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The Journal of Nutrition logoLink to The Journal of Nutrition
. 2023 Nov 19;154(5):1699–1710. doi: 10.1016/j.tjnut.2023.11.014

Prune Consumption Attenuates Proinflammatory Cytokine Secretion and Alters Monocyte Activation in Postmenopausal Women: Secondary Outcome Analysis of a 12-Mo Randomized Controlled Trial: The Prune Study

Janhavi J Damani 1, Ester S Oh 2,3, Mary Jane De Souza 4, Nicole CA Strock 4, Nancy I Williams 4, Cindy H Nakatsu 5, Hang Lee 6, Connie Weaver 7, Connie J Rogers 2,8,9,∗
PMCID: PMC11347809  PMID: 37984741

Abstract

Background

Proinflammatory cytokines are implicated in the pathophysiology of postmenopausal bone loss. Clinical studies demonstrate that prunes prevent bone mineral density loss; however, the mechanism underlying this effect is unknown.

Objective

We investigated the effect of prune supplementation on immune, inflammatory, and oxidative stress markers.

Methods

A secondary analysis was conducted in the Prune Study, a single-center, parallel-arm, 12-mo randomized controlled trial of postmenopausal women (55–75 y old; n = 235 recruited; n = 183 completed) who were assigned to 1 of 3 groups: “no-prune” control, 50 g prune/d and 100 g prune/d groups. At baseline and after 12 mo of intervention, blood samples were collected to measure serum high-sensitivity C-reactive protein (hs-CRP), serum total antioxidant capacity (TAC), plasma 8-isoprostane, proinflammatory cytokines [interleukin (IL)-1β, IL-6, IL-8, monocyte chemoattractant protein-1, and tumor necrosis factor (TNF)-α] concentrations in plasma and lipopolysaccharide (LPS)-stimulated peripheral blood mononuclear cells (PBMCs) culture supernatants, and the percentage and activation of circulating monocytes, as secondary outcomes.

Results

Prune supplementation did not alter hs-CRP, TAC, 8-isoprostane, and plasma cytokine concentrations. However, percent change from baseline in circulating activated monocytes was lower in the 100 g prune/d group compared with the control group (mean ± SD, −1.8% ± 4.0% in 100 g prune/d compared with 0.1% ± 2.9% in control; P < 0.01). Furthermore, in LPS-stimulated PBMC supernatants, the percent change from baseline in TNF-α secretion was lower in the 50 g prune/d group compared with the control group (−4.4% ± 43.0% in 50 g prune/d compared with 24.3% ± 70.7% in control; P < 0.01), and the percent change from baseline in IL-1β, IL-6, and IL-8 secretion was lower in the 100 g prune/d group compared with the control group (−8.9% ± 61.6%, −4.3% ± 75.3%, −14.3% ± 60.8% in 100 g prune/d compared with 46.9% ± 107.4%, 16.9% ± 70.6%, 39.8% ± 90.8% in control for IL-1β, IL-6, and IL-8, respectively; all P < 0.05).

Conclusions

Dietary supplementation with 50–100 g prunes for 12 mo reduced proinflammatory cytokine secretion from PBMCs and suppressed the circulating levels of activated monocytes in postmenopausal women.

This trial was registered at clinicaltrials.gov as NCT02822378.

Keywords: inflammatory cytokines, immunity, peripheral blood mononuclear cells, oxidative stress, dried plums, prunes, osteoporosis, menopause, nutritional intervention, randomized controlled trial

Introduction

Inflammation is a major contributing factor in the pathophysiology of age-related chronic diseases, including cardiovascular disease, diabetes mellitus, cancer, rheumatoid arthritis, and osteoporosis [1]. The chronic, low-grade inflammatory state that is concomitant with aging, also termed “inflammaging” [2], results in tissue damage by inducing oxidative stress, contributing to the risk and progression of the aforementioned chronic diseases [3,4]. Hypoestrogenism during menopause also increases circulating inflammatory mediators, which is linked to an adverse cardiometabolic and osteoporotic risk profile in postmenopausal women [[5], [6], [7], [8], [9], [10], [11], [12]].

Estrogen is an important hormonal regulator of proinflammatory cytokines, including IL-1β, IL-6, and TNF-α, that play a key role in postmenopausal bone loss [[13], [14], [15], [16]]. Estrogen inhibits the expression of inflammatory cytokines within the bone microenvironment, resulting in a balanced state of bone turnover [17]. However, estrogen deficiency resulting from ovarian senescence during menopause disrupts this balance, in part, due to the loss of estrogen’s inhibitory effect on cytokine production, leading to increased secretion of proinflammatory cytokines [18,19]. Thus, an elevated inflammatory profile may be linked to accelerated postmenopausal bone loss and may represent a potential target for osteoporosis therapies.

Pharmacologic drugs for osteoporosis have been associated with adverse effects [20] and poor compliance [21]; as such, nonpharmacologic alternatives for bone loss have grown in popularity over the recent years [22]. Epidemiologic evidence [[23], [24], 25] supports the role of fruit and vegetable intake in preventing bone loss in postmenopausal women. Prunes (i.e., dried plums) have been extensively studied as a functional food for improving bone health after menopause [[26], [27], [28]] and are abundant in bioactive compounds [29], including vitamins, minerals, and phenolic compounds, which are thought to act synergistically to reduce postmenopausal bone loss. Evidence from in vitro and animal studies suggests that prunes and their polyphenolic compounds improve bone outcomes through anti-inflammatory and antioxidant mechanisms [30]. Although several randomized controlled trials (RCTs) [[31], [32], [33], [34]] have reported bone-protective effects of prune supplementation in postmenopausal women, our understanding of the role of prune consumption in modulating inflammatory mediators is limited. Clinical studies [32,33,35] investigating potential anti-inflammatory effects of prunes in postmenopausal women have only measured circulating inflammatory markers, including IL-6, TNF-α, and C-reactive protein (CRP). Peripheral blood mononuclear cells (PBMCs), particularly monocytes, are an important source of bone-resorptive inflammatory cytokines [36]. However, no studies, to date, have evaluated the effect of prune consumption on monocyte activation or cytokine secretion from PBMCs in postmenopausal women.

Therefore, the purpose of the current investigation was to evaluate the effect of 12-mo dietary supplementation of prunes at 2 doses (50 g/d and 100 g/d) on a comprehensive panel of immune, inflammatory, and oxidative stress markers in postmenopausal women, particularly, circulating inflammatory markers [CRP, monocyte chemoattractant protein (MCP)-1, IL-1β, IL-6, IL-8, and TNF-α], inflammatory cytokine secretion from cultured PBMCs, the percentage and activation of circulating monocytes, serum total antioxidant capacity (TAC) concentrations, and plasma 8-isoprostane. We hypothesized that prune supplementation at 50 and 100 g/d for 12 mo may dose-dependently reduce inflammatory mediators and markers of oxidative stress in postmenopausal women.

Methods

Participants

Eligible study participants included postmenopausal women aged 55–75 y, with menopausal status (determined by self-report questionnaire) as having absence of menstruation for at least 12 consecutive months; who did not have severe obesity (BMI < 40 kg/m2); healthy (determined by a screening questionnaire and complete metabolic panel); willing to include prunes in their daily diet; not taking any natural dietary supplement containing phenolics or <1 cup/d of blueberries or apples for ≥2 mo before study entry; nonsmoking and ambulatory; and had eligible areal bone mineral density (BMD) as measured by dual-energy X-ray absorptiometry (DXA). Eligible BMD values from DXA assessments at the lumbar spine, total hip, and/or femoral neck corresponded to T-scores between 0.0 and −3.0. Exclusion criteria have been previously described in detail [37]. Briefly, women were excluded if they had a previous history of chronic disease or fractures; were regular consumers of prunes, dried apples, prune juice, or blueberries (>1 cup/d) (determined by a food frequency questionnaire); and were taking any medications (hormonal, osteoporosis, or other) within 12 mo of study participation that would interfere with primary bone outcomes.

Recruitment, screening, and randomization

Participants were recruited on a rolling basis between June 2016 and February 2021 in The Women’s Health and Exercise Laboratory (WHEL) at the Pennsylvania State University (PSU), University Park, PA. Recruitment was conducted through fliers posted in buildings and facilities on PSU campus and surrounding locations, and advertisements placed in university and local newspapers. Potential participants interested in the study (through call/emails) underwent preliminary screening through a telephonic interview involving a medical history and lifestyle questionnaire. Eligible subjects were scheduled for an in-person screening visit at the Penn State Clinical Research Center and were instructed to fast for 12 h before the screening visit. Upon provision of signed, written informed consent by the participant, a physical examination and evaluation of medical health history, areal BMD, and results from the fasting blood draw were reviewed to determine eligibility. Before the baseline visit, eligible participants were randomly assigned to treatment groups (1:1:1 allocation) using a computer-generated list. The randomization list was maintained by WHEL staff. Due to the nature of the intervention, participants and study staff were not blinded to the treatment allocation, but all data collectors and outcome assessors were blinded to the allocation.

Ethics approval

All study procedures, informed consent, and experiments were performed with the approval of the PSU Institutional Review Board, and the parent RCT [37] was registered at Clinicaltrials.gov as NCT02822378. This study was reported in compliance with the CONSORT reporting guidelines [38].

Study design and intervention

The Prune Study is a single-center, parallel-arm, 12-mo RCT designed to evaluate the effect of prune consumption (50 and 100 g/d) as a whole-food, dietary intervention supplemented with the recommended daily dose of calcium and vitamin D3, in comparison to a “no-prune” control group (with calcium and vitamin D3 supplementation alone) on BMD, bone geometry, and bone strength in postmenopausal women. Detailed study protocols and study design [37] and results of the primary bone endpoints [34] and secondary gut microbiome endpoints [39] have been previously reported. The parent RCT was designed to achieve 80% power for detecting a significant difference in the primary outcome, change from baseline in areal BMD, with a 2-sided type 1 error rate of 5% and anticipated 20% attrition rate.

In the parent trial, a total of 638 postmenopausal women were assessed for eligibility via telephone screening, and 235 women who met the eligibility criteria were randomly allocated to 1 of 3 treatment groups at baseline: control (n = 78), 50 g prune/d (n = 79), or 100 g prune/d (n = 78) (Figure 1). The current investigation is an ancillary study of the parent RCT that aimed to explore immune, inflammatory, and oxidative stress markers as prespecified secondary outcomes to better understand the mechanisms underlying bone-protective effects of prunes in postmenopausal women. Of the 235 women enrolled in the study, a total of 183 participants completed the entire 12-mo RCT and were evaluated for measurements of immune, inflammatory, and oxidative stress markers at baseline and after 12 mo of intervention: control (n = 70), 50 g prune/d (n = 67), and 100 g prune/d (n = 46). The overall participant dropout rate was 22%, with the highest dropout rate in the 100 g prune/d group (41%), primarily due to time commitment, poor tolerance to the intervention, or lost to follow-up [34]. For this secondary outcome analysis of inflammatory, immune, and oxidative stress markers, all 183 participants who completed the RCT were included in the analysis of plasma cytokines and oxidative stress markers (Figure 1). However, due to methodologic limitations with collection of blood and immune cells, the sample sizes per treatment group varied for the analysis of serum hs-CRP and PBMC outcomes, including inflammatory cytokine production from LPS-stimulated PBMCs and the percent of circulating monocytes and their activation status.

FIGURE 1.

FIGURE 1

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CONSORT flow diagram of participants. hs-CRP, high-sensitivity C-reactive protein; PBMC, peripheral blood mononuclear cell.

The prunes were provided by the California Prune Board, and the nutrient profiles of the 50 and 100 g prune interventions have been previously described [34]. Participants were counseled to gradually incorporate prunes into their daily diet during a “run-in” period, which has been outlined in the study protocol [37]. After the run-in period, participants were instructed to consume the prescribed amount of prunes and record the days and number of prunes consumed on a daily supplement log, which was used to monitor compliance and document any adverse symptoms (bloating, cramping, gas, etc.) throughout the study duration. Participants were considered compliant to the intervention if they consumed >80% of the prescribed treatment for the 12-mo RCT. Participants in all 3 treatment groups were administered calcium carbonate and vitamin D3 supplements (Nature Made Pharmavite LLC) to meet the recommended dietary allowance [40] of 1200 mg calcium and 800 IU vitamin D3 daily from diet plus supplements.

Anthropometric measurements

Height was measured to the nearest 0.1 cm using a calibrated stadiometer. Total body weight was measured to the nearest 0.5 kg on a physician’s scale (Seca, Model 770). BMI (kg/m2) was calculated as total body weight divided by height squared.

Blood sample collection

At baseline and the end of the 12-mo intervention, fasting blood samples (10 mL; after an overnight fast of ≥12 h) were drawn by venipuncture into different blood collection tubes (BD Biosciences), depending on the outcomes measured, details of which have been previously described [37]. Plasma and serum samples were aliquoted into 2-mL polyethylene storage tubes and frozen at –80°C until analysis.

Ex vivo inflammatory cytokine secretion assay

PBMCs were isolated from blood as previously described [37,41]. PBMCs (2 × 105/mL) were stimulated with 0.625 μg/mL LPS (Sigma–Aldrich) in 96-well round-bottomed plates (Corning Inc.), and supernatants (70 μL per replicate) were harvested after 4-h incubation at 37°C and frozen at −80°C until analysis.

Measurement of inflammatory cytokines, C-reactive protein, and oxidative stress markers

Cytokines and chemokines (MCP-1, IL-1β, IL-6, IL-8, and TNF-α [pg/mL]) were measured in plasma and supernatants harvested from LPS-stimulated PBMCs using the V-PLEX Proinflammatory Panel 1 Human Kit and V-PLEX Human MCP-1 kit (MesoScale Diagnostics, LLC) according to manufacturer’s instructions [intra-assay coefficient of variation (CV) of 6.6%–11.2%, 3.3%–4.1%, 3.6%–4.5%, 2.7%–3.0%, and 2.7%–3.4%, respectively, for MCP-1, IL-1β, IL-6, IL-8, and TNF-α; inter-assay CV of 5.0%–8.9%, 5.5%–7.7%, 5.2%–7.3%, 5.0%–7.1%, and 6.1%–10.1%, respectively, for MCP-1, IL-1β, IL-6, IL-8, and TNF-α]. High-sensitivity CRP (hs-CRP, mg/L) in serum was quantified using an Immulite hs-CRP kit (Siemens Healthcare) according to manufacturer’s instructions (intra-assay CV of 5.0%–6.0% and inter-assay CV of 7.3%–10%). The sensitivity of the hs-CRP kit was 0.3 mg/L. Plasma 8-isoprostane and serum TAC concentrations were measured using Cayman’s 8-isoprostane and antioxidant assay kits, respectively (Cayman Chemical) as per manufacturer’s instructions (intra- and inter-assay CVs were <10% for both assays). Each assay was performed in duplicate.

Flow cytometric analysis

PBMCs were stained with fluorescent labeled antibodies as previously described [37,42]. Briefly, PBMCs were washed twice in phosphate-buffered saline at 4°C, followed by incubation with mouse anti-human CD16 (Fc block) (Human TruStain FcX, BioLegend Inc.) at 5 μL per 1 × 106 cells. PBMCs were stained with fluorescence-labeled mouse anti-human antibodies (1 μg/1 × 106 cells) to the following cell surface markers: CD3, CD14, CD282 [Toll-like receptor (TLR)-2], and human leukocyte antigen–DR isotype (HLA-DR). Antibody isotype controls included: mouse IgG2a and mouse IgM. CD282 and CD14 were purchased from BioLegend, and all remaining antibodies were purchased from BD Biosciences. Following incubation with conjugated antibodies for 30 min at 4°C, cells were washed twice in phosphate-buffered saline and then fixed in cytofix (BD Biosciences) for flow cytometric analyses. Live lymphoid and myeloid cells were gated on forward compared with side scatter, and a total of 50,000 events were acquired with BD LSR-Fortessa (BD Biosciences). Data were analyzed and plotted using FlowJo software v10 (FlowJo, LLC). The gating strategies to identify CD14+/HLA-DR+ monocytes within the total PBMC population and percentage of CD14+/HLA-DR+ cells expressing TLR-2 within the monocyte population are presented in Supplemental Figure 1.

Statistical analysis

Statistical analyses were performed using SAS (Statistical Analysis System, version 9.4). We analyzed data from all randomly assigned participants who completed the 12-mo intervention, had data for secondary outcome measures of immune, inflammatory, and oxidative stress markers, and were included in the analysis regardless of compliance to intervention. Due to insufficient collection of biological samples, the sample sizes differ for the analysis of these secondary outcomes (Figure 1). No imputation was performed for missing observations. For hs-CRP, 2 data points that were >10 mg/L were regarded as outliers and removed, as these elevated values may be indicative of acute infection [43]. For the remaining continuous variables that were highly skewed, extreme outliers were winsorized [44] by identifying data points >1.5 IQR above the third quartile (Q3) and 1.5 IQR below the first quartile (Q1) and substituted with the trimmed mean. All secondary outcome data in the current investigation were first fitted into the linear model to test for the assumption of normality distribution of residuals. Data distribution was assessed for normality using the Shapiro–Wilk test. Residua compared with predicted value plots were assessed to confirm equal variance of the data, and Q–Q plots were assessed to confirm the normality of the residuals. If residuals followed a normal distribution, outcome variables were fitted using parametric models. However, if residuals followed a non-normal distribution, outcome variables were subject to natural logarithm or square root transformation. If transformations were unsuccessful at normalizing the distribution of residuals, non-parametric tests were used.

All outcomes were reported as percent change from baseline to 12 mo (calculated by subtracting measurements taken at baseline from postintervention values, then dividing this difference by the baseline value, and multiplying the result by 100), according to the prespecified statistical analysis plan [37]. Distributions of the baseline characteristics across all 3 groups are reported with mean ± SD or proportion (%). Values in the supplementary tables and figures are reported with mean ± SD. The effect sizes and their precisions are reported as between-group differences in the mean percent change along with a 95% confidence interval. A linear mixed-effects model, with a participant-level random intercept and specification of unstructured longitudinal correlation, was used to test the fixed effect of treatment on percent change outcomes. Furthermore, a linear mixed-effects model for repeated measures ANOVA was used to fit the longitudinal data at 2 time points (baseline and 12 mo/postintervention) to test the effect of time, treatment, and their interaction (treatment × time) modeled as fixed-effects (Supplemental Table 1). The effect of treatment on non-normally distributed percent change outcomes was analyzed using the Kruskal–Wallis test. For the linear mixed-effect models (SAS PROC MIXED), model selection was based on optimizing fit statistics (evaluated as the lowest Bayesian Information Criterion). Kruskal–Wallis test (SAS PROC NPAR1WAY) was used to test between-group differences when data were non-normally distributed. The magnitude of group-specific percent changes from baseline are presented in Supplemental Table 2. Statistical significance was accepted at P < 0.05 for all outcomes. Multiple comparisons were corrected with appropriate post hoc tests, such as the Tukey–Kramer or Dunn’s test. Graphs were plotted using GraphPad PRISM (version 9.4.1, GraphPad Software). SAS codes for statistical analyses are provided in Supplemental Table 3.

Results

Baseline characteristics

The descriptive characteristics of all 235 postmenopausal women enrolled in the parent RCT at baseline are reported elsewhere [34] and are similar to the baseline characteristics of the 183 participants who completed the 12-mo intervention (Table 1). Postmenopausal women were aged 62.1 ± 4.9 y (range: 55–75 y), had a BMI of 25.7 ± 4.1 kg/m2, and were mainly Caucasian (>98%; data not shown). Participants experienced self-reported menopause at the age of 50.3 ± 4.8 y (range: 30–61 y) and were in their late postmenopausal stage (80.4%), i.e., >8 y since their final menstrual period [45]. Although most participants had osteopenia (68.9%) or osteoporosis (18.0%) at baseline, a majority of women reported no previous use of hormone therapy or osteoporosis medications (Table 1). In this population of 183 postmenopausal women who completed the study, body weight, BMI, and fat mass were balanced among the control, 50 g prune/d, and 100 g prune/d groups at baseline and did not significantly change throughout the intervention period across all groups (data not shown). Among all 183 participants who completed the 12-mo RCT, compliance to the assigned intervention was on average >90% in all treatment groups, details previously reported [34].

TABLE 1.

Baseline characteristics of postmenopausal women who completed the trial1

Control (n = 70) 50 g Prune/d (n = 67) 100 g Prune/d (n = 46)
Demographics
 Age, y 62.0 ± 4.8 62.3 ± 4.6 61.9 ± 5.5
 Age at menopause, y 50.2 ± 4.9 50.7 ± 4.8 50.0 ± 4.9
 Time since menopause, y 11.8 ± 6.9 11.4 ± 6.3 11.8 ±7.5
 Height, cm 163.6 ± 5.7 162.0 ± 5.8 162.9 ± 5.7
 Body weight, kg 67.0 ± 10.9 69.3 ± 11.1 68.3 ± 10.7
 BMI, kg/m2 25.0 ± 3.8 26.4 ± 4.5 25.6 ± 3.6
 BMI category2
 Normal (%) 52.8 44.7 45.6
 Overweight (%) 32.8 35.8 43.4
 Obese (%) 14.4 19.5 11
Body composition
 Fat mass, kg 26.8 ± 8.3 28.8 ± 7.6 27.5 ± 6.7
 Lean mass, kg 36.9 ± 3.8 37.2 ± 4.1 37.4 ± 4.5
 Body fat, % 39.9 ± 6.7 41.6 ± 5.2 40.6 ± 4.5
Bone mineral density
 BMD category3
 Normal (%) 4.2 17.9 19.5
 Osteopenia (%) 74.3 62.7 69.5
 Osteoporosis (%) 21.5 19.4 11
 Total body BMD, g/cm2 1.0 ± 0.1 1.0 ± 0.1 1.0 ± 0.1
 Total body T-score –0.7 ± 0.9 –0.7 ± 0.9 –0.6 ± 1.2
 Lumbar spine BMD, g/cm2 0.8 ± 0.1 0.8 ± 0.1 0.9 ± 0.1
 Lumbar spine T-score –1.5 ± 0.7 –1.5 ± 0.8 –1.1 ± 0.9
 Total hip BMD, g/cm2 0.8 ± 0.1 0.8 ± 0.1 0.8 ± 0.1
 Total hip T-score –1.1 ± 0.6 –1.0 ± 0.7 –1.0 ± 0.6
 Femoral neck BMD, g/cm2 0.6 ± 0.1 0.6 ± 0.1 0.6 ± 0.1
 Femoral neck T-score –1.5 ± 0.7 –1.5 ± 0.7 –1.4 ± 0.7
 FRAX MOF, % 10.1 ± 3.9 9.8 ± 3.3 9.4 ± 4.4
 FRAX HF, % 1.3 ± 1.8 1.2 ± 1.1 1.3 ± 2.2
Health history
 Previous hysterectomy (%) 11.5 16.5 13.1
 Previous hormone therapy use (%) 22.9 26.9 26.1
 Previous osteoporosis medication use (%) 17.2 22.4 17.4
Menopause STRAW+10 classification4
 Early (%) 18.5 17.4 24.4
 Late (%) 81.5 82.6 75.6
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Abbreviations: BMD, bone mineral density; FRAX, fracture risk assessment tool; HF, hip fracture; MOF, major osteoporotic fracture; STRAW, Stages of Reproductive Aging Workshop.

1

n = 183; Data are presented as mean ± standard deviation or proportion (%).

2

BMI (kg/m2) classification: normal: 18.5–24.9; overweight: 25–29.9; obese: >30.

3

BMD classification: normal: T-score ≥ –1.0; osteopenia: T-score between –1.0 and –2.5; osteoporosis: T-score ≤ –2.5.

4

STRAW+10 classification is based on Harlow et al. [45] where “early” menopause is characterized as being <8 y from menopause and “late” menopause if characterized as >8 y from menopause.

Percentage of circulating monocytes and their activation status

The percent change in the expression (MFI) of HLA-DR (Figure 2A; P = 0.89) and TLR-2 (Figure 2B; P = 0.71) on CD14+/HLA-DR+ monocytes from baseline to 12 mo did not differ among the groups. There was no main effect of treatment on the percent change in circulating monocytes (CD14+/HLA-DR+ cells measured as a percentage of gated PBMCs) from baseline to 12 mo (Figure 2C; P = 0.28). Furthermore, there was a main effect of treatment on the percent change from baseline in activated monocytes (CD14+/HLA-DR+/TLR-2+ cells; Figure 2D; P < 0.01), with the percent change from baseline in activated monocytes significantly lower in the 100 g prune/d group compared with the control group [−1.8% ± 4.0% in 100 g prune/d compared with 0.1% ± 2.9% in control, Dunn’s post hoc test, P < 0.01; effect size: 1.9 (−0.3, 4.0)] (Figure 2D).

FIGURE 2.

FIGURE 2

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Change in the expression of activation markers HLA-DR (A) and TLR-2 (B) on monocytes (CD14+/HLA-DR+ cells) from baseline to 12 mo, and change in the percentages of monocytes (CD14+/HLA-DR+ cells) (C) and monocytes expressing TLR-2 (CD14+/HLA-DR+/TLR-2+ cells) (D) from baseline to 12 mo in postmenopausal women in the control (n = 23), 50 g prune/d (n = 29), and 100 g prune/d (n = 15) groups. Data are mean ± SD. Labeled means without a common letter differ, P < 0.01. CD, cluster of differentiation; HLA-DR, human leukocyte antigen–DR isotype; MFI, mean fluorescence intensity; TLR, Toll-like receptor.

Circulating markers of inflammation and oxidative stress: serum hs-CRP, plasma inflammatory cytokines, serum TAC, and plasma 8-isoprostane

The percent change in serum hs-CRP concentration (Figure 3A; P = 0.92), serum TAC (Figure 3B; P = 0.54), and plasma 8-isoprostane (Figure 3C; P = 0.39) from baseline to 12 mo did not differ among the groups. Additionally, there was no main effect of treatment on percent change in plasma levels of proinflammatory cytokines MCP-1 (P = 0.69), TNF-α (P = 0.39), IL-1β (P = 0.65), IL-6 (P = 0.23), and IL-8 (P = 0.86) from baseline to 12 mo (Figure 4A–E).

FIGURE 3.

FIGURE 3

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Change in serum hs-CRP (A); serum total antioxidant capacity (B) and plasma 8-isoprostane (C) from baseline to 12 mo in postmenopausal women in the control (n = 42), 50 g prune/d (n = 35), and 100 g prune/d (n = 29) groups for hs-CRP; and control (n = 70), 50 g prune/d (n = 67), and 100 g prune/d (n = 43) groups for serum total antioxidant capacity and plasma 8-isoprostane. Data are mean ± SD. hs-CRP, high-sensitivity C-reactive protein.

FIGURE 4.

FIGURE 4

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Change in plasma MCP-1 (A), TNF-α (B), IL-1β (C), IL-6 (D), and IL-8 (E) concentrations from baseline to 12 mo in postmenopausal women in the control (n = 70), 50 g prune/d (n = 67), and 100 g prune/d (n = 46) groups. Data are mean ± SD. IL, interleukin; MCP, monocyte chemoattractant protein; TNF, tumor necrosis factor.

Inflammatory cytokines from LPS-stimulated PBMCs

The percent change in MCP-1 secretion from LPS-stimulated PBMCs from baseline to 12 mo did not differ among the groups (Figure 5A; P = 0.30). However, there was a main effect of treatment on percent change in TNF-α (Figure 5B; P < 0.01), IL-1β (Figure 5C; P = 0.01), IL-6 (Figure 5D; P < 0.01), and IL-8 (Figure 5E; P = 0.03) secretion from LPS-stimulated PBMCs from baseline to 12 mo. The percent change from baseline in TNF-α secretion was significantly lower in the 50 g prune/d group compared with the control group [−4.4% ± 43.0% in 50 g prune/d compared with 24.3% ± 70.7% in control, Tukey’s post hoc test, P < 0.01; effect size: 28.7 (0.6, 56.8)]. Furthermore, the percent change from baseline in IL-1β, IL-6, and IL-8 secretion was significantly lower in the 100 g prune/d group compared with the control group [−8.9% ± 61.6%, −4.3% ± 75.3%, −14.3% ± 60.8% in 100 g prune/d compared with 46.9% ± 107.4%, 16.9% ± 70.6%, 39.8% ± 90.8% in control for IL-1β, IL-6, and IL-8, respectively, Tukey’s post hoc test, all P < 0.05; effect size: 55.8 (1.1, 110.3), 21.2 (−18.0, 60.4), 54.1 (−5.3, 85.1) for IL-1β, IL-6, and IL-8, respectively). SAS codes for statistical analyses are provided in Supplemental Table 3.

FIGURE 5.

FIGURE 5

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Change in MCP-1 (A), TNF-α (B), IL-1β (C), IL-6 (D), and IL-8 (E) secretion from LPS-stimulated peripheral blood mononuclear cells from baseline to 12 mo in postmenopausal women in the control (n = 30), 50 g prune/d (n = 36), and 100 g prune/d (n = 21) groups. Data are mean ± SD. Labeled means without a common letter differ, P < 0.05. IL, interleukin; LPS, lipopolysaccharide; MCP, monocyte chemoattractant protein; TNF, tumor necrosis factor.

Discussion

The current investigation is an ancillary study of the parent 12-mo RCT, the Prune Study, conducted in postmenopausal women to investigate the dose–response effect of prunes, at 50 and 100 g/d, as a whole-food, dietary intervention on a broad range of immune, inflammatory, and oxidative stress markers. We demonstrated a significant decrease in the percentage of circulating monocytes in the 100 g prune/d group compared with the no-prune control group at 12 mo. Furthermore, we observed a significant reduction in the percentage of circulating activated monocytes expressing TLR-2 from baseline in the 100 g prune/d group compared with the control. Although prune consumption did not modulate circulating levels of hs-CRP, markers of oxidative stress, and proinflammatory cytokines, we noted a significant reduction in TNF-α secretion and in IL-1β, IL-6, and IL-8 secretions from LPS-stimulated PBMCs from baseline, in the 50 and 100 g prune/d groups, respectively, compared with the control group. Collectively, our findings suggest that dietary supplementation with 50–100 g prunes may reduce inflammatory mediators that are important in the bone-signaling pathways and may attenuate bone loss in postmenopausal women but that this effect may not occur in dose-dependent manner for all outcomes.

Monocytes represent one of the major immune cell types in PBMCs that express MHC Class II (HLA-DR) upon activation and drive the chronic inflammatory response [46]. Additionally, monocytes express TLRs, which, upon co-stimulation with CD14 and LPS, activate nuclear factor-κB–mediated proinflammatory signaling cascades [47]. Activated CD14+ monocytes with upregulated expression of HLA-DR and TLRs mediate bone loss in inflammatory bone diseases, such as rheumatoid arthritis, by migrating to the bone microenvironment and differentiating into osteoclasts [48,49]. In our cohort of postmenopausal women, the intensity (MFI) of TLR-2 increased over time in all groups; however, 12-mo supplementation with 100 g prune/d resulted in a 1.8% decrease in the percentage of TLR-2+ activated monocytes from baseline, compared with the no-prune control group. Recent studies demonstrate that menopause is associated with a higher blood monocyte count with a concomitant increase in plasma TNF-α and IL-6 [50]. Moreover, PBMCs isolated from postmenopausal women with low bone mass or osteoporosis exhibited higher IL-1, TNF-α, and IL-6 secretion compared with healthy controls [51]. Previous human trials have assessed the immunomodulatory effects of other phenolic-rich foods as a dietary intervention in adults with chronic disease. In a crossover RCT of adults at risk of cardiometabolic disease, spice consumption for 4 wk lowered the percentage of classical monocytes by 4.5% from baseline [52]. Blueberry supplementation for 6 wk in adults with metabolic syndrome downregulated TLR4 gene expression in CD14+ monocytes compared with a placebo control group [53]. Prior in vitro work [54] demonstrates that polyphenolic extracts from prunes downregulate Tlr2 gene expression in LPS-stimulated RAW264.7 cells (osteoclast precursors). Previous studies and our findings together suggest that it is biologically plausible that prunes might exert bone-protective effects, in part, by suppressing activated monocytes and their secretion of bone-resorptive inflammatory cytokines.

CRP is associated with higher bone turnover [55], decline in bone density [7,56], and increased risk of osteoporotic fractures in postmenopausal women [57,58]. Additionally, elevated levels of markers of oxidative stress are associated with poorer bone outcomes in postmenopausal women [59]. We observed no significant change in hs-CRP, TAC, or 8-isoprostane in postmenopausal women after 12 mo of 50 or 100 g prune/d supplementation. Two other RCTs [32,33] investigated the effect of prunes on CRP levels in postmenopausal women with or without low bone mass and both reported no change in CRP at 6 mo following 50 or 100 g prune consumption/d. However, Hong et al. [35] report a significant increase in TAC following 6 mo of 50 g prune consumption/d. Although the prune doses administered in our study were similar to those by Hong et al., our sample size was larger (n = 183) than theirs (n = 40). Despite this, the lack of a significant dose-dependent effect of prunes on TAC might be partly attributed to several reasons, including high within-individual variation, different dietary patterns of individuals, timing of measurement (6 compared with 12 mo), and potential nonlinear associations between prune dose and TAC. Although hs-CRP is widely used as a systemic inflammatory marker [43], the null findings in CRP in the current and previous studies [33] suggest that it may not be a sensitive biomarker to evaluate the anti-inflammatory properties of prunes. Prune-related changes in antioxidant capacity have not been studied extensively; thus, additional studies are needed to determine if a reduction in oxidative stress may be a potential pathway by which prunes exert a beneficial effect on bone outcomes.

Epidemiologic evidence suggests that higher proinflammatory cytokine levels are linked to a decline in bone density and an increased risk of osteoporotic fractures in postmenopausal women [57,[60], [61], [62], [63]]. In the current study, plasma levels of proinflammatory cytokines did not differ among the no-prune control, 50 g prune/d, and 100 g prune/d groups after 12 mo of intervention. To date, only a single RCT [35] has investigated the effect of prune consumption on circulating levels of proinflammatory cytokines in postmenopausal women. In their report on secondary outcome analyses of a 6-mo RCT, Hong et al. [35] demonstrated that postmenopausal women who consumed 50 g prune/d for 6 mo had significantly lower plasma concentrations of IL-6 and TNF-α compared with baseline, but they report no changes in the no-prune control or 100 g prune/d groups. Although our RCT was comparable in prune dose and study population of postmenopausal women with osteopenia, the duration might partly explain the lack of prune effect observed on plasma levels of proinflammatory cytokines. These changes might have occurred after 3 or 6 mo of prune supplementation, which was not measured in the current study. Future RCTs should investigate the kinetics of plasma markers of inflammation and bone turnover to determine whether changes in these markers after prune supplementation at earlier time points predict the beneficial effects of prunes on bone density at later time points.

Proinflammatory cytokine profiles from ex vivo cultured PBMCs are associated with a higher bone-resorptive activity in postmenopausal women [36,64] and have been reported as a potential biomarker to discriminate postmenopausal women with chronic bone diseases, including osteopenia, osteoporosis, and rheumatoid arthritis, from healthy controls [51,65,66]. In our study, postmenopausal women in the no-prune control group experienced a 24.3% increase from baseline in TNF-α secretion from PBMCs. In contrast, women in the 50 g prune/d group had a 4.4% decrease from baseline in TNF-α secretion from PBMCs. In the primary end point article [34], 50 g prune/d prevented the loss of total hip BMD after 6 mo and persisted throughout the 12-mo RCT. Our current findings suggest that decreased TNF-α secretion with 50 g prune/d may be a potential mediator of the observed bone-protective effects; however, further investigation is needed to clarify this mechanistic association. Furthermore, although the control group experienced a percent increase from baseline in IL-1β, IL-6, and IL-8 secretion from PBMCs, 100 g prune/d blunted this rise in cytokines, resulting in 8.9%, 4.3%, and 14.3% decrease from baseline in IL-1β, IL-6, and IL-8 secretion, respectively. Additionally, 100 g/d of prunes reduced the percentage of activated TLR-2+ monocytes, which may contribute to the blunted cytokine secretion from PBMCs. Preclinical studies demonstrate that polyphenolic extracts from prunes are responsible for their anti-inflammatory properties by suppressing the expression of TLR-2, nuclear factor-κB, and their downstream proinflammatory cytokines [30]. The lack of a distinct dose–response effect of prune supplementation on inflammatory mediators in our study might be partly because of small sample sizes in our secondary data set, thus rendering low statistical power to detect these differences. The differential findings from our study might have been partly due to the free-living study design, in which participants may have added or replaced prunes into their habitual diet, and should be further investigated. Prior studies investigating the anti-inflammatory effects of polyphenol-rich fruits report inconsistent findings on the dose–response effect [67]. Future research is needed to better understand the optimal dose and duration required to elicit beneficial health effects.

A major strength of the current investigation is the assessment of a broad range of immune, inflammatory, and oxidative stress end points in the largest cohort of postmenopausal women, to date, to explore possible mediators linking prune consumption and bone health in postmenopausal women. Furthermore, all 183 participants who completed the 12-mo RCT were >90% compliant with the prune intervention, and the average daily intake of total kilocalories did not change across groups throughout the intervention period [34], suggesting successful incorporation of prunes into the background diet. Limitations of this study include racial and ethnic homogeneity of our study participants, as a majority of the postmenopausal women were Caucasian, and the possibility of selection bias, thus limiting the generalizability of our findings. Furthermore, participants were not blinded to the intervention, thus raising the possibility of potential bias. We only measured cytokine concentrations at a single time point of 4 h post–LPS stimulation, and thus, future work should include additional time points of supernatant cytokine measurement after LPS stimulation as cytokine secretion patterns may differ temporally [68]. Finally, although all immune, inflammatory, and oxidative stress markers reported in this study are prespecified secondary outcomes of the parent RCT [37], we cannot exclude the possibility of increased likelihood of type 1 error from the analysis of multiple secondary outcomes [69]. Therefore, these findings must be interpreted with caution and assessed in subsequent RCTs with larger, more diverse populations.

In conclusion, dietary supplementation with 50–100 g prunes reduced proinflammatory cytokine secretion from PBMCs and suppressed the percentage of activated monocytes in circulation. Postmenopausal women diagnosed with osteoporosis require lifelong management [70], and our findings suggest that prunes may represent a plausible non-pharmacologic treatment approach to improve bone health by attenuating chronic, low-grade inflammation associated with postmenopausal bone loss.

Author contributions

The authors’ responsibilities were as follows – CJR, MJD, NIW: designed the research; JJD, ESO, NCAS: conducted the research and collected data; JJD, HL, CJR: participated in data analysis and interpretation and/or wrote the paper; JJD, ESO, MJD, NCAS, NIW, CHN, HL, CW, CJR: revised the manuscript; CJR: had primary responsibility for the final content; and all authors: read and approved the final manuscript.

Funding

This work was supported by the California Prune Board Award Number: 180215 (to CJR and MJD). In addition, this study was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health (NIH) Award Number TL1TR002016 (to JJD). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. The funding agencies had no role in the study design, data collection, analysis, interpretation, writing, decision to publish, or preparation of the manuscript.

Data availability

Data described in the manuscript, code book, and analytic code will be made available upon request pending application and approval.

Conflict of interest

CW and CJR are members of the Nutritional Advisory Panel for the California Prune Board. All other authors report no conflict of interest.

Acknowledgments

We thank the California Prune Board for providing funding for this work. We thank the research staff at The Women’s Health and Exercise Lab and the Clinical Research Center (PSU). We thank the Biomarker Core Laboratory in the Department of Biobehavioral Health (PSU) for the use of the MesoScale Discovery platform to obtain biological assay data. We thank the Flow Cytometry Facility in the Huck Institutes of the Life Sciences (PSU) for use of the BD LSR-Fortessa Cytometer.

Footnotes

Appendix A

Supplementary data to this article can be found online at https://doi.org/10.1016/j.tjnut.2023.11.014.

Appendix A. Supplementary data

The following is the Supplementary data to this article:

Multimedia component 1
mmc1.docx (511.2KB, docx)

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Supplementary Materials

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Data Availability Statement

Data described in the manuscript, code book, and analytic code will be made available upon request pending application and approval.

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