More than 150 researchers from institutions around the world were involved, with NIH funding for the study coming from 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. Further, most clinical trials and behavioral studies have focused on individual substances, rather than addiction more broadly. New methods are being developed that will allow researchers to analyze data concurrently, as applied in plant 138 and mouse model 139 studies. In an early adaptation of this approach in humans 140, the Two-Way Orthogonal Partial Least Squares (O2PLS) method to RNA expression and metabolomics data in 466 Finnish participants recapitulated signals detected in sequential analyses of the two data types and detected new signals by modeling the data types together. Of the 11 loci, UGT2B10-UGT2A3 is the only one implicated for biomarkers but not extended to nicotine dependence or related smoking phenotypes.
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. For example, among adult U.S. smokers during 2015, an estimated 68% wanted to quit, 55% had made a quit attempt in the past year, but only 7% had recently quit 2. In 2021, more than 46 million people in the United States aged 12 or older had at least one substance use disorder, and only 6.3% had received treatment.
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More than 46 million people over the age of 12 years in the United States had at least one SUD in 2021, according to the National Survey on Drug Use and Health. 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. Other ‘omics data derived in blood or other peripheral tissues that are easily accessible in living participants may offer informative biomarkers of addiction but overall provide poor indicators of neurobiology. Poor correlations in RNA expression levels between blood and brain has been repeatedly shown 136, 137, 135. Most recently, pilot GTEx analyses with RNA expression measured in 43 tissues showed that blood vs. brain had the most distinct expression profiles among the tissue comparisons 135.
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- 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.
- Reliance on blood-specific regulatory effects could even lead to erroneous conclusions, as illustrated by the cis-eQTL SNP rs having opposing directions of association with CHRNA5 expression in lymphoblastoid cell lines, as compared to frontal cortex 49.
- Genetic and genomic studies of addiction can facilitate a more accurate molecular diagnosis and, ultimately, the development of appropriate treatments.
- For loci with more than one GWAS lead SNP indicated, r2 and D′ values are shown in reference to all 1000 Genomes phase 3 panels as calculated using LDlink 117.
- More than 150 researchers from institutions around the world were involved, with NIH funding for the study coming from 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.
- 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.
Substance use disorders (SUD), like many neuropsychiatric conditions, are a heterogeneous group of disorders with similar symptomatology but often different pathoetiology. As diagnosed by the DSM-V, SUD requires at least two of eleven diagnostic criteria, resulting in the possibility of over 2000 different combinations of symptoms. Genetic and genomic studies of addiction can facilitate a more accurate molecular diagnosis and, ultimately, the development of appropriate treatments. Sequenced genomes, new animal model resources, and Genome Wide Association Studies (GWAS) of large sample sizes have made vast inroads into our understanding of the genetics that underlies addiction. Future mechanistic studies will be driven by integrating big data from animal models and human studies to identify their consilient features.
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 genetic signature for drug addiction revealed in new analysis of more than a million genomes who had not yet used addictive substances—were also analyzed. The researchers found that children with the genetic signature for addiction were more likely to be related to someone who has a substance use disorder. The children also were more likely to show impulsive personality traits and disrupted sleep patterns, highlighting the possible role of these genes in early life behaviors, even before substance use occurs.
Upcoming concurrent integration of multi ‘omics data
- In children aged 9 or 10 years without any experience of substance use, these genes correlated with parental substance use and externalizing behavior.
- Substance use disorders (SUD), like many neuropsychiatric conditions, are a heterogeneous group of disorders with similar symptomatology but often different pathoetiology.
- Approximately 107,000 people died of drug overdoses in 2021, and 37% of these deaths involved simultaneous exposure to both opioids and stimulant drugs.
- Addiction is a chronic, relapsing disease that alters the brain’s reward circuitry and consequently leads to compulsive drug seeking and other behavioral changes.
- In an early adaptation of this approach in humans 140, the Two-Way Orthogonal Partial Least Squares (O2PLS) method to RNA expression and metabolomics data in 466 Finnish participants recapitulated signals detected in sequential analyses of the two data types and detected new signals by modeling the data types together.
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. Additional heritability may also be explained by complex interactions of genetic variants with one another and with prominent environmental exposures, which will likely require very large sample sizes with harmonized exposures and addiction phenotypes across multiple datasets. A new study suggests that a common genetic signature may increase a person’s risk of developing substance use disorders, regardless of whether the addiction is to alcohol, tobacco, cannabis or opioids. The research, led by Washington University School of Medicine in St. Louis, eventually could lead to universal therapies to treat multiple substance use disorders and potentially help people diagnosed with more than one. A new study suggests that a common genetic signature may increase a person’s risk of developing substance use disorders, regardless of whether the addiction is to alcohol, tobacco, cannabis or opioids.
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Thus, when analyzing gene regulatory potential to study the neurobiology of addiction, it is critical to use disease-relevant brain tissue. Reliance on blood-specific regulatory effects could even lead to erroneous conclusions, as illustrated by the cis-eQTL SNP rs having opposing directions of association with CHRNA5 expression in lymphoblastoid cell lines, as compared to frontal cortex 49. Moreover, gene regulatory effects can differ across the different brain tissues, so comprehensive functional and regulatory assessment will require the availability of ‘omics data across multiple brain tissues, including ones traditionally viewed as being addiction-relevant (e.g., PFC, nucleus accumbens) and others often overlooked (e.g., cerebellum). GTEx, Brain eQTL Almanac, and others provide an unprecedented opportunity to carry out comprehensive analyses in normal brains.
Julia covers medical news in genomics, cancer, cardiology, developmental biology, biochemistry & molecular biophysics, and gut microbiome research. Given by the Association of American Medical Colleges, the award recognized her coverage of long COVID-19. She has a research background with stints in labs focused on bioceramics, human motor control and tissue-engineered heart valves.
This Special Issue, “Genetics and Genomics of Addiction,” focuses on genetic contributions to this disease that may lead to better-targeted therapeutics and diagnostics. This issue contains five original research articles and one review paper that furthers our collective knowledge of SUD disease etiology and the genetic risk factors underlying the disease. “This study could ultimately shift our conceptualization of addictive disorders, allowing novel pathways to research that will uncover more effective therapies for addiction,” Hatoum said.
As these datasets become available, concurrent integration that jointly assess all data may unveil relationships not evident when each data type is analyzed separately by virtue of increased statistical power and their explicit biological relationships (Figure 1). It is expected that genetic variants with large effect sizes are identifiable in sequential analyses but that concurrent integration will enable the identification of genetic variants with moderate-sized, but multi-faceted, functional or regulatory effects. This approach can operate in a bidirectional fashion, with datasets rich in ‘omics informing follow-up in large-scale GWAS of addiction phenotypes/biomarkers and vice versa (Figure 1), and accelerate understanding of the biology underlying statistical associations with addiction phenotypes.
“Using genomics, we can create a data-driven pipeline to prioritize existing medications for further study and improve chances of discovering new treatments. “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.
Its faculty practice is consistently within the top five in the country, with more than 1,800 faculty physicians practicing at 65 locations and who are also the medical staffs of Barnes-Jewish and St. Louis Children’s hospitals of BJC HealthCare. All rights reserved, including those for text and data mining and training of large language models, artificial intelligence technologies, or similar technologies. Published today in Nature Mental Health, the study was led by researchers at the Washington University in St. Louis, along with more than 150 coauthors from around the world. It was supported by the National Institute on Drug Abuse (NIDA), the National Institute on Alcohol Abuse and Alcoholism (NIAAA), the National Institute of Mental Health (NIMH), the Eunice Kennedy Shriver National Institute of Child Health and Human Development, and the National Institute on Aging. This article does not contain any studies with human or animal subjects performed by any of the authors. For loci with more than one GWAS lead SNP indicated, r2 and D′ values are shown in reference to all 1000 Genomes phase 3 panels as calculated using LDlink 117.
Common Genetic Signature May Increase Risk of Multiple Substance Abuse Disorders
Its National Institutes of Health (NIH) research funding portfolio is the third largest among U.S. medical schools, has grown 52% in the last six years, and, together with institutional investment, WashU Medicine commits well over $1 billion annually to basic and clinical research innovation and training. Its faculty practice is consistently within the top five in the country, with more than 1,800 faculty physicians practicing at 65 locations and who are also the medical staffs of Barnes-Jewish and St. Louis Children’s hospitals of BJC HealthCare. WashU Medicine has a storied history in MD/PhD training, recently dedicated $100 million to scholarships and curriculum renewal for its medical students, and is home to top-notch training programs in every medical subspecialty as well as physical therapy, occupational therapy, and audiology and communications sciences. “This study could ultimately shift our conceptualization of addictive disorders, allowing novel pathways to research that will uncover more effective therapies for addiction,” Hatoum said. WashU Medicine is a global leader in academic medicine, including biomedical research, patient care and educational programs with 2,800 faculty.
She is a past Missouri Health Journalism Fellow and a current member of the National Association of Science Writers. 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. Of the 8 loci, TF is the only one implicated for biomarkers but not extended to alcohol use disorder or related alcohol phenotypes. Most GWAS analyses have been conducted in European ancestry populations 6, 9–11, 8, 12–14, 18, 19, 21, 22, 29, 32, although one focused on Hispanics 25, one focused on Japanese 17, eight included or focused exclusively on African Americans 15, 16, 20, 23, 24, 26, 28, 27, and two others included multiple ancestries 30, 31. Two GWAS analyses examined copy number variants 17, 23, while all others focused on SNP and insertion/deletion (indel) variants. WashU Medicine is a global leader in academic medicine, including biomedical research, patient care and educational programs with 2,800 faculty.
Genomics encompasses SNP/indel genotypes, rare variants, and structural variants including copy number variants; epigenomics includes DNA methylation and histone modification; and transcriptomics refers to expression of all RNA types. ‘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. Using larger samples sizes from harmonized datasets and new approaches to integrate GWAS with multiple ‘omics data across human brain tissues holds great promise to significantly advance our understanding of the biology underlying addiction.