NIH study reveals shared genetic markers underlying substance use disorders National Institutes of Health NIH

“… in a sample of drug-naive children, the addiction-rf PRS was correlated with parental substance use problems and externalizing behavior,” the researchers stated. Compared to other genetic predictors, the genomic pattern identified here was also a more sensitive predictor of having two or more substance use disorders at once. The genomic pattern linked to general addiction risk also predicted higher risk of mental and physical illness, including psychiatric disorders, suicidal behavior, respiratory disease, heart disease, and chronic pain conditions. In children aged 9 or 10 years without any experience of substance use, these genes correlated with parental substance use and externalizing behavior. This special issue aimed to bring together researchers of substance use disorder across various drugs of abuse and experimental systems to describe the current status of addiction genetics. The articles in this special issue covered various topics and provided diverse insights to direct future SUD genetics research.

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

In addition to identifying genetic loci that were linked with addiction to specific substances—alcohol, tobacco, cannabis, and opioids—the results identified more than a dozen independent single-nucleotide polymorphisms (SNPs) that were genome-wide significant for the general addiction risk factor (addiction-rf). The findings, the team suggested, could eventually lead to universal therapies for multiple substance use disorders, including treatments for treating more than one SUD in the same individual. The results of new research headed by a team at Washington University School of Medicine in St. Louis suggest that a common genetic signature may increase an individual’s risk of developing substance use disorders (SUDs), regardless of whether the addiction is to alcohol, tobacco, cannabis, or opioids. The researchers carried out a multivariate genome-wide association meta-analysis of the largest genome-wide association studies (GWAS) of SUDs, which together included genomic data from more than 1.1 million people of mostly European ancestry and a smaller population of people of African ancestry. 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.

• She holds a bachelor’s degree in engineering science from Iowa State University and a master’s degree in biomedical engineering from the University of Minnesota.
• The PrediXcan framework is applicable to other sources of ‘omics data (e.g., DNA methylation) in GTEx or elsewhere.
• She has a research background with stints in labs focused on bioceramics, human motor control and tissue-engineered heart valves.
• For discussion of genetics research, ethical and social issues arising from genetics and its applications, genetics career questions, etc.
• Of the 11 loci, UGT2B10-UGT2A3 is the only one implicated for biomarkers but not extended to nicotine dependence or related smoking phenotypes.

More than 46 million people over age 12 in the U.S. had at least one substance use disorder in 2021, according to the National Survey on Drug Use and Health. However, most medications target the use of a specific substance, such as tobacco or opioids, rather than treating addiction broadly. 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.

Common Genetic Signature May Increase Risk of Multiple Substance Abuse Disorders

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. 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. The genomic pattern also predicted higher risk of mental and physical illness, including psychiatric disorders, suicidal behavior, respiratory disease, heart disease, and chronic pain conditions. Replicable GWAS findings span 11 genetic loci for smoking, eight loci for alcohol, and two loci for illicit drugs combined and include missense functional variants and noncoding variants with regulatory effects in human brain tissues traditionally viewed as addiction-relevant (e.g., prefrontal cortex PFC) and, more recently, tissues often overlooked (e.g., cerebellum). Substance use disorders have increased dramatically in recent years, with rising numbers of overdose deaths and increasing social, emotional and financial costs to families and communities.

The growing number of pathways, genes, proteins, and molecules that appear to be involved in SUD is of special interest. We anticipate that this Special Issue will help researchers search for additional genetic associations that will help refine our understanding of the etiology of this complex disease. New research led by Washington University School of Medicine in St. Louis identifies a common genetic signature that may increase a person’s risk of developing substance use disorders.

Links to NCBI Databases

Future studies are needed for more thorough and well-powered assessment of brain tissues in participants with addiction phenotype data. Integration of GWAS with other ‘omics data types (such as, DNA methylation or RNA expression) commonly happens in a sequential fashion to infer functional or regulatory effects of top GWAS findings. 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. “This study represents a major advance in understanding how genetic factors predispose people to substance use disorders,” Agrawal said. “While we have known for a while that many genetic factors are shared between different substance use disorders, our study identified some of the contributing genes, providing avenues for future biological and therapeutic discoveries for individuals with multiple addictions.” Where once a single ‘omics type was used, studies that capture multiple ‘omics data types in the same dataset are emerging.

Cannabis use disorder: another COVID risk factor

Moreover, people who use drugs are facing an increasingly dangerous drug supply, now often tainted with fentanyl. Approximately 107,000 people died of drug overdoses in 2021, and 37% of these deaths involved simultaneous exposure to both opioids and stimulant drugs. Drug use and addiction represent a public health crisis, characterized by high social, emotional, and financial costs to families, communities, and society. Concurrent integrative analysis approach with multiple types of ‘omics data used to inform discovery or characterize top findings from large-scale addiction GWAS.

Multiple substance use disorders may share inherited genetic signature

Unlike GWAS of cigarette smoking and alcohol phenotypes, GWAS of these specific drugs have had limited success at identifying and replicating variant associations. “But here, we can implicate more specific mechanisms by which the brain regulates response to dopamine across different substances, and ultimately find processes that could reverse maladaptive regulation that leads to addiction.” There is a tremendous need for treatments that target addiction generally, given patterns of the use of multiple substances, lifetime substance use, and severity seen in the clinic. Our study opens the door to identifying medications that may be leveraged to treat addiction broadly, which may be especially useful for treating more severe forms, including addiction to multiple substances.” 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.

For loci with more than one GWAS lead or proxy SNP indicated, r2 and D′ values are shown in reference to all 1000 Genomes phase 3 panels as calculated using LDlink 117. For discussion of genetics research, ethical and social issues arising from genetics and its applications, genetics career questions, etc. Because of a lapse in government funding, the information on this website may not be up to date, transactions submitted via the website may not be processed, and the agency may not be able to respond to inquiries until appropriations are enacted. Updates regarding government operating status and resumption of normal operations can be found at opm.gov.

Upcoming concurrent integration of multi ‘omics data

The work eventually could lead to universal therapies to treat multiple substance use disorders and potentially help people diagnosed with more than one. The inclusion of data from different ancestral groups in genetic signature for drug addiction revealed in new analysis of more than a million genomes this study cannot and should not be used to assign or categorize variable genetic risk for substance use disorder to specific populations. As genetic information is used to better understand human health and health inequities, expansive and inclusive data collection is essential.

As part of the study, the researchers compiled a list of approved and investigational drugs that have the potential to be repurposed to treat SUDs because they target the effects of the newly discovered addiction genetic signature. The list includes more than 100 drugs to investigate in future clinical trials, including those that can influence regulation of dopamine signaling. This drug repurposing analysis, the investigators wrote, “identified 104 medications approved by the U.S. Previous research has implicated dopamine signaling in addiction, but most such studies have focused on a single substance. Further, the regulation of dopamine and neuronal development from the newly discovered genetic signature can help narrow down the specific forms of neuronal communication that are affected in substance use disorders. The incidence of SUDs has increased dramatically in recent years, with rising numbers of overdose deaths and increasing social, emotional, and financial costs to families and communities.

• To serve as a control group for exposure to addictive substances, genetic data from 4,491 nine- and 10-year-old children of European ancestry who are participating in the national Adolescent Brain Cognitive Development Study—and who had not yet used addictive substances—were also analyzed.
• Future studies are needed for more thorough and well-powered assessment of brain tissues in participants with addiction phenotype data.
• As part of the study, the researchers compiled a list of approved and investigational drugs that have the potential to be repurposed to treat SUDs because they target the effects of the newly discovered addiction genetic signature.
• ‘Omics data may pertain to endogenous factors along the flow of information according to the Central Dogma of Biology or exogenous factors such as environmental exposures.

The PrediXcan framework is applicable to other sources of ‘omics data (e.g., DNA methylation) in GTEx or elsewhere. Published March 22 in the journal Nature Mental Health, the study’s findings are drawn from an analysis of genomic data from more than 1.1 million people of mostly European ancestry and a smaller population of people of African ancestry. Published March 22 in the journal Nature Mental Health, the study’s findings are drawn from an analysis of genomic data from more than 1.1 million people of mostly European ancestry and a smaller population of people of African ancestry. But recent large-scale genome-wide association studies suggest that the genetic architecture of SUDs is characterized by a high degree of commonality, “that is, a general addiction genetic factor likely conveys vulnerability to multiple SUDs,” the team wrote. The research was supported by the National Institute on Drug Abuse, the National Institute on Alcohol Abuse and Alcoholism, the National Institute of Mental Health, the Eunice Kennedy Shriver National Institute of Child Health and Human Development, and the National Institute on Aging, all part of the National Institutes of Health (NIH). Co-senior authors on the study included Arpana Agrawal, PhD, a professor of psychiatry at Washington University School of Medicine; Ryan Bogdan, PhD, a professor of psychological & brain sciences at Washington University; Howard J. Edenberg, PhD, of Indiana University School of Medicine; and Joel Gelernter, MD, of the Yale School of Medicine.

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