{'fraction_non_alphanumeric': 0.02763677382966723, 'fraction_numerical': 0.029328821206993795, 'mean_word_length': 5.2027972027972025, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Biomarker identification of thyroid associated ophthalmopathy using microarray data.

AIM
To uncover the underlying pathogenesis of thyroid associated ophthalmopathy (TAO) and explore potential biomarkers of this disease.


METHODS
The expression profile GSE9340, which was downloaded from Gene Expression Omnibus database, included 18 specimens from 10 TAO patients and 8 hyperthyroidism patients without ophthalmopathy. The platform was HumanRef-8 v2 Expression BeadChip. Raw data were normalized using preprocess. Core package and the differentially expressed genes (DEGs) were identified based on t-test with limma package of R. Functional enrichment analyses were performed recruiting the DAVID tool. Based on STRING database, a protein-protein interaction (PPI) network was constructed, from which a module was extracted. The functional enrichment for genes in the module was performed by the BinGO plugin.


RESULTS
In total, 861 DEGs (433 up-regulated and 428 down-regulated) between TAO patients and hyperthyroidism patients without ophthalmopathy were identified. Crucial nodes in the PPI network included TPX2, CDCA5, PRC1, KIF23 and MKI67, which were also remarkable in the module and all enriched in cell cycle process. Additionally, MKI67 was highly correlated with TAO. Besides, the DEGs of GTF2F1, SMC3, USF1 and ZNF263 were predicted as transcription factors (TFs).


CONCLUSION
Several crucial genes are identified such as TPX2, CDCA5, PRC1 and KIF23, which all might play significant roles in TAO via the regulation of cell cycle process. Regulatory relationships between TPX2 and CDCA5 as well as between PRC1 and KIF23 may exist. Additionally, MKI67 may be a potent biomarker of TAO, and SMC3 and ZNF263 may exert their roles as TFs in TAO progression.