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Guo S, Liu C, Wang Y, Chen F, Zhu J, Li S, Li E. Effect of resveratrol on spermatogenesis in breeding boars and the proteomic analysis for testes. Reprod Biol 2024; 24:100930. [PMID: 39173316 DOI: 10.1016/j.repbio.2024.100930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 07/30/2024] [Accepted: 08/08/2024] [Indexed: 08/24/2024]
Abstract
Effect of resveratrol (RSV) on spermatogenesis and the mechanism of resveratrol in promoting spermatogenesis of breeding boars was explored by feeding sexually mature Duroc boars with normal diet and 20 mg/kg resveratrol diet for 14 days to the control group and experimental group, respectively. Semen volume, sperm density, motility, viability and abnormality rate were analyzed on day 0, 7, and 14. Blood samples were collected, and levels of follicle-stimulating hormone (FSH), luteinizing hormone (LH), and testosterone (T) in serum were analyzed. On day 14, the testis tissue was collected for antioxidant and proteomics analysis etc. The semen volume, sperm density, motility, and viability of the experimental group and the contents of serum FSH, LH, T and plasma SOD activity were significantly higher than those in the control group. However, the serum IL-6, TNF-α and plasma MDA were remarkably lower in experimental group. The above results showed that resveratrol can simulate spermatogenesis in breeding boars. Proteomic results demonstrated that three differentially expressed proteins (DEPs) were up-regulated and 12 DEPs were down-regulated; ODF1, calmodulin, Cabs1, and Hp were involved in spermatogenesis; and the main enriched metabolic pathway is steroid hormone synthesis pathway. Therefore, the improvement in sperm quality by resveratrol may be achieved by regulating the changes in outer dense fiber 1, calmodulin, spermatid specific 1, and haptoglobin expression and steroid synthesis pathway.
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Affiliation(s)
- Shuang Guo
- School of biological and food processing engineering, Huanghuai University, Zhumadian, Henan province 463000, PR China
| | - Chaoying Liu
- School of biological and food processing engineering, Huanghuai University, Zhumadian, Henan province 463000, PR China; Zhumadian Academy of Industry Innovation and Development, Zhumadian, Henan province 463000, PR China
| | - Ye Wang
- School of biological and food processing engineering, Huanghuai University, Zhumadian, Henan province 463000, PR China
| | - Fujia Chen
- School of biological and food processing engineering, Huanghuai University, Zhumadian, Henan province 463000, PR China
| | - Jinjin Zhu
- School of biological and food processing engineering, Huanghuai University, Zhumadian, Henan province 463000, PR China
| | - Siqiang Li
- School of biological and food processing engineering, Huanghuai University, Zhumadian, Henan province 463000, PR China
| | - Enzhong Li
- School of biological and food processing engineering, Huanghuai University, Zhumadian, Henan province 463000, PR China.
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Zhuang K, Wang W, Xu C, Guo X, Ren X, Liang Y, Duan Z, Song Y, Zhang Y, Cai G. Machine learning-based diagnosis and prognosis of IgAN: A systematic review and meta-analysis. Heliyon 2024; 10:e33090. [PMID: 38988582 PMCID: PMC11234108 DOI: 10.1016/j.heliyon.2024.e33090] [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: 08/09/2023] [Revised: 06/04/2024] [Accepted: 06/13/2024] [Indexed: 07/12/2024] Open
Abstract
Purpose Plenty of studies have explored the diagnosis and prognosis of IgA nephropathy (IgAN) based on machine learning (ML), but the accuracy lacks the support of evidence-based medical evidence. We aim at this problem to guide the precision treatment of IgAN. Methods Embase, Pubmed, Cochrane Library, and Web of Science were searched systematically until February 24th, 2024, for publications on ML-based diagnosis and prognosis of IgAN. Subgroup analysis or meta-regression was conducted according to modeling method, follow-up time, endpoint definition, and variable type. Further, the rank sum test was applied to compare the discrimination ability of prognosis. Results A total of 47 studies involving 51,935 patients were eligible. Among the 38 diagnostic models, the pooled C-index was 0.902 (95 % CI: 0.878-0.926) in 27 diagnostic models. Of the 162 prognostic models, the C-index for model discrimination of 144 prognostic models was 0.838 (95 % CI: 0.827-0.850) in training. The overall discrimination ability of prognosis was as follows: COX regression > new ML models (e.g. ANN, DT, RF, SVM, XGBoost) > traditional ML models (logistic regression) > Naïve Bayesian network (P < 0.05). External validation of IIgAN-RPT in 19 models showed a pooled C-index of 0.801 (95 % CI: 0.784-0.817). Conclusions New ML models have shown application values that are as good as traditional ML models, both in diagnosis and prognosis. In addition, future models are desired to use a more sensitive prognostic endpoint (albuminuria), improve predictive ability in moderate progression risk, and ultimately translate into clinically applicable intelligent tools.
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Affiliation(s)
- Kaiting Zhuang
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing 100853, China
| | - Wenjuan Wang
- School of Medicine, Nankai University, Tianjin, 300071, China
| | - Cheng Xu
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing 100853, China
| | - Xinru Guo
- School of Medicine, Nankai University, Tianjin, 300071, China
| | - Xuejing Ren
- Zhengzhou University People's Hospital, Henan Provincial People's Hospital, Henan Key Laboratory of Kidney Disease and Immunology, Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, 450003, China
| | - Yanjun Liang
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing 100853, China
| | - Zhiyu Duan
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing 100853, China
| | - Yanqi Song
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing 100853, China
| | - Yifan Zhang
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing 100853, China
| | - Guangyan Cai
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing 100853, China
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Shen L, Yue S. M6A-related bioinformatics analysis indicates that LRPPRC is an immune marker for ischemic stroke. Sci Rep 2024; 14:8852. [PMID: 38632288 PMCID: PMC11024132 DOI: 10.1038/s41598-024-57507-y] [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: 10/16/2023] [Accepted: 03/19/2024] [Indexed: 04/19/2024] Open
Abstract
Ischemic stroke (IS) is a common cerebrovascular disease whose pathogenesis involves a variety of immune molecules, immune channels and immune processes. 6-methyladenosine (m6A) modification regulates a variety of immune metabolic and immunopathological processes, but the role of m6A in IS is not yet understood. We downloaded the data set GSE58294 from the GEO database and screened for m6A-regulated differential expression genes. The RF algorithm was selected to screen the m6A key regulatory genes. Clinical prediction models were constructed and validated based on m6A key regulatory genes. IS patients were grouped according to the expression of m6A key regulatory genes, and immune markers of IS were identified based on immune infiltration characteristics and correlation. Finally, we performed functional enrichment, protein interaction network analysis and molecular prediction of the immune biomarkers. We identified a total of 7 differentially expressed genes in the dataset, namely METTL3, WTAP, YWHAG, TRA2A, YTHDF3, LRPPRC and HNRNPA2B1. The random forest algorithm indicated that all 7 genes were m6A key regulatory genes of IS, and the credibility of the above key regulatory genes was verified by constructing a clinical prediction model. Based on the expression of key regulatory genes, we divided IS patients into 2 groups. Based on the expression of the gene LRPPRC and the correlation of immune infiltration under different subgroups, LRPPRC was identified as an immune biomarker for IS. GO enrichment analyses indicate that LRPPRC is associated with a variety of cellular functions. Protein interaction network analysis and molecular prediction indicated that LRPPRC correlates with a variety of immune proteins, and LRPPRC may serve as a target for IS drug therapy. Our findings suggest that LRPPRC is an immune marker for IS. Further analysis based on LRPPRC could elucidate its role in the immune microenvironment of IS.
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Affiliation(s)
- Lianwei Shen
- Rehabitation Center, Qilu Hospital of Shandong University, No. 107, West Culture Road, Lixia District, Jinan, 250012, Shandong, China
| | - Shouwei Yue
- Rehabitation Center, Qilu Hospital of Shandong University, No. 107, West Culture Road, Lixia District, Jinan, 250012, Shandong, China.
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Fu X, Luo ZX, Yin HH, Liu YN, Du XG, Cheng W, Liu JY. Metabolomics study reveals blood biomarkers for early diagnosis of chronic kidney disease and IgA nephropathy: A retrospective cross-sectional study. Clin Chim Acta 2024; 555:117815. [PMID: 38309556 DOI: 10.1016/j.cca.2024.117815] [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: 12/08/2023] [Revised: 01/10/2024] [Accepted: 01/29/2024] [Indexed: 02/05/2024]
Abstract
BACKGROUND AND AIMS Chronic kidney disease (CKD) causes low quality of life and alarming morbidity and mortality. The crucial to retard CKD progression is to diagnose early for timely treatment. IgA nephropathy (IgAN) is a typical CKD and the most common glomerulonephritis. Both CKD and IgAN lack accurate and sensitive blood biomarkers for early diagnosis. Here we report the potential of plasma biomarkers for early diagnosis of CKD and IgAN. MATERIALS AND METHODS Plasma levels of metabolites derived from tryptophan were quantified with an LC-MS/MS-based metabolomics for two cohorts. Based on the predictive probability of each metabolite, multivariate models including logistic regression and random forest were used to establish the early diagnostic biomarkers for CKD and IgAN. RESULTS The plasma melatonin diagnosed early CKD (stages Ⅰ-Ⅱ) with an accuracy exceeding 95%, and a panel of melatonin and tryptophan achieved a remarkable 100% accuracy in diagnosing early CKD. Furthermore, indole-3-lactic acid had an excellent ability to distinguish IgAN among CKD patients. Based on the CKD screening and IgAN diagnosis primarily contributed by melatonin and indole-3-lactic acid, early IgAN could be diagnosed with an accuracy of over 85%. CONCLUSIONS This study provides promising plasma biomarkers for early diagnosis of CKD and IgAN.
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Affiliation(s)
- Xian Fu
- CNTTI of the Institute of Life Sciences & Anesthesia Department of the Second Affiliated Hospital, Chongqing Medical University, Chongqing 400016, China; Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, Chongqing 400016, China; College of Pharmacy, Chongqing Medical University, Chongqing 400016, China
| | - Zhi-Xiao Luo
- The Center for Clinical Molecular Medical Detection, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Hou-Hua Yin
- CNTTI of the Institute of Life Sciences & Anesthesia Department of the Second Affiliated Hospital, Chongqing Medical University, Chongqing 400016, China; Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, Chongqing 400016, China
| | - Ya-Nan Liu
- CNTTI of the Institute of Life Sciences & Anesthesia Department of the Second Affiliated Hospital, Chongqing Medical University, Chongqing 400016, China; Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, Chongqing 400016, China
| | - Xiao-Gang Du
- Department of Nephrology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
| | - Wei Cheng
- The Center for Clinical Molecular Medical Detection, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
| | - Jun-Yan Liu
- CNTTI of the Institute of Life Sciences & Anesthesia Department of the Second Affiliated Hospital, Chongqing Medical University, Chongqing 400016, China; Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, Chongqing 400016, China; College of Pharmacy, Chongqing Medical University, Chongqing 400016, China.
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de Souza Barcelos NE, Limeres ML, Peixoto-Dias AF, Vieira MAR, Peruchetti DB. Kidney Disease and Proteomics: A Recent Overview of a Useful Tool for Improving Early Diagnosis. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1443:173-186. [PMID: 38409421 DOI: 10.1007/978-3-031-50624-6_9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
Kidney disease is a critical and potentially life-threatening degenerative condition that poses a significant global public health challenge due to its elevated rates of morbidity and mortality. It manifests primarily in two distinct clinical forms: acute kidney injury (AKI) and chronic kidney disease (CKD). The development of these conditions hinges on a multitude of factors, including the etiological agents and the presence of coexisting medical conditions. Despite disparities in their underlying pathogenic mechanisms, both AKI and CKD can progress to end-stage kidney disease (ESKD). This advanced stage is characterized by organ failure and its associated complications, greatly increasing the risk of mortality. There is an urgent need to delve into the pathogenic mechanisms underlying these diseases and to identify novel biomarkers that can facilitate earlier diagnosis. Such early detection is crucial for enhancing the efficacy of therapy and impeding disease progression. In this context, proteomic approaches have emerged as invaluable tools for uncovering potential new markers of different pathological conditions, including kidney diseases. In this chapter, we overview the recent discoveries achieved through diverse proteomic techniques aimed at identifying novel molecules that may play a pivotal role in kidney diseases such as diabetic kidney disease (DKD), IgA nephropathy (IgAN), CKD of unknown origin (CKDu), autosomal dominant polycystic kidney disease (ADPKD), lupus nephritis (LN), hypertensive nephropathy (HN), and COVID-19-associated acute kidney injury (COVID-AKI).
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Affiliation(s)
- Nicolly Emanuelle de Souza Barcelos
- Department of Physiology and Biophysics, Institute of Biological Sciences, Federal University of Minas Gerais (UFMG), Belo Horizonte, MG, Brazil
| | - Maria Laura Limeres
- Department of Physiology and Biophysics, Institute of Biological Sciences, Federal University of Minas Gerais (UFMG), Belo Horizonte, MG, Brazil
| | - Ana Flavia Peixoto-Dias
- Department of Physiology and Biophysics, Institute of Biological Sciences, Federal University of Minas Gerais (UFMG), Belo Horizonte, MG, Brazil
| | - Maria Aparecida Ribeiro Vieira
- Department of Physiology and Biophysics, Institute of Biological Sciences, Federal University of Minas Gerais (UFMG), Belo Horizonte, MG, Brazil
| | - Diogo B Peruchetti
- Department of Physiology and Biophysics, Institute of Biological Sciences, Federal University of Minas Gerais (UFMG), Belo Horizonte, MG, Brazil.
- INCT-Nanobiofar, Belo Horizonte, MG, Brazil.
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Roointan A, Ghaeidamini M, Shafieizadegan S, Hudkins KL, Gholaminejad A. Metabolome panels as potential noninvasive biomarkers for primary glomerulonephritis sub-types: meta-analysis of profiling metabolomics studies. Sci Rep 2023; 13:20325. [PMID: 37990116 PMCID: PMC10663527 DOI: 10.1038/s41598-023-47800-7] [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: 03/13/2023] [Accepted: 11/18/2023] [Indexed: 11/23/2023] Open
Abstract
Primary glomerulonephritis diseases (PGDs) are known as the top causes of chronic kidney disease worldwide. Renal biopsy, an invasive method, is the main approach to diagnose PGDs. Studying the metabolome profiles of kidney diseases is an inclusive approach to identify the disease's underlying pathways and discover novel non-invasive biomarkers. So far, different experiments have explored the metabolome profiles in different PGDs, but the inconsistencies might hinder their clinical translations. The main goal of this meta-analysis study was to achieve consensus panels of dysregulated metabolites in PGD sub-types. The PGDs-related metabolome profiles from urine samples in humans were selected in a comprehensive search. Amanida package in R software was utilized for performing the meta-analysis. Through sub-type analyses, the consensus list of metabolites in each category was obtained. To identify the most affected pathways, functional enrichment analysis was performed. Also, a gene-metabolite network was constructed to identify the key metabolites and their connected proteins. After a vigorous search, among the 11 selected studies (15 metabolite profiles), 270 dysregulated metabolites were recognized in urine of 1154 PGDs and control samples. Through sub-type analyses by Amanida package, the consensus list of metabolites in each category was obtained. Top dysregulated metabolites (vote score of ≥ 4 or ≤ - 4) in PGDs urines were selected as main panel of meta-metabolites including glucose, leucine, choline, betaine, dimethylamine, fumaric acid, citric acid, 3-hydroxyisovaleric acid, pyruvic acid, isobutyric acid, and hippuric acid. The enrichment analyses results revealed the involvement of different biological pathways such as the TCA cycle and amino acid metabolisms in the pathogenesis of PGDs. The constructed metabolite-gene interaction network revealed the high centralities of several metabolites, including pyruvic acid, leucine, and choline. The identified metabolite panels could shed a light on the underlying pathological pathways and be considered as non-invasive biomarkers for the diagnosis of PGD sub-types.
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Affiliation(s)
- Amir Roointan
- Regenerative Medicine Research Center, Faculty of Medicine, Isfahan University of Medical Sciences, Hezar Jarib St., Isfahan, 81746-73461, Iran
| | - Maryam Ghaeidamini
- Regenerative Medicine Research Center, Faculty of Medicine, Isfahan University of Medical Sciences, Hezar Jarib St., Isfahan, 81746-73461, Iran
| | - Saba Shafieizadegan
- Regenerative Medicine Research Center, Faculty of Medicine, Isfahan University of Medical Sciences, Hezar Jarib St., Isfahan, 81746-73461, Iran
| | - Kelly L Hudkins
- Department of Laboratory Medicine and Pathology, University of Washington, School of Medicine, Seattle, USA
| | - Alieh Gholaminejad
- Regenerative Medicine Research Center, Faculty of Medicine, Isfahan University of Medical Sciences, Hezar Jarib St., Isfahan, 81746-73461, Iran.
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Dong L, Tan J, Zhong Z, Tang Y, Qin W. Altered serum metabolic profile in patients with IgA nephropathy. Clin Chim Acta 2023; 549:117561. [PMID: 37722576 DOI: 10.1016/j.cca.2023.117561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 09/11/2023] [Accepted: 09/15/2023] [Indexed: 09/20/2023]
Abstract
BACKGROUND We investigated alterations in the serum metabolomic profile of IgA nephropathy (IgAN) patients and screen biomarkers of IgA nephropathy based on ultra-performance liquid chromatography-mass spectrometry (UPLC-MS). METHODS Serum samples from 65 IgAN patients and 31 healthy controls were analyzed by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS). Univariate and multivariate analysis were performed to screen the differential metabolites. Differential metabolites should meet both the following two criteria: adjusted P < 0.05 in the univariate analysis and VIP value > 1 in the multivariate model. Pathway analysis was performed to reveal the metabolic pathways that were significantly influenced in IgAN. Spearman correlation analysis was applied to explore the correlation between metabolites and between the metabolites and clinicopathological features of IgAN. A random forest model and Logistics regression analysis were conducted to evaluate the predictive ability of the metabolites. RESULTS The metabolic profile was significantly altered in IgAN patients compared with healthy controls. Thirty-nine metabolites were identified, including glycerophospholipids, sphingolipids, vitamin K1, vitamin K2, bile acids and amino acids. Sphingolipid metabolism, ubiquinone and other terpenoid-quinone biosynthesis, and glycerophospholipid metabolism were found to be significantly disturbed in the pathway analysis. Differential metabolites were found to be associated with the clinical and pathological features of IgAN patients. Lanosterol, vitamin K1, vitamin K2, and β-elemonic acid were found to have promising predictive ability for IgAN. CONCLUSIONS We confirmed the differences in the metabolic profiles of IgAN patients and healthy controls and identified the differential metabolites of IgAN, which may help with the further exploration of the pathogenesis and treatment of IgAN.
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Affiliation(s)
- Lingqiu Dong
- Department of Nephrology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jiaxing Tan
- Department of Nephrology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Zhengxia Zhong
- Division of Nephrology, Department of Medicine, Affiliated Hospital of Zunyi Medical College, Zunyi, Guizhou, China
| | - Yi Tang
- Department of Nephrology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Wei Qin
- Department of Nephrology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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Mucha K, Pac M, Pączek L. Omics are Getting Us Closer to Understanding IgA Nephropathy. Arch Immunol Ther Exp (Warsz) 2023; 71:12. [PMID: 37060455 PMCID: PMC10105675 DOI: 10.1007/s00005-023-00677-w] [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: 10/23/2021] [Accepted: 03/02/2023] [Indexed: 04/16/2023]
Abstract
During the last decade, thanks to omics technologies, new light has been shed on the pathogenesis of many diseases. Genomics, epigenomics, transcriptomics, and proteomics have helped to provide a better understanding of the origin and heterogeneity of several diseases. However, the risk factors for most autoimmune diseases remain unknown. The successes and pitfalls of omics have also been observed in nephrology, including immunoglobulin A nephropathy (IgAN), the most common form of glomerulonephritis and a principal cause of end-stage renal disease worldwide. Unfortunately, the immense progress in basic research has not yet been followed by the satisfactory development of a targeted treatment. Although, most omics studies describe changes in the immune system, there is still insufficient data to apply their results in the constantly evolving multi-hit pathogenesis model and thus do to provide a complete picture of the disease. Here, we describe recent findings regarding the pathophysiology of IgAN and link omics studies with immune system dysregulation. This review provides insights into specific IgAN markers, which may lead to the identification of potential targets for personalised treatment in the future.
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Affiliation(s)
- Krzysztof Mucha
- Department of Immunology, Transplantology and Internal Diseases, Medical University of Warsaw, Warsaw, Poland.
- Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw, Poland.
| | - Michał Pac
- Department of Immunology, Transplantology and Internal Diseases, Medical University of Warsaw, Warsaw, Poland
| | - Leszek Pączek
- Department of Immunology, Transplantology and Internal Diseases, Medical University of Warsaw, Warsaw, Poland
- Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw, Poland
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