Browsing by Author "Liu, Shiwei"
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Item Functional insight into East Asian-specific genetic risk loci for Alzheimer's disease(Wiley, 2025) Cho, Minyoung; Chaudhuri, Soumilee; Liu, Shiwei; Park, Tamina; Huang, Yen-Ning; Rosewood, Thea; Bice, Paula J.; Saykin, Andrew J.; Won, Hong-Hee; Nho, Kwangsik; Radiology and Imaging Sciences, School of MedicineIntroduction: The functional study of genetic risk factors for Alzheimer's disease (AD) provides insights into the underlying mechanisms and identification of potential therapeutic targets. Investigating AD-associated genetic loci identified in East Asian populations using single-nucleus RNA-sequencing data may identify novel functional genetic contributors. Methods: Cell type-specific expression quantitative trait loci (eQTL) and peak-to-gene links were used to identify functional genes associated with 26 genetic loci from seven genome-wide association studies (GWAS) for AD in East Asians. Results: KCNJ6 and MAPK1IP1L were identified as significant eQTLs with AD risk loci. AD risk loci were in peaks related to four genes, with CLIC4 being connected across different cell types. Genes identified in European and East Asian GWAS interacted within networks and were enriched in AD pathology pathways in astrocytes. Discussion: Our findings suggest KCNJ6 and CLIC4 as novel AD-associated functional genes, providing insight into the genetic architecture of AD in East Asians. Highlights: Integrated functional analysis of Alzheimer's disease (AD) loci in seven East Asian genome-wide association studies (GWAS) was performed. Cell type-specific expression quantitative trait loci (eQTLs) and assay for transposase-accessible chromatin peaks were used to identify AD functional genes. An AD risk variant was linked to KCNJ6 through an oligodendrocyte progenitor cell-specific eQTL. An AD risk variant maps to open chromatin, linked to CLIC4 across six cell types. Astrocyte differentially expressed genes by AD pathology are enriched in East Asian and European GWAS genes.Item Genome-wide transcriptome analysis of Aβ deposition on PET in a Korean cohort(Wiley, 2024) Park, Tamina; Hwang, Jiyun; Liu, Shiwei; Chaudhuri, Soumilee; Han, Sang Won; Yi, Dahyun; Byun, Min Soo; Huang, Yen-Ning; Rosewood, Thea; Jung, Gijung; Kim, Min Jeong; Ahn, Hyejin; Lee, Jun-Young; Kim, Yu Kyeong; Cho, MinYoung; Bice, Paula J.; Craft, Hannah; Risacher, Shannon L.; Gao, Hongyu; Liu, Yunlong; Kim, SangYun; Park, Young Ho; Lee, Dong Young; Saykin, Andrew J.; Nho, Kwangsik; Radiology and Imaging Sciences, School of MedicineIntroduction: Despite the recognized importance of including ethnic diversity in Alzheimer's disease (AD) research, substantial knowledge gaps remain, particularly in Asian populations. Methods: RNA sequencing was performed on blood samples from the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer's Disease (KBASE) to perform differential gene expression (DGE), gene co-expression network, gene-set enrichment, and machine learning analyses for amyloid beta (Aβ) deposition on positron emission tomography. Results: DGE analysis identified 265 dysregulated genes associated with Aβ deposition and replicated three AD-associated genes in an independent Korean cohort. Network analysis identified two modules related to pathways including a natural killer (NK) cell-mediated immunity. Machine learning analysis showed the classification of Aβ positivity improved with the inclusion of gene expression data. Discussion: Our results in a Korean population suggest Aβ deposition-associated genes are enriched in NK cell-mediated immunity, providing a better understanding of AD molecular mechanisms and yielding potential diagnostic and therapeutic strategies. Highlights: Dysregulated genes were associated with amyloid beta (Aβ) deposition on positron emission tomography in a Korean cohort. Dysregulated genes in Alzheimer's disease were replicated in an independent Korean cohort. Gene network modules were associated with Aβ deposition. Natural killer (NK) cell proportion in blood was associated with Aβ deposition. Dysregulated genes were related to a NK cell-mediated immunity.Item HapCNV: A Comprehensive Framework for CNV Detection in Low-input DNA Sequencing Data(bioRxiv, 2025-01-07) Yu, Xuanxuan; Qin, Fei; Liu, Shiwei; Brown, Noah J.; Lu, Qing; Cai, Guoshuai; Guler, Jennifer L.; Xiao, Feifei; Radiology and Imaging Sciences, School of MedicineCopy number variants (CNVs) are prevalent in both diploid and haploid genomes, with the latter containing a single copy of each gene. Studying CNVs in genomes from single or few cells is significantly advancing our knowledge in human disorders and disease susceptibility. Low-input including low-cell and single-cell sequencing data for haploid and diploid organisms generally displays shallow and highly non-uniform read counts resulting from the whole genome amplification steps that introduce amplification biases. In addition, haploid organisms typically possess relatively short genomes and require a higher degree of DNA amplification compared to diploid organisms. However, most CNV detection methods are specifically developed for diploid genomes without specific consideration of effects on haploid genomes. Challenges also reside in reference samples or normal controls which are used to provide baseline signals for defining copy number losses or gains. In traditional methods, references are usually pre-specified from cells that are assumed to be normal or disease-free. However, the use of pre-defined reference cells can bias results if common CNVs are present. Here, we present the development of a comprehensive statistical framework for data normalization and CNV detection in haploid single- or low-cell DNA sequencing data called HapCNV. The prominent advancement is the construction of a novel genomic location specific pseudo-reference that selects unbiased references using a preliminary cell clustering method. This approach effectively preserves common CNVs. Using simulations, we demonstrated that HapCNV outperformed existing methods by generating more accurate CNV detection, especially for short CNVs. Superior performance of HapCNV was also validated in detecting known CNVs in a real P. falciparum parasite dataset. In conclusion, HapCNV provides a novel and useful approach for CNV detection in haploid low-input sequencing datasets, with easy applicability to diploids.Item Integration of GWAS summary statistics with cell type‐specific eQTLs prioritizes potential causal genes for Alzheimer’s disease(Wiley, 2025-01-09) Liu, Shiwei; Huang, Yen-Ning; Park, Tamina; Chaudhuri, Soumilee; Cho, Min Young; Jacobson Rosewood, Thea; Bennett, David A.; Saykin, Andrew J.; Nho, Kwangsik; Radiology and Imaging Sciences, School of MedicineBackground: Analyzing disease‐linked genetic variants via expression quantitative trait loci (eQTLs) is crucial for identifying disease‐causing genes. Previous research prioritized genes by integrating Genome‐Wide Association Study (GWAS) results with tissue‐level eQTLs. Recent studies explored brain cell type‐specific eQTLs, but they lack a systematic analysis across various AD GWAS datasets, nor did they compare effects between tissue and cell type levels or across different cell type‐specific eQTL datasets. Here, we integrated brain cell type‐specific eQTL datasets with AD GWAS datasets to identify potential causal genes at the cell type level. Method: To prioritize disease‐causing genes, we used summary data‐based Mendelian Randomization (SMR) and Bayesian colocalization (COLOC) methods to integrate the AD GWAS summary statistics with cell type‐specific eQTLs in human brain. We utilized five latest AD GWAS datasets and a cell type‐specific eQTL dataset comprising 424 participants of the Religious Orders Study (ROS) and Rush Memory and Aging Project (MAP) cohort. We replicated our analysis using a cell type‐specific eQTL dataset of 192 participants from Bryois et al., 2021. For comparison, we utilized a previous tissue‐level metabrain eQTL dataset from a meta‐analysis of 14 datasets. Furthermore, we visualized the colocalization of novel candidate causal genes using eQTpLot. Result: We identified 17 cell type‐specific candidate causal genes using the ROSMAP eQTL dataset. Our results showed that the largest number of candidate causal genes are identified in microglia, followed by astrocytes, oligodendrocytes, excitatory neurons, inhibitory neurons, and oligodendrocyte progenitor cells (OPCs). Four candidate causal genes were common across different cell types. Interestingly, JAZF1, detected as a candidate causal gene affected by the same leading variant in both microglia and OPCs, showed a congruous (same direction) colocalized SNP effect on the gene expression level and AD in OPCs, but an incongruous (opposite direction) colocalized SNP effect in microglia. After comparing our results with previously known prioritized causal genes, we identified PABPC1 in astrocyte as a novel potential causal gene. Conclusion: We systematically prioritized AD candidate causal genes based on cell type‐specific molecular evidence. The integrative approach enhances our understanding of molecular mechanisms of AD‐related genetic variants and facilitates the interpretation of AD GWAS results.Item Multi-Omics Analysis for Identifying Cell-Type-Specific Druggable Targets in Alzheimer’s Disease(medRxiv, 2025-01-09) Liu, Shiwei; Cho, Min Young; Huang, Yen-Ning; Park, Tamina; Chaudhuri, Soumilee; Jacobson Rosewood, Thea; Bice, Paula J.; Chung, Dongjun; Bennett, David A.; Ertekin-Taner, Nilüfer; Saykin, Andrew J.; Nho, Kwangsik; Radiology and Imaging Sciences, School of MedicineBackground: Analyzing disease-linked genetic variants via expression quantitative trait loci (eQTLs) is important for identifying potential disease-causing genes. Previous research prioritized genes by integrating Genome-Wide Association Study (GWAS) results with tissue-level eQTLs. Recent studies have explored brain cell type-specific eQTLs, but they lack a systematic analysis across various Alzheimer's disease (AD) GWAS datasets, nor did they compare effects between tissue and cell type levels or across different cell type-specific eQTL datasets. In this study, we integrated brain cell type-specific eQTL datasets with AD GWAS datasets to identify potential causal genes at the cell type level. Methods: To prioritize disease-causing genes, we used Summary Data-Based Mendelian Randomization (SMR) and Bayesian Colocalization (COLOC) to integrate AD GWAS summary statistics with cell-type-specific eQTLs. Combining data from five AD GWAS, three single-cell eQTL datasets, and one bulk tissue eQTL meta-analysis, we identified and confirmed both novel and known candidate causal genes. We investigated gene regulation through enhancer activity using H3K27ac and ATAC-seq data, performed protein-protein interaction and pathway enrichment analyses, and conducted a drug/compound enrichment analysis with the Drug Signatures Database (DSigDB) to support drug repurposing for AD. Results: We identified 27 candidate causal genes for AD using cell type-specific eQTL datasets, with the highest numbers in microglia, followed by excitatory neurons, astrocytes, inhibitory neurons, oligodendrocytes, and oligodendrocyte precursor cells (OPCs). PABPC1 emerged as a novel astrocyte-specific gene. Our analysis revealed protein-protein interaction (PPI) networks for these causal genes in microglia and astrocytes. We found the "regulation of aspartic-type peptidase activity" pathway being the most enriched among all the causal genes. AD-risk variants associated with candidate causal gene PABPC1 is located near or within enhancers only active in astrocytes. We classified the genes into three drug tiers and identified druggable interactions, with imatinib mesylate emerging as a key candidate. A drug-target gene network was created to explore potential drug targets for AD. Conclusions: We systematically prioritized AD candidate causal genes based on cell type-specific molecular evidence. The integrative approach enhances our understanding of molecular mechanisms of AD-related genetic variants and facilitates the interpretation of AD GWAS results.Item Pathway enrichment in genome‐wide analysis of longitudinal Alzheimer's disease biomarker endophenotypes(Wiley, 2024) Rosewood, Thea J.; Nho, Kwangsik; Risacher, Shannon L.; Liu, Shiwei; Gao, Sujuan; Shen, Li; Foroud, Tatiana; Saykin, Andrew J.; Alzheimer’s Disease Neuroimaging Initiative; Medical and Molecular Genetics, School of MedicineIntroduction: The genetic pathways that influence longitudinal heterogeneous changes in Alzheimer's disease (AD) may provide insight into disease mechanisms and potential therapeutic targets. Methods: Longitudinal endophenotypes from the Alzheimer's Disease Neuroimaging Initiative (ADNI) representing amyloid, tau, neurodegeneration (A/T/N), and cognition were selected. Genome-wide association analysis was performed using a linear mixed model (LMM) approach, followed by gene and pathway enrichment with significant and functionally relevant SNPs. Results: A total of 33 and 19 statistically significant pathways were identified associating with the intercept and longitudinal trajectory, respectively. The longitudinal intercept pathways represent eight groups: immune, metabolic, cell growth and survival, DNA maintenance, neuronal signaling, RAS/MAPK/ERK signaling pathways, vesicle and lysosomal transport, and transcription modification. Longitudinal trajectory pathways represented six groups: Immune, metabolic, cell signaling, cytoskeleton, and glycosylation. Discussion: Longitudinal enrichment identified pathways that uniquely associate with trajectories of key AD biomarkers and cognition, providing new insight into AD course-related mechanisms and potential new therapeutic targets. Highlights: A systematic genome-wide analysis with longitudinal AD biomarker endophenotypes was performed. Enriched pathways were identified with functionally derived SNP to gene analysis. Fifty-two pathways were associated with longitudinal trajectory and intercept. Many of the identified pathways are specific steps in larger pathways implicated in AD. The identified pathways may provide therapeutic targets and areas for further study.Item Pathway Enrichment of Longitudinal AD Endophenotypes Identifies Potential Therapeutic Targets for Modifying Disease Trajectory(Wiley, 2025-01-09) Jacobson Rosewood, Thea; Nho, Kwangsik; Risacher, Shannon L.; Liu, Shiwei; Gao, Sujuan; Saykin, Andrew J.; Radiology and Imaging Sciences, School of MedicineBackground: Alzheimer’s disease (AD) is characterized by longitudinal changes of biomarker endophenotypes over the course of the disease prodrome, onset, and progression. The genetic pathways that influence these heterogenous changes in longitudinal endophenotype trajectories may provide insight into disease mechanisms and represent potential therapeutic targets. Methods: Longitudinal endophenotypes from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) were selected: amyloid‐β (Amyloid PET and CSF), total tau and phosphorylated tau (CSF), glucose metabolism (FDG PET), neurodegeneration (atrophy on MRI), and cognition (composite scores for memory and executive functioning). Genome‐wide association analysis for the selected longitudinal endophenotypes was performed using Linear Mixed Modelling (LMM; LME4 R package), with (Time x Subject) as a random effect and age as the time variable. Gene‐based association analysis was performed using MAGMA on SNP P values from the LMM. The SNP to gene assignment was performed in two steps to select SNPs with a functional relation to each target gene: SNPs within gene transcription start and end positions, and SNPs that have significant eQTLs in brain tissue from the MetaBrain eQTL project. Gene‐based analysis results were then processed for gene‐set enrichment with MAGMA and the C2 curated gene set collection from the Gene Set Enrichment Analysis (GSEA) Molecular Signatures Database (MSigDB). Results: Pathway enrichment analysis identified 19 pathways (Figure 1) as significantly associated with longitudinal trajectories of AD endophenotypes. These pathways fall into six groups, with each pathway group having stronger association with different types of endophenotypes. Immune and cytoskeletal pathways largely associated with changes in amyloid trajectory. Metabolic pathways associated strongly with changes in amyloid and tau trajectories. Glycosylation pathways were associated with changes in brain atrophy. Pathways related to cell and neuronal signaling associated with changes in cognition, tau, and amyloid trajectories. Cell growth and survival was associated with changes in neurodegeneration trajectory (structural atrophy and hypometabolism). Conclusions: Pathway enrichment analysis of genetic variation associated with longitudinal changes of AD endophenotypes identified pathways that uniquely associate with trajectories of key AD biomarkers and cognition. These pathways may provide insight into AD pathological mechanisms and constitute new potential therapeutic targets to modify disease trajectory.Item Plasma miRNAs across the Alzheimer's disease continuum: Relationship to central biomarkers(Wiley, 2024) Liu, Shiwei; Park, Tamina; Krüger, Dennis M.; Pena-Centeno, Tonatiuh; Burkhardt, Susanne; Schutz, Anna-Lena; Huang, Yen-Ning; Rosewood, Thea; Chaudhuri, Soumilee; Cho, MinYoung; Risacher, Shannon L.; Wan, Yang; Shaw, Leslie M.; Sananbenesi, Farahnaz; Brodsky, Alexander S.; Lin, Honghuang; Krunic, Andre; Krzysztof Blusztajn, Jan; Saykin, Andrew J.; Delalle, Ivana; Fischer, Andre; Nho, Kwangsik; Alzheimer's Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of MedicineIntroduction: MicroRNAs (miRNAs) play important roles in gene expression regulation and Alzheimer's disease (AD) pathogenesis. Methods: We investigated the association between baseline plasma miRNAs and central AD biomarkers from the Alzheimer's Disease Neuroimaging Initiative (ADNI; N = 803): amyloid, tau, and neurodegeneration (A/T/N). Differentially expressed miRNAs and their targets were identified, followed by pathway enrichment analysis. Machine learning approaches were applied to investigate the role of miRNAs as blood biomarkers. Results: We identified nine, two, and eight miRNAs significantly associated with A/T/N positivity, respectively. We identified 271 genes targeted by amyloid-related miRNAs with estrogen signaling receptor-mediated signaling among the enriched pathways. Additionally, 220 genes targeted by neurodegeneration-related miRNAs showed enrichment in pathways including the insulin growth factor 1 pathway. The classification performance of demographic information for A/T/N positivity was increased up to 9% with the inclusion of miRNAs. Discussion: Plasma miRNAs were associated with central A/T/N biomarkers, highlighting their potential as blood biomarkers. Highlights: We performed association analysis of microRNAs (miRNAs) with amyloid/tau/neurodegeneration (A/T/N) biomarker positivity. We identified dysregulated miRNAs for A/T/N biomarker positivity. We identified Alzheimer's disease biomarker-specific/common pathways related to miRNAs. miRNAs improved the classification for A/T/N positivity by up to 9%. Our study highlights the potential of miRNAs as blood biomarkers.Item Replication stress increases de novo CNVs across the malaria parasite genome(bioRxiv, 2024-12-31) Brown, Noah; Luniewski, Aleksander; Yu, Xuanxuan; Warthan, Michelle; Liu, Shiwei; Zulawinska, Julia; Ahmad, Syed; Congdon, Molly; Santos, Webster; Xiao, Feifei; Guler, Jennifer L.; Radiology and Imaging Sciences, School of MedicineChanges in the copy number of large genomic regions, termed copy number variations (CNVs), contribute to important phenotypes in many organisms. CNVs are readily identified using conventional approaches when present in a large fraction of the cell population. However, CNVs that are present in only a few genomes across a population are often overlooked but important; if beneficial under specific conditions, a de novo CNV that arises in a single genome can expand during selection to create a larger population of cells with novel characteristics. While the reach of single cell methods to study de novo CNVs is increasing, we continue to lack information about CNV dynamics in rapidly evolving microbial populations. Here, we investigated de novo CNVs in the genome of the Plasmodium parasite that causes human malaria. The highly AT-rich P. falciparum genome readily accumulates CNVs that facilitate rapid adaptation to new drugs and host environments. We employed a low-input genomics approach optimized for this unique genome as well as specialized computational tools to evaluate the de novo CNV rate both before and after the application of stress. We observed a significant increase in genomewide de novo CNVs following treatment with a replication inhibitor. These stress-induced de novo CNVs encompassed genes that contribute to various cellular pathways and tended to be altered in clinical parasite genomes. This snapshot of CNV dynamics emphasizes the connection between replication stress, DNA repair, and CNV generation in this important microbial pathogen.Item Tau pathway-based gene analysis on PET identifies CLU and FYN in a Korean cohort(Wiley, 2025) Yi, Dahyun; Byun, Min Soo; Park, Jong-Ho; Kim, Jong-Won; Jung, Gijung; Ahn, Hyejin; Lee, Jun-Young; Lee, Yun-Sang; Kim, Yu Kyeong; Kang, Koung Mi; Sohn, Chul-Ho; Liu, Shiwei; Huang, Yen-Ning; Saykin, Andrew J.; Lee, Dong Young; Nho, Kwangsik; KBASE research group; Radiology and Imaging Sciences, School of MedicineIntroduction: The influence of genetic variation on tau protein aggregation, a key factor in Alzheimer's disease (AD), remains not fully understood. We aimed to identify novel genes associated with brain tau deposition using pathway-based candidate gene association analysis in a Korean cohort. Methods: We analyzed data for 146 older adults from the well-established Korean AD continuum cohort (Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer's Disease; KBASE). Fifteen candidate genes related to both tau pathways and AD were selected. Association analyses were performed using PLINK: A tool set for whole-genome association and population-based linkage analyses (PLINK) on tau deposition measured by 18F-AV-1451 positron emission tomography (PET) scans, with additional voxel-wise analysis conducted using Statistical Parametric Mapping 12 (SPM12). Results: CLU and FYN were significantly associated with tau deposition, with the most significant single-nucleotide polymorphisms (SNPs) being rs149413552 and rs57650567, respectively. These SNPs were linked to increased tau across key brain regions and showed additive effects with apolipoprotein E (APOE) ε4. Discussion: CLU and FYN may play specific roles in tau pathophysiology, offering potential targets for biomarkers and therapies. Highlights: Gene-based analysis identified CLU and FYN as associated with tau deposition on positron emission tomography (PET). CLU rs149413552 and FYN rs57650567 were associated with brain tau deposition. rs149413552 and rs57650567 were associated with structural brain atrophy. CLU rs149413552 was associated with immediate verbal memory. CLU and FYN may play specific roles in tau pathophysiology.