Eliot L. Gardner

Background/Objectives: Post-Traumatic Stress Disorder (PTSD) is a complex psychiatric condition with a strong polygenic and stress-related biological basis. Although Genome-Wide Association Studies (GWAS) have acknowledged abundant risk variants, translating these findings into biologically meaningful candidates remains challenging. This study introduces an integrative computational approach from raw file preparation by python-coded application into downstream in-depth silico analyses designed to systematically refine GWAS signals for PTSD using fine-mapping, linkage disequilibrium (LD), and haplotype analyses. Methods: GWAS source file for PTSD was obtained from the GWAS Catalog (EFO_0001358) and analyzed using a custom Python pipeline integrating data harmonization, genome-wide visualization, LD estimation via 1000 Genomes reference panels, approximate Bayesian fine-mapping, and Haploview-inspired haplotype inference. SNPs were filtered based on statistical significance, LD structure, and posterior inclusion probability. Downstream systems’ biology analyses included protein–protein interaction modeling and pharmacogenomics (PGx) annotations. Results: From the primary GWAS dataset, 100 top-ranked SNPs were selected, leading to the identification of 58 significant loci. LD and haplotype analyses refined these signals to 93 candidate SNPs (66 genes). Following the exclusion of non-protein-coding genes, 45 genes remained, and network-based prioritization generated a final list of 20 biologically connected and pharmacogenetically relevant genes associated with PTSD. Conclusions: This integrative approach provided a robust and reproducible framework for GWAS fine-mapping and variant prioritization, effectively reducing large-scale GWAS outputs to biologically interpretable PTSD risk loci and genes.

Background: There are important gaps in describing the associations between variants found by GWAS and various phenotypes. Prior reports suggest that SNPs in regulatory regions should be further investigated to uncover these associations. Thus, this study involved a novel approach, along with Pharmacoepigenomics, prompting a new coined term “CpG-PGx SNP”. Methods: The rationale behind our analysis strategy was based on the impact of SNPs playing dual roles both in the CpG site disruption/formation and having PGx associations. Thus, we employed GeneCards (relevance score), PharmGKB (significant p-value), and GWAS catalog data for each gene (p < 5 × 10⁻⁸). Following the obtainment of the 25 best-scored genes of four major epigenetic processes (methylation, demethylation, acetylation, and deacetylation), we generated two lists of candidate genes, including potential CpG-PGx SNPs and possible CpG-PGx SNPs. Results: Among 2900 significant PGx annotations, we found 99 potential CpG-PGx SNPs related to 16 genes. CYP2B6, CYP2C19, CYP2D6, and COMT genes were the top genes. Additionally, we found 1230 significant GWAS-based SNPs, among them 329 CpG-SNPs related to 48 genes with at least one CpG site disruption/formation. The top gene with the highest CpG-SNPs was TET2, followed by JMJD1C and HDAC9. Importantly, we detected some synonymous variants in the Epigenetically Modifiable Accessible Region (EMAR), which can provide insights into undiscovered roles of these SNPs. We identified 173 CpG-Disruptive SNPs, 155 CpG-Forming SNPs, and just 1 CpG SNP with both impacts. Conclusions: In conclusion, here we introduce CpG-PGx SNP for the first time and suggest three major genes playing crucial roles in Pharmacoepigenomics (PEpGx), CYP2D6 as the heart of PEpGx, and TET2 with the highest possibility of having CPG-PGx SNPs. We believe that this approach will help the scientific community to utilize “CpG-PGx SNP” to unravel complex disease-driven genetic and epigenetic interactions, yielding therapeutic opportunities.

We previously theorized that Attention-Deficit Hyperactivity Disorder (ADHD) may increase susceptibility to narcolepsy and hypersomnia, potentially sharing genomic and pathophysiological features with addictive behaviours linked to Reward Deficiency Syndrome (RDS). We further suggested that the emergence of narcolepsy in individuals with underlying ADHD or RDS may place additional stress on the dopaminergic reward system. To explore this, we conducted comprehensive data mining using GWAS catalog databases focused on ADHD and narcolepsy, identifying three relevant datasets. These were individually analyzed in GWAS meta-analyses, followed by a combined GWAS meta-meta-analysis. From this, we derived a Primary Gene List (PGL) of 512 genes and a Secondary Gene List (SGL) of 42 genes, which were further examined through in-depth silico, systems biology, and pharmacogenomic (PGx) approaches. Our findings revealed a fully connected protein–protein interaction (PPI) network between ADHD and narcolepsy, with FOXP2 and RBFOX1 emerging as shared genes. We also identified schizophrenia as a potential endophenotype linking ADHD and narcolepsy. PGx analysis revealed pharmacogenomic relevance for seven genes from the SGL. To further investigate PGx–PPI relationships, we incorporated ten GARS family genes along with eight identified pharmacogenes in PGx-PPIs, and included FOXP2, RBFOX1, and GRIN2A, despite the absence of PGx data for the latter three. This analysis highlighted DRD2 and NRXN1 as central components of the dopaminergic [Genetic Addiction Risk Severity (GARS)] pathway, forming critical connections in the ADHD–schizophrenia–narcolepsy axis. These results support our initial hypothesis of a shared genetic basis between ADHD and narcolepsy. Additionally, we identified potentially overlapping genes with schizophrenia and highlighted dopaminergic regulatory variants of FOXP2, RBFOX1, and GRIN2A as promising diagnostic markers and therapeutic targets for future research.

Background: There are important gaps in describing the associations between variants found by GWAS and various phenotypes. Prior reports suggested that SNPs in regulatory regions should be more investigated to uncover these associations. Thus, this study initiated a novel method along with Pharmacoepigenomics suggesting a new coined term “CpG-PGx SNP”. Methods: The rationale behind our analysis strategy was based on the impact of SNPs playing dual roles both in the CpG site disruption/formation and having PGx associations. Thus, we employed GeneCards (relevance score), PharmGKB (significant p-value), and GWAS catalog data for each gene (p<E-8). Following obtaining the 25 best-scored genes of four major epigenetic processes (methylation, demethylation, acetylation, and deacetylation), we generated two lists of candidate genes including potential CpG-PGx SNPs 2 of 22 and possible CpG-PGx SNPs. Results: Among 2,900 significant PGx annotations, we found 99 potential CpG-PGx SNPs related to 16 genes. CYP2B6, CYP2C19, CYP2D6, and COMT genes were the top genes. Additionally, we found 1,230 significant GWAS-based SNPs, among them 329 CpG-SNPs related to 48 genes with at least one CpG site disruption/formation. The top gene with the highest CpG-SNPs was TET2, followed by JMJD1C, and HDAC9. Importantly, we detected some synonymous variants in Epigenetically Modifiable Accessible Region (EMAR) which can open new insights into undiscovered roles of these SNPs. We identified 173 CpG-Disruptive SNPs, 155 CpG-Forming SNPs, and just 1 CpG SNP with both impacts. Conclusion: In conclusion, here we introduced CpG-PGx SNP for the first time, suggested 3 major genes playing crucial roles in Pharmacoepigenomics (PEpGx), CYP2D6 as the heart of PEpGx, and TET2 with the highest possibility of having CPG-PGx SNPs. We believe that his novel technological advance potentially will help the scientific community to utilize “CpG-PGx SNP” to unravel complex disease driven genetic and epigenetic interactions yielding therapeutic opportunities.

Autism Spectrum Disorder (ASD) is a complex syndrome with a plethora of clinical manifestations. Although such variability may be attributable to diverse genetic and epigenetic factors, mesolimbic dopaminergic reward pathways are consistently implicated in the illness’ course and neuropathobiology pointing to a need in an updated perspective on such a potential overlap area. To that end, we introduce a structured framework dissecting ASD's pathophysiology into stages while emphasizing the involvement of the classical reward structures. Through data mining of Genome-Wide Association Studies (GWAS) and in silico analyses, we uncovered genetic and epigenetic markers pointing to Reward Deficiency Syn-drome (RDS) component of ASD. We employ innovative approaches, including protein-protein interactions, gene regulatory networks, and systems biology analyses, to identify pathways and ASD gene ontologies. The multi-omics analysis integrates findings across genomics, proteomics, metabolomics, and phenomics, reinforcing the concept of ASD as an endophenotype of RDS. This comprehensive approach offers new insights into the genetic architecture and molecular mechanisms of ASD, paving the way for personalized medicine strategies thus yielding novel therapeutic interventions.

The convergence of neurogenetics, epigenetics, and functional neuroimaging presented in this article marks a critical inflection point in our understanding and management of reward deficiency syndrome (RDS) and its behavioral expressions across pain and addiction medicine. The evidence for a hypodopaminergic state, now supported by decades of molecular, clinical, and imaging data, has culminated in the formulation of a scientifically grounded, personalized, and preventative paradigm— anchored by the concept of early genetic testing to provide risk information linked to “prediction” predominantly due to dopaminergic dysfunction. From a translational standpoint, this model offers more than a framework for understanding neurobiological vulnerability; it provides a practical roadmap for early identification of “pre-addiction,” informed opioid prescribing, relapse prevention, and long-term neurorecovery. The coupling of Genetic Addiction Risk Severity (GARS) with dopaminergic modulation—via safe, non-addictive interventions—could redefine standard treatment algorithms not only for substance use disorders but also for a broader spectrum of compulsive and comorbid behaviors. This study by members of the RDS Consortium explores the concept of “pre-addiction” within addiction biology through a comprehensive in silico analysis of 88,788,381 genome-wide association study-based samples from 1,373 studies, identifying 18 significant genes (e.g., APOE with p=1.0E-126) linked to opioids, pain, aging, and apoptosis pathways. It aims to correlate these genes with GARS, which includes 10 specific genes, and highlights the most connected genes, such as MAOA, COMT, APOE, and SLC4A6, through a STRING model. The analysis expanded to 27 unique genes, emphasizing significant interactions with hsa-miR-16-5p and hsa-miR-24-3p, especially SLC6A4. Through pharmacogenomics mining, 1,173 variant annotations were identified for these genes. Enrichment analysis and meta-analysis further validated these findings, illustrating the pivotal role of dopaminergic pathways in connecting addictive behaviors and depressive symptoms. The results support the conceptualization of RDS as the fundamental preaddiction phenotype, with pain, opioid dependence, aging, and apoptosis as critical endophenotypes.

Background and Purpose: β‐Caryophyllene (BCP) is a plant‐derived terpenoid used as a food additive for many decades. Recent studies indicate that BCP is a cannabinoid CB₂ receptor agonist with medical benefits for a number of human diseases. However, little is known about its therapeutic potential for drug abuse and addiction.Experiment Approach: We used pharmacological, transgenic, and optogenetic approaches to systematically evaluate the effects of BCP on nicotine‐taking and nicotine‐seeking behaviour in animal models of drug self‐administration, electrical, and optical brain‐stimulation reward.Key Results: Systemic administration of BCP dose‐dependently inhibited nicotine self‐administration and motivation for nicotine seeking in rats and mice. The reduction in nicotine self‐administration was blocked by AM630, a selective CB₂ receptor antagonist, but not by AM251, a selective CB₁ receptor antagonist, suggesting involvement of a CB₂ receptor mechanism. Genetic deletion of CB₂ receptors in mice blocked the reduction in nicotine self‐administration produced only by low doses, but not by high doses, of BCP, suggesting involvement of both CB₂ and non‐CB₂ receptor mechanisms. Furthermore, in the intracranial self‐stimulation paradigm, BCP attenuated electrical brain‐stimulation reward and nicotine‐enhanced brain‐stimulation reward in rats. Lastly, BCP also attenuated brain‐stimulation reward maintained by optogenetic stimulation of dopaminergic neurons in the ventral tegmental area in DAT‐cre mice, suggesting the involvement of a dopamine‐dependent mechanism in BCP's action.Conclusions and Implications: The present findings suggest that BCP has significant anti‐nicotine effects via both CB₂ and non‐CB₂ receptor mechanisms and, therefore, deserves further study as a potential new pharmacotherapy for cigarette smoking cessation.

Background and Purpose: Cannabis or cannabinoids produce characteristic tetrad effects—analgesia, hypothermia, catalepsy and suppressed locomotion, which are believed to be mediated by the activation of cannabinoid CB₁ receptors. Given recent findings of CB₂ and GPR55 receptors in the brain, we examined whether these receptors are also involved in cannabinoid action.Experimental Approach: We compared Δ⁹‐tetrahydrocannabinol (Δ⁹‐THC)‐, WIN55212‐2‐, or XLR11‐induced tetrad effects between wild‐type (WT) and each genotype of CB₁‐, CB₂‐ or GPR55‐knockout (KO) mice and then observed the effects of antagonists of these receptors on these tetrad effects in WT mice.Key Results: Systemic administration of Δ⁹‐THC, WIN55212‐2 or XLR11 produced dose‐dependent tetrad effects in WT mice. Genetic deletion or pharmacological blockade of CB₁ receptors abolished the tetrad effects produced by all three cannabinoids. Unexpectedly, genetic deletion of CB₂ receptor abolished analgesia and catalepsy produced by Δ⁹‐THC or WIN55212‐2, but not by XLR11. Microinjections of Δ⁹‐THC into the lateral ventricles also produced tetrad effects in WT, but not in CB₁‐KO mice. CB₂‐KO mice displayed a reduction in intraventricular Δ⁹‐THC‐induced analgesia and catalepsy. In contrast to CB₁ and CB₂ receptors, genetic deletion of GPR55 receptors caused enhanced responses to Δ⁹‐THC or WIN55212‐2. Antagonisim of CB₁, CB₂ or GPR55 receptors produced alterations similar to those observed in each genotype mouse line.Conclusions and Implications: These findings suggest that in addition to CB₁, both CB₂ and GPR55 receptors are also involved in some pharmacological effects produced by cannabinoids. CB₁/CB₂, in contrast to GPR55, receptors appears to play opposite roles in cannabinoid action.