Browsing by Author "Huang, Yen-Ning"
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Item Association between known Alzheimer’s disease risk genetic variants and hippocampal atrophy along the Alzheimer’s disease continuum in a Korean cohort(Wiley, 2025-01-03) Ahn, Hyejin; Byun, Min Soo; Yi, Dahyun; Jung, Gijung; Huang, Yen-Ning; Risacher, Shannon L.; Griswold, Anthony J.; Pericak-Vance, Margaret A.; Kim, Yu Kyeong; Lee, Yun-Sang; Sohn, Chul-Ho; Kang, Koung Mi; Lee, Jun-Young; Saykin, Andrew J.; Nho, Kwangsik; Lee, Dong Young; Radiology and Imaging Sciences, School of MedicineBackground: Large‐scale genome‐wide association studies (GWAS) of Alzheimer’s disease (AD) from European ancestry identified many genetic variants associated with clinical diagnosis of AD dementia. However, it remains unclear whether these AD‐related variants are associated with AD biomarkers, particularly hippocampal atrophy, a well‐known neurodegeneration biomarker of AD in a Korean population. In this study, we investigated the association between known AD risk single nucleotide polymorphisms (SNPs) and hippocampal atrophy along the AD continuum in older Korean adults. Method: A total of 487 participants (258 cognitively normal olde adults [CN], 144 mild cognitive impairment [MCI], 85 AD dementia) from the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer’s disease (KBASE) were included for analysis. All participants underwent 11C‐PiB‐PET/MRI. Hippocampal volume adjusted for intracranial volume (HVa) was obtained from 3D T1‐weighted MRI scans using FreeSurfer and used as a neurodegeneration marker of AD. Global beta‐amyloid (Aβ) deposition was calculated from PiB uptake in the global cortical region‐of‐interest using SPM12. From the genetic evidence gathered by the AD Sequencing Project (ADSP), which consists of 76 SNPs associated with AD, we selected 38 SNPs with a minor allele frequency (MAF) greater than 1% from the genotyping data imputed using the TOPMed imputation server in the KBASE cohort. Result: Among 38 known AD‐related SNPs, three SNPs (rs6966331 in EPDR1, rs2242595 in MYO15A, and rs17125924 in FERMT2) were associated with HVa in an initial exploratory analysis (p<0.05). In a subsequent confirmatory analysis, the associations of rs6966331 in EPDR1 and rs2242595 in MYO15A with HVa remained significant after controlling for age, sex, and APOE4 carrier status, as well as global Aβ deposition (p<0.001 and p = 0.009 for rs6966331 and rs2242595, respectively) (Table 1). Conclusion: Our study identified associations of rs6966331 in EPDR1 and rs2242595 in MYO15A with hippocampal volume in Korean older adults, and these associations were independent of cerebral Aβ deposition and APOE4 carrier status. These findings suggest that these AD‐related loci may contribute to the development of AD dementia via Aβ‐independent neurodegeneration.Item Association of amyloid and cardiovascular risk with cognition: Findings from KBASE(Wiley, 2024) Chaudhuri, Soumilee; Dempsey, Desarae A.; Huang, Yen-Ning; Park, Tamina; Cao, Sha; Chumin, Evgeny J.; Craft, Hannah; Crane, Paul K.; Mukherjee, Shubhabrata; Choi, Seo-Eun; Scollard, Phoebe; Lee, Michael; Nakano, Connie; Mez, Jesse; Trittschuh, Emily H.; Klinedinst, Brandon S.; Hohman, Timothy J.; Lee, Jun-Young; Kang, Koung Mi; Sohn, Chul-Ho; Kim, Yu Kyeong; Yi, Dahyun; Byun, Min Soo; Risacher, Shannon L.; Nho, Kwangsik; Saykin, Andrew J.; Lee, Dong Young; KBASE Research Group; Radiology and Imaging Sciences, School of MedicineBackground: Limited research has explored the effect of cardiovascular risk and amyloid interplay on cognitive decline in East Asians. Methods: Vascular burden was quantified using Framingham's General Cardiovascular Risk Score (FRS) in 526 Korean Brain Aging Study (KBASE) participants. Cognitive differences in groups stratified by FRS and amyloid positivity were assessed at baseline and longitudinally. Results: Baseline analyses revealed that amyloid-negative (Aβ-) cognitively normal (CN) individuals with high FRS had lower cognition compared to Aβ- CN individuals with low FRS (p < 0.0001). Longitudinally, amyloid pathology predominantly drove cognitive decline, while FRS alone had negligible effects on cognition in CN and mild cognitive impairment (MCI) groups. Conclusion: Our findings indicate that managing vascular risk may be crucial in preserving cognition in Aβ- individuals early on and before the clinical manifestation of dementia. Within the CN and MCI groups, irrespective of FRS status, amyloid-positive individuals had worse cognitive performance than Aβ- individuals. Highlights: Vascular risk significantly affects cognition in amyloid-negative older Koreans. Amyloid-negative CN older adults with high vascular risk had lower baseline cognition. Amyloid pathology drives cognitive decline in CN and MCI, regardless of vascular risk. The study underscores the impact of vascular health on the AD disease spectrum.Item Associations between Amyloid, Cardiovascular Risk, and Cognitive Function in Korean Older Adults: Insights from the KBASE Cohort(Wiley, 2025-01-09) Chaudhuri, Soumilee; Dempsey, Desarae A.; Huang, Yen-Ning; Cao, Sha; Chumin, Evgeny J.; Craft, Hannah; Crane, Paul K.; Mukherjee, Shubhabrata; Choi, Seo-Eun; Lee, Michael L.; Scollard, Phoebe; Mez, Jesse; Trittschuh, Emily H.; Klinedinst, Brandon S.; Nakano, Connie; Hohman, Timothy J.; Yi, Dahyun; Byun, Min Soo; Risacher, Shannon L.; Nho, Kwangsik; Saykin, Andrew J.; Lee, Dong Young; Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer’s Disease (KBASE); Radiology and Imaging Sciences, School of MedicineBackground: Understanding the relationship between cardiovascular burden, amyloid, and cognition in Alzheimer’s disease (AD) is essential for targeted interventions, especially in ethnically diverse populations where research remains limited. This study aimed to investigate these relationships in a cohort of Korean older adults along the AD spectrum. Method: 526 participants from the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer’s Disease (KBASE) cohort were included in this study. Vascular burden was quantified using Framingham Risk Score (FRS) and participants were categorized into four groups based on combinations of FRS (FRS High or FRS Low with a median split) and amyloid status (Aβ+ or Aβ‐ based on a cut‐off of 1.2373). Cognitive function was evaluated using standardized neuropsychological tests processed with structural equation models to produce domain scores for memory, executive functioning, language, and visuospatial. ANOVA was employed at baseline to analyze cognitive differences among these groups and within each clinical diagnosis. Longitudinal mixed effects models spanning a period of four years from the initial visit captured cognitive changes over time within these groups (Figure 1). Result: Significant group and pairwise differences were observed among the four groups in all cognitive domains (p < 0.0001). Stratified analysis within each clinical diagnoses group revealed that CN individuals in FRS high Aβ‐ demonstrated significantly lower memory scores compared to those with FRS low Aβ‐ (p < 0.0001), this trend was absent from MCI and AD groups (Figure 2). Longitudinally, FRS high Aβ+ and FRS low Aβ+ groups consistently demonstrated lower memory scores compared to the FRS low Aβ‐ group. Interestingly, no significant difference in cognition was observed between FRS high Aβ‐ and FRS low Aβ‐ groups over time. However, the most pronounced divergence in longitudinal cognition of the four FRS and Amyloid groups was observed within the MCI diagnosis group (Figure 3). Conclusion: This study highlights the differential impact of cardiovascular risk on cognition depending on amyloid status and clinical diagnosis group. This underscores the importance of considering both cardiovascular risk factors and amyloid pathology early‐on in understanding clinical manifestation and cognitive decline in the AD spectrum, particularly in ethnically diverse populations.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 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 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 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.Item The plasma miRNAome in ADNI: Signatures to aid the detection of at-risk individuals(Wiley, 2024) Krüger, Dennis M.; Pena-Centeno, Tonatiuh; Liu, Shiwei; Park, Tamina; Kaurani, Lalit; Pradhan, Ranjit; Huang, Yen-Ning; Risacher, Shannon L.; Burkhardt, Susanne; Schütz, Anna-Lena; Wan, Yang; Shaw, Leslie M.; Brodsky, Alexander S.; DeStefano, Anita L.; Lin, Honghuang; Schroeder, Robert; Krunic, Andre; Hempel, Nina; Sananbenesi, Farahnaz; Krzysztof Blusztajn, Jan; Saykin, Andrew J.; Delalle, Ivana; Nho, Kwangsik; Fischer, Andre; Alzheimer's Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of MedicineIntroduction: MicroRNAs are short non-coding RNAs that control proteostasis at the systems level and are emerging as potential prognostic and diagnostic biomarkers for Alzheimer's disease (AD). Methods: We performed small RNA sequencing on plasma samples from 847 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants. Results: We identified microRNA signatures that correlate with AD diagnoses and help predict the conversion from mild cognitive impairment (MCI) to AD. Discussion: Our data demonstrate that plasma microRNA signatures can be used to not only diagnose MCI, but also, critically, predict the conversion from MCI to AD. Moreover, combined with neuropsychological testing, plasma microRNAome evaluation helps predict MCI to AD conversion. These findings are of considerable public interest because they provide a path toward reducing indiscriminate utilization of costly and invasive testing by defining the at-risk segment of the aging population. Highlights: We provide the first analysis of the plasma microRNAome for the ADNI study. The levels of several microRNAs can be used as biomarkers for the prediction of conversion from MCI to AD. Adding the evaluation of plasma microRNA levels to neuropsychological testing in a clinical setting increases the accuracy of MCI to AD conversion prediction.