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Jiang L, Yang Z, Liu G, Xia Z, Yang G, Gong H, Wang J, Wang L. A feature optimization study based on a diabetes risk questionnaire. Front Public Health 2024; 12:1328353. [PMID: 38463161 PMCID: PMC10920272 DOI: 10.3389/fpubh.2024.1328353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Accepted: 02/05/2024] [Indexed: 03/12/2024] Open
Abstract
Introduction The prevalence of diabetes, a common chronic disease, has shown a gradual increase, posing substantial burdens on both society and individuals. In order to enhance the effectiveness of diabetes risk prediction questionnaires, optimize the selection of characteristic variables, and raise awareness of diabetes risk among residents, this study utilizes survey data obtained from the risk factor monitoring system of the Centers for Disease Control and Prevention in the United States. Methods Following univariate analysis and meticulous screening, a more refined dataset was constructed. This dataset underwent preprocessing steps, including data distribution standardization, the application of the Synthetic Minority Oversampling Technique (SMOTE) in combination with the Round function for equilibration, and data standardization. Subsequently, machine learning (ML) techniques were employed, utilizing enumerated feature variables to evaluate the strength of the correlation among diabetes risk factors. Results The research findings effectively delineated the ranking of characteristic variables that significantly influence the risk of diabetes. Obesity emerges as the most impactful factor, overshadowing other risk factors. Additionally, psychological factors, advanced age, high cholesterol, high blood pressure, alcohol abuse, coronary heart disease or myocardial infarction, mobility difficulties, and low family income exhibit correlations with diabetes risk to varying degrees. Discussion The experimental data in this study illustrate that, while maintaining comparable accuracy, optimization of questionnaire variables and the number of questions can significantly enhance efficiency for subsequent follow-up and precise diabetes prevention. Moreover, the research methods employed in this study offer valuable insights into studying the risk correlation of other diseases, while the research results contribute to heightened societal awareness of populations at elevated risk of diabetes.
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Affiliation(s)
- Liangjun Jiang
- College of Information and Communication Engineering, State Key Lab of Marine Resource Utilization in South China Sea, Hainan University, Haikou, China
| | - Zerui Yang
- School of Electronics and Information, Yangtze University, Jingzhou, China
| | - Gang Liu
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Zhenhua Xia
- School of Electronics and Information, Yangtze University, Jingzhou, China
| | - Guangyao Yang
- School of Electronics and Information, Yangtze University, Jingzhou, China
| | - Haimei Gong
- College of Information and Communication Engineering, State Key Lab of Marine Resource Utilization in South China Sea, Hainan University, Haikou, China
| | - Jing Wang
- E-link Wisdom Co., Ltd., Shenzhen, China
| | - Lei Wang
- College of Information and Communication Engineering, State Key Lab of Marine Resource Utilization in South China Sea, Hainan University, Haikou, China
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Deng JY, Wu XQ, He WJ, Liao X, Tang M, Nie XQ. Targeting DNA methylation and demethylation in diabetic foot ulcers. J Adv Res 2023; 54:119-131. [PMID: 36706989 DOI: 10.1016/j.jare.2023.01.009] [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: 12/05/2022] [Revised: 01/07/2023] [Accepted: 01/10/2023] [Indexed: 01/26/2023] Open
Abstract
BACKGROUND Poor wound healing is a significant complication of diabetes, which is commonly caused by neuropathy, trauma, deformities, plantar hypertension and peripheral arterial disease. Diabetic foot ulcers (DFU) are difficult to heal, which makes patients susceptible to infections and can ultimately conduce to limb amputation or even death in severe cases. An increasing number of studies have found that epigenetic alterations are strongly associated with poor wound healing in diabetes. AIM OF REVIEW This work provides significant insights into the development of therapeutics for improving chronic diabetic wound healing, particularly by targeting and regulating DNA methylation and demethylation in DFU. Key scientific concepts of review: DNA methylation and demethylation play an important part in diabetic wound healing, via regulating corresponding signaling pathways in different breeds of cells, including macrophages, vascular endothelial cells and keratinocytes. In this review, we describe the four main phases of wound healing and their abnormality in diabetic patients. Furthermore, we provided an in-depth summary and discussion on how DNA methylation and demethylation regulate diabetic wound healing in different types of cells; and gave a brief summary on recent advances in applying cellular reprogramming techniques for improving diabetic wound healing.
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Affiliation(s)
- Jun-Yu Deng
- Key Lab of the Basic Pharmacology of the Ministry of Education, Zunyi Medical University, Zunyi 563006, China; Joint International Research Laboratory of Ethnomedicine of Ministry of Education, Zunyi Medical University, Zunyi 563006, China; College of Pharmacy, Zunyi Medical University, Zunyi 563006, China
| | - Xing-Qian Wu
- College of Pharmacy, Zunyi Medical University, Zunyi 563006, China
| | - Wen-Jie He
- College of Pharmacy, Zunyi Medical University, Zunyi 563006, China
| | - Xin Liao
- Affiliated Hospital of Zunyi Medical University, Zunyi 563006, China
| | - Ming Tang
- Queensland University of Technology (QUT), School of Biomedical Sciences, Centre for Genomics and Personalized Health at the Translational Research Institute (TRI), Brisbane, QLD 4102, Australia.
| | - Xu-Qiang Nie
- Key Lab of the Basic Pharmacology of the Ministry of Education, Zunyi Medical University, Zunyi 563006, China; Joint International Research Laboratory of Ethnomedicine of Ministry of Education, Zunyi Medical University, Zunyi 563006, China; College of Pharmacy, Zunyi Medical University, Zunyi 563006, China; Queensland University of Technology (QUT), School of Biomedical Sciences, Centre for Genomics and Personalized Health at the Translational Research Institute (TRI), Brisbane, QLD 4102, Australia.
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Barbagallo C, Stella M, Di Mauro S, Scamporrino A, Filippello A, Scionti F, Di Martino MT, Purrello M, Ragusa M, Purrello F, Piro S. An Uncharacterised lncRNA Coded by the ASAP1 Locus Is Downregulated in Serum of Type 2 Diabetes Mellitus Patients. Int J Mol Sci 2023; 24:13485. [PMID: 37686290 PMCID: PMC10488254 DOI: 10.3390/ijms241713485] [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: 07/11/2023] [Revised: 08/23/2023] [Accepted: 08/27/2023] [Indexed: 09/10/2023] Open
Abstract
Diabetes mellitus (DM) is a complex and multifactorial disease characterised by high blood glucose. Type 2 Diabetes (T2D), the most frequent clinical condition accounting for about 90% of all DM cases worldwide, is a chronic disease with slow development usually affecting middle-aged or elderly individuals. T2D represents a significant problem of public health today because its incidence is constantly growing among both children and adults. It is also estimated that underdiagnosis prevalence would strongly further increase the real incidence of the disease, with about half of T2D patients being undiagnosed. Therefore, it is important to increase diagnosis accuracy. The current interest in RNA molecules (both protein- and non-protein-coding) as potential biomarkers for diagnosis, prognosis, and treatment lies in the ease and low cost of isolation and quantification with basic molecular biology techniques. In the present study, we analysed the transcriptome in serum samples collected from T2D patients and unaffected individuals to identify potential RNA-based biomarkers. Microarray-based profiling and subsequent validation using Real-Time PCR identified an uncharacterised long non-coding RNA (lncRNA) transcribed from the ASAP1 locus as a potential diagnostic biomarker. ROC curve analysis showed that a molecular signature including the lncRNA and the clinicopathological parameters of T2D patients as well as unaffected individuals showed a better diagnostic performance compared with the glycated haemoglobin test (HbA1c). This result suggests that the application of this biomarker in clinical practice would help to improve the diagnosis, and therefore the clinical management, of T2D patients. The proposed biomarker would be useful in the context of predictive, preventive, and personalised medicine (3PM/PPPM).
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Affiliation(s)
- Cristina Barbagallo
- Section of Biology and Genetics, Department of Biomedical and Biotechnological Sciences, University of Catania, 95123 Catania, Italy; (C.B.); (M.S.); (M.P.)
| | - Michele Stella
- Section of Biology and Genetics, Department of Biomedical and Biotechnological Sciences, University of Catania, 95123 Catania, Italy; (C.B.); (M.S.); (M.P.)
| | - Stefania Di Mauro
- Department of Clinical and Experimental Medicine, Internal Medicine, Garibaldi-Nesima Hospital, University of Catania, 95122 Catania, Italy; (S.D.M.); (A.S.); (A.F.); (F.P.); (S.P.)
| | - Alessandra Scamporrino
- Department of Clinical and Experimental Medicine, Internal Medicine, Garibaldi-Nesima Hospital, University of Catania, 95122 Catania, Italy; (S.D.M.); (A.S.); (A.F.); (F.P.); (S.P.)
| | - Agnese Filippello
- Department of Clinical and Experimental Medicine, Internal Medicine, Garibaldi-Nesima Hospital, University of Catania, 95122 Catania, Italy; (S.D.M.); (A.S.); (A.F.); (F.P.); (S.P.)
| | - Francesca Scionti
- Department of Experimental and Clinical Medicine, Magna Graecia University, 88100 Catanzaro, Italy; (F.S.); (M.T.D.M.)
| | - Maria Teresa Di Martino
- Department of Experimental and Clinical Medicine, Magna Graecia University, 88100 Catanzaro, Italy; (F.S.); (M.T.D.M.)
| | - Michele Purrello
- Section of Biology and Genetics, Department of Biomedical and Biotechnological Sciences, University of Catania, 95123 Catania, Italy; (C.B.); (M.S.); (M.P.)
| | - Marco Ragusa
- Section of Biology and Genetics, Department of Biomedical and Biotechnological Sciences, University of Catania, 95123 Catania, Italy; (C.B.); (M.S.); (M.P.)
| | - Francesco Purrello
- Department of Clinical and Experimental Medicine, Internal Medicine, Garibaldi-Nesima Hospital, University of Catania, 95122 Catania, Italy; (S.D.M.); (A.S.); (A.F.); (F.P.); (S.P.)
| | - Salvatore Piro
- Department of Clinical and Experimental Medicine, Internal Medicine, Garibaldi-Nesima Hospital, University of Catania, 95122 Catania, Italy; (S.D.M.); (A.S.); (A.F.); (F.P.); (S.P.)
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Yang T, Wang J, Wu L, Guo F, Huang F, Song Y, Jing N, Pan M, Ding X, Cao Z, Liu S, Qin G, Zhao Y. Development and validation of a nomogram to estimate future risk of type 2 diabetes mellitus in adults with metabolic syndrome: prospective cohort study. Endocrine 2023; 80:336-345. [PMID: 36940011 DOI: 10.1007/s12020-023-03329-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 02/10/2023] [Indexed: 03/21/2023]
Abstract
OBJECTIVES To develop and validate the 4-year risk of type 2 diabetes mellitus among adults with metabolic syndrome. DESIGN Retrospective cohort study of a large multicenter cohort with broad validation. SETTINGS The derivation cohort was from 32 sites in China and the geographic validation cohort was from Henan population-based cohort study. RESULTS 568 (17.63) and 53 (18.67%) participants diagnosed diabetes during 4-year follow-up in the developing and validation cohort, separately. Age, gender, body mass index, diastolic blood pressure, fasting plasma glucose and alanine aminotransferase were included in the final model. The area under curve for the training and external validation cohort was 0.824 (95% CI, 0.759-0.889) and 0.732 (95% CI, 0.594-0.871), respectively. Both the internal and external validation have good calibration plot. A nomogram was constructed to predict the probability of diabetes during 4-year follow-up, and on online calculator is also available for a more convenient usage ( https://lucky0708.shinyapps.io/dynnomapp/ ). CONCLUSION We developed a simple diagnostic model to predict 4-year risk of type 2 diabetes mellitus among adults with metabolic syndrome, which is also available as web-based tools ( https://lucky0708.shinyapps.io/dynnomapp/ ).
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Affiliation(s)
- Tongyue Yang
- Division of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Jiao Wang
- Division of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Lina Wu
- Division of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Feng Guo
- Division of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Fengjuan Huang
- Division of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Yi Song
- Division of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Na Jing
- Division of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Mengxing Pan
- Division of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Xiaoxu Ding
- Division of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Zhe Cao
- Division of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Shiyu Liu
- Division of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Guijun Qin
- Division of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Yanyan Zhao
- Division of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, 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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