Metabolic flexibility in response to environmental stimuli, such as diet and exercise, are dramatically influenced by epigenetic factors as they influence gene expression by regulating access of transcriptional machinery to DNA. Evidence that epigenetic changes drive metabolic inflexibility in humans is emerging Metabolic networks, in particular those in the mitochondria, directly transmit information about the cells metabolic state to epigenetic programming enzymes that, for instance, add or remove epigenetic markers onto chromatin , Both global fluctuations in metabolite levels caused by nutritional inputs, circadian rhythm, and oxygenation, or local changes depending on intracellular metabolite distribution, can translate into epigenetic changes , The abundance of cofactors and the metabolic enzymes that generate them not only alter epigenetic enzyme histone modification, but also affect DNA methylation and posttranslational modification of the epigenetic enzymes themselves, resulting in a complex feedback network 42 , Moreover, the amplitude and duration of the metabolic stimulus required to alter the epigenome is dependent on the vastly different kinetics of epigenetic modifier enzymes How these epigenetic regulators are targeted to specific sites, such as promotor regions, how transient their epigenetic markers are, and how these changes are inherited, is still under active investigation People with a family history for T2DM have an increased risk for developing metabolic inflexibility; the lower HK II activity and PGC1 expression play a role in this For instance, skeletal muscle from families with a history of T2DM has altered methylation status of genes involved in muscle function and insulin and calcium signaling Tissue-specific epigenetic regulation may be of particular importance for metabolic flexibility because overweight patients with T2DM also have hypermethylated promoter regions of PGC1 α and an OXPHOS complex I subunit in skeletal muscle Promoters of many genes that are important for pancreatic β -cell survival and function are differentially methylated in T2DM patients compared with controls Moreover, obese patients have an altered epigenetic landscape associated with disrupted lipid oxidative metabolism and mitochondrial function in adipose tissue, skeletal muscle, and liver Although inborn errors of metabolism are clear examples of metabolic inflexibility, here we focus on acquired metabolic inflexibility.

For specific information on inborn errors of metabolism we refer the reader to a comprehensive book on the subject Here, we discuss the pathophysiology of metabolic flexibility in the context of obesity, metabolic syndrome and T2DM, as well as systemic inflammation, cardiovascular disease, and cancer.

At the heart of obesity lies the inability to regulate lipolytic and antilipolytic processes in adipose tissue during starvation and feeding, respectively. Obesity is predominantly associated with elevated levels of plasma free fatty acids High circulating levels of free fatty acids inhibit glycogen synthase activity and PDH activity, which leads to reduced disposal and oxidation of glucose.

Besides adipocyte metabolic dysfunction, skeletal muscle mitochondrial capacity and β -oxidation are reduced. Specifically, upregulation of PPAR α and its downstream targets in response to high-fat feeding are defective Excess calories are then stored in peripheral fat depots as triglyceride; when these depots reach their maximum capacity and fail to expand, fat accumulates in ectopic depots, including skeletal muscle and the liver.

Ectopic fat deposition is related to metabolic abnormalities and defects in insulin sensitivity, T2DM, cardiovascular disease, and cancer Finally, obesity is associated with a state of chronic low-grade inflammation because ectopic fat depots release more inflammatory mediators than peripheral fat depots and infiltration of macrophages Metabolic inflexibility and fat deposition therefore likely reinforce one another in a vicious cycle.

Together with excess body fat and physical inactivity, metabolic syndrome is a major risk factor for developing T2DM and related complications include cardiovascular disease; increased rates of specific cancers, physical, and cognitive disability 5 ; and is associated with increased risk for T2DM and cardiovascular disease, among cancer Consequently, individuals with metabolic syndrome have increased mortality and a shortened lifespan The best example of compromised metabolic flexibility in metabolic syndrome is a deteriorated insulin-mediated substrate switching.

As such, metabolic inflexibility is at the core of the pathophysiology of insulin resistance After a high-fat meal, patients with metabolic syndrome have higher levels of glycaemia and lower skeletal muscle free fatty acid uptake compared with healthy individuals.

In response to fasting, skeletal muscle from patients with insulin resistance are less able to switch to FAO compared with healthy individuals An increased dependency on glucose oxidation and decreased reliance on FAO in offspring from patients with T2DM suggests that impaired FAO may precede insulin resistance — Moreover, studies strongly imply that impaired mitochondrial function precedes insulin resistance 41 , The importance of OXPHOS and its maintenance in relation to insulin resistance is underscored by observations that skeletal muscle mitochondria from patients with T2DM or obesity are unable to increase replication of mtDNA, which encodes essential OXPHOS components, in response to exercise combined with CR Moreover, skeletal muscle mitochondria from insulin-resistant patients have lower expression of PGC1 α and its downstream targets, and differ in mass, morphology, and function In particular, muscle mitochondria from patients with T2DM show reduced expression of mitofusin-2, which regulates mitochondrial outer membrane fusion, and thus mitochondrial dynamics and quality control They also have a lower maximal oxidative capacity, smaller mitochondria and reduced NADH oxidase complex I activity Interestingly, studies have demonstrated that BCAA and associated metabolites are strongly associated with insulin resistance and T2DM Based on the theory of mitochondrial metabolic gridlock and anaplerosis, excessive BCAA metabolites are proposed to clog the β -oxidation machinery, particularly in skeletal muscle and liver, and thus contribute to accumulation of incompletely oxidized intermediates of fatty acids, particularly in the presence of a high-fat diet.

Collectively, under these conditions, such byproducts render glucose superfluous as a substrate and, combined with the upsurge in ROS, can lead to insulin resistance One of the hallmarks of metabolic syndrome is low-grade chronic systemic inflammation , In the case of obesity and insulin resistance, systemic inflammation can trigger and propagate metabolic inflexibility.

Systemic inflammation and metabolic inflexibility can cause a vicious circle because metabolic inflexibility can also trigger systemic inflammation. How this is regulated at the cellular and molecular level is currently unknown, but hyperglycemia-induced mitochondrial ROS production can stimulate inflammation by signaling factors , such as protein kinase C, p38 MAPK, and c-Jun- N -terminal kinase Systemic low-grade inflammation as a trigger of metabolic inflexibility is best described in the context of obesity and lipid toxicity As a result of excess fatty acid intake, organs that reach the maximum of their storage capacity and ectopic tissues that accumulate fatty acids upon overspill can become infiltrated by immune cells resulting in inflammatory processes.

Dysregulated release and storage of fatty acids can lead to an increased release of inflammatory cytokines such as TNF α and monocyte chemoattractant protein-1 and decreased secretion of anti-inflammatory adipokines such as adiponectin.

This can result in recruitment of M1 type macrophages and T cells. Additionally, B lymphocytes, neutrophils, eosinophils, mast cells, and natural killer cells have all been implicated in adipose tissue dysfunction.

This lipid toxicity can therefore generate signaling intermediates that can interfere with local and systemic immune responses, causing a vicious cycle of immune-metabolic degradation Although the mechanism and specific mediators in lipid-induced inflammation are not completely understood, the endoplasmic reticulum ER is central to these responses because this is where both lipid biosynthesis and esterification processes as well as inflammatory pathways converge.

Disrupted lipid synthesis in the ER can change ER membrane composition, leading to ER stress, dysfunction, and ultimately cell death, triggering inflammation Lipids are also able to instigate inflammatory processes through interaction with cell-surface receptors, such as Toll-like receptor-4, and stress kinases in the cytoplasm, such as protein kinase R that through downstream signaling can induce the expression of genes that mediate inflammation and apoptosis, and promote inflammasome activity.

Moreover, there is emerging evidence that lipids engage intracellular signaling pathways via protein kinase C isoforms that are related to T-cell activation and LPS responses It is unlikely, however, that one of such responses underlies lipotoxicity, but that a combination of factors mediate lipid-associated inflammation , Metabolic flexibility and the accompanied rerouting of metabolic flux are essential for immune function.

Following immune stimulation, naive lymphocytes that rely on β -oxidation of fatty acids and pyruvate oxidation via the TCA cycle become active and engage in glycolysis and glutaminolysis Additionally, the switch to glycolysis enables glycolysis and TCA cycle intermediates to be used as key sources of carbon molecules for biosynthesis of nucleotides, amino acids, and lipids.

In this way, glycolysis facilitates robust growth, rapid cellular proliferation, and the production of large quantities of effector molecules, ultimately to mount a sufficient immune response. The exact molecular regulation and thus the dependency on this metabolic switch differs between specific lymphocyte subsets Therefore, activated lymphocytes sustain OXPHOS for ATP production, which enhances cell survival and lifespan of lymphocytes and is essential for immune memory Memory T cells also use glucose and other fuels to synthesize triglycerides, which are then used in FAO Contrary to the dogma that innate immunity is nonspecific and lacks memory, classic innate immune cells such as macrophages, natural killer cells, and monocytes can become epigenetically reprogrammed by infection or vaccination, which confers nonspecific protection from secondary infection, a phenomenon called trained immunity The increase in glycolytic metabolism enables a more robust and swift response to intruding pathogens Training of immune cells is dependent on Akt, mTOR, hypoxia-inducible factor 1 α HIF1 α , and, to a lesser extent, SIRTs.

Their crucial roles were affirmed by inhibition of Akt by wortmannin, mTOR by rapamycin, HIF1 α by ascorbate, and activation of SIRT1 by resveratrol, because these compounds blunt trained immunity Recently, however, the notion that a shift from OXPHOS to glycolysis underlies activation of all immune cells upon microbial stimulation was challenged because pathogen-specific metabolic rewiring was observed in human monocytes.

This pathogen specificity was proposed to derive from signaling strength, rather than qualitative signaling differences between microbial stimuli, and consequently mediates different functional outputs such as phagocytic capacity Adipose tissue macrophages that have been activated and rely on glucose are proinflammatory type M1 and contribute to adipose inflammation and insulin resistance.

Conversely, macrophages that rely on fatty acid metabolism secrete anti-inflammatory cytokines and thus preserve insulin sensitivity of liver and adipose tissue type M2 , Proinflammatory activation can be achieved by overexpression of GLUT1, even in the absence of other conventional stimuli, or by decreasing expression of lipid trafficking proteins, such as fatty acid transport protein 1 FATP1.

FATP1 knockout mice fed high-fat diets showed an increased proinflammatory phenotype and worsened metabolic syndrome than mice with normal FATP1 expression. Alternatively, overexpression of FATP1 decreased substrate switching to glucose and reduced inflammation Thus, macrophage inflammatory status is mediated by rerouting metabolic pathways.

The metabolic switch of glucose metabolism generates ROS that drive the production of inflammatory enzymes, cytokines, and chemokines such as IL-6, monocyte chemoattractant protein-1, TNF- α , and inducible NO synthase iNOS. iNOS is an important metabolic regulator of the immune response because NO inhibits OXPHOS and oxidative metabolism, thus promoting the glycolytic and proinflammatory phenotype , In this way, low-grade systemic inflammation defined as a twofold to threefold increase of circulating inflammatory mediators including the infiltration of immune cells, particularly in metabolic tissues that have reached their capacity limits, can be driven by metabolic inflexibility Recently, inhibition of iNOS in mouse macrophages was shown to dampen the M1 phenotype through reduction of NO-induced OXPHOS inhibition and assist in the phenotypic and metabolic M1 to M2 repolarization, suggesting that editing macrophage re polarization is a promising target to reduce inflammation and promote tissue repair An example of metabolic inflexibility and disrupted inflammatory assuagement is sepsis.

During sepsis, a profound change in acute leukocyte metabolism occurs. Metabolic inflexibility drives sepsis-related innate immunoparalysis as the metabolism through glycolysis, β -oxidation, and OXPHOS pathways in leukocytes is downregulated, resulting in their inability to mount any response whatsoever A sudden mitochondrial complex I dysfunction in sepsis , possibly linked to the overproduction of NO and ROS, may be one of the causes of an upstream mitochondrial gridlock, and has been observed to relate to organ dysfunction Moreover, the impaired metabolic rate has been associated with reduced levels of mtDNA and mRNA expression of OXPHOS components , In summary, metabolic flexibility is not only necessary to mount an adequate immune response but also for mitigation of the inflammatory process.

Cardiac performance is sustained by fatty acid and glucose oxidation, although fatty acids are the preferred substrate in the heart because of the higher energy yield compared with glucose.

This flux is mediated by a high expression of PPAR α -regulated genes encoding key proteins in fatty acid uptake, esterification, and oxidation Under energetically demanding conditions such as exercise, the heart switches to the oxidation of glucose and lactate An increase in heart rate increases mitochondrial calcium concentration , allowing higher mitochondrial ATP production rates to sustain the increased energetic load of the heart.

Upon exercise-induced sympathetic nervous system stimulation, β -adrenergic signaling increases glycolytic flux via cAMP activation of cAMP-dependent protein kinase A, increasing pyruvate production and glucose metabolism.

Protein kinase A also activates phosphofructokinase-1 and PDH, stimulating the heart to rapidly oxidize glucose even in the presence of fatty acids As a consequence, triglyceride accumulation in cardiomyocytes likely leads to abnormal lipid signaling, increased ROS production, ER stress, and mitochondrial dysfunction Glucose metabolism is enhanced in a similar manner through insulin and nutrient stress signaling via Akt and AMPK, respectively A dependency on glucose and ketone body metabolism is also observed in myocardial ischemia, ventricular hypertrophy, and systemic hypertension , , as is mitochondrial dysfunction , A recent study in mice demonstrated that mildly increasing PPAR α expression in the progressive phase of heart failure, when FAO is decreased, maintains myocardial function and energetics, suggesting that modulating substrate utilization may be a promising therapeutic strategy for heart failure Obesity can cause metabolic inflexibility of the heart and alter substrate selection High-fat diet feeding and consequent insulin insensitivity, for instance, are known to cause cardiac metabolic inflexibility and reliance on fatty acids for energy production through PDK4 inhibition of PDH.

Similar to T2DM, increased circulating fatty acids only exacerbates the feed-forward dependency on fatty acid substrates for energy production through the allosteric inhibition of enzymes involved in glycolysis Conversely, the failing heart becomes metabolically inflexible with a decreased capacity to use fatty acids and an increased dependence on glucose metabolism The switch from fatty acid preference to glucose is maintained by increased acetyl-CoA production from pyruvate and subsequent increases in malonyl-CoA concentration, which inhibits CPT-1 and thus FAO Epidemiological evidence shows that through their relation to insulin resistance, excess body weight, and T2DM are associated with an increased risk of pancreatic, liver, and endometrial cancers, among others, and of colon cancer in males Excess body weight increases the risk of cancer via augmented circulating levels of leptin and decreased circulating levels of adiponectin Diet composition is also correlated to development of certain cancers [reviewed in Potter et al.

High-fat diets for instance have particularly been related to increased risk of colorectal , pancreatic , breast , lung , and prostate cancer Additionally, dietary fatty acid exposure increased tumor cell expression of CD36 and increased metastasis in mice Besides diets with a high fatty acid content, diets with a high amount of animal-derived amino acids also increase the risk of cancer in the middle-aged human population Reducing carbohydrate intake reduced tumor growth in mice Currently, clinical studies are under way, but various human studies point toward a reduced incidence of cancer after caloric restriction Our understanding of cancer metabolism has rapidly advanced in recent years.

Most cancer cells show a remarkable metabolic flexibility, which allows a survival advantage in the face of their energetic demand and the environmental supply of nutrients.

Mitochondrial-mediated flexibility is central in this process [reviewed in Vyas et al. Metabolic adaptations that underlie clonal evolution of tumor cells to a metastatic phenotype suggest that tumor cells do not become metabolically hardwired but remain able to reroute metabolism to adapt to their phenotype and the newly acquired environment Indeed, reducing metabolic flexibility in cancer cells may lead to potential treatment options, because metabolic interference can come at a substantial cost to oncogenic potential 1.

Tumors and their environment can be very diverse and, as such, their metabolism and substrate preference is also diverse Common traits, however, include increased glucose consumption via glycolysis and enhanced glutamine metabolism to support the energetic and anabolic demands of proliferation.

Notwithstanding the diversity of cancers, malignant cells share a common metabolic trait, namely that they can acquire and use nutrients from a predominantly nutrient-poor environment, a modus operandi that emerged as a promising target to battle tumors — As a prominent feature of cell activation and proliferation, tumor cells chiefly require increased amounts of glucose and glutamine to survive The metabolic reprogramming that underlies increased glucose consumption for use in glycolysis, as opposed to OXPHOS, is known as the Warburg effect.

In , Otto Warburg discovered that cancer cells metabolize glucose differently than cells of normal tissues: that even in conditions of sufficient oxygen availability, cancer cells convert glucose into lactate instead of using glucose for OXPHOS Warburg hypothesized that cancer cells have mitochondrial defects and impaired aerobic respiration that forces them to rely on glycolysis.

Today, we understand that mitochondrial respiration is not impaired but that cancer cells place emphasis on acquisition and generation of building blocks necessary for cell division. They do so by enhancing biosynthetic metabolism using glycolytic intermediates Interestingly, glucose catabolism in cancer cells is partially uncoupled from the TCA cycle and OXPHOS because increased activity of PDK dampens glucose metabolism through negative feedback on PDH , A glycolytic switch involving differential expression of pyruvate kinase isoforms and stabilization of HIF1 α upregulates rate-limiting enzymes within branching pathways of glycolysis, ensuring that glycolytic intermediates are free to take part in diverse biosynthetic reactions that are essential for increased proliferation These alternative pathways include the PPP using glucosephosphate, hexosamine biosynthesis using fructosephosphate, phospholipid biosynthesis using dihydroxyacetone phosphate, and glycine and serine biosynthesis using 3-phosphoglycerate.

The PPP is chiefly used for NADPH and ribose synthesis to produce nucleotides Lactate, produced from glycolysis, is excreted from the cell or used in biosynthetic reactions such as aspartate synthesis 1.

Aspartate is used to support protein and nucleotide synthesis in proliferating cells and sustains proliferation in the face of OXPHOS impairment Even TCA cycle intermediates are not solely used to produce NADH for mitochondrial respiration, but intermediates can also be used to form nonessential amino acids and fatty acids, which facilitate protein synthesis, membrane construction and cholesterol synthesis Glutamine can either be used as an important anaplerotic substrate in the TCA cycle, a carbon and nitrogen donor, or for production of purine and pyrimidine nucleotides that are necessary for DNA replication Intracellular glutamine can also be used as a substrate for the large neutral amino acid antiporter LAT1.

LAT1 can couple glutamine export with import of essential amino acids. Compared with glucose, glutamine tumorigenesis-associated metabolic reprogramming is only recently becoming clear.

In proliferating cells, the transcription factor Myc is a major driver of glutamine utilization and is frequently targeted for upregulation in various tumors, despite the abundance of glucose.

This glutamine addiction is beneficial for the cancer cell because it maintains mitochondrial TCA cycle integrity and provides the cell with large quantities of NADPH needed to meet the demands of cell proliferation Besides Myc-regulated glutamine addiction, the activity of the Rb tumor suppressor protein family, which negatively regulates glutamine uptake, is reduced, facilitating increased uptake of glutamine.

However, not all tumors are glutamine dependent because some tumors and embryonic stem cells are capable of proliferation without an exogenous supply of glutamine, because they can synthesize it Lifestyle interventions are pertinent for patients with metabolic syndrome.

Most patients with T2DM are overweight or obese and do not exercise frequently. Lifestyle interventions to reduce body weight predominantly include exercise training and controlled reduced caloric intake, but their efficacy depends on age, sex, ethnicity, and body weight upon inclusion As such, caution must be taken when interpreting results when assessing metabolic flexibility using suboptimal methods, because individual variability and experimental setup can considerably influence results.

Physical inactivity is likely one of the primary causes of metabolic inflexibility , ; regular habitual physical exercise has long been known to increase metabolic flexibility 7. As such, exercise training regimens can be used as an intervention to improve metabolic flexibility.

Both promote considerable health benefits such as increased mitochondrial content and improvements in glycemic control For example, a day endurance exercise training regimen increases FAO in the absence of increased mitochondrial content.

A high-intensity exercise training program, however, showed elevated citrate synthase and β -hydroxyacyl CoA dehydrogenase activity after 5 days and increased levels of mitochondrial complexes after 10 days AMPK is an important regulator of exercise-induced effects on metabolic flexibility Acute AMPK activation reduces glycogen and protein synthesis while promoting glucose transport and FAO A higher mitochondrial volume density and improved mitochondrial quality can be seen as consequences of chronic activation of AMPK and expression induction of PGC1 α , myocyte-specific enhancer factor 2 MEF2 , NRF-1 and NRF-2, and nuclear expulsion of histone deacetylase 4 and 5 41 , , Contraction-induced calcium uptake acutely increases OXPHOS 94 , and augments glucose transport and stimulates lipid uptake and oxidation through MEF2-induced expression of GLUT4 and PGC1 α , respectively.

Additionally, PGC1 α is expressed upon muscle contraction-induced activation of p38 MAPK Endurance exercise increases the activity of muscle oxidative enzymes and FAO, in part from increased volume of the mitochondrial reticulum and elevated levels of cardiolipin, a lipid that is necessary for the assembly of OXPHOS complexes 41 , 51 , Regular physical exercise positively influences insulin-stimulated glucose uptake and mitochondrial function in skeletal muscle, and, importantly, in patients with T2DM FAO in skeletal muscle increases during physical exertion independent of body mass index, although regular exercise is likely needed to sustain a long-lasting impact on metabolic flexibility Particularly combined with weight loss, exercise training improves insulin sensitivity, mitochondrial content, and fasting FAO Intriguingly, type II, glycolytic, muscle fiber density is higher in obese and insulin-resistant patients, although it is unknown whether these are due to inactivity or impaired glucose metabolism Observations of reduced PGC1 α , AMPK , and mitofusin-2 expression in insulin-resistant individuals after exercise might provide mechanistic information as to why mitochondrial function improves more in healthy volunteers compared with patients with T2DM and obesity.

Regular exercise can, for instance, reduce adipose cell size and enhance adipose glucose metabolism, resulting in improved insulin sensitivity in both adipose and muscle tissue. Moreover, habitual physical exercise remodels subcutaneous adipose tissue by stimulating browning in mice In rats, chronic endurance exercise induces browning in subcutaneous WAT concomitant with increased mobilization of energy stores, which were attenuated in animals fed high-fat diets.

The browning program initiated by exercise training promoted expression of PPAR α and PPAR γ , AMPK, PGC1 α , and adipose triglyceride lipase Although the exact mechanisms underlying this beneficial effect are still under investigation, exercise training in humans reduced intrahepatic lipid content In mice, PGC1 α is required for an exercise-induced increase in mitochondrial volume density and reduction in intrahepatic lipid content Also, in the human heart, exercise reduces cardiometabolic risk factors by increasing insulin sensitivity, decreasing cardiac lipid content, and improving glucose tolerance In mice, exercise increased cardiac PGC1 α , NRF1, and TFAM expression and augmented mitochondrial volume and number, which were all dependent on endothelial nitric oxide synthase Interestingly, exercise training also drives metabolic adaptations through epigenetic mechanisms.

Short-term, high-intensity exercise decreases muscle promoter methylation of genes involved in mitochondrial function such as PGC1 α , TFAM, MEF2A, and PDK4, whereas in patients with T2DM, these regions usually have higher methylation levels High-fat feeding in mice induced PGC1 α hypermethylation that was transferable to the offspring.

Maternal exercise, on the other hand, prevented high-fat feeding hypermethylation of PGC1 α and mitigated epigenetic associated metabolic dysfunction in the offspring Although more research is necessary, it is clear that regular exercise and exercise training may aid in reversing the pandemic of metabolic disease.

Weight loss is an important step in restoring metabolic flexibility and is the most common intervention for obesity and obesity-related metabolic comorbidities. Generally, energy-restricting diets are aimed at inducing a state of negative energy balance so that stored lipids inside adipocytes are used as alternative substrates Energy-restricting dietary regimens have proven effective in augmenting metabolic flexibility in animal studies and hold promise for application in humans During intermittent fasting, subjects go for extended periods with little or no energy intake, with intervening periods of normal energy intake.

Intermittent fasting in rodents improved insulin and leptin sensitivity increases ketone body levels and reduced adiposity and inflammation CR without hunger- or disease-related malnutrition in animals and humans results in healthier aging through improved metabolic health, reduced obesity, and the risk of T2DM, cancer, and cardiovascular disease Maintaining an energy-restricting diet, however, is challenging, because most people have difficulties maintaining compliance over long periods.

Moreover, a recent study highlighted the paucity of clinical evidence supporting energy-restricting diets in humans Although weight loss is generally achieved in overweight and obese subjects, potential adverse effects exist for leaner subjects Because compliance to energy-restricting diets is challenging, interventions that alter meal timing without reducing total caloric intake are actively pursued.

Popular concepts such as increasing or decreasing meal frequency, however, lack concrete scientific evidence supporting their efficacy Recently, attention has arisen for food intake restricted to the active time phase In rodents, food intake outside the active phase causes obesity, whereas time-restricted feeding protects against obesity and insulin resistance Time-restricted feeding restores both cycling of metabolic regulators such as cAMP response element-binding protein, mTOR and AMPK, and circadian clock gene expression Besides dietary interventions to reduce overall energy intake or restrict energy intake to restricted periods, specific dietary constituents can induce changes in metabolic flexibility.

For instance, carnitine is closely associated with the mechanism of metabolic flexibility Carnitine plays a role in the import of long-chain fatty acids into the mitochondria for use in β -oxidation and in the mitochondrial efflux of excess carbons in the form of acyl-carnitines Mechanistically, during substrate opulence or a deficiency of carnitine or carnitine acetyltransferase, accumulation of acetyl-CoA in skeletal muscle allosterically inhibits PDH resulting in impaired glucose utilization and whole-body glucose tolerance In obese rats, free carnitine in skeletal muscle is decreased and supplementation of l -carnitine restored metabolic flexibility In patients with T2DM, carnitine acetyltransferase expression is severely perturbed and free carnitine concentrations in diabetic mice are decreased compared with controls , Although not yet in clinical practice, l -carnitine supplementation improves metabolic flexibility by decreasing plasma glucose and insulin levels and increasing PDH activity in muscle of insulin-resistant subjects Carnitine metabolism may also be involved in the regulation of mitochondrial protein acetylation, because acetyl-CoA serve as acetyl donors and protein hyperacetylation is observed in high-fat feeding of mice Pharmaceutical approaches to improve metabolic flexibility have been studied in great detail.

Most pharmaceutical therapeutics target major players or key nodes in metabolic circuits, many acting on mitochondrial function The examples that follow provide strong support for continuing the search for future pharmacological principles that enhance metabolic flexibility Fig.

For more details on the mechanisms underlying the beneficial effects of these treatments on metabolic flexibility, we refer the reader to some excellent reviews described in each topic.

A selection of pharmaceutical compounds that target major players or key nodes in metabolic circuits, such as AMPK and sirtuins. Via altered transcription factors, these compounds act on mitochondrial function and positively affect metabolic flexibility.

Ac, acetyl; NA, nicotinic acid; NMN, nicotinamide mononucleotide; NR, nicotinamide riboside; P, phosphate; PARPi, poly ADP-ribose polymerase inhibitor; TF, transcription factor. Metformin is a biguanide and reduces hepatic glucose production and increases insulin sensitivity by activating AMPK, although several AMPK-independent mechanisms have been proposed [reviewed in Pryor and Cabreiro ].

Metformin is one of the first-line treatments of patients with T2DM, but it has also been used to treat patients at risk for T2DM, such as those with metabolic syndrome Resveratrol treatment also increased physical endurance and protected from high-fat diet-induced muscle accumulation of diacylglyceride and ceramide, and related mitochondrial dysfunction Because resveratrol activates mitochondrial biogenesis through the AMPK-SIRT1-PGC1 α axis, it prompts mitochondrial biogenesis, the unfolded protein response, and autophagy machinery that are known to extend longevity in animals 37 , Animal studies have also demonstrated that resveratrol could stimulate energy expenditure and protect against a high-fat diet-induced weight gain , via induction of FAO and reduced lipogenesis, mediated by activation of the AMPK-SIRT1 axis , In the context of insulin-controlled metabolic flexibility, rodent studies largely show improved insulin sensitivity and glucose tolerance in models of obesity, diabetes, and metabolic dysfunction [reviewed in de Ligt et al.

Clinical studies in humans suggest that resveratrol may improve insulin sensitivity and reduce plasma levels of glucose and insulin in patients with T2DM and mimic CR in obese subjects , As such, resveratrol use by humans is particularly beneficial in reversing the early stages of metabolic disorders.

Full confirmation of these beneficial effects in humans by placebo-controlled clinical trials remains relatively limited.

Variation in duration and dose of resveratrol may explain the diverse outcomes of these studies The AMPK agonist 5-aminoimidazolecarboxamide riboside AICAR improves skeletal muscle glucose uptake and transport, fatty acid uptake, mitochondrial protein content, and insulin sensitivity in mice AICAR also rescued mitochondrial function in mice deficient in cytochrome c oxidase and augmented exercise endurance in healthy animals in a PGC1 α -dependent manner, even if they were untrained , Chronic exposure of AICAR reduced white adiposity and increased OXPHOS in rat hearts by increasing PGC1 α expression and FAO , as well as glucose uptake Figure 5 summarizes the potential role of AMPK activators for metabolic flexibility.

SIRT1 and SIRT3 have particularly received attention in this respect. SIRT1 is predominantly found in the nucleus, although it can also be found in the cytosol. SIRT1 controls the activity of transcription factors and cofactors such as p53, MEF2, FOXO, and PGC1 α , which govern mitochondrial biogenesis and activity and lipid and glucose metabolism SIRT3, which is localized in the mitochondrial matrix, targets many proteins involved in metabolic homeostasis, including OXPHOS subunits Acetylation of mitochondrial proteins propagates metabolic inflexibility and deacetylation promotes metabolic flexibility , Additionally, nicotinamide riboside treatment in aging mice increased skeletal muscle function by preventing stem cell senescence, improved mitochondrial function, and a higher expression of genes involved in the TCA cycle and OXPHOS Nicotinamide mononucleotide administration to mice also enhances energy metabolism, promotes physical activity, improves lipid profiles, and ameliorates age-related pathophysiology Moreover, poly ADP-ribose polymerase inhibition rescued mitochondrial respiration defects and increased FAO in myotubes from obese patients by augmenting mitochondrial function PPARs are lipid sensors that transcriptionally modulate metabolic programs in response to nutrition and are interesting drug targets to improve metabolic flexibility [reviewed in Bugge and Holst ].

Fibrates activate PPAR α and are commonly used for treatment of hyperlipidemia. Of the fibrate drug class, fenofibrate and bezafibrate have recently gained interest as interventions to improve metabolic flexibility, in particular for the treatment of insulin resistance.

Fenofibrate improves FAO in primary human skeletal muscle cell cultures from obese and insulin resistant subjects. In vitro and in animal models, PPAR α activation increased expression of PDK and CPT1 In insulin-deficient mice, bezafibrate improves impaired glucose metabolism by augmenting hepatic mitochondrial performance [reviewed in Komen and Thorburn ], suppressing hepatic inflammatory pathways, and improving insulin sensitivity Another PPAR agonist is tesaglitazar, which binds and activates PPAR α and PPAR γ.

Tesaglitazar increases whole-body glucose metabolic insulin action in obese rats by reducing hepatic glucose output, restoring skeletal muscle glucose uptake, and suppressing free fatty acid release by adipocytes Finally, thiazolidinediones, such as rosiglitazone, potently activate PPAR γ and lower blood glucose levels in patients with T2DM.

Thiazolidinediones improve skeletal muscle glucose disposal via upregulation of GLUT1, decrease liver glucose output, and, as a primary target, improve the lipid-buffering capacity of WAT and as such improve hepatic steatosis , However, thiazolidinediones were rapidly sidelined as therapeutics because of their potential adverse effects such as an increased risk of myocardial infarction mTOR is a central regulator of growth and metabolism in all eukaryotes and its activity depends on the cells energy and nutrient levels [reviewed in Laplante and Sabatini ].

In general, anabolic processes such as protein and lipid synthesis, and protein turnover are controlled by mTOR complex 1 mTORC1.

As such, mTORC1 controls the balance between anabolism and catabolism in response to changing environments. mTORC1 facilitates cellular growth by a shift in glucose metabolism from OXPHOS to glycolysis, likely through an mTORC1-mediated increase in the translation of the transcription factor HIF1 α and an increased flux through the PPP, which uses carbons from glucose to generate NADPH and other intermediary metabolites needed for proliferation and growth A reduction in cellular energy charge, such as during glucose deprivation or fasting, inhibits mTORC1 by AMPK-dependent as well as AMPK-independent pathways, and is required for the generation of ketone bodies in the liver Similarly, low levels of amino acids particularly arginine and leucine and interaction with AMPK inhibit mTORC1 activity.

In these ways, energy-consuming processes such as mRNA translation are inhibited during periods of low energy. mTORC2 instead mainly controls cellular proliferation and survival, and has more limited effects on metabolic flexibility per se. Tissue-specific mTOR signaling can have profound effects on whole-body metabolism.

For instance, increased mTOR signaling in either adipose tissue, skeletal muscle, or the liver, negatively affects systemic glucose and insulin homeostasis Indeed, mTOR signaling is dysregulated in cancer, T2DM and obesity, and is therefore actively perused as a promising drug target [reviewed in Laplante and Sabatini and Albert and Hall ].

One compound that particularly received ample attention as an inhibitor of mTOR is rapamycin. Rapamycin is a natural bacterial product that acutely inhibits mTORC1 and, after prolonged treatment, also inhibits mTORC2 in some cell types.

As such, rapamycin has both positive and negative effects on metabolism depending on dose and duration. Short-term rapamycin treatment in mice instigates glucose intolerance, insulin resistance, and immunodeficiency.

Prolonged treatment improves metabolic profiles, increases oxygen consumption and ketogenesis, and markedly enhances insulin sensitivity [reviewed in Li et al.

Additionally, rapamycin has earned great interest over the years to prolong lifespan , , even when administered to aged animals Rapamycin, however, has poor solubility and pharmacokinetics, which led to the production of rapamycin analogs rapalogs , which are currently used in some cancer therapies Manipulating mTOR signaling is, however, very complex, because many positive and negative feedback loops exist, reducing efficacy of mTOR targeting compounds.

Moreover, because mTOR controls many vital cellular processes, its complete inhibition by high doses of rapamycin may negatively affect the maintenance of tissue functions and provoke adverse events Our molecular understanding of mTOR signaling is not yet comprehensive, and future research into rapalogs with fewer pleiotropic and adverse effects is necessary and will likely lead to therapeutics to ease metabolic disease.

Metabolic flexibility can be studied at various levels, from cell to whole-body studies. However, metabolic flexibility is likely best understood as a system of interacting components As such, metabolic flexibility should be measured by the ability to adapt to conditions of temporary stress, such as physical exercise, infections, or mental stress, in a healthy manner To understand metabolism at the system level, cellular metabolic programming, such as biochemical pathways and networks thereof, should be well annotated first.

Metabolic flux analysis, flux balance analysis, and metabolic pathway analysis are among the most popular tools in stoichiometric network analysis and are used extensively to study cancer metabolism , In general, intracellular fluxes are measured using isotope labeling of substrates, after which isotopomer distribution in metabolites can be quantified For instance, mass-isotopomeric flux analysis of glycolysis and the TCA cycle in a rat-derived β -cell line using [U- 13 C]- d -glucose has demonstrated that insulin secretion and oxygen consumption correlate with citrate synthase rates, and pyruvate carboxylase rates showed the highest fold change in response to glucose stimulation, confirming these enzymes as important nodes in glucose metabolism Labeling with [1,2- 13 C]-glucose and [U- 13 C]-glutamine revealed considerable differences in metabolic pathway fluxes between the exponential growth and stationary phase of Chinese hamster ovary cells.

Specifically, glycolytic flux and lactate production was high and PPP flux low in the exponential growth phase, which was collectively reversed in the stationary phase concomitant with lactate consumption and reduced TCA cycle flux.

Interestingly fatty acid biosynthesis remained high in both growth conditions Recent advances in metabolite extraction from isolated mitochondria demonstrate that metabolic flux models can be built with increasing precision Translation of the collected data, however, will likely be the most challenging task in the future Finally, metabolic flexibility modeling can give us insight into the evolution of metabolic pathways , demonstrating that genes encoding enzymes with high connectivity and high metabolic flux have a greater chance of conservation 12 and are the most likely sites of metabolic regulation The continued use of model organisms to understand metabolic flexibility regulation is vital.

Over the past few decades, model organisms such as primates, rodents, flies, nematodes, and yeast have proven their effectiveness in elucidating pathways and regulatory components involved in metabolic flexibility.

In humans, mixed meal tests, glucose clamping, isotope administration, and indirect calorimetry are regularly used to assess metabolic flexibility in intervention studies. Scientists have limited their research on a small number of animal models to further understand metabolic flexibility and its regulation.

Some examples are discussed in the following sections. The round worm Caenorhabditis elegans , for instance, is used to investigate metabolic pathways and has been instrumental in elucidating key genetic regulators of metabolism in relation to lifespan 36 , , Inbred lines have been generated for C.

elegans and, recently, metabolic network models became available , With relative ease, dietary and genetic influences can be simultaneously investigated in C. elegans Moreover, important advances have been made in quantifying the metabolic spectrum in C.

Work in mice and rats has particularly forwarded the field. For example, mice have been the driving force behind research into CR , and the use of recombinant inbred lines such as the BXD mouse strains now offer insights into the role of genetic background effects and can help translate the differences between gene variants into meaningful data for human populations and disease.

The natural variation in gene expression that is present in the human population is also recapitulated in these models and therefore more honestly reflect genotype-phenotype associations than artificial loss-of-function situations, such as gene knockouts or knock-down experiments Moreover, OXPHOS gene expression and supercomplex assembly, and PPAR and cholesterol biosynthesis pathways, which are known to influence metabolic diseases, are highly variable in the BXD population Although rats and mice share a high metabolic homogeneity with humans, they differ in many aspects.

For instance, vitamin C and bile acid synthesis pathways are different in rats and humans Additionally, the discrepancies between sex, or strain variations in sensing and handling of substrates, may convolute the interpretation of data derived from animal model systems Differences in experimental approaches and the techniques used to measure metabolic flexibility may influence outcomes Methodological differences can severely impact interpretation of study data , advocating for a gold-standard application of available methods and technology.

For instance, rodent models are susceptible to temperature and as such can show divergent metabolism depending on their environment. Moreover, cage-housing density of mice can strongly influence glucose metabolism To standardize and validate phenotyping in mice, standard operating procedures were developed by the Eumorphia program to ensure that test outcomes are comparable between different laboratories Finally, many different mechanisms influence metabolism, making the identification of causal mechanisms of metabolic inflexibility challenging.

Therefore, high-quality measurements of multiple complementing layers of data including genomics, transcriptomics, proteomics, metabolomics, and phenomics are needed. Such a multilayered cross-omics approach can help elucidate complex traits associated with metabolic flexibility Through development of mathematical and computational models, systems biology can identify meaningful components and interactions, especially at critical nodes in the network.

As such, systems biological approaches can represent, analyze, and predict the behavior of the whole system A good example of this is the global human metabolic network, Recon 1, which was released in A community-driven reconstruction, Recon 2, was released in and included 65 cell type—specific models In , Recon was updated as Recon 2.

Among other topics, Recon is used to predict biomarkers for inborn errors of metabolism, to identify drug targets and possible side effects, and to study cancer metabolism and the interactions between microorganisms and their host Although the models are not yet all-inclusive, they can yield meaningful insights into the regulation of metabolic flexibility.

For instance, genome-scale models of cancer metabolism can help us comprehend the complexity of human cancer heterogeneity in relation to substrate preference and therefore expedite the discovery of putative anticancer targets Genome-scale metabolic models can also be applied to investigate genetic variation in genotype-phenotype interactions and as such can be used to identify metabolic biomarkers and discover treatments based on genetic markers Recently, a compartmentalized mathematical model of human metabolism, which was not based on Recon 2, was implemented to study the effects of insulin resistance on individual tissues The model describes the transport, storage, and utilization of glucose and fats in the human body and suggested that insulin resistance in one tissue created a knock-on effect in other tissues that tries to compensate for the reduced flexibility.

The model also simulated that insulin resistance causes fatty liver regardless of the site of insulin resistance in the body, and that slightly reduced skeletal muscle metabolic flexibility is caused by insulin resistance of individual tissues, although the strongest effect on muscle metabolic flexibility is observed when the whole body is insulin resistant At the organ level, flux balance computational modeling of muscle metabolism during the fasted to fed state transition showed that key metabolic phenotypes characteristic of human insulin resistance can be recapitulated by decreasing flux through the PDH complex Notably, these observations corroborate knowledge that competition between fatty acids and glucose occurs at the level of the pyruvate dehydrogenase complex Additionally, maximum glycogen accumulation and homeostatic energy demand were found among the most important parameters regulating muscle cell metabolism , which supports previous findings that improving glycogen synthesis strongly influences exercise-induced skeletal muscle insulin sensitivity Collectively, these advances enable us to understand how biochemical networks behave under different conditions and help us identify important actors that can be targeted to eliminate the undesired effects of environmental or inherent factors The wealth of available preclinical data suggests that metabolic flexibility is the cornerstone of many patho biological processes.

It is this wealth, however, that hampers translation to applicable human interventions. Metabolic flexibility occurs at the substrate, cell, tissue, organ, and organism level and is affected by disease, diet, body composition, and many other epigenetic factors.

To gain further insights into our understanding of metabolic flexibility, a coherent, multidisciplinary approach is warranted. Such an approach includes specialists in phenomics, metabolomics, proteomics, genomics, enzymology, molecular biology, bioinformatics, systems biology, clinical genetics, nutrition, whole-cell systems, model systems, and in vivo human studies.

The latter are particularly required to study the metabolically flexible processes to prevent merely superficial and associative data. However, recent studies show that personalized analysis and tailoring of metabolism open up therapeutic possibilities — Supporting this collaboration, current diagnosis and research tools need to be improved, for instance in the field of metabolomics, in which faster and more accurate analyses are needed.

Major advances can be made by combining standalone analyses into combined methods and applying targeted metabolite platforms that cover emerging groups of metabolites, with a primary focus on human translation.

Metabolic flexibility is likely best understood as a system of interacting components to manage energy resources and requirements in health and disease Together with the endocrine system, mitochondria orchestrate the metabolic reprogramming necessary to sustain cell function in both healthy and pathological conditions.

Metabolic flexibility has a broad scope that can be daunting; nevertheless great progress has been made over the past few decades to understand its underpinnings However, because of the complexity of metabolic flexibility, many ends remain untied and solid translational steps are often missing.

The use of isotope labeling to determine metabolic flux and substrate preference is a common practice Flux measurements can aptly portray the dynamics of metabolism, whereas protein and gene expression analyses are typically static snapshots in time.

A biochemical revival of flux metabolism research will surely reveal insights into metabolic flexibility. Unveiling the key denominators of metabolic flexibility as targets for intervention strategies is paramount to stop the rise of metabolic disease.

Besides abating metabolic inflexibility such strategies may even prolong health span and lifespan. To advance translational research from bench to bedside, clinical trials need to be performed that are well-controlled and use state-of-the-art methods to measure metabolic flexibility.

With this review, we have summarized the current status of metabolic flexibility research and realize that, because of the vast amount of literature and the complexity of this research field, it is not comprehensive.

Nonetheless, it is evident that metabolic flexibility can be placed in the broad context of health and disease and a deeper understanding of its intricacies will significantly affect health care. As a final note, the situation portrayed here does not necessarily reflect that of each individual.

Because of the genetic and epigenetic disparity of humans and the enormous varieties in lifestyle, it is not unthinkable that each person fashions a unique way to maintain energy homeostasis.

In light of the rapid developments in the field of nutrigenomics and personalized medicine, future research will likely focus on the union between metabolic flexibility and personalized medicine. Clearly, there is still much work to be done, yet interesting times lie ahead.

peroxisome proliferator—activated receptor γ coactivator 1- α. Disclosure Summary: The authors have nothing to disclose. Olson KA , Schell JC , Rutter J.

Pyruvate and metabolic flexibility: illuminating a path toward selective cancer therapies. Trends Biochem Sci. Google Scholar. Speakman JR. Evolutionary perspectives on the obesity epidemic: adaptive, maladaptive, and neutral viewpoints. Annu Rev Nutr. López-Otín C , Galluzzi L , Freije JMP , Madeo F , Kroemer G.

Metabolic control of longevity. Muoio DM. Metabolic inflexibility: when mitochondrial indecision leads to metabolic gridlock. World Health Organization. Global report on diabetes. Available at: www. Accessed 24 April doi 92 4 7. International Food Policy Research Institute. Global Nutrition report from promise to impact ending malnutrition by Saltin B , Gollnick PD.

Skeletal muscle adaptability: significance for metabolism and performance. In: Peachy L , Adrian R , Geiger S , eds. Handbook of Physiology: section Skeletal Muscle. Bethesda, MD : American Physiological Society ; : — Google Preview. Kelley DE , Goodpaster B , Wing RR , Simoneau JA.

Skeletal muscle fatty acid metabolism in association with insulin resistance, obesity, and weight loss. Am J Physiol.

Kelley DE , Mandarino LJ. Fuel selection in human skeletal muscle in insulin resistance: a reexamination. Battaglia GM , Zheng D , Hickner RC , Houmard JA.

Effect of exercise training on metabolic flexibility in response to a high-fat diet in obese individuals. Am J Physiol Endocrinol Metab. Obre E , Rossignol R. Short sleep also increases hunger hormones. The extra sugar provides quick energy for fleeing a crazed hippopotamus but hampers your long-term health goals.

Keep stress in check with meditation, yoga, deep breathing, email avoidance, and other time-tested relaxation methods. And for real-time feedback on your metabolic flexibility, check out a new device called Lumen.

Pretty cool. If metabolic flexibility is the big hairy goal, what small, achievable steps should you take to reach it? In other words, what micro goals will lead to your desired result?

The micro goals should relate to the metabolic health boosters we talked about earlier: diet, sleep, intermittent fasting, stress reduction, and exercise. Your long-term health will appreciate it.

Disclaimer: This article contains affiliate links. Carb Manager may earn a commission for qualifying purchases made through these links. BlithesomeKetone a year ago. GrammyBev49 a year ago. Good explanations and recommendations in this article. SuperCauliflower a year ago.

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Gendreau Author and Scientific Reviewer. What Is Metabolic Flexibility? Insulin and Metabolic Flexibility Insulin is your master energy hormone, blood sugar boss, and fatty acid partitioner-in-chief. Access body fat for fuel and kiss the 4-o-clock slump goodbye.

Reduced cravings. Less reliance on glucose blood sugar for energy means fewer appetite swings. Fat loss. If you want to lose fat, it may help to increase your fat-burning capacity. Mental clarity.

Burning fat produces ketones that fuel your brain with clean, efficient energy. fasted state And for real-time feedback on your metabolic flexibility, check out a new device called Lumen.

Tracking Metrics for a Healthier Metabolism If metabolic flexibility is the big hairy goal, what small, achievable steps should you take to reach it? With Carb Manager, you can: Track macros and log meals to reduce your carb or calorie intake Optimize your fasting routine with our IF tracker Stay accountable by logging exercise and syncing your favorite fitness devices Prioritize sleep with our sleep tracking system And much more.

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To identify significant independent determinants of metabolic flexibility, we performed multiple regression analysis. We evaluated metabolic flexibility in youth with impaired glucose regulation prediabetes and type 2 diabetes compared with obese youth with normoglycemia and NW peers and evaluated the metabolic determinants of metabolic flexibility in these youth.

Our study demonstrates that youth with prediabetes and type 2 diabetes have impaired metabolic flexibility compared with youth with obesity and normoglycemia and with NW. This metabolic inflexibility is related to impairment in glucose and lipid metabolism, with inflexibility in suppressing fat oxidation by insulin and a defect in glucose transport in youth with impaired glucose regulation.

This suggests that metabolic inflexibility or defect in substrate utilization becomes manifest at the extreme of the metabolic phenotype in obese youth with more severe impairment in IS. Our finding of no significant differences in metabolic flexibility between youth with NW and with obesity and NGT is consistent with the observation that youth with NW or obesity are able to adapt to changes in macronutrient intake and increase substrate oxidation glucose vs.

fat oxidation in response to short-term changes in metabolic fuels through dietary manipulation 12 , However, our youth with prediabetes and type 2 diabetes manifested impairment in metabolic flexibility, with lower oxidative and nonoxidative glucose disposal and less suppression of fat oxidation in response to hyperinsulinemia, compared with the NGT and NW groups.

Peripheral IS independently contributed to the variance in metabolic flexibility in our study. The marked reduction in glucose disposal and peripheral IS in youth with prediabetes and type 2 diabetes compared with similarly obese youth with NGT and with NW peers is consistent with our previous reports In a study of obese youth with NGT pair matched for adiposity, those who were more insulin sensitive above the median glucose disposal rate during the clamp had greater metabolic flexibility However, in the latter study, the reduced suppression of lipid oxidation during hyperinsulinemia did not differ in the insulin-sensitive versus -resistant groups Perseghin et al.

reported lower fat oxidation in the fasting state and less suppression in fat oxidation in response to glucose challenge in youth with nonalcoholic fatty liver disease compared with obese peers without fatty liver, indicating impaired metabolic flexibility in nonalcoholic fatty liver disease 22 , a condition associated with reduced multiorgan IS 23 , In a previous study, we found that normoglycemic obese youth with severe versus moderate insulin resistance had less suppression of fat oxidation and less increase in glucose oxidation during the clamp Our study advances these findings to youth across the glycemic spectrum and demonstrates that the defect in metabolic flexibility is associated with the degree of impairment of glucose disposal i.

Our findings are consistent with the findings of Galgani et al. in adults with type 2 diabetes compared with obese controls 5.

In that study, the difference in metabolic flexibility between the 2 groups was no longer significant after adjusting for glucose disposal rate and was corrected after weight loss 5. The authors concluded that a defect in glucose transport was responsible for the metabolic inflexibility, rather than a primary defect in glucose oxidation.

Similarly, in adults with type 2 diabetes compared with obese controls, insulin-stimulated glucose oxidation during the hyperinsulinemic clamp was determined by insulin-stimulated glucose uptake 25 , suggesting that the primary defect is in substrate availability secondary to limitation in substrate transport.

In vivo mitochondrial function measured by phosphocreatine recovery kinetics was related only to basal substrate oxidation and was not a significant predictor of insulin-stimulated metabolic flexibility Nevertheless, skeletal muscle mitochondrial content was found to be a marker of metabolic flexibility Although HbA1c was related to ΔRER, the effect of glycemia was not significant in the multivariable analysis, suggesting that IS is the primary determinant of metabolic inflexibility in these youth early in the diabetes disease process and in relatively adequate glycemic control.

These findings are consistent with those in adults where ΔRER correlated with IS after adjusting for glycemia but not after adjustment for FFA Another important finding is that fatty acid metabolism plays an important role in metabolic flexibility.

The youth with obesity had significantly lower adipose tissue IS and higher fasting FFA compared with the NW group. Postabsorptive fat oxidation adjusted for lean and fat mass, Tanner stage, sex, and race was significantly higher in the youth with obesity compared with NW.

This is consistent with prior reports of higher fat oxidation in children with obesity compared with NW and the importance of both lean and fat mass as determinants of fat oxidation Higher fat oxidation in the obese state has been hypothesized to be a mechanism to limit further weight gain based on longitudinal studies in Pima Indians This may still be operational in youth as opposed to adults with obesity in whom fasting lipid oxidation is lower than in lean individuals at the total body level 3 and across the leg muscle bed 3.

Importantly, there was impairment of suppression of fat oxidation under hyperinsulinemic conditions and higher steady-state FFAs in the groups with dysglycemia compared with the groups with obesity and NGT and with NW. In our study, the reduced suppression of FFAs under hyperinsulinemic conditions was independently related to lower ΔRER, supporting the contribution of impaired suppression of fat oxidation to the metabolic inflexibility in the youth with prediabetes and type 2 diabetes.

An impaired capacity to regulate fat oxidation in response to high-fat feeding was reported in the obese insulin-resistant state High-fat diet and increased fat flux in insulin-sensitive humans and in mice were associated with reduction in the expression of genes involved in oxidative phosphorylation, possibly through reduction in insulin signaling Moreover, acute lipid infusion increasing FFAs is known to impair IS in adults and children 33 , Our results indicating an effect of FFA independent of IS on ΔRER are consistent with previous studies where elevated FFAs in adults with type 2 diabetes versus controls contributed to metabolic inflexibility 5 , Our findings of impaired metabolic flexibility only in the youth with more extreme phenotype of impaired IS prediabetes and type 2 diabetes compared with NW, with no significant difference in metabolic flexibility between the groups with NW and with obesity with NGT, supports the conclusion that the primary defect in metabolic flexibility lies in substrate availability related to reduction in glucose uptake and impaired fatty acid metabolism 5 , It remains unclear if metabolic inflexibility may be a primary cause of insulin resistance at least in some individuals with genetic predisposition.

Also in Pima Indians, increased clamp lipid oxidation predicted diabetes prospectively, after adjustment for relevant confounders including glucose disposal, acute insulin response, age, sex, and body fat The limitations of this study are inherent to the cross-sectional study design, which limits the assessment of the evolution of the metabolic abnormalities.

We used higher insulin infusion rate during the hyperinsulinemic clamp in the groups with obesity compared with the NW group. Despite the higher clamp insulin concentration in the groups with obesity, they had less responsiveness to insulin in substrate utilization, further supporting our conclusions.

In adults, studies have found racial differences in metabolic flexibility, with AAs having higher ΔRER compared with Whites, after adjusting for IS and diabetes status In conclusion, metabolic inflexibility is a feature of a more severe metabolic phenotype in obese youth who have more severe impairment in IS and altered glucose metabolism, i.

This is related to a defect in substrate utilization associated with reduced skeletal muscle and adipose tissue IS. Our findings support the use of metabolic flexibility as an outcome measure in assessing metabolic risk and the response to interventions aiming at improving metabolism.

Additional studies are needed to assess the predictive value of metabolic flexibility in metabolic risk.

Study participants. A total of adolescents, The mean duration of diabetes was Oral hypoglycemic agents and long-acting insulin therapy were discontinued 48 hours prior to study as before Short-acting insulin was administered as necessary up to 6 hours prior to OGTT or clamp to maintain glycemic control.

Participants were weight stable, not enrolled in scheduled physical activity or dietary intervention. They were instructed to refrain from participation in physical activity for 48 hours prior to admission to the research unit.

They were excluded in the presence of other diseases or chronic medication that could interfere with endocrine function or if pregnant. Participants were admitted to the MRU 24 hours prior to the clamp study. Anthropometric measurements. Standard anthropometric measurements were measured from the eligible participants.

Height was measured on a fixed wall stadiometer Holtin Ltd. to the nearest centimeter 3 times and then averaged. Weight was measured in light clothing to the nearest 0. Waist circumference was measured at the midline from the inferior margin of the last rib and the crest of the ileum to the nearest 0.

Although the response to meals was similar between the 2 subgroups, RQ and non-protein RQ during sleep were lower in the subjects with metabolic flexibility than in subjects with metabolic inflexibility Fig.

Accordingly, metabolically flexible subgroup oxidized more fat and less carbohydrate during the night Fig. Subjects took breakfast or , lunch , or , and dinner , and slept for 7 h —, grey bars.

e — h Absolute differences between metabolically flexible and inflexible subgroup were plotted against mean of the two subgroups for RQ, energy expenditure, carbohydrate oxidation and fat oxidation. Values during sleep were shown as filled symbols filled black circles.

Visual inspection of the time course of RQ suggested that the difference in RQ between the 2 subgroups became clearer when RQ of both subgroups was lower; in the late afternoon and during sleep. Absolute difference of RQ between the 2 subgroups was negatively correlated with mean values of the 2 subgroups, and similar negative correlation was also observed in carbohydrate oxidation Fig.

On the other hand, in energy expenditure and fat oxidation, difference between the 2 subgroups was not correlated with mean of the 2 subgroups Fig. Collectively, differences in energy metabolism between metabolically flexible and inflexible subgroups emerged as difference in fuel selection at midnight.

In addition to 41 men without obesity assessed for metabolically flexible and inflexible subgroups in a previous section 19 , 20 , 21 , 22 , another 12 male subjects aged The average RQ over the entire calorimetry was not significantly different between the 2 age groups 0.

Similarly, average non-protein RQ over the entire calorimetry was not significantly different between the 2 age groups 0. Compared to younger group, RQ and non-protein RQ were higher in older group during sleep Fig. Average energy expenditure over the 23 h in older group 1. There was no significant difference in substrate oxidation Fig.

Heart rate and autonomic nervous system activity were not statistically different between the two age groups Appendix Fig. Time course of energy metabolism in two age groups of 10 years apart. Subjects took breakfast , or , lunch , or , and dinner , and slept for 7 or 8 h from grey bars.

Because of unequal duration of sleeping period, the 8th hour of sleep in one experiment was not included for statistical analysis 9.

e — h Absolute difference between two age groups were plotted against mean of the two subgroups for RQ, energy expenditure, carbohydrate oxidation and fat oxidation. Values during sleep were shown as filled symbols filled blue circles.

RQ and core body temperature follow U-shaped time course during sleep. Since a sex difference exists in the time course of body temperature during sleep 11 , 12 , 13 , we compared time course of sleeping energy metabolism between men and women.

Men age Subjects slept for 7 h from to The women participated in the study during the follicular phase. The average RQ over the 24 h was similar between men 0. In both men and women, RQ and non-protein RQ decreased during sleep, and began to increase prior to awakening.

The increase in the RQ during sleep seemed to be earlier in women than in men, and RQ at 5th and 7th hour of sleep was significantly higher in women than that in men Fig. Energy expenditure, and substrate oxidation were higher in men than women reflecting the difference in their body size There were no significant differences in heart rate and its variability between men and women Appendix Fig.

e — h Relation between the mean and SE of RQ e , energy expenditure f , carbohydrate oxidation g and fat oxidation h of men blue filled circles and women red open circles. Negative correlation in RQ and positive correlation in energy expenditure, carbohydrate oxidation and fat oxidation were observed between the mean and SE.

We noticed that individual variation, reflected as SE in each group, changed throughout the day. Standard error of RQ became larger when mean value is low; after overnight fasting before breakfast, in the late afternoon and during sleep.

individual variation became clearer when RQ is low Fig. The U-shaped time course during the night were observed in RQ, and the increase in the RQ during sleep seemed to be earlier in women than in men. The time between bedtime and the nadir of the RQ 5-min period of the lowest value was compared between men and women by applying statistical rigor to our database of sleeping energy metabolism.

Data for 79 men and 36 women were collected from our previous studies with 24 h indirect calorimetry 18 , 19 , 20 , 21 , 22 and indirect calorimetry over an entire sleeping period 8 , 23 , 24 , The nadir of RQ was observed significantly earlier in women than in men, while the nadir of energy expenditure was observed significantly later in women than in men Table 2.

Time course of core body temperature was available for 30 men and 18 women 21 , 22 , 23 , 24 , and nadir was observed significantly earlier in women than in men.

Differences in RQ between metabolically flexible and inflexible subgroups emerged at midnight, and there was a sex difference in time course of RQ during the night. These observations led us to relate metabolic data with sleep architecture. Sleep followed characteristic cyclic changes in the sleep stage, termed the sleep cycle; after the first sleep cycle, SWS gradually decreased and was replaced by REM sleep in men and women Fig.

Despite the similar sleep architecture between men and women in this dataset, nadir of RQ after bedtime was observed significantly earlier in women 2. Cumulative display of sleep architecture during simultaneous assessment of energy metabolism.

The percentage of subjects in each sleep stage is shown for men upper panel and women lower panel. The total number of subjects was 38 men and 27 women 11 in follicular phase, 11 in luteal phase, and 5 cases without record.

Subjects slept for 8 h in a metabolic chamber for indirect calorimetry 8 , 23 , 24 , In this dataset, the nadir of the RQ was 3. We retrospectively analyzed the data of previous studies. In all studies, subjects took dinner 5 h before bedtime, but details of experimental protocol were not identical: differences in time of breakfast or and lunch , or and time in bed 7 h or 8 h.

Polysomnographic recording of sleep, thermometry and continuous glucose monitoring were not performed in every study. A key aspect of the present study is that it is based on indirect calorimetry in adults without obesity.

Obviously, additional data of subjects with obesity or diabetes helps to understand pathogenesis of metabolic inflexibility, insulin resistance and diabetes. Fuel selection in the body is estimated from the RQ, i. RQ is a dimensionless quantity, allowing for comparison between subjects of different body sizes such as men and women.

A higher RQ implies carbohydrate oxidation whereas a lower RQ reflects fat oxidation. To focus on the selection between carbohydrate and fat as substrate for oxidation, non-protein RQ is preferred rather than RQ.

However, there is one caveat that time resolution of urinary nitrogen excretion, with which non-protein RQ was calculated, is low.

Time course of non-protein RQ Appendix Fig. On the whole, RQ during sleep is lower than that when awake, and this is underscored by reduced levels of glucose and insulin during sleep A closer look at the time course of the RQ during sleep, however, revealed that RQ begins to increase prior to awakening.

Protein oxidation is estimated from the urinary excretion of nitrogen, and it is possible that protein catabolism and oxidation increase as fasting continues. The increase in RQ above this level, therefore, cannot be attributed to increased protein oxidation.

Collectively, the time course of the RQ during sleep suggests that oxidized substrates shift from fat to carbohydrate before awakening in a sex-specific manner, despite prolonged fasting. A circadian component of energy metabolism was demonstrated by a forced desynchrony protocol, in which subjects experienced a 3-week h rest-activity schedule The nadir of RQ was in the late biologic evening , earlier than we observed during 24 h indirect calorimetry.

The amplitude of the circadian component of the RQ assessed by cosinor regression was 0. More importantly, the identity of the mechanisms underlying circadian changes in the RQ is not known.

Along with cyclic transitions of sleep stages, the dominant sleep stage gradually shifts from SWS to stage 2 and REM sleep over the entire sleeping period, and there are short periods judged as wake based on electroencephalography, i.

wake after sleep onset Fig. In our previous study, the time course of energy metabolism during sleep was decomposed into the effect of sleep stages and the effect independent of sleep stages, i. Reflecting various physiologic changes during REM sleep and wake after sleep onset, energy expenditure during these sleep stages was higher than that during SWS.

However, the differences in the RQ among sleep stages were not significant 8. The findings from simultaneous assessment of sleep and energy metabolism in the present study were as follows. First, an increase in the RQ was observed during the night while confirming normal sleep patterns through electroencephalogram recordings.

This excluded possible experimental artifacts, such as difficulties in maintaining sleep in the experimental setting, affecting sleeping energy metabolism.

Second, sex differences in the sleep architecture are reported in some studies 15 , 16 , although another study found no differences in the sleep architecture between sexes In the present study, sleep architecture was similar between men and women, whereas the time of the nadir of the RQ during sleep was significantly earlier in women than in men.

Therefore, the sex-specific time difference in the increase in the RQ before awakening is not likely related to the differences in sleep architecture between men and women. Energy homeostasis depends on the substrate supply and demand 7 , the response to which is manifested as metabolic flexibility.

A number of studies measured circulating levels of metabolites during sleep. Despite prolonged fasting, blood glucose levels remain stable during sleep On the other hand, free fatty acid FFA levels peak in the middle of the sleep period and decline again toward the beginning of the next wake period This transient increase in circulating FFA may underlie the increase in its oxidation in the middle of the night, i.

Sex differences in the time course of circulating FFA have not been evaluated. Among lipolytic and antilipolytic hormones, the levels of epinephrine, norepinephrine, and insulin remain low during sleep 29 , The plasma adrenocorticotropic hormone ACTH concentration increases during the second half of sleep 34 , ruling out a possible causal link between ACTH secretion and elevated circulating FFA.

The time course of the RQ during sleep shares common features with that of core body temperature, which reaches its nadir at midnight and begins to increase prior to awakening. Time course of RQ and core body temperature was highly correlated, and time of the nadir of these two variables during sleep was significantly correlated.

These observations suggest that both rhythms are under control of the same endogenous circadian pacemaker. Core body temperature is regulated by an endogenous pacemaker in the hypothalamic suprachiasmatic nuclei The suprachiasmatic nuclei also drives the circadian rhythm of melatonin and cortisol, both of which are considered reliable markers of the master clock of the body 36 , Interestingly, the circadian rhythm of melatonin, but not of cortisol, shows a sex difference.

Melatonin secretion begins and ends earlier in women than in men 12 , Melatonin is not categorized as a classical lipolytic hormone. The physiologic concentration of melatonin stimulates lipolysis in porcine and bovine intramuscular adipocytes 39 , 40 , but inhibits lipolysis in rat inguinal adipocytes in a site-specific manner Discrepancies in the effect of melatonin on lipolysis seem to be related to differences between diurnal porcine, bovine and nocturnal animals rat.

Sex steroids are obvious mechanistic candidates underlying the time course of the RQ in a sex-specific manner. Despite dynamic changes in estrogen and progesterone levels during the menstrual cycle, the time of the nadir in the RQ is comparable between the follicular and luteal phases 23 , and earlier in women than in men in the present study.

An earlier timing of body temperature rhythm changes relative to the sleeping period in women compared with men was reported in young 12 and older subjects 42 , although postmenopausal women presumably had lower circulating ovarian steroid levels.

Testosterone increases during sleep 43 , but an acute effect of testosterone has little effect on either serum FFA or the RQ Therefore, ovarian and testicular steroids are unlikely to be directly involved in upregulating the RQ during sleep.

The concentrations of other hormones also change at midnight; leptin peaks and cortisol begin to increase at midnight Leptin, which stimulates glucose oxidation, declines when the RQ begins to increase during the second half of the sleeping period.

Cortisol increases blood glucose levels through gluconeogenesis, but its effect on glucose oxidation to increase the RQ is not established. Of note, there is no sex difference in the phase angle of the circadian rhythm of leptin 45 or in the cortisol concentration To our knowledge, melatonin is the only hormone that meets the requirement to explain time course of RQ during sleep; association with a decreased RQ during sleep, and a sex difference in its diurnal rhythm.

According to the above discussion, the diurnal rhythm of the RQ comprises several components. First, changes in the nutritional state, from fed to fasted, set the tone for a gradual decrease in the RQ during sleep.

As the third unidentified factor, homeostatic mechanisms regulating sleep may underlie the U-shaped time course of the RQ during sleep. A large number of substances tested for their effects on wakefulness and sleep have effects on hunger, satiety, and energy metabolism Neurosubstances, including orexin, serotonergic substances, insulin, leptin, neuropeptide Y, interleukin-6, and bombesin, have multiple roles in sleep and energy metabolism.

It is plausible that actions of these neurosubstances change as sleep drive decreases after sleep onset, and that energy metabolism is affected in turn.

The relation between the actions of these neurosubstances and sleeping energy metabolism remains to be addressed in human studies. Of note, we observed that an orexin receptor antagonist induces sleep, modifies sleep architecture, and suppresses energy expenditure As a working hypothesis, it has been proposed that certain characteristics of energy metabolism, which include the RQ, may precede the obese state and contribute to its development Subjects who are in energy balance are also in substrate balance; the RQ measured over the 24 h period is equal to the food quotient, the theoretical RQ produced by the diet As a consequence, h RQ assessed under a weight-stable and diet-controlled condition is not a predictor of future weight gain 49 , Even when the energy balance is maintained over the 24 h, the nutritional state alternates between postprandial and postabsorptive.

Inflexibility in adjusting the RQ to transient changes in the nutritional state within a day may be a metabolic characteristic that precedes an obese state. Considering the findings of the present study in young subjects without obesity in the context of the pathogenesis of metabolic syndrome, it is noteworthy that difference in RQ between metabolically flexible and inflexible subgroup became significant only during sleep without noticeable differences in RQ after overnight fasting or the response of the RQ to meal consumption Fig.

Individual difference in RQ became prominent when the RQ was lower during sleep Fig. The strong effects of meal consumption on blood glucose and subsequent insulin secretion increase the RQ and mask individual differences during the daytime.

Similarly, the effect of 10 years difference in age and sex difference in time course of RQ became significant during sleep Figs. Thus, inter-individual variations of RQ expands at midnight, and sleeping RQ might serve as a window to gain insight into the early-stage pathogenesis of metabolic inflexibility.

It is of note that average energy expenditure over the 23 h in older group was slightly lower than that of younger group although the difference was not statistically significant Fig.

Decrease in energy expenditure over a decay was not detected with statistical significance, while blunted decrease of RQ during sleep was detected in the present study.

According to the difference between h and sleep RQ, Mynatt et al. classified subjects as metabolically flexible 8 men and 8 women and metabolically inflexible 7 men and 8 women 6. BMI, homeostatic model assessment of insulin resistance, and mean RQ over the 24 h were similar between the 2 groups, but subjects with metabolic inflexibility had a higher sleep RQ 0.

Analysis of global skeletal muscle gene expression revealed that transcripts regulated by the RNA binding protein HuR were enriched in metabolically flexible subjects. Silencing HuR in human myotubes induced a metabolically inflexible phenotype, suggesting a role for HuR as a regulator of metabolic flexibility in skeletal muscle metabolism.

Thus, the lower amplitude of the h RQ rhythm due to elevated nocturnal values is an early-stage phenotype of metabolically inflexible individuals. Based on the data collected using a whole-room indirect calorimetry, the present study showed that sleeping energy metabolism is not simply the result of prolonged fasting.

The observed sex difference in the time course of RQ during sleep narrowed down the possible mechanisms underlying the upregulation of glucose oxidation during the latter part of the sleeping period, and suggests a possible role of melatonin.

Exogenous melatonin lowers the body temperature and promotes sleep in humans 52 , 53 , but elevates body temperature and increases the activity level and waking in nocturnal mammals 54 , Together, these lines of thought open avenues for further investigations of sleeping energy metabolism in humans by monitoring melatonin levels or intervening with melatonin secretion.

Inter-individual variability in the time course of the sleeping RQ may be an upstream event of the cascade that leads to obesity, diabetes, and metabolic diseases. To examine the components of the metabolic flexibility, Galgani et al.

Time course of plasma β-hydroxybutyrate and FFA during sleep was not available in the present study, and remained to be evaluated. One of the promising future directions is combining indirect calorimetry with omics studies to reveal the physiologic mechanism underlying individual differences in metabolic flexibility.

Tissue samples provide valuable information for clarifying the mechanism underlying individual variations in the RQ. Global skeletal muscle gene expression profiles by Mynatt et al. suggest a role of the RNA binding protein HuR underlying individual differences in the sleeping RQ 6.

Interestingly, in male mice, but not female mice, with skeletal muscle-specific knockout of the HuR-encoding gene exhibit metabolic inflexibility, with mild obesity, impaired glucose tolerance, and impaired fat oxidation, compared with control littermates. Sexual dimorphism in the role of HuR remains to be studied.

Metabolome analysis of urine and blood samples should be seriously considered. Particularly, urine samples are routinely collected to assess urinary nitrogen excretion, and taking advantage of this information would be a practical approach.

Another potential direction for future studies is an analysis of energy metabolism in larger and more heterogeneous populations. The present study was based on recordings of indirect calorimetry in adults without obesity and the majority of the subjects were in their 20 s.

The primary focus of these studies was not on metabolic flexibility or the time course of the RQ during sleep, but analysis of pooled data provided insight into the pathogenesis of the early stage of metabolic inflexibility. An international effort to set up a database for energy expenditure assessed by a doubly-labeled water method, the gold standard method for measuring energy expenditure in a free-living condition, has launched Why not pool the data of the other branches of indirect calorimetry, such as whole-room indirect calorimetry?

A guidance to ensure consistency and facilitate meaningful comparisons of human energy metabolism studies across publications, laboratories, and clinical sites has recently been proposed Kelley, D. Hyperglycemia normalizes insulin-stimulated skeletal muscle glucose oxidation and storage in noninsulin-dependent diabetes mellitus.

Article CAS PubMed PubMed Central Google Scholar. Skeletal muscle fatty acid metabolism in association with insulin resistance, obesity, and weight loss. CAS PubMed Google Scholar. Fuel selection in human skeletal muscle in insulin resistance: Reexamination.

Diabetes 49 , — Article CAS PubMed Google Scholar. Galgani, J. Metabolic flexibility and insulin resistance. CAS Google Scholar. Goodpaster, B. Metabolic flexibility in health and disease. Cell Metab. Mynatt, R. et al. impaired metabolic flexibility underlies insulin resistance.

This Research Topic in Metabolic Flexibility aimed to attract studies providing insights about determinant factors of metabolic flexibility and the health consequences of being metabolically inflexible.

In this regard, Glaves et al. conducted a systematic review on the association between adipose tissue features e. total amount, distribution and metabolic flexibility. Such research work faced the challenge of comparing studies that conceived different settings and markers of metabolic flexibility.

This heterogeneity in assessing metabolic flexibility has dampened the possibility of conducting comprehensive inter-study data analysis, for instance, through meta-analyses, a crucial tool to ponder the overall relevance of individual studies. From this systematic review, Glaves et al.

noted that adipose tissue total amount, waist circumference, and visceral fat were associated with metabolic flexibility, mainly when assessed by using the classic euglycemic clamp method.

Which functional aspects of adipose tissue can directly influence and explain such associations remain elusive. One may speculate that adipose tissue amount, distribution, or both could influence circulating adipokines and metabolites, affecting oxidative tissue capacity and tissue fuel availability i.

metabolic flexibility. Kalafati et al. conducted additional work on adipose tissue by taking advantage of publicly available datasets. They assessed the contribution of relative macrophage frequencies on overall subcutaneous adipose tissue gene expression.

Their analysis showed that subcutaneous adipose tissue from donors with high macrophage frequencies displayed increased inflammatory gene expression profile and decreased gene expression of lipid- and mitochondrial respiration-related pathways. From these studies, one may speculate that impaired metabolic flexibility could be one of the systemic consequences of such differential enrichment in adipose tissue macrophages.

Another study of this Research Topic Fernández-Verdejo et al. assessed volunteers of similar sex and age, who had the same excess body weight and composition, but contrasted metabolic flexibility to an oral glucose load. In general, such contrasting metabolic flexibility did not associate with differences in metabolic health.

However, metabolically flexible vs. inflexible individuals showed elevated abdominal subcutaneous fat depot and faster blood triglyceride clearance. This study may support the notion that adipose tissue fat storage capacity determines metabolic flexibility and health, as demonstrated in mice 3.

Lactate captured attention in two publications included in this Research Topic, where lactate may serve as a potential circulating biomarker of metabolic flexibility. Still, more elaborated studies are required to understand lactate dynamics and its link to metabolic flexibility.

The review by Zeng et al. reports on pyruvate dehydrogenase as a metabolic hub controlling lactate production. They proposed that pyruvate dehydrogenase could be a potential therapeutic target that can render benefit in extreme metabolic conditions such as sepsis.

Lessons from that model may eventually translate to less extreme metabolic conditions. Lactate was also the focus of study in the original publication by San-Millan et al. The authors speculated that high lactate concentration might impair metabolic flexibility.