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Bogdanowicz P, Bensadoun P, Noizet M, Béganton B, Philippe A, Alvarez-Georges S, Doat G, Tourette A, Bessou-Touya S, Lemaitre JM, Duplan H. Senomorphic activity of a combination of niacinamide and hyaluronic acid: correlation with clinical improvement of skin aging. Sci Rep 2024; 14:16321. [PMID: 39009698 PMCID: PMC11251187 DOI: 10.1038/s41598-024-66624-7] [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: 02/02/2024] [Accepted: 07/02/2024] [Indexed: 07/17/2024] Open
Abstract
Intrinsic and extrinsic factors, including lifestyle and sun exposure, can contribute to cell senescence, which impairs skin homeostasis, that may in turn lead to skin aging. Senescent cells have a specific secretome, called the senescence-associated secretory phenotype (SASP) that includes MMPs, CXCLs and S100A8/9. Reducing the SASP with senotherapeutics is a promising strategy to reduce skin aging. Here we evaluated the effect of a formula containing niacinamide and hyaluronic acid, which are known to limit senescence and skin aging. We conducted three different studies. (1) Ex vivo explants treated with the formula had more collagen and glycosaminoglycan. (2) In a clinical trial with forty-four women, two months of treatment improved fine lines, wrinkles, luminosity, smoothness, homogeneity, and plumpness. (3) In a third study on thirty women, we treated one arm for two months and took skin biopsies to study gene expression. 101 mRNAs and 13 miRNAs were differentially expressed. We observed a likely senomorphic effect, as there was a decrease in many SASP genes including MMP12 and CXCL9 and a significant downregulation of autocrine signaling genes: S100A8 and S100A9. These pharmaco-clinical results are the first to demonstrate the senomorphic properties of an effective anti-aging formula in skin.
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Affiliation(s)
| | - Paul Bensadoun
- INSERM IRMB UMR1183, Hôpital Saint Eloi, Université de Montpellier, Montpellier, France
| | - Maïté Noizet
- R&D Pierre Fabre Dermo-Cosmétique & Personal Care, Toulouse, France
| | - Benoît Béganton
- R&D Pierre Fabre Dermo-Cosmétique & Personal Care, Toulouse, France
| | - Armony Philippe
- R&D Pierre Fabre Dermo-Cosmétique & Personal Care, Toulouse, France
| | | | - Gautier Doat
- Laboratoires Dermatologiques Avène, Lavaur, France
| | - Amélie Tourette
- R&D Pierre Fabre Dermo-Cosmétique & Personal Care, Toulouse, France
| | | | - Jean-Marc Lemaitre
- INSERM IRMB UMR1183, Hôpital Saint Eloi, Université de Montpellier, Montpellier, France.
| | - Hélène Duplan
- R&D Pierre Fabre Dermo-Cosmétique & Personal Care, Toulouse, France
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Li Q, Wang B, Yang J, Wang Y, Duan F, Luo M, Zhao C, Wei W, Wang L, Liu S. Preliminary Analysis of Aging-Related Genes in Intracerebral Hemorrhage by Integration of Bulk and Single-Cell RNA Sequencing Technology. Int J Gen Med 2024; 17:2719-2740. [PMID: 38883702 PMCID: PMC11180471 DOI: 10.2147/ijgm.s457480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Accepted: 05/23/2024] [Indexed: 06/18/2024] Open
Abstract
Background Aging is recognized as the key risk for intracerebral hemorrhage (ICH). The detailed mechanisms of aging in ICH warrant exploration. This study aimed to identify potential aging-related genes associated with ICH. Methods ICH-specific aging-related genes were determined by the intersection of differentially expressed genes (DEGs) between perihematomal tissues and corresponding contralateral parts of four patients with ICH (GSE24265) and 349 aging-related genes obtained from the Aging Atlas database. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) analyses were performed to identify the potential biological functions and pathways in which these ICH-specific aging-related genes may be involved. Then, PPI network was established to identify the hub genes of ICH-specific aging-related genes. Meanwhile, miRNA-mRNA and transcription factor (TF)-mRNA regulatory networks were constructed to further explore the ICH-specific aging-related genes regulation. The relationship between these hub genes and immune infiltration was also further explored. Additional single-cell RNA-seq analysis (scRNA-seq, GSE167593) was used to locate the hub genes in different cell types. Besides, expression levels of the hub genes were validated using clinical samples from our institute and another GEO dataset (GSE206971). Results This study identified 24 ICH-specific aging-related genes, including 22 up-regulated and 2 down-regulated genes. The results of GO and KEGG suggested that the ICH-specific aging-related genes mainly enriched in immunity and inflammation-related pathways, suggesting that aging may affect the ich pathogenesis by regulating inflammatory and immune-related pathways. Conclusion Our study revealed 24 ICH-specific aging-related genes and their functions highly pertinent to ICH pathogenesis, providing new insights into the impact of aging on ICH.
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Affiliation(s)
- Qianfeng Li
- Department of Neurosurgery, Wuhan No.1 Hospital, Wuhan, People's Republic of China
| | - Bo Wang
- Brain Research Center, Zhongnan Hospital of Wuhan University, Wuhan, People's Republic of China
| | - Jun Yang
- Huanggang Central Hospital of Yangtze University, Huanggang, People's Republic of China
| | - Yuan Wang
- Department of Neurosurgery, Wuhan No.1 Hospital, Wuhan, People's Republic of China
| | - Faliang Duan
- Department of Neurosurgery, Wuhan No.1 Hospital, Wuhan, People's Republic of China
| | - Ming Luo
- Department of Neurosurgery, Wuhan No.1 Hospital, Wuhan, People's Republic of China
| | - Chungang Zhao
- Jilin Jianda Modern Agricultural Research Institute, Changchun, People's Republic of China
| | - Wei Wei
- Brain Research Center, Zhongnan Hospital of Wuhan University, Wuhan, People's Republic of China
| | - Lei Wang
- Huanggang Central Hospital of Yangtze University, Huanggang, People's Republic of China
| | - Sha Liu
- Brain Research Center, Zhongnan Hospital of Wuhan University, Wuhan, People's Republic of China
- Department of General Practice, Zhongnan Hospital of Wuhan University, Wuhan, People's Republic of China
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Jiang D, Xu Y, Yang L, Li P, Han X, Li Q, Yang Y, Chao L. Identification and validation of senescence-related genes in polycystic ovary syndrome. J Ovarian Res 2024; 17:7. [PMID: 38184636 PMCID: PMC10770899 DOI: 10.1186/s13048-023-01338-4] [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: 09/04/2023] [Accepted: 12/28/2023] [Indexed: 01/08/2024] Open
Abstract
BACKGROUND Polycystic ovary syndrome (PCOS) is an exceedingly intractable issue affecting female endocrine and reproductive health. However, the etiology and intricate pathological mechanisms of PCOS remain unclear. Nowadays, aging was found to share multiple common pathological mechanisms with PCOS, which causes probing into the pathogenesis of PCOS from senescence. However, no bioinformatics analyses have specifically focused on connection between PCOS and ovarian aging. METHODS Differentially expressed aging-related genes in PCOS were identified and then analyzed using function enrichment method. Hub genes were determined based on multiple algorithms, and expression validation of hub genes was performed in both datasets and experiments (human granulosa-like tumor cell line, KGN; human Granulosa Cell, hGCs). Finally, a transcription factor-miRNA-gene network of hub genes was constructed. RESULTS Here, we identified 73 aging-related differential expression genes (ARDEGs) by intersecting DEGs in PCOS and senescence-related gene set. Furthermore, we performed biological functions and potential pathways of ARDEGs and potential hub genes were also screened by multiple algorithms. From the perspective of immune dysfunction, we analyzed the correlation between PCOS and immune cells. Finally, TF-miRNA-gene networks were constructed. Finally, TF-miRNA-gene networks were constructed. CONCLUSIONS Our work aimed to elucidate the relation between PCOS and cellular senescence based on bioinformatics strategy, deepening the understanding of mechanisms and to seek for novel therapy strategies for improving reproductive lifespan and female health. Exploring the potential molecular mechanism of cell aging in PCOS is expected to bring a new breakthrough for PCOS diagnosis and therapy strategies. And this, might deepen our understanding about intricate mechanisms of ovarian aging.
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Affiliation(s)
- Danni Jiang
- Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Qilu Hospital, Shandong University, Jinan, China
| | - Yang Xu
- Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Qilu Hospital, Shandong University, Jinan, China
- Department of Reproductive Medicine, Linyi People's Hospital, Shandong University, Linyi, China
| | - Lin Yang
- Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Qilu Hospital, Shandong University, Jinan, China
| | - Pengfei Li
- Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Qilu Hospital, Shandong University, Jinan, China
| | - Xiaojuan Han
- Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Qilu Hospital, Shandong University, Jinan, China
| | - Qianni Li
- Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Qilu Hospital, Shandong University, Jinan, China
| | - Yang Yang
- Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Qilu Hospital, Shandong University, Jinan, China
| | - Lan Chao
- Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Qilu Hospital, Shandong University, Jinan, China.
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Huang J, Zhou J, Xue X, Dai T, Zhu W, Jiao S, Wu H, Meng Q. Identification of aging-related genes in diagnosing osteoarthritis via integrating bioinformatics analysis and machine learning. Aging (Albany NY) 2024; 16:153-168. [PMID: 38175691 PMCID: PMC10817387 DOI: 10.18632/aging.205357] [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: 07/26/2023] [Accepted: 11/13/2023] [Indexed: 01/05/2024]
Abstract
BACKGROUND Osteoarthritis (OA) is one of the main causes of pain and disability in the world, it may be caused by many factors. Aging plays a significant role in the onset and progression of OA. However, the mechanisms underlying it remain unknown. Our research aimed to uncover the role of aging-related genes in the progression of OA. METHODS In Human OA datasets and aging-related genes were obtained from the GEO database and the HAGR website, respectively. Bioinformatics methods including Gene Ontology (GO), Kyoto Encyclopedia of Genes Genomes (KEGG) pathway enrichment, and Protein-protein interaction (PPI) network analysis were used to analyze differentially expressed aging-related genes (DEARGs) in the normal control group and the OA group. And then weighted gene coexpression network analysis (WGCNA), the least absolute shrinkage and selection operator (LASSO) regression, and the Random Forest (RF) machine learning algorithms were used to find the hub genes. RESULTS Four overlapping hub genes: HMGB2, CDKN1A, JUN, and DDIT3 were identified. According to the nomogram model and receiver operating characteristic (ROC) curve analysis, four hub DEARGs had good diagnostic value in distinguishing normal from OA. Furthermore, the qRT-PCR test demonstrated that HMGB2, CDKN1A, JUN, and DDIT3 mRNA expression levels were lower in OA group than in normal group. CONCLUSION Finally, these four-hub aging-related genes may help us understand the underlying mechanism of aging in osteoarthritis and could be used as possible diagnostic and therapeutic targets.
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Affiliation(s)
- Jian Huang
- Guangzhou Institute of Traumatic Surgery, Guangzhou Red Cross Hospital of Jinan University, Guangzhou 510220, China
- Department of Traumatic Orthopedics, The Central Hospital of Xiaogan, Hubei 432100, China
| | - Jiangfei Zhou
- Department of Orthopedics, Guangzhou Red Cross Hospital of Jinan University, Guangzhou 510220, China
| | - Xiang Xue
- Department of Orthopedics, Guangzhou Red Cross Hospital of Jinan University, Guangzhou 510220, China
| | - Tianming Dai
- Guangzhou Institute of Traumatic Surgery, Guangzhou Red Cross Hospital of Jinan University, Guangzhou 510220, China
| | - Weicong Zhu
- Guangzhou Institute of Traumatic Surgery, Guangzhou Red Cross Hospital of Jinan University, Guangzhou 510220, China
| | - Songsong Jiao
- Department of Orthopedics, Guangzhou Red Cross Hospital of Jinan University, Guangzhou 510220, China
| | - Hang Wu
- Department of Traumatic Orthopedics, The Central Hospital of Xiaogan, Hubei 432100, China
| | - Qingqi Meng
- Guangzhou Institute of Traumatic Surgery, Guangzhou Red Cross Hospital of Jinan University, Guangzhou 510220, China
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Li J, Jiang S, Huang C, Lu B, Yang X. Identification and validation of genes associated with aging-related cardiovascular disease. FASEB J 2024; 38:e23370. [PMID: 38168496 DOI: 10.1096/fj.202301270rr] [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: 06/24/2023] [Revised: 11/15/2023] [Accepted: 11/30/2023] [Indexed: 01/05/2024]
Abstract
Aging is acknowledged as the most significant risk factor for cardiovascular disease (CVD). This study sought to identify and validate potential aging-related genes associated with CVD by using bioinformatics. The confluence of the limma test, weighted correlation network analysis (WGCNA), and 2129 aging and senescence-associated genes led to the identification of aging-related differential expression genes (ARDEGs). By using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), potential biological roles and pathways of ARDEGs were identified. To find the significantly different functions between CVD and non-cardiovascular disease (nCVD) and to reckon the processes score, enrichment analysis of all genes was carried out using gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA). By using GO and KEGG, potential biological roles and pathways of ARDEGs were identified. To evaluate the immune cell composition of the immune microenvironment, we performed an immune infiltration analysis on the dataset from the training group. We were able to acquire four ARDEGs (PTGS2, MMP9, HBEGF, and FN1). Aging, cellular senescence, and nitric oxide signal transduction were selected for biological function analysis. The diagnostic value of the four ARDEGs in distinguishing CVD from nCVD samples was deemed to be favorable. This research identified four ARDEGs that are associated with CVD. This study provides insight into prospective novel biomarkers for aging-related CVD diagnosis and progression monitoring.
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Affiliation(s)
- Jing Li
- School of Pharmaceutical Sciences, South-Central Minzu University, Wuhan, P. R. China
| | - Shengping Jiang
- School of Pharmaceutical Sciences, South-Central Minzu University, Wuhan, P. R. China
| | - Chengyun Huang
- School of Pharmaceutical Sciences, South-Central Minzu University, Wuhan, P. R. China
| | - Baihui Lu
- School of Pharmaceutical Sciences, South-Central Minzu University, Wuhan, P. R. China
| | - Xiaolong Yang
- School of Pharmaceutical Sciences, South-Central Minzu University, Wuhan, P. R. China
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Zhu XC, Tang BF, Zhu MZ, Lu J, Lin HX, Tang JM, Li R, Ma T. Analysis of complement system and its related factors in Alzheimer's disease. BMC Neurol 2023; 23:446. [PMID: 38114984 PMCID: PMC10729410 DOI: 10.1186/s12883-023-03503-0] [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: 04/02/2023] [Accepted: 12/09/2023] [Indexed: 12/21/2023] Open
Abstract
Alzheimer's disease (AD) is a primary cause of dementia. The complement system is closely related to AD pathology and may be a potential target for the prevention and treatment of AD. In our study, we conducted a bioinformatics analysis to analyze the role of the complement system and its related factors in AD using Gene Expression Omnibus (GEO) data. We also conducted a functional analysis. Our study verified that 23 genes were closely related to differentially expressed complement system genes in diseases after intersecting the disease-related complement system module genes and differentially expressed genes. The STRING database was used to predict the interactions between the modular gene proteins of the differential complement system. A total of 21 gene proteins and 44 interaction pairs showed close interactions. We screened key genes and created a diagnostic model. The predictive effect of the model was constructed using GSE5281 and our study indicated that the predictive effect of the model was good. Our study also showed enriched negative regulation of Notch signaling, cytokine secretion involved in the immune response pathway, and cytokine secretion involved in immune response hormone-mediated apoptotic signaling pathway. We hope that our study provides a promising target to prevent and delay the onset, diagnosis, and treatment of AD.
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Affiliation(s)
- Xi-Chen Zhu
- Department of Neurology, The Wuxi No. 2 People's Hospital, Jiangnan University Medical Center, Wuxi, Jiangsu Province, China.
- Brain Institue, Jiangnan University, Wuxi, Jiangsu Province, China.
- Department of Neurology, The Wuxi No. 2 People's Hospital, Affiliated Wuxi Clinical College of Nantong University, Wuxi, Jiangsu Province, China.
- Department of Neurology, The Affiliated Wuxi No. 2 People's Hospital of Nanjing Medical University, No. 68 Zhongshan Road, Wuxi, Jiangsu, 214000, China.
| | - Bin-Feng Tang
- Department of Neurology, The Wuxi No. 2 People's Hospital, Jiangnan University Medical Center, Wuxi, Jiangsu Province, China
| | - Meng-Zhuo Zhu
- Department of Neurology, The Wuxi No. 2 People's Hospital, Affiliated Wuxi Clinical College of Nantong University, Wuxi, Jiangsu Province, China
| | - Jing Lu
- Department of Neurology, The Affiliated Wuxi No. 2 People's Hospital of Nanjing Medical University, No. 68 Zhongshan Road, Wuxi, Jiangsu, 214000, China
| | - Han-Xiao Lin
- Department of Neurology, The Wuxi No. 2 People's Hospital, Affiliated Wuxi Clinical College of Nantong University, Wuxi, Jiangsu Province, China
| | - Jia-Ming Tang
- Department of Neurology, The Affiliated Wuxi No. 2 People's Hospital of Nanjing Medical University, No. 68 Zhongshan Road, Wuxi, Jiangsu, 214000, China
| | - Rong Li
- Department of Pharmacy, The Affiliated Wuxi No. 2 People's Hospital, Jiangnan University Medical Center, Wuxi, Jiangsu Province, China.
| | - Tao Ma
- Department of Neurology, The Wuxi No. 2 People's Hospital, Jiangnan University Medical Center, Wuxi, Jiangsu Province, China.
- Brain Institue, Jiangnan University, Wuxi, Jiangsu Province, China.
- Department of Neurology, The Wuxi No. 2 People's Hospital, Affiliated Wuxi Clinical College of Nantong University, Wuxi, Jiangsu Province, China.
- Department of Neurology, The Affiliated Wuxi No. 2 People's Hospital of Nanjing Medical University, No. 68 Zhongshan Road, Wuxi, Jiangsu, 214000, China.
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Song Z, Wu Z, Luo R, He C, Li Z, Yang M, Yu W, He J, Deng S, Cheng S. Identification of tryptophan metabolism-related genes in immunity and immunotherapy in Alzheimer's disease. Aging (Albany NY) 2023; 15:13077-13099. [PMID: 37988184 DOI: 10.18632/aging.205220] [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: 06/28/2023] [Accepted: 10/15/2023] [Indexed: 11/23/2023]
Abstract
Recent studies have highlighted the significant involvement of tryptophan metabolism in the pathogenesis of Alzheimer's disease (AD). However, a comprehensive investigation of the precise role of tryptophan metabolism in the context of AD is still lacking. This study employed a bioinformatics approach to identify and validate potential tryptophan metabolism-related genes (TrpMgs) associated with AD. The discovery of TrpMgs was facilitated through the intersection of the Weighted Gene Co-expression Network Analysis (WGCNA) test and 17 known tryptophan metabolism pathways. Subsequently, the putative biological functions and pathways of the TrpMgs were elucidated using Gene Set Variation Analysis (GSVA). Furthermore, the Least Absolute Shrinkage and Selection Operator (LASSO) method was applied to identify hub genes and evaluate the diagnostic efficiency of the 5 TrpMgs in distinguishing AD. The relationship between hub TrpMgs and clinical characteristics was also investigated. Finally, in vivo verification of the five TrpMgs was performed using APP/PS1 mice. We identified 5 TrpMgs associated with AD, including propionyl-CoA carboxylase subunit beta (PCCB), TEA Domain Transcription Factor 1 (TEAD1), Phenylalanyl-TRNA Synthetase Subunit Beta (FARSB), Neurofascin (NFASC), and Ezrin (EZR). Among these genes, PCCB, FARSB, NFASC, and TEAD1 showed correlations with age. In the hippocampus of APP/PS1 mice, we observed down-regulation of FARSB, PCCB, and NFASC mRNA expressions. Furthermore, PCCB and NFASC protein expressions were also down-regulated in the cerebral cortex and hippocampus of APP/PS1 mice. Our study paves the way for future research aimed at unraveling the intricate mechanisms underlying tryptophan metabolism dysregulation in AD and its therapeutic implications.
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Affiliation(s)
- Zhenyan Song
- School of Integrated Chinese and Western Medicine, Hunan University of Chinese Medicine, Changsha 410208, Hunan, China
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, Hunan University of Chinese Medicine, Changsha 410208, Hunan, China
| | - Zixuan Wu
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, Hunan University of Chinese Medicine, Changsha 410208, Hunan, China
| | - Rongsiqing Luo
- School of Integrated Chinese and Western Medicine, Hunan University of Chinese Medicine, Changsha 410208, Hunan, China
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, Hunan University of Chinese Medicine, Changsha 410208, Hunan, China
| | - Chunxiang He
- School of Integrated Chinese and Western Medicine, Hunan University of Chinese Medicine, Changsha 410208, Hunan, China
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, Hunan University of Chinese Medicine, Changsha 410208, Hunan, China
| | - Ze Li
- School of Integrated Chinese and Western Medicine, Hunan University of Chinese Medicine, Changsha 410208, Hunan, China
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, Hunan University of Chinese Medicine, Changsha 410208, Hunan, China
| | - Miao Yang
- School of Integrated Chinese and Western Medicine, Hunan University of Chinese Medicine, Changsha 410208, Hunan, China
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, Hunan University of Chinese Medicine, Changsha 410208, Hunan, China
| | - Wenjing Yu
- School of Integrated Chinese and Western Medicine, Hunan University of Chinese Medicine, Changsha 410208, Hunan, China
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, Hunan University of Chinese Medicine, Changsha 410208, Hunan, China
| | - Jiawei He
- School of Integrated Chinese and Western Medicine, Hunan University of Chinese Medicine, Changsha 410208, Hunan, China
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, Hunan University of Chinese Medicine, Changsha 410208, Hunan, China
| | - Sisi Deng
- School of Integrated Chinese and Western Medicine, Hunan University of Chinese Medicine, Changsha 410208, Hunan, China
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, Hunan University of Chinese Medicine, Changsha 410208, Hunan, China
| | - Shaowu Cheng
- School of Integrated Chinese and Western Medicine, Hunan University of Chinese Medicine, Changsha 410208, Hunan, China
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, Hunan University of Chinese Medicine, Changsha 410208, Hunan, China
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O’Connor LM, O’Connor BA, Zeng J, Lo CH. Data Mining of Microarray Datasets in Translational Neuroscience. Brain Sci 2023; 13:1318. [PMID: 37759919 PMCID: PMC10527016 DOI: 10.3390/brainsci13091318] [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: 07/25/2023] [Revised: 09/04/2023] [Accepted: 09/10/2023] [Indexed: 09/29/2023] Open
Abstract
Data mining involves the computational analysis of a plethora of publicly available datasets to generate new hypotheses that can be further validated by experiments for the improved understanding of the pathogenesis of neurodegenerative diseases. Although the number of sequencing datasets is on the rise, microarray analysis conducted on diverse biological samples represent a large collection of datasets with multiple web-based programs that enable efficient and convenient data analysis. In this review, we first discuss the selection of biological samples associated with neurological disorders, and the possibility of a combination of datasets, from various types of samples, to conduct an integrated analysis in order to achieve a holistic understanding of the alterations in the examined biological system. We then summarize key approaches and studies that have made use of the data mining of microarray datasets to obtain insights into translational neuroscience applications, including biomarker discovery, therapeutic development, and the elucidation of the pathogenic mechanisms of neurodegenerative diseases. We further discuss the gap to be bridged between microarray and sequencing studies to improve the utilization and combination of different types of datasets, together with experimental validation, for more comprehensive analyses. We conclude by providing future perspectives on integrating multi-omics, to advance precision phenotyping and personalized medicine for neurodegenerative diseases.
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Affiliation(s)
- Lance M. O’Connor
- College of Biological Sciences, University of Minnesota, Minneapolis, MN 55455, USA;
| | - Blake A. O’Connor
- School of Pharmacy, University of Wisconsin, Madison, WI 53705, USA;
| | - Jialiu Zeng
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore;
| | - Chih Hung Lo
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore;
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9
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Wu Z, Liu P, Huang B, Deng S, Song Z, Huang X, Yang J, Cheng S. A novel Alzheimer's disease prognostic signature: identification and analysis of glutamine metabolism genes in immunogenicity and immunotherapy efficacy. Sci Rep 2023; 13:6895. [PMID: 37106067 PMCID: PMC10140060 DOI: 10.1038/s41598-023-33277-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Accepted: 04/11/2023] [Indexed: 04/29/2023] Open
Abstract
Alzheimer's disease (AD) is characterized as a distinct onset and progression of cognitive and functional decline associated with age, as well as a specific neuropathology. It has been discovered that glutamine (Gln) metabolism plays a crucial role in cancer. However, a full investigation of its role in Alzheimer's disease is still missing. This study intended to find and confirm potential Gln-related genes associated with AD using bioinformatics analysis. The discovery of GlnMgs was made possible by the intersection of the WGCNA test and 26 Gln-metabolism genes (GlnMgs). GlnMgs' putative biological functions and pathways were identified using GSVA. The LASSO method was then used to identify the hub genes as well as the diagnostic efficiency of the four GlnMgs in identifying AD. The association between hub GlnMgs and clinical characteristics was also studied. Finally, the GSE63060 was utilized to confirm the levels of expression of the four GlnMgs. Four GlnMgs were discovered (ATP5H, NDUFAB1, PFN2, and SPHKAP). For biological function analysis, cell fate specification, atrioventricular canal development, and neuron fate specification were emphasized. The diagnostic ability of the four GlnMgs in differentiating AD exhibited a good value. This study discovered four GlnMgs that are linked to AD. They shed light on potential new biomarkers for AD and tracking its progression.
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Affiliation(s)
- Zixuan Wu
- Hunan University of Chinese Medicine, Changsha, 410128, China
| | - Ping Liu
- Hunan University of Chinese Medicine, Changsha, 410128, China
| | - Baisheng Huang
- Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
| | - Sisi Deng
- Hunan University of Chinese Medicine, Changsha, 410128, China
| | - Zhenyan Song
- Hunan University of Chinese Medicine, Changsha, 410128, China
| | - Xindi Huang
- Hunan University of Chinese Medicine, Changsha, 410128, China
| | - Jing Yang
- Hunan University of Chinese Medicine, Changsha, 410128, China.
| | - Shaowu Cheng
- Hunan University of Chinese Medicine, Changsha, 410128, China.
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Shikhevich S, Chadaeva I, Khandaev B, Kozhemyakina R, Zolotareva K, Kazachek A, Oshchepkov D, Bogomolov A, Klimova NV, Ivanisenko VA, Demenkov P, Mustafin Z, Markel A, Savinkova L, Kolchanov NA, Kozlov V, Ponomarenko M. Differentially Expressed Genes and Molecular Susceptibility to Human Age-Related Diseases. Int J Mol Sci 2023; 24:ijms24043996. [PMID: 36835409 PMCID: PMC9966505 DOI: 10.3390/ijms24043996] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 02/02/2023] [Accepted: 02/13/2023] [Indexed: 02/18/2023] Open
Abstract
Mainstream transcriptome profiling of susceptibility versus resistance to age-related diseases (ARDs) is focused on differentially expressed genes (DEGs) specific to gender, age, and pathogeneses. This approach fits in well with predictive, preventive, personalized, participatory medicine and helps understand how, why, when, and what ARDs one can develop depending on their genetic background. Within this mainstream paradigm, we wanted to find out whether the known ARD-linked DEGs available in PubMed can reveal a molecular marker that will serve the purpose in anyone's any tissue at any time. We sequenced the periaqueductal gray (PAG) transcriptome of tame versus aggressive rats, identified rat-behavior-related DEGs, and compared them with their known homologous animal ARD-linked DEGs. This analysis yielded statistically significant correlations between behavior-related and ARD-susceptibility-related fold changes (log2 values) in the expression of these DEG homologs. We found principal components, PC1 and PC2, corresponding to the half-sum and the half-difference of these log2 values, respectively. With the DEGs linked to ARD susceptibility and ARD resistance in humans used as controls, we verified these principal components. This yielded only one statistically significant common molecular marker for ARDs: an excess of Fcγ receptor IIb suppressing immune cell hyperactivation.
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Affiliation(s)
- Svetlana Shikhevich
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences (SB RAS), Novosibirsk 630090, Russia
| | - Irina Chadaeva
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences (SB RAS), Novosibirsk 630090, Russia
| | - Bato Khandaev
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences (SB RAS), Novosibirsk 630090, Russia
- The Natural Sciences Department, Novosibirsk State University, Novosibirsk 630090, Russia
| | - Rimma Kozhemyakina
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences (SB RAS), Novosibirsk 630090, Russia
| | - Karina Zolotareva
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences (SB RAS), Novosibirsk 630090, Russia
- The Natural Sciences Department, Novosibirsk State University, Novosibirsk 630090, Russia
| | - Anna Kazachek
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences (SB RAS), Novosibirsk 630090, Russia
- The Natural Sciences Department, Novosibirsk State University, Novosibirsk 630090, Russia
| | - Dmitry Oshchepkov
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences (SB RAS), Novosibirsk 630090, Russia
- The Natural Sciences Department, Novosibirsk State University, Novosibirsk 630090, Russia
| | - Anton Bogomolov
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences (SB RAS), Novosibirsk 630090, Russia
- The Natural Sciences Department, Novosibirsk State University, Novosibirsk 630090, Russia
| | - Natalya V. Klimova
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences (SB RAS), Novosibirsk 630090, Russia
| | - Vladimir A. Ivanisenko
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences (SB RAS), Novosibirsk 630090, Russia
- The Natural Sciences Department, Novosibirsk State University, Novosibirsk 630090, Russia
| | - Pavel Demenkov
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences (SB RAS), Novosibirsk 630090, Russia
| | - Zakhar Mustafin
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences (SB RAS), Novosibirsk 630090, Russia
- The Natural Sciences Department, Novosibirsk State University, Novosibirsk 630090, Russia
| | - Arcady Markel
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences (SB RAS), Novosibirsk 630090, Russia
- The Natural Sciences Department, Novosibirsk State University, Novosibirsk 630090, Russia
| | - Ludmila Savinkova
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences (SB RAS), Novosibirsk 630090, Russia
| | - Nikolay A. Kolchanov
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences (SB RAS), Novosibirsk 630090, Russia
- The Natural Sciences Department, Novosibirsk State University, Novosibirsk 630090, Russia
| | - Vladimir Kozlov
- Research Institute of Fundamental and Clinical Immunology (RIFCI) SB RAS, Novosibirsk 630099, Russia
| | - Mikhail Ponomarenko
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences (SB RAS), Novosibirsk 630090, Russia
- Correspondence: ; Tel.: +7-(383)-363-4963 (ext. 1311)
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Ma W, Lu K, Liang HM, Zhang JY. Synapsin 1 Ameliorates Cognitive Impairment and Neuroinflammation in Rats with Alzheimer's Disease: An Experimental and Bioinformatics Study. Curr Alzheimer Res 2023; 20:648-659. [PMID: 38213171 DOI: 10.2174/0115672050276594231229050906] [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: 09/28/2023] [Revised: 12/12/2023] [Accepted: 12/21/2023] [Indexed: 01/13/2024]
Abstract
BACKGROUND Alzheimer's disease (AD) is a persistent neuropathological injury that manifests via neuronal/synaptic death, age spot development, tau hyperphosphorylation, neuroinflammation, and apoptosis. Synapsin 1 (SYN1), a neuronal phosphoprotein, is believed to be responsible for the pathology of AD. OBJECTIVE This study aimed to elucidate the exact role of SYN1 in ameliorating AD and its potential regulatory mechanisms. METHODS The AD dataset GSE48350 was downloaded from the GEO database, and SYN1 was focused on differential expression analysis and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. After establishing an AD rat model, they were treated with RNAi lentivirus to trigger SYN1 overexpression. The amelioration of SYN1 in AD-associated behavior was validated using multiple experiments (water maze test and object recognition test). SYN1's repairing effect on the important factors in AD was confirmed by detecting the concentration of inflammatory factors (interleukin (IL)-6, IL-1β, tumor necrosis factor (TNF)-α), neurotransmitters (acetylcholine (ACh), dopamine (DA), and 5-hydroxytryptophan (5-HT)) and markers of oxidative stress (glutathione (GSH), malondialdehyde (MDA), reactive oxygen species (ROS)). Molecular biology experiments (qRT-PCR and western blot) were performed to examine AD-related signaling pathways after SYN1 overexpression. RESULTS Differential expression analysis yielded a total of 545 differentially expressed genes, of which four were upregulated and 541 were downregulated. The enriched pathways were basically focused on synaptic functions, and the analysis of the protein- protein interaction network focused on the key genes in SYN1. SYN1 significantly improved the spatial learning and memory abilities of AD rats. This enhancement was reflected in the reduced escape latency of the rats in the water maze, the significantly extended dwell time in the third quadrant, and the increased number of crossings. Furthermore, the results of the object recognition test revealed reduced time for rats to explore familiar and new objects. After SYN1 overexpression, the cAMP signaling pathway was activated, the phosphorylation levels of the CREB and PKA proteins were elevated, and the secretion of neurotransmitters such as ACh, DA, and 5-HT was promoted. Furthermore, oxidative stress was suppressed, as supported by decreased levels of MDA and ROS. Regarding inflammatory factors, the levels of IL-6, IL-1β, and TNF-α were significantly reduced in AD rats with SYN1 overexpression. CONCLUSION SYN1 overexpression improves cognitive function and promotes the release of various neurotransmitters in AD rats by inhibiting oxidative stress and inflammatory responses through cAMP signaling pathway activation. These findings may provide a theoretical basis for the targeted diagnosis and treatment of AD.
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Affiliation(s)
- Wei Ma
- Department of Neurology, General Hospital of Ningxia Medical University. Yinchuan750004, China
| | - Kui Lu
- Department of Neurology, The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Enshi, 445000, China
| | - Hua-Min Liang
- Department of Neurology, General Hospital of Ningxia Medical University. Yinchuan750004, China
| | - Jin-Yuan Zhang
- Department of Neurology, General Hospital of Ningxia Medical University. Yinchuan750004, China
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Peng L, Chen H, Wang Z, He Y, Zhang X. Identification and validation of a classifier based on hub aging-related genes and aging subtypes correlation with immune microenvironment for periodontitis. Front Immunol 2022; 13:1042484. [PMID: 36389665 PMCID: PMC9663931 DOI: 10.3389/fimmu.2022.1042484] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 10/18/2022] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND Periodontitis (PD), an age-related disease, is characterized by inflammatory periodontal tissue loss, and with the general aging of the global population, the burden of PD is becoming a major health concern. Nevertheless, the mechanism underlying this phenomenon remains indistinct. We aimed to develop a classification model for PD and explore the relationship between aging subtypes and the immune microenvironment for PD based on bioinformatics analysis. MATERIALS AND METHODS The PD-related datasets were acquired from the Gene Expression Omnibus (GEO) database, and aging-related genes (ARGs) were obtained from the Human Aging Genomic Resources (HAGR). Four machine learning algorithms were applied to screen out the hub ARGs. Then, an artificial neural network (ANN) model was constructed and the accuracy of the model was validated by receiver operating characteristic (ROC) curve analysis. The clinical effect of the model was evaluated by decision curve analysis (DCA). Consensus clustering was employed to determine the aging expression subtypes. A series of bioinformatics analyses were performed to explore the PD immune microenvironment and its subtypes. The hub aging-related modules were defined using weighted correlation network analysis (WGCNA). RESULTS Twenty-seven differentially expressed ARGs were dysregulated and a classifier based on four hub ARGs (BLM, FOS, IGFBP3, and PDGFRB) was constructed to diagnose PD with excellent accuracy. Subsequently, the mRNA levels of the hub ARGs were validated by quantitative real-time PCR (qRT-PCR). Based on differentially expressed ARGs, two aging-related subtypes were identified. Distinct biological functions and immune characteristics including infiltrating immunocytes, immunological reaction gene sets, the human leukocyte antigen (HLA) gene, and immune checkpoints were revealed between the subtypes. Additionally, the black module correlated with subtype-1 was manifested as the hub aging-related module and its latent functions were identified. CONCLUSION Our findings highlight the critical implications of aging-related genes in modulating the immune microenvironment. Four hub ARGs (BLM, FOS, IGFBP3, and PDGFRB) formed a classification model, and accompanied findings revealed the essential role of aging in the immune microenvironment for PD, providing fresh inspiration for PD etiopathogenesis and potential immunotherapy.
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Affiliation(s)
- Limin Peng
- College of Stomatology, Chongqing Medical University, Chongqing, China,Chongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, Chongqing, China,Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Chongqing, China
| | - Hang Chen
- College of Stomatology, Chongqing Medical University, Chongqing, China,Chongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, Chongqing, China,Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Chongqing, China
| | - Zhenxiang Wang
- College of Stomatology, Chongqing Medical University, Chongqing, China,Chongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, Chongqing, China,Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Chongqing, China
| | - Yujuan He
- Department of Laboratory Medicine, Key Laboratory of Diagnostic Medicine (Ministry of Education), Chongqing Medical University, Chongqing, China
| | - Xiaonan Zhang
- College of Stomatology, Chongqing Medical University, Chongqing, China,Chongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, Chongqing, China,Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Chongqing, China,*Correspondence: Xiaonan Zhang,
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Deng Y, Feng Y, Lv Z, He J, Chen X, Wang C, Yuan M, Xu T, Gao W, Chen D, Zhu H, Hou D. Machine learning models identify ferroptosis-related genes as potential diagnostic biomarkers for Alzheimer’s disease. Front Aging Neurosci 2022; 14:994130. [PMID: 36262887 PMCID: PMC9575464 DOI: 10.3389/fnagi.2022.994130] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 09/12/2022] [Indexed: 11/13/2022] Open
Abstract
Alzheimer’s disease (AD) is a complex, and multifactorial neurodegenerative disease. Previous studies have revealed that oxidative stress, synaptic toxicity, autophagy, and neuroinflammation play crucial roles in the progress of AD, however, its pathogenesis is still unclear. Recent researches have indicated that ferroptosis, an iron-dependent programmed cell death, might be involved in the pathogenesis of AD. Therefore, we aim to screen correlative ferroptosis-related genes (FRGs) in the progress of AD to clarify insights into the diagnostic value. Interestingly, we identified eight FRGs were significantly differentially expressed in AD patients. 10,044 differentially expressed genes (DEGs) were finally identified by differential expression analysis. The following step was investigating the function of DEGs using gene set enrichment analysis (GSEA). Weight gene correlation analysis was performed to explore ten modules and 104 hub genes. Subsequently, based on machine learning algorithms, we constructed diagnostic classifiers to select characteristic genes. Through the multivariable logistic regression analysis, five features (RAF1, NFKBIA, MOV10L1, IQGAP1, FOXO1) were then validated, which composed a diagnostic model of AD. Thus, our findings not only developed genetic diagnostics strategy, but set a direction for further study of the disease pathogenesis and therapy targets.
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Affiliation(s)
- Yanyao Deng
- Department of Rehabilitation, The First Hospital of Changsha, Changsha, China
| | - Yanjin Feng
- Department of Neurology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Zhicheng Lv
- Department of Neurosurgery, The First People’s Hospital of Chenzhou, Chenzhou, China
| | - Jinli He
- Department of Neurology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Xun Chen
- Department of Neurology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Chen Wang
- Department of Neurology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Mingyang Yuan
- Department of Neurology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Ting Xu
- Department of Neurology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Wenzhe Gao
- Department of Hepatopancreatobiliary Surgery, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Dongjie Chen
- Department of Hepatopancreatobiliary Surgery, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Hongwei Zhu
- Department of Hepatopancreatobiliary Surgery, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Deren Hou
- Department of Neurology, The Third Xiangya Hospital, Central South University, Changsha, China
- *Correspondence: Deren Hou,
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