Characterization of plasma lipidomics in adolescent subjects with increased risk for type 1 diabetes in the DiPiS cohort

INTRODUCTION

Type 1 diabetes (T1D) is caused by the destruction of pancreatic islet beta cells resulting in total loss of insulin production. Recent studies have suggested that the destruction may be interrelated to plasma lipids.

OBJECTIVES

Specific lipids have previously been shown to be decreased in children who develop T1D before four years of age. Disturbances of plasma lipids prior to clinical diagnosis of diabetes, if true, may provide a novel way to improve prediction, and monitor disease progression.

METHODS

A lipidomic approach was utilized to analyze plasma from 67 healthy adolescent subjects (10-15 years of age) with or without islet autoantibodies but all with increased genetic risk for T1D. The study subjects were enrolled at birth in the Diabetes Prediction in Skåne (DiPiS) study and after 10-15 years of follow-up we performed the present cross-sectional analysis. HLA-DRB345, -DRB1, -DQA1, -DQB1, -DPA1 and -DPB1 genotypes were determined using next generation sequencing. Lipidomic profiles were determined using ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry. Lipidomics data were analyzed according to genotype.

RESULTS

Variation in levels of several specific phospholipid species were related to level of autoimmunity but not development of T1D. Five glycosylated ceramides were increased in insulin autoantibody (IAA) positive adolescent subjects compared to adolescent subjects without this autoantibody. Additionally, HLA genotypes seemed to influence levels of long chain triacylglycerol (TG).

CONCLUSION

Lipidomic profiling of adolescent subjects in high risk of T1D may improve sub-phenotyping in this high risk population.

Systemic TNFα correlates with residual β-cell function in children and adolescents newly diagnosed with type 1 diabetes

BACKGROUND

Type 1 diabetes (T1D) is caused by immune-mediated destruction of the β-cells. After initiation of insulin therapy many patients experience a period of improved residual β-cell function leading to partial disease remission. Cytokines are important immune-modulatory molecules and contribute to β-cell damage in T1D. The patterns of systemic circulating cytokines during T1D remission are not clear but may constitute biomarkers of disease status and progression. In this study, we investigated if the plasma levels of various pro- and anti-inflammatory cytokines around time of diagnosis were predictors of remission and residual β-cell function in children with T1D followed for one year after disease onset.

METHODS

In a cohort of 63 newly diagnosed children (33% females) with T1D with a mean age of 11.3 years (3.3-17.7), ten cytokines were measured of which eight were detectable in plasma samples by Mesoscale Discovery multiplex technology at study start and after 6 and 12 months. Linear regression models were used to evaluate association of cytokines with stimulated C-peptide.

RESULTS

Systemic levels of tumor necrosis factor (TNF)-α, interleukin (IL)-2 and IL-6 inversely correlated with stimulated C-peptide levels over the entire study (P < 0.05). The concentrations of TNFα and IL-10 at study start predicted stimulated C-peptide level at 6 months (P = 0.011 and P = 0.043, respectively, adjusted for sex, age, HbA1c and stage of puberty).

CONCLUSIONS

In recent-onset T1D, systemic cytokine levels, and in particular that of TNFα, correlate with residual β-cell function and may serve as prognostic biomarkers of disease remission and progression to optimize treatment strategies.

TRIAL REGISTRATION

The study was performed according to the criteria of the Helsinki II Declaration and was approved by the Danish Capital Region Ethics Committee on Biomedical Research Ethics (journal number H-3-2014-052). The parents of all participants gave written consent.

Plasma lipid species at type 1 diabetes onset predict residual beta-cell function after 6 months

INTRODUCTION

The identification of metabolomic dysregulation appears promising for the prediction of type 1 diabetes and may also reveal metabolic pathways leading to beta-cell destruction. Recent studies indicate that regulation of multiple phospholipids precede the presence of autoantigens in the development of type 1 diabetes.

OBJECTIVES

We hypothesize that lipid biomarkers in plasma from children with recent onset type 1 diabetes will reflect their remaining beta-cell function and predict future changes in beta-cell function.

METHODS

We performed targeted lipidomic profiling by electrospray ionization tandem mass spectrometry to acquire comparative measures of 354 lipid species covering 25 lipid classes and subclasses in plasma samples from 123 patients < 17 years of age followed prospectively at 1, 3, 6 and 12 months after diagnosis. Lipidomic profiles were analysed using liner regression to investigate the relationship between plasma lipids and meal stimulated C-peptide levels at each time point. P-values were corrected for multiple comparisons by the method of Benjamini and Hochberg.

RESULTS

Linear regression analysis showed that the relative levels of cholesteryl ester, diacylglycerol and triacylglycerol at 1 month were associated to the change in c-peptide levels from 1 to 6 months (corrected p-values of 4.06E-03, 1.72E-02 and 1.72E02, respectively). Medium chain saturated and monounsaturated fatty acids were the major constituents of the di- and triacylglycerol species suggesting a link with increased lipogenesis.

CONCLUSION

These observations support the hypothesis of lipid disturbances as explanatory factors for residual beta-cell function in children with new onset type 1 diabetes.

High Neonatal Blood Iron Content Is Associated with the Risk of Childhood Type 1 Diabetes Mellitus

(1) Background: Iron requirement increases during pregnancy and iron supplementation is therefore recommended in many countries. However, excessive iron intake may lead to destruction of pancreatic β-cells. Therefore, we aim to test if higher neonatal iron content in blood is associated with the risk of developing type 1 diabetes mellitus (T1D) in childhood; (2) Methods: A case-control study was conducted, including 199 children diagnosed with T1D before the age of 16 years from 1991 to 2005 and 199 controls matched on date of birth. Information on confounders was available in 181 cases and 154 controls. Iron was measured on a neonatal single dried blood spot sample and was analyzed by laser ablation inductively coupled plasma mass spectrometry. Multivariate logistic regression was used to evaluate if iron content in whole blood was associated with the risk of T1D; (3) Results: A doubling of iron content increased the odds of developing T1D more than two-fold (odds ratio (95% CI), 2.55 (1.04; 6.24)). Iron content increased with maternal age (p = 0.04) and girls had higher content than boys (p = 0.01); (4) Conclusions: Higher neonatal iron content associates to an increased risk of developing T1D before the age of 16 years. Iron supplementation during early childhood needs further investigation, including the causes of high iron in neonates.

Metabolomic Biomarkers in the Progression to Type 1 Diabetes

Metabolomics is the snapshot of all detectable metabolites and lipids in biological materials and has potential in reflecting genetic and environmental factors contributing to the development of complex diseases, such as type 1 diabetes. The progression to seroconversion to development of type 1 diabetes has been studied using this technique, although in relatively small cohorts and at limited time points. Overall, three observations have been consistently reported; phospholipids at birth are lower in children developing type 1 diabetes early in childhood, methionine levels are lower in children at seroconversion, and triglycerides are increased at seroconversion and associated to microbiome diversity, indicating an association between the metabolome and microbiome in type 1 diabetes progression.

Lipidomic and metabolomic characterization of a genetically modified mouse model of the early stages of human type 1 diabetes pathogenesis

The early mechanisms regulating progression towards beta cell failure in type 1 diabetes (T1D) are poorly understood, but it is generally acknowledged that genetic and environmental components are involved. The metabolomic phenotype is sensitive to minor variations in both, and accordingly reflects changes that may lead to the development of T1D. We used two different extraction methods in combination with both liquid- and gas chromatographic techniques coupled to mass spectrometry to profile the metabolites in a transgenic non-diabetes prone C57BL/6 mouse expressing CD154 under the control of the rat insulin promoter (RIP) crossed into the immuno-deficient recombination-activating gene (RAG) knockout (-/-) C57BL/6 mouse, resembling the early stages of human T1D. We hypothesized that alterations in the metabolomic phenotype would characterize the early pathogenesis of T1D, thus metabolomic profiling could provide new insight to the development of T1D. Comparison of the metabolome of the RIP CD154 × RAG^-/- mice to RAG^-/- mice and C57BL/6 mice revealed alterations of >100 different lipids and metabolites in serum. Low lysophosphatidylcholine levels, accumulation of ceramides as well as methionine deficits were detected in the pre-type 1 diabetic mice. Additionally higher lysophosphatidylinositol levels and low phosphatidylglycerol levels where novel findings in the pre-type 1 diabetic mice. These observations suggest that metabolomic disturbances precede the onset of T1D.

Do post-translational beta cell protein modifications trigger type 1 diabetes?

Type 1 diabetes is considered an autoimmune disease characterised by specific T cell-mediated destruction of the insulin-producing beta cells. Yet, except for insulin, no beta cell-specific antigens have been discovered. This may imply that the autoantigens in type 1 diabetes exist in modified forms capable of specifically triggering beta cell destruction. In other immune-mediated diseases, autoantigens targeted by the immune system have undergone post-translational modification (PTM), thereby creating tissue-specific neo-epitopes. In a similar manner, PTM of beta cell proteins might create beta cell-specific neo-epitopes. We suggest that the current paradigm of type 1 diabetes as a classical autoimmune disease should be reconsidered since the immune response may not be directed against native beta cell proteins. A modified model for the pathogenetic events taking place in islets leading to the T cell attack against beta cells is presented. In this model, PTM plays a prominent role in triggering beta cell destruction. We discuss literature of relevance and perform genetic and human islet gene expression analyses. Both direct and circumstantial support for the involvement of PTM in type 1 diabetes exists in the published literature. Furthermore, we report that cytokines change the expression levels of several genes encoding proteins involved in PTM processes in human islets, and that there are type 1 diabetes-associated polymorphisms in a number of these. In conclusion, data from the literature and presented experimental data support the notion that PTM of beta cell proteins may be involved in triggering beta cell destruction in type 1 diabetes. If the beta cell antigens recognised by the immune system foremost come from modified proteins rather than native ones, the concept of type 1 diabetes as a classical autoimmune disease is open for debate.

Serum amyloid A and C-reactive protein levels may predict microalbuminuria and macroalbuminuria in newly diagnosed type 1 diabetic patients

BACKGROUND

In this study we evaluated the association of baseline levels of six different candidate proteins for the development of microalbuminuria and macroalbuminuria in type 1 diabetic patients, who were followed for approximately 30 years. Two of the proteins are markers of inflammation: serum amyloid A (SAA) and C-reactive protein (CRP), three are involved in lipid metabolism: apolipoprotein A1, apolipoprotein E and adiponectin and the last protein, fibronectin, is related to structural changes.

METHODS

A nested case control study population of 60 patients from an inception cohort of type 1 diabetic patients where 20 developed microalbuminuria followed by macroalbuminuria and 40 stayed normoalbuminuric during approximately 30 years of follow-up time was used to evaluate baseline levels of the six candidate biomarkers. The proteins were quantified by multiplexed immunoassays.

RESULTS

Log SAA levels were borderline predictor of microalbuminuria, HR 2.31 (1-5.4) p=0.053 in a univariate Cox regression model and predicted the development of macroalbuminuria HR 2.432 (1-6) p=0.049, also univariate. When adjusting for covariates, log SAA predicted the development of microalbuminuria with an HR 4.131 (1.1-15) p=0.03. Log CRP predicted the development of microalbuminuria, HR 2.928 (1.4-6.1) p=0.004, and macroalbuminuria, HR 2.785 (1.3-5.8) p=0.007 in univariate models. When adjusting for covariates, log CRP predicted the development of microalbuminuria with an HR 5.882 (1.7-20.9) p=0.006 and macroalbuminuria with an HR 3.233 (1.1-9.8) p=0.038. Apolipoprotein A1, apolipoprotein E, fibronectin and adiponectin were not associated with development of elevated albumin excretion rate.

CONCLUSIONS

SAA and CRP baseline levels predicted development of micro- and macroalbuminuria during 30 years of follow up, supporting the theory that inflammation is involved in the progression of diabetic nephropathy. Further studies are needed to fully establish the two proteins' potential as additional biomarkers for the development of diabetic nephropathy.

Quantitative iTRAQ-Based Proteomic Identification of Candidate Biomarkers for Diabetic Nephropathy in Plasma of Type 1 Diabetic Patients

Introduction

As part of a clinical proteomics programme focused on diabetes and its complications, it was our goal to investigate the proteome of plasma in order to find improved candidate biomarkers to predict diabetic nephropathy.

Methods

Proteins derived from plasma from a cross-sectional cohort of 123 type 1 diabetic patients previously diagnosed as normoalbuminuric, microalbuminuric or macroalbuminuric were enriched with hexapeptide library beads and subsequently pooled within three groups. Proteins from the three groups were compared by online liquid chromatography and tandem mass spectrometry in three identical repetitions using isobaric mass tags (iTRAQ). The results were further analysed with ingenuity pathway analysis. Levels of apolipoprotein A1, A2, B, C3, E and J were analysed and validated by a multiplex immunoassay in 20 type 1 diabetic patients with macroalbuminuria and 10 with normoalbuminuria.

Results

A total of 112 proteins were identified in at least two out of three replicates. The global protein ratios were further evaluated by ingenuity pathway analysis, resulting in the recognition of apolipoprotein A2, B, C3, D and E as key nodes in the top-rated network. The multiplex immunoassay confirmed the overall protein expression patterns observed by the iTRAQ analysis.

Conclusion

The candidate biomarkers discovered in this cross-sectional cohort may turn out to be progression biomarkers and might have several clinical applications in the treatment and monitoring of diabetic nephropathy; however, they need to be confirmed in a longitudinal cohort.

Electronic supplementary material

The online version of this article (doi:10.1007/s12014-010-9053-0) contains supplementary material, which is available to authorized users.