Georg Andreas Schett

This study shows CD19-CAR T-cell therapy depletes EBV+ autoreactive B cells and resets their repertoire, leading to sustained remission, while rituximab does not.

The paper uses spatial proteomic profiling to analyze cardiac stromal populations and microenvironments in systemic sclerosis-associated myocarditis, identifying distinct fibroblast subtypes and their spatial interactions.

This study identifies microbiota-specific serum IgG as a mediator of gut-joint immune-endothelial crosstalk in arthritis, showing its role in initiating autoimmunity through endothelial barrier impairment and microbial translocation.

This study shows that Prevotella intestinalis induces arthritis in resistant mice by activating intestinal immune cells and promoting Th17 differentiation through IL-6.

This study identifies transcriptomic differences in SLE neutrophils, shows shared ex vivo adaptation with healthy cells, and demonstrates CAR T-cell therapy can reset neutrophil gene expression toward healthy patterns.

The paper identifies a unique myeloid precursor population that facilitates the spread of psoriatic inflammation from skin to joints, interacting with fibroblasts to regulate T cell IL-17 expression.

The paper identifies gut microbiota-derived histamine as a factor enabling the CNS to suppress peripheral inflammation in RA by activating H3R in the intestine and modulating microglia.

The paper uses spatial transcriptomic methods to identify novel fibroblast subpopulations in systemic sclerosis skin and their pathogenic roles.

The paper maps the metabolic landscape of skin fibrosis in systemic sclerosis using single-cell analysis and identifies metabolically active cell types and their interactions.

This study performs a GWAS meta-analysis of psoriasis, identifying 109 susceptibility loci, including 45 new ones, and highlights potential therapeutic targets and disease mechanisms.

The paper compares glycosylation patterns of IgA1 and IgA2, finding subclass-specific differences despite similar glycosylation enzyme expression.

The paper benchmarks machine learning algorithms for cytometry data analysis, finding decision trees provide high accuracy, speed, and memory efficiency for immune cell phenotype quantification.

This study identifies genetic subsets of EGPA associated with asthma and eosinophil levels, revealing two distinct clinical and genetic syndromes.