Application of whole-exome sequencing to predict inborn errors of immunity in pediatric severe infections and sepsis.

Abstract

Increasing evidence supports the involvement of inborn errors of immunity in severe infections, but little is known about the prevalence of these genetic defects in children with sepsis. Due to the limited understanding of the molecular and immunological mechanisms driving sepsis, genetic testing is rarely used in routine diagnostics to identify genetic susceptibility to the condition. We performed a prospective observational study on previously healthy children hospitalized for severe infections, including sepsis. Patients underwent immunophenotyping and whole-exome sequencing, followed by in silico analysis to identify potentially causal variants. We assembled a cohort of 194 previously healthy children, including 149 (77%) patients with severe infection and 45 (23%) with sepsis. Our cohort was marked by a high frequency of respiratory tract infections (35%), bloodstream infections (20%), and central nervous system infections (16%). The genetic investigation identified 28 potentially causal variants, 18 (64%) are classified as variants with uncertain significance, and 10 (36%) are likely pathogenic variants. Of 45 patients with sepsis, 6 (13%) had potentially causal genetic variants. Similarly, 22/149 (15%) patients with severe infection presented potentially causal genetic variants. Whole-exome sequencing predicted the impairment of various immune mechanistic pathways such as immune dysregulation defects, antibody deficiencies, and combined immunodeficiencies (18% each). We found no clear association between genetic variants and the studied parameters: organ failure, microbe identification, immunoglobulin levels, and lymphocyte subset numbers. Although whole-exome sequencing is a valuable tool for detecting inborn errors of immunity underlying sepsis and unexplained severe infections, it could be selectively recommended for patients with a strong clinical suspicion of genetic abnormalities, balancing its diagnostic value with its cost and complexity.