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Chen Q, Hu K, Shi J, Li H, Li W. Hesperidin inhibits methylation and autophagy in LPS and high glucose-induced human villous trophoblasts. Biochem Biophys Res Commun 2023; 671:278-285. [PMID: 37311265 DOI: 10.1016/j.bbrc.2023.05.117] [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: 05/06/2023] [Revised: 05/23/2023] [Accepted: 05/28/2023] [Indexed: 06/15/2023]
Abstract
INTRODUCTION Gestational diabetes mellitus (GDM) is the first occurrence of diabetes due to abnormal maternal sugar metabolism after pregnancy, which may lead to adverse pregnancy outcomes. Hesperidin is known to decrease in the cord blood of GDM with obesity, but its role is unknown. This study aims to explore the potential function of hesperidin in GDM with obesity to develop new therapeutic ideas. METHODS Peripheral blood and placental tissues from GDM and GDM with obesity patients were collected to isolate human villous trophoblasts and detection. Bioinformatics was used to analyze the differential methylation genes between GDM and GDM with obesity. Immunofluorescence was applied for the detection of CK7 expression. Cells vitality was detected by CCK8 and transwell. Molecular docking was applied to predict the binding of hesperidin and ATG7 protein. Inflammation and m6A levels was analyzed by ELISA. ATG7, LC3, TLR4 and P62 proteins was analyzed by Western blot. RESULTS The methylation of ATG7 gene was up-regulated in GDM with obesity compared with GDM. The m6A and autophagy proteins levels in GDM with obesity were higher than that in GDM. LPS with 2.5-25 mM glucose induced the increase of autophagy proteins, inflammation and m6A levels in human villous trophoblasts. Hesperidin formed hydrogen bonds and hydrophobic interactions with ATG7 proteins. Hesperidin (0.25 μM) inhibited the autophagy proteins and m6A level in LPS and 25 mM glucose-induced human villous trophoblasts. DISCUSSION GDM with obesity followed the increase of autophagy proteins and m6A levels. Hesperidin inhibited the autophagy proteins and m6A level in LPS and glucose-induced human villous trophoblasts.
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Affiliation(s)
- Qiuling Chen
- Department of Obstetrics, Changsha Hospital for Maternal & Child Health Care Affiliated to Hunan Normal University, Changsha, 41700, Hunan, China
| | - Ke Hu
- Department of Obstetrics, Changsha Hospital for Maternal & Child Health Care Affiliated to Hunan Normal University, Changsha, 41700, Hunan, China
| | - Jun Shi
- Department of Obstetrics, Changsha Hospital for Maternal & Child Health Care Affiliated to Hunan Normal University, Changsha, 41700, Hunan, China
| | - Hua Li
- Department of Obstetrics, Changsha Hospital for Maternal & Child Health Care Affiliated to Hunan Normal University, Changsha, 41700, Hunan, China
| | - Wenxia Li
- Department of Obstetrics, Changsha Hospital for Maternal & Child Health Care Affiliated to Hunan Normal University, Changsha, 41700, Hunan, China.
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Wang G, Xu R, Zhang B, Hong X, Bartell TR, Pearson C, Liang L, Wang X. Impact of intrauterine exposure to maternal diabetes on preterm birth: fetal DNA methylation alteration is an important mediator. Clin Epigenetics 2023; 15:59. [PMID: 37029435 PMCID: PMC10082529 DOI: 10.1186/s13148-023-01473-1] [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: 01/08/2023] [Accepted: 03/21/2023] [Indexed: 04/09/2023] Open
Abstract
BACKGROUND In utero exposure to diabetes has been shown to contribute to preterm birth, though the underlying biological mechanisms are yet to be fully elucidated. Fetal epigenetic variations established in utero may be a possible pathway. This study aimed to investigate whether in utero exposure to diabetes was associated with a change in newborn DNA methylation, and whether the identified CpG sites mediate the association between diabetes and preterm birth in a racially diverse birth cohort population. METHODS This study included 954 mother-newborn pairs. Methylation levels in the cord blood were determined using the Illumina Infinium MethylationEPIC BeadChip 850 K array platform. In utero exposure to diabetes was defined by the presence of maternal pregestational or gestational diabetes. Preterm birth was defined as gestational age at birth less than 37 weeks. Linear regression analysis was employed to identify differentially methylated CpG sites. Differentially methylated regions were identified using the DMRcate Package. RESULTS 126 (13%) newborns were born to mothers with diabetes in pregnancy and 173 (18%) newborns were born preterm, while 41 newborns were born both preterm and to mothers with diabetes in pregnancy. Genomic-wide CpG analysis found that eighteen CpG sites in cord blood were differentially methylated by maternal diabetes status at an FDR threshold of 5%. These significant CpG sites were mapped to 12 known genes, one of which was annotated to gene Major Histocompatibility Complex, Class II, DM Beta (HLA-DMB). Consistently, one of the two identified significant methylated regions overlapped with HLA-DMB. The identified differentially methylated CpG sites mediated the association between diabetes in pregnancy and preterm birth by 61%. CONCLUSIONS In this US birth cohort, we found that maternal diabetes was associated with altered fetal DNA methylation patterns, which substantially explained the link between diabetes and preterm birth.
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Affiliation(s)
- Guoying Wang
- Center on Early Life Origins of Disease, Department of Population, Family and Reproductive Health, Johns Hopkins University Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD, 21205-2179, USA.
| | - Richard Xu
- Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Boyang Zhang
- Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Xiumei Hong
- Center on Early Life Origins of Disease, Department of Population, Family and Reproductive Health, Johns Hopkins University Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD, 21205-2179, USA
| | - Tami R Bartell
- Patrick M. Magoon Institute for Healthy Communities, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, USA
| | - Colleen Pearson
- Department of Pediatrics, Boston University Chobanian & Avedisian School of Medicine and Boston Medical Center, Boston, MA, USA
| | - Liming Liang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Xiaobin Wang
- Center on Early Life Origins of Disease, Department of Population, Family and Reproductive Health, Johns Hopkins University Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD, 21205-2179, USA
- Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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Ormazabal V, Nair S, Carrión F, Mcintyre HD, Salomon C. The link between gestational diabetes and cardiovascular diseases: potential role of extracellular vesicles. Cardiovasc Diabetol 2022; 21:174. [PMID: 36057662 PMCID: PMC9441052 DOI: 10.1186/s12933-022-01597-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 08/05/2022] [Indexed: 11/25/2022] Open
Abstract
Extracellular vesicles are critical mediators of cell communication. They encapsulate a variety of molecular cargo such as proteins, lipids, and nucleic acids including miRNAs, lncRNAs, circular RNAs, and mRNAs, and through transfer of these molecular signals can alter the metabolic phenotype in recipient cells. Emerging studies show the important role of extracellular vesicle signaling in the development and progression of cardiovascular diseases and associated risk factors such as type 2 diabetes and obesity. Gestational diabetes mellitus (GDM) is hyperglycemia that develops during pregnancy and increases the future risk of developing obesity, impaired glucose metabolism, and cardiovascular disease in both the mother and infant. Available evidence shows that changes in maternal metabolism and exposure to the hyperglycemic intrauterine environment can reprogram the fetal genome, leaving metabolic imprints that define life-long health and disease susceptibility. Understanding the factors that contribute to the increased susceptibility to metabolic disorders of children born to GDM mothers is critical for implementation of preventive strategies in GDM. In this review, we discuss the current literature on the fetal programming of cardiovascular diseases in GDM and the impact of extracellular vesicle (EV) signaling in epigenetic programming in cardiovascular disease, to determine the potential link between EV signaling in GDM and the development of cardiovascular disease in infants.
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Affiliation(s)
- Valeska Ormazabal
- Exosome Biology Laboratory, Centre for Clinical Diagnostics, UQ Centre for Clinical Research, Royal Brisbane and Women's Hospital, Faculty of Medicine + Biomedical Sciences, The University of Queensland, Building 71/918, Herston, QLD, 4029, Australia.,Faculty of Biological Sciences, Pharmacology Department, University of Concepcion, Concepción, Chile
| | - Soumyalekshmi Nair
- Exosome Biology Laboratory, Centre for Clinical Diagnostics, UQ Centre for Clinical Research, Royal Brisbane and Women's Hospital, Faculty of Medicine + Biomedical Sciences, The University of Queensland, Building 71/918, Herston, QLD, 4029, Australia
| | - Flavio Carrión
- Departamento de Investigación, Postgrado y Educación Continua (DIPEC), Facultad de Ciencias de la Salud, Universidad del Alba, Santiago, Chile
| | - H David Mcintyre
- Mater Research, Faculty of Medicine, University of Queensland, Mater Health, South Brisbane, Australia
| | - Carlos Salomon
- Exosome Biology Laboratory, Centre for Clinical Diagnostics, UQ Centre for Clinical Research, Royal Brisbane and Women's Hospital, Faculty of Medicine + Biomedical Sciences, The University of Queensland, Building 71/918, Herston, QLD, 4029, Australia. .,Departamento de Investigación, Postgrado y Educación Continua (DIPEC), Facultad de Ciencias de la Salud, Universidad del Alba, Santiago, Chile.
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Rout M, Kour B, Vuree S, Lulu SS, Medicherla KM, Suravajhala P. Diabetes mellitus susceptibility with varied diseased phenotypes and its comparison with phenome interactome networks. World J Clin Cases 2022; 10:5957-5964. [PMID: 35949812 PMCID: PMC9254192 DOI: 10.12998/wjcc.v10.i18.5957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Revised: 02/02/2022] [Accepted: 04/22/2022] [Indexed: 02/06/2023] Open
Abstract
An emerging area of interest in understanding disease phenotypes is systems genomics. Complex diseases such as diabetes have played an important role towards understanding the susceptible genes and mutations. A wide number of methods have been employed and strategies such as polygenic risk score and allele frequencies have been useful, but understanding the candidate genes harboring those mutations is an unmet goal. In this perspective, using systems genomic approaches, we highlight the application of phenome-interactome networks in diabetes and provide deep insights. LINC01128, which we previously described as candidate for diabetes, is shown as an example to discuss the approach.
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Affiliation(s)
- Madhusmita Rout
- Department of Pediatrics, University of Oklahoma Health Sciences Centre, Oklahoma City, OK 73104, United States
- Department of Biotechnology and Bioinformatics, Birla Institute of Scientific Research, Jaipur 302001, Rajasthan, India
| | - Bhumandeep Kour
- Department of Biotechnology, Lovely Professional University, Phagwara 144001, Punjab, India
| | - Sugunakar Vuree
- Department of Biotechnology, Lovely Professional University, Phagwara 144001, Punjab, India
| | - Sajitha S Lulu
- Department of Biotechnology, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India
| | - Krishna Mohan Medicherla
- Department of Biotechnology and Bioinformatics, Birla Institute of Scientific Research, Jaipur 302001, Rajasthan, India
| | - Prashanth Suravajhala
- Amrita School of Biotechnology, Amrita Vishwa Vidyapeetham, Vallikavu PO, Amritapuri, Clappana, Kollam 690525, Kerala, India
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Shen C, Li H, Li M, Niu Y, Liu J, Zhu L, Gui H, Han W, Wang H, Zhang W, Wang X, Luo X, Sun Y, Yan J, Guan F. DLRAPom: a hybrid pipeline of Optimized XGBoost-guided integrative multiomics analysis for identifying targetable disease-related lncRNA-miRNA-mRNA regulatory axes. Brief Bioinform 2022; 23:6537347. [PMID: 35224615 PMCID: PMC8921741 DOI: 10.1093/bib/bbac046] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 01/13/2022] [Accepted: 01/29/2022] [Indexed: 12/12/2022] Open
Abstract
The lack of a reliable and easy-to-operate screening pipeline for disease-related noncoding RNA regulatory axis is a problem that needs to be solved urgently. To address this, we designed a hybrid pipeline, disease-related lncRNA-miRNA-mRNA regulatory axis prediction from multiomics (DLRAPom), to identify risk biomarkers and disease-related lncRNA-miRNA-mRNA regulatory axes by adding a novel machine learning model on the basis of conventional analysis and combining experimental validation. The pipeline consists of four parts, including selecting hub biomarkers by conventional bioinformatics analysis, discovering the most essential protein-coding biomarkers by a novel machine learning model, extracting the key lncRNA-miRNA-mRNA axis and validating experimentally. Our study is the first one to propose a new pipeline predicting the interactions between lncRNA and miRNA and mRNA by combining WGCNA and XGBoost. Compared with the methods reported previously, we developed an Optimized XGBoost model to reduce the degree of overfitting in multiomics data, thereby improving the generalization ability of the overall model for the integrated analysis of multiomics data. With applications to gestational diabetes mellitus (GDM), we predicted nine risk protein-coding biomarkers and some potential lncRNA-miRNA-mRNA regulatory axes, which all correlated with GDM. In those regulatory axes, the MALAT1/hsa-miR-144-3p/IRS1 axis was predicted to be the key axis and was identified as being associated with GDM for the first time. In short, as a flexible pipeline, DLRAPom can contribute to molecular pathogenesis research of diseases, effectively predicting potential disease-related noncoding RNA regulatory networks and providing promising candidates for functional research on disease pathogenesis.
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Affiliation(s)
- Chen Shen
- Shanghai Key Laboratory of Forensic Medicine, Academy of Forensic Science; Key Laboratory of National Ministry of Health for Forensic Sciences, School of Medicine & Forensics, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Huiyu Li
- Key Laboratory of National Ministry of Health for Forensic Sciences, School of Medicine & Forensics, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Miao Li
- Department of Ultrasound, the Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Yu Niu
- Department of Endocrinology and Metabolism, Ninth Hospital of Xi'an City, Xi'an, China
| | - Jing Liu
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Li Zhu
- Key Laboratory of National Ministry of Health for Forensic Sciences, School of Medicine & Forensics, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Hongsheng Gui
- Center for Behavior Health and Psychiatry Research, Henry Ford Health System, Detroit, MI, USA
| | - Wei Han
- Key Laboratory of National Ministry of Health for Forensic Sciences, School of Medicine & Forensics, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Huiying Wang
- Key Laboratory of National Ministry of Health for Forensic Sciences, School of Medicine & Forensics, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Wenpei Zhang
- Key Laboratory of National Ministry of Health for Forensic Sciences, School of Medicine & Forensics, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Xiaochen Wang
- Key Laboratory of National Ministry of Health for Forensic Sciences, School of Medicine & Forensics, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Xiao Luo
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Yu Sun
- Department of Endocrinology and Metabolism, Qilu Hospital of Shandong University, Ji'nan, China
| | - Jiangwei Yan
- Department of Genetics, School of Medicine & Forensics, Shanxi Medical University, Taiyuan, China
| | - Fanglin Guan
- Shanghai Key Laboratory of Forensic Medicine, Academy of Forensic Science; Key Laboratory of National Ministry of Health for Forensic Sciences, School of Medicine & Forensics, Health Science Center, Xi'an Jiaotong University, Xi'an, China
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Huang X, Zha B, Zhang M, Li Y, Wu Y, Zhang R, Sheng L, Xu J, Yu Z, Gao C, Chen Z, Ding H, Ma L, Zhang Y, Zang S, Zhang TN, Liu J. Decreased Monocyte Count Is Associated With Gestational Diabetes Mellitus Development, Macrosomia, and Inflammation. J Clin Endocrinol Metab 2022; 107:192-204. [PMID: 34478541 DOI: 10.1210/clinem/dgab657] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Indexed: 12/24/2022]
Abstract
CONTEXT The immune system plays a central role in the pathophysiology of gestational diabetes mellitus (GDM). Monocytes, the main innate immune cells, are especially important in the maintenance of a normal pregnancy. OBJECTIVE Here, we investigated the potential effect of monocytes in GDM. METHODS Monocyte count was monitored throughout pregnancy in 214 women with GDM and 926 women without in a case-control and cohort study. Circulating levels of inflammatory cytokines, placenta-derived macrophages, and their products were measured. RESULTS Throughout pregnancy, monocyte count was significantly decreased in women with GDM, and was closely associated with glucose level, insulin resistance, and newborn weight. First-trimester monocyte count outperformed that of the second and third trimester as a risk factor and diagnostic predictor of GDM and macrosomia both in the case-control and cohort study. In addition, our cohort study showed that as first-trimester monocyte count decreased, GDM and macrosomia incidence, glucose level, and newborn weight increased in a stepwise manner. Risk of GDM started to decrease rapidly when first-trimester monocyte count exceeded 0.48 × 109/L. Notably, CD206 and interleukin 10 (IL-10) were significantly lower, whereas CD80, CD86, tumor necrosis factor α (TNF-α), and interleukin 6 (IL-6) were higher both in GDM placental tissue and peripheral blood. First-trimester monocyte count was positively related to IL-10 and CD206, but negatively related to CD80, CD86, TNF-α, and IL-6. CONCLUSION Decreased monocyte count throughout pregnancy was closely associated with the development of GDM, macrosomia, and the chronic inflammatory state of GDM. First-trimester monocyte count has great potential as an early diagnostic marker of GDM.
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Affiliation(s)
- Xinmei Huang
- Department of Endocrinology, Shanghai Fifth People's Hospital, Fudan University, Shanghai 200240, China
| | - Bingbing Zha
- Department of Endocrinology, Shanghai Fifth People's Hospital, Fudan University, Shanghai 200240, China
| | - Manna Zhang
- Department of Endocrinology & Metabolism, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai 200072, China
| | - Yue Li
- Department of Endocrinology, Shanghai Fifth People's Hospital, Fudan University, Shanghai 200240, China
| | - Yueyue Wu
- Department of Endocrinology, Shanghai Fifth People's Hospital, Fudan University, Shanghai 200240, China
| | - Rui Zhang
- Department of Endocrinology, Shanghai Fifth People's Hospital, Fudan University, Shanghai 200240, China
| | - Li Sheng
- Department of Endocrinology, Shanghai Fifth People's Hospital, Fudan University, Shanghai 200240, China
| | - Jiong Xu
- Department of Endocrinology, Shanghai Fifth People's Hospital, Fudan University, Shanghai 200240, China
| | - Zhiyan Yu
- Department of Endocrinology, Shanghai Fifth People's Hospital, Fudan University, Shanghai 200240, China
| | - Cuijun Gao
- Department of Obstetrics, Wujing Hospital, Shanghai 200241, China
| | - Zaoping Chen
- Department of Endocrinology, Shanghai Fifth People's Hospital, Fudan University, Shanghai 200240, China
| | - Heyuan Ding
- Department of Endocrinology, Shanghai Fifth People's Hospital, Fudan University, Shanghai 200240, China
| | - Ling Ma
- Department of Obstetrics, Wujing Hospital, Shanghai 200241, China
| | - Yanquan Zhang
- Department of Obstetrics, Wujing Hospital, Shanghai 200241, China
| | - Shufei Zang
- Department of Endocrinology, Shanghai Fifth People's Hospital, Fudan University, Shanghai 200240, China
| | - Tie-Ning Zhang
- Department of Pediatrics, Shengjing Hospital of China Medical University, Shenyang 110004, China
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang 110004, China
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang 110004, China
| | - Jun Liu
- Department of Endocrinology, Shanghai Fifth People's Hospital, Fudan University, Shanghai 200240, China
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Epigenetic Changes in Gestational Diabetes Mellitus. Int J Mol Sci 2021; 22:ijms22147649. [PMID: 34299269 PMCID: PMC8303885 DOI: 10.3390/ijms22147649] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 06/30/2021] [Accepted: 07/14/2021] [Indexed: 12/30/2022] Open
Abstract
Gestational diabetes mellitus (GDM) is defined as carbohydrate intolerance that appears or is for the first time diagnosed during pregnancy. It can lead to many complications in the mother and in the offspring, so diagnostics and management of GDM are important to avoid adverse pregnancy outcomes. Epigenetic studies revealed the different methylation status of genes in pregnancies with GDM compared to pregnancies without GDM. A growing body of evidence shows that the GDM can affect not only the course of the pregnancy, but also the development of the offspring, thus contributing to long-term effects and adverse health outcomes of the progeny. Epigenetic changes occur through histone modification, DNA methylation, and disrupted function of non-coding ribonucleic acid (ncRNA) including microRNAs (miRNAs). In this review, we focus on the recent knowledge about epigenetic changes in GDM. The analysis of this topic may help us to understand pathophysiological mechanisms in GDM and find a solution to prevent their consequences.
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Avilés-Santa ML, Monroig-Rivera A, Soto-Soto A, Lindberg NM. Current State of Diabetes Mellitus Prevalence, Awareness, Treatment, and Control in Latin America: Challenges and Innovative Solutions to Improve Health Outcomes Across the Continent. Curr Diab Rep 2020; 20:62. [PMID: 33037442 PMCID: PMC7546937 DOI: 10.1007/s11892-020-01341-9] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/10/2020] [Indexed: 02/06/2023]
Abstract
PURPOSE OF REVIEW Latin America is the scenario of great inequalities where about 32 million human beings live with diabetes. Through this review, we aimed at describing the current state of the prevalence, awareness, treatment, and control of diabetes mellitus and completion of selected guidelines of care across Latin America and identify opportunities to advance research that promotes better health outcomes. RECENT FINDINGS The prevalence of diabetes mellitus has been consistently increasing across the region, with some variation: higher prevalence in Mexico, Haiti, and Puerto Rico and lower in Colombia, Ecuador, Dominican Republic, Peru, and Uruguay. Prevalence assessment methods vary, and potentially underestimating the real number of persons with diabetes. Diabetes unawareness varies widely, with up to 50% of persons with diabetes who do not know they may have the disease. Glycemic, blood pressure, and LDL-C control and completion of guidelines to prevent microvascular complications are not consistently assessed across studies, and the achievement of control goals is suboptimal. On the other hand, multiple interventions, point-of-care/rapid assessment tools, and alternative models of health care delivery have been proposed and tested throughout Latin America. The prevalence of diabetes mellitus continues to rise across Latin America, and the number of those with the disease may be underestimated. However, some local governments are embedding more comprehensive diabetes assessments in their local national surveys. Clinicians and public health advocates in the region have proposed and initiated various multi-level interventions to address this enormous challenge in the region.
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Affiliation(s)
- M Larissa Avilés-Santa
- Division of Extramural Scientific Programs, Clinical and Health Services Research at the National Institute on Minority Health and Health Disparities, Bethesda, MD, USA.
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