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Gao J, Zou Y, Lv XY, Chen L, Hou XG. Novel insights into immune-related genes associated with type 2 diabetes mellitus-related cognitive impairment. World J Diabetes 2024; 15:735-757. [PMID: 38680704 PMCID: PMC11045412 DOI: 10.4239/wjd.v15.i4.735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Revised: 01/21/2024] [Accepted: 03/04/2024] [Indexed: 04/11/2024] Open
Abstract
BACKGROUND The cognitive impairment in type 2 diabetes mellitus (T2DM) is a multifaceted and advancing state that requires further exploration to fully comprehend. Neuroinflammation is considered to be one of the main mechanisms and the immune system has played a vital role in the progression of the disease. AIM To identify and validate the immune-related genes in the hippocampus associated with T2DM-related cognitive impairment. METHODS To identify differentially expressed genes (DEGs) between T2DM and controls, we used data from the Gene Expression Omnibus database GSE125387. To identify T2DM module genes, we used Weighted Gene Co-Expression Network Analysis. All the genes were subject to Gene Set Enrichment Analysis. Protein-protein interaction network construction and machine learning were utilized to identify three hub genes. Immune cell infiltration analysis was performed. The three hub genes were validated in GSE152539 via receiver operating characteristic curve analysis. Validation experiments including reverse transcription quantitative real-time PCR, Western blotting and immunohistochemistry were conducted both in vivo and in vitro. To identify potential drugs associated with hub genes, we used the Comparative Toxicogenomics Database (CTD). RESULTS A total of 576 DEGs were identified using GSE125387. By taking the intersection of DEGs, T2DM module genes, and immune-related genes, a total of 59 genes associated with the immune system were identified. Afterward, machine learning was utilized to identify three hub genes (H2-T24, Rac3, and Tfrc). The hub genes were associated with a variety of immune cells. The three hub genes were validated in GSE152539. Validation experiments were conducted at the mRNA and protein levels both in vivo and in vitro, consistent with the bioinformatics analysis. Additionally, 11 potential drugs associated with RAC3 and TFRC were identified based on the CTD. CONCLUSION Immune-related genes that differ in expression in the hippocampus are closely linked to microglia. We validated the expression of three hub genes both in vivo and in vitro, consistent with our bioinformatics results. We discovered 11 compounds associated with RAC3 and TFRC. These findings suggest that they are co-regulatory molecules of immunometabolism in diabetic cognitive impairment.
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Affiliation(s)
- Jing Gao
- Department of Endocrinology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, China
| | - Ying Zou
- Department of Endocrinology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, China
| | - Xiao-Yu Lv
- Department of Endocrinology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, China
| | - Li Chen
- Department of Endocrinology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, China
| | - Xin-Guo Hou
- Department of Endocrinology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, China
- Institute of Endocrine and Metabolic Diseases, Shandong University, Jinan 250012, Shandong Province, China
- Key Laboratory of Endocrine and Metabolic Diseases, Shandong Province Medicine & Health, Jinan 250012, Shandong Province, China
- Department of Endocrinology, Jinan Clinical Research Center for Endocrine and Metabolic Disease, Jinan 250012, Shandong Province, China
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Zhang Z, Liu X, Zhang S, Song Z, Lu K, Yang W. A review and analysis of key biomarkers in Alzheimer's disease. Front Neurosci 2024; 18:1358998. [PMID: 38445255 PMCID: PMC10912539 DOI: 10.3389/fnins.2024.1358998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Accepted: 02/02/2024] [Indexed: 03/07/2024] Open
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects over 50 million elderly individuals worldwide. Although the pathogenesis of AD is not fully understood, based on current research, researchers are able to identify potential biomarker genes and proteins that may serve as effective targets against AD. This article aims to present a comprehensive overview of recent advances in AD biomarker identification, with highlights on the use of various algorithms, the exploration of relevant biological processes, and the investigation of shared biomarkers with co-occurring diseases. Additionally, this article includes a statistical analysis of key genes reported in the research literature, and identifies the intersection with AD-related gene sets from databases such as AlzGen, GeneCard, and DisGeNet. For these gene sets, besides enrichment analysis, protein-protein interaction (PPI) networks utilized to identify central genes among the overlapping genes. Enrichment analysis, protein interaction network analysis, and tissue-specific connectedness analysis based on GTEx database performed on multiple groups of overlapping genes. Our work has laid the foundation for a better understanding of the molecular mechanisms of AD and more accurate identification of key AD markers.
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Affiliation(s)
- Zhihao Zhang
- School of Computer Science and Technology, Xinjiang University, Ürümqi, China
- College of Medical Engineering and Technology, Xinjiang Medical University, Ürümqi, China
| | - Xiangtao Liu
- College of Medical Engineering and Technology, Xinjiang Medical University, Ürümqi, China
| | - Suixia Zhang
- College of Medical Engineering and Technology, Xinjiang Medical University, Ürümqi, China
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
- State Key Laboratory of Pathogenesis, Prevention, Treatment of Central Asian High Incidence Diseases, First Affiliated Hospital of Xinjiang Medical University, Ürümqi, China
| | - Zhixin Song
- College of Medical Engineering and Technology, Xinjiang Medical University, Ürümqi, China
| | - Ke Lu
- School of Computer Science and Technology, Xinjiang University, Ürümqi, China
| | - Wenzhong Yang
- School of Computer Science and Technology, Xinjiang University, Ürümqi, China
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Xu X, Liang F, Chen J, Chen F, Kong L, Ding Y. Association of FHL5 and LPA genetic polymorphisms with diabetes mellitus risk: a case-control study. Aging Male 2023; 26:2235005. [PMID: 37452735 DOI: 10.1080/13685538.2023.2235005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 07/03/2023] [Accepted: 07/05/2023] [Indexed: 07/18/2023] Open
Abstract
BACKGROUND China is one of the countries with the fastest growing prevalence of diabetes mellitus (DM) in the world. This study intended to investigate the association of single nucleotide polymorphisms (SNPs) of FHL5 and LPA with DM risk in the Chinese population. METHODS This case-control study involved 1,420 Chinese individuals (710 DM patients and 710 controls). Four candidate loci (rs2252816/rs9373985 in FHL5 and rs3124784/rs7765781 in LPA) were successfully screened. The association of SNPs with DM risk was assessed by logistic regression analysis. Differences in clinical characteristics among subjects with different genotypes were analyzed by one-way analysis of variance. RESULTS Overall analysis indicated that rs3124784 was associated with an increased risk of DM. Stratification analysis showed that rs3124784 significantly increased DM risk in different subgroups (male, non-smoking, non-drinking, and BMI > 24), while rs7765781 increased DM risk only in participants with BMI ≤ 24. Rs2252816 was associated with the course of DM. We also found that rs2252816 GG genotype and rs9373985 GG genotype were linked to the increased cystatin c in DM patients. CONCLUSION The genetic polymorphisms of LPA may be associated with DM risk in the Chinese population, which will provide useful information for the prevention and diagnosis of DM.
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Affiliation(s)
- Xuezhong Xu
- Department of Endocrinology, People's Hospital of Wanning, Wanning, Hainan, China
| | - Fangyun Liang
- Department of Endocrinology, People's Hospital of Wanning, Wanning, Hainan, China
| | - Jinmei Chen
- Department of Endocrinology, People's Hospital of Wanning, Wanning, Hainan, China
| | - Feihong Chen
- Department of Endocrinology, People's Hospital of Wanning, Wanning, Hainan, China
| | - Lingyi Kong
- Department of Endocrinology, People's Hospital of Wanning, Wanning, Hainan, China
| | - Yipeng Ding
- Department of Pulmonary and Critical Care Medicine, Hainan Affiliated Hospital of Hainan Medical University, Hainan General Hospital, Haikou, Hainan, China
- Department of General Practice, Hainan Affiliated Hospital of Hainan Medical University, Hainan General Hospital, Haikou, Hainan, China
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Gong Y, Luo H, Li Z, Feng Y, Liu Z, Chang J. Metabolic Profile of Alzheimer's Disease: Is 10-Hydroxy-2-decenoic Acid a Pertinent Metabolic Adjuster? Metabolites 2023; 13:954. [PMID: 37623897 PMCID: PMC10456792 DOI: 10.3390/metabo13080954] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 08/12/2023] [Accepted: 08/17/2023] [Indexed: 08/26/2023] Open
Abstract
Alzheimer's disease (AD) represents a significant public health concern in modern society. Metabolic syndrome (MetS), which includes diabetes mellitus (DM) and obesity, represents a modifiable risk factor for AD. MetS and AD are interconnected through various mechanisms, such as mitochondrial dysfunction, oxidative stress, insulin resistance (IR), vascular impairment, inflammation, and endoplasmic reticulum (ER) stress. Therefore, it is necessary to seek a multi-targeted and safer approach to intervention. Thus, 10-hydroxy-2-decenoic acid (10-HDA), a unique hydroxy fatty acid in royal jelly, has shown promising anti-neuroinflammatory, blood-brain barrier (BBB)-preserving, and neurogenesis-promoting properties. In this paper, we provide a summary of the relationship between MetS and AD, together with an introduction to 10-HDA as a potential intervention nutrient. In addition, molecular docking is performed to explore the metabolic tuning properties of 10-HDA with associated macromolecules such as GLP-1R, PPARs, GSK-3, and TREM2. In conclusion, there is a close relationship between AD and MetS, and 10-HDA shows potential as a beneficial nutritional intervention for both AD and MetS.
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Affiliation(s)
| | | | | | | | | | - Jie Chang
- Department of Occupational and Environmental Health, School of Public Health, Soochow University, 199 Ren’ai Road, Suzhou 215123, China; (Y.G.)
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Hassan AS, Morsy NM, Aboulthana WM, Ragab A. Exploring novel derivatives of isatin-based Schiff bases as multi-target agents: design, synthesis, in vitro biological evaluation, and in silico ADMET analysis with molecular modeling simulations. RSC Adv 2023; 13:9281-9303. [PMID: 36950709 PMCID: PMC10026821 DOI: 10.1039/d3ra00297g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Accepted: 03/10/2023] [Indexed: 03/24/2023] Open
Abstract
Recently, scientists developed a powerful strategy called "one drug-multiple targets" to discover vital and unique therapies to fight the most challenging diseases. Novel derivatives of isatin-based Schiff bases 2-7 have been synthesized by the reaction of 3-hydrazino-isatin (1) with aryl aldehydes, hetero-aryl aldehydes, and dialdehydes. The structure of the synthesized derivatives was proved by physical and spectral analysis. Additionally, in vitro biological studies were performed, including antioxidant, anti-diabetic, anti-Alzheimer, and anti-arthritic activities. The four derivatives 3b, 5a, 5b, and 5c possess the highest activities. Among the four potent derivatives, compound 5a exhibited the highest antioxidant (TAC = 68.02 ± 0.15 mg gallic acid per g; IRP = 50.39 ± 0.11) and scavenging activities (ABTS = 53.98 ± 0.12% and DPPH = 8.65 ± 0.02 μg mL-1). Furthermore, compound 5a exhibited an α-amylase inhibitory percentage of 57.64 ± 0.13% near the acarbose (ACA = 69.11 ± 0.15%) and displayed inhibitor activity of the acetylcholinesterase (AChE) enzyme = 36.38 ± 0.08%. Moreover, our work extended to determining the anti-arthritic effect, and compound 5a revealed good inhibitor activities with very close values for proteinase denaturation (PDI) = 39.59 ± 0.09% and proteinase inhibition (PI) = 36.39 ± 0.08%, compared to diclofenac sodium PDI = 49.33 ± 0.11% and PI = 41.88 ± 0.09%. Additionally, the quantum chemical calculations, including HOMO, LUMO, and energy band gap were determined, and in silico ADMET properties were predicted, and their probability was recorded. Finally, molecular docking simulations were performed inside α-amylase and acetylcholinesterase enzymes.
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Affiliation(s)
- Ashraf S Hassan
- Organometallic and Organometalloid Chemistry Department, National Research Centre Dokki 12622 Cairo Egypt
| | - Nesrin M Morsy
- Organometallic and Organometalloid Chemistry Department, National Research Centre Dokki 12622 Cairo Egypt
| | - Wael M Aboulthana
- Biochemistry Department, Biotechnology Research Institute, National Research Centre Dokki 12622 Cairo Egypt
| | - Ahmed Ragab
- Chemistry Department, Faculty of Science (Boys), Al-Azhar University Nasr City Cairo 11884 Egypt
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Xia P, Ma H, Chen J, Liu Y, Cui X, Wang C, Zong S, Wang L, Liu Y, Lu Z. Differential expression of pyroptosis-related genes in the hippocampus of patients with Alzheimer's disease. BMC Med Genomics 2023; 16:56. [PMID: 36918839 PMCID: PMC10012531 DOI: 10.1186/s12920-023-01479-x] [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: 09/24/2022] [Accepted: 03/06/2023] [Indexed: 03/15/2023] Open
Abstract
BACKGROUND Alzheimer's disease (AD) is a progressive, neurodegenerative disorder with insidious onset. Some scholars believe that there is a close relationship between pyroptosis and AD. However, studies with evidence supporting this relationship are lacking. MATERIALS AND METHODS The microarray data of AD were retrieved from the Gene Expression Omnibus (GEO) database with the datasets merged using the R package inSilicoMerging. R software package Limma was used to perform the differential expression analysis to identify the differentially expressed genes (DEGs). We further performed the enrichment analyses of the DEGs based on Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases to identify the metabolic pathways with a significant difference. The Gene Set Enrichment Analysis (GSEA) was applied to identify the significant pathways. The protein-protein interaction (PPI) network was constructed based on the STRING database with the hub genes identified. Quantitative real-time PCR (qRT-PCR) analyses based on HT22 cells were performed to validate the findings based on the microarray analysis. Gene expression correlation heatmaps were generated to evaluate the relationships among the genes. RESULTS A new dataset was derived by merging 4 microarray datasets in the hippocampus of AD patients in the GEO database. Differential gene expression analysis yielded a volcano plot of a total of 20 DEGs (14 up-regulated and 6 down-regulated). GO analysis revealed a group of GO terms with a significant difference, e.g., cytoplasmic vesicle membrane, vesicle membrane, and monocyte chemotaxis. KEGG analysis detected the metabolic pathways with a significant difference, e.g., Rheumatoid arthritis and Fluid shear stress and atherosclerosis. The results of the Gene Set Enrichment Analysis of the microarray data showed that gene set ALZHEIMER_DISEASE and the gene set PYROPTOSIS were both up-regulated. PPI network showed that pyroptosis-related genes were divided into two groups. In the Aβ-induced HT22 cell model, three genes (i.e., BAX, IL18, and CYCS) were revealed with significant differences. Gene expression correlation heatmaps revealed strong correlations between pyroptotic genes and AD-related genes. CONCLUSION The pyroptosis-related genes BAX, IL18, and CYCS were significantly different between AD patients and normal controls.
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Affiliation(s)
- Pengcheng Xia
- Department of Clinical Laboratory Medicine, Shandong Provincial Hospital, Shandong First Medical University, Jinan, Shandong, China
| | - Huijun Ma
- Clinical Laboratory, Qingdao Women and Children's Hospital, Qingdao, Shandong, China
| | - Jing Chen
- Discipline of Anatomy and Pathology, Shandong First Medical University, Jinan, Shandong, China
| | - Yingchao Liu
- Department of Clinical Laboratory Medicine, Shandong Provincial Hospital, Shandong First Medical University, Jinan, Shandong, China
| | - Xiaolin Cui
- School of Medicine, Shandong University, Jinan, Shandong, China
| | - Cuicui Wang
- Department of Clinical Laboratory Medicine, Shandong Provincial Hospital, Shandong First Medical University, Jinan, Shandong, China
| | - Shuai Zong
- Department of Clinical Laboratory Medicine, Shandong Provincial Hospital, Shandong First Medical University, Jinan, Shandong, China
| | - Le Wang
- Department of Clinical Laboratory Medicine, Shandong Provincial Hospital, Shandong First Medical University, Jinan, Shandong, China
| | - Yun Liu
- Department of Clinical Laboratory Medicine, Shandong Provincial Hospital, Shandong First Medical University, Jinan, Shandong, China.
| | - Zhiming Lu
- Department of Clinical Laboratory Medicine, Shandong Provincial Hospital, Shandong First Medical University, Jinan, Shandong, China.
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Xia J, Zhang L, Gu T, Liu Q, Wang Q. Identification of ferroptosis related markers by integrated bioinformatics analysis and In vitro model experiments in rheumatoid arthritis. BMC Med Genomics 2023; 16:18. [PMID: 36717858 PMCID: PMC9887825 DOI: 10.1186/s12920-023-01445-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 01/25/2023] [Indexed: 01/31/2023] Open
Abstract
BACKGROUND Rheumatoid arthritis (RA) is an autoimmune disease characterized by destructive and symmetrical joint diseases and synovitis. This research attempted to explore the mechanisms involving ferroptosis in RA, and find the biological markers by integrated analysis. METHODS Gene expression data (GSE55235 and GSE55457) of synovial tissues from healthy and RA individuals were downloaded. By filtering the differentially expressed genes (DEGs) and intersecting them with the 484 ferroptosis-related genes (FRGs), the overlapping genes were identified. After the enrichment analysis, the machine learning-based approaches were introduced to screen the potential biomarkers, which were further validated in other two datasets (GSE77298 and GSE93272) and cell samples. Besides, we also analyze the infiltrating immune cells in RA and their correlation with the biomarkers. RESULTS With the criteria, 635 DEGs in RA were included, and 29 of them overlapped in the reported 484 FRGs. The enrichments of the 29 differentially expressed ferroptosis-related genes indicated that they may involve in the FoxO signaling pathway and inherited metabolic disorder. RRM2, validating by the external datasets and western blot, were identified as the biomarker with the high diagnostic value, whose associated immune cells, such as Neutrophils and Macrophages M1, were also further evaluated. CONCLUSION We preliminary explored the mechanisms between ferroptosis and RA. These results may help us better comprehend the pathophysiological changes of RA in basic research, and provide new evidences for the clinical transformation.
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Affiliation(s)
- Jinjun Xia
- grid.263761.70000 0001 0198 0694Department of Clinical Laboratory, Wuxi 9Th People’s Hospital Affiliated to Soochow University, No. 999 Liang Xi Road, Binhu District, Wuxi, 214000 Jiangsu China
| | - Lulu Zhang
- grid.263761.70000 0001 0198 0694Department of Clinical Laboratory, Wuxi 9Th People’s Hospital Affiliated to Soochow University, No. 999 Liang Xi Road, Binhu District, Wuxi, 214000 Jiangsu China
| | - Tao Gu
- grid.263761.70000 0001 0198 0694Department of Clinical Laboratory, Wuxi 9Th People’s Hospital Affiliated to Soochow University, No. 999 Liang Xi Road, Binhu District, Wuxi, 214000 Jiangsu China
| | - Qingyang Liu
- grid.263761.70000 0001 0198 0694Department of Clinical Laboratory, Wuxi 9Th People’s Hospital Affiliated to Soochow University, No. 999 Liang Xi Road, Binhu District, Wuxi, 214000 Jiangsu China
| | - Qiubo Wang
- grid.263761.70000 0001 0198 0694Department of Clinical Laboratory, Wuxi 9Th People’s Hospital Affiliated to Soochow University, No. 999 Liang Xi Road, Binhu District, Wuxi, 214000 Jiangsu China
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Savelieff MG, Chen KS, Elzinga SE, Feldman EL. Diabetes and dementia: Clinical perspective, innovation, knowledge gaps. J Diabetes Complications 2022; 36:108333. [PMID: 36240668 PMCID: PMC10076101 DOI: 10.1016/j.jdiacomp.2022.108333] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 09/30/2022] [Indexed: 10/31/2022]
Abstract
The world faces a pandemic-level prevalence of type 2 diabetes. In parallel with this massive burden of metabolic disease is the growing prevalence of dementia as the population ages. The two health issues are intertwined. The Lancet Commission on dementia prevention, intervention, and care was convened to tackle the growing global concern of dementia by identifying risk factors. It concluded, along with other studies, that diabetes as well as obesity and the metabolic syndrome more broadly, which are frequently comorbid, raise the risk of developing dementia. Type 2 diabetes is a modifiable risk factor; however, it is uncertain whether anti-diabetic drugs mitigate risk of developing dementia. Reasons are manifold but constitute a critical knowledge gap in the field. This review outlines studies of type 2 diabetes on risk of dementia, illustrating key concepts. Moreover, it identifies knowledge gaps, reviews strategies to help fill these gaps, and concludes with a series of recommendations to mitigate risk and advance understanding of type 2 diabetes and dementia.
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Affiliation(s)
- Masha G Savelieff
- NeuroNetwork for Emerging Therapies, University of Michigan, Ann Arbor, MI 48109, USA
| | - Kevin S Chen
- NeuroNetwork for Emerging Therapies, University of Michigan, Ann Arbor, MI 48109, USA; Department of Neurology, University of Michigan, Ann Arbor, MI 48109, USA; Department of Neurosurgery, University of Michigan, Ann Arbor, MI 48109, USA.
| | - Sarah E Elzinga
- NeuroNetwork for Emerging Therapies, University of Michigan, Ann Arbor, MI 48109, USA; Department of Neurology, University of Michigan, Ann Arbor, MI 48109, USA.
| | - Eva L Feldman
- NeuroNetwork for Emerging Therapies, University of Michigan, Ann Arbor, MI 48109, USA; Department of Neurology, University of Michigan, Ann Arbor, MI 48109, USA.
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Huang C, Hu D, Li K. Identification of Biomarkers in Intracranial Aneurysm and Their Immune Infiltration Characteristics. World Neurosurg 2022; 166:e199-e214. [PMID: 35798291 DOI: 10.1016/j.wneu.2022.06.138] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 06/28/2022] [Accepted: 06/28/2022] [Indexed: 12/15/2022]
Abstract
BACKGROUND Intracranial aneurysm (IA), known as the intracranial "unscheduled bomb," is one of the most dangerous cerebrovascular diseases, with unclear pathogenesis. This study aimed to show the mechanisms and identify the new biological targets by applying bioinformatics analysis. METHODS Expression profiling for control superficial temporal artery and IA walls in GSE26969 and GSE75436 datasets were downloaded. By executing the LIMMA package in R software, the differentially expressed genes (DEGs) were filtered, and the functional enrichments were consequently performed. Further cross-linking with the 2483 immune-related genes (IRGs) from the ImmPort database, the differentially expressed IRGs were identified. Based on them, the least absolute shrinkage and selection operator logistic regression and support vector machine-recursive feature elimination algorithms were used to screen the biomarkers, which were validated in the GSE54083 datasets. The CIBERSORT algorithm was applied to evaluate the infiltration of immune cells in tissues. RESULTS A total of 668 DEGs were obtained, and the functional enrichment suggested that they were closely related to the immune process. After intersecting them with the IRGs, 90 differentially expressed IRGs emerged, and ADIPOQ and ESM1 were identified as the biomarkers. Besides, we found that the infiltrated immune cells, such as the mast cells resting, might be associated with them. CONCLUSIONS We explored the contributing factors involving IA, which may generate a better understanding of the complex interactions among them and inspire a promising strategy for clinical works.
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Affiliation(s)
- Cheng Huang
- Department of Neurology and Stroke Center, The First Affiliated Hospital of Jinan University, Guangzhou, China; Clinical Neuroscience Institute of Jinan University, Guangzhou, China
| | - Di Hu
- Department of Neurology and Stroke Center, The First Affiliated Hospital of Jinan University, Guangzhou, China; Clinical Neuroscience Institute of Jinan University, Guangzhou, China
| | - Keshen Li
- Department of Neurology and Stroke Center, The First Affiliated Hospital of Jinan University, Guangzhou, China; Clinical Neuroscience Institute of Jinan University, Guangzhou, China.
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Identification and Experimental Validation of Marker Genes between Diabetes and Alzheimer’s Disease. OXIDATIVE MEDICINE AND CELLULAR LONGEVITY 2022; 2022:8122532. [PMID: 35996379 PMCID: PMC9391608 DOI: 10.1155/2022/8122532] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 06/15/2022] [Accepted: 08/01/2022] [Indexed: 11/21/2022]
Abstract
Currently, Alzheimer's disease (AD) and type 2 diabetes mellitus (T2DM) are widely prevalent in the elderly population, and accumulating evidence implies a strong link between them. For example, patients with T2DM have a higher risk of developing neurocognitive disorders, including AD, but the exact mechanisms are still unclear. This time, by combining bioinformatics analysis and in vivo experimental validation, we attempted to find a common biological link between AD and T2DM. We firstly downloaded the gene expression profiling (AD: GSE122063; T2DM: GSE161355) derived from the temporal cortex. To find the associations, differentially expressed genes (DEGs) of the two datasets were filtered and intersected. Based on them, enrichment analysis was carried out, and the least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine-recursive feature elimination (SVM-RFE) algorithms were used to identify the specific genes. After verifying in the external dataset and in the samples from the AD and type 2 diabetes animals, the shared targets of the two diseases were finally determined. Based on them, the ceRNA networks were constructed. Besides, the logistic regression and single-sample gene set enrichment analysis (ssGSEA) were performed. As a result, 62 DEGs were totally identified between AD and T2DM, and the enrichment analysis indicated that they were much related to the function of synaptic vesicle and MAPK signaling pathway. Based on the evidence from external dataset and RT-qPCR, CARTPT, EPHA5, and SERPINA3 were identified as the marker genes in both diseases, and their clinical significance and biological functions were further analyzed. In conclusion, discovering and exploring the marker genes that are dysregulated in both 2 diseases could help us better comprehend the intrinsic relationship between T2DM and AD, which may inspire us to develop new strategies for facing the dilemmas of clinical or basic research in cognitive dysfunction.
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