Browsing by Author "Wang, Minghui"

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    Integrative metabolomics-genomics approach reveals key metabolic pathways and regulators of Alzheimer's disease
    (Wiley, 2022) Horgusluoglu, Emrin; Neff, Ryan; Song, Won-Min; Wang, Minghui; Wang, Qian; Arnold, Matthias; Krumsiek, Jan; Galindo-Prieto, Beatriz; Ming, Chen; Nho, Kwangsik; Kastenmüller, Gabi; Han, Xianlin; Baillie, Rebecca; Zeng, Qi; Andrews, Shea; Cheng, Haoxiang; Hao, Ke; Goate, Alison; Bennett, David A.; Saykin, Andrew J.; Kaddurah-Daouk, Rima; Zhang, Bin; Alzheimer's Disease Neuroimaging Initiative (ADNI); Alzheimer Disease Metabolomics Consortium; Radiology and Imaging Sciences, School of Medicine
    Metabolites, the biochemical products of the cellular process, can be used to measure alterations in biochemical pathways related to the pathogenesis of Alzheimer's disease (AD). However, the relationships between systemic abnormalities in metabolism and the pathogenesis of AD are poorly understood. In this study, we aim to identify AD‐specific metabolomic changes and their potential upstream genetic and transcriptional regulators through an integrative systems biology framework for analyzing genetic, transcriptomic, metabolomic, and proteomic data in AD. Metabolite co‐expression network analysis of the blood metabolomic data in the Alzheimer's Disease Neuroimaging Initiative (ADNI) shows short‐chain acylcarnitines/amino acids and medium/long‐chain acylcarnitines are most associated with AD clinical outcomes, including episodic memory scores and disease severity. Integration of the gene expression data in both the blood from the ADNI and the brain from the Accelerating Medicines Partnership Alzheimer's Disease (AMP‐AD) program reveals ABCA1 and CPT1A are involved in the regulation of acylcarnitines and amino acids in AD. Gene co‐expression network analysis of the AMP‐AD brain RNA‐seq data suggests the CPT1A‐ and ABCA1‐centered subnetworks are associated with neuronal system and immune response, respectively. Increased ABCA1 gene expression and adiponectin protein, a regulator of ABCA1, correspond to decreased short‐chain acylcarnitines and amines in AD in the ADNI. In summary, our integrated analysis of large‐scale multiomics data in AD systematically identifies novel metabolites and their potential regulators in AD and the findings pave a way for not only developing sensitive and specific diagnostic biomarkers for AD but also identifying novel molecular mechanisms of AD pathogenesis.
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    Systems modeling of white matter microstructural abnormalities in Alzheimer's disease
    (Elsevier, 2020-02-04) Horgusluoglu-Moloch, Emrin; Xiao, Gaoyu; Wang, Minghui; Wang, Qian; Zhou, Xianxiao; Nho, Kwangsik; Saykin, Andrew J.; Schadt, Eric; Zhang, Bin; Alzheimer's Disease Neuroimaging Initiative (ADNI); Radiology and Imaging Sciences, School of Medicine
    INTRODUCTION: Microstructural abnormalities in white matter (WM) are often reported in Alzheimer's disease (AD). However, it is unclear which brain regions have the strongest WM changes in presymptomatic AD and what biological processes underlie WM abnormality during disease progression. METHODS: We developed a systems biology framework to integrate matched diffusion tensor imaging (DTI), genetic and transcriptomic data to investigate regional vulnerability to AD and identify genetic risk factors and gene subnetworks underlying WM abnormality in AD. RESULTS: We quantified regional WM abnormality and identified most vulnerable brain regions. A SNP rs2203712 in CELF1 was most significantly associated with several DTI-derived features in the hippocampus, the top ranked brain region. An immune response gene subnetwork in the blood was most correlated with DTI features across all the brain regions. DISCUSSION: Incorporation of image analysis with gene network analysis enhances our understanding of disease progression and facilitates identification of novel therapeutic strategies for AD.