Back

A Novel Association Between Human Papillomavirus and Thyroid Eye Disease

Garg, I.; Meyer, B. I.; Gallo, R. A.; Wester, S. T.; Pelaez, D.

2024-04-30 ophthalmology
10.1101/2024.04.27.24306443 medRxiv
Show abstract

ContextThyroid eye disease (TED) is an autoimmune disease characterized by orbital inflammation and tissue remodeling. TED pathogenesis is poorly understood but is linked to autoantibodies to thyroid-stimulating hormone receptor (TSHR) and insulin-like growth factor 1 receptor (IGF-1R). ObjectiveTo explore the potential involvement of viral infections in TED pathogenesis. MethodsUsing NCBI BLAST, we compared human TSHR and IGF-1R proteins to various viral proteomes, including Papillomaviridae, Paramyxoviridae, Herpesviridae, Enterovirus, Polyomaviridae, and Rhabdoviridae. Enzyme-linked immunoassays (ELISAs) were performed on orbital adipose tissue samples from 22 TED patients and controls to quantify antiviral antibody titers. Demographics and clinical data were reviewed. ResultsHomology analysis revealed conserved motifs between TSHR and IGF-1R with several viral proteins, particularly the human papillomavirus 18 (HPV18) L1 capsid protein. Basic demographic and clinical information between the cohorts were comparable. ELISAs showed statistically significant differences in the average HPV18 L1 IgG normalized optical density levels among tissues of control (M = 0.9387, SD = 0.3548), chronic TED (M = 2.305, SD = 1.064), and active acute TED (M = 4.087, SD = 2.034) patients. These elevated HPV18 L1 IgG titers did not statistically correlate with TSH, T4, or TSI levels, and were elevated in TED patients irrespective of treatment with teprotumumab, indicating a direct immunological response to HPV. ConclusionsThis study presents the first molecular evidence linking HPV and TED, highlighting molecular mimicry between HPV capsid protein and key autoimmunity targets in TED. This suggests an immunological link contributing to TEDs pathogenesis, opening new avenues for understanding and managing the disease.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.