Poster

  • P-III-0786

Deciphering cross-cohort metabolic signatures of immune responses and their implications for disease pathogenesis

Beitrag in

Data Integration: With Bioinformatics to Biological Knowledge

Posterthemen

Mitwirkende

Jianbo Fu (Hannover / DE; Zurich / CH), Nienke van Unen (Hannover / DE), Andrei Sarlea (Nijmegen / NL), Nhan Nguyen (Hannover / DE), Martin Jaeger (Nijmegen / NL), Javier Botey-Bataller (Hannover / DE), Valerie Koeken (Nijmegen / NL), L. Charlotte de Bree (Nijmegen / NL), Vera P. Mourits (Nijmegen / NL), Simone J.C.F.M. Moorlag (Nijmegen / NL), Godfrey Temba (Nijmegen / NL), Vesla I. Kullaya (Moshi / TZ), Quirijn de Mast (Nijmegen / NL), Leo A.B. Joosten (Nijmegen / NL), Cheng-Jian Xu (Hannover / DE), Mihai G. Netea (Nijmegen / NL), Yang Li (Hannover / DE)

Abstract

Background: The intricate interplay between circulating metabolites and immune responses, though crucial to disease pathophysiology, remains poorly understood and underexplored in systematic research.

Methods: We performed a comprehensive analysis of the relationships between 4,361 metabolic features and 172 different cytokine responses to stimuli in two Western European cohorts (534 and 324 healthy individuals) and one sub-Saharan Africa (323 healthy donors). To elucidate the metabolic networks underlying immune phenotypes, we specifically assessed the co-expression networks of metabolites and immune responses (IL-1β, IL-6, TNF, IFN-γ) following Staphylococcus aureus stimulation. In analyzing the relationship between metabolites and immune cytokines, we initially filtered features based on their Spearman correlation p-values, retaining only those that passed a specific threshold (0.05) for further analysis. Subsequently, we conducted in vitro experiments to further validate these relationships. To explore the potential role of metabolites in disease, we examined the differential expression of metabolites in infectious diseases and used the Mendelian randomization (MR) to study the causal relationships between these metabolites and the disease.

Results: Our study identified glycerophospholipid metabolism as a consistent link between metabolic pathways and immune responses, highlighting its role in regulating infection-induced immune responses, while revealing sex-specific differences in the correlation between phosphatidylcholine and cytokine responses to ex-vivo stimulations. Notably, a significant negative correlation was observed between sphingomyelin and the monocyte-derived cytokine response in response to Staphylococcus aureus stimulation, a relationship validated through functional experiments. Subsequently, employing MR analysis, we established a link between sphingomyelin and COVID-19 severity, providing compelling evidence for a modulatory effect of sphingomyelin on immune responses during human infection.

Conclusions: Collectively, our results represent a unique resource (https://lab-li.ciim-hannover.de/apps/imetabomap/) for exploring metabolic signatures associated with immune function in different populations, highlighting sphingomyelin as a potential target in treating inflammatory and infectious diseases.

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