Prediction of anti-VEGF efficacy in diabetic macular oedema using intraocular cytokines and macular optical coherence tomography
Purpose: In eyes with diabetic macular oedema (DME), aqueous humour (AH) cytokine levels before and after anti-vascular endothelial growth factor (VEGF) treatment were compared and correlated with optical coherence tomography structural parameters.Methods: This prospective study included 56 control patients with cataracts and 83 patients with DME manifesting as diffuse retinal thickening (DRT), cystoid macular oedema and serous retinal detachment (SRD). AH samples were obtained before intravitreal injection of anti-VEGF or cataract surgery. VEGF, interleukin (IL)-6, IL-8, IL-10, interferon-inducible protein 10 (IP-10) and monocyte chemotactic protein 1 (MCP-1) levels were measured by multiplex bead assay. AH cytokine levels, central macular thickness (CMT), number of hyper-reflective foci (HF), continuity of external limiting membrane and ellipsoid zone (EZ) and best-corrected visual acuity were evaluated.Results: In SRD, IL-6 and MCP-1 levels and HF were increased (all p < 0.05) compared to DRT. At baseline, the number of HF was correlated with VEGF, IL-6, IL-8, IP-10 and MCP-1 (all p < 0.05). Eyes sensitive to anti-VEGF treatment had high baseline levels of VEGF, MCP-1, HF and many EZ disruptions (all p < 0.05). DME patients with normal VEGF levels but with high levels of IL-8, IP-10 and MCP-1 (all p < 0.05) had little change in CMT after anti-VEGF treatment (p = 0.678).Conclusions: AH concentrations of some inflammatory cytokines in DME were differentially expressed among the three DME morphologies. HF was associated with VEGF and other inflammatory cytokine levels. Multiple HF at baseline predicted a significant decrease in CMT, and eyes with normal VEGF but increased inflammatory cytokines may be insensitive to anti-VEGF treatment.
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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