Elham Rostami

Traumatic Brain Injury (TBI) affects over 60 million people annually worldwide, leading to significant disabilities and increasing the risk of dementia. Despite TBI´s heterogeneity and varying outcomes among similarly injured patients, current treatment relies on a uniform, one-size-fits-all approach, often resulting in suboptimal care. This one-size-fits-all approach fails to accommodate the individual variations and complexities inherent in each case of TBI, leading to suboptimal outcomes. Recognizing the need for personalized treatment strategies, this project proposes the integration of clinical variables, head CT-scans, biological, high-resolution physiological data, and genetic variations, cognitive reserve, harnessing comprehensive Swedish and international TBI datasets, bolstered by extensive Swedish linkage registers. Employing machine learning algorithms, this approach strives for customized interventions and accurate prognosis tools, transforming care in neurointensive clinics. Additionally, addressing the gap between animal studies and human trials, we introduce a humanized in vivo model for TBI research, essential for testing neuroprotective drugs and understanding human cell responses. Combining clinical and experimental efforts with advanced data-driven techniques, our project targets the discovery of effective drug targets to improve TBI recovery, underscored by a humanized model for direct relevance to patient care.

This proposal builds on multi-disciplinary data describing abnormal synaptic pruning as a mechanism in schizophrenia (SZ). So far, increased expression of the SZ risk gene coding for complement component 4A (C4A) has been shown to contribute to excessive microglial engulfment of synaptic structures in patient-derived SZ models, while protein levels of C4A are elevated in first-episode SZ patients. However, the mechanistic understanding of the molecular events that leads to activity-dependent synapse elimination by microglia, and other glia cells, is largely incomplete due to the lack of adequate experimental models. This has complicated the identification of suitable drug targets and stalled the highly needed clinical studies using novel or repurposed compounds in SZ. Here, we propose a novel and unique integrated experimental and clinical approach - linked on subject level and supported by humanized in vivo models - to identify suitable drug targets for modifying glial synapse elimination in SZ. Using state-of-the-art organoid models combined with high-resolution single cell transcriptomic profiling we aim to identify cell types and mechanisms contributing to excessive pruning in SZ. By perturbing these mechanisms in our models, we select a set of candidate mechanisms that are validated in vivo and in a clincial context (CSF and longitudinal MRI imaging) using within-subjects analyses followed by case-control analyses utilizing a cohort consisting of &gt

200 subjects.