Multiomics characterization of acute child illness and mortality in Africa and South Asia

Childhood illnesses from infectious diseases in low- and middle-income countries contribute substantially to the global under-five mortality. Many hospitalised children experience incomplete recovery, readmission, and post-discharge mortality despite guideline-directed care. However, targeted interventions remain elusive due to a limited understanding of underlying mechanisms. In this work, we employ multiomic profiling and multivariate modeling to investigate biological drivers of inpatient and post-discharge mortality in 3,101 acutely ill children across nine sites in sub-Saharan Africa and South Asia. In a nested case-cohort (N=1,008), we generate plasma proteomics, serum metabolomics and lipidomics, stool metagenomics, and fecal pathogen data at admission and discharge. Additionally, we profile 270 geographically matched community children for biological baselines. We identify a generalizable mortality signature marked by immune, inflammatory, and metabolic dysregulation with gut dysbiosis. We show that mortality-associated signals persist from admission through discharge, indicating unresolved disease, and that malnourished children show greater baseline perturbations, explaining elevated risk. We also find some children with low clinical severity display high predicted mortality risk from targeted biomarkers. Finally, we distill predictive models to a clinically feasible biomarker panel and validate our findings in an independent cohort (N=100). By linking inpatient and post-discharge mortality to specific biological mechanisms, our findings highlight why current care can fail and demonstrate how biomarker-guided risk stratification can identify vulnerable children currently missed by clinical assessments, enabling targeted interventions to reduce mortality in low- and middle-income countries.

Methods
The study population consisted of a nested case-cohort (NCC) study (the discovery cohort) within the Childhood Acute Illness and Nutrition (CHAIN) Network cohort. The CHAIN study recruited 3,101 children from nine sites across six countries: Bangladesh, Burkina Faso, Kenya, Malawi, Pakistan, and Uganda. Children were stratified by nutritional status using mid-upper arm circumference (MUAC) during enrolment at hospital admission, and followed up for 180 days after discharge. Geographically-matched community participants were included as a comparison group. The study was approved by the institutional review boards of all partner sites. The discovery cohort consisted of a random 24% sub-cohort of children stratified by site, including 658 survivors (non-cases) and 109 deaths (cases). Additionally, all remaining deaths (241 cases) not included in the random sub-cohort were added, resulting in a total of 350 cases. Another 30 randomly selected community participants from each site (a total of 270) were also included.

Collection and processing of all sample types were performed according to harmonized operating procedures at all study sites. Samples were collected at admission, discharge, and follow-up, and included stool, fecal swabs, whole blood, serum, plasma, and dry blood spots. Sample processing occurred under cold-chain conditions before transfer to the KEMRI/Wellcome Trust Research Programme biorepository in Kilifi, Kenya. Proteomic features were generated using the SomaScan aptamer-based assay in plasma. Serum metabolomic and lipidomic features were generated using targeted and untargeted mass spectrometry techniques, respectively. Metagenomic features were generated through sequencing of DNA from stool samples. TaqMan Array Card (TAC) features were generated from nucleic acids extracted from fecal swabs.