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Objective: In cystic fibrosis (CF), hemoglobin A1c (HbA1c) is thought to underestimate glycemia. However, few studies have directly assessed the relationship between HbA1c and average glucose in CF. We determined the relationships among glycemic markers-HbA1c, fructosamine (FA), glycated albumin (%GA), and 1,5-anhydroglucitol (1,5-AG)-and continuous glucose monitoring (CGM) in CF, hypothesizing that alternate markers would better predict average sensor glucose (ASG) than HbA1c.Research Design and Methods: CF participants and a group of healthy control subjects (HCs), ages 6-25 years, wore CGM for up to 7 days. Pearson correlations assessed the relationships between CGM variables and HbA1c, FA, %GA, and 1,5-AG. The regression line between HbA1c and ASG was compared in CF versus HC. Linear regressions determined whether alternate markers predicted ASG after adjustment for HbA1c.Results: CF (n = 93) and HC (n = 29) groups wore CGM for 5.2 ± 1 days. CF participants were 14 ± 3 years of age and 47% were male, with a BMI z score -0.1 ± 0.8 and no different from HCs in age, sex, or BMI. Mean HbA1c in CF was 5.7 ± 0.8% (39 ± 9 mmol/mol) vs. HC 5.1 ± 0.2% (32 ± 2 mmol/mol) (P < 0.0001). All glycemic markers correlated with ASG (P ≤ 0.01): HbA1c (r = 0.86), FA (r = 0.69), %GA (r = 0.83), and 1,5-AG (r = -0.26). The regression line between ASG and HbA1c did not differ in CF versus HC (P = 0.44). After adjustment for HbA1c, %GA continued to predict ASG (P = 0.0009) in CF.Conclusions: HbA1c does not underestimate ASG in CF as previously assumed. No alternate glycemic marker correlated more strongly with ASG than HbA1c. %GA shows strong correlation with ASG and added to the prediction of ASG beyond HbA1c. However, we are not advocating use of HbA1c for diabetes screening in CF based on these results. Further study will determine whether glycemic measures other than ASG differ among different types of diabetes for a given HbA1c. [ABSTRACT FROM AUTHOR]

Adolescents with type 2 diabetes (T2D) have severe insulin resistance (IR) secondary to obesity, genetics, and puberty, and IR predicts metabolic comorbidities. Adults with T2D have multitissue IR, which has guided therapeutic developments, but this is not established in youth. We sought to assess adipose, hepatic, and peripheral insulin sensitivity in adolescents with and without T2D. Twenty-seven youth with T2D [age: 15.6 ± 0.4 yr; female: 78%; body mass index (BMI) percentile: 96.1 (52.6, 95.9), late puberty; hemoglobin A1c (HbA1c) 7.3% (6.2, 10.1)] and 21 controls of similar BMI, pubertal stage, and habitual activity were enrolled. Insulin action was measured with a four-phase hyperinsulinemic-euglycemic clamp (basal, 10, 16, and 80 mU·m -2 ·min -1 for studying adipose, hepatic, and peripheral IR, respectively) with glucose and glycerol isotope tracers. Total fat mass, fat-free mass, liver fat fraction, and visceral fat were measured with dual-energy x-ray absorptiometry (DXA) and MRI, respectively. Free fatty acids (FFAs), lipid profile, and inflammatory markers were also measured. Adolescents with T2D had higher lipolysis ( P = 0.012), endogenous glucose production ( P < 0.0001), and lower glucose clearance ( P = 0.002) during hyperinsulinemia than controls. In T2D, peripheral IR positively correlated to FFA ( P < 0.001), inflammatory markers, visceral ( P = 0.004) and hepatic fat ( P = 0.007); hepatic IR correlated with central obesity ( P = 0.004) and adipose IR ( P = 0.003). Youth with T2D have profound multitissue IR compared with BMI-equivalent youth without T2D. The development of multitissue interactions appears crucial to the pathogenesis of T2D. Therapeutic targets on multitissue IR may be of benefit, deserving of further research.

Objective: In cystic fibrosis (CF), hemoglobin A 1c (HbA 1c ) is thought to underestimate glycemia. However, few studies have directly assessed the relationship between HbA 1c and average glucose in CF. We determined the relationships among glycemic markers-HbA 1c , fructosamine (FA), glycated albumin (%GA), and 1,5-anhydroglucitol (1,5-AG)-and continuous glucose monitoring (CGM) in CF, hypothesizing that alternate markers would better predict average sensor glucose (ASG) than HbA 1c ., Research Design and Methods: CF participants and a group of healthy control subjects (HCs), ages 6-25 years, wore CGM for up to 7 days. Pearson correlations assessed the relationships between CGM variables and HbA 1c , FA, %GA, and 1,5-AG. The regression line between HbA 1c and ASG was compared in CF versus HC. Linear regressions determined whether alternate markers predicted ASG after adjustment for HbA 1c ., Results: CF ( n = 93) and HC ( n = 29) groups wore CGM for 5.2 ± 1 days. CF participants were 14 ± 3 years of age and 47% were male, with a BMI z score -0.1 ± 0.8 and no different from HCs in age, sex, or BMI. Mean HbA 1c in CF was 5.7 ± 0.8% (39 ± 9 mmol/mol) vs. HC 5.1 ± 0.2% (32 ± 2 mmol/mol) ( P < 0.0001). All glycemic markers correlated with ASG ( P ≤ 0.01): HbA 1c ( r = 0.86), FA ( r = 0.69), %GA ( r = 0.83), and 1,5-AG ( r = -0.26). The regression line between ASG and HbA 1c did not differ in CF versus HC ( P = 0.44). After adjustment for HbA 1c , %GA continued to predict ASG ( P = 0.0009) in CF., Conclusions: HbA 1c does not underestimate ASG in CF as previously assumed. No alternate glycemic marker correlated more strongly with ASG than HbA 1c . %GA shows strong correlation with ASG and added to the prediction of ASG beyond HbA 1c . However, we are not advocating use of HbA 1c for diabetes screening in CF based on these results. Further study will determine whether glycemic measures other than ASG differ among different types of diabetes for a given HbA 1c ., (© 2018 by the American Diabetes Association.)