summary: Researchers used an innovative approach to investigate genetic links to mental health problems in adolescents, identifying links with behaviors such as screen time and caffeine intake. By focusing on polygenic scores that reflect genetic predisposition, this study highlights a range of potentially modifiable factors that can contribute to risk of mental illness.
Although a causal relationship has not been established, these findings provide the basis for early intervention strategies in adolescence. This study highlights the potential of genomic research to inform preventative measures for mental health, even if limitations remain due to ancestral expression.
Important facts:
- Broad genetic screening reveals links between mental health risks and behaviors.
- Screen time, energy drink consumption, and stress-related events may be correlated with genetic risk.
- This study highlights the importance of developing diverse genomic datasets to gain broader insights.
sauce: wasl
Researchers at Washington University in St. Louis are taking a “big trawling” approach, casting a wide net, and trying to understand how genetic influences influence young people’s behavior. We captured all the measured characteristics, behaviors, and environments that make up our people. and investigate associations with genetic components of risk for mental health problems.
This cutting-edge methodology has yielded valuable new insights into factors associated with genetic risk for psychopathology, including stressful life events and screen time. The results were announced, but nature mental health, Although we cannot say whether one causes the other, the results of this study provide promising clues to understanding the nature of mental illness that develops in adolescence.
“We’re catching all the little fish here,” said Nicole Karcher, assistant professor of psychiatry at WashU Medicine, likening their genetic screening tools to trawling the ocean.
“But now we can wade through the fish we catch. Future steps include determining how meaningful these fish are in terms of their ability to reduce the risk of mental health concerns. It involves understanding what is.
An innovative approach to “catching” risk factors
Much of what we know about the association between genomes and behavior comes from genome-wide studies that identify associations between specific genetic variations and traits of interest, also known as phenotypes. Obtained from wide association studies (GWAS). Phenotypes range from physical characteristics to mental disorders (e.g., depression, anxiety).
Many behavioral disorders are correlated at the genetic level. Therefore, the results of GWAS scans for genetic associations with depression may also reflect genetic associations with frequently co-occurring conditions such as anxiety.
“We know that no single behavioral variable exhibits the sole association with genetic risk, so we have developed a more agnostic, data-driven approach to the wealth of information available in large datasets. We were interested in taking a type approach,” Karcher said.
In doing so, we will not only identify expected associations between genetic risk and psychiatric symptoms, but also new associations that may improve insight into how risk for mental illness evolves. We hope that you can identify it.
So, senior author Karcher and first author Sarah Paul, a graduate student in Ryan Bogdan’s Institute for Behavioral Research and Imaging Neurogenetics in Arts & Sciences, are working on a Phenomwide-related study (PheWAS) to reverse GWAS. ) was carried out.
Rather than starting with a mental state and looking for associated genetic variants, their PheWAS starts with genetic variants known to be associated with mental health disorders and then looks at behaviors, symptoms, environment, health issues, and other We investigated relationships with hundreds of measured variables that reflect the phenotype.
These included a total of approximately 1,300–1,700 phenotypes from the Adolescent Brain Cognitive Development (ABCD) study.
“We took a pretty broad approach,” Paul said, looking at a variety of phenotypes, “from impulse control issues and behavior problems to experiences like psychosis to screen time and caffeine intake. It extends to everything,” he explained.
Think of it like fishing with a big net.
This means we want to identify links between genetic predisposition and modifiable risk factors that can potentially be addressed. in front It’s the beginning of psychopathology, said Bogdan, Dean’s Distinguished Professor of Psychology and Brain Sciences in the Department of Arts and Sciences.
what they caught
The PheWAS results present some surprises and confirm some of what we already know about genetic risks and behaviors associated with mental health disorders in adolescents.
WashU researchers took 11 GWAS and created a polygenic score for four broad genetic risk factors: neurodevelopmental, internalizing (e.g., depression, anxiety), obsessive-compulsive, and psychotic.
Below are some of the associations found in these categories.
*Genetic risk for neurodevelopmental psychopathology (primarily ADHD and autism spectrum disorders, major depressive disorder and problematic alcohol use) is associated with inattention and impulsivity problems, total screen time, sleep disturbances, The experience was associated with approximately 190 phenotypes, including psychosis-like symptoms. Even environmental conditions, such as neighborhood crime rates and reduced parental supervision, are associated with genetic risk for neurodevelopment.
*Genetic risk for internalizing behaviors (major depressive disorder, generalized anxiety disorder, PTSD, and problematic alcohol use) is associated with depression, stressful life events, psychotic-like experiences, screen time, etc. It was widely associated with about 120 phenotypes.
*Psychiatric risk (mainly schizophrenia and bipolar disorder) had little phenotypic association, apart from lower school engagement and increased energy drink intake.
Karcher said it was somewhat surprising that “genetic responsibility” for mental health concerns could emerge through modifiable behaviors in childhood and early adolescence.
The study categorized hundreds of variables that may be associated with genetic risk, and the results highlighted several associations, including an association between genetic risk for neurodevelopment and screen time. she added.
“PheWAS was able to point out pockets of association that we might not have discovered otherwise,” she said.
One such pocket was the association between genetic risk for psychotic disorders and energy drink consumption. Because these studies looked at correlation rather than causation, we cannot conclude that energy drink consumption causes psychotic disorders.
There are genetic factors that put these people at increased risk for psychotic disorders, and those same factors may also make these people more likely to consume caffeinated beverages.
A similar phenomenon may be in play, where there is a strong association between screen time and neurodevelopmental risks.
The goal of PheWAS is not to sort out the details of causal relationships, but to point people in the right direction “from a 20,000-foot perspective of relationships,” Karcher said.
Only time will tell, as children with ABCD grow and the genomic database becomes more diverse.
“Following these young people into early adulthood will allow us to better understand how genetic risk is associated with screen time, psychopathology, symptoms, sleep, and more over the course of adolescence and early adulthood. “It will help,” Paul said.
“It helps paint a clearer picture of how associations between overall genetic risk and behaviors and traits change, or do not change, over time.”
Overall, the current study shows how PheWAS technology can be used to identify potential targets for future prevention and early intervention strategies, and in this study We have identified several modifiable targets, such as screen time and caffeinated beverage consumption, that may lead to Reduce your risk of developing mental health concerns.
Previous genome-wide studies of psychiatric diagnoses/phenotypes have utilized data from individuals most genetically similar to European reference populations, and the powerful GWAS available in other populations worldwide It was limited.
Therefore, one major limitation of this study was that only ABCD data from individuals with European ancestry could be used in PheWAS, as GWAS primarily used data from European reference populations.
“This really limits the generalizability of these findings,” Paul said. Please be more inclusive. ”
Funding: The data for this study are U01DA041022, U01DA041025, U01DA041028, U01DA041048, U01DA041089, U01DA041093, U01DA041106, U01DA041117, 041120, U01DA041134, U01DA041148 , U01DA041156, U01DA041174, U24DA041123, and U24DA041147 from the NIH and additional federal partners (https://abcdstudy. org/federal-partners.html).
This research was supported by R01 DA054750. The authors received funding from the NIH. SEP was supported by F31AA029934. NRK was supported by K23MH12179201. AJG was supported by NSF DGE-213989.
ECJ was supported by K01DA051759. ASH was supported by K01AA030083. DMB (R01-MH113883; R01-MH066031; U01-MH109589; U01-A005020803; R01-MH090786), RB (R01-DA054750, R01-AG045231, R01-AG061162, R21-AA027827, 04622 4, U01-DA055367). NME was supported by NSF DGE-1745038.
About this genetics and mental health research news
author: Leah Shafer
sauce: wasl
contact: Leah Shafer – WUSTL
image: Image credited to Neuroscience News
Original research: Closed access.
“A phenom-wide association study of genetic liability across disabilities in young people genetically similar to individuals in a European reference population.Written by Nicole Karcher et al. natural mental health
abstract
A phenom-wide association study of genetic liability across disabilities in young people genetically similar to individuals in a European reference population.
Aetiological insights into psychopathology are being gained using hypothesis-free methods to explore genetic risks for a wide range of psychopathologies, markers of child psychopathology, and neural structures that may link genetic risks and outcomes. could be obtained by identifying associations with phenotypes measured during adolescence, including both intermediate phenotypes.
Here we conducted an exploratory phenomenon-wide association study (phenotype). n= 1,271–1,697) Polygenic risk scores (PRS) for a wide range of psychopathology (i.e., obsessive-compulsive, psychotic, neurodevelopmental, and internalizing) in youth most genetically similar to individuals in European reference populations (n= 5,556; 9 to 13 years of age) who completed baseline and/or 2-year follow-up of the ongoing Adolescent Brain and Cognitive Development Study.
We found that neurodevelopmental and internalized PRS were significantly associated with phenotypes across multiple domains (neurodevelopmental, 190 and 214 (after pruning correlated phenotypes at one time point, 147 and 165)). r2 0.6); for internalizing, the phenotypes were 124 and 183 (93 and 131 after pruning) at baseline and 2-year follow-up, respectively), whereas after Bonferroni correction, obsessive-compulsive and psychotic PRS were 0, respectively. and 2 showed a significant association.
Obsessive-compulsive, psychotic, and neurodevelopmental PRS were further associated with brain structural indicators, and there was little evidence that brain structure was indirectly associated with PRS and 2-year follow-up outcomes.
Genetic variants that influence risk for psychopathology are widely manifested in behavior, psychopathological symptoms, and associated risk factors during middle childhood and early adolescence.
