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Updated: May 23, 2025
JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
Published on: October 19, 2021
Network analysis reveals protein modules associated with childhood respiratory diseases
Nicole Prince1, Sofina Begum1, Kevin M Mendez2
1Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Mass; Harvard Medical School, Boston, Mass.
Background:
The first year of life represents a dynamic immune development period that impacts the risk of developing respiratory-related diseases, including asthma, recurrent infections, and eczema. However, the role of immune-mediating proteins in childhood respiratory diseases is not well characterized in early life.
Objective:
The objective of this study was to investigate relationships between protein profiles at age 1 year and respiratory-related diseases by age 6 years, including asthma, recurrent wheeze, respiratory infections, and eczema.
Methods:
We applied weighted gene correlation network analysis to derive modules of highly correlated proteins during early life immune development using plasma samples collected from children at age 1 year (n = 294) in the Vitamin D Antenatal Asthma Reduction Trial. Using regression analysis, we evaluated relationships between protein modules at age 1 and respiratory-related diseases by age 6. We integrated protein modules with additional omics and social, demographic, and environmental data for further characterization.
Results:
Our analysis identified 4 protein modules at age 1 year associated with incidence of childhood asthma and/or recurrent wheeze (adjusted Ps = .02 to .03), respiratory infections (adjusted Ps = 6.3 × 10-9 to 2.9 × 10-6), and eczema (adjusted P = .01) by age 6 years; associations between modules and clinical outcomes were temporally sensitive and were not recapitulated using protein profiles at age 6 years. Age 1 modules were associated with environmental factors (adjusted Ps = 2.8 × 10-10 to .03) and alterations in metabolomic pathways (adjusted Ps = 2.8 × 10-6 to .04). No genome-wide single nucleotide polymorphisms were identified for any protein module.
Conclusion:
These findings suggested that protein profiles at age 1 year predicted development of respiratory-related diseases by age 6. Applying network approaches to study protein profiles may represent a new strategy to identify children susceptible to respiratory-related diseases in the first year of life.
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