Researchers are investigating the various behavioral, environmental, and neural elements that may reveal how genetic risks for mental health issues are seen in young people.
At Washington University in St. Louis, researchers are taking a comprehensive approach to explore how genetic influences relate to youth behavior. They are casting a wide net to gather all measurable traits, behaviors, and environments that define us, aiming to uncover connections between these factors and the genetic components associated with mental health risks.
This innovative method has uncovered significant new information about factors tied to genetic risks for psychological problems, including stress from life events and the impact of screen time. Although the findings, which appear in Nature Mental Health, cannot determine causation, they offer promising insights into understanding the development of mental health disorders during adolescence.
“We’re capturing all the diverse aspects here,” explained Nicole Karcher, an assistant professor of psychiatry at WashU Medicine, drawing an analogy between their genetic assessment tools and extensive fishing efforts.
“Now we can sort through our discoveries, and the next steps involve evaluating how meaningful these findings are in terms of mitigating risks for mental health problems.”
A groundbreaking strategy to identify risk factors
Much of our understanding of the relationship between genetics and behavior stems from Genome-wide Association Studies (GWAS). These studies pinpoint connections between specific genetic variants in the genome and various traits or characteristics, known as phenotypes, which can include everything from physical traits to psychiatric conditions such as depression and anxiety.
Many behavioral disorders share genetic correlations. Therefore, findings from a GWAS looking for genetic links to depression might also indicate genetic ties to related conditions like anxiety.
“We recognize that no single behavioral characteristic will solely correlate with genetic risk, which prompted us to adopt a more open and data-oriented approach to harness the information available in extensive datasets,” noted Karcher.
This approach aims to identify both expected connections between genetic risk and psychiatric symptoms as well as new associations that could provide deeper understanding of how the risk for mental disorders develops.
To achieve this, senior author Karcher and lead author Sarah Paul, a graduate student in Ryan Bogdan’s Behavioral Research and Imaging Neurogenetics Laboratory at Arts & Sciences, performed a phenome-wide association study (PheWAS) that reverses the typical GWAS approach.
While GWAS typically starts with a psychiatric condition to find related genetic variants, their PheWAS began with known genetic variants associated with mental health issues and explored those links to a wide array of measured factors, including behaviors, symptoms, environments, health problems, and other phenotypes, using approximately 1,300 to 1,700 phenotypes from the Adolescent Brain Cognitive Development (ABCD) Study.
“We took a very expansive perspective,” Paul said, describing different phenotypes as encompassing anything from impulsivity and troubling behaviors or unusual experiences to screen time and caffeine intake.
Imagine this as fishing with a large net.
This approach aims to discover connections between genetic tendencies and potentially alterable risk factors that could be addressed before mental health issues develop, according to Bogdan, the Dean’s Distinguished Professor of Psychological & Brain Sciences in Arts & Sciences.
Findings from their study
The outcomes of the PheWAS revealed some unexpected results while confirming existing knowledge about genetic risks and the associated behaviors tied to youth mental health disorders.
The WashU team synthesized results from 11 GWAS to create four major genetic risk categories, or polygenic scores: neurodevelopmental, internalizing (e.g., depression, anxiety), compulsive, and psychotic. Here are a few associations they discovered in these categories:
*Genetic risk for neurodevelopmental issues (primarily ADHD, Autism Spectrum Disorder, Major Depressive Disorder, and problematic alcohol use) was linked to around 190 phenotypes, including inattention, impulsivity, overall screen time, sleep problems, and unusual experiences. They also noted that environmental factors like higher crime rates in neighborhoods and less parental supervision are linked to this genetic risk.
*Genetic risk for internalizing behaviors (including Major Depressive Disorder, Generalized Anxiety Disorder, PTSD, and problematic alcohol use) broadly connected to around 120 phenotypes, such as depression, stressful events in life, unusual experiences, and screen time.
*Psychotic risk (primarily related to Schizophrenia and Bipolar Disorder) showed limited phenotype links, primarily relating to reduced school engagement and increased consumption of energy drinks.
Karcher expressed surprise that “genetic vulnerability” to mental health issues might emerge through potentially changeable behaviors during childhood and early adolescence.
The research examined numerous variables potentially tied to genetic risk, highlighting many associations—especially the link between neurodevelopmental genetic risk and screen time.
“The PheWAS succeeded in revealing these clusters of connections that might have otherwise gone unnoticed,” she stated.
One of those clusters highlighted the correlation between genetic risk for psychotic disorders and the consumption of energy drinks. These studies examine correlations, not causations, so they cannot establish that energy drink intake directly causes psychotic disorders. It’s possible that genetic factors predispose individuals to both psychotic disorders and a greater likelihood of consuming caffeinated drinks.
A similar situation appears valid regarding the strong relationship between screen time and neurodevelopmental risk.
The purpose of the PheWAS isn’t to clarify causation details, but instead to provide a broad overview of these associations from a high-level perspective, Karcher noted.
As time progresses and the ABCD participants mature along with the growing diversity of genomic databases, we will gain further insights.
“Tracking these young individuals into early adulthood will enhance our understanding of how genetic risk links to screen time, mental health issues, symptoms, and sleep during the transition from adolescence to early adulthood,” said Paul. “This will contribute to a more comprehensive view of how the connections between genetic risk and behavior evolve or remain stable over time.”
Overall, this research demonstrates how the PheWAS method can help identify potential targets for future preventive and early intervention measures. This study highlights several modifiable factors, such as screen time and energy drink consumption, that could serve as early signs for reducing the likelihood of developing mental health issues.
Past genome-wide research on psychiatric disorders often utilized data from individuals closely resembling European reference populations, with relatively few well-powered GWAS for other populations globally. Therefore, a significant limitation of this study was that, due to its reliance on data from European ancestry, only ABCD data from this group could be incorporated into the PheWAS.
“This significantly restricts the applicability of our findings,” Paul pointed out. “However, as more GWAS data becomes accessible from diverse populations and advanced polygenic score methods are developed, we should be able to broaden the participant pool to be more representative.”
