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Background: Chronic inflammatory demyelinating polyneuropathy (CIDP) is an inflammatory disease affecting the peripheral nerves and the most frequent autoimmune polyneuropathy. Given the lack of established biomarkers or risk factors for the development of CIDP and patients' treatment response, this research effort seeks to identify potential clinical factors that may influence disease progression and overall treatment efficacy. Methods: In this multicenter, retrospective analysis, we have screened 197 CIDP patients who presented to the University Hospitals in Düsseldorf, Berlin, Cologne, Essen, Magdeburg and Munich between 2018 and 2022. We utilized the respective hospital information system and examined baseline data with clinical examination, medical letters, laboratory results, antibody status, nerve conduction studies, imaging and biopsy findings. Aside from clinical baseline data, we analyzed treatment outcomes using the Standard of Care (SOC) definition, as well as a comparison of an early (within the first 12 months after manifestation) versus late (more than 12 months after manifestation) onset of therapy. Results: In terms of treatment, most patients received intravenous immunoglobulin (56%) or prednisolone (39%) as their first therapy. Patients who started their initial treatment later experienced a worsening disease course, as reflected by a significant deterioration in their Inflammatory Neuropathy Cause and Treatment (INCAT) leg disability score. SOC-refractory patients had worse clinical outcomes than SOC-responders. Associated factors for SOC-refractory status included the presence of fatigue as a symptom and alcohol dependence. Conclusion: Timely diagnosis, prompt initiation of treatment and careful monitoring of treatment response are essential for the prevention of long-term disability in CIDP and suggest a "hit hard and early" treatment paradigm. [ABSTRACT FROM AUTHOR]

Myasthenia gravis is a chronic antibody-mediated autoimmune disease disrupting neuromuscular synaptic transmission. Informative biomarkers remain an unmet need to stratify patients with active disease requiring intensified monitoring and therapy; their identification is the primary objective of this study. We applied mass spectrometry-based proteomic serum profiling for biomarker discovery. We studied an exploration and a prospective validation cohort consisting of 114 and 140 anti-acetylcholine receptor antibody (AChR-Ab)-positive myasthenia gravis patients, respectively. For downstream analysis, we applied a machine learning approach. Protein expression levels were confirmed by ELISA and compared to other myasthenic cohorts, in addition to myositis and neuropathy patients. Anti-AChR-Ab levels were determined by a radio receptor assay. Immunohistochemistry and immunofluorescence of intercostal muscle biopsies were employed for validation in addition to interactome studies of inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3). Machine learning identified ITIH3 as potential serum biomarker reflective of disease activity. Serum levels correlated with disease activity scores in the exploration and validation cohort and were confirmed by ELISA. Lack of correlation between anti-AChR-Ab levels and clinical scores underlined the need for biomarkers. In a subgroup analysis, ITIH3 was indicative of treatment responses. Immunostaining of muscle specimens from these patients demonstrated ITIH3 localization at the neuromuscular endplates in myasthenia gravis but not in controls, thus providing a structural equivalent for our serological findings. Immunoprecipitation of ITIH3 and subsequent proteomics lead to identification of its interaction partners playing crucial roles in neuromuscular transmission. This study provides data on ITIH3 as a potential pathophysiological-relevant biomarker of disease activity in myasthenia gravis. Future studies are required to facilitate translation into clinical practice. [ABSTRACT FROM AUTHOR]