A network analysis approach to identify protein clusters and multi-Omic determinants of childhood respiratory-related diseases

The first year of represents a critical period of immune development that can impact health trajectories and the risk of developing respiratory-related diseases, such as asthma, recurrent infections, and eczema. However, the underlying biology between perturbed immune protein profiles and subsequent disease development remains unknown. Using weighted gene correlation network analysis (WGCNA), we derived clusters of immune-mediating proteins based on plasma protein profiling data from children at age 1 (N=294) in the Vitamin D Antenatal Asthma Reduction Trial (VDAART). We then used regression analysis to understand the relationships between protein clusters during early life immune development and subsequent clinical outcomes. We further characterized genomic and environmental determinants of clusters and investigated downstream biochemical impacts through the metabolome. WGCNA identified four protein clusters at age 1 year associated with incidence of childhood asthma and/or recurrent wheeze (P_adj range: 0.02-0.03), respiratory infections (P_adj range: 6.3x10^-9-2.9x10^-6), and eczema (P_adj=0.01); three of these protein clusters were associated with at least one environmental exposure (P_adj range: 2.8x10^-10-0.03) and metabolomic alteration of at least one pathway (P_adj range: 2.8x10^-6-0.04). No significant genetic risk factors were identified for any protein cluster. Overall, these findings suggested protein clusters derived during the critical immune development window contribute to development of respiratory-related diseases, which may enlighten new strategies to clinically identify vulnerable groups based on immune protein profiling.