AccScience Publishing / GPD / Online First / DOI: 10.36922/gpd.8090
Submit to GPD
Cite this article
12
Download
153
Views
Journal Browser
Volume | Year
Issue
Search
Forthcoming Issue
Current Issue
View All
News and Announcements
View All
ORIGINAL RESEARCH ARTICLE

Pre-addiction phenotype is associated with dopaminergic dysfunction: Evidence from 88.8 million genome-wide association study-based samples

Kenneth Blum1,2,3,4,5,6,7,8,9, 10,11,12,13* ,  Alireza Sharafshah14 ,  Kai-Uwe Lewandrowski12,13,15,16 ,  Sérgio Luís Schmidt13 ,  Rossano Kepler Alvim Fiorelli13 ,  Albert Pinhasov1 ,  Abdalla Bowirrat1 ,  Mark S. Gold17 ,  Eliot L. Gardner18 ,  Panayotis K. Thanos1,19 ,  Brian Fuehrlein20 ,  David Baron2,21 ,  Igor Elman1,22 ,  Catherine A. Dennen23 ,  Nicole Jafari9, 24 ,  Foojan Zeine10,25 ,  Alexander P.L. Lewandrowski26 ,  Milan Makale27 ,  Edward J. Modestino28 ,  Keerthy Sunder2,7,29 ,  Kevin T. Murphy5 ,  Chynna Fliegelman30 ,  Shaurya Mahajan3,7 ,  Yatharth Mahajan3 ,  Rajendra D. Badgaiyan31
Show Less
1 Department of Molecular Biology, Adelson School of Medicine, Ariel University, Ariel, Israel
2 Division of Addiction Research and Education, Center for Sports, Exercise, and Mental Health, Western University of Health Sciences, Pomona, California, United States of America
3 Division of Clinical Neurology, The Blum Institute of Neurogenetics and Behavior, Austin, Texas, United States of America
4 Brain and Behavior Laboratory, Department of Psychology, Curry College, Milton, Massachusetts, United States of America
5 Division of Personalized Neuromodulation, PeakLogic, Del Mar, California, United States of America
6 Department of Psychology, Institute of Psychology, Eotvos Lorand University Budapest, Budapest, Hungary
7 Division of Precision Neuromodulation, Sunder Foundation, Palm Springs, California, United States of America
8 Department of Psychiatry, University of Vermont, Burlington, Massachusetts, United States of America
9 Division of Personalized Medicine, Cross-Cultural Research and Educational Institute, San Clemente, California, United States of America
10 Division Psychological Therapy, Awareness Integration Institute, San Clemente, California, United States of America
11 Department of Psychiatry, Wright University, Boonshoff School of Medicine, Dayton, Ohio, United States of America
12 Division of Personalize Pain Modulation, Center for Advanced Spine Care of Southern Arizona, Tucson, Arizona, United States of America
13 Programa de Pós-Graduação em Neurologia, Universidade Federal do Estado do Rio de Janeiro, Rio de Janeiro, Brazil
14 Cellular and Molecular Research Center, School of Medicine, Guilin University of Medical Sciences, Rasht, Iran
15 Department of Orthopedics, Sanitas University Foundation, Bogotá, Washington D.C., United States of America
16 Department of Spine Surgery, University of Arizona, School of Medicine, Tucson, Arizona, United States of America
17 Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, United States of America
18 Neuropsychopharmacology Section, Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, Baltimore, Maryland, United States of America
19 Behavioral Neuropharmacology and Neuroimaging Laboratory on Addictions, Clinical Research Institute on Addictions, Department of Pharmacology and Toxicology, Jacobs School of Medicine and Biosciences, State University of New York at Buffalo, Buffalo, New York, United States of America
20 Yale University School of Medicine, Yale-New Haven Hospital, New Haven, Connecticut, United States of America; Psychiatric Emergency Room, VA Connecticut, Yale University, United States of America
21 Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, California, United States of America
22 Department of Psychiatry, Harvard University, College of Medicine, Cambridge, Massachusetts, United States of America
23 Department of Family Medicine, Jefferson Health Northeast, Philadelphia, Pennsylvania, United States of America
24 Department of Applied Clinical Psychology, The Chicago School of Professional Psychology, Los Angeles, California, United States of America
25 Department of Health Science, California State University at Long Beach, Long Beach, California, United States of America
26 Department of Biological Sciences, Dornsife College of Letters, Arts & Sciences, University of Southern California, Los Angeles, California, United States of America
27 Department of Radiation Medicine and Applied Sciences, UC San Diego, La Jolla, California, United States of America
28 Brain and Behavior Laboratory, Curry College, Milton, Massachusetts, United States of America
29 Department of Medicine, University of California, Riverside School of Medicine, Riverside, California, United States of America
30 Department of Psychology, St. John’s University, Queens, New York City, New York, United States of America
31 Department of Psychiatry, Texas Tech University Health Sciences, School of Medicine, Midland, Texas, United States of America
GPD, 8090 https://doi.org/10.36922/gpd.8090
Received: 20 December 2024 | Revised: 6 May 2025 | Accepted: 6 May 2025 | Published online: 3 July 2025
© 2025 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
Download PDF
Cite
XML
Abstract

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.

Graphical abstract
Keywords
Pre-addiction
Genetic addiction risk severity
Dopaminergic pathways
Reward deficiency syndrome
APOE
Opioid dependence
Aging
Apoptosis
Funding
This study was funded by the grant (R41 MD012318/MD/ NIMHD NIH HHS/United States; K.B. and M.G.L.).
Conflict of interest
Dr. Kenneth Blum, the senior author, is credited with more than 100 worldwide patents on the GARS test and KB220 and patents pending for gene editing. Dr. Blum has licensed one of his patents (10,894,024) to Victory Nutrition International (VNI). He is a paid scientific advisor to some companies, including Electronic Waveform Labs (Huntington Beach, CA); PEAK LOGIC (Del Mar, CA); Center for Advanced Spine Care of Southern Arizona (Tucson); and Sunder Foundation (Palm Springs, CA). Dr. Kenneth Blum is also the Associate Editor and Kai Uwe Lewandowski and Rajendra D Badgaiyan are the Editorial Board Members of this journal but was not in any way involved in the editorial and peer-review process conducted for this paper, directly or indirectly. Separately, other authors declared that they have no known competing financial interests or personal relationships that could have influenced the work reported in this paper.
References
  1. Blum K, Elman I, Dennen CA, et al. “Preaddiction” construct and reward deficiency syndrome: Genetic link via dopaminergic dysregulation. Ann Transl Med. 2022;10:1181.

 

  1. United Nations Publication. World Drug Report. Sales No. E. 21. XI. 8; 2021.

 

  1. Blum K, Thanos PK, Hanna C, et al. “To be or not to be” GWAS ends the controversy about the DRD2 gene as a determinant of reward deficiency syndrome (RDS). Psychol Res Behav Manag. 2023;16:4287-4291. doi: 10.2147/PRBM.S428841

 

  1. McGrath JJ, Al-Hamzawi A, Alonso J, et al. Age of onset and cumulative risk of mental disorders: A cross-national analysis of population surveys from 29 countries. Lancet Psychiatry. 2023;10:668-681. doi: 10.1016/S2215-0366(23)00193-1

 

  1. Kenny PJ. Epigenetics, microRNA, and addiction. Dialogues Clin Neurosci. 2014;16:335-344. doi: 10.31887/DCNS.2014.16.3/pkenny

 

  1. Sillivan SE, Gillespie A. Circular RNA regulation and function in drug seeking phenotypes. Mol Cell Neurosci. 2023;125:103841. doi: 10.1016/j.mcn.2023.103841

 

  1. Blum K, Noble EP, Sheridan PJ, et al. Allelic association of human dopamine D2 receptor gene in alcoholism. JAMA. 1990;263:2055-2060.

 

  1. McLellan AT, Koob GF, Volkow ND. Preaddiction-a missing concept for treating substance use disorders. JAMA Psychiatry. 2022;79:749-751. doi: 10.1001/jamapsychiatry.2022.1652

 

  1. Ekhtiari H, Zare-Bidoky M, Sangchooli A, et al. A methodological checklist for fMRI drug cue reactivity studies: Development and expert consensus. Nat Protoc. 2022;17:567-595. doi: 10.1038/s41596-021-00649-4

 

  1. Blum K, Wood RC, Braverman E, Chen T, Sheridan P. The D2 dopamine receptor gene as a predictor of compulsive disease: Bayes’ theorem. Funct Neurol. 1995;10:37-44.

 

  1. Blum K, Sheridan PJ, Wood RC, et al. The D2 dopamine receptor gene as a determinant of reward deficiency syndrome. J R Soc Med. 1996;89:396-400. doi: 10.1177/014107689608900711

 

  1. Blum KG, Cull JR, Braverman ER, Comings DE. Reward deficiency syndrome. Am Sci. 1996;84:132-145.

 

  1. Blum K, Braverman ER, Holder JM, et al. The reward deficiency syndrome: A biogenetic model for the diagnosis and treatment of impulsive, addictive and compulsive behaviors. J Psychoact Drugs. 2000;32:1-112. doi: 10.1080/02791072.2000.10736099

 

  1. Wenzel A. The Sage Encyclopedia of Abnormal and Clinical Psychology. Vol. 1. United States: Sage Publications; 2017.

 

  1. Kótyuk E, Urbán R, Hende B, et al. Development and validation of the reward deficiency syndrome questionnaire (RDSQ-29). J Psychopharmacol. 2022;36:409-422. doi: 10.1177/02698811211069102

 

  1. Blum K, Han D, Gupta A, et al. Statistical validation of risk alleles in genetic addiction risk severity (GARS) test: Early identification of risk for alcohol use disorder (AUD) in 74,566 case-control subjects. J Pers Med. 2022;12:1385. doi: 10.3390/jpm12091385

 

  1. Blum K, Lott L, Ponce JV, et al. In search of reward deficiency syndrome (RDS)-free controls: The “holy grail” in genetic addiction risk testing. Curr Psychopharmacol. 2020;9:7-21.

 

  1. Blum K, Baron D, Lott L, et al. Biotechnical development of genetic addiction risk score (GARS) and selective evidence for inclusion of polymorphic allelic risk in substance use disorder (SUD). J Syst Integr Neurosci. 2020;6:10.15761/ JSIN.1000221. doi: 10.15761/JSIN.1000221

 

  1. Blum K, Chen AL, Thanos PK, et al. Genetic addiction risk score (GARS)™, a predictor of vulnerability to opioid dependence. Front Biosci. 2018;10:175-196. doi: 10.2741/e816

 

  1. Blum K, Brodie MS, Pandey SC, et al. Researching mitigation of alcohol binge drinking in polydrug abuse: KCNK13 and RASGRF2 gene (s) risk polymorphisms coupled with genetic addiction risk severity (GARS) guiding precision pro-dopamine regulation. J Pers Med. 2022;12:1009. doi: 10.3390/jpm12061009

 

  1. Gupta A, Bowirrat A, Gomez LL, et al. Hypothesizing in the face of the opioid crisis coupling Genetic Addiction Risk Severity (GARS) testing with electrotherapeutic nonopioid modalities such as H-Wave could attenuate both pain and hedonic addictive behaviors. Int J Environ Res Public Health. 2022;19:552. doi: 10.3390/ijerph19010552

 

  1. Blum K, Modestino EJ, Gondre-Lewis M, et al. The benefits of genetic addiction risk score (GARS™) testing in substance use disorder (SUD). Int J Genom Data Min. 2018;2018:115. doi: 10.29014/IJGD-115.000015

 

  1. Moran M, Blum K, Ponce JV, et al. High genetic addiction risk score (GARS) in chronically prescribed severe chronic opioid probands attending multi-pain clinics: An open clinical pilot trial. Mol Neurobiol. 2021;58:3335-3346. doi: 10.1007/s12035-021-02312-1

 

  1. Blum K, Siwicki D, Baron D, Modestino EJ, Badgaiyan RD. The benefits of genetic addiction risk score (GARS™) and pro-dopamine regulation in combating suicide in the American Indian population. J Syst Integr Neurosci. 2018;4:10.15761/ JSIN.1000195. doi: 10.15761/JSIN.1000195

 

  1. Blum K, Steinberg B, Gondre-Lewis MC, et al. A Review of DNA risk alleles to determine epigenetic repair of mRNA expression to prove therapeutic effectiveness in reward deficiency syndrome (RDS): Embracing “precision behavioral management”. Psychol Res Behav Manag. 2021;14:2115-2134. doi: 10.2147/PRBM.S292958

 

  1. Vereczkei A, Barta C, Magi A, et al. FOXN3 and GDNF polymorphisms as common genetic factors of substance use and addictive behaviors. J Pers Med. 2022;12:690. doi: 10.3390/jpm12050690

 

  1. Thanos PK, Hanna C, Mihalkovic A, et al. Genetic correlates as a predictor of bariatric surgery outcomes after 1 year. Biomedicines. 2023;11:2644. doi: 10.3390/biomedicines11102644

 

  1. Fried L, Modestino EJ, Siwicki D, et al. Hypodopaminergia and “precision behavioral management”(PBM): It is a generational family affair. Curr Pharm Biotechnol. 2020;21:528-541. doi: 10.2174/1389201021666191210112108

 

  1. Brewer R, Blum K, Bowirrat A, et al., Transmodulation of dopaminergic signaling to mitigate hypodopminergia and pharmaceutical opioid-induced hyperalgesia. Curr Psychopharmacol. 2020;9:164-184. doi: 10.2174/2211556009999200628093231

 

  1. Blum K, Oscar-Berman M, Demetrovics Z, Barh D, Gold MS. Genetic addiction risk score (GARS): Molecular neurogenetic evidence for predisposition to reward deficiency syndrome (RDS). Mol Neurobiol. 2014;50:765-796. doi: 10.1007/s12035-014-8726-5

 

  1. Blum K, Bowirrat A, Lewis MC, et al. Exploration of epigenetic state hyperdopaminergia (Surfeit) and genetic trait hypodopaminergia (Deficit) during adolescent brain development. Curr Psychopharmacol. 2021;10(3):181-196. doi: 10.2174/2211556010666210215155509

 

  1. Thanos PK, Hanna C, Mihalkovic A, et al. The First exploratory personalized medicine approach to improve bariatric surgery outcomes utilizing psychosocial and genetic risk assessments: Encouraging clinical research. J Pers Med. 2023;13:1164. doi: 10.3390/jpm13071164

 

  1. Blum K, Gold MS, Cadet JL, et al. Dopaminylation in psychostimulant use disorder protects against psychostimulant seeking behavior by normalizing nucleus accumbens (NAc) dopamine expression. Curr Psychopharmacol. 2022;11:11-17. doi: 10.2174/2211556009666210108112737

 

  1. Blum K, Oscar-Berman M, Femino J, et al. Withdrawal from buprenorphine/naloxone and maintenance with a natural dopaminergic agonist: A cautionary note. J Addict Res Ther. 2013;4:10.4172/2155-6105.1000146. doi: 10.4172/2155-6105.1000146

 

  1. Dennen CA, Blum K, Bowirrat A, et al. Genetic addiction risk severity assessment identifies polymorphic reward genes as antecedents to reward deficiency syndrome (RDS) hypodopaminergia’s effect on addictive and non-addictive behaviors in a nuclear family. J Pers Med. 2022;12:1864. doi: 10.3390/jpm12111864

 

  1. Blum K, McLaughlin T, Modestino EJ, et al. Epigenetic repair of terrifying lucid dreams by enhanced brain reward functional connectivity and induction of dopaminergic homeostatic signaling. Curr Psychopharmacol. 2021;10:10.2 174/2211556010666210215153513. doi: 10.2174/2211556010666210215153513

 

  1. Braverman ER, Dennen CA, Gold MS, et al. Proposing a “brain health checkup (BHC)” as a global potential “standard of care” to overcome reward dysregulation in primary care medicine: Coupling genetic risk testing and induction of “dopamine homeostasis”. Int J Environ Res Public Health. 2022;19:5480. doi: 10.3390/ijerph19095480

 

  1. Bajaj A, Blum K, Bowirrat A, et al. DNA Directed pro-dopamine regulation coupling subluxation repair, H-Wave® and other neurobiologically based modalities to address complexities of chronic pain in a female diagnosed with reward deficiency syndrome (RDS): Emergence of induction of “dopamine homeostasis” in the face of the opioid crisis. J Pers Med. 2022;12:1416. doi: 10.3390/jpm12091416

 

  1. Gondré-Lewis MC, Elman I, Alim T, et al. Frequency of the dopamine receptor D3 (rs6280) vs. opioid receptor μ1 (rs1799971) polymorphic risk alleles in patients with opioid use disorder: A preponderance of dopaminergic mechanisms? Biomedicines. 2022;10:870. doi: 10.3390/biomedicines10040870

 

  1. Blum K, Green R, Mullen P, et al. Reward deficiency syndrome solution system (RDSSS) a genetically driven putative inducer of “dopamine homeostasis” as a futuristic alternative to enhance rehabilitation instead of incarceration. Asian J Complement Altern Med. 2023;11:11-14. doi: 10.53043/2347-3894.acam11003

 

  1. Blum K, Gondré-Lewis MC, Baron D, et al. Introducing precision addiction management of reward deficiency syndrome, the construct that underpins all addictive behaviors. Front Psychiatry. 2018;9:548. doi: 10.3389/fpsyt.2018.00548

 

  1. Green DR. Means to an End: Apoptosis and Other Cell Death Mechanisms. United States: Cold Spring Harbor Laboratory Press; 2011.

 

  1. Böhm I, Schild H. Apoptosis: The complex scenario for a silent cell death. Mol Imaging Biol. 2003;5:2-14. doi: 10.1016/s1536-1632(03)00024-6

 

  1. Alberts B. Science. Vol. 320. American Association for the Advancement of Science; 2008. p. 19-19.

 

  1. Karam JA. Apoptosis in Carcinogenesis and Chemotherapy. Netherlands: Springer; 2009.

 

  1. Alberts B, Johnson A, Lewis J, Raff M, Roberts K and Peter W. Chapter 18: Apoptosis: Programmed cell death eliminates unwanted cells. In: Molecular Biology of the Cell. 5th ed. New York: Garland Science; 2008. p. 1115.

 

  1. Elmore S. Apoptosis: A review of programmed cell death. Toxicol Pathol. 2007;35:495-516. doi: 10.1080/01926230701320337

 

  1. Downs BW, Blum K, Baron D, et al. Death by Opioids: Are there non-addictive scientific solutions? J Syst Integr Neurosci. 2019;5:10.15761/JSIN.1000211. doi: 10.15761/JSIN.1000211

 

  1. Hill E, Han D, Dumouchel P, et al. Long term Suboxone™ emotional reactivity as measured by automatic detection in speech. PLoS One. 2013;8:e69043. doi:10.1371/annotation/be0b3a26-c1bc-4d92-98c1- c516acc8dcf2

 

  1. Blum K, Chen TJ, Bailey J, et al. Can the chronic administration of the combination of buprenorphine and naloxone block dopaminergic activity causing anti-reward and relapse potential? Mol Neurobiol. 2011;44:250-268. doi: 10.1007/s12035-011-8206-0

 

  1. Raad M, López WO, Sharafshah A, Assefi M, Lewandrowski KU. Personalized medicine in cancer pain management. J Pers Med. 2023;13(8):1201. doi: 10.3390/jpm13081201

 

  1. Assefi M, Lewandrowski KU, Lorio M, et al. Network-based in silico analysis of new combinations of modern drug targets with methotrexate for response-based treatment of rheumatoid arthritis. J Pers Med. 2023;13(11):1550. doi: 10.3390/jpm13111550

 

  1. Mezher M, Abdallah S, Ashekyan O, et al. Insights on the biomarker potential of exosomal non-coding RNAs in colorectal cancer: An in silico characterization of relatedexosomal lncRNA/circRNA-miRNA-Target Axis. Cells. 2023;12:1081. doi: 10.3390/cells12071081

 

  1. Liu ZP, Wu C, Miao H, Wu H. RegNetwork: An integrated database of transcriptional and post-transcriptional regulatory networks in human and mouse. Database. 2015;2015:bav095. doi: 10.1093/database/bav095

 

  1. Atreya RV, Sun J, Zhao Z. Exploring drug-target interaction networks of illicit drugs. BMC Genom. 2013;14:S1-12. doi: 10.1186/1471-2164-14-S4-S1

 

  1. Wang X, Shi Z, Zhao Z, et al. The causal relationship between neuromyelitis optica spectrum disorder and other autoimmune diseases. Front Immunol. 2022;13:959469. doi: 10.3389/fimmu.2022.959469

 

  1. Marballi KK, Alganem K, Brunwasser SJ, et al. Identification of activity-induced Egr3-dependent genes reveals genes associated with DNA damage response and schizophrenia. Transl Psychiatry. 2022;12(1):320. doi: 10.1038/s41398-022-02069-8

 

  1. Evangelista JE, Xie Z, Marino GB, Nguyen N, Clarke DJ, Ma’ayan A. Enrichr-KG: Bridging enrichment analysis across multiple libraries. Nucleic Acids Res. 2023;51(W1):W168-W179. doi: 10.1093/nar/gkad393

 

  1. Stark C, Breitkreutz BJ, Reguly T, Boucher L, Breitkreutz A, Tyers M. BioGRID: A general repository for interaction datasets. Nucleic Acids Res. 2006;34:D535-D539. doi: 10.1093/nar/gkj109

 

  1. Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun. 2019;10:1523. doi: 10.1038/s41467-019-09234-6

 

  1. Bader GD, Hogue CW. An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinformatics. 2003;4:1-27. doi: 10.1186/1471-2105-4-2

 

  1. Knowler WC, Fowler SE, Hamman RF, et al. 10-year follow-up of diabetes incidence and weight loss in the diabetes prevention program outcomes study. Lancet. 2009;374:1677-1686. doi: 10.1016/S0140-6736(09)61457-4

 

  1. Glechner A, Keuchel L, Affengruber L, et al. Effects of lifestyle changes on adults with prediabetes: A systematic review and meta-analysis. Prim Care Diabetes. 2018;12:393-408. doi: 10.1016/j.pcd.2018.07.003

 

  1. Elman I, Borsook D. Common brain mechanisms of chronicpain and addiction. Neuron. 2016;89:11-36. doi: 10.1016/j.neuron.2015.11.027

 

  1. Dennen AC, Blum K, Braverman RE, et al. How to combat the global opioid crisis. CPQ Neurol Psychol. 2023;5:93.

 

  1. García-Blanco A, Domingo-Rodriguez L, Cabana- Domínguez J, et al., miRNA signatures associated with vulnerability to food addiction in mice and humans. J Clin Invest. 2022;132:e156281. doi: 10.1172/JCI156281

 

  1. Zhao Y, Qin F, Han S, et al. MicroRNAs in drug addiction: Current status and future perspectives. Pharmacol Ther. 2022;236:108215. doi: 10.1016/j.pharmthera.2022.108215

 

  1. Xia H, Akay YM, Akay M. Investigating miRNA-mRNA interactions and gene regulatory networks from VTA dopaminergic neurons following perinatal nicotine and alcohol exposure using bayesian network analysis. IEEE J Biomed Health Inform. 2022;26:3550-3555. doi: 10.1109/JBHI.2022.3158620

 

  1. Gelernter J. SLC6A4 polymorphism, population genetics, and psychiatric traits. Hum Genet. 2014;133:459-461. doi: 10.1007/s00439-013-1412-2

 

  1. Hughes EM, Thornton AM, Kerr DM, et al. Kappa opioid receptor-mediated modulation of social responding in adolescent rats and in rats prenatally exposed to valproic acid. Neuroscience. 2020;444:9-18. doi: 10.1016/j.neuroscience.2020.07.055

 

  1. Hughes EM, Calcagno P, Sanchez C, et al. Mu-opioid receptor agonism differentially alters social behaviour and immediate early gene expression in male adolescent rats prenatally exposed to valproic acid versus controls. Brain Res Bull. 2021;174:260-267. doi: 10.1016/j.brainresbull.2021.06.018

 

  1. Antón-Galindo E, Cabana-Domínguez J, Torrico B, Corominas R, Cormand B, Fernàndez-Castillo N. The pleiotropic contribution of genes in dopaminergic and serotonergic pathways to addiction and related behavioral traits. Front Psychiatry. 2023;14:1293663. doi: 10.3389/fpsyt.2023.1293663

 

  1. Kimbrel NA, Ashley-Koch AE, Qin XJ, et al. Identification of novel, replicable genetic risk loci for suicidal thoughts and behaviors among US military veterans. JAMA Psychiatry, 2023;80:135-145. doi: 10.1001/jamapsychiatry.2022.3896

 

  1. Fernandes AM, Campos J, Silva D, et al. Cerebral organoids to study central mechanisms of pain: The effect of stem cell secretome on opioid receptors and neuroplasticity. Stem Cells Dev. 2022;31:641-657. doi: 10.1089/scd.2022.0116

 

  1. Sabaie H, Khorami Rouz S, Kouchakali G, et al. Identification of potential regulatory long non-coding RNA-associated competing endogenous RNA axes in periplaque regions in multiple sclerosis. Front Genet. 2022;13:1011350. doi: 10.3389/fgene.2022.1011350

 

  1. Fan X, Chen H, Jiang F, et al. Comprehensive analysis of cuproptosis-related genes in immune infiltration in ischemic stroke. Front Neurol. 2023;13:1077178. doi: 10.3389/fneur.2022.1077178

 

  1. Yue T, Chen S, Zhu J, et al. The aging-related risk signature in colorectal cancer. Aging (Albany NY). 2021;13(5): 7330-7349. doi: 10.18632/aging.202589

 

Next article in this issue
Share
Back to top
Gene & Protein in Disease, Electronic ISSN: 2811-003X Published by AccScience Publishing
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here
Accept