An investigation of the pattern and mechanism of comorbidity in patients with Hashimoto’s thyroiditis
Year: 2025
Type: article
Study design: Observational Study
Abstract: Objective: This study aimed to investigate comorbidity patterns and potential pathogenic mechanisms in patients with Hashimoto's thyroiditis (HT). Methods: Patients with HT who visited the outpatient clinic of the Thyroid Department at Dongzhimen Hospital, Beijing University of Chinese Medicine, between June 2021 and December 2024 were included. Association rule analysis and logistic regression analysis were performed using SPSS 25.0 and SPSS Modeler 18.0 to identify comorbidity patterns. Disease targets were screened using the GeneCards database, and protein interaction networks for intersecting targets were constructed using STRING and Cytoscape. GO function and KEGG pathway enrichment analyses were performed with Metascape to uncover relevant targets and potential pathways associated with comorbidities in patients with HT. Results: Among 429 patients with HT, 348 had comorbidities, resulting in a comorbidity prevalence of 81.19%. Association rule analysis identified thyroid nodules (TN) as the core binary comorbidity. The combination of TN and hyperplasia of the mammary gland (HMG) was central to ternary comorbidities, while the trio of TN, HMG, and uterine leiomyomas (UL) characterized quaternary comorbidities. Being a woman and advancing age were associated with increased risk of comorbidities, whereas levothyroxine sodium (L-T4) therapy was linked to reduced risk. Core targets associated with comorbidity prediction included AKT1, TP53, EGFR, INS, and TNF. Key pathways involved were the cancer pathway and PI3K-Akt signaling pathway. Conclusion: The high prevalence of comorbidities in patients with HT warrants increased clinical attention within the medical community.
Source: Frontiers in Endocrinology
Authors: Caihong Zhao, Haodong Xiong, Lingfei Zhu, Azijiang Adali, Weijie Yu, Simiao Tan, Shuying Wang, Chengbowen Zhao, Yan Lin, Zinan Wei, He Huang, Xinyu Peng
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W4413496447
