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      A Novel Precision Approach to Overcome the “Addiction Pandemic” by Incorporating Genetic Addiction Risk Severity (GARS) and Dopamine Homeostasis Restoration

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          Abstract

          This article describes a unique therapeutic precision intervention, a formulation of enkephalinase inhibitors, enkephalin, and dopamine-releasing neuronutrients, to induce dopamine homeostasis for detoxification and treatment of individuals genetically predisposed to developing reward deficiency syndrome (RDS). The formulations are based on the results of the addiction risk severity (GARS) test. Based on both neurogenetic and epigenetic evidence, the test evaluates the presence of reward genes and risk alleles. Existing evidence demonstrates that the novel genetic risk testing system can successfully stratify the potential for developing opioid use disorder (OUD) related risks or before initiating opioid analgesic therapy and RDS risk for people in recovery. In the case of opioid use disorders, long-term maintenance agonist treatments like methadone and buprenorphine may create RDS, or RDS may have been in existence, but not recognized. The test will also assess the potential for benefit from medication-assisted treatment with dopamine augmentation. RDS methodology holds a strong promise for reducing the burden of addictive disorders for individuals, their families, and society as a whole by guiding the restoration of dopamine homeostasisthrough anti-reward allostatic neuroadaptations. WC 175.

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          Identification of common genetic risk variants for autism spectrum disorder

          Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample-size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 individuals with ASD and 27,969 controls that identified five genome-wide-significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), we identified seven additional loci shared with other traits at equally strict significance levels. Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis, and establish that GWAS performed at scale will be much more productive in the near term in ASD.
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            A global overview of pleiotropy and genetic architecture in complex traits

            After a decade of genome-wide association studies (GWASs), fundamental questions in human genetics, such as the extent of pleiotropy across the genome and variation in genetic architecture across traits, are still unanswered. The current availability of hundreds of GWASs provides a unique opportunity to address these questions. We systematically analyzed 4,155 publicly available GWASs. For a subset of well-powered GWASs on 558 traits, we provide an extensive overview of pleiotropy and genetic architecture. We show that trait-associated loci cover more than half of the genome, and 90% of these overlap with loci from multiple traits. We find that potential causal variants are enriched in coding and flanking regions, as well as in regulatory elements, and show variation in polygenicity and discoverability of traits. Our results provide insights into how genetic variation contributes to trait variation. All GWAS results can be queried and visualized at the GWAS ATLAS resource ( https://atlas.ctglab.nl ).
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              Trans-ancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders

              Liability to alcohol dependence (AD) is heritable, but little is known about its complex polygenic architecture or its genetic relationship with other disorders. To discover loci associated with AD and characterize the relationship between AD and other psychiatric and behavioral outcomes, we carried out the largest GWAS to date of DSM-IV diagnosed AD. Genome-wide data on 14,904 individuals with AD and 37,944 controls from 28 case/control and family-based studies were meta-analyzed, stratified by genetic ancestry (European, N = 46,568; African; N = 6,280). Independent, genome-wide significant effects of different ADH1B variants were identified in European (rs1229984; p = 9.8E-13) and African ancestries (rs2066702; p = 2.2E-9). Significant genetic correlations were observed with 17 phenotypes, including schizophrenia, ADHD, depression, and use of cigarettes and cannabis. The genetic underpinnings of AD only partially overlap with those for alcohol consumption, underscoring the genetic distinction between pathological and non-pathological drinking behaviors.
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                Author and article information

                Contributors
                Role: Academic Editor
                Role: Academic Editor
                Journal
                J Pers Med
                J Pers Med
                jpm
                Journal of Personalized Medicine
                MDPI
                2075-4426
                16 March 2021
                March 2021
                : 11
                : 3
                : 212
                Affiliations
                [1 ]College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766, USA; shan.kazmi@ 123456westernu.edu (S.K.); dbaron@ 123456westernu.edu (D.B.)
                [2 ]Institute of Psychology, ELTE Eötvös Loránd University, 1117 Budapest, Hungary
                [3 ]Division of Nutrigenomics, The Kenneth Blum Behavioral Neurogenetic Institute, Austin, TX 78712, USA; tmclaugh50@ 123456gmail.com (T.M.); rickgreen@ 123456newresourcesmedicalarts.com (R.G.); rjalai@ 123456ivitalize.com (R.J.)
                [4 ]Department of Psychiatry, University of Vermont, Burlington, VT 05405, USA
                [5 ]Department of Psychiatry, Wright University Boonshoff School of Medicine, Dayton, OH 45435, USA
                [6 ]Division of Precision Nutrition, Victory Nutrition International, Lederach, PA 19450, USA; billd@ 123456vni.life (B.W.D.); debasisbagchi@ 123456gmail.com (D.B.)
                [7 ]Center for Genomic Testing, Geneus Health LLC, San Antonio, TX 78249, USA
                [8 ]Department of Psychology, Curry College, Milton, MA 02186, USA; edward.modestino@ 123456gmail.com
                [9 ]Department of Pharmaceutical Sciences, College of Pharmacy & Health Sciences, Texas Southern University, Houston, TX 77004, USA
                [10 ]Precision Translational Medicine (Division of Ivitalize), San Antonio, TX 78249, USA
                [11 ]Department of Psychology & Behavioral Neuropharmacology and Neuroimaging Laboratory on Addictions (BNNLA), Research Institute on Addictions, University at Buffalo, Buffalo, NY 14260, USA; pkthanos@ 123456gmail.com
                [12 ]Department of Psychiatry, Harvard University, School of Medicine, Cambridge, MA 02142, USA; dr.igorelman@ 123456gmail.com
                [13 ]Department of Psychiatry, South Texas Veteran Health Care System, Audie L. Murphy Memorial VA Hospital and Long School of Medicine, University of Texas Health Science Center, San Antonio, TX 78249, USA; badgaiyan@ 123456gmail.com
                [14 ]Department of Psychiatry, MT. Sinai School of Medicine, New York, NY 10003, USA
                [15 ]Department of Molecular Biology and Adelson School of Medicine, Ariel University, Ariel 40700, Israel; bowirrat@ 123456gmail.com
                [16 ]Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA; drmarkgold@ 123456gmail.com
                Author notes
                [* ]Correspondence: drd2gene@ 123456gmail.com ; Tel.: +1-619p-890-2167
                Author information
                https://orcid.org/0000-0001-6727-803X
                https://orcid.org/0000-0001-7611-5144
                https://orcid.org/0000-0001-5586-5114
                Article
                jpm-11-00212
                10.3390/jpm11030212
                8002215
                33809702
                4b3c60d2-6333-4824-83fc-d477f6094d44
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 07 January 2021
                : 11 March 2021
                Categories
                Review

                enkephalinase-inhibition,hypodopaminergia,reward deficiency syndrome (rds),dopamine homeostasis,pro-dopamine regulation,genetic addiction risk system (gars)

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