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Updated: Jul 7, 2025
Parallel Measurement of Circadian Clock Gene Expression and Hormone Secretion in Human Primary Cell Cultures
Published on: November 11, 2016
Identification of key genes modules linking diabetic retinopathy and circadian rhythm
Feng Ling1, Caijie Zhang1, Xin Zhao2
1Tianjin Key Laboratory of Retinal Functions and Diseases, Tianjin Branch of National Clinical Research Center for Ocular Disease, Eye Institute and School of Optometry, Tianjin Medical University Eye Hospital, Tianjin, China.
Background:
Diabetic retinopathy (DR) is a leading cause of vision loss worldwide. Recent studies highlighted the crucial impact of circadian rhythms (CR) on normal retinopathy in response to the external light cues. However, the role of circadian rhythms in DR pathogenesis and potential investigational drugs remains unclear.
Methods:
To investigate the weather CR affects DR, differential expression analysis was employed to identify differentially expressed genes (DEGs) from the GEO database (GSE160306). Functional enrichment analysis was conducted to identify relevant signaling pathways. LASSO regression was utilized to screen pivotal genes. Weighted gene co-expression network anlaysis (WGCNA) was applied to identify different modules. Additionally, we use the Comparative Toxicogenomics Database (CTD) database to search key genes related to drugs or molecular compounds. The diabetic mouse model received three consecutive intraperitoneal injections of streptozotocin (STZ) during 3 successive days.
Results:
We initially identified six key genes associated with circadian rhythm in DR, including COL6A3, IGFBP2, IGHG4, KLHDC7A, RPL26P30, and MYL6P4. Compared to normal tissue, the expression levels of COL6A3 and IGFB2 were significantly increased in DR model. Furthermore, we identified several signaling pathways, including death domain binding, insulin-like growth factor I binding, and proteasome binding. We also observed that COL6A3 was positively correlated with macrophages (cor=0.628296895, p=9.96E-08) and Th17 cells (cor=0.665120835, p=9.14E-09), while IGFBP2 showed a negatively correlated with Tgd (cor=-0.459953045, p=0.000247284) and Th2 cells (cor=-0.442269719, p=0.000452875). Finally, we identified four drugs associated with key genes: Resveratrol, Vitamin E, Streptozocin, and Sulindac.
Conclusion:
Our findings revealed several key genes related to circadian rhythms and several relevant drugs in DR, providing a novel insight into the mechanism of DR and potential implications for future DR treatment. This study contributes to a better understanding of CR in DR and its implications for future therapeutic interventions.
