| Title: | Stratifying Psychosis Using BioBank |
| Lead Institution: | University of Edinburgh |
| Principal investigator: | Professor Stephen Lawrie |
Application 16124
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About
Progress in understanding the causes of schizophrenia and related psychoses has been slow. Stratifying psychosis into subtypes could ultimately lead to more effective treatments. We will stratify individuals with schizophrenia, bipolar disorder, related psychoses and sub-threshold syndromes into categories using data from UK Biobank. Our aims are to: 1. Identify and characterise specific subtypes of psychosis within all those with psychotic symptoms. 2. Identify the mechanisms underlying stratified and unstratified psychosis using GWAS and MRI 3. Test whether resilience to psychosis can be accurately and validly measured. 4. Identify the mechanisms underlying resilience with GWAS and MRI. This research seeks to use the clinical, cognitive, imaging and genetic data from UKB to study the mechanisms of common medical conditions and use them as a platform to better diagnosis. These aims are completely consistent with UK Biobank's aims. Providing this mechanistic information may help to identify new drug targets for schizophrenia and other psychoses. Stratifying psychosis into more homogenous categories will provide better 'disease' targets for genome wide association studies and for other types of mechanism based research because there will be less aggregation of individuals with diverse aetiologies within the same heterogeneous category of schizophrenia, bipolar disorder etc. We will test whether sub-groups of people with psychotic symptoms have discrete neurobiological correlations in UKBiobank by comparing them with unstratified psychotic symptoms and controls using MRI and genetic data. We will firstly examine the associations of psychotic symptoms with cognition (baseline measures and web-based), brain structure, function and connectivity (MRI). We will examine the association of stratified and unstratified psychosis with biological intermediates (mechanistically important variables) using polygenic profiling. We will also compare resilient and non-resilient individuals. We are interested in the full cohort for the derivation of psychotic symptom measures - and the subgroups with genetic and imaging (brain MRI) data for more detailed analysis. We appreciate the time scale for the availability of genotyping and imaging data.3 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 9533 | Grey and white matter associations of psychotic-like experiences in a general population sample (UK Biobank) | Julie Schoorl (+6) | 2021 | Translational Psychiatry |
| 11236 | Pathway-Based Polygenic Risk Scores for Schizophrenia and Associations With Reported Psychotic-like Experiences and Neuroimaging Phenotypes in the UK Biobank | Miruna C. Barbu (+8) | 2023 | Biological Psychiatry Global Open Science |
| 12659 | White matter, cognition and psychotic-like experiences in UK Biobank | M. J. Bosma (+8) | 2021 | Psychological Medicine |
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