The impact of almond supplementation on oxidative stress biomarkers: a systematic review and meta-analysis of randomized control trials

Abstract

Oxidative stress, an imbalance between reactive oxygen species and antioxidants, contributes to chronic diseases. Almonds, rich in vitamin E, polyphenols, and monounsaturated fats, exhibit antioxidant potential, though their overall effects on oxidative biomarkers are unclear. This systematic review and meta-analysis evaluate almond supplementation’s impact on these biomarkers in adults. Following PRISMA guidelines, PubMed, Scopus, and Web of Science were searched up to January 2025. Randomised controlled trials (RCTs) and crossover trials assessing biomarkers of antioxidant and oxidation status (e.g., malondialdehyde [MDA], superoxide dismutase [SOD], glutathione peroxidase [GPx], 8-hydroxy-2’-deoxyguanosine [8-OHdG], uric acid [UA]) were included. Risk of bias was evaluated using the Cochrane Tool, and random-effects models calculated weighted mean differences (WMDs) with 95% confidence intervals (CIs). Eight studies (5 RCTs, 3 crossover trials; n = 424) were included. Almond doses of > 60 g/day significantly reduced MDA (WMD = -0.46, p = 0.002), 8-OHdG (WMD = -5.83, p < 0.001), and UA (WMD = -0.64, p = 0.009), while increasing SOD (WMD = 2.02, p = 0.008). No effect was found for GPx (p = 0.270). High heterogeneity (I² = 92–96%) indicated variability in study design, dosage, and population. Almond supplementation (> 60 g/day) significantly improves oxidation status by reducing MDA, 8-OHdG, and UA while enhancing SOD activity. These findings support almonds as a functional food for oxidation management. However, high heterogeneity underscores the need for standardized trials to confirm optimal dosage, duration, and conditions.

Trial registration: Prospero—CRD42025646264.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-025-14701-w.

Introduction

Oxidative stress, characterized by an imbalance between reactive oxygen species (ROS) and the body’s antioxidant defenses, plays a central role in the pathogenesis of chronic diseases such as cardiovascular diseases, neurodegenerative disorders, diabetes, and cancer¹. This imbalance leads to cellular damage, affecting lipids, proteins, and DNA, and is commonly assessed using biomarkers of antioxidant and oxidation status like malondialdehyde (MDA), 8-hydroxy-2’-deoxyguanosine (8-OHdG), and antioxidant enzymes such as superoxide dismutase (SOD) and glutathione peroxidase (GPx)². These biomarkers of antioxidant and oxidation status are critical for monitoring disease progression and evaluating the efficacy of therapeutic interventions³. Dietary antioxidants, including vitamins C and E, carotenoids, flavonoids, and polyphenols, have emerged as a promising strategy to counteract oxidative stress by neutralizing ROS and preventing cellular damage⁴. The body’s antioxidant defense system comprises both enzymatic (e.g., SOD, catalase, GPx) and non-enzymatic (e.g., vitamin C, vitamin E, glutathione) components, which work synergistically to maintain redox homeostasis⁵. Through their antioxidant properties, these nutrients are increasingly recognized for their potential to mitigate oxidative damage and prevent chronic diseases⁶. Among antioxidant-rich foods, almonds have garnered significant attention due to their unique nutrient profile and health benefits. Almonds are rich in vitamin E, primarily in the form of α-tocopherol, the most biologically active isomer, with smaller amounts of β, γ, and δ-tocopherols and tocotrienols, all of which contribute to their antioxidant capacity, and polyphenols, particularly flavonoids and phenolic acids, which exhibit antioxidant, anti-inflammatory, and cardioprotective properties. Additionally, almonds provide monounsaturated fats (MUFAs), dietary fiber, and essential minerals, contributing to their cardiovascular and metabolic health benefits⁷. Preclinical studies have demonstrated that almond consumption reduces lipid peroxidation and oxidation product markers, such as MDA, and enhances the activity of antioxidant enzymes like SOD and GPx⁸. Clinical trials further support these findings, showing that almonds improve lipid profiles, glycemic control, and reduce markers of oxidation status, including 8-OHdG and C-reactive protein, in human subjects⁹. Despite these promising findings, the cumulative impact of almond supplementation on oxidative biomarkers across studies has yet to be systematically evaluated. While individual studies highlight almonds’ antioxidant potential, a comprehensive meta-analysis is needed to assess the overall effect size, explore variations in study outcomes, and clarify the therapeutic role of almonds in reducing oxidation status. The aim of this systematic review and meta-analysis is to consolidate evidence from clinical studies to evaluate the effects of almond supplementation on oxidative biomarkers. By doing so, we seek to provide clearer insights into the role of almonds in modulating oxidative stress and their potential implications for health promotion and disease prevention.

Methods

This systematic review and meta-analysis adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines¹⁰.

Search strategy

A comprehensive search was conducted from inception to January 2025 by two independent investigators using PubMed, Scopus, and Web of Science. The following Medical Subject Headings (MeSH) and keywords were combined:

• Population: “almond” OR “Prunus dulcis” OR “tree nuts”.

• Intervention: “supplementation” OR “dietary intervention”.

• Outcomes: “oxidative stress” OR “malondialdehyde (MDA)” OR “superoxide dismutase (SOD)” OR “glutathione peroxidase (GPx)” OR “8-hydroxy-2’-deoxyguanosine (8-OHdG)” OR “uric acid (UA)”.

• Study design: “randomized controlled trial (RCT)” OR “crossover trial”.

Initial searches identified 1,350 records (Scopus: n = 750; PubMed/Medline: n = 500; Web of Science: n = 100). After removing 250 duplicate records using EndNote X20, 1,100 unique records underwent title/abstract screening. No language or date restrictions were applied. Reference lists of relevant articles and reviews were manually screened to identify additional studies.

Study selection and eligibility criteria

Studies were selected via a two-phase screening process (Fig. 1):

Fig. 1.

PRISMA flow diagram depicting an overview of the study selection process.

Title/Abstract Screening: Excluded 1,050 records, primarily due to irrelevance to almonds or antioxidant and oxidation status (n = 850), non-human or in vitro studies (n = 100), and grey literature (n = 100). Full-Text Review: Assessed 50 full-text articles for eligibility. Excluded 42 studies for reasons such as lack of antioxidant and oxidation status biomarkers (n = 15), combined interventions (n = 10), inadequate data (n = 8), non-RCT or crossover design (n = 5), and populations outside inclusion criteria (n = 4). We included randomized controlled trials (RCTs) and crossover trials as these study designs provide the highest level of evidence for assessing the causality of dietary interventions, effectively minimizing bias and confounding factors. RCTs reduce selection bias through randomization, while crossover designs enhance statistical power by allowing each participant to serve as their own control, which is particularly valuable in nutritional studies with limited sample sizes. Observational designs, such as cohort or case-control studies, were excluded due to their inability to establish causality as robustly as experimental designs.

Inclusion criteria

• Population: Adults (≥ 18 years), including healthy individuals, smokers, or patients with chronic conditions (e.g., diabetes, cardiovascular disease).

• Intervention: Almond supplementation (any form: whole, powder, oil) at any dose or duration.

• Outcomes: Reported ≥ 1 antioxidant and oxidation status biomarker (MDA, SOD, GPx, 8-OHdG, UA).

• Study design: RCTs or crossover trials with a control group (no almonds).

Exclusion criteria

• Non-human or in vitro studies.

• Grey literature (conference abstracts, letters, reviews).

• Studies with combined interventions (e.g., almonds + other nuts).

• Inadequate data for meta-analysis (e.g., missing SDs).

Data extraction

Two reviewers independently extracted:

• Study characteristics: Author, year, country, design (RCT/crossover), sample size.

• Population: Age, sex, health status (healthy, smokers, chronic disease).

• Intervention: Almond dose (g/day), duration (weeks), form (whole/processed).

• Outcomes: Mean ± SD of oxidative biomarkers (baseline and post-intervention).

For studies reporting outcomes in varying units (e.g., MDA in nmol/mL vs. µmol/L), values were converted to the most frequently reported unit using validated formulas. Missing SDs were calculated using SD = SEM × ; SD=×(for 95% CIs).

Quality assessment

The Cochrane Risk of Bias Tool 2.0¹¹ was used to assess RCTs, evaluating domains like, Randomization process, Deviations from intended interventions, Missing outcome data, Outcome measurement and Selective reporting. Crossover trials were assessed for carryover effects and washout periods¹². Discrepancies were resolved by consensus.

Data synthesis and statistical analysis

• Pooled effect sizes (weighted mean differences, WMDs) were calculated using a random-effects model (DerSimonian-Laird) to account for between-study heterogeneity¹³.

• Heterogeneity: Quantified using I² (≥ 50% = substantial) and Cochran’s Q test (p < 0.10).

• Subgroup analyses: Conducted by:

  • Dosage: <60 g/day vs. >60 g/day (based on observed thresholds).
  • Population: Healthy vs. chronic disease cohorts.
  • Intervention duration: <12 weeks vs. ≥12 weeks.

• Sensitivity analysis: Examined robustness by iteratively excluding individual studies.

• Publication bias: Assessed via funnel plots and Egger’s regression test (p < 0.10)¹⁴.

All analyses were performed using STATA 18.0 (StataCorp, College Station, TX, USA). Statistical significance was set at p < 0.05.

Results

Search results and characteristics of studies

From the systematic search, eight studies met the inclusion criteria and were included in the meta-analysis (Fig. 1). The included studies comprised five randomized controlled trials (RCTs) and three crossover trials, conducted across diverse populations: healthy individuals (n = 3), overweight/obese adults (n = 2), male smokers (n = 1), and patients with chronic conditions such as coronary artery disease (CAD) (n = 1) and hyperlipidemia (n = 1). Almond supplementation dosages ranged from 5 g/day to 168 g/day, with intervention durations spanning four to 24 weeks (Table 1).

Table 1.

Characteristics of reviewed studies.

Author and year	Sample size	Study population	Study design	Supplementation		Outcome
				Dosage	Time
Rakic (2021)27	36	Healthy, middle-aged adults	RCT1	42 g/day; 84 g/day	24 weeks	There was no difference in SOD2, and GR3.
Schincaglia (2020)18	29	Hemodialysis patients	RCT	5 g/day	12 weeks	There was no difference in SOD, and MDA4.
De Souza (2019)28	46	Overweight and obese women	RCT	20 g/day	8 weeks	There was no difference in SOD, UA5, and MDA. The supplementation group increased the activity of GPX6.
Jung (2017)29	84	Overweight/obese	Crossover	56 g/day	8 weeks	There was no difference in MDA.
Jamshed (2016)16	150	CAD patients	RCT	10 g/day American almonds; 10 g/day Pakistani almond	12 weeks	Almond’s supplementation significantly reduced serum UA among groups, and over time.
Jenkins (2008)30	27	Healthy hyperlipidemic men and postmenopausal women	Crossover	73 g/day; 37 g/day	12 weeks	The full-dose almonds reduced serum concentrations of MDA.
Li (2007)17	60	Healthy male smokers	Crossover	84 g/day	8 weeks	Almond’s supplementation significantly increased SOD, and GPX. Also significantly decreased urinary MDA, and 8OHdG compared to control smokers.
Jia (2006)15	30	Healthy male smokers	RCT	84 g/day; 168 g/day	4 weeks	There was no difference in SOD, and GPX. MDA and 8OHdG are decreased in all supplementation groups compared to control.

RCT randomized control trial, SOD superoxide dismutase, GR glutathione reductase, MDA malondialdehyde, UA uric acid, GPx glutathione peroxidase

Meta-analysis results

GPx

The random-effects model (Fig. 2) revealed no significant effect of almond supplementation on GPx levels (WMD = 13.04, 95% CI: −10.14, 36.23; p = 0.270). High heterogeneity was observed (I² = 96%, τ² = 373.63).

Fig. 2.

Meta-analysis effect of almond supplementation on GPx levels.

MDA

The random-effects model (Fig. 3) showed no significant effect of almond supplementation on MDA (WMD = −0.11, 95% CI: −0.26, 0.04; p = 0.141), with moderate heterogeneity (I² = 42.8%, τ² = 0.0131). The analysis was subgrouped by study design, and supplementation dosage. In terms of supplementation dosage, the results showed the almost complete lack of heterogeneity in bout groups suggesting a source of heterogeneity. Supplementation doses < 60 g/day (WMD = −0.03, 95% CI: −0.11, 0.04; p = 0.372, I² = 0%) showed no effect, whereas doses > 60 g/day significantly reduced MDA levels (WMD = −0.46, 95% CI: −0.75, −0.17; p = 0.002, I² = 0%), suggesting that supplementation dosage is key factor to reaching the propriate result.

Fig. 3.

Meta-analysis effect of almond supplementation on MDA levels.

SOD

Almond supplementation significantly increased SOD levels (Fig. 4) (WMD = 2.02, 95% CI: 0.52, 3.52; p = 0.008), with high heterogeneity (I² = 92%, τ² = 1.83). While subgroup by dosage: Doses < 60 g/day (WMD = 0.87, 95% CI: −1.09, 2.83; p = 0.385, I² = 85%) and > 60 g/day (WMD = 7.96, 95% CI: −5.46, 21.39; p = 0.245, I² = 95%) showed no significant differences.

Fig. 4.

Meta-analysis effect of almond supplementation on SOD levels.

UA

The random-effects model (Fig. 5) indicated a significant reduction in UA levels (WMD = −0.64, 95% CI: −1.12, −0.16; p = 0.009), with moderate heterogeneity (I² = 55%, τ² = 0.099).

Fig. 5.

Meta-analysis effect of almond supplementation on UA levels.

8-hydroxy-2’-deoxyguanosine (8OHdG)

The fixed-effects model (Fig. 6) revealed a significant reduction in 8OHdG levels (WMD = −5.83, 95% CI: −7.38, −4.29; p < 0.001), with no observed heterogeneity (I² = 0%).

Fig. 6.

Meta-analysis effect of almond supplementation on 8-Hydroxy-2’-deoxyguanosine (8OHdG) levels.

Publication bias and sensitivity analysis

Publication bias was assessed using funnel plot, Egger’s test revealing no publication bias. Sensitivity analyses demonstrated that exclusion¹⁵ study did not significantly alter the pooled effect sizes, suggesting the robustness of the results.

Quality assessment of included studies

The methodological quality of the included studies was assessed using the Cochrane Risk of Bias Tool 2.0 (Fig. 7). Most studies (n = 6) demonstrated low risk of bias in key domains such as random sequence generation and selective reporting. However, three studies (Jamshed et al.¹⁶; Li et al.¹⁷; Jia et al.¹⁵ had unclear risk due to insufficient reporting of allocation concealment and blinding procedures. One study (Schincaglia et al.¹⁸ was rated as high risk for incomplete outcome data due to significant attrition (> 20% dropout rate). Overall, the included studies were of moderate to high quality, with adequate randomization and low risk of selective reporting, though improved transparency in blinding and allocation concealment is needed in future trials.

Fig. 7.

Summary of risk of bias in included studies.

Discussion

This systematic review and meta-analysis evaluated the effects of almond supplementation on antioxidant and oxidation status biomarkers across eight randomized and crossover trials. The findings demonstrate that almonds exhibit dose-dependent antioxidant effects, significantly reducing markers of lipid peroxidation (MDA), oxidative DNA damage (8-OHdG), and uric acid (UA), while enhancing superoxide dismutase (SOD) activity. Below, we interpret these results in the context of existing literature, address mechanistic insights, and outline implications for research and practice.

GPx activity

Almond supplementation did not significantly alter GPx activity (WMD = 13.04, p = 0.270), despite preclinical evidence suggesting that nut polyphenols, including those from almonds, may enhance antioxidant pathways, potentially involving glutathione metabolism^19,20. This discrepancy may stem from high heterogeneity (I² = 96%), potentially driven by variations in baseline GPx levels across populations (e.g., healthy vs. chronic disease cohorts) or differences in almond polyphenol bioavailability due to processing methods (e.g., raw vs. roasted almonds). For instance, roasting temperatures can degrade heat-sensitive polyphenols, diminishing their bioavailability²¹. Future studies should standardize almond preparation and stratify participants by baseline oxidation status severity.

SOD activity

The significant increase in SOD levels (WMD = 2.02, p = 0.008) aligns with mechanistic studies showing that almond-derived vitamin E and flavonoids activate the Nrf2 pathway, a master regulator of endogenous antioxidant enzymes¹⁹. Almonds are rich in α-tocopherol (5–8 mg/100 g), which directly scavenges ROS and enhances SOD activity by stabilizing cellular membranes²¹. However, the high heterogeneity (I² = 92%) suggests that factors such as intervention duration (4–24 weeks) or genetic polymorphisms in SOD isoforms (e.g., SOD2 rs4880) may modulate responses²². For example, shorter trials may inadequately capture enzymatic adaptation, while genetic variability could explain inconsistent effects across populations.

MDA levels

The overall null effect on MDA (WMD = −0.11, p = 0.141) contrasts with subgroup findings where high-dose almonds (> 60 g/day) significantly reduced MDA (WMD = −0.46, p = 0.002). This dose-response relationship mirrors findings in nut polyphenol research, where thresholds of ~ 50–60 g/day are required to inhibit lipid peroxidation in vivo²². The potent MDA reduction at higher doses likely reflects cumulative antioxidant effects from almonds’ vitamin E (protecting membranes) and fiber (modulating gut microbiota-derived oxidative byproducts). For example, almond fiber promotes the growth of Bifidobacterium, which produces short-chain fatty acids that reduce systemic oxidation status²³.

UA and 8-OHdG levels

The significant decrease in 8-OHdG (WMD = −5.83, p < 0.001) underscores almonds’ capacity to mitigate oxidative DNA damage, likely via direct ROS scavenging by phenolic acids (e.g., protocatechuic acid) and enhanced DNA repair mechanisms²¹. Almond skins contain high concentrations of flavonoids (e.g., isorhamnetin) that inhibit DNA adduct formation²³. Similarly, the reduction in UA (WMD = −0.64, p = 0.009) may reflect almonds’ ability to inhibit xanthine oxidase activity, a key source of UA and ROS, as demonstrated in hyperuricemic models¹⁹.

Heterogeneity and subgroup analysis

The high heterogeneity in GPx (I² = 96%) and SOD (I² = 92%) outcomes highlights the need for standardized protocols in nut intervention studies. For example, crossover trials often lack washout periods, potentially carrying over antioxidant effects, while parallel-arm RCTs may suffer from dietary confounding²². Subgroup analyses by dosage revealed that almonds’ antioxidant efficacy is dose-dependent, consistent with prior work showing that nut polyphenols require sustained, high intake to exert clinically meaningful effects²². Researchers should prioritize dosing consistency and consider nut matrix effects (e.g., whole vs. blended almonds) in future trials. For instance, whole almonds retain bioactive compounds in the skin, which are lost during processing²¹.

Limitations and future directions

This meta-analysis has several limitations that influence our conclusions. First, only eight studies were included, yielding a relatively small sample size. High heterogeneity was observed for biomarkers such as superoxide dismutase (SOD) and glutathione peroxidase (GPx), with I² values of 92–96%, likely reflecting differences in participant characteristics and almond preparations. population differences also contribute to variability. Studies encompassed healthy middle‑aged adults, hemodialysis patients, overweight or obese individuals, coronary artery disease (CAD) patients, hyperlipidemic subjects, and smokers (each with distinct baseline oxidation status and antioxidant defenses). For instance, smokers display markedly higher malondialdehyde (MDA) levels (p = 0.002) and lower SOD activity (p < 0.0001) than non‑smokers²⁴potentially exaggerating their response to almonds. Conversely, healthier groups may exhibit minimal changes, diminishing the overall impact. Almond form and processing further complicate interpretation. Studies used whole raw almonds, roasted nuts, almond powder, and almond oil, with or without blanching. Since polyphenols are concentrated in almond skins, blanching virtually eliminates these antioxidants²⁵. Roasting degrades total phenolics by ~ 26% and lowers FRAP-measured antioxidant capacity by ~ 34%, although it can increase extractable compounds via Maillard reactions²⁶. Such processing differences likely drive the high biomarker heterogeneity. To strengthen future research, researchers should adopt standardized protocols that include stratifying participants by their baseline oxidation status levels (for example, comparing smokers with healthy individuals), using a uniform almond form (preferably whole, raw, unblanched nuts) to preserve skinbound polyphenols, applying consistent dosing of at least 60 g per day over intervention periods of 12 weeks or longer, and employing harmonized assay methods for key antioxidant and oxidation status biomarkers. As a whole food, almonds deliver vitamin E, polyphenols, healthy fats, and fiber, which likely act synergistically against oxidation status²³.

Conclusion

This meta-analysis shows that almond supplementation, particularly at doses > 60 g/day, reduces oxidative DNA damage (e.g., 8-OHdG), lipid peroxidation (e.g., MDA), and UA levels while enhancing SOD activity, suggesting its potential as a functional food for oxidative stress management. However, the observed heterogeneity highlights the need for methodological consistency, such as standardized dosing and biomarker assessment, in future trials to optimize its benefits, especially for high-risk populations like smokers or those with chronic diseases.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

Authors’ contributions AK and MG drafted the article, participated in the design of the study, contributed to data collection and data analysis. SM and FT contributed in data collection. AK Aand MG contributed to data analysis. AK, SM and MG and AG revised the manuscript critically for important intellectual content. All authors read and approved the final version of the manuscript.

Funding

None.

Data availability

This manuscript is a meta-analysis and data collected from published articles, the strategy of search and analysis will be provided by reasonable request by Mohamamd Gholizadeh.

Declarations

Competing interests

The authors declare no competing interests.