Quinoa may improve fatty liver disease by activating cell cleanup through the Ras-PLD pathway

Offspring of male ICR mice whose sires were obese and dams were normal (SCXK (Jing) 2016–0011) were purchased from Beijing Vital River Laboratory Animal Technology Limited Company (Beijing, China). Prior to the start of the experiment, all mice were acclimatized and fed in a standard animal feeding room for 3 days. The mice were fed an ordinary diet or a high‐fat diet (HFD). The diet was purchased from Beijing HFK Bioscience Co. LTD (Beijing, China), and HFD was 60% fat. The rearing environment and experimental diet were maintained as described previously (Wang et al. 2022). All animal experiments were approved by the Institutional Animal Care and Use Committee of Beijing University of Chinese Medicine and conformed to current animal welfare and approved guidelines (permission number: BUCM‐2019041501‐200J).

A total of 20 male ICR mice were fed a normal diet for 4 weeks and then randomly assigned to a control group (n = 5) and an obese group (n = 15), which were fed normal and high‐fat diets, respectively, for 12 weeks. Mice in the obese group were randomly divided into an NAFLD group, quinoa for random time (QRT) group, and quinoa for fixation time (QFT) group, with five mice in each group, and the intervention was initiated. Mice in the control group were fed a normal diet, whereas those in the NAFLD and intervention groups were fed a high‐fat diet. Mice in the QRT group were fed quinoa daily and had no time limit, whereas those in the QFT group were fed 2 g/piece of quinoa per mouse at a fixed time of the day (8:30 a.m.). Quinoa diets were purchased from Shanxi Hao Chen Biological Technology Co. Ltd. The intervention lasted for 6 weeks. During the intervention phase, body weight and blood glucose were measured at the end of each week. Body fat was measured using a small animal body composition analyzer (EMR‐170‐S) at the end of the sixth week, and body fat and lean content were expressed as a percentage of total body weight.

Blood was collected from mouse eyeballs and used for further analysis. Blood glucose (GLU), serum alanine transaminase (ALT), serum aspartate transaminase (AST), triglycerides (TG), cholesterol (TC), high‐density lipoprotein cholesterol (HDL‐C), low‐density lipoprotein cholesterol (LDL‐C), serum creatinine (CREA), and blood urea nitrogen (BUN) were measured using an automatic biochemical analyzer (Hitachi, Japan). Insulin levels were detected by radioimmunoassay. Homeostatic model assessment for insulin resistance (HOMA‐IR) was calculated (fasting insulin in μIU/mL × fasting glucose in mmol/l/22.5) and was used as a surrogate marker of insulin resistance (Wallace et al. 2004).

The liver, pancreas, white adipose tissues and inguinal adipose tissue were harvested from each mouse and fixed in formalin for 24 h, after which gradient dehydration was performed and tissues were embedded in paraffin for sectioning. The sections were subsequently stained with hematoxylin and eosin and mounted on slides in resin. Images were captured to evaluate pathological changes.

For IHC, the liver tissues were harvested, sectioned (5 μm), and fixed in 4% paraformaldehyde using conventional procedures. IHC was performed using rabbit ERK1/2 (1:150; ABclonal), Phospho ERK1/2 (p‐ERK1/2) (1:150; ABclonal), and N/H/K‐RAS (1:200; ImmunoWay), Raf1 (1:150; ABclonal), MEK‐1 (1:200; UpingBio), p62 (1:500; Servicebio), Beclin1 (1:100; Selleck), ULK1 (1:100; Wanlei), mTOR (1:100; Selleck). Image J software was used to assess the results and calculate the average optical density. Use WB to detect the expression of HNF4A, ACOX2, and glucagon protein in the liver and pancreas. WB was performed using first antibodies against rabbit HNF4A (1:2000; ABclone), rabbit ACOX2 (1:2000; ABclone), rabbit anti glucagon (1:20000; ABclone), rabbit anti LC3B (1:1000; Selleck) and rabbit anti β‐actin (1:5000; Biorigin). Use Image J to analyze protein expression bands and normalize them to the intensity of the corresponding bands of β‐actin. All WB experiments were conducted using three samples per group.

We screened prospective targets by intersecting quinoa‐ and NAFLD‐related targets. A literature review of PubMed and CNKI was performed to determine the chemical composition of quinoa. Chemical structures were obtained from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/pccompound/↗), chemical source network (www.Chemsrc.com↗), and a chemical professional database (www.organchem.csdb.cn↗). The obtained chemical structure was introduced into the SwissADME platform (http://www.swissadme.ch/↗), with two or more gastrointestinal absorption as "High" and five types of pharmacodynamic prediction (Lipinski, Ghose, Veber, Egan, Muegge) as "Yes" as potential active ingredients of quinoa. The key word "NAFLD" was used in the PharmGkb, OMIM, GeneCards, Drugbank, and TTD databases to search for related targets. These targets were then standardized using the UniProt database (https://www.uniprot.org/↗), and UniProt ID genes without human samples were removed.

Quinoa and NAFLD disease target data were imported together to a Venn diagram drawing website (http://bioinformatics.psb.ugent.be/webtools/Venn/↗), and the intersection of the drug and disease targets was obtained; the intersection genes in the Venn diagram output represented the potential targets of quinoa to treat NAFLD. The intersection genes were imported into the STRING database (https://string‐db.org/↗) to build a protein–protein interaction (PPI) network, and the confidence score was set to ≥ 0.7. After protein interaction analysis, the resulting file was exported using the Cytoscape software, and a core target map of the protein interaction network was created. Gene ontology (GO)–biological process function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the KOBAS (http://kobas.cbi.pku.edu.cn/↗), DAVID (https://david‐d.ncifcrf.gov/↗), and Metascape (http://metascape.org↗) databases.

Transcriptome profiling of the mouse liver tissues was performed by RNA‐Seq. Three biological replicates were made for each group transcriptomic comparison. RNA integrity was assessed using the RNA Nano 6000 Assay Kit of the Bioanalyzer 2100 system (Agilent Technologies, CA, USA). Total RNA was used as input material for the RNA sample preparations, and mRNA was purified from total RNA using poly‐T oligo‐attached magnetic beads. Subsequently, double‐stranded cDNA was constructed and subsequently used to establish the cDNA library, and the library fragments were purified with AMPure XP system. At last, PCR products were purified (AMPure XP system) and library quality was assessed on the Agilent Bioanalyzer 2100 system. The clustering of the index‐coded samples was performed on a cBot Cluster Generation System using TruSeq PE Cluster Kit v3‐cBot‐HS (Illumia) according to the manufacturer's instructions. After cluster generation, the library preparations were sequenced on an Illumina Novaseq platform and 150 bp paired‐end reads were generated. After quality control, index of the reference genome was built using Hisat2 v2.0.5 and paired‐end clean reads were aligned to the reference genome using Hisat2 v2.0.5. Differential expression analysis of two groups was performed using the DESeq2 R package (1.20.0). Finally, we used clusterProfiler R package to test the statistical enrichment of differential expression genes in KEGG pathways. Using GSEA software (version 3.0) to detect differential gene expression pathways between groups.

Total RNA was extracted from liver tissue using Trizol, and then reverse transcribed into cDNA using HiScript II Q RT SuperMix. Perform RT‐qPCR using Taq Pro Universal SYBR qPCR premix. The primers were designed and synthesized by Hunan Aikerui Bioengineering Co. Ltd. The upstream primer sequence of ras is CCTACCGGAAACAGGTGGTC, and the downstream primer sequence is GGTCCCGCATGGCACTATAC, with an amplification product length of 93 bp; the upstream primer sequence of Raf1 is TTCTTTCCCAATGCGTCGGA, and the downstream primer sequence is GGAGTGGACGTTGACCTCTG, with an amplification product length of 153 bp; the upstream primer sequence of Mek is GAGTGTTCGGAGTGGACCTG, and the downstream primer sequence is CTCCAAATTCCTTCTTCCAGTTGC, with an amplification product length of 139 bp; the upstream primer sequence of ERK is TTGCTTTCTCTCCCGCACAA, and the downstream primer sequence is CTGCTCCAGGTATGGGTGG, with an amplification product length of 156 bp; the upstream primer sequence of Pld1 is GGGAACGCTCTACAGGCAAT, and the downstream primer sequence is AGGTTTCCTTCCAGCTCTGC, with an amplification product length of 158 bp; the upstream primer sequence of β‐actin is CAGCCTTCCTTCTTGGGTAT, and the downstream primer sequence is AGGTCTTTACGGATGTCAACG, with an amplification product length of 95 bp. The relative expression of mRNA was quantified using 2^−ΔΔCT with β‐actin as an internal reference.

Data were analyzed using SPSS 20.0 and are expressed as means ± standard deviation. One‐way analysis of variance or non‐parametric tests were used for general data based on the normality test, and the least significant difference method was used for comparisons between groups. Graphs were drawn using GraphPad Prism (version 8.0). Related statistical methods were performed as previously described (Yu et al. 2024).

The effects of quinoa supplementation on body weight are shown in Figure 1A. During the 6‐week intervention phase, the weight of the NAFLD group was significantly higher than that of the control group (p < 0.01). Body weight in the QRT and QFT groups decreased considerably compared to that in the NAFLD group at each measurement time point (p < 0.01). Body fat mass and content were significantly higher in the NAFLD group than in the control group (p < 0.01), and the body fat mass and content in the QRT and QFT groups were lower than those in the NAFLD group (p < 0.01). Further, the body lean mass in the NAFLD group was slightly elevated compared to the other three groups, but the body lean content was markedly reduced (p < 0.01) (Figure 1B,C). The QRT and QFT groups exhibited nearly identical results. In addition to weight and body fat, we measured blood glucose and insulin levels and performed HOMA‐IR (Figure 1D–F). Throughout the intervention, blood glucose levels were higher in the NAFLD group than in the control group (p < 0.01), whereas blood glucose levels in the QRT and QFT groups tended to be lower than those in the NAFLD group (p < 0.01). Insulin levels were slightly lower in the NAFLD group than in the control group; however, this difference was not statistically significant. Insulin levels were significantly elevated in the QRT and QFT groups compared with those in the control and NAFLD groups (p < 0.01); HOMA‐IR in the NAFLD group was higher than that in the control group (p < 0.01), and decreased to various degrees in the QRT and QFT groups compared to the NAFLD group, although no significant difference was observed. In summary, quinoa reduced body weight, body fat, and blood glucose levels in mice with NAFLD.

Serum metabolic parameters were measured after the 6‐week intervention. Compared to the control group, the NAFLD group showed significant upregulation of TC, TG, LDL‐C, ALT, AST, CREA, and BUN (p < 0.01), whereas HDL‐C levels decreased significantly in the NAFLD group (p < 0.01) (Figure 1G–N). The TC, TG, LDL‐C, ALT, AST, and CREA levels in the QRT and QFT groups were lower than those in the NAFLD group (p < 0.01), with no significant differences between the two groups.

Histological analysis revealed excessive lipid accumulation and infiltration of inflammatory cells into the liver tissues of NAFLD mice (Figure 2A), suggesting chronic hepatocellular injury and inflammation. We observed a significant increase in the liver weight of NAFLD mice (p < 0.01) (Figure 2D), and hepatocyte degeneration and liver weight were significantly reduced in the QRT and QFT groups after the intervention. HE staining of the pancreatic sections (Figure 2B) showed that the islets were small, the cells in the islets were arranged irregularly, the size of the islet nuclei was irregular, and some cells showed vacuolar degeneration in the NAFLD group. The cells in the islets were arranged regularly, with clear boundaries, abundant cytoplasm, and islet nuclei of regular size and shape in the QRT and QFT groups. HE staining of white adipose tissue (WAT) (Figure 2C) showed that in the NAFLD group, the volume of adipocytes increased significantly, the size of adipocytes was uneven, the cell wall was not completely clear, and the number of intracellular lipid droplets increased. After quinoa supplementation, the WAT morphology improved to varying degrees, the cells were arranged neatly, and the cell volume decreased.

A network pharmacology analysis was performed to elucidate the mechanism of action of quinoa in NAFLD. A total of 118 chemical components of quinoa were identified through a literature review; subsequently, 72 potentially active components were identified following intestinal absorption and drug‐like screening. A total of 536 quinoa and 1231 disease targets were identified via network pharmacological screening, and an overlap of quinoa genes with NAFLD targets revealed 147 intersecting genes between quinoa and NAFLD (Figure 3A). The 147 intersecting genes were subjected to GO enrichment analyses, which included 1570 biological processes, 97 cell compositions, and 159 molecular functions (Figure 3B). The results showed that the biological effects of quinoa in treating NAFLD mainly included the regulation of hormone levels, hormone metabolic processes, and responses to hormones. The cellular composition mainly included membrane rafts, membrane microdomains, and dendrites. The molecular functions included binding to nuclear receptors, ligand‐activated transcription factors, and transcription factors. KEGG signaling pathway enrichment resulted in 180 signaling pathways (Figure 3C). The more abundant targets are the Ras signaling pathway, lipid and atherosclerosis, PI3K‐Akt signaling pathway, autophagy‐animal, and phospholipase D signaling pathway. We used Cytoscape 3.9.1 to build a quinoa component‐target‐pathway network diagram, which comprised 122 nodes and 576 edges (Figure 3D). The degree, betweenness, and closeness centralities of apigenin‐7‐methylether were 18, 0.029, and 0.426, respectively, suggesting that apigenin‐7‐methylether is the main compound affecting the mechanism of action of quinoa in NAFLD, followed by acacetin (16, 0.021, and 0.42) and linolenic acid (16, 0.016, and 0.403). This indicates that the mechanism of action of quinoa in treating NAFLD is based on the synergistic effects of multiple compounds, genes, and targets. Apigenin‐7‐methylether, acacetin, linolenic acid rank high in degree values. This indicates that the mechanism of action of quinoa in treating NAFLD is based on the synergistic effects of multiple compounds, genes, and targets.

The results of transcriptome analysis indicated a considerable difference between each group (Figure 4A). PCA (principal component analysis) showed that the four groups had distinct gene expression profiles (Figure 4B). The clustering heat map showed different clustering patterns between the Control group and the NAFLD group, while clustering patterns were similar between the Control group and the QFT group (Figure 4C). The KEGG pathway analysis results revealed that NAFLD was highly associated with the RAS signaling pathway, autophagy‐ animal, and phospholipase D signaling pathway (Figure 4D). Notably, differential genes between the NAFLD group and two treatment groups of quinoa were also enriched in the RAS signaling pathway and autophagy‐ animal (Figure 4E,F).

To determine whether the significantly enriched signaling pathways in NAFLD were activated or inhibited by quinoa intervention, GSEA analysis was conducted. The results showed that after quinoa intervention, the RAS signaling pathway was inhibited in NAFLD mice (Figure 5A), and the autophagy‐animal pathway was activated (Figure 5B). Interestingly, the phospholipase D signaling pathway is also a key node in the RAS pathway (Figure 5C).

The above results indicate that the Ras‐PLD signaling pathway and autophagy play important roles in NAFLD. Therefore, we investigated the role of quinoa in this pathway. Compared with the control group, the expression levels of Ras, Raf1, MEK‐1, ERK1/2, p‐ERK1/2, PLD1, mTOR, and p62 in the liver tissue of NAFLD group mice were significantly increased (p < 0.01), while the expression levels were significantly decreased after quinoa intervention. The expression of ULK1 and Beclin1 in the liver tissue of NAFLD group mice was significantly reduced (p < 0.01), while the expression level was significantly increased after quinoa intervention. Meanwhile, the LC3‐II/I ratio in the NAFLD group was markedly decreased compared to the control group, while the QRT and QFT groups showed a significant upregulation trend compared to the NAFLD group (Figure 6). The results indicate that quinoa has an impact on NAFLD, which may be related to the Ras‐PLD signaling pathway and autophagy.

To further elucidate the Ras‐PLD signaling pathway and autophagy mechanism in the treatment of NAFLD with quinoa, the mRNA levels of ras, Raf1, Mek, ERK, and Pld1 in liver tissue were evaluated by RT‐qPCR (Figure 7). The results showed that the mRNA levels of ras, Raf1, Mek, ERK, and Pld1 in the liver tissue of NAFLD group mice were significantly higher than those in the control group (p < 0.01), while the mRNA levels significantly decreased after quinoa intervention (p < 0.05), which were consistent with the results of IHC experiments.

We evaluated the expression of HNF4A in liver and pancreatic tissues, and the results showed that compared with the control group, the expression of HNF4A in the NAFLD group showed a significant downward trend (Figure 8). In the QRT and QFT groups, the expression of HNF4A increased in the liver of mice, and slightly increased in the pancreas of mice in the QFT group. The expression of ACOX2 in the liver and pancreas of NAFLD group mice was lower than that in the control group, and slightly increased after quinoa intervention. The expression of glucagon in the liver and pancreatic tissues of NAFLD group mice was significantly higher than that of the control group (p < 0.01), while the expression of glucagon in QRT and QFT group mice was lower than that of the NAFLD group.