FOXN3 and GDNF Polymorphisms as Common Genetic Factors of Substance Use and Addictive Behaviors

Vereczkei, Andrea; Barta, Csaba; Mägi, Anna; Farkas, Judit; Eisinger, Andrea; Király, Orsolya; Belik, Andrea; Griffiths, Mark D.; Székely, Anna; Sasvári-Székely, Mária; Potenza, Marc N.; Badgaiyan, Rajendra D.; Blum, Kenneth; Demetrovics, Zsolt; Kótyuk, Eszter

doi:10.3390/jpm12050690

Cited by 16 publications

(10 citation statements)

References 146 publications

(162 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The point of a number of studies was to scrutinize the possible genetic overlaps between different types of substance use, behavioral addictions, and other compulsive behaviors. A genetic association analysis was carried out as a part of the PGA study [12,13], assessing various kinds of addictions in a sample of 3003 adolescent participants. The genetic association analyses targeted 32 single-nucleotide polymorphisms (SNPs) and four substances of abuse (alcohol, tobacco, marijuana, and other drugs), and seven potentially addictive behaviors: internet addiction, gaming, social networking sites addiction, gambling disorder, exercise addiction, trichotillomania, and eating disorders.…”

Section: Reward Deficiency Syndrome Index (Rdsi) and Geneticsmentioning

confidence: 99%

Genetic Addiction Risk and Psychological Profiling Analyses for “Preaddiction” Severity Index

Blum

Han

Bowirrat

et al. 2022

JPM

Self Cite

View full text Add to dashboard Cite

Since 1990, when our laboratory published the association of the DRD2 Taq A1 allele and severe alcoholism in JAMA, there has been an explosion of genetic candidate association studies, including genome-wide association studies (GWAS). To develop an accurate test to help identify those at risk for at least alcohol use disorder (AUD), a subset of reward deficiency syndrome (RDS), Blum’s group developed the genetic addiction risk severity (GARS) test, consisting of ten genes and eleven associated risk alleles. In order to statistically validate the selection of these risk alleles measured by GARS, we applied strict analysis to studies that investigated the association of each polymorphism with AUD or AUD-related conditions, including pain and even bariatric surgery, as a predictor of severe vulnerability to unwanted addictive behaviors, published since 1990 until now. This analysis calculated the Hardy–Weinberg Equilibrium of each polymorphism in cases and controls. Pearson’s χ2 test or Fisher’s exact test was applied to compare the gender, genotype, and allele distribution if available. The statistical analyses found the OR, 95% CI for OR, and the post risk for 8% estimation of the population’s alcoholism prevalence revealed a significant detection. Prior to these results, the United States and European patents on a ten gene panel and eleven risk alleles have been issued. In the face of the new construct of the “preaddiction” model, similar to “prediabetes”, the genetic addiction risk analysis might provide one solution missing in the treatment and prevention of the neurological disorder known as RDS.

show abstract

Section: Reward Deficiency Syndrome Index (Rdsi) and Geneticsmentioning

confidence: 99%

Genetic Addiction Risk and Psychological Profiling Analyses for “Preaddiction” Severity Index

Blum

Han

Bowirrat

et al. 2022

JPM

Self Cite

View full text Add to dashboard Cite

show abstract

“…The aim of one notable study was to investigate the possible genetic overlaps between different types of substance use, behavioral addictions, and other compulsive behaviors. A genetic association analysis was carried out as a part of the Psychological and Genetic Factors of Addictions (PGA) study [ 27 ] to assess several types of addictions in a sample of 3003 adolescent participants. The genetic association analyses focused on 32 SNPs, addictive substances (alcohol, tobacco, marijuana, and other illicit drugs), and potentially addictive behaviors (internet use, gaming, social media use, gambling, exercise, trichotillomania, and eating disorders).…”

Section: Rds Criteriamentioning

confidence: 99%

Should Reward Deficiency Syndrome (RDS) Be Considered an Umbrella Disorder for Mental Illness and Associated Genetic and Epigenetic Induced Dysregulation of Brain Reward Circuitry?

Blum

Dennen

Elman

et al. 2022

JPM

View full text Add to dashboard Cite

Reward Deficiency Syndrome (RDS) is defined as a breakdown of reward neurotransmission that results in a wide range of addictive, compulsive, and impulsive behaviors. RDS is caused by a combination of environmental (epigenetic) influences and DNA-based (genetic) neurotransmission deficits that interfere with the normal satisfaction of human physiological drives (i.e., food, water, and sex). An essential feature of RDS is the lack of integration between perception, cognition, and emotions that occurs because of (1) significant dopaminergic surges in motivation, reward, and learning centers causing neuroplasticity in the striato-thalamic-frontal cortical loop; (2) hypo-functionality of the excitatory glutamatergic afferents from the amygdala–hippocampus complex. A large volume of literature regarding the known neurogenetic and psychological underpinnings of RDS has revealed a significant risk of dopaminergic gene polymorphic allele overlap between cohorts of depression and subsets of schizophrenia. The suggestion is that instead of alcohol, opioids, gambling disorders, etc. being endophenotypes, the true phenotype is RDS. Additionally, reward deficiency can result from depleted or hereditary hypodopaminergia, which can manifest as a variety of personality traits and mental/medical disorders that have been linked to genetic studies with dopamine-depleting alleles. The carrying of known DNA antecedents, including epigenetic insults, results in a life-long vulnerability to RDS conditions and addictive behaviors. Epigenetic repair of hypodopaminergia, the causative basis of addictive behaviors, may involve precision DNA-guided therapy achieved by combining the Genetic Addiction Risk Severity (GARS) test with a researched neutraceutical having a number of variant names, including KB220Z. This nutraceutical formulation with pro-dopamine regulatory capabilities has been studied and published in peer-reviewed journals, mostly from our laboratory. Finally, it is our opinion that RDS should be given an ICD code and deserves to be included in the DSM-VI because while the DSM features symptomology, it is equally important to feature etiological roots as portrayed in the RDS model.

show abstract

“…The statistical analyses found the OR, 95% CI for OR, and a post-risk for 8% estimation of the population's alcoholism prevalence showed a significant detection. The OR results indicated significance for COMT, OPRM1, DRD2, DRD3, DRD4, DAT1, and 5HTT at 5% (Blum et al 2018 , 2020 , 2021 ; Blum et al 2022a , b ; Blum et al 2022a , b ; Fried et al 2020 ; Moran et al 2021 ; Bajaj et al 2022 ; Dennen et al 2022 ; Gondré-Lewis et al 2022 ; Gupta et al 2022 ; Vereczkei et al 2022 ; Thanos et al 2023a , b ; Thanos et al 2023a , b ). Consequently, this study aimed to explore the most effective pharmacogenomic approach to managing spinal pain in postoperative patients by analyzing potential actionable genetic variants associated with FDA-approved drugs targeting specific receptors, that is, the genes themselves (Table 2 ).…”

Section: Introductionmentioning

confidence: 99%

A Pharmacogenomics-Based In Silico Investigation of Opioid Prescribing in Post-operative Spine Pain Management and Personalized Therapy

Lewandrowski,

Sharafshah,

Elfar

et al. 2024

Cell Mol Neurobiol

Self Cite

View full text Add to dashboard Cite

Considering the variability in individual responses to opioids and the growing concerns about opioid addiction, prescribing opioids for postoperative pain management after spine surgery presents significant challenges. Therefore, this study undertook a novel pharmacogenomics-based in silico investigation of FDA-approved opioid medications. The DrugBank database was employed to identify all FDA-approved opioids. Subsequently, the PharmGKB database was utilized to filter through all variant annotations associated with the relevant genes. In addition, the dpSNP (https://www.ncbi.nlm.nih.gov/snp/), a publicly accessible repository, was used. Additional analyses were conducted using STRING-MODEL (version 12), Cytoscape (version 3.10.1), miRTargetLink.2, and NetworkAnalyst (version 3). The study identified 125 target genes of FDA-approved opioids, encompassing 7019 variant annotations. Of these, 3088 annotations were significant and pertained to 78 genes. During variant annotation assessments (VAA), 672 variants remained after filtration. Further in-depth filtration based on variant functions yielded 302 final filtered variants across 56 genes. The Monoamine GPCRs pathway emerged as the most significant signaling pathway. Protein–protein interaction (PPI) analysis revealed a fully connected network comprising 55 genes. Gene–miRNA Interaction (GMI) analysis of these 55 candidate genes identified miR-16-5p as a pivotal miRNA in this network. Protein–Drug Interaction (PDI) assessment showed that multiple drugs, including Ibuprofen, Nicotine, Tramadol, Haloperidol, Ketamine, l-Glutamic Acid, Caffeine, Citalopram, and Naloxone, had more than one interaction. Furthermore, Protein–Chemical Interaction (PCI) analysis highlighted that ABCB1, BCL2, CYP1A2, KCNH2, PTGS2, and DRD2 were key targets of the proposed chemicals. Notably, 10 chemicals, including carbamylhydrazine, tetrahydropalmatine, Terazosin, beta-methylcholine, rubimaillin, and quinelorane, demonstrated dual interactions with the aforementioned target genes. This comprehensive review offers multiple strong, evidence-based in silico findings regarding opioid prescribing in spine pain management, introducing 55 potential genes. The insights from this report can be applied in exome analysis as a pharmacogenomics (PGx) panel for pain susceptibility, facilitating individualized opioid prescribing through genotyping of related variants. The article also points out that African Americans represent an important group that displays a high catabolism of opioids and suggest the need for a personalized therapeutic approach based on genetic information. Graphical Abstract

show abstract

FOXN3 and GDNF Polymorphisms as Common Genetic Factors of Substance Use and Addictive Behaviors

Cited by 16 publications

References 146 publications

Genetic Addiction Risk and Psychological Profiling Analyses for “Preaddiction” Severity Index

Genetic Addiction Risk and Psychological Profiling Analyses for “Preaddiction” Severity Index

Should Reward Deficiency Syndrome (RDS) Be Considered an Umbrella Disorder for Mental Illness and Associated Genetic and Epigenetic Induced Dysregulation of Brain Reward Circuitry?

A Pharmacogenomics-Based In Silico Investigation of Opioid Prescribing in Post-operative Spine Pain Management and Personalized Therapy

Contact Info

Product

Resources

About