Identification of key genes modules linking diabetic retinopathy and circadian rhythm.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38124748", "kind": "science-record", "revision": 4, "content_hash": "sha256:43bc586bd1f5814cba48826405708f331f19d70661979c562755d752ca9316c5", "created_at": "2026-11-01T19:20:03Z", "updated_at": "2026-11-01T22:53:19Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of key genes modules linking diabetic retinopathy and circadian rhythm.", "doi": "10.3389/fimmu.2023.1260350", "pmid": "38124748", "authors": ["Feng Ling", "Caijie Zhang", "Xin Zhao", "Xiangyang Xin", "Shaozhen Zhao"], "journal": "Frontiers in immunology", "year": 2023, "abstract": "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.\nMethods: 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.\nResults: 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.\nConclusion: 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.", "claims": [{"id": "claim-method", "statement": "To identify differentially expressed genes (DEGs) between DR and normal samples, a differential expression analysis was conducted on 20 normal samples and 39 DR samples from the GSE160306 dataset using the R package ‘DESeq2’ ( Figure 1 ).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38124748", "locator": "sections[14] \"Differential expression analysis and clustering reveals distinct expression patterns in diabetic retinopathy samples\" paragraph 2", "quote": "To identify differentially expressed genes (DEGs) between DR and normal samples, a differential expression analysis was conducted on 20 normal samples and 39 DR samples from the GSE160306 dataset using the R package ‘DESeq2’ ( Figure 1 )."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38124748", "locator": "sections[20] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/supplementary material. 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The diabetic mouse model received three consecutive intraperitoneal i", "o drugs or molecular compounds. The diabetic mouse model received three consecutive intraperito", "ures involving animals. Wild-type male C57BL mice were housed in a temperature-controlled room (23", "d water. To induce diabetes, 3-week-old male mice were fasted and subjected to chemical induction a"], "order_basis": "paper_text_order:939", "id": "assay:1"}, {"role": "data_generation", "definition_id": "cell_imaging", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["he slices were examined using laser scanning confocal microscopy (Zeiss LSM800; Zeiss, Oberkochen, Germany).", "were examined using laser scanning confocal microscopy (Zeiss LSM800; Zeiss, Oberkochen, Germany)."], "order_basis": "paper_text_order:5261", "id": "assay:2"}, {"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["To identify differentially expressed genes (DEGs) between DR and normal samples, a differential expression analysis was conducted on 20 normal samples and 39 DR samples from the GSE160306 dataset using the R package ‘DESeq2’ ( Figure 1 )."], "order_basis": "consumes_earlier_output", "id": "assay:3"}]}