Conference Agenda

Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease affecting ~1% of the global population, with current therapies largely limited to symptom control and are associated with adverse effects. There is an urgent need for novel treatments targeting underlying disease mechanisms. Hookworms secrete immunomodulatory proteins that have evolved to regulate host immunity.

Here, we investigate a recombinant fatty acid- and retinol-binding protein, Ac-FAR-2, derived from the secretome of Ancylostoma caninum, as a hookworm-inspired therapeutic candidate for RA. Ac-FAR-2 significantly attenuated disease severity in a murine model of RA, with histological and confocal analyses revealing reduced macrophage infiltration in joint tissues. In vitro, Ac-FAR-2 suppressed inflammatory cytokine production in human peripheral blood mononuclear cells and THP-1-derived macrophages. This effect was associated with reduced co-stimulatory marker expression and impaired T-cell proliferation in co-culture systems.

Mechanistically, Ac-FAR-2 interacted with macrophage surface molecules and disrupted the arachidonic acid–prostaglandin E2 pathway. Transcriptomic profiling further demonstrated downregulation of NF-κB signaling, inflammasome-related genes, and other pro-inflammatory pathways in LPS-stimulated human macrophages.

These findings identify Ac-FAR-2 as a promising immunomodulatory candidate for RA and other macrophage-driven autoimmune diseases.

Malaria remains a major global health burden, with an estimated 282 million cases and 610,000 deaths across 80 countries in 2024. However, the mechanisms underlying protective immunity and inter-individual immune heterogeneity are still poorly understood, contributing to variation in susceptibility, disease severity, and vaccine efficacy.

This study applies a systems immunology and multi-omics approach to investigate the molecular basis of immune heterogeneity during Controlled Human Malaria Infection (CHMI). We aim to define an integrated framework of genes, proteins, and immune cell states that underpin Plasmodium parasite control and immune heterogeneity.

Using bulk RNA sequencing and single-cell data from peripheral blood mononuclear cells (PBMCs), we identified highly expressed and strongly correlated transcript pairs across mRNA, miRNA, and long non-coding RNAs (lncRNAs). These were incorporated into co-expression and regulatory networks to map transcriptional interactions. Correlation analyses revealed putative regulatory relationships, with lncRNA–mRNA pairs showing predominantly positive associations, suggesting coordinated expression across patient samples and over time.

Building on these findings, we are applying a probabilistic unsupervised machine learning framework to link transcriptional programs with proteomic signatures of immune activation. This integrative approach provides new insights into immune mechanisms driving parasite control while advancing multi-omics capabilities to the field of parasitology.