Background: Lipids are ubiquitous metabolites with diverse functions. Excessive lipid accumulation can trigger lipid redistribution among metabolic organs such as adipose, liver and muscle, thus altering the lipid metabolism. It has been revealed that disturbed lipid metabolism would cause multiple disease complications and is highly correlated with human morbidity. Resveratrol (RSV), a phytoestrogen with antioxidant, can modulate insulin resistance and lipid profile. Recently, research on RSV supplementation to improve glucose and lipid metabolism has been controversial. A meta-analysis may provide a scientific reference for the relationship between lipid metabolism and RSV supplementation.
Methods and Analysis: We searched the PubMed, Cochrane Library, Web of Science, and Embase databases from inception to October 2021 using relevant keywords. A comprehensive search for randomized controlled trials (RCTs) was performed. For calculating pooled effects, continuous data were pooled by mean difference (MD) and 95% confidence interval (CI). Adopting the method of inverse-variance with a random-effect, all related statistical analyses were performed using the Rev Man V.5.3 and STATA V.15 software.
Results: A total of 25 articles were incorporated into the final meta-analysis after removal of duplicates by checking titles and abstracts and excluding non-relevant articles. The selected articles had a total of 1,171 participants, including 578 in the placebo group and 593 in the intervention group. According to the current meta-analysis, which demonstrated that there was a significant decrease in waist circumference (SMD = –0.36; 95% CI: –0.59, –0.14; P = 0.002; I 2 = 88%), hemoglobin A1c (–0.48; –0.69, –0.27; P ≤ 0.001; I 2 = 94%), total cholesterol (–0.15; –0.3, –0.01; P = 0.003; I 2 = 94%), low density lipoprotein cholesterol (–0.42; –0.57, –0.27; P ≤ 0.001; I 2 = 92%), high density lipoprotein cholesterol (0.16; –0.31, –0.02; P = 0.03; I 2 = 81%) following resveratrol administration.
Conclusion: These results suggest that RSV has a dramatic impact on regulating lipid and glucose metabolism, and the major clinical value of resveratrol intake is for obese and diabetic patients. We hope that this study could provide more options for clinicians using RSV. Furthermore, in the future, large-scale and well-designed trials will be warranted to confirm these results.
Systematic Review Registration: Website, identifier [CRD42021244904].
Lipids are ubiquitous metabolites with diverse functions. Excessive lipid accumulation can trigger lipid redistribution among metabolic organs such as adipose, liver and muscle, thus altering the lipid metabolism. Disturbed lipid metabolism will cause multiple disease complications and is highly correlated with human morbidity. Even some reports have indicated that lipid redistribution was tightly associated with progression of various cancers, and these discoveries might be significant for treatment of antileukemic and epigenetic effects. Regulation of lipid metabolism is essential for maintenance of whole-body metabolic and energy homeostasis.
Resveratrol (RSV) is a phytoestrogen with antioxidant and can modulate insulin resistance and lipid profile. In previous studies, RSV has been suggested to improve motor function, extension of life span and well loss in weight in animal models, such as such as diminishing the deposits of white adipose tissue (WAT) and reducing total body fat. However, it was reported that for obese men, high-dose resveratrol (hRSV) used for four weeks had no effect on ectopic or visceral fat content and lipid oxidation rates. Also, RSV is a plant-derived nutritional supplement shown to have antidiabetic properties in many animals models. In summary, the research on RSV supplementation improving glucose and lipid metabolism remains controversial.
Systematic review and meta-analysis were performed to summarize the published clinical trials to date, and we tried to incorporate the evidence as a new model for revaluating the effect of RSV on glucose and lipid metabolism more comprehensively. The results of data-analysis further define the relationship between lipid metabolism and RSV supplementation, clarifying the contribution of RSV in lipid-related components and elucidating the comparative causal role of lipid-related components by RSV supplementation.
(1) To provide insights into the relationship between lipid metabolism and RSV supplementation; (2) to identify resveratrol contributions in lipid-related components; (3) to elucidate the comparative causal role of lipid-related components by RSV supplementation.
Meta-analysis, a statistical procedure for systematic statistical synthesis of data from independent studies, is the primary source of concise up-to-date information. We performed a meta-analysis in accordance with the methodology described in Paterson et al. (2001) and included quantitative, qualitative, and mixed-method studies. Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocols (PRISMA-P) were followed to perform a systematic review. Methods were designed based on PRISMA, a proposal for reporting, and Cochrane Collaboration Handbook.
We searched the PubMed, Cochrane Library, Web of Science, Google Scholar, and Embase databases from inception to October 2021 using relevant keywords, and a comprehensive search for human randomized controlled trials (RCTs) was also performed. All ongoing RCTs were searched in the International Standard Randomized Controlled Trial Number register (ISRCTN), WHO International Clinical Trials Registry Platform (ICTRP), and Clinical Trials. There was a systemic search for relevant literature and exploration of the association between treatment with resveratrol and biological indexes. We used combinations of the following keywords and MeSH terms for the literature search: intervention (“resveratrol” or “resveratrols” and “supplementation” or “intake” or “use”) and outcome (“body weight” or “body mass index” or “waist circumference” or “Hemoglobin A1c” or “HOMA index” or “Insulin” or “glucose” or “fat percentage total cholesterol” or “triglyceride” or “low density lipoprotein cholesterol” or “high density lipoprotein cholesterol” or “leptin” or “adiponectin”).
Articles that fulfilled the following criteria were selected for this study:
Reviews, conference abstracts, and studies with unavailable full text were excluded.
The process of study selection is shown in the PRISMA flow chart.
Two researchers independently performed study selection and extracted data of included studies using an Excel form. Disagreement between both researchers was resolved by consensus. The following items were extracted: first author’s name, publication year, location, age and gender, sample size (intervention and placebo groups), duration of intervention, number of sessions (or dose), underlying diseases, and mean value and standard deviation (SD) in intervention and placebo groups for TC, TG, LDL-C, HDL-C, body weight, BMI, WC, HbA1c, HOMA index, insulin, leptin, fasting glucose, fat percentage, and adiponectin level.
The methodological quality and bias of all eligible studies were assessed by two independent reviewers using the Cochrane Collaboration risk of bias tool and standard Excel forms Any ambiguity or discrepancy in this course was resolved by discussion and involvement of a third person. Using the following seven criteria, we assessed the quality of studies: (1) random sequence generation, (2) allocation concealment, (3) blinding of participants and personnel, (4) blinding of outcome assessment, (5) incomplete outcome data, (6) selective reporting, and (7) other probable sources of risk biases.
Patient characteristics are summarized in detail and are shown in Table 1. The authors estimated clinical information of all eligible studies on anthropometric measurements including: (1) TC, (2) TG, (3) LDL-C, (4) HDL-C, (5) body weight, (6) BMI, (7) WC, (8) HbA1c, (9) HOMA index, (10) insulin, (11) leptin, (12) fasting glucose, (13) fat percentage, and (14) adiponectin level. For calculating pooled effects, continuous data were pooled using mean difference (MD) with 95% confidence interval (CI). Inverse variance with a random-effect was applied. All related statistical analyses were performed with the Rev Man V.5.3 and STATA V.15 software. Cochran’s Q- test and the I 2 statistic were performed to test for heterogeneity and quantify the proportion of total variation that resulted from heterogeneity, and P< 0.05 was regarded as significant heterogeneity.
