Author: Gary Jackson

Genetic Signature for Drug Addiction Revealed in New Analysis of More Than A Million Genomes

The terms genetics and heredity are sometimes used interchangeably, but there are differences that are important to understand. Linkage-disequilibrium patterns differ across populations, which is one reason that discovery GWAS of European ancestry may not lead to maximally-predictive PGS in non-European ancestry target samples (Martin et al., 2019). It is thus imperative, in the interest of scientific discovery and ensuring that everyone benefits equally from those discoveries, that future SUD GWAS focus on increasing the number of samples of non-European ancestry. One gene therapy being tested in mice generates antibodies that trap methamphetamine, preventing it from reaching the brain. In another, mice transplanted with genetically modified skin cells make an enzyme that degrades cocaine. This article does not contain any studies with human or animal subjects performed by any of the authors.

• If you or someone you care about are struggling with addiction, you should know that treatment can help you start the path to recovery to overcome addiction.
• Because people have complex and varied lives, in-depth studies are often done using animals in a controlled lab setting.
• Despite divergent patterns of genetic overlap suggesting non-uniform genetic influences, it should be noted that genes influencing alcohol-metabolizing enzymes (e.g. ADH1B, ALDH2) directly affect alcohol consumption, and in turn, play a role in the risk of AUD development.
• Further research is needed to fully understand the potential benefits, and possible harms, of incorporating genetic information (e.g. PGS) into SUD treatment planning (Driver, Kuo, & Dick, 2020; Lebowitz, 2019; Lebowitz & Ahn, 2018).

For example, lifetime cannabis ever-use shows positive genetic correlations with education and age at first birth, and a negative correlation with BMI (+, +, −; Pasman et al., 2018), while CanUD shows genetic correlations in the opposite direction of effect for these three traits (−, −, +; Johnson et al., 2020b). This suggests that, while necessary for the development of CanUD, cannabis initiation is at least partly genetically distinct from CanUD. “Using genomics, we can create a data-driven pipeline to prioritize existing medications for further study and improve chances of discovering new treatments. In taking integration to the next level, PrediXcan [134] is a promising new gene-based method that utilizes genome-wide SNP genotypes and RNA-sequencing data in GTEx to build genetically regulated gene expression models in a diverse set of tissues and applying those models in GWAS with disease phenotypes of interest.

When Addiction Runs in the Family

This type of sequential integration in moving from GWAS to functional or regulatory characterization has also yielded other important discoveries in addiction [21, 48, 119]. These sequential integration examples highlight a challenge for the field of addiction, and psychiatric disease more broadly, because functional and regulatory effects can be highly tissue-specific [135] and brain is the most relevant tissue for studying the neurobiology of addiction. GWAS genotypes, other ‘omics data in brain, and addiction phenotypes are seldom available in the same dataset.

GWAS analyses have identified several genetic loci with statistically robust and reproducible SNP/indel associations, cementing the polygenic nature of addiction. However, with only a fraction of the heritability explained (for example, 15% of the variance in nicotine dependence [121] and 13% of the variance in alcohol consumption [58] explained by common SNPs together) and limited knowledge of the neurobiological pathways leading to addiction, much remains to be discovered. We fully expect that GWAS analyses conducted with sample sizes into the hundreds of thousands and millions will replicate previously suggested, but currently unreplicated, genetic variants and will also unveil novel variants. As evidenced by the GWAS-identified variants identified to date (mainly SNPs), novel variants will likely exert small effect sizes on developing addiction but potentially uncover previously unrecognized neurobiological pathways.

Reduced drug use is a meaningful treatment outcome for people with stimulant use disorders

As genetic information is used to better understand human health and health inequities, expansive and inclusive data collection is essential. NIDA and other Institutes at NIH supported a recently released report on responsible use and interpretation of population-level genomic data, by the National Academies of Sciences, Engineering, and Medicine. Recent years have brought substantial progress in advancing our understanding of the genetic architecture of SUDs and other substance use behaviors (e.g. consumption quantity), and relating these findings to etiologically-relevant processes for the development of SUDs. The field will continue to see significant advances in genetic discovery as larger sample sizes of individuals of diverse ancestry begin to become realized.

This raises the need for efforts to study SUDs in transancestral populations, such as the All of Us Research Program. As shown in Table 1, GWAS of SUDs have included relatively more diverse samples compared to other psychiatric disorders, but the numbers of non-European samples are still well below the European-ancestry sample sizes. Candidate gene and genome-wide analyses are increasingly integrated to identify genetic variations influencing addiction. In the former, genes known to influence the pathogenesis or treatment of addictions are selected, for example, based on discoveries in animal pharmacobehavioral and genetic studies or based on what is known about the pharmacokinetics and pharmacodynamics of the drug. The inclusion of data from different ancestral groups in this study cannot and should not be used to assign or categorize variable genetic risk for substance use disorder to specific populations.

Heritability of Addictions

Addiction is a chronic, relapsing disease that alters the brain’s reward circuitry and consequently leads to compulsive drug seeking and other behavioral changes. The long-lasting biological effects of drug exposure cause a multitude of adverse effects throughout the body. Despite these well-known health consequences and widespread public health campaigns to curb use of addictive drugs, prevalence remains high. Among individuals aged 12 and older in the U.S. in 2015, an estimated 30.2 million (11.3%) smoked cigarettes daily in the past month; 15.7 million (5.9%) had an alcohol use disorder and 7.7 million (2.9%) had an illicit drug use disorder in the past year [1]. Individuals with addiction often have strong desires to quit, but rates of successful treatment and recovery are low.

• Fagerström Tolerance Questionnaire (FTQ), Fagerström Test for Nicotine Dependence (FTND)] in comparison to NicUD as determined by DSM diagnostic criteria (Cohen, Myers, & Kelly, 2002; Payne, Smith, McCracken, McSherry, & Antony, 1994).
• These sequential integration examples highlight a challenge for the field of addiction, and psychiatric disease more broadly, because functional and regulatory effects can be highly tissue-specific [135] and brain is the most relevant tissue for studying the neurobiology of addiction.
• Disease can be woven into your DNA — and that includes the disease of drug addiction.

“Substance use disorders and mental disorders often co-occur, and we know that the most effective treatments help people address both issues at the same time. The shared genetic mechanisms between substance use and mental disorders revealed in this study underscore the importance of thinking about these disorders in tandem,” said NIMH Director Joshua A. Gordon, M.D., Ph.D. Unlike GWAS of cigarette smoking and alcohol phenotypes, GWAS of these specific drugs have had limited success at identifying and replicating variant associations. Finally, there are multiple substance classes not covered in this review, including hallucinogens, ‘club drugs’, and inhalants. These substance classes have been included in a handful of twin and family studies examining drug use, but no well-powered GWAS exist. Future GWAS efforts will be informative for how the genetics of these additional SUDs overlap with or diverge from well-studied SUDs.

To learn more about how animal models, like mice and fruit flies, have taught us so much about addiction, visit Animal Models for Addiction Research. The pedigrees (family trees) above show affected people in red and unaffected in white. Anybody can develop an SUD, and they can do it for any number of reasons in their life.