MECHANISMS IN ENDOCRINOLOGY: SGLT2 inhibitors: clinical benefits by restoration of normal diurnal metabolism?

in European Journal of Endocrinology
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Russell L EsterlineAstraZeneca Pharmaceuticals, Gaithersburg, Maryland, USA

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Allan VaagCardiovascular and Metabolic Disease (CVMD) Translational Medicine Unit, Early Clinical Development, IMED Biotech Unit, AstraZeneca, Gothenburg, Sweden

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Jan OscarssonAstraZeneca Pharmaceuticals, Gaithersburg, Maryland, USA

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Jiten VoraRoyal Liverpool University Hospital, University of Liverpool, Liverpool, UK

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Correspondence should be addressed to J Vora; Email: jitenvora@btinternet.com
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Type 2 diabetes (T2D) is associated with inhibition of autophagic and lysosomal housekeeping processes that detrimentally affect key organ functioning; a process likely to be exacerbated by conventional insulin-driven anabolic therapies. We propose that the cardio-renal benefits demonstrated with sodium–glucose cotransporter-2 inhibitor (SGLT2i) treatment in T2D partly may be explained by their ability to drive consistent, overnight periods of increased catabolism brought about by constant glucosuria. Key steps driving this catabolic mechanism include: a raised glucagon/insulin ratio initially depleting glycogen in the liver and ultimately activating gluconeogenesis utilizing circulating amino acids (AAs); a general fuel switch from glucose to free fatty acids (accompanied by a change in mitochondrial morphology from a fission to a sustained fusion state driven by a decrease in AA levels); a decrease in circulating AAs and insulin driving inhibition of mammalian target of rapamycin complex 1 (mTORC1), which enhances autophagy/lysosomal degradation of dysfunctional organelles, eventually causing a change in mitochondrial morphology from a fission to a sustained fusion state. Resumption of eating in the morning restores anabolic biogenesis of new and fully functional organelles and proteins. Restoration of diurnal metabolic rhythms and flexibility by SGLT2is may have therapeutic implications beyond those already demonstrated for the cardio-renal axis and may therefore affect other non-diabetes disease states.

Abstract

Type 2 diabetes (T2D) is associated with inhibition of autophagic and lysosomal housekeeping processes that detrimentally affect key organ functioning; a process likely to be exacerbated by conventional insulin-driven anabolic therapies. We propose that the cardio-renal benefits demonstrated with sodium–glucose cotransporter-2 inhibitor (SGLT2i) treatment in T2D partly may be explained by their ability to drive consistent, overnight periods of increased catabolism brought about by constant glucosuria. Key steps driving this catabolic mechanism include: a raised glucagon/insulin ratio initially depleting glycogen in the liver and ultimately activating gluconeogenesis utilizing circulating amino acids (AAs); a general fuel switch from glucose to free fatty acids (accompanied by a change in mitochondrial morphology from a fission to a sustained fusion state driven by a decrease in AA levels); a decrease in circulating AAs and insulin driving inhibition of mammalian target of rapamycin complex 1 (mTORC1), which enhances autophagy/lysosomal degradation of dysfunctional organelles, eventually causing a change in mitochondrial morphology from a fission to a sustained fusion state. Resumption of eating in the morning restores anabolic biogenesis of new and fully functional organelles and proteins. Restoration of diurnal metabolic rhythms and flexibility by SGLT2is may have therapeutic implications beyond those already demonstrated for the cardio-renal axis and may therefore affect other non-diabetes disease states.

Introduction

The Empagliflozin, Cardiovascular (CV) Outcomes, and Mortality in Type 2 Diabetes (EMPA-REG OUTCOME) trial reported an early reduction in the otherwise increased risk of major adverse CV and renal outcomes in type 2 diabetes, with the sodium–glucose cotransporter-2 inhibitor (SGLT2i) empagliflozin (1, 2). These findings were replicated in CANVAS (CANagliflozin cardioVascular Assessment Study), which utilized the SGLT2i canagliflozin (3), and with multiple SGLT2is, including dapagliflozin, in the Comparative Effectiveness of Cardiovascular Outcomes (CVD REAL) real-world study (4). The early timing and nature of the CV and renal effects imply that SGLT2is have influences beyond glucose lowering or weight loss per se, with the precise mechanism driving these early benefits as yet unresolved. SGLT2i-induced glucosuria, diuresis and natriuresis, leading to decreased blood pressure and systemic sodium levels, enhanced ketone body production and increased availability of free fatty acids (FFAs) as a metabolic fuel, have all been suggested to contribute to the observed CV and renal effects (5, 6, 7, 8, 9, 10, 11, 12, 13, 14). The metabolic hypotheses to explain the positive effects of SGLT2is on CV and renal health have centered on increased lipolysis and generation of ketone bodies, proposed to be a more efficient fuel for mitochondria than FFAs and thus hypothesized to contribute to the observed cardio-renal benefit (10, 11, 12, 14). Evidence of enhanced fasting protein catabolism paralleling lipid oxidation and ketone body production following dapagliflozin use has been demonstrated (15). It is likely that the catabolic benefit goes beyond just ketone body production, extending into the cellular housekeeping processes that drive turnover of proteins and organelles, thereby correcting mitochondrial dysfunction and metabolic inflexibilty.

Patients with T2D, as well as non-diabetic insulin-resistant individuals, have characteristic metabolic inflexibility, defined as an inability to switch from mainly fatty acid (FA) oxidation in the fasting state to mainly glucose oxidation in the fed state (16, 17). Metabolic inflexibility has been demonstrated in obese insulin-resistant individuals, defined by a lack of change in measured respiratory quotient (RQ) between fasting and insulin-stimulated fed states. SGLT2 inhibition has been demonstrated to reduce whole body fasting RQ which is indicative of increased FA oxidation (11), and to increase fasting AA oxidation (15), suggesting partial restoration of metabolic flexibility. The mechanisms that cause metabolic inflexibility are not fully elucidated, but there is evidence that substrate overload and impaired fuel switching at the level of mitochondria plays a role (18). Evidence of enhanced FA and AA oxidation following an overnight fast (15) implicates improved fuel switching at the level of the mitochondria during an SGLT2i-driven catabolic state. An increased glucose disposal rate corrected for urinary glucose losses has also been observed in hyperinsulinemic–euglycemic clamp studies of SGLT2is (11, 17, 19). However, the increased glucose uptake was not driven by increased glucose oxidation but rather by non-oxidative glucose disposal. It could be speculated that the increased non-oxidative glucose disposal observed with SGLT2is (11, 19) resulted from enhanced hepatic glycogen depletion, subsequently restored through enhanced insulin-stimulated glycogen synthesis.

Here we propose that restoration of daily metabolic cycling between anabolic and catabolic states and restoration of cellular housekeeping processes mediated by caloric offloading by glucosuria, support an additional explanation of the SGLT2i-driven benefits, consistent with the rapid onset CV and renal benefits observed in the outcomes trials. Uniquely, we propose that the main drivers of the observed benefits are repeated SGLT2i-driven periods of overnight gluconeogenesis occurring against the backdrop of a net decrease in circulating glucose and insulin. Treatment with SGLT2i results in a daily glucosuria-induced loss of approximately 60–80 g of glucose, which is equivalent to 240–320 kilocalories per day. Whilst diuresis due to glucosuria and natriuresis may contribute to weight loss, the energy loss due to glucosuria appears to be the dominant weight reduction mechanism and would result in a body weight loss of 10–12 kg. However, net weight loss plateaus at 2–3 kg by 24 weeks of treatment, predominantly due to reduction of adipose tissue (20, 21). By this stage, patients are likely eating to undertake increased daytime feeding to compensate for this loss of energy in the urine (25). However, during the night, compensatory eating will not occur and the SGLTi induced glucose losses should still result in an enhanced catabolic response.

Metabolic cycling

Regular diurnal anabolic and catabolic cycling occurs in lean healthy adults, with metabolic adjustments occurring between nutrient-rich (fed; anabolic) and nutrient-poor (fasted; catabolic) periods based on energy intake, hormonal status, energy requirements and fuel availability (http://www.diapedia.org/5104085111/rev/67; Last accessed October 2, 2017) (22). The post-meal anabolic state is characterized by increased levels of circulating glucose, and increased uptake of FFAs in adipose tissue and AAs in muscle tissues, as well as a lower glucagon/insulin ratio. Glucose is the primary fuel during this state, producing energy via glycolysis and mitochondrial oxidative phosphorylation in the muscle, with active storage of excess glucose and FFAs as glycogen in the liver and muscle, and as triglycerides in adipocytes (http://www.diapedia.org/5104085111/rev/67; Last accessed October 2, 2017). In addition, protein synthesis is active. Catabolic periods occur during the overnight fast, driven by decreasing levels of circulating glucose and insulin and the physiological need to meet the continuous energy/glucose demands of the brain. To counteract this glucose decrease, the glucagon/insulin ratio increases, stimulating increased hepatic glycogenolysis. As glycogen stores deplete (usually after 8–12 h of fasting), gluconeogenesis activates to maintain glucose levels, supported initially by lactate and pyruvate as the carbon source but ultimately by glycerol and glucogenic AAs (http://www.diapedia.org/5104085111/rev/67; Last accessed October 2, 2017) (23). Due to the decreased insulin levels, lipolysis increases, resulting in increased plasma levels of FFA available for β-oxidation. Products of β-oxidation both allosterically regulate nicotinamide adenine dinucleotide (NADH), adenosine triphosphate (ATP), and citrate, and support the energy requirements of hepatic gluconeogenesis. Decreased insulin levels and increased plasma levels of FFAs limit the amount of glucose entering skeletal muscle, driving the cells to switch to FFA as fuel. Upon eating, a new anabolic period commences (24, 25).

In patients with metabolic disease developing hepatic and peripheral insulin resistance, the interplay between insulin and glucagon becomes disturbed. During the progression of prediabetes toward T2D, insulin secretion is markedly increased resulting in β-cell stress and hyperinsulinemia. Eventually a tipping point is reached when β-cells can no longer compensate for the insulin resistance, resulting in lower insulin secretion, paradoxical glucagon secretion and increased plasma levels of glucose and FFAs. These processes support sustained increases in gluconeogenesis which contribute to the hyperglycemia characteristic of the disease (26). Increases in gluconeogenesis in patients with T2D have therefore been viewed negatively and have been pharmacologically targeted with chronic insulin-supporting, anabolic drug therapies designed to counteract the glycemic impact of glucagon. Despite this, interventions that promote periodic increases in the glucagon/insulin ratio through caloric restriction/loss (i.e., intermittent fasting, gastric bypass and exercise) are agreed to be impactful non-pharmacological treatment options for T2D and metabolic disease (27, 28, 29). Interestingly, time-restricted feeding, allowing a night-time fasting period >12 h, has also been shown to improve metabolic health by enhancing the robustness of feeding/fasting signals regulating the circadian metabolic oscillations (30).

We believe that chronic overeating, lack of exercise and anabolic therapeutic interventions (increasing intracellular glucose concentrations), that chronically work against the likelihood of an increased glucagon/insulin ratio, diminish the opportunity for hepatic glycogen stores to sufficiently deplete to activate hepatic gluconeogenesis during overnight fasting. As a result, circulating AA levels remain elevated, the mammalian target of rapamycin (mTOR) signaling pathway remains chronically active, and housekeeping processes that rely on mTOR inhibition remain suppressed (Fig. 1) (31).

Figure 1
Figure 1

Impact of SGLT2 inhibitor-enhanced fasting on hepatic metabolism. Glucagon levels are increased and insulin levels diminished to maintain glucose levels for the brain, initially through glycogenolysis and eventually through gluconeogenesis. FFA levels rise as insulin levels drop, providing the fuel required to support gluconeogenesis and cellular function. Once activated, hepatic gluconeogenesis consumes the available oxaloacetate slowing down the Krebs cycle and allowing acetyl CoA to build up in the cytosol generating ketone bodies for export outside the liver. As insulin levels drop and fuel switches from glucose to FFAs, gluconeogenic substrates (lactate/pyruvate) become rate limiting, forcing a switch to glucogenic AAs as the carbon source to support glucose synthesis. Autophagy/mitophagy and lysosomal degradation are rapidly activated by the drop in circulating AAs to resupply AAs for this critical function. AA, amino acid; ATP, adenosine triphosphate; BOHB, β-hydroxybutyrate; CoA, coenzyme A; FFA, free fatty acid; mTORC1, mammalian target of rapamycin complex 1.

Citation: European Journal of Endocrinology 178, 4; 10.1530/EJE-17-0832

mTOR signaling pathway and autophagy

The mTOR signaling pathway is a central regulator of cell metabolism, proliferation, and survival, implicated in pathological conditions including diabetes and obesity (24, 32, 33, 34). It includes the sensing of nutrients, insulin, AAs, growth factors, and environmental stimuli, such as hypoxia and stress (24, 32, 34), affecting changes in cellular metabolism to allow rapid adaptation to these conditions, thus enabling metabolic cycling (Fig. 2) (24, 32). mTOR interacts with multiple proteins to form two distinct complexes, mTORC1 and mTORC2, which have different sensitivities to environmental conditions (32).

Figure 2
Figure 2

mTOR pathways in the fed and fasted states. In the fed state, mTOR is activated by high levels of circulating AAs via AA-dependent RAG GTPases leading to an anabolic state characterized by inhibited autophagy and enhanced protein synthesis, mitochondrial biogenesis, glycolysis and lipogenesis. In the fasted state, mTOR is inhibited by decreased levels of AAs as a result of activation of gluconeogenesis by SGLT2 inhibitor use, in addition to increased demand for glucogenic AAs as a result of an increased glucagon/insulin ratio. Decreased AA levels then diminish RAG GTPase activity leading to enhanced autophagy and lysosomal fusion with autophagosomes, rapidly generating new AAs for support of gluconeogenesis. The inhibition of mTOR produces a catabolic state characterized by inhibited protein synthesis, mitochondrial biogenesis, glycolysis and lipogenesis. Caloric intake reverses the mTOR inhibition and reinstitutes an anabolic state. 4E-BP1, 4E-binding protein 1; AA, amino acid; HIF1A, hypoxia-inducible factor 1α; mTORC1, mammalian target of rapamycin complex 1; PGC1A, peroxisome proliferator-activated receptor γ coactivator-1α; PPARG, peroxisome proliferator-activated receptor γ; S6K, s6 kinase; SREBP1, Sterol regulatory element-binding protein 1; ULK1, unc-51-like autophagy-activating kinase 1. Adapted with permission from: Maiese K. Molecules to Medicine with mTOR, 1st Edition. Translating Critical Pathways into Novel Therapeutic Strategies. Academic Press Feb 2016. ISBN. 9780128027332.

Citation: European Journal of Endocrinology 178, 4; 10.1530/EJE-17-0832

mTORC1 acts as a sensor for nutritional cues and is activated in nutrient-rich conditions (i.e., high levels of insulin and AAs) thereby suppressing autophagy, and inhibiting autophagic flux by blocking the ability of lysosomes to fuse with autophagosomes (35, 36, 37). Under nutrient-poor conditions (i.e. low levels of insulin and AAs), mTORC1 is inhibited and autophagy and lysosomal degradation are active, releasing AAs into circulation until mTORC1 is reactivated through direct feedback as either increased circulating levels of autophagy-released AA reach a critical threshold or AAs are reintroduced systemically through eating. Tissues in healthy lean individuals therefore transiently activate autophagy for a few hours per day according to the duration of their AA deficit-driven catabolic state (25, 38, 39). We propose that periodic entry into a catabolic state is critical for ongoing maintenance and renewal of damaged cellular enzymatic machinery, particularly that of the mitochondria, to prevent or slow the progression of metabolic disease (40, 41).

Mitochondrial function is maintained through a rapid and constant process of fission and fusion during which sister mitochondria rapidly come together and separate, redistributing critical components between them to maintain function (42). The overall balance between these processes is also impacted by the nutrient status of the cell, particularly the levels of circulating AA (43, 44). In normal cells under AA-poor, catabolic conditions, mitochondria undergo a sustained fusion process during which dysfunctional units of the mitochondrial electron transport chain are actively segregated into areas within the elongated fused mitochondria. These areas are then pinched off into smaller daughter mitochondrial units during the next anabolic fission cycle. Under subsequent periods of sustained nutritional stress/low insulin and AA levels, the functional mitochondrial units are able to re-fuse into large networks to maximize energy production and to protect the functioning fused mitochondria from autophagy while the smaller dysfunctional mitochondrial units are unable to fuse and are therefore vulnerable to phagocytosis and degradation (43, 45). Dysfunctional units are phagocytized to form autophagosomes that fuse with mTOR-inhibited lysosome complexes to produce autophagolysosomes. We propose that gluconeogenesis-driven systemic AA utilization during low insulin states results in activation of lysosomal processes and the subsequent degradation of autophagocitized organelles/proteins to maintain an adequate supply of glucogenic AA precursors to the liver (38, 46). The rate of autophagy is controlled through feedback by rising AA levels (particularly leucine – a non-glucogenic AA) and the reactivation/modulation of mTOR activity. The subsequent return to an anabolic state upon eating returns the mitochondria to a high AA-driven rapid fission/fusion cycling state and initiates replacement of the proteins and mitochondria/organelles catabolized during mitochondrial fusion through biogenesis. We suggest that any chronic impediment of metabolic anabolic/catabolic, fission/fusion cycling would interrupt the regular autophagic cellular housekeeping cycle of cells and slowly degrade the function of critical organs through progressive mitochondrial dysfunction (35, 38, 42, 46). Indeed, emerging evidence supports a role for impaired autophagy in the pathophysiology of T2D (38, 47), with autophagy disrupted in β-cells in T2D, leading to β-cell stress and possibly cell death (48, 49). In addition, it has been hypothesized that autophagy is altered in the diabetic kidney (33, 50) and heart (51). Impaired autophagy has also been implicated in a broad range of other diseases associated with metabolic dysfunction (52).

Mitochondrial dysfunction

The relationship between mitochondria and insulin sensitivity is highly complex and the debate continues as to whether mitochondrial dysfunction is causing insulin resistance (53, 54). A possible causal relationship between mitochondrial function and skeletal muscle insulin sensitivity is the ability of the mitochondria to export excess acetyl-coenzyme A (CoA) as acetyl carnitine by the action of carnitine acetyltransferase (CRAT). Increased CRAT activity reduces acetyl CoA levels, which alleviates the allosteric inhibition of the pyruvate dehydrogenase complex and allows oxidation of glucose to occur in the mitochondria (55, 56). A strong association between levels of acetyl carnitine in skeletal muscles and insulin sensitivity has been shown in subjects with various levels of insulin resistance, indicating that decreased mitochondrial formation of acetylcarnitine could help to explain skeletal muscle insulin resistance (57). Moreover, mitochondrial function, as well as mitochondrial fusion and fission which maintains mitochondrial function, is influenced by nutrient availability and metabolic disease. Animal models show that sustained hyperglycemia causes mitochondrial fission (58, 59, 60), and obesity and excess energy intake also shift the balance of mitochondrial fission–fusion toward fission, leading to an increased number of dysfunctional mitochondria (60). Accumulation of increasingly dysfunctional mitochondria in a highly anabolic environment with excess NADH may cause superoxide anion production, oxidative damage and inflammation (61, 62). Interestingly, disease states associated with diabetes, metabolic syndrome and aging such as non-alcoholic steatohepatitis (63, 64), neurodegenerative diseases (65), diabetic kidney disease (66, 67) and diabetic heart failure (68, 69) are all characterized histologically by smaller distended mitochondria (consistent with sustained fission) and cells with disrupted autophagy/lysosomal processes (Fig. 3A). Thus, it is not unlikely that a therapy that corrects the underlying metabolic disturbances preventing mitochondrial cycling and function can have broad and profound effects on diabetic complications impact mortality in type 2 diabetes.

Figure 3
Figure 3

The impact of ‘insulin’ and SGLT2 inhibitor treatment on the mitochondrial fission/fusion cycle. (A) In ‘insulin’-treated type 2 diabetes, the patient is held in sustained anabolic state brought about by excess caloric intake/lack of exercise and reinforced by insulin or insulin-enhancing therapies to lower circulating glucose. The lack of a catabolic state results in the accumulation of autophagosomes that are not triggered for lysosomal degradation due to the lack of hepatic demand for AAs owing to the diminished glucagon/gluconeogenesis axis. Mitochondria are blocked from mitophagy due to the autophagosome backlog and become increasingly dysfunctional, resulting in a shift to a more reduced redox state. Excess NADH causes an increase in superoxide anion levels, setting in motion a chain of oxidative damage and inflammation. As the mitochondrial dysfunction reaches a critical phase, the cells slip into senescence and contribute to organ dysfunction. (B) In patients with type 2 diabetes treated with an SGLT2 inhibitor, the overnight catabolic state is restored by the loss of glucose and increase in glucagon release driving all of the processes necessary for the upkeep of the cells improving global organ health, including activation of AMPK and Sirt1 and autophagy/lysosomal processes. AA, amino acid; β-OHB, β-hydroxybutyrate; FFA, free fatty acid; Gluc, glucose; mTOR, mammalian target of rapamycin; NAD+, nicotinamide adenine dinucleotide; NADH, nicotinamide adenine dinucleotide (reduced form); PGC1a, peroxisome proliferator-activated receptor γ coactivator-1α.

Citation: European Journal of Endocrinology 178, 4; 10.1530/EJE-17-0832

Chronic catabolic conditions such as fasting produce a state mimicking insulin resistance, characterized by low circulating glucose and insulin levels and elevated FFA levels, as part of a coordinated adaptive physiological response to reduced caloric intake (70). In a study of healthy male volunteers placed under fasted conditions for 60 h, whole body FA oxidation increased, while the levels of coupled and uncoupled mitochondrial respiration were significantly decreased. When a hyperinsulinemic–euglycemic clamp was applied, levels of endogenous glucose production rapidly dropped (i.e., hepatic insulin sensitivity remained intact) and carbohydrate oxidation increased (~two-fold) but was blunted relative to the carbohydrate oxidation observed under non-fasted conditions. Remarkably, FA oxidation remained elevated under these clamp conditions suggesting metabolic inflexibility is retained for a period after prolonged fasting. In marathon runners, plasma FFA levels were elevated the morning after running a marathon and hyperinsulinemic–euglycemic clamp conditions also showed blunted glucose oxidation and sustained enhanced rates of lipid oxidation (71). The metabolic pattern found after fasting and the day after a marathon was also replicated in patients with T2D treated with an SGLT2i (dapagliflozin) for 2 weeks (11). Fasting lipid oxidation was increased and ATP production from isolated mitochondria was decreased in these patients, which correlated with increased plasma ketone levels. Upon application of a hyperinsulinemic–euglycemic clamp, carbohydrate oxidation remained depressed in the presence of a sustained increase in whole body lipid oxidation; however, non-oxidative glucose disposal was increased under these conditions suggestive of repletion of hepatic glycogen as discussed earlier (11).

The similarity between these three conditions/studies suggests that SGLT2is are producing a night-time fasting-like state in patients with T2D, resulting in enhanced utilization of FFA. Furthermore, it suggests that some other essential metabolic signal beyond insulin or glucose is responsible for holding the metabolism (and perhaps the morphological status of the mitochondria) in a catabolic state, which we propose is diminished availability of AAs, which then enables an enhanced and sustained flux and use of AAs from lysosomal degradation of autophaged organelles and protein for use in gluconeogenesis (44). Experimental infusion of excess AAs under such conditions during the hyperinsulinemic–euglycemic clamp may change mitochondrial morphology and increase glucose oxidation, which would show that the insulin resistance observed under these catabolic conditions is at least, in part, a result of the experimental conditions (lack of circulating AAs). Therefore, the ability of mitochondria to optimally utilize lipids under fasted conditions may depend on increased AA catabolism triggered by hepatic gluconeogenesis. The intracellular AA deficiency in turn results in a state of sustained mitochondrial fusion, as well as potentially enhancing the flux of liberated FAs from lipid droplets to the mitochondria for energy production, thereby reducing ectopic fat (72). In the over-nutritioned state, hepatic glycogen stores are high and the constant availability of circulating lactate, pyruvate and digested AAs would likely limit the occurrence of catabolic conditions and periods of sustained mitochondrial fusion.

Sustained anabolic signaling through excess insulin and high AA levels may also explain the increases in glucagon occurring with type 2 diabetes progression, contributing to the observed magnitude of hyperglycemia. Recent work in mice suggests that elevated AA levels may be a critical hepatically derived factor regulating pancreatic α- and β-cell mass, acting through mTOR to increase α-cell proliferation and glucagon production (73). The increased α-cell proliferation can be blocked by administration of rapamycin (an mTOR inhibitor), which also permits trans-differentiation of α-cells back into functional, insulin-producing β-like cells.

Mitochondrial dysfunction and mTOR

Direct clinical evaluation of the role of periodic mTOR inhibition and enhanced autophagy in treating metabolic disease has been impeded both by the difficulty of reliably imposing fasting conditions on patients and the absence of a drug that reliably creates periodic caloric restriction, a gap which may now be filled by the SGLT2i class. It has been further clouded by the results of chronic use of mTOR inhibitors, such as the anti-rejection drug rapamycin, on metabolic disease biomarkers. Rapamycin has been shown to produce a diabetes-like state with elevated glucose and low-density lipoprotein (LDL) cholesterol levels (http://www.medicines.org.uk/emc/medicine/5747; Last accessed October 2, 2017) (74, 75) both of which would be of metabolic concern with long-term use. However, it should be noted that the preclinical metabolic signature of rapamycin use (weight loss, increased lipid oxidation and peripheral insulin resistance measured under hyperinsulinemic–euglycemic clamp) mirrors that of the physiological catabolic insulin resistance described earlier (76). Also, rapamycin and other currently used mTOR inhibitors cause 24-h inhibition of mTOR (http://www.medicines.org.uk/emc/medicine/5747; Last accessed October 2, 2017) mimicking constant catabolic conditions, potentially blocking the anabolic periods required to restore catabolized cellular function, which could also explain the observed increases in glucose and LDL levels (77). Furthermore, in contrast to fasting, experimental evidence suggests that rapamycin does not activate lysosomal function, so the full catabolic effect of mTOR inhibition may not occur (78). Interestingly, 1 week of fasting has been shown to result in a marked increase in LDL levels (77). This effect could be mediated by mTOR inhibition. Rapamycin increases LDL cholesterol levels by increasing levels of circulating proprotein convertase subtilisin/kexin type 9 via mTOR inhibition, which causes a diminishment of LDL cholesterol receptors and therefore elevates levels of circulating LDL cholesterol (79). SGLT2is also modestly increase LDL cholesterol levels, which may reflect a softer periodic entry into an mTOR-inhibited state (37). SGLT2is may be the first agents that can produce repeated overnight catabolic states, directly driven by energy loss in the urine, interspersed with daily anabolic periods, both of which, we propose, are required to maintain mitochondrial and metabolic health.

Summary of hypothesis

During the daytime, food/energy consumption adequately covers the SGLT2i-mediated glucose gap and supports beneficial anabolic activities, but at night, when gastric absorption of glucose diminishes, a glucose gap is established with activation of hepatic gluconeogenesis driven by an increased glucagon/insulin ratio (19, 80). The insulin drop also increases the rate of lipolysis in adipocytes, thereby increasing circulating levels of FFAs, which impede glucose entry into muscle and cause a switch to FFA as fuel, driven by increased intracellular levels of NAD (+) (nicotinamide adenine dinucleotide +) and activation of Sirt1 (silent mating type information regulation 2 homolog 1) (81).

The liver also uses more FFAs to fuel gluconeogenesis and effectively becomes a sink for circulating FFA. Initially, the glucose gap is filled by activation of glycogenolysis but eventually glycogen levels are reduced sufficiently to activate gluconeogenesis (Figs 3, 4 and 5). The overnight period of gluconeogenesis requires a sustained carbon source, ultimately provided by circulating glucogenic AAs. The level of AAs controls autophagic processes via activation and inactivation of mTOR; as AA levels drop and mTOR is inhibited, activated autophagolysosome complexes drive protein degradation to maintain a steady supply of glucogenic AAs. Mitochondrial elongation/fusion triggered by low levels of AAs also occurs, improving mitochondrial function and supporting the metabolic switch (44). In the morning, eating stimulates insulin release, restoring the daily anabolic processes to rebuild cells and organelles and metabolic rhythm/clock and flexibility (30, 61).

Figure 4
Figure 4

The impact of SGLT2 inhibitor treatment on mitochondrial function. Healthy patients cycle through daily anabolic periods characterized by increased insulin levels and glucose utilization as fuel, with fuel storage and protein/organelle synthesis occurring with excess glucose. Overnight, a period of fasting occurs which is deep enough to trigger glucagon release, depleting glycogen stores to a degree sufficient to require a glucogenic AA source to support gluconeogenesis. AAs are supplied through lysosomal degradation of damaged proteins (autophagy/mitophagy/ubiquitin/proteasome system (UPS)) throughout the body caused by inhibition of mTOR following a drop in circulating AAs as a result of gluconeogenesis. Ketone bodies are generated as gluconeogenesis blocks the Krebs cycle providing another important extrahepatic fuel source. Patients with type 2 diabetes receiving insulin-based therapies experience increased insulin levels, which forces glucose into cells, making it harder to achieve an overnight fast, locking the patients in an anabolic state. The increase in insulin levels also prevents an increase in glucagon, preventing its beneficial catabolic effects. Use of an SGLT2 inhibitor strengthens the overnight fast owing to constant glucose loss, restoring overnight glucagon release enabling its catabolic benefit while allowing restoration of the anabolic state in the morning following eating, thus reinstituting the metabolic cycling characteristic of healthy patients. FFA, free fatty acid; SGLT2i, sodium–glucose cotransporter-2 inhibitor; T2D, type 2 diabetes.

Citation: European Journal of Endocrinology 178, 4; 10.1530/EJE-17-0832

Figure 5
Figure 5

Metabolic mechanism of benefit. Areas where direct evidence is still lacking are shown in yellow. AA, amino acid; ATP, adenosine triphosphate; β-OHB, β-hydroxybutyrate; FFA, free fatty acid; GNG, gluconeogenesis; mTOR, mammalian target of rapamycin; SGLT2, sodium–glucose cotransporter-2.

Citation: European Journal of Endocrinology 178, 4; 10.1530/EJE-17-0832

Future perspective

While direct clinical assessments of glycogen flux in the liver and muscle following SGLT2i treatment in humans are not yet available, Briand and coworkers (82) published data in dyslipidemic hamsters showing that empagliflozin dramatically enhances the fasting state, with an 84% reduction in hepatic glycogen levels. Similarly, while increased gluconeogenesis has not been directly measured clinically, increased endogenous glucose production (EGP) following SGLT2i use has been consistently measured (9, 12, 13). The increase in EGP seen with SGLT2i use is consistent with increased gluconeogenesis, as diversion of oxaloacetate into gluconeogenesis during fasting is known to inhibit flux through the Krebs cycle and drive the concomitant generation of ketone bodies from excess acetyl CoA accompanying increased FFA oxidation, processes which have been documented (22, 83). Direct evidence that SGLT2is cause mTOR-directed systemic catabolism and enhanced autophagy/lysosomal activity is not yet available but is suggested by the alterations in glucagon/insulin levels and the increased rate of AA and FA oxidation in patients with type 2 diabetes treated with dapagliflozin, in addition to the overall lower rate of carbohydrate oxidation (11, 15). These metabolic characteristics are consistent with an mTOR-inhibited state. In planned clinical studies, diurnal changes in glycogen levels, night-time gluconeogenesis and protein/lipid catabolism as well as mitochondrial function and turnover will be investigated.

It may be speculated that the proposed mechanisms based on enhanced nocturnal catabolism may have beneficial effects on heart failure and kidney disease in people without diabetes, especially in obese and insulin-resistant patients, since metabolic inflexibility and associated mitochondrial dysfunction are also found in non-diabetic patients with insulin resistance (16, 57). Ongoing trials including non-diabetics with heart failure (Nbib3036124) and chronic kidney disease (Nbib3036150) will tell if SGLT2is also have beneficial effects in non-diabetic patients with these diseases. Moreover, the effects of SGLT2is on CV outcomes and diabetic nephropathy in patients with type 1 diabetes are also unknown. Weight reduction and improved glucose control, including reduced glucose variability have been demonstrated in patients with type 1 diabetes, indicating similar metabolic adjustments as those observed in patients with type 2 diabetes (84). The application of the hypothesis of enhanced nocturnal catabolism in type 1 diabetes is complicated by the fact that patients with type 1 diabetes require insulin treatment. However, we speculate that if the night-time dose/concentration of insulin is appropriately managed (i.e., not requiring the patient to eat at night to maintain glucose levels), then the proposed hypothesis and benefit is likely to be applicable to this patient group as well.

This view of the beneficial effects of SGLT2is may also advance the discussion of treatment of metabolic disease away from weight loss per se by suggesting that restoration of adequate catabolic periods interspersed within the inevitable anabolic periods could drive improvements in metabolic health. This is a more achievable and impactful public health target and could apply to other metabolic disease states that are also driven by chronic mitochondrial dysfunction, including, but not limited to, heart failure, chronic kidney disease, cancer, obesity, severe asthma and chronic obstructive pulmonary disease, Alzheimer’s disease, Parkinson’s disease and non-alcoholic steatohepatitis (24).

Declaration of interest

R E, J O and A V are employees of AstraZeneca. J V is Consultant Endocrinologist/Prof. at the Royal Liverpool University Hospital/University of Liverpool and reveals Research Support, Advisory Board attendance, and Speaker Bureau involvement from Sanofi, Lilly, Novo Nordisk, MSD, BMS, AstraZeneca, Novartis, Boehringer Ingelheim, Takeda, GSK, Roche and Abbott. J V also has a role as Chief Medical Advisor for Cardiovascular and Metabolic Diseases at AstraZeneca.

Funding

This research did not receive any specific grant from any funding agency in the public, commercial or not-for-profit sector. Medical writing assistance was funded by AstraZeneca.

Author contribution statement

R E wrote the first draft. All authors critically reviewed and revised the manuscript and approved it for submission.

Acknowledgements

The authors would like to thank Fredrik Karpe, Stephen O’Rahilly, Ele Ferrannini, Grazyna Söderbom and Peter Sartipy for discussion and input during the development of this manuscript. Medical writing assistance was provided by Alexander Jones, of inScience Communications, funded by AstraZeneca.

References

  • 1

    Zinman B, Wanner C, Lachin JM, Fitchett D, Bluhmki E, Hantel S, Mattheus M, Devins T, Johansen OE & Woerle HJ et al. Empagliflozin, cardiovascular outcomes, and mortality in type 2 diabetes. New England Journal of Medicine 2015 373 21172128. (https://doi.org/10.1056/NEJMoa1504720)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 2

    Wanner C, Inzucchi SE, Lachin JM, Fitchett D, von Eynatten M, Mattheus M, Johansen OE, Woerle HJ, Broedl UC, Zinman B. Empagliflozin and progression of kidney disease in type 2 diabetes. New England Journal of Medicine 2016 375 323334. (https://doi.org/10.1056/NEJMoa1515920)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 3

    Neal B, Perkovic V, Mahaffey KW, de Zeeuw D, Fulcher G, Erondu N, Shaw W, Law G, Desai M & Matthews DR. Canagliflozin and cardiovascular and renal events in type 2 diabetes. New England Journal of Medicine 2017 377 644657. (https://doi.org/10.1056/NEJMoa1611925)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 4

    Kosiborod M, Cavender MA, Fu AZ, Wilding JP, Khunti K, Holl RW, Norhammar A, Birkeland KI, Jorgensen M & Thuresson M et al. Lower risk of heart failure and death in patients initiated on SGLT-2 inhibitors versus other glucose-lowering drugs: the CVD-REAL study. Circulation 2017 136 249259. (https://doi.org/10.1161/circulationaha.117.029190)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5

    Abdul-Ghani M, Del Prato S, Chilton R & DeFronzo RA. SGLT2 inhibitors and cardiovascular risk: lessons learned from the EMPA-REG OUTCOME study. Diabetes Care 2016 39 717725. (https://doi.org/10.2337/dc16-0041)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6

    Inzucchi SE, Zinman B, Wanner C, Ferrari R, Fitchett D, Hantel S, Espadero RM, Woerle HJ, Broedl UC & Johansen OE. SGLT-2 inhibitors and cardiovascular risk: proposed pathways and review of ongoing outcome trials. Diabetes and Vascular Disease Research 2015 12 90100. (https://doi.org/10.1177/1479164114559852)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 7

    Sattar N, McLaren J, Kristensen SL, Preiss D & McMurray JJ. SGLT2 inhibition and cardiovascular events: why did EMPA-REG Outcomes surprise and what were the likely mechanisms? Diabetologia 2016 59 13331339. (https://doi.org/10.1007/s00125-016-3956-x)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8

    McMurray J. EMPA-REG – the ‘diuretic hypothesis’. Journal of Diabetes and its Complications 2016 30 34. (https://doi.org/10.1016/j.jdiacomp.2015.10.012)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 9

    DeFronzo RA. The EMPA-REG study: what has it told us? A diabetologist’s perspective. Journal of Diabetes and its Complications 2016 30 12. (https://doi.org/10.1016/j.jdiacomp.2015.10.013)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 10

    Jorgensen NB, Pedersen J, Vaag AA. EMPA-REG: glucose excretion and lipid mobilization – not storage – saves lives. Journal of Diabetes and its Complications 2016 30 753. (https://doi.org/10.1016/j.jdiacomp.2016.02.015)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11

    Daniele G, Xiong J, Solis-Herrera C, Merovci A, Eldor R, Tripathy D, DeFronzo RA, Norton L & Abdul-Ghani M. Dapagliflozin enhances fat oxidation and ketone production in patients with type 2 diabetes. Diabetes Care 2016 39 20362041. (https://doi.org/10.2337/dc15-2688)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12

    Ferrannini E, Baldi S, Frascerra S, Astiarraga B, Heise T, Bizzotto R, Mari A, Pieber TR & Muscelli E. Shift to fatty substrate utilization in response to sodium-glucose cotransporter 2 inhibition in subjects without diabetes and patients with type 2 diabetes. Diabetes 2016 65 11901195. (https://doi.org/10.2337/db15-1356)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13

    Ferrannini E, Mark M & Mayoux E. CV protection in the EMPA-REG OUTCOME trial: a ‘thrifty substrate’ hypothesis. Diabetes Care 2016 39 11081114. (https://doi.org/10.2337/dc16-0330)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 14

    Mudaliar S, Alloju S & Henry RR. Can a shift in fuel energetics explain the beneficial cardiorenal outcomes in the EMPA-REG OUTCOME study? A unifying hypothesis. Diabetes Care 2016 39 11151122. (https://doi.org/10.2337/dc16-0542)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15

    Mudaliar S, Henry RR, Boden G, Smith S, Chalamandaris AG, Duchesne D, Iqbal N & List J. Changes in insulin sensitivity and insulin secretion with the sodium glucose cotransporter 2 inhibitor dapagliflozin. Diabetes Technology and Therapeutics 2014 16 137144. (https://doi.org/10.1089/dia.2013.0167)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 16

    Storlien L, Oakes ND & Kelley DE. Metabolic flexibility. Proceedings of the Nutrition Society 2004 63 363368. (https://doi.org/10.1079/PNS2004349)

  • 17

    Kelley DE, Goodpaster B, Wing RR & Simoneau JA. Skeletal muscle fatty acid metabolism in association with insulin resistance, obesity, and weight loss. American Journal of Physiology 1999 277 E1130E1141. (https://doi.org/10.1152/ajpcell.1999.277.6.C1130)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 18

    Muoio DM. Metabolic inflexibility: when mitochondrial indecision leads to metabolic gridlock. Cell 2014 159 12531262. (https://doi.org/10.1016/j.cell.2014.11.034)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19

    Merovci A, Solis-Herrera C, Daniele G, Eldor R, Fiorentino TV, Tripathy D, Xiong J, Perez Z, Norton L & Abdul-Ghani MA et al. Dapagliflozin improves muscle insulin sensitivity but enhances endogenous glucose production. Journal of Clinical Investigation 2014 124 509514. (https://doi.org/10.1172/JCI70704)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 20

    Bolinder J, Ljunggren O, Kullberg J, Johansson L, Wilding J, Langkilde AM, Sugg J & Parikh S. Effects of dapagliflozin on body weight, total fat mass, and regional adipose tissue distribution in patients with type 2 diabetes mellitus with inadequate glycemic control on metformin. Journal of Clinical Endocrinology and Metabolism 2012 97 10201031. (https://doi.org/10.1210/jc.2011-2260)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 21

    Bolinder J, Ljunggren O, Johansson L, Wilding J, Langkilde AM, Sjostrom CD, Sugg J & Parikh S. Dapagliflozin maintains glycaemic control while reducing weight and body fat mass over 2 years in patients with type 2 diabetes mellitus inadequately controlled on metformin. Diabetes, Obesity and Metabolism 2014 16 159169. (https://doi.org/10.1111/dom.12189)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 22

    Berg JM, Tymoczko JL, Stryer L. Section 30, the integration of metabolism. In Biochemistry, 5 ed., ch 30, pp 12501280. New York: W H Freeman, 2002.

    • Search Google Scholar
    • Export Citation
  • 23

    Longo VD & Mattson MP. Fasting: molecular mechanisms and clinical applications. Cell Metabolism 2014 19 181192. (https://doi.org/10.1016/j.cmet.2013.12.008)

  • 24

    Laplante M & Sabatini DM. mTOR signaling in growth control and disease. Cell 2012 149 274293. (https://doi.org/10.1016/j.cell.2012.03.017)

  • 25

    Lee J, Giordano S, Zhang J. Autophagy, mitochondria and oxidative stress: cross-talk and redox signalling. Biochemical Journal 2012 441 523540. (https://doi.org/10.1042/BJ20111451)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 26

    D’Alessio D. The role of dysregulated glucagon secretion in type 2 diabetes. Diabetes, Obesity and Metabolism 2011 13 (Supplement 1) 126132. (https://doi.org/10.1111/j.1463-1326.2011.01449.x)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 27

    Lim EL, Hollingsworth KG, Aribisala BS, Chen MJ, Mathers JC & Taylor R. Reversal of type 2 diabetes: normalisation of beta cell function in association with decreased pancreas and liver triacylglycerol. Diabetologia 2011 54 25062514. (https://doi.org/10.1007/s00125-011-2204-7)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28

    Colberg SR, Sigal RJ, Fernhall B, Regensteiner JG, Blissmer BJ, Rubin RR, Chasan-Taber L, Albright AL & Braun B. Exercise and type 2 diabetes: the American College of Sports Medicine and the American Diabetes Association: joint position statement executive summary. Diabetes Care 2010 33 26922696. (https://doi.org/10.2337/dc10-1548)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29

    Jorgensen NB, Dirksen C, Bojsen-Moller KN, Jacobsen SH, Worm D, Hansen DL, Kristiansen VB, Naver L, Madsbad S & Holst JJ. Exaggerated glucagon-like peptide 1 response is important for improved beta-cell function and glucose tolerance after Roux-en-Y gastric bypass in patients with type 2 diabetes. Diabetes 2013 62 30443052. (https://doi.org/10.2337/db13-0022)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30

    Longo VD, Panda S. Fasting, circadian rhythms, and time-restricted feeding in healthy lifespan. Cell Metabolism 2016 23 10481059. (https://doi.org/10.1016/j.cmet.2016.06.001)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31

    Kelley DE. Skeletal muscle fat oxidation: timing and flexibility are everything. Journal of Clinical Investigation 2005 115 16991702. (https://doi.org/10.1172/JCI25758)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 32

    Laplante M & Sabatini DM. mTOR signaling at a glance. Journal of Cell Science 2009 122 35893594. (https://doi.org/10.1242/jcs.051011)

  • 33

    Kume S, Koya D, Uzu T & Maegawa H. Role of nutrient-sensing signals in the pathogenesis of diabetic nephropathy. BioMed Research International 2014 2014 315494. (https://doi.org/10.1155/2014/315494)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 34

    Zoncu R, Efeyan A & Sabatini DM. mTOR: from growth signal integration to cancer, diabetes and ageing. Nature Reviews Molecular Cell Biology 2011 12 2135. (https://doi.org/10.1038/nrm3025)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 35

    Russell RC, Yuan HX & Guan KL. Autophagy regulation by nutrient signaling. Cell Research 2014 24 4257. (https://doi.org/10.1038/cr.2013.166)

  • 36

    Korolchuk VI, Saiki S, Lichtenberg M, Siddiqi FH, Roberts EA, Imarisio S, Jahreiss L, Sarkar S, Futter M & Menzies FM et al. Lysosomal positioning coordinates cellular nutrient responses. Nature Cell Biology 2011 13 453460. (https://doi.org/10.1038/ncb2204)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 37

    Zhou J, Tan SH, Nicolas V, Bauvy C, Yang ND, Zhang J, Xue Y, Codogno P & Shen HM. Activation of lysosomal function in the course of autophagy via mTORC1 suppression and autophagosome-lysosome fusion. Cell Research 2013 23 508523. (https://doi.org/10.1038/cr.2013.11)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 38

    Sandri M. FOXOphagy path to inducing stress resistance and cell survival. Nature Cell Biology 2012 14 786788. (https://doi.org/10.1038/ncb2550)

  • 39

    Webster BR, Scott I, Traba J, Han K & Sack MN. Regulation of autophagy and mitophagy by nutrient availability and acetylation. Biochimica et Biophysica Acta 2014 1841 525534. (https://doi.org/10.1016/j.bbalip.2014.02.001)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 40

    Twig G, Elorza A, Molina AJ, Mohamed H, Wikstrom JD, Walzer G, Stiles L, Haigh SE, Katz S & Las G et al. Fission and selective fusion govern mitochondrial segregation and elimination by autophagy. EMBO Journal 2008 27 433446. (https://doi.org/10.1038/sj.emboj.7601963)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 41

    Ding WX & Yin XM. Mitophagy: mechanisms, pathophysiological roles, and analysis. Biological Chemistry 2012 393 547564. (https://doi.org/10.1515/hsz-2012-0119)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 42

    Liesa M & Shirihai OS. Mitochondrial dynamics in the regulation of nutrient utilization and energy expenditure. Cell Metabolism 2013 17 491506. (https://doi.org/10.1016/j.cmet.2013.03.002)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 43

    Terman A, Kurz T, Navratil M, Arriaga EA & Brunk UT. Mitochondrial turnover and aging of long-lived postmitotic cells: the mitochondrial-lysosomal axis theory of aging. Antioxidants and Redox Signaling 2010 12 503535. (https://doi.org/10.1089/ars.2009.2598)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 44

    Gomes LC, Di Benedetto G & Scorrano L. Essential amino acids and glutamine regulate induction of mitochondrial elongation during autophagy. Cell Cycle 2011 10 26352639. (https://doi.org/10.4161/cc.10.16.17002)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 45

    Meijer AJ, Codogno P. Autophagy: regulation and role in disease. Critical Reviews in Clinical Laboratory Sciences 2009 46 210240. (https://doi.org/10.1080/10408360903044068)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 46

    Song M, Mihara K, Chen Y, Scorrano L & Dorn GW 2nd. Mitochondrial fission and fusion factors reciprocally orchestrate mitophagic culling in mouse hearts and cultured fibroblasts. Cell Metabolism 2015 21 273285. (https://doi.org/10.1016/j.cmet.2014.12.011)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 47

    Gonzalez CD, Lee MS, Marchetti P, Pietropaolo M, Towns R, Vaccaro MI, Watada H & Wiley JW. The emerging role of autophagy in the pathophysiology of diabetes mellitus. Autophagy 2011 7 211. (https://doi.org/10.4161/auto.7.1.13044)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 48

    Las G & Shirihai OS. The role of autophagy in beta-cell lipotoxicity and type 2 diabetes. Diabetes, Obesity and Metabolism 2010 12 (Supplement 2) 1519. (https://doi.org/10.1111/j.1463-1326.2010.01268.x)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 49

    Marrif HI & Al-Sunousi SI. Pancreatic beta cell mass death. Frontiers in Pharmacology 2016 7 83. (https://doi.org/10.3389/fphar.2016.00083)

  • 50

    Tanaka Y, Kume S, Kitada M, Kanasaki K, Uzu T, Maegawa H & Koya D. Autophagy as a therapeutic target in diabetic nephropathy. Experimental Diabetes Research 2012 2012 628978. (https://doi.org/10.1155/2012/628978)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 51

    De Meyer GR, De Keulenaer GW & Martinet W. Role of autophagy in heart failure associated with aging. Heart Failure Reviews 2010 15 423430. (https://doi.org/10.1007/s10741-010-9166-6)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 52

    Levine B & Kroemer G. Autophagy in the pathogenesis of disease. Cell 2008 132 2742. (https://doi.org/10.1016/j.cell.2007.12.018)

  • 53

    Montgomery MK & Turner N. Mitochondrial dysfunction and insulin resistance: an update. Endocrine Connections 2015 4 R1R15. (https://doi.org/10.1530/EC-14-0092)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 54

    Yoon Y, Galloway CA, Jhun BS & Yu T. Mitochondrial dynamics in diabetes. Antioxidants and Redox Signaling 2011 14 439457. (https://doi.org/10.1089/ars.2010.3286)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 55

    Noland RC, Koves TR, Seiler SE, Lum H, Lust RM, Ilkayeva O, Stevens RD, Hegardt FG & Muoio DM. Carnitine insufficiency caused by aging and overnutrition compromises mitochondrial performance and metabolic control. Journal of Biological Chemistry 2009 284 2284022852. (https://doi.org/10.1074/jbc.M109.032888)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 56

    Muoio DM, Noland RC, Kovalik JP, Seiler SE, Davies MN, DeBalsi KL, Ilkayeva OR, Stevens RD, Kheterpal I & Zhang J et al. Muscle-specific deletion of carnitine acetyltransferase compromises glucose tolerance and metabolic flexibility. Cell Metabolism 2012 15 764777. (https://doi.org/10.1016/j.cmet.2012.04.005)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 57

    Lindeboom L, Nabuurs CI, Hoeks J, Brouwers B, Phielix E, Kooi ME, Hesselink MK, Wildberger JE, Stevens RD & Koves T et al. Long-echo time MR spectroscopy for skeletal muscle acetylcarnitine detection. Journal of Clinical Investigation 2014 124 49154925. (https://doi.org/10.1172/JCI74830)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 58

    Edwards JL, Quattrini A, Lentz SI, Figueroa-Romero C, Cerri F, Backus C, Hong Y & Feldman EL. Diabetes regulates mitochondrial biogenesis and fission in mouse neurons. Diabetologia 2010 53 160169. (https://doi.org/10.1007/s00125-009-1553-y)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 59

    Vincent AM, Edwards JL, McLean LL, Hong Y, Cerri F, Lopez I, Quattrini A & Feldman EL. Mitochondrial biogenesis and fission in axons in cell culture and animal models of diabetic neuropathy. Acta Neuropathologica 2010 120 477489. (https://doi.org/10.1007/s00401-010-0697-7)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 60

    Jheng HF, Tsai PJ, Guo SM, Kuo LH, Chang CS, Su IJ, Chang CR & Tsai YS. Mitochondrial fission contributes to mitochondrial dysfunction and insulin resistance in skeletal muscle. Molecular and Cellular Biology 2012 32 309319. (https://doi.org/10.1128/MCB.05603-11)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 61

    Perier C & Vila M. Mitochondrial biology and Parkinson’s disease. Cold Spring Harbor Perspectives in Medicine 2012 2 a009332. (https://doi.org/10.1101/cshperspect.a009332)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 62

    Ramsay RR, Kowal AT, Johnson MK, Salach JI & Singer TP. The inhibition site of MPP+, the neurotoxic bioactivation product of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine is near the Q-binding site of NADH dehydrogenase. Archives of Biochemistry and Biophysics 1987 259 645649. (https://doi.org/10.1016/0003-9861(87)90531-5)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 63

    Aravinthan A, Scarpini C, Tachtatzis P, Verma S, Penrhyn-Lowe S, Harvey R, Davies SE, Allison M, Coleman N & Alexander G. Hepatocyte senescence predicts progression in non-alcohol-related fatty liver disease. Journal of Hepatology 2013 58 549556. (https://doi.org/10.1016/j.jhep.2012.10.031)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 64

    Koliaki C, Szendroedi J, Kaul K, Jelenik T, Nowotny P, Jankowiak F, Herder C, Carstensen M, Krausch M & Knoefel WT et al. Adaptation of hepatic mitochondrial function in humans with non-alcoholic fatty liver is lost in steatohepatitis. Cell Metabolism 2015 21 739746. (https://doi.org/10.1016/j.cmet.2015.04.004)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 65

    Chen H & Chan DC. Mitochondrial dynamics – fusion, fission, movement, and mitophagy – in neurodegenerative diseases. Human Molecular Genetics 2009 18 R169R176. (https://doi.org/10.1093/hmg/ddp326)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 66

    Huber TB, Edelstein CL, Hartleben B, Inoki K, Jiang M, Koya D, Kume S, Lieberthal W, Pallet N & Quiroga A et al. Emerging role of autophagy in kidney function, diseases and aging. Autophagy 2012 8 10091031. (https://doi.org/10.4161/auto.19821)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 67

    Higgins GC & Coughlan MT. Mitochondrial dysfunction and mitophagy: the beginning and end to diabetic nephropathy? British Journal of Pharmacology 2014 171 19171942. (https://doi.org/10.1111/bph.12503)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 68

    Kobayashi S & Liang Q. Autophagy and mitophagy in diabetic cardiomyopathy. Biochimica et Biophysica Acta 2015 1852 252261. (https://doi.org/10.1016/j.bbadis.2014.05.020)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 69

    Liang Q & Kobayashi S. Mitochondrial quality control in the diabetic heart. Journal of Molecular and Cellular Cardiology 2016 95 5769. (https://doi.org/10.1016/j.yjmcc.2015.12.025)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 70

    Hoeks J, van Herpen NA, Mensink M, Moonen-Kornips E, van Beurden D, Hesselink MK & Schrauwen P. Prolonged fasting identifies skeletal muscle mitochondrial dysfunction as consequence rather than cause of human insulin resistance. Diabetes 2010 59 21172125. (https://doi.org/10.2337/db10-0519)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 71

    Tuominen JA, Ebeling P, Bourey R, Koranyi L, Lamminen A, Rapola J, Sane T, Vuorinen-Markkola H & Koivisto VA. Postmarathon paradox: insulin resistance in the face of glycogen depletion. American Journal of Physiology 1996 270 E336E343. (https://doi.org/10.1152/ajpendo.1996.270.2.E336)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 72

    Rambold AS, Cohen S & Lippincott-Schwartz J. Fatty acid trafficking in starved cells: regulation by lipid droplet lipolysis, autophagy, and mitochondrial fusion dynamics. Developmental Cell 2015 32 678692. (https://doi.org/10.1016/j.devcel.2015.01.029)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 73

    Solloway MJ, Madjidi A, Gu C, Eastham-Anderson J, Clarke HJ, Kljavin N, Zavala-Solorio J, Kates L, Friedman B & Brauer M et al. Glucagon couples hepatic amino acid catabolism to mTOR-dependent regulation of alpha-cell mass. Cell Reports 2015 12 495510. (https://doi.org/10.1016/j.celrep.2015.06.034)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 74

    Johnston O, Rose CL, Webster AC & Gill JS. Sirolimus is associated with new-onset diabetes in kidney transplant recipients. Journal of the American Society of Nephrology: JASN 2008 19 14111418. (https://doi.org/10.1681/ASN.2007111202)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 75

    Bamgbola O. Metabolic consequences of modern immunosuppressive agents in solid organ transplantation. Therapeutic Advances in Endocrinology and Metabolism 2016 7 110127. (https://doi.org/10.1177/2042018816641580)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 76

    Deblon N, Bourgoin L, Veyrat-Durebex C, Peyrou M, Vinciguerra M, Caillon A, Maeder C, Fournier M, Montet X & Rohner-Jeanrenaud F et al. Chronic mTOR inhibition by rapamycin induces muscle insulin resistance despite weight loss in rats. British Journal of Pharmacology 2012 165 23252340. (https://doi.org/10.1111/j.1476-5381.2011.01716.x)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 77

    Savendahl L, Underwood LE. Fasting increases serum total cholesterol, LDL cholesterol and apolipoprotein B in healthy, nonobese humans. Journal of Nutrition 1999 129 20052008. (https://doi.org/10.1093/jn/129.11.2005)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 78

    Spinar J & Smahelova A. SAVOR TIMI 53 – saxagliptin and cardiovascular outcomes in patients with type 2 diabetes mellitus. Vnitrni Lekarstvi 2013 59 10031007.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 79

    Ai D, Chen C, Han S, Ganda A, Murphy AJ, Haeusler R, Thorp E, Accili D, Horton JD & Tall AR. Regulation of hepatic LDL receptors by mTORC1 and PCSK9 in mice. Journal of Clinical Investigation 2012 122 12621270. (https://doi.org/10.1172/JCI61919)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 80

    Bonner C, Kerr-Conte J, Gmyr V, Queniat G, Moerman E, Thevenet J, Beaucamps C, Delalleau N, Popescu I & Malaisse WJ et al. Inhibition of the glucose transporter SGLT2 with dapagliflozin in pancreatic alpha cells triggers glucagon secretion. Nature Medicine 2015 21 512517. (https://doi.org/10.1038/nm.3828)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 81

    Canto C & Auwerx J. Targeting sirtuin 1 to improve metabolism: all you need is NAD(+)? Pharmacological Reviews 2012 64 166187. (https://doi.org/10.1124/pr.110.003905)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 82

    Briand F, Mayoux E, Brousseau E, Burr N, Urbain I, Costard C, Mark M, Sulpice T. Empagliflozin, via switching metabolism toward lipid utilization, moderately increases LDL cholesterol levels through reduced LDL catabolism. Diabetes 2016 65 20322038. (https://doi.org/10.2337/db16-0049)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 83

    Siess EA, Kientsch-Engel RI & Wieland OH. Role of free oxaloacetate in ketogenesis. Derivation from the direct measurement of mitochondrial [3-hydroxybutyrate]/[acetoacetate] ratio in hepatocytes. European Journal of Biochemistry 1982 121 493499. (https://doi.org/10.1111/j.1432-1033.1982.tb05814.x)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 84

    Dandona P, Mathieu C, Phillip M, Hansen L, Griffen SC, Tschope D, Thoren F, Xu J & Langkilde AM. Efficacy and safety of dapagliflozin in patients with inadequately controlled type 1 diabetes (DEPICT-1): 24 week results from a multicentre, double-blind, phase 3, randomised controlled trial. Lancet Diabetes and Endocrinology 2017 5 864876. (https://doi.org/10.1016/S2213-8587(17)30308-X)

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    • Search Google Scholar
    • Export Citation

 

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    Impact of SGLT2 inhibitor-enhanced fasting on hepatic metabolism. Glucagon levels are increased and insulin levels diminished to maintain glucose levels for the brain, initially through glycogenolysis and eventually through gluconeogenesis. FFA levels rise as insulin levels drop, providing the fuel required to support gluconeogenesis and cellular function. Once activated, hepatic gluconeogenesis consumes the available oxaloacetate slowing down the Krebs cycle and allowing acetyl CoA to build up in the cytosol generating ketone bodies for export outside the liver. As insulin levels drop and fuel switches from glucose to FFAs, gluconeogenic substrates (lactate/pyruvate) become rate limiting, forcing a switch to glucogenic AAs as the carbon source to support glucose synthesis. Autophagy/mitophagy and lysosomal degradation are rapidly activated by the drop in circulating AAs to resupply AAs for this critical function. AA, amino acid; ATP, adenosine triphosphate; BOHB, β-hydroxybutyrate; CoA, coenzyme A; FFA, free fatty acid; mTORC1, mammalian target of rapamycin complex 1.

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    mTOR pathways in the fed and fasted states. In the fed state, mTOR is activated by high levels of circulating AAs via AA-dependent RAG GTPases leading to an anabolic state characterized by inhibited autophagy and enhanced protein synthesis, mitochondrial biogenesis, glycolysis and lipogenesis. In the fasted state, mTOR is inhibited by decreased levels of AAs as a result of activation of gluconeogenesis by SGLT2 inhibitor use, in addition to increased demand for glucogenic AAs as a result of an increased glucagon/insulin ratio. Decreased AA levels then diminish RAG GTPase activity leading to enhanced autophagy and lysosomal fusion with autophagosomes, rapidly generating new AAs for support of gluconeogenesis. The inhibition of mTOR produces a catabolic state characterized by inhibited protein synthesis, mitochondrial biogenesis, glycolysis and lipogenesis. Caloric intake reverses the mTOR inhibition and reinstitutes an anabolic state. 4E-BP1, 4E-binding protein 1; AA, amino acid; HIF1A, hypoxia-inducible factor 1α; mTORC1, mammalian target of rapamycin complex 1; PGC1A, peroxisome proliferator-activated receptor γ coactivator-1α; PPARG, peroxisome proliferator-activated receptor γ; S6K, s6 kinase; SREBP1, Sterol regulatory element-binding protein 1; ULK1, unc-51-like autophagy-activating kinase 1. Adapted with permission from: Maiese K. Molecules to Medicine with mTOR, 1st Edition. Translating Critical Pathways into Novel Therapeutic Strategies. Academic Press Feb 2016. ISBN. 9780128027332.

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    The impact of ‘insulin’ and SGLT2 inhibitor treatment on the mitochondrial fission/fusion cycle. (A) In ‘insulin’-treated type 2 diabetes, the patient is held in sustained anabolic state brought about by excess caloric intake/lack of exercise and reinforced by insulin or insulin-enhancing therapies to lower circulating glucose. The lack of a catabolic state results in the accumulation of autophagosomes that are not triggered for lysosomal degradation due to the lack of hepatic demand for AAs owing to the diminished glucagon/gluconeogenesis axis. Mitochondria are blocked from mitophagy due to the autophagosome backlog and become increasingly dysfunctional, resulting in a shift to a more reduced redox state. Excess NADH causes an increase in superoxide anion levels, setting in motion a chain of oxidative damage and inflammation. As the mitochondrial dysfunction reaches a critical phase, the cells slip into senescence and contribute to organ dysfunction. (B) In patients with type 2 diabetes treated with an SGLT2 inhibitor, the overnight catabolic state is restored by the loss of glucose and increase in glucagon release driving all of the processes necessary for the upkeep of the cells improving global organ health, including activation of AMPK and Sirt1 and autophagy/lysosomal processes. AA, amino acid; β-OHB, β-hydroxybutyrate; FFA, free fatty acid; Gluc, glucose; mTOR, mammalian target of rapamycin; NAD+, nicotinamide adenine dinucleotide; NADH, nicotinamide adenine dinucleotide (reduced form); PGC1a, peroxisome proliferator-activated receptor γ coactivator-1α.

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    The impact of SGLT2 inhibitor treatment on mitochondrial function. Healthy patients cycle through daily anabolic periods characterized by increased insulin levels and glucose utilization as fuel, with fuel storage and protein/organelle synthesis occurring with excess glucose. Overnight, a period of fasting occurs which is deep enough to trigger glucagon release, depleting glycogen stores to a degree sufficient to require a glucogenic AA source to support gluconeogenesis. AAs are supplied through lysosomal degradation of damaged proteins (autophagy/mitophagy/ubiquitin/proteasome system (UPS)) throughout the body caused by inhibition of mTOR following a drop in circulating AAs as a result of gluconeogenesis. Ketone bodies are generated as gluconeogenesis blocks the Krebs cycle providing another important extrahepatic fuel source. Patients with type 2 diabetes receiving insulin-based therapies experience increased insulin levels, which forces glucose into cells, making it harder to achieve an overnight fast, locking the patients in an anabolic state. The increase in insulin levels also prevents an increase in glucagon, preventing its beneficial catabolic effects. Use of an SGLT2 inhibitor strengthens the overnight fast owing to constant glucose loss, restoring overnight glucagon release enabling its catabolic benefit while allowing restoration of the anabolic state in the morning following eating, thus reinstituting the metabolic cycling characteristic of healthy patients. FFA, free fatty acid; SGLT2i, sodium–glucose cotransporter-2 inhibitor; T2D, type 2 diabetes.

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    Metabolic mechanism of benefit. Areas where direct evidence is still lacking are shown in yellow. AA, amino acid; ATP, adenosine triphosphate; β-OHB, β-hydroxybutyrate; FFA, free fatty acid; GNG, gluconeogenesis; mTOR, mammalian target of rapamycin; SGLT2, sodium–glucose cotransporter-2.

  • 1

    Zinman B, Wanner C, Lachin JM, Fitchett D, Bluhmki E, Hantel S, Mattheus M, Devins T, Johansen OE & Woerle HJ et al. Empagliflozin, cardiovascular outcomes, and mortality in type 2 diabetes. New England Journal of Medicine 2015 373 21172128. (https://doi.org/10.1056/NEJMoa1504720)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 2

    Wanner C, Inzucchi SE, Lachin JM, Fitchett D, von Eynatten M, Mattheus M, Johansen OE, Woerle HJ, Broedl UC, Zinman B. Empagliflozin and progression of kidney disease in type 2 diabetes. New England Journal of Medicine 2016 375 323334. (https://doi.org/10.1056/NEJMoa1515920)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 3

    Neal B, Perkovic V, Mahaffey KW, de Zeeuw D, Fulcher G, Erondu N, Shaw W, Law G, Desai M & Matthews DR. Canagliflozin and cardiovascular and renal events in type 2 diabetes. New England Journal of Medicine 2017 377 644657. (https://doi.org/10.1056/NEJMoa1611925)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 4

    Kosiborod M, Cavender MA, Fu AZ, Wilding JP, Khunti K, Holl RW, Norhammar A, Birkeland KI, Jorgensen M & Thuresson M et al. Lower risk of heart failure and death in patients initiated on SGLT-2 inhibitors versus other glucose-lowering drugs: the CVD-REAL study. Circulation 2017 136 249259. (https://doi.org/10.1161/circulationaha.117.029190)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5

    Abdul-Ghani M, Del Prato S, Chilton R & DeFronzo RA. SGLT2 inhibitors and cardiovascular risk: lessons learned from the EMPA-REG OUTCOME study. Diabetes Care 2016 39 717725. (https://doi.org/10.2337/dc16-0041)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6

    Inzucchi SE, Zinman B, Wanner C, Ferrari R, Fitchett D, Hantel S, Espadero RM, Woerle HJ, Broedl UC & Johansen OE. SGLT-2 inhibitors and cardiovascular risk: proposed pathways and review of ongoing outcome trials. Diabetes and Vascular Disease Research 2015 12 90100. (https://doi.org/10.1177/1479164114559852)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 7

    Sattar N, McLaren J, Kristensen SL, Preiss D & McMurray JJ. SGLT2 inhibition and cardiovascular events: why did EMPA-REG Outcomes surprise and what were the likely mechanisms? Diabetologia 2016 59 13331339. (https://doi.org/10.1007/s00125-016-3956-x)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8

    McMurray J. EMPA-REG – the ‘diuretic hypothesis’. Journal of Diabetes and its Complications 2016 30 34. (https://doi.org/10.1016/j.jdiacomp.2015.10.012)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 9

    DeFronzo RA. The EMPA-REG study: what has it told us? A diabetologist’s perspective. Journal of Diabetes and its Complications 2016 30 12. (https://doi.org/10.1016/j.jdiacomp.2015.10.013)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 10

    Jorgensen NB, Pedersen J, Vaag AA. EMPA-REG: glucose excretion and lipid mobilization – not storage – saves lives. Journal of Diabetes and its Complications 2016 30 753. (https://doi.org/10.1016/j.jdiacomp.2016.02.015)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11

    Daniele G, Xiong J, Solis-Herrera C, Merovci A, Eldor R, Tripathy D, DeFronzo RA, Norton L & Abdul-Ghani M. Dapagliflozin enhances fat oxidation and ketone production in patients with type 2 diabetes. Diabetes Care 2016 39 20362041. (https://doi.org/10.2337/dc15-2688)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12

    Ferrannini E, Baldi S, Frascerra S, Astiarraga B, Heise T, Bizzotto R, Mari A, Pieber TR & Muscelli E. Shift to fatty substrate utilization in response to sodium-glucose cotransporter 2 inhibition in subjects without diabetes and patients with type 2 diabetes. Diabetes 2016 65 11901195. (https://doi.org/10.2337/db15-1356)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13

    Ferrannini E, Mark M & Mayoux E. CV protection in the EMPA-REG OUTCOME trial: a ‘thrifty substrate’ hypothesis. Diabetes Care 2016 39 11081114. (https://doi.org/10.2337/dc16-0330)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 14

    Mudaliar S, Alloju S & Henry RR. Can a shift in fuel energetics explain the beneficial cardiorenal outcomes in the EMPA-REG OUTCOME study? A unifying hypothesis. Diabetes Care 2016 39 11151122. (https://doi.org/10.2337/dc16-0542)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15

    Mudaliar S, Henry RR, Boden G, Smith S, Chalamandaris AG, Duchesne D, Iqbal N & List J. Changes in insulin sensitivity and insulin secretion with the sodium glucose cotransporter 2 inhibitor dapagliflozin. Diabetes Technology and Therapeutics 2014 16 137144. (https://doi.org/10.1089/dia.2013.0167)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 16

    Storlien L, Oakes ND & Kelley DE. Metabolic flexibility. Proceedings of the Nutrition Society 2004 63 363368. (https://doi.org/10.1079/PNS2004349)

  • 17

    Kelley DE, Goodpaster B, Wing RR & Simoneau JA. Skeletal muscle fatty acid metabolism in association with insulin resistance, obesity, and weight loss. American Journal of Physiology 1999 277 E1130E1141. (https://doi.org/10.1152/ajpcell.1999.277.6.C1130)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 18

    Muoio DM. Metabolic inflexibility: when mitochondrial indecision leads to metabolic gridlock. Cell 2014 159 12531262. (https://doi.org/10.1016/j.cell.2014.11.034)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19

    Merovci A, Solis-Herrera C, Daniele G, Eldor R, Fiorentino TV, Tripathy D, Xiong J, Perez Z, Norton L & Abdul-Ghani MA et al. Dapagliflozin improves muscle insulin sensitivity but enhances endogenous glucose production. Journal of Clinical Investigation 2014 124 509514. (https://doi.org/10.1172/JCI70704)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 20

    Bolinder J, Ljunggren O, Kullberg J, Johansson L, Wilding J, Langkilde AM, Sugg J & Parikh S. Effects of dapagliflozin on body weight, total fat mass, and regional adipose tissue distribution in patients with type 2 diabetes mellitus with inadequate glycemic control on metformin. Journal of Clinical Endocrinology and Metabolism 2012 97 10201031. (https://doi.org/10.1210/jc.2011-2260)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 21

    Bolinder J, Ljunggren O, Johansson L, Wilding J, Langkilde AM, Sjostrom CD, Sugg J & Parikh S. Dapagliflozin maintains glycaemic control while reducing weight and body fat mass over 2 years in patients with type 2 diabetes mellitus inadequately controlled on metformin. Diabetes, Obesity and Metabolism 2014 16 159169. (https://doi.org/10.1111/dom.12189)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 22

    Berg JM, Tymoczko JL, Stryer L. Section 30, the integration of metabolism. In Biochemistry, 5 ed., ch 30, pp 12501280. New York: W H Freeman, 2002.

    • Search Google Scholar
    • Export Citation
  • 23

    Longo VD & Mattson MP. Fasting: molecular mechanisms and clinical applications. Cell Metabolism 2014 19 181192. (https://doi.org/10.1016/j.cmet.2013.12.008)

  • 24

    Laplante M & Sabatini DM. mTOR signaling in growth control and disease. Cell 2012 149 274293. (https://doi.org/10.1016/j.cell.2012.03.017)

  • 25

    Lee J, Giordano S, Zhang J. Autophagy, mitochondria and oxidative stress: cross-talk and redox signalling. Biochemical Journal 2012 441 523540. (https://doi.org/10.1042/BJ20111451)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 26

    D’Alessio D. The role of dysregulated glucagon secretion in type 2 diabetes. Diabetes, Obesity and Metabolism 2011 13 (Supplement 1) 126132. (https://doi.org/10.1111/j.1463-1326.2011.01449.x)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 27

    Lim EL, Hollingsworth KG, Aribisala BS, Chen MJ, Mathers JC & Taylor R. Reversal of type 2 diabetes: normalisation of beta cell function in association with decreased pancreas and liver triacylglycerol. Diabetologia 2011 54 25062514. (https://doi.org/10.1007/s00125-011-2204-7)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28

    Colberg SR, Sigal RJ, Fernhall B, Regensteiner JG, Blissmer BJ, Rubin RR, Chasan-Taber L, Albright AL & Braun B. Exercise and type 2 diabetes: the American College of Sports Medicine and the American Diabetes Association: joint position statement executive summary. Diabetes Care 2010 33 26922696. (https://doi.org/10.2337/dc10-1548)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29

    Jorgensen NB, Dirksen C, Bojsen-Moller KN, Jacobsen SH, Worm D, Hansen DL, Kristiansen VB, Naver L, Madsbad S & Holst JJ. Exaggerated glucagon-like peptide 1 response is important for improved beta-cell function and glucose tolerance after Roux-en-Y gastric bypass in patients with type 2 diabetes. Diabetes 2013 62 30443052. (https://doi.org/10.2337/db13-0022)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30

    Longo VD, Panda S. Fasting, circadian rhythms, and time-restricted feeding in healthy lifespan. Cell Metabolism 2016 23 10481059. (https://doi.org/10.1016/j.cmet.2016.06.001)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31

    Kelley DE. Skeletal muscle fat oxidation: timing and flexibility are everything. Journal of Clinical Investigation 2005 115 16991702. (https://doi.org/10.1172/JCI25758)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 32

    Laplante M & Sabatini DM. mTOR signaling at a glance. Journal of Cell Science 2009 122 35893594. (https://doi.org/10.1242/jcs.051011)

  • 33

    Kume S, Koya D, Uzu T & Maegawa H. Role of nutrient-sensing signals in the pathogenesis of diabetic nephropathy. BioMed Research International 2014 2014 315494. (https://doi.org/10.1155/2014/315494)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 34

    Zoncu R, Efeyan A & Sabatini DM. mTOR: from growth signal integration to cancer, diabetes and ageing. Nature Reviews Molecular Cell Biology 2011 12 2135. (https://doi.org/10.1038/nrm3025)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 35

    Russell RC, Yuan HX & Guan KL. Autophagy regulation by nutrient signaling. Cell Research 2014 24 4257. (https://doi.org/10.1038/cr.2013.166)

  • 36

    Korolchuk VI, Saiki S, Lichtenberg M, Siddiqi FH, Roberts EA, Imarisio S, Jahreiss L, Sarkar S, Futter M & Menzies FM et al. Lysosomal positioning coordinates cellular nutrient responses. Nature Cell Biology 2011 13 453460. (https://doi.org/10.1038/ncb2204)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 37

    Zhou J, Tan SH, Nicolas V, Bauvy C, Yang ND, Zhang J, Xue Y, Codogno P & Shen HM. Activation of lysosomal function in the course of autophagy via mTORC1 suppression and autophagosome-lysosome fusion. Cell Research 2013 23 508523. (https://doi.org/10.1038/cr.2013.11)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 38

    Sandri M. FOXOphagy path to inducing stress resistance and cell survival. Nature Cell Biology 2012 14 786788. (https://doi.org/10.1038/ncb2550)

  • 39

    Webster BR, Scott I, Traba J, Han K & Sack MN. Regulation of autophagy and mitophagy by nutrient availability and acetylation. Biochimica et Biophysica Acta 2014 1841 525534. (https://doi.org/10.1016/j.bbalip.2014.02.001)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 40

    Twig G, Elorza A, Molina AJ, Mohamed H, Wikstrom JD, Walzer G, Stiles L, Haigh SE, Katz S & Las G et al. Fission and selective fusion govern mitochondrial segregation and elimination by autophagy. EMBO Journal 2008 27 433446. (https://doi.org/10.1038/sj.emboj.7601963)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 41

    Ding WX & Yin XM. Mitophagy: mechanisms, pathophysiological roles, and analysis. Biological Chemistry 2012 393 547564. (https://doi.org/10.1515/hsz-2012-0119)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 42

    Liesa M & Shirihai OS. Mitochondrial dynamics in the regulation of nutrient utilization and energy expenditure. Cell Metabolism 2013 17 491506. (https://doi.org/10.1016/j.cmet.2013.03.002)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 43

    Terman A, Kurz T, Navratil M, Arriaga EA & Brunk UT. Mitochondrial turnover and aging of long-lived postmitotic cells: the mitochondrial-lysosomal axis theory of aging. Antioxidants and Redox Signaling 2010 12 503535. (https://doi.org/10.1089/ars.2009.2598)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 44

    Gomes LC, Di Benedetto G & Scorrano L. Essential amino acids and glutamine regulate induction of mitochondrial elongation during autophagy. Cell Cycle 2011 10 26352639. (https://doi.org/10.4161/cc.10.16.17002)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 45

    Meijer AJ, Codogno P. Autophagy: regulation and role in disease. Critical Reviews in Clinical Laboratory Sciences 2009 46 210240. (https://doi.org/10.1080/10408360903044068)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 46

    Song M, Mihara K, Chen Y, Scorrano L & Dorn GW 2nd. Mitochondrial fission and fusion factors reciprocally orchestrate mitophagic culling in mouse hearts and cultured fibroblasts. Cell Metabolism 2015 21 273285. (https://doi.org/10.1016/j.cmet.2014.12.011)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 47

    Gonzalez CD, Lee MS, Marchetti P, Pietropaolo M, Towns R, Vaccaro MI, Watada H & Wiley JW. The emerging role of autophagy in the pathophysiology of diabetes mellitus. Autophagy 2011 7 211. (https://doi.org/10.4161/auto.7.1.13044)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 48

    Las G & Shirihai OS. The role of autophagy in beta-cell lipotoxicity and type 2 diabetes. Diabetes, Obesity and Metabolism 2010 12 (Supplement 2) 1519. (https://doi.org/10.1111/j.1463-1326.2010.01268.x)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 49

    Marrif HI & Al-Sunousi SI. Pancreatic beta cell mass death. Frontiers in Pharmacology 2016 7 83. (https://doi.org/10.3389/fphar.2016.00083)

  • 50

    Tanaka Y, Kume S, Kitada M, Kanasaki K, Uzu T, Maegawa H & Koya D. Autophagy as a therapeutic target in diabetic nephropathy. Experimental Diabetes Research 2012 2012 628978. (https://doi.org/10.1155/2012/628978)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 51

    De Meyer GR, De Keulenaer GW & Martinet W. Role of autophagy in heart failure associated with aging. Heart Failure Reviews 2010 15 423430. (https://doi.org/10.1007/s10741-010-9166-6)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 52

    Levine B & Kroemer G. Autophagy in the pathogenesis of disease. Cell 2008 132 2742. (https://doi.org/10.1016/j.cell.2007.12.018)

  • 53

    Montgomery MK & Turner N. Mitochondrial dysfunction and insulin resistance: an update. Endocrine Connections 2015 4 R1R15. (https://doi.org/10.1530/EC-14-0092)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 54

    Yoon Y, Galloway CA, Jhun BS & Yu T. Mitochondrial dynamics in diabetes. Antioxidants and Redox Signaling 2011 14 439457. (https://doi.org/10.1089/ars.2010.3286)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 55

    Noland RC, Koves TR, Seiler SE, Lum H, Lust RM, Ilkayeva O, Stevens RD, Hegardt FG & Muoio DM. Carnitine insufficiency caused by aging and overnutrition compromises mitochondrial performance and metabolic control. Journal of Biological Chemistry 2009 284 2284022852. (https://doi.org/10.1074/jbc.M109.032888)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 56

    Muoio DM, Noland RC, Kovalik JP, Seiler SE, Davies MN, DeBalsi KL, Ilkayeva OR, Stevens RD, Kheterpal I & Zhang J et al. Muscle-specific deletion of carnitine acetyltransferase compromises glucose tolerance and metabolic flexibility. Cell Metabolism 2012 15 764777. (https://doi.org/10.1016/j.cmet.2012.04.005)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 57

    Lindeboom L, Nabuurs CI, Hoeks J, Brouwers B, Phielix E, Kooi ME, Hesselink MK, Wildberger JE, Stevens RD & Koves T et al. Long-echo time MR spectroscopy for skeletal muscle acetylcarnitine detection. Journal of Clinical Investigation 2014 124 49154925. (https://doi.org/10.1172/JCI74830)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 58

    Edwards JL, Quattrini A, Lentz SI, Figueroa-Romero C, Cerri F, Backus C, Hong Y & Feldman EL. Diabetes regulates mitochondrial biogenesis and fission in mouse neurons. Diabetologia 2010 53 160169. (https://doi.org/10.1007/s00125-009-1553-y)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 59

    Vincent AM, Edwards JL, McLean LL, Hong Y, Cerri F, Lopez I, Quattrini A & Feldman EL. Mitochondrial biogenesis and fission in axons in cell culture and animal models of diabetic neuropathy. Acta Neuropathologica 2010 120 477489. (https://doi.org/10.1007/s00401-010-0697-7)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 60

    Jheng HF, Tsai PJ, Guo SM, Kuo LH, Chang CS, Su IJ, Chang CR & Tsai YS. Mitochondrial fission contributes to mitochondrial dysfunction and insulin resistance in skeletal muscle. Molecular and Cellular Biology 2012 32 309319. (https://doi.org/10.1128/MCB.05603-11)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 61

    Perier C & Vila M. Mitochondrial biology and Parkinson’s disease. Cold Spring Harbor Perspectives in Medicine 2012 2 a009332. (https://doi.org/10.1101/cshperspect.a009332)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 62

    Ramsay RR, Kowal AT, Johnson MK, Salach JI & Singer TP. The inhibition site of MPP+, the neurotoxic bioactivation product of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine is near the Q-binding site of NADH dehydrogenase. Archives of Biochemistry and Biophysics 1987 259 645649. (https://doi.org/10.1016/0003-9861(87)90531-5)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 63

    Aravinthan A, Scarpini C, Tachtatzis P, Verma S, Penrhyn-Lowe S, Harvey R, Davies SE, Allison M, Coleman N & Alexander G. Hepatocyte senescence predicts progression in non-alcohol-related fatty liver disease. Journal of Hepatology 2013 58 549556. (https://doi.org/10.1016/j.jhep.2012.10.031)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 64

    Koliaki C, Szendroedi J, Kaul K, Jelenik T, Nowotny P, Jankowiak F, Herder C, Carstensen M, Krausch M & Knoefel WT et al. Adaptation of hepatic mitochondrial function in humans with non-alcoholic fatty liver is lost in steatohepatitis. Cell Metabolism 2015 21 739746. (https://doi.org/10.1016/j.cmet.2015.04.004)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 65

    Chen H & Chan DC. Mitochondrial dynamics – fusion, fission, movement, and mitophagy – in neurodegenerative diseases. Human Molecular Genetics 2009 18 R169R176. (https://doi.org/10.1093/hmg/ddp326)

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 66

    Huber TB, Edelstein CL, Hartleben B, Inoki K, Jiang M, Koya D, Kume S, Lieberthal W, Pallet N & Quiroga A et al. Emerging role of autophagy in kidney function, diseases and aging. Autophagy 2012 8 10091031. (https://doi.org/10.4161/auto.19821)