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 over 14,000 adolescents from two major cohorts, researchers identified distinct trajectories of depressive symptoms and linked these patterns to genetic risks shared 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. Depression rates significantly increase 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 depression trajectories in adolescents, providing insights into the nature and etiology of adolescent depression.
“Depression presents itself differently both between and within individuals over time. We know that depression is influenced by both genetic and environmental factors. I am interested in how the genetic risk of psychiatric traits contributes to these heterogeneous patterns of depression symptoms across adolescent development,” explained study author Poppy Z. Grimes, a PhD student at the Centre for Clinical Brain Sciences at the University of Edinburgh.
The researchers conducted their study using data from two large adolescent cohorts: 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 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 of longitudinal data on depression symptoms and genetic information.
To measure depression symptoms, the researchers used validated self-report scales specific to each cohort. In the ABCD study, they utilized 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 depression 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 these genetic data to analyze the shared genetic risk, referred to as the genetic p-factor, which represents the overall genetic predisposition to psychiatric conditions.
The researchers applied growth mixture modeling (GMM) to identify different trajectories of depression symptoms over time. This method allowed them to classify individuals into subgroups based on their depression symptom patterns. They identified four main trajectories across both cohorts: stable low, increasing, decreasing, and adolescent persistent.
The majority of adolescents fell into the stable low group, which exhibited few or no depressive symptoms over time. The other three groups showed varying patterns of depression symptoms, with the adolescent persistent group experiencing high and consistent levels of depression.
The study’s findings revealed that the combined genetic risk for multiple psychiatric conditions was strongly associated with the persistent depression trajectory. This combined risk, or genetic p-factor, had a stronger association with depression trajectories than individual genetic risks for specific conditions like 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 issues.
“Our study showed that an individual’s genetic risk for multiple psychiatric conditions (depression, anxiety, neuroticism, bipolar, schizophrenia, autism, ADHD) all contribute to their longitudinal pattern of depression symptoms,” Grimes told PsyPost. “This means that varying levels of genetic risk to ‘general psychopathology’ could potentially predict the trajectory of depression symptoms over time. People with the most severe depression symptoms have very high combined genetic risk among these traits. Whereas people who experience more fluctuating symptoms over their teenage years might be more impacted by environmental factors.”
The increasing trajectory group consisted of adolescents who began with relatively low levels of depression 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 cohort. In the ALSPAC cohort, the increasing trajectory was linked to genetic risks for ASD, neuroticism, and depression. These less consistent associations suggest that adolescents in the increasing trajectory group may have a combination of genetic predisposition and environmental risk that makes them more susceptible to developing higher levels of depression symptoms as they age.
On the other hand, the decreasing trajectory group included adolescents who started with high levels of depression symptoms that diminished over time. This group exhibited strong associations with genetic risk for neurodevelopmental conditions like ADHD and ASD in both cohorts. In the ABCD cohort, the decreasing trajectory was also associated with polygenic risk for depression and neuroticism. In the ALSPAC cohort, this trajectory was additionally linked to anxiety and depression.
“Interestingly, we found that the decreasing pattern of depression symptoms (i.e. starting with high symptoms at ~10 years old and diminishing to low symptoms by mid-late adolescence) was strongly associated with genetic risk for neurodevelopmental conditions (autism and ADHD). We discuss that this could potentially indicate an early onset of depressive symptoms that aligns with the onset or diagnosis of neurodevelopmental conditions,” Grimes explained. “These individuals then may subsequently overcome early depressive symptoms as they are supported with, manage and understand their neurodivergence. However, this will need further investigation to substantiate.”
But the study, like all research, includes some limitations. The study took steps to generalise to non-European ancestries. The authors used GWAS data for depression in African, East Asian and Hispanic ancestries to test depression genetic risk with the trajectories in the diverse ABCD cohort. However, GWAS for other psychiatric conditions was less available meaning they couldn’t test for general psychopathological risk, limiting the generalizability of the results to other ethnic groups. The weak findings highlights the need for more diverse populations to be included in both GWAS studies and large birth cohorts to ensure that findings are applicable across different genetic backgrounds.
In addition, participant attrition over time is a common issue in longitudinal studies, and while the researchers used statistical methods to account for missing data, this could still influence the findings.
“All longitudinal data is subject to attrition (participant drop-out),” Grimes noted. “As we collect more data over time, we see more dropouts with participants not completing the follow-up. So, we have many people completing questionnaires early in the study but fewer later on.”
“This can bias results, especially as we know people with severe depression are less likely to complete follow-up questionnaires. However, we ran lots of sensitivity analyses with different subsets of our samples and found the same consistency in our results suggesting they are robust. We also replicated all our results in two large cohorts, further strengthening our conclusions.”
Nevertheless, the study highlights the importance of considering shared genetic risk across multiple psychiatric conditions to understand the development of depression during adolescence. Looking forward, Grimes aims to understand how depression symptoms change and interact over time, as well as focusing on genetic factors to improve prediction and treatment for adolescent depression.
“My continuing research will explore the longitudinal dynamics of depression symptoms,” she said. “I am interested in the idea that depression is a complex dynamic system with symptoms interacting over time, moving from unstable to stable states. I am currently looking at changes in symptom networks over time which aligns with the work on trajectories we have done here.”
“On the genomics front, I am looking to determine 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 Adolescent Depression Trajectories 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 S. F. Kwong.
