Feasibility and Validity of In-Home Self-Collected Capillary Blood Spot Screening for Type 1 Diabetes Risk
Publication: Diabetes Technology & Therapeutics
Volume 26, Issue Number 2
Abstract
Aims: Self-collection of a blood sample for autoantibody testing has potential to facilitate screening for type 1 diabetes risk. We sought to determine the feasibility and acceptability of this approach and the performance of downstream antibody assays.
Methods: People living with type 1 diabetes and their family members (N = 97) provided paired capillary blood spot and serum samples collected, respectively, by themselves and a health worker. They provided feedback on the ease, convenience, and painfulness of blood spot collection. Islet antibodies were measured in blood spots by antibody detection by agglutination PCR (ADAP) or multiplex enzyme-linked immunoassay (ELISA), and in serum by radioimmunoassay (RIA) or ELISA.
Results: Using serum RIA and ELISA to define antibody status, 50 antibody-negative (Abneg) and 47 antibody-positive (Abpos) participants enrolled, of whom 43 and 47, respectively, returned testable blood spot samples. The majority indicated that self-collection was easier, more convenient, and less painful than formal venesection. The sensitivity and specificity for detection of Abpos by blood spot were, respectively, 85% and 98% for ADAP and 87% and 100% for multiplex ELISA. The specificities by ADAP for each of the four antigen specificities ranged from 98% to 100% and areas under the receiver operator curve from 0.841 to 0.986.
Conclusions: Self-collected blood spot sampling is preferred over venesection by research participants. ADAP and multiplex ELISA are highly specific assays for islet antibodies in blood spots with acceptable performance for use alone or in combination to facilitate screening for type 1 diabetes risk.
Clinical Trial Registration number: ACTRN12620000510943.
Get full access to this article
View all available purchase options and get full access to this article.
Dualities
J.M.W. and PGC direct Type1Screen and serve on the Steering Committee of the National Screening Program. J.M.W. has a research agreement with ENABLE Biosciences that permits data sharing for the purpose of ADAP assay optimization. ENABLE Biosciences donated assay reagents to J.M.W. to facilitate assay implementation and optimization.
References
1. Quattrin T, Mastrandrea LD, Walker LSK. Type 1 diabetes. Lancet 2023;401(10394):2149–2162.
2. Dayan CM, Besser REJ, Oram RA, et al. Preventing type 1 diabetes in childhood. Science 2021;373(6554):506–510.
3. Narendran P. Screening for type 1 diabetes: Are we nearly there yet? Diabetologia 2019;62(1):24–27.
4. Wentworth JM, Oakey H, Craig ME, et al. Decreased occurrence of ketoacidosis and preservation of beta cell function in relatives screened and monitored for type 1 diabetes in Australia and New Zealand. Pediatr Diabetes 2022;23(8):1594–1601.
5. Herold KC, Bundy BN, Long SA, et al. An anti-CD3 antibody, teplizumab, in relatives at risk for type 1 diabetes. N Engl J Med 2019;381(7):603–613.
6. Sims EK, Besser REJ, Dayan C, et al. Screening for type 1 diabetes in the general population: A status report and perspective. Diabetes 2022;71(4):610–623.
7. Ziegler AG, Kick K, Bonifacio E, et al. Yield of a public health screening of children for islet autoantibodies in Bavaria, Germany. JAMA 2020;323(4):339–351.
8. Navarro M, Nicolas A, Ferrandez A, et al. Colorectal cancer population screening programs worldwide in 2016: An update. World J Gastroenterol 2017;23(20):3632–3642.
9. Hawkes D, Keung MHT, Huang Y, et al. Self-collection for cervical screening programs: From research to reality. Cancers (Basel) 2020;12(4):1053.
10. Till AM, Kenk H, Rjasanowski I, et al. Autoantibody-defined risk for type 1 diabetes mellitus in a general population of schoolchildren: results of the Karlsburg Type 1 Diabetes Risk Study after 18 years. Diabet Med 2015;32(8):1008–1016.
11. So M, O'Rourke C, Bahnson HT, et al. Autoantibody reversion: Changing risk categories in multiple-autoantibody-positive individuals. Diabetes Care 2020;43(4):913–917.
12. Cortez FJ, Gebhart D, Robinson PV, et al. Sensitive detection of multiple islet autoantibodies in type 1 diabetes using small sample volumes by agglutination-PCR. PLoS One 2020;15(11):e0242049.
13. Auchenbach P, Lampasona V, editors. IASP Autoantibody Workshop. IDS Scientific Meeting: Paris; 2023.
14. Knitza J, Tascilar K, Vuillerme N, et al. Accuracy and tolerability of self-sampling of capillary blood for analysis of inflammation and autoantibodies in rheumatoid arthritis patients-results from a randomized controlled trial. Arthritis Res Ther 2022;24(1):125.
15. Australian Institute of Heath and Welfare. AIoHa. Rural and Remote Health. 2022. Available from: https://www.aihw.gov.au/reports/rural-remote-australians/rural-and-remote-health [Last accessed: August 1, 2023].
16. Parviainen A, Harkonen T, Ilonen J, et al. Heterogeneity of type 1 diabetes at diagnosis supports existence of age-related endotypes. Diabetes Care 2022;45(4):871–879.
17. Urrutia I, Martinez R, Calvo B, et al. Autoimmune diabetes from childhood to adulthood: The role of pancreatic autoantibodies and Hla-Drb1 genotype. J Clin Endocrinol Metab 2023;108(11):e1341–e1346
18. Achenbach P, Koczwara K, Knopff A, et al. Mature high-affinity immune responses to (pro)insulin anticipate the autoimmune cascade that leads to type 1 diabetes. J Clin Invest 2004;114(4):589–597.
19. Penno MA, Couper JJ, Craig ME, et al. Environmental determinants of islet autoimmunity (ENDIA): A pregnancy to early life cohort study in children at-risk of type 1 diabetes. BMC Pediatr 2013;13:124.
20. Cortez FJ, Gebhart D, Tandel D, et al. Automation of a multiplex agglutination-PCR (ADAP) type 1 diabetes (T1D) assay for the rapid analysis of islet autoantibodies. SLAS Technol 2022;27(1):26–31.
21. Lind A, de Jesus Cortez F, Ramelius A, et al. Multiplex agglutination-PCR (ADAP) autoantibody assays compared to radiobinding autoantibodies in type 1 diabetes and celiac disease. J Immunol Methods 2022;506:113265.
22. Ziegler AG, Rewers M, Simell O, et al. Seroconversion to multiple islet autoantibodies and risk of progression to diabetes in children. JAMA 2013;309(23):2473–2479.
23. Ng K, Anand V, Stavropoulos H, et al. Quantifying the utility of islet autoantibody levels in the prediction of type 1 diabetes in children. Diabetologia 2023;66(1):93–104.
24. Weiss A, Zapardiel-Gonzalo J, Voss F, et al. Progression likelihood score identifies substages of presymptomatic type 1 diabetes in childhood public health screening. Diabetologia 2022;65(12):2121–2131.
25. Jacobsen LM, Bocchino L, Evans-Molina C, et al. The risk of progression to type 1 diabetes is highly variable in individuals with multiple autoantibodies following screening. Diabetologia 2020;63(3):588–596.
26. Kwon BC, Anand V, Achenbach P, et al. Progression of type 1 diabetes from latency to symptomatic disease is predicted by distinct autoimmune trajectories. Nat Commun 2022;13(1):1514.
27. Bediaga NG, Li-Wai-Suen CSN, Haller MJ, et al. Simplifying prediction of disease progression in pre-symptomatic type 1 diabetes using a single blood sample. Diabetologia 2021;64(11):2432–2444.
28. Willemsen RH, Burling K, Barker P, et al. Frequent monitoring of C-peptide levels in newly diagnosed type 1 subjects using dried blood spots collected at home. J Clin Endocrinol Metab 2018;103(9):3350–3358.
29. Mastronardi CA, Whittle B, Tunningley R, et al. The use of dried blood spot sampling for the measurement of HbA1c: A cross-sectional study. BMC Clin Pathol 2015;15:13.
30. Skyler JS, Krischer JP, Wolfsdorf J, et al. Effects of oral insulin in relatives of patients with type 1 diabetes: The Diabetes Prevention Trial—Type 1. Diabetes Care 2005;28(5):1068–1076.
31. Hannelius U, Beam CA, Ludvigsson J. Efficacy of GAD-alum immunotherapy associated with HLA-DR3-DQ2 in recently diagnosed type 1 diabetes. Diabetologia 2020;63(10):2177–2181.
Information & Authors
Information
Published In
Diabetes Technology & Therapeutics
Volume 26 • Issue Number 2 • February 2024
Pages: 87 - 94
PubMed: 37976038
Copyright
Copyright 2024, Mary Ann Liebert, Inc., publishers.
History
Published in print: February 2024
Published online: 31 January 2024
Published ahead of print: 16 January 2024
Published ahead of production: 17 November 2023
Authors
Authors' Contributions
J.M.W. designed the study and obtained funding. A.B.E.S., G.N., K.W., D.H., and J.M.W. performed laboratory tests. A.B.E.S., G.N., L.C.H., P.G.C., and J.M.W. discussed assay design and analyzed the data. A.B.E.S. and J.M.W. drafted the article, which all the authors edited and approved.
Author Disclosure Statement
No competing financial interests exist.
Funding Information
This study was funded by the Diabetes Australia Research Program (Y22G-WENJ), JDRF Australia (2-SRA-2022-1282-M-X and 4-SRA-2022-1246-M-N), and the Lions Australia Diabetes Foundation.
Metrics & Citations
Metrics
Citations
Export Citation
Export citation
Select the format you want to export the citations of this publication.
View Options
Access content
To read the fulltext, please use one of the options below to sign in or purchase access.⚠ Society Access
If you are a member of a society that has access to this content please log in via your society website and then return to this publication.