Browsing by Subject "schizophrenia"

Schizophrenia is a debilitating psychiatric disorder associated with reduced life expectancy. The biological mechanism of schizophrenia is nebulous; however, many findings point to the central nervous system and neurons, where a reduction in dendritic spines has been indicated by previous research. The genetic findings support the involvement of synapses in the pathogenesis of schizophrenia. To study the biological properties stemming from genetics, relevant model systems and efficient methods are needed. Induced pluripotent stem cell (iPSC) technology offers a robust method for modeling the biological processes underlying schizophrenia. Somatic cells, e.g. fibroblasts, can be reprogrammed back to a pluripotent state resembling embryonic stem cells, and further differentiated into any cell type of the body, which might not be otherwise accessible. This allows establishing and characterizing neuronal cultures from patient and control cell lines, potentially revealing biological differences associated to the disease phenotype. The field of schizophrenia research has adopted iPSC technology and multiple studies have been conducted. These include assessments of synaptic density in the produced neuronal cultures, many of which reported decreased density associated with schizophrenia. In this thesis, a modified version of Nehme et al. (2018) protocol was used to differentiate iPSCs into neurons in co-cultures with human iPSC-derived astrocytes. The overarching aim was to construct an immunocytochemistry (ICC) -based assay to measure synaptic density in the produced co-cultures. First, suitable markers for characterization by ICC were tested and selected. The markers were selected to inform about neuronal identity, maturity, and synapses of the differentiated neurons. Next, the culturing conditions were optimized regarding the cell density and coating of the culturing wells. Finally, to estimate the utility of the assay, a pilot study was performed with three cell lines derived from a healthy control and a monozygotic twin pair discordant for schizophrenia. iPSCs from these cell lines were differentiated into neurons in co-cultures with astrocytes, and then characterized with ICC using selected markers and image analysis software. The synaptic density was quantified for each cell line. The performance of the assay was evaluated with analysis of variance (ANOVA) and restricted maximum likelihood model (RELM). An assay to quantify synaptic structures in mature neurons was established. The average synaptic density for all cell lines was approximately 1 synapse per 100μm of neurite. Analysis of the data produced with the assay revealed a notable batch effect and technical variation. This suggests that further optimization is needed to reduce variance from undesired sources. The pilot data suggests that the differences in synaptic density between cases and controls may be modest, further highlighting the need for minimizing noise in the assay to improve signal to noise ratio. However, indicated by power analysis, large sample sizes are needed to identify meaningful differences between cases and controls. In light of these results, more attention should be drawn to the methodology in the field of iPSC-based studies, as the principals of the assay constructed here were similar to other synaptic assays used in previous publications.

Schizophrenia (SZ) is a neurodevelopmental psychiatric disorder with high heritability. Patients with SZ commonly suffer from sleep problems of different types, some of them with potential underlying abnormalities in sleep oscillations. These changes in sleep are usually accompanied by deficits in cognitive performance. However, the relationship between sleep, cognitive performance and genetic risk factors are not well known in SZ. In this study, patients were selected from a nation-wide SUPER -cohort. Sleep and circadian rhythm of patients with SZ (n = 26) and age-matched healthy controls (n = 11) were followed for a week with actigraphy and sleep diary, combined with word-pair -memory task and polysomnography at the end of the week. The results showed that patients spend more time in lighter sleep and awake during the night than controls. As expected, patients had impaired sleep spindle density compared to controls. Additionally, patient had worse overnight memory consolidation. However, sleep spindle density was not associated with memory performance. Lastly, polygenic risk score (PRS) for long sleep, but not PRS for SZ, predicted lower spindle density in patients, which could be indirect evidence for deviated neurophysiological processes of sleep behind the observed deviations in EEG oscillations among the patients. These results show that, as compared to controls, patients with SZ demonstrate abnormalities in their sleep, which can be seen both in macro- and microstructures of sleep. Further analyses of the interplay between sleep oscillations and genetic risk factors are likely needed to link sleep problems with overnight memory consolidation.