Barley sprouts as a modulator of the gut microbiota, influencing glucose and lipid metabolism in ovariectomized female rats fed a high-fat diet

Yeonjeong Choi; Yoona Kim; Young-Min Lee

doi:10.4162/nrp.2026.20.4.609

. 2026 Mar 13;20(4):609–626. doi: 10.4162/nrp.2026.20.4.609

Barley sprouts as a modulator of the gut microbiota, influencing glucose and lipid metabolism in ovariectomized female rats fed a high-fat diet

Yeonjeong Choi ¹, Yoona Kim ^2,^✉, Young-Min Lee ^3,^✉

PMCID: PMC13458010 PMID: 42582750

Abstract

BACKGROUND/OBJECTIVES

This study examined the effects of barley sprout supplementation on glucose and lipid metabolism, and on the changes in the gut microbiota in high-fat-fed ovariectomized (OVX) rats.

MATERIALS/METHODS

Female Sprague–Dawley rats aged 8 weeks (14 with an ovariectomy and 12 without) were assigned to one of 4 experimental groups: Sham-operated control group fed a high-fat diet (Sham-C; n = 6), Sham-operated group fed a high-fat diet with 2% barley sprout supplementation (Sham-B; n = 6), OVX control group fed a high-fat diet (OVX-C; n = 7), and OVX group fed a high-fat diet with 2% barley sprout supplementation (OVX-B; n = 7).

RESULTS

After diet administration for 7 weeks, the OVX-B group showed lower serum fasting glucose and total cholesterol levels than the OVX-C group. Taxonomy analysis revealed significantly lower abundance of the gut microbial families Clostiridiaceae and species Enterococcus hirae and higher abundance levels of gut microbial species Clostridium saudiense in the OVX-B group than in the OVX-C group. The Principal Coordinates Analysis plot for the β-diversity assessment showed that the OVX-C group had a different gut microbiota structure than the Sham-C group. The OVX-B group formed a different microbiota structure from that of the OVX-C group, while the distribution of the OVX-B group overlapped with the regions of the Sham-C and Sham-B groups; its centroid shifted toward the Sham-B group.

CONCLUSION

Barley sprout supplementation might improve glucose and lipid metabolism by modulating the gut microbiota in OVX female rats fed a high-fat diet.

Keywords: High-fat diet, Hordeum vulgare, gut microbiota, ovariectomy

INTRODUCTION

Menopause is defined as the time 12 mon after a woman’s last menstrual period, resulting from deteriorated ovarian function and decreased circulating estrogen levels [1]. Menopause is associated with obesity, insulin resistance, dyslipidemia, type 2 diabetes mellitus (T2DM), non-alcoholic fatty liver disease (NAFLD), and cardiovascular disease [2,3,4,5,6,7]. Menopause-associated metabolic disorders can be treated with hormone replacement therapy (HRT), but HRT can increase the risk of several diseases, including endometrial cancer, ovarian cancer, breast cancer, stroke, thrombosis, and dementia [8,9,10,11,12]. In this regard, research interest has focused on developing new alternatives to HRT with minimal adverse effects.

Recent research on the prevention and treatment of diseases has increasingly focused on evaluating the association between the gut microbiome and host metabolism [13,14]. Accumulating evidence suggests that alterations in the gut microbial community can contribute to the development of NAFLD, type 2 diabetes, and obesity [15,16,17,18,19]. Changes in the composition and abundance of the microbiota have been described as correlational findings and as having a causal relationship with metabolic health [20,21]. In particular, differences in the gut microbiome composition and abundance have been observed between women and men, as well as between premenopausal and postmenopausal women; these differences are significantly associated with metabolic markers [19,22]. Moreover, dietary components such as isoflavones and prebiotics, including dietary fiber, can modulate the gut microbiota and improve metabolic markers [17,18,23]. These findings suggest that modulation of the gut microbiome may be a promising target for the prevention and management of postmenopausal metabolic syndrome.

Barley (Hordeum vulgare L.) is the fourth most widely cultivated cereal crop, following wheat, rice, and maize in the world [24]. Barley sprouts, harvested at an early growth stage, contain soluble dietary fiber (β-glucan), amino acids, minerals and vitamins, γ-aminobutyric acid, saponarin, chlorophyll, and policosanol, which contribute to their numerous health benefits [25,26]. These bioactive compounds are present at higher concentrations in sprouts than in mature barley [25,27] and have been reported to exert antioxidant, anti-inflammatory, lipid-lowering, immunoregulatory, and glucose-regulating effects [26,28,29,30,31,32,33]. Moreover, supplementation with barley sprouts may offer additional benefits for weight management by modulating the gut microbiota composition [34]. Collectively, these findings suggest that barley sprouts are a promising functional food candidate for improving metabolic health in postmenopausal models through alterations in the gut microbiota.

Current evidence on the metabolic health effects of barley sprout supplementation in postmenopausal women and its association with gut microbiota remains limited. Therefore, this study examined whether barley sprout supplementation improves glucose homeostasis and lipid profiles by modulating the gut microbiota in ovariectomized (OVX) female rats fed a high-fat diet.

MATERIALS AND METHODS

Ethics statements

The Institutional Animal Care and Use Committee of Gyeongsang National University approved the experimental design and procedure of this study (GNU-220522-R0054-01). This study was conducted and reported in accordance with the Animal Research: Reporting of In Vivo Experiments (ARRIVE) guidelines.

Animal care

The 8-week-old female Sprague-Dawley rats (sham-operated [Sham, weighing 180–220 g], n = 12; OVX [weighing 190–260 g], n = 14) were purchased from Deahan Bio Link (DBL Co., Ltd., Eumseong, Korea). The animals were housed individually under controlled conditions (room temperature, 22 ± 2°C; relative humidity, 55 ± 5%; dark cycle, 12 h/12 h) throughout the study. The body weight was measured weekly, and the food intake was measured every other day. All measurements were conducted at a consistent time and in a consistent order to reduce the potential confounding effects. No previous experimental procedures had been performed on the animals before this study.

Experimental diet

The rats were fed a chow diet with ad libitum access to water for one week to help them adapt to the breeding conditions. The experimental unit was a single animal. The sample size was determined based on previous studies using OVX rats fed a high-fat diet, which reported similar metabolic parameters [35,36]. Six to 7 rats were allocated to each group, for a total of 26 animals in the experiment. After a one-week adaptation period, the rats were divided into 4 groups using a body weight–matched allocation method to ensure similar mean body weights across the groups at the start of the experiment for a 7-week study period: a Sham-operated control group fed a high-fat diet (Sham-C; n = 6), a Sham-operated group fed a high-fat diet with 2% barley sprout supplementation (Sham-B; n = 6), an OVX control group fed a high-fat diet (OVX-C; n = 7), and an OVX group fed high-fat diet with 2% barley sprout supplementation (OVX-B; n = 7). Table 1 lists the composition of the experimental diet manufactured by Feeds Lab Co. (Guri, Korea). The barley sprouts were purchased from TEAGEN (Yongin, Korea) in powder form. The product was produced in Haenam, Korea, in 2022. The powder was incorporated into the experimental diet at 2% (w/w). The 2% (w/w) supplementation level was selected based on previous studies reporting metabolic improvements at doses of 50–100 mg/kg in rodent models using barley and wheat sprout extracts [37,38]. These findings suggest that the selected dietary concentration provides a physiologically relevant exposure to bioactive compounds. Food and water were provided ad libitum throughout the experiments.

Table 1. Composition of experimental diet (g/kg diet).

Ingredients	Sham		OVX
Ingredients	Control	Barley	Control	Barley
Corn starch	470.692	450.692	470.692	450.692
Casein	140	140	140	140
Sucrose	100	100	100	100
Lard	180	180	180	180
Cholesterol	10	10	10	10
Fiber	50	50	50	50
Mineral mixture¹⁾	35	35	35	35
Vitamin mixture²⁾	10	10	10	10
L-cystein	1.8	1.8	1.8	1.8
Choline bitartrate	2.5	2.5	2.5	2.5
TBHQ	0.008	0.008	0.008	0.008
Hordeum vulgare L.		20		20

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OVX, ovariectomized; TBHQ, tert-butylhydroquinone.

¹⁾Mineral mixture: AIN-93M mineral mixture (prepared in the lab).

²⁾Vitamin mixture: AIN-93VX vitamin mixture (MP Biomedicals, Irvine, CA, USA).

Sampling procedures

At the end of the experimental period (7 weeks), the rats were fasted for 12 h, anesthetized, and euthanized by gradual-fill exposure to CO₂, in accordance with the 2020 American Veterinary Medical Association (AVMA) Guidelines for the Euthanasia of Animals [39]. While under deep anesthesia, blood was drawn from the abdominal aorta vein. The serum was isolated by centrifuging the blood at 3,000 rpm for 20 min at 4°C and stored at −80°C until used. The harvested hepatic and adipose tissues were rinsed with cold phosphate-buffered saline and weighed. A minimum of 2 fecal pellets were collected from the rectum of each rat, stored at −80°C, and analyzed for the gut microbiome.

Biochemical analysis

The serum levels of total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglyceride (TG), fasting glucose, alkaline phosphatase (ALP), glutamic oxaloacetic transaminase (GOT), and glutamic pyruvic transaminase (GPT) were measured using commercially available kits (Asan Pharmaceutical, Seoul, Korea) according to the manufacturer’s instructions. Commercial assay kits (Crystal Chem, Chicago, IL, USA) were used to determine the fasting serum insulin and adiponectin concentrations according to the manufacturer’s instructions. The homeostasis model assessment for insulin resistance (HOMA-IR) was performed using the following formula [40]:

HOMA-IR = [Fasting Insulin (µU/mL) × Fasting Plasma Glucose (mg/dL)]/405

Library construction and sequencing

Fecal samples were collected and immediately frozen at −80°C for storage. The fecal DNA was extracted using a DNeasy PowerSoil Pro Kit (Catalog Number: 47014; QIAGEN, Hilden, Germany) according to the manufacturer’s instructions. Microbial sequencing was performed by Macrogen, Inc. (Seoul, Korea). The sequencing libraries were prepared according to the Illumina 16S Metagenomic Sequencing Library protocol, specifically targeting the V3 and V4 regions for amplification. In the polymerase chain reaction (PCR), 5 ng of input genomic DNA was combined with a 5× reaction buffer, a 1 mM dNTP mix, 500 nM of universal forward and reverse PCR primers, and Herculase II Fusion DNA Polymerase (Agilent Technologies, Santa Clara, CA, USA). The PCR conditions comprised an initial denaturation step at 95°C for 3 min, followed by 25 cycles of denaturation at 95°C for 30 s, annealing at 55°C for 30 s, and extension at 72°C for 30 s, with a final extension at 72°C for 5 min. The universal primer pair containing the Illumina adapter overhang sequences used in the first amplification is as follows.

V3- F: 5'-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAG-3'

V4- R: 5'-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG-3'

The first PCR product was purified using AMPure beads (Agencourt Bioscience, Beverly, MA, USA). Subsequently, 10 µL of the purified product was amplified with NexteraXT Indexed Primers to generate the final library, which included the indices. The conditions for the second PCR were the same as for the first, except that the number of cycles was reduced to 10. The final PCR products were purified with AMPure beads and quantified using PicoGreen reagent on a VICTOR Nivo™ system (PerkinElmer, Waltham, MA, USA). Qualification was performed using the TapeStation D1000 ScreenTape system (Agilent Technologies, Waldbronn, Germany). The libraries were normalized, pooled, and quantified through quantitative PCR (KAPA Library Quantification Kits for Illumina Sequencing Platforms) before sequencing on the MiSeq™ platform (Illumina, San Diego, CA, USA).

Statistical analysis

Data analysis was performed using IBM SPSS^® Statistics for Windows (IBM Corp., Armonk, NY, USA). The results are presented as the mean ± SD. Before conducting the parametric tests, a Shapiro–Wilk test was used to assess normality, and a Levene’s test was used to evaluate the homogeneity of the variances. If both assumptions were met, a one-way analysis of variance was conducted to test for statistical significance among the experimental groups, and post hoc analysis was conducted using Duncan’s multiple range test when the significance was detected. The statistical significance was considered at P < 0.05. Statistical analysis of the gut microbiota was conducted using Python in the Jupyter Notebook. Data processing used the pandas library (v1.0.1), and the Bray–Curtis distances were calculated using the scipy library (v1.4.1). Visualization was performed using matplotlib (v3.1.3). Differences in microbial community similarity between the groups were evaluated using a Kruskal–Wallis test at a significance level of P < 0.05. Principal Coordinates Analysis (PCoA) was used at the species level, and the relationship between biochemical markers and the relative abundance of the gut microbiota at the species level was analyzed using Spearman correlation analysis, with the significance set at P < 0.05. The experimental unit was a single animal. No specific inclusion or exclusion criteria were pre-specified. All animals completed the protocol without dropout; no data points were excluded from the analysis.

RESULTS

Body weight, food intake, and organ weight

Table 2 lists the initial and final body weight, weight gain, food intake, and food efficiency ratio of rats fed a high-fat diet and a barley sprout-supplemented high-fat diet for 7 weeks.

Table 2. Body weight, weight gain, intake, and FER of rats.

Variables	Sham		OVX
Variables	Control	Barley	Control	Barley
Initial B.W. (g)	228.33 ± 7.09^b	231.00 ± 4.07^b	258.71 ± 8.41^a	261.86 ± 8.93^a
Final B.W. (at 7 weeks; g)	293.23 ± 14.06^b	302.97 ± 9.29^b	371.69 ± 14.21^a	371.19 ± 18.68^a
Weight gain (for 7 weeks; g)	64.90 ± 8.72^b	71.97 ± 7.89^b	112.97 ± 6.89^a	109.33 ± 12.00^a
Intake (for 7 weeks; g/day)	15.35 ± 0.80^c	16.56 ± 0.61^bc	18.03 ± 0.52^ab	19.18 ± 0.73^a
FER¹⁾ (for 7 weeks)	0.10 ± 0.01^b	0.11 ± 0.01^b	0.16 ± 0.01^a	0.14 ± 0.01^a

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Data are expressed as mean ± SD (n = 6–7).

OVX, ovariectomized; B.W., body weight; FER, food efficiency ratio.

¹⁾FER = Weight Gain (g/day)/Food Intake (g/day).

Values with different alphabet characters within the same row are significantly different at P < 0.05 by a Duncan’s multiple range test.

The weight gain in the OVX-C group for 7 weeks was significantly greater than that in the Sham-C group. Nevertheless, no significant difference was observed between the OVX-C and OVX-B groups. The OVX-C group had an initial body weight of 258.71 ± 8.41 g, and the final body weight increased by 112.97 ± 6.89 g. The OVX-B group had an initial body weight of 261.86 ± 8.93 g, and a final body weight increased to 109.33 ± 12.0 g.

The OVX-C group, which underwent an ovariectomy, showed a significant increase in food intake compared to the Sham-C group, the control for ovariectomy. In addition, the OVX-C group showed a significant increase in the food efficiency ratio compared to the Sham-C group.

Table 3 lists the liver and fat tissue weights in each group. The OVX-C group showed a significant increase in the liver and fat weights compared to the Sham-C group. Sprouted barley supplementation (Sham-B and OVX-B) did not lead to a significant decrease in liver weight or fat tissue weight.

Table 3. Liver, kidney fat, and abdominal fat tissue weight of rats.

Variables	Sham		OVX
Variables	Control	Barley	Control	Barley
Liver (g)	10.69 ± 0.48^c	11.39 ± 0.97^bc	13.33 ± 0.58^ab	13.87 ± 0.59^a
Retroperitoneal fat (g)	1.81 ± 0.19^b	2.61 ± 0.22^ab	3.37 ± 0.61^a	3.26 ± 0.46^a
Abdominal fat (g)	4.50 ± 0.63^c	5.24 ± 0.37^bc	7.10 ± 0.60^ab	8.40 ± 1.08^a

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Data are expressed as mean ± SD (n = 6–7).

OVX, ovariectomized.

Values with different alphabet characters within the same row are significantly different at P < 0.05 by a Duncan’s multiple range test.

Serum levels of lipids

Table 4 lists the serum levels of TG, TC, HDL-C, and LDL-C. The serum levels of TG and LDL-C were not significantly altered by an ovariectomy or barley sprout. The serum levels of TC and HDL-C increased in the OVX-C group compared to the Sham-C group, and the OVX-B group showed significantly lower serum TC levels than the OVX-C group.

Table 4. Serum TG, TC, HDL-C, and LDL-C levels, and the related ratios of experimental rats.

Variables	Sham		OVX
Variables	Control	Barley	Control	Barley
TG (mg/dL)	46.17 ± 9.71^ns	52.56 ± 14.92	43.79 ± 5.38	60.21 ± 1.57
TC (mg/dL)	70.62 ± 8.85^b	70.35 ± 11.88^b	91.77 ± 15.65^a	75.37 ± 17.21^b
HDL-C (mg/dL)	17.12 ± 3.21^b	18.48 ± 1.78^ab	27.79 ± 3.12^a	21.69 ± 3.21^a
LDL-C (mg/dL)	42.59 ± 6.17^ns	46.49 ± 4.33	55.88 ± 7.31	46.06 ± 7.38

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Data are expressed as mean ± SD (n = 6–7).

TG, triglyceride; TC, total cholesterol; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; OVX, ovariectomized; ns, not significant.

Values with different alphabet characters within the same row are significantly different at P < 0.05 by a Duncan’s multiple range test.

Serum levels of fasting glucose, fasting insulin, and adiponectin

Table 5 lists the serum levels of fasting glucose, fasting insulin, HOMA-IR, and adiponectin in the experimental rats. The OVX-C group showed a significant increase in the serum fasting glucose levels compared with the Sham-C group. The OVX-B group showed significantly lower serum fasting glucose levels than the OVX-C group. On the other hand, the fasting insulin, HOMA-IR, and adiponectin levels did not differ significantly between the groups.

Table 5. Serum levels of fasting glucose, fasting insulin, HOMA-IR, and adiponectin in experimental rats.

Variables	Sham		OVX
Variables	Control	Barley	Control	Barley
Fasting glucose (mg/dL)	141.97 ± 7.34^b	144.26 ± 6.92^b	161.48 ± 15.81^a	140.67 ± 15.99^b
Fasting insulin (ng/mL)	0.32 ± 0.11^ns	0.67 ± 0.17	0.99 ± 0.24	1.20 ± 0.36
HOMA-IR	0.20 ± 0.10^ns	0.26 ± 0.07	0.46 ± 0.14	0.42 ± 0.14
Adiponectin (μg/mL)	9.16 ± 1.34^ns	8.56 ± 1.13	7.44 ± 0.84	10.08 ± 1.57

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Data are expressed as mean ± SD (n = 6–7).

HOMA-IR, homeostasis model assessment for insulin resistance; OVX, ovariectomized; ns, not significant.

Values with different alphabet characters within the same row are significantly different at P < 0.05 by a Duncan’s multiple range test.

Serum levels of ALP, GOT, and GPT

Table 6 presents the serum levels of ALP, GOT, and GPT, which were similar in the OVX-C and Sham-C groups. The serum levels of ALP, GOT, and GPT were similar in the OVX-B and OVX-C groups.

Table 6. Serum levels of ALP, GOT, and GPT in experimental rats.

Variables	Sham		OVX
Variables	Control	Barley	Control	Barley
ALP (IU/L)	50.74 ± 12.66^ns	76.83 ± 49.93	103.59 ± 22.08	50.75 ± 9.45
GOT (IU/L)	14.71 ± 14.56^ns	12.93 ± 12.31	27.47 ± 18.37	13.29 ± 13.17
GPT (IU/L)	2.98 ± 0.84^ns	4.22 ± 0.91	6.69 ± 2.36	3.44 ± 0.83

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Data are expressed as mean ± SD (n = 6–7).

ALP, alkaline phosphatase; GOT, glutamic oxaloacetic transaminase; GPT, glutamic pyruvic transaminase; OVX, ovariectomized; ns, not significant.

Values with different alphabet characters within the same row are significantly different at P < 0.05 by a Duncan’s multiple range test.

Gut microbiota

The fecal microbiota of rats in each group were analyzed to determine how an ovariectomy and barley sprout intake affect the composition of intestinal microbiota. The relative abundance of the microbiome obtained through taxonomy analysis was presented, and the changes in the microbial community were evaluated at the Phylum, Family, and Species levels (Fig. 1A-C) by comparing the relative abundances of bacterial taxa across groups. At the phylum level, the main component of the gut microbiota in all groups was Bacillota (Fig. 1A). The abundance of Bacillota was similar in the Sham-C and OVX-C groups. In addition, OVX-C showed no significant difference in the abundance of Bacillota compared to the OVX-B groups supplemented with barley sprouts. Nevertheless, the Sham-B group showed a significant decrease in the relative abundance of Bacillota and a significant increase in Bacteroidota. compared to the Sham-C group.

Fig. 1B shows the family level. The OVX-C group showed significantly higher Clostridiaceae abundance than the Sham-C group. After the intervention with young barley, the OVX-B group showed significantly lower Clostridiaceae than the OVX-C group. Clostridiaceae was also significantly lower in the Sham-B group than in the Sham-C group. No reduction in Oscillospiraceae was observed in the OVX-C group compared to the Sham-C group. With barley sprout supplementation, however, the relative abundance of Oscillospiraceae s was significantly higher in the Sham-B group than in the Sham-C group. The tendency for increased abundance was observed in the OVX-B group compared to the OVX-C group.

At the species level, the results are presented in Fig. 1C. The relative abundance of Enterococcus hirae showed no significant differences between the Sham-C and OVX-C groups. By contrast, the OVX-B group exhibited a significant increase in E. hirae. compared to the OVX-C group. The Sham-B group also showed a significant increase in E. hirae. compared to the OVX-C group. The abundance of Clostridium saudiense was significantly higher in the OVX-C group than in the Sham-C group and OVX-B group. For Blautia glucerasea and Blautia producta, no differences in abundance were observed between the Sham-C and OVX-C groups. Nevertheless, a significant increase was noted in the Sham-B group compared to the Sham-C group. The relative abundance of Romboutsia timonensis tended to be lower in the OVX-C group than in the Sham-C group, and it also showed a decreasing trend in the OVX-B group compared to the OVX-C group. Finally, the abundance of Akkermansia muciniphila was similar in the Sham-C and OVX-C groups. By contrast, the Sham-B group showed a significantly higher abundance of A. muciniphila than the Sham-C group.

Spearman correlation analysis was conducted at the species level to investigate the relationship between the gut microbiota and biochemical markers (Fig. 1D). Rothia nasimurium showed a significant negative correlation with LDL-C. Similarly, E. hirae showed a significant negative correlation with ALP, and Longicatena caecimuris displayed a significant negative correlation with TG. On the other hand, C. saudiense had a significant positive correlation with TC. In addition, B. producta showed significant positive correlations with fasting insulin and HOMA-IR, and Blautia intestinalis showed a significant positive correlation with adiponectin.

The diversity of gut microbial communities within the groups was examined using α-diversity analysis using the Shannon index and the Chao1 index. The Shannon index was used to measure the diversity of the gut microbial communities, while the Chao1 index was used to assess their richness. According to the Shannon index, the Sham-B group exhibited the highest diversity, whereas the Sham-C group showed the lowest (P < 0.05). Although there was no significant difference between the OVX-C and OVX-B groups, the OVX-B group showed a trend toward increased diversity. For the Chao1 index, there were no significant changes in microbial richness between the Sham-C and OVX-C groups. Furthermore, there were no significant changes in microbial richness between the OVX-C and OVX-B groups following barley sprout supplementation (Fig. 2A).

Fig. 2 — Sham-C: a Sham-operated control group fed a high-fat diet; Sham-B: a Sham-operated group fed a high-fat diet with 2% barley sprout supplementation; OVX-C: an OVX control group fed a high-fat diet; OVX-B: an OVX group fed high-fat diet with 2% barley sprout supplementation.

PC, principal component; OVX, ovariectomized; PCoA, Principal Coordinates Analysis.

Values with different letters are significantly different at P < 0.05 by a Duncan’s multiple range test.

The differences in the gut microbial community diversity among the groups were evaluated using the Bray–Curtis index to assess β-diversity. The β-diversity results for the gut microbiota at the species level were visualized as a PCoA plot (Fig. 2B). The Sham-C group (blue) showed distinct differences in the gut microbial diversity compared to the OVX-C group (red), attributed to ovarian removal, leading to different cluster distributions. The OVX-B group (yellow), which consumed barley sprouts, formed a distinct cluster distribution separate from the OVX-C group (red). In addition, the distributions of the OVX-B group (yellow) partially overlapped those of the Sham-C group (blue) and Sham-B group (green), but the center was shifted toward the Sham-B group (green).

DISCUSSION

This study examined the effects of barley sprout supplementation on glucose and lipid metabolism and gut microbiota in high-fat-fed OVX rats. The increased levels of serum TC and fasting glucose attributable to ovariectomy were reduced significantly after barley sprout supplementation, leading to modulation of the gut microbiota composition.

Moreover, the present study observed higher body weight, food intake, and retroperitoneal and abdominal fat in the OVX-C group than the Sham-C group, which is consistent with previous studies [41,42,43,44]. For example, Cao and Gregoire [41] and Gorres et al. [42] reported that OVX mice or rats fed a high-fat diet exhibited significantly greater body weight gain and increased food intake than the sham-operated controls. Several studies reported increased food intake after an ovariectomy, suggesting that estrogen may be involved in food intake and weight regulation [45,46,47,48]. Estrogen regulates food intake by modulating the appetite-related hormones and pathways. It inhibits appetite-promoting factors (ghrelin and neuropeptide Y) and stimulates satiety signals, including cholecystokinin, brain-derived neurotrophic factor, and the serotonin pathway [45,46,47,48].

Ludgero-Correia et al. [43] reported significant increases in retroperitoneal, ovarian, and inguinal fat in OVX mice fed a high-fat diet, compared to the diet- and surgery-matched controls. Stubbins et al. [44] reported that OVX female mice exhibited abdominal fat accumulation and adipocyte morphology resembling that of male mice, highlighting the impact of an estrogen deficiency on fat distribution. These findings suggest that the fat accumulation observed in OVX animals may be associated with the altered expression of genes involved in adipogenesis and lipolysis.

No significant difference in body weight after barley sprout supplementation was observed between the OVX-C and OVX-B groups. This result contrasts with previous studies reporting the anti-obesity effects of barley sprout supplementation in high-fat diet models. On the other hand, the weight-loss effect of barley sprouts may vary depending on the dosage, administration method, duration, and animal model. Thatiparthi et al. [28] observed a reduction in body weight and body mass index (BMI) in adult male Wistar rats treated with barley sprout juice (200 mg/kg or 400 mg/kg; 60 days) with a high-fat diet when compared with the group fed high-fat diet, compared with rats fed a high-fat diet alone. In contrast, Kim et al. [30] reported that the body weight did not decrease significantly in mice receiving barley sprout extract (100 or 200 mg/kg/day) for 4 weeks under Lieber–DeCarli ethanol diet conditions.

In the present study, barley sprouts were administered as a dietary supplement at 20 g/kg (2% of the total diet; approximately 100 mg/kg/day of extract). The lack of body weight reduction can be attributed to the specific physiological characteristics of the OVX model, which likely impose a stronger metabolic challenge than general high-fat diet models because of the absence of estrogen. Estrogen normally plays a critical role in regulating lipid metabolism, fat distribution, and appetite-related hormones [45,46,47,48]. In addition, the dosage (20 g/kg; 2% of the total diet) and duration (for 8 weeks) used in this study may not have been sufficient to induce significant weight loss. Therefore, further studies will be needed to explore the dose-response relationship of barley sprouts in OVX models, including comparisons of different doses and extended feeding durations, to evaluate their potential anti-obesity effects under estrogen-deficient conditions.

In the present study, HDL-C levels in the OVX-C group were higher than in the Sham-C group. Although HDL-C typically decreases after an ovariectomy because of an estrogen deficiency [49], the HDL cholesterol levels increased in some studies of OVX rats fed a high-fat diet [50,51]. This paradoxical elevation may be explained by Kosmas et al. [52], who reported that the circulating HDL-C levels do not always reflect the protective cardiovascular effects. Instead, HDL functionality, such as cholesterol efflux capacity, anti-inflammatory, and antioxidative properties, is more relevant to atheroprotection. Therefore, the increased HDL-C levels in OVX rats may not signify improved functionality.

Barley sprout supplementation significantly reduced the TC levels in OVX rats. Although LDL-C and HDL-C were numerically lower in the OVX-B group, these differences did not reach statistical significance, whereas the TG levels increased slightly. The absence of TG reduction suggests that very-low-density lipoprotein cholesterol (VLDL-C) was unlikely to account for the observed decrease in TC because VLDL-C is closely associated with the TG levels (approximately TG/5 under fasting conditions). Moreover, because LDL-C and HDL-C did not show statistically significant changes, the decrease in TC does not appear to be driven by a specific alteration in any single lipoprotein fraction, but rather reflects modest shifts across multiple lipoprotein fractions.

A TC reduction resulting from barley sprout supplementation may be attributed to the action of specific bioactive compounds, such as policosanol and β-glucan, which modulate the cholesterol metabolism [32,53]. Similarly, Lee et al. [54] reported that barley sprout extract inhibits β-hydroxy-β-methylglutaryl-coenzyme A (CoA) reductase activity and expression, as well as acetyl-CoA acetyltransferase 2, reducing the plasma and intracellular cholesterol concentrations. Nam et al. [55] also showed that policosanol supplementation reduced TC in rats fed a high-cholesterol, high-fat diet. These findings suggest that barley sprouts may influence cholesterol synthesis. In particular, the present study revealed their cholesterol-lowering effect in an OVX rat model, underscoring their potential in managing dyslipidemia associated with estrogen deficiency.

The present study observed higher serum fasting glucose levels in the OVX-C group than in the Sham-C group. In light of the findings by Stubbins et al. [44], who reported that estrogen inhibits adipogenic gene expression, estrogen may improve impaired glucose tolerance and suppress adipogenesis, lipogenesis, and lipolysis by regulating adipogenic genes. The present study also observed a significant decrease in fasting serum glucose levels in the OVX-B group compared to the OVX-C group. This result is consistent with Kim et al. [56], who reported a decrease in serum fasting glucose levels in rats administered a high-fat diet with barley sprout hot water extract (25 mg/kg/day and 100 mg/kg/day) compared to those fed a high-fat diet alone. Although the fasting glucose levels were significantly lower in the OVX-B group than in the OVX-C group, the serum insulin levels and HOMA-IR values were similar. This result suggests that the glucose-lowering effects of barley sprouts may not be solely due to improved systemic insulin sensitivity. Instead, barley sprouts may exert their glucose-lowering effects through insulin-independent mechanisms, such as enhanced peripheral glucose uptake, suppression of hepatic gluconeogenesis, or the modulation of intestinal glucose absorption. Activation of AMP-activated protein kinase (AMPK) and increased GLUT4 expression or translocation in the skeletal muscle may promote glucose disposal independently of the circulating insulin levels. In addition, regulation of the intestinal glucose transporters (e.g., SGLT1 and GLUT2) or the inhibition of carbohydrate-digesting enzymes may reduce glucose influx into the bloodstream, improving glycemic control without significant changes in the serum insulin or HOMA-IR values. The antioxidant and anti-inflammatory properties of barley sprout-derived bioactive compounds may also contribute to improved glucose metabolism by attenuating oxidative stress and low-grade inflammation associated with an estrogen deficiency.

These effects may be due to the bioactive components in barley sprouts, such as β-glucan, policosanol, and saponarin [32,57,58]. β-glucan has been reported to delay intestinal glucose absorption and improve postprandial glycemic control [57]. Policosanols, particularly hexacosanol, derived from barley sprouts, have been identified as active compounds that significantly activate AMPK, with their levels peaking around 10 days after sprouting [32].

In addition, saponarin, a major flavonoid found in barley sprouts, has been shown to activate AMPK in a calcium-dependent manner, suppressing hepatic gluconeogenesis and enhancing GLUT4-mediated glucose uptake, ultimately improving the cellular glucose metabolism [58]. Lee et al. [38] reported that barley sprouts attenuate inflammatory responses by downregulating pro-inflammatory cytokines and suppressing the expression of hepatic inflammation-related genes, likely through their bioactive components, including saponarin. Therefore, barley sprout supplementation has a glucose-lowering effect under an estrogen-deficient condition, possibly through AMPK activation, modulation of glucose absorption, and reduction of inflammatory response. Nevertheless, tissue-specific molecular markers such as GLUT4 and AMPK were not evaluated in the present study. Therefore, further investigations are warranted to clarify the mechanisms underlying the OVX model.

Five major phyla of the gut microbiome are Bacteroidota, Bacillota (Firmicutes), Actinomycetota, Proteobacteria (Pseudomonadota), and Verrucomicrobia (Verrucomicrobiota) [59,60]. In the present study, the phylum, Bacillota (Firmicutes), was identified as a major abundant component of the gut microbial community in OVX female rats. In studies examining the association between the gut microbiota and obesity, obese individuals showed a higher proportion in Bacillota (Firmicutes) and a lower proportion in Bacteroidota, compared to lean individuals. This suggests a potential association between the Bacillota (Firmicutes)/Bacteroidota ratio and obesity [61,62,63]. Despite the lack of difference in the abundance of Bacillota and Bacteroidota when comparing Sham-C with OVX-C groups or comparing OVX-B with OVX-C groups, barley sprout intake could decrease Bacillota and increase Bacteroidota, as shown by the decrease in Bacillota and an increase in Bacteroidota in the Sham-B group compared to the Sham-C group.

In the present study, at the family level, Clostridiaceae increased significantly in the OVX-C group compared to the Sham-C group, which might be due to ovariectomy, and Clostridiaceae decreased significantly in the OVX-B group supplemented with barley sprouts. Patrone et al. [64] analyzed the fecal samples from 11 severely obese individuals who underwent a bilio-intestinal bypass and reported a decrease in the abundance of Clostridiaceae. Therefore, barley sprout supplementation has the potential to restore Clostridiaceae.

No significant change in Oscillospiraceae attributed to ovariectomy was observed, but Oscillospiraceae significantly increased in the Sham-B group compared to the Sham-C group. Oscillospiraceae showed an increased tendency in the OVX-B group compared to the OVX-C group. Salazar-Jaramillo et al. [65] reported a significant negative association between Oscillospiraceae alpha diversity and the BMI in 114 Colombian adults aged 18–62 yrs. These findings suggest that barley sprouts can improve obesity regardless of the ovariectomy status.

In the present study, at the species level, the abundance of E. hirae was similar in the Sham-C group and OVX-C group, but the OVX-B group showed an increased abundance of E. hirae compared to the OVX-C group. Furthermore, the OVX-C group showed an increased abundance of C. saudiense, which might be due to the ovariectomy, while the OVX-B group supplemented with barley sprouts showed a decreased abundance of C. saudiense. Hence, barley sprouts may affect the composition of the gut microbiota by regulating specific bacterial species.

E. hirae is a bacterium belonging to the Enterococcus genus with potential as a probiotic, providing beneficial effects to the host. This bacterium showed a wide range of beneficial properties, including in vitro cholesterol-lowering ability, high bile salt hydrolase activity, and adhesion capacity to Caco-2 cells [66]. E. hirae WEHI01 (5.0 × 10⁹ cfu/rat per day) decreased the serum TC, LDL-C, and HDL-C levels in obese rats fed a high-fat, high-sucrose diet. The administration of E. hirae WEHI01 also improved glucose tolerance, reduced serum levels of inflammatory markers and bile acids, and restored the morphology of the pancreas, kidney, and liver in a T2DM rat model induced for an additional 5 weeks [67].

An increase in the abundance of C. saudiense was observed in the MRL/lpr lupus mouse model, which was used to examine the etiology of systemic lupus erythematosus. The increased C. saudiense was positively associated with the increased immunological markers of immunoglobulin G (IgG), IgG2a, and urine albumin-to-creatinine ratio associated with the lupus severity [68]. Although studies specifically focusing on C. saudiense are currently scarce, some studies-have reported a strong association between the Clostridium genus and metabolic diseases such as obesity and type 2 diabetes [69,70]. According to Yan et al. [69], at the genus level, the abundance of Clostridium spp. was significantly lower in diabetic rats than in lean and obese controls. Similarly, human case-control studies in individuals with prediabetes reported a decreased abundance of Clostridium and a negative correlation with the fasting glucose, insulin, HOMA-IR, and BMI [70]. These findings suggest that further investigation into the role of C. saudiense in metabolic dysregulation may be warranted.

Spearman correlation analysis revealed a significant association between the gut microbiota and biochemical parameters. R. nasimurium was inversely associated with LDL-C, and E. hirae was inversely associated with ALP. L. caecimuris was inversely associated with TG, and C. saudiense was positively associated with TC. B. intestinalis and B. producta were positively associated with fasting insulin and HOMA-IR. These results suggest that the positive association with Blautia is due to the high dietary fiber content in barley sprouts. Hulled barley contains 17.3 g of dietary fiber per 100 g of edible portion [71]. The total soluble carbohydrate and cellulose contents increase when barley grains are sprouting [27,72,73]. Based on the 2020–2025 dietary guidelines for Americans aged 19 yrs and above [74], the average daily recommended intake of dietary fiber is 25 g and 31 g for women and men, respectively. In light of this recommendation, barley sprouts are a rich source of dietary fiber. The elevated Blautia was observed in mice fed a high-fat diet plus dietary fiber (non-digestible feruloylated oligo- and polysaccharides) [75] and in dogs supplemented with potato fiber [76].

This study had several strengths. To the best of the authors’ knowledge, this is the first study to examine the effects of barley sprout supplementation on glucose homeostasis, lipid metabolism, and gut microbiota in menopausal rats with obesity induced by a high-fat diet. Second, an OVX female rat model representing menopause with estrogen deficiency was used as an experimental group, and a sham-operated female rat model was used as a control. Third, in light of the study findings, barley sprouts could lower the fasting serum glucose and TC in menopausal obese women. Lastly, barley sprouts positively altered the gut microbiome, as evidenced by 16S rRNA-based analysis. Therefore, barley sprouts can help modulate the gut microbiota. The limitations should be acknowledged. The amount of barley sprouts consumed by the rats could not be measured because they were mixed into the food and fed to the rats. Although barley sprouts appear to have a positive influence on the gut microbiota composition, the specific mechanisms through which the gut microbiota affects metabolism and the overall health remain to be investigated. Therefore, further research is needed to identify the bioactive compounds in barley sprouts.

In conclusion, barley sprouts improved the fasting blood glucose and TC levels in OVX rats fed a high-fat diet. In addition, barley sprouts improved the gut microbiota diversity and distribution. These findings provide strong evidence for the potential mechanism underlying the hypoglycemic and hypocholesterolemic effects of barley sprouts, which beneficially modulate the gut microbiota in postmenopausal women. Nevertheless, further clinical studies are required to determine if barley sprouts exert adjuvant effects for preventive treatments for postmenopausal obese women.

ACKNOWLEDGMENTS

The authors would like to thank Minkyung Je, Kyeonghoon Kang, and Eunseo Kim for their valuable contributions in obtaining samples after the animals were euthanized.

Footnotes

Funding: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. RS-2021-NR064134).

Conflict of Interest: The authors declare no potential conflicts of interests.

Author Contributions:

Conceptualization: Kim Y, Lee YM.
Data curation: Kim Y, Lee YM, Choi Y.
Formal analysis: Kim Y, Lee YM, Choi Y.
Investigation: Kim Y, Lee YM, Choi Y.
Methodology: Lee YM, Choi Y.
Supervision: Kim Y, Lee YM.
Validation: Kim Y, Lee YM, Choi Y.
Visualization: Kim Y, Lee YM, Choi Y.
Writing - original draft: Choi Y.
Writing - review & editing: Kim Y, Lee YM, Choi Y.

References

1.Opoku AA, Abushama M, Konje JC. Obesity and menopause. Best Pract Res Clin Obstet Gynaecol. 2023;88:102348. doi: 10.1016/j.bpobgyn.2023.102348. [DOI] [PubMed] [Google Scholar]
2.Iida M, Harada S, Kurihara A, Fukai K, Kuwabara K, Sugiyama D, Takeuchi A, Okamura T, Akiyama M, Nishiwaki Y, et al. Profiling of plasma metabolites in postmenopausal women with metabolic syndrome. Menopause. 2016;23:749–758. doi: 10.1097/GME.0000000000000630. [DOI] [PMC free article] [PubMed] [Google Scholar]
3.Jouyandeh Z, Nayebzadeh F, Qorbani M, Asadi M. Metabolic syndrome and menopause. J Diabetes Metab Disord. 2013;12:1. doi: 10.1186/2251-6581-12-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Park YW, Zhu S, Palaniappan L, Heshka S, Carnethon MR, Heymsfield SB. The metabolic syndrome: prevalence and associated risk factor findings in the US population from the Third National Health and Nutrition Examination Survey, 1988-1994. Arch Intern Med. 2003;163:427–436. doi: 10.1001/archinte.163.4.427. [DOI] [PMC free article] [PubMed] [Google Scholar]
5.Mauvais-Jarvis F, Clegg DJ, Hevener AL. The role of estrogens in control of energy balance and glucose homeostasis. Endocr Rev. 2013;34:309–338. doi: 10.1210/er.2012-1055. [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Palmisano BT, Zhu L, Stafford JM. Role of estrogens in the regulation of liver lipid metabolism. Adv Exp Med Biol. 2017;1043:227–256. doi: 10.1007/978-3-319-70178-3_12. [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Quinn MA, Xu X, Ronfani M, Cidlowski JA. Estrogen deficiency promotes hepatic steatosis via a glucocorticoid receptor-dependent mechanism in mice. Cell Reports. 2018;22:2690–2701. doi: 10.1016/j.celrep.2018.02.041. [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Collaborative Group on Epidemiological Studies of Ovarian Cancer. Beral V, Gaitskell K, Hermon C, Moser K, Reeves G, Peto R. Menopausal hormone use and ovarian cancer risk: individual participant meta-analysis of 52 epidemiological studies. Lancet. 2015;385:1835–1842. doi: 10.1016/S0140-6736(14)61687-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Manson JE, Chlebowski RT, Stefanick ML, Aragaki AK, Rossouw JE, Prentice RL, Anderson G, Howard BV, Thomson CA, LaCroix AZ, et al. Menopausal hormone therapy and health outcomes during the intervention and extended poststopping phases of the Women’s Health Initiative randomized trials. JAMA. 2013;310:1353–1368. doi: 10.1001/jama.2013.278040. [DOI] [PMC free article] [PubMed] [Google Scholar]
10.Rossouw JE, Anderson GL, Prentice RL, LaCroix AZ, Kooperberg C, Stefanick ML, Jackson RD, Beresford SA, Howard BV, Johnson KC, et al. Risks and benefits of estrogen plus progestin in healthy postmenopausal women: principal results from the Women’s Health Initiative randomized controlled trial. JAMA. 2002;288:321–333. doi: 10.1001/jama.288.3.321. [DOI] [PubMed] [Google Scholar]
11.Gu Y, Han F, Xue M, Wang M, Huang Y. The benefits and risks of menopause hormone therapy for the cardiovascular system in postmenopausal women: a systematic review and meta-analysis. BMC Womens Health. 2024;24:60. doi: 10.1186/s12905-023-02788-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Sung YF, Tsai CT, Kuo CY, Lee JT, Chou CH, Chen YC, Chou YC, Sun CA. Use of hormone replacement therapy and risk of dementia: a nationwide cohort study. Neurology. 2022;99:e1835–e1842. doi: 10.1212/WNL.0000000000200960. [DOI] [PubMed] [Google Scholar]
13.Lynch SV, Pedersen O. The human intestinal microbiome in health and disease. N Engl J Med. 2016;375:2369–2379. doi: 10.1056/NEJMra1600266. [DOI] [PubMed] [Google Scholar]
14.Hsiao EY, McBride SW, Hsien S, Sharon G, Hyde ER, McCue T, Codelli JA, Chow J, Reisman SE, Petrosino JF, et al. Microbiota modulate behavioral and physiological abnormalities associated with neurodevelopmental disorders. Cell. 2013;155:1451–1463. doi: 10.1016/j.cell.2013.11.024. [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Mokhtari Z, Gibson DL, Hekmatdoost A. Nonalcoholic fatty liver disease, the gut microbiome, and diet. Adv Nutr. 2017;8:240–252. doi: 10.3945/an.116.013151. [DOI] [PMC free article] [PubMed] [Google Scholar]
16.Le Chatelier E, Nielsen T, Qin J, Prifti E, Hildebrand F, Falony G, Almeida M, Arumugam M, Batto JM, Kennedy S, et al. Richness of human gut microbiome correlates with metabolic markers. Nature. 2013;500:541–546. doi: 10.1038/nature12506. [DOI] [PubMed] [Google Scholar]
17.Brahe LK, Le Chatelier E, Prifti E, Pons N, Kennedy S, Hansen T, Pedersen O, Astrup A, Ehrlich SD, Larsen LH. Specific gut microbiota features and metabolic markers in postmenopausal women with obesity. Nutr Diabetes. 2015;5:e159. doi: 10.1038/nutd.2015.9. [DOI] [PMC free article] [PubMed] [Google Scholar]
18.Brahe LK, Le Chatelier E, Prifti E, Pons N, Kennedy S, Blædel T, Håkansson J, Dalsgaard TK, Hansen T, Pedersen O, et al. Dietary modulation of the gut microbiota--a randomised controlled trial in obese postmenopausal women. Br J Nutr. 2015;114:406–417. doi: 10.1017/S0007114515001786. [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Kaliannan K, Robertson RC, Murphy K, Stanton C, Kang C, Wang B, Hao L, Bhan AK, Kang JX. Estrogen-mediated gut microbiome alterations influence sexual dimorphism in metabolic syndrome in mice. Microbiome. 2018;6:205. doi: 10.1186/s40168-018-0587-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
20.Vrieze A, Van Nood E, Holleman F, Salojärvi J, Kootte RS, Bartelsman JF, Dallinga-Thie GM, Ackermans MT, Serlie MJ, Oozeer R, et al. Transfer of intestinal microbiota from lean donors increases insulin sensitivity in individuals with metabolic syndrome. Gastroenterology. 2012;143:913–916.e7. doi: 10.1053/j.gastro.2012.06.031. [DOI] [PubMed] [Google Scholar]
21.Bäckhed F, Ding H, Wang T, Hooper LV, Koh GY, Nagy A, Semenkovich CF, Gordon JI. The gut microbiota as an environmental factor that regulates fat storage. Proc Natl Acad Sci U S A. 2004;101:15718–15723. doi: 10.1073/pnas.0407076101. [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Cox-York KA, Sheflin AM, Foster MT, Gentile CL, Kahl A, Koch LG, Britton SL, Weir TL. Ovariectomy results in differential shifts in gut microbiota in low versus high aerobic capacity rats. Physiol Rep. 2015;3:e12488. doi: 10.14814/phy2.12488. [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Clavel T, Fallani M, Lepage P, Levenez F, Mathey J, Rochet V, Sérézat M, Sutren M, Henderson G, Bennetau-Pelissero C, et al. Isoflavones and functional foods alter the dominant intestinal microbiota in postmenopausal women. J Nutr. 2005;135:2786–2792. doi: 10.1093/jn/135.12.2786. [DOI] [PubMed] [Google Scholar]
24.Kumari SG, Makkouk KM, Najar A. In: Viral Diseases of Field and Horticultural Crops. Awasthi LP, editor. Amsterdam: Elsevier; 2023. Chapter 6: Barley; pp. 55–61. [Google Scholar]
25.Thakur M, Rana S. In: Advances in Plant Sprouts: Phytochemistry and Biofunctionalities. Majid I, Kehinde BA, Dar B, Nanda V, editors. Cham: Springer; 2023. Barley sprouts; pp. 29–55. [Google Scholar]
26.Oh G, La IJ, Lee DS, Chae JW, Im JH, Park SW, Fu X, Lim JS, Kim MH, Seong YS, et al. Assessment of bioactive compounds and antioxidant activity of barley sprouts. Separations. 2025;12:68. [Google Scholar]
27.Ortiz LT, Velasco S, Treviño J, Jiménez B, Rebolé A. Changes in the nutrient composition of barley grain (Hordeum vulgare L.) and of morphological fractions of sprouts. Scientifica (Cairo) 2021;2021:9968864. doi: 10.1155/2021/9968864. [DOI] [PMC free article] [PubMed] [Google Scholar]
28.Thatiparthi J, Dodoala S, Koganti B, Kvsrg P. Barley grass juice (Hordeum vulgare L.) inhibits obesity and improves lipid profile in high fat diet-induced rat model. J Ethnopharmacol. 2019;238:111843. doi: 10.1016/j.jep.2019.111843. [DOI] [PubMed] [Google Scholar]
29.Kamiyama M, Shibamoto T. Flavonoids with potent antioxidant activity found in young green barley leaves. J Agric Food Chem. 2012;60:6260–6267. doi: 10.1021/jf301700j. [DOI] [PubMed] [Google Scholar]
30.Kim YJ, Hwang SH, Jia Y, Seo WD, Lee SJ. Barley sprout extracts reduce hepatic lipid accumulation in ethanol-fed mice by activating hepatic AMP-activated protein kinase. Food Res Int. 2017;101:209–217. doi: 10.1016/j.foodres.2017.08.068. [DOI] [PubMed] [Google Scholar]
31.Yan JK, Chen TT, Li LQ, Liu F, Liu X, Li L. The anti-hyperlipidemic effect and underlying mechanisms of barley (Hordeum vulgare L.) grass polysaccharides in mice induced by a high-fat diet. Food Funct. 2023;14:7066–7081. doi: 10.1039/d3fo01451g. [DOI] [PubMed] [Google Scholar]
32.Seo WD, Yuk HJ, Curtis-Long MJ, Jang KC, Lee JH, Han SI, Kang HW, Nam MH, Lee SJ, Lee JH, et al. Effect of the growth stage and cultivar on policosanol profiles of barley sprouts and their adenosine 5′-monophosphate-activated protein kinase activation. J Agric Food Chem. 2013;61:1117–1123. doi: 10.1021/jf3041879. [DOI] [PubMed] [Google Scholar]
33.Yu YM, Chang WC, Liu CS, Tsai CM. Effect of young barley leaf extract and adlay on plasma lipids and LDL oxidation in hyperlipidemic smokers. Biol Pharm Bull. 2004;27:802–805. doi: 10.1248/bpb.27.802. [DOI] [PubMed] [Google Scholar]
34.Cho HW, Seo K, Lee MY, Lee SY, So KM, Song SY, Seo WD, Chun JL, Kim KH. Anti-obesity potential of barley sprouts in dog diets and their impact on the gut microbiota. Microorganisms. 2025;13:594. doi: 10.3390/microorganisms13030594. [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Choi JS, Song J. Effect of genistein on insulin resistance, renal lipid metabolism, and antioxidative activities in ovariectomized rats. Nutrition. 2009;25:676–685. doi: 10.1016/j.nut.2008.11.027. [DOI] [PubMed] [Google Scholar]
36.Nagamma T, Konuri A, Bhat KMR, Udupa PEG, Nayak Y. Trigonella foenum-graecum L. seed extract modulates biochemical and histomorphological changes in therapeutic model of high-fat diet-fed ovariectomized rats. 3 Biotech. 2023;13:285. doi: 10.1007/s13205-023-03707-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Lee SH, Lee YM, Lee HS, Kim DK. Anti-oxidative and anti-hyperglycemia effects of Triticum aestivum wheat sprout water extracts on the streptozotocin-induced diabetic mice. Korean J Pharmacogn. 2009;40:408–414. [Google Scholar]
38.Lee YH, Kim JH, Kim SH, Oh JY, Seo WD, Kim KM, Jung JC, Jung YS. Barley sprouts extract attenuates alcoholic fatty liver injury in mice by reducing inflammatory response. Nutrients. 2016;8:440. doi: 10.3390/nu8070440. [DOI] [PMC free article] [PubMed] [Google Scholar]
39.American Veterinary Medical Association (AVMA) AVMA Guidelines for the Euthanasia of Animals: 2020 Edition. Schaumburg (IL): AVMA; 2020. p. 28. [Google Scholar]
40.Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28:412–419. doi: 10.1007/BF00280883. [DOI] [PubMed] [Google Scholar]
41.Cao JJ, Gregoire BR. A high-fat diet increases body weight and circulating estradiol concentrations but does not improve bone structural properties in ovariectomized mice. Nutr Res. 2016;36:320–327. doi: 10.1016/j.nutres.2015.12.008. [DOI] [PubMed] [Google Scholar]
42.Gorres BK, Bomhoff GL, Gupte AA, Geiger PC. Altered estrogen receptor expression in skeletal muscle and adipose tissue of female rats fed a high-fat diet. J Appl Physiol. 2011;110:1046–1053. doi: 10.1152/japplphysiol.00541.2010. [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Ludgero-Correia A, Jr, Aguila MB, Mandarim-de-Lacerda CA, Faria TS. Effects of high-fat diet on plasma lipids, adiposity, and inflammatory markers in ovariectomized C57BL/6 mice. Nutrition. 2012;28:316–323. doi: 10.1016/j.nut.2011.07.014. [DOI] [PubMed] [Google Scholar]
44.Stubbins RE, Holcomb VB, Hong J, Núñez NP. Estrogen modulates abdominal adiposity and protects female mice from obesity and impaired glucose tolerance. Eur J Nutr. 2012;51:861–870. doi: 10.1007/s00394-011-0266-4. [DOI] [PubMed] [Google Scholar]
45.Smith A, Woodside B, Abizaid A. Ghrelin and the control of energy balance in females. Front Endocrinol (Lausanne) 2022;13:904754. doi: 10.3389/fendo.2022.904754. [DOI] [PMC free article] [PubMed] [Google Scholar]
46.Tse MCL, Pang BPS, Bi X, Ooi TX, Chan WS, Zhang J, Chan CB. Estrogen regulates mitochondrial activity through inducing brain-derived neurotrophic factor expression in skeletal muscle. J Cell Physiol. 2025;240:e31483. doi: 10.1002/jcp.31483. [DOI] [PubMed] [Google Scholar]
47.Sloan DK, Spencer DS, Curtis KS. Estrogen effects on oxytocinergic pathways that regulate food intake. Horm Behav. 2018;105:128–137. doi: 10.1016/j.yhbeh.2018.08.007. [DOI] [PubMed] [Google Scholar]
48.Bethea CL, Kohama SG, Reddy AP, Urbanski HF. Ovarian steroids regulate gene expression in the dorsal raphe of old female macaques. Neurobiol Aging. 2016;37:179–191. doi: 10.1016/j.neurobiolaging.2015.10.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
49.Zhu J, Zhang L, Ji M, Jin B, Shu J. Elevated adipose differentiation-related protein level in ovariectomized mice correlates with tissue-specific regulation of estrogen. J Obstet Gynaecol Res. 2023;49:1173–1179. doi: 10.1111/jog.15565. [DOI] [PubMed] [Google Scholar]
50.Pitha J, Huttl M, Malinska H, Miklankova D, Bartuskova H, Hlinka T, Markova I. Cardiovascular, metabolic and inflammatory changes after ovariectomy and estradiol substitution in hereditary hypertriglyceridemic rats. Int J Mol Sci. 2022;23:2825. doi: 10.3390/ijms23052825. [DOI] [PMC free article] [PubMed] [Google Scholar]
51.da Silva BP, Toledo RCL, Mishima MDV, Moreira MEC, Vasconcelos CM, Pereira CER, Favarato LSC, Costa NMB, Martino HSD. Effects of chia (Salvia hispanica L.) on oxidative stress and inflammation in ovariectomized adult female Wistar rats. Food Funct. 2019;10:4036–4045. doi: 10.1039/c9fo00862d. [DOI] [PubMed] [Google Scholar]
52.Kosmas CE, Martinez I, Sourlas A, Bouza KV, Campos FN, Torres V, Montan PD, Guzman E. High-density lipoprotein (HDL) functionality and its relevance to atherosclerotic cardiovascular disease. Drugs Context. 2018;7:212525. doi: 10.7573/dic.212525. [DOI] [PMC free article] [PubMed] [Google Scholar]
53.Rico D, Peñas E, García MDC, Martínez-Villaluenga C, Rai DK, Birsan RI, Frias J, Martín-Diana AB. Sprouted barley flour as a nutritious and functional ingredient. Foods. 2020;9:296. doi: 10.3390/foods9030296. [DOI] [PMC free article] [PubMed] [Google Scholar]
54.Lee JH, Lee SY, Kim B, Seo WD, Jia Y, Wu C, Jun H, Lee SJ. Barley sprout extract containing policosanols and polyphenols regulate AMPK, SREBP2 and ACAT2 activity and cholesterol and glucose metabolism in vitro and in vivo . Food Res Int. 2015;72:174–183. [Google Scholar]
55.Nam DE, Yun JM, Kim D, Kim OK. Policosanol attenuates cholesterol synthesis via AMPK activation in hypercholesterolemic rats. J Med Food. 2019;22:1110–1117. doi: 10.1089/jmf.2019.4491. [DOI] [PubMed] [Google Scholar]
56.Kim MJ, Kawk HW, Kim SH, Lee HJ, Seo JW, Kim JT, Jang SH, Kim MJ, Kim YM. Anti-obesity effect of hot water extract of barley sprout through the inhibition of adipocyte differentiation and growth. Metabolites. 2021;11:610. doi: 10.3390/metabo11090610. [DOI] [PMC free article] [PubMed] [Google Scholar]
57.Kim IS, Park SY, Park MJ, Kim KJ, Kim JY. Effect of barley on postprandial blood glucose response and appetite in healthy individuals: a randomized, double-blind, placebo-controlled trial. Nutrients. 2024;16:3899. doi: 10.3390/nu16223899. [DOI] [PMC free article] [PubMed] [Google Scholar]
58.Seo WD, Lee JH, Jia Y, Wu C, Lee SJ. Saponarin activates AMPK in a calcium-dependent manner and suppresses gluconeogenesis and increases glucose uptake via phosphorylation of CRTC2 and HDAC5. Bioorg Med Chem Lett. 2015;25:5237–5242. doi: 10.1016/j.bmcl.2015.09.057. [DOI] [PubMed] [Google Scholar]
59.Ibrahim I, Syamala S, Ayariga JA, Xu J, Robertson BK, Meenakshisundaram S, Ajayi OS. Modulatory effect of gut microbiota on the gut-brain, gut-bone axes, and the impact of cannabinoids. Metabolites. 2022;12:1247. doi: 10.3390/metabo12121247. [DOI] [PMC free article] [PubMed] [Google Scholar]
60.Braune A, Blaut M. Bacterial species involved in the conversion of dietary flavonoids in the human gut. Gut Microbes. 2016;7:216–234. doi: 10.1080/19490976.2016.1158395. [DOI] [PMC free article] [PubMed] [Google Scholar]
61.Magne F, Gotteland M, Gauthier L, Zazueta A, Pesoa S, Navarrete P, Balamurugan R. The firmicutes/bacteroidetes ratio: a relevant marker of gut dysbiosis in obese patients? Nutrients. 2020;12:1474. doi: 10.3390/nu12051474. [DOI] [PMC free article] [PubMed] [Google Scholar]
62.Ley RE, Turnbaugh PJ, Klein S, Gordon JI. Microbial ecology: human gut microbes associated with obesity. Nature. 2006;444:1022–1023. doi: 10.1038/4441022a. [DOI] [PubMed] [Google Scholar]
63.Muheyati D, Han J, Lv M, Jielili M, Jing Z, Zaibibuli K, Aisike G, Aihemaiti A, Yu Y, Kaliszewski CR. Composition of gut microbiota in obese and normal-weight Uygur adults and its association with adipocyte-related factors. Sci Rep. 2024;14:24649. doi: 10.1038/s41598-024-76351-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
64.Patrone V, Vajana E, Minuti A, Callegari ML, Federico A, Loguercio C, Dallio M, Tolone S, Docimo L, Morelli L. Postoperative changes in fecal bacterial communities and fermentation products in obese patients undergoing bilio-intestinal bypass. Front Microbiol. 2016;7:200. doi: 10.3389/fmicb.2016.00200. [DOI] [PMC free article] [PubMed] [Google Scholar]
65.Salazar-Jaramillo L, de la Cuesta-Zuluaga J, Chica LA, Cadavid M, Ley RE, Reyes A, Escobar JS. Gut microbiome diversity within Clostridia is negatively associated with human obesity. mSystems. 2024;9:e0062724. doi: 10.1128/msystems.00627-24. [DOI] [PMC free article] [PubMed] [Google Scholar]
66.Zhang F, Qiu L, Xu X, Liu Z, Zhan H, Tao X, Shah NP, Wei H. Beneficial effects of probiotic cholesterol-lowering strain of Enterococcus faecium WEFA23 from infants on diet-induced metabolic syndrome in rats. J Dairy Sci. 2017;100:1618–1628. doi: 10.3168/jds.2016-11870. [DOI] [PubMed] [Google Scholar]
67.Wei M, Gu E, Luo J, Zhang Z, Xu D, Tao X, Shah NP, Wei H. Enterococcus hirae WEHI01 isolated from a healthy Chinese infant ameliorates the symptoms of type 2 diabetes by elevating the abundance of Lactobacillales in rats. J Dairy Sci. 2020;103:2969–2981. doi: 10.3168/jds.2019-17185. [DOI] [PubMed] [Google Scholar]
68.Han EJ, Ahn JS, Choi YJ, Kim DH, Chung HJ. Changes in gut microbiota according to disease severity in a lupus mouse model. Int J Mol Sci. 2025;26:1006. doi: 10.3390/ijms26031006. [DOI] [PMC free article] [PubMed] [Google Scholar]
69.Yan X, Feng B, Li P, Tang Z, Wang L. Microflora disturbance during progression of glucose intolerance and effect of sitagliptin: an animal study. J Diabetes Res. 2016;2016:2093171. doi: 10.1155/2016/2093171. [DOI] [PMC free article] [PubMed] [Google Scholar]
70.Allin KH, Tremaroli V, Caesar R, Jensen BAH, Damgaard MTF, Bahl MI, Licht TR, Hansen TH, Nielsen T, Dantoft TM, et al. Aberrant intestinal microbiota in individuals with prediabetes. Diabetologia. 2018;61:810–820. doi: 10.1007/s00125-018-4550-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
71.U.S. Department of Agriculture. USDA National Nutrient Database for Standard Reference (FoodData Central ID: 170283) Washington, D.C.: Nutrient Data Laboratory; 2019. [cited 2025 April 22]. Available from: https://fdc.nal.usda.gov/food-details/170283/nutrients. [Google Scholar]
72.Dhingra D, Michael M, Rajput H, Patil RT. Dietary fibre in foods: a review. J Food Sci Technol. 2012;49:255–266. doi: 10.1007/s13197-011-0365-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
73.Chung TY, Nwokolo EN, Sim JS. Compositional and digestibility changes in sprouted barley and canola seeds. Plant Foods Hum Nutr. 1989;39:267–278. doi: 10.1007/BF01091937. [DOI] [PubMed] [Google Scholar]
74.U.S. Department of Agriculture; U.S. Department of Health and Human Services. Dietary Guidelines for Americans, 2020–2025. 9th Edition. Washington, D.C.: U.S. Department of Agriculture; 2020. [Google Scholar]
75.Yang J, Bindels LB, Segura Munoz RR, Martínez I, Walter J, Ramer-Tait AE, Rose DJ. Disparate metabolic responses in mice fed a high-fat diet supplemented with maize-derived non-digestible feruloylated oligo- and polysaccharides are linked to changes in the gut microbiota. PLoS One. 2016;11:e0146144. doi: 10.1371/journal.pone.0146144. [DOI] [PMC free article] [PubMed] [Google Scholar]
76.Panasevich MR, Kerr KR, Dilger RN, Fahey GC, Jr, Guérin-Deremaux L, Lynch GL, Wils D, Suchodolski JS, Steer JM, Dowd SE, et al. Modulation of the faecal microbiome of healthy adult dogs by inclusion of potato fibre in the diet. Br J Nutr. 2015;113:125–133. doi: 10.1017/S0007114514003274. [DOI] [PubMed] [Google Scholar]

[B1] 1.Opoku AA, Abushama M, Konje JC. Obesity and menopause. Best Pract Res Clin Obstet Gynaecol. 2023;88:102348. doi: 10.1016/j.bpobgyn.2023.102348. [DOI] [PubMed] [Google Scholar]

[B2] 2.Iida M, Harada S, Kurihara A, Fukai K, Kuwabara K, Sugiyama D, Takeuchi A, Okamura T, Akiyama M, Nishiwaki Y, et al. Profiling of plasma metabolites in postmenopausal women with metabolic syndrome. Menopause. 2016;23:749–758. doi: 10.1097/GME.0000000000000630. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B3] 3.Jouyandeh Z, Nayebzadeh F, Qorbani M, Asadi M. Metabolic syndrome and menopause. J Diabetes Metab Disord. 2013;12:1. doi: 10.1186/2251-6581-12-1. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B4] 4.Park YW, Zhu S, Palaniappan L, Heshka S, Carnethon MR, Heymsfield SB. The metabolic syndrome: prevalence and associated risk factor findings in the US population from the Third National Health and Nutrition Examination Survey, 1988-1994. Arch Intern Med. 2003;163:427–436. doi: 10.1001/archinte.163.4.427. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B5] 5.Mauvais-Jarvis F, Clegg DJ, Hevener AL. The role of estrogens in control of energy balance and glucose homeostasis. Endocr Rev. 2013;34:309–338. doi: 10.1210/er.2012-1055. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B6] 6.Palmisano BT, Zhu L, Stafford JM. Role of estrogens in the regulation of liver lipid metabolism. Adv Exp Med Biol. 2017;1043:227–256. doi: 10.1007/978-3-319-70178-3_12. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B7] 7.Quinn MA, Xu X, Ronfani M, Cidlowski JA. Estrogen deficiency promotes hepatic steatosis via a glucocorticoid receptor-dependent mechanism in mice. Cell Reports. 2018;22:2690–2701. doi: 10.1016/j.celrep.2018.02.041. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B8] 8.Collaborative Group on Epidemiological Studies of Ovarian Cancer. Beral V, Gaitskell K, Hermon C, Moser K, Reeves G, Peto R. Menopausal hormone use and ovarian cancer risk: individual participant meta-analysis of 52 epidemiological studies. Lancet. 2015;385:1835–1842. doi: 10.1016/S0140-6736(14)61687-1. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B9] 9.Manson JE, Chlebowski RT, Stefanick ML, Aragaki AK, Rossouw JE, Prentice RL, Anderson G, Howard BV, Thomson CA, LaCroix AZ, et al. Menopausal hormone therapy and health outcomes during the intervention and extended poststopping phases of the Women’s Health Initiative randomized trials. JAMA. 2013;310:1353–1368. doi: 10.1001/jama.2013.278040. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B10] 10.Rossouw JE, Anderson GL, Prentice RL, LaCroix AZ, Kooperberg C, Stefanick ML, Jackson RD, Beresford SA, Howard BV, Johnson KC, et al. Risks and benefits of estrogen plus progestin in healthy postmenopausal women: principal results from the Women’s Health Initiative randomized controlled trial. JAMA. 2002;288:321–333. doi: 10.1001/jama.288.3.321. [DOI] [PubMed] [Google Scholar]

[B11] 11.Gu Y, Han F, Xue M, Wang M, Huang Y. The benefits and risks of menopause hormone therapy for the cardiovascular system in postmenopausal women: a systematic review and meta-analysis. BMC Womens Health. 2024;24:60. doi: 10.1186/s12905-023-02788-0. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B12] 12.Sung YF, Tsai CT, Kuo CY, Lee JT, Chou CH, Chen YC, Chou YC, Sun CA. Use of hormone replacement therapy and risk of dementia: a nationwide cohort study. Neurology. 2022;99:e1835–e1842. doi: 10.1212/WNL.0000000000200960. [DOI] [PubMed] [Google Scholar]

[B13] 13.Lynch SV, Pedersen O. The human intestinal microbiome in health and disease. N Engl J Med. 2016;375:2369–2379. doi: 10.1056/NEJMra1600266. [DOI] [PubMed] [Google Scholar]

[B14] 14.Hsiao EY, McBride SW, Hsien S, Sharon G, Hyde ER, McCue T, Codelli JA, Chow J, Reisman SE, Petrosino JF, et al. Microbiota modulate behavioral and physiological abnormalities associated with neurodevelopmental disorders. Cell. 2013;155:1451–1463. doi: 10.1016/j.cell.2013.11.024. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B15] 15.Mokhtari Z, Gibson DL, Hekmatdoost A. Nonalcoholic fatty liver disease, the gut microbiome, and diet. Adv Nutr. 2017;8:240–252. doi: 10.3945/an.116.013151. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B16] 16.Le Chatelier E, Nielsen T, Qin J, Prifti E, Hildebrand F, Falony G, Almeida M, Arumugam M, Batto JM, Kennedy S, et al. Richness of human gut microbiome correlates with metabolic markers. Nature. 2013;500:541–546. doi: 10.1038/nature12506. [DOI] [PubMed] [Google Scholar]

[B17] 17.Brahe LK, Le Chatelier E, Prifti E, Pons N, Kennedy S, Hansen T, Pedersen O, Astrup A, Ehrlich SD, Larsen LH. Specific gut microbiota features and metabolic markers in postmenopausal women with obesity. Nutr Diabetes. 2015;5:e159. doi: 10.1038/nutd.2015.9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B18] 18.Brahe LK, Le Chatelier E, Prifti E, Pons N, Kennedy S, Blædel T, Håkansson J, Dalsgaard TK, Hansen T, Pedersen O, et al. Dietary modulation of the gut microbiota--a randomised controlled trial in obese postmenopausal women. Br J Nutr. 2015;114:406–417. doi: 10.1017/S0007114515001786. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B19] 19.Kaliannan K, Robertson RC, Murphy K, Stanton C, Kang C, Wang B, Hao L, Bhan AK, Kang JX. Estrogen-mediated gut microbiome alterations influence sexual dimorphism in metabolic syndrome in mice. Microbiome. 2018;6:205. doi: 10.1186/s40168-018-0587-0. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B20] 20.Vrieze A, Van Nood E, Holleman F, Salojärvi J, Kootte RS, Bartelsman JF, Dallinga-Thie GM, Ackermans MT, Serlie MJ, Oozeer R, et al. Transfer of intestinal microbiota from lean donors increases insulin sensitivity in individuals with metabolic syndrome. Gastroenterology. 2012;143:913–916.e7. doi: 10.1053/j.gastro.2012.06.031. [DOI] [PubMed] [Google Scholar]

[B21] 21.Bäckhed F, Ding H, Wang T, Hooper LV, Koh GY, Nagy A, Semenkovich CF, Gordon JI. The gut microbiota as an environmental factor that regulates fat storage. Proc Natl Acad Sci U S A. 2004;101:15718–15723. doi: 10.1073/pnas.0407076101. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B22] 22.Cox-York KA, Sheflin AM, Foster MT, Gentile CL, Kahl A, Koch LG, Britton SL, Weir TL. Ovariectomy results in differential shifts in gut microbiota in low versus high aerobic capacity rats. Physiol Rep. 2015;3:e12488. doi: 10.14814/phy2.12488. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B23] 23.Clavel T, Fallani M, Lepage P, Levenez F, Mathey J, Rochet V, Sérézat M, Sutren M, Henderson G, Bennetau-Pelissero C, et al. Isoflavones and functional foods alter the dominant intestinal microbiota in postmenopausal women. J Nutr. 2005;135:2786–2792. doi: 10.1093/jn/135.12.2786. [DOI] [PubMed] [Google Scholar]

[B24] 24.Kumari SG, Makkouk KM, Najar A. In: Viral Diseases of Field and Horticultural Crops. Awasthi LP, editor. Amsterdam: Elsevier; 2023. Chapter 6: Barley; pp. 55–61. [Google Scholar]

[B25] 25.Thakur M, Rana S. In: Advances in Plant Sprouts: Phytochemistry and Biofunctionalities. Majid I, Kehinde BA, Dar B, Nanda V, editors. Cham: Springer; 2023. Barley sprouts; pp. 29–55. [Google Scholar]

[B26] 26.Oh G, La IJ, Lee DS, Chae JW, Im JH, Park SW, Fu X, Lim JS, Kim MH, Seong YS, et al. Assessment of bioactive compounds and antioxidant activity of barley sprouts. Separations. 2025;12:68. [Google Scholar]

[B27] 27.Ortiz LT, Velasco S, Treviño J, Jiménez B, Rebolé A. Changes in the nutrient composition of barley grain (Hordeum vulgare L.) and of morphological fractions of sprouts. Scientifica (Cairo) 2021;2021:9968864. doi: 10.1155/2021/9968864. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B28] 28.Thatiparthi J, Dodoala S, Koganti B, Kvsrg P. Barley grass juice (Hordeum vulgare L.) inhibits obesity and improves lipid profile in high fat diet-induced rat model. J Ethnopharmacol. 2019;238:111843. doi: 10.1016/j.jep.2019.111843. [DOI] [PubMed] [Google Scholar]

[B29] 29.Kamiyama M, Shibamoto T. Flavonoids with potent antioxidant activity found in young green barley leaves. J Agric Food Chem. 2012;60:6260–6267. doi: 10.1021/jf301700j. [DOI] [PubMed] [Google Scholar]

[B30] 30.Kim YJ, Hwang SH, Jia Y, Seo WD, Lee SJ. Barley sprout extracts reduce hepatic lipid accumulation in ethanol-fed mice by activating hepatic AMP-activated protein kinase. Food Res Int. 2017;101:209–217. doi: 10.1016/j.foodres.2017.08.068. [DOI] [PubMed] [Google Scholar]

[B31] 31.Yan JK, Chen TT, Li LQ, Liu F, Liu X, Li L. The anti-hyperlipidemic effect and underlying mechanisms of barley (Hordeum vulgare L.) grass polysaccharides in mice induced by a high-fat diet. Food Funct. 2023;14:7066–7081. doi: 10.1039/d3fo01451g. [DOI] [PubMed] [Google Scholar]

[B32] 32.Seo WD, Yuk HJ, Curtis-Long MJ, Jang KC, Lee JH, Han SI, Kang HW, Nam MH, Lee SJ, Lee JH, et al. Effect of the growth stage and cultivar on policosanol profiles of barley sprouts and their adenosine 5′-monophosphate-activated protein kinase activation. J Agric Food Chem. 2013;61:1117–1123. doi: 10.1021/jf3041879. [DOI] [PubMed] [Google Scholar]

[B33] 33.Yu YM, Chang WC, Liu CS, Tsai CM. Effect of young barley leaf extract and adlay on plasma lipids and LDL oxidation in hyperlipidemic smokers. Biol Pharm Bull. 2004;27:802–805. doi: 10.1248/bpb.27.802. [DOI] [PubMed] [Google Scholar]

[B34] 34.Cho HW, Seo K, Lee MY, Lee SY, So KM, Song SY, Seo WD, Chun JL, Kim KH. Anti-obesity potential of barley sprouts in dog diets and their impact on the gut microbiota. Microorganisms. 2025;13:594. doi: 10.3390/microorganisms13030594. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B35] 35.Choi JS, Song J. Effect of genistein on insulin resistance, renal lipid metabolism, and antioxidative activities in ovariectomized rats. Nutrition. 2009;25:676–685. doi: 10.1016/j.nut.2008.11.027. [DOI] [PubMed] [Google Scholar]

[B36] 36.Nagamma T, Konuri A, Bhat KMR, Udupa PEG, Nayak Y. Trigonella foenum-graecum L. seed extract modulates biochemical and histomorphological changes in therapeutic model of high-fat diet-fed ovariectomized rats. 3 Biotech. 2023;13:285. doi: 10.1007/s13205-023-03707-8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B37] 37.Lee SH, Lee YM, Lee HS, Kim DK. Anti-oxidative and anti-hyperglycemia effects of Triticum aestivum wheat sprout water extracts on the streptozotocin-induced diabetic mice. Korean J Pharmacogn. 2009;40:408–414. [Google Scholar]

[B38] 38.Lee YH, Kim JH, Kim SH, Oh JY, Seo WD, Kim KM, Jung JC, Jung YS. Barley sprouts extract attenuates alcoholic fatty liver injury in mice by reducing inflammatory response. Nutrients. 2016;8:440. doi: 10.3390/nu8070440. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B39] 39.American Veterinary Medical Association (AVMA) AVMA Guidelines for the Euthanasia of Animals: 2020 Edition. Schaumburg (IL): AVMA; 2020. p. 28. [Google Scholar]

[B40] 40.Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28:412–419. doi: 10.1007/BF00280883. [DOI] [PubMed] [Google Scholar]

[B41] 41.Cao JJ, Gregoire BR. A high-fat diet increases body weight and circulating estradiol concentrations but does not improve bone structural properties in ovariectomized mice. Nutr Res. 2016;36:320–327. doi: 10.1016/j.nutres.2015.12.008. [DOI] [PubMed] [Google Scholar]

[B42] 42.Gorres BK, Bomhoff GL, Gupte AA, Geiger PC. Altered estrogen receptor expression in skeletal muscle and adipose tissue of female rats fed a high-fat diet. J Appl Physiol. 2011;110:1046–1053. doi: 10.1152/japplphysiol.00541.2010. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B43] 43.Ludgero-Correia A, Jr, Aguila MB, Mandarim-de-Lacerda CA, Faria TS. Effects of high-fat diet on plasma lipids, adiposity, and inflammatory markers in ovariectomized C57BL/6 mice. Nutrition. 2012;28:316–323. doi: 10.1016/j.nut.2011.07.014. [DOI] [PubMed] [Google Scholar]

[B44] 44.Stubbins RE, Holcomb VB, Hong J, Núñez NP. Estrogen modulates abdominal adiposity and protects female mice from obesity and impaired glucose tolerance. Eur J Nutr. 2012;51:861–870. doi: 10.1007/s00394-011-0266-4. [DOI] [PubMed] [Google Scholar]

[B45] 45.Smith A, Woodside B, Abizaid A. Ghrelin and the control of energy balance in females. Front Endocrinol (Lausanne) 2022;13:904754. doi: 10.3389/fendo.2022.904754. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B46] 46.Tse MCL, Pang BPS, Bi X, Ooi TX, Chan WS, Zhang J, Chan CB. Estrogen regulates mitochondrial activity through inducing brain-derived neurotrophic factor expression in skeletal muscle. J Cell Physiol. 2025;240:e31483. doi: 10.1002/jcp.31483. [DOI] [PubMed] [Google Scholar]

[B47] 47.Sloan DK, Spencer DS, Curtis KS. Estrogen effects on oxytocinergic pathways that regulate food intake. Horm Behav. 2018;105:128–137. doi: 10.1016/j.yhbeh.2018.08.007. [DOI] [PubMed] [Google Scholar]

[B48] 48.Bethea CL, Kohama SG, Reddy AP, Urbanski HF. Ovarian steroids regulate gene expression in the dorsal raphe of old female macaques. Neurobiol Aging. 2016;37:179–191. doi: 10.1016/j.neurobiolaging.2015.10.004. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B49] 49.Zhu J, Zhang L, Ji M, Jin B, Shu J. Elevated adipose differentiation-related protein level in ovariectomized mice correlates with tissue-specific regulation of estrogen. J Obstet Gynaecol Res. 2023;49:1173–1179. doi: 10.1111/jog.15565. [DOI] [PubMed] [Google Scholar]

[B50] 50.Pitha J, Huttl M, Malinska H, Miklankova D, Bartuskova H, Hlinka T, Markova I. Cardiovascular, metabolic and inflammatory changes after ovariectomy and estradiol substitution in hereditary hypertriglyceridemic rats. Int J Mol Sci. 2022;23:2825. doi: 10.3390/ijms23052825. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B51] 51.da Silva BP, Toledo RCL, Mishima MDV, Moreira MEC, Vasconcelos CM, Pereira CER, Favarato LSC, Costa NMB, Martino HSD. Effects of chia (Salvia hispanica L.) on oxidative stress and inflammation in ovariectomized adult female Wistar rats. Food Funct. 2019;10:4036–4045. doi: 10.1039/c9fo00862d. [DOI] [PubMed] [Google Scholar]

[B52] 52.Kosmas CE, Martinez I, Sourlas A, Bouza KV, Campos FN, Torres V, Montan PD, Guzman E. High-density lipoprotein (HDL) functionality and its relevance to atherosclerotic cardiovascular disease. Drugs Context. 2018;7:212525. doi: 10.7573/dic.212525. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B53] 53.Rico D, Peñas E, García MDC, Martínez-Villaluenga C, Rai DK, Birsan RI, Frias J, Martín-Diana AB. Sprouted barley flour as a nutritious and functional ingredient. Foods. 2020;9:296. doi: 10.3390/foods9030296. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B54] 54.Lee JH, Lee SY, Kim B, Seo WD, Jia Y, Wu C, Jun H, Lee SJ. Barley sprout extract containing policosanols and polyphenols regulate AMPK, SREBP2 and ACAT2 activity and cholesterol and glucose metabolism in vitro and in vivo . Food Res Int. 2015;72:174–183. [Google Scholar]

[B55] 55.Nam DE, Yun JM, Kim D, Kim OK. Policosanol attenuates cholesterol synthesis via AMPK activation in hypercholesterolemic rats. J Med Food. 2019;22:1110–1117. doi: 10.1089/jmf.2019.4491. [DOI] [PubMed] [Google Scholar]

[B56] 56.Kim MJ, Kawk HW, Kim SH, Lee HJ, Seo JW, Kim JT, Jang SH, Kim MJ, Kim YM. Anti-obesity effect of hot water extract of barley sprout through the inhibition of adipocyte differentiation and growth. Metabolites. 2021;11:610. doi: 10.3390/metabo11090610. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B57] 57.Kim IS, Park SY, Park MJ, Kim KJ, Kim JY. Effect of barley on postprandial blood glucose response and appetite in healthy individuals: a randomized, double-blind, placebo-controlled trial. Nutrients. 2024;16:3899. doi: 10.3390/nu16223899. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B58] 58.Seo WD, Lee JH, Jia Y, Wu C, Lee SJ. Saponarin activates AMPK in a calcium-dependent manner and suppresses gluconeogenesis and increases glucose uptake via phosphorylation of CRTC2 and HDAC5. Bioorg Med Chem Lett. 2015;25:5237–5242. doi: 10.1016/j.bmcl.2015.09.057. [DOI] [PubMed] [Google Scholar]

[B59] 59.Ibrahim I, Syamala S, Ayariga JA, Xu J, Robertson BK, Meenakshisundaram S, Ajayi OS. Modulatory effect of gut microbiota on the gut-brain, gut-bone axes, and the impact of cannabinoids. Metabolites. 2022;12:1247. doi: 10.3390/metabo12121247. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B60] 60.Braune A, Blaut M. Bacterial species involved in the conversion of dietary flavonoids in the human gut. Gut Microbes. 2016;7:216–234. doi: 10.1080/19490976.2016.1158395. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B61] 61.Magne F, Gotteland M, Gauthier L, Zazueta A, Pesoa S, Navarrete P, Balamurugan R. The firmicutes/bacteroidetes ratio: a relevant marker of gut dysbiosis in obese patients? Nutrients. 2020;12:1474. doi: 10.3390/nu12051474. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B62] 62.Ley RE, Turnbaugh PJ, Klein S, Gordon JI. Microbial ecology: human gut microbes associated with obesity. Nature. 2006;444:1022–1023. doi: 10.1038/4441022a. [DOI] [PubMed] [Google Scholar]

[B63] 63.Muheyati D, Han J, Lv M, Jielili M, Jing Z, Zaibibuli K, Aisike G, Aihemaiti A, Yu Y, Kaliszewski CR. Composition of gut microbiota in obese and normal-weight Uygur adults and its association with adipocyte-related factors. Sci Rep. 2024;14:24649. doi: 10.1038/s41598-024-76351-8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B64] 64.Patrone V, Vajana E, Minuti A, Callegari ML, Federico A, Loguercio C, Dallio M, Tolone S, Docimo L, Morelli L. Postoperative changes in fecal bacterial communities and fermentation products in obese patients undergoing bilio-intestinal bypass. Front Microbiol. 2016;7:200. doi: 10.3389/fmicb.2016.00200. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B65] 65.Salazar-Jaramillo L, de la Cuesta-Zuluaga J, Chica LA, Cadavid M, Ley RE, Reyes A, Escobar JS. Gut microbiome diversity within Clostridia is negatively associated with human obesity. mSystems. 2024;9:e0062724. doi: 10.1128/msystems.00627-24. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B66] 66.Zhang F, Qiu L, Xu X, Liu Z, Zhan H, Tao X, Shah NP, Wei H. Beneficial effects of probiotic cholesterol-lowering strain of Enterococcus faecium WEFA23 from infants on diet-induced metabolic syndrome in rats. J Dairy Sci. 2017;100:1618–1628. doi: 10.3168/jds.2016-11870. [DOI] [PubMed] [Google Scholar]

[B67] 67.Wei M, Gu E, Luo J, Zhang Z, Xu D, Tao X, Shah NP, Wei H. Enterococcus hirae WEHI01 isolated from a healthy Chinese infant ameliorates the symptoms of type 2 diabetes by elevating the abundance of Lactobacillales in rats. J Dairy Sci. 2020;103:2969–2981. doi: 10.3168/jds.2019-17185. [DOI] [PubMed] [Google Scholar]

[B68] 68.Han EJ, Ahn JS, Choi YJ, Kim DH, Chung HJ. Changes in gut microbiota according to disease severity in a lupus mouse model. Int J Mol Sci. 2025;26:1006. doi: 10.3390/ijms26031006. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B69] 69.Yan X, Feng B, Li P, Tang Z, Wang L. Microflora disturbance during progression of glucose intolerance and effect of sitagliptin: an animal study. J Diabetes Res. 2016;2016:2093171. doi: 10.1155/2016/2093171. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B70] 70.Allin KH, Tremaroli V, Caesar R, Jensen BAH, Damgaard MTF, Bahl MI, Licht TR, Hansen TH, Nielsen T, Dantoft TM, et al. Aberrant intestinal microbiota in individuals with prediabetes. Diabetologia. 2018;61:810–820. doi: 10.1007/s00125-018-4550-1. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B71] 71.U.S. Department of Agriculture. USDA National Nutrient Database for Standard Reference (FoodData Central ID: 170283) Washington, D.C.: Nutrient Data Laboratory; 2019. [cited 2025 April 22]. Available from: https://fdc.nal.usda.gov/food-details/170283/nutrients. [Google Scholar]

[B72] 72.Dhingra D, Michael M, Rajput H, Patil RT. Dietary fibre in foods: a review. J Food Sci Technol. 2012;49:255–266. doi: 10.1007/s13197-011-0365-5. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B73] 73.Chung TY, Nwokolo EN, Sim JS. Compositional and digestibility changes in sprouted barley and canola seeds. Plant Foods Hum Nutr. 1989;39:267–278. doi: 10.1007/BF01091937. [DOI] [PubMed] [Google Scholar]

[B74] 74.U.S. Department of Agriculture; U.S. Department of Health and Human Services. Dietary Guidelines for Americans, 2020–2025. 9th Edition. Washington, D.C.: U.S. Department of Agriculture; 2020. [Google Scholar]

[B75] 75.Yang J, Bindels LB, Segura Munoz RR, Martínez I, Walter J, Ramer-Tait AE, Rose DJ. Disparate metabolic responses in mice fed a high-fat diet supplemented with maize-derived non-digestible feruloylated oligo- and polysaccharides are linked to changes in the gut microbiota. PLoS One. 2016;11:e0146144. doi: 10.1371/journal.pone.0146144. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B76] 76.Panasevich MR, Kerr KR, Dilger RN, Fahey GC, Jr, Guérin-Deremaux L, Lynch GL, Wils D, Suchodolski JS, Steer JM, Dowd SE, et al. Modulation of the faecal microbiome of healthy adult dogs by inclusion of potato fibre in the diet. Br J Nutr. 2015;113:125–133. doi: 10.1017/S0007114514003274. [DOI] [PubMed] [Google Scholar]

PERMALINK

Barley sprouts as a modulator of the gut microbiota, influencing glucose and lipid metabolism in ovariectomized female rats fed a high-fat diet

Yeonjeong Choi

Yoona Kim

Young-Min Lee

Abstract

BACKGROUND/OBJECTIVES

MATERIALS/METHODS

RESULTS

CONCLUSION

INTRODUCTION

MATERIALS AND METHODS

Ethics statements

Animal care

Experimental diet

Table 1. Composition of experimental diet (g/kg diet).

Sampling procedures

Biochemical analysis

Library construction and sequencing

Statistical analysis

RESULTS

Body weight, food intake, and organ weight

Table 2. Body weight, weight gain, intake, and FER of rats.

Table 3. Liver, kidney fat, and abdominal fat tissue weight of rats.

Serum levels of lipids

Table 4. Serum TG, TC, HDL-C, and LDL-C levels, and the related ratios of experimental rats.

Serum levels of fasting glucose, fasting insulin, and adiponectin

Table 5. Serum levels of fasting glucose, fasting insulin, HOMA-IR, and adiponectin in experimental rats.

Serum levels of ALP, GOT, and GPT

Table 6. Serum levels of ALP, GOT, and GPT in experimental rats.

Gut microbiota

Fig. 1. Effects of barley sprout intake on the gut microbiota composition in rats (n = 6–7). (A) The phylum level relative abundance of gut microbiota; (B) The family level; (C) The species level; (D) Heatmap of the Spearman correlation analysis of gut microbiota and biochemical markers.

Fig. 2. Effects of barley sprout intake on the gut microbiota diversity and abundance in each group (n = 6–7). (A) The α-diversity analysis in 2 indices (Shannon, Chao1) relative; (B) PC analysis of the gut microbial composition in rats.

DISCUSSION

ACKNOWLEDGMENTS

Footnotes

References

ACTIONS

PERMALINK

RESOURCES

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