Genetic factors predict patterns of adolescent depression

Follow PsyPost on Google News

A recent study published in JAMA Psychiatry has shed new light on how genetic factors contribute to different patterns of depression during adolescence. By analyzing the genetic data of more than 14,000 adolescents from two major cohorts, researchers identified distinct trajectories of depressive symptoms and linked these patterns to shared genetic risks across multiple psychiatric conditions.

Adolescence is a critical period marked by significant brain and body changes, often coinciding with the onset of mental health conditions, including depression. The rate of depression increases significantly between the ages of 13 and 18, and the severity of symptoms tends to be higher compared to adult-onset depression. The new study aimed to explore how shared genetic factors influence the trajectories of adolescent depression, providing insights into the nature and etiology of adolescent depression.

“Depression appears differently both between individuals and within them over time. We know that depression is influenced by genetic and environmental factors. I am interested in how genetic risk of psychiatric traits contributes to these heterogeneous patterns of depressive symptoms across adolescent development,” explained study author Poppy Z. Grimes, a PhD student at the Center for Clinical Brain Sciences at the University of Edinburgh.

The researchers conducted their study using data from two large cohorts of adolescents: the Adolescent Brain and Cognitive Development (ABCD) study and the Avon Longitudinal Study of Parents and Children (ALSPAC). The ABCD study, based in North America, included 11,876 participants aged 9–10 years at baseline, while the ALSPAC study, based in the United Kingdom, included 15,645 children born between 1991 and 1992. These cohorts provided a rich source longitudinal data on depression symptoms and genetic information.

To measure depressive symptoms, the researchers used validated self-report scales specific to each group. In the ABCD study, they used the Brief Problem Monitoring (BPM) scale, which includes a six-item subscale of internalizing symptoms collected every six months. In the ALSPAC study, they used the Short Mood and Feeling Questionnaire (SMFQ), an annual collection of 13 items indicative of clinical depression. These measures allowed the researchers to track changes in depressive symptoms over time.

Genetic data were obtained through genome-wide association studies (GWAS) for seven major psychiatric traits: anxiety, neuroticism, major depressive disorder, attention deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), schizophrenia and bipolar disorder. Using genomic structural equation modeling (GenomicSEM), the researchers combined this genetic data to analyze shared genetic risk, referred to as the genetic factor p, which represents overall genetic predisposition to psychiatric conditions.

The researchers applied growth mixture modeling (GMM) to identify different trajectories of depressive symptoms over time. This method allowed them to classify individuals into subgroups based on their patterns of depressive symptoms. They identified four main trajectories in both groups: low stable, increasing, decreasing, and persistent adolescent.

Most of the teens fell into the low stable group, which showed little or no depressive symptoms over time. The other three groups showed different patterns of depressive symptoms, with the persistent adolescent group experiencing high and sustained levels of depression.

The study findings revealed that combined genetic risk for multiple psychiatric conditions was strongly associated with the ongoing trajectory of depression. This combined risk, or genetic factor p, had a stronger association with depression trajectories than individual genetic risks for specific conditions such as anxiety or ADHD. The persistent depression group showed a significant genetic predisposition to multiple psychiatric disorders, suggesting that these individuals have a higher overall genetic risk for enduring mental health problems.

“Our study showed that an individual’s genetic risk for multiple psychiatric conditions (depression, anxiety, neuroticism, bipolarity, schizophrenia, autism, ADHD) all contribute to their longitudinal pattern of depressive symptoms,” Grimes told PsyPost. “This means that different levels of genetic risk to ‘general psychopathology’ could potentially predict the trajectory of depressive symptoms over time. People with the most severe depressive symptoms have very high combined genetic risk between these While people who experience more fluctuating symptoms during their teenage years may be more influenced by environmental factors.

The ascending trajectory group consisted of adolescents who began with relatively low levels of depressive symptoms that escalated over time. The study found that this group was associated with polygenic risk scores for bipolar disorder, anxiety and depression in the ABCD group. In the ALSPAC cohort, the upward trajectory was associated with genetic risks for ASD, neuroticism, and depression. These less stable associations suggest that adolescents in the upward trajectory group may have a combination of genetic predisposition and environmental risk that makes them more susceptible to developing higher levels of depressive symptoms as they age.

On the other hand, the downward trajectory group included adolescents who started with high levels of depressive symptoms that decreased over time. This group showed strong associations with genetic risk for neurodevelopmental conditions such as ADHD and ASD in both groups. In the ABCD group, the downward trajectory was also associated with polygenic risk for depression and neuroticism. In the ALSPAC group, this trajectory was also associated with anxiety and depression.

“Interestingly, we found that the declining pattern of depressive symptoms (ie, onset with high symptoms at ~10 years of age and decreasing to low symptoms by mid-late adolescence) was strongly associated with genetic risk for neurodevelopmental conditions (autism and ADHD). We argue that this could potentially indicate an early onset of depressive symptoms that coincides with the onset or diagnosis of neurodevelopmental conditions,” Grimes explained. “These individuals can then overcome early depressive symptoms once they are supported, managed, and understood their neurodivergence. However, this will need further investigation to confirm.”

But the study, like all research, includes some limitations. The study took steps to generalize to non-European backgrounds. The authors used GWAS data on depression in African, East Asian, and Hispanic ancestry to test the genetic risk of depression with trajectories in the different ABCD group. However, GWAS for other psychiatric conditions were less available meaning they could not test for overall psychopathological risk, limiting the generalizability of the results to other ethnic groups. The weak findings highlight the need to include more diverse populations in both GWAS studies and large birth cohorts to ensure that findings are applicable across different genetic backgrounds.

In addition, attrition of participants over time is a common issue in longitudinal studies, and while the researchers used statistical methods to account for missing data, this may still affect the findings.

“All longitudinal data are subject to attrition (dropout of participants),” Grimes noted. “As we collect more data over time, we see more dropouts with participants not completing the follow-up. So we have a lot of people filling out the questionnaires at the beginning of the study, but less later on.”

“This could bias the results, especially as we know that people with severe depression are less likely to complete follow-up questionnaires. However, we performed multiple sensitivity analyzes with different subsets of our samples and found the same consistency in our results, suggesting that they are robust. We also replicated all of our results in two large cohorts, further strengthening our conclusions.”

However, the study highlights the importance of considering shared genetic risk across multiple psychiatric conditions in understanding the development of depression during adolescence. Looking ahead, Grimes aims to understand how symptoms of depression change and interact over time, as well as focusing on genetic factors to improve prediction and treatment for adolescent depression.

“My ongoing research will explore the longitudinal dynamics of depressive symptoms,” she said. “I’m interested in the idea that depression is a complex dynamic system with symptoms that interact over time, moving from unstable to stable states. I’m currently looking at changes in symptom networks over time, which match the work on trajectories that we’ve done here.”

“On the genomic front, I’m looking to determine the genetic variants associated with adolescent-onset depression. Using genome-wide association, we hope to uncover specific variants for downstream causal analysis, clinical risk prediction, and pharmacological targets.

The study, “Genetic Architectures of Trajectories of Adolescent Depression in 2 Longitudinal Population Cohorts,” was authored by Poppy Z. Grimes, Mark J. Adams, Gladi Thng, Amelia J. Edmonson-Stait, Yi Lu, Andrew McIntosh, Breda Cullen, Henrik Larsson, Heather C. Whalley, and Alex SF Kwong.

#Genetic #factors #predict #patterns #adolescent #depression
Image Source : www.psypost.org

Leave a Comment

Your email address will not be published. Required fields are marked *

Scroll to Top