Top

Published in:

01-02-2017 | Article

Peptide serum markers in islet autoantibody-positive children

Authors: Christine von Toerne, Michael Laimighofer, Peter Achenbach, Andreas Beyerlein, Tonia de las Heras Gala, Jan Krumsiek, Fabian J. Theis, Anette G. Ziegler, Stefanie M. Hauck

Published in: Diabetologia | Issue 2/2017

Abstract

Aims/hypothesis

We sought to identify minimal sets of serum peptide signatures as markers for islet autoimmunity and predictors of progression rates to clinical type 1 diabetes in a case–control study.

Methods

A double cross-validation approach was applied to first prioritise peptides from a shotgun proteomic approach in 45 islet autoantibody-positive and -negative children from the BABYDIAB/BABYDIET birth cohorts. Targeted proteomics for 82 discriminating peptides were then applied to samples from another 140 children from these cohorts.

Results

A total of 41 peptides (26 proteins) enriched for the functional category lipid metabolism were significantly different between islet autoantibody-positive and autoantibody-negative children. Two peptides (from apolipoprotein M and apolipoprotein C-IV) were sufficient to discriminate autoantibody-positive from autoantibody-negative children. Hepatocyte growth factor activator, complement factor H, ceruloplasmin and age predicted progression time to type 1 diabetes with a significant improvement compared with age alone.

Conclusion/interpretation

Distinct peptide signatures indicate islet autoimmunity prior to the clinical manifestation of type 1 diabetes and enable refined staging of the presymptomatic disease period.

Available only for authorised users

Insel RA, Dunne JL, Atkinson MA et al (2015) Staging presymptomatic type 1 diabetes: a scientific statement of JDRF, the Endocrine Society, and the American Diabetes Association. Diabetes Care 38:1964–1974CrossRefPubMed

Ziegler AG, Bonifacio E (2012) Age-related islet autoantibody incidence in offspring of patients with type 1 diabetes. Diabetologia 55:1937–1943CrossRefPubMed

Parikka V, Nanto-Salonen K, Saarinen M et al (2012) Early seroconversion and rapidly increasing autoantibody concentrations predict prepubertal manifestation of type 1 diabetes in children at genetic risk. Diabetologia 55:1926–1936CrossRefPubMed

Krischer JP, Lynch KF, Schatz DA et al (2015) The 6 year incidence of diabetes-associated autoantibodies in genetically at-risk children: the TEDDY study. Diabetologia 58:980–987CrossRefPubMedPubMedCentral

Ziegler AG, Rewers M, Simell O et al (2013) Seroconversion to multiple islet autoantibodies and risk of progression to diabetes in children. JAMA 309:2473–2479CrossRefPubMedPubMedCentral

Achenbach P, Bonifacio E, Williams AJ, Ziegler AG, Gale EA, Bingley PJ (2008) Autoantibodies to IA-2β improve diabetes risk assessment in high-risk relatives. Diabetologia 51:488–492CrossRefPubMed

Achenbach P, Warncke K, Reiter J et al (2004) Stratification of type 1 diabetes risk on the basis of islet autoantibody characteristics. Diabetes 53:384–392CrossRefPubMed

Achenbach P, Lampasona V, Landherr U et al (2009) Autoantibodies to zinc transporter 8 and SLC30A8 genotype stratify type 1 diabetes risk. Diabetologia 52:1881–1888CrossRefPubMed

Achenbach P, Koczwara K, Knopff A, Naserke H, Ziegler AG, Bonifacio E (2004) Mature high-affinity immune responses to (pro)insulin anticipate the autoimmune cascade that leads to type 1 diabetes. J Clin Invest 114:589–597CrossRefPubMedPubMedCentral

10.

Mayr A, Schlosser M, Grober N et al (2007) GAD autoantibody affinity and epitope specificity identify distinct immunization profiles in children at risk for type 1 diabetes. Diabetes 56:1527–1533CrossRefPubMed

11.

Yassine H, Borges CR, Schaab MR et al (2013) Mass spectrometric immunoassay and MRM as targeted MS-based quantitative approaches in biomarker development: potential applications to cardiovascular disease and diabetes. Proteomics Clin Appl 7:528–540CrossRefPubMedPubMedCentral

12.

Pin E, Fredolini C, Petricoin EF 3rd (2013) The role of proteomics in prostate cancer research: biomarker discovery and validation. Clin Biochem 46:524–538CrossRefPubMed

13.

Chambers AG, Percy AJ, Simon R, Borchers CH (2014) MRM for the verification of cancer biomarker proteins: recent applications to human plasma and serum. Expert Rev Proteomics 11:137–148CrossRefPubMed

14.

Alberio T, Bucci EM, Natale M et al (2013) Parkinson’s disease plasma biomarkers: an automated literature analysis followed by experimental validation. J Proteomics 90:107–114CrossRefPubMed

15.

von Toerne C, Huth C, de Las Heras Gala T et al (2016) MASP1, THBS1, GPLD1 and ApoA-IV are novel biomarkers associated with prediabetes: the KORA F4 study. Diabetologia 59:1882–1892CrossRef

16.

Metz TO, Qian WJ, Jacobs JM et al (2008) Application of proteomics in the discovery of candidate protein biomarkers in a diabetes autoantibody standardization program sample subset. J Proteome Res 7:698–707CrossRefPubMed

17.

Zhang Q, Fillmore TL, Schepmoes AA et al (2013) Serum proteomics reveals systemic dysregulation of innate immunity in type 1 diabetes. J Exp Med 210:191–203CrossRefPubMedPubMedCentral

18.

Zhi W, Sharma A, Purohit S et al (2011) Discovery and validation of serum protein changes in type 1 diabetes patients using high throughput two dimensional liquid chromatography-mass spectrometry and immunoassays. Mol Cell Proteomics 10:M111.012203CrossRefPubMedPubMedCentral

19.

Moulder R, Bhosale SD, Erkkila T et al (2015) Serum proteomes distinguish children developing type 1 diabetes in a cohort with HLA-conferred susceptibility. Diabetes 64:2265–2278CrossRefPubMed

20.

Ziegler AG, Hummel M, Schenker M, Bonifacio E (1999) Autoantibody appearance and risk for development of childhood diabetes in offspring of parents with type 1 diabetes: the 2-year analysis of the German BABYDIAB Study. Diabetes 48:460–468CrossRefPubMed

21.

Hummel S, Pfluger M, Hummel M, Bonifacio E, Ziegler AG (2011) Primary dietary intervention study to reduce the risk of islet autoimmunity in children at increased risk for type 1 diabetes: the BABYDIET study. Diabetes Care 34:1301–1305CrossRefPubMedPubMedCentral

22.

Giannopoulou EZ, Winkler C, Chmiel R et al (2015) Islet autoantibody phenotypes and incidence in children at increased risk for type 1 diabetes. Diabetologia 58:2317–2323CrossRefPubMed

23.

Torn C, Mueller PW, Schlosser M, Bonifacio E, Bingley PJ (2008) Diabetes Antibody Standardization Program: evaluation of assays for autoantibodies to glutamic acid decarboxylase and islet antigen-2. Diabetologia 51:846–852CrossRefPubMed

24.

Schlosser M, Mueller PW, Torn C, Bonifacio E, Bingley PJ (2010) Diabetes Antibody Standardization Program: evaluation of assays for insulin autoantibodies. Diabetologia 53:2611–2620CrossRefPubMed

25.

Lampasona V, Schlosser M, Mueller PW et al (2011) Diabetes antibody standardization program: first proficiency evaluation of assays for autoantibodies to zinc transporter 8. Clin Chem 57:1693–1702CrossRefPubMed

26.

Expert Committee on the Diagnosis and Classification of Diabetes Mellitus (2003) Report of the expert committee on the diagnosis and classification of diabetes mellitus. Diabetes Care 26(Suppl 1):S5–20

27.

von Toerne C, Kahle M, Schafer A et al (2013) Apoe, Mbl2, and Psp plasma protein levels correlate with diabetic phenotype in NZO mice—an optimized rapid workflow for SRM-based quantification. J Proteome Res 12:1331–1343CrossRef

28.

Graessel A, Hauck SM, von Toerne C et al (2015) A combined omics approach to generate the surface atlas of human naive CD4⁺ T cells during early T-cell receptor activation. Mol Cell Proteomics 14:2085–2102

29.

Hauck SM, Dietter J, Kramer RL et al (2010) Deciphering membrane-associated molecular processes in target tissue of autoimmune uveitis by label-free quantitative mass spectrometry. Mol Cell Proteomics 9:2292–2305CrossRefPubMedPubMedCentral

30.

MacLean B, Tomazela DM, Shulman N et al (2010) Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics 26:966–968CrossRefPubMedPubMedCentral

31.

Abbatiello SE, Mani DR, Keshishian H, Carr SA (2010) Automated detection of inaccurate and imprecise transitions in peptide quantification by multiple reaction monitoring mass spectrometry. Clin Chem 56:291–305CrossRefPubMed

32.

Laimighofer M, Krumsiek J, Buettner F, Theis FJ (2016) Unbiased prediction and feature selection in high-dimensional survival regression. J Comput Biol 23:279–290CrossRefPubMedPubMedCentral

33.

Uno H, Cai T, Pencina MJ, D’Agostino RB, Wei LJ (2011) On the C-statistics for evaluating overall adequacy of risk prediction procedures with censored survival data. Stat Med 30:1105–1117PubMedPubMedCentral

34.

Xu N, Dahlback B (1999) A novel human apolipoprotein (apoM). J Biol Chem 274:31286–31290CrossRefPubMed

35.

Wu X, Niu N, Brismar K et al (2009) Apolipoprotein M promoter polymorphisms alter promoter activity and confer the susceptibility to the development of type 1 diabetes. Clin Biochem 42:17–21CrossRefPubMed

36.

Mughal SA, Park R, Nowak N et al (2013) Apolipoprotein M can discriminate HNF1A-MODY from type 1 diabetes. Diabet Med 30:246–250CrossRefPubMedPubMedCentral

37.

Singh IP, Chopra AK, Coppenhaver DH, Ananatharamaiah GM, Baron S (1999) Lipoproteins account for part of the broad non-specific antiviral activity of human serum. Antiviral Res 42:211–218CrossRefPubMed

38.

Tsai HC, Han MH (2016) Sphingosine-1-phosphate (S1P) and S1P signaling pathway: therapeutic targets in autoimmunity and inflammation. Drugs 76:1067–1079CrossRefPubMed

39.

Ley K (2016) 2015 Russell Ross Memorial Lecture in Vascular Biology: protective autoimmunity in atherosclerosis. Arterioscler Thromb Vasc Biol 36:429–438CrossRefPubMed

40.

Black LL, Srivastava R, Schoeb TR, Moore RD, Barnes S, Kabarowski JH (2015) Cholesterol-independent suppression of lymphocyte activation, autoimmunity, and glomerulonephritis by apolipoprotein A-I in normocholesterolemic lupus-prone mice. J Immunol 195:4685–4698CrossRefPubMedPubMedCentral

41.

Moreno-Navarrete JM, Martinez-Barricarte R, Catalan V et al (2010) Complement factor H is expressed in adipose tissue in association with insulin resistance. Diabetes 59:200–209CrossRefPubMed

42.

Cunningham J, Leffell M, Mearkle P, Harmatz P (1995) Elevated plasma ceruloplasmin in insulin-dependent diabetes mellitus: evidence for increased oxidative stress as a variable complication. Metabolism 44:996–999CrossRefPubMed

43.

Memisogullari R, Bakan E (2004) Levels of ceruloplasmin, transferrin, and lipid peroxidation in the serum of patients with type 2 diabetes mellitus. J Diabetes Complications 18:193–197CrossRefPubMed

Title: Peptide serum markers in islet autoantibody-positive children
Authors: Christine von Toerne
Michael Laimighofer
Peter Achenbach
Andreas Beyerlein
Tonia de las Heras Gala
Jan Krumsiek
Fabian J. Theis
Anette G. Ziegler
Stefanie M. Hauck
Publication date: 01-02-2017
Publisher: Springer Berlin Heidelberg
Published in: Diabetologia / Issue 2/2017
Print ISSN: 0012-186X
Electronic ISSN: 1432-0428
DOI: https://doi.org/10.1007/s00125-016-4150-x

ACC 2024 Congress Coverage

Heart Failure Video

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Peptide serum markers in islet autoantibody-positive children

Abstract

Aims/hypothesis

Methods

Results

Conclusion/interpretation

ACC 2024 Congress Coverage

Year in Review: Heart failure and cardiomyopathies

Semaglutide benefits people with type 2 diabetes and obesity-related heart failure

Incentivised to exercise

New intervention for STEMI-related cardiogenic shock

» View more highlights on the ACC 2024 congress hub page

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Abstract

Aims/hypothesis

Methods

Results

Conclusion/interpretation

Please log in to get access to this content

Other articles of this Issue 2/2017

Type 1 diabetes mellitus and risk of incident epilepsy: a population-based, open-cohort study

Adipocyte STAT5 deficiency promotes adiposity and impairs lipid mobilisation in mice

A Tbc1d1 Ser231Ala-knockin mutation partially impairs AICAR- but not exercise-induced muscle glucose uptake in mice

Erratum to: Glucose concentrations of less than 3.0 mmol/l (54 mg/dl) should be reported in clinical trials: a joint position statement of the American Diabetes Association and the European Association for the Study of Diabetes

Exposure to severe famine in the prenatal or postnatal period and the development of diabetes in adulthood: an observational study

Insulitis in human diabetes: a histological evaluation of donor pancreases

ACC 2024 Congress Coverage

Year in Review: Heart failure and cardiomyopathies

Semaglutide benefits people with type 2 diabetes and obesity-related heart failure

Incentivised to exercise

New intervention for STEMI-related cardiogenic shock

» View more highlights on the ACC 2024 congress hub page