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Funded Projects › HORIZON

MonitorMS · Monitor Multiple Sclerosis evolution using body fluids derive cell-free epigenomics

HORIZONStatus: SIGNED1 September 202431 August 2026EU funding €222,728Call HORIZON-MSCA-2023-PF-01

Multiple sclerosis (MS) affects 2.8 patients worldwide, 700000 in Europe alone, and is characterized by subsequent phases of different severity which eventually evolve into a chronic phase and untreatable paralysis. Current main diagnostic approaches are limited to symptom evaluation and imaging, underlying a lack of informative and reliable biomarkers. MonitorMS aims to test the use of cell-free Chromatin (cfChromatin) present in the plasma and cerebrospinal fluid (CSF) as a new biomarker to monitor the progression of MS pathology and response to treatment. The proposal includes the development of a new technology based on nanoCut&Tag(nanoCT) to improve and simplify the current methodology used to profile cfChromatin.Recently, it has been demonstrated that cell-free DNA in plasma is still wrapped around histones which still preserve the presence of post-translational modifications, termed cfChromatin. Chromatin immunoprecipitation followed by sequencing (ChIP-seq) has been recently used to profile cfChromatin from plasma of patients affected by liver, and heart damage or cancer showing a pathology and stage-specific signature. To decode the information inside cfChromatin a reference dataset is needed. The first aim of MonitorMS is to develop a protocol to profile cfChromatin from plasma/cell-free CSF with nanoCT and compare it to the actual reference (ChIP-seq). In the second phase, the technology will be employed on a larger cohort of samples from a KI biobank, including patients under immunosuppressant treatment. Simultaneously a single-cell multimodal dataset, from matched MS patients' immune cells and post-mortem tissues, will be generated to deconvolve the informative content of cfChromatin. The final phase of the project will include further integration of the generated cfChromatin data with several MS single-cell transcriptome and spatial data. Finally, machine learning will be used to test cfChromatin as a stage/treatment-specific biomarker in MS.

Consortium · 1 organisation

coordinator

KAROLINSKA INSTITUTET

SE · €222,728

Research fields

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