Understanding phenotypes of prediabetes: essential to influencing progression to type 2 diabetes. October 2015; SAGLB.DIA

Understanding phenotypes of prediabetes: essential to influencing progression to type 2 diabetes October 2015; SAGLB.DIA.15.10.0821

Acknowledgement The content of this slide deck summarizes the key points presented during the 47 th Claude Bernard lecture by Professor Hans-Ulrich Häring at the 51 st Annual Meeting of the European Association for the Study of Diabetes, Sept 14 18 2015, Stockholm, Sweden

Summary of content Introduction Background and overview of The TÜbingen Family Study (TÜF) and The TÜbingen lifestyle intervention programme (TULIP) Genetic mechanisms in the pathogenesis of diabetes Summary of findings from Tübingen investigators on genes involved with regulating insulin secretion in the face of increased insulin resistance Sub-phenotypes of obesity What are the differences between metabolically healthy and metabolically unhealthy obese individuals? Brain insulin resistance Summary of early findings related to brain insulin resistance as a risk factor for diabetes Conclusions

Introduction

Insulin secretion The TÜF includes data from >3,000 individuals at risk of developing T2DM 1 NGT NGT T2DM IGT NGT Insulin sensitivity IGT, impaired glucose tolerance; NGT, normal glucose tolerance; T2DM, type 2 diabetes mellitus, TÜF, TÜbingen Family Study The population shows a wide variety of phenotypes. Those with insulin resistance and low insulin secretion may develop IGT and then T2DM. Some individuals are able to counteract increasing insulin resistance by upregulating insulin secretion 1 1. Data presented by Häring HU at EASD 2015 (Claude Bernard Lecture; available at easdvirtualmeeting.org)

The TÜF is a clinical phenotyping programme identifying risk factors for diabetes 1 Brain Pancreas Liver Adipose tissue Skeletal tissue The data available from the TÜF are enabling investigation of the mechanisms occurring in key organs that lead to IGT and T2DM 1 1. Data presented by Häring HU at EASD 2015 (Claude Bernard Lecture; available at easdvirtualmeeting.org)

TULIP is investigating the impact of lifestyle interventions 1,2-5 % Increased physical activity TULIP, TÜbingen Lifestyle Intervention Programme Weight loss Healthier diet TULIP is an ongoing study of the effect of a 9-month individualized lifestyle intervention programme. 1,2 Data were presented for an 8-year follow-up of 400 people who also participated in the TÜF 3 1. Giel KE, et al. Diabetes Metab Rev 2009;25:83 8; 2. Stefan N et al. Diabetologia 2015;ePub ahead of print; 3. Data presented by Häring HU at EASD 2015 (Claude Bernard Lecture; available at easdvirtualmeeting.org)

TULIP: Lifestyle intervention was initially effective 1 Insulin secretion 12 months after initial intervention Insulin secretion Insulin sensitivity Insulin sensitivity NGT IGT In individuals with impaired glucose tolerance, moderate weight loss lead to significant reductions in total, visceral and ectopic fat, increased insulin sensitivity and improved glucose tolerance 1 1. Schäfer S et al. Eur J Clin Invest 2007;37:535 43

Despite the initial effectiveness of lifestyle intervention, insulin resistance was increasing after eight years 1 Insulin sensitivity 8 years after initial intervention Insulin sensitivity Insulin secretion Insulin secretion NGT IGT Those with normal insulin sensitivity at baseline were able to counter increasing insulin resistance with compensatory hypersecretion of insulin; however, those who had insulin resistance at baseline could not compensate and went on to develop IGT or T2DM 1 1. Data presented by Häring HU at EASD 2015 (Claude Bernard Lecture; available at easdvirtualmeeting.org)

Key questions raised by the TÜbingen studies What is pushing people towards insulin resistance over time? What enables some people to counteract increased insulin resistance by upregulating insulin secretion: Genetic mechanisms? Sub-phenotypes of obesity? Brain insulin resistance?

Phenotypes observed in pre-diabetes

Key questions raised by the TÜbingen studies What enables some people to counteract increased insulin resistance by upregulating insulin secretion: Genetic mechanisms?

Many potential genes have been identified over recent years, but none have a high odds ratio for predicting type 2 diabetes TSPAN8/ LGR5 2 HNF1B 4 WFS1 6 IGF2BP2 8,9 KCNJ11 8,11,12 THADA 14 HHEX/IDE 3,9,11,12,16,17 CKDN2B 18 TCF7L2 3,8,10,11,16, 19 23 ADAMTS9 1 JAZE1 3 CDC123/C AMK1D 5 NOTCH2 7 CDKAL1 10 PPARG 12,13 SLC30A8 9 FTO 12 KCNQ1 11,12,17 Odds ratio for predicting T2DM TCF7L2, transcription factor 7-like 2 (T-cell specific, high mobility group box) TCF7L2 is a transcription factor influencing the transcription of several genes. Of the genes investigated, TCF7L2 had the highest odds ratio of 1.37 per effect allele for predicting type 2 diabetes 18 1. Staiger H, et al. PLoS One 2008;3:e3019; 2. The Wellcome Trust Case Control Consortium. Nature 2010;464:713 20; 3. Haupt A, et al. JCEM 2009;94:1775 80; 4. Goda N, et al. BMC Med Genet 2015;16:75; 5. Simonis-Bik AM, et al. Diabetes 2010;59:293 301; 6. Schäfer SA, et al. Diabetologia 2009;52:1075 82; 7. Tam CH, et al. PLoS ONE 2013;8:e83093; 8. Groenewoud MJ, et al. Diabetologia 2008;51:1659 63; 9. t Hart LM, et al. Diabetes 2010;59:287 92; 10. Stancáková A, et al. JCEM 2008;93:1924 30; 11. Heni J, et al. Diabetes 2010;59:3247 52; 12. Linder K, et al. PLoS One 2012;7:e38224; 13. Parikh H, et al. BMC Medical Genomics 2009;2:72; 14. Boesgaard TW, et al. Diabetologia 2008;51:816 20; 15. Staiger H, et al. Diabetes 2008;57:514 7; 16. Haupt A, et al. Diabetologia 2009;52:457 62; 17. Müssig K, et al. Diabetes 2009;7:1715 20; 18. Data presented by Häring HU at EASD 2015 (Claude Bernard Lecture; available at easdvirtualmeeting.org); 19. Schäfer S, et al. Diabetologia 2007;50:2443 50; 20. Haupt A, et al. Diabetes 2010;9:747 50; 21. Heni M, et al. Diabetes Care 2012;35:e24; 22. Wagner R, et al. Sci Rep 2014;4:5296; 23. Wagner R, et al. Mol Metab 2014;3:261 7

Insulin sensitivity First phase insulin ( M) Genetic effects do not fully explain regulation of insulin secretion 1 20 2000 18 16 14 12 1800 1600 1400 1200 1000 10 1 2 3 4 5 6 7 Number of risk alleles 800 The combined effect of all of the genes investigated by the TÜbingen investigators was significant, but the effect size only accounted for ~10 15% of the observed differences in insulin secretion between those with NGT and those with IGT 1 1. Haupt A et al. J Clin Endocrinol Metab. 2009;94:1775 80

The TCF7L2 gene has the strongest association with type 2 diabetes 1 and is related to incretin resistance 2 Blood glucose (mmol/l) Insulin (pmol/l) 10,000 AIR arginine p=0.40 8,000 6,000 4,000 2,000 0 12 11 10 9 8 7 6 5 4 1st phase p=0.18 2nd phase p=0.80 Hyperglycaemia 2nd phase GLP-1 p=0.006 1st phase GLP-1 p=0.03 GLP-1 Arginine (5g) Open circles homozygous wild-type Closed circles heterozygous and homozygous variants with TCF7L2 gene GLP-1, glucagon-like peptide 1 50 0 50 100 150 200 250 Time (min) Hyperglycemic clamp studies show that wild-type individuals have 2-fold higher insulin secretion in response to GLP-1 infusion than those with the TCF7L2 gene 2 1. Wagner R et al. Mol Metab 2014;3:261 7; 2. Image adapted from Schäfer S et al. Diabetologia 2007

Insulin 30 min (pmol/l) log e -scale The TCF7L2 gene is also associated with compensatory hypersecretion 1 2980 TCFL7L2 P add <0.0001 P rec <0.0001 403 55 CC CT TT 7.4 2.7 7.4 20 Glucose 30 min (mmol/l) log e -scale In individuals who were homozygous for the TCF7L2 gene (TT), compensatory hypersecretion of insulin does not occur; however, it does in those who of heterozygous (CT) or do not have the gene (TT) 1 1. Heni M et al. Diabetes 2010;59:3247 52

Key questions raised by the TÜbingen studies What enables some people to counteract increased insulin resistance by upregulating insulin secretion: Sub-phenotypes of obesity?

Key questions raised by the TÜbingen studies What enables some people to counteract increased insulin resistance by upregulating insulin secretion: Sub-phenotypes of obesity? Metabolically healthy versus metabolically unhealthy

Metabolically healthy and metabolically unhealthy phenotypes of obesity have been identified 1,2 Subcutaneous fat Subcutaneous fat Liver fat Liver fat Visceral fat Visceral fat Skeletal muscle fat Skeletal muscle fat Metabolically healthy obesity Metabolically unhealthy obesity Metabolically healthy obese people tend to have high levels of subcutaneous fat and little visceral fat and are able to maintain insulin sensitivity; the opposite is true in metabolically unhealthy obese individuals 1,2 1. Stefan N et al. Arch Intern Med 2008;168:1609 16 2. Stefan N et al. Lancet Diabet Endocrinol 2013;1:152 62

Liver fat also affects metabolic health in obesity 1 Genetic predisposition towards liver fat in obesity Fatty acid pattern TLR-4 Benign fatty liver Immune cell Minimal effect PNPLA3, patatin-like phospholipase domain-containing protein 3; TLR4, toll-like receptor 4 Some obese individuals have a metabolically healthy benign fatty liver with limited lipotoxicity. In this scenario, PNPLA3 is still secreted from the liver and TLR4 is not affected 1 1. Stefan N and Häring HU. Nat Rev Endocrinol 2013;9:144 52

Liver fat also affects metabolic health in obesity 1 Genetic predisposition Fatty acid pattern Fetuin-A TLR-4 Benign fatty liver Malign fatty liver TLR-4 Immune cell Minimal effect Normal Micro-inflammation Localised insulin resistance Peripheral insulin resistance Immune cell Those with a metabolically unhealthy malign fatty liver have ectopic fat storage in the liver, which is associated with micro-inflammation and increased insulin resistance, and thought to be related to secretion of fetuin-a 1 1. Stefan N and Häring HU. Nat Rev Endocrinol 2013;9:144 52

Cross-talk between Fetuin-A, free-fatty acids, hepatocytes and immune cells in the liver may decrease the effect of TLR4 1,2 Insulin sensitivity (x 10 15 L 2 mol -2 OGTT, adjusted, log scale) 54.60 33.12 20.09 12.18 7.39 4.48 2.72 High FFA concentrations β = 1.35 P <0.0001 1.65 122 148 181 221 270 330 403 493 Fetuin-A (µg ml -1 log scale) Based on mouse studies 1, the TÜbingen investigators think that this may be leading to increased insulin resistance in the liver 2. This theory is unproven but there is some evidence to suggest that it is a valid theory 1. Pal D et al. Nature Med 2012;18:1279 85; 2. Stefan N and Häring HU. Nature Med 2013;19:934 95

Key questions raised by the TÜbingen studies What enables some people to counteract increased insulin resistance by upregulating insulin secretion: Sub-phenotypes of obesity? Presence of pancreatic fat

Expression (fold change) Expression (fold change) Expression (fold change) Pancreatic fat is thought to be similar to perivascular fat 1,2 40 30 IL6 mrna ** 35 30 25 IL8 mrna ** 8 6 MCP-1 mrna ** 20 20 15 4 10 10 5 2 0 C F+P F+P +inhibitor* 0 C F+P F+P +inhibitor* 0 C F+P F+P +inhibitor* C, control; F + P, 24 hours after treatment with 600 μg/ml fetuin + 50 μmol/l palmitate. *3 μmol/l TLR4 inhibitor CLI-095 Perivascular fat cells secrete high levels of interleukin (IL)-6, IL-8 and MCP-1 in the presence of Fetuin-A and palmitate 1. These characteristics are also present in pancreatic fat cells 2. 1. Image adapted from Siegel-Axel DI et al. Diabetologia 2014;57:1057 66; 2. Data presented by Häring HU at EASD 2015 (Claude Bernard Lecture; available at easdvirtualmeeting.org)

Pancreatic fat was unexpectedly observed in the TÜF and it correlated with insulin secretion in people with IGT 1 This unexpected finding has been observed in ~250 people participating in the TÜF 2 Pancreatic fat content was significantly and negatively associated with insulin secretion (C-peptide-based index: p=0.0002; r= 0.70) in people with impaired glucose tolerance but not in people with normal glucose tolerance (C-peptide-based index: p=1.0; r=0.00) 1 The fat substrate is unknown Fatty liver Fetuin-A Adipocytes Beta-cells The clusters of fat cells in the pancreas lie close to or in contact with the islets, and are associated with increased macrophage infiltration. 3 People with a fatty pancreas also have a fatty liver 2, and there is evidence that fetuin-a may be mediating cross-talk between the fatty liver and pancreatic fat cells 4 8 1. Heni M et al. Diabetes Metab Res Rev 2010;26:200 5; 2. Data presented by Häring HU at EASD 2015 (Claude Bernard Lecture; available at easdvirtualmeeting.org); 3. Data presented by Gerst F at EASD 2015 (Oral Presentation #92; available at easdvirtualmeeting.org); 4. Hennige et al. Diabetes 2010; 5. Wagner et al. Diabetes 2013; 6. Teutsch et al. Diabetologia 2014; 7. Wagner et al. Mol Metab 2014; 8. Gerst et al. Diabetologia 2015;58(Suppl. 1):S45 Islet

Insulinogenic index (pm/mm, adjusted, log scale) Fetuin-A levels correlate with insulin secretion in this population 665 403 245 148 90 55 33 IGT r = 0.37 P = 0.0004 20 122 148 181 221 270 330 403 493 Fetuin-A (µg ml -1 log scale) This also supports the validity of the hypothesis of Fetuin-A mediated cross-talk between the fatty pancreas and fatty liver 1. Image adapted from Stefan et al. PloS One 2014;9:e92238

Key questions raised by the TÜbingen studies What enables some people to counteract increased insulin resistance by upregulating insulin secretion: Sub-phenotypes of obesity? Exercise responders versus non-responders

TULIP: Presence of liver fat is one of the strongest indicators of people that will not respond to lifestyle intervention* 1 Epigenetics Fatty liver Plasma Muscle cells *Lifestyle intervention included modifications to dietary intake and composition, as well as three or more hours of moderate exercise per week Exercise is one of the most successful methods for reducing liver fat, and reductions of~30 40% can be attained in exercise responders. 2,3 Reducing liver fat is more difficult in exercise non-responders (~25% of the TULIP population) 1 1. Stefan N et al. Diabetologia 2015; epub ahead of print; 2. Kantartzis K et al. Gut 2009;58:1281 8; 3. Kantartzis K et al. Diabetologia 2011;54:864 8

Exercise non-responders have different mitochondrial activity compared with responders 1,2 PPARD PPARGCIA Genetic variants of PPARD and PPARGCIA are associated with response to exercise and mitochondrial function Improvements in anaerobic threshold Muscle growth Changes in adiposity Reductions in liver fat storage Improvements in insulin sensitivity TGF, transforming growth factor; PGC-1, peroxisome proliferator-activated receptor gamma co-activator 1 The TÜbingen investigators have not identified any exercise-response plasma biomarkers, but have observed different levels of TGF-beta regulation. TGF-beta seems to interact with PGC-1 alpha expression and links exercise response to differences in mitochondrial activities 1. Thamer C et al. J Clin Endrocinol Metab 2008;93:1497 500; 2. Stefan N et al. J Clin Endocrinol Metab 2007;92:1827 33

Key questions raised by the TÜbingen studies What enables some people to counteract increased insulin resistance by upregulating insulin secretion: Brain insulin resistance?

Insulin receptors in the brain control energy homeostasis and food intake/reward mechanisms 1 Hippocampus Memory formation Prefrontal area Integration of sensory information Inhibitory control of eating Fusiform gyrus Object recognition (including food) Processing of positive emotions Reward Hypothalamus Central regulator of whole-body energy homeostasis Homeostatic control of food intake It is thought that brain insulin resistance leads to problems with eating control because the desire to continue eating after food ingestion is not down-regulated 1 1. Image adapted from Heni M et al. Nat Rev Endocrinol 2015; epub ahead of print

Brain insulin signalling is also thought to play a role in fuel distribution through the tissues in the body 1 Subcutaneous fat Subcutaneous fat Liver fat Liver fat Visceral fat Visceral fat Skeletal muscle fat Skeletal muscle fat Metabolically healthy obesity Metabolically unhealthy obesity Research in mice suggests that the brain determines glucose uptake in the periphery. This suggests that in people with brain insulin resistance, glucose deposition in visceral adipose tissue may be favoured over subcutaneous deposition 1 1. Heni M et al. Nat Rev Endocrinol 2015; epub ahead of print

Foetal imaging is allowing investigation of brain insulin sensitivity in-utero 1 The foetus can hear and react to tones applied to the stomach of the mother, and the velocity of brain reactions to the tone can be measured. Latencies in response to glucose intake provide insights into the brain-insulin sensitivity of the foetus 1 1. Linder K et al. Diabetologia 2014;57:1192 8

Insulin (pmol/l) Latency (ms) Insulin sensitivity has been observed in-utero, challenging the assumption that brain insulin sensitivity occurs as a response to obesity 1,2 Effect of OGTT in insulin sensitive or insulin resistant mothers Mother Fetus 1250 350 1000 Resistant 300 Resistant * 750 250 500 250 Sensitive 200 Sensitive 0 0 60 120 Time after OGTT OGTT, oral glucose tolerance test 150 0 60 120 Time after OGTT In insulin sensitive mothers, latency in the fetal brain response decreases when glucose levels are at their highest (~60 mins after an OGTT), but this response does not occur in the fetus of insulin resistant mothers 1. The effect is even more pronounced in mothers with gestational diabetes 2 1.Images adapted from Linder K et al. Diabetologia 2014;57:1192 8; 2. Linder K et al. JCEM 2015; epub ahead of print

Conclusions

Consequences for prevention of type 2 diabetes Sub-phenotypes determine the success of prevention methods, such as lifestyle intervention Lifestyle non-responders should be treated according to their phenotype and may need therapeutic intervention Type 2 diabetes prevention needs to start early in life, with a focus on the gestational period Studies are required to investigate and develop pharmacological interventions to treat fatty liver, fatty pancreas, exercise non-response and brain insulin resistance

Future studies The TÜbingen investigators are interested in future studies focusing on: The fatty liver and the fatty pancreas How do they affect compensatory hypersecretion? How do they affect beta-cell dysfunction? Can beta-cell dysfunction be reversed by treating the fatty liver and/or fatty pancreas? Brain insulin resistance How early in life does it start? Is it a consequence of obesity? Does it lead to obesity? Can we establish new preventative measures for type 2 diabetes?

Further information To view the webcast of Professor Hans-Ulrich Häring s Claude Bernard lecture, copy the following link into your browser: http://www.easdvirtualmeeting.org/resources/understanding- phenotypes-of-prediabetes-essential-to-influencing-progression-to-type- 2-diabetes Notable related presentations at EASD 2015 were: The hepatokine fetuin-a has TLR4 dependent and independent effects in islets (F. Gerst) Webcast available at: http://www.easdvirtualmeeting.org/resources/the-hepatokine-fetuin-a-has-tlr4- dependent-and-independent-effects-in-islets Rising Star Symposium presentation: Insulin and the human brain (M. Heni) Webcast available at: http://www.easdvirtualmeeting.org/resources/insulin-and-the-human-brain All links last accessed November 10 th 2015