Stroke is the leading cause of long-term disability, the second most common cause of death world-wide and a major cause of dementia. About 80% of the cases are ischemic whereas ~20% are hemorrhagic (intracranial hemorrhage). Ischemic stroke is further divided into etiological subtypes such as large artery atherosclerotic stroke, small artery stroke, cardioembolic stroke, and other less frequent etiologies. Rapid and reliable distinction between ischemic stroke and stroke mimics, which present with similar clinical symptoms but have a non-vascular origin, is important for therapeutic decision-making. Vascular injury is reflected by circulating biomarkers which could be exploited to develop diagnostics for clinical use. Studying the dynamics of the circulating proteome at different time points after stroke may further inform pathophysiological processes particularly when integrated with other omics data. Thus, the aim of CLINSPECT-M`s workpackage 3 it to identify novel blood-based biomarkers for stroke that may support clinical decision-making in the acute phase, such as separating patients with ischemic stroke from patients with stroke mimics or hemorrhagic stroke. Further, scientists on this joint-project aim to decipher novel and potentially druggable pathways relevant to stroke pathophysiology.
A team of clinicians with special expertise on stroke around Prof. Martin Dichgans (Institute for Stroke and Dementia in Munich, LMU University Hospital Munich) provide and coordinate access to already available patient material from ongoing studies (CIRCULAS, DEMDAS, PROSCIS, BM-3N and CAPIAS), recruit further patients and produce other omics data (genomics) or collect and integrate already existing omics data (genomics, metabolomics). The proteomic experts form the Group of Prof. Axel Imhof (Protein Analysis Unit, Ludwigs Maximilians University of Munich) aim to develop an automated processing of patient’s plasma or serum samples and establish and apply an optimized data independent acquisition (DIA) scheme to generate a digital proteomic fingerprint of all patient samples. They will further perform a targeted investigation of histones, histone variants and histone modifications, which are potential biomarkers for patients with stroke.
A team of highly qualified bioinformaticians around Prof. Jürgen Cox (Computational Systems Biochemistry, Max Planck Institute of Biochemistry) will perform data analysis and integration using the in-house developed software platforms MaxQuant and Perseus. In the framework of this project, they will further develop the quantitative analysis of DIA data in MaxQuant and use phenotypic and molecular data of patients from the CIRCULAS study, including genomic and metabolomic data, to identify meaningful molecular signatures utilizing state-of-the-art machine learning approaches.