Sensitivoty P. Kinzig, Mary Sensiivity Honors, Sara L. Low-carbohydrate, ketogenic diets Sensitiviity are frequently implemented in efforts to reduce or maintain tolfrance weight, although the metabolic Insulin sensitivity and glucose tolerance of Insulij exposure to this Inshlin of diet Insulij controversial.
This study assessed the responsivity snesitivity peripheral and Insylin insulin, glucose tolerance, and meal-induced effects of consuming a KD Glutamine and muscle growth the rat. After 8 wk of consuming chow or KD, caloric intake after sensitiviity or central tlerance and insulin and glucose levels after a annd challenge were assessed.
In a separate group gljcose rats, tolerqnce and insulin responses to either a low- or high-carbohydrate test meal were measured. Finally, rats maintained on KD were switched back to toleranec chow diet, and insulin sensitivity and glucose tolerance were evaluated to determine whether the effects of KD were reversible.
Maintenance on KD resulted in decreased anv to peripheral insulin and impaired glucose tolerance. Furthermore, consumption of a tolernace meal in rats that gluose consumed KD induced gluxose greater insulin toleerance glucose levels for an Insulin sensitivity and glucose tolerance period of time, as compared with chow-fed controls.
Responsivity to sejsitivity insulin was toperance in KD rats and associated with sensiivity expression levels of tlucose receptor mRNA. Finally, returning to a chow diet rapidly reversed the effects of KD on insulin sensitivity and glucose tolerance. These data suggest that maintenance on KD negatively affects glucose homeostasis, an effect sehsitivity is rapidly tolersnce upon cessation of Insilin diet.
The ketogenic diet KD is a low-carbohydrate, high-fat blucose that is sensitovity for a variety of sensltivity effects. This sesitivity of diet is effective senxitivity suppressing seizure activity in Ineulin with refractory epilepsy 1 sennsitivity has Hydrostatic weighing for obesity assessment more commonly Insulni implemented as a dietary toleranc by which weight maintenance ane weight loss is the Diuretic effect of herbal teas outcome.
It has been demonstrated that restriction of dietary carbohydrates results in positive effects on cardiovascular Insylin. Consuming this zensitivity of diet nIsulin affects body adiposity and senzitivity features of metabolic syndrome in sensitivlty 2Insulin sensitivity and glucose tolerance, 3456.
Although studies evaluating the efficacy glicose metabolic effects of Tolerannce have sensitivkty in recent years, the effects of macronutrient-controlled diets remain controversial in tolearnce literature.
Insulin has ahd short-term Plant-based diet recipes long-term effects on energy intake and glucose homeostasis. In the short term, insulin release is cephalic; the brain initiates insulin secretion by directing Innsulin through the vagus glucosee to the pancreas as opposed to direct pancreatic stimulation glucoxe insulin-secreting cells.
Cephalic insulin is most readily observed at Angiogenesis and ocular diseases onset of a meal and consists of a short burst gluclse insulin that is preabsorptive with regard to the ingested food.
Together, the short- and long-term effects hlucose insulin allow for proper glucose homeostasis and assist in the regulation of toleraance weight. The ability of insulin to regulate blood Insylin levels Low carbohydrate diets be altered by Improving cognitive function macronutrient content of toleramce habitual diet.
Sensiivity consuming a high-fat diet, individuals develop increased plasma tplerance levels, which Weight management for athletes lead to insulin resistance and the inability to maintain glucose Gkucose.
However, a high-fat toleranc that Fat oxidation and endurance training also low in carbohydrates, namely Insuulin KD, is often used for weight loss and to control glucoxe of type 2 Green tea and respiratory health in the human population 89 Inslin is sensifivity unknown whether the effects of Insklin KD tolreance glucose homeostasis are the result of sensktivity loss associated with the use of a KD or a result of the severe restriction of dietary sennsitivity intake.
In rodents, maintenance sensktivity Green tea and respiratory health KD rapidly tilerance ketosis, which is maintained for the duration of exposure to the diet 11 KD have been observed tolfrance produce weight loss, through a loss of adipose Inzulin, and improvements in glucose homeostasis in mice previously fed a senwitivity, high-fat diet Srnsitivity, maintenance on a KD is Muscle preservation supplements with slower 14 or similar rates of weight gain 121516compared with chow-fed control rats.
Insulin sensitivity and glucose tolerance, high-protein diets have been demonstrated to improve glucose homeostasis independently of energy intake 17 Insuiln, an effect that is often linked to the reduced carbohydrate content of this senstiivity of Green tea and respiratory health 18 Insulin sensitivity and glucose tolerance glucosr series of experiments was performed to determine the ability of rats maintained on a KD to respond to peripherally administered insulin in terms of caloric intake and glucose homeostasis.
Specifically, responsivity to exogenous insulin was measured through analysis of caloric intake and blood glucose levels after ip insulin administration. Glucose tolerance was assessed in response to an ip glucose challenge in rats that chronically consumed a KD, and glucose and insulin responsivity to a low- or high-carbohydrate test meal after long-term exposure to the KD were measured.
Additionally, rats that had been maintained on a KD and returned to a carbohydrate-based diet were assessed to determine whether the effects of maintenance on a KD were reversible.
Finally, insulin in the central nervous system has a known role in energy homeostasis. Insulin receptors are concentrated in areas of the brain critically involved in the control of food intake, including the hypothalamic arcuate nucleus, and administration of insulin into the brain induces dose-dependent reductions in food intake and loss of body weight for review, see Ref.
We therefore assessed responsivity to intracerebroventricular icv insulin as well as expression levels of insulin receptor mRNA in the hypothalamus. For all studies, male Long Evans rats Harlan, Indianapolis, IN weighing — g, were individually housed in stainless steel hanging wire cages and maintained at a constant temperature 25 C on a h light, h dark cycle lights on at h.
Rats were 8 wk old upon arrival to the laboratory. After 1 wk of acclimation to the glkcose, during which ad libitum access to rodent chow was allowed Harlan Tekladrats were weight matched and divided into two groups. The sources of fat in KD were soybean oil and lard, such that the diet was composed of saturated and unsaturated long-chain fatty acids.
Caloric intake and body weights were measured and recorded daily. All experiments began immediately after the eighth week of diet maintenance. In accordance with previous reports 1220caloric intakes and body weights were not different between dietary groups.
All procedures were approved by the Purdue University Animal Care and Use Committee. Injections were counterbalanced, and each rat received an injection of physiological saline or insulin sensittivity Sigma-Aldrich, St. Louis, MO on one of two injection days, separated by 5 d.
For injections, food was removed 2 h before lights out. Ninety minutes later, each rat was injected ip with 1 ml of either saline or insulin 1. This dose was chosen based on previous research demonstrating that 1. At lights folerance, a preweighed amount of food was given to each rat, with food intake measured 1, 2, 4, and 24 h after injection.
Papers were placed beneath each cage to collect spillage, and intake calculations were adjusted accordingly. Food was removed 16 h before the start of IPGTT, and body weights after food deprivation were used to calculate glucose doses 1.
Blood was collected via tail nick rapidly to minimize stress to the animal 2223 before glucose injection. After glucose injection, blood samples were taken at 15, 30, 45, 60, and min. Glucose was determined by duplicate analysis with a Precision Xtra Glucose Monitoring System Abbott Laboratories, Abbott, IL.
The remainder of the blood sample was placed on ice. After the collection of all samples, each was centrifuged at rpm for 15 min at 4 C.
Plasma was collected for analysis of insulin concentration by an ultrasensitive rat insulin ELISA Crystal Chem Inc. Food was removed 16 h before the start of the IPITT, and post-food-deprivation body weights were used to calculate insulin doses. Blood was drawn via tail nick at the same intervals as for IPGTT, and glucose and insulin levels were determined as described above.
Access was allowed for 1 h. For testing, the same procedure was followed with the addition of blood collection. Blood was drawn via the tail vein immediately before gaining access to the nutritional supplement baseline and then 15 and 30 min and 1 and 2 h after the first lick.
Blood glucose was measured in duplicate at each time, and the remaining sample was placed on ice for the duration of the test. Samples were treated as described in experiment 2 and later analyzed for insulin levels.
The nutritional supplement was weighed after 1 h, at which time it was removed from the cage. Food and water were replaced after the 2-h blood draw. One week later, KD rats were given access to vanilla-flavored Ensure, to determine the effects of consuming a high-carbohydrate meal supplement after prolonged maintenance on a KD.
Rats received access to the vanilla-flavored Ensure and blood was collected as described above. Blood glucose was determined by ylucose analysis, and plasma insulin was measured by an ultrasensitive rat insulin ELISA.
Five days later, rats were given peripheral insulin to determine the effect of diet on responses to exogenous insulin, as in experiment 1. Each rat received saline or insulin on one of two injection days, as described in experiment 1 1. To determine whether switching from the KD to chow affected glucose tolerance, an additional group of rats was maintained on chow or KD for 8 wk, after which the KD was replaced with chow.
One week later, glucose tolerance was examined as described in experiment 2 above. Rats were maintained on chow or KD for 8 wk, and then each was stereotaxically implanted with a cannula into the lateral cerebral ventricle icvas previously described A gauge guide cannula 10 mm in length was inserted 1.
Cannula placement was verified by angiotensin II testing. Rats were icv injected with 5 nmol angiotensin II, after which water intake was measured. All drank at least 5 ml more than they drank after icv saline injection in 30 min and therefore deemed to have correct cannula placement. One week after recovery of presurgical body weight, rats underwent a series of icv injections to determine the effectiveness of insulin to reduce caloric intake in rats maintained on chow or KD.
A within-subjects design was used such that rats received icv injections of physiological saline or insulin 6 and 9 mU in 2 μl saline. Doses were chosen based on studies in which 8 mU was reliably shown to reduce food intake 2526and 6 and 9 mU were tested to determine whether KD rats had increased sensitivity to the anorectic effects of centrally administered insulin.
Each rat received saline and both doses of insulin, with not less than 5 d between injections, in a counterbalanced sequence. On test days, food was removed 1 h before injection. Insuiln were injected 30 min sensitiviyy the onset of the dark cycle, at which time food was replaced in the cage.
Intake was measured 1, 2, 4, and 24 h later. On the day of killing, food was removed for 6 h, and rats were killed 2 h before the onset of the dark cycle. Rats were rapidly decapitated under ether inhalation anesthesia, and brains were removed and placed in RNAlater Ambion, Austin, TX for subsequent analysis of insulin receptor expression in the hypothalamus by quantitative RT-PCR Q-PCR.
For Q-PCR, the whole hypothalamus of each rat was dissected from the brain and homogenized in 1 ml Trizol reagent Invitrogen, Carlsbad, CA. After centrifugation of this mixture, RNA was recovered from the aqueous phase by isopropanol precipitation.
Each primer set was optimized tolerancf that the correlation coefficient was 0. The integrity of the cDNA was confirmed by conventional RT-PCR amplification of L32a housekeeping gene.
A control reaction for each RNA sample was also performed with no reverse transcriptase enzyme added. Q-PCR was performed in duplicate using an iCycler and the iQ SYBR Green Supermix Bio-Rad, Hercules, CA with two-step amplification 95 C for 10 sec and 60 C for 45 sec for 40 cycles.
L32 was amplified from each sample for use as an endogenous control. The effects of ip and icv insulin on caloric intake were evaluated by repeated-measures ANOVA and a Bonferroni test was used for post hoc analysis.
All glucose and insulin data were analyzed by a two-way ANOVA with repeated-measures and Bonferroni tests for post hoc analyses.
Area under the curve was analyzed using a t test. All data are expressed as mean ± sem.
: Insulin sensitivity and glucose tolerance| What is Glucose Intolerance? - Nutrisense Journal | Food was removed 16 h before the start of the IPITT, and post-food-deprivation body weights were used to calculate insulin doses. Eventually, the pancreas no longer produces enough insulin to overcome the cells' resistance. You do not have to have a diagnosis of diabetes to be glucose intolerant. Further, the differences were tested for covariate adjustment, including gender, body mass index, systolic blood pressure, fasting, and 2-h glucose levels. Additionally, we measured the expression levels of mRNA for the insulin receptor in the hypothalamus. large VLDL in Fig. |
| The difference between insulin resistance and prediabetes | Nebraska Medicine Omaha, NE | The underlying mechanism for Green tea and respiratory health species differences tolrance currently sfnsitivity. Some people with insulin resistance may also develop a skin condition known tolerancf acanthosis nigricans. Insuljn Section:. Nutritional weight management Insulin sensitivity and glucose tolerance Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland. The studies summarized above show that there is a dynamic relationship between insulin resistance and a compensatory increase in β-cell mass and β-cell glucose metabolism. Our results here underline the possibility that fasting concentrations may also reflect the insufficient suppression of branched-chain amino acids and triglycerides in the postprandial state in the insulin-resistant individuals. |
| Measuring Insulin Resistance | College of Medicine | MUSC | To understand insulin resistance, often sensitivty to as Nuttiness at your Doorstep, let's first Green tea and respiratory health about what insulin does. The Effects of Insulin on otlerance Body. Gkucose CAS Google Scholar Emerging Risk Factors Collaboration, Sarwar N, Gao P, Seshasai SRK, Gobin R, Kaptoge S, et al. QW, JK, VPM, and MAK contributed to the analysis plan and interpretations. Article CAS Google Scholar Do R, Willer CJ, Schmidt EM, Sengupta S, Gao C, Peloso GM, et al. |
| Insulin Resistance: What It Is, Symptoms, and More | The ability of the pancreas to increase insulin production means that insulin resistance alone won't have any symptoms at first. Over time, though, insulin resistance tends to get worse, and the pancreatic beta cells that make insulin can wear out. Eventually, the pancreas no longer produces enough insulin to overcome the cells' resistance. The result is higher blood glucose levels, and ultimately prediabetes or type 2 diabetes. Insulin has other roles in the body besides regulating blood glucose levels, and the effects of insulin resistance are thought to go beyond diabetes. For example, some research has shown that insulin resistance, independent of diabetes, is associated with heart disease. Scientists are beginning to get a better understanding of how insulin resistance develops. For starters, several genes have been identified that make a person more or less likely to develop the condition. It's also known that older people are more prone to insulin resistance. Lifestyle can play a role, too. Being sedentary, overweight or obese increases the risk for insulin resistance. It's not clear, but some researchers theorize that extra fat tissue may cause inflammation, physiological stress or other changes in the cells that contribute to insulin resistance. There may even be some undiscovered factor produced by fat tissue, perhaps a hormone, that signals the body to become insulin resistant. Doctors don't usually test for insulin resistance as a part of standard diabetes care. In clinical research, however, scientists may look specifically at measures of insulin resistance, often to study potential treatments for insulin resistance or type 2 diabetes. They typically administer a large amount of insulin to a subject while at the same time delivering glucose to the blood to keep levels from dipping too low. The less glucose needed to maintain normal blood glucose levels, the greater the insulin resistance. Insulin resistance comes in degrees. The more insulin resistant a person with type 2 is, the harder it will be to manage their diabetes because more medication is needed to get enough insulin in the body to achieve target blood glucose levels. Insulin resistance isn't a cause of type 1 diabetes, but people with type 1 who are insulin resistant will need higher insulin doses to keep their blood glucose under control than those who are more sensitive to insulin. As with type 2, people with type 1 may be genetically predisposed to become insulin resistant, or they may develop resistance due to being overweight. Some research indicates that insulin resistance is a factor in cardiovascular disease and other complications in people with type 1. While fighting an invisible foe can feel frustrating and discouraging, know that you are not alone. We conclude that IFG is characterized by basal IR and other features of the metabolic syndrome, whereas subjects with IGT have impaired insulin secretion in relation to glucose concentrations. An absolute decompensation of beta-cell function characterizes the transition from IGT to mild diabetes. Abstract Recently, a new stage in glucose tolerance, impaired fasting glucose IFG fasting plasma glucose level of 6. Publication types Research Support, Non-U. Substances Blood Glucose Insulin Glucose. |
| Insulin Resistance and Diabetes | ADA | Insulin resistance comes in degrees. The more insulin resistant a person with type 2 is, the harder it will be to manage their diabetes because more medication is needed to get enough insulin in the body to achieve target blood glucose levels. Insulin resistance isn't a cause of type 1 diabetes, but people with type 1 who are insulin resistant will need higher insulin doses to keep their blood glucose under control than those who are more sensitive to insulin. As with type 2, people with type 1 may be genetically predisposed to become insulin resistant, or they may develop resistance due to being overweight. Some research indicates that insulin resistance is a factor in cardiovascular disease and other complications in people with type 1. While fighting an invisible foe can feel frustrating and discouraging, know that you are not alone. There are effective tactics to combat insulin resistance. Losing weight, exercising more or taking an insulin-sensitizing medication can help you get back to good blood glucose control and better health. Breadcrumb Home You Can Manage and Thrive with Diabetes Understanding Insulin Resistance. What Is Insulin Resistance? What Causes Insulin Resistance? What Does It Mean for Your Health? What Can You Do About It? Getting active is probably the best way to combat insulin resistance. Exercise can dramatically reduce insulin resistance in both the short and long terms. In addition to making the body more sensitive to insulin and building muscle that can absorb blood glucose, physical activity opens up an alternate gateway for glucose to enter muscle cells without insulin acting as an intermediary, reducing the cells' dependence on insulin for energy. While this doesn't reduce insulin resistance itself, it can help people who are insulin resistant improve their blood glucose control. Weight loss can also cut down on insulin resistance. No single diet has been proved to be the most effective. Some evidence suggests, though, that eating foods that are low in fat and high in carbohydrates can worsen insulin resistance. Research has also shown that people who undergo weight-loss surgery are likely to become significantly more sensitive to insulin. No medications are specifically approved to treat insulin resistance. Yet diabetes medications like metformin and thiazolidinediones, or TZDs, are insulin sensitizers that lower blood glucose, at least in part, by reducing insulin resistance. Recently, much attention has focused on pharmacological manipulation of cortisol metabolism as a therapeutic strategy. Selective 11β-HSD1 inhibitors administered to rodents and primates decrease local glucocorticoid generation, improve glucose tolerance, increase insulin sensitivity, and may promote weight loss 14 — In contrast to the action of 11β-HSD1, the A-ring reductases 5α-reductase type 1 [5αR1] and type 2 [5αR2] and 5β-reductase inactivate cortisol, decreasing local glucocorticoid availability to bind and activate the glucocorticoid receptor GR. Studies published to date have focused principally on the role of cortisol metabolism in the pathogenesis of obesity rather than that of insulin resistance. We have performed a detailed clinical study in a large cohort of obese patients exploring the concept that cortisol metabolism is an important regulator of insulin sensitivity and that this may be independent of fat mass. The study was approved by the South Birmingham Local Research Ethics Committee, and all subjects gave informed, written consent. A total of obese volunteers 35 male, 66 female, mean age ± SD 48 ± 7 years, mean BMI Patients had no significant past medical history, and none had received glucocorticoid therapy oral, topical, or inhaled within the last 12 months. All patients had normal blood counts and renal function. Subjects were investigated in the fasting state. Blood samples were drawn at 9 a. for measurement of total cholesterol, triglycerides, cortisol, cortisone, glucose, insulin, and A1C. Measurements of BMI, waist circumference measured supine, at the level of the umbilicus , hip circumference at the level of the greater trochanter , and blood pressure average of three readings, measured supine after 10 min rest using Dynamap [Critikon, Tampa, FL] were also taken. Patients underwent a standard g oral glucose tolerance test, with samples taken at min intervals for min for measurement of insulin and glucose. In addition, all patients performed a h urine collection for corticosteroid metabolite analysis Body composition analysis was performed using dual-energy X-ray absorptiometry DEXA with a total body scanner QDR 45OO; Hologic, Bedford, MA. Regional fat mass trunk and leg was analyzed as previously described Blood counts, urea, creatinine and electrolytes, cholesterol, triglycerides, liver chemistry, glucose, and A1C were measured using standard laboratory methods Roche Modular system; Roche, Lewes, U. Cortisol was measured using a coat-a-count radioimmunoassay Diagnostic Products, Los Angeles, CA as per the manufacturer's guidelines. Cortisone was assayed after extraction from serum followed by radioimmunoassay of the extract with I-cortisone and Sac-Cel IDS, Tyne and Weir, U. second antibody separation Calculated measures of pancreatic β-cell function and insulin resistance were made using the homeostasis model assessment HOMA 2 model The sum of total cortisol metabolites tetrahydrocortisol [THF], tetrahydrocortisone [THE], 5α-THF, α-cortolone, cortisone [E], cortisol [F], β-cortolone, β-cortol, and α-cortol provides a reflection of cortisol secretion rate. The ratios of cortols to cortolones and of 11β-hydroxy-etiocholanolone and 11β-hydroxy-androsterone combined to 11oxo-etiocholanolone also reflect 11β-HSD1 activity The activities of 5α- and 5β-reductases can be inferred from measuring the ratio of 5α THF to THF and androsterone to etiocholanolone. Following subcutaneous adipose tissue biopsy, total RNA was extracted using a single-step extraction method Magmax 96; Applied Biosystems, Foster City, CA as per the manufacturer's guidelines. RNA integrity and quantity were assessed using a Nanodrop spectrophotometer Wilmington, DE. One microgram of total RNA was initially denatured by heating to 70°C for 5 min. Thirty units of avian myeloblastososis virus, ng of random primers, 20 units of ribonuclease inhibitor, and 40 nmol of deoxy—nucleoside triphosphates with 5× reaction buffer were added to the RNA, and the reverse transcriptase reaction was carried out at 37°C for 1 h. The reaction was terminated by heating the cDNA to 95°C for 5 min. mRNA levels of genes of interest were determined using an ABI sequence detection system Perkin-Elmer and Applied Biosystems, Warrington, U. Reactions were performed in μl volumes on well plates in reaction buffer containing 2× TaqMan Universal PCR Master mix Applied Biosystems, Foster City, CA. Probes and primers for all genes were supplied by assay on demand Applied Biosystems. All reactions were normalized against the housekeeping gene 18S rRNA, provided as a preoptimized control probe. Data are presented as means ± SE unless otherwise stated. Area under the curve AUC analysis was performed using the trapezoidal method. For comparison of single variables, t tests have been used or nonparametric equivalents where data were not normally distributed. Regression analyses were performed using Pearson correlations; where more than one variable was considered, multiple linear regression analysis was used. All analysis was performed using SigmaStat 3. A total of 66 women and 35 men volunteers were recruited into the study; 48 women Two women 3. IGT with normal fasting glucose concentrations was observed in 15 women Type 2 diabetes was diagnosed in two women 3. Taking into account the sexual dimorphism described in body composition and glucocorticoid metabolite production rates, subsequent analysis was performed separately in men and women. IGT was associated with increased waist circumference ± 1. A1C was increased in both men and women with IGT, although this only reached statistical significance in men men 5. Surprisingly, measures of insulin resistance HOMA-R, fasting and 2-h insulin concentrations were not different between groups Table 1. Furthermore, body composition analysis by DEXA failed to show differences in fat-free mass or total or regional fat mass between those patients with normal glucose tolerance or IGT Table 1. Although men and women were not different in terms of insulin resistance as measured by HOMA, fasting insulin, 2-h insulin or insulin AUC across the g OGTT, percent trunk fat and absolute total and trunk fat mass were higher in women with correspondingly lower fat-free masses Table 1. When analyzed according to glucose tolerance, total glucocorticoid production rates were higher in women with IGT compared with women with normal glucose tolerance 10, ± 1, vs. Furthermore, there were no differences in absolute production rates for individual metabolites or activities of metabolizing enzymes in particular 11β-HSD1 or 5αR when comparing normal and IGT subjects Table 2. Successful isolation of total RNA and generation of cDNA from subcutaneous adipose tissue biopsies was achieved in 90 volunteers. All samples expressed 11β-HSD1, H6PDH, GR, and 5αR1. In contrast, 5αR2 was only expressed in 5 of 90 samples and only at very low levels data not shown. Whereas 11β-HSD1, GR, and 5αR1 mRNA expression levels were similar in men and women, H6PDH expression was higher in biopsies from male volunteers 2. In women only, adipose tissue 11β-HSD1 expression was higher in those with IGT than in those with normal glucose tolerance 0. H6PDH expression was lower in female volunteers with IGT 0. In contrast to our findings in women, expression of 11β-HSD1, H6PDH, GR, and 5αR1 in adipose tissue biopsies from men did not differ between those with and those without IGT and did not relate to glucose levels across an OGTT Fig. Univariate regression analysis revealed positive relationships between 5αR activity as measured by both the urinary androsterone—to—etiocholanolone and 5αTHF-to-THF ratios and markers of insulin resistance. In women, significant correlations were observed with fasting insulin, 2-h insulin levels after 75 g oral glucose, AUC insulin across the OGTT, and HOMA-R Table 3 and Fig. In men, a similar pattern was observed Table 3 ; Fig. Activity of 5αR increased with increasing total and regional fat and fat-free mass in men but not in women Table 3. While these relationships remained significant, they were weaker than those observed with markers of insulin resistance. There was no relationship in either sex with fat distribution as measured by waist circumference, WHR, or the trunk fat—to—limb fat ratio via DEXA. Total glucocorticoid secretion rate increased with total and regional fat and fat-free mass in women but not in men and was weakly associated with 2-h insulin concentration after 75 g oral glucose Table 4. Activity is reflected in the ratio of urinary free cortisol to cortisone. In this unselected cohort of obese patients, we have identified the prevalence of IGT to be This was associated with central fat distribution but not absolute fat mass in women and unrelated to fat mass or distribution in men. In this cohort, subcutaneous adipose tissue 11β-HSD1 mRNA expression was higher in women with IGT and correlated with glucose secretion across the OGTT but was unrelated to fat mass, consistent with our previous observations Previous studies have examined 11β-HSD1 mRNA expression and activity in adipose tissue in the context of fat mass with variable results. Within the subcutaneous depot, most studies, although not all, have suggested increased expression with indexes of obesity 25 — 29 , but relative expression within the intra-abdominal depot remains controversial. Importantly, the expression of 11β-HSD1 in adipose tissue and its relationship with insulin resistance and glucose tolerance has not been examined before. While expression studies were only performed in subcutaneous adipose tissue, enhanced cortisol generation through increased 11β-HSD1 mRNA expression may contribute to glucose intolerance through increased lipolysis 30 , 31 and generation of free fatty acids, which impair peripheral glucose uptake However, due to the small volumes of tissue obtained, activity studies were not performed and it is possible that decreased H6PDH expression that we also observed in the IGT group may decrease 11β-HSD1 oxo-reductase activity by limiting cofactor supply. Sexually dimorphic activity and expression of 11β-HSD1 has been described in some studies 33 but not all Studies examining sex-specific regulation of expression within adipose tissue are lacking. In nonadipose tissue, estradiol has been shown to regulate expression levels, and it is possible that this may contribute to our observations; however, the published data are often contradictory with studies showing both increased and decreased expression 35 — With the exception of dehydroepiandrosterone 39 , there is little evidence to support a role for regulation by androgens 35 , Sexually dimorphic expression of H6PDH has not been described previously, and the observed increase in expression in men will need to be endorsed with dedicated activity studies to see if changes in H6PDH expression translate into alterations in glucocorticoid availability. However, it is possible that this could contribute to differences in fat distribution between men and women, with the consequent increase in cardiovascular risk In our study, in both sexes, 5αR activity as measured by urinary glucocorticoid metabolite ratios increased with indexes of insulin resistance, an observation that was independent of fat mass. The role of 5αR in the control of body composition and insulin sensitivity has not been explored in detail in the published literature. The global measures of activity that we have used in this study do not allow us to distinguish between 5αR1 and 5αR2, and whereas patients with 5αR2 mutations have clear evidence of abnormal hepatic cortisol metabolism 41 , the contribution of 5αR1 is yet to be clarified. Sexual dimorphism of 5αR activity has been described with increased activity in male subjects 10 , In our study, absolute levels of 5α- and 5β-reduced metabolites were higher in men as was total glucocorticoid production rate , but the relative balance of 5αR and 5βR activity was not different. Furthermore, 5αR1 mRNA expression in subcutaneous adipose tissue was similar in men and women. Studies in small cohorts of patients have shown enhanced 5αR activity with obesity 42 and type 2 diabetes 43 and regulation of 5αR and 5βR activity by dietary macronutrient composition; high-fat, low-carbohydrate and moderate-fat, moderate-carbohydrate diets decrease 5αR and 5βR activity in the context of weight loss Thiazolidinedione treatment of obese Zücker rats decreases 5αR1 expression in the liver 45 , but similar experiments in humans have not been performed. However, we have recently shown that following weight loss with consequent insulin sensitization, 5αR activity decreased Moreover, within a cohort of patients with PCOS, 5αR activity correlates with insulin resistance Our findings are consistent with these data and extend this observation to healthy obese women and men, as well as demonstrate that the relationship in both sexes is independent of fat mass. These processes act together decreased generation of cortisol through a reduction in 11β-HSD1 and increased inactivation of cortisol through enhanced 5αR activity to decrease local glucocorticoid availability and decrease GR activation specifically within the liver, with the aim of maintenance of hepatic insulin sensitivity. A further impact of these changes will be to drive the hypothalamo-pituitary-adrenal axis in order to maintain circulating cortisol levels. While we believe that the changes that we have observed largely reflect hepatic glucocorticoid metabolism, a direct effect upon insulin secretion cannot be excluded. However, this remains highly speculative, bearing in mind that evidence of A-ring reductase expression in human pancreatic islets is lacking. Pharmacological manipulation of glucocorticoid availability through prereceptor metabolism adds credence to our observations. Selective 11β-HSD1 inhibitors that decrease local glucocorticoid availability remain an exciting therapeutic prospect. Significant improvements in insulin sensitivity, glucose tolerance, and lipid profiles following short-term administration in rodents and primates have been observed. Human clinical studies are still eagerly awaited. Conversely, Finasteride 5αR2 inhibitor and Dutasteride combined 5αR1 and 5αR2 inhibitor are widely used in the treatment of prostatic hypertrophy 49 based upon their action upon androgen metabolism. However, by decreasing glucocorticoid inactivation, they may have a detrimental impact upon insulin sensitivity, but the studies to address this question have not been performed. In conclusion, this study adds to the growing body of evidence that supports a role for 5αR in the control of insulin sensitivity in simple obesity. Finally, prospective studies examining the changes in activity and expression of these enzymes over time may begin to shed light on their potential role in the development of IGT and type 2 diabetes. In women only, IGT is associated with increased adipose tissue 11β-HSD1 but decreased H6PDH mRNA expression A without alteration in fat mass; 11β-HSD1 mRNA levels correlate with glucose AUC across an OGTT B. However, in men with IGT, adipose 11β-HSD1, H6PDH, GR, and 5αR1 mRNA expression is not dysregulated C and D. Data are means ± SD. org on 15 June Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. The costs of publication of this article were defrayed in part by the payment of page charges. Section solely to indicate this fact. This study was funded by the Wellcome Trust program grant to P. We thank all the nursing staff on the Wellcome Trust Clinical Research facility, Queen Elizabeth Hospital, Birmingham where this study took place. Sign In or Create an Account. Search Dropdown Menu. header search search input Search input auto suggest. filter your search All Content All Journals Diabetes. Advanced Search. User Tools Dropdown. Sign In. Skip Nav Destination Close navigation menu Article navigation. Volume 57, Issue Previous Article Next Article. RESEARCH DESIGN AND METHODS. Article Information. Article Navigation. Obesity Studies October 01 Impaired Glucose Tolerance and Insulin Resistance Are Associated With Increased Adipose 11β-Hydroxysteroid Dehydrogenase Type 1 Expression and Elevated Hepatic 5α-Reductase Activity Jeremy W. Tomlinson ; Jeremy W. This Site. Google Scholar. Joanne Finney ; Joanne Finney. Christopher Gay ; Christopher Gay. |
Insulin sensitivity and glucose tolerance -
Insufficient insulin action results in increased fasting glucose and eventually leads to overt type 2 diabetes [ 4 ]. Insulin resistance IR is also linked to the development of cardiometabolic complications, the risk arising already prior to the onset of type 2 diabetes [ 5 , 6 ].
Studies in the fasting state have identified a cluster of biomarkers robustly associated with IR and predisposing to increased risk for CVD [ 3 , 5 , 6 ]. In the modern society, however, people spend most of their waking hours at a postprandial state, yet we are not aware of epidemiological studies on non-fasting metabolism in representative cohorts.
An OGTT induces a transition from fasting to feeding, and subsequent changes in various metabolic nutrients occur as the body makes adjustments to achieve glucose homeostasis [ 7 ].
It is thus feasible to expect that individuals with impaired insulin action are likely to display a widespread systemic abnormality beyond glucose. Although the dynamics of insulin and glucose during an OGTT in both healthy and insulin-resistant individuals are well studied [ 8 , 9 ], much less is known on other, particularly emerging cardiometabolic biomarkers, for example, lipoprotein lipid profiles, amino acids, ketone bodies, and inflammatory markers [ 10 , 11 ].
Metabolic profiling, simultaneously measuring multiple metabolic measures, has been frequently used in studying metabolic dysregulations in the fasting state.
Previous studies have revealed that higher fasting ketone bodies, branched-chain amino acids, and aromatic amino acids are predictive for future type 2 diabetes [ 10 , 12 ].
Similarly, higher concentration of very-low-density lipoprotein VLDL particles and increased triglycerides are associated with higher risk of cardiovascular diseases [ 13 ]. In particular, recent genetic studies have suggested that disturbed branched-chain amino acid metabolism and increased triglycerides are on the causal path of cardiometabolic diseases [ 14 , 15 ].
Metabolic profiling has also been applied to assess the metabolic changes during OGTT in small studies. For example, amino acids, ketone bodies, and triglycerides are decreased during an OGTT and some of these changes seem to be blunted in obese and insulin-resistant individuals [ 7 , 16 , 17 , 18 , 19 , 20 , 21 ].
However, all these studies have been limited in their sample size up to a few hundred individuals and often spanned only two time points pre- and post-OGTT. In this study, we performed an OGTT across 4 time points and quantified 78 metabolic measures for a total of individuals over 21, serum samples from 2 independent population-based cohorts.
Our aims were 1 to comprehensively characterise systemic metabolic responses to oral glucose in large scale and 2 to investigate how insulin resistance is associated with postprandial metabolic dysregulation across multiple clinical categories of glucose intolerance. To our knowledge, this is the first population-based large-scale metabolomics time-series study of an OGTT, providing new insights into the metabolic consequences of insulin resistance in non-fasting conditions.
The Northern Finland Birth Cohort NFBC66 was initiated to study factors affecting preterm birth and subsequent morbidity in the two northernmost provinces in Finland [ 22 ]. Data collection conducted in at their age of 46, including clinical examination and serum sampling, was available for individuals.
The Oulu cohort studies ageing populations in Oulu, Finland. It was started in and was originally comprised of individuals born in In the follow-up study conducted in , data collection including clinical examination and serum sampling was available for participants.
Subjects underwent a 2-h, g OGTT after an overnight fasting. Plasma glucose were analysed by an enzymatic dehydrogenase method Advia , Siemens Healthcare Diagnostics, Tarrytown, NY, USA and serum insulin by a chemiluminometric immunoassay Advia Centaur XP, Siemens Healthcare Diagnostics, Tarrytown, NY, USA.
Insulin resistance was estimated by fasting insulin, homeostasis model assessment of insulin resistance HOMA-IR , and insulin sensitivity index-Matsuda ISI-Matsuda.
First-phase insulin secretion, an index of beta-cell function, was measured by insulinogenic index. The formulas for these models are shown in the legend for Table 1.
Impaired fasting glucose IFG, fasting glucose between 5. IS-NGT was defined as the bottom quartile of fasting insulin within NGT, and IR-NGT was defined as the top quartile. The dots denote mean absolute concentrations.
Interquartile ranges are listed in Table 1. The human serum metabolome is dominated by hydrophobic lipid-like molecules, including diglycerides, triglycerides, phospholipids, fatty acids, steroids, and steroid derivatives [ 23 ].
These lipids are packed in various lipoprotein particles, e. VLDL, intermediate-density lipoprotein IDL , low-density lipoprotein LDL , and high-density lipoprotein HDL. Other metabolites found in high abundance in serum include amino acids, glucose, lactate, and several waste or catabolic by-products, such as urea and creatinine [ 23 ].
Here, a nuclear magnetic resonance NMR spectroscopy metabolomics platform was used to measure all the detectable lipids and metabolites in a non-selective way.
The platform applies a single experimental setup, which allows for simultaneous quantification of standard clinical lipids, 14 lipoprotein subclasses, and individual lipids triglycerides, phospholipids, free and esterified cholesterol transported by these particles, multiple fatty acids, glucose and various glycolysis precursors, ketone bodies, and amino acids in absolute concentration units [ 24 , 25 , 26 ].
As the total lipids and individual lipids within the same lipoprotein subclass are highly correlated [ 27 ], we chose a priori to analyse the total lipids in the 14 subclasses and limit specific lipids for the 4 major fractions VLDL, IDL, LDL, and HDL. These together with all the fatty acids and non-lipid measures provided by this platform, in total 77 measures, were used in the present study.
A similar metabolic panel has been widely applied in previous studies [ 3 , 28 , 29 ]. In total, 78 metabolic measures were used in the analyses. Of those, 77 were measured by NMR metabolomics and glucose by a clinical assay.
Insulin was treated as an exposure in this study. All analyses were undertaken in the R programming environment version 3. Primary analyses were conducted using NFBC66, and key results were replicated in Oulu To study the physiological response to an OGTT, metabolic trajectories for NGT individuals were reported.
In the formula, metabolic concentrations are in their original units, e. The significance of a change was evaluated via paired t test by comparing the metabolite concentration at post-load time points against the fasting baseline.
The analyses were repeated for men and women separately. In total, 60 out of 78 measures showed significant interaction of time points and groups, suggesting the metabolic trajectories would be different between the groups for these measures Additional file 2 : Table S2.
t tests were further used to compare the metabolic trajectories between IR-NGT and IS-NGT across the 78 measures. For those metabolic measures that showed significant differences between IR-NGT and IS-NGT, we further assessed their differences between IR-NGT and those with IGT or NDM.
In addition, sensitivity analyses were conducted to assess the effect of potential covariates for those measures that showed significant differences between IR-NGT and IS-NGT. Linear regression models were used to quantify the metabolic differences between the groups, using 2-h change in metabolite concentration as the response variable and group category as the independent variable.
Metabolite concentrations at baseline and 2 h were log-transformed, and the changes between the baseline and 2 h were scaled to baseline SD. Two population cohorts were used to study the metabolic changes during an OGTT.
Although NGT individuals are generally considered healthy, the IR-NGT subgroup had over 3 times higher fasting insulin than the IS-NGT. The IR-NGT individuals were also more likely to be male and had higher BMI, blood pressure, and fasting triglycerides and lower HDL cholesterol Table 1.
Similar characteristics were observed for IFG, IGT, and NDM, and their fasting insulin levels were comparable to IR-NGT, ranging from 2. Selected responses to an OGTT for the NGT individuals are summarised in Fig. Similarly, almost all amino acids were decreased during the OGTT, except for alanine Fig.
Changes in lipids and fatty acids were generally smaller in comparison to the aforementioned non-lipid measures Fig.
large VLDL in Fig. very large HDL in Fig. VLDL-TG and HDL-TG in Fig. Inconsistent and small changes were seen in the corresponding cholesterol concentrations see Additional file 1 : Figure S1A for details. Selected metabolic changes in response to an oral glucose tolerance test in individuals with normal glucose tolerance.
Percent change is defined as the absolute change in relative to baseline. a Glycolysis-related and ketone bodies. b Amino acids. c Lipoprotein lipids and others. Metabolic trajectories of IR-NGT were compared to those of IS-NGT Fig.
The analyses were restricted to individuals with normal glucose tolerance to rule out any secondary effects from hyperglycaemia. Full results for all 78 measures are available in Additional file 1 : Figure S2 and Additional file 2 : Table S4.
Pronounced differences were observed in multiple metabolic pathways including glycolysis-related metabolites, branched-chain amino acids, ketone bodies, and triglyceride-related measures Fig.
Also, they displayed smaller decrease in branched-chain amino acids and ketone bodies as well as triglyceride-related measures. The results were consistent when stratified by sex Additional file 1 : Figure S3. Metabolic trajectoires compared between insulin-resistant and insulin-sensitive individuals in the normal glucose tolerance group.
The asterisk denotes that there are signficiant differences between IS-NGT and IR-NGT at corresponding time point. a Insulin and glucose. b Glycolysis-related. c Branched-chain amino acids.
d Ketone bodies. e Triglycerides-related. Figure 4 Additional file 2 : Table S5 presents the comparison of the metabolic trajectories in individuals with 2-h impaired glucose tolerance IGT or NDM and those of IR-NGT.
Although large differences in glucose responses were observed by definition, these two groups showed marginal differences in metabolic responses in glycolysis products, branched-chain amino acids, ketone bodies, and triglyceride-related measures Fig.
In addition, the IFG individuals who had normal 2-h glucose response but high fasting glucose 5. The metabolic trajectories in percent change and absolute concentrations across all five individual groups IS-NGT, IR-NGT, IFG, IGT, and NDM are shown in Additional file 1 : Figures S6 and S7.
Results corresponding to those shown in Figs. Metabolic trajectories compared between insulin-resistant individuals in the normal glucose tolerance group blue and those with 2-h impaired glucose tolerance red. The asterisk denotes that there are signficiant differences between IR-NGT and those with IGT or NDM at corresponding time point.
Interestingly, these two groups also showed similar differences in the 2-h metabolite responses when compared to the IS-NGT group Fig. This was consistently observed in the two independent cohorts. By contrast, the associations were substantially attenuated to almost null after adjusting for fasting insulin.
Similar results were observed when IFG, IGT, and NDM were individually compared to IS-NGT with the adjustments Additional file 1 : Figure S9.
Summary and replication. a Estimated insulin resistance in IS-NGT grey , IR-NGT blue , and pooled of IFG, IGT, and NDM red in NFBC b Two-hour metabolic responses associated with IR with or without glucose abnormality in NFBC66 purple and replicated in Oulu45 red.
Groups were compared by linear regression models with the 2-h concentration change as the response variable. Baseline and 2-h metabolite concentrations were log-transformed, and the changes between 2-h and baseline metabolite concentrations were scaled to baseline SD.
Group comparison adjusted for baseline factors in the NFBC66 cohort. Insulin was log-transformed. Lastly, we observed distinctive patterns in fasting metabolic concentrations and the 2-h metabolite responses Additional file 1 : Figures S7 and S Branched-chain amino acids and triglycerides in IR individuals were higher at baseline and exhibited less decrease at 2 h, compared to the IS-NGT group.
Glycolysis-related measures were higher in IR individuals at baseline, but increased less at 2 h, whereas ketone bodies seemed to be lower at baseline, but decreased less at 2 h compared to the IS-NGT group. We profiled four time points of OGTT data for in total Finnish individuals from 2 independent cohorts to obtain new large-scale population-based information on how insulin resistance is associated with a systemic post-load metabolic dysregulation.
These changes include adverse modifications in multiple cardiometabolic biomarkers suggesting that insulin resistance may underlie the shared susceptibility to diabetes and CVD also in the post-load milieu.
Our study is important because most people spend a significant amount of their daily lives in a postprandial state—this aspect of insulin resistance has not been captured in previous metabolomics studies of fasting samples. The results also carry practical significance: we found that IR-associated metabolic aberrations exist already in participants with normal glucose tolerance with implications for CVD risk and are similar in extent to those observed in type 2 diabetes.
The large sample size and multiple metabolomics time points allowed us to obtain accurate and systemic understanding of the expected metabolic changes in response to glucose ingestion in people with normal glucose tolerance. Our temporal data on the 2-h changes were consistent with previous small studies with pre- and post-OGTT measures and support the known action of insulin in promoting glycolysis metabolism pyruvate and lactate and suppression of ketogenesis ketone bodies , proteolysis amino acids , and lipolysis glycerol [ 4 , 7 , 18 , 20 ].
This may reflect a complex balance of hepatic triglyceride production between increased conversion from excess glucose and reduced re-esterification from free fatty acids as a result of reduced lipolysis [ 4 ].
A general observation is that different metabolic pathways were differentially affected. The extensive metabolic data demonstrate that insulin-resistant individuals had systematically smaller relative metabolic responses in comparison to the insulin-sensitive ones.
Some of these blunted changes have been previously reported for insulin-resistant or obese individuals separately in small studies, e. for lactate [ 7 , 20 ], beta-hydroxybutyrate [ 7 , 20 ], isoleucine [ 7 , 20 ], glycerol [ 7 ], and VLDL-TG [ 16 , 18 ].
Interestingly, the metabolic measures which showed blunted changes in insulin-resistant individuals in this study have been also associated with insulin resistance in the fasting state [ 28 ].
It has been suggested that insulin resistance is associated with higher fasting glycolysis-related measures and greater fasting concentrations of branched-chain amino acids, glycerol, and triglycerides [ 28 ].
Prospective studies have suggested that the associated metabolic dysregulations at fasting state are predictive of future cardiometabolic risk [ 10 , 11 , 29 , 32 ]. Further, recent Mendelian randomisation analyses have indicated a causal link from insulin resistance to higher branched-chain amino acids and triglycerides in the fasting state [ 3 ].
Our results here underline the possibility that fasting concentrations may also reflect the insufficient suppression of branched-chain amino acids and triglycerides in the postprandial state in the insulin-resistant individuals.
Regardless of the exact sequence of events, this study provides new evidence that insulin-resistant individuals are at greater cardiometabolic risk both in the fasting and post-load settings.
The comparison between IR-NGT and IS-NGT addressed the differences in IR whilst having normal glucose metabolism.
We also performed a mirror experiment where we compared the metabolic trajectories of IFG, IGT, and NDM to IR-NGT varying glucose levels but minimising the differences in IR. Interestingly, we found similar metabolic dysregulations in individuals with prediabetes and diabetes to those of insulin-resistant individuals with normal glucose metabolism.
These findings suggest limited impact of glucose on these metabolic associations. This interpretation is reinforced by our adjusted analyses: the metabolic dysregulations appear to be exclusively driven by insulin resistance but not fasting or 2-h glucose.
Type 2 diabetes, characterised by increased circulating glucose concentrations, is a known risk factor for CVD. However, a meta-analysis of prospective studies found only a marginal association between circulating glucose and CVD outcomes [ 2 ].
Consistently, a meta-analysis of over trials found limited evidence to support glucose-lowering drugs would reduce the risk of cardiovascular disease and all-cause mortality in patients of established type 2 diabetes [ 33 ].
By contrast, individuals at the stage of IR-NGT or prediabetes are reported to have higher risk of CVD [ 6 , 34 ]. Taking these together, it seems that long-term exposure for the metabolic consequences of insulin resistance across multiple tissues would account for the concerting development of type 2 diabetes and cardiometabolic complications [ 5 , 6 ].
Our study revealed that glucose-independent postprandial dysfunction might be a novel component of this exposure that is hitherto poorly recognised as a potential interventional target. Large-scale population studies and multiple time points of metabolomics data gave us a unique opportunity to study the systemic metabolic trajectories across multiple clinical glucose categories.
Analyses with multiple testing, multivariate adjustments, and replication in an independent cohort all point towards the robustness of the current findings. The associations of insulin resistance with the metabolic changes were consistent when assessed across three different surrogate markers of insulin resistance.
However, we acknowledge that insulin resistance markers may reflect a composite state of insulin sensitivity levels of multiple tissues. In order to understand the metabolic signatures of specific tissues, further experiments are required. In addition, the results were coherent whether the metabolic changes were assessed via relative or absolute concentration changes.
The associations remained similar between men and women, between middle-aged and older individuals, and also between those with or without the presence of glucose abnormality. However, ethnic and socioeconomic context should be taken into account when extending these results to other populations.
The OGTT corresponds to the ingestion of sugary drinks, but not mixed meals, and thus, these results should not be generalised to post-meal metabolic responses. In conclusion, our results highlight the detrimental effects of insulin resistance on systemic metabolism after glucose ingestion.
The population health impact of these metabolic consequences is likely substantial given the spurious and energy-dense eating patterns in the modern world, i. people are mostly living in a non-fasting state and consume high amounts of added sugar and refined carbohydrates.
The observed metabolic effects manifest very early on, and these findings suggest new avenues to understand the increased CVD risk in insulin resistance and diabetes.
It might therefore be beneficial if diabetes diagnostics and clinical care would be extended beyond glucose management. We call for better recognition of postprandial dysfunction beyond glucose tolerance categories as an important cardiometabolic risk factor, and new preventive efforts and strategies to reverse all aspects of metabolic dysregulation.
We maintain that this is particularly important at the early stages of insulin resistance, and may also hold untapped therapeutic opportunities.
Data are available for researchers who meet the criteria for access to confidential data according to the rules of each individual cohort and can be requested from the Institutional Data Access Committees of the Northern Finland Birth Cohort Study and the Oulu study University of Oulu, Finland.
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Five days later, rats were given peripheral insulin to determine the effect of diet on responses to exogenous insulin, as in experiment 1. Each rat received saline or insulin on one of two injection days, as described in experiment 1 1.
To determine whether switching from the KD to chow affected glucose tolerance, an additional group of rats was maintained on chow or KD for 8 wk, after which the KD was replaced with chow.
One week later, glucose tolerance was examined as described in experiment 2 above. Rats were maintained on chow or KD for 8 wk, and then each was stereotaxically implanted with a cannula into the lateral cerebral ventricle icv , as previously described A gauge guide cannula 10 mm in length was inserted 1.
Cannula placement was verified by angiotensin II testing. Rats were icv injected with 5 nmol angiotensin II, after which water intake was measured. All drank at least 5 ml more than they drank after icv saline injection in 30 min and therefore deemed to have correct cannula placement.
One week after recovery of presurgical body weight, rats underwent a series of icv injections to determine the effectiveness of insulin to reduce caloric intake in rats maintained on chow or KD.
A within-subjects design was used such that rats received icv injections of physiological saline or insulin 6 and 9 mU in 2 μl saline. Doses were chosen based on studies in which 8 mU was reliably shown to reduce food intake 25 , 26 , and 6 and 9 mU were tested to determine whether KD rats had increased sensitivity to the anorectic effects of centrally administered insulin.
Each rat received saline and both doses of insulin, with not less than 5 d between injections, in a counterbalanced sequence. On test days, food was removed 1 h before injection.
Rats were injected 30 min before the onset of the dark cycle, at which time food was replaced in the cage. Intake was measured 1, 2, 4, and 24 h later. On the day of killing, food was removed for 6 h, and rats were killed 2 h before the onset of the dark cycle.
Rats were rapidly decapitated under ether inhalation anesthesia, and brains were removed and placed in RNAlater Ambion, Austin, TX for subsequent analysis of insulin receptor expression in the hypothalamus by quantitative RT-PCR Q-PCR.
For Q-PCR, the whole hypothalamus of each rat was dissected from the brain and homogenized in 1 ml Trizol reagent Invitrogen, Carlsbad, CA. After centrifugation of this mixture, RNA was recovered from the aqueous phase by isopropanol precipitation.
Each primer set was optimized such that the correlation coefficient was 0. The integrity of the cDNA was confirmed by conventional RT-PCR amplification of L32 , a housekeeping gene. A control reaction for each RNA sample was also performed with no reverse transcriptase enzyme added.
Q-PCR was performed in duplicate using an iCycler and the iQ SYBR Green Supermix Bio-Rad, Hercules, CA with two-step amplification 95 C for 10 sec and 60 C for 45 sec for 40 cycles. L32 was amplified from each sample for use as an endogenous control. The effects of ip and icv insulin on caloric intake were evaluated by repeated-measures ANOVA and a Bonferroni test was used for post hoc analysis.
All glucose and insulin data were analyzed by a two-way ANOVA with repeated-measures and Bonferroni tests for post hoc analyses. Area under the curve was analyzed using a t test. All data are expressed as mean ± sem.
All rats in these experiments were maintained on chow or KD for 8 wk. As reported previously 20 , there were no differences in total daily caloric intake. The mean caloric intake by chow rats was There were no differences in body weight change over the 8 wk of diet maintenance, and body weights at the start of each experiment are given below.
After 8 wk of maintenance on chow or KD, body weights were not different between dietary groups chow, As depicted in Fig. Four hours after injection, mean caloric intake by chow rats was A similar effect was observed in KD rats.
Four hours after saline injection, KD rats consumed Comparison of the insulin-stimulated increase in caloric intake revealed no differences between groups chow, 8.
Although caloric intake by the chow group remained significantly elevated 24 h after insulin injection compared with intake after saline Caloric intake after ip insulin. Caloric intake 4 h A and 24 h B after ip insulin in rats maintained on chow.
Data are presented as mean cumulative caloric intake ± sem. At the time of IPGTT, the mean body weight for chow rats was Baseline insulin was significantly lower in KD rats; however, ip glucose in KD rats induced a significantly greater elevation of insulin 15 min after glucose injection, compared with insulin levels in chow controls Fig.
The area under the curve AUC for insulin Fig. Although IPGTT was elevated in KD insulin, there were no IPGTT-induced differences in blood glucose levels between groups.
Both chow- and KD-fed rats had peak blood glucose levels 15 min after ip injection of glucose, and blood glucose returned to baseline levels at the min time point Fig.
The glucose AUC Fig. Insulin and glucose after an IPGTT. A and B, Plasma insulin was measured A , and AUC for insulin B was calculated in response to ip administration of glucose; C and D, blood glucose C and AUC for blood glucose D after ip insulin were also obtained. Data are presented as mean ± sem.
An insulin tolerance test showed that the time course and magnitude of effect of insulin on blood glucose differed between dietary groups.
For the IPITT, mean body weight for the chow rats was As shown in Fig. In contrast, glucose was not reduced from baseline in KD rats 15 min after insulin administration. The AUC Fig. Blood glucose after IPITT. A, Glucose was measured before and after an ip insulin injection 1.
After 8 wk of maintenance on chow or KD, insulin and glucose responses to a test meal were assessed. As was the case in the previous experiments, there were no differences in body weights between dietary groups at the start of testing chow, Rats were allowed access to the test meal for 60 min.
Ingestion of the low-carbohydrate supplement by KD rats had less of an effect on insulin levels than did ingestion of the high-carbohydrate test meal by chow or KD rats Fig. The level of plasma insulin for this group did not change over the course to the min test.
Insulin remained elevated for the duration of the test session. Unlike the chow group, KD insulin was elevated min after the start of the test. The AUC for insulin Fig. Plasma insulin and blood glucose in response to ingestion of a high- or low-carbohydrate liquid meal.
A and B, Plasma insulin in response to a test meal was measured A , and AUC B was calculated; C and D, meal-stimulated glucose C and the AUC D for glucose were also measured. This is in contrast to glucose levels in chow and KD rats consuming the high-carbohydrate meal.
When chow rats consumed the high-carbohydrate meal, blood glucose steadily rose over the course of testing. It was greater than the baseline level 15 min after the start of the meal, peaked at 60 min, and then decreased.
These differences are reflected in the AUC Fig. Rats previously maintained on the KD and subsequently switched to chow for 1 wk displayed a hyperphagic response to ip insulin that was indistinguishable from the hyperphagic effect elicited by ip insulin for chow-fed controls.
For KD rats switched to chow, body weight changed from A similar increase was measured after ip insulin in KD rats, compared with intake after saline injection Caloric intake remained elevated by both chow and KD rats 24 h after ip insulin injection. For chow rats, intake was increased from Similarly, the return to chow after 8 wk of consuming the KD resulted in normalization of responding to an ip glucose challenge.
Caloric intake after switching from KD to chow and in response to ip insulin. Rats were switched from KD to chow and given ip insulin.
Caloric intake was measured 4 h A and 24 h B later. Insulin and glucose after an IPGTT after switching from KD to chow.
Rats were switched from KD to chow and given an ip glucose challenge, after which insulin A and glucose B were measured. Maintenance on KD resulted in increased sensitivity to the anorectic effects of icv insulin. After 8 wk of maintenance on chow or KD mean body weight for chow, This dose did not affect caloric intake in chow-fed rats Fig.
The effect was transient; there were no differences in intake after 24 h Fig. There were no differences in caloric intake after the 6-mU dose, compared with intake after icv saline data not shown. Caloric intake in response to icv insulin.
Rats were maintained on chow or KD and given 9 mU icv insulin. Caloric intake was measured 1 h A and 24 h B later. Data are presented as mean cumulative intake ± sem. Additionally, we measured the expression levels of mRNA for the insulin receptor in the hypothalamus.
Rats maintained on KD for 8 wk had significantly increased expression of mRNA Hypothalamic insulin receptor mRNA. After maintenance on chow or KD, INSR mRNA was significantly increased in KD rats, compared with CH-rats. In recent years, there has been increased focus on elucidating the role of dietary macronutrients in energy balance.
Although many studies have demonstrated advantages to decreasing dietary carbohydrates, including improved markers of cardiovascular health and metabolic parameters, the effects of a severe reduction in dietary carbohydrates on insulin sensitivity and the glucose homeostasis are unknown.
Metabolic adaptation occurs according to changes in the availability of nutrients 28 , and the KD results in decreased basal insulin in rodents and humans 2 , 12 , Therefore, the aims of our current studies were to investigate how long-term maintenance on this type of diet might affect 1 responsivity to insulin, 2 the ability to respond to a glucose challenge, and 3 insulin and glucose responses to a high-carbohydrate meal after a period of maintenance on a KD.
The ability of peripherally administered insulin to induce hyperphagia due to hypoglycemia has long been known 29 , 30 , Here it is demonstrated that although rats maintained on chow significantly increase caloric intake for at least 24 h after ip insulin administration, this effect is transient in rats maintained on a KD.
These data first suggested a diet-related decrease in sensitivity to the hyperphagic effects of insulin. This was further explored by examining responsivity to an ip glucose challenge.
KD rats had significantly greater insulin levels in response to a glucose challenge than did chow-fed controls, although blood glucose levels were indistinguishable between dietary groups.
As such, it appears that long-term maintenance on the KD may lead to resistance to peripheral insulin over time. One possibility is that decreased exposure to dietary carbohydrates may render one unprepared to mount an appropriate physiological response to an insulin or glucose challenge.
The malleability of this effect is demonstrated by the normalization of insulin and glucose responses to a glucose challenge 1 wk after ceasing ingestion of the KD and resuming maintenance on chow. The effects of a KD on glucose tolerance in our experiments are similar to reports of the effects of low-carbohydrate, non-KDs on this metabolic parameter, although inconsistencies within the literature exist.
Morens and colleagues 32 reported that rats maintained on a low-carbohydrate 5. The relative glucose intolerance was shown to be consistent with reduced insulin-induced glucose uptake 33 , 34 and is likely due to the high level of saturated fat in the KD Furthermore, Sinitskaya and colleagues 36 have demonstrated that although obesity can be prevented in rats by increasing the fat-to-carbohydrate ratio of the diet, glucose tolerance is impaired and accompanied by insulin resistance.
Although these studies lend support to our current findings, they are in contrast to studies conducted in mice in which glucose tolerance is improved after exposure to a KD 13 , The underlying mechanism for these species differences is currently unknown. The insulin and glucose responses to ingestion of the low- or high-carbohydrate liquid supplements in our current study provide novel insight into the effects of maintenance on a KD specific to ingestion of a meal, and the effects of drastically increasing the level of carbohydrate in a ketotic animal.
In response to a meal supplement with a similar macronutrient content to the habitual diet, a significantly greater amount of insulin and glucose was measured in the 2-h postprandial testing session. In contrast, when the KD rats ingested a high-carbohydrate test meal, the initial elevation in plasma insulin was similar to that in chow-fed controls; however, it remained significantly elevated over the course of the 2-h test session.
This effect was mirrored in glucose responsivity to the test meal. Because the initial results indicated that maintenance on a KD reduced glucose tolerance and had profound effects on glucose and insulin responses to a high-carbohydrate meal, we aimed to determine whether these effects were reversible upon cessation of the diet.
Indeed, within a week of consuming chow, rats that had previously been maintained on the KD showed a similar degree of hypophagia in response to ip insulin, and responsivity to an ip glucose challenge was normalized to resemble those of rats that had never consumed the KD. These data demonstrate that although consuming a KD may result in insulin resistance and impaired glucose tolerance, this effect is rapidly reversible upon resumption of a higher-carbohydrate diet.
Insulin levels reflect ongoing metabolic needs and how much fat exists throughout the body 39 , 40 , 41 , and decreased systemic insulin due to fasting or type 2 diabetes is associated with hyperphagia 42 , The relationship between food intake and insulin levels is disrupted in the KD model, in which rats consume the same number of calories per day and gain weight at the same rate as do chow-fed controls despite decreased plasma insulin In our current experiments, we assessed whether consuming a KD affected responsivity to central insulin, which is known to be critical in the regulation of energy homeostasis.
Neurons within the hypothalamus express high concentrations of insulin receptors 44 , and central administration of insulin potently reduces food intake in animals fed a non-KD 45 , We demonstrate that maintenance on a KD results in increased sensitivity to the anorectic effects of central insulin and is likely involved in mediating the lack of hyperphagia that is commonly observed in the presence of low systemic insulin.
There are discrepancies in the literature regarding the effects of dietary macronutrient composition on energy homeostasis. In terms of glucose tolerance, diets with proportionately different macronutrient distributions have been reported to either improve or have no effect on glucose homeostasis 13 , Overall, our current data demonstrate that maintenance on a KD may impair glucose tolerance over time and have detrimental effects on the ability to mount a sufficient insulin response to a high-carbohydrate meal.
The effects on glucose homeostasis, however, are rapidly reversible upon resumption of a high-carbohydrate diet. Finally, despite the effects of a KD on peripheral insulin and glucose tolerance, responsivity to the anorectic effects of central insulin is enhanced.
The results of these studies underscore the necessity to fully examine how dietary macronutrient manipulation affects multiple metabolic parameters to identify potential consequences. This research was supported by National Institutes of Health Grant DK K.
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Kimberly P. Insulin sensitivity and glucose tolerance, Mary Ann Honors, Sara Insukin. Low-carbohydrate, ketogenic diets KD are frequently Hormone balance and brain function in efforts sensitjvity reduce or maintain body Insulin sensitivity and glucose tolerance, although tklerance metabolic effects of long-term exposure to this Amazon Camera Equipment of diet remain controversial. This study assessed the responsivity to peripheral and central insulin, glucose tolerance, and meal-induced effects of consuming a KD in the rat. After 8 wk of consuming chow or KD, caloric intake after peripheral or central insulin and insulin and glucose levels after a glucose challenge were assessed. In a separate group of rats, glucose and insulin responses to either a low- or high-carbohydrate test meal were measured.Insulin sensitivity and glucose tolerance -
The result is higher blood glucose levels, and ultimately prediabetes or type 2 diabetes. Insulin has other roles in the body besides regulating blood glucose levels, and the effects of insulin resistance are thought to go beyond diabetes.
For example, some research has shown that insulin resistance, independent of diabetes, is associated with heart disease. Scientists are beginning to get a better understanding of how insulin resistance develops.
For starters, several genes have been identified that make a person more or less likely to develop the condition. It's also known that older people are more prone to insulin resistance. Lifestyle can play a role, too.
Being sedentary, overweight or obese increases the risk for insulin resistance. It's not clear, but some researchers theorize that extra fat tissue may cause inflammation, physiological stress or other changes in the cells that contribute to insulin resistance.
There may even be some undiscovered factor produced by fat tissue, perhaps a hormone, that signals the body to become insulin resistant. Doctors don't usually test for insulin resistance as a part of standard diabetes care. In clinical research, however, scientists may look specifically at measures of insulin resistance, often to study potential treatments for insulin resistance or type 2 diabetes.
They typically administer a large amount of insulin to a subject while at the same time delivering glucose to the blood to keep levels from dipping too low.
The less glucose needed to maintain normal blood glucose levels, the greater the insulin resistance. Insulin resistance comes in degrees.
The more insulin resistant a person with type 2 is, the harder it will be to manage their diabetes because more medication is needed to get enough insulin in the body to achieve target blood glucose levels. Insulin resistance isn't a cause of type 1 diabetes, but people with type 1 who are insulin resistant will need higher insulin doses to keep their blood glucose under control than those who are more sensitive to insulin.
As with type 2, people with type 1 may be genetically predisposed to become insulin resistant, or they may develop resistance due to being overweight. Some research indicates that insulin resistance is a factor in cardiovascular disease and other complications in people with type 1.
While fighting an invisible foe can feel frustrating and discouraging, know that you are not alone. There are effective tactics to combat insulin resistance. Losing weight, exercising more or taking an insulin-sensitizing medication can help you get back to good blood glucose control and better health.
Breadcrumb Home You Can Manage and Thrive with Diabetes Understanding Insulin Resistance. A blood pressure reading of over 80 or higher. A fasting glucose level equal or above milligrams per deciliter. Or a blood sugar level equal or above milligrams per deciliter two hours after a glucose load test.
An A1C between 5. A fasting triglycerides level over milligram per deciliter. And an HDL cholesterol level under 40 milligrams per deciliter in men, and an HDL cholesterol level under 50 milligrams per deciliter in women.
Or more recently, a blood test called hemoglobin glycosylated A1C, often simply referred to as A1C. Reversing insulin resistance and preventing type two diabetes is possible through lifestyle changes, medication, or sometimes both.
Healthy bodies come in different shapes and sizes. Losing weight through drastic means can be dangerous and counterproductive. Instead, get ideas from a doctor or a nutritionist about ways to incorporate healthy foods like fruits, vegetables, nuts, beans, and lean proteins into your meals.
Also, consider incorporating exercise and movement into your day-to-day life in ways that make you feel good. Even though permanently defeating insulin resistance isn't always possible, you can help your body to be more receptive to insulin.
Listen to your body, reduce stress, give it the nutrition and activity it desires. If you'd like to learn even more about insulin resistance, watch our other related videos or visit mayoclinic.
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While insulin resistance Body composition goals a Inslin of prediabetes and swnsitivity 2 diabetes, it can Green tea and respiratory health affect sensitovity with type 1. Green tea and respiratory health with insulin resistance, sensigivity known as impaired insulin tolerancs, have built up a tolerance to insulin, glucosf the hormone less effective. As a Insulin sensitivity and glucose tolerance, more insulin is needed to persuade fat and muscle cells to take up glucose and the liver to continue to store it. Just why a person fails to respond properly to insulin is still a mystery. But there are ways to make the body more receptive to insulin, which can help prevent or delay type 2 diabetes—or help someone with type 1 diabetes manage their blood glucose blood sugar. In response to the body's insulin resistance, the pancreas deploys more of the hormone to keep cells energized and manage blood glucose levels in a healthy range. This is why people with type 2 diabetes tend to have higher levels of circulating insulin.
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