Gene Expression Profile as a Predictor of Seizure Liability

Abstract

Analysis platforms to predict drug-induced seizure liability at an early phase of drug development would improve safety and reduce attrition and the high cost of drug development. We hypothesized that a drug-induced in vitro transcriptomics signature predicts its ictogenicity. We exposed rat cortical neuronal cultures to non-toxic concentrations of 34 compounds for 24 h; 11 were known to be ictogenic (tool compounds), 13 were associated with a high number of seizure-related adverse event reports in the clinical FDA Adverse Event Reporting System (FAERS) database and systematic literature search (FAERS-positive compounds), and 10 were known to be non-ictogenic (FAERS-negative compounds). The drug-induced gene expression profile was assessed from RNA-sequencing data. Transcriptomics profiles induced by the tool, FAERS-positive and FAERS-negative compounds, were compared using bioinformatics and machine learning. Of the 13 FAERS-positive compounds, 11 induced significant differential gene expression; 10 of the 11 showed an overall high similarity to the profile of at least one tool compound, correctly predicting the ictogenicity. Alikeness-% based on the number of the same differentially expressed genes correctly categorized 85%, the Gene Set Enrichment Analysis score correctly categorized 73%, and the machine-learning approach correctly categorized 91% of the FAERS-positive compounds with reported seizure liability currently in clinical use. Our data suggest that the drug-induced gene expression profile could be used as a predictive biomarker for seizure liability.

Keywords: attrition; cell culture; drug; gene expression; ictogenicity; neuronal.

Figure 1

Cytotoxicity analysis of (A) tool, (B) FAERS-positive, and (C) FAERS-negative compounds in rat cortical neuronal cell cultures. Each compound was tested using four concentrations and pentylenetetrazol using six concentrations. Abbreviations: VEH, vehicle. Statistical significance: * p < 0.05, ** p < 0.01, *** p < 0.001 (vehicle 0.1% DMSO vs. compound-treated sample, Kruskal–Wallis followed by Mann–Whitney U-test). Data are presented as mean ± SEM.

Figure 1

Cytotoxicity analysis of (A) tool, (B) FAERS-positive, and (C) FAERS-negative compounds in rat cortical neuronal cell cultures. Each compound was tested using four concentrations and pentylenetetrazol using six concentrations. Abbreviations: VEH, vehicle. Statistical significance: * p < 0.05, ** p < 0.01, *** p < 0.001 (vehicle 0.1% DMSO vs. compound-treated sample, Kruskal–Wallis followed by Mann–Whitney U-test). Data are presented as mean ± SEM.

Figure 2

Venn diagrams showing the number of differentially expressed genes (FDR < 0.05 and log2(|FC|) > 1.5) induced by tool, FAERS-positive, and FAERS-negative compounds in rat cortical neuronal cell cultures. (A) Both upregulated and downregulated genes. (B) Upregulated genes only. (C) Downregulated genes only.

Figure 3

Enriched Reactome pathways (y-axis) induced by tool, FAERS-positive, and FAERS negative compounds (x-axis). Pathways were identified, compared, and visualized by clusterProfiler.

Figure 3

Enriched Reactome pathways (y-axis) induced by tool, FAERS-positive, and FAERS negative compounds (x-axis). Pathways were identified, compared, and visualized by clusterProfiler.

Figure 4

The most prominent gene ontology (GO) terms of the (A) tool, (B) FAERS-positive, and (C) FAERS-negative compounds in a word cloud. The most frequent GO terms have the largest font size and the darkest blue color. In all the compound categories, “cell cycle process” was the most common GO term. In FAERS-positive and FAERS-negative categories, “apoptosis” was also prominent. See Supplementary File S2.

Figure 5

A 2-dimensional illustration of the UMAP reductions of the normalized rank-transformed replicate means of RNA-seq normalized read counts. (A) No clustering by compound category (tool, FAERS-positive, FAERS-negative compounds) is apparent. (B) A similar reduction for the vectors of a number of differentially expressed genes by FAERS-positive and FAERS-negative with a positive fold-change shared with each tool compound. Abbreviations: The 11 tool compounds: 4-aminopyridine (4AM), amoxapine (AMO), bicuculine (BIC), chlorpromazine (CPL), donepezil (DON), kainic acid (KAI), picrotoxin (PIC), pilocarpine (PIL), pentylenetetrazol (PTZ), strychnine (STR), and SNC80 (SNC). The 13 FAERS-positive compounds: amitriptyline (AMI), aminophylline (AMP), bupropion (BUP), clozapine (CLZ), diphenhydramine (DIP), isoniazid (ISO), maprotiline (MAP), mirtazapine (MIR), paroxetine (PAR), temozolomide (TEM), theophylline (TPH), tramadol (TRA), and venlafaxine (VEN). The 10 FAERS-negative compounds: azelastine (AZE), darifenacin (DAR), imiquimod (IMI), miconazole (MIC), minoxidil (MIN), niacin (NIA), ospemifene (OSP), rosiglitazone (ROS), roflumilast (ROF), and valdecoxib (VAL).

Figure 6

Production of embryos and set-up of cell cultures. (A) Production of embryos for the rat primary cortical cell cultures. (B) Treatment of cell cultures for the assessment of compound-induced cytotoxicity, dose-optimization, and compound-induced gene expression.