Periodic Reporting for period 1 - RISK-MATTER (Psychosis risk subtypes and white matter integrity: exploring subgroup trajectories)
Okres sprawozdawczy: 2024-07-01 do 2025-12-31
Mental health problems have increased worldwide in recent years, particularly among young people, and represent a major public health challenge in Europe. Psychotic disorders, although relatively rare, are among the leading causes of long-term disability. This immense burden is partly explained by the disorder’s early onset between late adolescence or early adulthood and can profoundly disrupt education, employment, and social participation. Importantly, individuals with psychotic disorders follow very different clinical trajectories: while some recover well after a first episode, others experience persistent symptoms and functional impairment. Currently, it remains difficult to predict these outcomes or to tailor interventions accordingly.
RISK-MATTER addresses this challenge by focusing on risk exposure profiles, i.e. combinations of genetic, social, and environmental factors that may shape both brain development and long-term clinical outcomes in psychosis. Rather than treating psychotic disorders as a single entity, the project aims to identify meaningful subgroups of individuals based on their exposure to different risk factors, such as early-life adversity or later environmental stressors. This approach aligns closely with recent European policy initiatives that emphasize prevention, and early intervention in mental health.
A central objective of RISK-MATTER is to understand how these risk exposure profiles relate to changes in white matter microstructure, a key component of brain connectivity that continues to develop during adolescence and early adulthood. White matter seems particularly relevant because abnormalities in white matter microstructure are consistently observed in affected individuals. By studying both static brain characteristics and changes over time, the project investigates whether white matter alterations may help explain why certain risk profiles are associated with poorer clinical outcomes.
To achieve these goals, RISK-MATTER integrates advanced neuroimaging, data-driven machine learning methods, and real-life outcome assessments, including smartphone-based measures that capture everyday functioning.
Ultimately, the project aims to contribute to more risk-informed and person-centered approaches to psychosis care. By improving the understanding of how social and environmental risks interact with brain development to influence outcomes, RISK-MATTER provides a basis for more risk-informed approaches to psychosis care, with the potential to inform future prevention strategies and personalized interventions.
RISK-MATTER addresses this challenge by focusing on risk exposure profiles, i.e. combinations of genetic, social, and environmental factors that may shape both brain development and long-term clinical outcomes in psychosis. Rather than treating psychotic disorders as a single entity, the project aims to identify meaningful subgroups of individuals based on their exposure to different risk factors, such as early-life adversity or later environmental stressors. This approach aligns closely with recent European policy initiatives that emphasize prevention, and early intervention in mental health.
A central objective of RISK-MATTER is to understand how these risk exposure profiles relate to changes in white matter microstructure, a key component of brain connectivity that continues to develop during adolescence and early adulthood. White matter seems particularly relevant because abnormalities in white matter microstructure are consistently observed in affected individuals. By studying both static brain characteristics and changes over time, the project investigates whether white matter alterations may help explain why certain risk profiles are associated with poorer clinical outcomes.
To achieve these goals, RISK-MATTER integrates advanced neuroimaging, data-driven machine learning methods, and real-life outcome assessments, including smartphone-based measures that capture everyday functioning.
Ultimately, the project aims to contribute to more risk-informed and person-centered approaches to psychosis care. By improving the understanding of how social and environmental risks interact with brain development to influence outcomes, RISK-MATTER provides a basis for more risk-informed approaches to psychosis care, with the potential to inform future prevention strategies and personalized interventions.
WP1 derived a score to quantify cumulative environmental risk exposure across multiple risk factors and investigated its associations with clinical symptoms, functional outcomes, familial risk, and white matter microstructure (manuscript, under review). In addition to cumulative risk, analyses focused on modifiable environmental exposures in individuals at clinical high risk for psychosis, with particular emphasis on cannabis use examined in relation to symptom profiles and legal context. These analyses demonstrated that cannabis-related risk expression varies with regulatory environments and is associated with distinct clinical symptom patterns. The project further contributed to a large multisite investigation of childhood trauma, strengthening evidence for associations between early-life adversity and psychosis-relevant clinical phenotypes (manuscript, under review).
To examine white matter microstructure as a neurobiological correlate of risk exposure, in WP2 diffusion-weighted MRI data from the PRONIA cohort were processed, harmonized, and quality controlled across sites and time points using rigorous automated and manual procedures. Using the harmonized dataset, initial analyses examined associations between white matter microstructure, familial risk, and the exposome score, and assessed free-water imaging as a sensitive marker of early-stage pathology. As a preparatory step for subsequent related free-water analyses in relation to risk factors, hormonal influences were examined as potential moderators of previously reported sex differences in psychosis-related free-water findings.
In preparation for real-life outcome assessment in WP3, smartphone-based daily surveys were evaluated as ecologically valid measures of psychosis-related symptoms. Associations between daily self-reported symptoms and established clinical dimensions were demonstrated, supporting the feasibility of smartphone-based assessments for capturing clinically meaningful symptom variability. In parallel, ethical approvals and study protocols for extended smartphone-based follow-up were initiated.
Finally, a multimodal baseline characterization of a large psychosis-risk cohort was conducted as a cross–work package effort to compare the sensitivity of clinical, neurobiological, and digital data domains, informing modality prioritization and the interpretation of confounding effects across analyses.
To examine white matter microstructure as a neurobiological correlate of risk exposure, in WP2 diffusion-weighted MRI data from the PRONIA cohort were processed, harmonized, and quality controlled across sites and time points using rigorous automated and manual procedures. Using the harmonized dataset, initial analyses examined associations between white matter microstructure, familial risk, and the exposome score, and assessed free-water imaging as a sensitive marker of early-stage pathology. As a preparatory step for subsequent related free-water analyses in relation to risk factors, hormonal influences were examined as potential moderators of previously reported sex differences in psychosis-related free-water findings.
In preparation for real-life outcome assessment in WP3, smartphone-based daily surveys were evaluated as ecologically valid measures of psychosis-related symptoms. Associations between daily self-reported symptoms and established clinical dimensions were demonstrated, supporting the feasibility of smartphone-based assessments for capturing clinically meaningful symptom variability. In parallel, ethical approvals and study protocols for extended smartphone-based follow-up were initiated.
Finally, a multimodal baseline characterization of a large psychosis-risk cohort was conducted as a cross–work package effort to compare the sensitivity of clinical, neurobiological, and digital data domains, informing modality prioritization and the interpretation of confounding effects across analyses.
The project advanced understanding of how environmental, clinical, and cognitive factors relate to white matter microstructure in psychosis. Using harmonised data from a large multisite cohort, it showed that white matter alterations are heterogeneous, reflecting both general impairments shared with other mental disorders and patterns linked to psychosis-related symptom severity.
By moving beyond simple group comparisons, the findings highlight the importance of distinguishing general vulnerability from disorder-related associations and show the value of combining information across multiple domains. The results suggest that future prognostic approaches need to consider both shared and psychosis-related impairments, with further progress requiring longitudinal validation in independent cohorts.
Further, RISK-MATTER showed that oral contraceptive use contributes to sex-related differences in free-water measures, which may help explain inconsistent findings in previous studies. We will in future analyses using free-water as an early marker of psychosis therefore account for oral contraceptive use.
Finally, analyses of modifiable environmental risk factors showed that cannabis exposure and childhood trauma are linked to distinct symptom patterns. Rather than affecting all symptoms in the same way, these exposures were associated with specific clinical profiles, highlighting the importance of considering the type and timing of environmental risk when studying psychosis.
By moving beyond simple group comparisons, the findings highlight the importance of distinguishing general vulnerability from disorder-related associations and show the value of combining information across multiple domains. The results suggest that future prognostic approaches need to consider both shared and psychosis-related impairments, with further progress requiring longitudinal validation in independent cohorts.
Further, RISK-MATTER showed that oral contraceptive use contributes to sex-related differences in free-water measures, which may help explain inconsistent findings in previous studies. We will in future analyses using free-water as an early marker of psychosis therefore account for oral contraceptive use.
Finally, analyses of modifiable environmental risk factors showed that cannabis exposure and childhood trauma are linked to distinct symptom patterns. Rather than affecting all symptoms in the same way, these exposures were associated with specific clinical profiles, highlighting the importance of considering the type and timing of environmental risk when studying psychosis.