Molecular phenotypes associated with antipsychotic drugs in the human caudate nucleus

Abstract

Antipsychotic drugs are the current first-line of treatment for schizophrenia and other psychotic conditions. However, their molecular effects on the human brain are poorly studied, due to difficulty of tissue access and confounders associated with disease status. Here we examine differences in gene expression and DNA methylation associated with positive antipsychotic drug toxicology status in the human caudate nucleus. We find no genome-wide significant differences in DNA methylation, but abundant differences in gene expression. These gene expression differences are overall quite similar to gene expression differences between schizophrenia cases and controls. Interestingly, gene expression differences based on antipsychotic toxicology are different between brain regions, potentially due to affected cell type differences. We finally assess similarities with effects in a mouse model, which finds some overlapping effects but many differences as well. As a first look at the molecular effects of antipsychotics in the human brain, the lack of epigenetic effects is unexpected, possibly because long term treatment effects may be relatively stable for extended periods.

Upper cortical layer–driven network impairment in schizophrenia

“…S1 and S4), imbalance of medication in the form of neuroleptic drugs could not be avoided, as the use of antipsychotics is standard among the schizophrenia patients and is not encountered in control individuals. To make sure that the patterns of DE are not associated with this medication regiment, we analyzed two bulk RNA datasets of the DLPFC: one large dataset consisting of ~150 human postmortem samples from antipsychotic-positive and antipsychotic-negative patients ( 44 ), and another consisting of ~35 rhesus macaque samples that were treated with the antipsychotic clozapine or haloperidol or with placebo ( 36 ). We overlapped human antipsychotic-associated or macaque drug treatment–associated DEGs with DEGs between control and schizophrenia samples either for all excitatory or inhibitory neurons or for each neuronal subtype in our dataset.…”

“…In addition, a list of DEGs was obtained from a human DLPFC antipsychotic dataset ( 44 ). DEGs were selected the same way as for the rhesus macaque dataset ( P < 0.05).…”

BiocMAP: A Bioconductor-friendly, GPU-Accelerated Pipeline for Bisulfite-Sequencing Data

“…Additional File 2 shows how you can then load the outputs of BiocMAP and use the data with R and Bioconductor packages such as bsseq [10], ggplot2 [27], and GGally [28] to perform exploratory data analysis as well as downstream statistical analyses. In addition, development versions of BiocMAP were used in other peer reviewed publications [30, 31, 32] that have publicly available R code for several downstream analyses.…”