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MicroRNAs in Metabolic Syndrome

  • Juan Francisco Codocedo
  • Nibaldo C. InestrosaEmail author
Reference work entry
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Abstract

Metabolic syndrome (MetS) corresponds to a cluster of several risk factors that increase the risk of other health problems, such as cardiovascular disease and diabetes. The combinatorial nature of MetS makes its etiology complex as it is determined by the interplay of both genetic and environmental factors like nutrition or physical activity. Accordingly, intricate regulatory networks have evolved to respond to changes in environmental conditions and physiological stress. In the search for key molecular pathways that could elucidate the complex physiopathology of MetS, as well as serve as therapeutic tools, microRNAs (miRNAs) have emerged as attractive molecules, given their role as important components of complex gene regulatory networks. MiRNAs typically control the expression of their target genes by imperfect base pairing to the 3′ untranslated regions (3′UTR) of their messenger RNAs (mRNAs) targets. Currently, several aspects of the miRNA biogenic process are known in detail, as well as the translational repression mechanisms exerted by miRNAs on their target mRNAs. The number of studies associating miRNAs with the metabolic risk factors of MetS is increasing; however, few studies directly relate miRNAs to a well-defined model of MetS. There is no doubt that miRNAs play an important role in the development of individual components of MetS; however, our understanding of their function during the different combinatorial modalities of MetS is poor. In this chapter, we review several of the studies investigating the relationship between miRNA dysfunction and MetS. We discuss the role of nutrition and genetic in the modulation of miRNAs activities and how our dietary behavior can have profound consequences in the metabolic health of our progeny.

Keywords

Metabolic syndrome High-fat diet Maternal obesity Paternal obesity Diabetes Nutrition Metabolism MicroRNAs Epigenetics Transgenerational inheritance Genetic burden 

List of Abbreviations

3′UTR

3′ untranslated region

HFD

High-fat diet

messenger RNAs

mRNAs

MetS

Metabolic syndrome

miRISC

miRNA-induced silencing complex

miRNAs

microRNAs

MRE

miRNA recognition element

NAFLD

Nonalcoholic fatty liver disease

SNPs

Single nucleotide polymorphisms

T2DM

Type-2 diabetes mellitus

Introduction

Metabolic syndrome (MetS), also known as “plurimetabolic syndrome,” “syndrome X,” “deadly quartet,” “insulin resistance syndrome,” and “dysmetabolic syndrome,” corresponds to a cluster of risk factors that increases the risk of other health problems, such as cardiovascular disease and diabetes. The variety of names that the syndrome has been given throughout its history is a reflection of the difficulties that physicians and scientists have had in agreeing on a unique definition, diagnosis and treatment. Currently, individuals with three out of five metabolic conditions – abdominal obesity, hypertriglyceridemia, low levels of high-density lipoprotein (HDL), hypertension, and impaired fasting glucose – are diagnosed with MetS, and their chances of suffering a stroke or developing diabetes are significantly higher than those if only one of these risk factors is present (Alberti et al. 2009; Grundy et al. 2005). Additionally, several other metabolic disorders, such as liver fat accumulation, have been associated with MetS (Boyraz et al. 2014). The combinatorial nature of the syndrome makes its etiology complex as it is determined by the interplay of both genetic and environmental factors (Miyamoto et al. 2009; Ye et al. 2013).

In the search for key molecular pathways that could elucidate the complex physiopathology of MetS, as well as serve as therapeutic tools, microRNAs (miRNAs) have emerged as attractive molecules, given their role as important components of complex gene regulatory networks (Yousef et al. 2014). miRNAs are small endogenous noncoding RNAs; in their mature form (approximately 22 nt), they are loaded onto a protein complex called the miRNA-induced silencing complex (miRISC) and direct the sequence-specific binding of the complex to target messenger RNAs (mRNAs), repressing their translation (Bartel 2009). Because the miRNA–mRNA binding site is very short (8–14 nt), each miRNA has the potential to regulate many target genes, and one gene may be targeted by several miRNAs (Bartel 2009). Additionally, miRNAs have different functional modalities that provide another layer of complexity to the miRNA-mediated effects (Codocedo et al. 2016). For example, the short recognition elements (miRNA recognition element, MRE) may occur in many transcripts that participate in the same pathway, indicating that a single miRNA could affect a whole pathway. Several reports have shown that a change in a single miRNA-target interaction can simultaneously affect multiple other miRNA-target interactions and modify physiological phenotypes (Hanin et al. 2014). Furthermore, the biogenesis of miRNAs is a complex multistep process that is modulated by several environmental factors, including nutrition, to generate homeostatic responses (Codocedo and Inestrosa 2016). The complex biology of miRNAs is hence compatible with a key role in metabolic functions. Thus, analysis of their deregulation in MetS patients and animal models could help to develop better therapeutic strategies to improve the quality of life of the increasing population of MetS patients.

The number of studies associating miRNAs with the metabolic risk factors of MetS is increasing; however, few studies directly relate miRNAs to a well-defined model of MetS. In this chapter, we review several of the studies investigating the relationship between miRNA dysfunction and MetS. We consider evidence that describes the role of the environment in the form of nutrition, as well as the genetic component in the form of mutation in metabolic miRNAs as well as their targets. Finally, we discuss the interaction between both components and their consequences in the offspring of progenitors affected by MetS, in a mechanism that could explain the epidemic increase in obesity, diabetes, and MetS.

Nutritional Modulation of miRNAs and Their Role in MetS

Dietary components affect the activity of endogenous miRNAs through different mechanisms, including modulation of critical enzymes of the miRNA biogenetic pathway or modulation of components of the miRISC (Fig. 1). Numerous studies have demonstrated the role of dietary components in miRNA modulation and their consequences in the development of metabolic syndrome (Rottiers and Näär 2012), cancer (Li et al. 2010; Parasramka et al. 2012), neurodegenerative (Codocedo et al. 2016), and anxiety disorders (Meydan et al. 2016) (Fig 1). These effects depend on the different properties of the dietary components, including their bioavailability, distribution to different organs and the effective concentration attained by nutritional uptake. Additionally, the cellular context constitutes another layer of complexity as the expression profile of miRNAs is different between organs, and tissue-specific miRNAs (e.g., MyomiR in muscle) are expressed. For example, a high-fat diet (HFD) induce changes in a specific group of liver miRNAs that are involved in the regulation of lipid metabolism and participate in the induction of various liver diseases, including nonalcoholic fatty liver disease (NAFLD) (Tessitore et al. 2016). At the same time, nutritional manipulation induces changes in a muscle-specific group of miRNAs (MyomiRs) that participate in the induction of insulin resistance and decreased myogenesis (Frias et al. 2016). Several other nutritional interventions have been related to changes in miRNA levels and their possible role in the development of metabolic risk factors by affecting specific biological processes in different tissues, including liver, muscle, adipose tissues, pancreas, and brain.
Fig. 1

Nutritional modulation of miRNAs and their role in MetS. The miRNA biogenesis pathway produces pri-miRNA transcripts by RNA polymerase II (Pol II) from miRNA genes. Next, the Drosha microprocessor complex processes pri-miRNA transcripts into pre-miRNAs. Pre-miRNAs are exported from the nucleus via Exportin 5 and subsequently cleaved by Dicer, and the miRNA/miRNA* duplex is unwound via Argonaute (AGO) and loaded in a TRBP-dependent manner into the miRNA-induced silencing complex (miRISC). The binding of target mRNAs to miRNAs in RISC is followed by the inhibition of translation and/or mRNA degradation. The miRNA biogenesis pathway may be subject to regulation at different levels to control the function of miRNAs and thus gene expression. In the figure, we show examples of nutritional factors related to MetS that regulate the expression of endogenous miRNAs through different mechanisms, including modulation of critical enzymes of the miRNA biogenetic pathway or modulation of components of the miRISC (see main text for more details). Different studies have suggested that these interactions have important consequences in the development of metabolic syndrome, cancer, neurodegenerative and anxiety disorders (Modified from Codocedo et al. 2016)

The mechanism by which diet regulates miRNA expression and, in consequence, contributes to the genesis of metabolic conditions is not fully understood. In both animal models and patients with MetS, altered expression levels of different miRNAs have been observed as a consequence of changes at different stages of biogenetic processes, including transcription, processing, and miRISC function. One of the best-studied transcription factors that regulate miRNA expression is the p53 tumor suppressor protein, which regulates the expression of stress-response genes, including the miR-34 family. Interestingly, the p53/miR-34 axis has been shown to be upregulated in islets of diabetic db/db mice and the beta-cell line MIN6B1. Treatment with fatty acids, such as palmitate, which is a predisposing factor for T2DM, also upregulates p53/miR-34 in the pancreatic islets of diabetic mice (Lovis et al. 2008). p53 has also been shown to participate in other clusters of MetS-related conditions, such as nonalcoholic fatty liver disease (NAFLD) (Castro et al. 2013). Additionally, p53 not only regulates miRNAs at the transcriptional level but also regulates the processing/maturation of additional miRNAs, including miR-16-1, miR-143, and miR-145. p53 was shown to interact with the DEAD-box RNA helicase p68 (also known as DDX5) and enhance its interaction with the DROSHA complex, thereby promoting miRNA maturation (Suzuki et al. 2009). This mechanism of p53 was described in the context of cancer development; however, its role in the induction of MetS has not yet been studied. Interestingly, several reports have shown that either lack of nutrients and excessive or deregulated signaling through the nutrient-sensing pathways can activate a p53 response (Hanin et al. 2014; Lee et al. 2007, 2009; Okoshi et al. 2008). Other studies have demonstrated that increased glucose metabolism stimulated by the expression of the glucose transporter GLUT1 or hexokinase also suppressed p53 activity (Zhao et al. 2008).

More recently, how nutritional factors induce changes in miRNAs through epigenetic DNA modifications and their role in the development of metabolic risk factors have been investigated (Yan et al. 2016). One of the major epigenetic mechanisms is DNA methylation, which is important in insulin sensitivity (Ma et al. 2013), obesity (Ali et al. 2016; Kühnen et al. 2016), and cardiovascular diseases (Rask-Andersen et al. 2016). DNA methylation leads to a decrease in gene transcription by inhibiting the binding of transcription factors to gene promoters (Kirchner et al. 2013; Nguyen et al. 2001). Recently, a reduction in miR-9 levels was found in the livers of HFD mice and ob/ob mice. Interestingly, this report described a concomitant increase in DNA methylation at the miR-9 promoter, which could be due to enhanced accumulation of DNA methyltransferase 1 (DNMT1) at the miR-9-3 promoter (Yan et al. 2016). miR-9 has been associated with the development of T2DM based on evidence showing that miR-9 plays an important role in the regulation of in vitro and in vivo insulin secretion via regulation of targets such as SIRT1 (Ramachandran et al. 2011) or Onecut-2 (Oc2) (Plaisance et al. 2006). The identification of new targets of miR-9, such as FOXO1, in the livers of obese mice has uncovered new biological roles associated with T2DM, including gluconeogenesis and insulin resistance (Yan et al. 2016). Despite the important advances made in this field, several questions are still unsolved. For example, it is not clear which signaling pathways the cells use to integrate specific nutritional manipulations and induce changes in miRNA expression that contribute to the development of MetS. Additionally, most of the preclinical studies did not determine whether the animals developed comorbidities suggestive of MetS at the end of the feeding protocol. Moreover, in several studies, the miRNA evaluation was performed when the animals reached a final metabolic state, such as T2DM, NAFLD, or a cardiac condition. As MetS is considered an early stage in the metabolic deterioration (i.e., prediabetic), the altered miRNAs observed in these animals have to be evaluated with caution because they could represent changes related to the advanced stage of MetS or not be related at all.

Genetics of miRNAs and Their Role in MetS

The genetic component of MetS has been examined in population studies that showed differing prevalence rates between the sexes and among ethnic groups (Sale et al. 2006; Terán-García and Bouchard 2007). These findings are supported by twin studies and an increased incidence of the MetS in individuals with a parental history of MetS (Pietiläinen et al. 2006). In mouse models, the genetic components are also evidenced by the effect of HFD on different strains. For example, B6J mice develop rapid and reproducible features of the MetS (including adipose tissue inflammation, hepatosteatosis, insulin resistance, and hyperglycemia) when exposed to a HFD (Kluth et al. 2014). In contrast, 129/Sv mice are resistant to diet-induced obesity and the development of MetS (Almind and Kahn 2004; Bezy et al. 2011; Kokkotou et al. 2005; Lin et al. 2013; Mori et al. 2010). Genome-wide analysis has identified mutations in several genes that correlate with metabolic alterations of MetS, including protein kinase C-δ (PKCδ) (Bezy et al. 2011), the solute carrier family 2 of the facilitated glucose transporter (GLUT2) (Le et al. 2013), and the catalytic α polypeptide of phosphoinositide 3-kinase (PIK3CA) (Barroso et al. 2003), which are all known to influence glucose-insulin homeostasis. Although several studies have suggested that DNA polymorphisms occurring within or close to miRNA or miRNA-binding sites may contribute to human diseases (Brendle et al. 2008; Kim et al. 2016; Zhang et al. 2016), few genetic studies have investigated miRNAs in relation to MetS. Mutations within the miRNA genes could potentially affect the processing or target selection of miRNAs by different means, including their transcription; pri-miRNA and pre-miRNA processing; and via miRNA–mRNA interactions (Ryan et al. 2010). These polymorphisms may be located in pri-miRNAs, pre-miRNAs, mature miRNA, or regulatory regions of miRNAs (Gong et al. 2014). For example, miR-124a, which plays an important role in pancreatic islet development and the regulation of insulin secretion, showed increased expression in T2DM human pancreatic islets, resulting in impaired glucose-stimulated insulin secretion (Sebastiani et al. 2015). In a case-control study of the association between genetic variations in candidate miRNA genes and T2DM susceptibility in Italians, Ciccacci et al. sequenced 13 miRNAs and found that rs531564 in pri-miR-124a was significantly associated with T2DM susceptibility (Ciccacci et al. 2013). The same association was described in a Han Chinese population with T2DM, which is important considering the significant genetic differences between Caucasian and Asian populations (Li et al. 2015). Bioinformatics prediction showed that the G variant allele of rs531564 in miR-124a can change the stability of the pri-miRNA by altering the formation of a ring-shaped structure in their predicted secondary structure, increasing the efficiency of processing into the mature form (Qi et al. 2012). Thus, the increased miR-124a expression caused by the G allele could alter insulin secretion and enhance the susceptibility to the development of T2DM and MetS. However, the occurrence of single nucleotide polymorphisms (SNPs) in miRNA genes is low. Approximately, 10% of human pre-miRNAs have documented SNPs, and fewer than 1% of miRNAs have SNPs in the functional seed region (Saunders et al. 2007), which corresponds to the sequence that recognizes the miRNA binding site in the 3′UTR of the mRNA target. Genetic polymorphisms that reside in the 3′ untranslated region (UTR) of miRNA target genes, which can eliminate an existing binding site, create an erroneous binding site or affect binding affinity (Fig 2), are more frequently observed. For example, the ACAA-insertion/deletion (144/140 bp) polymorphism in the 3′UTR of insulin-like growth factor II receptor gene (IGF2R) was associated with T2DM and insulin-resistant traits (Villuendas et al. 2006). Bioinformatics prediction showed that this polymorphism is located within the hsa-miR-657 and hsa-miR-453 binding sites, and luciferase reporter assays revealed that the polymorphism affected the binding affinity and the transcriptional repression mediated by hsa-miR-657. These results indicated that the ACAA-insertion/deletion polymorphism may change IGF2R expression levels at least in part by hsa-miR-657-mediated regulation, contributing to the elucidation of T2DM pathogenesis (Lv et al. 2008) More recently, eight SNPs, located in seven genes linked to MetS, were selected and genotyped in a Han Chinese population with MetS. Three SNPs were found to have a statistically significant effect on MetS risk and were located in the Apolipoprotein L6 (APOL6) gene and fatty acid binding protein 2 (FABP2) gene (Ye et al. 2013). These SNPs were located in the miRNA binding site of miR-143, miR-24, and miR-132, which have important roles in insulin resistance and differentiation, proliferation and growth of adipocytes (Esau et al. 2004; Kang et al. 2013; Klöting et al. 2009). The results demonstrated that different individuals and populations possess a genetic burden, including mutations in miRNA genes, that made them either resistant or vulnerable to the development of MetS. Genetic profiling could help to develop proper diets and therapies for individuals with these predispositions.
Fig. 2

Functional consequences of genetic polymorphisms within the 3′UTR of miRNA target gene. Genetic polymorphisms within the 3′UTR of miRNA target gene can change the normal regulation mediated by their regulatory miRNA. (a) In normal conditions, a putative miRISC X is able to repress the translation of their mRNA target through the base pairing directed by a specific miRNA. (b) Some mutations can weaken this interaction or (c) completely destroy the miRNA recognition element, increasing the translation of the protein. (d) In other rarer examples, a genetic polymorphism within the 3′UTR of miRNA target gene can destroy the original MRE for a putative miRISC X and create an erroneous binding site for a different miRNA (miRISC Y). A(n), poly A tail

Parental Inheritance of MetS and the Role of miRNAs

Thus far, we have discussed the role of the environment and genetics in the modulation of miRNAs related to MetS. However, the causes of common diseases, such as the metabolic risk factors that compose MetS, are normally more complex than the independent contribution of these factors. They often involve both susceptibility genes and their interactions with the environment. The interactions between the environment and genes are mediated by epigenetic changes of the genome, and epigenetic modifications of the genome are the response to environmental challenges (Jaenisch and Bird 2003). In this sense, epigenetic mechanisms may exacerbate the epidemic of metabolic disease by first contributing to the development of MetS risk factors, such as obesity and T2DM, and then passing modifications on to the subsequent generation via intergenerational effects and/or transgenerational inheritance (Kirchner et al. 2013) (Fig. 3). Maternal consumption of a HFD during pregnancy and lactation is closely related to metabolic changes, such as hepatic lipid accumulation, insulin resistance, and increased serum cytokine levels, in offspring that persist to adulthood. This is mediated in part by deleterious effects on fetal programming, predisposing offspring to adverse outcomes, including cardiometabolic and neurodevelopmental diseases (Neri and Edlow 2016). The underlying mechanism by which the in utero environment shapes the organism is through epigenetic modifications, which involve DNA methylation; posttranslational histone modifications; and changes in miRNA levels. For example, in a mouse model of maternal HFD exposure, miRNA analysis in pup livers showed reduced expression of miR-122 and miR-370. Interestingly, miR-370 targets the 3′UTR of carnitine palmitoyl transferase 1α (Cpt1α), decreasing the rate of β oxidation (Benatti et al. 2014). Similar observations have been made of MyomiRs involved in intramuscular adipogenesis in fetuses of obese sheep (Yan et al. 2013), fetal hearts of obese baboon’s progeny (Maloyan et al. 2013), and several other tissues. However, it is difficult to separate maternal effects on germ cells from the direct effects of in utero exposure on offspring. Considering that fathers contribute little more than sperm to offspring, the study of environmentally induced paternal germline epigenetic effects is currently expanding and may provide an explanation for the transgenerational influence of father’s experiences on offspring development (Curley et al. 2011). Recent studies have demonstrated that paternal metabolic health at conception can impact children’s health, with obese fathers more likely to father an obese child. In a cross-sectional study including 256 children and their parents, children who had at least one parent with MetS had higher levels of obesity and insulin resistance than children with parents who did not have MetS (Pankow et al. 2004). Additional studies have shown that offspring of parents with early coronary heart disease were consistently overweight beginning in childhood. In adulthood, the offspring with a positive parental history had a higher prevalence of obesity, elevated total cholesterol and LDL-C levels, and hyperglycemia, as well as a higher coexistence of these conditions (Bao et al. 1997). In rodents, diet-induced male obesity with or without diabetes induced a worse metabolic phenotype in their offspring, with glucose intolerance in female offspring due to pancreatic islet dysfunction and white adipose tissue dysfunction or insulin resistance and obesity, with some consequences evident across two generations (Fullston et al. 2013; Lin et al. 2014; Ng et al. 2014). Interestingly, HFD alters the transcriptional profile of the testes and results in differential content of sperm canonical miRNAs in F0 males. Pathway analysis of the predicted targets of the differentially expressed miRNAs in testis and sperm of HFD F0 male mice converged on pathways crucial to male reproductive system development and function, embryo development, and insulin signaling and metabolic disorders (Fullston et al. 2013). Conversely, short-term diet and exercise intervention in diet-induced obese founder male mice improved their metabolic health and prevented insulin resistance and large adipocytes in their female offspring, concomitant with a degree of normalization of sperm miRNA content (McPherson et al. 2015; Palmer et al. 2012). However, these studies did not exclude potential confounding variables, such as molecular factors present in seminal fluid or the maternal reproductive tract at conception (Bromfield et al. 2014), diet-induced environmental changes in utero during preimplantation and gestation (Sasson et al. 2015; Shankar et al. 2011), and milk composition during lactation (Vogt et al. 2014), among many others. To overcome this issue, a German group used in vitro fertilization and implanted the resulting embryos into healthy surrogate females to ensure exclusive inheritance via the gametes and confirmed that a parental HFD renders offspring more susceptible to developing obesity and diabetes in a sex- and parent of origin–specific mode (Huypens et al. 2016), providing strong evidence that acquired traits can be inherited. The molecular mechanisms accounting for the heritable epigenetic modifications acquired during the parent’s lifetime are still unclear. However, miRNA modifications as well as modifications in RNA transcripts and methylomes may play a crucial role.
Fig. 3

Parental inheritance of MetS and the role of miRNAs. Epidemiological studies shown that stressors we are exposed to during our lifetime might cause disease in our descendants. In murine models, a HFD induce epigenetic changes that first contributing to the development of MetS risk factors, such as obesity and T2DM in the individual exposed (somatic cells, F0 generation), and then passing modifications on to the subsequent generation via germinal cells. Epigenetic modifications involve DNA methylation, posttranslational histone modifications, and changes in miRNA levels. In pregnant dams, HFD exposure can also induce epigenetic changes in the next two generations (F1 and F2) through the fetus and its germ line (intergenerational inheritance). The effect of such multigenerational exposure in subsequent generations (F3 and beyond) would be considered a transgenerational inheritance. By contrast, intergenerational inheritance in males is limited to the F1 generation (Modified from Heard and Martienssen 2014)

Conclusion

In modern societies, the consumption of highly caloric foods and sedentary lifestyle has increased the rates of obesity, T2DM, and MetS at a pace that reaches pandemic levels. Additionally, individual genetic predispositions (or resistance) could worsen (or alleviate) the pathological outcome of a dietary challenge. Different molecules and biological pathways have been proposed as the mechanism by which organisms integrate the environmental signals and stressors that result in the development of the metabolic clusters that compose the MetS. In that sense, miRNAs have emerged as attractive molecules, given their role as important components of complex gene regulatory networks. miRNAs play a critical role in the development of individual components of MetS; however, our understanding of their function during the different combinatorial modalities of MetS is poor. More detailed metabolic profiles of the animals used for metabolic manipulations are needed to determine whether the miRNA alterations occur in a context of MetS.

Finally, the study of inter- and transgenerational inheritance has shown that our dietary sins are passed on to our children in the form of epigenetic modifications, such as DNA methylation, chromatin modification, and miRNAs. Biological examples have been documented of phenotypic plasticity emerging in relatively fast time-scales and of frequencies that are orders of magnitude higher than can be explained by natural selection of genetics variants. The hypothesis that our nutritional experiences are coded in our epigenome could help to explain the exponential increase in obesity, T2DM, and MetS observed in the modern world.

Key Facts

  • In USA, nearly 35% of all adults and 50% of those aged 60 years or older were estimated to have the metabolic syndrome.

  • Each miRNA potentially regulates hundreds of target gene products, and it is suggested that the entire protein coding genome is regulated by miRNAs.

  • Recently, a rapidly growing number of miRNAs have been implicated in regulation of genes and proteins involved in the control and maintenance of metabolic homeostasis including cholesterol and lipid homeostasis, insulin signaling and glucose homeostasis, as well as cardiometabolic disorders such as obesity, NAFLD, insulin resistance, T2DM, and coronary artery disease.

  • Environmental factors like nutrition could regulate the expression of miRNAs through different mechanisms including the modulation of their transcription, processing or assembling in their functional complex, miRISC.

  • Change in metabolic miRNAs could be passed to next generations through intergenerational and transgenerational inheritance which may exacerbate the epidemic of MetS.

Dictionary of Terms

  • Pri- and pre-miRNA – MicroRNAs are transcribed via Pol II into primary-microRNAs (pri-miRNA), which are then cleaved in the nucleus by the enzyme DROSHA. The hairpin structure formed by this cleavage is referred to as a pre-miRNAs (Fig. 1).

  • MicroRNA recognition element (MRE) – Correspond to a short sequence in the 3′UTR of the mRNA target that bind to the seed sequence in their cognate miRNA through imperfect RNA-RNA base pairing that involves not only the Watson-Crick A:U and G:C pairs but also the G:U pair.

  • miRNA-induced silencing complex (miRISC) – A ribonucleoprotein complex loaded with a specific miRNA that mediate translational repression of their mRNA target. The core proteins of the miRISC are Dicer, a class III RNase III, Argonaute (which bind to different classes of small noncoding RNAs, including microRNAs) and TAR RNA binding protein, a double-stranded RNA binding protein.

  • High-fat diet (HFD) – A diet-induced obesity model, that closely mimics the increasingly availability of the high-fat/high-density foods in modern society, which are main contributors to the obesity trend in human.

  • Transgenerational Inheritance – Correspond to the transmittance of epigenetic modifications (excluding DNA sequence changes) from one generation of an organism to the next one that affects the traits of offspring. In their stricter sense, the transgenerational inheritance occurs when a generation presents the trait and the epigenetic modification but never was exposed to the environmental challenges that induce such changes in their parents.

Summary Points

  • In modern societies, the consumption of highly caloric foods and sedentary lifestyle has increased the rates of obesity, T2DM, and MetS at a pace that reaches pandemic levels.

  • Metabolic syndrome corresponds to a cluster of several risk factors that increases the risk of other health problems, such as cardiovascular disease and diabetes.

  • miRNAs are small endogenous noncoding RNAs that typically control the expression of their target genes by imperfect base pairing to the 3′UTR of their messenger RNAs targets.

  • Nutritional components affect the expression and activity of endogenous miRNAs through different mechanisms, including modulation of critical enzymes of the miRNA biogenetic pathway or modulation of components of the miRISC.

  • Different individuals and populations possess a genetic burden, including mutations in miRNA genes, that made them either resistant or vulnerable to the development of MetS.

  • Mutations within the miRNA genes could potentially affect the processing or target selection of miRNAs by different means, including their transcription; pri-miRNA and pre-miRNA processing; and via miRNA–mRNA interactions.

  • Genetic polymorphisms that reside in the 3′UTR of miRNA target genes, which can eliminate an existing binding site, create an erroneous binding site, or affect binding affinity.

  • Epigenetic mechanisms may exacerbate the epidemic of MetS by first contributing to the development of MetS risk factors and then passing modifications on to the subsequent generation via parental inheritance.

  • The underlying mechanism by which environment shapes the organism is through epigenetic modifications, which involve DNA methylation, posttranslational histone modifications, and changes in miRNA levels.

  • The analysis of miRNA deregulation in MetS patients and animal models could help to develop better therapeutic strategies to improve the quality of life of the increasing population of MetS patients.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Juan Francisco Codocedo
    • 1
  • Nibaldo C. Inestrosa
    • 1
    • 2
    • 3
    Email author
  1. 1.CARE UC Biomedical Research Center, Faculty of Biological SciencesPontificia Universidad Católica de ChileSantiagoChile
  2. 2.Centre for Healthy Brain Ageing, School of Psychiatry, Faculty of MedicineUniversity of New South WalesSydneyAustralia
  3. 3.Centro de Excelencia en Biomedicina de Magallanes (CEBIMA)Universidad de MagallanesPunta ArenasChile

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