Gene expression profile analyses to identify potential biomarkers for myopia

Comparative analysis of corneal parameters in simple myopic anisometropia using Scheimpflug technology

Purpose

This study aims to investigate the differences in binocular corneal parameters and their interrelation with binocular biometric parameters asymmetry in patients with simple myopic anisometropia, thereby elucidating the influence of myopia process on various corneal parameters.

Methods

In this cross-sectional study, 65 patients with anisometropia in monocular myopia were included. They were divided into low anisometropia group: 3.00D<Δ spherical equivalent (SE)≤-1.00D (Δ represents the difference between the two eyes, i.e., myopic data minus emmetropic data) and high anisometropia group: ΔSE ≤ -3.00D. Corneal and ocular biometric parameters were measured using Pentacam, Corvis ST, and IOL Master 700. Statistical analyses focused on the binocular corneal parameters asymmetry, using the contralateral emmetropia as a control.

Results

The mean age of participants was 18.5 ± 1.3 years, with the average SE for myopia and emmetropia being -2.93 ± 1.09D and -0.16 ± 0.41D, respectively. The central corneal thickness (CCT), flat keratometry (Kf), keratometry astigmatism (Ka), total corneal aberration (6 mm) (TOA), surface variance index (ISV), vertical asymmetry index (IVA), stress-strain index (SSI), and first applanation stiffness parameter (SPA1) and ambrosia relational thickness-horizontal (ARTh) showed significant differences between anisometropic fellow eyes (p < 0.05). There were significant differences in ΔIVA, Δ the difference between the mean refractive power of the inferior and superior corneas (I-S), Δ deviation value of Belin/Ambrósio enhanced ectasia display (BAD-D), Δ deformation amplitude ratio max (2 mm) (DAR)and Δ tomographic biomechanical index (TBI) (p < 0.05) in two groups. Asymmetry of corneal parameters was correlated with asymmetry of ocular biometric parameters. Anisometropia (ΔSE) was positively correlated with ΔIVA (r = 0.255, p = 0.040), ΔBAD-D (r = 0.360, p = 0.006), and ΔSSI (r = 0.276, p = 0.039) and negatively correlated with ΔDAR (r = -0.329, p = 0.013) in multiple regression analysis. Δ mean keratometry (Km), Δ anterior chamber depth (ACD), and Δ biomechanically corrected intraocular pressure (bIOP) were also associated with binocular corneal differences.

Conclusion

Compared to contralateral emmetropia, myopic eyes have thinner corneas and smaller corneal astigmatism. Myopic corneas exhibit relatively more regular surface morphology but are more susceptible to deformation and possess marginally inferior biomechanical properties. In addition, there is a certain correlation between anisometropia and corneal parameter asymmetry, which would be instrumental in predicting the development of myopia.

Exploration of the pathophysiology of high myopia via proteomic profiling of human corneal stromal lenticules

This study aimed to investigate the underlying pathophysiology of high myopia by analyzing the proteome of human corneal stromal lenticule samples obtained through small incision lenticule extraction (SMILE). A total of thirty-two patients who underwent SMILE were included in the study. Label-free quantitative proteomic analysis was performed on corneal stromal lenticule samples, equally representing high myopia (n = 10) and low myopia (n = 10) groups. The identified and profiled lenticule proteomes were analyzed using in silico tools to explore biological characteristics of differentially expressed proteins (DEPs). Additionally, LASSO regression and random forest model were employed to identify key proteins associated with the pathophysiology of high myopia. The DEPs were found to be closely linked to immune activation, extracellular matrix, and cell adhesion-related pathways according to gene ontology analysis. Specifically, decreased expression of COL1A1 and increased expression of CDH11 were associated with the pathogenesis of high myopia and validated by western blotting (n = 6) and quantitative real time polymerase chain reaction (n = 6). Overall, this study provides evidence that COL1A1 and CDH11 may contribute to the pathophysiology of high myopia based on comparative proteomic profiling of human corneal stromal lenticules obtained through SMILE.

Corneal metabolic biomarkers for moderate and high myopia in human

This study aimed to identify the corneal metabolic biomarkers for moderate and high myopia in human. We enrolled 221 eyes from 221 subjects with myopia to perform the femtosecond laser small incision lenticule extraction (SMILE) surgery. Among these, 71 eyes of 71 subjects were enrolled in the low myopic group, 75 eyes of 75 subjects in the moderate myopic group and 75 eyes of 75 subjects in the high myopic group. The untargeted metabolomics analysis was performed to analyze the corneal tissues extracted during the SMILE surgery using an ultra-high-performance liquid chromatography (UHPLC) coupled to a quadrupole time-of-flight (Q-TOF) mass spectrometry (MS). The one-way analysis of variance (ANOVA) was used to identify the different metabolites among the three myopic groups, the orthogonal partial least-squares discriminant analysis (OPLS-DA) model was used to reveal the different metabolites between moderate myopia and low myopia, and between high myopia and low myopia. The Venn gram was used to find the overlapped metabolites of the three datasets of the different metabolites. The stepwise multiple linear regression analysis was used to determine the metabolic molecules associated with manifest refractive spherical equivalents (MRSE). The Receiver Operating Characteristics (ROC) analysis was performed to reveal the corneal biomarkers for moderate and high myopia. The hub biomarker was further selected by the networks among different metabolites created by the Cytoscape software. A total of 1594 metabolites were identified in myopic corneas. 321 metabolites were different among the three myopic groups, 106 metabolites were different between high myopic corneas and low myopic corneas, 104 metabolites were different between moderate myopic corneas and low myopic corneas, and 30 metabolic molecules overlapped among the three datasets. The multivariate linear regression analysis revealed the myopic degree was significantly influenced by the corneal levels of azelaic acid, arginine-proline (Arg-Pro), 1-stearoyl-2-myristoyl-sn-glycero-3-phosphocholine, and hypoxanthine. The ROC curve analysis showed that azelaic acid, Arg-Pro and hypoxanthine were effective in discriminating low myopia from moderate to high myopia with the area under the curve (AUC) values as 0.982, 0.991 and 0.982 for azelaic acid, Arg-Pro and hypoxanthine respectively. The network analysis suggested that Arg-Pro had the maximum connections among these three biomarkers. Thus, this study identified azelaic acid, Arg-Pro and hypoxanthine as corneal biomarkers to discriminate low myopia from moderate to high myopia, with Arg-Pro serving as the hub biomarker for moderate and high myopia.

RNA-Sequencing Analysis Reveals the Role of Mitochondrial Energy Metabolism Alterations and Immune Cell Activation in Form-Deprivation and Lens-Induced Myopia in Mice

Myopia is a substantial global public health concern primarily linked to the elongation of the axial length of the eyeball. While numerous animal models have been employed to investigate myopia, the specific contributions of genetic factors and the intricate signaling pathways involved remain incompletely understood. In this study, we conducted RNA-seq analysis to explore genes and pathways in two distinct myopia-inducing mouse models: form-deprivation myopia (FDM) and lens-induced myopia (LIM). Comparative analysis with a control group revealed significant differential expression of 2362 genes in FDM and 503 genes in LIM. Gene Set Enrichment Analysis (GSEA) identified a common immune-associated pathway between LIM and FDM, with LIM exhibiting more extensive interactions. Notably, downregulation was observed in OxPhos complex III of FDM and complex IV of LIM. Subunit A of complex I was downregulated in LIM but upregulated in FDM. Additionally, complex V was upregulated in LIM but downregulated in FDM. These findings suggest a connection between alterations in energy metabolism and immune cell activation, shedding light on a novel avenue for understanding myopia's pathophysiology. Our research underscores the necessity for a comprehensive approach to comprehending myopia development, which integrates insights from energy metabolism, oxidative stress, and immune response pathways.

Effects of inflammation on myopia: evidence and potential mechanisms

As the most common type of refractive error, myopia has become one of the leading causes of visual impairment. With the increasing prevalence of myopia, there is a growing need to better understand the factors involved in its development. Inflammation, one of the most fundamental pathophysiological processes in humans, is a rapid response triggered by harmful stimuli and conditions. Although controlled inflammatory responses are necessary, over-activated inflammation is the common soil for many diseases. The impact of inflammation on myopia has received rising attention in recent years. Elevated inflammation may contribute to myopia progression either directly or indirectly by inducing scleral remodeling, and myopia development may also increase ocular inflammation. This article provides a comprehensive review of the interplay between inflammation and myopia and the potential biological mechanisms, which may present new targets for understanding the pathology of myopia and developing myopia therapies.