- 1Department of Psychiatry and Behavioral Sciences, University of Miami, Miami, FL, United States
- 2Deparment of Psychiatry, Harvard University, Boston, MA, United States
- 3Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
- 4Department of Neuroscience, University of Texas Rio Grande Valley, Edinburg, TX, United States
Editorial on the Research Topic
Genome-wide molecular mechanisms of substance use disorders
Substance use disorders (SUDs) represent significant medical and socioeconomic problem. In the United States, while the opioid epidemic received heightened attention in recent years, the prevalence of other SUDs, particularly alcohol use disorder (AUD) and cannabis use disorder (CaUD), rises, reaching epidemic proportions as well (1). 14% of adults meet criteria for AUD and 29% met AUD criteria at least once during their lifetime (2). Prevalence of CaUD also increases, likely reflecting the legalization of marijuana across multiple states, and has reached 1.23% among adults (3). Current pharmacological options for AUD and CaUD are limited. AUD is typically treated with either naltrexone or acamprosate. These medications are moderately effective (4, 5), and relapse rates in AUD remain ~70–80% (6, 7). There are currently no FDA-approved medications for CaUD.
Lack of efficient treatment modalities often indicates insufficient insight into etiopathogenesis and molecular mechanisms of SUDs as well as anatomical regions and neuro-circuitries involved in the progression of these conditions. Although we begin to appreciate the complexity of addiction-induced global changes across brain regions, treatment strategies still revolve around single target (opioid receptors for naltrexone and NMDA receptors for acamprosate). The concept of the “silver bullet” has been generally accepted in likely most medical specialties, apparently emerging as a consequence of most successful treatments historically being developed for diseases with a clearly defined single pathogenetic mechanism (insulin for type 1 diabetes mellitus, imatinib for chronic myelogenous leukemia) and technical difficulties in targeting multiple pathways simultaneously. In the realm of internal medicine, this concept has nevertheless been successful also in the settings of multifactorial conditions, as evidenced by the utility of angiotensin-converting enzyme inhibitors or angiotensin receptor blockers for essential hypertension and statins for hyperlipidemia (even though treatment algorithms in these conditions continue to rely mainly on trial-and-error approach and many patients are resistant to first-line medicines (8)). Most mental health disorders are the result of complex interactions between numerous biological, environmental, and social determinants, likely far more complicated than in somatic diseases, and the concept of “silver bullet” has been particularly difficult to implement, and relapse rates in psychiatric diseases including SUDs are much higher than in non-psychiatric illnesses (9, 10).
It is currently clear that pathogenesis of addiction involves hundreds of genes and transcripts, with impairment of fundamental genome-wide molecular processes, but there are several important questions which have to be addressed. First, most studies are based on large sample sizes and therefore detect genes/transcripts commonly involved in SUDs, failing to identify rare variants responsible for pathogenesis in specific subpopulations which, in turn, hampers the development of personalized treatment approaches. Another obstacle is that investigations typically focus on one layer of informational flow (genome, transcriptome, or proteome) which provides limited insight into how the whole interactome is affected. As an example, genome-wide association studies have not been able to provide a comprehensive insight into etiopathogenesis of SUDs (11, 12), suggesting that more extensive studies of posttranscriptional mechanisms coupled with subsequent integration of genetic and epigenetic datasets as well as proteome and metabolome may be required.
The current Research Topic is an effort to further highlight the molecular complexity of addiction, using AUD and CaUD as examples. Study by Hill and Hostyk discerned new genetic loci associated with AUD in specific populations. Authors performed the analysis of multiplex families with AUD and detected a distinct, ultra-rare loss-of-function genes implicated in AUD, suggesting novel therapeutic targets specific for these patients. Another interesting AUD study was performed by Zhang et al.; while most investigations focus on genome and transcriptome, authors used liquid chromatography-mass spectrometry to profile serum metabolome in patients with AUD, identifying specific metabolomic profiles which may serve as biomarkers or/and represent pathogenetic links mediating systemic effects of AUD. Reece and Hulse (a, b) have embarked on a comprehensive assessment of dysregulation of interactome in the settings of CaUD, with an emphasis on epigenome, metabolome, immunome, and their interconnectedness. Of note, striking similarity was found between global molecular effects of cannabis and changes which accompany/mediate the process of aging.
These studies indicate that there are multiple knowledge gaps and that more work is needed to build the interactome in relevant brain regions and characterize its impairment in SUDs. Once addiction-related “patho-interactome” has been developed, new set of studies will be required to understand how it can be “repaired”. It is possible that such molecules as transcription factors and non-coding RNAs, being functionally pleiotropic (including their ability to interact simultaneously with proteins and RNAs), may potentially serve as “molecular corkscrews”. Their targeting may be achieved with either small molecules or nucleotide-based therapeutics. CRISPR-Cas9, for instance, offers a simple approach to make changes in genetic code. At mRNA levels, several tools for manipulation have been available for decades, with major technologies represented by small interfering RNAs (siRNAs), antisense oligonucleotides (ASOs), and morpholinos. Manipulation of genome and transcriptome on a genome-wide scale is getting increasingly feasible. Multiplexing editing of mammalian genome using CRISPR/Cas system was shown as early as in 2013 (13) and since then has been replicated multiple times (14). Multiplexing siRNAs and ASOs is more challenging because both technologies function only with support of enzymatic complexes, but morpholinos act via “steric blocking” and do not require intracellular machineries. Delivery of new medicines in the brain will represent another challenge. One potential approach is to use ultrasound-responsive nanoparticles which would release loaded medications in a specific brain region. In this regard, however, another layer of complexity should be taken into consideration. Gene expression profiles are highly dependent on the cellular lineage. For instance, transcriptomic effects of alcohol were distinctly different in astrocytes and microglia (15, 16). Delivery may therefore rather be executed based on cellular origin than anatomical site; in this case, exosomes loaded with therapeutics and expressing complementary epitope/protein (17) could represent one possible technology.
Author contributions
IB: Writing – original draft, Writing – review & editing. DM-G: Writing – review & editing. DP: Writing – review & editing. AD: Writing – review & editing. IS: Writing – review & editing.
Funding
The author(s) declare financial support was received for the research, authorship, and/or publication of this article. IB was supported by awards from the University of Miami and American Psychiatric Association. IS acknowledges support by USPHS Grants R0AA024933 and R01AA023540.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
References
1. Grant BF, Chou SP, Saha TD, Pickering RP, Kerridge BT, Ruan WJ, et al. Prevalence of 12-month alcohol use, high-risk drinking, and DSM-IV alcohol use disorder in the United States, 2001-2002 to 2012-2013: results from the national epidemiologic survey on alcohol and related conditions. JAMA Psychiatry. (2017) 74:911–23. doi: 10.1001/jamapsychiatry.2017.2161
2. Grant BF, Goldstein RB, Saha TD, Chou SP, Jung J, Zhang H, et al. Epidemiology of DSM-5 alcohol use disorder: results from the national epidemiologic survey on alcohol and related conditions III. JAMA Psychiatry. (2015) 72:757–66. doi: 10.1001/jamapsychiatry.2015.0584
3. Cerdá M, Mauro C, Hamilton A, Levy NS, Santaella-Tenorio J, Hasin D, et al. Association between recreational marijuana legalization in the United States and Changes in marijuana use and cannabis use disorder from 2008 to 2016. JAMA Psychiatry. (2020) 77:165–71. doi: 10.1001/jamapsychiatry.2019.3254
4. Kranzler HR, Soyka M. Diagnosis and pharmacotherapy of alcohol use disorder: a review. JAMA. (2018) 320:815–24. doi: 10.1001/jama.2018.11406
5. Mark TL, Kassed CA, Vandivort-Warren R, Levit KR, Kranzler HR. Alcohol and opioid dependence medications: prescription trends, overall and by physician specialty. Drug Alcohol Depend. (2009) 99:345–9. doi: 10.1016/j.drugalcdep.2008.07.018
6. Finney JW, Hahn AC, Moos RH. The effectiveness of inpatient and outpatient treatment for alcohol abuse: the need to focus on mediators and moderators of setting effects. Addiction. (1996) 91:1773–96. doi: 10.1111/j.1360-0443.1996.tb03801.x
7. Weiss RD, O'Malley S S, Hosking JD, Locastro JS, Swift R. Do patients with alcohol dependence respond to placebo? Results from the COMBINE study. J Stud Alcohol Drugs. (2008) 69:878–84. doi: 10.15288/jsad.2008.69.878
8. Acelajado MC, Hughes ZH, Oparil S, Calhoun DA. Treatment of resistant and refractory hypertension. Circ Res. (2019) 124:1061–70. doi: 10.1161/CIRCRESAHA.118.312156
9. Reinhold JA, Rickels K. Pharmacological treatment for generalized anxiety disorder in adults: an update. Expert Opin Pharmacother. (2015) 16:1669–81. doi: 10.1517/14656566.2015.1059424
10. Lally J, Gaughran F, Timms P, Curran SR. Treatment-resistant schizophrenia: current insights on the pharmacogenomics of antipsychotics. Pharmgenomics Pers Med. (2016) 9:117–29. doi: 10.2147/PGPM.S115741
11. Kranzler HR, Zhou H, Kember RL, Vickers Smith R, Justice AC, Damrauer S, et al. Genome-wide association study of alcohol consumption and use disorder in 274,424 individuals from multiple populations. Nat Commun. (2019) 10:1499. doi: 10.1038/s41467-019-11916-0
12. Palmer RH, McGeary JE, Heath AC, Keller MC, Brick LA, Knopik VS. Shared additive genetic influences on DSM-IV criteria for alcohol dependence in subjects of European ancestry. Addiction. (2015) 110:1922–31. doi: 10.1111/add.13070
13. Cong L, Ran FA, Cox D, Lin S, Barretto R, Habib N, et al. Multiplex genome engineering using CRISPR/Cas systems. Science. (2013) 339:819–23. doi: 10.1126/science.1231143
14. Adiego-Perez B, Randazzo P, Daran JM, Verwaal R, Roubos JA, Daran-Lapujade P, et al. Multiplex genome editing of microorganisms using CRISPR-Cas. FEMS Microbiol Lett. (2019) 366:fnz086. doi: 10.1093/femsle/fnz086
15. Erickson EK, Farris SP, Blednov YA, Mayfield RD, Harris RA. Astrocyte-specific transcriptome responses to chronic ethanol consumption. Pharmacogenomics J. (2018) 18:578–89. doi: 10.1038/s41397-017-0012-2
16. McCarthy GM, Farris SP, Blednov YA, Harris RA, Mayfield RD. Microglial-specific transcriptome changes following chronic alcohol consumption. Neuropharmacology. (2018) 128:416–24. doi: 10.1016/j.neuropharm.2017.10.035
Keywords: alcohol use disorder, cannabis use disorder, genome-wide association studies, interactome, small interfering RNA, CRISPR-Cas9
Citation: Blokhin IO, Martinez-Garza DM, Patel D, Douaihy AB and Salloum IM (2024) Editorial: Genome-wide molecular mechanisms of substance use disorders. Front. Psychiatry 14:1356103. doi: 10.3389/fpsyt.2023.1356103
Received: 15 December 2023; Accepted: 19 December 2023;
Published: 08 January 2024.
Edited and reviewed by: Ming D. Li, Zhejiang University, China
Copyright © 2024 Blokhin, Martinez-Garza, Patel, Douaihy and Salloum. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Ilya O. Blokhin, iob3@med.miami.edu