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Review

Malnutrition and Biomarkers: A Journey through Extracellular Vesicles

by
Herminia Mendivil-Alvarado
1,
Leopoldo Alberto Sosa-León
2,
Elizabeth Carvajal-Millan
3 and
Humberto Astiazaran-Garcia
1,4,*
1
Department of Nutrition, Research Center for Food and Development, CIAD, A.C., Hermosillo 83304, Mexico
2
Independent Researcher, Hermosillo 83304, Mexico
3
Biopolymers, Research Center for Food and Development, CIAD, A.C., Hermosillo 83304, Mexico
4
Department of Chemical and Biological Sciences, University of Sonora, Hermosillo 83000, Mexico
*
Author to whom correspondence should be addressed.
Nutrients 2022, 14(5), 1002; https://doi.org/10.3390/nu14051002
Submission received: 28 January 2022 / Revised: 24 February 2022 / Accepted: 25 February 2022 / Published: 27 February 2022
(This article belongs to the Section Nutrition and Metabolism)
Review Reports Versions Notes

Abstract

:
Extracellular vesicles (EVs) have been identified as active components in cellular communication, which are easily altered both morphologically and chemically by the cellular environment and metabolic state of the body. Due to this sensitivity to the conditions of the cellular microenvironment, EVs have been found to be associated with disease conditions, including those associated with obesity and undernutrition. The sensitivity that EVs show to changes in the cellular microenvironment could be a reflection of early cellular alterations related to conditions of malnutrition, which could eventually be used in the routine monitoring and control of diseases or complications associated with it. However, little is known about the influence of malnutrition alone; that is, without the influence of additional diseases on the heterogeneity and specific content of EVs. To date, studies in “apparently healthy” obese patients show that there are changes in the size, quantity, and content of EVs, as well as correlations with some metabolic parameters (glucose, insulin, and serum lipids) in comparison with non-obese individuals. In light of these changes, a direct participation of EVs in the development of metabolic and cardiovascular complications in obese subjects is thought to exist. However, the mechanisms through which this process might occur are not yet fully understood. The evidence on EVs in conditions of undernutrition is limited, but it suggests that EVs play a role in the maintenance of homeostasis and muscle repair. A better understanding of how EVs participate in or promote cellular signaling in malnutrition conditions could help in the development of new strategies to treat them and their comorbidities.

1. Introduction

The term malnutrition encompasses disorders associated with deficit or excess in the consumption of nutrients, which manifests in conditions such as undernutrition and excess weight (obesity), known as the double burden of malnutrition. The figures for malnutrition worldwide are alarming, and show that it affects children and adults alike. According to the World Health Organization, in 2014, there were approximately 462 million underweight adults. It has also been reported that global obesity prevalence has risen approximately 2 percentage points per decade since 1975 [1]. Worldwide, in 2016, 678 million adults were reported to have obesity [2], and it is proposed that this amount will increase to 1.12 billion obese individuals by 2030 [3].
Obesity is defined by the World Health Organization as excess body fat, using a body mass index (BMI) greater than or equal to 30 kg/m2 as a reference. The double burden of malnutrition causes health issues such as muscle wasting; the propensity to develop cardiovascular, chronic-degenerative diseases; and an increase in the incidence of infections, among other maladies, which affect the health status and quality of life of the sufferers.
Currently, anthropometric tools and indicators, biochemical parameters, and biomarkers are used to assess the nutritional status of the population, aiming at the timely detection of malnutrition in some of its forms [4]. Among these tools, the use of biomarkers of nutritional status stands out. Biomarkers are measurable parameters or molecules, that can be used to assess the stability or, alternatively, the degree of abnormality of a particular biological process, making it possible to detect or monitor the deterioration of health and, in some cases, nutritional alterations. However, the predictive power of traditional biomarkers used in the field of nutrition (e.g., plasma metabolites and/or body parameters) does not adequately reflect the nutritional status of the individual [5]. They are generally late in showing results of clinical value, because their quantification varies depending on the presence of disease, disease stage, pathological condition, or metabolic alteration [6]. Thus, the possibility of early detection of malnutrition conditions or complications associated with them is limited, which in turn increases the morbidity and mortality of sufferers. Given this, it is essential to go beyond specific metabolites and to explore new mechanisms of signaling and/or cellular communication [7].
In the last decade, the study of extracellular vesicles (EVs) has gained considerable interest due to the active role they play in cellular communication. It is known that EVs are particles released by cells into the extracellular space, and that both their release and content respond to the conditions surrounding the cellular microenvironment [8]. This response seems to be a highly calibrated one, such that it promises predictability of response in the event of alterations within the microenvironment surrounding the cells. This makes the study of EVs not only fascinating, but also relevant in that, precisely because of this predictability, it allows for the possibility for detectability and measurability, thereby helping to close the gap between the deterioration of health and time to detection. Henceforth, when we speak of the sensitivity of EVs, we are referring to this seemingly highly calibrated response, which is manifested with variations in the size, quantity, and content of EVs. Indeed, due to the response of EVs to situations of cellular stress, their use as potential biomarkers in some pathological conditions has been suggested, such as in neurodegenerative, cardiovascular, and chronic-degenerative diseases and some types of cancer [9,10,11,12].
Although the literature does show that there is an association between EVs and diseases or health complications associated with obesity and undernutrition, little is known about the influence of malnutrition alone (that is, without the influence of additional illnesses) on the heterogeneity and specific content of EVs. A better understanding of how EVs participate in or promote cellular signaling in situations of malnutrition could help in the development of new strategies to treat them and their comorbidities. With this in mind, the aim of this review is to examine the current research on the effect of malnutrition on EVs and the likely role of EVs in the development of comorbidities associated with undernutrition and obesity.
This review is divided into five sections. The first section deals with the basic general knowledge about EVs and their classification. The subsequent four sections examine the current evidence on the sensitivity of EVs to specific conditions of nutritional status: excess weight, adipose tissue, diet, weight loss, and undernutrition.

2. Definition and Biogenesis of Extracellular Vesicles

The study of EVs is broad and branches out into many areas such as renal diseases, cancer, and autoimmune and cardiac diseases. For a better understanding of this rapidly evolving and developing field of study, it is worth reviewing the theoretical bases about its biogenesis and classification that have so far been proposed, bearing in mind that little is known about the influence of nutritional status on the sensitivity of EVs.
It is well known that cells use different signals and vehicles to transmit information to other cells [13,14]. They expel cytoplasmic and membrane material through vesicles that, when found in the extracellular medium, are called EVs. The process of the production of EVs is carried out by most cells in the body and is a phenomenon that has been maintained throughout evolution, both in eukaryotic and prokaryotic organisms [15]. The International Society for Extracellular Vesicles (ISEV) proposed, as a generic concept, the term “extracellular vesicles” for all those particles delimited by a lipid bilayer, which are naturally released from the cell to the extracellular medium, with the characteristic that they cannot replicate nor have a nucleus [14].
At first, EVs were thought of as waste carriers only. It was not until 1987 that the first hypotheses about their existence as active components in cellular communication were raised [16]. Since then, research on EVs has increased, providing information about their components, possible biogenesis mechanism, and even their classification. More recently, a debate as to the most accurate classification of EVs subpopulations took place. As part of this debate, considerations regarding their content and morphometric characteristics were at issue, as questions were raised as to whether the mechanism of biogenesis and content of EVs were dependent on the type of cell that produced them. Faced with this problem, the ISEV proposed a series of guidelines regarding nomenclature, as well as the minimum requirements to define populations of EVs [14].
The classification of EVs is based on their biogenesis and size, broadly separates them into two groups, exosomes (50–150 nm) and microvesicles (<1000 nm), also known as small and medium EVs, respectively. However, the ISEV has encouraged caution when using the terms exosomes and microvesicles, as they could be confused with terms that were historically used to refer to something else, and might be contradictory and inaccurate when referring to concepts about EVs. Such is the case for small EVs, also known as exosomes, which should not be confused with the exosomal complex [14].

2.1. Exosomes

Exosomes represent a group of small vesicles with sizes ranging from 50 to 150 nm [14]. They can come from any type of cell, although initial investigations have suggested that they came from hematopoietic and dendritic cells [17,18,19].
Exosomes are initially generated within the lumen of endosomes as intraluminal vesicles (ILVs), and during their maturation they undergo a process to become late endosomes, also known as multivesicular bodies (MVBs). MVBs fuse their contents with the plasma membrane of the cell and are then expelled into the extracellular medium, by the cell, as EVs [16]. Some of the mechanisms through which this process takes place are still under study. However, within the main mechanisms involved, the endosomal transport sorting complex (ESCRT—endosomal sorting complexes required for transport) and its subcomplexes (ESCRT-0, -I, -II, and -III) are known to play a role in the sorting and conformation of multivesicular endosomes (an earlier form of MVBs), as well as in the secretion and excretion of exosomes [20,21,22]. Thus, the ESCRT complex, together with its four subcomplexes, represent an important step in the formation of exosomes. It has been shown in dendritic cells that the depletion in the formation of exosomes directly affects their production [22]. This mechanism does not seem to be the only one, however. The lipid microdomains in the plasma membrane, the activity of sphingomyelinase (nSMase) [23], the presence of flotiline [24], and the affinity of proteins associated with tetraspanins [25] have been shown to also be involved in the genesis of ILVs.
The presence and enrichment of proteins in the exosomes is varied and can include proteins involved in the process of biogenesis and/or vesicular traffic. These include the family of tetraspanins (CD81, CD63, CD82, and CD9), a group of transmembrane proteins that form complexes with each other, as well as with different transmembrane and cytosolic proteins [25,26,27,28]; associated proteins such as integrins and immunoglobulins; cytoskeleton proteins (tubulin and actin); ESCRT complex-related proteins (ALIX and TSG-101) [29,30]; and heat shock chaperone proteins (HSP70 and HSP90), which are found in most exosomes [31].
Exosome biogenesis is a complex process whose understanding is made more difficult by the fact that the regulation of each of the mechanisms hitherto described remains unknown; furthermore, the possibility that they could coexist in a given cell type also cannot be ruled out completely. Likewise, the targeting of these small vesicles is not fully understood, but to date, it is known that this could depend on their content, type of originating cell, mechanism of biogenesis, and/or the pathological situation of the cell [21]. Much work remains to be done to unravel the mechanisms of biogenesis and that of the targeting of exosomes.

2.2. Microvesicles

Microvesicles (MVs), also known as microparticles or ectosomes, are vesicles that measure from 100 to 1000nm [14]. They were originally considered tiny particles from platelets called “platelet dust/debris”, found in the plasma and serum [32]. Today, it is known that they come from different types of cells and are vesicles generated by direct sprouting of the plasma membrane, whose process involves the reorganization of actin and the subsequent detachment of the vesicle towards the cell exterior [14]. Although the biogenesis of MVs, as it relates to their release into the extracellular medium, is yet to be fully described, it is known that different mechanisms are required to integrate the rearrangement of lipids and membrane proteins to complete this process, including calcium-dependent and independent mechanisms [33].
The content of MVs can vary. However, within their components, lipids and proteins involved in their biogenesis can be found. An example of these is the group of RHO proteins (GTPases) and RHO (rock)-associated protein kinases. As for lipids, the most enriched in the MVs are different types of lipids/phospholipids, among them lysophosphatidylcholine, sphingolipids, ceramides, and cholesterol. The components of MVs, as well as their mechanisms of genesis and traffic, are still areas under study.
In general, the composition and specific markers of MVs and exosomes are different and depend on the biogenesis of each subpopulation and the type of cell from which they come. The use of membrane markers is one of the most used techniques to classify both MVs and exosomes. However, there are proteins or markers that are shared by both groups, which makes exact identification more difficult. In an attempt to standardize the classification and composition of specific markers, the ISEV has suggested minimum information for studies of EVs, considering the use of operational terms for EV subtypes to be referenced, including their physical characteristics (size and/or density) and chemical composition; a list of EV specific markers is also suggested [14]. Despite ISEV efforts, the characterization of these subpopulations remains a challenge.

3. Extracellular Vesicles and Excess Weight

Obesity, an excessive accumulation of body fat (BMI ≥ 30 kg/m2), adversely affects body function and favors the development of comorbidities, such as cardiovascular and metabolic diseases [34,35]. The early identification of these conditions is key to timely treatment. However, there are people with obesity who do not develop metabolic disorders and show apparent health, known as “metabolically healthy obese” (MHO) [36]. The situation of the MHO, however, does not preclude future deterioration of health. In fact, it is the MHO who present a higher cardiovascular risk, as alterations in communication at the cellular level continue to occur, even without the apparent changes traditional metabolic biomarkers [37,38,39,40,41]. Due to the sensitivity of EVs to situations of metabolic stress, recent studies conducted in animals and just a few in humans on the characteristics of EVs and excess weight have shown significant and interesting advances (Table 1). Even so, research on the use of EVs as potential biomarkers in situations of obesity remains limited.
Most of the studies on EVs have been conducted in murine models without metabolic complications; only a few have been carried out in obese subjects. In both, changes in the general characteristics of EVs, size, number, and content, e.g., nucleic acids (mRNA, miRNA, etc.), have been reported. Once these changes occur, they might be the subject of further changes, depending on the degree of obesity. Furthermore, some of these characteristics and the content of EVs have been positively correlated with indicators such as BMI and biomarkers such as glucose, insulin, and serum lipids [45,49,54,55,56,57], among others. This correlation has led some authors to suggest that the characteristics of EVs (level and size) are affected by the inflammatory microenvironment caused by obesity.
Studies in obese adults have found that the characteristics of EVs could depend on the level of development of obesity, but not on its associated metabolic complications [45]. Goichot, for example, reported that the increase in plasmatic EVs concentration in obese subjects could explain their higher risk of thrombotic complications [42]. Based on this, it has been suggested that endothelial and platelet-derived EVs could be involved in the pathogenesis of endothelial dysfunction in obesity. Additionally, the increase in the number and concentration of EVs has been correlated with the increase in the insulin resistance index (HOMA-IR) [43,49,52] and associated components in the insulin signaling pathway [53], as well as with high levels of triglycerides in blood and excess body fat [44,51]. Taken together, this research suggests that EVs could be involved in the development of metabolic complications, but more evidence is needed to reveal the cellular pathway by which these changes occur, which translate into metabolic alterations.
Despite the fact that most of the evidence to date suggests that EVs increase in number and size in many body fluids in obese people, there is one study that suggests otherwise. Santamaria et al. reported that miRNA cargo of plasma EVs are associated with obesity, as well as smaller sizes of EVs in obese women than in those with normal weight [52]. However, the number of small EVs isolated from obese and lean participants was found to be equivalent in obese and normal weight women [52]. It is not clear what explains these results, but Santamaria suggested that the significant differences in glucose parameters and increased fatness in obese women were responsible for the plasma EVs changes. In agreement with Santamaria et al., Durcin suggested that the production and expulsion of EVs occurs following exposure to different biological stimuli related to the chronic low-grade inflammation state associated with obesity [54].
So, the relationship that seems to exist between the characteristics of EVs and metabolic biomarkers suggests that EVs are also clear indicators of the development of metabolic disorders or diseases. This is promising for the study of EVs as biomarkers in excess weight morbidities. However, more research is needed in order to describe the specific role that EVs play in these pathological processes, as well as their subsequent validation as potential biomarkers in humans.

4. Extracellular Vesicles and Adipose Tissue

The study of EVs as potential biomarkers of alterations to nutritional status includes EVs from specific cells or tissues, such as endothelial, platelet, and adipose tissue [58,59].
It appears that alterations in the adipose tissue of MHO subjects have an influence on the characteristics of extracellular platelet and endothelial vesicles, which, in turn, seem to have an effect on the development of cardiovascular and metabolic diseases [45,47]. The reason for this, as has been explained, is that the adipose tissue of adults MHO secretes cytokines alter endothelial function and this, in turn, promotes the activation of the transcription factor NF-KB [60] and pro-inflammatory pathways. This mechanism has also been shown in murine models with hypertension [61,62,63,64]. Furthermore, it has been shown that the activation of NF-KB can also be stimulated by the EVs of macrophages [65] and adipocytes [50], which induce abnormalities in the glucose−insulin balance. The insulin-dependent decrease in glucose assimilation has been reported to be due to the inhibition, at least in part, of Akt phosphorylation [46,48], which in turn interferes with the translocation of GLUT-4 in adipocytes. Given this, it has been proposed that the decrease in insulin-stimulated glucose absorption is mediated by the activation of NF-KB induced by EVs [50]. However, this is just a small part of the role that EVs play in the main metabolic pathways involved in the development of comorbidities of obesity, such as insulin resistance.
Studies using adipose tissue explants (from obese adults) have shown changes in the expression of key proteins in signaling pathways, such as TFG-B, which is involved in the development of fibrosis in various processes of chronic inflammation, especially in the liver [48]. Koeck et al. reported that EVs from adipose tissue could play an important role in the pathogenesis and development of nonalcoholic fatty liver, commonly present in obesity [48]. Moreover, Eguchi et al. suggested that EVs from adipose tissue induce the recruitment and migration of macrophages, associated with obesity [57]. Furthermore, different EVs subpopulations (large and small), which differ in their lipid and protein content and that could be responsible for the inflammatory and metabolic alterations typical of obesity, have been found [54,66,67,68]. The mechanisms by which the content of EVs triggers any particular metabolic alteration, however, are not fully understood.

5. Extracellular Vesicles, Diet and Weight Loss

It is known that EVs are sensitive to many cellular stress situations, including sensitivity to nutrient deficiencies. Crewe et al. propose that EVs contain and transport proteins and lipids capable of modulating cellular signaling pathways between endothelial cells and adipocytes [69]. This transport event, which is made necessary in situations of fasting, refeeding, and obesity, is likely to be physiologically regulated so that EVs may participate in the tissue response to changes in the concentration of nutrients in the organism [69]. Thus, EVs could also be involved in the communication between adipose tissue and other cells. Gao et al. proposed that this involvement occurs as a means of communication between adipocytes and neurons [70]. This communication could modulate signaling pathways in the hypothalamus, which regulate appetite and weight gain.
A high-fat diet has been shown to cause morphometric changes (size) in EVs [56,71]. In addition, a high fat diet has been shown to cause changes in the expression of specific miRNAs contained in the EVs of hepatocytes, which, in turn, modulate the expression of various genes in other organs, such as the pancreas, causing hyperplasia in its islets [72]. Qi Fu et al. suggested that these changes caused by hepatocyte-derived EVs may be a compensatory measure of the B cells of the pancreatic islets under conditions of obesity and insulin resistance [72]. The sensitivity of EVs to insulin has also been shown by Eichner et al., who reported that, in humans, after receiving a glucose load, their levels of circulating EVs in the plasma decrease, and that this reduction could be associated with arterial stiffness, physical exercise, and insulin sensitivity [73]. Taking this research as a whole, it suggests that EVs are sensitive to specific modification of lipids and glucose in the diet. It is conceivable that, in humans without metabolic complications, EVs are also sensitive to the modifications of macronutrients, but research is needed to prove this.
Diet modification in obese subjects is a therapeutic tool for weight loss and improvements in metabolic biomarkers [74,75]. The evidence suggests that changes in the levels of EVs in the event of weight loss depend on the amount of weight lost and the degree of excess weight [62]. In adults with a BMI >35 kg/m2, weight loss of >25% does not show significant differences in the amount of EVs before and after weight loss [76]. In contrast, when compared to a control group, adults with an average BMI of 26 kg/m2 that presented weight losses of 5% had a significant decrease in the level of plasma EVs [44,75]. In addition, comparisons made between an excess vs. a normal weight group have shown a distinct EVs composition in the case of excess weight; in particular, differences in the profiles of proteins and nucleic acids (mainly miRNAS) involved in the development of cardiovascular diseases and diabetes [77,78,79].
The composition of EVs is known to be affected by changes in body weight, diet, and after bariatric surgery. Thrush reviewed the little information available on the changes in the characteristics of EVs that occur in successful- and unsuccessfully-treated subjects [80]. He reported that the EVs of obese patients that successfully respond to dietary treatment and weight loss stimulate oxidative metabolism in muscle cells to a greater extent than the EVs of obese patients resistant to treatment and weight loss [80]. This could help explain the variability that exists in response to dietary treatment and weight loss in obese subjects, but more evidence is needed to evaluate potential therapeutic goals to promote an appropriate dietary strategy for unsuccessfully treated patients.
Research has shown that the concentration and composition of EVs could change after bariatric surgery [47,81,82]. The physiological changes that occur after bariatric surgery also seems to bring about the modification of specific markers contained in EVs, which are implicated in the development of some alterations in adipose tissue, such as the free fatty acid transporter protein (FABP4) [82]. Given that FABP4 is mainly expressed in adipocytes, its changes in EVs after this surgical procedure could reflect the changes that occur in the adipose tissue, such as a reduction of adipocytes and of the total fat mass [82].
Although it is known that EVs are particularly sensitive to the early development of metabolic and cardiovascular disorders, the physiological role that they play in the pathogenesis of these disorders needs to be better understood so that they can eventually be used as biomarkers of these conditions, even before the first symptoms appear. Furthermore, more research is needed to validate their use in a clinical setting.

6. Extracellular Vesicles in Undernutrition

To date, the evidence pertaining to EVs in situations of undernutrition is limited and most of it has been developed in murine models or in vitro studies. For this reason, the available evidence on EVs and muscle depletion will be considered as a means to understand their possible involvement in undernutrition.
The skeletal muscle is one of the largest organ systems in the human body, representing ~40% of the body weight of an average adult. It plays a major role in maintaining homeostasis [4,83]. For instance, muscle mass plays an important role in the storage of glucose and amino acids, which are used by the body in stress or fasting situations, providing the backbone for the liver and gluconeogenesis process. Likewise, it plays an important role in the development of insulin resistance and other metabolic diseases [84]. However, there are situations that can affect the muscle mass composition and size, such as physical activity, chronic inflammation, sarcopenia, and malnutrition [83,85,86].
The communication between the muscle and other tissues such as adipose tissue, liver, and pancreas, is carried out through the release of myokines, “cytokines or peptides which are secreted by skeletal muscle cells and subsequently released into the circulation to exert endocrine or paracrine effects in other cells, tissues or organs” [87]. Researchers studying the transport mechanisms used by myokines to reach the bloodstream have suggested that they are transported by EVs [88]. This makes sense, as it is known that the muscle, like any other tissue in the body, releases EVs in the course of pathological conditions such as cancer [89], HIV [90], heart attacks [91], and kidney disease [92], or due to specific stimulus such as exercise [93]. Some authors have even suggested that the beneficial health effects that occur as a result of exercising are due to the content of myokines and miRNAs, among others, which are produced by muscle cells and transported via EVs [94,95]. Others have suggested that most of the circulating EVs during exercise are released by the muscle tissue, as it is the organ with the highest secretory activity [93,96,97]. The mechanisms for this process have not yet been fully understood. However, we could assume that the secretory activity of the muscle is not only reflected in the response to a specific physical activity, but also in response to another type of stimuli or condition that directly affects the proper functioning of muscle mass.
Based on the evidence that the muscle is responsible for the release of EVs during exercise, we could assume that this same process is replicated in other circumstances where the muscle is affected—among them, muscle loss in situations of undernutrition. Muscle mass is lost in undernourished adults in response to a deficient consumption of protein and to inflammatory response caused by pathological processes, which could manifest chronically or acutely [98]. The degree of inflammation is a key factor in the development and severity of undernutrition, including the development of extreme undernutrition (cachexia) [99]. Cachexia typically occurs in response to affections such as cancer, infectious diseases, or some autoimmune disorders [100]. Consequently, it leads to a greater propensity to develop infections, to a diminished response to pharmacological treatments, and to higher mortality [101].
The evidence on EVs and muscle wasting shows that these play a role in the development of cancer cachexia [102,103]. It has been proposed that the communication between cancer cells and other organs and tissues can cause an endocrine effect on muscle tissue. A mechanism has also been proposed in which EVs participate in muscle wasting, whereby the EVs content of HSP70/90 heat shock proteins activate, at the membrane level, the signaling pathway by TLR-4, which, in turn, triggers the degradation of regulatory and myofibrillar proteins [103]. It has also been hypothesized that the miRNA content in EVs promote myoblast death in murine cancer models via the TLR7 pathway [102]. Furthermore, various miRNAs in EVs, which are probably involved in the development of cachexia, have been identified and shown to participate in altering the signaling pathways that induce muscular apoptosis or dystrophy of this tissue [104,105], although the circulating levels of EVs with miRNAs are mainly attributed to the proliferation and communication of cancer cells and not specifically to muscle wasting. The identification of changes in EVs (content and composition) in neoplastic cachexia could potentially be a marker of muscle loss and wasting. Given this sensitivity of the EVs to this condition, which results in muscle loss and wasting, it could be hypothesized that undernutrition, free of cancer, could also bring about changes in EVs, which in turn could cause the muscle waste that typically accompanies undernutrition. To date, little is known about the changes in the size, characteristics, and content of EVs in undernutrition status when free of any disease.
Given the evidence that muscle is one of the most active tissues in releasing EVs into the blood stream during exercise and that inflammatory processes (e.g., cancer) affect the content of EVs, one could assume that the typical malnutrition abnormalities occur in response to the transport of proteins and of different nucleic acids transported by EVs. Thus, EVs could be responsible for or initiators of the typical muscle depletion observed in conditions of undernutrition. However, to our knowledge, there is no study that has tested this theory. Although much remains unknown about the physiological mechanisms that EVs follow in situations of undernutrition, if our theory is correct, the content and characteristics of EVs could serve as an early risk marker of muscle depletion in situations without associated comorbidities; for example, this could apply to patients with anorexia nervosa, as well as those undergoing muscle mass loss due to natural physiological changes associated with ageing, or due to lack of protein consumption for those with food insecurity. If EVs could be used as biomarkers of early risk of undernutrition, this would also contribute to the development of new therapeutic strategies for the prompt treatment of muscle depletion, which is a feature of this nutritional status. This is important, as current biomarkers only detect the condition in advanced stages.

7. Conclusions

The sensitivity of EVs to the cellular microenvironment could reflect early cellular alterations related to conditions of malnutrition (undernutrition and obesity). Despite the limited research to date on EVs in the area of nutrition, research in this area is increasing and could herald the discovery of mechanisms involved in the development of malnutrition and its pathological complications. This may lead to a better understanding of how EVs participate in or promote cellular signaling in malnutrition situations, which could help in the development of new strategies to treat them and their comorbidities. Thus, EVs could come to be excellent future biomarkers of early conditions associated with malnutrition and help to close the gap between the deterioration of health and time to detection. Of course, the use of EVs as biomarkers would not substitute the use of current ones. Rather, their use seeks a greater understanding of the physiological changes that occur prior to the development of health complications associated with malnutrition. This could also lead to them being used as a routine diagnostic tool in the future.

Author Contributions

Conceptualization and writing—original draft preparation, H.M.-A.; writing—review and editing, L.A.S.-L.; review and editing, supervision, and approval of the final draft, H.A.-G.; supervision, E.C.-M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Acknowledgments

Supported by a fellowship from the National Research and Technology Council (CONACYT), Mexico (for HM-A).

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Bentham, J.; Di Cesare, M.; Bilano, V.; Bixby, H.; Zhou, B.; Stevens, G.A.; Riley, L.M.; Taddei, C.; Hajifathalian, K.; Lu, Y.; et al. Worldwide Trends in Body-Mass Index, Underweight, Overweight, and Obesity from 1975 to 2016: A Pooled Analysis of 2416 Population-Based Measurement Studies in 128·9 Million Children, Adolescents, and Adults. Lancet 2017, 390, 2627–2642. [Google Scholar] [CrossRef] [Green Version]
  2. Fanzo, J.; Hawkes, C.; Emorn Afshin, A.; Allemandi, L.; Assery, O.; Baker, P.; Battersby, J.; Bhutta, Z.; Chen, K.; Corvalan, C.; et al. Global Nutrition Report; Technical Report; Development Initiatives: Bristol, UK, December 2018. [Google Scholar]
  3. Kelly, T.; Yang, W.; Chen, C.S.; Reynolds, K.; He, J. Global Burden of Obesity in 2005 and Projections to 2030. Int. J. Obes. 2008, 32, 1431–1437. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Gibson, R. Principles of Nutritional Assessment, 2th ed.; Oxford University Press: New York, NY, USA, 2005. [Google Scholar]
  5. Raiten, D.J.; Namasté, S.; Brabin, B.; Combs, G.; L’Abbe, M.R.; Wasantwisut, E.; Darnton-Hill, I. Executive Summary—Biomarkers of Nutrition for Development: Building a Consensus. Am. J. Clin. Nutr. 2011, 94, 633S–650S. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Poste, G. Bring on the Biomarkers. Nature 2011, 469, 156–157. [Google Scholar] [CrossRef] [PubMed]
  7. Jain, K.K. The Handbook of Biomarkers; Springer Nature: Berlin, Germany, 2010. [Google Scholar] [CrossRef]
  8. Oliveira Rodríguez, M.; Serrano Pertierra, E.; García Costa, A.; Soraya López, M.; Yáñez Mo, M.; Cernuda Morollón, E.; Blanco López, M.C. Point of Care Detection of Extracellular Vesicles: Sensitivity Optimization and Multiple Target Detection. Biosens. Bioelectron. 2017, 87, 38–45. [Google Scholar] [CrossRef]
  9. Dimassi, S.; Karkeni, E.; Laurant, P.; Tabka, Z.; Landrier, J.F.; Riva, C. Microparticle MiRNAs as Biomarkers of Vascular Function and Inflammation Response to Aerobic Exercise in Obesity? Obesity 2018, 26, 1584–1593. [Google Scholar] [CrossRef] [Green Version]
  10. Holvoet, P.; Vanhaverbeke, M.; Bloch, K.; Baatsen, P.; Sinnaeve, P.; Janssens, S. Low MT-CO1 in Monocytes and Microvesicles Is Associated with Outcome in Patients with Coronary Artery Disease. J. Am. Heart Assoc. 2016, 5, e004207. [Google Scholar] [CrossRef]
  11. Hu, W.; Ru, Z.; Zhou, Y.; Xiao, W.; Sun, R.; Zhang, S.; Gao, Y.; Li, X.; Zhang, X.; Yang, H. Lung Cancer-Derived Extracellular Vesicles Induced Myotube Atrophy and Adipocyte Lipolysis via the Extracellular IL-6-Mediated STAT3 Pathway. Biochim. Biophys. Acta Mol. Cell Biol. Lipids 2019, 1864, 1091–1102. [Google Scholar] [CrossRef]
  12. Eitan, E.; Tosti, V.; Suire, C.N.; Cava, E.; Berkowitz, S.; Bertozzi, B.; Raefsky, S.M.; Veronese, N.; Spangler, R.; Spelta, F.; et al. In a Randomized Trial in Prostate Cancer Patients, Dietary Protein Restriction Modifies Markers of Leptin and Insulin Signaling in Plasma Extracellular Vesicles. Aging Cell 2017, 16, 1430–1433. [Google Scholar] [CrossRef] [Green Version]
  13. Turturici, G.; Tinnirello, R.; Sconzo, G.; Geraci, F. Extracellular Membrane Vesicles as a Mechanism of Cell-to-Cell Communication: Advantages and Disadvantages. Am. J. Physiol. Cell Physiol. 2014, 306, C621–C633. [Google Scholar] [CrossRef] [Green Version]
  14. Théry, C.; Witwer, K.W.; Aikawa, E.; Alcaraz, M.J.; Anderson, J.D.; Andriantsitohaina, R.; Antoniou, A.; Arab, T.; Archer, F.; Atkin-Smith, G.K.; et al. Minimal Information for Studies of Extracellular Vesicles 2018 (MISEV2018): A Position Statement of the International Society for Extracellular Vesicles and Update of the MISEV2014 Guidelines. J. Extracell. Vesicles 2018, 7, 1535750. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Deatheragea, B.L.; Cooksona, B.T. Membrane Vesicle Release in Bacteria, Eukaryotes, and Archaea: A Conserved yet Underappreciated Aspect of Microbial Life. Infect. Immun. 2012, 80, 1948–1957. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  16. Johnstone, R.M.; Adam, M.; Hammonds, J.R.; Turbide, C. Vesicle Formation during Reticulocyte Maturation. J. Biol. Chem. 1987, 262, 9412–9420. [Google Scholar] [CrossRef]
  17. Harding, C.; Heuser, J.; Stahl, P. Endocytosis and Intracellular Processing of Transferrin and Colloidalgold Transferrin in Rat Reticulocytes: Demonstration. Eur. J. Cell Biol. 1984, 35, 256–263. [Google Scholar] [PubMed]
  18. Théry, C.; Regnault, A.; Garin, J.; Wolfers, J.; Zitvogel, L.; Ricciardi-Castagnoli, P.; Raposo, G.; Amigorena, S. Molecular Characterization of Dendritic Cell-Derived Exosomes. J. Cell Biol. 1999, 147, 599–610. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  19. Zitvogel, L.; Regnault, A.; Lozier, A.; Wolfers, J.; Flament, C.; Tenza, D.; Ricciardi-Castagnoli, P.; Raposo, G.; Amigorena, S. Eradication of Established Murine Tumors Using a Novel Cell-Free Vaccine: Dendritic Cell-Derived Exoomes. Nat. Med. 1998, 4, 594–600. [Google Scholar] [CrossRef] [PubMed]
  20. Hurley, J.H. ESCRT s Are Everywhere. EMBO J. 2015, 34, 2398–2407. [Google Scholar] [CrossRef] [Green Version]
  21. Van Niel, G.; D’Angelo, G.; Raposo, G. Shedding Light on the Cell Biology of Extracellular Vesicles. Nat. Rev. Mol. Cell Biol. 2018, 19, 213–228. [Google Scholar] [CrossRef]
  22. Tamai, K.; Tanaka, N.; Nakano, T.; Kakazu, E.; Kondo, Y.; Inoue, J.; Shiina, M.; Fukushima, K.; Hoshino, T.; Sano, K. Exosome Secretion of Dendritic Cells Is Regulated by Hrs, an ESCRT-0 Protein. Biochem. Biophys. Res. Commun. 2010, 399, 384–390. [Google Scholar] [CrossRef]
  23. Yuyama, K.; Sun, H.; Mitsutake, S. Sphingolipid-Modulated Exosome Secretion Promotes Clearance of Amyloid-B by Microglia. J. Biol. Chem. 2012, 287, 10977–10989. [Google Scholar] [CrossRef] [Green Version]
  24. Strauss, K.; Goebel, C.; Runz, H.; Mobius, W.; Weiss, S.; Feussner, I.; Simons, M.; Anja, S. Exosome Secretion Ameliorates Lysosomal Storage of Cholesterol in Niemann-Pick Type C Disease. J. Biol. Chem. 2010, 285, 26279–26288. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Ghossoub, R.; Chéry, M.; Audebert, S.; Leblanc, R.; Egea-jimenez, A.L. Tetraspanin-6 Negatively Regulates Exosome Production. Proc. Natl. Acad. Sci. USA 2020, 117, 5913–5922. [Google Scholar] [CrossRef] [PubMed]
  26. Rana, S.; Yue, S.; Stadel, D.; Zöller, M. Toward Tailored Exosomes : The Exosomal Tetraspanin Web Contributes to Target Cell Selection. Int. J. Biochem. Cell Biol. 2012, 44, 1574–1584. [Google Scholar] [CrossRef] [PubMed]
  27. Charrin, S.; Jouannet, S.; Boucheix, C.; Rubinstein, E. Tetraspanins at a Glance. J. Cell Sci. 2014, 127, 3641–3648. [Google Scholar] [CrossRef] [Green Version]
  28. Escola, J.; Kleijmeer, M.J.; Stoorvogel, W.; Griffith, J.M.; Yoshie, O.; Geuze, H.J. Selective Enrichment of Tetraspan Proteins on the Internal Vesicles of Multivesicular Endosomes and on Exosomes Secreted by Human B-Lymphocytes. J. Biol. 1998, 273, 20121–20127. [Google Scholar] [CrossRef] [Green Version]
  29. Razi, M.; Futter, E. Distinct Roles for TSG101 and Hrs in Multivesicular Body Formation and Inward Vesiculation. Mol. Biol. Cell 2006, 17, 3469–3483. [Google Scholar] [CrossRef] [Green Version]
  30. Colombo, M.; Moita, C.; Van Niel, G.; Kowal, J.; Vigneron, J. Analysis of ESCRT Functions in Exosome Biogenesis, Composition and Secretion Highlights the Heterogeneity of Extracellular Vesicles. J. Cell Sci. 2011, 126, 5553–5565. [Google Scholar] [CrossRef] [Green Version]
  31. Théry, C.; Boussac, M.; Véron, P.; Raposo, G.; Garin, J.; Amigorena, S. Proteomic Analysis of Dendritic Cell-Derived Exosomes: A Secreted Subcellular Compartment Distinct from Apoptotic Vesicles. J. Immunol. 2001, 166, 7309–7319. [Google Scholar] [CrossRef] [Green Version]
  32. Wolf, P. The Nature and Significance of Platelet Products in Human Plasma. Br. J. Haematol. 1967, 13, 269–288. [Google Scholar] [CrossRef]
  33. Sedgwick, A.E.; D’Souza-Sschorey, C. The Biology of Extracellular Microvesicles. Traffic 2018, 19, 319–327. [Google Scholar] [CrossRef]
  34. Gotthelf, S.J. Prevalencia de Síndrome Metabólico Según Definición de La International Diabetes Federation (IDF) En Adolescentes Escolarizados de La Provincia de Salta, Argentina. Rev. Fed. Argent. Cardiol. 2013, 42, 119–126. [Google Scholar]
  35. Hernández Murúa, J.; Salazar Landeros, M.; Salazar, C.; Gómez Figueroa, J.; Ortiz Bojórquez, C.; De Souza Teixeira, F.; de Paz Fernández, J. Influencia Del Estilo de Vida y La Funcionalidad Sobre La Calidad de Vida Relacionada Con La Salud En Población Mexicana Con Salud Comprometida. Educ. Física Y Cienc. 2015, 17, 1–11. Available online: https://www.redalyc.org/articulo.oa?id=439942661005 (accessed on 10 January 2022).
  36. Achilike, I.; Hazuda, H.P.; Fowler, S.P.; Aung, K.; Lorenzo, C. Predicting the Development of the Metabolically Healthy Obese Phenotype. Int. J. Obes. 2015, 39, 228–234. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  37. Alcocer, L.A.; Lozada, O.; Fanghänel, G.; Sánchez Reyes, L.; Campos Franco, E. Estratificación Del Riesgo Cardiovascular Global. Comparación de Los Métodos Framingham y SCORE En Población Mexicana Del Estudio PRIT. Cirugía Y Cir. 2011, 79, 168–174. [Google Scholar]
  38. Xu, Y.; Li, H.; Wang, A.; Su, Z.; Yang, G.; Luo, Y.; Tao, L.; Chen, S.; Wu, S.; Wang, Y.; et al. Association between the Metabolically Healthy Obese Phenotype and the Risk of Myocardial Infarction: Results from the Kailuan Study. Eur. J. Endocrinol. 2018, 179, 343–352. [Google Scholar] [CrossRef] [Green Version]
  39. Twig, G.; Gerstein, H.C.; Shor, D.B.A.; Derazne, E.; Tzur, D.; Afek, A.; Tirosh, A. Coronary Artery Disease Risk among Obese Metabolically Healthy Young Men. Eur. J. Endocrinol. 2015, 173, 305–312. [Google Scholar] [CrossRef] [Green Version]
  40. Aguilar-Salinas, C.A.; García, E.; Robles, L.; Riaño, D.; Ruiz-Gomez, D.G.; García-Ulloa, A.C.; Melgarejo, M.A.; Zamora, M.; Guillen-Pineda, L.E.; Mehta, R.; et al. High Adiponectin Concentrations Are Associated with the Metabolically Healthy Obese Phenotype. J. Clin. Endocrinol. Metab. 2008, 93, 4075–4079. [Google Scholar] [CrossRef] [PubMed]
  41. Togliatto, G.; Dentelli, P.; Gili, M.; Gallo, S.; Deregibus, C.; Biglieri, E.; Iavello, A.; Santini, E.; Rossi, C.; Solini, A.; et al. Obesity Reduces the Pro-Angiogenic Potential of Adipose Tissue Stem Cell-Derived Extracellular Vesicles (EVs) by Impairing MiR-126 Content: Impact on Clinical Applications. Int. J. Obes. 2016, 40, 102–111. [Google Scholar] [CrossRef] [Green Version]
  42. Goichot, B.; Grunebaum, L.; Desprez, D.; Vinzio, S.; Meyer, L.; Schlienger, J.L.; Lessard, M.; Simon, C. Circulating Procoagulant Microparticles in Obesity. Diabetes Metab. 2006, 32, 82–85. [Google Scholar] [CrossRef]
  43. Esposito, K.; Ciotola, M.; Schisano, B.; Gualdiero, R.; Sardelli, L.; Misso, L.; Giannetti, G.; Giugliano, D. Endothelial Microparticles Correlate with Endothelial Dysfunction in Obese Women. J. Clin. Endocrinol. Metab. 2006, 91, 3676–3679. [Google Scholar] [CrossRef] [Green Version]
  44. Murakami, T.; Horigome, H.; Tanaka, K.; Nakata, Y.; Ohkawara, K.; Katayama, Y.; Matsui, A. Impact of Weight Reduction on Production of Platelet-Derived Microparticles and Fibrinolytic Parameters in Obesity. Thromb. Res. 2007, 119, 45–53. [Google Scholar] [CrossRef] [PubMed]
  45. Stepanian, A.; Bourguignat, L.; Hennou, S.; Coupaye, M.; Hajage, D.; Salomon, L.; Alessi, M.-C.; Msika, S.; de Prost, D. Microparticle Increase in Severe Obesity: Not Related to Metabolic Syndrome and Unchanged after Massive Weight Loss. Obesity 2013, 21, 2236–2243. [Google Scholar] [CrossRef] [PubMed]
  46. Kranendonk, E.G.; Visseren, F.L.J.; Van Herwaarden, J.A.; Hoen, E.N.M.N.; De Jager, W. Effect of Extracellular Vesicles of Human Adipose Tissue on Insulin Signaling in Liver and Muscle Cells. Obesity 2014, 22, 2216–2223. [Google Scholar] [CrossRef] [PubMed]
  47. Campello, E.; Zabeo, E.; Radu, C.M.; Spiezia, L.; Foletto, M.; Prevedello, L.; Gavasso, S.; Bulato, C.; Vettor, R.; Simioni, P. Dynamics of Circulating Microparticles in Obesity after Weight Loss. Intern. Emerg. Med. 2016, 11, 695–702. [Google Scholar] [CrossRef]
  48. Koeck, E.S.; Iordanskaia, T.; Sevilla, S.; Ferrante, S.C.; Hubal, M.J.; Freishtat, R.J.; Nadler, E.P. Adipocyte Exosomes Induce Transforming Growth Factor Beta Pathway Dysregulation in Hepatocytes : A Novel Paradigm for Obesity-Related Liver Disease. J. Surg. Res. 2014, 192, 268–275. [Google Scholar] [CrossRef]
  49. Eguchi, A.; Lazic, M.; Armando, A.M.; Phillips, S.A.; Katebian, R.; Maraka, S.; Quehenberger, O.; Sears, D.D.; Feldstein, A.E. Circulating Adipocyte-Derived Extracellular Vesicles Are Novel Markers of Metabolic Stress. J. Mol. Med. 2016, 94, 1241–1253. [Google Scholar] [CrossRef]
  50. Mleczko, J.; Ortega, F.J.; Falcon-Perez, J.M.; Wabitsch, M.; Fernandez-Real, J.M.; Mora, S. Extracellular Vesicles from Hypoxic Adipocytes and Obese Subjects Reduce Insulin-Stimulated Glucose Uptake. Mol. Nutr. Food Res. 2018, 62, 1700917. [Google Scholar] [CrossRef] [Green Version]
  51. Mendivil Alvarado, H.; Chavez Munguia, B.; Carvajal Millan, E.; Hernandez Hernandez, M.; Lopez Teros, V.; Pacheco Moreno, B.; Rascon Duran, L.; Astiazaran Garcia, H. Morphometric Characterization of Extracellular Vesicles in Adults with Obesity. FASEB J. 2020, 34, 1. [Google Scholar] [CrossRef]
  52. Santamaria-Martos, F.; Benitez, I.D.; Latorre, J.; Llunch, A.; Moreno-Navarrete, J.M.; Sabater, M.; Ricart, W.; Sanchez de la Torre, M.; Mora, S.; Fernández-Real, J.M.; et al. Comparative and Functional Analysis of Plasma Membrane-Derived Extracellular Vesicles from Obese vs Nonobese Women. Clin. Nutr. 2020, 39, 1067–1076. [Google Scholar] [CrossRef]
  53. Afrisham, R.; Sadegh-Nejadi, S.; Meshkani, R.; Emamgholipour, S.; Paknejad, M. Effect of Circulating Exosomes Derived from Normal-Weight and Obese Women on Gluconeogenesis, Glycogenesis, Lipogenesis and Secretion of FGF21 and Fetuin A in HepG2 Cells. Diabetol. Metab. Syndr. 2020, 12, 32. [Google Scholar] [CrossRef] [Green Version]
  54. Durcin, M.; Fleury, A.; Taillebois, E.; Hilairet, G.; Krupova, Z.; Henry, C.; Truchet, S.; Trötzmüller, M.; Köfeler, H.; Mabilleau, G.; et al. Characterisation of Adipocyte-Derived Extracellular Vesicle Subtypes Identifies Distinct Protein and Lipid Signatures for Large and Small Extracellular Vesicles. J. Extracell. Vesicles 2017, 6, 1305677. [Google Scholar] [CrossRef] [PubMed]
  55. Rafiei, H.; Robinson, E.; Barry, J.; Jung, M.E.; Little, J.P. Short-Term Exercise Training Reduces Glycaemic Variability and Lowers Circulating Endothelial Microparticles in Overweight and Obese Women at Elevated Risk of Type 2 Diabetes. Eur. J. Sport Sci. 2019, 19, 1140–1149. [Google Scholar] [CrossRef] [PubMed]
  56. Heinrich, L.F.; Andersen, D.K.; Cleasby, M.E.; Lawson, C. Long-Term High Fat Feeding of Rats Results in Increased Numbers of Circulating Microvesicles with pro-Inflammatory Effects on Endothelial Cells. Br. J. Nutr. 2015, 113, 1704–1711. [Google Scholar] [CrossRef] [Green Version]
  57. Eguchi, A.; Mulya, A.; Lazic, M.; Radhakrishnan, D.; Berk, M.P. Microparticles Release by Adipocytes Act as “Find-Me” Signals to Promote Macrophage Migration. PLoS ONE 2015, 10, e0123110. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  58. Martinez, M.C.; Tual-Chalot, S.; Leonetti, D.; Andriantsitohaina, R. Microparticles: Targets and Tools in Cardiovascular Disease. Trends Pharmacol. Sci. 2011, 32, 659–665. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  59. Piccin, A.; Murphy, W.G.; Smith, O.P. Circulating Microparticles: Pathophysiology and Clinical Implications. Blood Rev. 2007, 21, 157–171. [Google Scholar] [CrossRef]
  60. Hanzu, F.A.; Palomo, M.; Kalko, S.G.; Parrizas, M.; Garaulet, M.; Escolar, G.; Gomis, R.; Diaz-Ricart, M. Translational Evidence of Endothelial Damage in Obese Individuals: Inflammatory and Prothrombotic Responses. J. Thromb. Haemost. 2011, 9, 1236–1245. [Google Scholar] [CrossRef]
  61. Osada-oka, M.; Shiota, M.; Izumi, Y.; Nishiyama, M.; Tanaka, M.; Yamaguchi, T.; Sakurai, E.; Miura, K.; Iwao, H. Macrophage-Derived Exosomes Induce Inflammatory Factors in Endothelial Cells under Hypertensive Conditions. Hypertens. Res. 2017, 40, 353–360. [Google Scholar] [CrossRef]
  62. Gündüz, Z.; Dursun, İ.; Tülpar, S.; Baştuğ, F.; Baykan, A.; Yikilmaz, A.; Patıroğlu, T.; Poyrazoglu, H.M.; Akin, L.; Yel, S.; et al. Increased Endothelial Microparticles in Obese and Overweight Children. J. Pediatr. Endocrinol. Metab. 2012, 25, 1111–1117. [Google Scholar] [CrossRef]
  63. López Andrés, N.; Tesse, A.; Regnault, V.; Louis, H.; Cattan, V.; Thornton, S.N.; Labat, C.; Kakou, A.; Tual-Chalot, S.; Faure, S.; et al. Increased Microparticle Production and Impaired Microvascular Endothelial Function in Aldosterone-Salt-Treated Rats: Protective Effects of Polyphenols. PLoS ONE 2012, 7, e39235. [Google Scholar] [CrossRef] [Green Version]
  64. Burger, D.; Montezano, A.C.; Nishigaki, N.; He, Y.; Carter, A.; Touyz, R.M. Endothelial Microparticle Formation by Angiotensin II Is Mediated via Ang II Receptor Type I/NADPH Oxidase/Rho Kinase Pathways Targeted to Lipid Rafts. Arterioscler. Thromb. Vasc. Biol. 2011, 31, 1898–1907. [Google Scholar] [CrossRef] [Green Version]
  65. Zhang, Y.; Shi, L.; Mei, H.; Zhang, J.; Zhu, Y.; Han, X.; Zhu, D. Inflamed Macrophage Microvesicles Induce Insulin Resistance in Human Adipocytes. Nutr. Metab. 2015, 12, 21. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  66. Ferrante, S.C.; Nadler, E.P.; Pillai, D.K.; Hubal, M.J.; Wang, J.M.; Gordish-dressman, H.; Koeck, E.; Wiles, A.A.; Freishtat, R.J.; Wang, J.M.; et al. Adipocyte-Derived Exosomal MiRNAs: A Novel Mechanism for Obesity-Related Disease. Pediatr. Res. 2015, 77, 447–454. [Google Scholar] [CrossRef] [PubMed]
  67. Amosse, J.; Durcin, M.; Malloci, M.; Vergori, L.; Fleury, A.; Gagnadoux, F.; Dubois, S.; Simard, G.; Boursier, J.; Hue, O.; et al. Phenotyping of Circulating Extracellular Vesicles (EVs) in Obesity Identifies Large EVs as Functional Conveyors of Macrophage Migration Inhibitory Factor. Mol. Metab. 2018, 18, 134–142. [Google Scholar] [CrossRef] [PubMed]
  68. Camino, T.; Lago-Baameiro, N.; Bravo, S.B.; Molares-Vila, A.; Sueiro, A.; Couto, I.; Baltar, J.; Casanueva, E.F.; Pardo, M. Human Obese White Adipose Tissue Sheds Depot-Specific Extracellular Vesicles and Reveals Candidate Biomarkers for Monitoring Obesity and Its Comorbidities. Transl. Res. 2022, 239, 85–102. [Google Scholar] [CrossRef]
  69. Crewe, C.; Joffin, N.; Rutkowski, J.M.; Kim, M.; Zhang, F.; Dwight, A.T.; Gordillo, R.; Scherer, P.E. An Endothelial to Adipocyte Extracellular Vesicle Axis Governed by Metabolic State. Cell 2019, 175, 695–708. [Google Scholar] [CrossRef] [Green Version]
  70. Gao, J.; Li, X.; Wang, Y.; Cao, Y.; Yao, D.; Sun, L.; Qin, L.; Qiu, H.; Zhan, X. Adipocyte-Derived Extracellular Vesicles Modulate Appetite and Weight through MTOR Signalling in the Hypothalamus. Acta Physiol. 2020, 228, e13339. [Google Scholar] [CrossRef]
  71. Bushman, T.; Lin, T.-Y.; Chen, X. Intermittent Fasting Alters Serum Exosomes in Middle-Aged Male Mice on Long-Term High-Fat Diet. Curr. Dev. Nutr. 2021, 5 (Suppl. S2), 1199. [Google Scholar] [CrossRef]
  72. Fu, Q.; Li, Y.; Jiang, H.; Shen, Z.; Gao, R.; He, Y.; Liu, Y. Hepatocytes Derived Extracellular Vesicles from High-Fat Diet Induced Obese Mice Modulate Genes Expression and Proliferation of Islet b Cells. Biochem. Biophys. Res. Commun. 2019, 516, 1159–1166. [Google Scholar] [CrossRef]
  73. Eichner, N.Z.M.; Gilbertson, N.M.; Musante, L.; La Salvia, S.; Weltman, A.; Erdbrügger, U.; Malin, S.K. An Oral Glucose Load Decreases Postprandial Extracellular Vesicles in Obese Adults with and without Prediabetes. Nutrient 2019, 11, 580. [Google Scholar] [CrossRef] [Green Version]
  74. Hohensinner, P.J.; Kaun, C.; Ebenbauer, B.; Hackl, M.; Demyanets, S.; Richter, D.; Prager, M.; Wojta, J.; Rega-Kaun, G. Reduction of Premature Aging Markers after Gastric Bypass Surgery in Morbidly Obese Patients. Obes. Surg. 2018, 28, 2804–2810. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  75. Rega-Kaun, G.; Kaun, C.; Ebenbauer, B.; Jaegersberger, G.; Prager, M.; Wojta, J.; Hohensinner, P.J. Bariatric Surgery in Morbidly Obese Individuals Affects Plasma Levels of Protein C and Thrombomodulin. J. Thromb. Thrombolysis 2019, 47, 51–56. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  76. Morel, O.; Luca, F.; Grunebaum, L.; Jesel, L.; Meyer, N.; Desprez, D.; Robert, S.; Dignat-George, F.; Toti, F.; Simon, C.; et al. Short-Term Very Low-Calorie Diet in Obese Females Improves the Haemostatic Balance through the Reduction of Leptin Levels, PAI-1 Concentrations and a Diminished Release of Platelet and Leukocyte-Derived Microparticles. Int. J. Obes. 2011, 35, 1479–1486. [Google Scholar] [CrossRef] [Green Version]
  77. Lee, J.-E.; Moon, P.-G.; Lee, I.-K.; Baek, M.-C. Proteomic Analysis of Extracellular Vesicles Released by Adipocytes of Otsuka Long-Evans Tokushima Fatty (OLETF) Rats. Protein J. 2015, 34, 220–235. [Google Scholar] [CrossRef]
  78. Barrachina, M.N.; Sueiro, A.M.; Casas, V.; Izquierdo, I.; Hermida-Nogueira, L.; Guitián, E.; Casanueva, F.F.; Abián, J.; Carrascal, M.; Pardo, M.; et al. A Combination of Proteomic Approaches Identifies A Panel of Circulating Extracellular Vesicle Proteins Related to the Risk of Suffering Cardiovascular Disease in Obese Patients. Proteomics 2018, 19, 1800248. [Google Scholar] [CrossRef] [Green Version]
  79. Yang, Z.; Wei, Z.; Wu, X.; Yang, H. Screening of Exosomal MiRNAs Derived from Subcutaneous and Visceral Adipose Tissues: Determination of Targets for the Treatment of Obesity and Associated Metabolic Disorders. Mol. Med. Rep. 2018, 18, 3314–3324. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  80. Thrush, A.B.; Antoun, G.; Nikpay, M.; Patten, D.A.; Devlugt, C.; Mauger, J.; Beauchamp, B.L.; Lau, P.; Reshke, R.; Doucet, É.; et al. Diet-Resistant Obesity Is Characterized by a Distinct Plasma Proteomic Signature and Impaired Muscle Fiber Metabolism. Int. J. Obes. 2018, 42, 353–362. [Google Scholar] [CrossRef] [Green Version]
  81. Rega-kaun, G.; Ritzel, D.; Kaun, C.; Ebenbauer, B.; Thaler, B.; Prager, M.; Demyanets, S.; Wojta, J.; Hohensinner, P.J. Changes of Circulating Extracellular Vesicles from the Liver after Roux-En-Y Bariatric Surgery. Int. J. Mol. Sci. 2019, 20, 2153. [Google Scholar] [CrossRef] [Green Version]
  82. Witczak, J.K.; Min, T.; Prior, S.L.; Stephens, J.W.; James, P.E.; Rees, A. Bariatric Surgery Is Accompanied by Changes in Extracellular Vesicle-Associated and Plasma Fatty Acid Binding Protein 4. Obes. Surg. 2018, 28, 767–774. [Google Scholar] [CrossRef]
  83. Janssen, I.; Heymsfield, S.B.; Wang, Z.M.; Ross, R. Skeletal Muscle Mass and Distribution in 468 Men and Women Aged 18–88 Yr. J. Appl. Physiol. 2000, 89, 81–88. [Google Scholar] [CrossRef] [Green Version]
  84. Seok, W.P.; Goodpaster, B.H.; Strotmeyer, E.S.; Kuller, L.H.; Broudeau, R.; Kammerer, C.; De Rekeneire, N.; Harris, T.B.; Schwartz, A.V.; Tylavsky, F.A.; et al. Accelerated Loss of Skeletal Muscle Strength in Older Adults with Type 2 Diabetes: The Health, Aging, and Body Composition Study. Diabetes Care 2007, 30, 1507–1512. [Google Scholar] [CrossRef] [Green Version]
  85. Lemmer, J.T.; Hurlbut, D.E.; Martel, G.F.; Tracy, B.L.; Ivey, F.M.; Metter, E.J.; Fozard, J.L.; Fleg, J.L.; Hurley, B.F. Age and Gender Responses to Strength Training and Detraining. Med. Sci. Sports Exerc. 2000, 32, 1505–1512. [Google Scholar] [CrossRef] [PubMed]
  86. Aagaard, P.; Suetta, C.; Caserotti, P.; Magnusson, S.P.; Kjær, M. Role of the Nervous System in Sarcopenia and Muscle Atrophy with Aging: Strength Training as a Countermeasure. Scand. J. Med. Sci. Sport. 2010, 20, 49–64. [Google Scholar] [CrossRef] [PubMed]
  87. Pedersen, B.K.; Åkerström, T.C.A.; Nielsen, A.R.; Fischer, C.P. Role of Myokines in Exercise and Metabolism. J. Appl. Physiol. 2007, 103, 1093–1098. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  88. Trovato, E.; Felice, V.D.; Barone, R. Extracellular Vesicles: Delivery Vehicles of Myokines. Front. Phisiol. 2019, 10, 522. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  89. Osti, D.; Bene, M.D.; Rappa, G.; Santos, M.; Matafora, V.; Richichi, C.; Faletti, S.; Beznoussenko, G.V.; Mironov, A.; Bachi, A.; et al. Clinical Significance of Extracellular Vesicles in Plasma from Glioblastoma Patients. Clin. Cancer Res. 2019, 25, 266–276. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  90. Pérez, P.S.; Romaniuk, M.A.; Duette, G.A.; Zhao, Z.; Huang, Y.; Martin-Jaular, L.; Witwer, K.W.; Théry, C.; Ostrowski, M. Extracellular Vesicles and Chronic Inflammation during HIV Infection. J. Extracell. Vesicles 2019, 8, 1687275. [Google Scholar] [CrossRef]
  91. Gasecka, A.; Nieuwland, R.; Budnik, M.; Dignat-George, F.; Eyileten, C.; Harrison, P.; Huczek, Z.; Kapłon-Cieślicka, A.; Lacroix, R.; Opolski, G.; et al. Randomized Controlled Trial Protocol to Investigate the Antiplatelet Therapy Effect on Extracellular Vesicles (AFFECT EV) in Acute Myocardial Infarction. Platelets 2020, 31, 26–32. [Google Scholar] [CrossRef]
  92. Lundwall, K.; Mörtberg, J.; Mobarrez, F.; Jacobson, S.H.; Jörneskog, G.; Spaak, J. Changes in Microparticle Profiles by Vitamin D Receptor Activation in Chronic Kidney Disease—A Randomized Trial. BMC Nephrol. 2019, 20, 290. [Google Scholar] [CrossRef] [Green Version]
  93. Lovett, J.A.C.; Durcan, P.J.; Myburgh, K.H. Investigation of Circulating Extracellular Vesicle MicroRNA Following Two Consecutive Bouts of Muscle-Damaging Exercise. Front. Physiol. 2018, 9, 1149. [Google Scholar] [CrossRef]
  94. Rigamonti, A.E.; Bollati, V.; Pergoli, L.; Iodice, S.; De Col, A.; Tamini, S.; Cicolini, S.; Tringali, G.; De Micheli, R.; Cella, S.G.; et al. Effects of an Acute Bout of Exercise on Circulating Extracellular Vesicles: Tissue-, Sex-, and BMI-Related Differences. Int. J. Obes. 2020, 44, 1108–1118. [Google Scholar] [CrossRef] [PubMed]
  95. Bei, Y.; Xu, T.; Lv, D.; Yu, P.; Xu, J.; Che, L.; Das, A.; Tigges, J.; Toxavidis, V.; Ghiran, I.; et al. Exercise-Induced Circulating Extracellular Vesicles Protect against Cardiac Ischemia–Reperfusion Injury. Basic Res. Cardiol. 2017, 112, 38. [Google Scholar] [CrossRef] [PubMed]
  96. Whitham, M.; Parker, B.L.; Friedrichsen, M.; James, D.E.; Febbraio, M.A.; Whitham, M.; Parker, B.L.; Friedrichsen, M.; Hingst, J.R.; Hjorth, M.; et al. Extracellular Vesicles Provide a Means for Tissue Crosstalk during Exercise Resource. Cell Metab. 2018, 27, 237–251. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  97. Guescini, M.; Canonico, B.; Lucertini, F.; Maggio, S.; Annibalini, G.; Barbieri, E.; Luchetti, F.; Papa, S.; Stocchi, V. Muscle Releases Alpha-Sarcoglycan Positive Extracellular Vesicles Carrying MiRNAs in the Bloodstream. PLoS ONE 2015, 10, e0125094. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  98. Gallagher, D.; Ruts, E.; Visser, M.; Heshka, S.; Baumgartner, R.N.; Wang, J.; Pierson, R.N.; Pi-Sunyer, F.X.; Heymsfield, S.B. Weight Stability Masks Sarcopenia in Elderly Men and Women. Am. J. Physiol. Endocrinol. Metab. 2000, 279, 366–375. [Google Scholar] [CrossRef]
  99. Ezeoke, C.C.; Morley, J.E. Pathophysiology of Anorexia in the Cancer Cachexia Syndrome. J. Cachexia. Sarcopenia Muscle 2015, 6, 287–302. [Google Scholar] [CrossRef] [Green Version]
  100. Lee, J.H.; Jun, H.-S. Role of Myokines in Regulating Skeletal Muscle Mass and Function. Front. Physiol. 2019, 10, 42. [Google Scholar] [CrossRef]
  101. Goiburu, M.E.; Jure Goiburu, M.M.; Bianco, H.; Ruiz Díaz, J.; Alderete, F.; Palacios, M.C.; Cabral, V.; Escobar, D.; López, R.; Waitzberg, D.L. The Impact of Malnutrition on Morbidity, Mortality and Length of Hospital Stay in Trauma Patients. Nutr. Hosp. 2006, 21, 604–610. [Google Scholar]
  102. He, W.A.; Calore, F.; Londhe, P.; Canella, A.; Guttridge, D.C.; Croce, C.M. Microvesicles Containing MiRNAs Promote Muscle Cell Death in Cancer Cachexia via TLR7. Proc. Natl. Acad. Sci. USA 2014, 111, 4525–4529. [Google Scholar] [CrossRef] [Green Version]
  103. Zhang, G.; Liu, Z.; Ding, H.; Zhou, Y.; Doan, H.A.; Wai, K.; Sin, T.; Zhu, Z.J.; Flores, R.; Wen, Y.; et al. Tumor Induces Muscle Wasting in Mice through Releasing Extracellular Hsp70 and Hsp90. Nat. Commun. 2017, 8, 589. [Google Scholar] [CrossRef] [Green Version]
  104. Beltrà, M.; Costelli, P.; Penna, F. Promising Treatments for Muscle Wasting in Cancer: Focus on MicroRNA. Expert Rev. Qual. Life Cancer Care 2016, 1, 313–321. [Google Scholar] [CrossRef]
  105. Marinho, R.; Alcântara, P.S.M.; Ottoch, J.P.; Seelaender, M. Role of Exosomal MicroRNAs and MyomiRs in the Development of Cancer Cachexia-Associated Muscle Wasting. Front. Nutr. 2018, 4, 69. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Table
Table 1. Studies of extracellular vesicles in obesity.
Table 1. Studies of extracellular vesicles in obesity.
Author, Year
(Refs.)		Source of
Isolation		EVs Size
/Method of Isolation		EVs ClassificationSpecific Cell MarkerEVs CharacteristicsMain Finding
Goichot, 2006 [42]PlasmaNR AMPAnnexin VIncrease in EVs concentration (ug/mL)Negative association with BMI
Esposito, 2006 [43]PlasmaNR AMPCD31, CD42
Increase in the number of EVs Association with waist-hip ratio; C-reactive protein; HOMA-IR
Murakami,
2007 [44]		PlasmaNR AMPCD41Increase in the number of EVs Association with BMI; waist circumference; subcutaneous body fat
Stepanian, 2013 [45]PlasmaNR AMPCD41, CD31, Annexin VIncrease in the number of EVsThe characteristics of EVs are independent of the metabolic syndrome
Kranendonk, 2014 [46]Explant
subcutaneous and omental adipose tissue		NR BEVsCD9
Adiponectin		Association between the amount of EVs and WC and liver enzymes Adipose tissue EVs can stimulate or inhibit insulin signaling at the liver level, depending on their adipokine content
Campello, 2015 [47]PlasmaNR AMPAnnexin V, CD62, CD61, CD45Increase in the number of EVsAssociation with BMI, waist, fibrinogen, IL6, and FVIII; overproduction of EVs could induce the generation of thrombin
Koeck,
2015 [48]		Subcutaneous and visceral adipose tissue50–100 nm CEXOCD63Increase in EVs concentration (ug/mL)Higher BMI decreases the concentration of EVs
Togliatto, 2016 [41]Visceral adipocyte stem cells primary culture<1000 nm DEVsCD63, CD81No apparent change in size or quantityObesity impacts on the proangiogenic potential of EVs
Eguchi,
2016 [49]		Adipose tissueNRDEXO & ETPerilipin AIncrease in EVs quantityAssociation with biomarkers: glucose, insulin, and HOMA-IR; presence of perilipin A in adipocyte EVs
Mleczko, 2018 [50]Plasma and adipocytes culture100–150 DEXOCD81, MHCI
TSG101		No apparent change in size or quantityEVs of obese subjects decrease insulin-stimulated 2-deoxyglucose caption in adipocytes
Mendivil, 2019 [51]Plasma<100 nm CEXOALIXIncrease in size of EVsAssociation with BMI, TG, and % body fat
Santamarina, 2019 [52]Plasma<116 nm DEVsNRSmaller EVs sizeGlucose, HOMA-IR, BMI, TG, HDL, and HA1c
Reza,
2020 [53]		Plasma161 nm DEXOCD63No changes between groups were findParticipation in the insulin signaling pathway; increase in the intracellular content of TG and decrease the secretion of FGF21 in hepatocytes
BMI: body mass index; EVs: extracellular vesicles; EXO: exosomes; ET: ectosomes; method of isolation: A none reported, B sucrose gradient and ultracentrifugation, C synthetic polymer precipitation, D ultracentrifugation; MP: microparticles; MV: microvesicles; TG: triglycerides; WC: waist circumference; HOMA-IR: insulin resistance index; HDL: high density lipoprotein; HA1c: hemoglobin A1c.
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Mendivil-Alvarado, H.; Sosa-León, L.A.; Carvajal-Millan, E.; Astiazaran-Garcia, H. Malnutrition and Biomarkers: A Journey through Extracellular Vesicles. Nutrients 2022, 14, 1002. https://doi.org/10.3390/nu14051002

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Mendivil-Alvarado H, Sosa-León LA, Carvajal-Millan E, Astiazaran-Garcia H. Malnutrition and Biomarkers: A Journey through Extracellular Vesicles. Nutrients. 2022; 14(5):1002. https://doi.org/10.3390/nu14051002

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Mendivil-Alvarado, Herminia, Leopoldo Alberto Sosa-León, Elizabeth Carvajal-Millan, and Humberto Astiazaran-Garcia. 2022. "Malnutrition and Biomarkers: A Journey through Extracellular Vesicles" Nutrients 14, no. 5: 1002. https://doi.org/10.3390/nu14051002

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Mendivil-Alvarado, H., Sosa-León, L. A., Carvajal-Millan, E., & Astiazaran-Garcia, H. (2022). Malnutrition and Biomarkers: A Journey through Extracellular Vesicles. Nutrients, 14(5), 1002. https://doi.org/10.3390/nu14051002

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