Flare changes after intravitreal injection of ocriplasmin in symptomatic vitreomacular traction syndrome

Identification of novel gene signatures and immune cell infiltration in intervertebral disc degeneration using bioinformatics analysis

Background: Intervertebral disc degeneration (IDD) is the leading cause of lower back pain, and an overall understanding of the molecular mechanisms related to IDD is still lacking. The purpose of this study was to explore gene signatures and immune cell infiltration related to IDD via bioinformatics analysis. Methods: A total of five expression profiles of mRNA and non-coding RNA were downloaded from the Gene Expression Omnibus (GEO) database. The potentially involved lncRNA/circRNA-miRNA-mRNA networks and protein-protein interaction networks were constructed by miRNet, circBank, STRING, and the Cytoscape database. Gene ontology, Kyoto Encyclopaedia of Genes and Genomes Analysis, Gene Set Enrichment Analysis, Gene Set Variation Analysis, Immune Infiltration Analysis, and Drug-Gene Interaction were used to analyse the top 20 hub genes. RT-qPCR was conducted to confirm the 12 differential expressions of genes both in the nucleus pulposus and annulus fibrosus tissues Results: There were 346 differentially expressed mRNAs, 12 differentially expressed miRNAs, 883 differentially expressed lncRNAs, and 916 differentially expressed circRNAs in the GEO database. Functional and enrichment analyses revealed hub genes associated with platelet activation, immune responses, focal adhesion, and PI3K-Akt signalling. The apoptotic pathway, the reactive oxygen species pathway, and oxidative phosphorylation play an essential role in IDD. Immune infiltration analysis demonstrated that the Treg cells had significant infiltration, and three levels of immune cells, including dendritic cells, Th2 cells, and tumour-infiltrating lymphocytes, were inhibited in IDD. Drug-gene interaction analysis showed that COL1A1 and COL1A2 were targeted by collagenase clostridium histolyticum, ocriplasmin, and PDGFRA was targeted by 66 drugs or molecular compounds. Finally, 24 cases of IDD tissues and 12 cases of normal disc tissues were collected, and the results of RT-qPCR were consistent with the bioinformatics results. Conclusion: Our data indicated that the 20 hub genes and immune cell infiltration were involved in the pathological process of IDD. In addition, the PDGFRA and two potential drugs were found to be significant in IDD development.

Pneumatic vitreolysis versus vitrectomy for the treatment of vitreomacular traction syndrome and macular holes: complication analysis and systematic review with meta-analysis of functional outcomes

BACKGROUND

We conducted a systematic review to compare  the effects of pneumatic vitreolysis (PV), enzymatic vitreolysis (EVL) with ocriplasmin, and pars plana vitrectomy (PPV) on vitreomacular traction (VMT) syndrome and macular holes (MHs) to assess their efficacy as treatment options.

METHODS

Databases, including PubMed, ClinicalTrials.gov ( www.

CLINICALTRIALS

gov ), the Cochrane Central Register of Controlled Trials (CENTRAL)-including the Cochrane Eyes and Vision Group Trials Register (The Cochrane Library 2013, Issue 2)-, Ovid MEDLINE, and EMBASE (January 2000-October 2022), were searched to identify studies comparing the outcomes of PV versus PPV, PPV versus ocriplasmin and ocriplasmin versus PV. RevMan 5.1 was used for the meta-analysis of the studies.

RESULTS

Among the 89 studies, 79 were considered eligible for qualitative analysis, and 10 quantitative studies were subjected to meta-analysis. PPV resulted in better postoperative visual acuity improvement than ocriplasmin (standardized mean deviation (SMD) = 0.38, 95% CI 0.03-0.73, p = 0.0003). PV resulted in no significant difference in visual improvement compared  with  PPV (SMD = - 0.15, 95% CI - 0.47 to 0.16, p = 0.35). PPV was significantly more effective in terms of the VMT release rate (risk ratio = 0.48, 95% CI 0.38-0.62, p = 0.00001) and MH closure rate (risk ratio = 0.49, 95% CI 0.30-0.81, p = 0.006) than ocriplasmin. PV was more effective than ocriplasmin in terms of the VMT release rate (risk ratio = 0.49, 95% CI 0.35-0.70, p = 0.0001). Qualitative analysis showed MH closure rates of 46%, 47.8%, and 95% and VMT releases rates of 46%, 68% and 100% after ocriplasmin, PV, and PPV treatments, respectively.  Adverse events and postoperative complications occurring after treatment have also been documented in these studies.

CONCLUSION

PPV appears to be the most promising option for MH closure and VMT release, with fewer serious complications than EVL  or PV. However, given the limited number of studies comparing these treatments, further research is needed to establish the superiority of PPV over the other options.

Association between blood-aqueous barrier disruption and extent of retinal detachment

PURPOSE

To investigate the association between anatomical features of rhegmatogenous retinal detachment (RRD) and the extent of blood-aqueous barrier disorder measured by non-invasiv laser flare photometry.

METHODS

Retrospective evaluation of consecutive patients with RRD that underwent surgery between November 2016 and October 2018. Descriptive evaluation of pre- and postoperative parameters and correlation to preoperative laser flare value, extent of retinal detachment and re-detachment rate were performed.

RESULTS

266 patients (mean age 62.73 ± 10.40 years, 62.8% male) were included. Mean preoperative flare value was 11.0 ± 11.9 pc/ms. In pseudophakia flare values were higher than in phakia (12.7 ± 10.4 pc/ms versus 9.8 ± 12.9 pc/ms; p = 0.042). Flare increased and correlated significantly with the number of affected retinal quadrants (Q) (1 Q 6.4 ± 3.3 pc/ms; 2 Q 10.5 ± 8.8 pc/ms; 3 Q 15.6 ± 9.1 pc/ms; 4 Q 27.5 ± 33.3 pc/ms; p < 0.001; r = 0.40). Macular status correlated significantly with flare values (macula on 8.6 ± 7.1 pc/ms, off 13.1 ± 15.0 pc/ms; p = 0.004; r = 0.17).

CONCLUSION

The level of objective tyndallometry in RRD seems to be influenced by lens status and extent of retinal detachment. Thus, the greater the affected retinal area is, the more blood-aqueous barrier disruption seems to be present.

Lens status and degree of lens opacity influence laser flare photometry (objective tyndallometry)

PURPOSE

Objective tyndallometry using laser flare photometry can be utilized e.g., in management of uveitis. Previous studies showed a significant difference in flare values between pseudophakic and phakic eyes. We investigate a potential association between the degree of lens opacification and flare value in a large cohort phakic eyes.

METHODS

Retrospective, non-interventional single center study. Laser flare values of 460 healthy fellow eyes from two large cohorts (primary rhegmatogenous retinal detachment (RRD), macular holes (MH)) were correlated with lens status, degree of lens opacity, and age.

RESULTS

Out of 460 patients (mean age 64.6 ± 11.2, 57% male) 30.4% were pseudophakic (70.2 ± 10.9) and 69.6% phakic, of which 47.8% showed a clear lens (57.3 ± 9.1), 43.2% an mild cataract (65.2 ± 9.0) and 9.0% a moderate cataract (73.5 ± 9.0).In pseudophakia, flare (8.14 ± 4.6 pc/ms) was significantly higher compared to phakia (6.4 ± 3.9 pc/ms; p < 0.001). In phakic eyes, flare values increased significantly with increasing lens opacity (clear lens 5.3 ± 2.8 pc/ms; mild cataract 7.0 ± 4.0 pc/ms; moderate cataract 9.5 ± 6.1 pc/ms; p < 0.001). In clear lenses and mild cataract, age correlated significantly with flare (two-sided, p < 0.001, clear lenses R = 0.3; mild cataract R = 0.4). In clear lenses, flare values increased with age by 0.09 per year, in mild cataract by 0.17 (regression coefficients). No significant correlation was found between age and flare value in moderate cataract and pseudophakic eyes.

CONCLUSION

The level of objective tyndallometry seems to be dependent on lens status, degree of lens opacity and age. These factors should therefore be taken into account when interpreting laser flare values in the future.

Identification of the circRNA–miRNA–mRNA regulatory network in osteoarthritis using bioinformatics analysis

Background: Osteoarthritis (OA) is a degenerative joint disease that seriously affects the quality of people. Unfortunately, the pathogenesis of OA has not been fully known. Therefore, this study aimed to construct a ceRNA regulatory network related to OA to explore the pathogenesis of OA.

Methods: Differentially expressed circRNAs (DEcircRNAs), microRNAs (DEmiRNAs), and mRNAs (DEmRNAs) were obtained from the Gene Expression Omnibus microarray data (GSE175959, GSE105027, and GSE169077). The miRNA response elements and target mRNAs were identified using bioinformatics approaches. Additionally, a circRNA–miRNA–mRNA network was established using Cytoscape version 3.8.0. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of mRNAs in the network were conducted to explore the possible mechanisms underlying OA development. Protein–protein interaction (PPI) analysis was performed to determine the hub genes. Based on the hub genes, a sub network was constructed using Cytoscape 3.8.0 version. Finally, connectivity map (CMap) and drug–gene interaction database (DGIdb) analyses were performed to identify the potential therapeutic targets for OA.

Results: Altogether, five DEcircRNAs, 89 DEmiRNAs, and 345 DEmRNAs were identified. Moreover, a circRNA–miRNA–mRNA network was established using three circRNAs, seven miRNAs, and 37 mRNAs. GO and KEGG analyses demonstrated that the mRNAs in the network could be related to the occurrence and development of OA. PPI analysis was performed and six key genes, namely serpin family H member 1 [SERPINH1], collagen type VIII alpha 2 chain [COL8A2], collagen type XV alpha 1 chain [COL15A1], collagen type VI alpha 3 chain [COL6A3], collagen type V alpha 1 chain [COL5A1], and collagen type XI alpha 1 chain [COL11A1], were identified. Furthermore, a circRNA–miRNA–hub gene subnetwork was established in accordance with two circRNAs (hsa_circ_0075320 and hsa_circ_0051428), two miRNAs (hsa-miR-6124 and hsa-miR-1207-5p), and six hub genes (COL11A1, SERPINH1, COL6A3, COL5A1, COL8A2, and COL15A1). Finally, three chemicals (noscapine, diazepam, and TG100-115) based on CMap analysis and two drugs (collagenase Clostridium histolyticum and ocriplasmin) based on DGIdb were discovered as potential treatment options for OA.

Conclusion: This study presents novel perspectives on the pathogenesis and treatment of OA based on circRNA-related competitive endogenous RNA regulatory networks.