Summary

The hippocampus formation, though prominently implicated in schizophrenia pathogenesis, has been overlooked in large-scale genomics efforts in schizophrenic brain. We performed RNA-seq in the hippocampus and dorsolateral prefrontal cortex (DLPFC) from 551 individuals (286 with schizophrenia). We identified substantial regional differences in gene expression, and found widespread developmental differences that were independent of cellular composition. We identified 48 and 245 differentially expressed genes (DEG) associated with schizophrenia within hippocampus and DLPFC, with little overlap between the brain regions. Of schizophrenia GWAS risk loci, 124/163 (76.6%) contained eQTLs in any region. Transcriptome-wide association studies in each region identified many novel schizophrenia risk features that were brain region-specific. We lastly identified potential molecular correlates of in vivo evidence of altered prefrontal-hippocampal functional coherence in schizophrenia. These results underscore the complexity and regional heterogeneity of the transcriptional correlates of schizophrenia and offer new insights into potentially causative biology.

Data Browser Links

• eQTL Browser
• Developmental Browser

Processed Data

Processed Results

• Table S15. Genome wide significant eQTL snp-feature pairs
• DLPFC vs HIPPO differential expressed genes (DEG) RData objects (adult and prenatal, includes BrainSpan replication and cell RNA fraction sensitivity results)
• Development DEG RData objects (includes BrainSpan replication and cell RNA fraction sensitivity results)
• SCZD vs non-psychiatric control DEG RData objects (includes qSVs as well as results for the interaction and no-qSVA gene-level sensitivity analyses). See BrainSeq Phase I SCZD DE features if you want to compare with BSP1 and the CMC dataset processed in hg19.
• TWAS DLPFC weights.
• TWAS HIPPO weights.
• TWAS results RData objects.
• Supplementary Figures and Tables via Mendelay Data at DOI 10.17632/3j93ybf4md.1.

For more details about these files and their contents, please check the BrainSeq Phase II README.

Raw Data

• RNA-seq reads: FASTQ via Globus collections jhpce#bsp2-dlpfc and jhpce#bsp2-hippo. See this page at the JHPCE knowledge base for instructions on how to use Globus.
• Phenotype data: RData. This demographic table, which includes cell RNA fraction estimates, can be used to replace the colData() slot of the RangedSummarizedExperiment objects.
• Genotype data: dbGaP - we will share analysis-ready genotype data with researchers that obtain dbGaP access of that accession.