Network Analysis

Uses

How it works

Evidence quality

Highlighted claims

• Primary modelling endpoints include exacerbation timing and frequency, FEV1, exacerbation occurrence, and asthma control by ACT or GINA. — Real-world and Genomic data-based Asthma Insights through Network Analysis (REGAIN study): protocol for a novel retrospective and prospective longitudinal asthma cohort study
• Coexpression, Bayesian, and other network models will be used to study molecular heterogeneity and predict treatment response. — Real-world and Genomic data-based Asthma Insights through Network Analysis (REGAIN study): protocol for a novel retrospective and prospective longitudinal asthma cohort study
• The primary objective is to describe asthma clinically and molecularly by type 2 biology and asthma control across treatments. — Real-world and Genomic data-based Asthma Insights through Network Analysis (REGAIN study): protocol for a novel retrospective and prospective longitudinal asthma cohort study
• Secondary objectives include finding biomarkers that classify endotypes, differentiate trajectories, and distinguish biologic responders from non-responders. — Real-world and Genomic data-based Asthma Insights through Network Analysis (REGAIN study): protocol for a novel retrospective and prospective longitudinal asthma cohort study
• The analytical team will model blood RNA sequencing and nasal brushing RNA sequencing separately. — Real-world and Genomic data-based Asthma Insights through Network Analysis (REGAIN study): protocol for a novel retrospective and prospective longitudinal asthma cohort study
• Larger group sizes enable stronger network modelling, including central node identification and Bayesian key driver analysis. — Real-world and Genomic data-based Asthma Insights through Network Analysis (REGAIN study): protocol for a novel retrospective and prospective longitudinal asthma cohort study