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Variability in Associations of Phosphatidylcholine Molecular Species with Metabolic Syndrome in Mexican–American Families

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Lipids

Abstract

Plasma lipidomic studies using high performance liquid chromatography and mass spectroscopy offer detailed insights into metabolic processes. Taking the example of the most abundant plasma lipid class (phosphatidylcholines) we used the rich phenotypic and lipidomic data from the ongoing San Antonio Family Heart Study of large extended Mexican–American families to assess the variability of association of the plasma phosphatidylcholine species with metabolic syndrome. Using robust statistical analytical methods, our study made two important observations. First, there was a wide variability in the association of phosphatidylcholine species with risk measures of metabolic syndrome. Phosphatidylcholine 40:7 was associated with a low risk while phosphatidylcholines 32:1 and 38:3 were associated with a high risk of metabolic syndrome. Second, all the odd chain phosphatidylcholines were associated with a reduced risk of metabolic syndrome implying that phosphatidylcholines derived from dairy products might be beneficial against metabolic syndrome. Our results demonstrate the value of lipid species-specific information provided by the upcoming array of lipidomic studies and open potential avenues for prevention and control of metabolic syndrome in high prevalence settings.

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Abbreviations

BMI:

Body mass index

DBP:

Diastolic blood pressure

FG:

Fasting glucose

FI:

Fasting insulin

HDL:

High density lipoproteins

IDF:

International diabetes federation

LDL:

Low density lipoprotein

MS:

Metabolic syndrome

ROC:

Receiver operating characteristic

SAFHS:

San Antonio family heart study

SBP:

Systolic blood pressure

TG:

Triglycerides

TSC:

Total serum cholesterol

WC:

Waist circumference

References

  1. Meikle PJ, Christopher MJ (2011) Lipidomics is providing new insight into the metabolic syndrome and its sequelae. Curr Opin Lipidol 22:210–215

    Article  PubMed  CAS  Google Scholar 

  2. Kontush A, Chapman MJ (2010) Lipidomics as a tool for the study of lipoprotein metabolism. Curr Atheroscler Rep 12:194–201

    Article  PubMed  CAS  Google Scholar 

  3. Kotronen A, Velagapudi VR, Yetukuri L, Westerbacka J, Bergholm R, Ekroos K, Makkonen J, Taskinen MR, Oresic M, Yki-Jarvinen H (2009) Serum saturated fatty acids containing triacylglycerols are better markers of insulin resistance than total serum triacylglycerol concentrations. Diabetologia 52:684–690

    Article  PubMed  CAS  Google Scholar 

  4. Koerner TA, Cunningham MT, Zhang DS (1992) The role of membrane lipid in the platelet storage lesion. Blood Cells 18:481–497 (discussion 498–500)

    PubMed  CAS  Google Scholar 

  5. MacCluer JW, Stern MP, Almasy L, Atwood LA, Blangero J, Comuzzie AG, Dyke B, Haffner SM, Henkel RD, Hixson JE et al (1999) Genetics of atherosclerosis risk factors in Mexican Americans. Nutr Rev 57:S59–S65

    Article  PubMed  CAS  Google Scholar 

  6. Voruganti VS, Lopez-Alvarenga JC, Nath SD, Rainwater DL, Bauer R, Cole SA, Maccluer JW, Blangero J, Comuzzie AG (2008) Genetics of variation in HOMA-IR and cardiovascular risk factors in Mexican-Americans. J Mol Med (Berl) 86:303–311

    Article  CAS  Google Scholar 

  7. IDF (2006) The IDF consensus worldwide definition of metabolic syndrome. IDF Communications, Brussels, Belgium

  8. Murphy RC, James PF, McAnoy AM, Krank J, Duchoslav E, Barkley RM (2007) Detection of the abundance of diacylglycerol and triacylglycerol molecular species in cells using neutral loss mass spectrometry. Anal Biochem 366:59–70

    Article  PubMed  CAS  Google Scholar 

  9. Smyth I, Hacking DF, Hilton AA, Mukhamedova N, Meikle PJ, Ellis S, Satterley K, Collinge JE, de Graaf CA, Bahlo M et al (2008) A mouse model of harlequin ichthyosis delineates a key role for Abca12 in lipid homeostasis. PLoS Genet 4:e1000192

    Article  PubMed  Google Scholar 

  10. Almasy L, Blangero J (1998) Multipoint quantitative-trait linkage analysis in general pedigrees. Am J Hum Genet 62:1198–1211

    Article  PubMed  CAS  Google Scholar 

  11. Li J, Ji L (2005) Adjusting multiple testing in multilocus analyses using the eigenvalues of a correlation matrix. Heredity (Edinb) 95:221–227

    Article  CAS  Google Scholar 

  12. Cheverud JM (2001) A simple correction for multiple comparisons in interval mapping genome scans. Heredity (Edinb) 87:52–58

    Article  CAS  Google Scholar 

  13. Melton PE, Rutherford S, Voruganti VS, Goring HH, Laston S, Haack K, Comuzzie AG, Dyer TD, Johnson MP, Kent JW Jr et al (2010) Bivariate genetic association of KIAA1797 with heart rate in American Indians: the Strong Heart Family Study. Hum Mol Genet 19:3662–3671

    Article  PubMed  CAS  Google Scholar 

  14. Diego VP, Goring HH, Cole SA, Almasy L, Dyer TD, Blangero J, Duggirala R, Laston S, Wenger C, Cantu T et al (2006) Fasting insulin and obesity-related phenotypes are linked to chromosome 2p: the Strong Heart Family Study. Diabetes 55:1874–1878

    Article  PubMed  CAS  Google Scholar 

  15. Almasy L, Dyer TD, Blangero J (1997) Bivariate quantitative trait linkage analysis: pleiotropy versus co-incident linkages. Genet Epidemiol 14:953–958

    Article  PubMed  CAS  Google Scholar 

  16. Rainwater DL, Comuzzie AG, VandeBerg JL, Mahaney MC, Blangero J (1997) Serum leptin levels are independently correlated with two measures of HDL. Atherosclerosis 132:237–243

    Article  PubMed  CAS  Google Scholar 

  17. Ng DS, Saw NM (2012) The role of HDL and its modulators in the development of diabetes. Curr Opin Lipidol 23:167–168

    Article  PubMed  CAS  Google Scholar 

  18. Gaby AR (2009) Nutritional approaches to prevention and treatment of gallstones. Altern Med Rev 14:258–267

    PubMed  Google Scholar 

  19. Nash DT (2004) Cardiovascular risk beyond LDL-C levels. Other lipids are performers in cholesterol story. Postgrad Med 116:11–15

    Article  PubMed  Google Scholar 

  20. Yanagita T, Nagao K (2008) Functional lipids and the prevention of the metabolic syndrome. Asia Pac J Clin Nutr 17(Suppl 1):189–191

    PubMed  CAS  Google Scholar 

  21. Shirouchi B, Nagao K, Inoue N, Ohkubo T, Hibino H, Yanagita T (2007) Effect of dietary omega 3 phosphatidylcholine on obesity-related disorders in obese Otsuka Long-Evans Tokushima fatty rats. J Agric Food Chem 55:7170–7176

    Article  PubMed  CAS  Google Scholar 

  22. Zhao Y, Fu L, Li R, Wang LN, Yang Y, Liu NN, Zhang CM, Wang Y, Liu P, Tu BB et al (2012) Metabolic profiles characterizing different phenotypes of polycystic ovary syndrome: plasma metabolomics analysis. BMC Med 10:153

    Article  PubMed  CAS  Google Scholar 

  23. Duncan D, Rubin JP, Golitz L, Badylak S, Kesel L, Freund J (2009) Refinement of technique in injection lipolysis based on scientific studies and clinical evaluation. Clin Plast Surg, 36:195–209 (v–vi; discussion 211–193)

    Google Scholar 

  24. Walker AK, Jacobs RL, Watts JL, Rottiers V, Jiang K, Finnegan DM, Shioda T, Hansen M, Yang F, Niebergall LJ et al (2011) A conserved SREBP-1/phosphatidylcholine feedback circuit regulates lipogenesis in metazoans. Cell 147:840–852

    Article  PubMed  CAS  Google Scholar 

  25. Khaw KT, Friesen MD, Riboli E, Luben R, Wareham N (2012) Plasma phospholipid fatty acid concentration and incident coronary heart disease in men and women: the EPIC-Norfolk prospective study. PLoS Med 9:e1001255

    Article  PubMed  CAS  Google Scholar 

  26. Meissner T, Leichsenring M, Mayatepek E (2004) Odd-numbered long-chain fatty acids in erythrocyte phospholipids as long-term follow-up parameter in propionic acidemia. Clin Chem Lab Med 42:1005–1008

    Article  PubMed  CAS  Google Scholar 

  27. Wolk A, Furuheim M, Vessby B (2001) Fatty acid composition of adipose tissue and serum lipids are valid biological markers of dairy fat intake in men. J Nutr 131:828–833

    PubMed  CAS  Google Scholar 

  28. Kroger J, Zietemann V, Enzenbach C, Weikert C, Jansen EH, Doring F, Joost HG, Boeing H, Schulze MB (2011) Erythrocyte membrane phospholipid fatty acids, desaturase activity, and dietary fatty acids in relation to risk of type 2 diabetes in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study. Am J Clin Nutr 93:127–142

    Article  PubMed  Google Scholar 

  29. Kim OY, Lim HH, Lee MJ, Kim JY, Lee JH: (2011) Association of fatty acid composition in serum phospholipids with metabolic syndrome and arterial stiffness. Nutr Metab Cardiovasc Dis (epub ahead of print)

  30. Pietilainen KH, Rog T, Seppanen-Laakso T, Virtue S, Gopalacharyulu P, Tang J, Rodriguez-Cuenca S, Maciejewski A, Naukkarinen J, Ruskeepaa AL et al (2011) Association of lipidome remodeling in the adipocyte membrane with acquired obesity in humans. PLoS Biol 9:e1000623

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgments

This work was supported in part by NIH grants R01 DK082610 and R01 DK079169. Data collection for the San Antonio Family Heart Study was supported by NIH grant P01 HL045522. We are grateful to the participants of the San Antonio Family Heart Study for their continued involvement. The development of the analytical methods and software used in this study was supported by NIH grant R37 MH059490. The AT&T Genomics Computing Center supercomputing facilities used for this work were supported in part by a gift from the AT&T Foundation and with support from the National Center for Research Resources Grant Number S10 RR029392. This investigation was conducted in facilities constructed with support from Research Facilities Improvement Program grants C06 RR013556 and C06 RR017515 from the National Center for Research Resources of the National Institutes of Health.

Conflict of interest

None declared.

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Authors and Affiliations

  1. Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, 78227, USA

    Hemant Kulkarni, Manju Mamtani, Claire Bellis, Thomas D. Dyer, Matthew P. Johnson, David L. Rainwater, Laura Almasy, Michael C. Mahaney, Anthony G. Comuzzie, John Blangero & Joanne E. Curran

  2. Baker IDI Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia

    Peter J. Meikle, Jacquelyn M. Weir, Christopher K. Barlow & Jeremy B. Jowett

  3. Texas Biomedical Research Institute, PO Box 760549, San Antonio, TX, 78245, USA

    Hemant Kulkarni

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  1. Hemant Kulkarni
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  2. Peter J. Meikle
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Correspondence to Hemant Kulkarni.

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Kulkarni, H., Meikle, P.J., Mamtani, M. et al. Variability in Associations of Phosphatidylcholine Molecular Species with Metabolic Syndrome in Mexican–American Families. Lipids 48, 497–503 (2013). https://doi.org/10.1007/s11745-013-3781-7

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  • DOI: https://doi.org/10.1007/s11745-013-3781-7

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