bioRxivImmunologyPreprint
Dynamic Responses to an Inflammatory Challenge Distinguish Metabolic Health Across Lean and Obese Individuals
Saeideh TavajohiD, Bianca E SuuriD, Madison ClarkiD, Adriana Araceli Becerril-CamposiD, Elia Velasco, Brigita Medelytė, Line Boel NørregaardiD, Stine Julie TingskoviD, Amanda BækiD, Lykke Moran SkaarupiD, Erik Schröder, Maryam Dost, Sigrid Bjerge GribsholtiD, Jens Meldgaard BruuniD, Marianne Quiding‐Järbrink, Sofia N. NyströmiD, Ida Bergström, Catherine Åhlund, Jane Palsgaard Pedersen, Niels JesseniD, Lin LiniD, András HaraziniD, Henrik Holm ThomseniD, Per‐Anders JanssoniD, Robert BlomgraniD, , Emma BörgesoniD
Abstract
Inflammation is a key driver of cardiometabolic disease, yet it remains unclear whether systemic inflammatory markers can distinguish metabolically healthy from unhealthy individuals or capture the temporal dynamics of inflammation. Here, we combined systemic immune profiling with a cantharidin-induced peripheral blister model to investigate dynamic inflammatory regulation across metabolic phenotypes in metabolically healthy lean (MHL), metabolically unhealthy lean (MUL), metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO) individuals. While systemic inflammation was elevated in obesity, differences between metabolically healthy and unhealthy groups were modest, with limited discrimination by plasma proteomics, circulating leukocyte phenotyping, and whole-blood transcriptomics. In contrast, the dynamic response to inflammatory challenge revealed pronounced differences at proteomic, cellular, and transcriptomic levels. Metabolically unhealthy individuals exhibited exaggerated early innate immune responses, impaired inflammatory resolution and tissue repair, reduced recruitment of reparative immune cells, and sustained T cell presence. Transcriptomic analyses further showed blunted dynamic gene regulation and defective epidermal barrier restoration. These findings indicate that metabolic health is better reflected in tissue-level inflammatory dynamics than in systemic measures.
- organism: human
- assay: proteomics
- assay: bulk RNA-seq
- assay: imaging
- research focus: cell type annotation
- research focus: differential expression
- research focus: spatial domain detection
- approach: experimental assay
- Citations
- 0
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