Immunophenotype and genetic risk scores to improve autoantibody negative type 1 diabetes classification: study protocol

Shivani K. Patel, Cindy S. Ma, Kirstine J. Bell, Richard Oram, William A. Hagopian, Spiros Fourlanos, Jerry R. Greenfield

Abstract

Background: An estimated 10-30% of type 1 diabetes (T1D) individuals do not have detectable autoantibodies at diagnosis, thus are classified as “idiopathic” or “non-immune.” Given the non-pathogenic role of islet autoantibodies, the validity of excluding an immune basis for disease in such individuals needs to be questioned. The pan-autoantibody negative type 1 diabetes in adults (PANDA) study aims to characterise the immune, clinical and metabolic phenotype of autoantibody negative T1D individuals.

Methods: This is a two-part, multi-centre study which is recruiting 100 participants: autoantibody positive T1D (N=25), autoantibody negative T1D (N=25), latent autoimmune diabetes in adults (N=25) and age- and sex-matched normoglycaemic control (N=25) individuals. Study 1 involves baseline pathology collection and high dimensional immune-phenotyping using flow cytometry. DNA will be extracted from saliva samples to calculate type 1 diabetes genetic risk scores (T1DGRS). Autoantibody negative individuals will undergo monogenic diabetes testing. Study 2 is a prospective, longitudinal sub-study of study 1 participants within 5 years of diagnosis. Beta cell function will be assessed using glucagon stimulated C-peptide at 0, 9 and 18 months. The primary outcome of study 1 is to determine the phenotype of immune cells in autoantibody positive and negative T1D compared to healthy controls. Secondary outcomes of study 1 include clinical and metabolic characteristics and the T1DGRS. The primary outcome of study 2 is the rate of decline of stimulated C-peptide over time.

Conclusions: The PANDA study is the first study of its kind which aims to improve diagnosis and characterisation of autoantibody negative T1D.

Keywords

Autoantibody-negative, Type 1 diabetes, Autoimmune diabetes, Immune phenotype, Characterisation

Full Text:

PDF

References

Bravis V, Kaur A, Walkey HC, et al. Relationship between islet autoantibody status and the clinical characteristics of children and adults with incident type 1 diabetes in a UK cohort. BMJ Open 2018;8:e020904.

Classification of diabetes mellitus. Available at: https://www.who.int/publications/i/item/classification-of-diabetes-mellitus. Accessed on 20 October 2021.

Vipin VP, Zaidi G, Watson K, et al. High prevalence of idiopathic (islet antibody‐negative) type 1 diabetes among Indian children and adolescents. Pediatr Diab. 2021;22:47-51.

Tiberti C, Buzzetti R, Anastasi E. Autoantibody negative new onset Type 1 diabetic patients lacking high risk HLA alleles in a Caucasian population: are these Type 1b diabetes cases? Diab Metab Res Rev. 2000;16:8-14.

Classification and diagnosis of diabetes: standards of medical care in diabetes-2021. Diab Care. 2021;44:S15-33.

Fourlanos S, Narendran P, Byrnes GB, Colman PG, Harrison LC. Insulin resistance is a risk factor for progression to Type 1 diabetes. Diabetol. 2004;47:1661-7.

Wilkin TJ. The accelerator hypothesis: a review of the evidence for insulin resistance as the basis for type I as well as type II diabetes. Int J Obesity. 2009;33:716-26.

Hameed S, Ellard S, Woodhead HJ. Persistently autoantibody negative (PAN) type 1 diabetes mellitus in children. Pediatr Diab. 2011;12:142-9.

Carlsson A, Shepherd M, Ellard S. Absence of Islet autoantibodies and modestly raised glucose values at diabetes diagnosis should lead to testing for MODY: lessons from a 5-year pediatric Swedish national cohort study. Diab Care. 2020;43:82-9.

1Guarnotta V, Vigneri E, Pillitteri G, Ciresi A, Pizzolanti G, Giordano C. Higher cardiometabolic risk in idiopathic versus autoimmune type 1 diabetes: a retrospective analysis. Diab Metab Syndrome. 2018;10.

Aguilera E, Casamitjana R, Ercilla G, Oriola J, Gomis R, Conget I. Adult-onset atypical (type 1) diabetes: additional insights and differences with type 1a diabetes in a european mediterranean population. Diab Care. 2004;27:1108-14.

Catarino D, Silva D, Guiomar J. Non-immune-mediated versus immune-mediated type 1 diabetes: diagnosis and long-term differences-retrospective analysis. Diab Metab Syndrome. 2020;12.

Ahmed S, Cerosaletti K, James E. Standardizing T-Cell biomarkers in type 1 diabetes: challenges and recent advances. Diabetes. 2019;68:1366-79.

Patel KA, Oram RA, Flanagan SE. Type 1 Diabetes genetic risk score: a novel tool to discriminate monogenic and type 1 diabetes. Diabetes. 2016;65:2094-9.

Oram RA, Patel K, Hill A. A Type 1 Diabetes Genetic risk score can aid discrimination between type 1 and type 2 diabetes in young adults. Diab Care. 2016;39:337-44.

Richardson CC, Dromey JA, McLaughlin KA. High frequency of autoantibodies in patients with long duration type 1 diabetes. Diabetologia 2013;56:2538-40.

Williams GM, Long AE, Wilson IV. Beta cell function and ongoing autoimmunity in long-standing, childhood onset type 1 diabetes. Diabetologia. 2016;59:2722-6.

Payne K, Li W, Salomon R, Ma CS. OMIP-063: 28-Color Flow Cytometry Panel for Broad Human Immunophenotyping. Cytometry A. 2020;97:777-81.

Faber OK, Binder C. C-peptide Response to Glucagon: A Test for the Residual -cell Function in Diabetes Mellitus. Diabetes. 1977;26:605-10.

Fourlanos S. Latent autoimmune diabetes in adults : new clinical, immunogenetic and metabolic perspectives. J Univ Melbourne. 2006.

Kenefeck R, Wang CJ, Kapadi T. Follicular helper T cell signature in type 1 diabetes. J Clin Invest. 2015;125:292-303.

Xu X, Shi Y, Cai Y. Inhibition of Increased Circulating Tfh Cell by Anti-CD20 monoclonal antibody in patients with type 1 diabetes. PLoS One. 2013;8:e79858.

Oras A, Peet A, Giese T, Tillmann V, Uibo R. A study of 51 subtypes of peripheral blood immune cells in newly diagnosed young type 1 diabetes patients. Clin Exper Immunol. 2019;198:57-70.

Menart-Houtermans B, Rütter R, Nowotny B. Leukocyte profiles differ between type 1 and type 2 diabetes and are associated with metabolic phenotypes: results from the german diabetes study (GDS). Diab Care. 2014;37:2326-33.

So M, O’Rourke C, Bahnson H, Greenbaum C, Speake C. Autoantibody Reversion: changing risk categories in multiple-autoantibody–positive individuals. Diab Care. 2020;43:191731.

Speake C. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004;363:157-63.