (AD). CpGs sharing similar biological functions or pathways tend to be co-methylated. Methods: We performed an integrative network-based DNA methylation analysis on 2 independent cohorts (N = 941) using brain DNA methylation profiles and RNA-sequencing as well as AD pathology data. Results: Weighted co-methylation network analysis identified 6 modules as significantly associated with neuritic plaque burden. In total, 15 hub CpGs including 3 novel CpGs were identified and replicated as being significantly associated with AD pathology. Furthermore, we identified and replicated 4 target genes (ATP6V1G2, VCP, RAD52, and LST1) as significantly regulated by DNA methylation at hub CpGs. In particular, VCP gene expression was also associated with AD pathology in both cohorts. Conclusions: This integrative network-based multiomics study provides compelling evidence for a potential role of DNA methylation alternations and their target genes in AD.
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    Whole-genome sequencing analyses suggest novel genetic factors associated with Alzheimer’s disease and a cumulative effects model for risk liability
    (Springer Nature, 2025-05-26) Kim, Jun Pyo; Cho, Minyoung; Kim, Chanhee; Lee, Hyunwoo; Jang, Beomjin; Jung, Sang-Hyuk; Kim, Yujin; Koh, In Gyeong; Kim, Seoyeon; Shin, Daeun; Lee, Eun Hye; Lee, Jong-Young; Park, YoungChan; Jang, Hyemin; Kim, Bo-Hyun; Ham, Hongki; Kim, Beomsu; Kim, Yujin; Cho, A-Hyun; Raj, Towfique; Kim, Hee Jin; Na, Duk L.; Seo, Sang Won; An, Joon-Yong; Won, Hong-Hee; Radiology and Imaging Sciences, School of Medicine
    Genome-wide association studies (GWAS) on Alzheimer's disease (AD) have predominantly focused on identifying common variants in Europeans. Here, we performed whole-genome sequencing (WGS) of 1,559 individuals from a Korean AD cohort to identify various genetic variants and biomarkers associated with AD. Our GWAS analysis identified a previously unreported locus for common variants (APCDD1) associated with AD. Our WGS analysis was extended to explore the less-characterized genetic factors contributing to AD risk. We identified rare noncoding variants located in cis-regulatory elements specific to excitatory neurons associated with cognitive impairment. Moreover, structural variation analysis showed that short tandem repeat expansion was associated with an increased risk of AD, and copy number variant at the HPSE2 locus showed borderline statistical significance. APOE ε4 carriers with high polygenic burden or structural variants exhibited severe cognitive impairment and increased amyloid beta levels, suggesting a cumulative effects model of AD risk.