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Liu S, Cao Y, Zhang Y. Regulatory roles of RNA methylation in vascular lesions in ocular and cardiopulmonary diseases. Crit Rev Clin Lab Sci 2024:1-15. [PMID: 38957015 DOI: 10.1080/10408363.2024.2370267] [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: 12/28/2023] [Accepted: 06/17/2024] [Indexed: 07/04/2024]
Abstract
RNA methylation is a widespread regulatory mechanism that controls gene expression in physiological processes. In recent years, the mechanisms and functions of RNA methylation under diseased conditions have been increasingly unveiled by RNA sequencing technologies with large scale and high resolution. In this review, the fundamental concept of RNA methylation is introduced, and the common types of transcript methylation and their machineries are described. Then, the regulatory roles of RNA methylation, particularly N6-methyladenosine and 5-methylcytosine, in the vascular lesions of ocular and cardiopulmonary diseases are discussed and compared. The ocular diseases include corneal neovascularization, retinopathy of prematurity, diabetic retinopathy, and pathologic myopia; whereas the cardiopulmonary ailments involve atherosclerosis and pulmonary hypertension. This review hopes to shed light on the common regulatory mechanisms underlying the vascular lesions in these ocular and cardiopulmonary diseases, which may be conducive to developing therapeutic strategies in clinical practice.
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Affiliation(s)
- Siyi Liu
- Tianjin Key Laboratory of Retinal Functions and Diseases, Tianjin Branch of National Clinical Research Center for Ocular Disease, Eye Institute and School of Optometry, Tianjin Medical University Eye Hospital, Tianjin, China
| | - Yunshan Cao
- Department of Cardiology, Gansu Provincial Hospital, Lanzhou, China
| | - Yan Zhang
- Tianjin Key Laboratory of Retinal Functions and Diseases, Tianjin Branch of National Clinical Research Center for Ocular Disease, Eye Institute and School of Optometry, Tianjin Medical University Eye Hospital, Tianjin, China
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2
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Golubnitschaja O, Polivka J, Potuznik P, Pesta M, Stetkarova I, Mazurakova A, Lackova L, Kubatka P, Kropp M, Thumann G, Erb C, Fröhlich H, Wang W, Baban B, Kapalla M, Shapira N, Richter K, Karabatsiakis A, Smokovski I, Schmeel LC, Gkika E, Paul F, Parini P, Polivka J. The paradigm change from reactive medical services to 3PM in ischemic stroke: a holistic approach utilising tear fluid multi-omics, mitochondria as a vital biosensor and AI-based multi-professional data interpretation. EPMA J 2024; 15:1-23. [PMID: 38463624 PMCID: PMC10923756 DOI: 10.1007/s13167-024-00356-6] [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: 02/01/2024] [Accepted: 02/08/2024] [Indexed: 03/12/2024]
Abstract
Worldwide stroke is the second leading cause of death and the third leading cause of death and disability combined. The estimated global economic burden by stroke is over US$891 billion per year. Within three decades (1990-2019), the incidence increased by 70%, deaths by 43%, prevalence by 102%, and DALYs by 143%. Of over 100 million people affected by stroke, about 76% are ischemic stroke (IS) patients recorded worldwide. Contextually, ischemic stroke moves into particular focus of multi-professional groups including researchers, healthcare industry, economists, and policy-makers. Risk factors of ischemic stroke demonstrate sufficient space for cost-effective prevention interventions in primary (suboptimal health) and secondary (clinically manifested collateral disorders contributing to stroke risks) care. These risks are interrelated. For example, sedentary lifestyle and toxic environment both cause mitochondrial stress, systemic low-grade inflammation and accelerated ageing; inflammageing is a low-grade inflammation associated with accelerated ageing and poor stroke outcomes. Stress overload, decreased mitochondrial bioenergetics and hypomagnesaemia are associated with systemic vasospasm and ischemic lesions in heart and brain of all age groups including teenagers. Imbalanced dietary patterns poor in folate but rich in red and processed meat, refined grains, and sugary beverages are associated with hyperhomocysteinaemia, systemic inflammation, small vessel disease, and increased IS risks. Ongoing 3PM research towards vulnerable groups in the population promoted by the European Association for Predictive, Preventive and Personalised Medicine (EPMA) demonstrates promising results for the holistic patient-friendly non-invasive approach utilising tear fluid-based health risk assessment, mitochondria as a vital biosensor and AI-based multi-professional data interpretation as reported here by the EPMA expert group. Collected data demonstrate that IS-relevant risks and corresponding molecular pathways are interrelated. For examples, there is an evident overlap between molecular patterns involved in IS and diabetic retinopathy as an early indicator of IS risk in diabetic patients. Just to exemplify some of them such as the 5-aminolevulinic acid/pathway, which are also characteristic for an altered mitophagy patterns, insomnia, stress regulation and modulation of microbiota-gut-brain crosstalk. Further, ceramides are considered mediators of oxidative stress and inflammation in cardiometabolic disease, negatively affecting mitochondrial respiratory chain function and fission/fusion activity, altered sleep-wake behaviour, vascular stiffness and remodelling. Xanthine/pathway regulation is involved in mitochondrial homeostasis and stress-driven anxiety-like behaviour as well as molecular mechanisms of arterial stiffness. In order to assess individual health risks, an application of machine learning (AI tool) is essential for an accurate data interpretation performed by the multiparametric analysis. Aspects presented in the paper include the needs of young populations and elderly, personalised risk assessment in primary and secondary care, cost-efficacy, application of innovative technologies and screening programmes, advanced education measures for professionals and general population-all are essential pillars for the paradigm change from reactive medical services to 3PM in the overall IS management promoted by the EPMA.
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Affiliation(s)
- Olga Golubnitschaja
- Predictive, Preventive and Personalised (3P) Medicine, Department of Radiation Oncology, University Hospital Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn, 53127 Bonn, Germany
| | - Jiri Polivka
- Department of Histology and Embryology, Faculty of Medicine in Plzen, Charles University, Prague, Czech Republic
- Biomedical Centre, Faculty of Medicine in Plzen, Charles University, Prague, Czech Republic
| | - Pavel Potuznik
- Department of Neurology, University Hospital Plzen and Faculty of Medicine in Plzen, Charles University, Prague, Czech Republic
| | - Martin Pesta
- Department of Biology, Faculty of Medicine in Plzen, Charles University, Prague, Czech Republic
| | - Ivana Stetkarova
- Department of Neurology, University Hospital Kralovske Vinohrady, Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Alena Mazurakova
- Department of Anatomy, Jessenius Faculty of Medicine, Comenius University in Bratislava, Martin, Slovakia
| | - Lenka Lackova
- Department of Histology and Embryology, Jessenius Faculty of Medicine, Comenius University in Bratislava, Martin, Slovakia
| | - Peter Kubatka
- Department of Histology and Embryology, Jessenius Faculty of Medicine, Comenius University in Bratislava, Martin, Slovakia
| | - Martina Kropp
- Experimental Ophthalmology, University of Geneva, 1205 Geneva, Switzerland
- Ophthalmology Department, University Hospitals of Geneva, 1205 Geneva, Switzerland
| | - Gabriele Thumann
- Experimental Ophthalmology, University of Geneva, 1205 Geneva, Switzerland
- Ophthalmology Department, University Hospitals of Geneva, 1205 Geneva, Switzerland
| | - Carl Erb
- Private Institute of Applied Ophthalmology, Berlin, Germany
| | - Holger Fröhlich
- Artificial Intelligence & Data Science Group, Fraunhofer SCAI, Sankt Augustin, Germany
- Bonn-Aachen International Center for IT (B-It), University of Bonn, 53115 Bonn, Germany
| | - Wei Wang
- Edith Cowan University, Perth, Australia
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China
| | - Babak Baban
- The Dental College of Georgia, Departments of Neurology and Surgery, The Medical College of Georgia, Augusta University, Augusta, USA
| | - Marko Kapalla
- Negentropic Systems, Ružomberok, Slovakia
- PPPM Centre, s.r.o., Ruzomberok, Slovakia
| | - Niva Shapira
- Department of Nutrition, School of Health Sciences, Ashkelon Academic College, Ashkelon, Israel
| | - Kneginja Richter
- CuraMed Tagesklinik Nürnberg GmbH, Nuremberg, Germany
- Technische Hochschule Nürnberg GSO, Nuremberg, Germany
- University Clinic for Psychiatry and Psychotherapy, Paracelsus Medical University, Nuremberg, Germany
| | - Alexander Karabatsiakis
- Department of Psychology, Clinical Psychology II, University of Innsbruck, Innsbruck, Austria
| | - Ivica Smokovski
- University Clinic of Endocrinology, Diabetes and Metabolic Disorders Skopje, University Goce Delcev, Faculty of Medical Sciences, Stip, North Macedonia
| | - Leonard Christopher Schmeel
- Department of Radiation Oncology, University Hospital Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn, 53127 Bonn, Germany
| | - Eleni Gkika
- Department of Radiation Oncology, University Hospital Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn, 53127 Bonn, Germany
| | | | - Paolo Parini
- Cardio Metabolic Unit, Department of Medicine Huddinge, and Department of Laboratory Medicine, Karolinska Institutet, and Medicine Unit of Endocrinology, Theme Inflammation and Ageing, Karolinska University Hospital, Stockholm, Sweden
| | - Jiri Polivka
- Department of Neurology, University Hospital Plzen and Faculty of Medicine in Plzen, Charles University, Prague, Czech Republic
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3
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Gao J, Tao L, Jiang Z. Alleviate oxidative stress in diabetic retinopathy: antioxidant therapeutic strategies. Redox Rep 2023; 28:2272386. [PMID: 38041593 PMCID: PMC11001280 DOI: 10.1080/13510002.2023.2272386] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2023] Open
Abstract
OBJECTIVES This review outlines the function of oxidative stress in DR and discusses therapeutic strategies to treat DR with antioxidants. METHODS Published papers on oxidative stress in DR and therapeutic strategies to treat DR with antioxidants were collected and reviewed via database searching on PubMed. RESULTS The abnormal development of DR is a complicated process. The pathogenesis of DR has been reported to involve oxidative stress, despite the fact that the mechanisms underlying this are still not fully understood. Excessive reactive oxygen species (ROS) accumulation can damage retina, eventually leading to DR. Increasing evidence have demonstrated that antioxidant therapy can alleviate the degeneration of retinal capillaries in DR. CONCLUSION Oxidative stress can play an important contributor in the pathogenesis of DR. Furthermore, animal experiments have shown that antioxidants are a beneficial therapy for treating DR, but more clinical trial data is needed.
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Affiliation(s)
- Jie Gao
- Department of Ophthalmology, The Second Affiliated Hospital of Anhui Medical University, Hefei, People’s Republic of China
| | - Liming Tao
- Department of Ophthalmology, The Second Affiliated Hospital of Anhui Medical University, Hefei, People’s Republic of China
| | - Zhengxuan Jiang
- Department of Ophthalmology, The Second Affiliated Hospital of Anhui Medical University, Hefei, People’s Republic of China
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Fang J, Wang H, Niu T, Shi X, Xing X, Qu Y, Liu Y, Liu X, Xiao Y, Dou T, Shen Y, Liu K. Integration of Vitreous Lipidomics and Metabolomics for Comprehensive Understanding of the Pathogenesis of Proliferative Diabetic Retinopathy. J Proteome Res 2023. [PMID: 37329324 DOI: 10.1021/acs.jproteome.3c00007] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
As a vision-threatening complication of diabetes mellitus (DM), proliferative diabetic retinopathy (PDR) is associated with sustained metabolic disorders. Herein, we collected the vitreous cavity fluid of 49 patients with PDR and 23 control subjects without DM for metabolomics and lipidomics analyses. Multivariate statistical methods were performed to explore relationships between samples. For each group of metabolites, gene set variation analysis scores were generated, and we constructed a lipid network by using weighted gene co-expression network analysis. The association between lipid co-expression modules and metabolite set scores was investigated using the two-way orthogonal partial least squares (O2PLS) model. A total of 390 lipids and 314 metabolites were identified. Multivariate statistical analysis revealed significant vitreous metabolic and lipid differences between PDR and controls. Pathway analysis showed that 8 metabolic processes might be associated with the development of PDR, and 14 lipid species were found to be altered in PDR patients. Combining metabolomics and lipidomics, we identified fatty acid desaturase 2 (FADS2) as an important potential contributor to the pathogenesis of PDR. Collectively, this study integrates vitreous metabolomics and lipidomics to comprehensively unravel metabolic dysregulation and identifies genetic variants associated with altered lipid species in the mechanistic pathways for PDR.
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Affiliation(s)
- Junwei Fang
- Department of Ophthalmology, Shanghai General Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, China
- National Clinical Research Center for Eye Diseases, Shanghai 200080, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases, Shanghai 200080, China
| | - Hanying Wang
- Department of Ophthalmology, Shanghai General Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, China
- National Clinical Research Center for Eye Diseases, Shanghai 200080, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases, Shanghai 200080, China
| | - Tian Niu
- Department of Ophthalmology, Shanghai General Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, China
- National Clinical Research Center for Eye Diseases, Shanghai 200080, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases, Shanghai 200080, China
| | - Xin Shi
- Department of Ophthalmology, Shanghai General Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, China
- National Clinical Research Center for Eye Diseases, Shanghai 200080, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases, Shanghai 200080, China
| | - Xindan Xing
- Department of Ophthalmology, Shanghai General Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, China
- National Clinical Research Center for Eye Diseases, Shanghai 200080, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases, Shanghai 200080, China
| | - Yuan Qu
- Department of Ophthalmology, Shanghai General Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, China
- National Clinical Research Center for Eye Diseases, Shanghai 200080, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases, Shanghai 200080, China
| | - Yujuan Liu
- Department of Ophthalmology, Shanghai General Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, China
- National Clinical Research Center for Eye Diseases, Shanghai 200080, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases, Shanghai 200080, China
| | - Xinyi Liu
- Department of Ophthalmology, Shanghai General Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, China
- National Clinical Research Center for Eye Diseases, Shanghai 200080, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases, Shanghai 200080, China
| | - Yu Xiao
- Department of Ophthalmology, Shanghai General Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, China
- National Clinical Research Center for Eye Diseases, Shanghai 200080, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases, Shanghai 200080, China
| | - Tianyu Dou
- Department of Ophthalmology, Shanghai General Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, China
- National Clinical Research Center for Eye Diseases, Shanghai 200080, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases, Shanghai 200080, China
| | - Yinchen Shen
- Department of Ophthalmology, Shanghai General Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, China
- National Clinical Research Center for Eye Diseases, Shanghai 200080, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases, Shanghai 200080, China
| | - Kun Liu
- Department of Ophthalmology, Shanghai General Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, China
- National Clinical Research Center for Eye Diseases, Shanghai 200080, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases, Shanghai 200080, China
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Kropp M, De Clerck E, Vo TTKS, Thumann G, Costigliola V, Golubnitschaja O. Short communication: unique metabolic signature of proliferative retinopathy in the tear fluid of diabetic patients with comorbidities - preliminary data for PPPM validation. EPMA J 2023; 14:43-51. [PMID: 36845280 PMCID: PMC9944425 DOI: 10.1007/s13167-023-00318-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Accepted: 02/08/2023] [Indexed: 02/24/2023]
Abstract
Type 2 diabetes (T2DM) defined as the adult-onset type that is primarily not insulin-dependent, comprises over 95% of all diabetes mellitus (DM) cases. According to global records, 537 million adults aged 20-79 years are affected by DM that means at least 1 out of 15 persons. This number is projected to grow by 51% by the year 2045. One of the most common complications of T2DM is diabetic retinopathy (DR) with an overall prevalence over 30%. The total number of the DR-related visual impairments is on the rise, due to the growing T2DM population. Proliferative diabetic retinopathy (PDR) is the progressing DR and leading cause of preventable blindness in working-age adults. Moreover, PDR with characteristic systemic attributes including mitochondrial impairment, increased cell death and chronic inflammation, is an independent predictor of the cascading DM-complications such as ischemic stroke. Therefore, early DR is a reliable predictor appearing upstream of this "domino effect". Global screening, leading to timely identification of DM-related complications, is insufficiently implemented by currently applied reactive medicine. A personalised predictive approach and cost-effective targeted prevention shortly - predictive, preventive and personalised medicine (PPPM / 3PM) could make a good use of the accumulated knowledge, preventing blindness and other severe DM complications. In order to reach this goal, reliable stage- and disease-specific biomarker panels are needed characterised by an easy way of the sample collection, high sensitivity and specificity of analyses. In the current study, we tested the hypothesis that non-invasively collected tear fluid is a robust source for the analysis of ocular and systemic (DM-related complications) biomarker patterns suitable for differential diagnosis of stable DR versus PDR. Here, we report the first results of the comprehensive ongoing study, in which we correlate individualised patient profiles (healthy controls versus patients with stable D as well as patients with PDR with and without co-morbidities) with their metabolic profiles in the tear fluid. Comparative mass spectrometric analysis performed has identified following metabolic clusters which are differentially expressed in the groups of comparison: acylcarnitines, amino acid & related compounds, bile acids, ceramides, lysophosphatidyl-choline, nucleobases & related compounds, phosphatidyl-cholines, triglycerides, cholesterol esters, and fatty acids. Our preliminary data strongly support potential clinical utility of metabolic patterns in the tear fluid indicating a unique metabolic signature characteristic for the DR stages and PDR progression. This pilot study creates a platform for validating the tear fluid biomarker patterns to stratify T2DM-patients predisposed to the PDR. Moreover, since PDR is an independent predictor of severe T2DM-related complications such as ischemic stroke, our international project aims to create an analytical prototype for the "diagnostic tree" (yes/no) applicable to healthrisk assessment in diabetes care.
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Affiliation(s)
- Martina Kropp
- Experimental Ophthalmology, University of Geneva, 1205 Geneva, Switzerland
- Ophthalmology Department, University Hospitals of Geneva, 1205 Geneva, Switzerland
| | - Eline De Clerck
- Experimental Ophthalmology, University of Geneva, 1205 Geneva, Switzerland
- Ophthalmology Department, University Hospitals of Geneva, 1205 Geneva, Switzerland
| | - Trong-Tin Kevin Steve Vo
- Experimental Ophthalmology, University of Geneva, 1205 Geneva, Switzerland
- Ophthalmology Department, University Hospitals of Geneva, 1205 Geneva, Switzerland
| | - Gabriele Thumann
- Experimental Ophthalmology, University of Geneva, 1205 Geneva, Switzerland
- Ophthalmology Department, University Hospitals of Geneva, 1205 Geneva, Switzerland
| | | | - Olga Golubnitschaja
- Predictive, Preventive and Personalised (3P) Medicine, Department of Radiation Oncology, University Hospital Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn, 53127 Bonn, Germany
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Huang X, Weng Z, Zhang S, Li X, Zhou S, Liang J. LC-MS/MS-based metabolomic profiling identifies candidate biomarkers in follicular fluid of infertile women with chronic pelvic inflammatory disease. INTERNATIONAL JOURNAL OF CLINICAL AND EXPERIMENTAL PATHOLOGY 2023; 16:20-31. [PMID: 36910890 PMCID: PMC9993017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 02/13/2023] [Indexed: 03/14/2023]
Abstract
OBJECTIVES How chronic pelvic inflammatory disease (CPID), the most common cause of infertility, affects metabolic profiles of follicular fluid (FF) remains unknown. This study aimed to identify candidate biomarkers in FF of infertile women with CPID. METHOD FF samples were collected from infertile women with CPID (n = 8) and healthy controls (n = 8) at the time of oocyte retrieval. Untargeted metabolomic profiling of FF samples was conducted using the liquid chromatography-tandem mass spectrometry (LC-MS/MS). RESULTS A total of 240 differential metabolites (104 named biochemicals and 136 unnamed biochemicals) were screened out and identified. Among them, pregnane-3,3-diol, pc(p-18:1(11z)/18:3(6z,9z,12z)), and 1-octadecanoyl-2-(4z,7z,10z,13z,16z,19z-docosahexaenoyl)-sn-glycero-3-phosphoethanolamine were markedly down-regulated, while 17,21-dihydroxypregnenolone was significantly up-regulated in infertile women with CPID. Furthermore, KEGG biological pathway analysis revealed that these metabolites were especially enriched in steroid hormone biosynthesis, glyoxylate and dicarboxylate metabolism, glucagon signaling pathway, and the tricarboxylic acid (TCA) cycle. CONCLUSION FF of infertile women with CPID showed unique metabolic changes that may be involved in the pathogenesis of infertility and serve as new therapeutic targets or diagnostic biomarkers.
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Affiliation(s)
- Xuekun Huang
- Department of Reproductive Medicine, The First Affiliated Hospital of Guangzhou University of Chinese Medicine Guangzhou 510095, Guangdong, P. R. China
| | - Zhiwei Weng
- Department of Reproductive Medicine, The First Affiliated Hospital of Guangzhou University of Chinese Medicine Guangzhou 510095, Guangdong, P. R. China
| | - Shuting Zhang
- Department of Reproductive Medicine, The First Affiliated Hospital of Guangzhou University of Chinese Medicine Guangzhou 510095, Guangdong, P. R. China
| | - Xuerong Li
- Department of Reproductive Medicine, The First Affiliated Hospital of Guangzhou University of Chinese Medicine Guangzhou 510095, Guangdong, P. R. China
| | - Shaohu Zhou
- Department of Reproductive Medicine, The First Affiliated Hospital of Guangzhou University of Chinese Medicine Guangzhou 510095, Guangdong, P. R. China
| | - Jingyao Liang
- Department of Dermatology, Guangzhou Institute of Dermatology Guangzhou 510095, Guangdong, P. R. China
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7
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Zheng R, Su R, Xing F, Li Q, Liu B, Wang D, Du Y, Huang K, Yan F, Wang J, Chen H, Feng S. Metabolic-Dysregulation-Based iEESI-MS Reveals Potential Biomarkers Associated with Early-Stage and Progressive Colorectal Cancer. Anal Chem 2022; 94:11821-11830. [PMID: 35976989 DOI: 10.1021/acs.analchem.2c02072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Abstract
The application of rapid and accurate diagnostic methods can improve colorectal cancer (CRC) survival rates dramatically. Here, we used a non-targeted metabolic analysis strategy based on internal extractive electrospray ionization mass spectrometry (iEESI-MS) to detect metabolite ions associated with the progression of CRC from 172 tissues (45 stage I/II CRC, 41 stage III/IV CRC, and 86 well-matched normal tissues). A support vector machine (SVM) model based on 10 differential metabolite ions for differentiating early-stage CRC from normal tissues was built with a good prediction accuracy of 92.6%. The biomarker panel consisting of lysophosphatidylcholine (LPC) (18:0) has good diagnostic potential in differentiating early-stage CRC from advanced-stage CRC. We showed that the down-regulation of LPC (18:0) in tumor tissues is associated with CRC progression and related to the regulation of the epidermal growth factor receptor. Pathway analysis showed that metabolic pathways in CRC are related to glycerophospholipid metabolism and purine metabolism. In conclusion, we built an SVM model with good performance to distinguish between early-stage CRC and normal groups based on iEESI-MS and found that LPC (18:0) is associated with the progression of CRC.
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Affiliation(s)
- Ran Zheng
- State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, College of Chemistry, Jilin University, Changchun 130012, China
| | - Rui Su
- State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, College of Chemistry, Jilin University, Changchun 130012, China
| | - Fan Xing
- State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, College of Chemistry, Jilin University, Changchun 130012, China
| | - Qing Li
- State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, College of Chemistry, Jilin University, Changchun 130012, China
| | - Botong Liu
- State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, College of Chemistry, Jilin University, Changchun 130012, China
| | - Daguang Wang
- Department of Gastric Colorectal and Anal Surgery, First Hospital of Jilin University, Changchun 130021, China
| | - Yechao Du
- Department of Gastric Colorectal and Anal Surgery, First Hospital of Jilin University, Changchun 130021, China
| | - Keke Huang
- State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, College of Chemistry, Jilin University, Changchun 130012, China
| | - Fei Yan
- State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, College of Chemistry, Jilin University, Changchun 130012, China
| | - Jianfeng Wang
- Department of Radiotherapy, China-Japan Union Hospital of Jilin University, Changchun 130021, China
| | - Huanwen Chen
- School of Pharmacy, Jiangxi University of Chinese Medicine, Nanchang 330004, China
| | - Shouhua Feng
- State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, College of Chemistry, Jilin University, Changchun 130012, China
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