Over the past several decades, the global mental health landscape has witnessed a notable rise in the diagnosis rates of various psychiatric disorders, including schizophrenia, depression, autism spectrum disorder (ASD), and attention deficit hyperactivity disorder (ADHD). These increases, however, have puzzled clinicians and researchers alike, prompting questions about the underlying genetic and environmental factors contributing to such trends. Intriguingly, while many studies have examined the epidemiological shifts in psychiatric illness, few have ventured into exploring whether the genetic predisposition—or polygenic burden—associated with these conditions has experienced temporal changes within affected populations. Addressing this gap, a recent groundbreaking study leveraging data from over 100,000 individuals in Denmark sheds new light on the evolving genetic architecture of psychiatric disorders across nearly three decades of birth cohorts.
The Danish iPSYCH2015 study, a large-scale population-based genetic epidemiology project, provides a fertile resource for investigating such complex questions. By encompassing individuals born from 1981 through 2008 and tracking psychiatric diagnoses from 1994 to 2015, this unique cohort offers unprecedented insight into temporal shifts in genetic risk burden. In this comprehensive analysis, researchers integrated polygenic scores—quantitative measures derived from millions of common genetic variants collectively contributing to disorder susceptibility—to reveal nuanced patterns in how these scores have fluctuated across birth cohorts within diagnosed case populations and a population-based subcohort serving as controls.
One of the study’s most striking findings is that the average polygenic scores among individuals drawn from the general population (the random subcohort) have remained remarkably stable over time. This finding suggests that the underlying genetic predispositions to psychiatric disorders in the general Danish population have not shifted substantially, at least in aggregate, across the 27 years spanning the birth cohorts examined. However, among diagnosed individuals, the narrative unfolds quite differently. For schizophrenia, depression, and autism, the polygenic burden has demonstrably decreased over time, with the steepest decline observed in schizophrenia cases. This temporal reduction in polygenic risk within case groups hints towards evolving environmental or diagnostic factors influencing disease manifestation, even as genetic risk appears to be waning among those being diagnosed.
Delving deeper into schizophrenia, the data expose a decline of approximately 0.13 standard deviations in polygenic score per decade within diagnosed individuals. This decrease carries significant implications, as it suggests that individuals developing schizophrenia in more recent birth cohorts carry a measurably lower load of common genetic risk variants than those born earlier. Remarkably, these findings complicate the prevailing narrative that rising incidence rates for psychiatric disorders purely reflect increased genetic vulnerability. Instead, they point to a dynamic interplay whereby environmental changes, diagnostic evolutions, or other non-genetic factors may be increasingly shaping the schizophrenia phenotype as time progresses.
In contrast to schizophrenia, depression and autism also reflect decreases in polygenic score burden but at more moderate levels—about 0.06 and 0.08 standard deviations per decade, respectively. ADHD presents a somewhat more nuanced picture: the polygenic scores within cases show minimal change and a wide confidence interval that even overlaps with no effect. Such divergence among psychiatric disorders underscores the heterogeneity in both genetic architecture and how external influences may modulate these disorders’ penetrance across generational spans.
An additional layer to this research involves analyzing how the polygenic scores’ power to predict psychiatric diagnosis—the hazard ratio for developing a disorder per standard deviation increase in risk score—has shifted over these birth cohorts. Aligning with the downward trend observed for schizophrenia polygenic scores, the study reveals a concomitant decline in their predictive performance for this disorder. For depression, autism, and ADHD, however, the hazard ratios have largely remained stable. This suggests that for schizophrenia, the evolving genetic landscape affects not only the average polygenic risk in cases but also the extent to which genetics informs individual susceptibility, a revelation with profound consequences for future risk prediction models.
Complementing these analyses, the researchers estimated the number of additional cases attributable to a one-standard-deviation increase in polygenic score over time. Interestingly, while schizophrenia and depression exhibited decreasing numbers of excess cases per unit increase in risk score, autism and ADHD showed the opposite trend, with increasing case numbers associated with polygenic burden increments. This intriguing pattern implies that for neurodevelopmental disorders like autism and ADHD, genetic risk may be gaining relative prominence in disease onset within newer cohorts, juxtaposed against a waning genetic influence in schizophrenia observed across the same timespan.
These cumulative findings compel a reevaluation of established assumptions concerning psychiatric disorder risk. The observed decline in polygenic burden accompanying stable or increasing incidence rates hints towards stronger contributions from environmental exposures, changes in diagnostic criteria, healthcare access, or social factors influencing detection rates. This dynamic underscores the necessity of integrating genetic data with nuanced environmental and epidemiological contexts to holistically understand psychiatric disorders.
Moreover, the temporal evolution in genetic architecture, particularly for schizophrenia, may portent crucial adjustments to how polygenic risk scores are applied clinically. Traditionally heralded as promising tools for stratifying individuals by genetic risk and tailoring interventions, the diminishing polygenic burden and predictive accuracy in recent birth cohorts warn against overreliance on static genetic models. Incorporating temporal trends and population shifts will be vital for refining these models’ utility and ensuring equitable application.
The study also raises fascinating questions about the biological mechanisms underpinning these temporal trends. Could environmental risk factors such as urbanization, prenatal exposures, or lifestyle changes be interacting with the genetic substrate in ways that alter disease presentation or onset age? Are shifts in societal awareness and diagnostic practices leading to changes in the case mix, thus affecting observed polygenic distributions? Untangling these factors presents a rich avenue for future interdisciplinary research.
Importantly, by focusing explicitly on common genetic variants aggregated into polygenic scores, the study captures only a portion of the heritable component of psychiatric disorders. The role of rare variants, epigenetic modifications, and gene-environment interactions remain to be fully elucidated. Expanding analyses to encompass these dimensions may further clarify the complex dynamics exposing the interplay between genetics and time in psychiatric illness.
The robustness of the iPSYCH2015 data set, characterized by its large size, population-based sampling, and comprehensive genetic and clinical information, lends confidence to these findings. Nonetheless, replication in other populations with diverse ancestries and healthcare contexts will be essential to confirm generalizability and discern population-specific trends.
Collectively, this study contributes a transformative perspective on how the polygenic underpinnings of major psychiatric disorders have shifted over the course of multiple decades within Denmark. By revealing disorder-specific trajectories and changing genetic predictive capacities, it paves the way for more dynamic models integrating temporal, genetic, and environmental data. These insights hold the promise of informing future research, public health strategies, and personalized psychiatry in an era when genetics is but one piece of a complex puzzle.
As the field of psychiatric genomics progresses, appreciating the fluidity of genetic burden across generations will be crucial to harnessing the full potential of polygenic risk scores. This study acts as a clarion call for ongoing vigilance in interpreting genetic risk within broader temporal and societal contexts, ensuring that genetic advances translate effectively into improved mental health outcomes.
In essence, the intricate dance of genes and environment revealed by shifting polygenic burdens accentuates psychiatry’s complexity. Rather than static determinants, genetic risks appear embedded within evolving epidemiological matrices, demanding innovative research frameworks to adequately capture the kaleidoscope of factors driving mental illness today and in the future.
Subject of Research: Changes in polygenic burden for psychiatric disorders across birth cohorts
Article Title: Changes in polygenic burden for psychiatric disorders across two decades of birth cohorts
Article References:
Lousdal, M.L., LaBianca, S., Agerbo, E. et al. Changes in polygenic burden for psychiatric disorders across two decades of birth cohorts. Nat. Mental Health 3, 1037–1045 (2025). https://doi.org/10.1038/s44220-025-00478-4
Image Credits: AI Generated
