Dissecting the genetic basis of comorbid epilepsy phenotypes in neurodevelopmental disorders

Abstract

Background: Neurodevelopmental disorders (NDDs) such as autism spectrum disorder, intellectual disability, developmental disability, and epilepsy are characterized by abnormal brain development that may affect cognition, learning, behavior, and motor skills. High co-occurrence (comorbidity) of NDDs indicates a shared, underlying biological mechanism. The genetic heterogeneity and overlap observed in NDDs make it difficult to identify the genetic causes of specific clinical symptoms, such as seizures.

Methods: We present a computational method, MAGI-S, to discover modules or groups of highly connected genes that together potentially perform a similar biological function. MAGI-S integrates protein-protein interaction and co-expression networks to form modules centered around the selection of a single "seed" gene, yielding modules consisting of genes that are highly co-expressed with the seed gene. We aim to dissect the epilepsy phenotype from a general NDD phenotype by providing MAGI-S with high confidence NDD seed genes with varying degrees of association with epilepsy, and we assess the enrichment of de novo mutation, NDD-associated genes, and relevant biological function of constructed modules.

Results: The newly identified modules account for the increased rate of de novo non-synonymous mutations in autism, intellectual disability, developmental disability, and epilepsy, and enrichment of copy number variations (CNVs) in developmental disability. We also observed that modules seeded with genes strongly associated with epilepsy tend to have a higher association with epilepsy phenotypes than modules seeded at other neurodevelopmental disorder genes. Modules seeded with genes strongly associated with epilepsy (e.g., SCN1A, GABRA1, and KCNB1) are significantly associated with synaptic transmission, long-term potentiation, and calcium signaling pathways. On the other hand, modules found with seed genes that are not associated or weakly associated with epilepsy are mostly involved with RNA regulation and chromatin remodeling.

Conclusions: In summary, our method identifies modules enriched with de novo non-synonymous mutations and can capture specific networks that underlie the epilepsy phenotype and display distinct enrichment in relevant biological processes. MAGI-S is available at https://github.com/jchow32/magi-s .

Keywords: Autism; De novo mutation; Developmental disability; Epilepsy; Intellectual disability; Module discovery.

Fig. 1

General overview of MAGI-S. A seed gene (e.g., SCN1A), protein-protein interaction (PPI) network, co-expression network, and LOF mutations in control samples are provided to MAGI-S to produce a seed centric module. Each gene in the PPI and co-expression networks is assigned a score based on the gene’s degree of co-expression with the seed gene relative to all other genes in the networks. Seed pathways are high-scoring simple paths formed from genes that are highly co-expressed relative to the seed gene, connected in the PPI network, and have a low number of LOF variants in control samples. Seed pathways are clustered into modules via a random walk of a graph created by seed pathways, and the total score of a module is improved by local search (similar to the MAGI algorithm in Hormozdiari et al. [16]). MAGI-S is run with varied parameters related to module size, minimum co-expression, and minimum PPI density, and the highest scoring module is retrieved. We have used the human developmental data from BrainSpan Atlas for the co-expression network construction. Furthermore, the combination of protein interactions from HPRD and STRING datasets was used as the PPI networks in our analysis

Fig. 2

Average number of non-synonymous and synonymous de novo mutations per individual for probands and controls in seed genes (Seed), modules excluding seed genes (Module), module genes excluding 128 previously reported neurodevelopmental disorder genes (M-ND) (Additional file 2: Table S2: “established NDD genes”), and genes outside of any module (Outside). a No significant difference in the number of synonymous mutations exists between cases and controls. Cases display significantly more non-synonymous (b), including missense (c) and loss-of-function (d), variants than controls in the Seed, Module, and M-ND groups

Fig. 3

Summary of significant enrichment in de novo mutation and copy number variation (CNV) overlap in neurodevelopmental modules. Modules are grouped by class to indicate the degree of association of the seed gene with the epilepsy phenotype. Class 1, class 2, and class 3 modules correspond to the seed genes that have strong, moderate, and weak evidence of association with epilepsy, respectively. a Significant enrichment of missense (miss.) and loss-of-function (LOF) mutations for autism spectrum (ASD), intellectual disability (ID), developmental disability (DD), epilepsy (E), and schizophrenia cohorts within modules. b Comparison of log2 of significant (p < 0.05) enrichment of de novo mutation for variants annotated as ASD/ID/DD (left) or epilepsy (right). c Average odds ratio of de novo mutations annotated in epilepsy cases relative to controls is significantly greater in class 1 modules compared to class 3 modules

Fig. 4

Phenotypic enrichment of genes in modules while including the seed gene. Enrichment is defined (M_P/M_P′)/(G_P/(19,986 − G_P)), where M_P is the number of genes annotated as a certain neurodevelopmental disorder (NDD) phenotype inside a module, M_P′ is the complement of M_P, and G_P is the total number of genes annotated as a certain phenotype. The total number of genes in the human genome is 19,986 (Gencode GRCh38.p12). Increased enrichment of NDD with or without epilepsy for a module corresponds respectively to the presence or absence of epilepsy phenotypes associated with the seed gene. Modules are grouped by evidence of epilepsy association of the seed genes—i.e., class 1 (strong), class 2 (moderate), and class 3 (weak association). a Increased enrichment of NDDs with epilepsy observed in class 1 modules are indicated by an increased y-intercept of class 1 regression line relative to class 2 and class 3. b Average enrichment of NDD with epilepsy is significantly greater in class 1 modules compared to class 2 or class 3 modules

Fig. 5

Cell type-specific expression analyses (CSEA) profile for the union of class 1 modules. Transcripts from provided gene lists that overlap significantly in specific cell types are indicated by intensity of color. Modules with seed genes strongly associated with epilepsy (class 1) show selective expression in the cortical neurons and spiny neurons in the striatum