T2D risk phenotype after recent GDM. Supplemental Materials and Methods. Methodology of IVGTT/euglycemic hyperinsulinemic clamp

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1 Supplemental Materials and Methods Methodology of IVGTT/euglycemic hyperinsulinemic clamp A combined IVGTT/euglycemic hyperinsulinemic clamp was performed in subgroups of study participants following the Botnia protocol (12). For the IVGTT a glucose bolus of 0,3g/kg body weight was injected over 1 minute. Blood samples were drawn at 0, 2, 4, 6, 8, 10, 20, 30, 45 and 60 minutes. First phase insulin secretion (FPIR) was calculated as the incremental area under the insulin curve from 0 to 10 minutes, second phase insulin secretion as the incremental area under the curve from 10 to 60 minutes. For the euglycemic clamp a primed infusion of 40mU/m2 body surface area of human insulin was administered for 150 to 180 minutes. A 20% glucose infusion was adjusted in 5 minute intervals to maintain a plasma glucose level of 90 mg/dl. To terminate the test, a stable plasma glucose level as well a stable infusion rate had to be achieved. The M-value was calculated as infused glucose (mmol) per minute. M/ffm*I was calculated as the M-value divided by fat-free body weight and by the steady state plasma insulin concentration (nmol/l). Detailed methodology of MRI/MRS studies Whole body imaging was done with an anterior body coil and a posterior coil integrated in the tabletop. Subjects were scanned in supine position with arms extended. For the determination of adipose and lean tissue distribution, an axial modified Dixon sequence (repetition time 4.0 ms, first echo time 1.45 ms, second echo time 0.7 ms, flip angle 10, slice thickness 10 mm, gap 10 mm, 208 x 161 matrix, 520 x 400 x 190 field of view) or an axial T1 weighted sequence (repetition time 672 ms, echo time 7.6 ms, flip angle 90, slice thickness 10mm, gap 10 mm, 208 x 197 matrix, 520 x 400 x 190 field of view) were used. Seven to ten stacks were acquired depending on the patient s height. Scan time was approximately 20 minutes. Semiautomatic segmentation of body fat compartments was performed using SliceOmatic 4.3 Version 11 (TomoVision, Magog, Canada). Abdominal visceral adipose tissue was defined as fat between the diaphragm, the pelvic floor and the abdominal musculature. Total subcutaneous fat was determined from wrist to ankle, excluding the mammae due to the potential influence of the breastfeeding status. Two threshold values were individually set for the separation of subcutaneous and visceral adipose tissue. Manual adjustments were performed to account for signal inhomogeneities. Liver fat estimates were derived from a modified two-point Dixon sequence using the following parameters: repetion time 4.1ms, first echo time 1.5 ms, second echo time, 2.7 ms, flip angle 5, slice thickness 5mm, 184 x 170 matrix, 320 x 300 x 200 field of view. Subjects were scanned in the supine position using a phased-array abdominal coil. Imaging was performed during a single breath hold of about 10 seconds. Afterwards, liver fat content was calculated from a fat fraction map generated with a dedicated algorithm as described elsewhere (14). Regions of interest of approximately 35 mm2 size were placed in three different sites of segment VII in the right liver lobe. Muscle fat was determined in the anterior tibial and the soleus muscle by using a point resolved spectroscopy (PRESS) with a repetition time 2000 ms, echo time 33 ms, flip angle 90 with and without chemical shift-selective water suppression (scan times 4 and 1 minute, respectively). 1

2 Subjects were scanned in supine position using a small flexible transmitter/receiver extremity coil. Axial and sagittal T1 weighted images of the calf were used to place a voxel with 20x10x10 mm3 size in the center of the muscles avoiding the edges of subcutaneous tissue. Spectral analysis was performed using jmrui 4.0 (freeware: The MRUI Project; mrui-mgr@mrui.uab.es). The integral of the methylene signal of extramyocellular lipid (EMCL) at 1.5 ppm (parts per million) and of intramyocellular lipid (IMCL) at 1.2 ppm was determined in relation to the water signal at 4.7 ppm as described elsewhere (15). Blood sample collection and analysis Blood was drawn into containers without additives (Serum monovettes, Sarstedt, Germany) for serum and into BD p800 EDTA-vials for plasma. Plasma was centrifuged immediately at room temperature and frozen on dry ice in aliquots. For serum, blood was left in upright containers for 30 minutes at room temperature followed by immediate centrifugation and freezing of aliquots on dry ice. All samples were stored at -80 C until analysis. Each aliquot was only thawed once. Glucose concentrations were measured from fresh sodium fluoride plasma. List of laboratory assays used in this study Serum insulin Glucose HbA1c hscrp Fetuin-A Leptin Adiponectin Resistin gamma-gt NEFA triglycerides cholesterol HDL-chol. LDL-chol. CLIA, DiaSorin LIAISON systems, Saluggia, Italy Glucose HK Gen.3, Roche Diagnostics, Mannheim, Germany) VARIANT II TURBO HbA1c Kit - 2.0, Bio-Rad Laboratories, Hercules, USA wide-range CRP, Siemens Healthcare Diagnostics, Erlangen, Germany ELISA, BioVendor, Heidelberg, Germany ELISA "Dual Range", Merck Millipore, Darmstadt, Germany RIA, Merck Millipore, Darmstadt, Germany Quantikine ELISA, R&D Systems, Wiesbaden-Nordenstadt, Germany enzymatic caloric test, Roche Diagnostics, Mannheim, Germany Wako Chemicals, Neuss, Germany enzymatic caloric test, Roche Diagnostics, Mannheim, Germany enzymatic caloric test, Roche Diagnostics, Mannheim, Germany enzymatic caloric test, Roche Diagnostics, Mannheim, Germany Friedewald equation (All triglyceride values were below 400 mg/dl.) 2

3 Supplemental Table 1: To validate the insulin sensitivity index (ISI) calculated from the OGTT we performed a combined IVGTT/euglycemic clamp study in 40 study participants. The table shows the result of a univariate linear regression analysis with the dependent variable M/ffm*I. The predictive capacity of the ISI is very good and similar to the original publication by Matsuda et al. (12). parameter regression standard error p-value R² coefficient ISI (Matsuda) < Supplemental Table 2: We also evaluated OGTT parameters for the prediction of first phase insulin secretion (FPIR) in our study cohorts. The table shows univariate linear regression analyses with the dependent variable FPIR. The insulinogenic index (the ratio of the increment of insulin to that of plasma glucose during the first 30 minutes of the OGTT; IGI) exhibited only a poor capacity to predict the FPIR, whereas the increment of plasma insulin during the first 30 minutes of the OGTT ( I 30 ) was sufficiently well predictive of FPIR. We therefore used this parameter in our analyses. parameter regression standard error p-value R² coefficient IGI I < Supplemental Table 3: Univariate logistic regression for post-cgm/control status Parameter regression coefficient (standard error) p-value odds ratio (95% confidence interval) age (years) (0.044) ( ) month post delivery (month) (0.060) ( ) Primiparous (0.174) ( ) smoking (0.405) ( ) family history T2DM (firstdegree (0.210) ( ) relative) family history GDM (firstdegree (0.398) ( ) relative) BMI (kg/m²) (0.040) ( ) waist circumference (cm) (0.018) ( ) systolic blood pressure (0.018) ( ) diastolic blood pressure (0.020) ( ) triglycerides (mg/dl) (0.005) ( ) LDL cholesterol (mg/dl) (0.006) ( ) HDL cholesterol (mg/dl) (0.011) ( ) hscrp (0.922) ( ) ferritin (µg/l) (0.008) ( ) gamma-gt (U/l) (0.023) ( ) tsh (µu/ml) (0.151) ( ) ISI (0.055) ( ) DI (0.002) < ( ) fetuin A (0.005) < ( ) leptin (0.029) ( ) Adiponectin (0.026) ( ) resistin (0.035) ( ) nefa (0.000) ( ) 3

4 Supplemental Table 4: Multiple logistic regression for post-gdm/control status. All variables with a p-value < 0.05 in the univariate analysis were included. parameter regression coefficient (standard error) p-value odds ratio (95% confidence interval) BMI (kg/m²) (0.100) ( ) waist circumference (0.045) ( ) (cm) systolic blood pressure (0.032) ( ) diastolic blood pressure (0.036) ( ) HDL cholesterol (0.014) ( ) (mg/dl) tsh (µu/ml) (0.186) ( ) ISI (0.078) ( ) DI (0.002) ( ) fetuin A (0.006) ( ) leptin (0.049) ( ) R 2 4

5 Supplemental Table 5: Baseline characteristics only of normoglycemic study participants Group post-gdm controls p-value no. of patients (n) clinical characteristics insulin during pregnancy (n, %) 32 (51.6%) - age (years) 35.5± ± months post delivery (month) (mean ± SD) 9.5± ± primiparous (n, %) 34 (54.8%) 26 (54.2%) # breast feeding full at time of visit (n, %) 5 (8.1%) partial 18 (29.0%) 22 (45.8%) no 39 (62.9%) 26 (54.2%) smoking (n, %) yes 5 (8.1%) 2 (4.2%) no 57 (91.9%) 46 (95.8%) ex-smoker 16 (28.6%) 13 (28.9%) # family history T2DM (first-degree relative) (n, %) yes 15 (24.2%) 10 (20.8%) # family history GDM (first-degree relative) (n, %) yes 5 (8.1%) 2 (4.2%) BMI (kg/m²) 25.2± ± waist circumference (cm) 81.3± ± systolic blood pressure 119.7± ± diastolic blood pressure 75.7± ± clinical chemistry triglycerides (mg/dl) 65.0 ( ) 62.5 ( ) LDL cholesterol (mg/dl) ( ) ( ) HDL cholesterol (mg/dl) 64.0 ( ) 63.0 ( ) hscrp 0.06 ( ) 0.04 ( ) ferritin (µg/l) 31.0 ( ) 25.0 ( ) gamma-gt (U/l) 13.5 ( ) 14.0 ( ) tsh (µu/ml) 1.6 ( ) 1.8 ( ) glucose metabolism fasting plasma glucose (mg/dl) 91.0 ( ) 89.5 ( ) plasma glucose 2h (mg/dl) ( ) 93.5 ( ) <0.001 ISI 5.3 ( ) 6.7 ( ) IR ( ) 44.6 ( ) DI ( ) ( ) protein mediators fetuin A ( ) ( ) leptin 8.7 ( ) 6.8 ( ) adiponectin 10.0 ( ) 11.6 ( ) resistin 8.5 ( ) 8.9 ( ) nefa (median(q1-q3)) ( ) ( ) Fisher Exact test; # Chi-square test; Mann-Whitney-U test 5

6 Supplemental Table 6: Univariate logistic regression for PGT versus NGT after GDM parameter regression coefficient (standard error) p-value odds ratio (95% confidence interval) age (years) (0.054) ( ) month post delivery (month) (0.070) ( ) primiparous (0.215) ( ) smoking (0.382) ( ) family history T2DM (firstdegree (0.233) ( ) relative) family history GDM (firstdegree (0.336) ( ) relative) BMI (kg/m²) (0.035) ( ) waist circumference (cm) (0.018) ( ) systolic blood pressure (0.020) ( ) diastolic blood pressure (0.024) ( ) triglycerides (mg/dl) (0.007) ( ) LDL cholesterol (mg/dl) (0.008) ( ) HDL cholesterol (mg/dl) (0.017) ( ) hscrp (0.690) ( ) ferritin (µg/l) (0.009) ( ) gamma-gt (U/l) (0.028) ( ) tsh (µu/ml) (0.220) ( ) ISI (0.119) ( ) DI (0.0032) ( ) fetuin A (0.0056) ( ) leptin (0.029) ( ) adiponectin (0.037) ( ) resistin (0.040) ( ) nefa (0.001) ( ) Supplemental Table 7: Baseline characteristics for the magnetic resonance imaging sub-sample (Mann-Whitney-U tests) group post-gdm controls p-value no. of patients (n) clinical characteristics age (years) 35.6± ± months post delivery (month) 10.0± ± BMI (kg/m²) 25.8± ± waist circumference (cm) 82.1±12.5 n= ± waist to hip ratio 0.82±0.06 n= ± MRI/MRS parameter intraabdominal fat (liter) 1.8 ( ) 1.4 ( ) liver fat (%) 0.7 ( ) 0.4 ( ) intramyocellular lipids in soleus muscle (%) 1.6 ( ) 1.7 ( ) intramyocellular lipids in tibialis anterior muscle (%) 0.9 ( ) 1.0 ( ) ratio intraabdominal fat / Subcutaneous fat 0.3 ( ) 0.3 ( ) ratio intraabdominal fat / total body fat (%) 8.0 ( ) 7.0 ( ) glucose metabolism ISI 5.1 ( ) 7.6 ( )

7 Supplemental Figure 1: Relationship between ISI and M/ffm*I. The solid line is the linear regression curve and the shaded bands around the curve indicate the 95% confidence interval. The Matsuda index of insulin sensitivity (ISI), derived from the OGTT, is highly predictive of insulin sensitivity measured in the euglycemic clamp (M/ffm*I). 7

8 Supplemental Figure 2: Relationship between IGI and FPIR. The solid line is the linear regression curve and the shaded bands around the curve indicate the 95% confidence interval. In this study, Supplemental Figure 3: Relationship between I 30 and FPIR. The solid line is the linear regression curve and the shaded bands around the curve indicate the 95% confidence interval. 8

9 Supplemental Figure 4: Coefficient selected by lasso regression (dependent variable: log ISI ). Panels show standardized coefficient on the y-axis and the individual variables on the x-axis (a), mean square error (b), selection criterion Schwarz Bayesian Information Criterion (c), and selection criterion 5-fold Cross Validation (d). 9