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      Association between ELMO1 gene polymorphisms and diabetic kidney disease: A systematic review and meta-analysis

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          Abstract

          Background

          Previous research has suggested that the ELMO1 gene may play a role in the development of diabetic kidney disease. Diabetic kidney disease (DKD) is a serious complication of diabetes and the leading cause of chronic kidney disease and end-stage renal disease (ESRD).

          Objective and rationale

          This study aim was to systematically review and explore the association between ELMO1 gene polymorphisms and diabetic kidney disease. A comprehensive systematic review provides a clear conclusion and high-level evidence for the association between ELMO1 gene and DKD for future application in personalized medicine.

          Methods

          A comprehensive search of electronic databases, per PRISMA instructions, was conducted in Scopus, EMBASE, Web of Science, and PubMed databases from 1980 to January 2023. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using appropriate models. Subgroup and sensitivity analyses were performed to explore potential sources of heterogeneity and assess the robustness of the findings.

          Results

          A total of 5794 diabetes patients with DKD, 4886 diabetes patients without DKD, and 2023 healthy controls were included in the 17 studies that made up this systematic review. In the investigation of DM (Diabetes Mellitus) with DKD vs. DM without DKD, the susceptibility for DKD for the EMLO1 rs741301 polymorphism indicated a significant difference under the dominant, homozygote, and recessive genetic models. The susceptibility for DKD for the EMLO1 rs1345365, rs10255208, and rs7782979 polymorphisms demonstrated a significant difference under the allele genetic models in the analysis of DM with DKD vs. DM without DKD groups. There was a considerable increase in DKD risk in the Middle East when the population was stratified by the region.

          Conclusion

          The findings of the meta-analysis show that there are a significant connection between the EMLO1 rs741301 polymorphism and DKD susceptibility in overall analyses; as well as rs1345365, rs10255208, and rs7782979 polymorphisms; especially in the Middle East region.

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          Most cited references41

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          Measuring inconsistency in meta-analyses.

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            Bias in meta-analysis detected by a simple, graphical test

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              Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement.

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: Project administrationRole: Validation
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: ResourcesRole: SupervisionRole: Validation
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: ResourcesRole: SupervisionRole: Validation
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: SupervisionRole: Validation
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: ResourcesRole: SupervisionRole: Validation
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                26 January 2024
                2024
                : 19
                : 1
                : e0295607
                Affiliations
                [1 ] Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
                [2 ] School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
                [3 ] Metabolic Disorders Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
                [4 ] Evidence Based Medicine Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
                [5 ] Cell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
                [6 ] Diabetes Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
                [7 ] Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
                Neyshabur University of Medical Sciences, ISLAMIC REPUBLIC OF IRAN
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0003-3399-2360
                https://orcid.org/0000-0003-0359-3043
                Article
                PONE-D-23-23941
                10.1371/journal.pone.0295607
                10817128
                38277369
                fcee3c8a-cef8-4e17-8206-dd5d4f96d866
                © 2024 Azarboo et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 1 August 2023
                : 25 November 2023
                Page count
                Figures: 7, Tables: 2, Pages: 18
                Funding
                The author(s) received no specific funding for this work.
                Categories
                Research Article
                Medicine and Health Sciences
                Endocrinology
                Endocrine Disorders
                Diabetes Mellitus
                Medicine and Health Sciences
                Medical Conditions
                Metabolic Disorders
                Diabetes Mellitus
                Biology and Life Sciences
                Genetics
                Heredity
                Homozygosity
                Biology and Life Sciences
                Genetics
                Genetic Loci
                Alleles
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Metaanalysis
                Physical Sciences
                Mathematics
                Statistics
                Statistical Methods
                Metaanalysis
                Biology and Life Sciences
                Anatomy
                Renal System
                Kidneys
                Medicine and Health Sciences
                Anatomy
                Renal System
                Kidneys
                Medicine and Health Sciences
                Epidemiology
                Medical Risk Factors
                Biology and Life Sciences
                Genetics
                Human Genetics
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Genome-Wide Association Studies
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Analysis
                Genome-Wide Association Studies
                Biology and Life Sciences
                Genetics
                Human Genetics
                Genome-Wide Association Studies
                Custom metadata
                All relevant data are within the paper and its Supporting information files.

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