Next Article in Journal
Understanding Parents’ Experiences with Children with Type 1 Diabetes: A Qualitative Inquiry
Next Article in Special Issue
Effects of Δ9-Tetrahydrocannibinol (THC) on Obesity at Different Stages of Life: A Literature Review
Previous Article in Journal
Environmental Regulation Intensity, Carbon Footprint and Green Total Factor Productivity of Manufacturing Industries
Previous Article in Special Issue
Illegal Drug Use and Risk of Hearing Loss in the United States: A National Health and Nutrition Examination Survey
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Perspective

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

1
Future Biologics, Lawrenceville, GA 30043, USA
2
Department of Molecular Biology, Adelson School of Medicine, Ariel University, Ariel 40700, Israel
3
The Kenneth Blum Behavioral & Neurogenetic Institute, Austin, TX 78701, USA
4
Graduate College, Western University Health Sciences, Pomona, CA 91766, USA
5
Center for Pain and the Brain (P.A.I.N Group), Department of Anesthesiology, Critical Care & Pain Medicine, Boston Children’s Hospital, Boston, MA 02115, USA
6
Cambridge Health Alliance, Harvard Medical School, Cambridge, MA 02139, USA
7
South Beach Detox & Treatment Center, North Miami Beach, FL 33169, USA
8
Department of Precision Behavioral Management, Geneus Health, San Antonio, TX 78249, USA
9
Department of Psychiatry, South Texas Veteran Health Care System, Audie L. Murphy Memorial VA Hospital, Long School of Medicine, University of Texas Medical Center, San Antonio, TX 78229, USA
10
Department of Psychology, Curry College, Milton, MA 02186, USA
11
Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
12
Bajaj Chiropractic, New York, NY 10010, USA
13
Institute of Psychology, ELTE Eötvös Loránd University, Egyetem tér 1-3, 1053 Budapest, Hungary
14
Department of Psychiatry, School of Medicine, University of Vermont, Burlington, VT 05405, USA
15
Centre for Genomics and Applied Gene Technology, Institute of Integrative Omics and Applied Biotechnology, Nonakuri, Purba Medinipur 721172, West Bengal, India
16
Department of Psychiatry, Wright State University Boonshoft School of Medicine and Dayton VA Medical Centre, Dayton, OH 45324, USA
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2022, 19(1), 552; https://doi.org/10.3390/ijerph19010552
Submission received: 16 November 2021 / Revised: 16 December 2021 / Accepted: 31 December 2021 / Published: 4 January 2022
(This article belongs to the Special Issue Addiction: A Public Health Global Pandemic)

Abstract

:
In the United States, amid the opioid overdose epidemic, nonaddicting/nonpharmacological proven strategies are available to treat pain and manage chronic pain effectively without opioids. Evidence supporting the long-term use of opioids for pain is lacking, as is the will to alter the drug-embracing culture in American chronic pain management. Some pain clinicians seem to prefer classical analgesic agents that promote unwanted tolerance to analgesics and subsequent biological induction of the “addictive brain”. Reward genes play a vital part in modulation of nociception and adaptations in the dopaminergic circuitry. They may affect various sensory and affective components of the chronic pain syndromes. The Genetic Addiction Risk Severity (GARS) test coupled with the H-Wave at entry in pain clinics could attenuate pain and help prevent addiction. The GARS test results identify high-risk for both drug and alcohol, and H-Wave can be initiated to treat pain instead of opioids. The utilization of H-Wave to aid in pain reduction and mitigation of hedonic addictive behaviors is recommended, notwithstanding required randomized control studies. This frontline approach would reduce the possibility of long-term neurobiological deficits and fatalities associated with potent opioid analgesics.

1. Introduction

1.1. The Purpose

In the United States, amid the opioid overdose epidemic, nonaddicting/nonpharmacological proven strategies are available to treat pain and manage chronic pain effectively without opioids. Evidence supporting the long-term use of opioids for pain is lacking, as is the will to alter the drug-embracing culture in American chronic pain management. Some pain clinicians seem to prefer classical analgesic agents that promote unwanted tolerance to analgesics and subsequent biological induction of the “addictive brain”. Reward genes play a vital part in modulation of nociception and adaptations in the dopaminergic circuitry. The purpose of this hypothesis article argues for the novel idea that in the face of the opioid crisis, Genetic Addiction Risk Severity (GARS) testing with electrotherapeutic nonopioid modalities such as H-Wave could attenuate both pain and hedonic addictive behavior overdoses.

1.2. The Opioid Crisis

Noncancerous pain treatment is challenging for primary care medicine. The USA has faced an iatrogenically induced opiate/opioid epidemic that has killed thousands, with as many as 130 dying daily from a narcotic overdose [1,2]. While some argue that big pharma was not the culprit, we fervently disagree with this retort. The driver in the surge in drug overdose mortality rates has been the greater use of prescription opioid analgesics. Unintentional drug overdose deaths increased in 2007 to one every 19 min. Although initially more overdose deaths involved opioid analgesics than heroin and cocaine combined [3,4], the current accessibility of inexpensive street opiates has increased dependence on heroin [5,6,7]. A National Institute of Health (NIH) survey estimated that by 2014, 25.3 million adults suffered with pain every day for the previous three months. In 2016–2017, several thousand people died from opioid/opiate overdose, particularly with the synthetic opioid fentanyl. Fentanyl is 50 times more potent than prescription opioids. In 2016, to mitigate this rising threat to public safety, new guidelines for prescribing opioids to patients suffering with chronic pain were released by the Center for Disease Control (CDC). In 2017, morphine milligram equivalents dropped by 29%, although more than 64,000 people still succumbed to narcotics overdose, resulting in a reduction in the national life expectancy. According to the National Institute on Drug Abuse (NIDA), about 116 million Americans suffer from chronic pain currently. People who suffer from chronic pain are also more prone to having worse overall mental and physical health conditions. Owing to the contribution of big pharmaceutical industries in promoting opioid usage and subsequent addiction, the estimate is that personally, the David Sackler family will pay USD 8.3 billion in fines over ten years without any criminal charges. In 2021, the CDC estimates that 91,000 people died from opioid-related overdoses.

1.3. Pain Estimates

Once every 14 min, 150 million people suffer from pain conditions. About 300 million narcotic prescriptions are filled per year with costs in USD in the hundreds of billions. Some of these people die from a prescription overdose. Pain experts intend to offer needed help to pain patients. It is recognized that consumption of powerful narcotics to alleviate pain can cause high tolerance and severe withdrawal symptoms in a fairly short duration [8]. A current site that describes the impact of chronic pain in the USA can be found at https://www.cdc.gov/mmwr/volumes/67/wr/mm6736a2.htm, accessed on 31 December 2021. “Reward Deficiency Syndrome” (RDS) [9] is a genetically based hypodopaminergia known to affect about one-third of people in the United States [10]. It is understood that while a few people can tolerate powerful narcotics, and no longer want opioids after being treated for pain even after withdrawal, others, because of genetic and epigenetic insults, become enthralled with addictive-like behaviors after the pain is alleviated [11]. It is noteworthy that our group recently reported on a study utilizing the Genetic Addiction Risk Severity (GARS) test showing a high drug and alcohol risk in probands attending multipain clinics chronically prescribed opioids. In chronic pain conditions, their continued requirement for powerful narcotics may depend upon the genetic antecedents [12].

1.4. Why GARS

The double-edged sword for pain experts, on one hand, is that their patients may be dishonest about their actual pain level or sensitivity owing to being stuck within the “addictive process”, perhaps associated with polymorphisms of their genes associated with the reward circuitry. In contrast, patients need potent narcotics to circumvent disruptive pain-related symptoms. The problem is to establish a way to distinguish between these two types of patients at beginning of their treatment. Genetic testing may provide the solution to this problem. Though this sounds simple, and we will describe the concept in more detail, we must contemplate that our DNA may predispose to addictive-like behaviors, the environment, or particularly epigenetic processes impacting expression of genes [13]. Currently, there are at least 48 reviews and original studies on GARS, per a PubMed search conducted on 12 December 2021. Unfortunately, these articles are primarily from our group, however, we encourage others to independently confirm these early studies [9].
Nevertheless, in today’s world, with numerous people dying from legal and illegal narcotics, state laws, government organizations, and “big pharma” make it very difficult to continue treating chronic pain victims during this opioid crisis [14]. It is likely that knowing a patient’s GARS result can help provide better care by offering an in-depth view of a patient’s addiction risk and eliminating presumptions related to becoming addicted.
It is rather strange to criticize the pain expert for assisting relieve pain, and in doing so, for being accountable for the unwitting individual’s so-called “bad” behavior. In addition to this dilemma of pain experts treating patients with both acute and chronic pain, this perspective article will try to shed light on evidence-based genetic guidance to help the pain experts to circumvent guessing with “Precision Addiction Management”. Therefore, after required randomized control (RCT) studies, the hypothesis is that to help those patients who show addiction liability/vulnerability, as measured by the GARS test, pain reduction utilizing H-wave therapy without addicting analgesics will be a laudable goal.

1.5. The Case for Electrotherapy for Pain

Iatrogenic prescription drug abuse is the swiftest rising drug problem in the United States. The two main populations in the US at risk for prescription drug overdose are roughly the 9 million people who report long-term medical opioid use and around 5 million people who report nonmedical use. The 20% of patients prescribed high daily doses and receiving care from several physicians account for nearly 80% of overdoses and are more prone to give drugs to others who consume them without prescription [15].
Additionally, the main pain pathways that arise from the dorsal horn of the spinal cord to the medulla, and numerous genes and their polymorphisms that inhabit the mesolimbic reward center of the brain have a function in the control of pain sensitivity and tolerance [16,17,18].
Identifying the reward genes and their polymorphisms may provide distinctive therapeutic targets for non-narcotic pharmacogenomic solutions to cure pain. The GARS test [19] can recognize patients with a susceptibility to addiction in the initial stages of treatment; for example, reward genes’ alleles such as DRD2 A1 and the G allele of the Mu Opioid Receptor are associated with a risk for narcotic addiction. These are the patients who will require a nonaddictive alternative pain treatment. The electrotherapeutic H-Wave® device (Electronic Waveform Lab Inc., Huntington Beach, CA, USA) is one such alternative [20].

1.6. The Characteristics of H-Wave Electrotherapy

The physiological mechanisms of action of the H-Wave device stimulation (HWDS) examined in animals reduced edema owing to the stimulation of smooth muscle fibers within the lymphatic vessels [21]. Additionally, using HWDS aids tissue healing by the induction of nitric oxide (NO)-dependent microcirculation augmentation and angiogenesis [22].
The characteristics of HWDS include:
  • Contraction of smooth and skeletal muscle (red, slow-twitch) fibers through low-frequency (1–2 Hz) stimulation results in tissue loading whilst maintaining the low muscle force tension characteristics, thus being nontetanizing and nonfatiguing;
  • Arteriolar vasodilation associated with HWDS is attributed to a NO mechanism, as shown in rat studies;
  • Increased angiogenesis demonstrated via bromouridine staining in repetitive stimulation in rats;
  • HWDS specifically and directly stimulates the smooth muscle fibers within the lymphatic vessels, finally resulting in fluid shifts and decreasing edema and protein clearance.
There is a necessity for nonpharmacological substitutes to treat pain during the opioid crisis. The published peer-reviewed literature related to the positive effects of H-Wave includes a total of over 18 publications. These original articles, reviews, and abstracts illustrate an important, evidence-based series demonstrating noteworthy pain relief and mechanisms of action [19,20,21,22,23,24,25,26,27,28,29]. Additional studies show a vital role for electrotherapy for pain [29,30,31].
Markedly, in the face of our most awful drug crisis, with many lives lost daily, the whole pain community should adopt an alternative to potent pain medications.

1.7. Potential Mechanism of H-Wave Therapy

During the last two decades, researchers have been progressively interested in controlling pain and restoring function via electrical stimulation. One of the focus areas is use of H-Wave device [32].
  • The purpose of the HWDS is to reduce chronic pain and inflammation. Four mechanisms achieve this aim: first, through interstitial fluid shifts produced at very low frequencies (1–2 Hz) by direct stimulation of small-diameter skeletal muscle fibers and smooth muscles of the lymphatic system. HWDS causes long rhythmical contractions of these specific muscle types, reducing the accumulation of proteins associated with inflammation, an important component of pain, and related disability in trauma or chronic injury patients [29,33];
  • Second, the H-Wave device also produces profound anesthetic/analgesic effects when used at high frequencies (60 Hz) by affecting the function of the sodium pump within the nerve [34];
  • Third, animal research has demonstrated that skeletal muscle stimulation by the H-Wave device leads to a significant increase in microcirculation, which was NO-dependent [22,35].
  • Fourth, repetitive HWDS to rat hind limbs produced a profound and swift increase in blood flow as a function of observed angiogenesis [23,28,36,37]. These factors obviate the likelihood that the repetitive HWDS decreases inflammation and supports faster healing and improved recovery due to reducing protein buildup in postoperative conditions such as rotator cuff reconstruction.
Blum et al. published a meta-analysis where they systematically reviewed the efficacy and safety of the HWDS as a nonpharmacological analgesic treatment in chronic soft tissue inflammation and neuropathic pain. The analysis included five studies related to pain relief, pain medication reduction, and increased function achieved with the H-Wave device. Data were analyzed using the random-effects model, including adjustment to evaluate variability, study size, and bias in effect size [21]. The meta-analysis used data from a total of 6535 participants [21,38,39,40]. In this specific meta-analysis, though the findings indicate a moderate-to-strong effect of the H-Wave device in providing pain relief, a reduced necessity for pain medication, and enhanced function, we suggest additional studies. The most robust effect was observed for increased function, suggesting that the H-Wave device may help a faster return to work and other related daily activities [41].

1.8. Rationale for Pain Reduction

Pain may be undertreated, contributing to agony, as stated by the World Health Organization (WHO). Pain may also be overtreated, unintentionally leading to drug addiction, drug diversion, and even death. Thus, “primum non-nocerefirst, do no harm”—is not easily attained, in the pharmacological pain treatment, especially in chronic pain. In 2008, Henn et al. [42] reported in a prospective study involving 125 patients with Workers’ Compensation claims worse outcomes, even after controlling for confounding factors including, age, work demands, lower marital rates, education levels, preoperative expectations, compared to non-Workers’ Compensation patients. This study by Henn et al. delivers proof that the presence of a Workers’ Compensation claim portends a less robust outcome following a rotator cuff repair and stimulated interest in assessing HWDS to improve outcomes.
Additionally, according to Kasten et al. [43], even with today’s ultra- technical elegance, shoulder surgery can cause significant pain. Data from randomized controlled trials (RCTs) resulted in recommendations for local or regional anesthesia for analgesia during and after surgery of the upper extremity. This treatment entails potent addictive opioids and nonsteroidal anti-inflammatory drugs (NSAIDs) in a multimodal analgesia method. Moreover, according to a meta-analysis of RCTs, since the pain is profound, an interscalene nerve block is suggested for analgesia during and after surgery of the shoulder. Other recommendations include physiotherapy postoperatively. Interestingly, while the use of arthroscopic procedures for most knee conditions lead to comparatively mild and controlled pain, it is known that arthroscopic procedures for rotator cuff repair and reconstruction can lead to more significant pain for the patient’s undergoing recovery, and thus remains a greater challenge.
The introduction of pain pumps at first was met with enthusiasm by several shoulder surgeons but has resulted in serious complications involving chondrolysis. Various studies utilizing bovine and rabbit cartilage suggested that there is significant chondrotoxicity from bupivacaine, a local anesthetic frequently used in pain pumps [44].

1.9. Linking GARS Testing to Medical Necessity for Nonaddicting H-Wave Therapy

Millions of Americans suffer through pain daily. In 2017, opioid overdose took 64,000 lives, increasing to 84,000 lives in 2020 and 91,000 in 2021, resulting in decreased national life expectancy. Long-term opioid usage results in dependency, drug tolerance, neuroadaptation, hyperalgesia, potential addictive behaviors, or RDS caused by hypodopaminergia [45]. Table 1 displays the genes and associated risk alleles measured in the GARS test.
Evaluation of pain patients with the GARS test and the Addiction Severity Index (ASI-Media Version V) showed that GARS scores equal to or greater than 4 and 7 alleles considerably predicted drug and alcohol severity, respectively [41]. In a recent study by Moran et al. [12], we used RT-PCR for SNP genotyping and multiplex PCR/capillary electrophoresis for fragment analysis of the role of 11 alleles in a 10 reward-gene panel, displaying the activity of brain reward circuitry in 121 chronic opioid users. The study comprised 55 males and 66 females, with an average age of 54 and 53 years, respectively. The patients included Caucasians, African Americans, Hispanics, and Asians. Inclusion criteria required that the Morphine Milligram Equivalent (MME) was 30–600 mg/day for males and 20–180 mg/day for females, for treatment of chronic pain over 12 months. In total, 96% carried four or more risk alleles, and 73% carried seven or more risk alleles, implying a high predictive risk for opioid and alcohol dependence, respectively. These data suggested that chronic, licit prescribed opioid users going to a pain clinic possess a high genetic risk for drug and alcohol addiction. Early recognition of genetic risk, using the GARS testing upon entry to treatment, might prevent iatrogenic induced opioid dependence. Upon entry to pain clinic, a score of above four risk alleles may provide clinicians with the medical necessity to prescribe H-Wave instead of potent addictive analgesics. Utilization of this novel approach has the clinical potential to reduce iatrogenically induced subsequent addiction liability, especially in patients characterized as high risk for all addictive or reward-deficiency addictive behaviors, both drug and nondrug [46]. Figure 1 is a schematic of the proposed alternative treatment of pain.
While it is true that the major body of the RDS concept resides in many publications on the subject from our laboratory, there is an emerging increase in independent citations that embrace this novel construct. A brief sampling of this global cited work, while mostly favorable, can be assessed by reviewing specific references [47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111].

2. Conclusions

It is important to realize that vulnerability to drug and even nondrug addictive behaviors may reside in both genetic and epigenetic antecedents and impacts, respectively. In many important definitions of addiction, the genetic role is highlighted in relation to other factors, such as the environment, life experiences, the psychology of the individual. There are a number of examples revealing that people with addiction use substances or engage in behaviors that become compulsive and often continue despite harmful consequences [https://www.asam.org/QualityScience/definition-of-addiction; https://www.apa.org/topics/substanceuse-abuse-addiction, accessed on 31 December 2021]. Of cause, there also exists the issue related to the neurobiology of spirituality and environmental epigenetic insults as well [47,48,49]. The authors are proposing a paradigm shift, whereby at entry in pain clinics, the potential coupling of the GARS test with H-Wave modality could attenuate both pain and addiction. However, while there is indeed a scientific foundation related to the efficacy and rationale to utilize H-Wave, there is a continual need to research this important DNA-guided combination approach to reduce unnecessary utilization of long-term treatment with opioids, especially in high-risk, genetically vulnerable populations. Precision addiction management uses GARS test results to treat RDS in these genetically vulnerable populations. This frontline approach will also potentially temper the possibility of long-term issues and possible fatalities associated with addictive opioid analgesics. This dual-modality, H-Wave, and GARS testing, if adopted to help treat pain and RDS, could indeed reduce iatrogenic opioid-induced fatalities.

Author Contributions

Conceptualization, K.B. and A.G.; writing—original draft preparation, K.B.; writing—review and editing, A.G., A.B. (Abdalla Bowirrat), L.L.G., D.B., I.E., J.G., R.J., R.D.B., E.J.M., M.S.G., E.R.B., A.B. (Anish Bajaj) and K.B. All authors have read and agreed to the published version of the manuscript.

Funding

The primary funder of this perspective is Electronic Waveform Lab Inc., Huntington Beach, CA, USA. RDB is the recipient of NIH R01NS073884.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

The authors appreciate the expert edits of Margaret A. Madigan.

Conflicts of Interest

A.G. is a consultant for Electronic Waveform Lab Inc. K.B. holds US and foreign patients for KB220 and GARS. Some of these patients have been licensed to Ivitalize Inc. and K.B. has assigned his H-Wave patient to Electronic Waveform Lab Inc. The other authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

References

  1. Bell, J.; Strang, J. Medication Treatment of Opioid Use Disorder. Biol. Psychiatry 2020, 87, 82–88. [Google Scholar] [CrossRef]
  2. Beauchamp, G.A.; Nelson, L.S.; Perrone, J.; Lyons, M.S. A theoretical framework and nomenclature to characterize the iatrogenic contribution of therapeutic opioid exposure to opioid induced hyperalgesia, physical dependence, and opioid use disorder. Am. J. Drug Alcohol Abus. 2020, 46, 671–683. [Google Scholar] [CrossRef]
  3. Han, B.H.; Tuazon, E.; Kunins, H.V.; Mantha, S.; Paone, D. Unintentional drug overdose deaths involving cocaine among middle-aged and older adults in New York City. Drug Alcohol Depend. 2019, 198, 121–125. [Google Scholar] [CrossRef]
  4. Boyd, S. Heroin and the illegal drug overdose death epidemic: A history of missed opportunities and resistance. Int. J. Drug Policy 2021, 91, 102938. [Google Scholar] [CrossRef]
  5. Dydyk, A.M.; Jain, N.K.; Gupta, M. Opioid Use Disorder. In StatPearls; StatPearls Publishing: Treasure Island, FL, USA, 2021. [Google Scholar]
  6. Kuo, Y.F.; Baillargeon, J.; Raji, M.A. Overdose deaths from nonprescribed prescription opioids, heroin, and other synthetic opioids in Medicare beneficiaries. J. Subst. Abus. Treat. 2021, 124, 108282. [Google Scholar] [CrossRef]
  7. Wu, Z.H.; Yong, Q.; Walker, J.M.; Grady, J.J.; Laurencin, C.T. Fentanyl, Heroin, and Cocaine Overdose Fatalities are Shifting to the Black Community: An Analysis of the State of Connecticut. J. Racial Ethn. Health Disparities 2021. [Google Scholar] [CrossRef]
  8. Dumas, E.O.; Pollack, G.M. Opioid tolerance development: A pharmacokinetic/pharmacodynamic perspective. AAPS J. 2008, 10, 537–551. [Google Scholar] [CrossRef] [Green Version]
  9. Blum, K.; Kazmi, S.; Modestino, E.J.; Downs, B.W.; Bagchi, D.; Baron, D.; McLaughlin, T.; Green, R.; Jalali, R.; Thanos, P.K.; et al. A Novel Precision Approach to Overcome the “Addiction Pandemic” by Incorporating Genetic Addiction Risk Severity (GARS) and Dopamine Homeostasis Restoration. J. Pers. Med. 2021, 11, 212. [Google Scholar] [CrossRef]
  10. Blum, K.; Raza, A.; Schultz, T.; Jalali, R.; Green, R.; Brewer, R.; Thanos, P.K.; McLaughlin, T.; Baron, D.; Bowirrat, A.; et al. Should We Embrace the Incorporation of Genetically Guided “Dopamine Homeostasis” in the Treatment of Reward Deficiency Syndrome (RSD) as a Frontline Therapeutic Modality? Acta Sci. Neurol. 2021, 4, 17–24. [Google Scholar]
  11. Freda, P.J.; Moore, J.H.; Kranzler, H.R. The phenomics and genetics of addictive and affective comorbidity in opioid use disorder. Drug Alcohol Depend. 2021, 221, 108602. [Google Scholar] [CrossRef]
  12. Moran, M.; Blum, K.; Ponce, J.V.; Lott, L.; Gondré-Lewis, M.C.; Badgaiyan, S.; Brewer, R.; Downs, B.W.; Fynman, P.; Weingarten, A.; 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. [Google Scholar] [CrossRef]
  13. Ammon-Treiber, S.; Höllt, V. Morphine-induced changes of gene expression in the brain. Addict. Biol. 2005, 10, 81–89. [Google Scholar] [CrossRef]
  14. Lister, B.J. Dilemmas in the treatment of chronic pain. Am. J. Med. 1996, 101, 2S–5S. [Google Scholar] [CrossRef]
  15. Rice, J.B.; White, A.G.; Birnbaum, H.G.; Schiller, M.; Brown, D.A.; Roland, C. A model to identify patients at risk for prescription opioid abuse, dependence, and misuse. Pain Med. 2012, 13, 1162–1173. [Google Scholar] [CrossRef] [Green Version]
  16. Chen, A.L.; Chen, T.J.; Waite, R.L.; Reinking, J.; Tung, H.L.; Rhoades, P.; Downs, B.W.; Braverman, E.; Braverman, D.; Kerner, M.; et al. Hypothesizing that brain reward circuitry genes are genetic antecedents of pain sensitivity and critical diagnostic and pharmacogenomic treatment targets for chronic pain conditions. Med. Hypotheses 2009, 72, 14–22. [Google Scholar] [CrossRef] [Green Version]
  17. Blum, K.; Chen, A.L.C.; Thanos, P.K.; Febo, M.; Demetrovics, Z.; Dushaj, K.; Kovoor, A.; Baron, D.; Smith, D.E.; Roy, A.K., III; et al. Genetic addiction risk score (GARS) ™, a predictor of vulnerability to opioid dependence. Front. Biosci. 2018, 10, 175–196. [Google Scholar] [CrossRef] [Green Version]
  18. Kwok, C.H.; Trang, T. Pain: From genes and proteins to cells in the living organism. J. Neurosci. Res. 2017, 95, 1239–1241. [Google Scholar] [CrossRef]
  19. Blum, K.; Bowirrat, A.; Baron, D.; Lott, L.; Ponce, J.V.; Brewer, R.; Siwicki, D.; Boyett, B.; Gondre-Lewis, M.C.; Smith, D.E.; 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. [Google Scholar] [CrossRef]
  20. Williamson, T.K.; Rodriguez, H.C.; Gonzaba, A.; Poddar, N.; Norwood, S.M.; Gupta, A. H-Wave® Device Stimulation: A Critical Review. J. Pers. Med. 2021, 11, 1134. [Google Scholar] [CrossRef]
  21. Blum, K.; Chen, A.L.; Chen, T.J.; Prihoda, T.J.; Schoolfield, J.; DiNubile, N.; Waite, R.L.; Arcuri, V.; Kerner, M.; Braverman, E.R.; et al. The H-Wave device is an effective and safe non-pharmacological analgesic for chronic pain: A meta-analysis. Adv. Ther. 2008, 25, 644–657. [Google Scholar] [CrossRef]
  22. Blum, K.; Ho, C.K.; Chen, A.L.; Fulton, M.; Fulton, B.; Westcott, W.L.; Reinl, G.; Braverman, E.R.; Dinubile, N.; Chen, T.J. The H-Wave((R)) Device Induces NODependent Augmented Microcirculation and Angiogenesis, Providing Both Analgesia and Tissue Healing in Sports Injuries. Physician Sportsmed. 2008, 36, 103–114. [Google Scholar] [CrossRef]
  23. Smith, T.L.; Callahan, M.F.; Blum, K.; Dinubile, N.A.; Chen, T.J.; Waite, R.L. H-Wave® effects on blood flow and angiogenesis in longitudinal studies in rats. J. Surg. Orthop. Adv. 2011, 20, 255–259. [Google Scholar]
  24. Blum, K.; Chen, A.L.; Chen, T.J.; Waite, R.L.; Downs, B.W.; Braverman, E.R.; Kerner, M.M.; Savarimuthu, S.M.; DiNubile, N. Repetitive H-wave device stimulation and program induces significant increases in the range of motion of post operative rotator cuff reconstruction in a double-blinded randomized placebo controlled human study. BMC Musculoskelet. Disord. 2009, 10, 132. [Google Scholar] [CrossRef] [Green Version]
  25. Blum, K.; DiNubile, N.A.; Tekten, T.; Chen, T.J.; Waite, R.L.; Schoolfield, J.; Martinez-Pons, M.; Callahan, M.F.; Smith, T.L.; Mengucci, J.; et al. H-Wave, a nonpharmacologic alternative for the treatment of patients with chronic soft tissue inflammation and neuropathic pain: A preliminary statistical outcome study. Adv. Ther. 2006, 23, 446–455. [Google Scholar] [CrossRef]
  26. Blum, K.; Chen, T.J.; Martinez-Pons, M.; Dinubile, N.A.; Waite, R.L.; Schoolfield, J.; Blum, S.H.; Mengucci, J.; Downs, B.W.; Meshkin, B. The H-Wave small muscle fiber stimulator, a nonpharmacologic alternative for the treatment of chronic soft-tissue injury and neuropathic pain: An extended population observational study. Adv. Ther. 2006, 23, 739–749. [Google Scholar] [CrossRef]
  27. Blum, K.; Chen, A.L.; Chen, T.J.; Downs, B.W.; Braverman, E.R.; Kerner, M.; Savarimuthu, S.; Bajaj, A.; Madigan, M.; Blum, S.H.; et al. Healing enhancement of chronic venous stasis ulcers utilizing H-WAVE(R) device therapy: A case series. Cases J. 2010, 3, 54. [Google Scholar] [CrossRef] [Green Version]
  28. Smith, T.L.; Blum, K.; Callahan, M.F.; DiNubile, N.A.; Chen, T.J.; Waite, R.L. H-Wave induces arteriolar vasodilation in rat striated muscle via nitric oxide-mediated mechanisms. J. Orthop Res. 2009, 27, 1248–1251. [Google Scholar] [CrossRef]
  29. Blum, K.; Chen, T.J.; Ross, B.D. Innate properties of H-Wave device, a small fiber stimulator provides the basis for a paradigm shift of electro-therapeutic treatment of pain with increased functional restoration associated with human neuropathies by affecting tissue circulation: A hypothesis. Med. Hypotheses 2005, 64, 1066–1067. [Google Scholar] [CrossRef]
  30. Corriveau, M.; Lake, W.; Hanna, A. Nerve Stimulation for Pain. Neurosurg. Clin. N. Am. 2019, 30, 257–264. [Google Scholar] [CrossRef]
  31. Kim, B.; Lohman, E.; Yim, J. Acupuncture-like Transcutaneous Electrical Nerve Stimulation for Pain, Function, and Biochemical Inflammation After Total Knee Arthroplasty. Altern. Ther. Health Med. 2021, 27, 28–34. [Google Scholar]
  32. Kessler, T.M.; Mordasini, L.; Weisstanner, C.; Jüni, P.; da Costa, B.R.; Wiest, R.; Thalmann, G.N. Sono-electro-magnetic therapy for treating chronic pelvic pain syndrome in men: A randomized, placebo-controlled, double-blind trial. PLoS ONE 2014, 9, e113368. [Google Scholar] [CrossRef] [Green Version]
  33. Fass, A.; Van Eiijk, J.T.M.; Chavannes, A.W.; Gubbels, J.W. A randomized trial of exercise therapy in patients with acute low back pain: Efficacy on sickness absence. Spine 1995, 20, 941–947. [Google Scholar] [CrossRef]
  34. Misawa, S.; Sakurai, K.; Shibuya, K.; Isose, S.; Kanai, K.; Ogino, J.; Ishikawa, K.; Kuwabara, S. Neuropathic pain is associated with increased nodal persistent Na(+) currents in human diabetic neuropathy. J. Peripher. Nerv. Syst. 2009, 14, 279–284. [Google Scholar] [CrossRef]
  35. Lorenz, I.H.; Kolbitsch, C.; Hinteregger, M.; Bauer, P.; Spiegel, M.; Luger, T.J.; Schmidauer, C.; Streif, W.; Pfeiffer, K.P.; Benzer, A. Remifentanil and nitrous oxide reduce changes in cerebral blood flow velocity in the middle cerebral artery caused by pain. Br. J. Anaesth. 2003, 90, 296–299. [Google Scholar] [CrossRef] [Green Version]
  36. Gokani, V.J.; Kangesu, L.; Harper, J.; Sebire, N.J. Venous malformation associated nerve profiles and pain: An immunohistochemical study. J. Plast. Reconstr. Aesthetic Surg. 2011, 64, 439–444. [Google Scholar] [CrossRef]
  37. Attanasio, S.; Snell, J. Therapeutic angiogenesis in the management of critical limb ischemia: Current concepts and review. Cardiol. Rev. 2009, 17, 115–120. [Google Scholar] [CrossRef]
  38. Kumar, D.; Marshall, H.J. Diabetic peripheral neuropathy: Amelioration of pain with transcutaneous electrostimulation. Diabetes Care 1997, 20, 1702–1705. [Google Scholar] [CrossRef]
  39. Kumar, D.; Alvaro, M.S.; Julka, I.S.; Marshall, H.J. Diabetic peripheral neuropathy: Effectiveness of electrotherapy and amitriptyline for symptomatic relief. Diabetes Care 1998, 21, 1322–1325. [Google Scholar] [CrossRef]
  40. Julka, I.S.; Alvaro, M.; Kumar, D. Beneficial effects of electrical stimulation on neuropathic symptoms in diabetes patients. J. Foot Ankle Surg. 1998, 37, 191–194. [Google Scholar] [CrossRef]
  41. Blum, K.; Oscar-Berman, M.; Blum, S.H.; Madigan, M.A.; Waite, R.L.; McLaughlin, T.; Barh, D. Can Genetic Testing Coupled with Enhanced Dopaminergic Activation Reduce Recidivism Rates in the Workers Compensation Legacy Cases? J. Alcohol Drug Depend. 2014, 2, 161. [Google Scholar] [CrossRef] [Green Version]
  42. Henn, R.F., III; Tashjian, R.Z.; Kang, L.; Green, A. Patients with workers’ compensation claims have worse outcomes after rotator cuff repair. J. Bone Joint Surg. Am. 2008, 90, 2105–2113. [Google Scholar] [CrossRef]
  43. Kasten, P.; Christian, J.P.; Volk, T.; Schmelzer-Schmied, N. Analgesia in shoulder, elbow and hand surgery. Orthopede 2008, 27, 972–976. [Google Scholar]
  44. Busfield, B.T.; Romero, D.H. Pain pump use after shoulder arthroscopy as a cause of glenohumeral chondrolysis. Arthroscopy 2009, 25, 647–652. [Google Scholar] [CrossRef]
  45. Fried, L.; Modestino, E.J.; Siwicki, D.; Lott, L.; Thanos, P.K.; Baron, D.; Badgaiyan, R.D.; Ponce, J.V.; Giordano, J.; Downs, W.B.; et al. Hypodopaminergia and “Precision Behavioral Management” (PBM): It is a Generational Family Affair. Curr. Pharm. Biotechnol. 2020, 21, 528–541. [Google Scholar] [CrossRef]
  46. Hagelberg, N.; Jääskeläinen, S.K.; Martikainen, I.K.; Mansikka, H.; Forssell, H.; Scheinin, H.; Hietala, J.; Pertovaara, A. Striatal dopamine D2 receptors in modulation of pain in humans: A review. Eur. J. Pharmacol. 2004, 500, 187–192. [Google Scholar] [CrossRef]
  47. Caretti, V.; Gori, A.; Craparo, G.; Giannini, M.; Iraci-Sareri, G.; Schimmenti, A. A New Measure for Assessing Substance-Related and Addictive Disorders: The Addictive Behavior Questionnaire (ABQ). J. Clin. Med. 2018, 7, 194. [Google Scholar] [CrossRef] [Green Version]
  48. Fouyssac, M.; Puaud, M.; Ducret, E.; Marti-Prats, L.; Vanhille, N.; Ansquer, S.; Zhang, X.; Belin-Rauscent, A.; Giuliano, C.; Houeto, J.L.; et al. Environment-dependent behavioral traits and experiential factors shape addiction vulnerability. Eur. J. Neurosci. 2021, 53, 1794–1808. [Google Scholar] [CrossRef]
  49. Robbins, T.W.; Ersche, K.D.; Everitt, B.J. Drug addiction and the memory systems of the brain. Ann. N. Y. Acad. Sci. 2008, 1141, 1–21. [Google Scholar] [CrossRef]
  50. Bowirrat, A.; Oscar-Berman, M. Relationship between dopaminergic neurotransmission, alcoholism, and Reward Deficiency syndrome. Am. J. Med. Genet. B Neuropsychiatr. Genet. 2005, 132, 29–37. [Google Scholar] [CrossRef]
  51. Borsook, D.; Linnman, C.; Faria, V.; Strassman, A.M.; Becerra, L.; Elman, I. Reward deficiency and anti-reward in pain chronification. Neurosci. Biobehav. Rev. 2016, 68, 282–297. [Google Scholar] [CrossRef]
  52. Linazaroso, G.; van Blercom, N.; Lasa, A. Hipótesis: Enfermedad de Parkinson, síndrome de deficiencia de recompensa y efectos adictivos de la levodopa [Hypothesis: Parkinson’s disease, reward deficiency syndrome and addictive effects of levodopa]. Neurologia 2004, 19, 117–127. (In Spanish) [Google Scholar]
  53. Ferré, S. Mechanisms of the psychostimulant effects of caffeine: Implications for substance use disorders. Psychopharmacology 2016, 233, 1963–1979. [Google Scholar] [CrossRef] [Green Version]
  54. Green, A.I.; Zimmet, S.V.; Strous, R.D.; Schildkraut, J.J. Clozapine for comorbid substance use disorder and schizophrenia: Do patients with schizophrenia have a reward-deficiency syndrome that can be ameliorated by clozapine? Harv. Rev. Psychiatry 1999, 6, 287–296. [Google Scholar] [CrossRef]
  55. Benton, D.; Young, H.A. A meta-analysis of the relationship between brain dopamine receptors and obesity: A matter of changes in behavior rather than food addiction? Int. J. Obes. 2016, 40 (Suppl. 1), S12–S21. [Google Scholar] [CrossRef] [Green Version]
  56. Kuss, D.J.; Pontes, H.M.; Griffiths, M.D. Neurobiological Correlates in Internet Gaming Disorder: A Systematic Literature Review. Front. Psychiatry 2018, 9, 166. [Google Scholar] [CrossRef]
  57. Hou, L.; Chang, L.; Chen, L.; Zhou, R. Reduced Reward Responsiveness in Women with Moderate-to-Severe Premenstrual Syndrome: Evidence from a Probabilistic Reward Task. Front. Psychiatry 2020, 11, 28. [Google Scholar] [CrossRef] [Green Version]
  58. Gola, M.; Draps, M. Ventral Striatal Reactivity in Compulsive Sexual Behaviors. Front. Psychiatry 2018, 9, 546. [Google Scholar] [CrossRef]
  59. Dölen, G.; Darvishzadeh, A.; Huang, K.W.; Malenka, R.C. Social reward requires coordinated activity of nucleus accumbens oxytocin and serotonin. Nature 2013, 501, 179–184. [Google Scholar] [CrossRef] [Green Version]
  60. Wolters, E.C.; van der Werf, Y.D.; van den Heuvel, O.A. Parkinson’s disease-related disorders in the impulsive-compulsive spectrum. J. Neurol. 2008, 255 (Suppl. 5), 48–56. [Google Scholar] [CrossRef]
  61. Elman, I.; Borsook, D.; Volkow, N.D. Pain and suicidality: Insights from reward and addiction neuroscience. Prog. Neurobiol. 2013, 109, 1–27. [Google Scholar] [CrossRef] [Green Version]
  62. Lin, X.; Deng, J.; Shi, L.; Wang, Q.; Li, P.; Li, H.; Liu, J.; Que, J.; Chang, S.; Bao, Y.; et al. Neural substrates of smoking and reward cue reactivity in smokers: A meta-analysis of fMRI studies. Transl. Psychiatry 2020, 10, 97. [Google Scholar] [CrossRef]
  63. Contarino, A.; Kitchener, P.; Vallée, M.; Papaleo, F.; Piazza, P.V. CRF1 receptor-deficiency increases cocaine reward. Neuropharmacology 2017, 117, 41–48. [Google Scholar] [CrossRef]
  64. Maigaard, K.; Nejad, A.B.; Andersen, K.W.; Herz, D.M.; Hagstrøm, J.; Pagsberg, A.K.; Skov, L.; Siebner, H.R.; Plessen, K.J. A superior ability to suppress fast inappropriate responses in children with Tourette syndrome is further improved by prospect of reward. Neuropsychologia 2019, 131, 342–352. [Google Scholar] [CrossRef]
  65. Rovai, L.; Maremmani, A.G.; Pacini, M.; Pani, P.P.; Rugani, F.; Lamanna, F.; Schiavi, E.; Mautone, S.; Dell’Osso, L.; Maremmani, I. Negative dimension in psychiatry. Amotivational syndrome as a paradigm of negative symptoms in substance abuse. Riv. Psichiatr. 2013, 48, 1–9. [Google Scholar] [CrossRef]
  66. Mangge, H.; Summers, K.; Almer, G.; Prassl, R.; Weghuber, D.; Schnedl, W.; Fuchs, D. Antioxidant food supplements and obesity-related inflammation. Curr. Med. Chem. 2013, 20, 2330–2337. [Google Scholar] [CrossRef]
  67. Gyollai, A.; Griffiths, M.D.; Barta, C.; Vereczkei, A.; Urbán, R.; Kun, B.; Kökönyei, G.; Székely, A.; Sasvári-Székely, M.; Blum, K.; et al. The genetics of problem and pathological gambling: A systematic review. Curr. Pharm. Des. 2014, 20, 3993–3999. [Google Scholar] [CrossRef] [Green Version]
  68. Manzardo, A.M.; Penick, E.C. A theoretical argument for inherited thiamine insensitivity as one possible biological cause of familial alcoholism. Alcohol Clin. Exp. Res. 2006, 30, 1545–1550. [Google Scholar] [CrossRef]
  69. Paelecke-Habermann, Y.; Paelecke, M.; Giegerich, K.; Reschke, K.; Kübler, A. Implicit and explicit reward learning in chronic nicotine use. Drug Alcohol Depend. 2013, 129, 8–17. [Google Scholar] [CrossRef]
  70. Paelecke-Habermann, Y.; Paelecke, M.; Mauth, J.; Tschisgale, J.; Lindenmeyer, J.; Kübler, A. A comparison of implicit and explicit reward learning in low risk alcohol users versus people who binge drink and people with alcohol dependence. Addict. Behav. Rep. 2019, 9, 100178. [Google Scholar] [CrossRef]
  71. Johnson, R.J.; Gold, M.S.; Johnson, D.R.; Ishimoto, T.; Lanaspa, M.A.; Zahniser, N.R.; Avena, N.M. Attention-deficit/hyperactivity disorder: Is it time to reappraise the role of sugar consumption? Postgrad. Med. 2011, 123, 39–49. [Google Scholar] [CrossRef]
  72. Carroll, D.; Ginty, A.T.; Whittaker, A.C.; Lovallo, W.R.; de Rooij, S.R. The behavioural, cognitive, and neural corollaries of blunted cardiovascular and cortisol reactions to acute psychological stress. Neurosci. Biobehav. Rev. 2017, 77, 74–86. [Google Scholar] [CrossRef]
  73. Maremmani, A.G.I.; Pacini, M.; Maremmani, I. What we have learned from the Methadone Maintenance Treatment of Dual Disorder Heroin Use Disorder patients. Int. J. Environ. Res. Public Health 2019, 16, 447. [Google Scholar] [CrossRef] [Green Version]
  74. McAllister, C.J.; Whittington, J.E.; Holland, A.J. Development of the eating behaviour in Prader-Willi Syndrome: Advances in our understanding. Int. J. Obes. 2011, 35, 188–197. [Google Scholar] [CrossRef] [Green Version]
  75. Kamarajan, C.; Rangaswamy, M.; Tang, Y.; Chorlian, D.B.; Pandey, A.K.; Roopesh, B.N.; Manz, N.; Saunders, R.; Stimus, A.T.; Porjesz, B. Dysfunctional reward processing in male alcoholics: An ERP study during a gambling task. J. Psychiatr. Res. 2010, 44, 576–590. [Google Scholar] [CrossRef] [Green Version]
  76. Hahn, T.; Notebaert, K.H.; Dresler, T.; Kowarsch, L.; Reif, A.; Fallgatter, A.J. Linking online gaming and addictive behavior: Converging evidence for a general reward deficiency in frequent online gamers. Front. Behav. Neurosci. 2014, 8, 385. [Google Scholar] [CrossRef] [Green Version]
  77. Oberlin, B.G.; Dzemidzic, M.; Bragulat, V.; Lehigh, C.A.; Talavage, T.; O’Connor, S.J.; Kareken, D.A. Limbic responses to reward cues correlate with antisocial trait density in heavy drinkers. Neuroimage 2012, 60, 644–652. [Google Scholar] [CrossRef] [Green Version]
  78. Verbeken, S.; Braet, C.; Lammertyn, J.; Goossens, L.; Moens, E. How is reward sensitivity related to bodyweight in children? Appetite 2012, 58, 478–483. [Google Scholar] [CrossRef] [Green Version]
  79. Davis, C.; Fox, J. Sensitivity to reward and body mass index (BMI): Evidence for a non-linear relationship. Appetite 2008, 50, 43–49. [Google Scholar] [CrossRef]
  80. Harb, M.R.; Almeida, O.F. Altered motivation masks appetitive learning potential of obese mice. Front. Behav. Neurosci. 2014, 8, 377. [Google Scholar] [CrossRef] [Green Version]
  81. Davis, C.; Levitan, R.D.; Kaplan, A.S.; Carter, J.; Reid, C.; Curtis, C.; Patte, K.; Hwang, R.; Kennedy, J.L. Reward sensitivity and the D2 dopamine receptor gene: A case-control study of binge eating disorder. Prog. Neuro-Psychopharmacol. Biol. Psychiatry 2008, 32, 620–628. [Google Scholar] [CrossRef]
  82. Rahman, N.; Mihalkovic, A.; Geary, O.; Haffey, R.; Hamilton, J.; Thanos, P.K. Chronic aerobic exercise: Autoradiographic assessment of GABA(a) and mu-opioid receptor binding in adult rats. Pharmacol. Biochem. Behav. 2020, 196, 172980. [Google Scholar] [CrossRef]
  83. Kotyuk, E.; Magi, A.; Eisinger, A.; Király, O.; Vereczkei, A.; Barta, C.; Griffiths, M.D.; Székely, A.; Kökönyei, G.; Farkas, J.; et al. Co-occurrences of substance use and other potentially addictive behaviors: Epidemiological results from the Psychological and Genetic Factors of the Addictive Behaviors (PGA) Study. J. Behav. Addict. 2020, 9, 272–288. [Google Scholar] [CrossRef]
  84. Nestor, L.; Hester, R.; Garavan, H. Increased ventral striatal BOLD activity during non-drug reward anticipation in cannabis users. Neuroimage 2010, 49, 1133–1143. [Google Scholar] [CrossRef] [Green Version]
  85. Gerra, M.C.; Manfredini, M.; Cortese, E.; Antonioni, M.C.; Leonardi, C.; Magnelli, F.; Somaini, L.; Jayanthi, S.; Cadet, J.L.; Donnini, C. Genetic and Environmental Risk Factors for Cannabis Use: Preliminary Results for the Role of Parental Care Perception. Subst. Use Misuse 2019, 54, 670–680. [Google Scholar] [CrossRef]
  86. Wu, C.; Garamszegi, S.P.; Xie, X.; Mash, D.C. Altered Dopamine Synaptic Markers in Postmortem Brain of Obese Subjects. Front. Hum. Neurosci. 2017, 11, 386. [Google Scholar] [CrossRef] [Green Version]
  87. Rothman, R.B.; Blough, B.E.; Baumann, M.H. Dual dopamine/serotonin releasers as potential medications for stimulant and alcohol addictions. AAPS J. 2007, 9, E1–E10. [Google Scholar] [CrossRef] [Green Version]
  88. Rivas-Grajales, A.M.; Sawyer, K.S.; Karmacharya, S.; Papadimitriou, G.; Camprodon, J.A.; Harris, G.J.; Kubicki, M.; Oscar-Berman, M.; Makris, N. Sexually dimorphic structural abnormalities in major connections of the medial forebrain bundle in alcoholism. Neuroimage Clin. 2018, 19, 98–105. [Google Scholar] [CrossRef]
  89. Lazaratou, H.; Palaiologou, A.; Anagnostopoulos, D. Impulsivity as an immediate factor between addictive disorders and Attention Deficit-Hyperactivity Disorder. Psychiatriki 2017, 28, 156–164. [Google Scholar] [CrossRef] [Green Version]
  90. Fronczek, R.; Schinkelshoek, M.; Shan, L.; Lammers, G.J. The orexin/hypocretin system in neuropsychiatric disorders: Relation to signs and symptoms. Handb. Clin. Neurol. 2021, 180, 343–358. [Google Scholar] [CrossRef]
  91. Vanhanen, J.K.; Nuutinen, S.; Tuominen, M.; Panula, P. Histamine H3 Receptor Regulates Sensorimotor Gating and Dopaminergic Signaling in the Striatum. J. Pharmacol. Exp. Ther. 2016, 357, 264–272. [Google Scholar] [CrossRef] [Green Version]
  92. Kim, M.; Custodio, R.J.; Botanas, C.J.; de la Peña, J.B.; Sayson, L.V.; Abiero, A.; Ryoo, Z.Y.; Cheong, J.H.; Kim, H.J. The circadian gene, Per2, influences methamphetamine sensitization and reward through the dopaminergic system in the striatum of mice. Addict. Biol. 2019, 24, 946–957. [Google Scholar] [CrossRef]
  93. Suzuki, H.; Han, S.D.; Lucas, L.R. Chronic passive exposure to aggression decreases D2 and 5-HT 1B receptor densities. Physiol. Behav. 2010, 99, 562–570. [Google Scholar] [CrossRef]
  94. Ananth, M.; Hetelekides, E.M.; Hamilton, J.; Thanos, P.K. Dopamine D4 receptor gene expression plays important role in extinction and reinstatement of cocaine-seeking behavior in mice. Behav. Brain Res. 2019, 365, 1–6. [Google Scholar] [CrossRef]
  95. Shukla, A.; Beroun, A.; Panopoulou, M.; Neumann, P.A.; Grant, S.G.; Olive, M.F.; Dong, Y.; Schlüter, O.M. Calcium-permeable AMPA receptors and silent synapses in cocaine-conditioned place preference. EMBO J. 2017, 36, 458–474. [Google Scholar] [CrossRef] [Green Version]
  96. Hamilton, J.; Swenson, S.; Hajnal, A.; Thanos, P.K. Roux-en-Y gastric bypass surgery normalizes dopamine D1, D2, and DAT levels. Synapse 2018. [Google Scholar] [CrossRef]
  97. Kosillo, P.; Bateup, H.S. Dopaminergic Dysregulation in Syndromic Autism Spectrum Disorders: Insights from Genetic Mouse Models. Front. Neural Circuits 2021, 15, 700968. [Google Scholar] [CrossRef]
  98. Althaus, M.; Groen, Y.; Wijers, A.A.; Mulder, L.J.; Minderaa, R.B.; Kema, I.P.; Dijck, J.D.; Hartman, C.A.; Hoekstra, P.J. Differential effects of 5-HTTLPR and DRD2/ANKK1 polymorphisms on electrocortical measures of error and feedback processing in children. Clin. Neurophysiol. 2009, 120, 93–107. [Google Scholar] [CrossRef]
  99. Figueiredo, A.; Hamilton, J.; Marion, M.; Blum, K.; Kaczocha, M.; Haj-Dahmane, S.; Deutsch, D.; Thanos, P.K. Pharmacological Inhibition of Brain Fatty Acid Binding Protein Reduces Ethanol Consumption in Mice. J. Reward Defic. Syndr. Addict. Sci. 2017, 3, 21–27. [Google Scholar] [CrossRef]
  100. Cui, Y.; Ostlund, S.B.; James, A.S.; Park, C.S.; Ge, W.; Roberts, K.W.; Mittal, N.; Murphy, N.P.; Cepeda, C.; Kieffer, B.L.; et al. Targeted expression of μ-opioid receptors in a subset of striatal direct-pathway neurons restores opiate reward. Nat. Neurosci. 2014, 17, 254–261. [Google Scholar] [CrossRef] [Green Version]
  101. Ponce, G.; Jimenez-Arriero, M.A.; Rubio, G.; Hoenicka, J.; Ampuero, I.; Ramos, J.A.; Palomo, T. The A1 allele of the DRD2 gene (TaqI A polymorphisms) is associated with antisocial personality in a sample of alcohol-dependent patients. Eur. Psychiatry 2003, 18, 356–360. [Google Scholar] [CrossRef]
  102. Porat, O.; Hassin-Baer, S.; Cohen, O.S.; Markus, A.; Tomer, R. Asymmetric dopamine loss differentially affects effort to maximize gain or minimize loss. Cortex 2014, 51, 82–91. [Google Scholar] [CrossRef]
  103. Robison, L.S.; Ananth, M.; Hadjiargyrou, M.; Komatsu, D.E.; Thanos, P.K. Chronic oral methylphenidate treatment reversibly increases striatal dopamine transporter and dopamine type 1 receptor binding in rats. J. Neural Transm. 2017, 124, 655–667. [Google Scholar] [CrossRef] [Green Version]
  104. Obici, S.; Magrisso, I.J.; Ghazarian, A.S.; Shirazian, A.; Miller, J.R.; Loyd, C.M.; Begg, D.P.; Carhuatanta, K.A.K.; Haas, M.K.; Davis, J.F.; et al. Moderate voluntary exercise attenuates the metabolic syndrome in melanocortin-4 receptor-deficient rats showing central dopaminergic dysregulation. Mol. Metab. 2015, 4, 692–705. [Google Scholar] [CrossRef] [Green Version]
  105. Castañé, A.; Robledo, P.; Matifas, A.; Kieffer, B.L.; Maldonado, R. Cannabinoid withdrawal syndrome is reduced in double mu and delta opioid receptor knockout mice. Eur. J. Neurosci. 2003, 17, 155–159. [Google Scholar] [CrossRef]
  106. Trigo, J.M.; Zimmer, A.; Maldonado, R. Nicotine anxiogenic and rewarding effects are decreased in mice lacking beta-endorphin. Neuropharmacology 2009, 56, 1147–1153. [Google Scholar] [CrossRef] [Green Version]
  107. Alguacil, L.F.; González-Martín, C. Target identification and validation in brain reward dysfunction. Drug Discov. Today 2015, 20, 347–352. [Google Scholar] [CrossRef]
  108. Hommer, D.W.; Bjork, J.M.; Gilman, J.M. Imaging brain response to reward in addictive disorders. Ann. N. Y. Acad. Sci. 2011, 1216, 50–61. [Google Scholar] [CrossRef]
  109. Koob, G.F.; Le Moal, M. Addiction and the brain antireward system. Annu. Rev. Psychol. 2008, 59, 29–53. [Google Scholar] [CrossRef] [Green Version]
  110. Doremus-Fitzwater, T.L.; Spear, L.P. Reward-centricity and attenuated aversions: An adolescent phenotype emerging from studies in laboratory animals. Neurosci. Biobehav. Rev. 2016, 70, 121–134. [Google Scholar] [CrossRef] [Green Version]
  111. Chang, Y.; Wang, Y.; Mei, S.; Yi, W.; Zheng, Y. Blunted neural effects of perceived control on reward feedback in major depressive disorder. J. Affect. Disord. 2020, 276, 112–118. [Google Scholar] [CrossRef]
Figure 1. A nonaddicting/nonpharmacologic alternative to aid in pain mitigation.
Figure 1. A nonaddicting/nonpharmacologic alternative to aid in pain mitigation.
Ijerph 19 00552 g001
Table 1. Representation of the GARS SNPs and VNTRs (snapshot).
Table 1. Representation of the GARS SNPs and VNTRs (snapshot).
GenePolymorphismLocationRisk Allele(s)
Dopamine D1 Receptor DRD1Rs4532 SNPChr 5A
Dopamine D2 Receptor DRD2 Rs1800497 SNP Chr11 A
Dopamine D3 Receptor DRD3 Rs6280 SNP Chr 3 C
Dopamine D4 Receptor DRD4 Rs1800955 SNP Chr 11 C
48 bases repeat VNTR Chr 11, Exon 3 7R, 8R, 9R, 10R, 11R
Catechol-O-Methyltransferase COMT Rs4680 SNP Chr 22 G
Mu-Opioid Receptor OPRM1 Rs1799971 SNP Chr 6 G
Dopamine Active Transporter DAT1 40 bases repeat VNTR Chr 5, Exon 15 3R, 4R, 5R, 6R, 7R, 8R
Monoamine Oxidase A MAOA 30 bases repeat VNTR Chr X, Promoter 3.5R, 4R
Serotonin Transporter SLC6A4 (5HTTLPR) 43 bases repeat INDEL/VNTR plus rs25531 SNP Chr 17 LG, S
GABA (A) Receptor, Alpha 3 GABRB3 CA-Repeat DNR Chr 15 (downstream) 181
Abbreviations: Single Nucleotide Polymorphisms (SNP), Variable Number Tandem Repeats (VNTR).r 17
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Gupta, A.; Bowirrat, A.; Gomez, L.L.; Baron, D.; Elman, I.; Giordano, J.; Jalali, R.; Badgaiyan, R.D.; Modestino, E.J.; Gold, M.S.; 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. https://doi.org/10.3390/ijerph19010552

AMA Style

Gupta A, Bowirrat A, Gomez LL, Baron D, Elman I, Giordano J, Jalali R, Badgaiyan RD, Modestino EJ, Gold MS, 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. International Journal of Environmental Research and Public Health. 2022; 19(1):552. https://doi.org/10.3390/ijerph19010552

Chicago/Turabian Style

Gupta, Ashim, Abdalla Bowirrat, Luis Llanos Gomez, David Baron, Igor Elman, John Giordano, Rehan Jalali, Rajendra D. Badgaiyan, Edward J. Modestino, Mark S. Gold, and et al. 2022. "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" International Journal of Environmental Research and Public Health 19, no. 1: 552. https://doi.org/10.3390/ijerph19010552

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop