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A High-Throughput Multiplexed Screening for Type 1 Diabetes, Celiac Diseases, and COVID-19
Published on: July 5, 2022
Non-HLA risk variants in a type 1 diabetes pediatric population: Clinical and autoimmune profiles
Miriam Díez Blanco1, Clara Pérez Barrios1, María Encarnación Donoso Navarro1
1Servicio de Bioquímica Clínica - Análisis Clínicos, Hospital Universitario Puerta de Hierro-Majadahonda, Madrid, Spain.
Introduction:
The interplay between genetic and environmental factors plays a critical role in the development of type 1 diabetes (T1D). While variants in non-HLA coding regions have been identified as potential therapeutic targets, their exact contribution to the pathophysiology of disease remains unclear. The aim of the study was to characterize six non-HLA variants in pediatric patients with T1D and explore their potential association with clinical parameters and other autoimmune diseases, such as thyroiditis and celiac disease (CD).
Methods:
We analyzed six variants (c.1858T>C, c.49A>G, c.919A>G, c.784T>C, c.461G>A, and c.-17-6T, located in the PTPN22, CTLA4, CD226, SH2B3, FUT2 and INS genes) in a pediatric sample (age ≤ 18 years) with T1D, comparing it with a CD group and a control group. The variants were genotyped using quantitative PCR with TaqMan probes.
Results:
We observed that variants in PTPN22, CD226 and INS were overrepresented in patients with T1D compared to the control and CD groups. There was a significant association between the presence of anti-glutamate decarboxylase autoantibodies (GADA) and the CTLA4 variant (P = .005), as well as between insulinoma-associated anti-tyrosine phosphatase autoantibodies (IA2A) and the PTPN22 variant (P < .03).The number of positive pancreatic autoantibodies was associated with the FUT2 variant (P = .02). Additionally, age at onset was associated with CTLA4 (P = .01) and SH2B3 (P < .05) variants.
Conclusion:
The analyzed variants in the PTPN22, CD226, and INS genes were overrepresented in pediatric patients with T1D, suggesting potential therapeutic targets for modulating the autoimmune process. Their associations with specific clinical and autoimmune profiles can be applied in the identification of high-risk patients and help optimize their follow-up.
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