Associations among circulating sphingolipids, β-cell function, and risk of developing type 2 diabetes: A population-based cohort study in China

Background Animal studies suggest vital roles of sphingolipids, especially ceramides, in the pathogenesis of type 2 diabetes (T2D) via pathways involved in insulin resistance, β-cell dysfunction, and inflammation, but human studies are limited. We aimed to evaluate the associations of circulating sphingolipids with incident T2D and to explore underlying mechanisms. Methods and findings The current study included 826 men and 1,148 women who were aged 50–70 years, from Beijing and Shanghai, and without T2D in 2005 and who were resurveyed in 2011. Cardiometabolic traits were measured at baseline and follow-up surveys. A total of 76 sphingolipids were quantified using high-coverage targeted lipidomics. Summary data for 2-sample Mendelian randomization were obtained from genome-wide association studies of circulating sphingolipids and the China Health and Nutrition Survey (n = 5,731). During the 6-year period, 529 participants developed T2D. Eleven novel and 3 reported sphingolipids, namely ceramides (d18:1/18:1, d18:1/20:0, d18:1/20:1, d18:1/22:1), saturated sphingomyelins (C34:0, C36:0, C38:0, C40:0), unsaturated sphingomyelins (C34:1, C36:1, C42:3), hydroxyl-sphingomyelins (C34:1, C38:3), and a hexosylceramide (d18:1/20:1), were positively associated with incident T2D (relative risks [RRs]: 1.14–1.21; all P < 0.001), after multivariate adjustment including lifestyle characteristics and BMI. Network analysis further identified 5 modules, and 2 modules containing saturated sphingomyelins showed the strongest associations with increased T2D risk (RRQ4 versus Q1 = 1.59 and 1.43; both Ptrend < 0.001). Mediation analysis suggested that the detrimental associations of 13 sphingolipids with T2D were largely mediated through β-cell dysfunction, as indicated by HOMA-B (mediation proportion: 11.19%–42.42%; all P < 0.001). Moreover, Mendelian randomization evidenced a positive association between a genetically instrumented ceramide (d18:1/20:1) and T2D (odds ratio: 1.15 [95% CI 1.05–1.26]; P = 0.002). Main limitations in the current study included potential undiagnosed cases and lack of an independent population for replication. Conclusions In this study, we observed that a panel of novel sphingolipids with unique structures were positively associated with incident T2D, largely mediated through β-cell dysfunction, in Chinese individuals.

[1]  C. Gelfi,et al.  Sphingolipids in Obesity and Correlated Co-Morbidities: The Contribution of Gender, Age and Environment , 2019, International journal of molecular sciences.

[2]  G. Shulman,et al.  Nonalcoholic Fatty Liver Disease, Insulin Resistance, and Ceramides. , 2019, The New England journal of medicine.

[3]  D. Mozaffarian,et al.  Trends in Dietary Carbohydrate, Protein, and Fat Intake and Diet Quality Among US Adults, 1999-2016. , 2019, JAMA.

[4]  V. Fuster,et al.  Does Socioeconomic Status Influence the Risk of Subclinical Atherosclerosis?: A Mediation Model. , 2019, Journal of the American College of Cardiology.

[5]  Hyungwon Choi,et al.  Large-scale lipidomics identifies associations between plasma sphingolipids and T2DM incidence. , 2019, JCI insight.

[6]  James E. Cox,et al.  Targeting a ceramide double bond improves insulin resistance and hepatic steatosis , 2019, Science.

[7]  F. Hu,et al.  The dietary transition and its association with cardiometabolic mortality among Chinese adults, 1982-2012: a cross-sectional population-based study. , 2019, The lancet. Diabetes & endocrinology.

[8]  T. Langer,et al.  CerS6-Derived Sphingolipids Interact with Mff and Promote Mitochondrial Fragmentation in Obesity , 2019, Cell.

[9]  D. Siscovick,et al.  Circulating sphingolipids, fasting glucose, and impaired fasting glucose: The Strong Heart Family Study , 2018, EBioMedicine.

[10]  L. Liang,et al.  Plasma Lipidomic Profiling and Risk of Type 2 Diabetes in the PREDIMED Trial , 2018, Diabetes Care.

[11]  D. Herr,et al.  Sphingolipidomics analysis of large clinical cohorts. Part 1: Technical notes and practical considerations. , 2018, Biochemical and biophysical research communications.

[12]  Dermot F. Reilly,et al.  Relation of plasma ceramides to visceral adiposity, insulin resistance and the development of type 2 diabetes mellitus: the Dallas Heart Study , 2018, Diabetologia.

[13]  Cassandra N. Spracklen,et al.  Identification and functional analysis of glycemic trait loci in the China Health and Nutrition Survey , 2018, PLoS genetics.

[14]  D. Siscovick,et al.  Circulating Sphingolipids, Insulin, HOMA-IR, and HOMA-B: The Strong Heart Family Study , 2018, Diabetes.

[15]  V. Salomaa,et al.  Ceramide stearic to palmitic acid ratio predicts incident diabetes , 2018, Diabetologia.

[16]  Frank B. Hu,et al.  Global aetiology and epidemiology of type 2 diabetes mellitus and its complications , 2018, Nature Reviews Endocrinology.

[17]  M. Hussain,et al.  Sphingolipids and Lipoproteins in Health and Metabolic Disorders , 2017, Trends in Endocrinology & Metabolism.

[18]  Yichong Li,et al.  Prevalence and Ethnic Pattern of Diabetes and Prediabetes in China in 2013 , 2017, JAMA.

[19]  N. Abate,et al.  Risk of Obesity-Related Cardiometabolic Complications in Special Populations: A Crisis in Asians. , 2017, Gastroenterology.

[20]  Ioannis Xenarios,et al.  Plasma Dihydroceramides Are Diabetes Susceptibility Biomarker Candidates in Mice and Humans. , 2017, Cell reports.

[21]  P. Meikle,et al.  Sphingolipids and phospholipids in insulin resistance and related metabolic disorders , 2017, Nature Reviews Endocrinology.

[22]  Mark Woodward,et al.  Plasma Lipidomic Profiles Improve on Traditional Risk Factors for the Prediction of Cardiovascular Events in Type 2 Diabetes Mellitus , 2016, Circulation.

[23]  Christian Gieger,et al.  Non-targeted metabolomics combined with genetic analyses identifies bile acid synthesis and phospholipid metabolism as being associated with incident type 2 diabetes , 2016, Diabetologia.

[24]  L. Liang,et al.  Early Prediction of Developing Type 2 Diabetes by Plasma Acylcarnitines: A Population-Based Study , 2016, Diabetes Care.

[25]  D. Siscovick,et al.  Genome-wide meta-analyses identify novel loci associated with n-3 and n-6 polyunsaturated fatty acid levels in Chinese and European-ancestry populations. , 2016, Human molecular genetics.

[26]  S. Summers,et al.  Ceramides – Lipotoxic Inducers of Metabolic Disorders , 2015, Trends in Endocrinology & Metabolism.

[27]  K. Yuyama,et al.  Altered levels of serum sphingomyelin and ceramide containing distinct acyl chains in young obese adults , 2014, Nutrition & Diabetes.

[28]  C. Magnan,et al.  Roles of Sphingolipid Metabolism in Pancreatic β Cell Dysfunction Induced by Lipotoxicity , 2014, Journal of clinical medicine.

[29]  Qi Sun,et al.  Associations of erythrocyte fatty acids in the de novo lipogenesis pathway with risk of metabolic syndrome in a cohort study of middle-aged and older Chinese. , 2013, The American journal of clinical nutrition.

[30]  A. Peters,et al.  Identification of Serum Metabolites Associated With Risk of Type 2 Diabetes Using a Targeted Metabolomic Approach , 2013, Diabetes.

[31]  K. Node,et al.  Mitochondrial Dysfunction and Increased Reactive Oxygen Species Impair Insulin Secretion in Sphingomyelin Synthase 1-null Mice* , 2010, The Journal of Biological Chemistry.

[32]  J. Benito-León,et al.  Several factors influenced attrition in a population-based elderly cohort: neurological disorders in Central Spain Study. , 2010, Journal of clinical epidemiology.

[33]  Thomas Meitinger,et al.  Genetic Determinants of Circulating Sphingolipid Concentrations in European Populations , 2009, PLoS genetics.

[34]  O. Franco,et al.  Obesity related metabolic abnormalities: distribution and geographic differences among middle-aged and older Chinese populations. , 2009, Preventive medicine.

[35]  Seng H. Cheng,et al.  Inhibiting Glycosphingolipid Synthesis Improves Glycemic Control and Insulin Sensitivity in Animal Models of Type 2 Diabetes , 2007, Diabetes.

[36]  O. Franco,et al.  Distributions of C-reactive protein and its association with metabolic syndrome in middle-aged and older Chinese people. , 2007, Journal of the American College of Cardiology.

[37]  A. Merrill,et al.  Sphingolipidomics: high-throughput, structure-specific, and quantitative analysis of sphingolipids by liquid chromatography tandem mass spectrometry. , 2005, Methods.

[38]  G. Zou,et al.  A modified poisson regression approach to prospective studies with binary data. , 2004, American journal of epidemiology.

[39]  M. Zunzunegui,et al.  Loss to follow-up in a longitudinal study on aging in Spain. , 2001, Journal of clinical epidemiology.

[40]  A. Smilde,et al.  Large-scale human metabolomics studies: a strategy for data (pre-) processing and validation. , 2006, Analytical chemistry.