The effect of coenzyme Q10 supplementation on oxidative stress: A systematic review and meta-analysis of randomized controlled clinical trials.
Zohreh Sadat SangsefidiFatemeh YaghoubiSalimeh HajiahmadiMahdieh HosseinzadehPublished in: Food science & nutrition (2020)
Some evidence exists in supporting the beneficial effects of coenzyme Q10 (CoQ10) on oxidative stress. Since the findings of studies over the impact of CoQ10 supplementation on oxidative stress are contradictory, this study was conducted. The aim was to evaluate CoQ10 supplementation effect on total antioxidant capacity (TAC), malondialdehyde (MDA), glutathione peroxidase (GPx), superoxide dismutase (SOD), and catalase (CAT) levels using data collected from randomized controlled trials (RCTs). Several databases including PubMed, Web of Science, Google Scholar, and Scopus were comprehensively searched up to 23 January 2019 to identify RCTs. A random-effects model, standardized mean difference (SMD), and 95% confidence interval (CI) were applied for data analysis. According to the meta-analysis results on 19 eligible studies, CoQ10 increased the levels of TAC (SMD = 1.29; 95% CI = 0.35-2.23; p = .007), GPX (SMD = 0.45; 95% CI = 0.17-0.74; p = .002), SOD (SMD = 0.63; 95% CI = 0.29-0.97; p < .0001), and CAT (SMD = 1.67; 95% CI = 0.29-3.10; p = .018) significantly. This supplementation also caused a significant reduction in MDA levels (SMD = -1.12; 95% CI = -1.58 to -0.65; p < .0001). However, the results of SOD and CAT should be stated carefully due to the publication bias. In conclusion, this research indicated that CoQ10 supplementation had beneficial effects on oxidative stress markers. However, further studies are needed to confirm these findings.
Keyphrases
- oxidative stress
- data analysis
- case control
- systematic review
- clinical trial
- dna damage
- diabetic rats
- ischemia reperfusion injury
- amyotrophic lateral sclerosis
- induced apoptosis
- randomized controlled trial
- meta analyses
- phase ii
- breast cancer cells
- machine learning
- nitric oxide
- heat shock
- deep learning
- study protocol
- endoplasmic reticulum stress
- neural network