Diabetologia

, Volume 60, Issue 12, pp 2341–2351 | Cite as

Non-alcoholic fatty liver disease and impaired proinsulin conversion as newly identified predictors of the long-term non-response to a lifestyle intervention for diabetes prevention: results from the TULIP study

  • Vera Schmid
  • Robert Wagner
  • Corinna Sailer
  • Louise Fritsche
  • Konstantinos Kantartzis
  • Andreas Peter
  • Martin Heni
  • Hans-Ulrich Häring
  • Norbert Stefan
  • Andreas Fritsche
Article

Abstract

Aims/hypothesis

Lifestyle intervention is effective to prevent type 2 diabetes. However, a considerable long-term non-response occurs to a standard lifestyle intervention. We investigated which risk phenotypes at baseline and their changes during the lifestyle intervention predict long-term glycaemic non-response to the intervention.

Methods

Of 300 participants at high risk for type 2 diabetes who participated in a 24 month lifestyle intervention with diet modification and increased physical activity, 190 participants could be re-examined after 8.7 ± 1.6 years. All individuals underwent a five-point 75 g OGTT and measurements of body fat compartments and liver fat content with MRI and spectroscopy at baseline, 9 and 24 months during the lifestyle intervention, and at long-term follow-up. Fasting proinsulin to insulin conversion (PI/I ratio) and insulin sensitivity and secretion were calculated from the OGTT. Non-response to lifestyle intervention was defined as no decrease in glycaemia, i.e. no decrease in AUC for glucose at 0–120 min during OGTT (AUCglucose0–120 min).

Results

Before the lifestyle intervention, 56% of participants had normal glucose regulation and 44% individuals had impaired fasting glucose and/or impaired glucose tolerance. At long-term follow-up, 11% had developed diabetes. Multivariable regression analysis with adjustment for age, sex, BMI and change in BMI during the lifestyle intervention revealed that baseline insulin secretion and insulin sensitivity, as well as change in insulin sensitivity during the lifestyle intervention, predicted long-term glycaemic control after 9 years. In addition, increased hepatic lipid content as well as impaired fasting proinsulin conversion at baseline were newly detected phenotypes that independently predicted long-term glycaemic control.

Conclusions/interpretation

Increased hepatic lipid content and impaired proinsulin conversion are new predictors, independent of change in body weight, for non-response to lifestyle intervention in addition to the confirmed factors, impaired insulin secretion and insulin sensitivity.

Keywords

Fatty liver Insulin secretion Insulin sensitivity Lifestyle intervention Prediabetes Predictors Proinsulin 

Abbreviations

AUCglucose0–120 min

AUC for glucose at 0–120 min during OGTT

DPP

Diabetes Prevention Program

DPPOS

Diabetes Prevention Program Outcome Study

DPS

Diabetes Prevention Study

1H-MRS

Proton magnetic resonance spectroscopy

IFG

Impaired fasting glucose

IGT

Impaired glucose tolerance

IGI

Insulinogenic index

ISI

Insulin sensitivity index

NAFLD

Non-alcoholic fatty liver disease

PI/I ratio

Proinsulin/insulin ratio

SCAT

Subcutaneous adipose tissue

TAT

total adipose tissue

TULIP

Tübingen Lifestyle Intervention Program

VAT

Visceral adipose tissue

Supplementary material

125_2017_4407_MOESM1_ESM.pdf (322 kb)
ESM Table 1(PDF 321 kb)

References

  1. 1.
    Tuomilehto J, Lindström J, Eriksson JG et al (2001) Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med 344:1343–1350CrossRefPubMedGoogle Scholar
  2. 2.
    Lindström J, Ilanne-Parikka P, Peltonen M et al (2006) Sustained reduction in the incidence of type 2 diabetes by lifestyle intervention: follow-up of the Finnish Diabetes Prevention Study. Lancet 368:1673–1679CrossRefPubMedGoogle Scholar
  3. 3.
    Knowler WC, Barrett-Connor E, Fowler SE et al (2002) Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 346:393–403CrossRefPubMedGoogle Scholar
  4. 4.
    Diabetes Prevention Program Research Group, Knowler WC, Fowler SE et al (2009) 10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study. Lancet 374:1677–1686CrossRefPubMedCentralGoogle Scholar
  5. 5.
    Pan XR, Li GW, Hu YH et al (1997) Effects of diet and exercise in preventing NIDDM in people with impaired glucose tolerance. The Da Qing IGT and Diabetes Study. Diabetes Care 20:537–544CrossRefPubMedGoogle Scholar
  6. 6.
    Li G, Zhang P, Wang J et al (2008) The long-term effect of lifestyle interventions to prevent diabetes in the China Da Qing Diabetes Prevention Study: a 20-year follow-up study. Lancet 371:1783–1789CrossRefPubMedGoogle Scholar
  7. 7.
    Lindström J, Peltonen M, Eriksson JG et al (2013) Improved lifestyle and decreased diabetes risk over 13 years: long-term follow-up of the randomised Finnish Diabetes Prevention Study (DPS). Diabetologia 56:284–293CrossRefPubMedGoogle Scholar
  8. 8.
    Ramachandran A, Snehalatha C, Mary S et al (2006) The Indian Diabetes Prevention Programme shows that lifestyle modification and metformin prevent type 2 diabetes in Asian Indian subjects with impaired glucose tolerance (IDPP-1). Diabetologia 49:289–297CrossRefPubMedGoogle Scholar
  9. 9.
    Schwarz PE, Greaves CJ, Lindström J et al (2012) Nonpharmacological interventions for the prevention of type 2 diabetes mellitus. Nat Rev Endocrinol 8:363–373PubMedGoogle Scholar
  10. 10.
    Kantartzis K, Thamer C, Peter A et al (2009) High cardiorespiratory fitness is an independent predictor of the reduction in liver fat during a lifestyle intervention in non-alcoholic fatty liver disease. Gut 58:1281–1288CrossRefPubMedGoogle Scholar
  11. 11.
    Häring H-U (2016) Novel phenotypes of prediabetes? Diabetologia 59:1806–1818Google Scholar
  12. 12.
    Ferrannini E (2014) Definition of intervention points in prediabetes. Lancet Diabetes Endocrinol 2:667–675CrossRefPubMedGoogle Scholar
  13. 13.
    Kahn SE, Cooper ME, Del Prato S (2014) Pathophysiology and treatment of type 2 diabetes: perspectives on the past, present, and future. Lancet 383:1068–1083CrossRefPubMedGoogle Scholar
  14. 14.
    Stefan N, Fritsche A, Schick F, Häring H-U (2016) Phenotypes of prediabetes and stratification of cardiometabolic risk. Lancet Diabetes Endocrinol 4:789–798CrossRefPubMedGoogle Scholar
  15. 15.
    Stefan N, Staiger H, Wagner R et al (2015) A high-risk phenotype associates with reduced improvement in glycaemia during a lifestyle intervention in prediabetes. Diabetologia 58:2877–2884CrossRefPubMedGoogle Scholar
  16. 16.
    Kitabchi AE, Temprosa M, Knowler WC et al (2005) Role of insulin secretion and sensitivity in the evolution of type 2 diabetes in the diabetes prevention program: effects of lifestyle intervention and metformin. Diabetes 54:2404–2414CrossRefPubMedGoogle Scholar
  17. 17.
    Abdul-Ghani MA, Williams K, DeFronzo RA, Stern M (2007) What is the best predictor of future type 2 diabetes? Diabetes Care 30:1544–1548CrossRefPubMedGoogle Scholar
  18. 18.
    Lyssenko V, Almgren P, Anevski D et al (2005) Predictors of and longitudinal changes in insulin sensitivity and secretion preceding onset of type 2 diabetes. Diabetes 54:166–174CrossRefPubMedGoogle Scholar
  19. 19.
    de Mello VDF, Lindström J, Eriksson J et al (2012) Insulin secretion and its determinants in the progression of impaired glucose tolerance to type 2 diabetes in impaired glucose-tolerant individuals: the Finnish Diabetes Prevention Study. Diabetes Care 35:211–217CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Perreault L, Pan Q, Mather KJ et al (2012) Effect of regression from prediabetes to normal glucose regulation on long-term reduction in diabetes risk: results from the Diabetes Prevention Program Outcomes Study. Lancet 379:2243–2251CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Perreault L, Kahn SE, Christophi CA et al (2009) Regression from pre-diabetes to normal glucose regulation in the diabetes prevention program. Diabetes Care 32:1583–1588CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Wareham NJ, Byrne CD, Williams R et al (1999) Fasting proinsulin concentrations predict the development of type 2 diabetes. Diabetes Care 22:262–270CrossRefPubMedGoogle Scholar
  23. 23.
    Pfützner A, Kunt T, Hohberg C et al (2004) Fasting intact Proinsulin is a highly specific predictor of insulin resistance in type 2 diabetes. Diabetes Care 27:682–687CrossRefPubMedGoogle Scholar
  24. 24.
    Mykkänen L, Zaccaro DJ, Hales CN et al (1999) The relation of proinsulin and insulin to insulin sensitivity and acute insulin response in subjects with newly diagnosed type II diabetes: the Insulin Resistance Atherosclerosis Study. Diabetologia 42:1060–1066CrossRefPubMedGoogle Scholar
  25. 25.
    Bergman RN, Finegood DT, Kahn SE (2002) The evolution of β-cell dysfunction and insulin resistance in type 2 diabetes. Eur J Clin Investig 32:35–45CrossRefGoogle Scholar
  26. 26.
    Kahn SE (2000) The importance of the beta-cell in the pathogenesis of type 2 diabetes mellitus. Am J Med 108(Suppl 6a):2S–8SCrossRefPubMedGoogle Scholar
  27. 27.
    Hanley AJG, D’Agostino R, Wagenknecht LE et al (2002) Increased proinsulin levels and decreased acute insulin response independently predict the incidence of type 2 diabetes in the Insulin Resistance Atherosclerosis Study. Diabetes 51:1263–1270CrossRefPubMedGoogle Scholar
  28. 28.
    Loopstra-Masters RC, Haffner SM, Lorenzo C et al (2011) Proinsulin-to-C-peptide ratio versus proinsulin-to-insulin ratio in the prediction of incident diabetes: the Insulin Resistance Atherosclerosis Study (IRAS). Diabetologia 54:3047–3054CrossRefPubMedGoogle Scholar
  29. 29.
    Zethelius B, Byberg L, Hales CN et al (2003) Proinsulin and acute insulin response independently predict type 2 diabetes mellitus in men—report from 27 years of follow-up study. Diabetologia 46:20–26CrossRefPubMedGoogle Scholar
  30. 30.
    Pfützner A, Pfützner AH, Larbig M, Forst T (2004) Role of intact Proinsulin in diagnosis and treatment of type 2 diabetes mellitus. Diabetes Technol Ther 6:405–412CrossRefPubMedGoogle Scholar
  31. 31.
    Uusitupa M, Lindi V, Louheranta A et al (2003) Long-term improvement in insulin sensitivity by changing lifestyles of people with impaired glucose tolerance: 4-year results from the Finnish Diabetes Prevention Study. Diabetes 52:2532–2538CrossRefPubMedGoogle Scholar
  32. 32.
    Yoshioka N, Kuzuya T, Matsuda A, Iwamoto Y (1989) Effects of dietary treatment on serum insulin and Proinsulin response in newly diagnosed NIDDM. Diabetes 38:262–266CrossRefPubMedGoogle Scholar
  33. 33.
    Kahn SE, Halban PA (1997) Release of incompletely processed proinsulin is the cause of the disproportionate proinsulinemia of NIDDM. Diabetes 46:1725–1732CrossRefPubMedGoogle Scholar
  34. 34.
    Røder ME, Porte D, Schwartz RS, Kahn SE (1998) Disproportionately elevated proinsulin levels reflect the degree of impaired B cell secretory capacity in patients with noninsulin-dependent diabetes mellitus. J Clin Endocrinol Metab 83:604–608PubMedGoogle Scholar
  35. 35.
    Larsson H, Ahrén B (1999) Relative Hyperproinsulinemia as a sign of islet dysfunction in women with impaired glucose tolerance. J Clin Endocrinol Metab 84:2068–2074PubMedGoogle Scholar
  36. 36.
    Hofsø D, Jenssen T, Bollerslev J et al (2011) Beta cell function after weight loss: a clinical trial comparing gastric bypass surgery and intensive lifestyle intervention. Eur J Endocrinol 164:231–238CrossRefPubMedPubMedCentralGoogle Scholar
  37. 37.
    Ramos JS, Dalleck LC, Borrani F et al (2016) The effect of different volumes of high-intensity interval training on proinsulin in participants with the metabolic syndrome: a randomised trial. Diabetologia 59:2308–2320CrossRefPubMedGoogle Scholar
  38. 38.
    McCaffery JM, Jablonski KA, Franks PW et al (2011) TCF7L2 polymorphism, weight loss and proinsulin∶insulin ratio in the diabetes prevention program. PLoS One 6:e21518CrossRefPubMedPubMedCentralGoogle Scholar
  39. 39.
    Kantartzis K, Machann J, Schick F et al (2011) Effects of a lifestyle intervention in metabolically benign and malign obesity. Diabetologia 54:864–868CrossRefPubMedGoogle Scholar
  40. 40.
    Machann J, Thamer C, Stefan N et al (2010) Follow-up whole-body assessment of adipose tissue compartments during a lifestyle intervention in a large cohort at increased risk for type 2 diabetes. Radiology 257:353–363CrossRefPubMedGoogle Scholar
  41. 41.
    Haupt A, Thamer C, Heni M et al (2010) Gene variants of TCF7L2 influence weight loss and body composition during lifestyle intervention in a population at risk for type 2 diabetes. Diabetes 59:747–750CrossRefPubMedGoogle Scholar
  42. 42.
    Pfützner A, Kunt T, Langenfeld M et al (2005) Clinical and laboratory evaluation of specific chemiluminescence assays for intact and total proinsulin. Clin Chem Lab Med 41:1234–1238Google Scholar
  43. 43.
    Matsuda M, DeFronzo RA (1999) Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp. Diabetes Care 22:1462–1470CrossRefPubMedGoogle Scholar
  44. 44.
    Szczepaniak LS, Nurenberg P, Leonard D et al (2005) Magnetic resonance spectroscopy to measure hepatic triglyceride content: prevalence of hepatic steatosis in the general population. Am J Physiol Endocrinol Metab 288:E462–E468CrossRefPubMedGoogle Scholar
  45. 45.
    Lindström J, Louheranta A, Mannelin M et al (2003) The Finnish Diabetes Prevention Study (DPS): lifestyle intervention and 3-year results on diet and physical activity. Diabetes Care 26:3230–3236CrossRefPubMedGoogle Scholar
  46. 46.
    Schellenberg ES, Dryden DM, Vandermeer B et al (2013) Lifestyle interventions for patients with and at risk for type 2 diabetes: a systematic review and meta-analysis. Ann Intern Med 159:543–551CrossRefPubMedGoogle Scholar
  47. 47.
    Stefan N, Kantartzis K, Machann J et al (2008) Identification and characterization of metabolically benign obesity in humans. Arch Intern Med 168:1609–1616CrossRefPubMedGoogle Scholar
  48. 48.
    Hotamisligil GS (2006) Inflammation and metabolic disorders. Nature 444:860–867CrossRefPubMedGoogle Scholar
  49. 49.
    Stefan N, Hennige AM, Staiger H et al (2006) α2-Heremans-Schmid glycoprotein/fetuin-A is associated with insulin resistance and fat accumulation in the liver in humans. Diabetes Care 29:853–857CrossRefPubMedGoogle Scholar
  50. 50.
    Snehalatha C, Mary S, Selvam S et al (2009) Changes in insulin secretion and insulin sensitivity in relation to the glycemic outcomes in subjects with impaired glucose tolerance in the Indian Diabetes Prevention Programme-1 (IDPP-1). Diabetes Care 32:1796–1801CrossRefPubMedPubMedCentralGoogle Scholar
  51. 51.
    Ahrén B (2005) Type 2 diabetes, insulin secretion and beta-cell mass. Curr Mol Med 5:275–286CrossRefPubMedGoogle Scholar
  52. 52.
    Fritsche A, Madaus A, Stefan N et al (2002) Relationships among age, Proinsulin conversion, and β-cell function in nondiabetic humans. Diabetes 51:S234–S239CrossRefPubMedGoogle Scholar
  53. 53.
    Vangipurapu J, Stančáková A, Kuulasmaa T et al (2015) Both fasting and glucose-stimulated proinsulin levels predict hyperglycemia and incident type 2 diabetes: a population-based study of 9,396 Finnish men. PLoS One 10:e0124028CrossRefPubMedPubMedCentralGoogle Scholar
  54. 54.
    Nijpels G, Popp-Snijders C, Kostense PJ et al (1996) Fasting proinsulin and 2-h post-load glucose levels predict the conversion to NIDDM in subjects with impaired glucose tolerance: the Hoorn study. Diabetologia 39:113–118PubMedGoogle Scholar
  55. 55.
    Haffner SM, Mykkänen L, Valdez RA et al (1994) Disproportionately increased proinsulin levels are associated with the insulin resistance syndrome. J Clin Endocrinol Metab 79:1806–1810PubMedGoogle Scholar
  56. 56.
    American Diabetes Association (2016) Prevention or delay of type 2 diabetes. Diabetes Care 39(Suppl 1):S36–S38Google Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Vera Schmid
    • 1
    • 2
  • Robert Wagner
    • 1
    • 3
    • 4
  • Corinna Sailer
    • 1
    • 3
    • 4
  • Louise Fritsche
    • 1
    • 3
    • 4
  • Konstantinos Kantartzis
    • 1
    • 3
    • 4
  • Andreas Peter
    • 1
    • 3
    • 4
  • Martin Heni
    • 1
    • 3
    • 4
  • Hans-Ulrich Häring
    • 1
    • 3
    • 4
  • Norbert Stefan
    • 1
    • 3
    • 4
  • Andreas Fritsche
    • 1
    • 3
    • 4
  1. 1.Department of Internal Medicine IVUniversity Hospital of TübingenTübingenGermany
  2. 2.International Research Training Group 1302University of TübingenTübingenGermany
  3. 3.Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Centre Munich at the University of TübingenTübingenGermany
  4. 4.German Centre for Diabetes Research (DZD)TübingenGermany

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