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Review

Dietary Soy Impact on Host Transcriptome Profile—A Review

by
Andrei Anghel
,
Maria Sala-Cirtog
*,
Catalin Marian
,
Corina Samoila
and
Ioan Ovidiu Sirbu
Biochemistry Department, University of Medicine and Pharmacy “Victor Babes”, 300041 Timisoara, Romania
*
Author to whom correspondence should be addressed.
Appl. Sci. 2021, 11(17), 7905; https://doi.org/10.3390/app11177905
Submission received: 9 July 2021 / Revised: 20 August 2021 / Accepted: 23 August 2021 / Published: 27 August 2021
(This article belongs to the Special Issue Trends and Prospects in Pathophysiology of Diet-Related Diseases)
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Abstract

:
Whether eaten, drank, or taken in the form of supplements, soybean has been a part of the human diet for centuries. The dietary use of soybean has been extensively proven to be beneficial for human health, protecting against a wide range of chronic diseases. However, our knowledge regarding the impact of soy intake on global gene expression is still incomplete. The present review summarizes and compares data describing the transcriptional changes in several tissues from two different phyla (fish and mammals) upon soybean diet supplementation. We performed comparative STRING-based pathway enrichment analysis of both individual and aggregated soy-induced transcriptome data in fish and mammals and identified the signaling pathways common between the two datasets. We hypothesize that these pathways represent a conserved transcriptome response to the soy-enriched dietary challenge.

1. Introduction

Known as a wonder food, wonder crop, or meat without bone, soybean has been a matter of intense debate regarding its diet-induced health effects. Soybean is not only a notoriously rich source of proteins and essential amino acids but also of folate, riboflavin and vitamin K, minerals (calcium, magnesium, iron, copper, manganese, molybdenum), and fibers [1,2]. Replacing meat with soy has beneficial health effects such as lowering cholesterol and saturated fat while increasing folate, calcium, magnesium, iron, vitamin K and fiber intake [3]. In addition, soybean contains unique nutrients such as isoflavonoids (ISO), phenolic acids, phytoalexins, phytosterols, and saponins, the roles of which are not yet fully understood [4]. These bioactive compounds may act through synergic or independent mechanisms to confer positive effects on human health [5].
Global soybean consumption varies from one country to another and even within the same country. For example, the average daily intake of soybean in China, Japan or Taiwan is around 36 g [6], while in Europe and the US is only 4 g [7]. There are also significant changes in dietary habits in Asians living in the US, and even in Asians living in urban vs. rural areas [6]. Furthermore, soy consumption varies according to age. In Japan, as the diet of young adults becomes more and more westernized, soy foods have begun to be replaced, such that older Japanese consume almost twice as much soy as the young ones [8]. These outstanding variations in diet habits might explain the divergent results of the health benefits analyses.
Most of the beneficial health effects of a soy diet have been attributed to isoflavones, generally known as phytoestrogens [9], while data on other soy phytochemicals are more limited [10]. After being metabolized by gut microbiota, their active compounds, genistein and daidzein, are either absorbed in the small intestine or delivered into the large intestine for further metabolism via intestinal microflora [11]. It is well known that among day-to-day dietary products, only soybean provides a relevant amount of isoflavones: 3.5 mg per gram of protein [12]. The concentration of isoflavones highly depends on the processing method: whole soy products such as edamame or soy flour have the highest dose of isoflavones, while soy milk, soy sauce or other highly processed soy foods have up to 80% lower content of isoflavones [13].
The cardiovascular benefits of the soy diet are mainly linked to HDL cholesterol elevation and lowering LDL cholesterol/total cholesterol/triglycerides [14,15]. This effect is directly linked to soy proteins and saponins, which, due to their amphiphilic nature, form insoluble complexes that reduce the absorption of LDL cholesterol in the intestine [16,17]. Furthermore, the ISO, as well as genistein and daidzein, has an antioxidant effect by lowering LDL cholesterol oxidation [18], stimulating the production of superoxide dismutase [19], activating the Nrf2 pathway [20], and inhibiting nitric oxide synthesis in macrophages [21,22,23]. Of note, the combination of active soy principles was found to have an additive hypocholesterolemic effect compared to soy protein ingestion alone [24]. Furthermore, a high intake soy has been shown to promote vascular dilation in the periphery, while the data on cerebrovascular area are not conclusive [25]. However, a possible connection between soy diet and the development and management of vascular cerebral lesions including cerebral cavernous malformations (possibly mediated by gut lining bacteria) has not been explored so far [26,27].
Although supported by many ex vivo and in vivo data, the cancer prevention benefit of a soy enriched diet is still one of the most controversial, mainly due to the modest, inconsistent, and sometimes even controversial epidemiological data [28]. It is unanimously accepted that soy isoflavones, in general, and genistein, in particular, are the main cancer-preventing compounds. Genistein might exert its chemo-preventive properties through a combination of epigenetic (histone acetylation, DNA methylation), antiproliferative, proapoptotic, as well as anti-inflammatory, antioxidant, and antiangiogenic mechanisms [29,30,31,32]. Soy ISOs could bind to estrogen receptors (with significantly higher affinities for ER-β) [33] and androgen receptors [34] and thus impact the evolution of hormone-dependent cancers [35,36]. Although both ex vivo and clinical experiments show that soy ISOs might also promote the proliferation of malignant cells [37], the epidemiological data suggest an inverse correlation between soy food intake and the risk of cancer [38,39].
In women, ISOs might exert both estrogenic and antiestrogenic effects: in postmenopausal women, the phytoestrogens act as estrogens, while in premenopausal women, the estrogen levels are high, and exert the opposite effect [29].
Dietary soy could also have a protective effect against yet another chronic disorder, diabetes mellitus. Isoflavones, especially genistein, have a beneficial impact on the homeostasis of carbohydrate metabolism by lowering glucose uptake [34]. In addition, due to their high content in glycine and arginine, soy proteins might directly influence the secretion of insulin and glucagon [40]. Overall, soy diet intake is associated with a reduced risk of diabetes, although differences in sex and ethnicity might apply [41,42].
Overall, soy consumption has been demonstrated to provide health benefits, most notably regarding chronic diseases. Nevertheless, the components that seem to be responsible and their mechanisms of action are still debated. This review will focus on the transcriptional changes in several tissues from different species after whole soybean and soy protein/derivate dietary interventions.

2. Materials and Methods

In order to retrieve the current data on transcriptomic changes upon whole soybean (+/− soy protein) diet supplementation, we searched PubMed [43] using the keywords “soy diet”, “transcriptome”, “nutrigenomics”, and gene expression regulation”. Exclusion criteria were as follows: experiments using only soy components (proteins, genistein, saponins, etc.) instead of whole soybean/soybean + soy proteins, lack of high throughput methods (microarray or next-generation sequencing), and written in a language other than English. At the end of the selection process, only eight studies were included in the analysis. The details regarding the animal species used, the characteristics of the dietary intervention (composition, duration), tissues analyzed, and the analytical platform used are presented in Table 1.
We retrieved the sets of differentially expressed genes (as communicated by the authors) and subjected them to gene ontology/KEGG pathway overrepresentation analysis using the STRING platform, version 11.0 (http://string-db.org/), accessed on 21 May 2021). (using FDR = 0.05 as cutoff). The flowchart of our research work is presented in Figure 1. This represents Method 1.
To identify which soy-induced pathways changes are conserved in evolution, we aggregated the transcriptome data based on their phyla source: fish (Atlantic salmon, zebrafish, yellow perch) and mammals (rats, mice, humans). After removing the duplicates, we performed a novel STRING analysis (FDR < 0.05) of differentially expressed genes and compared the significant KEGG pathways from the fish group with those in the mammal group. This represents Method 2.

3. Results

To our surprise, only eight reports matched our selection criteria and could be roughly divided into fish (four studies) and mammals (four studies). After removing the duplicates and the low confidence transcripts, the expression of 1.779 genes were reported as significantly altered in mammals, of which 838 (47.1%) were downregulated and 941 were upregulated. In the fish group, the expression of 1.524 genes was reported as significantly changed, of which 932 (61.1%) were downregulated and 592 were upregulated. The ratios between upregulated and downregulated genes in the two phyla are significantly different (p-value for the Z test < 0.00001). After combining fish and mammal data, 1770 (53.6%) genes were downregulated, and 1533 were upregulated upon soy diet intervention. All the upregulated and downregulated genes for both phyla groups and the commonly altered ones are shown in Supplementary Table S1. To better understand the biological significance of these changes, we decided to use two methods of analysis.
We submitted each set of reported data to STRING analysis (using a medium confidence interaction score of 0.400), focusing on retrieving the enriched KEGG pathways (FDR < 0.05). We have chosen STRING, since it builds gene interaction networks based on experimental and co-expression data, thus reducing the noise inherent to expression data from multiple cell/tissue types. The gene networks obtained are of relatively low complexity, with statistically significant protein–protein interaction (PPI) enrichment obtained for only six datasets. Overall, 67 KEGG pathways in mammals and 72 KEGG pathways in fish are potentially altered by soy enriched diet, of which 22 are common to both phyla (Table 2). These common pathways might represent a response to the soy diet conserved between fish and mammals and include metabolic pathways, biosynthesis of unsaturated fatty acids, steroid biosynthesis, fatty acid metabolism, fatty acid elongation, retinol, and xenobiotic metabolism. These pathways include most of the candidate genes for diabetes, atherosclerosis, regulation of lipid metabolism. Of note, the shared, potentially conserved pathways are composed of different sets of altered genes, suggesting that distinct transcriptome changes mediate these common metabolic effects.
Given that due to their size not all datasets allowed a successful STRING analysis, we performed a STRING/KEGG pathway enrichment analysis on pooled transcriptome data from fish, respectively, mammal samples. The gene interaction networks were of higher complexity, with significantly higher PPI probabilities, thus richer information. Nevertheless, the KEGG pathway analysis results were similar: 61 KEGG pathways in fish, 55 pathways in mammals, of which 23 are common to both phyla (Table 3). The two analysis methods (Method 1 and Method 2) lead to 16 KEGG pathways that are common between fish and mammals (Figure 2). See Supplementary Table S2 for all the DEGs corresponding to each Common KEGG pathways of individual and pooled datasets (Method 1 and Method 2).
Next, in order to find the pathways upon which the soy supplementation has an ambiguous effect in both fish and mammals, we stratified the data in upregulated and downregulated DEGs and performed separate STRING analyses. In fish, the up vs. down analysis found 10 pathways, while in mammals, only three pathways were found (of which, only the metabolic pathway is shared between the two phyla) (Table 4).

4. Discussion

Nutrients can act as dietary signals detected by the cellular sensors and influence gene expression and metabolite production [52]. The health benefits of whole soybean diet include protection against chronic diseases, including heart diseases, diabetes, and osteoporosis [15,16]. The molecular mechanisms responsible for these effects are still intensely debated. Interventional studies focused only on soybeans components (proteins, genistein, saponins) attempted to shed on into how soy diet affects gene expression but fail in reproducing the natural changes induced by a regular (every day) soybean-supplemented diet. Since whole soybean and soy protein are among the most widely used soy diet supplements, and, in an attempt to make our analysis relevant to naturally occurring humans’ feeding regimens, we chose to include in our analysis the transcriptome data only from this kind of interventional studies.
Our comparative analysis of fish and mammal transcriptome data identified multiple common pathways potentially impacted upon soy diet intervention.
As expected, the metabolic pathway was enriched in all species and tissues, irrespective of the dietary intervention regimen, reflecting soy’s overall well-known metabolic impact. However, the enrichment was also common for both downregulated and upregulated genes datasets, suggesting that the overall metabolic effect results from balancing subclusters of metabolic gene networks. Previous studies indicated that soy might have a serum cholesterol-lowering effect in humans when consumed at levels of 1.5–2 g per day [53]. The hypocholesterolemic action of the soy diet relies on reducing associated risk factors for cardiovascular disease by lowering low-density lipoprotein (LDL) concentrations, increasing HDL (high-density lipoproteins), and by inhibiting lipid peroxidation [54].
Nevertheless, we also found several discrepancies between fish and mammals. In mammals, gene sets related to lipid catabolism were upregulated after soy dietary intervention. Both Acacb (Acetyl-CoA carboxylase 2), which is responsible for fatty acids oxidation [55], and Ces1d (Carboxylesterase 1D), whose function is to hydrolyze triacylglycerols and monoacylglycerols [56], were overexpressed. On the other hand, genes involved in cholesterol biosynthesis (such as Cyp2c23 or Cyp2c11, members of cytochrome P450, subfamily 2) were repressed. Cyp2c11 is an essential component of steroid hormones and fatty acid metabolism and a biomarker for hypertension [57]. We also noticed the downregulation of Lipc (Lipase C), involved in the conversion of very-low-density lipoproteins (VLDL) and intermediate-density lipoproteins (IDL) to low-density lipoproteins (LDL) [58]. Its repression is associated with a delay in atherosclerosis in mice [59].
While the hypocholesterolemic effect of the soy diet in mammals was expected, the impact in fish is puzzling, especially regarding cholesterol homeostasis. Sc5d (Sterol-C5-desaturase-like), fdft1 (Farnesyl-diphosphate farnesyltransferase 1), acat2 (Acetyl-CoA Acetyltransferase 2) are genes involved in cholesterol synthesis and absorption, and they were all upregulated with over 2-fold changes. Cytochrome P450 lanosterol 14α-demethylase (cyp51), a key enzyme responsible for an essential step in the biosynthesis of sterols, was increased [60] while cyp7a1 (cholesterol 7-alpha-hydroxylase), an enzyme that oxidizes cholesterol, was decreased.
Rainbow trout subjected to plant-based diet interventions show enhanced hepatic cholesterol synthesis mediated by srebp-2, lxr-α (liver X receptor alpha), and miR-223 [61]. Physiologically, when dietary cholesterol level is low, cyp7a1 is downregulated by Srebp (sterol regulatory element-binding protein) [62], which leads to an increase in the hepatocytes’ cholesterol level [63]. It is possible that the soy-induced upregulation of cholesterol biosynthesis is meant to compensate for its dietary lack and thus maintains cholesterol homeostasis [50].
We also found that the biosynthesis of unsaturated fatty acids, fatty acid metabolism, and fatty acid elongation pathways were also highly enriched. In rodents, acot1, acot2, acot3 (Acyl-CoA thioesterase), and acaa1b (Acetyl-Coenzyme A acyltransferase 1), enzymes responsible for acyl-Coa and acetyl-CoA hydrolysis were upregulated [64]. Although the role of Acot enzymes in fatty acid metabolism is not fully understood, they are considered a key element in maintaining an optimal level of fatty acids’ beta-oxidation [65]. In fish, we noticed a possible activation of these lipids’ pathways. Fads2 (Fatty acid desaturase 2), known to catalyze the biosynthesis of fatty acids [66], is upregulated, while genes such as hadha and hadhb (hydroxyacyl-CoA dehydrogenase trifunctional multienzyme complex), essential for fatty acid oxidation, are downregulated. They are all essential components of the multistep process that breaks down fat molecules and converts them into energy [67]. The well-known impact of soy intake on lipid metabolism in mammals (reduction in hepatic lipotoxicity by preventing the transport of fatty acids to extra-adipose tissues) might thus be explained by these coordinated transcriptome changes [68]. One should nevertheless take into account that the response to soy diet is tissue-specific: reduced lipogenesis in the liver [69], increased unsaturated fatty acid biosynthesis (monounsaturated fatty acids, polyunsaturated fatty acids, C18:1 trans-11, C18:2 trans-10, cis-12, omega-3) in the mammary gland [70]. As for the 240 fatty acid metabolism gene alterations in fish, we noticed changes that suggest an increase in fatty acid biosynthesis in the intestine. Since dietary fatty acids are taken up by enterocytes, resynthesized into triacylglycerol, and stored as lipid droplets, it is conceivable that the lipids-poor soy-rich diet increases intestinal fatty acid metabolism in an attempt to maintain lipid homeostasis [68].
Closely related to cholesterol metabolism, steroid hormone biosynthesis is another pathway common to fish and mammals. Rodent Cyp4A14, a member of the cytochrome P450 monooxygenases family, considered female-predominant [71], was overexpressed in the liver. Moreover, genes such as Hsh17b (hydroxysteroid 17-beta dehydrogenase family), involved in androgen and estrogen metabolism [72], were deregulated. In mammals, Hsh17b6 (essential for dihydrotestosterone-DHT-biosynthesis and involved in the pathophysiology of Polycystic Ovary Syndrome) [73] was downregulated. In fish, hsh17b7, involved in the activation of estrogens (estrone to estradiol) and inactivation of androgens (dihydrotestosterone to androstanediol), was overexpressed [73]. Estradiol stimulates breast carcinogenesis while dihydrotestosterone (DHT) inhibits it [74]. Hence, the anti-carcinogenic effect of the soy diet might be explained by the modulation of 17β-HSD (17β-hydroxysteroid dehydrogenases) gene activity in breast cancer cells through its phytoestrogenic effects, presumably mediated by Genistein’s high affinity for the estrogen receptor [75,76].
Another expected fish-mammal common pathway targeted by the soy diet is retinol metabolism. Retinoids are obtained solely from the diet (and soybeans are rich in vitamin A), being required for maintaining normal growth, development, reproduction, vision, and a healthy immune system [77]. The clinical use of retinoids is known to induce hypertriglyceridemia [78], a side effect that could be counteracted by soy protein diet supplementation since soy is known to inhibit signaling through RAR-beta (Retinoic acid receptor beta) in the liver [78,79]. One should add that in the analysis of the fish dataset, we noticed a downregulation of retsat (retinoid saturase). Retsat has an important role in adipogenesis (promotes normal differentiation) and is downregulated in obese mice and humans [80].
Both phyla showed a downregulation of several UGT (UDP-Glucuronosyltransferases) superfamily genes. Based on current knowledge, xenobiotic metabolism (common among mammals and fish) is one of the main pathways altered by the soy diet [81]. UGT enzymes are essential members of phase I and II drug metabolism, which convert endogenous and exogenous lipophilic metabolites into more polar, less toxic, and easy to excrete compounds. They are often considered modulators for xenobiotics and steroids, thereby controlling their potency and availability [82]. We noticed downregulation of various genes from UGT1 and UGT2 families; since phytoestrogens’ most important detoxification pathway is glucuronidation, this effect (most probably mediated by genistein) explains the pro-estrogenic role of soy diet supplementation [71]. Soy-induced diet inhibition of UDP-glucuronosyltransferases genes might increase the toxicity of anti-cancer drugs and contribute to drug resistance of cancer cells [83,84,85].
One of the fish-mammal common pathways, found enriched after STRING analysis of the pooled datasets (Method 2) is ferroptosis. Ferroptosis is a unique iron/ROS-dependent form of cell death driven by the accumulation of iron-dependent lipid peroxidation products [86]. Fe3+ is imported into the cell through TFR (transferrin receptor) and then reduced to Fe2+, released in the cytoplasm by SLC11A2 (Solute Carrier Family 11 Member 2) metal transporter [87]. Ferroptosis is a natural tumor suppressor pathway and plays a significant anti-cancer role [88]. In our study, multiple inhibitors of ferroptosis, such as Slc7a11 (Solute Carrier Family 7 Member 11), Alox15 (15-lipoxygenase), and Ftl (Ferritin Light Chain) were found downregulated. Recent studies demonstrated that the overexpression of Slc7a11 promotes tumor growth by suppressing ferroptosis [89]. By increasing iron uptake and reducing iron storage, the soy diet might promote ferroptosis; this could explain the reports linking soy diet to anti-tumoral effect and provides yet another strategy for cancer therapy. Moreover, the soy diet could counteract the age-related accumulation of iron stores, decreasing the risk for cardiovascular diseases [90].
An aspect that is often forgotten is that the soy diet has been shown to modulate the levels of specific mature microRNAs. Thus far, only two reports have assessed the relationship between soy intake and the changes in miRNA expression in mammals. Guo et al. evaluated the association of long-term (one year), pre-diagnosis soy consumption with the expression of miRNAs in patients diagnosed with triple-negative breast cancer (TNBC) [47]. A long-term soy diet was associated with strong upregulation of 13 microRNAs, including the well-known tumor suppressor miR-29a-3p. Seclaman et al. examined the liver of soy-fed male mice [46] and described the transcriptome impact of upregulated miR-145a-5p and miR-455-3p. Interestingly, the transcriptome analysis identified iron metabolism and xenobiotic/fatty acid metabolizing pathways as coordinately regulated by the two microRNAs. To the best of our knowledge, this is the first soy interventional study indicating that soy induced transcriptome changes might be due to post-transcriptional regulatory mechanisms. It is also worth noting that the conserved miR-150-5p was found to be upregulated in both studies, despite the differences in tissue analyzed (breast cancer cells vs. normal liver), duration of soy-diet (one year vs. one month), and species analyzed (humans vs. mice). This might suggest that miR-150-5p is part of mammals’ common, evolutionary-conserved transcriptome response to soy-enriched diet. Of note, besides its role in lipid and iron metabolism, miR-150-5p is also known to be involved in carcinogenesis [91,92].
Taken together, these findings indicate that the soy diet induces significant gene expression responses in different experimental models, an effect that could be modulated at both transcriptional and post-transcriptional levels. The best-known transcriptional factors mediating soy transcriptional effects are RICTOR (rapamycin-insensitive companion of TOR, complex 2) and SREBF1 (sterol regulatory element-binding transcription factor 1) [45,46]. The soy-induced suppression of these two transcription factors protects against insulin resistance and fatty liver [93,94]. CEBPD (CCAAT/enhancer-binding protein delta), a transcriptional regulator that acts as a tumor suppressor, is strongly induced by soy-diet, which might explain the repression of multiple oncogene targets [39]. On the other hand, the impact on microRNA expression indicates that soy-induced gene regulation also involves post-transcriptional mechanisms [46,47].
Significant data show that diet might lead to epigenetic changes such as DNA methylation or histone modifications [95]. Genistein has been shown to induce specific DNA methylation changes in rodents by altering coat color and protecting mice offspring from obesity [96]. Additionally, epigenetic changes associated with the soy diet were observed in primates [97,98]. Howard et al. described an interesting pattern of DNA methylation for seven primate genes, among which, unexpectedly, the homeobox genes. These changes were then related to lipid and glucose metabolism modifications, suggesting increased insulin sensitivity [97]. Moreover, epigenetic changes in Hox genes can affect a variety of cancers [99].
By analyzing the similarities and differences of soy-related transcriptome impact in several experimental models and tissues, this review is an attempt to better understand the gene expression changes induced by soy diet. Taken together, the transcriptome data analyzed here fully support the already known benefits/risks associated with the soybean diet. On the one hand, the common responses of fish and mammals (such as retinol, xenobiotic or ferroptosis pathways) under different experimental conditions point towards a possibly conserved transcriptome response to soy diet. On the other hand, we found some evident discrepancies between the two phyla regarding cholesterol and fatty acid pathways. Some pathways, such as cancer-related pathways (bladder cancer, breast cancer, endometrial cancer) or thyroid hormone pathways, were enriched only in mammals, while others (glucose and amino acids metabolism), surprisingly, only in fish. Furthermore, it would be interesting to monitor miR-150p association with soy diet data in other, more complex experimental setups.
It should also be pointed out that, by restricting our analysis to transcriptome analyses upon whole soybean/soy proteins dietary interventions, only eight datasets were finally included. Some of the datasets included did not support an enrichment analysis due to their small size. Although still more data are required to fully understand the link between soybean nutrients and gene expression changes, this review could be a helpful tool for further research.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/app11177905/s1, Table S1: Upregulated and downregulated genes for both phyla groups; Table S2: DEGs corresponding to Common KEGG pathways (Method 1 and Method 2).

Author Contributions

Conceptualization: M.S.-C., I.O.S., Investigation: A.A., C.S. and C.M.; Methodology: M.S.-C., I.O.S.; formal analysis: A.A., M.S.-C.; writing—original draft preparation: M.S.-C., I.O.S.; writing—review and editing: M.S.-C., I.O.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Karr-Lilienthal, L.K.; Kadzere, C.T.; Grieshop, C.M.; Fahey, G.C. Chemical and nutritional properties of soybean carbohydrates as related to nonruminants. Livest. Prod. Sci. 2005, 97, 1–12. [Google Scholar] [CrossRef]
  2. Medic, J.; Atkinson, C.; Hurburgh, C.R. Current Knowledge in Soybean Composition. J. Am. Oil Chem. Soc. 2014, 91, 363–384. [Google Scholar] [CrossRef]
  3. Tucker, K.L.; Qiao, N.; Maras, J.E. Simulation with Soy Replacement Showed That Increased Soy Intake Could Contribute to Improved Nutrient Intake Profiles in the U.S. Population. J. Nutr. 2010, 140, 2296S–2301S. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Kalaiselvan, V.; Kalaivani, M.; Vijayakumar, A.; Sureshkumar, K.; Venkateskumar, K. Current knowledge and future direction of research on soy isoflavones as a therapeutic agents. Pharmacogn. Rev. 2010, 4, 111–117. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. McCue, P.; Kalidas, S. Health benefits of soy isoflavonoids and strategies for enhancement: A review. Crit. Rev. Food Sci. Nutr. 2004, 44, 361–367. [Google Scholar] [CrossRef]
  6. Wu, A.H.; Ziegler, R.G.; Nomura, A.M.Y.; West, D.W.; Kolonel, L.N.; Horn-Ross, P.L.; Hoover, R.N.; Pike, M.C. Soy intake and risk of breast cancer in Asians and Asian Americans. Am. J. Clin. Nutr. 1998, 68, 1437S–1443S. [Google Scholar] [CrossRef] [PubMed]
  7. Shu, X.O.; Jin, F.; Dai, Q.; Wen, W.; Potter, J.; Kushi, L.; Ruan, Z.; Gao, Y.T.; Zheng, W. Soyfood intake during adolescence and subsequent risk of breast cancer among Chinese women. Cancer Epidemiol. Biomark. Prev. 2001, 10, 483–488. [Google Scholar]
  8. Nagata, C. Factors to Consider in the Association Between Soy Isoflavone Intake and Breast Cancer Risk. J. Epidemiol. 2010, 20, 83–89. [Google Scholar] [CrossRef] [Green Version]
  9. Patisaul, H.B.; Jefferson, W. The pros and cons of phytoestrogens. Front. Neuroendocrinol. 2010, 31, 400–419. [Google Scholar] [CrossRef] [Green Version]
  10. Ramdath, D.D.; Padhi, E.M.T.; Sarfaraz, S.; Renwick, S.; Duncan, A.M. Beyond the Cholesterol-Lowering Effect of Soy Protein: A Review of the Effects of Dietary Soy and Its Constituents on Risk Factors for Cardiovascular Disease. Nutrients 2017, 9, 324. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  11. Sirtori, C.R.; Even, R.; Lovati, M.R. Soybean Protein Diet and Plasma Cholesterol: From Therapy to Molecular Mechanisms. Ann. N. Y. Acad. Sci. 1993, 676, 188–201. [Google Scholar] [CrossRef] [PubMed]
  12. Wang, H.J.; Murphy, P.A. Isoflavone Content in Commercial Soybean Foods. J. Agric. Food Chem. 1994, 42, 1666–1673. [Google Scholar] [CrossRef]
  13. Wang, H.; Murphy, P.A. Isoflavone Composition of American and Japanese Soybeans in Iowa: Effects of Variety, Crop Year, and Location. J. Agric. Food Chem. 1994, 42, 1674–1677. [Google Scholar] [CrossRef]
  14. Taku, K.; Umegaki, K.; Sato, Y.; Taki, Y.; Endoh, K.; Watanabe, S. Soy isoflavones lower serum total and LDL cholesterol in humans: A meta-analysis of 11 randomized controlled trials. Am. J. Clin. Nutr. 2007, 85, 1148–1156. [Google Scholar] [CrossRef] [PubMed]
  15. Hermansen, K.; Dinesen, B.; Hoie, L.H.; Morgenstern, E.; Gruenwald, J. Effects of soy and other natural products on LDL:HDL ratio and other lipid parameters: A literature review. Adv. Ther. 2003, 20, 50–78. [Google Scholar] [CrossRef]
  16. Lovati, M.R.; Manzoni, C.; Gianazza, E.; Arnoldi, A.; Kurowska, E.; Carroll, K.K.; Sirtori, C.R. Soy Protein Peptides Regulate Cholesterol Homeostasis in Hep G2 Cells. J. Nutr. 2000, 130, 2543–2549. [Google Scholar] [CrossRef] [Green Version]
  17. Adams, M.R.; Golden, D.L.; Franke, A.A.; Potter, S.M.; Smith, H.S.; Anthony, M.S. Dietary Soy—Conglycinin (7S Globulin) inhibits atherosclerosis in mice. J. Nutr. 2004, 134, 511–516. [Google Scholar] [CrossRef] [Green Version]
  18. Wiseman, H.; O’Reilly, J.D.; Adlercreutz, H.; I Mallet, A.I.; Bowey, E.A.; Rowland, I.R.; Sanders, T.A. Isoflavone phytoestrogens consumed in soy decrease F(2)-isoprostane concentrations and increase resistance of low-density lipoprotein to oxidation in humans. Am. J. Clin. Nutr. 2000, 72, 395–400. [Google Scholar] [CrossRef] [Green Version]
  19. Szkudelska, K.; Nogowski, L. Genistein—A dietary compound inducing hormonal and metabolic changes. J. Steroid Biochem. Mol. Biol. 2007, 105, 37–45. [Google Scholar] [CrossRef]
  20. Mann, G.E.; Bonacasa, B.; Ishii, T.; Siow, R.C. Targeting the redox sensitive Nrf2–Keap1 defense pathway in cardiovascular disease: Protection afforded by dietary isoflavones. Curr. Opin. Pharmacol. 2009, 9, 139–145. [Google Scholar] [CrossRef]
  21. Rimbach, G.; Boesch-Saadatmandi, C.; Frank, J.; Fuchs, D.; Wenzel, U.; Daniel, H.; Hall, W.L.; Weinberg, P.D. Dietary isoflavones in the prevention of cardiovascular disease—A molecular perspective. Food Chem. Toxicol. 2008, 46, 1308–1319. [Google Scholar] [CrossRef]
  22. Güçlü-Ustundağ, Ö.; Mazza, G. Saponins: Properties, applications and processing. Crit. Rev. Food Sci. Nutr. 2007, 47, 231–258. [Google Scholar] [CrossRef] [PubMed]
  23. Kang, J.; Badger, T.; Ronis, M.; Wu, X. Non-isoflavone phytochemicals in soy and their health effects. J. Agric. Food Chem. 2010, 58, 8119–8813. [Google Scholar] [CrossRef] [PubMed]
  24. Høie, L.H.; Morgenstern, E.C.; Gruenwald, J.; Graubaum, H.J.; Busch, R.; Luder, W.; Zunft, H.J. A double-blind placebo- controlled clinical trial compares the cholesterol-lowering effects of two different soy protein preparations in hypercholesterolemic subjects. Eur. J. Nutr. 2005, 44, 65–71. [Google Scholar] [CrossRef] [PubMed]
  25. Schreihofer, D.A.; Deutsch, C.; Lovekamp-Swan, T.; Sullivan, J.C.; Dorrance, A.M. Effect of high soy diet on the cerebrovasculature and endothelial nitric oxide synthase in the ovariectomized rat. Vasc. Pharmacol. 2010, 52, 236–242. [Google Scholar] [CrossRef] [Green Version]
  26. Scimone, C.; Donato, L.; Alibrandi, S.; Esposito, T.; Alafaci, C.; D’Angelo, R.; Sidoti, A. Transcriptome analysis provides new molecular signatures in sporadic Cerebral Cavernous Malformation endothelial cells. Biochim. Biophys. Acta Mol. Basis Dis. 2020, 1866, 165956. [Google Scholar] [CrossRef]
  27. Scimone, C.; Donato, L.; Katsarou, Z.; Bostantjopoulou, S.; D’Angelo, R.; Sidoti, A. Two Novel KRIT1 and CCM2 Mutations in Patients Affected by Cerebral Cavernous Malformations: New Information on CCM2 Penetrance. Front. Neurol. 2018, 9, 953. [Google Scholar] [CrossRef]
  28. Sak, K. Epidemiological Evidences on Dietary Flavonoids and Breast Cancer Risk: A Narrative Review. Asian Pac. J. Cancer Prev. 2017, 18, 2309–2328. [Google Scholar] [CrossRef]
  29. Messina, M. Soyfoods and soybean phyto-estrogens (isoflavones) as possible alternatives to hormone replacement therapy (HRT). Eur. J. Cancer 2000, 36, S71–S72. [Google Scholar] [CrossRef]
  30. Djuric, Z.; Chen, G.; Doerge, D.R.; Heilbrun, L.K.; Kucuk, O. Effect of soy isoflavone supplementation on oxidative stress in men and women. Cancer Lett. 2001, 172, 1–6. [Google Scholar] [CrossRef]
  31. Tuli, H.S.; Tuorkey, M.J.; Thakral, F.; Sak, K.; Kumar, M.; Sharma, A.K.; Sharma, U.; Jain, A.; Aggarwal, V.; Bishayee, A. Molecular Mechanisms of Action of Genistein in Cancer: Recent Advances. Front. Pharmacol. 2019, 10, 1336. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  32. Sahin, I.; Bilir, B.; Ali, S.; Sahin, K.; Kucuk, O. Soy Isoflavones in Integrative Oncology: Increased Efficacy and Decreased Toxicity of Cancer Therapy. Integr. Cancer Ther. 2019, 18, 1–11. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Kuiper, G.G.; Carlsson, B.; Grandien, K.; Enmark, E.; Häggblad, J.; Nilsson, S.; Gustafsson, J.A. Comparison of the ligand binding specificity and transcript tissue distribution of estrogen receptors alpha and beta. Endocrinology 1997, 138, 863–870. [Google Scholar] [CrossRef]
  34. Sivoňová, M.K.; Kaplán, P.; Tatarková, Z.; Lichardusová, L.; Dušenka, R.; Jurečeková, J. Androgen receptor and soy isoflavones in prostate cancer (Review). Mol. Clin. Oncol. 2018, 10, 191–204. [Google Scholar] [CrossRef] [Green Version]
  35. Khan, N.; Adhami, V.M.; Mukhtar, H. Apoptosis by dietary agents for prevention and treatment of prostate cancer. Endocr. Relat. Cancer 2010, 17, 39–52. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  36. Shike, M.; Doane, A.S.; Russo, L.; Cabal, R.; Reis-Filo, J.; Gerald, W.; Cody, H.; Khanin, R.; Bromberg, J.; Norton, L. The Effects of Soy Supplementation on Gene Expression in Breast Cancer: A Randomized Placebo-Controlled Study. J. Natl. Cancer Inst. 2014, 106, dju189. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  37. Messina, M. Impact of Soy Foods on the Development of Breast Cancer and the Prognosis of Breast Cancer Patients. Forsch Komplementmed. 2016, 23, 75–80. [Google Scholar] [CrossRef]
  38. Applegate, C.C.; Rowles, J.L.; Ranard, K.M.; Jeon, S.; Erdman, J.W. Soy Consumption and the Risk of Prostate Cancer: An Updated Systematic Review and Meta-Analysis. Nutrients 2018, 10, 40. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  39. Ali, A.A.; Velasquez, M.T.; Hansen, C.T.; Mohamed, A.I.; Bhathena, S.J. Modulation of carbohydrate metabolism and peptide hormones by soybean isoflavones and probiotics in obesity and diabetes. J. Nutr. Biochem. 2005, 16, 693–699. [Google Scholar] [CrossRef]
  40. van Nielen, M.; Feskens, E.J.; Rietman, A.; Siebelink, E.; Mensink, M. Partly replacing meat protein with soy protein alters insulin resistance and blood lipids in postmenopausal women with abdominal obesity. J. Nutr. 2014, 144, 1423–1429. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  41. Li, W.; Ruan, W.; Peng, Y.; Wang, D. Soy and the risk of type 2 diabetes mellitus: A systematic review and meta-analysis of observational studies. Diabetes Res. Clin. Pract. 2018, 137, 190–199. [Google Scholar] [CrossRef]
  42. Konishi, K.; Wada, K.; Yamakawa, M.; Goto, Y.; Mizuta, F.; Koda, S.; Uji, T.; Tsuji, M.; Nagata, C. Dietary Soy Intake Is Inversely Associated with Risk of Type 2 Diabetes in Japanese Women but Not in Men. J. Nutr. 2019, 149, 1208–1214. [Google Scholar] [CrossRef]
  43. Pubmed. Available online: www.ncbi.nlm.nih.gov/ (accessed on 20 April 2021).
  44. Bédard, K.; Bédard, J.; Rocheleau, G.; Ferland, G.; Gaudreau, P. Aging and Diets Regulate the Rat Anterior Pituitary and Hypothalamic Transcriptome. Neuroendocrinology 2012, 97, 146–159. [Google Scholar] [CrossRef]
  45. Song, S.; Hooiveld, G.J.; Li, M.; Zhao, F.; Zhang, W.; Xu, X.; Müller, M.; Li, C.; Zhou, G. Dietary soy and meat proteins induce distinct physiological and gene expression changes in rats. Sci. Rep. 2016, 6, 20036. [Google Scholar] [CrossRef] [Green Version]
  46. Seclaman, E.; Balacescu, L.; Balacescu, O.; Bejinar, C.; Udrescu, M.; Marian, C.; Sirbu, I.O.; Anghel, A. MicroRNAs mediate liver transcriptome changes upon soy diet intervention in mice. J. Cell. Mol. Med. 2019, 23, 2263–2267. [Google Scholar] [CrossRef] [Green Version]
  47. Guo, X.; Cai, Q.; Bao, P.; Wu, J.; Wen, W.; Ye, F.; Zheng, W.; Zheng, Y.; Shu, X.-O. Long-term soy consumption and tumor tissue MicroRNA and gene expression in triple-negative breast cancer. Cancer 2016, 122, 2544–2551. [Google Scholar] [CrossRef]
  48. Kiron, V.; Park, Y.; Siriyappagouder, P.; Dahle, D.; Vasanth, G.K.; Dias, J.; Fernandes, J.; Sørensen, M.; Trichet, V.V. Intestinal Transcriptome Analysis Reveals Soy Derivative-Linked Changes in Atlantic Salmon. Front. Immunol. 2020, 11, 596514. [Google Scholar] [CrossRef]
  49. Król, E.; Douglas, A.; Tocher, D.R.; Crampton, V.O.; Speakman, J.R.; Secombes, C.J.; Martin, S.A. Differential responses of the gut transcriptome to plant protein diets in farmed Atlantic salmon. BMC Genom. 2016, 17, 156. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  50. Kemski, M.M.; Rappleye, C.A.; Dabrowski, K.; Bruno, R.S.; Wick, M. Transcriptomic response to soybean meal-based diets as the first formulated feed in juvenile yellow perch (Perca flavescens). Sci. Rep. 2020, 10, 3998. [Google Scholar] [CrossRef] [Green Version]
  51. Valenzuela, L.; Pacheco, S.; Rincón, G.; Pavez, L.; Lam, N.; Hernández, A.; Dantagnan, P.; González, F.; Jilberto, F.; Ravanal, M.; et al. Intestinal Transcriptome Analysis Reveals Enrichment of Genes Associated with Immune and Lipid Mechanisms, Favoring Soybean Meal Tolerance in High-Growth Zebrafish (Danio Rerio). Genes (Basel) 2021, 12, 700. [Google Scholar] [CrossRef]
  52. Osada, J. The Use of Transcriptomics to Unveil the Role of Nutrients in Mammalian Liver. ISRN Nutr. 2013, 2013, 403792. [Google Scholar] [CrossRef] [Green Version]
  53. Piironen, V.; Lampi, A. Occurrence and Levels of Phytosterols in Foods. In Phytosterols as Functional Foods Components and Nutraceuticals; Dutta, P., Ed.; CRC Press: Boca Raton, FL, USA, 2004; pp. 1–32. ISBN 9780824747503. [Google Scholar]
  54. Omoni, A.O.; Aluko, R.E. Soybean Foods and Their Benefits: Potential Mechanisms of Action. Nutr. Rev. 2005, 63, 272–283. [Google Scholar] [CrossRef]
  55. Corbett, J.W.; Harwood, J.H. Inhibitors of mammalian acetyl-CoA carboxylase. Recent Pat. Cardiovasc. Drug Discov. 2007, 2, 162–180. [Google Scholar] [CrossRef]
  56. Soni, K.G.; Lehner, R.; Metalnikov, P.; O’Donnell, P.; Semache, M.; Gao, W.; Ashman, K.; Pshezhetsky, A.V.; Mitchell, G.A. Carboxylesterase 3 (EC 3.1.1.1) is a major adipocyte lipase. J. Biol. Chem. 2004, 279, 40683–40689. [Google Scholar] [CrossRef] [Green Version]
  57. Matsumoto, T.; Emi, Y.; Kawabata, S.-I.; Omura, T. Purification and Characterization of Three Male-Specific and One Female-Specific Forms of Cytochrome P-450 from Rat Liver Microsomes. J. Biochem. 1986, 100, 1359–1371. [Google Scholar] [CrossRef]
  58. Tilly-Kiesi, M.; Schaefer, E.J.; Knudsen, P.; Welty, F.K.; Dolnikowski, G.G.; Taskinen, M.R.; Lichtenstein, A.H. Lipoprotein me-tabolism in subjects with hepatic lipase deficiency. Metabolism 2004, 53, 520–525. [Google Scholar] [CrossRef]
  59. Karackattu, S.L.; Trigatti, B.; Krieger, M. Hepatic lipase deficiency delays atherosclerosis, myocardial infarction, and cardiac dysfunction and extends lifespan in SR-BI/apolipoprotein E double knockout mice. Arterioscler. Thromb. Vasc. Biol. 2006, 26, 548–554. [Google Scholar] [CrossRef] [Green Version]
  60. Lepesheva, G.I.; Waterman, M.R. Sterol 14alpha-demethylase cytochrome P450 (CYP51), a P450 in all biological kingdoms. Biochim. Biophys. Acta (BBA)—Gen. Subj. 2007, 1770, 467–477. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  61. Zhu, T.; Corraze, G.; Plagnes-Juan, E.; Skiba-Cassy, S. Cholesterol metabolism regulation mediated by SREBP-2, LXRα and miR-33a in rainbow trout (Oncorhynchus mykiss) both in vivo and in vitro. PLoS ONE 2020, 15, e0223813. [Google Scholar] [CrossRef] [PubMed]
  62. Hubacek, J.A.; Bobkova, D. Role of Cholesterol 7alpha-Hydroxylase (CYP7A1) in Nutrigenetics and Pharmacogenetics of Cholesterol Lowering. Mol. Diagn. Ther. 2006, 10, 93–100. [Google Scholar] [CrossRef] [PubMed]
  63. Cohen, J.C.; Cali, J.J.; Jelinek, D.F.; Mehrabian, M.; Sparkes, R.S.; Lusis, A.J.; Russell, D.W.; Hobbs, H.H. Cloning of the human cholesterol 7alpha-hydroxylase gene (CYP7) and localization to chromosome 8q11–q. Genomics 1992, 14, 153–161. [Google Scholar] [CrossRef]
  64. Li, H.; Huang, W.; Wang, M.; Chen, P.; Chen, L.; Zhang, X. Tandem Mass Tag-based quantitative proteomics analysis of metabolic associated fatty liver disease induced by high fat diet in mice. Nutr. Metab. (Lond.) 2020, 17, 97. [Google Scholar] [CrossRef]
  65. Berthiaume, L.; Deichaite, I.; Peseckis, S.; Resh, M.D. Regulation of enzymatic activity by active site fatty acylation. A new role for long chain fatty acid acylation of proteins. J. Biol. Chem. 1994, 269, 6498–6505. [Google Scholar] [CrossRef]
  66. He, Z.; Zhang, R.; Jiang, F.; Zhang, H.; Zhao, A.; Xu, B.; Jin, L.; Wang, T.; Jia, W.; Jia, W.; et al. FADS1-FADS2 genetic polymorphisms are associated with fatty acid metabolism through changes in DNA methylation and gene expression. Clin. Epigenet. 2018, 10, 113. [Google Scholar] [CrossRef] [PubMed]
  67. Oey, N.A.; den Boer, M.E.; Wijburg, F.A.; Vekemans, M.; Augé, J.; Steiner, C.; Wanders, R.J.A.; Waterham, H.R.; Ruiter, J.P.; Attié-Bitach, T. Long-Chain Fatty Acid Oxidation during Early Human Development. Pediatr. Res. 2005, 57, 755–759. [Google Scholar] [CrossRef] [Green Version]
  68. Torres, N.; Torre-Villalvazo, I.; Tovar, A.R. Regulation of lipid metabolism by soy protein and its implication in diseases me-diated by lipid disorders. J. Nutr. Biochem. 2006, 17, 365–373. [Google Scholar] [CrossRef]
  69. Takahashi, Y.; Ide, T. Effects of soy protein and isoflavone on hepatic fatty acid synthesis and oxidation and mRNA expression of uncoupling proteins and peroxisome proliferator-activated receptor gamma in adipose tissues of rats. J. Nutr. Biochem. 2008, 19, 682–693. [Google Scholar] [CrossRef]
  70. Santos e Silva, L.; Cavalcanti, J.V.F.L.; Magalhães, A.L.R.; Santoro, K.R.; Gonçalves, G.D.; Vasconcelos Santana, L.P.; Barbosa da Silva, J.K.; Calvacanti de Almeida, O. Soybean oil modulates the fatty acid synthesis in the mammary gland, improving nutritional quality of the goat milk. Small Rumin. Res. 2020, 183, 106041. [Google Scholar] [CrossRef]
  71. Zhang, Y.; Klaassen, C.D. Hormonal regulation of Cyp4a isoforms in mouse liver and kidney. Xenobiotica 2013, 43, 1055–1063. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  72. Jones, M.R.; Italiano, L.; Wilson, S.G.; Mullin, B.H.; Mead, R.; Dudbridge, F.; Watts, G.F.; Stuckey, B.G. Polymorphism in HSD17B6 is associated with key features of polycystic ovary syndrome. Fertil. Steril. 2006, 86, 1438–1446. [Google Scholar] [CrossRef] [PubMed]
  73. Strauss, J.F.; Barbieri, R.L. Yen and Jaffe’s Reproductive Endocrinology; Elsevier Health Sciences: Philadelphia, PA, USA, 2013; p. 82. [Google Scholar]
  74. Russo, I.H.; Russo, J. Role of Hormones in Mammary Cancer Initiation and Progression. J. Mammary Gland. Biol. Neoplasia 1998, 3, 49–61. [Google Scholar] [CrossRef]
  75. Wang, X.; Gérard, C.; Thériault, J.-F.; Poirier, D.; Doillon, C.J.; Lin, S.-X. Synergistic control of sex hormones by 17β-HSD type 7: A novel target for estrogen-dependent breast cancer. J. Mol. Cell Biol. 2015, 7, 568–579. [Google Scholar] [CrossRef] [Green Version]
  76. Seppen, J. A diet containing the soy phytoestrogen genistein causes infertility in female rats partially deficient in UDP glucuronyltransferase. Toxicol. Appl. Pharmacol. 2015, 264, 335–342. [Google Scholar] [CrossRef] [PubMed]
  77. D’Ambrosio, D.N.; Clugston, R.D.; Blaner, W.S. Vitamin A Metabolism: An Update. Nutrients 2011, 3, 63–103. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  78. Standeven, A.M.; Beard, R.L.; Johnson, A.T.; Boehm, M.F.; Escobar, M.; Heyman, R.A.; Chandraratna, R.A. Retinoid-induced hypertriglyceridemia in rats is mediated by retinoic acid receptors. Fundam. Appl. Toxicol. 1996, 33, 264–271. [Google Scholar] [CrossRef]
  79. Radcliffe, J.D.; Czajka-Narins, D.M. Partial replacement of dietary casein with soy protein isolate can reduce the severity of retinoid-induced hypertriglyceridemia. Plant Foods Hum. Nutr. 1998, 52, 97–108. [Google Scholar] [CrossRef]
  80. Schupp, M.; Lefterova, M.I.; Janke, J.; Leitner, K.; Cristancho, A.G.; Mullican, S.E.; Qatanani, M.; Szwergold, N.; Steger, D.J.; Curtin, J.C. Retinol saturase promotes adipogenesis and is downregulated in obesity. Proc. Natl. Acad. Sci. USA 2009, 106, 1105–1110, corrected in Proc. Natl. Acad. Sci. USA 2009, 106, 4571. [Google Scholar] [CrossRef] [Green Version]
  81. Hodges, R.E.; Minich, D.M. Modulation of Metabolic Detoxification Pathways Using Foods and Food- Derived Components: A Scientific Review with Clinical Application. J. Nutr. Metabol. 2015, 2015, 760689. [Google Scholar] [CrossRef]
  82. Senafi, S.B.; Clarke, D.J.; Burchell, B. Investigation of the substrate specificity of a cloned expressed human bilirubin UDP- glu-ronosyltransferase: UDP-sugar specificity and involvement in steroid and xenobiotic glucuronidation. Biochem J. 1994, 303, 233–240. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  83. Allain, E.P.; Rouleau, M.; Lévesque, E.; Guillemette, C. Emerging roles for UDP-glucuronosyltransferases in drug resistance and cancer progression. Br. J. Cancer 2020, 122, 1277–1287. [Google Scholar] [CrossRef] [Green Version]
  84. Fay, M.J.; Nguyen, M.T.; Snouwaert, J.N.; Dye, R.; Grant, D.J.; Bodnar, W.M.; Koller, B.H. Xenobiotic Metabolism in Mice Lacking the UDP-Glucuronosyltransferase 2 Family. Drug Metab. Dispos. 2015, 43, 1838–1846. [Google Scholar] [CrossRef] [Green Version]
  85. Wang, Y.; Huang, H.; Wu, Q. Characterization of the Zebrafish Ugt Repertoire Reveals a New Class of Drug-Metabolizing UDP Glucuronosyltransferases. Mol. Pharmacol. 2014, 86, 62–75. [Google Scholar] [CrossRef]
  86. Li, D.; Li, Y. The interaction between ferroptosis and lipid metabolism in cancer. Signal Transduct. Target. Ther. 2020, 5, 108. [Google Scholar] [CrossRef]
  87. Magtanong, L.; Ko, P.-J.; To, M.; Cao, J.Y.; Forcina, G.C.; Tarangelo, A.; Ward, C.C.; Cho, K.; Patti, G.J.; Nomura, D.K.; et al. Exogenous Monounsaturated Fatty Acids Promote a Ferroptosis-Resistant Cell State. Cell Chem. Biol. 2019, 26, 420–432.e9. [Google Scholar] [CrossRef] [PubMed]
  88. Xie, Y.; Hou, W.; Song, X.; Yu, Y.; Huang, J.; Sun, X.; Kang, R.; Tang, D. Ferroptosis: Process and function. Cell Death Differ. 2016, 23, 369–379. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  89. Koppula, P.; Zhuang, L.; Gan, B. Cystine transporter SLC7A11/xCT in cancer: Ferroptosis, nutrient dependency, and cancer therapy. Protein Cell 2020, 12, 599–620. [Google Scholar] [CrossRef] [PubMed]
  90. Sullivan, J. Iron and the sex difference in heart disease risk. Lancet 1981, 317, 1293–1294. [Google Scholar] [CrossRef]
  91. Liu, F.; Di Wang, X. miR-150-5p represses TP53 tumor suppressor gene to promote proliferation of colon adenocarcinoma. Sci. Rep. 2019, 9, 6740. [Google Scholar] [CrossRef]
  92. Li, T.; Xie, J.; Shen, C.; Cheng, D.; Shi, Y.; Wu, Z.; Zhan, Q.; Deng, X.; Chen, H.; Shen, B.; et al. miR-150-5p Inhibits Hepatoma Cell Migration and Invasion by Targeting MMP. PLoS ONE 2014, 9, e115577. [Google Scholar] [CrossRef] [Green Version]
  93. Li, S.; Brown, M.S.; Goldstein, J.L. Bifurcation of insulin signaling pathway in rat liver: mTORC1 required for stimulation of lipogenesis, but not inhibition of gluconeogenesis. Proc. Natl. Acad. Sci. USA 2010, 107, 3441–3446. [Google Scholar] [CrossRef] [Green Version]
  94. Kumar, A.; Lawrence, J.C., Jr.; Jung, D.Y.; Ko, H.J.; Keller, S.R.; Kim, J.K.; Magnuson, M.A.; Harris, T.E. Fat Cell-Specific Ablation of Rictor in Mice Impairs Insulin-Regulated Fat Cell and Whole-Body Glucose and Lipid Metabolism. Diabetes 2010, 59, 1397–1406. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  95. Chango, A.; Pogribny, I.P. Considering Maternal Dietary Modulators for Epigenetic Regulation and Programming of the Fetal Epigenome. Nutrients 2015, 7, 2748–2770. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  96. Dolinoy, D.C.; Weidman, J.R.; Waterland, R.A.; Jirtle, R.L. Maternal genistein alters coat color and protects Avy mouse offspring from obesity by modifying the fetal epigenome. Environ. Health Perspect. 2006, 114, 567–572. [Google Scholar] [CrossRef] [Green Version]
  97. Howard, T.D.; Ho, S.-M.; Zhang, L.; Chen, J.; Cui, W.; Slager, R.; Gray, S.; Hawkins, G.A.; Medvedovic, M.; Wagner, J.D. Epigenetic Changes with Dietary Soy in Cynomolgus Monkeys. PLoS ONE 2011, 6, e26791. [Google Scholar] [CrossRef] [Green Version]
  98. Wagner, J.D.; Jorgensen, M.J.; Cline, J.M.; Lees, C.J.; Franke, A.A.; Zhang, L.; Ayers, M.R.; Schultz, C.; Kaplan, J.R. Effects of soy vs. casein protein on body weight and glycemic control in female monkeys and their offspring. Am. J. Primatol. 2009, 71, 802–811. [Google Scholar] [CrossRef]
  99. Paço, A.; de Bessa Garcia, S.A.; Freitas, R. Methylation in HOX Clusters and Its Applications in Cancer Therapy. Cells 2020, 9, 1613. [Google Scholar] [CrossRef] [PubMed]
Applsci 11 07905 g001 550
Figure 1. Flowchart displaying the process of our systematic review study.
Figure 1. Flowchart displaying the process of our systematic review study.
Applsci 11 07905 g001
Applsci 11 07905 g002 550
Figure 2. Venn diagram showing common KEGG pathways between mammals and fish (Method 1: blue circle; Method 2: red circle).
Figure 2. Venn diagram showing common KEGG pathways between mammals and fish (Method 1: blue circle; Method 2: red circle).
Applsci 11 07905 g002
Table
Table 1. Experimental conditions of studies reporting transcriptomic changes upon soy ingestion.
Table 1. Experimental conditions of studies reporting transcriptomic changes upon soy ingestion.
SpeciesSoy DietDuration of FeedingTissueAnalytical PlatformRef.
Male rats
(Rattus norvegicus)		Regular chow diet containing 20% soybean meal18 monthsAnterior pituitary
and hypothalamus		Microarray[44]
Male rats
(Rattus norvegicus)		Regular chow containing 20% soy protein + 7% soybean oil7 daysLiverRNA-seq[45]
Male mice
(Mus musculus)		Regular chow containing 25% soybean meal28 daysLiverRNA-seq/Microarray[46]
Human
(Homo sapiens)
breast cancer patients		Different soy foods12 monthsTumor TissueNanoString nCounter[47]
Atlantic salmon
(Salmo salar)		Regular chow containing 20% soy protein + 10% soybean meal + 2% soy saponin36 daysDistal intestineRNA-seq[48]
Atlantic salmon
(Salmo salar)		Regular chow containing 45% soy protein/Regular chow containing 36% soybean meal8 weeksDistal intestineMicroarray[49]
Yellow perch
(Perca flavescens)		Regular chow containing 75% soybean meal61 daysMid intestineRNA-seq[50]
Zebrafish
(Danio Rerio)		Regular chow containing 50% soybean meal + 2% soy saponin53 daysIntestineRNA-seq[51]
Table
Table 2. STRING analysis of individual datasets (Method 1).
Table 2. STRING analysis of individual datasets (Method 1).
Common Pathways for
Downregulated Genes		Common Pathways for
Upregulated Genes		Common Pathways in Fish vs. Mammals (Up and Down DEGs)
Drug metabolism-other enzymesBiosynthesis of unsaturated fatty acidsPPAR signaling pathway
PeroxisomePhagosomeSteroid biosynthesis
Retinol metabolismProteasomeDrug metabolism-other enzymes
Biosynthesis of amino acidsMetabolic pathwaysArginine and proline metabolism
Metabolism of xenobiotics by cytochrome P450 Peroxisome
Drug metabolism-cytochrome P450 Metabolic pathways
PPAR signaling pathway Biosynthesis of unsaturated fatty acids
ABC transporters Retinol metabolism
Arginine biosynthesis Metabolism of xenobiotics by cytochrome P450
Metabolic pathways Fatty acid elongation
Steroid hormone biosynthesis Pentose and glucuronate interconversions
Arginine and proline metabolism Glutathione metabolism
Alanine, aspartate and glutamate metabolism Phagosome
Pentose and glucuronate interconversions Apoptosis
Glutathione metabolism Carbon metabolism
Carbon metabolism Glycine, serine and threonine
metabolism
Ascorbate and aldarate metabolism ABC transporters
Drug metabolism-cytochrome P450
Proteasome
Arginine biosynthesis
Alanine, aspartate and glutamate metabolism
Biosynthesis of amino acids
Table
Table 3. STRING analysis of pooled datasets (Method 2).
Table 3. STRING analysis of pooled datasets (Method 2).
Common Pathways for
Downregulated Genes		Common Pathways for
Upregulated Genes		Common Pathways in Fish vs. Mammals
(Up and Down DEGs)
Drug metabolism-other enzymesBiosynthesis of unsaturated fatty acidsPPAR signaling pathway
PeroxisomeProtein exportSteroid biosynthesis
Retinol metabolismProteasomeDrug metabolism-other enzymes
Biosynthesis of amino acidsMetabolic pathwaysMetabolic pathways
Metabolism of xenobiotics by cytochrome P450 Biosynthesis of unsaturated fatty acids
Drug metabolism-cytochrome P450 Retinol metabolism
PPAR signaling pathway Metabolism of xenobiotics by cytochrome P450
ABC transporters Fatty acid metabolism
Porphyrin and chlorophyll metabolism ABC transporters
Metabolic pathways Drug metabolism-cytochrome P450
Steroid hormone biosynthesisPentose and glucuronate interconversions
Arginine and proline metabolismGlutathione metabolism
Alanine, aspartate and glutamate metabolismPeroxisome
Pentose and glucuronate interconversionsGlycine, serine and threonine metabolism
Glutathione metabolismProteasome
Carbon metabolismAlanine, aspartate and glutamate metabolism
Ascorbate and aldarate metabolismAscorbate and aldarate metabolism
Glycolysis/GluconeogenesisGlycolysis/Gluconeogenesis
FerroptosisFerroptosis
Protein export
Biosynthesis of amino acids
Porphyrin and chlorophyll metabolism
Arginine and proline metabolism
Table
Table 4. Ambiguously changed KEGG pathways (found both up and downregulated in fish and mammals).
Table 4. Ambiguously changed KEGG pathways (found both up and downregulated in fish and mammals).
Up vs. Down Common Pathways
in Mammals		Up vs. Down Common Pathways
in Fish
Metabolic pathwaysMetabolic pathways
Autophagy-animalProtein processing in endoplasmic reticulum
Hepatocellular carcinomaCarbon metabolism
Citrate cycle (TCA cycle)
Amino sugar and nucleotide sugar metabolism
Fatty acid metabolism
Glyoxylate and dicarboxylate metabolism
Starch and sucrose metabolism
Glycosaminoglycan degradation
PPAR signaling pathway
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Anghel, A.; Sala-Cirtog, M.; Marian, C.; Samoila, C.; Sirbu, I.O. Dietary Soy Impact on Host Transcriptome Profile—A Review. Appl. Sci. 2021, 11, 7905. https://doi.org/10.3390/app11177905

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Anghel A, Sala-Cirtog M, Marian C, Samoila C, Sirbu IO. Dietary Soy Impact on Host Transcriptome Profile—A Review. Applied Sciences. 2021; 11(17):7905. https://doi.org/10.3390/app11177905

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Anghel, Andrei, Maria Sala-Cirtog, Catalin Marian, Corina Samoila, and Ioan Ovidiu Sirbu. 2021. "Dietary Soy Impact on Host Transcriptome Profile—A Review" Applied Sciences 11, no. 17: 7905. https://doi.org/10.3390/app11177905

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