Abstract
BackgroundGenome-wide association studies have identified genetic variants associated with the risk of brain-related diseases, such as neurological and psychiatric disorders, while the causal variants and the specific vulnerable cell types are often needed to be studied. Many disease-associated genes are expressed in multiple cell types of human brains, while the pathologic variants affect primarily specific cell types. We hypothesize a model in which what determines the manifestation of a disease in a cell type is the presence of disease module comprised of disease-associated genes, instead of individual genes. Therefore, it is essential to identify the presence/absence of disease gene modules in cells.MethodsTo characterize the cell type-specificity of brain-related diseases, we construct human brain cell type-specific gene interaction networks integrating human brain nucleus gene expression data with a referenced tissue-specific gene interaction network. Then from the cell type-specific gene interaction networks, we identify significant cell type-specific disease gene modules by performing statistical tests.ResultsBetween neurons and glia cells, the constructed cell type-specific gene networks and their gene functions are distinct. Then we identify cell type-specific disease gene modules associated with autism spectrum disorder and find that different gene modules are formed and distinct gene functions may be dysregulated in different cells. We also study the similarity and dissimilarity in cell type-specific disease gene modules among autism spectrum disorder, schizophrenia and bipolar disorder. The functions of neurons-specific disease gene modules are associated with synapse for all three diseases, while those in glia cells are different. To facilitate the use of our method, we develop an R package, CtsDGM, for the identification of cell type-specific disease gene modules.ConclusionsThe results support our hypothesis that a disease manifests itself in a cell type through forming a statistically significant disease gene module. The identification of cell type-specific disease gene modules can promote the development of more targeted biomarkers and treatments for the disease. Our method can be applied for depicting the cell type heterogeneity of a given disease, and also for studying the similarity and dissimilarity between different disorders, providing new insights into the molecular mechanisms underlying the pathogenesis and progression of diseases.
Highlights
Genome-wide association studies have identified genetic variants associated with the risk of brainrelated diseases, such as neurological and psychiatric disorders, while the causal variants and the specific vulnerable cell types are often needed to be studied
Here we further hypothesize that the presence of disease gene modules instead of individual genes determines the manifestation of a disease in cells from different cell types
After removing the nuclei not assigned to any specific cell types, we obtained the final data matrix, which contains the expression level of 17,120 protein-coding genes in 12,246 nuclei, including 8994, 2762, 227, 3, 15, 112, and 133 nuclei from glutamatergic neuron (Gluta), GABAergic interneuron (GABA), astrocyte (Ast), endothelial (End), microglia (Mic), oligodendrocyte (Oli), and oligodendrocyte precursor cell (OPC), respectively
Summary
Genome-wide association studies have identified genetic variants associated with the risk of brainrelated diseases, such as neurological and psychiatric disorders, while the causal variants and the specific vulnerable cell types are often needed to be studied. Many disease-associated genes are expressed in multiple cell types of human brains, while the pathologic variants affect primarily specific cell types. We hypothesize a model in which what determines the manifestation of a disease in a cell type is the presence of disease module comprised of disease-associated genes, instead of individual genes. Genome-wide association studies have identified genetic variants associated with the risk of brain-related diseases, such as neurological and psychiatric disorders, the causal variants and the specific cell types in which the disease-risk variants may be active are often needed to be studied. Here we further hypothesize that the presence of disease gene modules instead of individual genes determines the manifestation of a disease in cells from different cell types
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