Pathomechanisms and Signatures in the Longitudinal Course of Psychosis



003_ Brain cell type-specific polygenic risk in schizophrenia: influence on clinical phenotypes

Research Question and Aims

Here we leverage the cell type-specific expression profiles derived from a single-cell RNAseq study (Skene et al., 2018) and from our own experimental work using primary cells (Sharma et al., 2015) to generate cell type-specific PRS in schizophrenia/schizoaffective patients within the PsyCourse cohort. We want to analyze the association of these PRS with the rich clinical information available in this sample. PsyCourse is one of the samples included in this study, that will also involve Exercise II, RESIS & RIE cohorts.

Analytic Plan

We hypothesize that genetic/polygenic risk associated to specific CNS cell types factors will be associated with specific clinical outcomes in schizophrenia/schizoaffective patients.
Data from all schizophrenia/schizoaffective patients in PsyCourse who have genotype data available will be included in this study.
Polygenic risk scores:
Cell type-specific gene-sets definition:
1) the 5% most specifically expressed genes in each mouse brain cell type as published in the aforementioned single-cell RNAseq study (Skene et al., 2018);
2) by high-throughput RNAseq or deep proteomic analyses of primary mouse brain cells differentiated in vitro into different cell types (Sharma et al., 2015). PLINK 1.90 will be used for PRS calculation. The most recent SCZ GWAS was used as discovery sample for these calculations (Pardiñas et al., 2018). SCZ PRS will be calculated based on summary statistics from the discovery dataset excluding rare SNPs (MAF < 5%), low quality imputed variants (info score <90%), indels, ambiguous markers (A/T and C/G), and SNPs in the extended major histocompatibility complex region (chromosome 6: 25-34 Mbp). Data will be clumped in windows of 500 kbp, discarding variants in LD (R2>.1) with another more significant marker. Scores will be calculated based on p value thresholds ranging from p < 5 x 10-8 to p < 1.
Statistical analysis:
The association of cell type-specific risk profile scores with relevant clinical variables (psychopathology, cognition, functioning) will be studied using linear models adjusting for sex, age, treatment, premorbid intelligence, ancestry components, and recruitment site, to determine the association of PRS or single genetic variants of special interest on age at onset.

Resources needed

Sociodemographic variables and clinical, functioning and cognition data in Visit 1. Genetic data (imputed).