Supplemental Information. Weight Gain and Impaired Glucose. Metabolism in Women Are Predicted. by Inefficient Subcutaneous Fat Cell Lipolysis

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1 Cell Metabolism, Volume 28 Supplemental Information Weight Gain and Impaired Glucose Metabolism in Women Are Predicted by Inefficient Subcutaneous Fat Cell Lipolysis Peter Arner, Daniel P. Andersson, Jesper Bäckdahl, Ingrid Dahlman, and Mikael Rydén

2 Weight gain and impaired glucose metabolism in women is predicted by inefficient subcutaneous fat cell lipolysis Peter Arner, Daniel P. Andersson, Jesper Bäckdahl, Ingrid Dahlman, Mikael Rydén Supplemental Tables and Figures Table of contents Table S1 (related to Figure 2). Clinical characteristics in cohort Table S2 (related to Table 1). Reported use of oral pharmaceutical agents in cohort Table S3 (related to Figure 1). Clinical and adipocyte characteristics at second examination in cohort Table S4 (related to Table 2). Prognostic value of fat cell volume Table S5 (related to Figure 2). Influence of fat cell volume on the association between lipolysis and BMI changes Table S6 (related to Figure 4). Genes encoding proteins involved in lipolysis regulation Table S7 (related to Figure 4). TaqMan probes used for qpcr validation Table S8 (related to Figure 5). Relationship between stimulated lipolysis and different parameters in cohort Table S9 (related to Figure 5). Algorithm for estimation of fat cell lipolysis Legends to Supplemental Figures

3 Table S1 (related to Figure 2). Clinical characteristics in cohort 2. Parameter First examination Second examination p-value Age, years 38.9± ± Body weight, 65.4± ± kg BMI, kg/m ± ± P-Glucose, 4.9± ± mmol/l S-Insulin, mu/l 6.4± ± HOMA IR 1.4± ± P-Triglycerides, 0.9± ± mmol/l P-HDLcholesterol, 1.5± ± mmol/l P-Total 5.0± ± cholesterol, mmol/l S-Leptin, ng/ml 11.2± ± Values are mean ± SD and range and compared by paired t-test. Mean body weight increase was 7.6±8.7%. With the exception of two individuals that were on anti-hypertensive treatment at follow-up, none of the subjects were on any regular pharmacotherapy at either the first or second examination. BMI=body mass index. P=fasting plasma. S=fasting serum. HOMA IR =homeostasis model assessment insulin resistance. IFG=impaired fasting glucose. ISO=isoprenaline. 2

4 Table S2 (related to Table 1). Reported use of oral pharmaceutical agents in cohort 1. ID# Group Oral medication at first examination Oral medication at second examination 1 WS WS WS WS WG WS WS WS WS - Losartan 10 WS - Ramipril, low-dose ASA, Omeprazole 11 WS Oral contraceptive - 12 WS - Lamotrigin, Omeprazole 13 WG - Citalopram, Losartan, low-dose ASA, Bisoprolol 14 WS WS - Metformin, Enalapril, Atorvastatin, Cobalamine 16 WS WS - Furosemide, Citalopram 18 WG WS WS - Litium, Levomepromazin 21 WG WG - Enalapril, Desloratidine 23 WS WG - Amiloride/Hydrochlorthiazide 25 WS - Litium, Risperidon 26 WG - Sertraline 27 WS WG WS - Felodipine, Tamoxifen 30 WS - 31 WG - Enalapril, Simvastatin 32 WG - Enalapril 33 WS WS WG WG WS WG - Pravidel, Oral contraceptive 39 WS WG - Clomipramine, Fluoxetine 41 WS Oral contraceptive - 42 WS - Oral contraceptive 3

5 43 WS Oral contraceptive - 44 WG WS - Metformin 46 WG WS WS - Hydrochlorthiazide, Candersartan 49 WS * WG - Candersartan, Folic acid, Potassium chloride, Metoprolol, Mesalazine, Omeprazole, Zolpidem 51 WG WS * WS - Mesalazine, Cholecalciferol/Calcium carbonate, Omeprazole 54 WS - Cholecalciferol, Folic acid, Omeprazole Each row details an individual subjects (ID#), their grouping category (weight stable-ws or weight gain-wg) and reported oral medication at baseline and follow-up examination. *At the second examination, these subjects had been diagnosed with mild Crohn s disease and were on intermittent treatment with Mesalazine which was not considered to influence body weight. 4

6 Table S3 (related to Figure 1). Clinical and adipocyte characteristics at second examination in cohort 1. Second examination Parameter Weight stable Weight gain p-value Body weight, 86± ± 16 < kg BMI, kg/m ± ± 6 < Physical 2.1 ± ± activity, score P-Glucose, 5.6± ± mmol/l S-Insulin, mu/l 10.4±8 19.8± HOMA IR 2.7± ± P-Triglycerides, 0.9± ± mmol/l P-HDLcholesterol, 1.5± ± mmol/l P-Total 4.7± ± cholesterol, mmol/l S-Leptin, ng/ml 44.0 ± ± Fat cell volume, pl Log Basal lipolysis (µmol glycerol/2h/g lipid) Log NA/basal lipolysis Log ISO/basal lipolysis Log dcamp/basal lipolysis Log ISO/NA lipolysis 582± ± ± ± ± ± ± ± ± ± ± ± Values are mean ± SD and range and compared by unpaired t-test. BMI=body mass index. P=fasting plasma. S=fasting serum. HOMA IR =homeostasis model assessment insulin resistance. NA=noradrenaline. ISO=isoprenaline. dcamp=dibutyryl cyclic AMP. 5

7 Table S4 (related to Table 2). Prognostic value of fat cell volume. Parameter OR (Large FCV) CI (95%) p-value Weight gain T2DM/IFG IR Subjects in cohort 1 were subdivided according to median fat cell volume (FCV) at baseline into large or small fat cells. Odds ratios, 95 % confidence intervals and p values using Likelihood ratio test are shown for changes over time in individual clinical parameters. 6

8 Table S5 (related to Figure 2). Influence of fat cell volume on the association between lipolysis and BMI changes. Parameter Delta BMI (r-; p-values) After correction for FCV (Std β-coeff; p-value) Log Basal lipolysis (µmol 0.39; ; glycerol/2h/g lipid) Log NA/Basal lipolysis -0.36; ; Log ISO/Basal lipolysis -0.38; ; Log dcamp/basal lipolysis -035; ; The left column shows r-values; p-values (by simple linear regression analyses) between lipolysis measures and delta BMI as already detailed in Figure 2. The right column shows standardized beta coefficients; p-values for individual lipolysis measures and delta BMI following multiple regression analyses correcting for baseline fat cell volume (FCV) as a continuous variable. 7

9 Table S6 (related to Figure 4). Genes encoding proteins involved in lipolysis regulation. Feature ID Gene symbol TC hg.1 ABCA1 TC hg.1 ABCG1 TC hg.1 ABHD5 TC hg.1 ADCY1 TC hg.1 ADCY2 TC hg.1 ADCY3 TC hg.1 ADCY4 TC hg.1 ADCY5 TC hg.1 ADCY6 TC hg.1 ADCY7 TC hg.1 ADCY9 TC hg.1 ADORA1 TC hg.1 ADRA2A TC hg.1 ADRA2B TC hg.1 ADRA2C TC hg.1 ADRB1 TC hg.1 ADRB2 TC hg.1 ADRB3 TC hg.1 AQP7 TC hg.1 CAV1 TC hg.1 CAV2 TC hg.1 CIDEA TC hg.1 CIDEC TC hg.1 EDNRA TC hg.1 EDNRB TC hg.1 FABP4 TC hg.1 GNAI1 TC hg.1 GNAI2 TC hg.1 GNAI3 TC hg.1 GNAT1 TC hg.1 GNAT2 TC hg.1 GNB1 TC hg.1 GNB2 TC hg.1 GNB3 TC hg.1 GNG10 TC hg.1 GNG11 TC hg.1 GNG12 TC hg.1 GNG2 TC hg.1 GNG3 TC hg.1 GNG5 TC hg.1 GNG7 TC hg.1 GNG8 TC hg.1 IGF1R 8

10 TC hg.1 IL6R TC hg.1 INSR TC hg.1 LIPE TC hg.1 MGLL TC hg.1 NPR1 TC hg.1 NPR3 TC hg.1 NPY1R TC hg.1 PDE3B TC hg.1 PDE5A TC hg.1 PLIN1 TC hg.1 PLIN2 TC hg.1 PLIN3 TC hg.1 PNPLA2 TC hg.1 PPARG TC hg.1 PRKAA1 TC hg.1 PRKAA2 TC hg.1 PRKAR1A TC hg.1 PRKAR1A TC hg.1 PRKAR2A TC hg.1 PRKAR2B TC hg.1 PRKG1 TC hg.1 PRKG2 TC hg.1 PTGER3 TC hg.1 SREBF1 TC hg.1 TNFRSF1A A list of 67 individual genes involved in lipolysis regulation was compiled based on the work by Langin and co-workers as detailed in the Supplemental Information. Microarray probe sets (Feature ID) for each corresponding gene are listed. Please note that PRKAR1A is detected by two probe sets. 9

11 Table S7 (related to Figure 4). TaqMan probes used for qpcr validation. Gene Assay LRP10 Hs _m1 GNG12 Hs _m1 PRKAR2B Hs _m1 MGLL Hs _m1 FABP4 Hs _m1 AQP7 Hs _m1 10

12 Table S8 (related to Figure 5). Relationship between stimulated lipolysis and different parameters in cohort 3. Variable r-value p-value Waist circumference* 0.37 < P-HDL cholesterol* 0.36 < P-Adrenaline* Body weight* 0.51 < S-Insulin log value* < Lipolysis index*# 0.48 < P-Noradrenaline Hip circumference < Waist-to-hip ratio <0.001 Height Body fat < Body mass index < P-Total cholesterol P-Triglycerides S-Leptin <0.001 P-Glucose <0.001 P-Glycerol Age Log isoprenaline/basal lipolysis was compared with different clinical and clinical chemistry variables using simple regression analysis in cohort 3. R- and p-values are shown for each parameter. *=used in algorithm, # P-glycerol divided by body fat. P=fasting plasma, S=fasting serum. 11

13 Table S9 (related to Figure 5). Algorithm for estimation of fat cell lipolysis. Term Estimate Std Error t Ratio Prob> t Std Beta Intercept < Waist (cm) < HDL-Cholesterol (mmol/l) P-Adrenaline (nmol/l) Body weight (kg) Lipolysis index log S-Insulin A multiple regression model was used to predict log isoprenaline/basal lipolysis based on fat cell and clinical data available from 226 out of 1045 subjects. The variables that contributed to the model are listed including p-values and standardized beta coefficients. P=fasting plasma, S=fasting serum. 12

14 Legends to Supplemental Figures Figure S1. (related to Figure 2). Relationship between lipolysis and changes in body weight over time. A-E. Graphs show the relationship between changes in body weight (delta kg) vs log isoprenaline/basal (A), log noradrenaline/basal (B), log dibutyryl cyclic AMP/basal (C) log basal expressed as glycerol release per gram lipids (µmol glycerol/2h/g lipid) (D) and log basal expressed per number of cells (E) at baseline in cohort 1. F-G. A similar association between delta kg and log isoprenaline/basal (F) or log basal/g lipid (µmol glycerol/2h/g lipid) (G) at baseline as in cohort 1 was observed in cohort 2. NA=noradrenaline, ISO=isoprenaline, dcamp=dibutyryl cyclic AMP. Linear regression was used, r- and p-values are shown. Open circles denote WG and black dots WS in cohort 1. Figure S2 (related to Figure 2). No associations between BMI changes and lipolysis measures at follow-up examination. A-D. In cohort 1 there was no association between delta BMI and log isoprenaline/basal (A), log basal expressed per gram lipid (µmol glycerol/2h/g lipid) (B), log noradrenaline/basal (C) and log dibutyryl cyclic AMP/basal (D) at the second examination. E-F. A similar lack of association between delta BMI and log isoprenaline /basal (E) or log basal/g lipid (µmol glycerol/2h/g lipid) (F) at follow-up were observed in cohort 2. See legend to Figure S1 for abbreviations. Figure S3 (related to Figure 3). Lipolysis measures and RQ in cohort 3. A-D. RQ measures were available in 363 subjects from cohort 3. There was no association between RQ and log isoprenaline/basal (A), log noradrenaline/basal (B), log basal expressed either per gram lipid (µmol glycerol/2h/g lipid) (C) or number of fat cells (10 7 cells) (D). See legend to Figure S1 for abbreviations. Figure S4 (related to Figure 4). Changes in lipolysis measures over time. A-F. All subjects in cohort 1 were combined and lipolysis measures at baseline and follow-up were compared. There was a significant reduction in log basal lipolysis expressed per gram lipid 13

15 (µmol glycerol/2h/g lipid) (A) or per cells (10 7 cells) (B). The observation that log noradrenaline/basal did not change (C) while both log isoprenaline/basal (D) and log dibutyryl cyclic AMP/basal (E) increased suggested an increase in both beta- and alpha2a adrenoceptor signaling/activity which balanced each other out. An increased alpha2a effect was confirmed by the log isoprenaline/noradrenaline ratio which increased over time (F). Values are mean±standard error of the mean and compared by paired t-test. See legend to Figure S1 for abbreviations. Figure S5 (related to Figure 4). Association between lipolysis measures and weight change in subjects where gene expression was not analyzed. In 16 individuals of cohort 1, samples for gene expression analyses were not available. However, the relationship between log isoprenaline/basal and log basal lipolysis was similar for delta BMI (A-B) and delta kg (C-D) as for the whole cohort. ISO=isoprenaline. Linear regression was used, r- and p-values are shown. 14

16 Figure S1 A B C r=-0.38, p=0.005 r=-0.36, p=0.01 r=-0.35, p=0.01 D E r=0.39, p=0.004 r=0.38, p=0.004 F r=-0.49, p=0.014 G r=0.57, p=0.003

17 Figure S2 A B C D E F

18 Figure S3 A B C D

19 Figure S4 A B C D E F

20 Figure S5 A B C D