Insight into the Predictive Power of Surrogate Diagnostic Indices for Identifying Individuals with Metabolic Syndrome.

BACKGROUND: This study aimed to assess the diagnostic capability of insulin surrogate measurements in identifying individuals with metabolic syndrome (MetS) and propose applicable indices derived from fasting values, particularly in large study populations. METHODS: Data were collected from the datasets of the Surveillance of Risk Factors of NCDs in Iran Study (STEPS). MetS was defined based on the National Cholesterol Education Program (NCEP) criteria. Various insulin surrogate indices, including Homeostasis Model Assessment (HOMA), Quantitative Insulin Sensitivity Check Index (QUICKI), Fasting glucose to insulin ratio (FGIR), Reynaud, Reciprocal insulin, McAuley, Metabolic Score for Insulin Resistance (METS-IR), Triglyceride-glucose index (TyG), TG/ HDL-C, TG/ BMI, and TG/ WC ratio were assessed. Receiver Operating Characteristic (ROC) curves were used to assess pathologic conditions and determine the optimal cut-off through the highest score of the Youden index. Also, Area Under the Curve (AUC) values were established for each index totally and according to sex, age, and BMI differences. RESULTS: The study population consisted of 373 individuals (49.9% women; 75.1% middle age, 39.1% obese, and 27.3% overweight), of whom 117 (31.4%) had MetS. The METS-IR (AUC: 0.856; 95% CI: 0.817-0.895), TG/ HDL-C (AUC: 0.820; 95% CI: 0.775-0.886), TyG (AUC: 0.808; 95% CI: 0.759-0.857), and McAuley (AUC: 0.804; 95% CI: 0.757-0.852) indices provided the greatest AUC respectively for detection of MetS. The values of AUC for all the indices were higher in men than women. This trend was consistent after data stratification based on BMI categories, middle age, and senile individuals. CONCLUSION: The present study indicated that indices of insulin, including METS-IR, TG/HDLC, TyG, and McAuley, have an equal or better capacity in determining the risk of MetS than HOMA-IR, are capable of identifying individuals with MetS and may provide a simple approach for identifying populations at risk of insulin resistance.

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

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.

Metabolomics signature of cardiovascular disease in patients with diabetes, a narrative review.

Objectives: The exact underlying mechanism of developing diabetes-related cardiovascular disease (CVD) among patients with type 2 diabetes (T2D) is not clear. Metabolomics can provide a platform enabling the prediction, diagnosis, and understanding of the risk of CVD in patients with diabetes mellitus. The aim of this review is to summarize the available evidence on the relationship between metabolomics and cardiovascular diseases in patients with diabetes. Methods: The literature was searched to find out studies that have investigated the relationship between the alteration of specific metabolites and cardiovascular diseases in patients with diabetes. Results: Evidence proposed that changes in the metabolism of certain amino acids, lipids, and carbohydrates, independent of traditional CVD risk factors, are associated with increased CVD risk. Conclusions: Metabolomics can provide a platform to enable the prediction, diagnosis, and understanding of the risk of CVD in patients with diabetes mellitus. The association of the alteration in specific metabolites with CVD may be considered in the investigations for the development of new therapeutic targets for the prevention of CVD in patients with diabetes mellitus.

Metabolomics profile and 10-year atherosclerotic cardiovascular disease (ASCVD) risk score.

Background: The intermediate metabolites associated with the development of atherosclerotic cardiovascular disease (ASCVD) remain largely unknown. Thus, we conducted a large panel of metabolomics profiling to identify the new candidate metabolites that were associated with 10-year ASCVD risk. Methods: Thirty acylcarnitines and twenty amino acids were measured in the fasting plasma of 1,102 randomly selected individuals using a targeted FIA-MS/MS approach. The 10-year ASCVD risk score was calculated based on 2013 ACC/AHA guidelines. Accordingly, the subjects were stratified into four groups: low-risk (n = 620), borderline-risk (n = 110), intermediate-risk (n = 225), and high-risk (n = 147). 10 factors comprising collinear metabolites were extracted from principal component analysis. Results: C4DC, C8:1, C16OH, citrulline, histidine, alanine, threonine, glycine, glutamine, tryptophan, phenylalanine, glutamic acid, arginine, and aspartic acid were significantly associated with the 10-year ASCVD risk score (p-values ≤ 0.044). The high-risk group had higher odds of factor 1 (12 long-chain acylcarnitines, OR = 1.103), factor 2 (5 medium-chain acylcarnitines, OR = 1.063), factor 3 (methionine, leucine, valine, tryptophan, tyrosine, phenylalanine, OR = 1.074), factor 5 (6 short-chain acylcarnitines, OR = 1.205), factor 6 (5 short-chain acylcarnitines, OR = 1.229), factor 7 (alanine, proline, OR = 1.343), factor 8 (C18:2OH, glutamic acid, aspartic acid, OR = 1.188), and factor 10 (ornithine, citrulline, OR = 1.570) compared to the low-risk ones; the odds of factor 9 (glycine, serine, threonine, OR = 0.741), however, were lower in the high-risk group. "D-glutamine and D-glutamate metabolism", "phenylalanine, tyrosine, and tryptophan biosynthesis", and "valine, leucine, and isoleucine biosynthesis" were metabolic pathways having the highest association with borderline/intermediate/high ASCVD events, respectively. Conclusions: Abundant metabolites were found to be associated with ASCVD events in this study. Utilization of this metabolic panel could be a promising strategy for early detection and prevention of ASCVD events.

The association between acylcarnitine and amino acids profile and metabolic syndrome and its components in Iranian adults: Data from STEPs 2016.

Background: Evidence, albeit with conflicting results, has suggested that cardiometabolic risk factors, including obesity, type 2 diabetes (T2D), dyslipidemia, and hypertension, are highly associated with changes in metabolic signature, especially plasma amino acids and acylcarnitines levels. Here, we aimed to evaluate the association of circulating levels of amino acids and acylcarnitines with metabolic syndrome (MetS) and its components in Iranian adults. Methods: This cross-sectional study was performed on 1192 participants from the large-scale cross-sectional study of Surveillance of Risk Factors of non-communicable diseases (NCDs) in Iran (STEP 2016). The circulating levels of amino acids and acylcarnitines were measured using liquid chromatography-tandem mass spectrometry (LC-MS/MS) in individuals with MetS (n=529) and without MetS (n=663). Results: The higher plasma levels of branched-chain amino acids (Val, Leu), aromatic amino acids (Phe, Tyr), Pro, Ala, Glu, and the ratio of Asp to Asn were significantly associated with MetS, whereas lower circulating levels of Gly, Ser, His, Asn, and citrulline were significantly associated with MetS. As for plasma levels of free carnitine and acylcarnitines, higher levels of short-chain acylcarnitines (C2, C3, C4DC), free carnitine (C0), and long-chain acylcarnitines (C16, C18OH) were significantly associated with MetS. Principal component analysis (PCA) showed that factor 3 (Tyr, Leu, Val, Met, Trp, Phe, Thr) [OR:1.165, 95% CI: 1.121-1.210, P<0.001], factor 7 (C0, C3, C4) [OR:1.257, 95% CI: 1.150-1.374, P<0.001], factor 8 (Gly, Ser) [OR:0.718, 95% CI: 0.651-0.793, P< 0.001], factor 9 (Ala, Pro, C4DC) [OR:1.883, 95% CI: 1.669-2.124, P<0.001], factor 10 (Glu, Asp, C18:2OH) [OR:1.132, 95% CI: 1.032-1.242, P= 0.009], factor 11 (citrulline, ornithine) [OR:0.862, 95% CI: 0.778-0.955, P= 0.004] and 13 (C18OH, C18:1 OH) [OR: 1.242, 95% CI: 1.042-1.480, P= 0.016] were independently correlated with metabolic syndrome. Conclusion: Change in amino acid, and acylcarnitines profiles were seen in patients with MetS. Moreover, the alteration in the circulating levels of amino acids and acylcarnitines is along with an increase in MetS component number. It also seems that amino acid and acylcarnitines profiles can provide valuable information on evaluating and monitoring MetS risk. However, further studies are needed to establish this concept.

Association of plasma acylcarnitines and amino acids with hypertension: A nationwide metabolomics study.

BACKGROUND: Identification of metabolomics profile in subjects with different blood pressure, including normal blood pressure, elevated blood pressure, stage 1 hypertension, and stage 2 hypertension, would be a promising strategy to understand the pathogenesis of hypertension. Thus, we conducted this study to investigate the association of plasma acylcarnitines and amino acids with hypertension in a large Iranian population. METHODS: 1200 randomly selected subjects from the national survey on the Surveillance of Risk Factors of Non-Communicable Diseases in Iran (STEPs 2016) were divided into four groups based on the ACC/AHA hypertension criteria: normal blood pressure (n = 293), elevated blood pressure (n = 135), stage 1 hypertension (n = 325), and stage 2 hypertension (n = 447). Plasma concentrations of 30 acylcarnitines and 20 amino acids were measured using a targeted approach with flow-injection tandem mass spectrometry. Univariate and multivariate logistic regression analysis was applied to estimate the association between metabolites level and the risk of hypertension. Age, sex, BMI, total cholesterol, triglyceride, HDL cholesterol, fasting plasma glucose, use of oral glucose-lowering drugs, statins, and antihypertensive drugs were adjusted in regression analysis. RESULTS: Of 50 metabolites, 34 were associated with an increased likelihood of stage 2 hypertension and 5 with a decreased likelihood of stage 2 hypertension. After full adjustment for potential confounders, 5 metabolites were still significant risk markers for stage 2 hypertension including C0 (OR = 0.75; 95%CI: 0.63, 0.90), C12 (OR = 1.18; 95%CI: 1.00, 1.40), C14:1 (OR = 1.20; 95%CI: 1.01, 1.42), C14:2 (OR = 1.19; 95%CI: 1.01, 1.41), and glycine (OR = 0.81; 95%CI: 0.68, 0.96). An index that included glycine and serine also showed significant predictive value for stage 2 hypertension after full adjustment (OR = 0.86; 95%CI: 0.75, 0.98). CONCLUSIONS: Five metabolites were identified as potentially valuable predictors of stage 2 hypertension.

Evaluating the association between amino acid and acylcarnitine profiles and different levels of coronary artery disease risk in postmenopausal women using targeted metabolomics technique.

OBJECTIVES: Postmenopausal women are at increased risk of developing coronary artery disease (CAD). Metabolomic approaches aim at discovering more helpful biomarkers of CAD to reduce the disease burden in the future. Here, we intend to find potential blood biomarkers, amino acids, and acylcarnitines in postmenopausal women with different severity of CAD by using high-throughput methods. METHOD: This cross-sectional study was performed on postmenopausal women ( n = 183) who underwent coronary CT scans. Coronary artery calcium scoring (CACS) was assessed to detect plaque burden and degree of coronary artery obstruction. The participants were divided into three groups based on the score as follows (i) "low CACS" ( n = 96); a score of 0 to 10, (ii) "medium CACS" ( n = 35); a score between 11 and 100 and (iii) "high CACS" ( n = 52); a score greater than 100. Metabolites, including amino acids and acylcarnitines, were quantified using a targeted mass spectrometry method in serum samples. The association between metabolites and disease status was evaluated using univariate and multivariate regression analyses with adjustment for confounding factors. Factor analysis was used to deal with multiple comparisons. RESULTS: Metabolites, including proline, glutamic acid, and phenylalanine, were significantly lower in the high CACS group than the low CACS one. Also, a lower level of lysine and phenylalanine in high CACS compared with medium one was observed. Concerning acylcarnitines, it was found that C4 and C8:1 significantly were higher in women with high CACS. The logistic regression analysis revealed that the circulating levels of these metabolites (except C4) were associated with the presence of coronary artery calcification independently of age, body mass index, and time of menopause. Also, the amino acids were associated independently of medication and diabetes. CONCLUSIONS: The present study indicated that circulating levels of amino acids and acylcarnitines profile in postmenopausal women are partly associated with the severity of CAD in these participants.

Circulating amino acids and acylcarnitines correlated with different CAC score ranges in diabetic postmenopausal women using LC-MS/MS based metabolomics approach.

BACKGROUND: Diabetes mellitus (DM) and its cardiovascular disease (CVD) complication are among the most frequent causes of death worldwide. However, the metabolites linking up diabetes and CVD are less understood. In this study, we aimed to evaluate serum acylcarnitines and amino acids in postmenopausal women suffering from diabetes with different severity of CVD and compared them with healthy controls. METHODS: Through a cross-sectional study, samples were collected from postmenopausal women without diabetes and CVD as controls (n = 20), patients with diabetes and without CVD (n = 16), diabetes with low risk of CVD (n = 11), and diabetes with a high risk of CVD (n = 21) referred for CT angiography for any reason. Metabolites were detected by a targeted approach using LC-MS/MS and metabolic -alterations were assessed by applying multivariate statistical analysis. The diagnostic ability of discovered metabolites based on multivariate statistical analysis was evaluated by ROC curve analysis. RESULTS: The study included women aged from 50-80 years with 5-30 years of menopause. The relative concentration of C14:1, C14:2, C16:1, C18:1, and C18:2OH acylcarnitines decreased and C18 acylcarnitine and serine increased in diabetic patients compared to control. Besides, C16:1 and C18:2OH acylcarnitines increased in high-risk CVD diabetic patients compared to no CVD risk diabetic patients. CONCLUSION: Dysregulation of serum acylcarnitines and amino acids profile correlated with different CAC score ranges in diabetic postmenopausal women. (Ethic approval No: IR.TUMS.EMRI.REC.1399.062).

Bibliometric overview of Ramadan fasting studies during 2010-2021.

BACKGROUND AND AIMS: To quantify the bibliometric parameters of Ramadan fasting literature from 2010 to 2021. MATERIALS AND METHODS: Scopus was searched for all articles related to Ramadan fasting or Islamic fasting from the beginning of 2010 to the end of 2021. Only original articles and reviews were included and their bibliometric and scientometric parameters were determined using Excel, Graph Pad Prism, VOSviewer, and Sci2 tool software. RESULTS: Finally 1276 articles, including 1109 original articles and 167 reviews, were included. These articles had 14263 citations and an H-index of 48. Based on the number of publications, top institute, top journal, top country, and top authors were University of Sfax (n = 48 articles), Diabetes Research and Clinical Practice (n = 69), the United States (n = 144), and Chtourou H & Hassanein M (n = 38), respectively. Also, Diabetes Research and Clinical Practice had a strong bibliographic coupling with other journals. The recent bursting words were adrenal insufficiency and COVID-19. The most co-occurred topics were the effect of Ramadan fasting on diabetic patients, pregnant women, and glycemic state and body composition of diabetic patients. CONCLUSION: This study provided a comprehensive bibliometric overview of Ramadan fasting literature from 2010 to 2021. The temporal change in the number of publications and other analyses on the literature of 2019, 2020 and 2021 showed that substantial increasing publications with new emerging subjects had become of interest to many researchers during the last three years.

Knowledge gaps in diabetes research: an evidence mapping of the literature.

Background: Mapping the available evidence can be used to inform current diabetes research, identify relevant gaps, and prioritize future research. In this regard, we mapped diabetes research performed in Iran. Method: We searched the Scopus and PubMed databases from 01/01/2015 till 01/01/2020 using keywords such as diabetes and Iran. The included articles were classified according to their document types, level of evidence, and subject areas. Results: The majority of the included articles (53%) were related to diabetes types, followed by complications (28%). Most of the documents were original articles (82%), and reviews were 18% of the publications. Systematic reviews constitute only 6% of the total documents. Observational studies were the most common types of study designs (26%), followed by clinical trials (20%). Moreover, topics on control and management of diabetes were the most prevalent subject areas (58%), and fewer studies were on preventive strategies (6%). In diabetes management studies, less attention has been paid to evaluate psychological (10%), educational (9%), and physical activity-related (7%) interventions. There was a shortage of secondary studies related to physical activity, psychology, diagnostic, and screening-related studies. Conclusion: To fill diabetes research gaps, more investment in cost-effectiveness interventions, such as preventive strategies and behavioral self-management programs, need. Moreover, we need to pay more attention on applied sciences and real world evidence to bridge translational gaps from bench to bedside. In this regard, further data synthesis can be helpful in evaluating the effectiveness of the available studies and avoiding unnecessary investigations.

Targeted metabolomics analysis of amino acids and acylcarnitines as risk markers for diabetes by LC-MS/MS technique.

Diabetes is a common chronic disease affecting millions of people worldwide. It underlies various complications and imposes many costs on individuals and society. Discovering early diagnostic biomarkers takes excellent insight into preventive plans and the best use of interventions. Therefore, in the present study, we aimed to evaluate the association between the level of amino acids and acylcarnitines and diabetes to develop diabetes predictive models. Using the targeted LC-MS/MS technique, we analyzed fasting plasma samples of 206 cases and 206 controls that were matched by age, sex, and BMI. The association between metabolites and diabetes was evaluated using univariate and multivariate regression analysis with adjustment for systolic and diastolic blood pressure and lipid profile. To deal with multiple comparisons, factor analysis was used. Participants' average age and BMI were 61.6 years, 28.9 kg/m2, and 55% were female. After adjustment, Factor 3 (tyrosine, valine, leucine, methionine, tryptophan, phenylalanine), 5 (C3DC, C5, C5OH, C5:1), 6 (C14OH, C16OH, C18OH, C18:1OH), 8 (C2, C4OH, C8:1), 10 (alanine, proline) and 11 (glutamic acid, C18:2OH) were positively associated with diabetes. Inline, factor 9 (C4DC, serine, glycine, threonine) and 12 (citrulline, ornithine) showed a reverse trend. Some amino acids and acylcarnitines were found as potential risk markers for diabetes incidents that reflected the disturbances in the several metabolic pathways among the diabetic population and could be targeted to prevent, diagnose, and treat diabetes.

The trend in application of omics in type 2 diabetes researches; A bibliometric study.

AIMS: Due to the importance of omics approaches in diabetes diagnosis, we were assumed to study the scientific activities on omics and type 2 diabetes worldwide. METHOD: Bibliometric approach was utilized to evaluate the documents on proteomics, lipidomics, and metabolomics in patients with type 2 diabetes in the Scopus database from the beginning to 2020. The articles were screened by two reviewers and the number of publications and citations on omics and type 2 diabetes, top-ranked journals, top-cited articles, country co-contributions, co-authorships, author keywords, and terms were analyzed. RESULTS: The scientific publications in this field consisted of 551 original articles, of which the USA shares the most percent, followed by China and Germany. The frequent keywords showed that the following hotspots were of interest: "Metabolomics, proteomics, and lipidomics as biomarkers for diabetes", "Omics and diabetic nephropathy", "The application of omics in obesity, insulin resistance, and type 2 diabetes". CONCLUSION: This study showed an increasing trend in applying omics in type 2 diabetes researches and determined the leading producers in this field. Besides, the research hotspots and the main subjects of documents were provided for future research and policy decision-making.

Mass spectrometry with derivatization method for concurrent measurement of amino acids and acylcarnitines in plasma of diabetic type 2 patients with diabetic nephropathy.

BACKGROUND: Amino acids (AAs) and acylcarnitines play a key role in metabolic disease and can be used as biomarkers of various diseases such as malignancies, type 2 diabetes (T2D), insulin resistance, and cardiovascular diseases, therefore, designing an accurate and simple laboratory method that simultaneously measure both groups of substances, could improve the process of analytes quantification. In this research, a flow injection tandem mass spectrometry (FI-MS/MS) method for simultaneous measurement of AAs and acylcarnitines in addition to results of validation is explained. METHODS: Samples were mixed with internal standards and after derivatization (with butanolic-HCL), AAs, and acylcarnitines were quantified by tandem mass spectrometry (SCIEX API 3200). Analytical performance studies were designed based on the Clinical and Laboratory Standards Institute (CLSI) guidelines including precision, accuracy, linearity, and limit of detection-quantification (LOD-LOQ) experiments. Samples from patients with T2D in different stages of kidney disease were also analyzed to ensure the clinical usage of the method. RESULTS: Performance evaluation of the method demonstrated adequate results. The mean of estimated inter-assay precision (reported as a coefficient variation) for AAs and acylcarnitines were less than 8.7% and 12.3%, the estimated mean bias was below 8.8% and 10.2% respectively. LOD of analytes ranged between 0.6-10 µmol per liter (µmol/L) for AAs and 0.02-1 µmol/L for acylcarnitines. LOQ analytes showed a range of 2-25 µmol/L and 0.05-5 µmol/L for AAs and carnitine/acylcarnitines respectively. In diabetic patients sample analysis, a significant increase in acylcarnitines (C2, C4, C5DC, C6, C8, C10, C14) and citrulline with a significant decrease in valine were seen in patients with severely increased albuminuria. CONCLUSION: FI-MS/MS method with pre-injection derivatization with butanolic-HCL can be used for concurrent measurement of AAs and carnitine/acylcarnitines in a short time and it satisfies the analytical performance requirements. This method is applied for AAs and carnitine/acylcarnitines measurement in patient with T2DM and results show some of the acylcarnitines and AAs can be involved in diabetic nephropathy development. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40200-021-00786-3.

Association of circulating omega 3, 6 and 9 fatty acids with gestational diabetes mellitus: a systematic review.

BACKGROUND: Gestational diabetes mellitus (GDM) is associated with increased risks of disease for mother and child during pregnancy and after that. Early diagnosis of GDM would promote both maternal and fetal health. Metabolomics can simplify and develop our understanding of the etiology, manifestation, or pathophysiology of the disease. This systematic review investigates the association of circulating omega 3, 6, and 9 fatty acids with GDM. METHODS: We conducted a systematic search of PubMed, Scopus, Web of Science, and EMBASE databases up to May 8, 2020, using the key term combinations of all types of omega fatty acids with gestational diabetes mellitus. Additional articles were identified through searching the reference lists of included studies. RESULTS: This systematic review included 15 articles. Five were cohort studies, four included nested case-control studies and four were case-control studies. The results of this study demonstrate an increasing trend in the amount of oleic acid and palmitoleic acid in the second trimester and an increase in decosahexanoic acid in the third trimester of GDM mothers. The changes in other fatty acids of interest are either not significant or if significant, their results are inconsistent with the other existing articles. CONCLUSIONS: Omega fatty acids, as potential biomarkers, are considered to be associated with GDM risk and thus provide useful information regarding the prevention and early diagnosis of GDM. Moreover, existing metabolomic studies on GDM are shown to provide conflicting results about metabolite profile characteristics. This systematic review was registered at PROSPERO ( www.crd.york.ac.uk/PROSPERO ) as CRD42020196122.

Effect of rosiglitazone on circulating malondialdehyde (MDA) level in diabetes based on a systematic review and meta-analysis of eight clinical trials.

Patients with type 2 diabetes have high levels of malondialdehyde (MDA), and clinical data suggest a reducing effect of rosiglitazone (RSG) on the level of MDA in these patients. However, the results of available studies on the level of MDA in RSG-treated patients are not univocal. This meta-analysis aimed to assess the impact of RSG on the level of MDA. We performed a comprehensive search of PubMed, the Institute for Scientific Information Web of Science, Embase, Scopus, and Cochrane Library for related controlled trials until July 2020. Eligible studies were selected based on the inclusion criteria. Extracted data from each study were combined using a random-effects model. Sensitivity and subgroup analyses were conducted to explore potential heterogeneity. Eight trials with 456 subjects met the inclusion criteria. The results significantly showed the reducing effect of RSG on circulating MDA level (-0.47 µmol/mL; 95% CI -0.93 to -0.01; p=0.04; I2=82.1%; p heterogeneity=0.00) in individuals with T2D. No publication bias was observed with Begg's rank correlation (p=0.71) and Egger's linear regression (p=0.52) tests. Subgroup analyses showed that an intervention dose of 8 mg/day in serum samples was found to have a reducing effect on the level of MDA (-0.56 µmol/mL; 95% CI -0.98 to -0.14; p=0.008; I2=11.4%; p heterogeneity=0.32). Random-effects meta-regression did not show any significant association between the level of MDA and potential confounders including RSG dose, treatment duration, and sex. In conclusion, we found a significant reduction in MDA concentration in subjects with T2D who received a dose of 8 mg of RSG daily.