Fig. 1: Increased glucocorticoid activation and 11β-HSD1 expression in bone are associated with systemic metabolic disorders and trabecular bone loss in mice with high-fat diet.
From: Targeting osteoblastic 11β-HSD1 to combat high-fat diet-induced bone loss and obesity
a–d The HSD11B1 expression of cancellous bone in human femoral head. a Bubble Chart depicting body mass index (BMI), blood glucose level (BG), and skeletal HSD11B1 expression in 27 human participants. b Participants with overweight (n = 8) and normal weight (n = 19). c Participants with hyperglycemia (n = 12) and normal blood glucose level (n = 15). d Participants with both normal weight and normal blood glucose level (n = 12), only hyperglycemia (n = 7), only normal glucose level (n = 4), and with both overweight and hyperglycemia (n = 4). Overweight: BMI > 25. Hyperglycemia: BG > 6.11 mmol/L. e–i Weight gain, weights of gonadal white adipose tissues (gWAT) and glucose handling tests of wild-type mice with high-fat diet (HFD) or chow diet (Chow). *P < 0.05, **P < 0.01, ***P < 0.001 when HFD vs. Chow. e Weight gain. f Weights of gWAT. g The fasting blood glucose. h The insulin resistant test (ITT). i The oral glucose tolerance test (oGTT). j–k The micro-CT analysis of wild-type mice with HFD or Chow. j The trabecular bone microstructure. k The trabecular bone volume/total volume (Tb. BV/TV) and trabecular bone density (Tb. v. BMD). l Systemic corticosterone in wild-type mice with HFD or Chow. m The mRNA expression of the 11β-HSD1 gene (Hsd11b1) and the glucocorticoid target gene Glucocorticoid-induced leucine zipper (Gilz) in liver, WAT, bone and muscle in wild-type mice with HFD, *P < 0.05, **P < 0.01 when HFD vs. Chow. n Linear regression analysis of skeletal Hsd11b1 / Gilz expression versus Tb. BV/TV, weight gain and ITT, respectively, in wild-type mice with HFD or Chow. Note: Data were presented as mean value ± SEM for (b–i, k–m). Box plot with centre line = median, cross = mean, box limits = upper and lower quartiles, whiskers = min to max (l–m). n = 4 biologically independent samples at each time-point for (e–n). Statistical significance was calculated using two-tailed Student’s t-test (a–d) and two-way ANOVA followed by two-stage step-up method by Benjamini, Krieger and Yekutieli to adjust for multiple comparisons (e–i, k–m). All tests were two-sided.
