Periodic Reporting for period 2 - CoMorMent (Predicting comorbid cardiovascular disease in individuals with mental disorder by decoding disease mechanisms)
Okres sprawozdawczy: 2021-07-01 do 2022-12-31
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). Recent 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 co-morbitidity 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 co-morbitidity 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).
During the 2nd part of the project (months 18-36), the CoMorMent project has moved forward according to plan.
For analyses, we built on and extended achievements from the first period - the developed distributed container-based analysis pipeline and for cross-country analysis of the standardized data of cardiovascular and mental disorder diagnoses.
Main results and achievements:
Trajectories: In the Swedish registries, we observed a substantially higher risk of psychiatric disorder during the first year after CVD diagnosis which was lowered but still higher in the subsequent years. Increased risks were observed for all types of psychiatric disorders and among all diagnoses of CVD. These results were replicated in other cohorts.
Identification of genetic risk factors: All partners have finished Genome-wide association analyses (identifying common variants associated with disease) for MDD, early onset MDD, late onset MDD and sex stratified MDD, and the results have been meta-analysed and compared to the latest PGC MDD GWAS meta-analysis results. We identified shared genetic risk loci between schizophrenia and CVD risk factors, especially BMI and tobacco. We analysed non-transmitted polygenic risk score impact for several disorders on 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 identified genetic loci associated with body composition as measured by visceral (inside the body) and subcutaneous (under the skin fat) and muscle fat infiltration. Some of these genetic loci overlapped with risk loci for mental disorders.
Brain and body interplay: We leveraged large-scale body and brain imaging data and found that adipose tissue distribution and cardiometabolic risk factors impact the deviation from estimated brain age and chronological age, a phenotype termed “brain age gap”. Likewise, we found that body mass index, waist-to-hip ratio, and body fat percentage show sex- and age-specific associations with brain age gap and that higher visceral and subcutaneous adipose tissue is associated with higher brain age in post-menopausal women.
Initial results showed that individuals with MDD receiving medication (antidepressants) have a lower rate of CVD compared to matched controls with 0-1 months of therapy.
Cooordination, dissemination and exploitation: CoMorMent researchers continue to publish papers and give presentations to the scientific community locally, nationally and internationally on a regular basis. The CoMorMent webpage features 10 lay summaries of CoMorMent publications and CoMorMent twitter tweets on results and updates. Two stakeholder forum meetings were held where information from the project was passed on to our stakeholder forum (currently 13 members, clinicians, patient and industry representatives and policy makers) and we received input on future directions. UEDIN conducted a user-led Citizen Science Project called Depression Detectives https://blogs.ed.ac.uk/depressiondetectives/.
Exploitation: The US business parner (Cortechs/Healthlytix) has initiated the process of establishing a new company in Europe (Precision Health), and they are working to organize this into the main unit for their activities.
For analyses, we built on and extended achievements from the first period - the developed distributed container-based analysis pipeline and for cross-country analysis of the standardized data of cardiovascular and mental disorder diagnoses.
Main results and achievements:
Trajectories: In the Swedish registries, we observed a substantially higher risk of psychiatric disorder during the first year after CVD diagnosis which was lowered but still higher in the subsequent years. Increased risks were observed for all types of psychiatric disorders and among all diagnoses of CVD. These results were replicated in other cohorts.
Identification of genetic risk factors: All partners have finished Genome-wide association analyses (identifying common variants associated with disease) for MDD, early onset MDD, late onset MDD and sex stratified MDD, and the results have been meta-analysed and compared to the latest PGC MDD GWAS meta-analysis results. We identified shared genetic risk loci between schizophrenia and CVD risk factors, especially BMI and tobacco. We analysed non-transmitted polygenic risk score impact for several disorders on 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 identified genetic loci associated with body composition as measured by visceral (inside the body) and subcutaneous (under the skin fat) and muscle fat infiltration. Some of these genetic loci overlapped with risk loci for mental disorders.
Brain and body interplay: We leveraged large-scale body and brain imaging data and found that adipose tissue distribution and cardiometabolic risk factors impact the deviation from estimated brain age and chronological age, a phenotype termed “brain age gap”. Likewise, we found that body mass index, waist-to-hip ratio, and body fat percentage show sex- and age-specific associations with brain age gap and that higher visceral and subcutaneous adipose tissue is associated with higher brain age in post-menopausal women.
Initial results showed that individuals with MDD receiving medication (antidepressants) have a lower rate of CVD compared to matched controls with 0-1 months of therapy.
Cooordination, dissemination and exploitation: CoMorMent researchers continue to publish papers and give presentations to the scientific community locally, nationally and internationally on a regular basis. The CoMorMent webpage features 10 lay summaries of CoMorMent publications and CoMorMent twitter tweets on results and updates. Two stakeholder forum meetings were held where information from the project was passed on to our stakeholder forum (currently 13 members, clinicians, patient and industry representatives and policy makers) and we received input on future directions. UEDIN conducted a user-led Citizen Science Project called Depression Detectives https://blogs.ed.ac.uk/depressiondetectives/.
Exploitation: The US business parner (Cortechs/Healthlytix) has initiated the process of establishing a new company in Europe (Precision Health), and they are working to organize this into the main unit for their activities.
In our published work on body composition, we identified the first genetic loci associated with measures of body composition. We identified non-transmitted allele and identified an effect of depression PRS on Tourette in the Icelandic sample. we observed a substantially higher risk of psychiatric disorder during the first year after CVD diagnosis which was lowered but still higher in the subsequent years. We showed overlapping genetic structure of mental disorder and cardiovascular disease.
CoMorMent will use the discoveries from first phase of the project to accellearte the identification of genetic, brain and body biomarkers and pathological mechanisms of comorbid CVD in mental disorders and its relationship to behavior and unhealthy lifestyle. We will improve our analyses by adding more data from international repositories, to enrich the novel Nordic and UK data sources. We will use recent statistical genetics discoveries to develop tools for prediction, early diagnosis and better disease monitoring.
This knowledge 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.
CoMorMent will use the discoveries from first phase of the project to accellearte the identification of genetic, brain and body biomarkers and pathological mechanisms of comorbid CVD in mental disorders and its relationship to behavior and unhealthy lifestyle. We will improve our analyses by adding more data from international repositories, to enrich the novel Nordic and UK data sources. We will use recent statistical genetics discoveries to develop tools for prediction, early diagnosis and better disease monitoring.
This knowledge 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.