Objectives: Genome‐wide association studies (GWAS) have become increasingly popular to identify associations between single nucleotide polymorphisms (SNPs) and phenotypic traits. The GWAS method is commonly applied within the social sciences. However, statistical analyses will need to be carefully conducted and the use of dedicated genetics software will be required. This tutorial aims to provide a guideline for conducting genetic analyses.Methods: We discuss and explain key concepts and illustrate how to conduct GWAS using example scripts provided through GitHub (https://github.com/MareesAT/GWA_tutorial/ ).In addition to the illustration of standard GWAS, we will also show how to apply polygenic risk score (PRS) analysis. PRS does not aim to identify individual SNPs but aggregates information from SNPs across the genome in order to provide individual‐level scores of genetic risk.Results: The simulated data and scripts that will be illustrated in the current tutorial provide hands‐on practice with genetic analyses. The scripts are based on PLINK, PRSice, and R, which are commonly used, freely available software tools that are accessible for novice users.Conclusions: By providing theoretical background and hands‐on experience, we aim to make GWAS more accessible to researchers without formal training in the field.

It has been previously suggested that morphine can regulate the expression and function of some proteins of the cytoskeleton. In the present study, we used real-time quantitative polymerase chain reaction to examine the effects of chronic morphine administration, in rat striatum, on 14 proteins involved in microtubule polymerization and stabilization, intracellular trafficking, and serving as markers of neuronal growth and degeneration. Chronic morphine treatment led to modulation of the mRNA level of seven of the 14 genes tested. Glial fibrillary acidic protein (Gfap) and activity-regulated cytoskeleton-associated protein (Arc) mRNA were upregulated, while growth associated protein (Gap43), clathrin heavy chain (Cltc), α-tubulin, Tau, and stathmin were downregulated. In order to determine if the regulation of an mRNA correlates with a modulation of the expression of the corresponding protein, immunoblot analyses were performed. With the exception of Gap43, the levels of Cltc, Gfap, Tau, stathmin, and α-tubulin proteins were found to be in good agreement with those from mRNA quantification. These results demonstrate that neuroadaptation to chronic morphine administration in rat striatum implies modifications of the expression pattern of several genes and proteins of the cytoskeleton and cytoskeleton-associated components.

So far, genetic studies of treatment response in schizophrenia, bipolar disorder, and major depression have returned results with limited clinical utility. A gene × environment interplay has been proposed as a factor influencing not only pathophysiology but also the treatment response. Therefore, epigenetics has emerged as a major field of research to study the treatment of these three disorders. Among the epigenetic marks that can modify gene expression, DNA methylation is the best studied. We performed a systematic search (PubMed) following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA guidelines for preclinical and clinical studies focused on genome-wide and gene-specific DNA methylation in the context of schizophrenia, bipolar disorders, and major depressive disorder. Out of the 112 studies initially identified, we selected 31 studies among them, with an emphasis on responses to the gold standard treatments in each disorder. Modulations of DNA methylation levels at specific CpG sites have been documented for all classes of treatments (antipsychotics, mood stabilizers, and antidepressants). The heterogeneity of the models and methodologies used complicate the interpretation of results. Although few studies in each disorder have assessed the potential of DNA methylation as biomarkers of treatment response, data support this hypothesis for antipsychotics, mood stabilizers and antidepressants.