Investigation of convergent and divergent genetic influences underlying schizophrenia and alcohol use disorder

A multi-omics Mendelian randomization study identifies new therapeutic targets for alcohol use disorder and problem drinking

Integrating proteomic and transcriptomic data with genetic architectures of problematic alcohol use and alcohol consumption behaviours can advance our understanding and help identify therapeutic targets. We conducted systematic screens using genome-wise association study data from ~3,500 cortical proteins (N = 722) and ~6,100 genes in 8 canonical brain cell types (N = 192) with 4 alcohol-related outcomes (N ≤ 537,349), identifying 217 cortical proteins and 255 cell-type genes associated with these behaviours, with 36 proteins and 37 cell-type genes being new. Although there was limited overlap between proteome and transcriptome targets, downstream neuroimaging revealed shared neurophysiological pathways. Colocalization with independent genome-wise association study data further prioritized 16 proteins, including CAB39L and NRBP1, and 12 cell-type genes, implicating mechanisms such as mTOR signalling. In addition, genes such as SAMHD1, VIPAS39, NUP160 and INO80E were identified as having favourable neuropsychiatric profiles. These findings provide insights into the genetic landscapes governing problematic alcohol use and alcohol consumption behaviours, highlighting promising therapeutic targets for future research.

Rare and Common Variants Associated with Alcohol Consumption Identify a Conserved Molecular Network

Genome-wide association studies (GWAS) have identified hundreds of common variants associated with alcohol consumption. In contrast, rare variants have only begun to be studied for their role in alcohol consumption. No studies have examined whether common and rare variants implicate the same genes and molecular networks. To address this knowledge gap, we used publicly available alcohol consumption GWAS summary statistics (GSCAN, N=666,978) and whole exome sequencing data (Genebass, N=393,099) to identify a set of common and rare variants for alcohol consumption. Gene-based analysis of each dataset have implicated 294 (common variants) and 35 (rare variants) genes, including ethanol metabolizing genes ADH1B and ADH1C, which were identified by both analyses, and ANKRD12, GIGYF1, KIF21B, and STK31, which were identified only by rare variant analysis, but have been associated with related psychiatric traits. We then used a network colocalization procedure to propagate the common and rare gene sets onto a shared molecular network, revealing significant overlap. The shared network identified gene families that function in alcohol metabolism, including ADH, ALDH, CYP, and UGT. 74 of the genes in the network were previously implicated in comorbid psychiatric or substance use disorders, but had not previously been identified for alcohol-related behaviors, including EXOC2, EPM2A, CACNB3, and CACNG4. Differential gene expression analysis showed enrichment in the liver and several brain regions supporting the role of network genes in alcohol consumption. Thus, genes implicated by common and rare variants identify shared functions relevant to alcohol consumption, which also underlie psychiatric traits and substance use disorders that are comorbid with alcohol use.

Identifying potential risk genes and pathways for neuropsychiatric and substance use disorders using intermediate molecular mediator information

Neuropsychiatric and substance use disorders (NPSUDs) have a complex etiology that includes environmental and polygenic risk factors with significant cross-trait genetic correlations. Genome-wide association studies (GWAS) of NPSUDs yield numerous association signals. However, for most of these regions, we do not yet have a firm understanding of either the specific risk variants or the effects of these variants. Post-GWAS methods allow researchers to use GWAS summary statistics and molecular mediators (transcript, protein, and methylation abundances) infer the effect of these mediators on risk for disorders. One group of post-GWAS approaches is commonly referred to as transcriptome/proteome/methylome-wide association studies, which are abbreviated as T/P/MWAS (or collectively as XWAS). Since these approaches use biological mediators, the multiple testing burden is reduced to the number of genes (∼20,000) instead of millions of GWAS SNPs, which leads to increased signal detection. In this work, our aim is to uncover likely risk genes for NPSUDs by performing XWAS analyses in two tissues-blood and brain. First, to identify putative causal risk genes, we performed an XWAS using the Summary-data-based Mendelian randomization, which uses GWAS summary statistics, reference xQTL data, and a reference LD panel. Second, given the large comorbidities among NPSUDs and the shared cis-xQTLs between blood and the brain, we improved XWAS signal detection for underpowered analyses by performing joint concordance analyses between XWAS results i) across the two tissues and ii) across NPSUDs. All XWAS signals i) were adjusted for heterogeneity in dependent instruments (HEIDI) (non-causality) p-values and ii) used to test for pathway enrichment. The results suggest that there were widely shared gene/protein signals within the major histocompatibility complex region on chromosome 6 (BTN3A2 and C4A) and elsewhere in the genome (FURIN, NEK4, RERE, and ZDHHC5). The identification of putative molecular genes and pathways underlying risk may offer new targets for therapeutic development. Our study revealed an enrichment of XWAS signals in vitamin D and omega-3 gene sets. So, including vitamin D and omega-3 in treatment plans may have a modest but beneficial effect on patients with bipolar disorder.

Pairwise genetic meta-analyses between schizophrenia and substance dependence phenotypes reveals novel association signals with pharmacological significance

Almost half of individuals diagnosed with schizophrenia also present with a substance use disorder, however, little is known about potential molecular mechanisms underlying this comorbidity. We used genetic analyses to enhance our understanding of the molecular overlap between these conditions. Our analyses revealed a positive genetic correlation between schizophrenia and the following dependence phenotypes: alcohol (rg = 0.368, SE = 0.076, P = 1.61 × 10-6), cannabis use disorder (rg = 0.309, SE = 0.033, P = 1.97 × 10-20) and nicotine (rg = 0.117, SE = 0.043, P = 7.0 × 10-3), as well as drinks per week (rg = 0.087, SE = 0.021, P = 6.36 × 10-5), cigarettes per day (rg = 0.11, SE = 0.024, P = 4.93 × 10-6) and life-time cannabis use (rg = 0.234, SE = 0.029, P = 3.74 × 10-15). We further constructed latent causal variable (LCV) models to test for partial genetic causality and found evidence for a potential causal relationship between alcohol dependence and schizophrenia (GCP = 0.6, SE = 0.22, P = 1.6 × 10-3). This putative causal effect with schizophrenia was not seen using a continuous phenotype of drinks consumed per week, suggesting that distinct molecular mechanisms underlying dependence are involved in the relationship between alcohol and schizophrenia. To localise the specific genetic overlap between schizophrenia and substance use disorders (SUDs), we conducted a gene-based and gene-set pairwise meta-analysis between schizophrenia and each of the four individual substance dependence phenotypes in up to 790,806 individuals. These bivariate meta-analyses identified 44 associations not observed in the individual GWAS, including five shared genes that play a key role in early central nervous system development. The results from this study further supports the existence of underlying shared biology that drives the overlap in substance dependence in schizophrenia, including specific biological systems related to metabolism and neuronal function.

The role of alcohol intake in the pharmacogenetics of treatment with clozapine

Clozapine (CLZ) is an atypical antipsychotic reserved for patients with refractory psychosis, but it is associated with a significant risk of severe adverse reactions (ADRs) that are potentiated with the concomitant use of alcohol. Additionally, pharmacogenetic studies have explored the influence of several genetic variants in CYP450, receptors and transporters involved in the interindividual response to CLZ. Herein, we systematically review the current multiomics knowledge behind the interaction between CLZ and alcohol intake, and how its concomitant use might modulate the pharmacogenetics. CYP1A2*1F, *1C and other alleles not yet discovered could support a precision medicine approach for better therapeutic effects and fewer CLZ ADRs. CLZ monitoring systems should be amended and include alcohol intake to protect patients from severe CLZ ADRs.