Background
In 2017, Meaney, Pokhvisneva and Silveira created a novel approach to genomic profiling, informed by biological function, characterizing gene networks based on the levels of
co-expression in a specific tissue 1-4, called expression-based polygenic risk score (ePRS) (McGill University, ROI# 2021-094). This new method builds upon years of discoveries in Molecular Biology, while applying novel omics technologies.
As opposed to the current GWAS/PRS techniques, that are focused on predicting highly significant genetic effects of small magnitude, this ePRS approach identifies cohesive, biologically relevant and tissue-specific gene networks, providing critical mechanistic insights as complement to predictions.
In addition, ePRS offers the researcher with a proper genomic tool to identify gene by environment interactions, paving the way to a deeper understanding of cumulative exposure and experience effects over the life-course
The goal of the ePRS Cluster is to be a dedicated and highly specialized cluster to provide a faster solution to ePRS and different traditional genomic needs, by means of training, immediate access to processing pipelines, designing and deriving ePRS, and/or interpreting and communicating results.
Workshop Modules
• Designing ePRSs – overview: GWAS and PRS technology – meaning, advantages and use. Expression-based polygenic scores: definition and differences. How to generate a tissue specific co-expression gene network from genome-wide RNAseq data. Examples of gene networks. Enrichment analysis and visualization pipelines.
• Genotyping Quality Control (QC): GenomeStudio usage, pre- and post-imputation QC and imputation of the genotyping data. Also, will include the necessary commands and tools to implement the QC, different data formats and conversion between them, and explain our approach to QC and imputation of the family genotyping data. Pre-imputation QC will include: samples and SNPs quality check, sex, relatedness, and Hardy-Weinberg equilibrium checks, strand and the Haplotype Reference Consortium Panel (HRC) alignment. Will discuss how to submit the genotyping data for the imputation using the Sanger Institutes service. Post-imputation QC will also include imputation accuracy scores.
• PRS/ePRS (calculation of the polygenic risk scores): tools and commands, reference data sets (GWAS, GTeX). Approaches for parallel calculation and very large data sets.
• Genetically predicted gene expression tools (e.g. PrediXcan): theory behind it and how to calculate the scores.
• Ancestry considerations: how to account for the population genetic background in the analysis. How to obtain principal components for the genotyping data.
• Statistical analysis & model fitting: share our approach in including the polygenic scores in the analysis. Will discuss adjustments for ethnicity/PCs. Analysis of the form of interaction: will explore differential susceptibility/diathesis stress concept and specific R libraries.
References
1. Miguel PM, Pereira LO, Barth B, et al. Prefrontal Cortex Dopamine Transporter Gene Network Moderates the Effect of Perinatal Hypoxic-Ischemic Conditions on Cognitive Flexibility and Brain Gray Matter Density in Children. Biol Psychiatry. 2019;86(8):621-630.
2. Hari Dass SA, McCracken K, Pokhvisneva I, et al. A biologically-informed polygenic score identifies endophenotypes and clinical conditions associated with the insulin receptor function on specific brain regions. EBioMedicine. 2019;42:188-202.
3. Silveira PP, Pokhvisneva I, Parent C, et al. Cumulative prenatal exposure to adversity reveals associations with a broad range of neurodevelopmental outcomes that are moderated by a novel, biologically informed polygenetic score based on the serotonin transporter solute carrier family C6, member 4 (SLC6A4) gene expression. Dev Psychopathol. 2017;29(5):1601-1617.
4. de Lima RMS, Barth B, Arcego DM, et al. Amygdala 5-HTT Gene Network Moderates the Effects of Postnatal Adversity on Attention Problems: Anatomo-Functional Correlation and Epigenetic Changes. Front Neurosci-Switz. 2020;14(198).