Attention-deficit/hyperactivity disorder (ADHD) and major depressive disorder (MDD) are highly prevalent mental health conditions with many overlapping symptoms (Biederman, 2005). The idea that ADHD shares features with other psychiatric disorders is well-established, with early discussions dating back to Millberger et al. (1995). Some of the key shared symptoms between ADHD and MDD include:
- Difficulty with focus and attention
- Emotional dysregulation
- Low motivation and fatigue
- Irritability
- Low self-esteem
- Sleep disturbances
ADHD is typically diagnosed in childhood, with prevalence estimates ranging from 5–10% in youths and 2–5% in adults. In contrast, MDD is usually diagnosed later in life, with an approximate lifetime prevalence of 12% in adolescents and 16% in adults (Faraone et al., 2021; Fernandez-Pujals et al., 2015). ADHD is also frequently associated with psychiatric comorbidities and longitudinal studies report high rates of antisocial and substance use disorders in individuals with ADHD (Reale et al., 2017). ADHD and MDD frequently co-occur. A substantial genetic correlation between ADHD and MDD has been reported (Powell et al., 2021). However, while this genetic connection is well-established, few prospective studies have directly examined whether having ADHD increases the likelihood of developing MDD later in life. Many existing studies suffer from methodological limitations or small sample sizes, leaving this question only partially addressed.
In their recent publication, Garcia-Argibay et al. (2024) aimed to assess whether ADHD causally increases the risk of subsequent MDD diagnoses.
ADHD and depression frequently co-occur, and research suggests that as well as an overlap in reported symptoms, there may also be an underlying genetic overlap between these two disorders.
Methods
The author applied a comprehensive three-pronged genetically informed approach, controlling for sex and birth year in all analyses:
1. Longitudinal sibling cohort analysis
A Swedish sibling cohort of 1,018,489 individuals was analysed, controlling for key confounders such as age, sex, and education level. By leveraging sibling comparisons, this analysis helped isolate the genetic and shared environmental effects relevant to ADHD and MDD while reducing bias introduced by confounders.
2. Child and adolescent twin cohort analysis
Using data from the Child and Adolescent Twin Study in Sweden (CATSS), a co-twin control analysis was conducted, a method designed to assess causality by comparing twins discordant for ADHD exposure. Specifically, they investigated whether the twin diagnosed with ADHD had a higher likelihood of developing MDD compared to their non-exposed co-twin, while controlling for shared genetic and environmental influences.
3. Mendelian randomization (MR) analysis
MR was used to leverage genome-wide association study (GWAS) summary statistics, which link common genetic variations to specific traits, to explore whether ADHD plays a causal role in the development of MDD. By using genetic variants as instrumental variables, MR analysis helps mitigate the influence of confounding factors that often affect observational studies.
Results
1. Longitudinal sibling cohort
The sibling cohort was nearly evenly split between biological males (51%) and biological females (49%), with a median age of 14 years at their last follow-up. The prevalence of ADHD and depression were as follows:
- 3.53% of individuals had an ADHD diagnosis
- 1.20% were diagnosed with depression
- Depression rates were significantly higher among those with ADHD
- 12.07 events per 10,000 person-years in individuals without ADHD
- 62.37 events per 10,000 person-years in individuals with ADHD
The big takeaway? At the population level, individuals diagnosed with ADHD had a 7.4 times higher risk of developing depression compared to those without ADHD. This risk remained elevated even after adjusting for shared familial factors in sibling-stratified analyses, though it was slightly reduced.
2. Child and adolescent twin cohort
The Child and Adolescent Twin Cohort in Sweden included 16,477 twins (5,084 monozygotic [MZ] and 11,393 dizygotic [DZ]) born between 1992 and 2004. The sample consisted of 53% biological females and 47% biological males.
The findings? In monozygotic twins, ADHD factor scores—based on parental reports—were linked to higher depression scores at ages 15 and 18. Even after accounting for unmeasured shared familial factors, the association remained large, though somewhat weaker.
This suggests that while shared genetics and family environment play a role, ADHD itself still uniquely contributes to depression risk.
3. Mendelian randomization (MR)
Finally, researchers turned to MR to test whether ADHD might cause depression at a genetic level. They found a moderate-to-strong genetic correlation between ADHD and major depressive disorder (rg = 0.52). MR analyses also provided evidence of a causal relationship, with ADHD genetic liability increasing the risk of depression (OR = 1.15). Using a stricter MDD definition led to slightly stronger results (OR = 1.26).
Individuals diagnosed with ADHD had a 7.4 times higher risk of developing depression compared to those without ADHD and MR analyses suggest this relationship may indeed be causal.
Conclusions
Taken together, these findings paint a compelling picture:
- ADHD is strongly associated with a higher risk of depression, as seen in both population-wide and sibling-controlled analyses.
- Genetics and shared family environments contribute to this link, but ADHD itself appears to be a driving factor.
- Genetic analyses suggest a causal relationship, reinforcing the idea that ADHD is not just correlated with depression—it may increase the risk.
This research highlights the importance of early intervention and mental health support for individuals with ADHD. Understanding these connections can help clinicians and researchers develop better prevention and treatment strategies, ultimately improving long-term outcomes for those affected.
Understanding the connection between ADHD and depression can help us develop better prevention and treatment strategies, ultimately improving long-term outcomes for those affected.
Strengths and limitations
Like any well-designed research, this study comes with notable strengths as well as some limitations. By using a three-way, genetically-informed design, the authors were able to examine the potential causal relationship between ADHD and major depressive disorder (MDD) from multiple angles.
Key strengths
One major advantage of this study is its longitudinal design, which allowed the authors to account for shared but unmeasured familial factors in their sibling analysis. This means they could better separate genetic influences from environmental ones when evaluating the link between ADHD and MDD and assess temporality (i.e., the order in which events occurred).
In the twin study, standardised and well-validated clinical scales were used, ensuring a reliable assessment of symptoms. Additionally, the MR analysis leveraged the largest and most recent GWAS for ADHD, further strengthening the case for a causal relationship between ADHD and MDD.
A frequent challenge in genetic studies on ADHD is the overrepresentation of males, since ADHD tends to be underdiagnosed in females. This can result in underpowered analyses when investigating sex-specific effects. However, this study was more balanced in sex representation (51% males, 49% females), helping to mitigate this issue.
Limitations to consider
The authors used symptom-based questionnaires to diagnose cases and this could have led to some misclassification between ADHD and MDD. Since these disorders share overlapping symptoms, the observed associations may have been inflated due to measurement errors.
There are several generalisability issues also to consider:
- The study focused on young/adolescent populations, which means the findings may not necessarily apply to adults.
- The cohorts were restricted to European (specifically Swedish) populations, limiting the ability to generalise results to other populations.
- The participants ranged from early childhood to adolescence, potentially missing critical developmental stages that could further shape the ADHD-MDD relationship.
- Higher-functioning individuals may have been more likely to participate and less likely to drop out, skewing the findings (i.e., selection bias).
A final limitation relates to the “streetlight effect”—the tendency to find what one is specifically looking for, even if the broader reality is more complex (Evans et al., 2020). While this study tested the causal link between ADHD and MDD, expanding the analysis to a wider range of mental health conditions might reveal that the effect is not as specific as initially thought.
Research suggests that many mental health disorders share transdiagnostic features (Caspi & Moffitt, 2018; Sprooten et al., 2022). Over time, specific correlations once thought to be unique have been found to apply across multiple disorders. This raises an important question:
Is the ADHD-MDD relationship truly distinct, or part of a broader pattern of psychiatric comorbidity?
A three-way, genetically informed design examined the potential causal relationship between ADHD and MDD from multiple angles. But is the ADHD-MDD relationship truly distinct, or part of a broader pattern of psychiatric comorbidity?
Implications for practice
Studies establishing a genetic relationship between ADHD and MDD are not novel. However, these findings underscore the need for effective treatment and assessment of ADHD and a requirement for a deeper understanding of the potential causal mechanisms linking ADHD and MDD. Establishing this relationship can help inform the management and assessment of individuals with ADHD and could lead to an improvement in symptoms and overall well-being for individuals affected by ADHD.
One of the key insights from this study is that the genetic relationship between ADHD and MDD cannot be fully explained by shared genetic and environmental factors. This highlights the role of unique environmental influences, which, crucially, are often modifiable and actionable.
The implications for clinical practice and future research can be distilled into two key recommendations:
1. Expanding the Scope of Psychopathology Research
Traditional research has often focused narrowly on pairwise disorder comparisons, missing broader patterns of mental health interconnectivity. A more comprehensive, multidimensional approach—one that balances both depth and breadth of phenotyping—is needed to capture the full complexity of behavioural and psychiatric traits. Future studies should embrace wider-ranging data collection across multiple disorders rather than limiting themselves to rigid diagnostic labels.
2. Emphasising Modifiable Environmental Factors
While genetic factors play a significant role, environmental influences actively shape the development and progression of mental health conditions. Several potential modifiable pathways warrant further investigation, including:
- Parental treatment differences
- Traumatic experiences
- Peer relationships
- Unique life events not shared with siblings
- Chronic stressors
- Substance misuse-related experiences
Identifying and targeting these factors could lead to more effective prevention and intervention strategies.
Regardless of the lens used—genetic, neuroimaging, sociological, or cultural—understanding the inner workings of mental health disorders remains immensely complex. A truly integrative, multidisciplinary approach is essential for refining psychiatric classification systems and translating research findings into clinically meaningful tools. By adopting more dynamic, biologically and environmentally informed models, the field has the potential to develop more effective, personalized treatment strategies—ultimately improving mental health outcomes for a diverse range of individuals.
By adopting more dynamic, biologically and environmentally informed models, we have the potential to develop more effective, personalized treatment strategies that will ultimately improve health outcomes for a diverse range of individuals.
Statement of interests
Tim is a PhD candidate with King’s College London and A*STAR Singapore. He researches the genetic relationship between major depressive disorder, schizophrenia and cognitive health and is not involved with research groups investigating the relationship between ADHD and MDD. He has no conflicts of interest to report.
Links
Primary paper
Garcia-Argibay, M., Brikell, I., Thapar, A., Lichtenstein, P., Lundström, S., Demontis, D., & Larsson, H. (2024). Attention-Deficit/Hyperactivity Disorder and Major Depressive Disorder: Evidence From Multiple Genetically Informed Designs. Biological Psychiatry, 95(5), 444-452. https://doi.org/10.1016/j.biopsych.2023.07.017
Other references
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Evans B. J. (2020). The Streetlight Effect: Regulating Genomics Where the Light Is. The Journal of law, medicine & ethics : a journal of the American Society of Law, Medicine & Ethics, 48(1), 105–118. https://doi.org/10.1177/1073110520916998
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