Abstract
Glaucoma is an optic neuropathy, and the leading cause of irreversible blindness worldwide. However, the early detection of glaucoma remains challenging as chronic forms of glaucoma remain largely asymptomatic until considerable irreversible visual field deficits have ensued. Thus, biomarkers that facilitate early diagnosis and treatment for patients with a high risk of progression are critical. Network medicine approaches can be useful in identifying key relationships and important biomolecules for complex diseases. In this paper, we identified several hub biomarkers/drug targets for the diagnosis, treatment and prognosis for glaucoma and explored their associations for glaucoma based on human disease-biomarker and disease-target-drug networks. These results were verified by text-mining and genomic/epidemiology data. We also predicted the new application of BMP1 and MMP9 to diagnose glaucoma and confirm the theory of hub biomarkers with multiple clinical applications. Further, relevant pivotal pathways (regulation of the multicellular organismal process, regulation of localisation, and cytoplasmic vesicle for biomarkers; signal transduction and developmental process for targets) for these hub biomolecules were discovered, which may be foundations for future biomarker and drug target prediction for glaucoma. In conclusion, based on complex networks, hub biomolecules, essential pathways, and close diseases were identified for glaucoma in diagnosis, treatment and prognosis.
Xueli Zhang
PhD of Bioinformatics, Assistant Professor
My research interest is to explore the comorbidity relationship of diseases based on complex networks and to find new combination markers, and has constructed multiple biomarker databases and prediction models.
Shuo Ma
M.M. in Epidemiology and Health Statistics
My expertise lies in the fields of epidemiology and bioinformatics. With skills in multi-modal data processing and AI algorithms, I utilize these proficiencies to effectively tackle challenges within clinical and public health domains.
Lingcong Kong
MSc in Biomedical Engineering
My research interest is to explore the comorbidity relationship of diseases based on complex networks and to find new combination markers, and has constructed multiple biomarker databases and prediction models.
Shunming Liu
MSc in Technical Economy and Management
I’m drawn to the study of wearable devices and possess expertise in machine learning and big data analysis. My goal is to seamlessly blend technology and medicine to develop enhanced and precise medical solutions.
Ke Zhao
PostDoc
My research interest is to explore the comorbidity relationship of diseases based on complex networks and to find new combination markers, and has constructed multiple biomarker databases and prediction models.