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Review | Open | Published:

Role of microRNAs in obesity and obesity-related diseases


In recent years, the link between regulatory microRNAs (miRNAs) and diseases has been the object of intensive research. miRNAs have emerged as key mediators of metabolic processes, playing crucial roles in maintaining/altering physiological processes, including energy balance and metabolic homeostasis. Altered miRNAs expression has been reported in association with obesity, both in animal and human studies. Dysregulation of miRNAs may affect the status and functions of different tissues and organs, including the adipose tissue, pancreas, liver, and muscle, possibly contributing to metabolic abnormalities associated with obesity and obesity-related diseases. More recently, the discovery of circulating miRNAs easily detectable in plasma and other body fluids has emphasized their potential as both endocrine signaling molecules and disease indicators. In this review, the status of current research on the role of miRNAs in obesity and related metabolic abnormalities is summarized and discussed.


Obesity: a global epidemic

About 10 years ago, the World Health Organization indicated the increasing prevalence of overweight and/or obesity worldwide as a challenge for public health, due the adverse consequences associated with obesity and overweight [1, 2]. The trend has been so steep and sudden that some researchers refer to it as an “epidemic.” Nowadays, over 60% of the United States (USA) adult population is considered overweight or obese, but the high prevalence of obesity is not limited to the USA, being observed in industrialized as well as in least developed countries. Even more worrisome is the rapidly increasing prevalence of obesity among children observed over the last 30 years [3]. Epidemiological studies have established a firm association between an elevated BMI and chronic conditions such as diabetes, dyslipidemia, hypertension, heart disease, non-alcoholic fatty liver disease, and some types of cancer [4, 5]. Dyslipidemia and type 2 diabetes (T2D) have exhibited a corresponding increase over the same time span also in children [6].

The medical costs of obesity, and also the growing mortality among obese individuals, are likely related to comorbid conditions rather than obesity per se. A surplus in energy intake and a limited physical activity are considered among the driving factors of obesity; however, the contribution of genetic and epigenetic traits could not be disregarded. In the last decade, large and well-powered studies have shown that multiple loci on the human genome are associated with obesity and obesity-related phenotypes [7,8,9].

A new layer of control

The individual susceptibility to weight gain and the associated clinical effects may largely vary due to differences in the genetic background, lifestyle, and environmental stimuli. It is well recognized that the “common” obesity is the result of the interplay of environmental factors with genetic factors reflecting the additive contribution of many genes that confer different degrees of susceptibility (polygenic obesity) [10]. Of note, most of the genes associated to obesity predisposition are also related to food intake and regulation of energy balance [11], with about 20–40% of the variance in energy and macronutrient intake explained by genetic effects [12]. Recent studies suggest that as much as 21% of BMI variation can be explained by common genetic variants [13]. Even though the genetics of obesity has been extensively explored, most of the genetic variability in BMI remains unexplained and, in addition, the confirmation of the effects of single candidate genes or their combination is still incomplete.

Genomes contain information that is mandatory to build and run cells, including the self-coordination responsible to define complex organs and ultimately to self-assemble an organism by driving cellular differentiation and morphogenesis programs. Together, these processes require contribution of information-dense and dynamic regulatory systems involving a number of mechanisms including transcription factors, DNA methylation, ATP-dependent chromatin remodeling mechanisms, and post-translational modifications of histones, as well the dynamic acetylation and deacetylation of core histones [14,15,16]. Virtually, any step of the gene expression flow is finely controlled, and the discovery of small non-coding RNAs (ncRNAs) has added new critical players to the wide range of existing mechanisms [17].

In a few years, microRNA (miRNA) research has proceeded from the discovery of a non-coding RNA in C. elegans [18, 19] to thousands of publications describing their critical connection to a variety of cell processes and diseases [20]. miRNAs are short ncRNAs, with a length of 20–24 nucleotides, which are engaged in the control of gene expression programs [21,22,23]. At present, more than 2000 different miRNAs have been described in humans, and their number is still increasing in the miRBase database [24]. The release of 21 of the repository contains 28,645 entries representing hairpin precursor miRNAs, expressing 35,828 mature miRNA products, in 223 species. In recent years, miRNA biogenesis and mechanisms of action have been thoroughly described as illustrated in Fig. 1 [25,26,27,28,29,30,31]. miRNAs are essential elements of the cell epigenetic machinery which post-transcriptionally repress the expression of target genes, usually by binding to the 3′ UTR of messenger RNA, contributing to the regulation of many biological processes [32].

Fig. 1

miRNA biogenesis. Single miRNAs are transcribed by RNA polymerase II (pri-miRNA) from genomic DNA. The pri-miRNA is processed to pre-miRNA by Drosha-DGCR8. The pre-miRNA is transferred to the cytoplasm by exportin-5 where it is recognized and cleaved by the DICER complex to create a miRNA duplex. The duplex unwinds, and the mature miRNA assembles into RISC. The miRNA base-pairs with target mRNA determines gene silencing via mRNA cleavage or translation repression depending on the degree of homology between the miRNA “seed” to the 3′ UTR target sequence of the mRNA

For base-pairing with a target mRNA, nucleotides in positions 2–8 of a miRNA are relevant. This sequence motif is referred to as “seed sequence” and is closely connected to the recognition of a mRNA target. However, other regions also contribute in determining the target specificity [33]. A numeric designation has been given in sequential order to individual miRNAs according to the discovery date, and matching miRNAs found in different organisms have been assigned through the same numeric code with a species-specific preface. Moreover, miRNAs have been clustered into families constructed on seed region similarity, which is accountable for the corresponding ability to target common groups of gene transcripts [34]. Although some miRNAs exhibit a tissue-specific localization, most miRNAs show a broader tissue distribution [35]. Each miRNA can simultaneously regulate large cohorts of transcripts, and individual mRNA may include multiple binding sites for different miRNAs originating an intricate regulatory network [32, 36]. Even though miRNAs usually act as slight modulators, defining only a weak inhibitory effect on a single target, more often, they coordinately affect multiple transcripts in a signaling pathway or nodes correlated in complex regulatory networks, exercising significant cumulative effects. A notable example is given by the members of the miR-200 family, acting at multiple levels as enforcers of the epithelial phenotype. Actually, they target both cytoskeletal effectors, regulating actin filament organization, and pathways that locally coordinate the cytoskeleton organization to preserve cell morphology and prevent cell migration [37].

Computational and experimental analyses support the view that endogenous miRNAs may comprehensively influence the expression of up to 60% of mouse and human genes [38, 39] and that a huge number of miRNAs are under the control of relevant signal transduction cascades. Therefore, miRNAs have been reported to be involved in a countless cellular processes, including proliferation, differentiation, DNA repair, apoptosis, and metabolism [40, 41]. Additionally, increasing evidence indicates that miRNA dysregulation is causative and/or indicative of several diseases, including cancer [42,43,44,45]. Substantial progress has been made in interpreting the role of individual miRNAs in a number of biological settings. As an example, members of the highly conserved miR-34 family act as tumor suppressor. Dysregulation or loss of the host gene from which this miRNA is derived is associated with cancer progression in numerous cell types [45].

miRNA detection

miRNA profiling is a key step which requires sensitive and reproducible detection methods. A number of different techniques have been developed to determine miRNAs in biological samples, such as NGS (RNAseq), reverse transcription quantitative PCR, and microarray, each method having its own strengths and weaknesses [46]. In general, miRNA characterization, as compared to mRNA profiling techniques, is more difficult to perform because procedures should be able to discriminate miRNAs differing by as little as a single nucleotide, also taking into account differences between mature miRNAs and their precursors (which also encompass the sequence of the mature miRNA species).

Furthermore, precise measurement of circulating miRNAs can be challenging, due to their relatively low concentration, to the presence of undesired inhibitors potentially interfering in the downstream quantification procedures and, finally, to confounding sources of intracellular miRNAs that may contaminate the extraction process. Indeed, the inconsistencies and dissimilar results reported among different studies could be partially explained by differences in both detection procedures and experimental setup. The source of miRNAs, the extraction procedures, the quantities used in profiling analysis workflow, and the methods of data analysis all together possibly contribute to the uncertainty still observed in the literature, highlighting the need for reproducible and well-standardized methods [47,48,49].

miRNAs in obesity and metabolic diseases

At the time of our search, 61,363 published papers concerning miRNAs were found on PubMed. Most of them deal with human diseases/disorders and a growing number of reports about miRNAs as useful clinical tools [50], in particular with regard to the identification of “circulating” miRNAs (see the “Circulating miRNAs” section) as cancer biomarkers [51, 52]. Omics studies have indeed demonstrated that changes in miRNA profiles of various tissues (e.g., pancreas, adipose tissue, and liver) correlate with obesity [8] and several metabolic diseases [53, 54]. There are intriguing reports suggesting that miRNAs may be regulated by diet and lifestyle factors [55] and could be responsive to various nutritional interventions [56].

For the purpose of the present review, we thoroughly explored PubMed using different combinations of the subsequent keywords: “microRNA,” “circulating miRNAs,” “adipose tissue,” “adipogenesis,” “obesity,” “diabetes,” and “metabolic diseases.” Obviously, a complete and comprehensive scrutiny of the available literature was outside our scope. Actually, the most cited research papers as well as the most recent and complete reviews on this research area were included.

miRNAs in the adipose tissue

The obesity–diabetes connection has been long time established, having its roots in interdependent alterations of glucose and lipid metabolism. Adipose tissue, the storage site of triglycerides, is the key machinery where energy homeostasis is regulated, to the extent that adipose tissue is now considered an endocrine organ (see Table 1) [57, 58]. In this context, it is not surprising that miRNAs may contribute to the regulation of energy balance and metabolic homeostasis, by controlling a wide range of metabolic pathways [54].

Table 1 White adipose tissue in brief

The first evidence suggesting a role of miRNAs in fat cells regulation was in Drosophila, showing that miR-14 exerts a suppressive effect on fat metabolism by targeting p38 and MAPK [59]. Subsequentely, a wide array of miRNAs involved in the regulation of glucose and lipid metabolism was identified, with particular focus on adipocyte differentiation, control of β-cell mass, and insulin signaling pathway in both physiological and pathological conditions [60, 61]. However, the information regarding the possible mechanisms is still limited [62]. As an example, the miRNAs reported in Table 2 have been shown to possibly promote adipogenesis through different mechanisms, while other species (Table 3) have been reported to interfere with adipocyte differentiation [63].

Table 2 Adipogenesis promoting miRNAs
Table 3 Anti-adipogenic miRNAs

miR-143 and miR-130 are the best studied among the miRNAs linked to adipogenesis. miR-143 and miR-145 are often investigated together, since they are closely located and can be co-transcribed. miR-143 has been identified as a positive regulator of human adipocyte differentiation acting via ERK5 signaling. Expression of miR-143 and miR-145 is upregulated in the liver of mouse models of obesity, and the iperexpression of miR-143 impairs insulin-stimulated AKT activation and glucose homeostasis. On the contrary, mice lacking for the miR-143–145 cluster did not develop the obesity-associated insulin resistance [64]. Another notable example is given by miR-27a and miR-130a that inhibit adipocyte differentiation through PPARγ downregulation [65, 66]. The overexpression of miR-27a and miR-130a clearly suppresses adipocyte differentiation along with PPARγ expression. Lower expression levels of miR-130a and miR-130b have been reported in the abdominal subcutaneous adipose tissue and in the plasma of obese women compared with those of lean subjects [67]. In contrast, circulating miR-130b has been found to be higher in obese children [68]. An interesting study from Wang et al. identified miR-130b as a potential biomarker for overweight, hypertriacylglycerolemia, and metabolic syndrome, suggesting a mechanism linking obesity and obesity-related metabolic diseases, through an adipose–muscle crosstalk mediated by circulating miRNAs [69]. They have also found that the addition of TGF-β in matured 3T3-L1 adipocytes dramatically elevated the level of miR-130b in the culture medium, while slightly decreasing intracellular level of miR-130b, thus confirming that this miRNA is released from differentiating adipocytes during adipogenesis. Other miRNAs affect lineage determination. As an example, miR-124 has a pro-adipogenic effect by targeting Dlx5, a pro-osteogenic transcription factor that determines cell fate in human bone marrow-derived mesenchymal stem cells [70].

miRNAs can be expressed from separate transcripts or from a primary transcript structured in co-transcribed clusters encoding more than one miRNA (polycistronic) [71]. The best-characterized polycistronic miRNA cluster is represented by miR-17-92, encoding for miR-17, miR-18a, miR-19a, miR-20a, miR-19b-1, and miR-92a [72]. This cluster is overexpressed during adipocyte clonal expansion and acts by directly repressing the RB family Rb2/p130, so controlling the RB-E2F-mediated checkpoint. In the same pathway, miR-363 inhibits adipocyte differentiation by targeting E2F and concomitantly downregulating C/EBPα and PPARγ [73].

Let-7 was the first human miRNA discovered. This miRNA is included in a well-conserved family counting 11 members associated with many critical cell functions (e.g., apoptosis, proliferation, and cell cycle checkpoints). This miRNA family directly regulates oncogenes such as RAS and HMGA2 and plays a significant role in developmental processes. Moreover, miRNAs of this family regulate glucose metabolism and peripheral insulin resistance by targeting IGF1R, insulin receptor (INSR), and insulin receptor substrate-2. Let-7 negatively controls adipogenesis by regulating the expression of high-mobility group AT-hook2. Let-7 is upregulated in the model of 3T3-L1 adipogenesis. The ectopic introduction of let-7 in 3T3-L1 and 3T3-F442A cells decreased the clonal expansion as well as the terminal differentiation [74]. Overall, there is an indication that let-7 acts as an anti-adipogenic factor controlling the transition from clonal expansion to terminal differentiation. Moreover, let-7 has been shown to be directly involved in glucose metabolism and insulin resistance acting on targets associated with the insulin/IGF-1R pathway in mice [75]. In let-7 knockout mice, animals with a reduced expression of let-7 did not develop insulin resistance despite diet-induced obesity, suggesting that let-7 may represent an interesting therapeutic target for diabetes [76].

Various miRNAs affect adipocyte differentiation by targeting C/EBPs and insulin signaling. miR-375 has been shown to promote 3T3-L1 adipocyte differentiation by increasing mRNA levels of C/EBPα and PPARγ2 and by inducting adipocyte fatty acid-binding protein (aP2) and triglyceride accumulation. Conversely, miR-375 suppresses phosphorylation levels of ERK1/2 in 3T3-L1 cells [77].

There is evidence that miR-206 plays a key role in the growth and development of the skeletal muscle, promoting the myogenic differentiation and has been related to the pathogenesis of numerous diseases, including heart failure, chronic obstructive pulmonary disease, Alzheimer’s disease, and some cancers [78]. In most of these diseases, miR-206 is downregulated, suggesting this miRNA as a “disease-avoiding” molecule [78]. Interestingly, miR-206 expression is abundant in brown adipocytes in mice but missing in white adipocytes [79]. Moreover, miR-206 suppresses liver X receptor α (LXRα), a gene target of PPAR, thus inhibiting lipogenesis and controlling lipid metabolism in HepG2 cells [80]. Another miRNA involved in the regulation of adipogenic differentiation is miR-26b [81]. Overexpression of miR-26b in 3T3-L1 cells significantly accelerated the mRNA expression of adipogenic markers, PPARγ, fatty acid synthase (FAS), C/EBPα, and lipoprotein lipase, and increased lipid accumulation, by inhibiting the PTEN expression. In contrast, inhibition of miR-26b expression decreased cell differentiation [81].

Current findings indicate that miR-146b expression in 3T3-L1 is evidently increased during adipogenesis [82]. Sirtuin 1 (SIRT1) is negatively regulated by miR-146b. SIRT1 promotes gene transcription by deacetylating various transcription factors, including the forkhead box O1 (FOXO1). The role of SIRT1 as a regulator of metabolic homeostasis has been extensively investigated. SIRT1 level is decreased during adipogenesis. SIRT1, by interacting with the PPARγ co-repressors N-CoR and SMRT, inhibits PPARγ and prevents adipogenesis. Accordingly, differentiation of 3T3-L1 cells is induced by overexpression of miR-146b, and on the contrary, inhibition of miR-146b reduces adipocyte differentiation in 3T3-L1 [83].

The highly conserved miR-8/miR-200 family consists of a single ortholog in the fruit fly (miR-8) and of five members in the vertebrates (miR-200a, miR-200b, miR-200c, miR-141, and miR-429) [84]. miR-8/miR-200 have been reported as repressors of the evolutionarily conserved Wnt/wingless pathway in the Drosophila eye and in mouse mesenchymal stem cells, controlling the eye size and the differentiation of the mesenchymal stem cells into adipocytes, respectively [85]. Drosophila miR-8 and human miR-200 family also prevent the expression of an inhibitor of the insulin/phosphoinositide-3 kinase (PI3K) signaling in fat body and liver cells, thus controlling fat body/liver cell growth and proliferation [86]. In particular, overexpression of members of this miRNA family increases adipogenesis, the level of fatty acid-binding protein 4 (FABP4), and lipid accumulation.

Liang et al. showed that the expression of miR-210 was highly increased during 3T3-L1 adipogenesis. Transfection of miR-210 mimics into 3T3-L1 cells promoted the expression of adipogenic markers and adipocyte differentiation by targeting SHIP1, a negative regulator of the PI3K/Akt pathway. Additionally, ectopic inhibition of the endogenous miR-210 during adipogenesis possibly blocks adipocyte differentiation [87].

Likewise, miR-21 in 3T3-L1 cells significantly promotes adipocyte differentiation and increases adiponectin expression, while decreasing AP-1 protein level. miR-21 may enhance differentiation of human adipose-derived stem cells by direct inhibition of the TGF-β receptor 2 expression [88].

Current evidence indicates that inflammation induces a specific miRNA response in adipocytes with effects on the physiopathology of obesity-induced inflammation of adipose tissue [89]. As an additional example, a research in mice identified a pro-inflammatory loop mediated by NF-κB and miR-155 that could participate in the amplification of inflammatory status in adipocytes [90].

An interesting paper from Thomou et al. has recently defined a new role for adipose tissue and its potential implications in the mechanism of cell crosstalk [91]. The authors have established the role of adipose tissue as a major source of circulating miRNAs, which can regulate gene expression in distant tissues so acting as regulators of metabolism. Mice with an adipose tissue-specific knockout of Dicer miRNA-processing enzyme, as well as humans with lipodystrophy, display an extensive decline in the levels of circulating miRNAs. Transplantation of both white and brown adipose tissues reestablishes the level of many circulating miRNAs associated with an improvement in glucose tolerance and a reduction in hepatic fibroblast growth factor 21 (FGF21) mRNA and circulating protein. FGF21 plays a critical role in metabolism, stimulating the fatty acid oxidation in the liver and glucose uptake in fat. Of note, levels of FGF21 are significantly increased in patients with T2D and non-alcoholic fatty liver disease and positively correlate with BMI in humans, indicating obesity as a possible FGF21-resistant state [91].

miRNAs in the pancreas

The endocrine pancreas plays a major role in regulating glucose homeostasis through the secretion of insulin and glucagon. Alterations of pancreatic hormone production and activity are causally linked to diabetes. T2D is a complex disease characterized by pancreatic islet dysfunction and insulin resistance in peripheral tissues. Declined insulin levels in T2D have been attributed to a decrease in β-cell function/mass [92]. Identity and dedifferentiation of β-cells may also contribute to the insulin production decay. The first suggestion for a role of miRNAs in hormone secretion in vertebrates came from a cloning approach of small RNAs from the β-cell-derived line MIN6 [93]. Comparing islet–cell miRNA profiles with those of 15 other human tissues, a panel of 40 miRNAs predominantly expressed in the islets have been recently identified [94]. Numerous miRNAs have been reported to be involved in pancreatic development, with some of them playing positive roles, while others exhibiting negative effects [95, 96]. One of the most relevant is miR-375, which is the most abundant in pancreatic islets and is essential in maintaining normal pancreatic β-cell mass [97]. An increase in miR-375 expression is observed during pancreatic islet cell development, whereas β-cell functioning is linked to its decrease [98]. Numerous genes associated with cellular growth are controlled by this miRNA during human pancreas development [99]. Moreover, miR-375 targets a number of transcription factors, such as PDX1, HNF6, and INSM1, engaged in pancreatic islet functioning [100]. Interestingly, the transcription factor neurogenin3 (Ngn3), considered as an early marker of pancreatic islet cells with a prominent role during the development of the endocrine lineages in mice [101], also interferes with miR-375 expression. Additional miRNAs, such as miR-15a, miR-15b, miR-16, and miRNA-195, also target Ngn3. Remarkably, miR-375 has been reported to be involved in the modulation of insulin secretion in stimulated cell line MIN6 [93]. More in detail, miR-375 leads to a reduced glucose-stimulated insulin secretion by downregulating myotrophin mRNA (encoding a key protein involved in cell membrane fusion with insulin granules) and therefore inhibiting exocytosis. Furthermore, it has been shown that miR-375 concurrently downregulates expression of insulin by targeting the phosphoinositide-dependent kinase-1 in INS1-E cells [102]. Other miRNAs such as miR-7 and miR-124 have been recognized to be engaged in regulation of β-cell differentiation and establishment of pancreatic islets [97]. High levels of miR-7 are detectable in the pancreatic cells, both in the developing and adult phases [103]. Overexpression of miR-7 in pancreatic progenitors has been shown to impair the differentiation of both α- and β-cells and is associated with a repression of Pax6 expression. The knockdown of miR-7 during early embryonic life determines an overall downregulation of insulin production, a decrease in the number of β-cells, and the onset of glucose intolerance in the postnatal period. Furthermore, an in vitro inhibition of miR-7 promotes death of β-cell in explanted pancreatic buds. In summary, data suggest that dysregulation of miR-7 signaling network in response to metabolic stress or cellular insults contribute to the loss of β-cell identity and establishment of T2D [104].

Other miRNAs, like miR-146a and miR-34a, seem overexpressed only during the differentiation processes and have been shown to contribute, at least partially, to cytokine-mediated β-cell dysfunction occurring during the initial phases of type 1 diabetes in non-obese diabetic (NOD) mice [54]. Further, miRNAs expressed in pancreatic islets, such as miR-143 and let-7, have been connected to glucose homeostasis by targeting key insulin signaling components [75].

Other pancreatic functions can be modulated by miRNAs. For instance, miR-29, in addition to its ability to regulate β-cell proliferation, has also been shown to negatively regulate insulin secretion by directly targeting Stx-1a involved in insulin exocytosis [105]. Similarly, miR-124a, miR-9, and miR-96 can regulate insulin release by β-cells [106]. During the late pancreas development, miR-124a is upregulated [107]. This miRNA targets mRNA of both cAMP-responsive element-binding protein 1 (Creb1) and forkhead box protein A2 (Foxa2). Notably, Foxa2 modulates the expression of the insulin gene in multiple pathways responsible for the secretion of this hormone, mainly through an upstream regulation of pancreatic and duodenal homeobox 1 (Pdx1). Pdx1 is critical for glucose balance and pancreas development and together with Ngn3 is required for β-cell differentiation. Moreover, miR124a increases the levels of SNAP25, Rab3A, and synapsin-1A and decreases those of Rab27A and Noc2, targets involved in the exocytotic mechanisms for insulin release [106].

Overexpression of miR-9 in insulin-secreting INS-1E cells results in a reduction of insulin exocytosis. mir-9 acts by downregulating the expression of the transcription factor Onecut-2 and, in turn, by increasing the level of Granuphilin/Slp4, a Rab GTPase effector associated with β-cell secretory granules [108].

Finally, miR-29 also controls insulin secretion by regulating the monocarboxylate transporter 1 (Mct1) expression [105].

miRNAs in the muscle

The skeletal muscle represents the major user of glucose in human body, accounting for about 75% of insulin-mediated glucose uptake. Several miRNAs, referred to as myomiR family, are preferentially detectable in muscle tissue and act as modulators of skeletal and cardiac muscle myogenesis, proliferation, and metabolism, as well as hypertrophy. The myomiRs include miR-1, miR-133a, miR-133b, miR-206, miR-208a, miR-208b, miR-486, and miR-499 [109]. miR-206 is specifically expressed in the skeletal muscle, whereas miR-208a is cardio-specific; nevertheless, most of these miRNAs are co-expressed in the heart and skeletal muscles [110]. MyomiRs have been proven to directly target pathways regulating skeletal muscle homeostasis; their deregulation is observed across cardiac and muscular dysfunctions [111]. As an example, a reduced expression of miR-133 is observed in mouse and human models of cardiac hypertrophy, with several studies connecting this miRNA to the pathogenesis of heart diseases [112]. Interestingly, it has been proven that acute exercise determines an increase in the levels of miR-1, miR-133a, and miR-206 [113], important molecules possibly driving cell-to-cell communication. A recent paper from Zhou et al. has demonstrated the involvement of miR-29a in the induction of insulin resistance by targeting PPARδ in rats’ skeletal muscle cells. Overexpression of miR-29a in the cell line C2C12 suppresses the expression of PPARδ, finally affecting the expression of its coactivator PGC-1α. PPARδ/PGC-1α-dependent signaling determines a decrease in levels of glucose transporter 4, the principal glucose transporter in the skeletal muscle, which partially induces a decrease in insulin-dependent glucose uptake and adenosine triphosphate (ATP) availability [114]. Similarly, another study found that miR-29a levels are elevated in the diabetic (db/db) mouse liver and its overexpression prevents insulin-mediated inhibition of hepatic phosphoenolpyruvate carboxykinase (PEPCK) gene expression, which is normally implicated in inhibition of gluconeogenesis and suppressed in diabetes [115]. Other studies have shown that high-fat diet significantly increases the expression of miR-29a in myocytes, impairing insulin signaling and glucose uptake through an extensive decrease in insulin receptor substrate 1 (IRS-1). Possibly, the upregulation of miR-29a by saturated fatty acids (SFA) is causally related to the development of insulin resistance in the muscle [116]. miR-106b, highly expressed in the muscle of diabetic subjects, has been associated to skeletal muscle insulin resistance and T2D. Overexpression of miR-106b determines mitochondrial dysfunction and insulin resistance in C2C12 myotubes by targeting mitofusin-2. Notably, expression of this miRNA is improved following TNF-α treatment, suggesting that its enhanced production under chronic low-grade inflammation may represent a valuable link between mitochondrial alteration and T2D [117].

A fascinating research topic is the pleiotropic regulatory network exerted by miR-208a, a heart-specific miRNA that also controls glucose metabolism and energy homeostasis. The heart contributes to regulate systemic energy homeostasis via MED13 [118], a subunit of the Mediator complex, which governs the transcription by the thyroid hormone (that enhances energy expenditure and regulates body weight) and other nuclear hormone receptors [119]. MED13 is negatively controlled by miR-208a. Remarkably, anti-miR-208 oligonucleotides confer resistance to diet-induced obesity and improve glucose tolerance in mice [120].

miRNAs in the liver

miRNAs control various functions in the liver, and cumulative evidence suggests that they have a relevant role in this organ pathology [121]. miR-122 is a dominant hepatocyte-specific miRNA accounting for about 75% of total miRNA expression in human hepatocytes with approximately 135,000 copies, making it one of the highly expressed in the human body. Levels of miR-122 are controlled by liver-enriched transcription factors (LETFs), including hepatocyte nuclear factor (HNF) 6 and 4a. Interestingly, miR-122 regulatory network has been implicated in numerous liver functions, ranging from cholesterol metabolism, stress responses, viral infection, cancer, and circadian regulation of hepatic genes [122]. The role of this miRNA is also emerging in the metabolic syndrome and other liver diseases, such as liver inflammation related to alcohol use, autoimmune processes, and the development of liver fibrosis both in human and animal models. Pathological suppression of miR-122 has been described in hepatocellular carcinoma [123], non-alcoholic steatohepatitis [124], and liver cirrhosis [121]. This miRNA is intensely investigated because of its role in cholesterol metabolism. Antisense inhibition of miR-122 in normal mice results in lower levels of serum cholesterol, LDL, and serum triglyceride and increased hepatic fatty acid oxidation. These effects on lipid metabolism have been associated with the expression of key genes involved in fatty acid metabolism and cholesterol biosynthesis, including the rate-limiting enzyme 3-hydroxy-3-methylglutaryl-CoA-reductase [125]. Similarly, antisense inhibition of this miRNA in chimpanzee provokes a plasma cholesterol reduction supporting its key role in maintaining liver homeostasis [126]. Since miR-122 can be detected in blood, it has been proposed as a circulating biomarker of liver injury in chronic hepatitis B and C, non-alcoholic fatty liver disease, and drug-induced liver disease [127].

Other miRNAs, such as miR-27b, miR-33, miR-34, miR-103, miR-104, 223, and miR-370, also control the fatty acid metabolism and cholesterol biosynthesis in the liver. As an example, miR-27b could exert regulatory effects in the lipid metabolism and is altered in dyslipidemia, theoretically affecting both liver and heart functions in mouse [128]. Moreover, miR-34a targets hepatic SIRT1. The upregulation of miR-34a, with a concomitant decrease in SIRT1 levels, has been described in fatty livers of mice with diet-induced obesity [129]. Additionally, the mitochondrial enzyme carnitine palmitoyl transferase, involved in the transport of long-chain fatty acids across the membrane, is targeted by miR-370 that concurrently affects lipid metabolism [130].

MiR-33-3p regulates cholesterol and lipid metabolism as well as fatty acid oxidation [131]. This miRNA downregulates several genes encoding key enzymes involved in fatty acid metabolism, cholesterol efflux, such as ATP-binding cassette A1 (ABCA1), and insulin signaling. This miRNA in vitro targets IRS2 and SIRT6 genes involved in insulin signaling. Inhibition of miR-33 in non-human primates resulted in elevated plasma HDL and protective effects against atherosclerosis. However, recent studies suggest that miR-33 inhibition may have adverse effects on lipid and insulin metabolism in mice [132].

Hepatic miR-223 has been shown to reduce cholesterol biosynthesis in mice by targeting the 3-hydroxy-3-methylglutaryl-CoA synthase 1 and the sterol-C4-methyloxidase-like protein. Moreover, this miRNA inhibits the HDL-C uptake by targeting the scavenger receptor class B member 1 and promotes cholesterol efflux by positively regulating the expression of ABCA1. Notably, miR-223 level is controlled by the cholesterol levels [133].

miR-26a additionally regulates insulin signaling as well as metabolism of glucose and lipids in mice and humans [134]. Overweight compared with lean subjects exhibit a decreased liver expression of miR-26a. Overexpression of this miRNA in mice fed a high-fat diet enhanced insulin sensitivity and reduced hepatic glucose and fatty acid synthesis, so preventing obesity-induced metabolic complications [134].

Remarkably, a number of hepatic miRNAs have been reported to be dysregulated in obese patients with NAFLD and NASH [124, 135, 136].

Circulating miRNAs

Although miRNAs were first identified inside cells, more recently, an increasing number of miRNAs have been found, in surprisingly high concentrations, in plasma and other body fluids such as serum, urine, and saliva [137]. The concept that miRNAs could be stable in blood and body fluids [138], in spite of the ubiquity of nucleases, was originally met with skepticism by the scientific community. However, this characteristic generated high interest for the possibility that variations in cell-free miRNA expression could be used as non-invasive biomarkers for several diseases and, possibly, as early diagnostic tools. [139]. Due to their accessibility, the most common miRNA sources investigated are whole blood, serum, and plasma [140].

Circulating miRNAs (cmiRNAs), as expected, are not naked molecules, and two major mechanisms have been identified to shield them from nuclease activity. The first one consists in the formation of complexes of specific binding proteins, such as Argonaute 2 (AGO-2) [141], a protein involved in the RNA silencing complex, with high-density lipoproteins [142], or nucleophosmin-1 (NPM-1), a nucleolar RNA-binding protein implicated in the nuclear export of the ribosome [143]. The second proposed mechanism stems from the discovery of cmiRNAs enclosed within circulating microvesicles or exosomes [144] deriving either from the endosomal compartments or from the cell plasma membrane [145]. Although an established mechanism for the release of miRNAs from cells remains largely unknown, growing evidence supports the indication that extracellular miRNAs, arranged either into exosomes or protein complexes, may be delivered to the receiver cells, where they can be engaged in the control of target gene translation [146]. However, the physiological role of circulating miRNAs is still uncertain.

Differential cmiRNA profiles have been reported in individuals with obesity and T2D [147]. In Table 4, the behavior of specific cmiRNAs in different metabolic disorders is summarized. For instance, miR-126 is reduced in T2D [148] and has been proposed as a biomarker of endothelial dysfunction caused by uncontrolled glycemia in T2D [149]; miR-1, miR-21, miR-133a, and miR-208 are enriched in the plasma after myocardial infarction [150]; miR-122 is enhanced in hepatic injury and steatosis [151], as well as let-7e in hypertension [152]. Additionally, circulating miR-130a and miR-195 have been connected with high blood pressure [153]. Alterations in circulating miR-23a, miR-27a, miR-130, miR-195, miR-197, miR-320a, and miR-509-5p have been associated to metabolic syndrome [153, 154]. Moreover, cmiRNA profiles exhibited a sex-specific association with metabolic syndrome [155]. Circulating let-7b, miR-143, and 221 have been proposed to regulate atherogenic and adipogenic processes [156]. Furthermore, the expression of circulating miR-17-5p and miR-132 was decreased in obesity, mirroring the expression pattern of miRNAs in omental fat from the same group of obese subjects [157]. Different cmRNA profiles have also been described in pre-gestational and gestational obesity [158].

Table 4 Summary of the current knowledge on circulating miRNAs in the context of obesity and metabolic diseases

Ortega et al. have reported that morbidly obese patients exhibit a marked increase of circulating miR-140-5p, miR-142-3p, and miR-222 and a decrease of miR-532-5p, miR-125b, miR-130b, miR-221, miR-15a, miR-423-5p, and miR-520c-3p. In the same study, a surgery-induced weight loss caused a significant decrease of circulating miR-140-5p, miR-122, miR-193a-5p, and miR-16-1 and an increase of miR-221 and miR-199a-3p [67].

Furthermore, various studies have shown a differential cmiRNA signature in overweight/obese as compared in normal weight children and adolescents [68, 159,160,161], thus suggesting that these molecules could have a promising role in the early identification of children at risk of excess body fat accumulation and related metabolic abnormalities.


Since their first detection in 1993, miRNAs have attracted growing interest among the scientific community. Considerable progress has been achieved in the research of contributory crosstalk between regulatory miRNAs and diseases. miRNAs have emerged as key regulators of lipid and glucose metabolism and play pivotal roles in the onset of obesity and obesity-related diseases by affecting status and functions of the adipose tissue, pancreas, liver, and muscle (Fig. 2). However, information about the mechanisms of action remains nearly limited, due to the miRNAs’ ability to simultaneously affect multiple pathways/gene networks and to the technical limitations of in vivo profiling [48].

Fig. 2

Overview of miRNAs possibly associated with obesity and metabolic diseases in different tissues. Circulating miRNAs are additionally reported in Table 4

A comprehensive understanding of the role of miRNAs in tissue metabolism and energy homeostasis may in perspective open the road to therapeutics strategies. Two main approaches are currently considered: the inhibition strategy, which uses anti-miR sequences able to target a specific miRNA and block its function, and the replacement therapy employing miRNA mimics [162].

The exciting emergence of circulating miRNAs as stable and accessible molecules opened a promising research avenue for the detection of non-invasive biomarkers potentially useful to the early identification of subjects at risk of excess body fat accumulation and related metabolic abnormalities.

For the etiological characterization, prospectively designed studies are strongly needed. A number of miRNA candidate signatures have been defined, and clinical trials are ongoing to validate their significance.



ATP-binding cassette A1




Body mass index


CCAAT/enhancer-binding proteins


circulating miRNAs


cAMP-responsive element-binding protein 1


Extracellular signal-regulated kinases


Fatty acid-binding protein 4


Fatty acid synthase


Fibroblast growth factor 21


Forkhead box protein A2


Forkhead box O1


Hepatocyte nuclear factor


Insulin receptor


Insulin receptor substrate 1


Liver-enriched transcription factors

LXRα :

Liver X receptor α


Monocarboxylate transporter




Non-alcoholic fatty liver disease


Non-alcoholic steatohepatitis


Nuclear receptor corepressor


Small non-coding RNAs




Next-generation sequencing


Non-obese diabetic mice




Pancreatic and duodenal homeobox 1


Phosphoenolpyruvate carboxykinase


Insulin/phosphoinositide-3 kinase


Proliferator-activated receptor-γ


Retinoblastoma susceptibility protein


RNA-induced silencing complexes


RNA sequencing


Saturated fatty acids


SH2 (Src homology 2)-containing inositol phosphatase-1


Sirtuin 1


Silencing mediator for retinoid and thyroid hormone receptors


Sterol regulatory element-binding protein


Type 2 diabetes


  1. 1.

    Hurt RT, Kulisek C, Buchanan LA, McClave SA. The obesity epidemic: challenges, health initiatives, and implications for gastroenterologists. Gastroenterol Hepatol (N Y). 2010;6(12):780–92.

  2. 2.

    Branca F, Nikogosian H, Lobstein T, World Health Organization. Regional office for Europe.: The challenge of obesity in the WHO European region and the strategies for response summary. In. Copenhagen: World Health Organization, Regional Office for Europe; 2007: xiii, 60 p.

  3. 3.

    WHO library cataloguing in publication data report of the commission on ending childhood obesity; 2016.

  4. 4.

    Ahima RS, Lazar MA. Physiology. The health risk of obesity—better metrics imperative. Science. 2013;341(6148):856–8.

  5. 5.

    Bluher M. Adipose tissue dysfunction contributes to obesity related metabolic diseases. Best Pract Res Cl En. 2013;27(2):163–77.

  6. 6.

    D'Adamo E, Caprio S. Type 2 diabetes in youth: epidemiology and pathophysiology. Diabetes Care. 2011;34(Suppl 2):S161–5.

  7. 7.

    Berndt SI, Gustafsson S, Magi R, Ganna A, Wheeler E, Feitosa MF, Justice AE, Monda KL, Croteau-Chonka DC, Day FR, et al. Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture. Nat Genet. 2013;45(5):501–12.

  8. 8.

    Kunej T, Jevsinek Skok D, Zorc M, Ogrinc A, Michal JJ, Kovac M, Jiang Z. Obesity gene atlas in mammals. J Genomics. 2013;1:45–55.

  9. 9.

    Loos RJF, Yeo GSH. The bigger picture of FTO: the first GWAS-identified obesity gene. Nat Rev Endocrinol. 2014;10(1):51–61.

  10. 10.

    Stranger BE, Stahl EA, Raj T. Progress and promise of genome-wide association studies for human complex trait genetics. Genetics. 2011;187(2):367–83.

  11. 11.

    O'Rahilly S, Farooqi IS. Human obesity: a heritable neurobehavioral disorder that is highly sensitive to environmental conditions. Diabetes. 2008;57(11):2905–10.

  12. 12.

    Rankinen T, Bouchard C. Genetics of food intake and eating behavior phenotypes in humans. Annu Rev Nutr. 2006;26:413–34.

  13. 13.

    Locke AE, Kahali B, Berndt SI, Justice AE, Pers TH, Felix R, Powell C, Vedantam S, Buchkovich ML, Yang J, et al. Genetic studies of body mass index yield new insights for obesity biology. Nature. 2015;518(7538):197–U401.

  14. 14.

    Iacomino G, Medici MC, Napoli D, Russo GL. Effects of histone deacetylase inhibitors on p55CDC/Cdc20 expression in HT29 cell line. J Cell Biochem. 2006;99(4):1122–31.

  15. 15.

    Iacomino G, Tecce MF, Grimaldi C, Tosto M, Russo GL. Transcriptional response of a human colon adenocarcinoma cell line to sodium butyrate. Biochem Biophys Res Commun. 2001;285(5):1280–9.

  16. 16.

    Venkatesh S, Workman JL. Histone exchange, chromatin structure and the regulation of transcription. Nat Rev Mol Cell Biol. 2015;16(3):178–89.

  17. 17.

    Catalanotto C, Cogoni C, Zardo G: MicroRNA in control of gene expression: an overview of nuclear functions. Int J Mol Sci. 2016;17(10):1712.

  18. 18.

    Lee RC, Feinbaum RL, Ambros V. The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell. 1993;75(5):843–54.

  19. 19.

    Wightman B, Ha I, Ruvkun G. Posttranscriptional regulation of the heterochronic gene lin-14 by lin-4 mediates temporal pattern formation in C. elegans. Cell. 1993;75(5):855–62.

  20. 20.

    Rupaimoole R, Slack FJ. MicroRNA therapeutics: towards a new era for the management of cancer and other diseases. Nat Rev Drug Discov. 2017;16(3):203–22.

  21. 21.

    Bartel DP. MicroRNAs: target recognition and regulatory functions. Cell. 2009;136(2):215–33.

  22. 22.

    Ghildiyal M, Zamore PD. Small silencing RNAs: an expanding universe. Nat Rev Genet. 2009;10(2):94–108.

  23. 23.

    Ha M, Kim VN. Regulation of microRNA biogenesis. Nat Rev Mol Cell Biol. 2014;15(8):509–24.

  24. 24.

    Kozomara A, Griffiths-Jones S. miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res. 2014;42(Database issue):D68–73.

  25. 25.

    Finnegan EF, Pasquinelli AE. MicroRNA biogenesis: regulating the regulators. Crit Rev Biochem Mol Biol. 2013;48(1):51–68.

  26. 26.

    Kim VN, Han J, Siomi MC. Biogenesis of small RNAs in animals. Nat Rev Mol Cell Biol. 2009;10(2):126–39.

  27. 27.

    Gulyaeva LF, Kushlinskiy NE. Regulatory mechanisms of microRNA expression. J Transl Med. 2016;14(1):143.

  28. 28.

    Faller M, Guo F. MicroRNA biogenesis: there’s more than one way to skin a cat. Biochim Biophys Acta. 2008;1779(11):663–7.

  29. 29.

    Xiong XP, Vogler G, Kurthkoti K, Samsonova A, Zhou R. SmD1 modulates the miRNA pathway independently of its pre-mRNA splicing function. PLoS Genet. 2015;11(8):e1005475.

  30. 30.

    Park JH, Shin C. MicroRNA-directed cleavage of targets: mechanism and experimental approaches. BMB Rep. 2014;47(8):417–23.

  31. 31.

    Pawlicki JM, Steitz JA. Primary microRNA transcript retention at sites of transcription leads to enhanced microRNA production. J Cell Biol. 2008;182(1):61–76.

  32. 32.

    Ebert MS, Sharp PA. Roles for microRNAs in conferring robustness to biological processes. Cell. 2012;149(3):515–24.

  33. 33.

    Grimson A, Farh KK, Johnston WK, Garrett-Engele P, Lim LP, Bartel DP. MicroRNA targeting specificity in mammals: determinants beyond seed pairing. Mol Cell. 2007;27(1):91–105.

  34. 34.

    Wang Y, Luo J, Zhang H, Lu J. microRNAs in the same clusters evolve to coordinately regulate functionally related genes. Mol Biol Evol. 2016;33(9):2232–47.

  35. 35.

    Li P, Hua X, Zhang Z, Li J, Wang J. Characterization of regulatory features of housekeeping and tissue-specific regulators within tissue regulatory networks. BMC Syst Biol. 2013;7:112.

  36. 36.

    Krek A, Grun D, Poy MN, Wolf R, Rosenberg L, Epstein EJ, MacMenamin P, da Piedade I, Gunsalus KC, Stoffel M, et al. Combinatorial microRNA target predictions. Nat Genet. 2005;37(5):495–500.

  37. 37.

    Bracken CP, Li XC, Wright JA, Lawrence DM, Pillman KA, Salmanidis M, Anderson MA, Dredge BK, Gregory PA, Tsykin A, et al. Genome-wide identification of miR-200 targets reveals a regulatory network controlling cell invasion. EMBO J. 2014;33(18):2040–56.

  38. 38.

    Friedman RC, Farh KK, Burge CB, Bartel DP. Most mammalian mRNAs are conserved targets of microRNAs. Genome Res. 2009;19(1):92–105.

  39. 39.

    Lewis BP, Burge CB, Bartel DP. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell. 2005;120(1):15–20.

  40. 40.

    van Rooij E. The art of microRNA research. Circ Res. 2011;108(2):219–34.

  41. 41.

    Bartel DP. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell. 2004;116(2):281–97.

  42. 42.

    Mendell JT, Olson EN. MicroRNAs in stress signaling and human disease. Cell. 2012;148(6):1172–87.

  43. 43.

    Paul P, Chakraborty A, Sarkar D, Langthasa M, Rahman M, Bari M, Singha RS, Malakar AK, Chakraborty S. Interplay between miRNAs and human diseases: a review. J Cell Physiol. 2017;

  44. 44.

    Bracken CP, Scott HS, Goodall GJ. A network-biology perspective of microRNA function and dysfunction in cancer. Nat Rev Genet. 2016;17(12):719–32.

  45. 45.

    Li XJ, Ren ZJ, Tang JH. MicroRNA-34a: a potential therapeutic target in human cancer. Cell Death Dis. 2014;5:e1327.

  46. 46.

    Mestdagh P, Hartmann N, Baeriswyl L, Andreasen D, Bernard N, Chen C, Cheo D, D’Andrade P, DeMayo M, Dennis L, et al. Evaluation of quantitative miRNA expression platforms in the microRNA quality control (miRQC) study. Nat Methods. 2014;11(8):809–15.

  47. 47.

    El-Khoury V, Pierson S, Kaoma T, Bernardin F, Berchem G. Assessing cellular and circulating miRNA recovery: the impact of the RNA isolation method and the quantity of input material. Sci Rep. 2016;6:19529.

  48. 48.

    Riffo-Campos AL, Riquelme I, Brebi-Mieville P: Tools for sequence-based miRNA target prediction: what to choose? Int J Mol Sci. 2016;17(12):1987.

  49. 49.

    Liu B, Li J, Cairns MJ. Identifying miRNAs, targets and functions. Brief Bioinform. 2014;15(1):1–19.

  50. 50.

    Keller A, Meese E. Can circulating miRNAs live up to the promise of being minimal invasive biomarkers in clinical settings? Wiley Interdiscip Rev RNA. 2016;7(2):148–56.

  51. 51.

    Calin GA, Croce CM. MicroRNA signatures in human cancers. Nat Rev Cancer. 2006;6(11):857–66.

  52. 52.

    Matsuzaki J, Ochiya T. Circulating microRNAs and extracellular vesicles as potential cancer biomarkers: a systematic review. Int J Clin Oncol. 2017;

  53. 53.

    Jiang Q, Wang Y, Hao Y, Juan L, Teng M, Zhang X, Li M, Wang G, Liu Y. miR2Disease: a manually curated database for microRNA deregulation in human disease. Nucleic Acids Res. 2009;37(Database issue):D98–104.

  54. 54.

    Dumortier O, Hinault C, Van Obberghen E. MicroRNAs and metabolism crosstalk in energy homeostasis. Cell Metab. 2013;18(3):312–24.

  55. 55.

    Slattery ML, Herrick JS, Mullany LE, Stevens JR, Wolff RK. Diet and lifestyle factors associated with miRNA expression in colorectal tissue. Pharmgenomics Pers Med. 2017;10:1–16.

  56. 56.

    Palmer JD, Soule BP, Simone BA, Zaorsky NG, Jin L, Simone NL. MicroRNA expression altered by diet: can food be medicinal? Ageing Res Rev. 2014;17:16–24.

  57. 57.

    Rosen ED, Spiegelman BM. Adipocytes as regulators of energy balance and glucose homeostasis. Nature. 2006;444(7121):847–53.

  58. 58.

    Schaffler A, Muller-Ladner U, Scholmerich J, Buchler C. Role of adipose tissue as an inflammatory organ in human diseases. Endocr Rev. 2006;27(5):449–67.

  59. 59.

    Xu P, Vernooy SY, Guo M, Hay BA. The Drosophila microRNA Mir-14 suppresses cell death and is required for normal fat metabolism. Curr Biol. 2003;13(9):790–5.

  60. 60.

    Arner P, Kulyte A. MicroRNA regulatory networks in human adipose tissue and obesity. Nat Rev Endocrinol. 2015;11(5):276–88.

  61. 61.

    Hartig SM, Hamilton MP, Bader DA, McGuire SE. The miRNA interactome in metabolic homeostasis. Trends Endocrin Met. 2015;26(12):733–45.

  62. 62.

    Zhang R, Wang D, Xia Z, Chen C, Cheng P, Xie H, Luo X. The role of microRNAs in adipocyte differentiation. Front Med. 2013;7(2):223–30.

  63. 63.

    Price NL, Fernandez-Hernando C. miRNA regulation of white and brown adipose tissue differentiation and function. Biochim Biophys Acta. 2016;1861(12 Pt B):2104–10.

  64. 64.

    Jordan SD, Kruger M, Willmes DM, Redemann N, Wunderlich FT, Bronneke HS, Merkwirth C, Kashkar H, Olkkonen VM, Bottger T, et al. Obesity-induced overexpression of miRNA-143 inhibits insulin-stimulated AKT activation and impairs glucose metabolism. Nat Cell Biol. 2011;13(4):434–46.

  65. 65.

    Qin L, Chen Y, Niu Y, Chen W, Wang Q, Xiao S, Li A, Xie Y, Li J, Zhao X, et al. A deep investigation into the adipogenesis mechanism: profile of microRNAs regulating adipogenesis by modulating the canonical Wnt/beta-catenin signaling pathway. BMC Genomics. 2010;11:320.

  66. 66.

    Lee EK, Lee MJ, Abdelmohsen K, Kim W, Kim MM, Srikantan S, Martindale JL, Hutchison ER, Kim HH, Marasa BS, et al. miR-130 suppresses adipogenesis by inhibiting peroxisome proliferator-activated receptor gamma expression. Mol Cell Biol. 2011;31(4):626–38.

  67. 67.

    Ortega FJ, Mercader JM, Catalan V, Moreno-Navarrete JM, Pueyo N, Sabater M, Gomez-Ambrosi J, Anglada R, Fernandez-Formoso JA, Ricart W, et al. Targeting the circulating microRNA signature of obesity. Clin Chem. 2013;59(5):781–92.

  68. 68.

    Prats-Puig A, Ortega FJ, Mercader JM, Moreno-Navarrete JM, Moreno M, Bonet N, Ricart W, Lopez-Bermejo A, Fernandez-Real JM. Changes in circulating microRNAs are associated with childhood obesity. J Clin Endocrinol Metab. 2013;98(10):E1655–60.

  69. 69.

    Wang YC, Li Y, Wang XY, Zhang D, Zhang H, Wu Q, He YQ, Wang JY, Zhang L, Xia H, et al. Circulating miR-130b mediates metabolic crosstalk between fat and muscle in overweight/obesity. Diabetologia. 2013;56(10):2275–85.

  70. 70.

    Qadir AS, Woo KM, Ryoo HM, Baek JH. Insulin suppresses distal-less homeobox 5 expression through the up-regulation of microRNA-124 in 3T3-L1 cells. Exp Cell Res. 2013;319(14):2125–34.

  71. 71.

    Truscott M, Islam AB, Frolov MV. Novel regulation and functional interaction of polycistronic miRNAs. RNA. 2016;22(1):129–38.

  72. 72.

    Concepcion CP, Bonetti C, Ventura A. The microRNA-17-92 family of microRNA clusters in development and disease. Cancer J. 2012;18(3):262–7.

  73. 73.

    Chen L, Cui J, Hou J, Long J, Li C, Liu L. A novel negative regulator of adipogenesis: microRNA-363. Stem Cells. 2014;32(2):510–20.

  74. 74.

    Sun T, Fu M, Bookout AL, Kliewer SA, Mangelsdorf DJ. MicroRNA let-7 regulates 3T3-L1 adipogenesis. Mol Endocrinol. 2009;23(6):925–31.

  75. 75.

    Zhu H, Shyh-Chang N, Segre AV, Shinoda G, Shah SP, Einhorn WS, Takeuchi A, Engreitz JM, Hagan JP, Kharas MG, et al. The Lin28/let-7 axis regulates glucose metabolism. Cell. 2011;147(1):81–94.

  76. 76.

    Frost RJ, Olson EN. Control of glucose homeostasis and insulin sensitivity by the Let-7 family of microRNAs. Proc Natl Acad Sci U S A. 2011;108(52):21075–80.

  77. 77.

    Ling HY, Wen GB, Feng SD, Tuo QH, Ou HS, Yao CH, Zhu BY, Gao ZP, Zhang L, Liao DF. MicroRNA-375 promotes 3T3-L1 adipocyte differentiation through modulation of extracellular signal-regulated kinase signalling. Clin Exp Pharmacol Physiol. 2011;38(4):239–46.

  78. 78.

    Novak J, Kruzliak P, Bienertova-Vasku J, Slaby O, Novak M. MicroRNA-206: a promising theranostic marker. Theranostics. 2014;4(2):119–33.

  79. 79.

    Walden TB, Timmons JA, Keller P, Nedergaard J, Cannon B. Distinct expression of muscle-specific microRNAs (myomirs) in brown adipocytes. J Cell Physiol. 2009;218(2):444–9.

  80. 80.

    Zhong D, Huang G, Zhang Y, Zeng Y, Xu Z, Zhao Y, He X, He F. MicroRNA-1 and microRNA-206 suppress LXRalpha-induced lipogenesis in hepatocytes. Cell Signal. 2013;25(6):1429–37.

  81. 81.

    Li G, Ning C, Ma Y, Jin L, Tang Q, Li X, Li M, Liu H: miR-26b promotes 3T3-L1 adipocyte differentiation through targeting PTEN. DNA Cell Biol 2017.

  82. 82.

    Ahn J, Lee H, Jung CH, Jeon TI, Ha TY. MicroRNA-146b promotes adipogenesis by suppressing the SIRT1-FOXO1 cascade. EMBO Mol Med. 2013;5(10):1602–12.

  83. 83.

    Jing E, Gesta S, Kahn CR. SIRT2 regulates adipocyte differentiation through FoxO1 acetylation/deacetylation. Cell Metab. 2007;6(2):105–14.

  84. 84.

    Trumbach D, Prakash N. The conserved miR-8/miR-200 microRNA family and their role in invertebrate and vertebrate neurogenesis. Cell Tissue Res. 2015;359(1):161–77.

  85. 85.

    Kennell JA, Gerin I, MacDougald OA, Cadigan KM. The microRNA miR-8 is a conserved negative regulator of Wnt signaling. Proc Natl Acad Sci U S A. 2008;105(40):15417–22.

  86. 86.

    Hyun S, Lee JH, Jin H, Nam J, Namkoong B, Lee G, Chung J, Kim VN. Conserved microRNA miR-8/miR-200 and its target USH/FOG2 control growth by regulating PI3K. Cell. 2009;139(6):1096–108.

  87. 87.

    Liang WC, Wang Y, Wan DC, Yeung VS, Waye MM. Characterization of miR-210 in 3T3-L1 adipogenesis. J Cell Biochem. 2013;114(12):2699–707.

  88. 88.

    Kim YJ, Hwang SJ, Bae YC, Jung JS. MiR-21 regulates adipogenic differentiation through the modulation of TGF-beta signaling in mesenchymal stem cells derived from human adipose tissue. Stem Cells. 2009;27(12):3093–102.

  89. 89.

    Ortega FJ, Moreno M, Mercader JM, Moreno-Navarrete JM, Fuentes-Batllevell N, Sabater M, Ricart W, Fernandez-Real JM. Inflammation triggers specific microRNA profiles in human adipocytes and macrophages and in their supernatants. Clin Epigenetics. 2015;7:49.

  90. 90.

    Karkeni E, Astier J, Tourniaire F, El Abed M, Romier B, Gouranton E, Wan L, Borel P, Salles J, Walrand S, et al. Obesity-associated inflammation induces microRNA-155 expression in adipocytes and adipose tissue: outcome on adipocyte function. J Clin Endocrinol Metab. 2016;101(4):1615–26.

  91. 91.

    Thomou T, Mori MA, Dreyfuss JM, Konishi M, Sakaguchi M, Wolfrum C, Rao TN, Winnay JN, Garcia-Martin R, Grinspoon SK, et al. Adipose-derived circulating miRNAs regulate gene expression in other tissues. Nature. 2017;542(7642):450–5.

  92. 92.

    Butler AE, Dhawan S. Beta-cell identity in type 2 diabetes: lost or found? Diabetes. 2015;64(8):2698–700.

  93. 93.

    Poy MN, Eliasson L, Krutzfeldt J, Kuwajima S, Ma X, Macdonald PE, Pfeffer S, Tuschl T, Rajewsky N, Rorsman P, et al. A pancreatic islet-specific microRNA regulates insulin secretion. Nature. 2004;432(7014):226–30.

  94. 94.

    van de Bunt M, Gaulton KJ, Parts L, Moran I, Johnson PR, Lindgren CM, Ferrer J, Gloyn AL, McCarthy MI. The miRNA profile of human pancreatic islets and beta-cells and relationship to type 2 diabetes pathogenesis. PLoS One. 2013;8(1):e55272.

  95. 95.

    Kaviani M, Azarpira N, Karimi MH, Al-Abdullah I. The role of microRNAs in islet beta-cell development. Cell Biol Int. 2016;40(12):1248–55.

  96. 96.

    Sebastiani G, Nigi L, Grieco GE, Mancarella F, Ventriglia G, Dotta F: Circulating microRNAs and diabetes mellitus: a novel tool for disease prediction, diagnosis, and staging? J Endocrinol Invest 2017.

  97. 97.

    Baroukh NN, Van Obberghen E. Function of microRNA-375 and microRNA-124a in pancreas and brain. FEBS J. 2009;276(22):6509–21.

  98. 98.

    Wei R, Yang J, Liu GQ, Gao MJ, Hou WF, Zhang L, Gao HW, Liu Y, Chen GA, Hong TP. Dynamic expression of microRNAs during the differentiation of human embryonic stem cells into insulin-producing cells. Gene. 2013;518(2):246–55.

  99. 99.

    Joglekar MV, Joglekar VM, Hardikar AA. Expression of islet-specific microRNAs during human pancreatic development. Gene Expr Patterns. 2009;9(2):109–13.

  100. 100.

    Avnit-Sagi T, Kantorovich L, Kredo-Russo S, Hornstein E, Walker MD. The promoter of the pri-miR-375 gene directs expression selectively to the endocrine pancreas. PLoS One. 2009;4(4):e5033.

  101. 101.

    Gu G, Dubauskaite J, Melton DA. Direct evidence for the pancreatic lineage: NGN3+ cells are islet progenitors and are distinct from duct progenitors. Development. 2002;129(10):2447–57.

  102. 102.

    El Ouaamari A, Baroukh N, Martens GA, Lebrun P, Pipeleers D, van Obberghen E. miR-375 targets 3′-phosphoinositide-dependent protein kinase-1 and regulates glucose-induced biological responses in pancreatic beta-cells. Diabetes. 2008;57(10):2708–17.

  103. 103.

    Kredo-Russo S, Mandelbaum AD, Ness A, Alon I, Lennox KA, Behlke MA, Hornstein E. Pancreas-enriched miRNA refines endocrine cell differentiation. Development. 2012;139(16):3021–31.

  104. 104.

    Martinez-Sanchez A, Rutter GA, Latreille M. MiRNAs in beta-cell development, identity, and disease. Front Genet. 2016;7:226.

  105. 105.

    Pullen TJ, da Silva XG, Kelsey G, Rutter GA. miR-29a and miR-29b contribute to pancreatic beta-cell-specific silencing of monocarboxylate transporter 1 (Mct1). Mol Cell Biol. 2011;31(15):3182–94.

  106. 106.

    Lovis P, Gattesco S, Regazzi R. Regulation of the expression of components of the exocytotic machinery of insulin-secreting cells by microRNAs. Biol Chem. 2008;389(3):305–12.

  107. 107.

    Ozcan S. Minireview: microRNA function in pancreatic beta cells. Mol Endocrinol. 2014;28(12):1922–33.

  108. 108.

    Plaisance V, Abderrahmani A, Perret-Menoud V, Jacquemin P, Lemaigre F, Regazzi R. MicroRNA-9 controls the expression of Granuphilin/Slp4 and the secretory response of insulin-producing cells. J Biol Chem. 2006;281(37):26932–42.

  109. 109.

    McCarthy JJ. The MyomiR network in skeletal muscle plasticity. Exerc Sport Sci Rev. 2011;39(3):150–4.

  110. 110.

    Kirby TJ, McCarthy JJ. MicroRNAs in skeletal muscle biology and exercise adaptation. Free Radic Biol Med. 2013;64:95–105.

  111. 111.

    Polakovicova M, Musil P, Laczo E, Hamar D, Kyselovic J: Circulating MicroRNAs as potential biomarkers of exercise response. Int J Mol Sci. 2016;17(10):1553.

  112. 112.

    Feng B, Chen S, George B, Feng Q, Chakrabarti S. miR133a regulates cardiomyocyte hypertrophy in diabetes. Diabetes Metab Res Rev. 2010;26(1):40–9.

  113. 113.

    Gomes CP, Oliveira-Jr GP, Madrid B, Almeida JA, Franco OL, Pereira RW. Circulating miR-1, miR-133a, and miR-206 levels are increased after a half-marathon run. Biomarkers. 2014;19(7):585–9.

  114. 114.

    Zhou Y, Gu P, Shi W, Li J, Hao Q, Cao X, Lu Q, Zeng Y. MicroRNA-29a induces insulin resistance by targeting PPARdelta in skeletal muscle cells. Int J Mol Med. 2016;37(4):931–8.

  115. 115.

    Pandey AK, Verma G, Vig S, Srivastava S, Srivastava AK, Datta M. miR-29a levels are elevated in the db/db mice liver and its overexpression leads to attenuation of insulin action on PEPCK gene expression in HepG2 cells. Mol Cell Endocrinol. 2011;332(1–2):125–33.

  116. 116.

    Yang WM, Jeong HJ, Park SY, Lee W. Induction of miR-29a by saturated fatty acids impairs insulin signaling and glucose uptake through translational repression of IRS-1 in myocytes. FEBS Lett. 2014;588(13):2170–6.

  117. 117.

    Zhang Y, Yang L, Gao YF, Fan ZM, Cai XY, Liu MY, Guo XR, Gao CL, Xia ZK. MicroRNA-106b induces mitochondrial dysfunction and insulin resistance in C2C12 myotubes by targeting mitofusin-2. Mol Cell Endocrinol. 2013;381(1–2):230–40.

  118. 118.

    Baskin KK, Grueter CE, Kusminski CM, Holland WL, Bookout AL, Satapati S, Kong YM, Burgess SC, Malloy CR, Scherer PE, et al. MED13-dependent signaling from the heart confers leanness by enhancing metabolism in adipose tissue and liver. EMBO Mol Med. 2014;6(12):1610–21.

  119. 119.

    Baskin KK, Winders BR, Olson EN. Muscle as a “mediator” of systemic metabolism. Cell Metab. 2015;21(2):237–48.

  120. 120.

    Grueter CE, van Rooij E, Johnson BA, DeLeon SM, Sutherland LB, Qi X, Gautron L, Elmquist JK, Bassel-Duby R, Olson EN. A cardiac microRNA governs systemic energy homeostasis by regulation of MED13. Cell. 2012;149(3):671–83.

  121. 121.

    Szabo G, Bala S. MicroRNAs in liver disease. Nat Rev Gastroenterol Hepatol. 2013;10(9):542–52.

  122. 122.

    Tsai WC, Hsu SD, Hsu CS, Lai TC, Chen SJ, Shen R, Huang Y, Chen HC, Lee CH, Tsai TF, et al. MicroRNA-122 plays a critical role in liver homeostasis and hepatocarcinogenesis. J Clin Invest. 2012;122(8):2884–97.

  123. 123.

    Burchard J, Zhang C, Liu AM, Poon RT, Lee NP, Wong KF, Sham PC, Lam BY, Ferguson MD, Tokiwa G, et al. microRNA-122 as a regulator of mitochondrial metabolic gene network in hepatocellular carcinoma. Mol Syst Biol. 2010;6:402.

  124. 124.

    Cheung O, Puri P, Eicken C, Contos MJ, Mirshahi F, Maher JW, Kellum JM, Min H, Luketic VA, Sanyal AJ. Nonalcoholic steatohepatitis is associated with altered hepatic microRNA expression. Hepatology. 2008;48(6):1810–20.

  125. 125.

    Esau C, Davis S, Murray SF, Yu XX, Pandey SK, Pear M, Watts L, Booten SL, Graham M, McKay R et al: miR-122 regulation of lipid metabolism revealed by in vivo antisense targeting. Cell Metab 2006, 3(2):87-98.

  126. 126.

    Elmen J, Lindow M, Schutz S, Lawrence M, Petri A, Obad S, Lindholm M, Hedtjarn M, Hansen HF, Berger U, et al. LNA-mediated microRNA silencing in non-human primates. Nature. 2008;452(7189):896–9.

  127. 127.

    Bandiera S, Pfeffer S, Baumert TF, Zeisel MB. miR-122—a key factor and therapeutic target in liver disease. J Hepatol. 2015;62(2):448–57.

  128. 128.

    Vickers KC, Shoucri BM, Levin MG, Wu H, Pearson DS, Osei-Hwedieh D, Collins FS, Remaley AT, Sethupathy P. MicroRNA-27b is a regulatory hub in lipid metabolism and is altered in dyslipidemia. Hepatology. 2013;57(2):533–42.

  129. 129.

    Lee J, Padhye A, Sharma A, Song G, Miao J, Mo YY, Wang L, Kemper JK. A pathway involving farnesoid X receptor and small heterodimer partner positively regulates hepatic sirtuin 1 levels via microRNA-34a inhibition. J Biol Chem. 2010;285(17):12604–11.

  130. 130.

    Iliopoulos D, Drosatos K, Hiyama Y, Goldberg IJ, Zannis VI. MicroRNA-370 controls the expression of microRNA-122 and Cpt1alpha and affects lipid metabolism. J Lipid Res. 2010;51(6):1513–23.

  131. 131.

    Goedeke L, Vales-Lara FM, Fenstermaker M, Cirera-Salinas D, Chamorro-Jorganes A, Ramirez CM, Mattison JA, de Cabo R, Suarez Y, Fernandez-Hernando C. A regulatory role for microRNA 33* in controlling lipid metabolism gene expression. Mol Cell Biol. 2013;33(11):2339–52.

  132. 132.

    Karunakaran D, Richards L, Geoffrion M, Barrette D, Gotfrit RJ, Harper ME, Rayner KJ. Therapeutic inhibition of miR-33 promotes fatty acid oxidation but does not ameliorate metabolic dysfunction in diet-induced obesity. Arterioscler Thromb Vasc Biol. 2015;35(12):2536–43.

  133. 133.

    Vickers KC, Landstreet SR, Levin MG, Shoucri BM, Toth CL, Taylor RC, Palmisano BT, Tabet F, Cui HL, Rye KA, et al. MicroRNA-223 coordinates cholesterol homeostasis. Proc Natl Acad Sci U S A. 2014;111(40):14518–23.

  134. 134.

    Fu X, Dong B, Tian Y, Lefebvre P, Meng Z, Wang X, Pattou F, Han W, Wang X, Lou F, et al. MicroRNA-26a regulates insulin sensitivity and metabolism of glucose and lipids. J Clin Invest. 2015;125(6):2497–509.

  135. 135.

    Trajkovski M, Hausser J, Soutschek J, Bhat B, Akin A, Zavolan M, Heim MH, Stoffel M. MicroRNAs 103 and 107 regulate insulin sensitivity. Nature. 2011;474(7353):649–53.

  136. 136.

    Zarfeshani A, Ngo S, Sheppard AM. MicroRNA expression relating to dietary-induced liver Steatosis and NASH. J Clin Med. 2015;4(11):1938–50.

  137. 137.

    Turchinovich A, Weiz L, Langheinz A, Burwinkel B. Characterization of extracellular circulating microRNA. Nucleic Acids Res. 2011;39(16):7223–33.

  138. 138.

    Cortez MA, Calin GA. MicroRNA identification in plasma and serum: a new tool to diagnose and monitor diseases. Expert Opin Biol Ther. 2009;9(6):703–11.

  139. 139.

    Kim YK. Extracellular microRNAs as biomarkers in human disease. Chonnam Med J. 2015;51(2):51–7.

  140. 140.

    Grasedieck S, Sorrentino A, Langer C, Buske C, Dohner H, Mertens D, Kuchenbauer F. Circulating microRNAs in hematological diseases: principles, challenges, and perspectives. Blood. 2013;121(25):4977–84.

  141. 141.

    Arroyo JD, Chevillet JR, Kroh EM, Ruf IK, Pritchard CC, Gibson DF, Mitchell PS, Bennett CF, Pogosova-Agadjanyan EL, Stirewalt DL, et al. Argonaute2 complexes carry a population of circulating microRNAs independent of vesicles in human plasma. Proc Natl Acad Sci U S A. 2011;108(12):5003–8.

  142. 142.

    Vickers KC, Palmisano BT, Shoucri BM, Shamburek RD, Remaley AT. MicroRNAs are transported in plasma and delivered to recipient cells by high-density lipoproteins. Nat Cell Biol. 2011;13(4):423–33.

  143. 143.

    Wang K, Zhang S, Weber J, Baxter D, Galas DJ. Export of microRNAs and microRNA-protective protein by mammalian cells. Nucleic Acids Res. 2010;38(20):7248–59.

  144. 144.

    Mittelbrunn M, Gutierrez-Vazquez C, Villarroya-Beltri C, Gonzalez S, Sanchez-Cabo F, Gonzalez MA, Bernad A, Sanchez-Madrid F. Unidirectional transfer of microRNA-loaded exosomes from T cells to antigen-presenting cells. Nat Commun. 2011;2:282.

  145. 145.

    Camussi G, Deregibus MC, Bruno S, Grange C, Fonsato V, Tetta C. Exosome/microvesicle-mediated epigenetic reprogramming of cells. Am J Cancer Res. 2011;1(1):98–110.

  146. 146.

    Weber JA, Baxter DH, Zhang S, Huang DY, Huang KH, Lee MJ, Galas DJ, Wang K. The microRNA spectrum in 12 body fluids. Clin Chem. 2010;56(11):1733–41.

  147. 147.

    Guay C, Regazzi R. Circulating microRNAs as novel biomarkers for diabetes mellitus. Nat Rev Endocrinol. 2013;9(9):513–21.

  148. 148.

    Zampetaki A, Kiechl S, Drozdov I, Willeit P, Mayr U, Prokopi M, Mayr A, Weger S, Oberhollenzer F, Bonora E, et al. Plasma microRNA profiling reveals loss of endothelial miR-126 and other microRNAs in type 2 diabetes. Circ Res. 2010;107(6):810–7.

  149. 149.

    Zhang T, Lv C, Li L, Chen S, Liu S, Wang C, Su B. Plasma miR-126 is a potential biomarker for early prediction of type 2 diabetes mellitus in susceptible individuals. Biomed Res Int. 2013;2013:761617.

  150. 150.

    Zile MR, Mehurg SM, Arroyo JE, Stroud RE, DeSantis SM, Spinale FG. Relationship between the temporal profile of plasma microRNA and left ventricular remodeling in patients after myocardial infarction. Circ Cardiovasc Genet. 2011;4(6):614–9.

  151. 151.

    Cermelli S, Ruggieri A, Marrero JA, Ioannou GN, Beretta L. Circulating microRNAs in patients with chronic hepatitis C and non-alcoholic fatty liver disease. PLoS One. 2011;6(8):e23937.

  152. 152.

    Li S, Zhu J, Zhang W, Chen Y, Zhang K, Popescu LM, Ma X, Lau WB, Rong R, Yu X, et al. Signature microRNA expression profile of essential hypertension and its novel link to human cytomegalovirus infection. Circulation. 2011;124(2):175–84.

  153. 153.

    Karolina DS, Tavintharan S, Armugam A, Sepramaniam S, Pek SL, Wong MT, Lim SC, Sum CF, Jeyaseelan K. Circulating miRNA profiles in patients with metabolic syndrome. J Clin Endocrinol Metab. 2012;97(12):E2271–6.

  154. 154.

    Deiuliis JA. MicroRNAs as regulators of metabolic disease: pathophysiologic significance and emerging role as biomarkers and therapeutics. Int J Obes. 2016;40(1):88–101.

  155. 155.

    Wang YT, Tsai PC, Liao YC, Hsu CY, Juo SH. Circulating microRNAs have a sex-specific association with metabolic syndrome. J Biomed Sci. 2013;20:72.

  156. 156.

    Hulsmans M, De Keyzer D, Holvoet P. MicroRNAs regulating oxidative stress and inflammation in relation to obesity and atherosclerosis. FASEB J. 2011;25(8):2515–27.

  157. 157.

    Heneghan HM, Miller N, McAnena OJ, O'Brien T, Kerin MJ. Differential miRNA expression in omental adipose tissue and in the circulation of obese patients identifies novel metabolic biomarkers. J Clin Endocrinol Metab. 2011;96(5):E846–50.

  158. 158.

    Carreras-Badosa G, Bonmati A, Ortega FJ, Mercader JM, Guindo-Martinez M, Torrents D, Prats-Puig A, Martinez-Calcerrada JM, Platero-Gutierrez E, De Zegher F, et al. Altered circulating miRNA expression profile in pregestational and gestational obesity. J Clin Endocrinol Metab. 2015;100(11):E1446–56.

  159. 159.

    Iacomino G, Russo P, Stillitano I, Lauria F, Marena P, Ahrens W, De Luca P, Siani A. Circulating microRNAs are deregulated in overweight/obese children: preliminary results of the I.Family study. Genes Nutr. 2016;11:7.

  160. 160.

    Can U, Buyukinan M, Yerlikaya FH. The investigation of circulating microRNAs associated with lipid metabolism in childhood obesity. Pediatr Obes. 2016;11(3):228–34.

  161. 161.

    Thompson MD, Cismowski MJ, Serpico M, Pusateri A, Brigstock DR: Elevation of circulating microRNA levels in obese children compared to healthy controls. Clin Obes 2017.

  162. 162.

    Christopher AF, Kaur RP, Kaur G, Kaur A, Gupta V, Bansal P. MicroRNA therapeutics: discovering novel targets and developing specific therapy. Perspect Clin Res. 2016;7(2):68–74.

  163. 163.

    Fischer-Posovszky P, Roos J, Kotnik P, Battelino T, Inzaghi E, Nobili V, Cianfarani S, Wabitsch M. Functional significance and predictive value of microRNAs in pediatric obesity: tiny molecules with huge impact? Horm Res Paediatr. 2016;86(1):3–10.

  164. 164.

    Jung UJ, Choi MS. Obesity and its metabolic complications: the role of adipokines and the relationship between obesity, inflammation, insulin resistance, dyslipidemia and nonalcoholic fatty liver disease. Int J Mol Sci. 2014;15(4):6184–223.

  165. 165.

    Wellen KE, Hotamisligil GS. Inflammation, stress, and diabetes. J Clin Invest. 2005;115(5):1111–9.

  166. 166.

    Kammoun HL, Kraakman MJ, Febbraio MA. Adipose tissue inflammation in glucose metabolism. Rev Endocr Metab Disord. 2014;15(1):31–44.

  167. 167.

    Kraakman MJ, Murphy AJ, Jandeleit-Dahm K, Kammoun HL. Macrophage polarization in obesity and type 2 diabetes: weighing down our understanding of macrophage function? Front Immunol. 2014;5:470.

  168. 168.

    Tang QQ, Lane MD. Adipogenesis: from stem cell to adipocyte. Annu Rev Biochem. 2012;81:715–36.

  169. 169.

    Kim H-J, Cho H, Alexander R, Patterson HC, Gu M, Lo KA, Xu D, Goh VJ, Nguyen LN, Chai X, et al. MicroRNAs are required for the feature maintenance and differentiation of brown adipocytes. Diabetes. 2014;63(12):4045–56.

  170. 170.

    Li J, Zhou C, Li J, Su Z, Sang H, Jia E, Si D. Global correlation analysis for microRNA and gene expression profiles in human obesity. Pathol Res Pract. 2015;211(5):361–8.

  171. 171.

    Rottiers V, Naar AM. MicroRNAs in metabolism and metabolic disorders. Nat Rev Mol Cell Biol. 2012;13(4):239–50.

  172. 172.

    Xie H, Lim B, Lodish HF. MicroRNAs induced during adipogenesis that accelerate fat cell development are downregulated in obesity. Diabetes. 2009;58(5):1050–7.

  173. 173.

    Ali AT, Hochfeld WE, Myburgh R, Pepper MS. Adipocyte and adipogenesis. Eur J Cell Biol. 2013;92(6–7):229–36.

  174. 174.

    Linhart HG, Ishimura-Oka K, DeMayo F, Kibe T, Repka D, Poindexter B, Bick RJ, Darlington GJ. C/EBPalpha is required for differentiation of white, but not brown, adipose tissue. Proc Natl Acad Sci U S A. 2001;98(22):12532–7.

  175. 175.

    Moseti D, Regassa A, Kim WK: Molecular regulation of adipogenesis and potential anti-adipogenic bioactive molecules. Int J Mol Sci. 2016;17(1):124.

  176. 176.

    Wang Q, Li YC, Wang J, Kong J, Qi Y, Quigg RJ, Li X. miR-17-92 cluster accelerates adipocyte differentiation by negatively regulating tumor-suppressor Rb2/p130. Proc Natl Acad Sci U S A. 2008;105(8):2889–94.

  177. 177.

    Song G, Xu G, Ji C, Shi C, Shen Y, Chen L, Zhu L, Yang L, Zhao Y, Guo X. The role of microRNA-26b in human adipocyte differentiation and proliferation. Gene. 2014;533(2):481–7.

  178. 178.

    Zaragosi LE, Wdziekonski B, Brigand KL, Villageois P, Mari B, Waldmann R, Dani C, Barbry P. Small RNA sequencing reveals miR-642a-3p as a novel adipocyte-specific microRNA and miR-30 as a key regulator of human adipogenesis. Genome Biol. 2011;12(7):R64.

  179. 179.

    Li M, Liu Z, Zhang Z, Liu G, Sun S, Sun C. miR-103 promotes 3T3-L1 cell adipogenesis through AKT/mTOR signal pathway with its target being MEF2D. Biol Chem. 2015;396(3):235–44.

  180. 180.

    Esau C, Kang X, Peralta E, Hanson E, Marcusson EG, Ravichandran LV, Sun Y, Koo S, Perera RJ, Jain R, et al. MicroRNA-143 regulates adipocyte differentiation. J Biol Chem. 2004;279(50):52361–5.

  181. 181.

    Chen L, Dai YM, Ji CB, Yang L, Shi CM, Xu GF, Pang LX, Huang FY, Zhang CM, Guo XR. MiR-146b is a regulator of human visceral preadipocyte proliferation and differentiation and its expression is altered in human obesity. Mol Cell Endocrinol. 2014;393(1–2):65–74.

  182. 182.

    Shi C, Zhang M, Tong M, Yang L, Pang L, Chen L, Xu G, Chi X, Hong Q, Ni Y, et al. miR-148a is associated with obesity and modulates adipocyte differentiation of mesenchymal stem cells through Wnt signaling. Sci Rep. 2015;5:9930.

  183. 183.

    Li H, Chen X, Guan L, Qi Q, Shu G, Jiang Q, Yuan L, Xi Q, Zhang Y. MiRNA-181a regulates adipogenesis by targeting tumor necrosis factor-alpha (TNF-alpha) in the porcine model. PLoS One. 2013;8(10):e71568.

  184. 184.

    Shi XE, Li YF, Jia L, Ji HL, Song ZY, Cheng J, Wu GF, Song CC, Zhang QL, Zhu JY, et al. MicroRNA-199a-5p affects porcine preadipocyte proliferation and differentiation. Int J Mol Sci. 2014;15(5):8526–38.

  185. 185.

    Huang J, Zhao L, Xing L, Chen D. MicroRNA-204 regulates Runx2 protein expression and mesenchymal progenitor cell differentiation. Stem Cells. 2010;28(2):357–64.

  186. 186.

    Hamam D, Ali D, Vishnubalaji R, Hamam R, Al-Nbaheen M, Chen L, Kassem M, Aldahmash A. Alajez NM: microRNA-320/RUNX2 axis regulates adipocytic differentiation of human mesenchymal (skeletal) stem cells. Cell Death Dis. 2014;5:e1499.

  187. 187.

    Bork S, Horn P, Castoldi M, Hellwig I, Ho AD, Wagner W. Adipogenic differentiation of human mesenchymal stromal cells is down-regulated by microRNA-369-5p and up-regulated by microRNA-371. J Cell Physiol. 2011;226(9):2226–34.

  188. 188.

    Gerin I, Bommer GT, McCoin CS, Sousa KM, Krishnan V, MacDougald OA. Roles for miRNA-378/378* in adipocyte gene expression and lipogenesis. Am J Physiol Endocrinol Metab. 2010;299(2):E198–206.

  189. 189.

    Zhang JF, Fu WM, He ML, Wang H, Wang WM, Yu SC, Bian XW, Zhou J, Lin MC, Lu G, et al. MiR-637 maintains the balance between adipocytes and osteoblasts by directly targeting Osterix. Mol Biol Cell. 2011;22(21):3955–61.

  190. 190.

    Andersen DC, Jensen CH, Schneider M, Nossent AY, Eskildsen T, Hansen JL, Teisner B, Sheikh SP. MicroRNA-15a fine-tunes the level of delta-like 1 homolog (DLK1) in proliferating 3T3-L1 preadipocytes. Exp Cell Res. 2010;316(10):1681–91.

  191. 191.

    Huang S, Wang S, Bian C, Yang Z, Zhou H, Zeng Y, Li H, Han Q, Zhao RC. Upregulation of miR-22 promotes osteogenic differentiation and inhibits adipogenic differentiation of human adipose tissue-derived mesenchymal stem cells by repressing HDAC6 protein expression. Stem Cells Dev. 2012;21(13):2531–40.

  192. 192.

    Tang YF, Zhang Y, Li XY, Li C, Tian W, Liu L. Expression of miR-31, miR-125b-5p, and miR-326 in the adipogenic differentiation process of adipose-derived stem cells. OMICS. 2009;13(4):331–6.

  193. 193.

    Taniguchi M, Nakajima I, Chikuni K, Kojima M, Awata T, Mikawa S. MicroRNA-33b downregulates the differentiation and development of porcine preadipocytes. Mol Biol Rep. 2014;41(2):1081–90.

  194. 194.

    Cioffi M, Vallespinos-Serrano M, Trabulo SM, Fernandez-Marcos PJ, Firment AN, Vazquez BN, Vieira CR, Mulero F, Camara JA, Cronin UP, et al. MiR-93 controls adiposity via inhibition of Sirt7 and Tbx3. Cell Rep. 2015;12(10):1594–605.

  195. 195.

    Ji HL, Song CC, Li YF, He JJ, Li YL, Zheng XL. Yang GS: miR-125a inhibits porcine preadipocytes differentiation by targeting ERRalpha. Mol Cell Biochem. 2014;395(1–2):155–65.

  196. 196.

    Yang Z, Bian C, Zhou H, Huang S, Wang S, Liao L, Zhao RC. MicroRNA hsa-miR-138 inhibits adipogenic differentiation of human adipose tissue-derived mesenchymal stem cells through adenovirus EID-1. Stem Cells Dev. 2011;20(2):259–67.

  197. 197.

    Guo Y, Chen Y, Zhang Y, Zhang Y, Chen L, Mo D. Up-regulated miR-145 expression inhibits porcine preadipocytes differentiation by targeting IRS1. Int J Biol Sci. 2012;8(10):1408–17.

  198. 198.

    Skarn M, Namlos HM, Noordhuis P, Wang MY, Meza-Zepeda LA, Myklebost O. Adipocyte differentiation of human bone marrow-derived stromal cells is modulated by microRNA-155, microRNA-221, and microRNA-222. Stem Cells Dev. 2012;21(6):873–83.

  199. 199.

    Belarbi Y, Mejhert N, Lorente-Cebrian S, Dahlman I, Arner P, Ryden M, Kulyte A. MicroRNA-193b controls adiponectin production in human white adipose tissue. J Clin Endocrinol Metab. 2015;100(8):E1084–8.

  200. 200.

    Jeong BC, Kang IH, Hwang YC, Kim SH, Koh JT. MicroRNA-194 reciprocally stimulates osteogenesis and inhibits adipogenesis via regulating COUP-TFII expression. Cell Death Dis. 2014;5:e1532.

  201. 201.

    Peng Y, Xiang H, Chen C, Zheng R, Chai J, Peng J, Jiang S. MiR-224 impairs adipocyte early differentiation and regulates fatty acid metabolism. Int J Biochem Cell Biol. 2013;45(8):1585–93.

  202. 202.

    Sun L, Xie H, Mori MA, Alexander R, Yuan B, Hattangadi SM, Liu Q, Kahn CR, Lodish HF. Mir193b-365 is essential for brown fat differentiation. Nat Cell Biol. 2011;13(8):958–65.

  203. 203.

    Kinoshita M, Ono K, Horie T, Nagao K, Nishi H, Kuwabara Y, Takanabe-Mori R, Hasegawa K, Kita T, Kimura T. Regulation of adipocyte differentiation by activation of serotonin (5-HT) receptors 5-HT2AR and 5-HT2CR and involvement of microRNA-448-mediated repression of KLF5. Mol Endocrinol. 2010;24(10):1978–87.

  204. 204.

    Chen H, Mo D, Li M, Zhang Y, Chen L, Zhang X, Li M, Zhou X, Chen Y. miR-709 inhibits 3T3-L1 cell differentiation by targeting GSK3beta of Wnt/beta-catenin signaling. Cell Signal. 2014;26(11):2583–9.

  205. 205.

    Chen J, Xu L, Hu Q, Yang S, Zhang B, Jiang H. MiR-17-5p as circulating biomarkers for the severity of coronary atherosclerosis in coronary artery disease. Int J Cardiol. 2015;197:123–4.

  206. 206.

    Rotllan N, Price N, Pati P, Goedeke L, Fernandez-Hernando C. microRNAs in lipoprotein metabolism and cardiometabolic disorders. Atherosclerosis. 2016;246:352–60.

  207. 207.

    Willeit P, Skroblin P, Moschen AR, Yin X, Kaudewitz D, Zampetaki A, Barwari T, Whitehead M, Ramirez CM, Goedeke L, et al. Circulating MicroRNA-122 is associated with the risk of new-onset metabolic syndrome and type 2 diabetes. Diabetes. 2017;66(2):347–57.

  208. 208.

    Pirola CJ, Fernandez Gianotti T, Castano GO, Mallardi P, San Martino J, Mora Gonzalez Lopez Ledesma M, Flichman D, Mirshahi F, Sanyal AJ, Sookoian S: Circulating microRNA signature in non-alcoholic fatty liver disease: from serum non-coding RNAs to liver histology and disease pathogenesis. Gut 2015, 64(5):800-812.

  209. 209.

    Marchand L, Jalabert A, Meugnier E, Van den Hende K, Fabien N, Nicolino M, Madec AM, Thivolet C, Rome S. miRNA-375 a sensor of glucotoxicity is altered in the serum of children with newly diagnosed type 1 diabetes. J Diabetes Res. 2016;2016:1869082.

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The authors are grateful to Dr. Paola Russo for hepful discussion and comments.


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  • Obesity
  • Metabolic disease
  • Disease biomarkers
  • miRNAs
  • microRNA