Identification of the Risk Genes Associated With Vulnerability to Addiction: Major Findings From Transgenic Animals

Understanding risk factors for substance use disorders (SUD) can facilitate medication development for SUD treatment. While a rich literature exists discussing environmental factors that influence SUD, fewer articles have focused on genetic factors that convey vulnerability to drug use. Methods to identify SUD risk genes include Genome-Wide Association Studies (GWAS) and transgenic approaches. GWAS have identified hundreds of gene variants or single nucleotide polymorphisms (SNPs). However, few genes identified by GWAS have been verified by clinical or preclinical studies. In contrast, significant progress has been made in transgenic approaches to identify risk genes for SUD. In this article, we review recent progress in identifying candidate genes contributing to drug use and addiction using transgenic approaches. A central hypothesis is if a particular gene variant (e.g., resulting in reduction or deletion of a protein) is associated with increases in drug self-administration or relapse to drug seeking, this gene variant may be considered a risk factor for drug use and addiction. Accordingly, we identified several candidate genes such as those that encode dopamine D2 and D3 receptors, mGluR2, M4 muscarinic acetylcholine receptors, and α5 nicotinic acetylcholine receptors, which appear to meet the risk-gene criteria when their expression is decreased. Here, we describe the role of these receptors in drug reward and addiction, and then summarize major findings from the gene-knockout mice or rats in animal models of addiction. Lastly, we briefly discuss future research directions in identifying addiction-related risk genes and in risk gene-based medication development for the treatment of addiction.

Unravelling the Impact of the Genetic Variant rs1042058 within the TPL2 Risk Gene Locus on Molecular and Clinical Disease Course Patients with Inflammatory Bowel Disease

Background: The single nucleotide polymorphism (SNP) rs1042058 within the gene locus encoding tumor progression locus 2 (TPL2) has been recently identified as a risk gene for inflammatory bowel disease (IBD). TPL2 has been shown to regulate pro-inflammatory signaling and cytokine secretion, while inhibition of TPL2 decreases intestinal inflammation in vivo. However, the clinical and molecular implications of this disease-associated TPL2 variation in IBD patients have not yet been studied. Methods: We analyzed the impact of the IBD-associated TPL2 variation using clinical data of 2145 genotyped patients from the Swiss IBD Cohort Study (SIBDCS). Furthermore, we assessed the molecular consequences of the TPL2 variation in ulcerative colitis (UC) and Crohn’s disease (CD) patients by real-time PCR and multiplex ELISA of colon biopsies or serum, respectively. Results: We found that presence of the SNP rs1042058 within the TPL2 gene locus results in significantly higher numbers of CD patients suffering from peripheral arthritis. In contrast, UC patients carrying this variant feature a lower risk for intestinal surgery. On a molecular level, the presence of the rs1042058 (GG) IBD-risk polymorphism in TPL2 was associated with decreased mRNA levels of IL-10 in CD patients and decreased levels of IL-18 in the intestine of UC patients. Conclusions: Our data suggest that the presence of the IBD-associated TPL2 variation might indicate a more severe disease course in CD patients. These results reveal a potential therapeutic target and demonstrate the relevance of the IBD-associated TPL2 SNP as a predictive biomarker in IBD.

Integrated multi-omics data analysis identifies a novel genetics-risk gene of IRF4 associated with prognosis of oral cavity cancer

Oral cavity cancer (OCC) is one of the most common carcinoma diseases. Recent genome-wide association studies (GWAS) have reported numerous genetic variants associated with OCC susceptibility. However, the regulatory mechanisms of these genetic variants underlying OCC remain largely unclear. By combining GWAS summary statistics (N = 4,151) with expression quantitative trait loci (eQTL) across 49 different tissues from the GTEx database, we performed an integrative genomics analysis to uncover novel risk genes associated with OCC. By leveraging various computational methods based on multi-omics data, risk genes were prioritized as promising candidate genes for drug repurposing in OCC.Using two independent computational algorithms, we found that 14 risk genes whose genetics-modulated expressions showed a notable association with OCC. Among them, nine genes were newly identified, such as IRF4 (P = 2.5x10-9 and P = 1.06x10-4), TNS3 (P = 1.44x10-6 and P = 4.45x10-3), ZFP90 (P = 2.37x10-6 and P = 2.93x10-4), and DRD2 (P = 2.0x10-5 and P = 6.12x10-3). These 14 genes were significantly overrepresented in several cancer-related terms, and 10 of 14 genes were enriched in 10 potential druggable gene categories. Based on differential gene expression analysis, the majority of these genes (71.43%) showed remarkable differential expressions between OCC patients and paracancerous controls. Integration of multi-omics-based evidence from genetics, eQTL, and gene expression, we identified that the novel risk gene of IRF4 exhibited the highest ranked risk score for OCC. Survival analysis showed that dysregulation of IRF4 expression was significantly associated with cancer patients outcomes (P = 8.1x10-5). In summary, we prioritized 14 OCC-associated genes with nine novel risk genes, especially the IRF4 gene, which provides a drug repurposing resource to develop therapeutic drugs for oral cancer.

Over-representation of potential SP4 target genes within schizophrenia-risk genes

Reduction of Sp4 expression causes age-dependent hippocampal vacuolization and many other intermediate phenotypes of schizophrenia in Sp4 hypomorphic mice. Recent human genetic studies from both the Schizophrenia Exome Sequencing Meta-Analysis (SCHEMA) and the Genome-Wide Association Study (GWAS) validated SP4 as a schizophrenia-risk gene over the exome-wide or the genome-wide significance. Truncation of the human SP4 gene has an odds ratio of 9.37 (3.38–29.7) for schizophrenia. Despite successful identification of many schizophrenia-risk genes, it is unknown whether and how these risk genes may interact with each other in the development of schizophrenia. By taking advantage of the specific localization of the GC-boxes bound by SP4 transcription factors, I analyzed the relative abundance of these GC-boxes in the proximal promoter regions of schizophrenia-risk genes. I found that the GC-box containing genes are significantly over-represented within schizophrenia-risk genes, suggesting that SP4 is not only a high-risk gene for schizophrenia, but may also act as a hub of network in the regulation of many other schizophrenia-risk genes via these GC-boxes in the pathogenesis of schizophrenia.

Identification of Myeloma-Initiating Cells By Single-Cell RNA Sequencing

Background: The outcomes of patients with multiple myeloma (MM) have improved due to treatment advances. However, some patients still experience rapid progression, multiple drug resistance or recurrent relapse. Tumor-initiating cells, also known as cancer stem cells (CSC) in some cancer types, have been speculated to induce recurrence of the disease. The aim of this study is to infer the identity of myeloma-initiating cells (MICs) utilizing single-cell transcriptome analysis and explore the unique biological characteristics relating with high-risk and drug-resistance. Method: We applied single cell RNA sequencing to fresh bone marrow mononuclear cell samples collecting from 7 healthy donors and 12 newly diagnosed MM patients utilizing 10x Chromium platform. Results: Firstly, we segregated the patients by tumor cell infiltration at single cell resolution and found that Myc pathway was significantly enriched in patients with high tumor burden (HTB). Next, we performed clustering analysis to tumor cells and identified 13 tumor subpopulations in total. Surprisingly, the distribution pattern of tumor subpopulations presented similarity among HTB patients, whereas we did not find the uniform subpopulation composition among the patients with low (LTB) or medium tumor burden (MTB). Via the tumor subpopulation analysis, we clarified the divergence in biological characteristics of these 13 malignant subpopulations. We identified plasmablasts as displaying high expression of B-cell gene signatures (CD19, CD27, MS4A1 and CD79B) and relatively low expression of plasma cell gene signatures (SDC1 and BCMA). Additionally, we also noted that they showed high level of CD24, which has been validated to be the marker gene for MICs. We next examined proliferative capability and utilized the 70 high-risk gene model and 56 drug resistance-related gene model to further distinguish subpopulations with the most malignant gene expression features. Notably, we found that plasmablasts possessed characteristics of high proliferation, drug-resistance and high-risk gene profiling, indicating their role as the root of myeloma, namely MIC subpopulation. Gene enrichment analysis also implicated that Wnt pathway, Notch pathway, stem cell differentiation pathway and Hedgehog pathway were enriched in MIC subpopulation which were associated with the proliferation, migration and drug resistance of MM. Differentially expressed gene (DEG) analysis showed that common driver genes in myeloma, such as CCND2, ITGB7 and CD74, were upregulated in MIC subpopulation comparing with other subpopulations. Conclusion: Our work presents an integral profiling for tumor cells in myeloma at single cell resolution. We uncovered divergence in the distribution of malignant subclusters across patients and distinct heterogeneity in gene expression across malignant subclusters as well. Plasmablasts expressing high level of CD24, CD27 and dim CD138 presented as the MICs with characteristics of higher proliferation, drug-resistance and high-risk gene profiling. Disclosures No relevant conflicts of interest to declare.