Glycerophosphocholine Metabolites and Cardiovascular Disease Risk Factors in Adolescents: A Cohort Study

Background: Glycerophosphocholine (GPC) metabolites modulate atherosclerosis and thus risk for cardiovascular disease (CVD). Preclinical CVD may start during adolescence. Here, we used targeted serum lipidomics to identify a new panel of GPCs, and tested whether any of these GPCs are associated, in adolescence, with classical risk factors of CVD, namely excess visceral fat (VF), elevated blood pressure, insulin resistance, and atherogenic dyslipidemia. Methods: We studied a population-based sample of 990 adolescents (12–18 years, 48% male), as part of the Saguenay Youth Study. Using liquid chromatography-electrospray ionization-mass spectrometry, we identified 69 serum GPCs within the 450 to 680 m/z range. We measured VF with MRI. Results: We identified several novel GPCs that were associated with multiple CVD risk factors. Most significantly, PC16:0/2:0 was negatively associated with VF (P=1.4×10–19), blood pressure (P=7.7×10–5), and fasting triacylglycerols (P=9.0×10–5), and PC14:1/0:0 was positively associated with VF (P=3.0×10–7), fasting insulin (P=5.4×10–32), and triacylglycerols (P=1.4×10–29). The Sobel test of mediation revealed that both GPCs mediated their respective relations between VF (as a potential primary exposure) and CVD risk factors (as outcomes, P values<1.3×10–3). Furthermore, a GPC shown recently to predict incident coronary heart disease in older adults, PC18:2/0:0, was associated with several CVD risk factors in adolescents; these associations were less strong than those with the newly identified GPCs. Conclusions: We identified novel GPCs strongly associated with multiple CVD risk factors in adolescents. These GPCs may be sensitive indicators of obesity-related risk for CVD outcomes in adults, and may improve biological understanding of CVD risk.

[1]  Louis Richer,et al.  Cohort Profile: The Saguenay Youth Study (SYS). , 2016, International journal of epidemiology.

[2]  Amy F. Subar,et al.  Dietary Assessment Methodology , 2017 .

[3]  S. Kahn,et al.  Increased Visceral Adipose Tissue Is an Independent Predictor for Future Development of Atherogenic Dyslipidemia. , 2016, The Journal of clinical endocrinology and metabolism.

[4]  C. Fox,et al.  Association Between Visceral and Subcutaneous Adipose Depots and Incident Cardiovascular Disease Risk Factors , 2015, Circulation.

[5]  M. Portero-Otín,et al.  Metabolomics predicts stroke recurrence after transient ischemic attack , 2015, Neurology.

[6]  M. Mayr,et al.  Lipidomics: Quest for Molecular Lipid Biomarkers in Cardiovascular Disease , 2014, Circulation. Cardiovascular genetics.

[7]  Anders Larsson,et al.  Large-scale Metabolomic Profiling Identifies Novel Biomarkers for Incident Coronary Heart Disease , 2014, PLoS genetics.

[8]  M. Fischer,et al.  Alterations of Plasma Lysophosphatidylcholine Species in Obesity and Weight Loss , 2014, PloS one.

[9]  G. Marathe,et al.  To hydrolyze or not to hydrolyze: the dilemma of platelet-activating factor acetylhydrolase , 2014, Journal of Lipid Research.

[10]  D. Bates,et al.  Fitting Linear Mixed-Effects Models Using lme4 , 2014, 1406.5823.

[11]  T. Spector,et al.  Lipidomics Profiling and Risk of Cardiovascular Disease in the Prospective Population-Based Bruneck Study , 2014, Circulation.

[12]  Gerd Schmitz,et al.  Glycerophospholipid and Sphingolipid Species and Mortality: The Ludwigshafen Risk and Cardiovascular Health (LURIC) Study , 2014, PloS one.

[13]  Bruce M. Spiegelman,et al.  What We Talk About When We Talk About Fat , 2014, Cell.

[14]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[15]  D. Figeys,et al.  Targeted lipidomics – advances in profiling lysophosphocholine and platelet‐activating factor second messengers , 2013, The FEBS journal.

[16]  Eugene Demidenko,et al.  Mixed Models: Theory and Applications with R , 2013 .

[17]  V. Aidinis,et al.  Lysoglycerophospholipids in chronic inflammatory disorders: the PLA(2)/LPC and ATX/LPA axes. , 2013, Biochimica et biophysica acta.

[18]  A. Khera,et al.  Dysfunctional adiposity and the risk of prediabetes and type 2 diabetes in obese adults. , 2012, JAMA.

[19]  M. Shields,et al.  Overweight and obesity in children and adolescents: results from the 2009 to 2011 Canadian Health Measures Survey. , 2012, Health reports.

[20]  Eoin Fahy,et al.  Lipid classification, structures and tools. , 2011, Biochimica et biophysica acta.

[21]  I. Haviv,et al.  Plasma Lipidomic Analysis of Stable and Unstable Coronary Artery Disease , 2011, Arteriosclerosis, thrombosis, and vascular biology.

[22]  B. Norrving,et al.  Global atlas on cardiovascular disease prevention and control. , 2011 .

[23]  Eoin Fahy,et al.  Lipidomics reveals a remarkable diversity of lipids in human plasma1[S] , 2010, Journal of Lipid Research.

[24]  A. Shevchenko,et al.  Lipidomics: coming to grips with lipid diversity , 2010, Nature Reviews Molecular Cell Biology.

[25]  Aaron Fenster,et al.  Dietary Intervention to Reverse Carotid Atherosclerosis , 2010, Circulation.

[26]  T. Pickering,et al.  Prevalence and determinants of isolated systolic hypertension among young adults: the 1999–2004 US National Health And Nutrition Examination Survey , 2010, Journal of hypertension.

[27]  S. Grundy,et al.  Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International As , 2009, Circulation.

[28]  Shumei S. Sun,et al.  Visceral adiposity and its anatomical distribution as predictors of the metabolic syndrome and cardiometabolic risk factor levels. , 2008, The American journal of clinical nutrition.

[29]  T. Paus,et al.  Intra-abdominal adiposity and individual components of the metabolic syndrome in adolescence: sex differences and underlying mechanisms. , 2008, Archives of pediatrics & adolescent medicine.

[30]  M. Hermansson,et al.  Acyl chain‐dependent effect of lysophosphatidylcholine on human neutrophils , 2007, Journal of leukocyte biology.

[31]  Udo Hoffmann,et al.  Abdominal Visceral and Subcutaneous Adipose Tissue Compartments: Association With Metabolic Risk Factors in the Framingham Heart Study , 2007, Circulation.

[32]  Z. Pausova From big fat cells to high blood pressure: a pathway to obesity-associated hypertension , 2006, Current opinion in nephrology and hypertension.

[33]  R. D'Agostino,et al.  Metabolic Syndrome as a Precursor of Cardiovascular Disease and Type 2 Diabetes Mellitus , 2005, Circulation.

[34]  S. Franklin,et al.  Systolic hypertension: an overview. , 2005, American heart journal.

[35]  S. Kritchevsky,et al.  Association of visceral adipose tissue with incident myocardial infarction in older men and women: the Health, Aging and Body Composition Study. , 2004, American journal of epidemiology.

[36]  S. Kahn,et al.  Visceral Adiposity Is an Independent Predictor of Incident Hypertension in Japanese Americans , 2004, Annals of Internal Medicine.

[37]  H. Suh,et al.  Therapeutic effects of lysophosphatidylcholine in experimental sepsis , 2004, Nature Medicine.

[38]  David P Mackinnon,et al.  Confidence Limits for the Indirect Effect: Distribution of the Product and Resampling Methods , 2004, Multivariate behavioral research.

[39]  Heather Y. Lovelace,et al.  Nutrition in the Prevention and Treatment of Disease , 2003 .

[40]  S. Daniels,et al.  Obesity hypertension in children: a problem of epidemic proportions. , 2002, Hypertension.

[41]  R. Tracy,et al.  Association between multiple cardiovascular risk factors and atherosclerosis in children and young adults. The Bogalusa Heart Study. , 1998, The New England journal of medicine.

[42]  I M Buzzard,et al.  Monitoring dietary change in a low-fat diet intervention study: advantages of using 24-hour dietary recalls vs food records. , 1996, Journal of the American Dietetic Association.

[43]  O. Thulesius,et al.  Continuous non‐invasive finger blood pressure monitoring in children , 1994, Acta paediatrica.

[44]  G. Parati,et al.  Comparison of Finger and Intra‐arterial Blood Pressure Monitoring at Rest and During Laboratory Testing , 1989, Hypertension.

[45]  F. Snyder Platelet-Activating Factor and Related Lipid Mediators , 1987, Springer US.

[46]  M. Sobel Asymptotic Confidence Intervals for Indirect Effects in Structural Equation Models , 1982 .