PROJECT SUMMARY Malaria is currently rising and continues to pose a significant public health threat, with 249 million cases and 608,000 deaths annually, primarily in sub-Saharan Africa. The disease disproportionally affects children under five years residing in holoendemic Plasmodium falciparum (Pf) transmission regions, who account for 94% of the cases and 78% of the mortality. Young children, such as our study participants in Siaya, Kenya, are highly vulnerable to developing life-threatening severe malarial anemia [SMA, hemoglobin (Hb)<5.0 g/dL]. To address this challenge, we have conducted molecular-based clinical research for 23 years in our state-of-the-art facilities in this high-transmission area. Despite concerted national malaria control efforts, transmission intensity in Siaya has remained constant over the last decade. During the NIAID-funded R01 (2018-2022; current NCE), we investigated the impact of immune response genes on the development of SMA in acute disease (day 0-14: n=820). Findings from these studies provide valuable insights into the relationship between malaria immunity and short-term recovery. In addition, we recently completed a longitudinal birth cohort study (0-36 months, n=750) in children who did not receive a malaria vaccine. This study can be leveraged to discover molecular profiles linked to long-term immunity against malaria in the absence of vaccination. The recent rollout of the 1st approved malaria vaccine, RTS,S/AS01, in Siaya offers promise for malaria control. However, the vaccine has limited efficacy, particularly in high transmission settings, and the mechanisms of protection are largely unknown. For the renewal activities, we propose the recruitment of a birth cohort (0-36 mos.: n=750) that will receive RTS,S/AS01 using identical recruitment and follow-up. This strategy creates a unique opportunity to examine temporal molecular profiles in clinical phenotypes pre- and post-vaccination. The overall goal is to identify essential molecular networks that impact clinical outcomes throughout the crucial phases of naturally acquired immunity. We will employ mRNAseq to capture the entire expressed human transcriptome and Pf gene expression (concomitantly in whole blood), along with aptamer-based technologies to catalog the human proteome (plasma), collectively defining the Malarial Immunity Omics Landscape (MIOL). Temporal measures of high-dimensional multi-omics data will be analyzed with innovative modeling approaches that integrate bioinformatics, statistical analyses, and machine learning to achieve the following aims: (1) Determine how changes in the MIOL influence malarial severity throughout the development of naturally acquired immunity (unvaccinated children), (2) Determine the impact of vaccination on the MIOL to identify molecular profiles associated with protection, breakthrough infections, and disease severity, and (3) Identify molecular networks in the MIOL that can be therapeutically targeted to ...