RESUMO

Two adrenalectomies py -45erformed fourteen years apart notoriously alleviated insulin resistance in a female teenager with Congenital Generalized Lipoatrophy (CGL, 1988) and in a murine model of CGL (2002). Following a successful therapeutic trial with anti-glucocorticoids, we performed the first surgical procedure on an 18-year-old girl. Before surgery, the anti-glucocorticoid therapy produced a rapid and striking drop in fasting serum insulin levels (from over 400 to 7.0 mU/L) and a slower -but impressive- fall in fasting serum triglycerides from 7,400 to 220-230 mg/dL. In contrast, fasting serum glucose levels dropped more slowly, from 225-290 to 121-138 mg/dL. Two weeks following total adrenalectomy, the fasting serum glucose level was 98 mg/dL, with a corresponding serum insulin level of 10 mU/L. During an Oral Glucose Tolerance Test, the 2-hour serum glucose was 210 mg/dL, and serum insulin values during the test did not exceed 53 mU/L. In 2002, the A-ZIP/F1 hypoleptinemic mouse had its adrenal glands removed. Even though this CGL model does not respond well to leptin replacement, an infusion of recombinant leptin reduced the characteristic hypercorticosteronemia of this murine model of CGL. Adrenalectomy in this transgenic mouse improved insulin sensitivity in the liver and muscle. In summary, adrenalectomy -in both a human and a mouse case of CGL- limited adipose tissue exposure to corticosteroid action and led to a notorious metabolic improvement. On a broader scenario, given that leptin restrains the adrenal axis, the reduced leptin activity of the leptin resistance displayed by obese subjects should lead to adrenal axis overactivity. This overactivity should result in elevated serum levels of free cortisol, free fatty acids, and glycerol. In this manner, leptin resistance should lead to peripheral (adipose tissue, liver, and muscle) insulin resistance and islet beta-cell apoptosis, paving the way to Type 2 diabetes.

Assuntos

Diabetes Mellitus Lipoatrófica , Diabetes Mellitus Tipo 2 , Resistência à Insulina , Insulinas , Lipodistrofia Generalizada Congênita , Adolescente , Animais , Feminino , Humanos , Camundongos , Adrenalectomia , Modelos Animais de Doenças , Glucose , Leptina , Relatos de Casos como Assunto

Assuntos

Resistência à Insulina , Glicemia , Intolerância à Glucose , Teste de Tolerância a Glucose , Humanos , Insulina

RESUMO

Background An instrument to help clinicians to evaluate the oral glucose tolerance test (OGTT) at-a-glance is lacking. Aim To generate a program written in HTML squeezing relevant information from the OGTT with glucose and insulin measurements. Material and Methods We reanalyzed a database comprising 90 subjects. All of them had both an OGTT and a pancreatic suppression test (PST) measuring insulin resistance directly. Thirty-seven of the 90 studied participants were insulin resistant (IR). Receiver operating characteristic (ROC) curves and Bayesian analyses delineated the diagnostic performances of four predictors of insulin resistance: HOMA, QUICKI, ISI-OL (Matsuda-DeFronzo) and I0*G60. We validated a new biochemical predictor, the Percentual Relative Insulin Sensitivity (%RIS), and calculated the Percentual Relative Beta Cell Function (%RBCF). Results The best diagnostic performance of the five predictors were those of the I0*G60 and the %RIS. The poorest diagnostic performances were those of the HOMA and QUICKI. The ISI-OL's performance was in between. The %RIS of participants with and without IR was 44.4 ± 7.3 and 101.1 ± 8.8, respectively (p < 0.05). The figures for % RBCF were 55.8 ± 11.8 and 90.8 ± 11.6, respectively (p < 0.05). Mathematical modeling of the relationship between these predictors and the Steady State Plasma Glucose Value from the PST was performed. We developed a program with 10 inputs (glucose and insulin values) and several outputs: I0*G60, HOMA, QUICKI, ISI-OL, Insulinogenic Index, Disposition Index, %RBCF, %RIS, and metabolic categorization of the OGTT (ADA 2003). Conclusions The OGTT data permitted us to write successfully an HTML program allowing the user to fully evaluate at-a-glance its metabolic information.

Assuntos

Humanos , Resistência à Insulina , Glicemia , Intolerância à Glucose , Teste de Tolerância a Glucose , Insulina

RESUMO

OBJECTIVE: To evaluate the diagnostic performance of several biochemical predictors of insulin resistance (IR). DESIGN: A total of 90 nondiabetic subjects were tested with both the pancreatic suppression test (PST) and the oral glucose tolerance test (OGTT). Of them, 53 were non-insulin-resistant (NIR) subjects and the remaining 37 were insulin resistant subjects. RESULTS: All glucose and insulin values from the OGTT were positively correlated with the steady-state plasma glucose (SSPG) value of the PST. Among the OGTT values, basal insulin (I0) displayed a stronger correlation with SSPG (r = 0.604). Receiver operating characteristic analysis of the OGTT data demonstrated that I0 exhibited the highest area under the receiver operating characteristic curve (AUROC), compared with the rest of the OGTT data. However, the reduced sensitivity of this predictor precluded its clinical use.We then tested six potential predictors of IR derived from the OGTT values. Of them, the I0*G60 had a correlation coefficient of 0.697 with the SSPG and an AUROC of 0.867, surpassing the respective values of the traditional biochemical predictors of IR. Its cutoff predicting IR was >1110 mg/dL*µΙU/mL (>428 nM*pM), its sensitivity was 0.865, and its global accuracy was 0.822. We then selected the six best biochemical predictors of IR according to their posttest probability ratio. The order was as follows: I0*G60, ISI composite, AUC-Gl*In/', quantitative insulin sensitivity check index, homeostatic model assessment 1 (HOMA1), and HOMA2. CONCLUSION: We conclude that the I0*G60 is a promising, inexpensive, and easily calculable predictor of IR that outperforms the predictive power of the traditional predictors of IR, including the insulin sensitivity index composite.

Assuntos

Resistência à Insulina , Idoso , Humanos , Insulina , Assistência de Longa Duração , Masculino , Testosterona

RESUMO

A cohort of 141 males (18-80 yo, 42.9 ± 12.9) strongly suspected of being Insulin Resistant (IR) was prospectively studied by determining their insulin sensitivity (Pancreatic Suppression Test, PST) and testicular function (total testosterone and SHBG). The subjects were labeled as IR when the Steady State Plasma Glucose (SSPG) was ≥150 mg/dL and Non-Insulin Resistant (NIR) when SSPG was <150 mg/dl; similarly, the subjects were labeled as Hypogonadal (HYPOG) when total testosterone was ≤3.0 ng/mL and Eugonadal (EUG) when total testosterone was >3.0 ng/mL. Two out of three subjects turned out to be IR, while around one in four subjects were HYPOG. Contingency analysis indicated a significant interdependence between insulin resistance and hypogonadism (chi-square was 4.69, p = 0.0303). Age (>43 yo) predicted hypogonadism (AUROC 0.606, p = 0.0308). Twice as many HYPOG subjects were IR as compared with EUG subjects. Also, HYPOG subjects exhibited higher SSPG values as compared with EUG subjects. Statistically, neither Weight nor BMI predicted hypogonadism, while Waist Circumference (>110 cm) was only a mediocre predictor (AUROC 0.640, p = 0.009). SSPG (>224 mg/dL) on the other hand, was the best predictor of hypogonadism (AUROC 0.709, p = 0.002), outperforming Waist Circumference (half of the subjects with an SSPG >224 mg/dL were HYPOG). Age did not predict insulin resistance, while Weight (>99 kg), BMI (>29), and especially, Waist Circumference (>99 cm, AUROC 0.812, p < 0.0001) were all predictors of insulin resistance. Almost 90% of the subjects with a waist circumference >99 cm was IR. As a logical consequence of the selection criteria (various clues suggesting insulin resistance), most subjects with normal weight in this cohort were IR (53.3%) while 20% were HYPOG. On the other hand, 13.6% of the obese subjects were NIR, and 2 out of 3 of them were both NIR and EUG. In conclusion, Waist Circumference predicted both insulin resistance (>99 cm) and hypogonadism (>110 cm), suggesting that the first hit of abdominal obesity is insulin resistance and the second hit is male hypogonadism. Normal weight did not protect from IR, while a relevant proportion of obese subjects were NIR (with 2/3 being also EUG).