Effects of coenzyme Q10 administration on blood pressure and heart rate in adults: A systematic review and meta-analysis of randomized controlled trials

Abstract

Background and objective

Coenzyme Q10 is a naturally occurring antioxidant that has been suggested to improve cardiovascular health. Studies examining the effects of Q10 on blood pressure (BP) and heart rate (HR) have found inconsistent results. This meta-analysis aims to clarify the effects of Q10 administration on BP and HR in adults.

Methods

A comprehensive search of online databases was conducted until February 2025 to identify relevant randomized controlled trials (RCTs). Following screening, relevant data were extracted from the eligible studies. Statistical analyses were conducted using weighted mean differences (WMD) with 95 % confidence intervals (CI). Data analysis was performed using the "meta" package in R.

Results

The pooled analysis of 45 RCTs (48 effect sizes) showed that Q10 administration significantly reduced systolic BP (WMD: −3.44 mmHg; 95 %CI: [-5.13 to −1.55], p < 0.01), while no significant effect was observed on diastolic BP (WMD: −1.13 mmHg; 95 %CI: [-2.16 – 0.50], p = 0.23) and HR (WMD: −0.10 bpm; 95 %CI: [-2.09 – 1.89], p = 0.44). Subgroup analysis indicated that lower doses (<200 mg/day) and longer interventions (>8 weeks) resulted in greater systolic BP reductions.

Conclusion

This meta-analysis indicates that CoQ10 supplementation may be an effective adjunctive therapy for reducing systolic blood pressure, especially at doses below 200 mg/day and with longer treatment durations. However, its impact on diastolic blood pressure and heart rate appears minimal. Given its favorable safety profile, CoQ10 could be considered as a supportive option in the management of hypertension, particularly for patients seeking non-pharmacological interventions or those with mild elevations in systolic BP.

1. Introduction

Cardiovascular diseases (CVD) are the most common non-communicable conditions and the leading cause of mortality and morbidity worldwide [1], which are reported to account for approximately 20 million (34 %) global deaths each year [2]. Blood pressure (BP) and heart rate (HR) are two important factors in cardiovascular health [3], and a disturbance in each of these factors leads to an increase in the risk of CVD. BP control to guideline-recommended target levels is frequently not achieved, even with the use of various treatment modalities [4] While lifestyle modification and many pharmaceutical interventions have been effective in correcting these factors, there has recently been a growing interest in alternative, complementary, and natural treatments or combined therapies, including dietary supplements [5,6].

For decades, nutritional strategies to reduce the risk of CVD have attracted much attention [[7], [8], [9]]. Coenzyme Q10 (CoQ10), also known as ubiquinone, is a multi-functional, fat-soluble, vitamin-like, non-essential nutrient [10], which is located in the inner mitochondrial membrane and serves as a key player in the normal functioning of cells, and plays a vital role in the production of cellular energy by helping to produce ATP in the electron transport chain [11,12]. In addition to its role in providing cellular energy, CoQ10 has antioxidant properties that protect cell/subcellular organelle membranes against oxidative damage caused by free radicals [11,13]. CoQ10 occurs naturally mainly from endogenous synthesis in the body, although it can also be obtained through diet or supplements [14]. In general, the human body cannot synthesize a sufficient amount of CoQ10 in some pathological conditions, such as high BP [15], so the use of additional CoQ10 administration may be effective in correcting the deficiency in these conditions.

Several randomized controlled trials (RCTs) have suggested that CoQ10 administration has beneficial effects on systolic BP and diastolic BP, including several previous meta-analyses of RCTs, which have shown that significantly reduces systolic BP among people taking CoQ10 compared to a control group [[16], [17], [18]]. However, a previous meta-analysis study with an insufficient sample size failed to show beneficial effects and demonstrated that this coenzyme did not have any effect on systolic BP and diastolic BP [19]. Also, the effect of CoQ10 on HR has been reported differently in different populations, leading to questions about its efficacy and mechanisms of action [20,21]. This inconsistency in the findings suggests that the role of CoQ10 in cardiovascular function and other factors is still controversial. Finally, considering that no study has simultaneously investigated the effect of CoQ10 on both BP and HR factors in the general population in these dimensions, the information gap has limited the use of CoQ10 supplements in controlling CVD-related factors such as BP and HR.

Due to the increasing prevalence of BP and cardiometabolic disorders and the contradictions among the findings of original RCT studies, we conducted this systematic review and meta-analysis to systematically evaluate the existing literature on CoQ10 administration and determine its overall effectiveness in reducing BP levels and modulating HR among different populations. In addition, the current study seeks to identify moderating factors, such as supplement dosage, duration of use, and characteristics that may influence outcomes.

2. Methods

2.1. Study design and protocol

This study adhered to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to ensure transparency and methodological rigor [22]. The protocol was registered in the PROSPERO database under registration number CRD42025647807.

2.2. Search strategy

A comprehensive systematic search was conducted across medical databases, including PubMed, Web of Science, and Scopus, to identify randomized controlled trials (RCTs) evaluating the effects of CoQ10 administration on BP and HR in adults up to February 2025 without restrictions on language or publication date. The search strategy employed a combination of Medical Subject Headings (MeSH) terms, synonyms, keywords, and Boolean operators within the "Title & Abstract" field, using the following terms: (“Q10” OR “Q-10” OR “Q-ter” OR “CoQ10” OR “coenzyme-Q″ OR “Coenzyme Q-10” OR “Coenzyme Q10” OR “Ubiquinol” OR “ubidecarenone” OR “ubiquinone” OR “ubisemiquinone” OR “Bio-quinone”) AND (“blood pressure” OR “systolic” OR “diastolic” OR “BP” OR “SBP” OR “DBP” OR “pulse pressure” OR “heart rate” OR “pulse rate”). The detailed search strategy and specific search strings for each database are provided in the Supplementary File. Additionally, a manual review of reference lists from selected studies and an extended search on Google Scholar were conducted to identify any additional relevant studies, ensuring a comprehensive and exhaustive literature search.

2.3. Eligibility criteria

Studies were included if they met the following criteria: [1]: randomized controlled trials (RCTs) investigating the effects of CoQ10 administration on BP and HR in adults; [2]; participants aged 18 years or older, with or without hypertension; [3]; interventions involving any form, dosage, and duration of CoQ10 administration compared to a placebo or control group; [4]; outcomes reporting at least one measure of systolic and diastolic BP, and heart rate; and [5] published in any language and any publication year. Observational studies, reviews, meta-analyses, animal studies, in vitro research, and studies lacking relevant outcome measures were excluded.

Studies were excluded if they met any of the following criteria: [1]: not a randomized controlled trial (e.g., observational studies, case reports, reviews, or meta-analyses); [2]; did not investigate the effects of CoQ10 administration on BP; [3]; included participants younger than 18 years; [4]; lacked a placebo or control group for comparison; [5]; did not report relevant outcomes; [6]; focused on animal or in vitro studies; or [7] were conference abstracts, editorials, letters, or unpublished dissertations.

2.4. Study selection process

The study selection process involved several stages to ensure the inclusion of relevant studies. First, duplicates were removed from the initial search results. Then, titles and abstracts were screened independently by two reviewers (S.P. and M.K.) to identify studies that potentially met the inclusion criteria. Full-text articles of selected studies were subsequently assessed for eligibility based on the predefined inclusion and exclusion criteria. Disagreements between reviewers during the screening and eligibility assessment phases were resolved through discussion or consultation with a third reviewer (S.M.A.P). Studies that met all inclusion criteria and did not fall under any exclusion criteria were included in the final analysis. The entire selection process was conducted systematically, with detailed documentation of each step.

2.5. Data extraction

Data extraction was independently performed by two reviewers (M.K. and S.P.), who carefully examined the selected studies and gathered all pertinent information. In cases of disagreements about data relevance or interpretation, a third reviewer (S.M.A.P) was consulted to reach a consensus and ensure accuracy. The extracted data were systematically organized in an Excel spreadsheet to maintain consistency and order. The collected data included the first author's name, publication year, study location, trial design, sample size, mean age, body mass index (BMI), gender distribution, type of intervention, dosage, study duration, and participants' overall health status. Additionally, systolic and diastolic BP values and standard deviations were recorded. This structured approach enabled a clear and thorough synthesis of the data for subsequent analysis.

2.6. Quality assessment

The quality assessment of the included studies was conducted using the Cochrane Risk of Bias 2 (RoB-2) tool, which evaluates the risk of bias across five domains: randomization process, deviations from intended interventions, missing outcome data, measurement of the outcome, and selection of the reported result. Each study was classified as having a low, some concerns, or high risk of bias based on predefined criteria [23]. This systematic approach ensured a rigorous assessment of the study's reliability and validity in the meta-analysis (Table 3).

Table 3.

The findings of meta-regression analysis.

Variables	Predictor variable	Heterogeneity accounted for	Residual heterogeneity (I2)	Test of moderator (P-value)
SBP	Publication year	3.99 %	87.30 %	0.28
	Sample size	0.0 %	89.17 %	0.43
	Dose	9.61 %	88.51 %	0.06
	Trial Duration	4.80 %	88.92 %	0.07
DBP	Publication year	0.45 %	90.29 %	0.42
	Sample size	0.0 %	91.68 %	0.44
	Dose	0.0 %	90.92 %	0.52
	Trial Duration	0.0 %	92.02 %	0.89
HR	Publication year	0.0 %	0.0 %	0.70
	Sample size	0.0 %	0.0 %	0.70
	Dose	0.0 %	0.0 %	0.52
	Trial Duration	0.0 %	0.0 %	0.34

(SBP: Systolic Blood pressure, DBP: diastolic blood pressure; HR: heart rate).

2.7. Statistical analysis

The difference between the mean of the baseline and endpoint variables in each arm was extracted, and the weighted mean differences (WMD) and standard deviation (SD) of the difference between the two arms were selected as the effect size [24]. In case that study did not directly report the difference between baseline and endpoint values, we calculate the change of mean and related SD using the following formula: SD change = square root [(SD baseline2 + SD final2) - (2 × 0.5 × SD baseline × SD final)] [25]. The WMDs were pooled using the random-effects model with restricted maximum likelihood estimation. Cochrane's Q statistic and Hedges I² estimation were used to evaluate the heterogeneity across the articles [26]. We classified the observed between-study heterogeneity based on the I² estimation into low (I² less than 25 %), moderate (I² between 25 % and 75 %), and high (I² more than 75 %) heterogeneity. Further subgroup analyses based on the dosage (≤200 mg and >200 mg), duration (≤8 weeks and >8 weeks), type of Q10 (pure and mixed), population (healthy and non-healthy), and study design (open-label and double-blind) were conducted. The risk of publication bias was assessed visually by funnel plots and statistically by Begg's [27] and Egger's [28] tests. If there was a high probability of publication bias, the trim-and-fill method was applied to address the potential bias and missing studies [29]. The meta-regression analysis was performed to investigate the impact of the year of publication, sample size, dosage, and duration of treatment on the pooled effect sizes. All statistical tests with a p-value less than 0.05 were considered significant. All analyses were conducted in R Statistical Software using the "meta" package (v4.4.2; R Core Team 2023).

3. Results

3.1. Study selection

The study selection process began with the identification of 3,249 records from databases, including PubMed (n = 641), Scopus (n = 1,752), and ISI Web of Science (n = 856). After removing 752 duplicate records, 2,497 records were screened based on titles and abstracts. A total of 3,179 records were excluded due to being review studies, non-human studies, or having irrelevant titles and abstracts. Following this, 70 full-text articles were assessed for eligibility, and 25 studies that did not meet the inclusion criteria were excluded. Ultimately, 45 RCTs were included in the systematic review and meta-analysis (20, 30–72) (Fig. 1).

Fig. 1.

PRISMA Flow chart of study selection for inclusion trials in the systematic review.

3.2. Study characteristics

The RCTs included in this meta-analysis were published between 1985 and 2024 and were conducted across various countries. Iran had the highest representation (n = 10) (46, 48, 50, 52–54, 64, 65, 71), followed by Australia (n = 7) (20, 35, 36, 38, 41, 56), Japan (n = 7) (30, 37, 40, 58), and Denmark (n = 5) (31, 33, 47, 55, 62) and other nations, including the United States, China, Iraq, and the United Kingdom. The study populations comprised individuals with various health conditions, including T2DM (n = 10) (31–33, 35, 36, 38, 39, 41, 50, 52, 53), cardiovascular disease (n = 4) (30, 42, 46, 47, 51, 56, 58), chronic kidney disease (n = 3) (20, 67), hypertension (n = 3) (20, 34, 44, 59, 64, 67), dyslipidemia (n = 5) (35, 36, 46, 61, 73) metabolic syndrome (n = 3), along with healthy participants (n = 7) (37, 45, 57). The majority of trials were double-blind RCTs (n = 41), with a smaller number of crossover (n = 4) and single-blind (n = 1) designs. The trial durations ranged from 12 h to 96 weeks, with the majority lasting 8–24 weeks (n = 30). CoQ10 administration was administered at doses ranging from 20 mg to 1200 mg per day (Table 1).

Table 1.

Basic characteristics of the included studies in the systematic review and meta-analysis.

Studies

Country

Study Design

Participant

Gender (M/F)

Sample size (Int./Cont.)

Trial Duration

Age (Int.)

Age (Cont.)

BMI (Int.)

BMI (Cont.)

Q10 (mg/day)

Control

Kamikawa et al. (1985) [1]

Japan

RCT, DB

CVD

M: 10

24 (12/12)

4 weeks

54.7 ± 9.39

55.5 ± 6.36

NR

NR

150

Placebo

F: 2

Andersen et al. (1997) [2]

Denmark

RCT, DB

D1DM

M: 19

34 (17/17)

12 weeks

35 ± 8.24

35.3 ± 9.89

23.5 ± 2.88

24 ± 2.47

100

Placebo

F: 15

Eriksson et al. (1999) [3]

Finland

RCT, DB

T2DM

NR

23 (12/11)

24 weeks

65 ± 17.32

64 ± 23.21

29 ± 14.54

29.8 ± 11.27

200

Placebo

Henriksen et al. (1999) [4]

Denmark

RCT, DB

D1DM

M: 19

34 (17/17)

12 weeks

35.5 ± 8.2

35.3 ± 10

23.5 ± 2.7

24.0 ± 2.6

100

Placebo

F: 15

Burke et al. (2001) [5]

America

RCT, DB

Isolated Systolic Hypertension

M: 39

71 (39/32)

12 weeks

69.7 ± 25.6

67.3 ± 19.23

24 ± 11.86

23 ± 12.44

120

Placebo

F: 32

Hodgson et al. (2002) [6]

Australia

RCT, DB

T2DM/Dyslipidemia

M: 30

37 (19/18)

12 weeks

52.3 ± 6.1

55.2 ± 9.75

NR

NR

200

Placebo

F: 7

Hodgson et al. (2002) [6]

Australia

RCT, DB

T2DM/Dyslipidemia

M: 31

37 (19/18)

12 weeks

51.7 ± 6.97

53.6 ± 10.18

NR

NR

200

Fenofibrate

F: 6

Playford et al. (2003) [7]

Australia

RCT, DB

T2DM/Dyslipidemia

M: 33

40 (20/20)

12 weeks

52.7 ± 6.25

54.7 ± 9.38

29.9 ± 3.13

30.9 ± 4.47

200

Placebo

F: 7

Playford et al. (2003) [7]

Australia

RCT, DB

T2DM/Dyslipidemia

M: 32

40 (20/20)

12 weeks

52.7 ± 8.04

53.5 ± 9.83

30.3 ± 4.02

30 ± 3.57

200

Fenofibrate

F: 8

Ikematsu et al. (2006) [8]

Japan

RCT, DB

Healthy

M: 20

41 (21/20)

4 weeks

NR

NR

NR

NR

300

Placebo

F: 21

Ikematsu et al. (2006) [8]

Japan

RCT, DB

Healthy

M: 20

42 (22/20)

4 weeks

NR

NR

NR

NR

600

Placebo

F: 22

Ikematsu et al. (2006) [8]

Japan

RCT, DB

Healthy

M: 31

42 (22/20)

4 weeks

NR

NR

NR

NR

900

Placebo

F: 11

Chew et al. (2008) [9]

Australia

RCT, DB

T2DM

M: 27

36 (16/20)

24 weeks

61.3 ± 4.1

62.4 ± 8.8

30.1 ± 4.6

30.7 ± 5.0

200

Placebo

F: 9

Chew et al. (2008) [9]

Australia

RCT, DB

T2DM

M: 26

38 (19/19)

24 weeks

63 ± 9.4

64.8 ± 7.3

30.1 ± 4.6

29.9 ± 5.6

200

Fenofibrate

F: 12

Lim et al. (2008) [10]

Singapore

RCT, DB

T2DM

M: 39

80 (40/40)

12 weeks

54 ± 9

53 ± 9

24.8 ± 5.5

25.2 ± 3.4

200

Placebo

F: 41

Mizuno et al. (2008) [11]

Japan

RCT, Crossover, DB

Healthy

M: 8

17

8 days

37.5 ± 9.9

37.5 ± 9.9

21.9 ± 4

21.9 ± 4

100 & 300

Placebo

F: 9

Hamilton et al. (2009) [12]

Australia

Crossover-DB

T2DM

M: NR

23 (NR)

12 weeks

68 ± 6

68 ± 6

29 ± 4

29 ± 4

200

Placebo

F: NR

Mori et al. (2009) [13]

Australia

RCT, DB

CKD

M: 25

36 (21/15)

8 weeks

55.4 ± 12.37

58.6 ± 10.06

26.6 ± 4.12

27.6 ± 6.58

200

Placebo

F: 11

Mori et al. (2009) [13]

Australia

RCT, DB

CKD

M: 29

38 (18/20)

8 weeks

56.9 ± 16.54

53.3 ± 14.31

27.9 ± 3.39

26.7 ± 5.36

200

Omega 3FA

F: 9

Lee et al. (2011) [14]

Korea

RCT, DB

Obese

M: 21

51 (26/25)

12 weeks

42.7 ± 11.3

42.5 ± 11.2

27.9 ± 2.3

27.6 ± 3.8

200

Placebo

F: 30

Dai et al. (2011) [15]

China

RCT, DB

CVD

M: 52

56 (28/28)

8 weeks

67.7 ± 9.4

70.1 ± 9.8

25.3 ± 3.2

24.7 ± 3.2

300

Placebo

F: 4

Young et al. (2012) [16]

New Zealand

RCT, Crossover, DB

Hypertensive/MetS

M: 15

30 (15/15)

12 weeks

64 ± 5.47

64 ± 5.47

32.1 ± 4.92

32.1 ± 4.92

200

Placebo

F: 15

Mortensen et al. (2014) [17]

Denmark

RCT, DB

Heart failure

M: 305

420 (202/218)

96 weeks

62.3 ± 12

62.3 ± 11

28 ± 5

28 ± 6

300

Placebo

F: 115

Mohseni et al. (2014) [18]

Iran

RCT, DB

Hyperlipidemia/MI

M: 39

52 (26/26)

12 weeks

60 ± 8

61 ± 7

25.91 ± 2.53

26 ± 3.34

200

Placebo

F: 13

Holloway et al. (2014) [19]

UK

RCT, Cross-over

Healthy

M: 10

23 (12/11)

3 weeks

48.5 ± 14.9

43.1 ± 15.5

24.3 ± 3.6

24.7 ± 4.6

300

Control + Trek

F: 13

Abdollahzad et al. (2015) [20]

Iran

RCT, DB

Rheumatoid arthritis

M: 6

45 (22/23)

8 weeks

48.77 ± 11.58

50.41 ± 11.28

NR

NR

100

Placebo

F: 39

Zhang et al. (2017) [21]

China

RCT, DB

Dyslipidemia

M: 32

101 (51/50)

24 weeks

51.78 ± 8.92

50.02 ± 10.91

25.23 ± 3.96

24.91 ± 3.32

120

Placebo

F: 69

Singh et al. (2018) [22]

India

RCT, DB

CVD

M: 45

55 (27/28)

24 weeks

48.5 ± 9.5

48.7 ± 9.3

NR

NR

120

Vitamin B

F: 10

Zarei et al. (2018) [23]

Iran

RCT, DB

T2DM

M: 0

68 (34/34)

12 weeks

53.1 ± 36.32

53.35 ± 38.24

36.44 ± 3.32

32.56 ± 3.55

100

Placebo

F: 68

Sedeh et al. (2018) [24]

Iran

RCT, DB

T2DM

M: 39

68 (34/34)

72 weeks

60.2 ± 11.4

54.3 ± 9.6

NR

NR

100

Placebo

F: 29

Suzuki et al. (2019) [25]

Japan

RCT, DB

Healthy

M: 17

41 (21/20)

12 weeks

67 ± 4.2

66.2 ± 3.2

24.2 ± 3.9

24.2 ± 3.2

150

Placebo

F: 24

Kuhlman et al. (2019) [26]

Denmark

RCT, DB

Simvastatin user

M: 22

35 (18/17)

8 weeks

62 ± 4.24

61 ± 8.24

27.7 ± 2.54

28.8 ± 2.88

400

Placebo

F: 13

Gholami et al. (2019) [27]

Iran

RCT, DB

T2DM

M: 0

68 (34/34)

12 weeks

52.97 ± 6.14

53.68 ± 6.74

29.3 ± 3.54

28.51 ± 3.07

100

Placebo

F: 70

Izadi et al. (2019) [28]

Iran

RCT, DB

PCOS

M: 0

43 (22/21)

8 weeks

27.64 ± 5.2

26 ± 4.53

28.97 ± 2.95

28.73 ± 3.39

200

Placebo

F: 43

Izadi et al. (2019) [28]

Iran

RCT, DB

PCOS

M: 0

43 (21/22)

8 weeks

28.33 ± 5.52

27.18 ± 5.77

29.28 ± 3.23

29.28 ± 4.24

200

Vit E

F: 43

Mortensen et al. (2019) [29]

Australia

RCT, DB

Heart failure

M: 177

231 (108/123)

96 weeks

65.7 ± 10

64 ± 12

29 ± 5

29 ± 7

300

Placebo

F: 54

Kawashima et al. (2020) [30]

Japan

RCT, Crossover, DB

Heart failure

M: 12

14 (5/9)

12 weeks

70 ± 9

70 ± 9

NR

NR

400

Placebo

F: 2

Yesser et al. (2021) [31]

Iraq

RCT

Dyslipidemia

NR

39 (20/19)

12 weeks

59.24 ± 5.57

58.11 ± 7.1

32.59 ± 4.59

30.52 ± 4.99

200

Atorvastatin

Farsi et al. (2021) [32]

Iraq

RCT, DB

Ulcerative colitis

M: 44

86 (43/43)

8 weeks

38.39 ± 8.79

40.18 ± 11.46

24.92 ± 3.43

25.41 ± 2.89

200

Placebo

F: 42

Dawood et al. (2021) [33]

Iraq

RCT

Prehypertensive

M: 30

50 (25/25)

12 weeks

NR

NR

NR

NR

200

Placebo

F: 20

Kunching et al. (2021) [34]

Thailand

RCT, DB

Overweight, obesity

NR

28 (14/14)

6 weeks

26.1 ± 2.7

24.5 ± 2.6

26.1 ± 2.3

25.7 ± 2

200

Placebo

Kunching et al. (2022) [35]

Thailand

RCT, DB

Trained men

M: 29

29 (15/14)

6 weeks

23.5 ± 8.13

22.8 ± 8.6

23.1 ± 1.54

22.8 ± 0.74

200

Maltodextrin

F: 0

Masoumi-Ardakani et al. (2022) [36]

Iran

RCT, DB

HTN

M: 26

26 (13/13)

6 weeks

49 ± 2.52

49 ± 2.52

27 ± 1.8

26 ± 1.8

20

Placebo

F: 0

Masoumi-Ardakani et al. (2022) [36]

Iran

RCT, DB

HTN

M: 26

26 (13/13)

6 weeks

47 ± 3.96

48 ± 3.24

27 ± 1.44

26 ± 1.44

20

ET

F: 0

Kuhlman et al. (2022) [37]

Denmark

RCT, DB

Simvastatin user

M: 19

19 (9/10)

8 weeks

56 ± 8

56 ± 9

28.6 ± 2.4

27.5 ± 2.2

400

Placebo + Simvastatin

F: 0

Sangouni et al. (2023) [38]

Iran

RCT, DB

MetS

M: 28

44 (22/22)

12 weeks

39 ± 4.5

39.5 ± 5

30.7 ± 4.9

30 ± 4.7

60

Placebo

F: 16

Elsharkawy et al. (2023) [39]

Egypt

RCT, SB

Acute aluminum phosphide poisoning

M: 17

56 (28/28)

12 h

NR

NR

NR

NR

1200

Coconut oil

F: 39

Kirkman et al. (2023) [40]

USA

RCT, DB

CKD

M: 15

18 (10/8)

4 weeks

61

64

NR

NR

20

Placebo

F: 3

Vrentzos et al. (2024) [41]

Greece

RCT, DB

MASLD

M: 33

60 (30/30)

24 weeks

51 ± 10

53 ± 11

32 ± 5.8

31.4 ± 4.4

240

Placebo

F: 27

Fogacci et al. (2024) [42]

Italy

RCT, DB

Statin-Associated Asthenia

M: 33

60 (30/30)

8 3weeks

74 ± 2

73 ± 3

24 ± 1

25 ± 1

300

Placebo

F: 27

Casagrande et al. (2024) [43]

Brazil

RCT, DB

NAFLD, MetS

M: 0

22 (11/11)

12 weeks

41.5 ± 5.94

38.8 ± 6.91

32.88 ± 5.5

36.93 ± 7.2

200

Placebo

F: 22

Kiani et al. (2024) [44]

Iran

RCT, DB

Burn patients

M: 42

60 (30/30)

10 days

34.9 ± 10.77

36.77 ± 11

26.23 ± 5.57

24.43 ± 3.51

300

Placebo

F: 18

Al-Thanoon et al. (2024) [45]

Iraq

RCT, DB

Pollution-exposed Workers

M: 131

132 (72/60)

8 weeks

42 ± 8

35 ± 5

29.11 ± 4.68

27.38 ± 4.69

200

Placebo

F: 0

(RCT: randomized controlled trial; PC: placebo-control; S: single-blind; DB: double-blind; M: male; F: female; Int. Intervention; Cont.: control; NAFLD: non-alcoholic fatty liver disease; CVD: cardiovascular disease; T1DM: type 1 diabetes Mellitus; T2DM: diabetes Mellitus; CKD: chronic kidney disease; HF: heart failure; MetS: metabolic syndrome; PCOS: polycystic ovary syndrome).

3.3. Risk of bias assessment

The findings of the RoB-2 revealed varying levels of bias across the included RCTs. While some studies demonstrated a low risk of bias in most domains, others showed concerns in specific areas. The most common issues were related to the randomization process, where some trials lacked proper allocation concealment, potentially introducing selection bias. Additionally, concerns were observed in deviations from the intended interventions, particularly in trials with inadequate blinding, which may have influenced the reported outcomes. Some studies also had missing outcome data, which could affect the reliability of the findings. Overall, while some trials maintained a low risk of bias, the presence of these concerns in others suggests that caution is needed when interpreting the results of the meta-analysis (Fig. 2).

Fig. 2.

Quality assessment of studies according to Cochrane risk-of-bias 2 (RoB-2).

3.4. Meta-analysis

3.4.1. Effects of CoQ10 on systolic BP

The pooled analysis of 43 RCTs comprising 48 effect sizes indicated that CoQ10 administration significantly reduced systolic BP by a WMD of −3.48 mmHg (95 % CI: −5.27 to −1.70, p < 0.01), though with substantial heterogeneity (I² = 87.5 %) (Fig. 3)

Fig. 3.

Forest plot demonstrating weighted mean difference (WMD) and 95 % confidence intervals (CIs) for the overall effect of Q10 administration on systolic blood pressure (mmHg) in adults.

The subgroup meta-analysis findings are presented in Table 2. Subgroup analysis based on administration dose revealed a more significant systolic BP reduction in dosage <200 mg/day (WMD = −6.05 mmHg, p = 0.03) compared to ≤ 200 (mg/day) (WMD: −2.72 mmHg, p < 0.01) (Fig. 4). The trials lasting longer than 8 weeks had a more significant systolic BP-lowering effect (WMD = −4.67 mmHg, 95 % CI: −7.32 to −2.01, p < 0.01) than shorter trials (≤8 weeks; p = 0.07) (Fig. 5). The findings of subgroup analysis based on health status revealed a significant improvement in systolic BP in patients with a pre-existing health condition compared to healthy individuals (Fig. 6). Administration with CoQ10 alone significantly lowered systolic BP levels compared to mixed formulation or MitoQ administration (Fig. 7). However, the considerable heterogeneity suggests that the findings should be interpreted cautiously Table 2.

Table 2.

Meta-analysis findings for the effects of Co-Q10 on blood pressure and heart rate.

Group	No. of ES	WMD	95 % CI	P value1	Heterogeneity (I2)	P value2
Systolic Blood Pressure (SBP) (mmHg)
Overall effects	48	−3.34	(-5.13 to −1.56)	< 0.01∗	87.5 %	<0.01
Dose
≤200 (mg/day)	13	−6.05	(-11.38 to −0.72)	0.03	80.0 %	<0.01
>200 (mg/day)	35	−2.72	(-4.34 to −1.09)	< 0.01∗	89.1 %	<0.01
Trial duration
≤8 weeks	19	−1.82	(-3.81 to −0.17)	0.07	58.1 %	<0.01
>8 weeks	29	−4.67	(-7.32 to −2.01)	< 0.01∗	82.8 %	<0.01
Health status
Non-healthy	41	−3.52	(-5.50 to −1.53)	< 0.01∗	74.4 %	<0.01
Healthy	7	−2.43	(-7.87 – 3.01)	0.32	89.2 %	<0.01
Type of Q10
Q10	38	−3.60	(-5.70 to −1.49)	< 0.01∗	88.8 %	<0.01
Mixed	9	−1.47	(-4.92 – 1.99)	0.36	6.0 %	0.39
MitoQ	1	−2.00	(-17.1 – 13.1)	0.50	87.0 %	<0.01
Diastolic Blood Pressure (DBP) (mmHg)
Overall effect	44	−0.83	(-2.16 – 0.50)	0.23	95.4 %	<0.01
Dose
≤200 (mg/day)	12	−1.14	(-4.11 – 1.83)	0.42	78.1 %	<0.01
>200 (mg/day)	32	−0.71	(-2.27 – 0.85)	0.36	96.5 %	<0.01
Trial duration
≤8 weeks	18	0.09	(-1.43 – 1.61)	0.90	82.5 %	<0.01
>8 weeks	26	−1.57	(-3.60 – 0.47)	0.13	96.5 %	<0.01
Health status
Non-healthy	36	−1.00	(-2.56 – 0.56)	0.20	91.9 %	<0.01
Healthy	8	−0.24	(-3.08 – 2.59)	0.84	96.8 %	<0.01
Type of Q10
Q10	35	−0.55	(-1.91 – 0.82)	0.42	96.1 %	<0.01
Mixed	8	−2.61	(-7.96 – 2.75)	0.29	76.1 %	<0.01
MitoQ	1	2	(-7.19 – 11.19)	0.58	95.0 %	<0.01
Heart Rate (HR) (bpm)
Overall effect	11	−0.10	(-2.09 – 1.89)	0.91	0.2 %	0.43
Dose
≤200 (mg/day)	3	3.52	(-13.22 – 20.25)	0.46	65.9 %	0.06
>200 (mg/day)	8	−0.73	(-1.96 – 0.50)	0.21	0.0 %	0.96
Trial duration
≤8 weeks	7	0.48	(-3.05 – 4.02)	0.75	28.3 %	0.21
>8 weeks	4	−0.77	(-3.43 – 1.89)	0.43	0.0 %	0.76
Health status
Non-healthy	8	0.55	(-2.35 – 3.44)	0.67	22.6 %	0.25
Healthy	3	−1.47	(-3.68 – 0.74)	0.10	0.0 %	0.92
Type of Q10
Q10	8	−0.68	(-1.86 – 0.50)	0.22	0.0 %	0.96
Mixed	2	−0.02	(-6.80 – 6.75)	0.97	0.0 %	0.87
MitoQ	1	–	–	–	–	–

1 p-value of MD between intervention and control groups of variables based on the random effect model.2 p-value of heterogeneity based on Cochran's Q.

(∗: Significant. WMD: weighted mean difference, ES: effect size.).

Fig. 4.

Forest plot demonstrating weighted mean difference (WMD) and 95 % confidence intervals (CIs) for the subgroup analysis based on the dose (≤200 vs. >200 mg) of Q10 administration on systolic blood pressure (mmHg) in adults.

Fig. 5.

Forest plot demonstrating weighted mean difference (WMD) and 95 % confidence intervals (CIs) for the subgroup analysis based on the trial duration (≤8 vs. >8 weeks) of Q10 administration on systolic blood pressure (mmHg) in adults.

Fig. 6.

Forest plot demonstrating weighted mean difference (WMD) and 95 % confidence intervals (CIs) for the subgroup analysis based on the health status (healthy vs. patients) of Q10 administration on systolic blood pressure (mmHg) in adults.

Fig. 7.

Forest plot demonstrating weighted mean difference (WMD) and 95 % confidence intervals (CIs) for the subgroup analysis based on the type of Q10 administration (CoQ10 vs. mixed vs. MitoQ) on systolic blood pressure (mmHg) in adults.

3.4.2. Effects of CoQ10 on diastolic BP

The pooled analysis of data from 40 RCTs, including 44 effect sizes, revealed a slight nonsignificant reduction in diastolic BP after Q10 administration (WMD: −0.83 mmHg; 95 % CI: −2.16, to 0.49; p = 0.23; I² = 95.4 %) (Fig. 8, Table 2).

Fig. 8.

Forest plot demonstrating weighted mean difference (WMD) and 95 % confidence intervals (CIs) for the overall effect of Q10 administration on diastolic blood pressure (mmHg) in adults.

Subgroup analysis based on dosage of administration revealed a stronger diastolic BP-lowering effect at doses less than 200 mg/day of CoQ10 compared to higher doses. However, none of them were statistically significant (Fig. 9). Interventions lasting more than 8 weeks demonstrated a higher but non-significant reduction in diastolic BP compared to shorter trials (Fig. 10). Non-healthy individuals experienced a greater but non-significant reduction in diastolic BP compared to healthy participants (Fig. 11). Administration with mixed formulation resulted in a greater decrease in diastolic BP compared to CoQ10 alone or MitoQ administration. However, neither was statistically meaningful (Fig. 12). Despite these subgroup analyses, heterogeneity remained high, indicating considerable variability in study design, populations, and intervention characteristics (Table 2).

Fig. 9.

Forest plot demonstrating weighted mean difference (WMD) and 95 % confidence intervals (CIs) for the subgroup analysis based on the dose (≤200 vs. >200 mg/day) of Q10 administration on diastolic blood pressure (mmHg) in adults.

Fig. 10.

Forest plot demonstrating weighted mean difference (WMD) and 95 % confidence intervals (CIs) for the subgroup analysis based on the trial duration (>8 vs. ≤8 weeks) of Q10 administration on diastolic blood pressure (mmHg) in adults.

Fig. 11.

Forest plot demonstrating weighted mean difference (WMD) and 95 % confidence intervals (CIs) for the subgroup analysis based on the participants' health status (healthy vs. patients) of Q10 administration on diastolic blood pressure (mmHg) in adults.

Fig. 12.

Forest plot demonstrating weighted mean difference (WMD) and 95 % confidence intervals (CIs) for the subgroup analysis based on the type of Q10 (CoQ10 vs. mixed vs. MitoQ) administration on diastolic blood pressure (mmHg) in adults.

3.4.3. Effects of CoQ10 on heart rate

The pooled meta-analysis of 10 RCTs with 11 effect sizes found no significant impact of CoQ10 administration on HR (WMD = −0.10 bpm; 95 % CI: −2.09 to 1.89, p = 0.44), with minimal heterogeneity among studies (I² = 0 %) (Fig. 13, Table 2).

Fig. 13.

Forest plot demonstrating weighted mean difference (WMD) and 95 % confidence intervals (CIs) for the overall effect of Q10 administration on heart rate (bpm) in adults.

The subgroup analysis based on the dosage of the CoQ10 supplement showed a slight, non-significant decrease in HR in dosages higher than 200 mg/day. The subgroup analysis findings based on the intervention duration were not meaningful at a dosage higher or lower than 200 mg/day. Administration with CoQ10 alone demonstrated a nonsignificant minimal reduction in diastolic BP, whereas no changes were observed in the case of mixed formulation or MitoQ administration. A non-significant HR lowering effect of CoQ10 was detected in non-healthy participants, while no notable changes were observed in healthy individuals (Fig. 14, Table 2).

Fig. 14.

Forest plot demonstrating weighted mean difference (WMD) and 95 % confidence intervals (CIs) for the subgroup analysis based on the dose (mg/day), duration (weeks), type of Q10 (CoQ10 vs. mixed vs. MitoQ) and health status (Healthy vs. patients) of Q10 administration on heart rate (bpm) in adults.

3.5. Sensitivity analyses

A sensitivity analysis was conducted using the leave-one-out approach to evaluate the robustness of the meta-analysis findings. The results indicated that the overall effect sizes for systolic BP (Fig. 15), diastolic BP (Fig. 16), and HR (Fig. 17) remained stable, suggesting that no individual study disproportionately influenced the pooled estimates. This consistency supports the reliability of the findings and suggests they were not driven by outliers.

Fig. 15.

Sensitivity analyses of systolic blood pressure (mmHg) based on the Leave-one-out method.

Fig. 16.

Sensitivity analyses of diastolic blood pressure (DBP) based on the Leave-one-out method.

Fig. 17.

Sensitivity analyses of heart rate (HR) (bpm) based on the Leave-one-out method.

3.6. Meta-regression analysis

Meta-regression analysis was conducted to assess the impact of potential moderator variables on study heterogeneity. For systolic BP, dose accounted for the highest proportion of heterogeneity (9.61 %, I² = 88.51 %, p = 0.06), followed by trial duration (4.80 %, I² = 88.92 %, p = 0.07) and publication year (3.99 %, I² = 87.30 %, p = 0.28), while sample size had no effect (0.0 %, I² = 89.17 %, p = 0.43). For diastolic BP, none of the moderators significantly accounted for heterogeneity, with dose, sample size, and trial duration each explaining 0.0 %, and publication year explaining only 0.45 % (I² = 90.29 %, p = 0.42). For HR, no heterogeneity was observed (I² = 0.0 %), and all moderators had no impact (0.0 %, p > 0.05). Overall, while dose and trial duration may contribute to heterogeneity in systolic BP, no significant moderators were identified for diastolic BP or HR (Table 3).

3.7. Publication bias

Assessment of publication bias using funnel plots for systolic BP, diastolic BP, and HR revealed varying degrees of asymmetry, suggesting a potential underreporting of smaller or nonsignificant studies (Fig. 18). Egger's test confirmed significant publication bias for systolic BP (p < 0.01) and diastolic BP (p = 0.03).

Fig. 18.

Funnel plots for the effect of Q10 administration on systolic blood pressure (SBP), diastolic blood pressure (DBP), and heart rate (HR).

The trim-and-fill method identified missing studies, and adjustments suggested that the true effect size of CoQ10 may be even more pronounced. Specifically, the trim-and-fill results for systolic BP analysis indicated 70 studies (with 22 added missing studies), yielding a WMD of −8.94 [95 % CI: −11.40 to −6.48] with a p-value <0.0001 and 88.6 % heterogeneity. For diastolic BP analysis, 63 studies (with 19 added missing studies) were identified, resulting in a WMD of −4.00 [95 % CI: −5.55 to −4.44] with a p-value <0.0001 and 97.0 % heterogeneity. These findings suggest that the observed effects may be influenced by selective reporting, potentially leading to an overestimation of CoQ10's efficacy. However, the high heterogeneity (I² > 80 %) across studies indicates additional variability beyond publication bias, necessitating cautious interpretation of the results (Supplementary Table).

4. Discussion

4.1. Aim and main funding

The current comprehensive systematic review and meta-analysis of RCTs aimed to evaluate the effectiveness of CoQ10 on BP and HR in adults. Overall, this meta-analysis showed that CoQ10 administration caused a significant reduction in systolic BP but no significant effect on diastolic BP or HR in adults. Subgroup analysis suggests that the reduction in systolic BP was more pronounced in trials with a longer duration, lower doses (<200 mg/day), and among individuals with preexisting health conditions.

4.2. Underlying mechanism

Several mechanisms have been proposed underlying the antihypertensive effects of CoQ10. One of the main potential mechanisms is related to its antioxidant properties (74). There is evidence that oxidative stress can reduce the level of superoxide dismutase (SOD), a key endogenous antioxidant, which in turn decreases nitric oxide (NO) availability (75, 76). The reduction in NO release further results in vasoconstriction and increased BP (77). CoQ10 is believed to enhance extracellular SOD activity and NO bioavailability, which is essential for endothelial function, and prevents vasoconstriction (78). This notion is supported by a meta-analysis in 2024, which demonstrated a significant improvement in vascular endothelial flow-mediated dilation (FMD) following CoQ10 administration. Enhanced FMD contributes to greater vasodilation, reduced vascular resistance, and subsequent BP reduction (79). Additionally, its antioxidant and anti-inflammatory properties help mitigate oxidative stress and inflammation, improving arterial elasticity and reducing arterial stiffness, which predominantly affects systolic BP (72). Beyond its vascular effects, CoQ10 plays a crucial role in mitochondrial ATP production, which optimizes cardiac output, a key determinant of systolic BP (80). Another potential mechanism involves the modulation of the renin-angiotensin-aldosterone system (RAAS), which helps regulate vascular tone and fluid balance, contributing to BP reduction [19]. However, unlike BP, it is more influenced by peripheral resistance and microvascular function, which are less affected by CoQ10. Since diastolic BP reflects the pressure in smaller arteries and arterioles, where CoQ10's vasodilatory and elasticity-improving effects are less pronounced, the reduction in diastolic BP tends to be smaller or non-significant compared to systolic BP (81, 82).

4.3. CoQ10 on blood pressure

Our findings demonstrated a significant reduction in systolic BP following CoQ10 administration. However, no meaningful changes were observed in diastolic BP. Along with our findings, a meta-analysis conducted by Zhao et al. evaluated the antihypertensive effects of CoQ10 in cardiometabolic disorders, reporting a significant reduction in systolic BP, but no improvement in diastolic BP was observed [17]. Similarly, Tabrizi et al. found a significant decrease in systolic BP among patients with metabolic disorders, while diastolic BP remained unchanged [18]. Additionally, a recent systematic review of 13 studies reinforced the potential of CoQ10 in lowering BP (83)The result of subgroup analysis based on administration dosage demonstrated a greater reduction in systolic BP in CoQ10 dosages lower than 200 mg/day, whereas diastolic BP remained unchanged across different dosages. This finding was consistent with the study by Zhao et al. [17], which reported a U-shaped dose-response relation between CoQ10 dosage and systolic BP in cardiometabolic patients. A greater reduction in systolic BP was reported with an approximate dose of 100–200 mg daily consumption [17]. Similarly, Tabrizi et al. found that CoQ10 administration at 100–150 mg/day significantly lowered systolic BP compared to higher doses [18]. A study also suggested a nonlinear relationship between oral CoQ10 intake and its plasma concentration, with diminishing absorption efficiency at higher doses. Additionally, longer intervention durations (>8 weeks) were linked to greater systolic BP reductions, a trend consistent with previous meta-analyses [17,18]. Moreover, a more pronounced significant reduction in systolic BP was observed in the non-healthy population compared to healthy participants. Non-healthy individuals often have lower endogenous CoQ10 levels due to oxidative stress and mitochondrial dysfunction (84). For instance, lower level of endogenous levels of CoQ10 were observed in patients with dyslipidemia and diabetes (85, 86). It has been proposed that patients with lower circulating CoQ10 concentrations may experience greater antihypertensive response to CoQ10 administration (87).

4.4. CoQ10 on heart rate

The findings of the present study indicate that CoQ10 administration does not result in significant changes in HR. The previous studies have reported contradictory findings. For instance, Baggio et al. reported a significant improvement in HR among patients with heart failure following CoQ10 administration (88). Whereas a study conducted by Mortensen et al. found no significant changes in HR; however, a reduction in major adverse cardiac events, cardiovascular and all-cause mortality, were reported in patients with heart failure following CoQ10 administration (47). Furthermore, a RCT by Castro-Marrero et al. found no significant changes in daytime or nighttime HR following the CoQ10 administration [21]. The subgroup analysis further demonstrated no meaningful changes in HR in different dosages or duration of administration, population, and type of intervention. While CoQ10 is known for its beneficial effects on the cardiovascular system, current evidence does not support a significant impact of CoQ10 administration on HR. This may be due to CoQ10's primary role in enhancing myocardial mitochondrial energy and reducing oxidative stress rather than exerting direct chronotropic effects on HR regulation (80).

4.5. Clinical messages

The findings of this meta-analysis highlight the potential clinical significance of CoQ10 administration in the management of BP. The observed reduction in systolic BP, particularly with higher doses and longer intervention durations, suggests that CoQ10 may serve as a complementary therapy for individuals with hypertension or those at risk of cardiovascular diseases. Even a modest reduction in systolic BP is associated with a lower incidence of cardiovascular events (89), reinforcing the potential role of CoQ10 in cardiovascular prevention strategies. However, the lack of a significant effect on diastolic BP and HR and high heterogeneity across studies underscores the need for further investigation. Future research should focus on large-scale, well-controlled, randomized clinical trials to determine the optimal dose and duration of CoQ10 administration. Additionally, investigating its efficacy in specific populations, such as patients with hypertension, metabolic syndrome, or cardiovascular disease, will further clarify its therapeutic potential.

4.6. Strengths and limitations

The present meta-analysis has several strengths. First, it includes a large number of RCTs, enhancing the reliability and generalizability of the findings. The use of a systematic and comprehensive search strategy across multiple databases reduces the risk of selection bias. Additionally, the study applies subgroup analyses to investigate the source of heterogeneity between studies and assess the effects of CoQ10 administration based on dosage, trial duration, and participant health status to provide deeper insights into potential moderating factors. Sensitivity analyses further confirmed the consistency and stability of the results. However, some limitations must be acknowledged. Despite including numerous RCTs, high heterogeneity across studies may affect the consistency of the results. The variability in dosage, intervention duration, and participant characteristics (e.g., healthy vs. non-healthy individuals) could introduce confounding effects. Furthermore, the presence of potential publication bias, particularly in systolic and diastolic BP outcomes, suggests that missing data might influence the observed effects.

5. Conclusion

This meta-analysis demonstrates that CoQ10 supplementation significantly reduces systolic blood pressure, especially at doses below 200 mg/day and with longer intervention durations. While its effects on diastolic blood pressure and heart rate were not significant, the modest reduction in systolic BP may still offer meaningful cardiovascular benefits. Given its favorable safety profile, CoQ10 may be considered a supportive, adjunctive option in hypertension management. However, substantial heterogeneity among the included studies highlights the need for further high-quality randomized controlled trials. Future research should focus on identifying optimal dosing regimens and determining which patient subgroups are most likely to benefit from CoQ10 supplementation in clinical practice.

CRediT authorship contribution statement

Mehdi Karimi: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Samira Pirzad: Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation. Farnaz Hooshmand: Writing – review & editing, Writing – original draft, Validation, Software, Resources, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Niyousha Shirsalimi: Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Investigation, Funding acquisition, Data curation. Seyed Morteza Ali Pourfaraji: Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Clinical trial number

Not applicable.

Code availability

Not applicable.

Data availability

All data generated or analyzed during this study are included in this published article.

Funding

None.

Declaration of competing interest

The authors declare no conflicts of interest.

Handling Editor: D Levy

List of Abbreviations:

⁃ CoQ10

Coenzyme Q10

⁃ CVD

Cardiovascular diseases

⁃ BP

Blood pressure

⁃ HR

Heart rate

Appendix A. Supplementary data

The following is the Supplementary data to this article: