Intestinal Perforation in ACTH-Dependent Cushing’s Syndrome

Previous studies have linked systemic glucocorticoid use with intestinal perforation. However, the association between intestinal perforation and endogenous hypercortisolism has not been well described, with only 14 previously published case reports. In this study, we investigated if intestinal perforation occurred more frequently in patients with ectopic ACTH syndrome and in those with a greater than 10-fold elevation of 24-hour urinary free cortisol level. Of 110 patients with ACTH-dependent Cushing’s syndrome followed in two clinics in Canada, six cases with intestinal perforation were identified over 15 years. Age of patients ranged from 52 to 72, five females and one male, four with Cushing’s disease and two with ectopic ACTH production, one from a pancreatic neuroendocrine tumor and one from medullary carcinoma of the thyroid. Five had diverticular perforation and one had intestinal perforation from a stercoral ulcer. All cases had their lower intestinal perforation when the cortisol production was high, and one patient had diverticular perforation 15 months prior to the diagnosis of Cushing’s disease. As in previously reported cases, most had hypokalemia and abdominal pain with minimal or no peritoneal symptoms and this occurred during the active phase of Cushing’s syndrome. Whereas all previously reported cases occurred in patients with 24-hour urinary free cortisol levels greater than 10-fold the upper limit of normal when measured and 11 of 14 patients had ectopic ACTH production, only one of our patients had this degree of hypercortisolism and four of our six patients had Cushing’s disease. Similar to exogenous steroid use, patients with endogenous hypercortisolism also have a higher risk of intestinal, in particular diverticular, perforation and should be monitored closely for its occurrence with a low threshold for investigation and surgical intervention. Elective colonoscopy probably should be deferred until Cushing’s syndrome is under control

Significant Beneficial Association of High Dietary Selenium Intake with Reduced Body Fat in the CODING Study

Selenium (Se) is a trace element which plays an important role in adipocyte hypertrophy and adipogenesis. Some studies suggest that variations in serum Se may be associated with obesity. However, there are few studies examining the relationship between dietary Se and obesity, and findings are inconsistent. We aimed to investigate the association between dietary Se intake and a panel of obesity measurements with systematic control of major confounding factors. A total of 3214 subjects participated in the study. Dietary Se intake was determined from the Willett food frequency questionnaire. Body composition was measured using dual-energy X-ray absorptiometry. Obese men and women had the lowest dietary Se intake, being 24% to 31% lower than corresponding normal weight men and women, classified by both BMI and body fat percentage. Moreover, subjects with the highest dietary Se intake had the lowest BMI, waist circumference, and trunk, android, gynoid and total body fat percentages, with a clear dose-dependent inverse relationship observed in both gender groups. Furthermore, significant negative associations discovered between dietary Se intake and obesity measurements were independent of age, total dietary calorie intake, physical activity, smoking, alcohol, medication, and menopausal status. Dietary Se intake alone may account for 9%–27% of the observed variations in body fat percentage. The findings from this study strongly suggest that high dietary Se intake is associated with a beneficial body composition profile

High Dietary Magnesium Intake Is Associated with Low Insulin Resistance in the Newfoundland Population

Background Magnesium plays a role in glucose and insulin homeostasis and evidence suggests that magnesium intake is associated with insulin resistance (IR). However, data is inconsistent and most studies have not adequately controlled for critical confounding factors. Objective The study investigated the association between magnesium intake and IR in normal-weight (NW), overweight (OW) and obese (OB) along with pre- and post- menopausal women. Design A total of 2295 subjects (590 men and 1705 women) were recruited from the CODING study. Dietary magnesium intake was computed from the Willett Food Frequency Questionnaire (FFQ). Adiposity (NW, OW and OB) was classified by body fat percentage (%BF) measured by Dual-energy X-ray absorptiometry according to the Bray criteria. Multiple regression analyses were used to test adiposity-specific associations of dietary magnesium intake on insulin resistance adjusting for caloric intake, physical activity, medication use and menopausal status. Results Subjects with the highest intakes of dietary magnesium had the lowest levels of circulating insulin, HOMA-IR, and HOMA-ß and subjects with the lowest intake of dietary magnesium had the highest levels of these measures, suggesting a dose effect. Multiple regression analysis revealed a strong inverse association between dietary magnesium with IR. In addition, adiposity and menopausal status were found to be critical factors revealing that the association between dietary magnesium and IR was stronger in OW and OB along with Pre-menopausal women. Conclusion The results of this study indicate that higher dietary magnesium intake is strongly associated with the attenuation of insulin resistance and is more beneficial for overweight and obese individuals in the general population and pre-menopausal women. Moreover, the inverse correlation between insulin resistance and dietary magnesium intake is stronger when adjusting for %BF than BMI

Regression Models of Magnesium Intake on Insulin Resistance based upon %BF and BMI.

1<p>Regression model adjusted for caloric intake, physical activity, medication use and menopausal status.Subjects were also stratified into a tertiles(Low, Medium and High) based upon %BF and BMI.</p>2<p>β = Unstandardized Beta (standard error), β* = Standardized Beta (standard error), Magnesium intake (g/day/kg).</p>3<p>Magnesium intake (Low BMI 409.78±243.5 mg/day, Medium BMI 353.24±180.9 mg/day, High BMI 342.76±196.1 mg/day) (Low %BF 387.5±230.3 mg/day, Medium %BF 360.54±187.5 mg/day, High %BF 357.68±210.7 mg/day).</p>4<p>Statistical significance was set to p<0.05 (IBM SPSS Statistics 19).</p

Regression Models of Magnesium Intake on Insulin Resistance.

1<p>Regression model adjusted for caloric intake, physical activity, medication use and menopausal status.</p>2<p>β = Unstandardized Beta (standard error), β* = Standardized Beta (standard error), Magnesium intake (g/day/kg).</p>3<p>Normal-weight, overweight and obese groups are based upon %BF according to the Bray criteria (25).</p>4<p>Magnesium intake (Pre-Menopause 360.63±209.8 mg/day, Post-Menopause 353.82±192.9 mg/day) (Entire cohort, Normal-weight, Overweight, & Obese – See Table.1).</p>5<p>Statistical significance was set to p<0.05 (IBM SPSS Statistics 19).</p

Physical, Biochemical, and Dietary Intake Characteristics of Normal-weight, Overweight, and Obese Participants.

1<p>Data presented as mean ± SD. Homeostasis model assessment of insulin resistance (HOMA-IR) and β-cell function (HOMA-β). Gender differences were assessed with a one-way ANOVA. Subjects were also stratified into normal-weight, overweight and obese based upon %BF according to the Bray criteria (25). Adiposity differences were assessed with an ANCOVA controlling for caloric intake, physical activity, medication use, and menopause. ²Significantly greater for men compared to women. ³Significantly greater for women compared to men. ⁴Statistical significance for one-way ANOVA and ANCOVA were set to p<0.05 (IBM SPSS Statistics 19).</p

Physical, Biochemical, and Dietary Intake Characteristics According to Magnesium Intake.

1<p>Data presented as mean ± SD. Homeostasis model assessment of insulin resistance (HOMA-IR) and β-cell function (HOMA-β).</p>2<p>Subjects were stratified into a tertile (low, medium and high) based upon magnesium intake (mg/day).</p>3<p>Magnesium intake group differences were assessed with an ANCOVA controlling for caloric intake, physical activity, medication use, menopause and %BF.</p>4<p>Statistical significance for one-way ANCOVA was set to p<0.05 (IBM SPSS Statistics 19).</p