A genetic architecture underlying alcohol and cigarette abuse

Summary: Genes associated with alcohol and tobacco addiction are overrepresented in specific neurons, a new study finds. The researchers found that genes associated with smoking were also linked to pain perception and food response, while genes linked to alcohol dependence were associated with stress and learning.

Source: University of North Carolina

Have you ever wondered why one person can smoke cigarettes for a year and quit easily, while another person becomes addicted for life? Why can’t some people stop abusing alcohol and others can take it or leave it?

One of the reasons is a person’s genetic propensity to abuse substances. UNC School of Medicine researchers led by Hyejung Won, Ph.D., are beginning to understand these underlying genetic differences.

The more they learn, the more likely they are to be able to create therapies to help the millions of people struggling with addiction.

Won, an assistant professor of genetics and a member of the UNC Neuroscience Center, and his colleagues have identified genes linked to smoking and alcohol consumption. The researchers found that these genes are overrepresented in certain types of neurons, brain cells that trigger other cells to send chemical signals throughout the brain.

The researchers, who published their work in the journal Molecular Psychiatry, also found that the genes underlying smoking were linked to pain perception and response to food, as well as the abuse of other drugs, such as cocaine. Other genes associated with alcohol use were linked to stress and learning, as well as the abuse of other drugs, such as morphine.

Given the lack of current treatment options for substance use disorders, the researchers also conducted analyzes of a publicly available drug database to identify potential new treatments for substance abuse. .

“We found that antipsychotics and other mood stabilizers could potentially provide therapeutic relief for people struggling with addiction,” said first author Nancy Sey, a graduate student in the Won lab. “And we believe our research provides a good foundation for research focused on creating better treatments for drug addiction.”

Analyze the genome

Long-term substance use and substance use disorders have been linked to many common diseases and conditions, such as lung cancer, liver disease, and mental illness. Yet few treatment options are available, largely due to gaps in our understanding of the biological processes involved.

“We know from twin studies that genetics may explain why some people use and abuse substances, aside from environmental factors, such as family issues or personal trauma,” Won said. “Genetic studies such as genome-wide association studies (GWAS) provide a way to identify genes associated with complex human traits, such as nicotine addiction or excessive alcohol consumption. “

Using GWAS, Won added, researchers can identify regions of the genome that play a role in particular traits, compared to individuals who don’t exhibit the trait. Yet genome-wide studies can’t tell us much about how genes in these regions affect a trait. This is because these regions are often found in “non-coding” regions of the genome.

“Non-coding” refers to the fact that the genes in these regions do not translate – or code – their genetic information directly into the creation of proteins, which then perform a known biological function. Therefore, what is actually happening biologically in these “non-coding” regions remains mostly unknown.

“We wanted to know what’s going on in those areas,” Won said. “So we developed Hi-C coupled MAGMA (H-MAGMA), a computational tool to help us better understand what we see in genome-scale studies.”

In a previous publication, Won’s lab showed how applying H-MAGMA to brain disorders identifies their associated genes and describes their underlying biology. And for this current paper, his lab extended the tool to smoking and alcohol consumption.

They developed H-MAGMA frameworks from dopaminergic neurons and cortical neurons, types of brain cells that researchers have long implicated in substance use. Focusing on these two cell types, Won’s team, led by Sey, an HHMI Gilliam Fellow, applied H-MAGMA to GWAS results related to smoking intensity, nicotine dependence, problem drinking and intensity of drinking to identify genes associated with each trait. .

This shows a glass of wine
Given the lack of current treatment options for substance use disorders, the researchers also conducted analyzes of a publicly available drug database to identify potential new treatments for substance abuse. . Image is in public domain

Genes associated with alcohol consumption and smoking were also associated with other types of substances, such as morphine and cocaine. While the opioid crisis has caused a detrimental social burden, potent GWAS on cocaine and opioid use are not currently available.

Won’s team therefore set out to determine whether genes associated with alcohol consumption and smoking may reveal the genetics underlying general addictive behavior, genetic findings that could be extended to other substances of abuse. abuse.

“Our analyzes showed that the expression of genes shared between smoking and drinking traits can be altered by other types of substances such as cocaine,” Won said.

“By characterizing the biological function of these genes, we will be able to identify the biological mechanisms underlying addiction, which could be generalized to various forms of substance use disorders.”

In addition to the different types of excitatory neurons, Won’s team also identified other cell types, including cortical glutamatergic, midbrain dopaminergic, GABAergic, and serotonergic neurons associated with risk genes.

With these discoveries in hand, it is now possible for researchers at UNC and others to study the molecules that make addiction much less likely.

See also

This shows the outline of a head

About this genetics and addictions research news

Author: Press office
Source: University of North Carolina
Contact: Press Office – University of North Carolina
Image: Image is in public domain

Original research: Access closed.
“Chromatin Architecture in Addiction Circuits Identifies Risk Genes and Potential Biological Mechanisms Underlying Patterns of Smoking and Alcohol Use” by Nancy YA Sey et al. Molecular Psychiatry


Summary

Chromatin Architecture in Addiction Circuitry Identifies Risk Genes and Potential Biological Mechanisms Underlying Patterns of Smoking and Alcohol Use

Smoking and alcohol consumption are among the most prevalent substances in the world and account for a significant proportion of preventable morbidity and mortality, underscoring the public health importance of understanding their etiology. Genome-wide association studies (GWAS) have successfully identified genetic variants associated with characteristics of smoking and alcohol consumption.

However, the vast majority of risk variants reside in non-coding regions of the genome, and their target genes and neurobiological mechanisms are unknown. Chromosomal conformation maps can fill this knowledge gap by mapping the patterns of interaction of risk-associated regulatory variants with target genes.

To investigate the functional impact of common variants associated with smoking and alcohol consumption, we applied Hi-C coupled MAGMA (H-MAGMA) based on newly generated cortical dopaminergic neural datasets to summary statistics GWAS of nicotine addiction, cigarettes per day, problematic alcohol consumption and drinks per week.

Identified risk genes are mapped to major pathways associated with smoking and alcohol consumption, including drug metabolic processes and neuronal apoptosis.

Risk genes were highly expressed in cortical glutamatergic, midbrain dopaminergic, GABAergic, and serotonergic neurons, suggesting them as relevant cell types for understanding the mechanisms by which genetic risk factors influence smoking and alcohol consumption. .

Finally, we identified pleiotropic genes between smoking and drinking traits hypothesizing that they might reveal shared and substance-independent neurobiological mechanisms. The number of pleiotropic genes was about 26 times higher in dopaminergic neurons than in cortical neurons, highlighting the critical role of ascending dopaminergic pathways in mediating general addictive phenotypes.

Collectively, brain region and neuronal subtype-specific 3D genome architecture helps refine neurobiological hypotheses for smoking, alcohol, and general dependence phenotypes by linking genetic risk factors to their target genes.

Leave a Comment