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Carling GK, Fan L, Foxe NR, Norman K, Ye P, Wong MY, Zhu D, Yu F, Xu J, Yarahmady A, Chen H, Huang Y, Amin S, Zacharioudakis E, Chen X, Holtzman DM, Mok SA, Gavathiotis E, Sinha SC, Cheng F, Luo W, Gong S, Gan L. Alzheimer's disease-linked risk alleles elevate microglial cGAS-associated senescence and neurodegeneration in a tauopathy model. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.24.577107. [PMID: 38328219 PMCID: PMC10849737 DOI: 10.1101/2024.01.24.577107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
The strongest risk factors for Alzheimer's disease (AD) include the χ4 allele of apolipoprotein E (APOE), the R47H variant of triggering receptor expressed on myeloid cells 2 (TREM2), and female sex. Here, we combine APOE4 and TREM2R47H ( R47H ) in female P301S tauopathy mice to identify the pathways activated when AD risk is the strongest, thereby highlighting disease-causing mechanisms. We find that the R47H variant induces neurodegeneration in female APOE4 mice without impacting hippocampal tau load. The combination of APOE4 and R47H amplified tauopathy-induced cell-autonomous microglial cGAS-STING signaling and type-I interferon response, and interferon signaling converged across glial cell types in the hippocampus. APOE4-R47H microglia displayed cGAS- and BAX-dependent upregulation of senescence, showing association between neurotoxic signatures and implicating mitochondrial permeabilization in pathogenesis. By uncovering pathways enhanced by the strongest AD risk factors, our study points to cGAS-STING signaling and associated microglial senescence as potential drivers of AD risk.
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Zheng L, Shi S, Sun X, Lu M, Liao Y, Zhu S, Zhang H, Pan Z, Fang P, Zeng Z, Li H, Li Z, Xue W, Zhu F. MoDAFold: a strategy for predicting the structure of missense mutant protein based on AlphaFold2 and molecular dynamics. Brief Bioinform 2024; 25:bbae006. [PMID: 38305456 PMCID: PMC10835750 DOI: 10.1093/bib/bbae006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 12/26/2023] [Accepted: 01/01/2024] [Indexed: 02/03/2024] Open
Abstract
Protein structure prediction is a longstanding issue crucial for identifying new drug targets and providing a mechanistic understanding of protein functions. To enhance the progress in this field, a spectrum of computational methodologies has been cultivated. AlphaFold2 has exhibited exceptional precision in predicting wild-type protein structures, with performance exceeding that of other methods. However, predicting the structures of missense mutant proteins using AlphaFold2 remains challenging due to the intricate and substantial structural alterations caused by minor sequence variations in the mutant proteins. Molecular dynamics (MD) has been validated for precisely capturing changes in amino acid interactions attributed to protein mutations. Therefore, for the first time, a strategy entitled 'MoDAFold' was proposed to improve the accuracy and reliability of missense mutant protein structure prediction by combining AlphaFold2 with MD. Multiple case studies have confirmed the superior performance of MoDAFold compared to other methods, particularly AlphaFold2.
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Affiliation(s)
- Lingyan Zheng
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
- Industry Solutions Research and Development, Alibaba Cloud Computing, Hangzhou 330110, China
| | - Shuiyang Shi
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Xiuna Sun
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
- Industry Solutions Research and Development, Alibaba Cloud Computing, Hangzhou 330110, China
| | - Mingkun Lu
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
- Industry Solutions Research and Development, Alibaba Cloud Computing, Hangzhou 330110, China
| | - Yang Liao
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Sisi Zhu
- Key Laboratory of Elemene Class Anti-cancer Chinese Medicines, School of Pharmacy, Hangzhou Normal University, Hangzhou 311121, China
| | - Hongning Zhang
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Ziqi Pan
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Pan Fang
- Industry Solutions Research and Development, Alibaba Cloud Computing, Hangzhou 330110, China
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou 330110, China
| | - Zhenyu Zeng
- Industry Solutions Research and Development, Alibaba Cloud Computing, Hangzhou 330110, China
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou 330110, China
| | - Honglin Li
- School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China
| | - Zhaorong Li
- Industry Solutions Research and Development, Alibaba Cloud Computing, Hangzhou 330110, China
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou 330110, China
| | - Weiwei Xue
- School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
| | - Feng Zhu
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
- Industry Solutions Research and Development, Alibaba Cloud Computing, Hangzhou 330110, China
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou 330110, China
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Sun YY, Wang Z, Huang HC. Roles of ApoE4 on the Pathogenesis in Alzheimer's Disease and the Potential Therapeutic Approaches. Cell Mol Neurobiol 2023; 43:3115-3136. [PMID: 37227619 PMCID: PMC10211310 DOI: 10.1007/s10571-023-01365-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 05/17/2023] [Indexed: 05/26/2023]
Abstract
The Apolipoprotein E ε4 (ApoE ε4) allele, encoding ApoE4, is the strongest genetic risk factor for late-onset Alzheimer's disease (LOAD). Emerging epidemiological evidence indicated that ApoE4 contributes to AD through influencing β-amyloid (Aβ) deposition and clearance. However, the molecular mechanisms of ApoE4 involved in AD pathogenesis remains unclear. Here, we introduced the structure and functions of ApoE isoforms, and then we reviewed the potential mechanisms of ApoE4 in the AD pathogenesis, including the effect of ApoE4 on Aβ pathology, and tau phosphorylation, oxidative stress; synaptic function, cholesterol transport, and mitochondrial dysfunction; sleep disturbances and cerebrovascular integrity in the AD brains. Furthermore, we discussed the available strategies for AD treatments that target to ApoE4. In general, this review overviews the potential roles of ApoE4 in the AD development and suggests some therapeutic approaches for AD. ApoE4 is genetic risk of AD. ApoE4 is involved in the AD pathogenesis. Aβ deposition, NFT, oxidative stress, abnormal cholesterol, mitochondrial dysfunction and neuroinflammation could be observed in the brains with ApoE4. Targeting the interaction of ApoE4 with the AD pathology is available strategy for AD treatments.
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Affiliation(s)
- Yu-Ying Sun
- Beijing Key Laboratory of Bioactive Substances and Functional Foods, Beijing Union University, Beijing, 100191 China
- Key Laboratory of Natural Products Development and Innovative Drug Research, Beijing Union University, Beijing, 100023 China
| | - Zhun Wang
- Beijing Key Laboratory of Bioactive Substances and Functional Foods, Beijing Union University, Beijing, 100191 China
- Key Laboratory of Natural Products Development and Innovative Drug Research, Beijing Union University, Beijing, 100023 China
| | - Han-Chang Huang
- Beijing Key Laboratory of Bioactive Substances and Functional Foods, Beijing Union University, Beijing, 100191 China
- Key Laboratory of Natural Products Development and Innovative Drug Research, Beijing Union University, Beijing, 100023 China
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Theron D, Hopkins LN, Sutherland HG, Griffiths LR, Fernandez F. Can Genetic Markers Predict the Sporadic Form of Alzheimer's Disease? An Updated Review on Genetic Peripheral Markers. Int J Mol Sci 2023; 24:13480. [PMID: 37686283 PMCID: PMC10488021 DOI: 10.3390/ijms241713480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 08/22/2023] [Accepted: 08/25/2023] [Indexed: 09/10/2023] Open
Abstract
Alzheimer's disease (AD) is the most common form of dementia that affects millions of individuals worldwide. Although the research over the last decades has provided new insight into AD pathophysiology, there is currently no cure for the disease. AD is often only diagnosed once the symptoms have become prominent, particularly in the late-onset (sporadic) form of AD. Consequently, it is essential to further new avenues for early diagnosis. With recent advances in genomic analysis and a lower cost of use, the exploration of genetic markers alongside RNA molecules can offer a key avenue for early diagnosis. We have here provided a brief overview of potential genetic markers differentially expressed in peripheral tissues in AD cases compared to controls, as well as considering the changes to the dynamics of RNA molecules. By integrating both genotype and RNA changes reported in AD, biomarker profiling can be key for developing reliable AD diagnostic tools.
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Affiliation(s)
- Danelda Theron
- School of Behavioural and Health Sciences, Faculty of Heath Sciences, Australian Catholic University, Banyo, QLD 4014, Australia;
- Centre for Genomics and Personalised Health, School of Biomedical Sciences, Queensland University of Technology, 60 Musk Ave, Kelvin Grove, QLD 4059, Australia; (L.N.H.); (H.G.S.); (L.R.G.)
| | - Lloyd N. Hopkins
- Centre for Genomics and Personalised Health, School of Biomedical Sciences, Queensland University of Technology, 60 Musk Ave, Kelvin Grove, QLD 4059, Australia; (L.N.H.); (H.G.S.); (L.R.G.)
| | - Heidi G. Sutherland
- Centre for Genomics and Personalised Health, School of Biomedical Sciences, Queensland University of Technology, 60 Musk Ave, Kelvin Grove, QLD 4059, Australia; (L.N.H.); (H.G.S.); (L.R.G.)
| | - Lyn R. Griffiths
- Centre for Genomics and Personalised Health, School of Biomedical Sciences, Queensland University of Technology, 60 Musk Ave, Kelvin Grove, QLD 4059, Australia; (L.N.H.); (H.G.S.); (L.R.G.)
| | - Francesca Fernandez
- School of Behavioural and Health Sciences, Faculty of Heath Sciences, Australian Catholic University, Banyo, QLD 4014, Australia;
- Centre for Genomics and Personalised Health, School of Biomedical Sciences, Queensland University of Technology, 60 Musk Ave, Kelvin Grove, QLD 4059, Australia; (L.N.H.); (H.G.S.); (L.R.G.)
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Upregulation of APOC1 Promotes Colorectal Cancer Progression and Serves as a Potential Therapeutic Target Based on Bioinformatics Analysis. JOURNAL OF ONCOLOGY 2023; 2023:2611105. [PMID: 36908705 PMCID: PMC9995190 DOI: 10.1155/2023/2611105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 10/11/2022] [Indexed: 03/05/2023]
Abstract
Background Approximately 10% of cancer patients worldwide have colorectal cancer (CRC), a prevalent gastrointestinal malignancy with substantial mortality and morbidity. The purpose of this work was to investigate the APOC1 gene's expression patterns in the CRC tumor microenvironment and, using the findings from bioinformatics, to assess the biological function of APOC1 in the development of CRC. Methods The TCGA portal was employed in this investigation to find APOC1 expression in CRC. Its correlation with other genes and clinicopathological data was examined using the UALCAN database. To validate APOC1's cellular location, the Human Protein was employed. In order to forecast the relationship between APOC1 expression and prognosis in CRC patients, the Kaplan-Meier plotter database was used. TISIDB was also employed to evaluate the connection between immune responses and APOC1 expression in CRC. The interactions of APOC1 with other proteins were predicted using STRING. In order to understand the factors that contribute to liver metastasis from CRC, single-cell RNA sequencing (scRNA-seq) was done on one patient who had the disease. This procedure included sampling preoperative blood and the main colorectal cancer tissues, surrounding colorectal cancer normal tissues, liver metastatic cancer tissues, and normal liver tissues. Finally, an in vitro knockdown method was used to assess how APOC1 expression in tumor-associated macrophages (TAMs) affected CRC cancer cell growth and migration. Results When compared to paracancerous tissues, APOC1 expression was considerably higher in CRC tissues. The clinicopathological stage and the prognosis of CRC patients had a positive correlation with APOC1 upregulation and a negative correlation, respectively. APOC1 proteins are mostly found in cell cytosols where they may interact with APOE, RAB42, and TREM2. APOC1 was also discovered to have a substantial relationship with immunoinhibitors (CD274, IDO1, and IL10) and immunostimulators (PVR, CD86, and ICOS). According to the results of scRNA-seq, we found that TAMs of CRC tissues had considerably more APOC1 than other cell groups. The proliferation and migration of CRC cells were impeded in vitro by APOC1 knockdown in TAMs. Conclusion Based on scRNA-seq research, the current study shows that APOC1 was overexpressed in TAMs from CRC tissues. By inhibiting APOC1 in TAMs, CRC progression was reduced in vitro, offering a new tactic and giving CRC patients fresh hope.
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