Time-resolved autoantibody profiling facilitates stratification of preclinical type 1 diabetes in children
(2019) In Diabetes 68(1). p.119-130- Abstract
Progression to clinical type 1 diabetes varies among children who develop b-cell autoantibodies. Differences in autoantibody patterns could relate to disease progression and etiology. Here we modeled complex longitudinal autoantibody profiles by using a novel wavelet-based algorithm. We identified clusters of similar profiles associated with various types of progression among 600 children from The Environmental Determinants of Diabetes in the Young (TEDDY) birth cohort study; these children developed persistent insulin autoantibodies (IAA), GAD autoantibodies (GADA), insulinoma-associated antigen 2 autoantibodies (IA-2A), or a combination of these, and they were followed up prospectively at 3- to 6-month intervals (median follow-up 6.5... (More)
Progression to clinical type 1 diabetes varies among children who develop b-cell autoantibodies. Differences in autoantibody patterns could relate to disease progression and etiology. Here we modeled complex longitudinal autoantibody profiles by using a novel wavelet-based algorithm. We identified clusters of similar profiles associated with various types of progression among 600 children from The Environmental Determinants of Diabetes in the Young (TEDDY) birth cohort study; these children developed persistent insulin autoantibodies (IAA), GAD autoantibodies (GADA), insulinoma-associated antigen 2 autoantibodies (IA-2A), or a combination of these, and they were followed up prospectively at 3- to 6-month intervals (median follow-up 6.5 years). Children who developed multiple autoantibody types (n = 370) were clustered, and progression from seroconversion to clinical diabetes within 5 years ranged between clusters from 6% (95% CI 0, 17.4) to 84% (59.2, 93.6). Children who seroconverted early in life (median age <2 years) and developed IAA and IA-2A that were stable-positive on follow-up had the highest risk of diabetes, and this risk was unaffected by GADA status. Clusters of children who lacked stable-positive GADA responses contained more boys and lower frequencies of the HLA-DR3 allele. Our novel algorithm allows refined grouping of b-cell autoantibody–positive children who distinctly progressed to clinical type 1 diabetes, and it provides new opportunities in searching for etiological factors and elucidating complex disease mechanisms.
(Less)
- author
- author collaboration
- organization
- publishing date
- 2019
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Diabetes
- volume
- 68
- issue
- 1
- pages
- 12 pages
- publisher
- American Diabetes Association Inc.
- external identifiers
-
- pmid:30305370
- scopus:85058886151
- ISSN
- 0012-1797
- DOI
- 10.2337/db18-0594
- language
- English
- LU publication?
- yes
- id
- cb69de7b-cbad-434d-8667-537a2aca4cf6
- date added to LUP
- 2019-01-03 08:14:45
- date last changed
- 2024-09-17 10:09:14
@article{cb69de7b-cbad-434d-8667-537a2aca4cf6, abstract = {{<p>Progression to clinical type 1 diabetes varies among children who develop b-cell autoantibodies. Differences in autoantibody patterns could relate to disease progression and etiology. Here we modeled complex longitudinal autoantibody profiles by using a novel wavelet-based algorithm. We identified clusters of similar profiles associated with various types of progression among 600 children from The Environmental Determinants of Diabetes in the Young (TEDDY) birth cohort study; these children developed persistent insulin autoantibodies (IAA), GAD autoantibodies (GADA), insulinoma-associated antigen 2 autoantibodies (IA-2A), or a combination of these, and they were followed up prospectively at 3- to 6-month intervals (median follow-up 6.5 years). Children who developed multiple autoantibody types (n = 370) were clustered, and progression from seroconversion to clinical diabetes within 5 years ranged between clusters from 6% (95% CI 0, 17.4) to 84% (59.2, 93.6). Children who seroconverted early in life (median age <2 years) and developed IAA and IA-2A that were stable-positive on follow-up had the highest risk of diabetes, and this risk was unaffected by GADA status. Clusters of children who lacked stable-positive GADA responses contained more boys and lower frequencies of the HLA-DR3 allele. Our novel algorithm allows refined grouping of b-cell autoantibody–positive children who distinctly progressed to clinical type 1 diabetes, and it provides new opportunities in searching for etiological factors and elucidating complex disease mechanisms.</p>}}, author = {{Endesfelder, David and zu Castell, Wolfgang and Bonifacio, Ezio and Rewers, Marian and Hagopian, William A. and She, Jin Xiong and Lernmark, Ake and Toppari, Jorma and Vehik, Kendra and Williams, Alistair J.K. and Yu, Liping and Akolkar, Beena and Krischer, Jeffrey P. and Ziegler, Anette G. and Achenbach, Peter}}, issn = {{0012-1797}}, language = {{eng}}, number = {{1}}, pages = {{119--130}}, publisher = {{American Diabetes Association Inc.}}, series = {{Diabetes}}, title = {{Time-resolved autoantibody profiling facilitates stratification of preclinical type 1 diabetes in children}}, url = {{http://dx.doi.org/10.2337/db18-0594}}, doi = {{10.2337/db18-0594}}, volume = {{68}}, year = {{2019}}, }