Changes in histone H3 lysine 4 trimethylation in Hashimoto’s thyroiditis

Lu, Xixuan; Sun, Jing; Liu, Tingting; Zhang, Hao; Shan, Zhongyan; Wang, Teng

doi:10.5114/aoms.2019.85225

Cited by 5 publications

(4 citation statements)

References 29 publications

(30 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…collagen deposition [15], and significantly correlated with the severity of interstitial lung lesions [14]. CCL2 is also highly expressed in thyroid cells of HT patients [16],…”

Section: Discussionmentioning

confidence: 99%

Bioinformatics Analysis of the Cross-talk Between Idiopathic Pulmonary Fibrosis and Hashimoto's Thyroiditis on the Hub Genes and Key Pathways

Ding

Kong

et al. 2022

Preprint

View full text Add to dashboard Cite

Background: Idiopathic pulmonary fibrosis (IPF) is a disease of unknown cause, and there is increasing evidence that Hashimoto's thyroiditis (HT) is closely related to IPF. However, the mechanism of their interaction relationship remains unclear. The purpose of this study was to explore the common genetic features and underlying molecular and immune mechanisms between HT and IPF. Methods: Microarray data of HT and IPF were obtained from the Gene Expression Omnibus (GEO) database. The R software was used to identify the differential genes between two datasets and take the common differential genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of common DEGs present in HT and IPF using R software. The protein-protein interaction (PPI) network of their DEGs was constructed Utilizing the Search Tool for Retrieval of Interacting Genes/Proteins (STRING) database, identified and visualized hub genes by the Cytoscape software. To further investigate the diagnostic value of the hub genes, the receptor operating characteristic (ROC) curves were constructed utilizing the ‘pROC’ package. Subsequently, ROC analysis in two independent GEO datasets further validates the diagnostic value of these six hub genes. A miRNA-gene interactions network, TF-gene interactions network, and TF-miRNA coregulatory network were constructed by the NetworkAnalyst using hub genes and visualized by the Cytoscape for further analysis. In addition, R software was also applied to analyze immunological infiltration. Results: A total of 572 common DEGs were identified from the two datasets for subsequent analysis, which were primarily enriched in immune and inflammatory-related pathways. The plug-in ‘cytoHubba’ of the Cytoscape software was utilized to recognize six shared hub genes after validation, including CYBB, CD68, CD8A, CCL2, CCL5, and PTPRC. We predicted the miRNAs related to hub genes, including miR-106b-5p, miR-155-5p, miR-98-5p, let-7g-3p, and potential TFs (SPI1, NFKB1, NFKB2) through the interaction network. In addition, immune cell infiltration analysis revealed a significant infiltration of central memory CD4+ T cells infiltration in both IPF and HT samples. Conclusions: Bioinformatics studies reveal the common pathogenesis and immunological features between Hashimoto's thyroiditis and idiopathic pulmonary fibrosis. These common pathways and hub genes may serve as molecular biomarkers for diagnosable as well as prognostic assessment, providing new targets and ideas for further mechanistic studies. Additionally, the immune system plays a crucial role in the initiation and progression of both diseases. Keywords: idiopathic pulmonary fibrosis, Hashimoto's Thyroiditis, hub gene, immune process, bioinformatics

show abstract

“…collagen deposition [15], and significantly correlated with the severity of interstitial lung lesions [14]. CCL2 is also highly expressed in thyroid cells of HT patients [16],…”

Section: Discussionmentioning

confidence: 99%

Bioinformatics Analysis of the Cross-talk Between Idiopathic Pulmonary Fibrosis and Hashimoto's Thyroiditis on the Hub Genes and Key Pathways

Ding

Kong

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…In our study, lysine was increased only in the PTC1 group. According to the referenced authors, alterations in lysine degradation affect the occurrence of HT (42).…”

Section: Discussionmentioning

confidence: 99%

Alterations in the amino acid profile in patients with papillary thyroid carcinoma with and without Hashimoto’s thyroiditis

Hellmann,

Turyn,

Zwara

et al. 2023

Front. Endocrinol.

View full text Add to dashboard Cite

PurposeAmino acids (AAs) play important physiological roles in living cells. Some amino acid changes in blood are specific for autoimmune disorders, and some are specific for thyroid cancer. The aims of this study were to profile AA metabolites in the serum of patients with papillary thyroid carcinoma (PTC0) without Hashimoto’s thyroiditis (HT) and patients with PTC with HT (PTC1) and predict whether AA metabolites are associated with thyroid disease, thyroid hormone and thyroid autoantibodies.MethodsA total of 95 serum samples were collected, including 28 healthy controls (HCs), 28 PTC0 patients and 39 PTC1 patients. Serum samples were analyzed by high-performance liquid chromatography-triple stage quadrupole-mass spectrometry (HPLC-TSQ-MS), and twenty-one amino acids (AAs) were detected.ResultsThe serum concentration of glutamic acid was significantly elevated in PTC1 patients compared with PTC0 patients. Lysine was the second amino acid that differentiated these two groups of PTC patients. In addition, the serum concentrations of glycine, alanine and tyrosine were significantly reduced in both PTC patient groups compared to the HC group. These AAs were also correlated with thyroid hormones and antibodies. Five amino acid markers, namely, glycine, tyrosine, glutamic acid, glutamine and arginine, separated/distinguished PTC0 patients from healthy subjects, and eight AA markers, the same AAs as above without arginine but with alanine, leucine, valine and histidine, separated/distinguished PTC1 patients from healthy subjects based on ROC analysis.ConclusionCompared with the HCs, changes in AAs in PTC0 and PTC1 patients showed similar patterns, suggesting the possibility of a common pathophysiological basis, which confirms preliminary research that PTC is significantly associated with pathologically confirmed HT. We found two AAs, lysine and alanine, that can perform diagnostic functions in distinguishing PTC1 from PTC0.

show abstract

“…Lysine is increased in the serum of HT patients, including pTAb, HTS, and HT (9). Lu X et al found that trimethylated histone H3 lysine 4 (H3K4me3), a marker of gene activation, was interrelated with genes of HT (28). As HT progresses in patients, the abnormalities of lysine degradation are more severe.…”

Section: Discussionmentioning

confidence: 99%

Serum metabolomic analysis in patients with Hashimoto’s thyroiditis

Jiang

Zhao²,

Gu³

et al. 2022

Front. Endocrinol.

View full text Add to dashboard Cite

BackgroundHashimoto’s thyroiditis, an autoimmune thyroid disease, shows high morbidity worldwide, particularly in female. Patients with Hashimoto’s thyroiditis have an increasing risk of hypothyroidism during the occurrence and progression of Hashimoto’s thyroiditis. In recent years, metabolomics has been widely applied in autoimmune diseases, especially thyroid disorders. However, metabolites analysis in Hashimoto’s thyroiditis is still absent.MethodsA total of 92 samples were collected, including 35 cases in the control group, 30 cases in the Hashimoto’s thyroiditis with euthyroidism group, and 27 cases in the Hashimoto’s thyroiditis with subclinical hypothyroidism group. SPSS 25.0 for statistical analysis and ROC curve, SIMCA 14.0, Metaboanalysis for multifactor analysis, and Origin 2021 for correlation analysis.Results21 metabolites were identified. 10 metabolites were obtained from control group versus HTE group, 8 serum metabolites were abnormal between control group and HTS group, 3 metabolites were derived from HTE group versus HTS. Kyoto Encyclopedia of Genes and Genomes Enrichment analysis showed that fatty acid degradation, Arginine, and proline metabolism have a significant impact on HTE, while lysine degradation, tyrosine metabolism play an important role HTS group, compared to control group. In the comparison between the HTE and HTS group, Valine, leucine, and isoleucine degradation and Valine, leucine, and isoleucine biosynthesis exists a key role. Correlation analysis shows clinical are not related to metabolites. ROC curve indicates SM, LPC, PC can efficiency in identification patients with HT in different clinical stage from healthy individuals.ConclusionSerum metabolites were changed in HT. Phospholipids such as SM, LPC, PC influence the pathogenesis of Hashimoto’s thyroiditis. Fatty acid degradation and lysine degradation pathways have an impact on different clinical stage of HT.

show abstract

Changes in histone H3 lysine 4 trimethylation in Hashimoto’s thyroiditis

Cited by 5 publications

References 29 publications

Bioinformatics Analysis of the Cross-talk Between Idiopathic Pulmonary Fibrosis and Hashimoto's Thyroiditis on the Hub Genes and Key Pathways

Bioinformatics Analysis of the Cross-talk Between Idiopathic Pulmonary Fibrosis and Hashimoto's Thyroiditis on the Hub Genes and Key Pathways

Alterations in the amino acid profile in patients with papillary thyroid carcinoma with and without Hashimoto’s thyroiditis

Serum metabolomic analysis in patients with Hashimoto’s thyroiditis

Contact Info

Product

Resources

About