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Piergiorge RM, da Silva Francisco Junior R, de Vasconcelos ATR, Santos-Rebouças CB. Multi-layered transcriptomic analysis reveals a pivotal role of FMR1 and other developmental genes in Alzheimer's disease-associated brain ceRNA network. Comput Biol Med 2023; 166:107494. [PMID: 37769462 DOI: 10.1016/j.compbiomed.2023.107494] [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: 05/08/2023] [Revised: 09/05/2023] [Accepted: 09/15/2023] [Indexed: 09/30/2023]
Abstract
Alzheimer's disease (AD) is an increasingly neurodegenerative disorder that causes progressive cognitive decline and memory impairment. Despite extensive research, the underlying causes of late-onset AD (LOAD) are still in progress. This study aimed to establish a network of competing regulatory interactions involving circular RNAs (circRNAs), microRNAs (miRNAs), RNA-binding proteins (RBPs), and messenger RNAs (mRNAs) connected to LOAD. A systematic analysis of publicly available expression data was conducted to identify integrated differentially expressed genes (DEGs) from the hippocampus of LOAD patients. Subsequently, gene co-expression analysis identified modules comprising highly expressed DEGs that act cooperatively. The competition between co-expressed DEGs and miRNAs/RBPs and the simultaneous interactions between circRNA and miRNA/RBP revealed a complex ceRNA network responsible for post-transcriptional regulation in LOAD. Hippocampal expression data for miRNAs, circRNAs, and RBPs were used to filter relevant relationships for AD. An integrated topological score was used to identify the highly connected hub gene, from which a brain core ceRNA subnetwork was generated. The Fragile X Messenger Ribonucleoprotein 1 (FMR1) coding for the RBP FMRP emerged as the prominent driver gene in this subnetwork. FMRP has been previously related to AD but not in a ceRNA network context. Also, the substantial number of neurodevelopmental genes in the ceRNA subnetwork and their related biological pathways strengthen that AD shares common pathological mechanisms with developmental conditions. Our results enhance the current knowledge about the convergent ceRNA regulatory pathways underlying AD and provide potential targets for identifying early biomarkers and developing novel therapeutic interventions.
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Affiliation(s)
- Rafael Mina Piergiorge
- Department of Genetics, Institute of Biology Roberto Alcantara Gomes, State University of Rio de Janeiro, Rio de Janeiro, Brazil
| | | | | | - Cíntia Barros Santos-Rebouças
- Department of Genetics, Institute of Biology Roberto Alcantara Gomes, State University of Rio de Janeiro, Rio de Janeiro, Brazil.
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Hamza EA, Moustafa AA, Tindle R, Karki R, Nalla S, Hamid MS, El Haj M. Effect of APOE4 Allele and Gender on the Rate of Atrophy in the Hippocampus, Entorhinal Cortex, and Fusiform Gyrus in Alzheimer's Disease. Curr Alzheimer Res 2023; 19:CAR-EPUB-130079. [PMID: 36892120 DOI: 10.2174/1567205020666230309113749] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 02/21/2023] [Accepted: 02/25/2023] [Indexed: 03/10/2023]
Abstract
BACKGROUND The hippocampus, entorhinal cortex, and fusiform gyrus are brain areas that deteriorate during early-stage Alzheimer's disease (AD). The ApoE4 allele has been identified as a risk factor for AD development, is linked to an increase in the aggregation of amyloid ß (Aß) plaques in the brain, and is responsible for atrophy of the hippocampal area. However, to our knowledge, the rate of deterioration over time in individuals with AD, with or without the ApoE4 allele, has not been investigated. METHOD In this study, we, for the first time, analyze atrophy in these brain structures in AD patients with and without the ApoE4 using the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. RESULTS It was found that the rate of decrease in the volume of these brain areas over 12 months was related to the presence of ApoE4. Further, we found that neural atrophy was not different for female and male patients, unlike prior studies, suggesting that the presence of ApoE4 is not linked to the gender difference in AD. CONCLUSION Our results confirm and extend previous findings, showing that the ApoE4 allele gradually impacts brain regions impacted by AD.
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Affiliation(s)
- Eid Abo Hamza
- Faculty of Education, Department of Mental Health, Tanta University, Egypt
- College of Education, Humanities & Social Sciences, Al Ain University, UAE
| | - Ahmed A Moustafa
- School of Psychology, Faculty of Society and Design, Bond University, Gold Coast, Queensland, Australia
- Department of Human Anatomy and Physiology, the Faculty of Health Sciences, University of Johannesburg, South Africa
| | - Richard Tindle
- Department of Psychology, University of the Sunshine Coast, Sunshine Coast, Queensland, Australia
| | - Rasu Karki
- Department of Psychology, Western Sydney University, Penrith, NSW, 2214, Australia
| | - Shahed Nalla
- Department of Human Anatomy and Physiology, the Faculty of Health Sciences, University of Johannesburg, South Africa
| | | | - Mohamad El Haj
- Laboratoire de Psychologie des Pays de la Loire (LPPL - EA 4638), Nantes Université, Univ. Angers., Nantes, F-44000, France
- Clinical Gerontology Department, CHU Nantes, Bd Jacques Monod,Nantes, F44093, France
- Institut Universitaire de France, Paris, France
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Zou T, Duan Y, Zhou X, Chen W, Ying X, Liu G, Zhao Y, Zhu M, Pari A, Alimu K, Miao H, Kabinur K, Zhang L, Wang Q, Duan S. Significant association of 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) rs3846662 and sirtuin 1 (SIRT1) rs7895833 and apolipoprotein E (APOE) hypermethylation with mild cognitive impairment (MCI). Medicine (Baltimore) 2019; 98:e16405. [PMID: 31305452 PMCID: PMC6641831 DOI: 10.1097/md.0000000000016405] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
Our study investigated the association of five genes with MCI in the Xinjiang Uygur population in China. In addition, we also analyzed the association between APOE methylation and MCI.Forty-three MCI and 125 controls were included in the present study. Genotyping was done by Sanger sequencing. DNA methylation assay was done using quantitative methylation-specific polymerase chain reaction (qMSP).The distribution of HMGCR rs3846662 allele frequencies was significantly different between the MCI group and the control group (P = .04), especially in women (P = .032). Subgroup analysis showed that there was a statistically significant association of HMGCR rs3846662 with MCI in the non-APOE ε4 group (P = .024), especially in the females with non-APOE ε4. Similarly, HMGCR rs3846662 genotype and allele frequency in the ApoE E2 protein group were significantly different in the MCI group and the control group (genotype P = .021; allele P = .007). In addition, SIRT1 rs7895833 genotype frequency in the APOE ε4 group was found to be significantly different between the MCI and the control group (P = .005). We also observed a significant association of SIRT1 rs7895833 with MCI in the ApoE E4 protein subgroup (P = .005). In addition, APOE methylation levels were significantly different between the MCI group and the control group (P = .021), especially in men (P = .006). Subgroup analysis showed that APOE methylation levels were significantly associated with MCI in the non-APOE ε4 group (P = .009), especially in men (P = .015).This study found a significant association of HMGCR rs3846662 with MCI in females independent of APOE ε4. In contrast, we revealed that the association of SIRT1 rs7895833 with MCI was dependent on with APOE ε4. We also showed that hypermethylation of APOE in MCI was independent of APOE ε4.
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Affiliation(s)
- Ting Zou
- Department of Geriatrics, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang Province
| | - Yali Duan
- Department of Geriatrics, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang Province
| | - Xiaohui Zhou
- Department of Geriatrics, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang Province
| | - Wei Chen
- Department of Geriatrics, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang Province
| | - Xiuru Ying
- Ningbo Key Lab of Behavior Neuroscience, Zhejiang Provincial Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, Zhejiang Province, China
| | - Guili Liu
- Ningbo Key Lab of Behavior Neuroscience, Zhejiang Provincial Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, Zhejiang Province, China
| | - Yongjie Zhao
- Department of Geriatrics, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang Province
| | - Meisheng Zhu
- Department of Geriatrics, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang Province
| | - Abuliz Pari
- Department of Geriatrics, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang Province
| | - Kader Alimu
- Department of Geriatrics, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang Province
| | - Haijun Miao
- Department of Geriatrics, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang Province
| | - Keyim Kabinur
- Department of Geriatrics, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang Province
| | - Lei Zhang
- Department of Geriatrics, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang Province
| | - Qinwen Wang
- Ningbo Key Lab of Behavior Neuroscience, Zhejiang Provincial Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, Zhejiang Province, China
| | - Shiwei Duan
- Ningbo Key Lab of Behavior Neuroscience, Zhejiang Provincial Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, Zhejiang Province, China
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Ma S, Sun W, Gao L, Liu S. Therapeutic targets of hypercholesterolemia: HMGCR and LDLR. Diabetes Metab Syndr Obes 2019; 12:1543-1553. [PMID: 31686875 PMCID: PMC6709517 DOI: 10.2147/dmso.s219013] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Accepted: 07/25/2019] [Indexed: 12/14/2022] Open
Abstract
Cholesterol homeostasis is critical and necessary for the body's functions. Hypercholesterolemia can lead to significant clinical problems, such as cardiovascular disease (CVD). 3-Hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR) and low-density lipoprotein cholesterol receptor (LDLR) are major points of control in cholesterol homeostasis. We summarize the regulatory mechanisms of HMGCR and LDLR, which may provide insight for new drug design and development.
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Affiliation(s)
- Shizhan Ma
- Department of Endocrinology and Metabolism, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan250021, People’s Republic of China
- Department of Endocrinology and Metabolism, Shandong Provincial Hospital Affiliated to Shandong University, Jinan250021, People’s Republic of China
| | - Wenxiu Sun
- Department of Pharmacy, Taishan Vocational College of Nursing, Taian271000, People’s Republic of China
| | - Ling Gao
- Department of Endocrinology and Metabolism, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan250021, People’s Republic of China
- Scientific Center, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan250021, People’s Republic of China
- Scientific Center, Shandong Provincial Hospital Affiliated to Shandong University, Jinan250021, People’s Republic of China
- Correspondence: Ling GaoScientific Center, Shandong Provincial Hospital Affiliated to Shandong University, 324 Jing 5 Road, Jinan, Shandong Province250021, People’s Republic of ChinaTel +86 531 6877 6910Email
| | - Shudong Liu
- Department of Endocrinology, Shandong Rongjun General Hospital, Jinan250013, People’s Republic of China
- Shudong LiuDepartment of Endocrinology, Shandong Rongjun General Hospital, 23 Jiefang Road, Jinan, Shandong Province250013, People’s Republic of ChinaTel +86 531 8238 2351Email
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Veitch DP, Weiner MW, Aisen PS, Beckett LA, Cairns NJ, Green RC, Harvey D, Jack CR, Jagust W, Morris JC, Petersen RC, Saykin AJ, Shaw LM, Toga AW, Trojanowski JQ. Understanding disease progression and improving Alzheimer's disease clinical trials: Recent highlights from the Alzheimer's Disease Neuroimaging Initiative. Alzheimers Dement 2018; 15:106-152. [PMID: 30321505 DOI: 10.1016/j.jalz.2018.08.005] [Citation(s) in RCA: 249] [Impact Index Per Article: 41.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2018] [Accepted: 08/21/2018] [Indexed: 02/06/2023]
Abstract
INTRODUCTION The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI is a multisite, longitudinal, observational study that has collected many biomarkers since 2004. Recent publications highlight the multifactorial nature of late-onset AD. We discuss selected topics that provide insights into AD progression and outline how this knowledge may improve clinical trials. METHODS We used standard methods to identify nearly 600 publications using ADNI data from 2016 and 2017 (listed in Supplementary Material and searchable at http://adni.loni.usc.edu/news-publications/publications/). RESULTS (1) Data-driven AD progression models supported multifactorial interactions rather than a linear cascade of events. (2) β-Amyloid (Aβ) deposition occurred concurrently with functional connectivity changes within the default mode network in preclinical subjects and was followed by specific and progressive disconnection of functional and anatomical networks. (3) Changes in functional connectivity, volumetric measures, regional hypometabolism, and cognition were detectable at subthreshold levels of Aβ deposition. 4. Tau positron emission tomography imaging studies detailed a specific temporal and spatial pattern of tau pathology dependent on prior Aβ deposition, and related to subsequent cognitive decline. 5. Clustering studies using a wide range of modalities consistently identified a "typical AD" subgroup and a second subgroup characterized by executive impairment and widespread cortical atrophy in preclinical and prodromal subjects. 6. Vascular pathology burden may act through both Aβ dependent and independent mechanisms to exacerbate AD progression. 7. The APOE ε4 allele interacted with cerebrovascular disease to impede Aβ clearance mechanisms. 8. Genetic approaches identified novel genetic risk factors involving a wide range of processes, and demonstrated shared genetic risk for AD and vascular disorders, as well as the temporal and regional pathological associations of established AD risk alleles. 9. Knowledge of early pathological changes guided the development of novel prognostic biomarkers for preclinical subjects. 10. Placebo populations of randomized controlled clinical trials had highly variable trajectories of cognitive change, underscoring the importance of subject selection and monitoring. 11. Selection criteria based on Aβ positivity, hippocampal volume, baseline cognitive/functional measures, and APOE ε4 status in combination with improved cognitive outcome measures were projected to decrease clinical trial duration and cost. 12. Multiple concurrent therapies targeting vascular health and other AD pathology in addition to Aβ may be more effective than single therapies. DISCUSSION ADNI publications from 2016 and 2017 supported the idea of AD as a multifactorial disease and provided insights into the complexities of AD disease progression. These findings guided the development of novel biomarkers and suggested that subject selection on the basis of multiple factors may lower AD clinical trial costs and duration. The use of multiple concurrent therapies in these trials may prove more effective in reversing AD disease progression.
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Affiliation(s)
- Dallas P Veitch
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA; Northern California Institute for Research and Education (NCIRE), Department of Veterans Affairs Medical Center, San Francisco, CA, USA
| | - Michael W Weiner
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA; Department of Radiology, University of California, San Francisco, CA, USA; Department of Medicine, University of California, San Francisco, CA, USA; Department of Psychiatry, University of California, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, CA, USA.
| | - Paul S Aisen
- Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, CA, USA
| | - Laurel A Beckett
- Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA, USA
| | - Nigel J Cairns
- Knight Alzheimer's Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA; Department of Neurology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Robert C Green
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Danielle Harvey
- Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA, USA
| | | | - William Jagust
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA
| | - John C Morris
- Knight Alzheimer's Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA
| | | | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Arthur W Toga
- Laboratory of Neuroimaging, Institute of Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Institute on Aging, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Alzheimer's Disease Core Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Udall Parkinson's Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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