Abstract
Age-related macular degeneration (AMD) is a chronic and progressive macular degeneration disease, which can also lead to serious visual loss. In our research, we aim to efficiently identify biomarkers relevant for AMD diagnosis. We collected the gene expression data of retinal segmented epithelium (RPE) and retina tissues of GSE29801 and GSE135092 and performed differential expression analysis. The differentially expressed genes (DEGs) related to the RPE and retina in the two sets of data were identified and enriched by intersection analysis. A PPI network was constructed for intersection genes, and the top 20 genes with the largest connectivity in the network were selected as candidate genes. The LASSO model was used to identify key genes from candidate genes, and the nomogram and ROC curve were used to evaluate the diagnostic ability of key genes. We identified 464 intersection genes associated with RPE and 509 intersection genes associated with retina. The TGF-beta signaling pathway was enriched by RPE-related DEGs, while oxidative phosphorylation was enriched by retina-related DEGs. Among the candidate genes of RPE, the LASSO model identified 7 key genes. MAPK1 and LUM can predict the clinical diagnosis of AMD. Among the candidate genes of retina, the LASSO model identified four key genes. PTPN11 has the highest predictive diagnostic value. The results suggest that the imbalance mechanism of RPE in AMD may be related to the TGF-beta signaling pathway, and the imbalance mechanism of the retina may be related to oxidative phosphorylation. MAPK1 and LUM are potential diagnostic markers of RPE, and PTPN11 is a potential diagnostic marker of the retina. Also, our results provide a theoretical basis for better understanding the molecular mechanisms of AMD onset and treatment in the future.
Highlights
Age-related macular degeneration (AMD) is a chronic and progressive macular degenerative disease
To efficiently identify biomarkers relevant for AMD diagnosis, we proposed a systematic pipeline for identifying relevant genes for AMD by collecting gene expression data of the retinal pigment epithelium (RPE) and retina in gse29801 and gse135092 and performing bioinformatics analysis. is method has high predictive value for early clinical diagnosis of AMD and provides a theoretical basis for better understanding the molecular mechanisms of AMD onset and treatment in the future
We found that oxidative phosphorylation (OXPHOS) was enriched by retina-associated differentially expressed genes (DEGs). e retinal pigment epithelium is very active in metabolism and consists of a large number of mitochondria
Summary
Age-related macular degeneration (AMD) is a chronic and progressive macular degenerative disease. According to the global burden of disease study, the number of people with AMD will increase substantially in the decades as the global population ages [5]. Experts have predicted that there will be approximately 196 million patients with AMD worldwide in 2020, and by the end of 2040, the number of global patients with ADM will increase to 288 million [6, 7]. Erefore, there is an urgent need for relevant clinical markers to assist clinicians to make an accurate early diagnosis of AMD and predict clinical outcomes without individualized medical treatment provision. E study of AMD prediction from the genetic level may become one of the important methods for AMD diagnosis and treatment in the future Until now, there is still no consensus to systematically identify and predict AMD biomarkers, so for the research of AMD, further exploration is needed. e onset of AMD has a certain complexity and is triggered by a Journal of Healthcare Engineering combination of genetic and environmental factors [8, 9]. e study of AMD prediction from the genetic level may become one of the important methods for AMD diagnosis and treatment in the future
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
