Biology subjects

Prezzemolo, T.

Publications and source records attributed to Prezzemolo, T..

3 recordsLinked to original sources

bioRxiv2024

Adults patients with autoinflammation of unknown origin partially phenocopy the immune presentation of Still's disease

Autoinflammation of unknown origin remains amongst the most enigmatic of systemic autoinflammatory disorders (SAIDs), immunological disorders characterized by inappropriate activation of the innate immune response. Recent clinical research has identified multiple distinct disorders, although overlap in clinical characteristics and genetic drivers impede rapid and precise diagnosis, and the immunological underpinning of disease is poorly understood. Here we aimed to understand the immunological process behind patients with autoinflammation of unknown origin. In a multi-center European trial, we collected samples from 36 patients with recent disease activity, and used deep immunophenotyping and plasma proteomics to compare to 58 healthy controls and an additional demographically-similar 92 SAID patients. Key immunological changes were upregulation of CD38 and HLA across T cell subsets and upregulation of acute phase plasma proteins in autoinflammation of unknown origin patients. These previously poorly characterised patients partially phenocopied the Stills disease presentation. Together this study identifies potential biomarkers and disease-mediators in autoinflammation of unknown origin.

immunology↗

bioRxiv2022

Astrocyte-targeted gene delivery of interleukin 2 specifically increases brain-resident regulatory T cell numbers and protects against pathological neuroinflammation

The ability of immune-modulating biologics to prevent and reverse pathology has transformed recent clinical practice. Full utility in the neuroinflammation space, however, requires identification of both effective targets for local immune-modulation and a delivery system capable of crossing the blood-brain-barrier. The recent identification and characterization of a small population of regulatory T cells (Tregs) resident in the brain presents one such potential therapeutic target. Here we identified brain IL2 levels as a limiting factor for brain-resident Tregs. We developed a gene-delivery approach for astrocytes, with a small-molecule on-switch to allow temporal control, and enhanced production in reactive astrocytes to spatially-direct delivery to inflammatory sites. Mice with brain-specific IL2 delivery were protected from traumatic brain injury, stroke and multiple sclerosis models, without impacting the peripheral immune system. These results validate brain-specific IL2 gene-delivery as effective protection against neuroinflammation, and provide a versatile platform for delivery of diverse biologics to neuroinflammatory patients.

immunology↗

bioRxiv2020

AutoSpill: a method for calculating spillover coefficients in high-parameter flow cytometry

Compensating in classical flow cytometry or unmixing in spectral systems is an unavoidable challenge in the data analysis of fluorescence-based flow cytometry. In both cases, spillover coefficients are estimated for each fluorophore using single-color controls. This approach has remained essentially unchanged since its inception, and is increasingly limited in its ability to deal with high-parameter flow cytometry. Here, we present AutoSpill, a novel approach for calculating spillover coefficients or spectral signatures of fluorophores. The approach combines automated gating of cells, calculation of an initial spillover matrix based on robust linear regression, and iterative refinement to reduce error. Moreover, autofluorescence can be compensated out, by processing it as an endogenous dye in an unstained control. AutoSpill uses single-color controls and is compatible with common flow cytometry software, but it differs in two key aspects from current methods: (1) it is much less demanding in the preparation of controls, as it does not require the presence of well-defined positive and negative populations, and (2) it does not require manual tuning of the spillover matrix, as the algorithm iteratively computes the tuning, producing an optimal compensation matrix. Another algorithm, AutoSpread, complements this approach, providing a robust estimate of the Spillover Spreading Matrix (SSM), while avoiding the need for well-defined positive and negative populations. Together, AutoSpill and AutoSpread provide a superior solution to the problem of fluorophore spillover, allowing simpler and more robust workflows in high-parameter flow cytometry.

immunology↗