Protein Interaction Networks Define the Genetic Architecture of Preterm Birth

Abstract

Rather than pathogenic variants in single genes, the likely genetic architecture of complex diseases is that subgroups of patients share variants in genes in specific networks and pathways sufficient to give rise to a shared phenotype. We combined high throughput sequencing with advanced bioinformatic approaches to identify subgroups of patients with shared networks and pathways associated with preterm birth (PTB). We previously identified genes, gene sets and haplotype blocks that were highly associated with preterm birth. We performed targeted sequencing on these genes and genomic regions on highly phenotyped patients with 2 or 3 generations of preterm birth, and term controls with no family history of preterm birth. We performed a genotype test for differential abundance of variants between cases and controls. We used the genotype association statistics for ranking purposes in order to analyze the data using a multi-sample, protein-protein interaction (PPI) tool to identify significant clusters of patients associated with preterm birth. We identified shared interaction networks of proteins among 45 preterm cases in two statistically significant clusters, p<0.001. We also found two small control-dominated clusters. For replication, we compared our data to an independent, large birth cohort. Sequence data on 60 cases and 321 controls identified 34 preterm cases with shared networks of proteins distributed in two significant clusters. Analysis of the layered PPI networks of these clusters showed significant similarity scores between the clusters from the two independent cohorts of patients. Canonical pathway analysis of the unique genes defining these clusters demonstrated enrichment in inflammatory signaling pathways, the glucocorticoid receptor, the insulin receptor, EGF and B-cell signaling, These results provide insights into the genetics of PTB and support a genetic architecture defined by subgroups of patients that Share variants in genes in specific networks and pathways which are sufficient to give rise to the disease phenotype. Author SummaryThe genetic architecture of complex diseases is reflected in subgroups of patients with variants in genes in specific networks and pathways. There are likely multiple networks that give rise to similar phenotypes. Preterm birth is an important complex genetic disease. We combined high throughput sequencing with advanced bioinformatic approaches to identify subgroups of patients with shared networks and pathways associated with preterm birth (PTB). We sequenced patients with 2 or 3 generations of preterm birth, and term controls with no family history of preterm birth. We used a novel protein-protein interaction network analysis to identify clusters of patients with shared networks in pathways for this important clinical problem. We identified shared interaction networks two significant clusters. We replicated these data, finding similar clusters, in an independent, large birth cohort.