Identification of Vulnerable Cell Types in Major Brain Disorders Using Single Cell Transcriptomes and Expression Weighted Cell Type Enrichment

Abstract

The cell types that trigger the primary pathology in many brain diseases remain largely unknown. One route to understanding the primary pathological cell type for a particular disease is to identify the cells expressing susceptibility genes. Although this is straightforward for monogenic conditions where the causative mutation may alter expression of a cell type specific marker, methods are required for the common polygenic disorders. We developed the Expression Weighted Cell Type Enrichment (EWCE) method that uses single cell transcriptomes to generate the probability distribution associated with a gene list having an average level of expression within a cell type. Following validation, we applied EWCE to human genetic data from cases of epilepsy, Schizophrenia, Autism, Intellectual Disability, Alzheimer's disease, Multiple Sclerosis and anxiety disorders. Genetic susceptibility primarily affected microglia in Alzheimer's and Multiple Sclerosis; was shared between interneurons and pyramidal neurons in Autism and Schizophrenia; while intellectual disabilities and epilepsy were attributable to a range of cell-types, with the strongest enrichment in interneurons. We hypothesized that the primary cell type pathology could trigger secondary changes in other cell types and these could be detected by applying EWCE to transcriptome data from diseased tissue. In Autism, Schizophrenia and Alzheimer's disease we find evidence of pathological changes in all of the major brain cell types. These findings give novel insight into the cellular origins and progression in common brain disorders. The methods can be applied to any tissue and disorder and have applications in validating mouse models.

Keywords: Alzheimer's Disease; RNA-seq; anxiety; autism; genetics; schizophrenia; single cell genomics; transcriptome.

Figure 1

Depiction of the expression weighted cell-type enrichment method. (A) Flow diagram showing the steps involved in going from either genetic or transcriptional data to a probability of enrichment. (B) Demonstration of the principles of EWCE method using four Alzheimer's genes (target list) and three randomly generated lists. In the left most column, the cell type expression proportions for the target list is shown. The row with blue bars shows the average over the genes shown above. All four of the target genes are not specific marker genes for microglia; Apoe for instance also has high expression in astrocytes. Nonetheless, when averaged together, there is a higher mean expression in microglia than in the averaged random list.

Figure 2

Susceptibility genes for major human brain disorders show distinct cell type enrichments. (A) Two gene sets with a strong prior expectation for cell type enrichment—the human postsynaptic density, and genes with Human Phenotype Ontology annotations for abnormal myelination—were detected using bootstrapping to have higher expression in neurons and oligodendrocytes, respectively. (B) Bootstrapping tests performed using the EWCE method show that seven different classes of brain disorder show enrichment in particular cell types. (C) Multiple Sclerosis associated genes are strongly enriched for microglial expression. This plot shows that this is not just a property of a few genes, but instead almost every single gene shows higher levels of expression in microglia than would be expected by chance. The plot shows the actual level of expression of the susceptibility gene, against the mean expression level of the ith most expressed gene in a bootstrapping analysis of lists of 19 genes. If microglial expression in MS genes was randomly distributed, the genes would be expected to fall along the red line. (D) All Alzheimer's disease susceptibility genes are more enriched for microglial expression than expected by chance. (E) Bootstrap distributions of expected microglial expression levels of Alzheimer's disease genes. Red dots mark the expression level of the susceptibility genes, while the associated boxplots denote the expected expression level of the ith most expressed gene, in a list of 19 genes, as determined using bootstrapping. Asterisks behind the red dots denote that the gene has higher expression in the cell type than expected by chance (p < 0.05). (F) Genes associated with Autism are found to show increased expression in pyramidal neurons. (G) The hundreds of genes associated with Schizophrenia are found to show a moderate, but highly significantly, increased expression in pyramidal neurons.

Figure 3

Post-mortem transcriptomes from patients with Alzheimer's disease, Autism and Schizophrenia show distinctive cellular phenotypes. (A) Consistent fold enrichments were found for each cell type across fourteen cortical and three subcortical brain regions of Alzheimer's patients. The box plots mark the distribution of cellular fold enrichments across all the brain regions examined. Asterisks mark that the fold enrichment for each cell type that was found to be significantly non-zero with p < 0.05. (B) Two independent autism studies show the same cellular phenotypes, including upregulation of glial cells and downregulation of neurons. Asterisks mark those cell types found to be significantly differential with p < 0.05 after BH correction over all groups. (C) Cellular phenotypes in Schizophrenia are regionally dependent but cluster into groups, with a number of regions including the cingulate cortex and temporal pole showing downregulation of oligodendrocyte genes while the prefrontal cortex exhibits upregulation of endothelial and astrocyte genes as well as downregulation of deep pyramidal neurons in the anterior region. The analyses shown are based on an integrative analysis of six independent studies, though not all brain regions featured in all studies.