Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Physiology

Plasma lipid profiling of tissue-specific insulin resistance in human obesity

Abstract

Background/Objectives

Obesity-associated insulin resistance (IR) may develop in multiple organs, representing different aetiologies towards cardiometabolic diseases. This study aimed to identify distinct plasma lipid profiles in overweight/obese individuals who show muscle-IR and/or liver-IR.

Subjects/Methods

Baseline data of the European multicenter DiOGenes project were used (n = 640; 401 women, nondiabetic BMI: 27-45 kg/m2). Muscle insulin sensitivity index (MISI) and hepatic insulin resistance index (HIRI) were derived from a 5-point oral glucose tolerance test. The 140 plasma lipids were quantified by liquid chromatography–mass spectrometry. Linear mixed models were used to evaluate associations between MISI, HIRI and plasma lipids.

Results

MISI was comparable between sexes while HIRI and triacylglycerol (TAG) levels were lower in women than in men. MISI was associated with higher lysophosphatidylcholine (LPC) levels (standardized (std)β = 0.126; FDR-p = 0.032). Sex interactions were observed for associations between HIRI, TAG and diacylglycerol (DAG) lipid classes. In women, but not in men, HIRI was associated with higher levels of TAG (44 out of 55 species) and both DAG species (stdβ: 0.139–0.313; FDR-p < 0.05), a lower odd-chain/even-chain TAG ratio (stdβ = −0.182; FDR-p = 0.005) and a lower very-long-chain/long-chain TAG ratio (stdβ = −0.156; FDR-p = 0.037).

Conclusions

In overweight/obese individuals, muscle insulin sensitivity is associated with higher plasma LPC concentrations. Women have less hepatic IR and lower TAG than men. Nevertheless, hepatic IR is associated with higher plasma TAG and DAG concentrations and a lower abundance of odd-chain and very-long-chain TAG in women, but not in men. This suggests a more pronounced worsening of plasma lipid profile in women with the progression of hepatic IR.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Ng M, Fleming T, Robinson M, Thomson B, Graetz N, Margono C, et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2014;384:766–81.

    Article  Google Scholar 

  2. Kahn SE, Hull RL, Utzschneider KM. Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature. 2006;444:840–6.

    Article  CAS  Google Scholar 

  3. Samuel VT, Petersen KF, Shulman GI. Lipid-induced insulin resistance: unravelling the mechanism. Lancet. 2010;375:2267–77.

    Article  CAS  Google Scholar 

  4. Valsesia A, Saris WH, Astrup A, Hager J, Masoodi M. Distinct lipid profiles predict improved glycemic control in obese, nondiabetic patients after a low-caloric diet intervention: the Diet, Obesity and Genes randomized trial. Am J Clin Nutr. 2016;104:566–75.

    Article  CAS  Google Scholar 

  5. Stinkens R, Goossens GH, Jocken JWE, Blaak EE. Targeting fatty acid metabolism to improve glucose metabolism. Obes Rev. 2015;16:715–57.

    Article  CAS  Google Scholar 

  6. Coen PM, Goodpaster BH. Role of intramyocelluar lipids in human health. Trends Endocrinol Metab. 2012;23:391–8.

    Article  CAS  Google Scholar 

  7. Tonks KT, Coster AC, Christopher MJ, Chaudhuri R, Xu A, Gagnon-Bartsch J, et al. Skeletal muscle and plasma lipidomic signatures of insulin resistance and overweight/obesity in humans. Obesity. 2016;24:908–16.

    Article  CAS  Google Scholar 

  8. Mika A, Sledzinski T. Alterations of specific lipid groups in serum of obese humans: a review. Obes Rev. 2017;18:247–72.

    Article  CAS  Google Scholar 

  9. Rauschert S, Uhl O, Koletzko B, Kirchberg F, Mori TA, Huang R-C, et al. Lipidomics reveals associations of phospholipids with obesity and insulin resistance in young adults. J Clin Endocrinol Metab. 2016;101:871–9.

    Article  CAS  Google Scholar 

  10. Meikle PJ, Wong G, Barlow CK, Weir JM, Greeve MA, MacIntosh GL, et al. Plasma lipid profiling shows similar associations with prediabetes and type 2 diabetes. PLoS One. 2013;8:e74341–11.

    Article  CAS  Google Scholar 

  11. Weir JM, Wong G, Barlow CK, Greeve MA, Kowalczyk A, Almasy L, et al. Plasma lipid profiling in a large population-based cohort. J Lipid Res. 2013;54:2898–908.

    Article  CAS  Google Scholar 

  12. Rhee EP, Cheng S, Larson MG, Walford GA, Lewis GD, McCabe E, et al. Lipid profiling identifies a triacylglycerol signature of insulin resistance and improves diabetes prediction in humans. J Clin Invest. 2011;121:1402–11.

    Article  CAS  Google Scholar 

  13. Kulkarni H, Meikle PJ, Mamtani M, Weir JM, Almeida M, Diego V, et al. Plasma lipidome is independently associated with variability in metabolic syndrome in Mexican American families. J Lipid Res. 2014;55:939–46.

    Article  CAS  Google Scholar 

  14. Barber MN, Risis S, Yang C, Meikle PJ, Staples M, Febbraio MA, et al. Plasma lysophosphatidylcholine levels are reduced in obesity and type 2 diabetes. PLoS ONE. 2012;7:e41456–12.

    Article  CAS  Google Scholar 

  15. Floegel A, Stefan N, Yu Z, Mühlenbruch K, Drogan D, Joost H-G, et al. Identification of serum metabolites associated with risk of type 2 diabetes using a targeted metabolomic approach. Diabetes. 2013;62:639–48.

    Article  CAS  Google Scholar 

  16. Pietiläinen KH, Sysi-Aho M, Rissanen A, Seppänen-Laakso T, Yki-Jarvinen H, Kaprio J, et al. Acquired obesity is associated with changes in the serum lipidomic profile independent of genetic effects – a monozygotic twin study. PLoS ONE. 2007;2:e218–14.

    Article  Google Scholar 

  17. Stefan N, Fritsche A, Schick F, Häring H-U. Phenotypes of prediabetes and stratification of cardiometabolic risk. Lancet Diabetes Endocrinol. 2016;4:789–98.

    Article  Google Scholar 

  18. Goossens G, Moors C, Jocken J, van der Zijl N, Jans A, Konings E, et al. Altered skeletal muscle fatty acid handling in subjects with impaired glucose tolerance as compared to impaired fasting glucose. Nutrients. 2016;8:164–15.

    Article  Google Scholar 

  19. Bird SR, Hawley JA. Update on the effects of physical activity on insulin sensitivity in humans. BMJ Open Sport Exerc Med. 2016;2:e000143.

    Article  Google Scholar 

  20. Zheng J, Woo S-L, Hu X, Botchlett R, Chen L, Huo Y, et al. Metformin and metabolic diseases: a focus on hepatic aspects. Front Med. 2015;9:173–86.

    Article  Google Scholar 

  21. Blanco-Rojo R, Alcala-Diaz JF, Wopereis S, Perez-Martinez P, Quintana-Navarro GM, Marin C, et al. The insulin resistance phenotype (muscle or liver) interacts with the type of diet to determine changes in disposition index after 2 years of intervention: the CORDIOPREV-DIAB randomised clinical trial. Diabetologia. 2016;59:67–76.

    Article  CAS  Google Scholar 

  22. Larsen TM, Dalskov S-M, van Baak M, Jebb SA, Papadaki A, Pfeiffer AFH, et al. Diets with high or low protein content and glycemic index for weight-loss maintenance. N Engl J Med. 2010;363:2102–13.

    Article  CAS  Google Scholar 

  23. Abdul-Ghani MA, Matsuda M, Balas B, DeFronzo RA. Muscle and liver insulin resistance indexes derived from the oral glucose tolerance test. Diabetes Care. 2007;30:89–94.

    Article  CAS  Google Scholar 

  24. Forouhi NG, Koulman A, Sharp SJ, Imamura F. Differences in the prospective association between individual plasma phospholipid saturated fatty acids and incident type 2 diabetes: the EPIC-InterAct case-cohort study. Lancet Diabetes Endocrinol. 2014;2:810–8.

    Article  CAS  Google Scholar 

  25. Goossens GH. The metabolic phenotype in obesity: fat mass, body fat distribution, and adipose tissue function. Obes Facts. 2017;10:207–15.

    Article  CAS  Google Scholar 

  26. Wang X, Magkos F, Mittendorfer B. Sex differences in lipid and lipoprotein metabolism: it’s not just about sex hormones. J Clin Endocrinol Metab. 2011;96:885–93.

    Article  CAS  Google Scholar 

  27. Kontush A, Lhomme M, Chapman MJ. Unraveling the complexities of the HDL lipidome. J Lipid Res. 2013;54:2950–63.

    Article  CAS  Google Scholar 

  28. Ferrannini E, Natali A, Camastra S, Nannipieri M, Mari A, Adam K-P, et al. Early metabolic markers of the development of dysglycemia and type 2 diabetes and their physiological significance. Diabetes. 2013;62:1730–7.

    Article  CAS  Google Scholar 

  29. Wang-Sattler R, Yu Z, Herder C, Messias AC, Floegel A, He Y, et al. Novel biomarkers for pre-diabetes identified by metabolomics. Mol Syst Biol. 2012;8:615–11.

    Article  Google Scholar 

  30. Felder TK, Ring-Dimitriou S, Auer S, Soyal SM, Kedenko L, Rinnerthaler M, et al. Specific circulating phospholipids, acylcarnitines, amino acids and biogenic amines are aerobic exercise markers. J Sci Med Sport. 2017;20:700–5.

    Article  Google Scholar 

  31. Klingler C, Zhao X, Adhikary T, Li J, Xu G, Häring H-U, et al. Lysophosphatidylcholines activate PPARδ and protect human skeletal muscle cells from lipotoxicity. Biochim Biophys Acta. 2016;1861:1980–92.

    Article  CAS  Google Scholar 

  32. Rzehak P, Hellmuth C, Uhl O, Kirchberg FF, Peissner W, Harder U, et al. Rapid growth and childhood obesity are strongly associated with LysoPC(14:0). Ann Nutr Metab. 2014;64:294–303.

    Article  Google Scholar 

  33. Kim JY, Park JY, Kim OY, Ham BM, Kim H-J, Kwon DY, et al. Metabolic profiling of plasma in overweight/obese and lean men using ultra performance liquid chromatography and Q-TOF mass spectrometry (UPLC-Q-TOF MS). J Proteome Res. 2010;9:4368–75.

    Article  CAS  Google Scholar 

  34. Magkos F, Patterson BW, Mohammed BS, Klein S, Mittendorfer B. Women produce fewer but triglyceride-richer very low-density lipoproteins than men. J Clin Endocrinol Metab. 2007;92:1311–8.

    Article  CAS  Google Scholar 

  35. Sparks JD, Sparks CE, Adeli K. Selective hepatic insulin resistance, VLDL overproduction, and hypertriglyceridemia. Arterioscler Thromb Vasc Biol. 2012;32:2104–12.

    Article  CAS  Google Scholar 

  36. Magkos F, Fabbrini E, Mohammed BS, Patterson BW, Klein S, Mittendorfer B. Estrogen deficiency after menopause does not result in male very-low-density lipoprotein metabolism phenotype. J Clin Endocrinol Metab. 2010;95:3377–84.

    Article  CAS  Google Scholar 

  37. Santaren ID, Watkins SM, Liese AD, Wagenknecht LE, Rewers MJ, Haffner SM, et al. Serum pentadecanoic acid (15:0), a short-term marker of dairy food intake, is inversely associated with incident type 2 diabetes and its underlying disorders. Am J Clin Nutr. 2014;100:1532–40.

    Article  CAS  Google Scholar 

  38. Yilmaz M, Claiborn KC, Hotamisligil GS. De novo lipogenesis products and endogenous lipokines. Diabetes. 2016;65:1800–7.

    Article  CAS  Google Scholar 

  39. Weijers RNM. Lipid composition of cell membranes and its relevance in type 2 diabetes mellitus. Curr Diabetes Rev. 2012;8:390–400.

    Article  CAS  Google Scholar 

  40. Holman RT, Adams CE, Nelson RA, Grater S, Jaskiewicz JA, Johnson SB, et al. Patients with anorexia-nervosa demonstrate deficiencies of selected essential fatty-acids, compensatory changes in nonessential fatty-acids and decreased fluidity of plasma-lipids. J Nutr. 1995;125:901–7.

    CAS  PubMed  Google Scholar 

  41. Andersson A, Nälsén C, Tengblad S, Vessby B. Fatty acid composition of skeletal muscle reflects dietary fat composition in humans. Am J Clin Nutr. 2002;76:1222–9.

    Article  CAS  Google Scholar 

Download references

Author contributions

WHMS and AA designed the DiOGenes clinical study; AV, AA, WHMS and TH designed the lipidomics studies; EEB designed and led the present study; NV and BWvdK conducted the statistical analyses; JWEJ, NV and MMJvG supervised the lipidomics data analyses; BWvdK wrote the manuscript. All authors contributed to revising the article critically for important intellectual content and gave their final approval of the version to be published. EEB is the guarantor of this work.

Funding

This study was supported by the European Commission, Food Quality and Safety Priority of the Sixth Framework Program (FP6-2005-513946), through a grant from the Maastricht University Medical Center and Nestlé Institute of Health Sciences, Lausanne, Switzerland.

Author information

Authors and Affiliations

Authors

Consortia

Corresponding author

Correspondence to Birgitta W. van der Kolk.

Ethics declarations

Conflict of interest

AV is a full-time employee at Nestlé Institute of Health Sciences SA. WHMS reports having received research support from several food companies such as Nestlé, DSM, Unilever, Nutrition et Sante and Danone as well as Pharmaceutical companies such as GSK, Novartis and Novo Nordisk; he is an unpaid scientific advisor for the International Life Science Institute, ILSI Europe. AA reports grants and personal fees from Global Dairy Platform, personal fees from McCain Foods, McDonald’s, Arena Pharmaceuticals Inc., Basic Research, Dutch Beer Knowledge Institute, Netherlands, Gelesis, Novo Nordisk, Denmark, Orexigen Therapeutics Inc., S-Biotek, Denmark, Twinlab and Vivus Inc., grants from Arla Foods, Denmark, Danish Dairy Research Council and Nordea Foundation, Denmark, outside the submitted work, and royalties received for the book first published in Danish as 'Verdens Bedste Kur' (Politiken; Copenhagen, Denmark), and subsequently published in Dutch as 'Het beste dieet ter wereld' (Kosmos Uitgevers; Utrecht/Antwerpen, Netherlands), in Spanish as 'Plan DIOGENES para el control del peso. La dieta personalizada inteligente' (Editorial Evergra ́ficas; Léon, Spain) and in English as 'World’s Best Diet' (Penguin, Australia). EEB receives grant support from food industry such as DSM, Danone, Friesland Campina, Avebe and Sensus, partly within the context of public–private consortia and has received funding from pharmaceutical companies like Novartis. She is involved in several task forces/expert groups related to the International Life Science Institute, ILSI Europe.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

van der Kolk, B.W., Vogelzangs, N., Jocken, J.W.E. et al. Plasma lipid profiling of tissue-specific insulin resistance in human obesity. Int J Obes 43, 989–998 (2019). https://doi.org/10.1038/s41366-018-0189-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41366-018-0189-8

This article is cited by

Search

Quick links