Evidence-Based Complementary and Alternative Medicine

Evidence-Based Complementary and Alternative Medicine / 2021 / Article

Research Article | Open Access

Volume 2021 |Article ID 6109406 | https://doi.org/10.1155/2021/6109406

Zhao Jie, Mo Chao, Ai Jun, Shi Wei, Meng LiFeng, "Effect of Curcumin on Diabetic Kidney Disease: A Systematic Review and Meta-Analysis of Randomized, Double-Blind, Placebo-Controlled Clinical Trials", Evidence-Based Complementary and Alternative Medicine, vol. 2021, Article ID 6109406, 14 pages, 2021. https://doi.org/10.1155/2021/6109406

Effect of Curcumin on Diabetic Kidney Disease: A Systematic Review and Meta-Analysis of Randomized, Double-Blind, Placebo-Controlled Clinical Trials

Academic Editor: Yanggang Yuan
Received05 Sep 2021
Accepted05 Nov 2021
Published02 Dec 2021

Abstract

Background. Curcumin, a polyphenolic constituent from Curcuma longa, possesses antioxidant, hypolipidemic, and antidiabetic properties and has been reported to protect against diabetic kidney disease (DKD); however, the effect is inconsistent. Objective. This systematic review and meta-analysis aimed to investigate the effect of curcumin supplementation on renal function, lipid profile, blood pressure, and glycemic control in DKD. Methods. A systematic and comprehensive literature search of interrelated randomized controlled trials (RCTs) was conducted in PubMed, Embase, Cochrane Library, Web of Science, Scopus, and ClinicalTrials.gov from inception to July 30, 2021. Two investigators independently extracted data and assessed the risk of bias. Weighted mean differences (WMDs) with 95% confidence intervals (CIs) were calculated to describe the effect sizes using a fixed-effect model. Statistical analysis was performed using STATA 14.0 and RevMan 5.3. Results. Five RCTs involving 290 participants with DKD were included. Curcumin supplementation significantly improved the serum creatinine (WMD: −0.16 mg/dL, 95% CI: −0.3 to −0.02,  = 0.029, I2 = 0%, moderate certainty), total cholesterol (WMD: −10.13 mg/dL, 95% CI: −17.84 to −2.14,  = 0.01, I2 = 0%, moderate certainty), systolic blood pressure (WMD: 3.94 mmHg, 95% CI: 1.86 to 6.01,  < 0.01, I2 = 33.5%, moderate certainty), and fasting blood glucose (WMD: −8.29 mg/dL, 95% CI: −15.19 to −1.39,  = 0.019, I2 = 43.7%, moderate certainty) levels; however, it had no significant effects on blood urea nitrogen, proteinuria, triglyceride, low-density lipoprotein-cholesterol, high-density lipoprotein-cholesterol, and diastolic blood pressure levels. Conclusions. Curcumin may provide great potential effects against DKD. More large-scale and high-quality RCTs are required to confirm these findings.

1. Introduction

Diabetic kidney disease (DKD), a common microvascular complication of diabetes, is characterized by increased albuminuria level or urinary albumin-to-creatinine ratio (UACR), decreased glomerular filtration rate (GFR), or both [1]. According to the International Diabetes Federation data, approximately 463 million people were living with diabetes mellitus in 2019, and this number is projected to increase to 700 million by 2045 [2]. Up to 40% of patients with type 2 diabetes develop DKD, and DKD is currently the leading cause of end-stage renal disease (ESRD) worldwide [3]. Patients with DKD have a higher risk for cardiovascular morbidity and mortality, which are closely associated with risk factors such as hyperglycemia, dyslipidemia, and hypertension, than those without DKD [4]. DKD has become a considerable and growing challenge for health systems.

The introduction of lifestyle changes, for example, exercise and diet, optimal control of blood pressure (BP), glucose, and lipids, and treatment with pharmacological agents or pharmaceuticals, such as angiotensin-converting enzyme inhibitors and angiotensin receptor blockers, are recommended by clinical practice guidelines for the treatment of patients with DKD [5, 6]. Sodium-glucose cotransporter 2 inhibitors, a new class of antidiabetic agents, have now been shown to prevent major kidney outcomes in individuals with diabetes [3, 7]; however, close attention needs to be paid to their adverse effects [8]. Although these managements are effective, they do not seem to substantially decrease the morbidity of DKD and patients with this condition still have a high risk of disease progression [9], indicating the urgent need for complementary and alternative therapies.

Turmeric, a powder of the rhizomes of Curcuma longa L. (Zingiberaceae), is a well-known spice additive that is ubiquitous in Asian cuisine [10]. Turmeric is also a staple component of Ayurveda and traditional Chinese medicine and has been used as a remedy for various chronic diseases, such as cardiovascular disease and diabetes [11] and Alzheimer’s disease [12]. Curcumin is a naturally occurring polyphenolic compound extracted from turmeric and has various pharmacological activities, including antioxidant, anti-inflammatory, immunomodulatory, hypolipidemic, glycemic control, and improving hepatic function as well as serum cortisol levels [1315]. Glucose and lipid metabolism disorder, oxidative stress, and inflammation are among the major contributors to the pathogenesis of DKD [5], indicating that curcumin has properties that might improve the pathological changes in DKD. Animal experiments have revealed that curcumin administration in rats or mice with DKD could alleviate kidney damage by increasing antioxidant mediators [16], suppressing inflammatory factors [17], and decreasing proteinuria (PRO) [18]. Clinical trials have shown that curcumin supplementation is beneficial in improving renal function, lipid profile, BP, and fasting blood glucose (FBG) in patients with DKD [1923]; however, contradictory results have been reported. Some studies reported that curcumin administration can significantly improve renal function [21, 22], lipid profile [19], BP [19], and FBG levels [19, 20], whereas other trials reported contrasting results [20, 23]. Therefore, this study aimed to perform a comprehensive review and meta-analysis of previous pilot, double blind, placebo-controlled, randomized controlled trials (RCTs) on the effect of curcumin supplementation on DKD.

2. Materials and Methods

This meta-analysis was performed according to the guidelines of Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) [24] and was registered at INPLASY (https://inplasy.com/) with a registration ID INPLASY202180001. The checklist of PRISMA is shown in Supplementary Table S1.

2.1. Search Strategy

The literature was systematically searched using electronic databases, including PubMed, Embase, Cochrane Library, and Web of Science and a clinical trial registry (ClinicalTrials.gov), from inception to July 30, 2021. Medical Subject Heading terms and text words were used as search terms, including “curcumin,” “turmeric,” “diabetic,” “diabetic nephropathies,” “diabetic kidney disease,” and “randomized controlled trial.” All searches were limited to English-language publications. We also manually screened the reference list of eligible studies in case of missing appropriate studies. The detailed search strategies for databases are presented in Supplementary Table S2.

2.2. Study Selection

A trial was included if it met the following criteria: (i) designed as an RCT; (ii) included patients diagnosed with DKD, defined as urinary albumin-to-creatinine ratio ≥30 mg/g or albumin excretion rate ≥30 mg/24 h or estimated GFR (eGFR) <60 mL/min/1.73 m2 for ≥3 months caused by diabetes mellitus [25] (no restrictions on the patients’ sex, region, race, and disease course were implemented); (iii) administered curcumin to participants in the intervention group and placebo to the control group (with no limitation in dosage or follow-up period); and (iv) reported at least one of the following outcomes: renal function parameters: including serum creatinine (SCr), blood urea nitrogen (BUN), and PRO; lipid profile, including total cholesterol (TC), triglycerides (TG), low-density lipoprotein-cholesterol (LDL-C), high-density lipoprotein-cholesterol (HDL-C); BP, including systolic blood pressure (SBP) and diastolic blood pressure (DBP); and FBG levels. A study was excluded if it met the following criteria: (i) included participants not diagnosed with DKD; (ii) performed the trial in animals; (iii) published as an observational study, case report, meta-analysis, or review; and (iv) included participants who received drugs or supplements other than curcumin.

2.3. Data Extraction

Two investigators (J.Z. and C.M.) independently screened eligible studies according to predetermined criteria. One investigator (J.Z.) extracted the following data from each study: study characteristics, including first author, publication year, country, and study design; participant characteristics, including sample size, mean age, and sex ratio; interventions and comparison, including the use and dosage of turmeric/curcumin and the follow-up period; and available outcomes. The other investigator (C.M.) rechecked the data for consistency. Any discrepancy between the two investigators (J.Z. and C.M.) was resolved through a discussion with a third investigator (J.A.). For missing data, we tried our best to contact corresponding authors via e-mail.

2.4. Risk of Bias Assessment

Two investigators (J.Z. and C.M.) independently assessed the risk of bias of the included studies using the Cochrane Risk of Bias tool [26], including six items: selection bias, performance bias, detection bias, attrition bias, reporting bias, and bias from other sources. These items were judged as “low risk,” “high risk,” or “unclear.” Any disagreements were resolved through a discussion with a third investigator (J.A.).

2.5. Data Synthesis and Analysis

The effects of outcomes in the intervention and placebo groups were estimated by comparing the changes in mean differences before and after therapy (i.e., end values minus baseline values). The standard deviation (SD) changes in outcomes were calculated according to the following formula: SD = sqrt [(SD before treatment) 2 + (SD after treatment) 2–(2R × SD before treatment × SD after treatment)], where R, a correlation coefficient, was equal to 0.5 [27]. Weighted mean differences (WMDs) with corresponding 95% confidence intervals (CIs) for continuous outcomes were calculated to describe the effect sizes. Cochran’s Q and I2 statistics were employed to evaluate statistical heterogeneity. I2 values of <25%, >50%, and >75% were considered to indicate low, moderate, and high heterogeneity, respectively [28]. Participants (≤60 versus > 60 years), dosage of curcumin supplementation (≥1500 versus < 1500 mg/day), and follow-up period (≤2 versus > 2 months) or sensitivity analysis was conducted to identify the sources of heterogeneity. Furthermore, sensitivity analysis was performed to evaluate the robustness of outcomes. For outcomes with small heterogeneity, sensitivity analyses were performed using the conversion effect model. In contrast, if outcomes had considerable heterogeneity, sensitivity analysis was performed by omitting one study at a time. Begg’s and Egger’s tests were used to examine potential publication bias [29]. Statistical analysis was performed using STATA 14.0 (StataCorp, College Station, TX, USA) and RevMan 5.3. values <0.05 were considered statistically significant.

2.6. GRADE Assessment

Two investigators (J.Z. and C.M., W.S., or J.A.) independently evaluated the certainty of the evidence for outcomes according to the GRADE system, an approach for rating the quality of evidence and strength of recommendations, graded as high, moderate, low, or very low certainty [30]. GRADE assessments were downgraded according to the following criteria: (i) risk of bias was downgraded if one of the items used to evaluate the risk of bias was considered to be at a high risk of bias and most of the included studies were identified as having a high risk of bias; (ii) imprecision was downgraded if the 95% CIs for effect estimates overlap zero for continuous outcomes; (iii) inconsistency was downgraded if there was substantial heterogeneity (I2 > 50% and  < 0.1) that was unexplained by any subgroup or sensitivity analysis; (iv) indirectness was downgraded if there were any influencing factors that limited the interpretation of outcomes; and (v) publication bias was downgraded if there was a significant difference in the evidence of publication bias according to either Begg’s test or Egger’s test ( < 0.05).

3. Results

3.1. Description of Included Studies

A total of 160 potentially relevant records were obtained from PubMed (n = 12), Embase (n = 43), Cochrane Library (n = 20), Scopus (n = 69), Web of Science (n = 16), and ClinicalTrials.gov (n = 0). After removing 48 duplicates, 112 records remained for screening. According to predefined inclusion criteria, 100 records were excluded after screening the titles and abstracts. Consequently, after full-text assessment and detailed examination, seven records were excluded because of having an inappropriate study design, using an inappropriate intervention, or not reporting the data of interest. Ultimately, five RCTs [1923] were included. The PRISMA flow diagram is shown in Figure 1.

3.2. Characteristics of Included Studies

Overall, five trials involving 290 patients were included. These trials were conducted in Iran and Mexico and were published between 2011 and 2020. Two trials included patients with overt diabetic nephropathy [21, 22]; two trials were performed in patients with diabetic proteinuric chronic kidney disease [20, 23]; and one trial enrolled patients with diabetes requiring hemodialysis [19]. All included studies were randomized, double-blind, placebo-controlled trials. The sample size varied from 20 to 54. The mean age of patients was 60 years. Three trials used curcumin capsules at doses ranging from 320 to 1670 mg/day [20, 22, 23]. One study used turmeric capsules that included curcumin at a dose of 66.3 mg/day [21], whereas another trial used nanocurcumin capsules at a dose of 80 mg/day [19]. The follow-up periods ranged from 2 to 6 months. The main characteristics of included trials are summarized in Table 1.


First author, publication year, countryStudy characteristicsPopulation characteristicsIntervention and compairionFollow-up time (M)Outcomes
Study designParticipantsSample sizes (I/C)Mean age (years, I/C)Males (%, I/C)Mean duration of DM (years, I/C)Intervention groupControl groupRenal functionLipid profileGlycemic controlBlood pressure

Khajehdehi 2011, IranRandomized, double-blind, placebo-controlled clinical trialDKD20/2052.9/52.645/65NATurmeric capsule 1500 mg/day, which included curcumin 66.3 mg/dayPlacebo2SCr, PRO, BUNTC, TG, HDL-C, LDL-CFBGSBP, DBP
Jiménez-Osorio 2016, MexicoRandomized, double-blind, placebo-controlled clinical trialDKD28/2373.9/67.955/56.2NACurcumin capsule 320 mg/dayPlacebo2SCr, PROTC, TGFBGSBP, DBP
Vanaie 2019, IranRandomized, double-blind, placebo-controlled clinical trialDKD27/1959/6159/5816/15Curcumin capsule 1500 mg/dayPlacebo4SCr, BUN, PROTC, TG, HDL-C, LDL-CFBGNA
Shafabakhsh 2020, IranRandomized, double-blind, placebo-controlled clinical trialDKD26/2758.3/56.265.4/55.6NANanocurcumin capsule 80 mg/dPlacebo3SCr, BUNTC, TG, HDL-C, LDL-CFBGSBP, DBP
Martinez 2020, MexicoRandomized, double-blind, placebo-controlled clinical trialDKD54/4659.3/57.457.4/78.3NACurcumin 1670 mg/dayPlacebo6PRONANASBP, DBP

SCr, serum creatinine; BUN, blood urea nitrogen; PRO, proteinuria; TC, total cholesterol; TG, triglycerides; LDL-C, low-density lipoprotein-cholesterol; HDL-C, high-density lipoprotein-cholesterol; SBP; systolic blood pressure; DBP, diastolic blood pressure; DKD, diabetic kidney disease; FBG, fasting blood glucose; NA, not available; I, intervention group; C, control group; M, month.
3.3. Methodological Quality Assessment

All studies had a randomized parallel design. Two trials (40%) showed a low risk of bias and used permuted blocks [22] and computer-generated random numbers [19], respectively. The remaining three RCTs were classified as having an unclear risk of bias owing to inadequate descriptions of randomization methods [20, 21, 23]. With respect to allocation concealment, blinding of participants and researchers, incomplete outcome data, selective reporting, and other biases, all included trials were classified as having a low risk of bias. Notably, four trials (80%) that did not blind outcomes were assessed as having a high risk of bias [2023]. The risk of bias is presented in Figure 2.

3.4. Meta-Analysis of Outcomes
3.4.1. Effects of Curcumin Supplementation on Renal Function

3.4.1.1 SCr. Four trials with 190 participants reported the effects of curcumin supplementation on SCr. Compared with placebo, curcumin supplementation was associated with a significant decrease in SCr levels (WMD: −0.16 mg/dL, 95% CI: −0.3 to −0.02,  = 0.029; I2 = 0%, Pheterogeneity = 0.648; Figure 3(a) and Table 2).


OutcomesNo. of studiesSample sizeHeterogeneityAnalysis modelWMD (95% CI)value
I2P heterogeneity

Renal function
 SCr41900%0.648Fixed−0.16 (−0.3 to −0.02)0.029
 BUN2860%0.601Fixed1.10 (−1.72 to 3.92)0.446
 PRO423786.90%<0.01Random0.09 (−0.73 to 0.92)0.614

Lipid profile
 TC41900%0.426Fixed−10.13 (−17.84 to −2.14)0.01
 TG41900%0.661Fixed3.42 (−6.93 to 13.22)0.495
 HDL-C31390%0.587Fixed1.16 (−1.55 to 3.87)0.402
 LDL-C313977.20%0.012Random−1.06 (−17.89 to 15.77)0.902

Blood pressure
 SBP424433.50%0.212Fixed3.94 (1.86 to 6.01)<0.01
 DBP424492.30%<0.001Random0.21 (−5.64 to 6.05)0.944

Glycemic control
 FBG419043.70%0.149Fixed−8.29 (−15.19 to −1.39)0.019

SCr, serum creatinine; BUN, blood urea nitrogen; PRO, proteinuria; TC, total cholesterol; TG, triglycerides; LDL-C, low-density lipoprotein-cholesterol; HDL-C, high-density lipoprotein-cholesterol; SBP, systolic blood pressure; DBP, diastolic blood pressure; FBG, fasting blood glucose.

3.4.1.2 BUN. Three trials with 139 participants studied the effect of curcumin on BUN. The pooled effect of curcumin administration showed no significant difference in BUN (WMD: −0.80 mg/dL, 95% CI: −5.62 to 4.02,  = 0.933), with high heterogeneity (I2 = 60% and Pheterogeneity = 0.082). Subgroup analysis showed that the effect of curcumin supplementation on BUN also had substantial heterogeneity in all the analyzed subgroups (Table 3). Further sensitivity analysis revealed that the heterogeneity of I2 = 60% changed to I2 = 0% after removing the study by Shafabakhsh et al. [19], which was probably the major source of the heterogeneity. When the other two trials with 86 participants were pooled, the revised result showed that the effect of curcumin on BUN still had no significant difference from that of placebo (WMD: 1.10 mg/dL, 95% CI: −1.72 to 3.92,  = 0.446; I2 = 0%, Pheterogeneity = 0.601; Figure 3(b) and Table 2).


OutcomesOverall effectsSubgroups analyzed
Mean ageCurcumin intakeFollow-up period
≤60 years>60 years≥1500 mg/day<1500 mg/day≤2 months>2 months

Blood urea nitrogenNo. of trials331212
WMD (95% CI)−0.8 (−5.62, 4.02)−0.11 (−2.71, 2.49)0.72 (−2.43, 3.87)−1.12 (−1.53, 7.28)2.60 (−3.71, 8.91)−2.54 (−10.02, 4.93)
value0.9330.9330.6540.6580.4190.505
(%)606075.975.9
heterogeneity0.0820.0820.0410.042

ProteinuriaNo. of trials4312222
WMD (95% CI)−0.09 (−0.73, 0.92)−0.23 (−0.95, 0.05)0.80 (0.38, 1.22)−0.06 (−0.82, 0.69)−0.12 (−2.24, 2.01)−0.12 (−2.24, 2.01)−0.06 (−0.82, 0.69)
value0.8230.536<0.0010.8750.9140.9140.875
(%)86.90%41.40%47.40%81.50%81.50%47.40%
heterogeneity<0.0010.1810.1680.0020.020.168

Low-density lipoprotein-cholesterolNo. of trials331212
WMD (95% CI)−1.06 (−17.89, 15.77)0.34 (−2.73, 3.41)0.72 (−2.43, 3.87)−0.79 (−0.05, 38.47)20.10 (−2.91, 43.11)−8 (−28.05, 12.05)
value0.9020.9020.6540.9680.0870.434
(%)77.277.28783
heterogeneity0.0120.0120.0050.015

Diastolic blood pressureNo. of trials4311322
WMD (95% CI)0.21 (−5.64, 6.05)−1.91 (−6.79, 2.96)5.90 (4.32, 7.48)2.00 (−1.98, 5.98)−0.44 (−8.51, 7.63)−0.05 (−11.96, 11.87)0.42 (−2.90, 3.75)
value0.9440.441<0.0010.3250.9150.8030.994
(%)92.376.894.896.921.4
heterogeneity<0.0010.013<0.001<0.0010.259

WMD, weight mean difference; CI, confidence interval.

3.4.1.3 PRO. Four trials with 237 participants assessed the effect of curcumin on PRO. No significant difference in PRO was observed with curcumin supplementation (WMD:0.09 g/24 h, 95% CI: −0.73 to 0.92,  = 0.614), with considerable heterogeneity between studies (I2 = 86.9%, Pheterogeneity<0.01) (Figure 3(c) and Table 2). Subgroup analysis revealed that the statistical heterogeneity decreased in participants with age ≤60 years (I2 = 41.4% and heterogeneity = 0.181), dosage of curcumin intake ≥1500 mg/day (I2 = 47.4% and heterogeneity = 0.168), and follow-up period >2 months (I2 = 47.4% and heterogeneity = 0.168), suggesting that these factors may be the sources of the heterogeneity (Table 3).

3.4.2. Effects of Curcumin Supplementation on Lipid Profile

3.4.2.1 TC. Four trials with 190 participants analyzed the impact of curcumin supplementation on TC. The result of the meta-analysis showed a significant decrease in TC after curcumin administration (WMD: −10.13 mg/dL, 95% CI: −17.84 to −2.14,  = 0.01; I2 = 0%, Pheterogeneity = 0.426; Figure 4(a) and Table 2).

3.4.2.2 TG. Four trials with 190 participants reported the effect of supplemental curcumin on TG. No significant difference in TG was observed after curcumin administration (WMD: 3.42 g/dL, 95% CI: −6.93 to 13.22,  = 0.495; I2 = 0%; Pheterogeneity = 0.661; Figure 4(b) and Table 2).

3.4.2.3 HDL-C. Three trials with 139 participants assessed the effects of curcumin on HDL-C. Compared with placebo, curcumin supplementation showed a nonsignificant effect on HDL-C (WMD: 1.16 mg/dL, 95% CI: −1.55 to 3.87,  = 0.402; I2 = 0%, heterogeneity = 0.587; Figure 4(c) and Table 2).

3.4.2.4 LDL-C. Three trials with 139 participants assessed the effects of curcumin on LDL-C. The meta-analysis showed that curcumin supplementation did not affect changes in LDL-C (WMD: −1.06 mg/dL, 95% CI: −17.89 to 15.77,  = 0.902; I2 = 77.2%, heterogeneity = 0.012; Figure 4(d) and Table 2). The considerable heterogeneity between studies remained after subgroup analysis according to the mean age of participants, dosage of curcumin, and follow-up period (Table 3). The sensitivity analysis also did not explain the heterogeneity. After carefully reading the original articles, we found that the participants in the three studies were different, although they were all diagnosed with DKD. Participants with overt type 2 diabetic nephropathy were included in two studies, and patients with diabetes undergoing hemodialysis were enrolled in the other trial, and this difference was perhaps the source of the heterogeneity.

3.4.3. Effects of Curcumin Supplementation on BP

3.4.3.1 SBP. Four trials with 244 participants investigated the effect of curcumin supplementation on SBP. The pooled effect size of curcumin supplementation for SBP was 3.94 mmHg (95% CI: 1.86 to 6.01,  = 0.00), with heterogeneity between studies (I2 = 33.5%, heterogeneity = 0.212) for SBP (Figure 5(a) and Table 2).

3.4.3.2 DBP. Four trials with 244 participants investigated the effect of curcumin supplementation on DBP. The differences in DBP were not statistically significant (WMD: 0.21 mmHg, 95% CI: −5.64 to 6.05,  = 0.944; I2 = 92.3%, Pheterogeneity<0.001) between the curcumin group and the placebo group (Figure 5(b) and Table 2). Heterogeneity between studies was insignificant (I2 = 21.4%, heterogeneity = 0.259) after subgroup analysis according to follow-up period (>2 months), which was probably the source of the heterogeneity (Table 3).

3.4.4. Effects of Curcumin Supplementation on FBG

Four trials with 190 participants analyzed the impact of curcumin supplementation on FBG. The overall effect size revealed a significant decrease in FBG after curcumin administration (WMD: −8.29 mg/dL, 95% CI: −15.19 to −1.39,  = 0.019; I2 = 43.7%, heterogeneity = 0.149; Figure 5(c) and Table 2).

3.5. Sensitivity Analysis

For outcomes with insignificant heterogeneity (SCr, TC, TG, and HDL-C), no significant impact of the conversion effect model on the overall effect sizes was observed. With respect to outcomes with substantial heterogeneity (BUN, PRO, LDL-C, and DBP), the overall effect sizes were not significantly affected when any single study was omitted. These indicated the robustness of the combined result. However, the overall effect sizes for outcomes with insignificant heterogeneity (SBP and FBG) were influenced by the conversion effect model, indicating the poor robustness of SBP and FBG as outcomes. Therefore, the results on SBP and FBG should be interpreted with caution.

3.6. Publication Bias

No evidence of publication bias was observed for the effects of curcumin supplementation on SCr, BUN, PRO, TC, TG, HDL-C, LDL-C, SBP, DBP, and FBG based on Begg’s test and Egger’s test (Supplementary Table 2S3).

3.7. GRADE Assessment

The overall certainty of the evidence for the effects of curcumin supplementation on renal function, lipid profile, BP, and glycemic control is presented in Table 4. The quality of the evidence for SCr, TC, SBP, and FBG was graded as “moderate” after being downgraded for risk of bias. Meanwhile, the quality of the evidence for BUN, PRO, TG, HDL-C, and DBP was graded as “low” after being downgraded for risk of bias and imprecision. The quality of the evidence for LDL-C was downgraded for risk of bias, inconsistency, and imprecision and was graded as “very low.”


OutcomesNo. of trialsStudy designQuality assessmentEffect of WMD (95% CIs)Quality
Risk of biasInconsistencyIndirectnessImprecisionPublication bias

Renal function
 SCr4RCTsSeriousaNot seriousNot seriousNot seriousNot serious−0.16 (−0.30, −0.02)⨁⨁⨁◯ moderate
 BUN2RCTsSeriousaNot seriousbNot seriousSeriouscNot serious1.10 (−1.72, 3.92)⨁⨁◯◯ low
 PRO4RCTsSeriousaNot seriousdNot seriousSeriouscNot serious−0.09 (−0.73, 0.92)⨁⨁◯◯ low

Lipid profile
 TC4RCTsSeriousaNot seriousNot seriousNot seriousNot serious−10.13 (−17.84, −2.41)⨁⨁⨁◯ moderate
 TG4RCTsSeriousaNot seriousNot seriousSeriouscNot serious3.42 (−6.39, 13.22)⨁⨁◯◯ low
 HDL-C3RCTsSeriousaNot seriousNot seriousSeriouscNot serious1.16 (−1.55, 3.87)⨁⨁◯◯ low
 LDL-C3RCTsSeriousaSeriouseNot seriousSeriouscNot serious−1.06 (−17.89,15.77)⨁◯◯◯ very low

Blood pressure
 SBP4RCTsSeriousaNot seriousNot seriousNot seriousNot serious3.94 (1.87, 6.01)⨁⨁⨁◯ moderate
 DBP4RCTsSeriousaNot seriousfNot seriousSeriouscNot serious0.21 (−5.64, 6.05)⨁⨁◯◯ low

Glycemic control
 FBG4RCTsSeriousaNot seriousNot seriousNot seriousNot serious−8.29 (−15.19, −1.39)⨁⨁⨁◯ moderate

SCr, serum creatinine; BUN, blood urea nitrogen; PRO, proteinuria; TC, total cholesterol; TG, triglycerides; LDL-C, low-density lipoprotein-cholesterol; HDL-C, high-density lipoprotein-cholesterol; SBP, systolic blood pressure; DBP, diastolic blood pressure; FBG, fasting blood glucose; WMD, weight mean difference; CI, confidence interval; RCT, randomized controlled trial. aFor risk of bias, the majority of included studies were considered to be at high risk of bias due to the fact that outcomes assessment was not blinded, so it was downgraded. bAlthough there was substantial heterogeneity for the effect of curcumin on BUN, it was explained when the study conducted by Shafabakhsh et al. was removed according to the sensitivity analysis (original:  = 60%, heterogeneity = 0.082; after study was removed:  = 0%, heterogeneity = 0.601). cThe 95% CIs for effect estimates overlap the zero. dAlthough there was considerable heterogeneity for the effect of curcumin on PRO, it was associated with mean age (≤60 years,  = 41.4%), curcumin intake (≥1500 mg/day,  = 47.4%), and follow-up period (>2 months,  = 47.4%). eThere was substantial heterogeneity ( ≥ 77.2%, < 0.1) that was unexplained by any subgroup or sensitivity analysis for the effect of curcumin on LDL-C. fAlthough there was substantial heterogeneity, it was explained for the effect of curcumin on DBP with follow-up periods (>2 months,  = 21.4%).

4. Discussion

To our knowledge, this is the first meta-analysis of RCTs to analyze the effects of curcumin supplementation on DKD. Our findings showed that supplemental curcumin, in comparison with placebo, significantly improved the SCr, TC, SBP, and FBG levels in patients with DKD, with moderate certainty of evidence; however, it had no significant effects on the BUN, PRO, TG, HDL-C, LDL-C, and DBP levels.

The presence of PRO indicates renal parenchymal injury, which has been considered a clinical hallmark and a sign of renal dysfunction [31]. As PRO increases, eGFR decreases, resulting in end-stage renal disease and an increased risk of cardiovascular events [32, 33]. It is generally known that elevated levels of SCr and BUN in serum also indicate renal impairment. In the current meta-analysis, curcumin supplementation significantly decreased the SCr levels. Nevertheless, no effects of curcumin on BUN and PRO were observed in patients with DKD, consistent with the findings of a previous systematic review that investigated the role of curcumin in the treatment of renal disorders [34]. However, evidence from animal studies showed that curcumin significantly reduced the levels of SCr, BUN, and PRO [18], indicating that the differences in the effects of curcumin between animal experiments and clinical trials need further verification.

Lipid accumulation in podocytes results in podocyte injury and renal impairment and has been considered a driving factor for the development and progression of DKD [35]. Dyslipidemia is positively related to atherosclerosis and increases the risk of cardiovascular disease [36], indicating the urgent need for the management of dyslipidemia. Curcumin has been widely investigated owing to its obvious hypolipidemic effects. A study showed that curcumin significantly reduced the elevated levels of TC and TG and increased the level of HDL-C in rats fed a high-fat diet by increasing hepatic fatty acid oxidation activity and improving the apoptotic status of liver tissue [37]. In addition, the hypolipidemic effects of curcumin are also attributed to the suppression of the rate-limiting enzyme in the TC synthesis pathway; upregulation of the expressions of ABCA1, Apo-A1, and SR-BI, which are associated with reverse TC transport through HDL-C particles; induction of LDL-C-receptor expression; and inhibition of ApoB100 expression [38]. Meta-analyses of RCTs reported that curcumin supplementation showed benefits on lipid metabolism in patients with type 2 diabetes [39], polycystic ovary syndrome [14], and nonalcoholic fatty liver disease [40]. Our findings demonstrated a remarkable reduction in the TC level after curcumin administration in patients with DKD. However, the results should be interpreted with caution owing to the limited number of studies, and larger-scale trials are required to verify the results.

Hypertension is also closely associated with CKD development and progression [1]. It has been demonstrated that a 10–20 mmHg increase in SBP increases the risk of DKD by 21% [41]. Therefore, reducing BP, particularly SBP, can help decrease the risk of DKD. The effect of curcumin supplementation on BP is not fully conclusive. Damoon et al. reported that the hypotensive effect of nanocurcumin on cardiovascular disease is mainly focused on decreasing SBP [42]. Amir et al. observed favourable effects of curcumin administration only on SBP levels in different participants with a ≥12-week follow-up [43]. In contrast, Maryam et al. observed that curcumin supplementation improved DBP in participants with metabolic syndrome; however, it was not associated with a change in SBP [44]. The result of the present meta-analysis indicated that curcumin administration had a prominent effect on SBP in patients with DKD. We speculate that the discrepancy in the effects of curcumin supplementation on BP may be associated with differences in participants and follow-up periods across studies. A few potential mechanisms have been proposed to explain the beneficial effects of curcumin on BP. Curcumin prevents the development of hypertension by downregulating angiotensin II type-1 receptor (AT1R) expression to alleviate AT1R-mediated vasoconstriction [45]. In addition, curcumin inhibits vascular smooth muscle cell (VSMC) migration by inhibiting NF-κB-mediated NLRP3 expression in angiotensin II-treated VSMCs [46].

Hyperglycemia is also identified as an important factor for CKD development beyond its links to lipid accumulation and hypertension [1]. Intensive glycemic therapy, such as controlling the haemoglobin A1c levels within 6.5–7.0%, contributes to reducing the risk of DKD [47]. Evidence from both in vivo and vitro studies indicated a strong potential effect of curcumin against insulin resistance and diabetes [48, 49]. Previous meta-analyses showed that curcumin significantly improved FBG levels in individuals with polycystic ovary syndrome [14], some degree of dysglycemia [50], and metabolic syndrome [44]. Consistent with these findings, we also observed conspicuous effects of curcumin supplementation on FBG levels in patients with DKD, adding to the existing evidence on the benefits of curcumin in improving FBG. However, there is no evidence about the impact of curcumin supplementation on other glycemic parameters, such as haemoglobin A1c, serum insulin, and homeostasis model assessment-insulin resistance index in the included trials. Large-scale studies focusing on these topics are needed in the future.

4.1. Strengths and Limitations

To our knowledge, this is the first meta-analysis of RCTs to assess the effects of curcumin supplementation on DKD and to provide evidence for curcumin as a promising agent in the treatment of this condition. We conducted the current study strictly according to the PRISMA guidelines and observed significant effects of curcumin on SCr, TC, SBP, and FBG levels. Furthermore, we evaluated the certainty of the evidence for outcomes using the GRADE method. The evidence for SCr, TC, SBP, and FBG was graded as having moderate certainty.

Several limitations should be considered when interpreting our findings. First, the sample sizes and the number of trials that were eligible for inclusion were small. Second, various dosages and durations of treatment were applied for the intervention. Third, the adverse effects of curcumin require attention; however, it is difficult to assess the safety of curcumin owing to the limited number of reports on its potential adverse effects. Finally, three (60%) trials did not provide adequate information on randomization methods and four (80%) trials did not perform blinding of outcomes, which may have reduced the quality of the evidence of the studies.

4.2. Implications for Practice

According to the available evidence from this meta-analysis, curcumin supplementation has beneficial effects on SCr, TC, SBP, and FBG levels, with moderate certainty, in patients with DKD and seems to be a promising agent against DKD. Nevertheless, our results should be interpreted with caution considering the above-mentioned limitations.

4.3. Implications for Research

As the results of meta-analyses are closely related to evidence-based treatment decisions in the clinic, rigorously designed studies are highly warranted. Large-sample, multicentre, high-quality, and well-designed clinical trials should be registered to ensure the transparency of the process and improve the methodological quality. Moreover, future studies should also focus on adverse effects, apart from efficacy, to evaluate the safety of curcumin.

5. Conclusions

In conclusion, the current study shows that curcumin supplementation provides evident improvements in the SCr, TC, DBP, and FBG levels in patients with DKD, with moderate certainty of evidence. However, although curcumin supplementation has great potential effects on DBP and FBG, the results should be interpreted with caution because of the poor robustness of the evidence. The effect of curcumin supplementation on DKD should be confirmed by more large-scale and high-quality RCTs.

Data Availability

The data used to support the findings of this study are included within the article and in the Supplementary Materials.

Disclosure

Zhao Jie and Mo Chao are co-first authors.

Conflicts of Interest

The authors declare that there are no conflicts of interest.

Authors’ Contributions

Z.J., M.C., and A.J. conceptualized and designed the study; Z.J. and M.C. developed the methodology; Z.J. and M.C. performed data extraction; S.W. and M.L.F. performed statistical analyses and data interpretation; Z.J. and M.C. drafted the manuscript; and A.J. reviewed and edited the article. All the authors approved the final manuscript for submission. Zhao Jie and Mo Chao contributed equally to this work.

Acknowledgments

This research was funded by the National Natural Science Foundation of China (no. 81860838). Shi Wei’s Studio for the Heritage of Famous Traditional Chinese Medicine Practitioners (no. 2017 [11]), Guangxi First-class Discipline: Traditional Chinese Medicine (Scientific Research of Guangxi Education Department [2018] no. 12), and Youth Fund Project of Guangxi University of Traditional Chinese Medicine (no. 2019QN018).

Supplementary Materials

Table S1: PRISMA 2020 Checklist. Table S2: search strategies of the database. Table S3: Begg’s test and Egger’s test of curcumin supplementation on outcomes. (Supplementary Materials)

References

  1. M. C. Thomas, M. Brownlee, K. Susztak et al., “Diabetic kidney disease,” Nature Reviews Disease Primers, vol. 1, no. 1, p. 15018, 2015. View at: Publisher Site | Google Scholar
  2. I. D. Federation, “International diabetes federation diabetes atlas,” 2019, https://www.idf.org/. View at: Google Scholar
  3. P. Fioretto, R. Vettor, and R. Pontremoli, “SGLT2 inhibitors to prevent diabetic kidney disease,” The Lancet Diabetes & Endocrinology, vol. 8, no. 1, pp. 4-5, 2020. View at: Publisher Site | Google Scholar
  4. M. Maqbool, M. E. Cooper, and K. A. M. Jandeleit-Dahm, “Cardiovascular disease and diabetic kidney disease,” Seminars in Nephrology, vol. 38, no. 3, pp. 217–232, 2018. View at: Publisher Site | Google Scholar
  5. N. M. Selby and M. W. Taal, “An updated overview of diabetic nephropathy: diagnosis, prognosis, treatment goals and latest guidelines,” Diabetes, Obesity and Metabolism, vol. 22, no. Suppl 1, pp. 3–15, 2020. View at: Publisher Site | Google Scholar
  6. N. K. Foundation, “KDOQI clinical practice guideline for diabetes and CKD: 2012 update,” American Journal of Kidney Diseases, vol. 60, no. 5, pp. 850–886, 2012. View at: Google Scholar
  7. B. L. Neuen, T. Young, H. J. L. Heerspink et al., “SGLT2 inhibitors for the prevention of kidney failure in patients with type 2 diabetes: a systematic review and meta-analysis,” The Lancet Diabetes & Endocrinology, vol. 7, no. 11, pp. 845–854, 2019. View at: Publisher Site | Google Scholar
  8. G. P. Fadini, B. M. Bonora, and A. Avogaro, “SGLT2 inhibitors and diabetic ketoacidosis: data from the FDA adverse event reporting system,” Diabetologia, vol. 60, no. 8, pp. 1385–1389, 2017. View at: Publisher Site | Google Scholar
  9. D. De Zeeuw and H. J. L. Heerspink, “Unmet need in diabetic nephropathy: failed drugs or trials?” The Lancet Diabetes & Endocrinology, vol. 4, no. 8, pp. 638–640, 2016. View at: Publisher Site | Google Scholar
  10. K. Balachandran and J. Stebbing, “Turmeric: a spice for life?” The Lancet Oncology, vol. 17, no. 12, p. 1639, 2016. View at: Publisher Site | Google Scholar
  11. H. A. Zhang and D. D. Kitts, “Turmeric and its bioactive constituents trigger cell signaling mechanisms that protect against diabetes and cardiovascular diseases,” Molecular and Cellular Biochemistry, vol. 476, pp. 1–30, 2021. View at: Publisher Site | Google Scholar
  12. T. Ahmed and A.-H. Gilani, “Therapeutic potential of turmeric in Alzheimer’s disease: curcumin or curcuminoids?” Phytotherapy Research, vol. 28, no. 4, pp. 517–525, 2014. View at: Publisher Site | Google Scholar
  13. A. Memarzia, M. R. Khazdair, S. Behrouz et al., “Experimental and clinical reports on anti‐inflammatory, antioxidant, and immunomodulatory effects of Curcuma longa and curcumin, an updated and comprehensive review,” BioFactors, vol. 47, no. 3, pp. 311–350, 2021. View at: Publisher Site | Google Scholar
  14. Y. J. Chien, C. Y. Chang, M. Y. Wu, C. H. Chen, Y. S. Horng, and H. C. Wu, “Effects of curcumin on glycemic control and lipid profile in polycystic ovary syndrome: systematic review with meta-analysis and trial sequential analysis,” Nutrients, vol. 13, no. 2, 2021. View at: Publisher Site | Google Scholar
  15. A. F. G. Cicero, A. Sahebkar, F. Fogacci, M. Bove, M. Giovannini, and C. Borghi, “Effects of phytosomal curcumin on anthropometric parameters, insulin resistance, cortisolemia and non-alcoholic fatty liver disease indices: a double-blind, placebo-controlled clinical trial,” European Journal of Nutrition, vol. 59, no. 2, pp. 477–483, 2020. View at: Publisher Site | Google Scholar
  16. J. Z. ALTamimi, N. A. AlFaris, A. M. Al-Farga, G. M. Alshammari, M. N. BinMowyna, and M. A. Yahya, “Curcumin reverses diabetic nephropathy in streptozotocin-induced diabetes in rats by inhibition of PKCβ/p(66) Shc axis and activation of FOXO-3a,” The Journal of Nutritional Biochemistry, vol. 87, p. 108515, 2021. View at: Google Scholar
  17. M. Lu, N. Yin, W. Liu, X. Cui, S. Chen, and E. Wang, “Curcumin ameliorates diabetic nephropathy by suppressing NLRP3 inflammasome signaling,” BioMed Research International, vol. 2017, Article ID 1516985, 2017. View at: Publisher Site | Google Scholar
  18. W. Wu, H. Geng, Z. Liu, H. Li, and Z. Zhu, “Effect of curcumin on rats/mice with diabetic nephropathy: a systematic review and meta-analysis of randomized controlled trials,” Journal of Traditional Chinese Medicine, vol. 34, no. 4, pp. 419–429, 2014. View at: Publisher Site | Google Scholar
  19. R. Shafabakhsh, Z. Asemi, Z. Reiner, A. Soleimani, E. Aghadavod, and F. Bahmani, “The effects of nano-curcumin on metabolic status in patients with diabetes on hemodialysis, a randomized, double blind, placebo-controlled trial,” Iranian Journal of Kidney Diseases, vol. 14, no. 4, pp. 290–299, 2020. View at: Google Scholar
  20. A. S. Jiménez-Osorio, W. R. García-Niño, S. González-Reyes et al., “The effect of dietary supplementation with curcumin on redox status and Nrf2 activation in patients with nondiabetic or diabetic proteinuric chronic kidney disease: a pilot study,” Journal of Renal Nutrition, vol. 26, no. 4, pp. 237–244, 2016. View at: Google Scholar
  21. P. Khajehdehi, M. Pakfetrat, K. Javidnia et al., “Oral supplementation of turmeric attenuates proteinuria, transforming growth factor-β and interleukin-8 levels in patients with overt type 2 diabetic nephropathy: a randomized, double-blind and placebo-controlled study,” Scandinavian Journal of Urology and Nephrology, vol. 45, no. 5, pp. 365–370, 2011. View at: Publisher Site | Google Scholar
  22. A. Vanaie, S. Shahidi, B. Iraj et al., “Curcumin as a major active component of turmeric attenuates proteinuria in patients with overt diabetic nephropathy,” Journal of Research in Medical Sciences: The Official Journal of Isfahan University of Medical Sciences, vol. 24, p. 77, 2019. View at: Publisher Site | Google Scholar
  23. A. P. H. Martinez, Y. Cheng, A. Gindl-Bracho et al., “Effect of oral supplementation with curcumin in diabetic subjects with proteinuric kidney disease: a randomized controlled trial,” Journal of the American Society of Nephrology, vol. 31, p. 351, 2020. View at: Google Scholar
  24. M. J. Page, J. E. McKenzie, P. M. Bossuyt et al., “The PRISMA 2020 statement: an updated guideline for reporting systematic reviews,” BMJ, vol. 372, p. n71, 2021. View at: Publisher Site | Google Scholar
  25. M. E. Molitch, A. I. Adler, A. Flyvbjerg et al., “Diabetic kidney disease: a clinical update from kidney disease: improving global outcomes,” Kidney International, vol. 87, no. 1, pp. 20–30, 2015. View at: Publisher Site | Google Scholar
  26. J. P. T. Higgins, D. G. Altman, P. C. Gotzsche et al., “The Cochrane Collaboration's tool for assessing risk of bias in randomised trials,” BMJ, vol. 343, no. oct18 2, p. d5928, 2011. View at: Publisher Site | Google Scholar
  27. D. Follmann, P. Elliott, I. Suh, and J. Cutler, “Variance imputation for overviews of clinical trials with continuous response,” Journal of Clinical Epidemiology, vol. 45, no. 7, pp. 769–773, 1992. View at: Publisher Site | Google Scholar
  28. J. Bowden, J. F. Tierney, A. J. Copas, and S. Burdett, “Quantifying, displaying and accounting for heterogeneity in the meta-analysis of RCTs using standard and generalised Qstatistics,” BMC Medical Research Methodology, vol. 11, no. 1, p. 41, 2011. View at: Publisher Site | Google Scholar
  29. C. B. Begg and J. A. Berlin, “Publication bias and dissemination of clinical research,” JNCI Journal of the National Cancer Institute, vol. 81, no. 2, pp. 107–115, 1989. View at: Publisher Site | Google Scholar
  30. G. H. Guyatt, A. D. Oxman, G. E. Vist et al., “GRADE: an emerging consensus on rating quality of evidence and strength of recommendations,” BMJ, vol. 336, no. 7650, pp. 924–926, 2008. View at: Publisher Site | Google Scholar
  31. C.-y. Hsu, V. M. Chinchilli, S. Coca et al., “Post-acute kidney injury proteinuria and subsequent kidney disease progression,” JAMA Internal Medicine, vol. 180, no. 3, pp. 402–410, 2020. View at: Publisher Site | Google Scholar
  32. O. Buyadaa, D. J. Magliano, A. Salim, D. N. Koye, and J. E. Shaw, “Risk of rapid kidney function decline, all-cause mortality, and major cardiovascular events in nonalbuminuric chronic kidney disease in type 2 diabetes,” Diabetes Care, vol. 43, no. 1, pp. 122–129, 2020. View at: Publisher Site | Google Scholar
  33. P. L. Drury, R. Ting, D. Zannino et al., “Estimated glomerular filtration rate and albuminuria are independent predictors of cardiovascular events and death in type 2 diabetes mellitus: the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) study,” Diabetologia, vol. 54, no. 1, pp. 32–43, 2011. View at: Publisher Site | Google Scholar
  34. M. Bagherniya, D. Soleimani, M. H. Rouhani, G. Askari, T. Sathyapalan, and A. Sahebkar, “The use of curcumin for the treatment of renal disorders: a systematic review of randomized controlled trials,” Studies on Biomarkers and New Targets in Aging Research in Iran, vol. 1291, pp. 327–343, 2021. View at: Publisher Site | Google Scholar
  35. A. Falkevall, A. Mehlem, I. Palombo et al., “Reducing VEGF-B signaling ameliorates renal lipotoxicity and protects against diabetic kidney disease,” Cell Metabolism, vol. 25, no. 3, pp. 713–726, 2017. View at: Publisher Site | Google Scholar
  36. N. Tolonen, C. Forsblom, V.-P. Mäkinen et al., “Different lipid variables predict incident coronary artery disease in patients with type 1 diabetes with or without diabetic nephropathy: the FinnDiane study,” Diabetes Care, vol. 37, no. 8, pp. 2374–2382, 2014. View at: Publisher Site | Google Scholar
  37. Z. H. Xia, W. B. Chen, L. Shi et al., “The underlying mechanisms of curcumin inhibition of hyperglycemia and hyperlipidemia in rats fed a high-fat diet combined with STZ treatment,” Molecules, vol. 25, no. 2, 2020. View at: Publisher Site | Google Scholar
  38. Y. Panahi, Y. Ahmadi, M. Teymouri, T. P. Johnston, and A. Sahebkar, “Curcumin as a potential candidate for treating hyperlipidemia: a review of cellular and metabolic mechanisms,” Journal of Cellular Physiology, vol. 233, no. 1, pp. 141–152, 2018. View at: Publisher Site | Google Scholar
  39. E. Altobelli, P. M. Angeletti, C. Marziliano, M. Mastrodomenico, A. R. Giuliani, and R. Petrocelli, “Potential therapeutic effects of curcumin on glycemic and lipid profile in uncomplicated type 2 diabetes-A meta-analysis of randomized controlled trial,” Nutrients, vol. 13, no. 2, 2021. View at: Publisher Site | Google Scholar
  40. Z. Wei, N. Liu, X. Tantai et al., “The effects of curcumin on the metabolic parameters of non-alcoholic fatty liver disease: a meta-analysis of randomized controlled trials,” Hepatology International, vol. 13, no. 3, pp. 302–313, 2019. View at: Publisher Site | Google Scholar
  41. W. Jiang, J. Wang, X. Shen et al., “Establishment and validation of a risk prediction model for early diabetic kidney disease based on a systematic review and meta-analysis of 20 cohorts,” Diabetes Care, vol. 43, no. 4, pp. 925–933, 2020. View at: Publisher Site | Google Scholar
  42. D. Ashtary-Larky, M. Rezaei Kelishadi, R. Bagheri et al., “The effects of nano-curcumin supplementation on risk factors for cardiovascular disease: a GRADE-assessed systematic review and meta-analysis of clinical trials,” Antioxidants, vol. 10, no. 7, 2021. View at: Publisher Site | Google Scholar
  43. A. Hadi, M. Pourmasoumi, E. Ghaedi, and A. Sahebkar, “The effect of Curcumin/Turmeric on blood pressure modulation: a systematic review and meta-analysis,” Pharmacological Research, vol. 150, p. 104505, 2019. View at: Publisher Site | Google Scholar
  44. M. Azhdari, M. Karandish, and A. Mansoori, “Metabolic benefits of curcumin supplementation in patients with metabolic syndrome: a systematic review and meta‐analysis of randomized controlled trials,” Phytotherapy Research, vol. 33, no. 5, pp. 1289–1301, 2019. View at: Publisher Site | Google Scholar
  45. Y. Yao, W. Wang, M. Li et al., “Curcumin exerts its anti-hypertensive effect by down-regulating the AT1 receptor in vascular smooth muscle cells,” Scientific Reports, vol. 6, no. 1, p. 25579, 2016. View at: Publisher Site | Google Scholar
  46. Y. Han, H.-J. Sun, Y. Tong et al., “Curcumin attenuates migration of vascular smooth muscle cells via inhibiting NFκB-mediated NLRP3 expression in spontaneously hypertensive rats,” The Journal of Nutritional Biochemistry, vol. 72, p. 108212, 2019. View at: Publisher Site | Google Scholar
  47. M. S. Kirkman, H. Mahmud, and M. T. Korytkowski, “Intensive blood glucose control and vascular outcomes in patients with type 2 diabetes mellitus,” Endocrinology and Metabolism Clinics of North America, vol. 47, no. 1, pp. 81–96, 2018. View at: Publisher Site | Google Scholar
  48. D. J. Den Hartogh, A. Gabriel, and E. Tsiani, “Antidiabetic properties of curcumin II: evidence from in vivo studies,” Nutrients, vol. 12, no. 1, 2019. View at: Publisher Site | Google Scholar
  49. D. J. Den Hartogh, A. Gabriel, and E. Tsiani, “Antidiabetic properties of curcumin I: evidence from in vitro studies,” Nutrients, vol. 12, no. 1, 2020. View at: Publisher Site | Google Scholar
  50. I. S. V. D. Melo, A. F. D. Santos, and N. B. Bueno, “Curcumin or combined curcuminoids are effective in lowering the fasting blood glucose concentrations of individuals with dysglycemia: systematic review and meta-analysis of randomized controlled trials,” Pharmacological Research, vol. 128, pp. 137–144, 2018. View at: Publisher Site | Google Scholar

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