Periodic Reporting for period 5 - STRATIFY (Brain network based stratification of mental illness)
Période du rapport: 2023-01-01 au 2023-09-30
STRATIFY, seeks to alleviate the burden of mental disorders through the identification of widely applicable disease markers rooted in neural processes, predicting psychopathology and enabling targeted interventions. By generating a neurobehavioral framework, STRATIFY aims to stratify psychopathology based on the characterization of links between network properties of brain function and structure and reinforcement-related behaviors – fundamental components of prevalent mental disorders.
1. Identification of Brain-Based Behavioral Symptom Groups:
- Grouping clinical symptoms based on underlying quantitative neurobiological measures, laying the foundation for precision psychiatry.
- Utilized innovative methods, including multiple sparse canonical correlation analysis (msCCA), to correlate three neuroimaging modalities with individual ICD10 symptoms of psychiatric disorders (Ing et al. 2019).
- Refined the msCCA method to integrate seven modalities, by providing a framework for a brain-derived psychiatric nosology (Lett et al. in prep).
- Identification of a shared neural basis for identifying psychiatric comorbidity (Xie et al. Nature Medicine 23).
2. Linking Macroenvironment with Brain and Behavior:
- Developed remote sensing satellite measures and identified environmental profiles related to urbanicity (Xu et al. Nature Human Behaviour 2022)
- Investigated the correlation between macroenvironmental factors (urbanicity, pollution, social inequality) and brain/behavioral symptoms. (Xu et al. Nature Medicine 2023)
- Established the impact of macroenvironmental challenges on mental illness, providing a critical basis for global comparisons. (Vaidya et al. JAMA Network Open 2023)
3. Advancements in Neuroimaging Analysis:
- Created novel methodologies to enhance the sensitivity of neuroimaging analysis, including predicting 7T neuroimaging using 3T data. (Dai et al. in preparation)
- Developed methods for measuring time-varying functional brain networks in task-based MRI, demonstrating increased sensitivity. (Chang et al. in preparation)
Conclusions of the Action:
Our findings collectively contribute to the overarching goal of identifying neurobehavioral markers and advancing precision psychiatry. In the initial phases, we identified neurobehavioral symptom groups based on shared brain mechanisms and shared genetics pathways. A transdiagnostic approach shed light on shared etiologies, emphasizing the importance of understanding common neural bases. The methodology was further refined for multi-modal integrated analysis. This approach challenges traditional diagnostic boundaries and opens new avenues for more holistic and personalized treatment strategies. In response to the unique challenges posed by the COVID-19 pandemic, the project investigated its impact on youth mental health (Qi et al. BJP Open 2023). The findings deepens our understanding of mental health responses to external stressors.
1. Identification of Brain-Based Behavioral Symptom Groups:
- Grouping clinical symptoms based on underlying quantitative neurobiological measures, laying the foundation for precision psychiatry.
- Utilized innovative methods, including multiple sparse canonical correlation analysis (msCCA), to correlate three neuroimaging modalities with individual ICD10 symptoms of psychiatric disorders (Ing et al. 2019).
- Refined the msCCA method to integrate seven modalities, by providing a framework for a brain-derived psychiatric nosology (Lett et al. in prep).
- Identification of a shared neural basis for identifying psychiatric comorbidity (Xie et al. Nature Medicine 23).
2. Linking Macroenvironment with Brain and Behavior:
- Developed remote sensing satellite measures and identified environmental profiles related to urbanicity (Xu et al. Nature Human Behaviour 2022)
- Investigated the correlation between macroenvironmental factors (urbanicity, pollution, social inequality) and brain/behavioral symptoms. (Xu et al. Nature Medicine 2023)
- Established the impact of macroenvironmental challenges on mental illness, providing a critical basis for global comparisons. (Vaidya et al. JAMA Network Open 2023)
3. Advancements in Neuroimaging Analysis:
- Created novel methodologies to enhance the sensitivity of neuroimaging analysis, including predicting 7T neuroimaging using 3T data. (Dai et al. in preparation)
- Developed methods for measuring time-varying functional brain networks in task-based MRI, demonstrating increased sensitivity. (Chang et al. in preparation)
Conclusions of the Action:
Our findings collectively contribute to the overarching goal of identifying neurobehavioral markers and advancing precision psychiatry. In the initial phases, we identified neurobehavioral symptom groups based on shared brain mechanisms and shared genetics pathways. A transdiagnostic approach shed light on shared etiologies, emphasizing the importance of understanding common neural bases. The methodology was further refined for multi-modal integrated analysis. This approach challenges traditional diagnostic boundaries and opens new avenues for more holistic and personalized treatment strategies. In response to the unique challenges posed by the COVID-19 pandemic, the project investigated its impact on youth mental health (Qi et al. BJP Open 2023). The findings deepens our understanding of mental health responses to external stressors.
To date the STRATIFY project has published 63 papers. Some key manuscripts are described below:
Alex Ing et. al. 'Identifying neurobehavioural symptom groups based on shared brain mechanisms', Nature Human Behaviour (2019).
We discovered symptom clusters with shared biology (see Figure). This paper describes a new method to find relations between behavioral symptoms, and neuroimaging measures of brain structure and function. By characterising behavioral symptom groups based on shared neural mechanisms, the results provide a framework for developing a classification system for psychiatric illness, which is based on quantitative neurobehavioural measures.
Evangelou et al., 'Novel alcohol-related genes suggest shared genetic mechanisms with neuropsychiatric disorders', Nature Human Behaviour (2019).
In a large GWAS meta-analysis we investigated 480.842 cases participants to decipher the genetic architecture of alcohol intake. The study identified genetic pathways associated with alcohol consumption and suggested shared genetic mechanisms with neuropsychiatric disorders including schizophrenia.
Robinson L et al. Association of Genetic and Phenotypic Assessments With Onset of Disordered Eating Behaviors and Comorbid Mental Health Problems Among Adolescents. JAMA Network Open (2020).
The findings of this study delineate temporal associations and shared etiologies among disordered eating behaviour and other mental health disorders. We emphasize the potential of genetic and phenotypical assessments of obesity, behavioral disorders, and neuroticism to improve early and differential diagnosis of eating disorders.
Jia et. al. 'Neurobehavioural characterisation of reinforcement-related behaviour', Nature Human Behaviour (2020)
We describe the identification of stratification markers of externalising symptoms based on functional brain activity during reinforcement processes. Neural network underlying hyperactivity and inattention of ADHD while similar during reward anticipation, were distinct during motor inhibition, suggesting different neural mechanisms underlying distinct ADHD behaviours.
Zuo Zhang et al. Development of Disordered Eating Behaviors and Comorbid Depressive Symptoms in Adolescence: Neural and Psychopathological Predictors. Biological Psychiatry (2021).
Our findings suggest that alterations in frontal brain circuits are part of the shared etiology among eating disorders, attention-deficit/hyperactivity disorder, conduct disorder, and depression. We highlight the importance of a transdiagnostic approach to treating these conditions.
Xie C et al. A shared neural basis underlying psychiatric comorbidity. Nature Medicine. (2023)
We identify a reproducible and general neural basis underlying symptoms of multiple mental health disorders, bridging multidimensional evidence from behavioral, neuroimaging and genetic substrates. These findings may help to develop new therapeutic interventions for psychiatric comorbidities.
Qi L et al. Differing impact of the COVID-19 pandemic on youth mental health: combined population and clinical study. BJPsych Open (2023).
In the population cohort, depression and eating disorder symptoms increased during the pandemic, respectively. By contrast, these remained high over time in the clinical cohort. Conversely, trajectories of alcohol misuse were similar in both cohorts, decreasing continuously during the pandemic. Pre-pandemic symptom severity predicted the observed mental health trajectories in the population cohort. Surprisingly, being relatively healthy predicted increases in depression and eating disorder symptoms and in body mass index. By contrast, those initially at higher risk for depression or eating disorders reported a lasting decrease. Thus, healthier young people may be at greater risk of developing depressive or eating disorder symptoms during the COVID-19 pandemic.
Alex Ing et. al. 'Identifying neurobehavioural symptom groups based on shared brain mechanisms', Nature Human Behaviour (2019).
We discovered symptom clusters with shared biology (see Figure). This paper describes a new method to find relations between behavioral symptoms, and neuroimaging measures of brain structure and function. By characterising behavioral symptom groups based on shared neural mechanisms, the results provide a framework for developing a classification system for psychiatric illness, which is based on quantitative neurobehavioural measures.
Evangelou et al., 'Novel alcohol-related genes suggest shared genetic mechanisms with neuropsychiatric disorders', Nature Human Behaviour (2019).
In a large GWAS meta-analysis we investigated 480.842 cases participants to decipher the genetic architecture of alcohol intake. The study identified genetic pathways associated with alcohol consumption and suggested shared genetic mechanisms with neuropsychiatric disorders including schizophrenia.
Robinson L et al. Association of Genetic and Phenotypic Assessments With Onset of Disordered Eating Behaviors and Comorbid Mental Health Problems Among Adolescents. JAMA Network Open (2020).
The findings of this study delineate temporal associations and shared etiologies among disordered eating behaviour and other mental health disorders. We emphasize the potential of genetic and phenotypical assessments of obesity, behavioral disorders, and neuroticism to improve early and differential diagnosis of eating disorders.
Jia et. al. 'Neurobehavioural characterisation of reinforcement-related behaviour', Nature Human Behaviour (2020)
We describe the identification of stratification markers of externalising symptoms based on functional brain activity during reinforcement processes. Neural network underlying hyperactivity and inattention of ADHD while similar during reward anticipation, were distinct during motor inhibition, suggesting different neural mechanisms underlying distinct ADHD behaviours.
Zuo Zhang et al. Development of Disordered Eating Behaviors and Comorbid Depressive Symptoms in Adolescence: Neural and Psychopathological Predictors. Biological Psychiatry (2021).
Our findings suggest that alterations in frontal brain circuits are part of the shared etiology among eating disorders, attention-deficit/hyperactivity disorder, conduct disorder, and depression. We highlight the importance of a transdiagnostic approach to treating these conditions.
Xie C et al. A shared neural basis underlying psychiatric comorbidity. Nature Medicine. (2023)
We identify a reproducible and general neural basis underlying symptoms of multiple mental health disorders, bridging multidimensional evidence from behavioral, neuroimaging and genetic substrates. These findings may help to develop new therapeutic interventions for psychiatric comorbidities.
Qi L et al. Differing impact of the COVID-19 pandemic on youth mental health: combined population and clinical study. BJPsych Open (2023).
In the population cohort, depression and eating disorder symptoms increased during the pandemic, respectively. By contrast, these remained high over time in the clinical cohort. Conversely, trajectories of alcohol misuse were similar in both cohorts, decreasing continuously during the pandemic. Pre-pandemic symptom severity predicted the observed mental health trajectories in the population cohort. Surprisingly, being relatively healthy predicted increases in depression and eating disorder symptoms and in body mass index. By contrast, those initially at higher risk for depression or eating disorders reported a lasting decrease. Thus, healthier young people may be at greater risk of developing depressive or eating disorder symptoms during the COVID-19 pandemic.
Our research extends beyond the current state of the art by innovatively grouping psychiatric symptoms based on neurobiological measures, employing advanced multiple sparse canonical correlation analysis. It pioneers the integration of seven neuroimaging modalities towards redefining psychiatric nosology. Additionally, novel methodologies also enhance neuroimaging sensitivity, showcasing significant progress in precision psychiatry and global mental health research.