Candidate pharmacological treatments for substance use disorder and suicide identified by gene co‐expression network‐based drug repositioning

Abstract

Patients with substance use disorders (SUD) are at high risk to die by suicide. So far, the neurobiology of the suicide-SUD association has not been elucidated. This study aimed to identify potential pharmacological targets among hub genes from brain gene co-expression networks of individuals with SUD in a suicidal and non-suicidal context. Post-mortem samples from the prefrontal cortex of 79 individuals were analyzed. Individuals were classified into the following groups: suicides with SUD (n = 28), suicides without SUD (n = 23), nonsuicides with SUD (n = 9), nonsuicides without SUD (n = 19). Gene expression profiles were evaluated with the Illumina HumanHT-12 v4 array. Co-expression networks were constructed in WGCNA using the differentially expressed genes found in the comparisons: (a) suicides with and without SUD and (b) nonsuicides with and without SUD. Hub genes were selected for druggene interaction testing in the DGIdb database. Among drugs interacting with hub genes in suicides we found MAOA inhibitors and dextromethorphan. In the nonsuicide individuals, we found interactions with eglumegad and antipsychotics (olanzapine, clozapine, loxapine). Modafinil was found to interact with genes in both suicides and nonsuicides. These drugs represent possible candidate treatments for patients with SUD with and without suicidal behavior and their study in each context is encouraged.

Repurposing Drugs via Network Analysis: Opportunities for Psychiatric Disorders

“…As an example of the former, Cabrera-Mendoza et al used transcriptional profiles from post-mortem brain samples of substance-use disorder individuals with and without suicidal behaviour to build gene co-expression networks associated with each phenotype ( Table 2 ). The hub genes from these networks were then subjected to drug–gene interaction testing using the DGIdb database [ 94 ] to identify drug repurposing candidates [ 75 ]. Integration of transcriptomic profiles with GWAS data was adopted by Rodriguez-López et al for finding druggable targets in schizophrenia.…”

“…GWAS ATLAS [60] NCBI Database of Genotypes and Phenotypes (dbGaP) [61] GWAS (psychiatry): NIMH Repository and Genomics Resource (NRGR) [62] Psychiatric Genomics Consortium (PGC) [63] Autism Sequencing Consortium (ASC) [64] Whole-Genome Sequencing Consortium for Psychiatric Disorders (WGSPD) [65] Human brain resources: PsychENCODE [66] Brain Somatic Mosaicism Network [67] CommonMind Consortium [68] Allen Brain Atlas [69] Drug response: Connectivity Map (CMap) [70] Library of Integrated Network-Based Cellular Signatures (LINCS) [71] Drug Gene Budger (DGB) [72] Depression [73] Schizophrenia [74] Substance use disorder [75] Autism spectrum disorder [76] Interactome Protein-protein interaction:…”

Genomics and epigenomics of substance use disorders: An introduction

“…This special issue includes a total of seven works (Cabrera-Mendoza et al, 2021;Gerring, Vargas, Gamazon, & Derks, 2020;Lai et al, 2020;Maldonado et al, 2021;Markunas et al, 2020;Soundararajan et al, 2021;Vilar-Rib o et al, 2020) that cover different topics on the genomics and epigenomics of SUD, one of them a review and the rest original research articles.…”

“…We close our issue with work by Cabrera-Mendoza et al (2021) that aims at identifying potential pharmacological targets for SUD in the context of suicide behavior, given that 40% of patients seeking treatment for SUD report at least one suicide attempt. The authors hypothesize that SUD patients with comorbid suicidal behavior may require a treatment different from those without this behavior.…”