Periodic Reporting for period 3 - CoMorMent (Predicting comorbid cardiovascular disease in individuals with mental disorder by decoding disease mechanisms)
Berichtszeitraum: 2023-01-01 bis 2024-12-31
Severe mental disorders are major public health concerns and pose a considerable financial burden on the European Health Care systems. At the individual level, human suffering is enormous and associated with a substantial reduction in quality of life, due to the clinical manifestations of the disease (depression/psychosis/mania and cognitive dysfunction) and loss of financial stability. In fact, people with severe mental disorders in Europe live 15-20 years less than the rest of the population, mainly due to comorbid cardiovascular diseases (CVD). Results indicate that overlapping genetic risk factors and brain mechanisms between mental illness and behavioural traits are associated with a lifestyle leading to CVD.
The main objective of the CoMorMent project is to find new paths for clinical management of mental disorders and CVD co-morbidities through identification and validation of biomarkers.
We are addressing this through three different sub-objectives:
1. To identify genetic variants associated with different trajectories of the comorbidity of CVD and mental disorders comorbidity (Discovery).
2. To identify genetic variants associated with lifestyle and behavioural factors and determine their correlation with CVD and mental disorders comorbidity, and role of non-inherited factors (Nature and Nurture).
3. To identify the causative mechanisms of the gene variants and develop prediction tools for targeted prevention in a personalized medicine framework (Validation and Biomarkers).
The main objective of the CoMorMent project is to find new paths for clinical management of mental disorders and CVD co-morbidities through identification and validation of biomarkers.
We are addressing this through three different sub-objectives:
1. To identify genetic variants associated with different trajectories of the comorbidity of CVD and mental disorders comorbidity (Discovery).
2. To identify genetic variants associated with lifestyle and behavioural factors and determine their correlation with CVD and mental disorders comorbidity, and role of non-inherited factors (Nature and Nurture).
3. To identify the causative mechanisms of the gene variants and develop prediction tools for targeted prevention in a personalized medicine framework (Validation and Biomarkers).
The CoMorMent project has moved forward according to plan.
Main results and achievements:
Infrastructure & analyses:
We developed a distributed container-based analysis pipeline for analysis of data on cardiovascular and mental disorder diagnoses. The latter we harmonized across countries.
Discovery:
Trajectories and non-inherited factors: We have observed a substantially higher risk of psychiatric disorder in the years following a cardiovascular disease (CVD) diagnosis and higher risk of mental disorders after trauma. These results are replicated in several cohorts.
Novel genetic variants: Novel loci associated with major depression was identified by contribution of all academic partners to the Psychiatric Genetics Consortium Genome-wide association studies on major depression disorder (MDD). We identified shared genetic risk loci between mental disorders and CVD risk factors, including body mass index (BMI) and tobacco, major depression and lifestyle/behavioral factors as well as overlap of mental disorders with genetic variants associated with levels of metabolic markers in blood.
We found that high-impact variants with risk of schizophrenia negatively associated with cognition, education and Townsend deprivation index (TDI) but that they did not associate strongly with cardiovascular traits such as BMI or CVD-traits in controls.
Nature and nurture:
We analysed how non-transmitted polygenic risk score (PRS) for several disorders impacted neurodevelopmental disorders and identified an effect of depression PRS on Tourette in the Icelandic sample. Taken together, there are overlapping genetic factors between mental disorders and CVD and cardiometabolic risk factors. We studied how parental factors, such as socio-economic status, educational attainment, and personality traits, influence offspring health and lifestyle choices and amongst others found that the PRS for the non-transmitted alleles of has an estimated effect on the proband’s educational attainment that is approximately 40% of the observed transmitted effect.
Validation and Biomarkers:
We showed that the use of antidepressive medication (selective serotonin reuptake inhibitors (SSRIs) or tricyclic antidepressants (TCAs)) were associated with adverse body composition measures and that different medications may yield different CVD risk profiles/trajectories in men and women.
We found significantly lower adherence and persistence to antihypertensive therapy among individuals diagnosed with MDD, and an improvement in adherence after initiation of antidepressant medications, indicating that MDD can negatively impact adherence to CVD treatments, and that antidepressants may improve adherence.
We studied the relationship between health indicators and biological aging.
We developed risk stratification models based on metabolomics and genomic data and investigated the role of PRS and known pharmacogenes in the development of cardiometabolic side-effects of antidepressants and antipsychotics medications.
Cooordination, dissemination and exploitation:
CoMorMent researchers have published papers and given presentations to both the scientific and industrial community locally, nationally and internationally. The CoMorMent webpage features ten lay summaries of CoMorMent publications and CoMorMent twitter has tweeted on results and updates. Five stakeholder forum meetings have been held where information from the project was passed on to our stakeholder forum (13 members - clinicians, patient and industry representatives and policy makers) and we received input on future directions. University of Edinburgh conducted a user-led Citizen Science Project called Depression Detectives https://blogs.ed.ac.uk/depressiondetectives/(öffnet in neuem Fenster).
Exploitation:
The company Precision Health was established in Norway and has designed, developed, and implemented the "clinical workbench" software platform, which hosts and deploys algorithms and computations from the CoMorMent project. The platform includes patient report generation functionality.
Main results and achievements:
Infrastructure & analyses:
We developed a distributed container-based analysis pipeline for analysis of data on cardiovascular and mental disorder diagnoses. The latter we harmonized across countries.
Discovery:
Trajectories and non-inherited factors: We have observed a substantially higher risk of psychiatric disorder in the years following a cardiovascular disease (CVD) diagnosis and higher risk of mental disorders after trauma. These results are replicated in several cohorts.
Novel genetic variants: Novel loci associated with major depression was identified by contribution of all academic partners to the Psychiatric Genetics Consortium Genome-wide association studies on major depression disorder (MDD). We identified shared genetic risk loci between mental disorders and CVD risk factors, including body mass index (BMI) and tobacco, major depression and lifestyle/behavioral factors as well as overlap of mental disorders with genetic variants associated with levels of metabolic markers in blood.
We found that high-impact variants with risk of schizophrenia negatively associated with cognition, education and Townsend deprivation index (TDI) but that they did not associate strongly with cardiovascular traits such as BMI or CVD-traits in controls.
Nature and nurture:
We analysed how non-transmitted polygenic risk score (PRS) for several disorders impacted neurodevelopmental disorders and identified an effect of depression PRS on Tourette in the Icelandic sample. Taken together, there are overlapping genetic factors between mental disorders and CVD and cardiometabolic risk factors. We studied how parental factors, such as socio-economic status, educational attainment, and personality traits, influence offspring health and lifestyle choices and amongst others found that the PRS for the non-transmitted alleles of has an estimated effect on the proband’s educational attainment that is approximately 40% of the observed transmitted effect.
Validation and Biomarkers:
We showed that the use of antidepressive medication (selective serotonin reuptake inhibitors (SSRIs) or tricyclic antidepressants (TCAs)) were associated with adverse body composition measures and that different medications may yield different CVD risk profiles/trajectories in men and women.
We found significantly lower adherence and persistence to antihypertensive therapy among individuals diagnosed with MDD, and an improvement in adherence after initiation of antidepressant medications, indicating that MDD can negatively impact adherence to CVD treatments, and that antidepressants may improve adherence.
We studied the relationship between health indicators and biological aging.
We developed risk stratification models based on metabolomics and genomic data and investigated the role of PRS and known pharmacogenes in the development of cardiometabolic side-effects of antidepressants and antipsychotics medications.
Cooordination, dissemination and exploitation:
CoMorMent researchers have published papers and given presentations to both the scientific and industrial community locally, nationally and internationally. The CoMorMent webpage features ten lay summaries of CoMorMent publications and CoMorMent twitter has tweeted on results and updates. Five stakeholder forum meetings have been held where information from the project was passed on to our stakeholder forum (13 members - clinicians, patient and industry representatives and policy makers) and we received input on future directions. University of Edinburgh conducted a user-led Citizen Science Project called Depression Detectives https://blogs.ed.ac.uk/depressiondetectives/(öffnet in neuem Fenster).
Exploitation:
The company Precision Health was established in Norway and has designed, developed, and implemented the "clinical workbench" software platform, which hosts and deploys algorithms and computations from the CoMorMent project. The platform includes patient report generation functionality.
In our work on body composition, we identified the first genetic loci associated with measures of body composition and showed how different medications impact body composition differently in men and women. We identified genes associated with metabolite concentrations in blood and showed overlapping genetic structure of mental disorder and cardiovascular disease. We developed risk stratification models based on metabolomics and genomic data and investigated the role of polygenic risk scores and known pharmacogenes in the development of cardiometabolic side-effects of antidepressants and antipsychotics.
We showed overlapping genetic structure of mental disorder and cardiovascular disease.
The CoMorMent partners will build on the CoMorMent discoveries to feed into their research on mental disorders and cardiovascular disease.
The knowledge gained in the context of CoMorMent is critical for development of prevention and better treatment regimens, which will form the basis for a new approach in clinical studies with improved quality of life for individuals living with mental disorders.
We showed overlapping genetic structure of mental disorder and cardiovascular disease.
The CoMorMent partners will build on the CoMorMent discoveries to feed into their research on mental disorders and cardiovascular disease.
The knowledge gained in the context of CoMorMent is critical for development of prevention and better treatment regimens, which will form the basis for a new approach in clinical studies with improved quality of life for individuals living with mental disorders.