New NIH study reveals shared genetic markers underlying substance use disorders National Institute on Drug Abuse NIDA

Is Drug Addiction Genetic

Moreover, the persistent nature of the changes induced by drugs in the brain reward pathway (and other circuits), along with the chronicity of the addictive process, are known to be closely linked to pathological neuroplasticity (Van den Oever et al. 2012; Kalivas and Volkow 2011). “Using genomics, we can create a data-driven pipeline to prioritize existing medications for further study and improve chances of discovering new treatments. In 2021, more than 46 million people celebrities with fetal alcohol syndrome in the United States aged 12 or older had at least one substance use disorder, and only 6.3% had received treatment.

Thinking of addiction as genetic begins with understanding that addiction is a chronic relapsing brain disorder. “In many ways, it’s no different than having a family history with heart disease or diabetes,” says Dr. Anand. There has been limited knowledge of the molecular genetic underpinnings of addiction until now.

Changes in Gene Effects Across the Lifespan

The coding variants in these genes provide a protective effect for AUD by producing aversive effects when drinking alcohol, often resulting in lower levels of consumption and AUD risk (Edenberg & Mcclintick, 2018). However, it is likely that thousands of additional genetic loci play a role beyond the genes encoding alcohol metabolizing enzymes. Additional studies have examined subdomains of alcohol consumption, suggesting potential etiological differences between alcohol consumption frequency and alcohol consumption quantity (Mallard et al., 2020; Marees et al., 2020b). Specifically, alcohol consumption quantity was found to be more genetically similar to AUD and psychopathology, while frequency demonstrated negative relationships with AUD and other psychiatric outcomes, and was found to be influenced by measures of SES (Mallard et al., 2020; Marees et al., 2020b). Thus, evidence of genetic dissimilarity between consumption and AUD may be being driven by frequency of drinking, which in turn, is being influenced by indices of SES. Further studies probing this relationship will be needed to fully disentangle the nuance of the shared and unique genetic etiology across the spectrum of alcohol consumption levels (e.g. normative consumption, binge drinking) and AUD.

Help for Mental Illnesses

Twin and family studies have estimated that ~50% of the liability to opioid dependence is due to additive genetic factors (Berrettini, 2017; Kendler, Jacobson, Prescott, & Neale, 2003; Tsuang, Bar, Harley, & Lyons, 2001). Tsuang et al. (1998) estimated that 38% of the variation in opioid addiction was due to genetic factors specific to opioids (i.e. not shared with other substances). Twin and family studies have demonstrated strong familial inheritance patterns for SUDs (Prom-Wormley, Ebejer, Dick, & Bowers, 2017). Heritability (h2) estimates across SUDs vary, but broadly suggest that genetic influences account for approximately 50% of the risk. For example, a study of more than 3 million people suggests that marriage may protect against AUD, particularly for those with genetic loading for AUD. However, researchers also noted that while marriage to a spouse without alcohol problems may protect against alcohol use disorders, being married to a spouse with alcohol use problems has the opposite effect, increasing one’s risk.

Another issue is that there is no certain way to cross-map animal and human phenotypes, limiting the opportunities for translation. The majority of GWAS of SUDs to date are composed primarily of individuals of European-ancestry, and thus, the generalizability of these findings to other ancestry groups is uncertain. This gap has the potential to further exacerbate health disparities for individuals of diverse ancestry. This raises the need for efforts to study SUDs in transancestral populations, such as the All of sun rocks weed Us Research Program.

Mark S. Gold, M.D., is a pioneering researcher, professor, and chairman of psychiatry at Yale, the University of Florida, and Washington University in St Louis. His theories have changed the field, stimulated additional research, and led to new understanding and treatments for opioid use disorders, cocaine use disorders, overeating, smoking, and depression. The world around you also can play a significant role in opening a door that leads to problematic substance use, notes Dr. Anand. About half of your susceptibility to developing a substance use disorder (SUD) can be hereditary. Genetics can mark you as more how to flush alcohol out of your system for urine test prone to use alcohol, tobacco products or drugs such as cocaine, heroin and opioids. Personalized medicine in addiction treatment considers individual differences in behavioral and psychological factors.

Associated Data

  1. It is the hope that these continued advancements will have clinically meaningful implications for SUD prevention and treatment in the future.
  2. Both HTR2B and MAOA influence impulsivity and behavioral control and findings for these genes in humans remarkably parallel animal models.
  3. Similar to findings for alcohol, recent GWAS of CanUD have found divergence between cannabis use and CanUD, both at the level of individual risk loci as well as genetic relationships with other traits and disorders.
  4. This knowledge offers a unique opportunity for investigating how variations in these targets influence the responses to drugs of abuse.
  5. However, it is likely that thousands of additional genetic loci play a role beyond the genes encoding alcohol metabolizing enzymes.
  6. Fowler and Kenny (2012) present how a diverse array of genetically modified mice can be used to investigate the role of specific genes in drug responses.

In the VA and Yale study, researchers analyzed genetic data from nearly 2,000 people who participated in a prior study by Yale and University of Pennsylvania researchers (called the Yale-Penn study) on substance use genetics. Researchers examined the role of recently developed polygenic risk scores for opioid use disorder and environmental factors such as education level, adverse childhood experiences, and psychiatric conditions. “We’ve made great progress in understanding some of the genetic and environmental factors that influence risk for opioid use disorder, but we know less about the complex interplay between them,” said Yale’s Joseph Deak.

Is Drug Addiction Genetic

It has been estimated that 50%-70% of an individual’s risk for cannabis use disorder is due to genetic factors, although environmental factors also play a role. Yale’s group, led by Joel Gelertner, has been trying to identify these risks and predict who might develop cannabis use disorder, with its many negative outcomes, including increased risk of psychiatric disorders, heart disease, cancer, and respiratory illnesses. It is important to point out that, with the exception of genes involved in protection against alcohol or nicotine addictions, via their effects on drug metabolism, the risk of SUDs attributable to other classes of genes identified to date is very small. However, findings from genetic/genomic studies have been extremely successful at expanding our understanding of the neurobiology underlying drug addiction while, at the same time, helping us identify new targets for medication development.

About the Acting NIMH Director

Such studies, however, cannot yet address the critical mechanistic question about how genetic diversity influences the sensitivity to either adverse or protective environments vis á vis abuse and addiction trajectories. One overarching question that has emerged from the first-generation of well-powered SUD GWAS is whether measures of non-problematic substance use have divergent genetic underpinnings from SUDs, and if so, to what extent. Another area of interest has been dissecting the genetic relationships between SUDs, other psychiatric disorders, and relevant complex traits; by leveraging large GWAS and advanced statistical genetics methods e.g. Cross-trait genetic correlations, genomicSEM (Grotzinger et al., 2019), interesting patterns of pleiotropy have emerged (Abdellaoui, Smit, Van Den Brink, Denys, & Verweij, 2021; Hatoum et al., 2021; Jang et al., 2020).

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