Skip to main content
Intended for healthcare professionals
Free access
Review article
First published online February 15, 2019

Insulin resistance and insulin hypersecretion in the metabolic syndrome and type 2 diabetes: Time for a conceptual framework shift

Abstract

While few dispute the existence of the metabolic syndrome as a clustering of factors indicative of poor metabolic health, its utility above that of its individual components in the clinical care of individual patients is questioned. This is likely a consequence of the failure of clinicians and scientists to agree on a unifying mechanism to explain the metabolic syndrome. Insulin resistance has most commonly been proposed for this role and is generally considered to be a root causative factor for not only metabolic syndrome but also for its associated conditions of non-alcoholic fatty liver disease (NAFLD), polycystic ovary syndrome (PCOS), obesity-related type 2 diabetes (T2D) and atherosclerotic cardiovascular disease (ASCVD). An alternative view, for which evidence is mounting, is that hyper-responsiveness of islet β-cells to a hostile environment, such as westernised lifestyle, is primary and that the resulting hyperinsulinaemia drives the other components of the metabolic syndrome. Importantly, within this new conceptual framework, insulin resistance, while always a biomarker and state of poor metabolic health, is not considered to be harmful, but a protective adaptive response of critical tissues including the myocardium against insulin-induced metabolic stress. This major shift in how metabolic syndrome can be considered puts insulin hypersecretion into position as the unifying mechanism. If shown to be correct, this new conceptual framework has major implications for the future prevention and management of the metabolic syndrome, including its associated conditions of NAFLD, PCOS, obesity-related T2D and ASCVD.
Professor Gerald ‘Jerry’ Reaven, in his 1988 American Diabetes Association Banting Lecture titled ‘Role of insulin resistance in human disease’, showed strong associations between insulin resistance, hyperinsulinaemia, glucose intolerance, hypertriglyceridaemia, reduced high-density lipoprotein cholesterol and hypertension.1 He termed the clustering of these factors ‘syndrome X’ and demonstrated links between this syndrome and increased risk of atherosclerotic cardiovascular disease (ASCVD).1 Syndrome X, renamed ‘metabolic syndrome’ (MetS), has been expanded to include additional factors such as central or visceral adiposity, increased apolipoprotein B and small dense low-density lipoprotein (LDL) particles (proatherogenic), elevated plasma fibrinogen and plasminogen activator inhibitor (PAI)-1 (prothrombotic), increased C-reactive protein and inflammatory cytokines (systemic inflammation) and microalbuminuria.2,3 It is generally accepted that the clustered components of the MetS, including insulin resistance, contribute to the pathogenesis of conditions such as non-alcoholic fatty liver disease (NAFLD), polycystic ovary syndrome (PCOS), type 2 diabetes (T2D) and ASCVD.25 MetS has also been associated with increased risk for chronic kidney disease, cognitive impairment, obstructive sleep apnoea and chronic respiratory diseases.69 While the usefulness of a diagnosis of MetS over its individual components in predicting T2D and ASCVD has been questioned, MetS is now listed as a disease entity (E88.81) in the International Classification of Diseases – 10th Revision (ICD-10), avowing to the importance of Reaven’s contribution in bringing this clustering of factors involved in cardiometabolic diseases to the attention of clinicians and scientists.1,10

Insulin resistance: root cause of MetS and T2D or a protective adaptive response?

Ongoing controversy surrounding the MetS, in terms of its predictive value for particular diseases, is a consequence of the failure of metabolic scientists and clinicians to establish it as a precise condition or to provide a unifying mechanism to explain its clustering of factors, with insulin resistance and visceral adiposity being most commonly proposed.2,10 Reaven argued for insulin resistance as the unifying mechanism or primary causal factor and, supporting this view, the European Group for the Study of Insulin Resistance proposed ‘insulin resistance syndrome’ as an alternate name for MetS.1,11 Furthermore, the mainstream understanding of pathogenesis of T2D is that it develops as a consequence of failure of pancreatic islet β-cells to sustain the hyperinsulinaemia required to compensate for insulin resistance, giving insulin resistance a high-level causative role.12,13 Thus, within the current conceptual framework, insulin resistance is considered to be ‘harmful’ and the root cause of T2D and all the other conditions linked to the MetS; furthermore, it should be overcome at any cost.
An alternate view gaining momentum is that insulin resistance has a role in protecting critical tissues of the body from metabolic injury in situations of chronic nutrient excess.1417 Its presence within the MetS, while indicative and a biomarker of poor metabolic health, does not mean insulin resistance has a causative role. Furthermore, if insulin resistance does have an adaptive protective role, attempts to override it in patient treatment have the potential to cause harm. Thus, we believe a shift is needed in the conceptual framework by which we understand insulin resistance and the aetiology of T2D and that this has implications on safe management of patients with MetS, T2D and related conditions.

Insulin sensitivity: adaptable to physiological demands

Physiological adaptability in insulin sensitivity is an important mechanism by which the body can regulate nutrient partitioning between tissues, necessitated by wide fluctuations in dietary intake and physical activity, and life events such as rapid pubertal growth, pregnancy, illness and ageing. For example, in response to short-term overfeeding, a rapid fall in insulin sensitivity occurs which allows diversion of nutrients from skeletal muscle to adipose tissue for storage, potentially important moving between situations of feast and famine.18,19 Pregnancy necessitates diversion of nutrients to the developing foetus and insulin resistance in the mother is a mechanism by which this is achieved.20 Key to this discussion is the role of adaption in insulin sensitivity to a chronic nutrient oversupply, as occurs in westernised lifestyles. As discussed below, the development of insulin resistance in such situations could provide important protection to critical tissues such as the heart from nutrient overload and toxicity.1417

Insulin resistance: a protective mechanism against nutrient-induced intracellular metabolic stress

We previously proposed that in response to chronic over-nutrition, tissues normally responsive to insulin for glucose uptake, such as the heart and skeletal muscle, protect themselves from nutrient-induced toxicity by becoming insulin resistant.14,15 Without this mechanism at times of nutrient surplus, or by overriding this protective insulin resistance with high-dose insulin therapy, these tissues will be damaged by nutrient overload, a process we have termed ‘insulin-induced metabolic stress’ (Figure 1).14,15
Figure 1. Model illustrating the molecular basis of insulin-induced metabolic stress in obese insulin-resistant and poorly controlled type 2 diabetes patients. Depicted is a cell in which (a) insulin resistance (IR) protects from nutrient overload and metabolic stress by limiting glucose flux into the cell at times when both glucose and free fatty acids (FFA) are elevated in blood; (b) the IR protection is overridden by a high dose of exogenous insulin therapy which promotes excess glucose uptake and both glucotoxicity and lipotoxicity. High FFA availability inhibits glucose oxidation at the level of pyruvate dehydrogenase (PDH), such that a high glucose flux promoted by high levels of insulin will be forced into glucotoxic pathways above this step, including the polyol and hexosamine pathways, as well as the production of advanced glycation end product (AGE) precursors. Furthermore, high glucose availability promotes build-up of cytosolic malonyl-CoA which will inhibit carnitine palmitoyltransferase 1 (CPT1) and the transfer of long-chain acyl-CoAs (LC-AcylCoA) into mitochondria for β-oxidation. This will result in a push of intracellular FFA metabolism towards synthesis of complex lipids, such as diacylglycerols, cholesterol esters and ceramides, and steatosis causing lipotoxicity. Excess glucose supply to the mitochondria in the presence of high FFA supply will also promote reactive oxygen species (ROS) production and oxidative damage.
CD36: free fatty acid transporter; GLUT4: facilitative glucose transporter 4; Ins-R: insulin receptor.
A failure to limit excess entry of glucose at times of concomitant high free fatty acid (FFA) availability will cause cell injury by the mechanisms of glucolipotoxicity.12 High FFA availability will inhibit glucose oxidation at the level of pyruvate dehydrogenase, such that a high glucose flux will be forced into pathways above this step, including glycogen synthesis, the polyol and hexosamine pathways, and the production of advanced glycation end product (AGE) precursors (Figure 1).21,22 Similarly, high glucose availability, via malonyl-CoA/AMPK metabolic sensing mechanisms, will inhibit FFA oxidation such that intracellular FFA metabolism will be pushed towards esterification and other processes causing intracellular steatosis and accumulation of complex lipids such as diacylglycerols, cholesterol esters and ceramides (Figure 1).23,24 An excessive mixed nutrient entry into cells will also overload the electron transfer chain resulting in mitochondrial dysfunction and increased reactive oxygen species (ROS) production.25,26 Endoplasmic reticulum stress and activation of the inflammasome are also known consequences of excessive nutrient entry.23,2729 The concept of ‘insulin-induced metabolic stress’ has been discussed in more detail previously.15

Islet β-cell role in obesity and T2D: upstream or downstream of insulin resistance?

The predominant view is that islet β-cell failure in obesity-related T2D is a consequence of it not being able to sustain high enough insulin secretion to compensate for insulin resistance, suggesting it is downstream and a victim of insulin resistance.12 However, increasing evidence from pre-clinical and clinical studies support an alternate possibility, at least in subsets of individuals at risk of T2D, that hyper-responsiveness of the islet β-cell to a hostile environment (e.g. from a westernised lifestyle) drives hyperinsulinaemia, this being the culprit and upstream to excessive weight gain, insulin resistance, subsequent β-cell failure and the development of T2D.3033
There is considerable heterogeneity in islet β-cell function in mouse strains with those that have a tendency for insulin hypersecretion (e.g. DBA/2 compared to the C57Bl/6 and 129 T2 strains) being more prone to high fat diet–induced weight gain and β-cell failure.33,34 Further-more, there are several examples by which suppression of insulin secretion through genetic manipulation can reduce high fat diet–induced obesity and insulin resistance. Islet β-cell-specific deletion of the adipose triglyceride lipase, through reducing the lipid amplification arm of fuel-induced insulin secretion, protects mice from obesity, hyperinsulinaemia, insulin resistance and hyperglycaemia.35 In addition, through suppressing insulin secretion by knocking out three of the four insulin gene alleles (Ins1−/−; Ins2+/− and Ins1−/−; Ins2+/+), it has been shown that ageing female mice have lower glycaemia, improved insulin sensitivity and an extended life span.36 The model less predictably altered insulin secretion in male mice.30 In the leptin deficient ob/ob mouse model of obesity, a similar genetic approach to lowering insulin secretion, while successfully being able to attenuate obesity, resulted in the development of diabetes, indicative of a need for compensatory hyperinsulinaemia for obesity-related insulin resistance when a rare monogenic cause of obesity rather than hyperinsulinaemia is the primary cause of the excessive weight gain.37
Of relevance within human studies is the Da Qing Children Cohort Study which showed that fasting insulin at the age of 5 years, after the adjustment for age, sex, birth weight, TV-viewing time and weight (or body mass index) at baseline, predicted weight gain from age 5 to 10 years.38 Furthermore, higher insulin levels at 5 years of age were also predictive of higher levels of systolic blood pressure, fasting plasma glucose, insulin resistance as determined by the homeostasis model and triglycerides at 10 years of age, all features of the MetS.38 The findings were similar to those in a study of Pima Indian children.39 In addition, adolescent girls with PCOS have been shown to have early-onset insulin hypersecretion in association with insulin resistance.40
Pharmacological approaches to suppress insulin secretion in humans also support the view that hyperinsulinaemia may have more of a primary role in the MetS. In obese men, 6 months treatment of lifestyle change with either diazoxide (DZ) alone (inhibits insulin secretion by activating the ATP sensitive potassium channels), DZ with metformin (DZ + M) or placebo showed that DZ (DZ and DZ + M groups combined) markedly reduced fasting insulin levels by 72% compared to only 23% in the placebo group (p < 0.001), and this was accompanied by greater improvements in body weight, LDL cholesterol, HDL cholesterol, triglyceride, and systolic and diastolic blood pressure.41 Similar findings were found when hyperinsulinaemia was suppressed by the somatostatin analogue octreotide LAR in obese subjects, with evidence of responders and non-responders to this therapy.42 Also of relevance, in subjects with T2D, short-term DZ use is capable of restoring islet β-cell function through β-cell rest.43,44
Thus, considerable evidence points to insulin hypersecretion as being at, or close to, the root cause of MetS and its related conditions, with insulin resistance being downsteam. Focus on reducing insulin hypersecretion, at least early in the course of these conditions, is likely to have beneficial metabolic effects.

Towards better stratification of diabetes: subset of severe insulin-resistant and hyperinsulinaemic diabetes

Within a recently reported study of adult-onset diabetes from Scandinavia, five subgroups were identified: severe autoimmune diabetes (SAID), severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD) and mild age-related diabetes (MARD).45
The subgroup that seems most relevant to this discussion is SIRD, with the predominant characteristics being obesity, severe hyperinsulinaemia and insulin resistance. An alternative name for this subgroup could have been ‘severe hyperinsulinaemic diabetes’. Individuals within this subgroup, in keeping with the concept of insulin-induced metabolic stress, were also more likely to develop diabetic nephropathy and have coronary events.45 Surprisingly, the age of diabetes onset in the SIRD group was relatively high, which may relate to the predominant Scandinavian ethnicity within the diabetes registries used.45 The SIRD subgroup characteristics of more severe hyperinsulinaemia and insulin resistance tend to be mirrored in young people presenting with obesity-related T2D, as was found in the Restoring Insulin Secretion (RISE) study and is also reported in various high-risk indigenous groups.40,46,47 T2D in youth is also associated with a much higher risk of early-onset nephropathy and macrovascular disease.40 If in this subset of diabetes (SIRD), insulin hypersecretion rather than insulin resistance has the primary role, as remains to be determined, it will have major implications on the best approaches to prevention and treatment.
In the SIDD, MOD, and MARD subgroups, insulin resistance is of lesser degree at the time of diabetes diagnosis; however, islet β-cell failure must be involved in the pathogenesis. Whether mild suppression of insulin secretion in at least some of those at risk within these subgroups would prevent this β-cell failure and T2D development is unknown. A precision medicine approach will most likely be required in which the correct approach to diabetes prevention and treatment will require detailed phenotypic and genotypic classification of individual patients within these subgroups.

A paradigm shift: new conceptual framework for considering insulin resistance and the MetS

If insulin resistance, while clearly being a biomarker of poor metabolic health, is also to be considered a defensive mechanism used by critical tissues against hyperinsulinaemia and nutrient overload, a complete revision of the conceptual framework within which hyperinsulinaemia, insulin resistance and the MetS are viewed, is needed (Figure 2). Such a revision is not trivial, as it has major implications for how MetS and its associated conditions, including T2D, PCOS, NAFLD and ASCVD, should be prevented and managed. Within this new framework and paradigm shift, hyperinsulinaemia has a more primary or causative role. In doing so, instead of the role of the islet β-cell being one of ‘compensation’ for insulin resistance, it becomes the primary driver, with insulin hypersecretion and the resulting hyperinsulinaemia taking up position as the unifying mechanism. Thus, the development of new therapeutic approaches for MetS, and at least the SIRD subgroup of T2D, will need to move to prevention and/or suppression of the hypersecreting β-cell (Figure 2). Approaches to lower glucose and other elevated nutrients in the blood of MetS and T2D patients through overriding the protective role of insulin resistance will be contraindicated, as we and others have previously advocated.1417 While research into mechanisms of islet β-cell failure and insulin resistance will continue to be important, more focus on the mechanisms driving insulin hypersecretion will be required, whether they be genetic or acquired, including those acquired early in life from epigenetic processes and/or consequent on islet β-cell response to new environmental exposures.31
Figure 2. A new conceptual framework for considering insulin resistance and the metabolic syndrome (MetS) and its associated disorders. The key changes in this conceptual framework are the roles of hyperinsulinaemia and insulin resistance in the MetS. Islet β-cell hyper-responsiveness to adverse environmental factors in genetically or epigenetically predisposed individuals results in hyperinsulinaemia and this is the primary driver of the MetS. Insulin resistance provides protection for critical tissues against insulin-induced metabolic stress and, while being a biomarker of metabolic ill health, is not a driver of pathogenesis. The characteristic features of MetS are driven by hyperinsulinaemia. The MetS-related disease entities, type 2 diabetes (T2D), cardiovascular diseases (CVD), non-alcoholic fatty liver disease/non-alcoholic steatohepatitis (NAFLD/NASH) and polycystic ovary syndrome (PCOS) are a downstream consequence of hyperinsulinaemia and the MetS.

Relevance to management of T2D

Optimisation of cellular nutrient status

In managing disturbed metabolic homeostasis in T2D, the focus of clinicians is currently on normalising glucose and lipid parameters in the blood. Less thought is given to optimising intracellular metabolism, even though nutrient-induced tissue injury in obesity-related T2D is predominantly a consequence of excess entry of nutrients from the blood into cells. This is understandable, as measuring nutrient levels is much easier in blood (e.g. blood glucose, HbA1c and plasma triglycerides) than in cells. The corollary is that approaches to normalise glycaemia in obesity-related T2D that drive glucose and other nutrients into already nutrient-overloaded cells, such as by high-dose insulin therapy or sulphonylureas to override insulin resistance, or insulin sensitisers to reverse insulin resistance depending on mechanism of action, may unintentionally cause harm.15 According to this argument, alternative approaches to lowering glycaemia that nutrient off-load cells, such as intensive lifestyle measures, sodium-glucose transporter 2 (SGLT2) inhibitors, glucagon-like peptide-1 receptor agonists or bariatric surgery, should be beneficial in the majority of patients with obesity-associated T2D (Figure 3(a)).15
Figure 3. Optimisation of cellular nutrient status in patients with hyper- or hypoinsulinaemic type 2 diabetes: importance of the approach to glucose lowering. (a) In untreated type 2 diabetes (T2D) with hyperinsulinaemic diabetes, insulin resistance (IR) protects insulin-responsive cells such as cardiomyocytes and skeletal muscle cells from nutrient overload; cells such as endothelial cells that are non-responsive to insulin with respect to glucose uptake, however, are not protected and are injured by glucotoxicity contributing to diabetes complications (left panel). Glucose-lowering approaches that override the physiological IR to force glucose into insulin-responsive tissues (e.g. by high-dose insulin therapy) may reduce glucotoxicty in some tissues, but at the cost of nutrient-induced injury to the insulin-responsive tissues (e.g. causing a metabolic cardiomyopathy) (centre panel). Glucose-lowering approaches that off-load glucose from cells of critical body tissues, by either reducing glucose entry into the blood (e.g. intensive lifestyle, α-glucosidase inhibitors and bariatric surgery) or glucose clearance from the blood via non-toxic routes (e.g. SGLT2 inhibitors to promote urinary glucose loss, exercise and activation of brown adipose tissue), will reduce nutrient-induced tissue injury in all cell types (right panel). (b) In untreated hypoinsulinaemic T2D, a starvation response to insulin deprivation occurs in which free fatty acid (FFA) release from adipose tissue is increased and hepatic ketone body production is increased; cardiomyocytes and skeletal muscle cells are starved of glucose and switch to use FFA and ketone body for energy; cells such as endothelial cells are not protected from hyperglycaemia (left panel). In this circumstance, insulin therapy will prevent the starvation response and normalise cellular nutrient status in insulin-responsive tissues and prevent glucotoxicity in endothelial cells (centre panel). Glucose-lowering approaches that off-load glucose from cells (e.g. by very low carbohydrate diets or fasting for surgery) together with glucose clearance from the blood (e.g. SGLT2 inhibitors) will exacerbate the starvation response in hypoinsulinaemic T2D and induce euglycaemic ketoacidosis (right panel). Healthy cells are shown in green; unhealthy nutrient-overloaded cells are shown in red; and unhealthy nutrient-deprived cells are shown in blue.
The alternate scenario of intracellular nutrient depletion in patients with hypoinsulinaemic diabetes is also important to consider, particularly, with the increasing occurrence of cases of euglycaemic ketoacidosis in patients treated with SGLT2 inhibitors.48 Avoidance of SGLT2 inhibitors and most often a shift to insulin therapy will be necessary in such patients (Figure 3(b)).
Thus, the approach to diabetes management should take into account some consideration of cellular nutrient status (Figure 3). For these reasons, new blood biomarkers of cellular nutrient or energy status may also be of value in patient care and once discovered should be examined for clinical utility.
In support of the proposition that glucose-lowering approaches that work by driving glucose into tissues can be harmful in overweight and obese subjects with T2D and insulin resistance, we reviewed major T2D clinical trials and found that whenever intensive glucose-lowering approaches were associated with weight gain of greater than 1.0 kg/year [Action to Control Cadiovascular Risk in Diabetes (ACCORD), Veterans Affairs Diabetes Trial (VADT) and Diabetes Mellitus Insulin-Glucose Infusion in Acute Myocardial Infarction 2 (DIGAMI 2)], cardiovascular and all-cause mortality increased, although only reaching statistical significance in ACCORD given the greater sample size.15 Furthermore, among adults with diabetes and stable ischaemic heart disease aged ⩾75 years, insulin provision therapy was associated with an increased risk for all-cause mortality [hazard ratio = 1.89, confidence interval (CI) = 1.1–3.2, p = 0.020].49
In support of the benefits of nutrient off-loading approaches are more recent clinical trials of new classes of glucose-lowering agents, such as SGLT2 inhibitors (by promoting urinary glucose loss) and GLP-1 receptor agonists (by reducing weight through increased satiety), as well as bariatric surgery that have demonstrated reductions in major adverse cardiovascular and renal outcomes in high-risk T2D patients.5052 The recent consensus statement of the American Diabetes Association (ADA) and European Association for the Study of Diabetes (EASD) on the management of hyperglycaemia in T2D has taken the results of these major clinical trials into consideration in their recommendations.53

Prevention of insulin hypersecretion

The nutrient off-loading approaches to glucose lowering available in the management of T2D, including intensive lifestyle change, SGLT2 inhibitors, GLP-1 receptor antagonists, α-glucosidase inhibitors and bariatric surgery, will all reduce insulin hypersecretion. However, often these therapies are started once T2D is established and failure of islet β-cells has already commenced. Optimal approaches for reversal of severe hyperinsulinaemia in patients prior to development of T2D or early in its course, in particular in younger individuals, when lifestyle measures are generally unsuccessful, are not known. Of note, bariatric surgery has been shown to be effective in reversing hyperinsulinaemia and MetS in obese adolescents.54 In the RISE study, neither 3 months of insulin glargine followed by 9 months of metformin nor 12 months of metformin alone slowed the progressive deterioration of β-cell function in young people with early T2D, suggesting different approaches are required.55 The development of specific islet β-cell therapies to limit insulin hypersecretion in high-risk individuals with MetS-related conditions and obesity-related pre-diabetes and early T2D should be pursued.

Conclusion

The part played by Jerry Reaven in linking the dots between the various components of the MetS and the relevance of MetS to ASCVD, NAFLD, PCOS and T2D has been enormously important. The search for the unifying mechanism has been contentious. Here, we make a case for putting ‘insulin hypersecretion’ into this role, while considering insulin resistance as a protective downstream response. This necessitates a complete revision of the conceptual framework within which we view insulin resistance and the pathophysiology of the MetS and obesity-associated T2D, which if confirmed, has major implications for the prevention and management of these metabolic conditions.

Declaration of conflicting interests

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: C.J.N. has received speaking fees from AstraZeneca, Servier and Sanofi; M.P. declares no conflicts of interest.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: This work was supported in part by grants from the Canadian Institutes of Health Research (M.P.) and the National Health and Medical Research Council [project grant 1128442 (C.J.N.)].

References

1. Reaven GM. Banting Lecture 1988: role of insulin resistance in human disease. Diabetes 1988; 37: 1595–1607.
2. Sperling LS, Mechanick JI, Neeland IJ, et al. The cardiometabolic health alliance: working toward a new care model for the metabolic syndrome. J Am Coll Cardiol 2015; 66: 1050–1067.
3. Cornier MA, Dabelea D, Hernandez TL, et al. The metabolic syndrome. Endocr Rev 2008; 29: 777–822.
4. Lim SS, Kakoly NS, Tan JWJ, et al. Metabolic syndrome in polycystic ovary syndrome: a systematic review, meta-analysis and meta-regression. Obes Rev 2018; 20: 339–352.
5. Farrell GC, Haczeyni F, Chitturi S. Pathogenesis of NASH: how metabolic complications of overnutrition favour lipotoxicity and pro-inflammatory fatty liver disease. Adv Exp Med Biol 2018; 1061: 19–44.
6. Drager LF, Togeiro SM, Polotsky VY, et al. Obstructive sleep apnea: a cardiometabolic risk in obesity and the metabolic syndrome. J Am Coll Cardiol 2013; 62: 569–576.
7. Baffi CW, Wood L, Winnica D, et al. Metabolic syndrome and the lung. Chest 2016; 149: 1525–1534.
8. Joyce T, Chirino YI, Natalia MT, et al. Renal damage in the metabolic syndrome (MetSx): disorders implicated. Eur J Pharmacol 2018; 818: 554–568.
9. Kim B, Feldman EL. Insulin resistance as a key link for the increased risk of cognitive impairment in the metabolic syndrome. Exp Mol Med 2015; 47: e149.
10. Simmons RK, Alberti KG, Gale EA, et al. The metabolic syndrome: useful concept or clinical tool? Report of a WHO expert consultation. Diabetologia 2010; 53: 600–605.
11. Balkau B, Charles MA. Comment on the provisional report from the WHO consultation: European group for the study of insulin resistance (EGIR). Diabetic Med 1999; 16: 442–443.
12. Prentki M, Nolan CJ. Islet beta cell failure in type 2 diabetes. J Clin Invest 2006; 116: 1802–1812.
13. Kahn SE, Cooper ME, Del Prato S. Pathophysiology and treatment of type 2 diabetes: perspectives on the past, present, and future. Lancet 2014; 383: 1068–1083.
14. Nolan CJ, Ruderman NB, Prentki M. Intensive insulin for type 2 diabetes: the risk of causing harm. Lancet Diabetes Endo 2013; 1: 9–10.
15. Nolan CJ, Ruderman NB, Kahn SE, et al. Insulin resistance as a physiological defense against metabolic stress: implications for the management of subsets of type 2 diabetes. Diabetes 2015; 64: 673–686.
16. Taegtmeyer H, Beauloye C, Harmancey R, et al. Insulin resistance protects the heart from fuel overload in dysregulated metabolic states. Am J Physiol: Heart C 2013; 305: H1693–H1697.
17. Connor T, Martin SD, Howlett KF, et al. Metabolic remodelling in obesity and type 2 diabetes: pathological or protective mechanisms in response to nutrient excess? Clin Exp Pharmacol P 2015; 42: 109–115.
18. Schenk S, Saberi M, Olefsky JM. Insulin sensitivity: modulation by nutrients and inflammation. J Clin Invest 2008; 118: 2992–3002.
19. Kraegen EW, Saha AK, Preston E, et al. Increased malonyl-CoA and diacylglycerol content and reduced AMPK activity accompany insulin resistance induced by glucose infusion in muscle and liver of rats. Am J Physiol: Endoc M 2006; 290: E471–E479.
20. Freinkel N. Banting Lecture 1980: of pregnancy and progeny. Diabetes 1980; 29: 1023–1035.
21. Chess DJ, Stanley WC. Role of diet and fuel overabundance in the development and progression of heart failure. Cardiovasc Res 2008; 79: 269–278.
22. Brownlee M. The pathobiology of diabetic complications: a unifying mechanism. Diabetes 2005; 54: 1615–1625.
23. El-Assaad W, Joly E, Barbeau A, et al. Glucolipotoxicity alters lipid partitioning and causes mitochondrial dysfunction, cholesterol, and ceramide deposition and reactive oxygen species production in INS832/13 beta-cells. Endocrinology 2010; 151: 3061–3073.
24. Ruderman N, Prentki M. AMP kinase and malonyl-CoA: targets for therapy of the metabolic syndrome. Nat Rev Drug Discov 2004; 3: 340–351.
25. Hoehn KL, Salmon AB, Hohnen-Behrens C, et al. Insulin resistance is a cellular antioxidant defense mechanism. P Natl Acad Sci USA 2009; 106: 17787–17792.
26. Muoio DM, Neufer PD. Lipid-induced mitochondrial stress and insulin action in muscle. Cell Metab 2012; 15: 595–605.
27. Preston AM, Gurisik E, Bartley C, et al. Reduced endoplasmic reticulum (ER)-to-Golgi protein trafficking contributes to ER stress in lipotoxic mouse beta cells by promoting protein overload. Diabetologia 2009; 52: 2369–2373.
28. Poitout V, Robertson RP. Glucolipotoxicity: fuel excess and beta-cell dysfunction. Endocr Rev 2008; 29: 351–366.
29. Donath MY. Targeting inflammation in the treatment of type 2 diabetes: time to start. Nat Rev Drug Discov 2014; 13: 465–476.
30. Page MM, Johnson JD. Mild suppression of hyperinsulinemia to treat obesity and insulin resistance. Trends Endocrin Met 2018; 29: 389–399.
31. Corkey BE. Diabetes: have we got it all wrong? Insulin hypersecretion and food additives: cause of obesity and diabetes? Diabetes Care 2012; 35: 2432–2437.
32. Czech MP. Insulin action and resistance in obesity and type 2 diabetes. Nat Med 2017; 23: 804–814.
33. Andrikopoulos S. Obesity and type 2 diabetes: slow down! Can metabolic deceleration protect the islet beta cell from excess nutrient-induced damage? Mol Cell Endocrinol 2010; 316: 140–146.
34. Andrikopoulos S, Massa CM, Aston-Mourney K, et al. Differential effect of inbred mouse strain (C57BL/6, DBA/2, 129T2) on insulin secretory function in response to a high fat diet. J Endocrinol 2005; 187: 45–53.
35. Attane C, Peyot ML, Lussier R, et al. A beta cell ATGL-lipolysis/adipose tissue axis controls energy homeostasis and body weight via insulin secretion in mice. Diabetologia 2016; 59: 2654–2663.
36. Templeman NM, Flibotte S, Chik JHL, et al. Reduced circulating insulin enhances insulin sensitivity in old mice and extends lifespan. Cell Rep 2017; 20: 451–463.
37. D’Souza AM, Johnson JD, Clee SM, et al. Suppressing hyperinsulinemia prevents obesity but causes rapid onset of diabetes in leptin-deficient Lepob/ob mice. Mol Metab 2016; 5: 1103–1112.
38. Chen YY, Wang JP, Jiang YY, et al. Fasting plasma insulin at 5 years of age predicted subsequent weight increase in early childhood over a 5-year period: the Da Qing children cohort study. PLoS ONE 2015; 10: e0127389.
39. Odeleye OE, de Courten M, Pettitt DJ, et al. Fasting hyperinsulinemia is a predictor of increased body weight gain and obesity in Pima Indian children. Diabetes 1997; 46: 1341–1345.
40. Arslanian S, Bacha F, Grey M, et al. Evaluation and management of youth-onset type 2 diabetes: a position statement by the American Diabetes Association. Diabetes Care 2018; 41: 2648–2668.
41. Loves S, van Groningen L, Filius M, et al. Effects of diazoxide-mediated insulin suppression on glucose and lipid metabolism in nondiabetic obese men. J Clin Endocr Metab 2018; 103: 2346–2353.
42. Velasquez-Mieyer PA, Cowan PA, Arheart KL, et al. Suppression of insulin secretion is associated with weight loss and altered macronutrient intake and preference in a subset of obese adults. Int J Obesity 2003; 27: 219–226.
43. Greenwood RH, Mahler RF, Hales CN. Improvement in insulin secretion in diabetes after diazoxide. Lancet 1976; 1: 444–447.
44. Laedtke T, Kjems L, Porksen N, et al. Overnight inhibition of insulin secretion restores pulsatility and proinsulin/insulin ratio in type 2 diabetes. Am J Physiol: Endoc M 2000; 279: E520–E528.
45. Ahlqvist E, Storm P, Karajamaki A, et al. Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. Lancet Diabetes Endo 2018; 6: 361–369.
46. The RISE Consortium. Metabolic contrasts between youth and adults with impaired glucose tolerance or recently diagnosed type 2 diabetes: I: observations using the hyperglycemic clamp. Diabetes Care 2018; 41: 1696–1706.
47. Rowley KG, Best JD, McDermott R, et al. Insulin resistance syndrome in Australian aboriginal people. Clin Exp Pharmacol P 1997; 24: 776–781.
48. Isaacs M, Tonks KT, Greenfield JR. Euglycaemic diabetic ketoacidosis in patients using sodium-glucose co-transporter 2 inhibitors. Intern Med J 2017; 47: 701–704.
49. Damluji AA, Cohen ER, Moscucci M, et al. Insulin provision therapy and mortality in older adults with diabetes mellitus and stable ischemic heart disease: insights from BARI-2D trial. Int J Cardiol 2017; 241: 35–40.
50. Zelniker TA, Wiviott SD, Raz I, et al. SGLT2 inhibitors for primary and secondary prevention of cardiovascular and renal outcomes in type 2 diabetes: a systematic review and meta-analysis of cardiovascular outcome trials. Lancet 2019; 393: 31–39.
51. Martin WP, Docherty NG, Le Roux CW. Impact of bariatric surgery on cardiovascular and renal complications of diabetes: a focus on clinical outcomes and putative mechanisms. Expert Rev Endocrinol Metab 2018; 13: 251–262.
52. Bethel MA, Patel RA, Merrill P, et al. Cardiovascular outcomes with glucagon-like peptide-1 receptor agonists in patients with type 2 diabetes: a meta-analysis. Lancet Diabetes Endo 2018; 6: 105–113.
53. Davies MJ, D’Alessio DA, Fradkin J, et al. Management of hyperglycaemia in type 2 diabetes, 2018: a consensus report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetologia 2018; 61: 2461–2498.
54. Cummings DE, Rubino F. Metabolic surgery in the treatment algorithm for type 2 diabetes: a joint statement by international diabetes organizations. Diabetes Care 2016; 39: 861–877.
55. The RISE Consortium. Impact of insulin and metformin versus metformin alone on beta-cell function in youth with impaired glucose tolerance or recently diagnosed type 2 diabetes. Diabetes Care 2018; 41: 1717–1725.

Cite article

Cite article

Cite article

OR

Download to reference manager

If you have citation software installed, you can download article citation data to the citation manager of your choice

Share options

Share

Share this article

Share with email
EMAIL ARTICLE LINK
Share on social media

Share access to this article

Sharing links are not relevant where the article is open access and not available if you do not have a subscription.

For more information view the Sage Journals article sharing page.

Information, rights and permissions

Information

Published In

Article first published online: February 15, 2019
Issue published: March 2019

Keywords

  1. Cardiovascular diseases
  2. insulin hypersecretion
  3. insulin-mediated metabolic stress
  4. insulin resistance
  5. metabolic syndrome
  6. non-alcoholic fatty liver disease
  7. polycystic ovary syndrome
  8. type 2 diabetes

Rights and permissions

© The Author(s) 2019.
Request permissions for this article.
PubMed: 30770030

Authors

Affiliations

Christopher J Nolan
Department of Endocrinology, The Canberra Hospital, Garran, ACT, Australia
Australian National University Medical School and John Curtin School of Medical Research, Australian National University, Canberra, ACT, Australia
Marc Prentki
CRCHUM and Montreal Diabetes Research Center, University of Montreal, Montreal, QC, Canada
Department of Nutrition and Department of Biochemistry and Molecular Medicine, University of Montreal, Montreal, QC, Canada

Notes

Christopher J Nolan, Department of Endocrinology, The Canberra Hospital, Yamba Drive, Garran, ACT 2606, Australia. Email: [email protected]
Marc Prentki, CRCHUM and Montreal Diabetes Research Center, University of Montreal, 900 St-Denis, Room R08.412, Montreal, QC H2X 0A9, Canada. Email: [email protected]

Metrics and citations

Metrics

Journals metrics

This article was published in Diabetes & Vascular Disease Research.

VIEW ALL JOURNAL METRICS

Article usage*

Total views and downloads: 28464

*Article usage tracking started in December 2016


Altmetric

See the impact this article is making through the number of times it’s been read, and the Altmetric Score.
Learn more about the Altmetric Scores



Articles citing this one

Receive email alerts when this article is cited

Web of Science: 132 view articles Opens in new tab

Crossref: 150

  1. A novel machine learning approach for diagnosing diabetes with a self-...
    Go to citation Crossref Google Scholar
  2. Multiomics Analyses With Stool-Type Stratification in Patient Cohorts ...
    Go to citation Crossref Google Scholar
  3. Overnutrition in the early postnatal period influences lifetime metabo...
    Go to citation Crossref Google Scholar
  4. A mandatory practice in type 2 diabetes mellitus to maintain quality o...
    Go to citation Crossref Google Scholar
  5. Fat as a Friend or Foe of the Bone
    Go to citation Crossref Google Scholar
  6. Changes in Cells Associated with Insulin Resistance
    Go to citation Crossref Google Scholar
  7. The Metabolic Syndrome, a Human Disease
    Go to citation Crossref Google Scholar
  8. Vitamin K-dependent carboxylation in β-cells and diabetes
    Go to citation Crossref Google Scholar
  9. Complete blood count inflammation derived indexes as predictors of met...
    Go to citation Crossref Google Scholar
  10. Absence of Slc39a14/Zip14 in mouse pancrea...
    Go to citation Crossref Google Scholar
  11. Insulin resistance and metabolic syndrome in hepatitis C virus seroneg...
    Go to citation Crossref Google Scholar
  12. Metabolic hormones are integral regulators of female reproductive heal...
    Go to citation Crossref Google Scholar
  13. Sedentarismo, sobrepeso e microbiota intestinal: risco aumentado de di...
    Go to citation Crossref Google Scholar
  14. Restoration of PITPNA in Type 2 diabetic human islets reverses pancrea...
    Go to citation Crossref Google Scholar
  15. Plant-based dietary patterns and fasting insulin: a cross-sectional st...
    Go to citation Crossref Google Scholar
  16. Association Between Metabolic Syndrome and the Risk of Lung Cancer: A ...
    Go to citation Crossref Google Scholar
  17. Bisphenol A (BPA) and Cardiovascular or Cardiometabolic Diseases
    Go to citation Crossref Google Scholar
  18. Early insulin resistance in normoglycemic low-risk individuals is asso...
    Go to citation Crossref Google Scholar
  19. BAM15 as a mitochondrial uncoupler: a promising therapeutic agent for ...
    Go to citation Crossref Google Scholar
  20. Licensed Physical Therapists’ Preparation, Comfort in and Frequency of...
    Go to citation Crossref Google Scholar
  21. Type 2 Diabetes Mellitus and Metabolic Syndrome
    Go to citation Crossref Google Scholar
  22. Tuina (Chinese massage) for insulin resistance and sensitivity: A prot...
    Go to citation Crossref Google Scholar
  23. Ameliorative effect of Stevia rebaudiana B...
    Go to citation Crossref Google Scholar
  24. Managing type 2 diabetes in children and young people: challenges and ...
    Go to citation Crossref Google Scholar
  25. Glycemic and Metabolic Sub-classification of Prediabetes and Risk Fact...
    Go to citation Crossref Google Scholar
  26. Maternal Western-style diet in nonhuman primates leads to offspring is...
    Go to citation Crossref Google Scholar
  27. МІСЦЕ ІНГІБІТОРІВ SGLT2 ТА L-КАРНІТИНУ В ЛІКУВАННІ ХВОРИХ ІЗ ГКС (STEM...
    Go to citation Crossref Google Scholar
  28. Mitophagy in metabolic syndrome
    Go to citation Crossref Google Scholar
  29. The positive association between white blood cell count and metabolic ...
    Go to citation Crossref Google Scholar
  30. Diagnostic features of polycystic ovary syndrome: A review
    Go to citation Crossref Google Scholar
  31. In Vitro α-Amylase and α-Glucosidase Inhibitory Effects, Antioxidant A...
    Go to citation Crossref Google Scholar
  32. Ghrelin regulates the proliferation and apoptosis of high glucose‐indu...
    Go to citation Crossref Google Scholar
  33. Enhancing intestinal barrier efficiency: A novel metabolic diseases th...
    Go to citation Crossref Google Scholar
  34. Revisiting the high-fat diet/low streptozotocin prediabetic rat model:...
    Go to citation Crossref Google Scholar
  35. Gut Microbiota Dysbiosis Ameliorates in LNK-Deficient Mouse Models wit...
    Go to citation Crossref Google Scholar
  36. The Mechanism of Kelulut Honey in Reversing Metabolic Changes in Rats ...
    Go to citation Crossref Google Scholar
  37. Acute Insulin Secretory Effects of a Classic Ketogenic Meal in Healthy...
    Go to citation Crossref Google Scholar
  38. Reducing Sedentary Time and Whole-Body Insulin Sensitivity in Metaboli...
    Go to citation Crossref Google Scholar
  39. Phenols from Potentilla anserina L. Improv...
    Go to citation Crossref Google Scholar
  40. Design, synthesis, spectroscopic characterization, single crystal X-ra...
    Go to citation Crossref Google Scholar
  41. Modeling the progression of Type 2 diabetes with underlying obesity
    Go to citation Crossref Google Scholar
  42. Insulin Metabolism in Polycystic Ovary Syndrome: Secretion, Signaling,...
    Go to citation Crossref Google Scholar
  43. Serum Homocysteine as a Biomarker in Diabetes
    Go to citation Crossref Google Scholar
  44. Big data and machine learning to tackle diabetes management
    Go to citation Crossref Google Scholar
  45. Synthetic Small Molecules Induce Insulin Secretion and Pancreatic Beta...
    Go to citation Crossref Google Scholar
  46. Upregulation of α-ENaC induces pancreatic β-cell dysfunction, ER stres...
    Go to citation Crossref Google Scholar
  47. Influence of maternal periuterine and periovarian fat on reproductive ...
    Go to citation Crossref Google Scholar
  48. Nutri-stress, mitochondrial dysfunction, and insulin resistance—role o...
    Go to citation Crossref Google Scholar
  49. Mapping research trends of insulin resistance in polycystic ovary synd...
    Go to citation Crossref Google Scholar
  50. Pathogenesis of (smoking-related) non-communicable diseases—Evidence f...
    Go to citation Crossref Google Scholar
  51. Progression from prediabetes to type 2 diabetes mellitus induced by ov...
    Go to citation Crossref Google Scholar
  52. Hepatic glycerol shunt and glycerol-3-phosphate phosphatase control li...
    Go to citation Crossref Google Scholar
  53. Metabolic and proteomic signatures of type 2 diabetes subtypes in an A...
    Go to citation Crossref Google Scholar
  54. Changes in hyperglycaemia-related testing for prediabetes and type 2 d...
    Go to citation Crossref Google Scholar
  55. Sexual dimorphism in the molecular mechanisms of insulin resistance du...
    Go to citation Crossref Google Scholar
  56. Testing a very low-carbohydrate adaption of the Diabetes Prevention Pr...
    Go to citation Crossref Google Scholar
  57. Profiling of insulin and resveratrol interaction using multi-spectrosc...
    Go to citation Crossref Google Scholar
  58. Prognostic Value of Histological and Immunohistochemical Data in Diabe...
    Go to citation Crossref Google Scholar
  59. Neue Ansätze zur Regeneration der insulinproduzierenden β-Zelle
    Go to citation Crossref Google Scholar
  60. The bidirectional association of nonalcoholic fatty liver disease with...
    Go to citation Crossref Google Scholar
  61. Association between vitamin D serum levels and insulin resistance asse...
    Go to citation Crossref Google Scholar
  62. Low and insufficient birth weights as important factors of development...
    Go to citation Crossref Google Scholar
  63. Perhexiline Therapy in Patients with Type 2 Diabetes: Incremental Insu...
    Go to citation Crossref Google Scholar
  64. Two models of insulin resistance development and the strategy to comba...
    Go to citation Crossref Google Scholar
  65. Sleep disturbances, sleep quality, and cardiovascular risk factors in ...
    Go to citation Crossref Google Scholar
  66. Targeting pancreatic β cells for diabetes treatment
    Go to citation Crossref Google Scholar
  67. Alisporivir Normalizes Mitochondrial Function of Primary Mouse Lung En...
    Go to citation Crossref Google Scholar
  68. Hibiscus sabdariffa in Diabetes Prevention and Treatment—Does It Work?...
    Go to citation Crossref Google Scholar
  69. A Review of the Potential Consequences of Pearl Millet (Pennisetum gla...
    Go to citation Crossref Google Scholar
  70. miRNAs: Regulators of immune system in diabetes
    Go to citation Crossref Google Scholar
  71. Triglyceride-Glucose Index for the Diagnosis of Metabolic Syndrome: A ...
    Go to citation Crossref Google Scholar
  72. Long-Term Diabetes Improvement After Duodenal Exclusion in Zucker Diab...
    Go to citation Crossref Google Scholar
  73. Glycerol-3-phosphate phosphatase operates a glycerol shunt in pancreat...
    Go to citation Crossref Google Scholar
  74. The Mighty Mitochondria Are Unifying Organelles and Metabolic Hubs in ...
    Go to citation Crossref Google Scholar
  75. Individuals with Metabolic Syndrome Show Altered Fecal Lipidomic Profi...
    Go to citation Crossref Google Scholar
  76. Clinical guidelines «Polycystic Ovary Syndrome»
    Go to citation Crossref Google Scholar
  77. Early Effects of Metabolic Syndrome on ATP-Sensitive Potassium Channel...
    Go to citation Crossref Google Scholar
  78. Identification of the Metabolomics Signature of Human Follicular Fluid...
    Go to citation Crossref Google Scholar
  79. Data-driven subgroups of type 2 diabetes, metabolic response, and rena...
    Go to citation Crossref Google Scholar
  80. The Role of Selenoprotein Tissue Homeostasis in MetS Programming: Ener...
    Go to citation Crossref Google Scholar
  81. Polycystic Ovary Syndrome: An Evolutionary Adaptation to Lifestyle and...
    Go to citation Crossref Google Scholar
  82. Metformin and Insulin Resistance: A Review of the Underlying Mechanism...
    Go to citation Crossref Google Scholar
  83. Medicinal Components in Edible Mushrooms on Diabetes Mellitus Treatmen...
    Go to citation Crossref Google Scholar
  84. Serum Homocysteine as a Biomarker in Diabetes
    Go to citation Crossref Google Scholar
  85. Histone deacetylase inhibition improves metabolism and mitochondrial d...
    Go to citation Crossref Google Scholar
  86. The quality of spermatozoa and testicular histology in insulin-injecte...
    Go to citation Crossref Google Scholar
  87. Metabolic Syndrome During Pregnancy: Prevalence and Determinants Among...
    Go to citation Crossref Google Scholar
  88. Association of Two Indices of Insulin Resistance Marker with Abnormal ...
    Go to citation Crossref Google Scholar
  89. Targeting the insulin granule for modulation of insulin exocytosis
    Go to citation Crossref Google Scholar
  90. Vertical sleeve gastrectomy triggers fast β-cell recovery upon overt d...
    Go to citation Crossref Google Scholar
  91. Maternal diet quality during pregnancy is associated with biomarkers o...
    Go to citation Crossref Google Scholar
  92. BACE2 suppression in mice aggravates the adverse metabolic consequence...
    Go to citation Crossref Google Scholar
  93. High-Fat, Western-Style Diet, Systemic Inflammation, and Gut Microbiot...
    Go to citation Crossref Google Scholar
  94. Evaluation of Grapefruit Juice in terms of Interleukin 18 Gene Express...
    Go to citation Crossref Google Scholar
  95. On the causal relationships between hyperinsulinaemia, insulin resista...
    Go to citation Crossref Google Scholar
  96. How does exposure to overnutrition in utero lead to childhood adiposit...
    Go to citation Crossref Google Scholar
  97. Prevalence and Predictors of Impaired Glucose Tolerance and Diabetes M...
    Go to citation Crossref Google Scholar
  98. Insulin Resistance, Secretion and Clearance –Taming the Three Effector...
    Go to citation Crossref Google Scholar
  99. The Human Islet: Mini-Organ With Mega-Impact
    Go to citation Crossref Google Scholar
  100. Oral ethinylestradiol–levonorgestrel therapy counteracts fructose-indu...
    Go to citation Crossref Google Scholar
  101. Insulin resistance in cardiovascular disease, uremia, and peritoneal d...
    Go to citation Crossref Google Scholar
  102. Functional Role of miR-155 in the Pathogenesis of Diabetes Mellitus an...
    Go to citation Crossref Google Scholar
  103. Diabetes in Youth
    Go to citation Crossref Google Scholar
  104. Hormone metabolic pattern in the preclinical stage of preeclampsia
    Go to citation Crossref Google Scholar
  105. Hyperinsulinemia and Its Pivotal Role in Aging, Obesity, Type 2 Diabet...
    Go to citation Crossref Google Scholar
  106. Low Carbohydrate Dietary Approaches for People With Type 2 Diabetes—A ...
    Go to citation Crossref Google Scholar
  107. Probiotics-rich emulsion improves insulin signalling in Palmitate/Olea...
    Go to citation Crossref Google Scholar
  108. Western Diet Decreases the Liver Mitochondrial Oxidative Flux of Succi...
    Go to citation Crossref Google Scholar
  109. Molecular Insulin Actions Are Sexually Dimorphic in Lipid Metabolism
    Go to citation Crossref Google Scholar
  110. The Ups and Downs of BACE1: Walking a Fine Line between Neurocognitive...
    Go to citation Crossref Google ScholarPub Med
  111. Genetic variants in the SLC16A11 gene are associated with increased BM...
    Go to citation Crossref Google Scholar
  112. Stage stratification of pregnant women at risk of preeclampsia
    Go to citation Crossref Google Scholar
  113. Elafibranor improves diet-induced nonalcoholic steatohepatitis associa...
    Go to citation Crossref Google Scholar
  114. Sphingolipids as a Culprit of Mitochondrial Dysfunction in Insulin Res...
    Go to citation Crossref Google Scholar
  115. Effect of Yogurt Consumption on Metabolic Syndrome Risk Factors: a Nar...
    Go to citation Crossref Google Scholar
  116. Early postnatal stress impairs insulin secretion in response to psycho...
    Go to citation Crossref Google Scholar
  117. Catestatin peptide of chromogranin A as a potential new target for sev...
    Go to citation Crossref Google Scholar
  118. G-protein–coupled receptors controlling pancreatic β-cell functional m...
    Go to citation Crossref Google Scholar
  119. Hepatokines and adipokines in NASH-related hepatocellular carcinoma
    Go to citation Crossref Google Scholar
  120. The Mechanism of Honey in Reversing Metabolic Syndrome
    Go to citation Crossref Google Scholar
  121. The Molecular Mechanisms of Hypoglycemic Properties and Safety Profile...
    Go to citation Crossref Google Scholar
  122. Maternal blood glucose level and offspring glucose–insulin homeostasis...
    Go to citation Crossref Google Scholar
  123. Evaluation of hyperglycemia
    Go to citation Crossref Google Scholar
  124. Undernutrition and suboptimal growth during the first year are associa...
    Go to citation Crossref Google Scholar
  125. The changes of Lp-PLA2 in patients with gestational diabetes and its c...
    Go to citation Crossref Google Scholar
  126. A nine-hub-gene signature of metabolic syndrome identified using machi...
    Go to citation Crossref Google Scholar
  127. Dysmetabolic mechanisms of preeclampsia development
    Go to citation Crossref Google Scholar
  128. Predicting the birth of a large fetus in obese women
    Go to citation Crossref Google Scholar
  129. NLRP3 inflammasome deficiency attenuates metabolic disturbances involv...
    Go to citation Crossref Google Scholar
  130. The importance of pathological insulin resistance and hyperinsulinemia...
    Go to citation Crossref Google Scholar
  131. Combinations of regenerative medicine and Lab-on-a-chip systems: New h...
    Go to citation Crossref Google Scholar
  132. New progress in the pharmacology of protocatechuic acid: A compound in...
    Go to citation Crossref Google Scholar
  133. lncRNA Eif4g2 improves palmitate-induced dysfunction of mouse β-cells ...
    Go to citation Crossref Google Scholar
  134. Early beta cell dysfunction vs insulin hypersecretion as the primary e...
    Go to citation Crossref Google Scholar
  135. Diabetes and Sarcopenic Obesity: Pathogenesis, Diagnosis, and Treatmen...
    Go to citation Crossref Google Scholar
  136. Exploring Therapeutic Targets to Reverse or Prevent the Transition fro...
    Go to citation Crossref Google Scholar
  137. Mechanism Underlying the Formation of a Cluster of Metabolic Syndrome
    Go to citation Crossref Google Scholar
  138. Nutrient-Induced Metabolic Stress, Adaptation, Detoxification, and Tox...
    Go to citation Crossref Google Scholar
  139. Mitochondrial Proton Leak Regulated by Cyclophilin D Elevates Insulin ...
    Go to citation Crossref Google Scholar
  140. Adaptation of Mitochondrial Substrate Flux in a Mouse Model of Nonalco...
    Go to citation Crossref Google Scholar
  141. Overview of the Comorbidity Between Medical Illnesses and Overweight/O...
    Go to citation Crossref Google Scholar
  142. Interplay between dietary sugars and fats and insulin resistance
    Go to citation Crossref Google Scholar
  143. The effects of stress on cardiovascular disease and Alzheimer's diseas...
    Go to citation Crossref Google Scholar
  144. <p>Development of Obesity: The Driver and the Passenger</p>
    Go to citation Crossref Google Scholar
  145. Effect of High β-glucan Barley on Postprandial Blood Glucose and Insul...
    Go to citation Crossref Google Scholar
  146. Mechanisms of hyperinsulinaemia in apparently healthy non-obese young ...
    Go to citation Crossref Google Scholar
  147. β-Cell Maturation and Identity in Health and Disease
    Go to citation Crossref Google Scholar
  148. Designer cytokine for the treatment of diabetes
    Go to citation Crossref Google Scholar
  149. β Cell dysfunction during progression of metabolic syndrome to type 2 ...
    Go to citation Crossref Google Scholar
  150. Physical Activity, Cardiorespiratory Fitness, and the Metabolic Syndro...
    Go to citation Crossref Google Scholar

Figures and tables

Figures & Media

Tables

View Options

View options

PDF/ePub

View PDF/ePub

Get access

Access options

If you have access to journal content via a personal subscription, university, library, employer or society, select from the options below:


Alternatively, view purchase options below:

Purchase 24 hour online access to view and download content.

Access journal content via a DeepDyve subscription or find out more about this option.