The study harnesses the formidable power of polygenic scores (PGSs)—quantitative indices capturing the cumulative effect of myriad genetic variants linked to various traits and disorders. Traditional research often concentrated on individual genetic risks within children or explored parent-child genetic resemblance superficially. However, Chegeni and colleagues embarked on a nuanced journey, examining both direct genetic contributions from children’s own genomes and indirect genetic influences derived from their parents’ genomes. This dual perspective acknowledges that parental genetics shape offspring environments subtly but significantly, shaping mental health outcomes.

Employing data drawn from an expansive Norwegian cohort—the Mother, Father, and Child Cohort Study—this team analyzed genetic and phenotypic information from 9,314 parent–child triads. By integrating 90 distinct polygenic scores encompassing both the child and parents, they created an ambitious multi-variable model to predict depression and anxiety symptoms measured at ages 8 and 14. This approach is notable for its scalability and depth, as it accounts for a broad spectrum of traits potentially influencing mental health beyond the traditionally studied psychiatric conditions.

Central to their analytical strategy was the application of elastic net regression, a sophisticated machine learning method adept at handling multicollinearity in datasets with vast predictor numbers. This method allowed the identification of pivotal genetic predictors amidst a complex web of genomic contributions. Importantly, the analysis incorporated not only main effects of each PGS but also interaction terms between child and parent PGSs, capturing the dynamic interplay across generations.

Findings reveal a multidimensional genetic architecture governing internalizing problems, with predictive accuracy improving markedly with age. At 14 years, models explained up to 2.7% of the variance in depression symptomatology and approximately 1.2% for anxiety, figures reflecting the polygenic and multifactorial nature of these disorders. Although seemingly modest, these percentages are substantial given the multitude of environmental and genetic factors influencing mental health.

Intriguingly, child polygenic scores for attention deficit hyperactivity disorder (ADHD) emerged as robust predictors for depressive and anxiety symptoms. This link accentuates neurodevelopmental pathways intersecting with emotional regulation and vulnerability, suggesting overlapping genetic etiologies between ADHD and internalizing psychopathology. Additionally, child polygenic profiles associated with cognitive skills and well-being spectrum traits also displayed predictive value, underscoring mental health’s deep interconnection with cognitive and positive psychological factors.

Parental genetics contributed compelling insights too. Specifically, maternal polygenic scores related to smoking behavior and cognitive skills held predictive importance. Maternal smoking PGSs likely proxy environmental effects related to prenatal and early-life exposures, while maternal cognitive skill-related genetics may influence parenting behaviors and household cognitive climates, thereby indirectly modulating offspring mental health risk. Furthermore, paternal well-being spectrum polygenic scores were implicated, hinting at the father’s psychological profile playing an influential role in shaping the child’s emotional development.

The inclusion of these diverse parental genetic traits profoundly enriches our understanding of intergenerational genetic risk transmission. It moves beyond simplistic heritability estimates to expose the nuanced pathways through which parental genetics unfold effects—both through genetic inheritance and environmental shaping—across crucial developmental windows.

This study also shines a spotlight on developmental changes, illustrating that genetic predictors’ influence on internalizing symptoms evolves over time. The increasing predictive power at age 14 relative to age 8 may reflect gene-environment interplay modulated by adolescence’s dynamic social and biological transformations. It underscores adolescence as a sensitive period when genetic vulnerabilities more prominently translate into observable psychopathology.

Moreover, the methodology’s comprehensiveness—covering hundreds of polygenic scores and their interactions—sets a new benchmark for psychiatric genetic research. It paves the way for more refined predictive models that account for familial genetic contexts rather than isolated genomic snapshots. Such advancements have vital implications for early identification frameworks and preventive interventions tailored to individual risk profiles.

Despite these promising insights, the relatively small variance explained also signals that substantial environmental, epigenetic, and stochastic factors remain to be integrated to fully elucidate internalizing disorders’ pathogenesis. Future research could benefit from incorporating longitudinal environmental measures, gene-by-environment interactions, and epigenomic data to portray a holistic risk landscape.

In clinical translation terms, this research suggests that parental genetic screenings alongside child genomic profiling might enhance the predictive identification of children at heightened risk for anxiety and depression. It offers a scaffold for personalized approaches in mental health prevention, advocating for family-centered genetic and psychosocial assessments.

By unraveling the intertwined genetic threads spanning generations, Chegeni et al.’s work eloquently underscores the importance of viewing child mental health through a multifaceted, dynamic, and developmental lens. It challenges reductionist paradigms and beckons a future where integrative genetic models foster tailored, timely, and effective mental health interventions.

In essence, these findings herald a transformative step forward in developmental psychopathology, embracing complexity to unravel the genetic mosaic of internalizing problems. As the field marches towards precision psychiatry, the integration of direct and indirect genetic effects exemplifies the sophisticated toolkit researchers need to dissect the biology of mental health disorders that shape the lives of millions globally.

Subject of Research: Direct and indirect genetic effects from parents and children influencing internalizing mental health problems during childhood and adolescence.

Article Title: Direct and indirect parental genetic effects on offspring susceptibility to internalizing problems across development.

Article References:
Chegeni, R., Nes, R.B., Cheesman, R. et al. Direct and indirect parental genetic effects on offspring susceptibility to internalizing problems across development. Nat. Mental Health (2026). https://doi.org/10.1038/s44220-026-00619-3

Image Credits: AI Generated

DOI: https://doi.org/10.1038/s44220-026-00619-3

Polygenic scores, which aggregate the effects of multiple genetic variants, have garnered attention as potential indicators of predispositions to various mental health disorders. They have been linked to many behavioral and psychological outcomes, providing a framework for understanding how genetic makeup can influence one’s response to different therapeutic modalities. In the current study, the authors sought to explore how these polygenic scores might predict changes in symptom severity following ICBT, a form of therapy that has gained popularity due to its accessibility and efficacy.

The research team, led by renowned psychologists including Bäckman, Wallert, and Halvorsen, postulates that an individual’s genetic profile may significantly influence their response to ICBT. The underlying hypothesis posits that certain genetic markers could correlate with better resilience or susceptibility to mental health disorders and therapeutic responses. By integrating genetic data with psychological assessments, this study offers a more comprehensive understanding of the factors at play in mental health treatment.

Internet-delivered cognitive behavioral therapy stands out in the landscape of mental health interventions due to its convenience and adaptability. With platforms that allow individuals to engage with therapeutic exercises and content at their own pace, ICBT has proven particularly effective for those who may face barriers to traditional in-person therapy. However, there’s a growing recognition that treatment responses can vary widely among individuals, and the current research addresses the possibility that genetics may play a crucial role in these differences.

The study employs a robust methodology, analyzing data from a substantial cohort of participants who received ICBT for depression or anxiety. By measuring participant outcomes through standardized scales for symptom severity, the researchers were able to track changes over time, correlating these shifts with the participants’ polygenic scores. Through this meticulously designed research framework, the authors provided compelling evidence that genetic predispositions could indeed inform the effectiveness of therapeutic interventions.

As mental health researchers continue to advocate for more personalized approaches to treatment, findings from this study underscore the importance of integrating genomic data into therapeutic strategies. The implications extend beyond academic curiosity; they highlight the potential for improving treatment efficacy by tailoring interventions based on genetic profiles. For practitioners, this could lead to more individualized treatment plans that align with a patient’s biological and psychological makeup.

Moreover, understanding the role of polygenic scores in ICBT responses may inform future research directions. For instance, projects aimed at identifying specific genetic variants associated with therapy outcomes could pave the way for more targeted interventions. Such insights could ultimately catalyze advancements in precision medicine, offering hope to millions grappling with depression and anxiety who might not find relief in conventional therapies.

While the findings are promising, the researchers also emphasize the complexity of their implications. Mental health treatment is influenced by multifaceted factors, including environmental, psychological, and social variables. Therefore, while polygenic scores provide significant insights, they are but one piece of the intricate puzzle of human psychology and mental health. Continued research is essential to unravel these interconnections, potentially leading to a more holistic approach to treatment.

The study inevitably stokes discussions about ethics in genetic research, particularly in how genetic information is used within the context of mental health care. As we venture further into the realm of genetics and personalized medicine, it is crucial to establish ethical guidelines that protect individuals’ privacy while promoting innovation in therapeutic approaches.

Overall, this cutting-edge research elevates our understanding of mental health treatment by spotlighting the interplay between genetics and therapeutic efficacy. The potential for polygenic scores to improve treatment outcomes could resonate widely, inspiring further studies and offering new hope for individuals navigating the often-challenging landscapes of anxiety and depression.

The endeavor of linking genetic data with therapeutic outcomes is not merely an academic curiosity; it is a tangible step toward bridging the gap between genetics and psychological resilience. As society grapples with increasing rates of mental illness, such innovative research holds the promise of unlocking new pathways to healing. The authors’ insights challenge us to rethink how we approach mental health and the tools available to facilitate recovery and well-being in the ever-evolving landscape of psychological care.

In conclusion, the intersection of genetics and mental health therapy has opened a veritable treasure trove of possibilities for improving interventions and reshaping how therapy is approached. As this research highlights, there is much to learn about how our genes influence our healing journeys, and the future of mental health care may very well be rooted in these revelations. This study not only represents a significant stride toward personalized therapy but also signals an ongoing commitment to understanding the complexities of human behavior and health in a holistic manner.

Subject of Research: The relationship between polygenic scores and symptom severity changes after internet-delivered cognitive behavioral therapy for depression and anxiety.

Article Title: Polygenic scores and symptom severity change after internet-delivered cognitive behaviour therapy for depression and anxiety.

Article References:
Bäckman, J., Wallert, J., Halvorsen, M. et al. Polygenic scores and symptom severity change after internet-delivered cognitive behaviour therapy for depression and anxiety.
Discov Ment Health 5, 82 (2025). https://doi.org/10.1007/s44192-025-00213-6

Image Credits: AI Generated

DOI:

Keywords: Polygenic scores, internet-delivered cognitive behavioral therapy, depression, anxiety, mental health, personalized treatment, genetic factors, therapeutic response.