Motivation: In the last years, systems-level network-based approaches have gained ground in the research field of systems biology. These approaches are based on the analysis of high-throughput sequencing studies, which are rapidly increasing year by year. Nowadays, the single-cell RNA-sequencing, an optimized next-generation sequencing (NGS) technology that offers a better understanding of the function of an individual cell in the context of its microenvironment, prevails.
Results: Toward this direction, a method is developed in which active molecular subpathways are recorded during the time evolution of the disease under study. This method operates for expression profiling by high-throughput sequencing data. Its capability is based on capturing the temporal changes of local gene communities that form a disease-perturbed subpathway. The aforementioned methods are applied to real data from a recent study that uses single-cell RNA-sequencing data related with the progression of neurodegeneration. More specific, microglia cells were isolated from the hippocampus of a mouse model with Alzheimer's disease-like phenotypes and severe neurodegeneration and of control mice at multiple time points during progression of neurodegeneration. Our analysis offers a different view for neurodegeneration progression under the perspective of systems biology.
Conclusion: Our approach into the molecular perspective using a temporal tracking of active pathways in neurodegeneration at single-cell resolution may offer new insights for designing new efficient strategies to treat Alzheimer's and other neurodegenerative diseases.
Keywords: Alzheimer’s disease; Molecular pathways; Systems biology; Temporal evolution.