Periodic Reporting for period 2 - PainFACT (Molecular Mechanisms Associating Chronic Pain with Fatigue, Affective Disorders, Cardiovascular Disease and Total Comorbidity)
Période du rapport: 2021-07-01 au 2022-12-31
Chronic pain is a common health problem with major impact on quality of life and functioning. It is the leading cause of disability and societal costs due to productivity loss are huge, - far greater than those of cardiovascular disease, diabetes, or cancer. The causes of chronic pain are poorly understood, symptomatic treatment efficacy is poor, and curative treatment is lacking for most chronic pain condition. The sheer number of patients affected also presents a challenge and there is a need to find screening methods for early identification of patients at risk for developing severe disabling chronic pain. Notably, chronic pain patients also tend to suffer from a number of additional conditions, including anxiety, depression, fatigue, cardiovascular diseases and premature mortality. The full extent of this clustering of diseases with chronic pain is unknown, and the mechanisms causing these conditions to cluster together remain to be identified.
The overall objective of PainFACT is therefore to identify patterns of disease that co-occur with chronic pain and to identify the mechanisms that cause these diseases to occur together. Through analysis of patient data from the population of an entire country, PainFACT aims to characterize clusters of medical conditions that are associated with chronic pain. Using state-of-the-art, genomic, proteomic, and brain imaging data from humans and mice, PainFACT will identify molecular mechanisms and develop predictive algorithms for new-onset chronic pain and pain-related comorbidity.
The overall objective of PainFACT is therefore to identify patterns of disease that co-occur with chronic pain and to identify the mechanisms that cause these diseases to occur together. Through analysis of patient data from the population of an entire country, PainFACT aims to characterize clusters of medical conditions that are associated with chronic pain. Using state-of-the-art, genomic, proteomic, and brain imaging data from humans and mice, PainFACT will identify molecular mechanisms and develop predictive algorithms for new-onset chronic pain and pain-related comorbidity.
Key to the discovery phase of PainFACT, is the analysis of very large datasets, and the project is still very much engaged in securing access, preprocessing, quality control and annotation for all relevant data sources. For human discovery, this includes in-house resources as well as large external studies, such as UK-Biobank (500k), the Danish Bloodbank (500k), and the Norwegian Patient Registry (5.2M) as well as smaller studies, such as the Tromsø Study (25k), with more specialized assessments of pain sensitivity. PainFACT has also started collection of new data on pain sensitivity among participants in the Rotterdam Study and for rare genetic variant carriers in Iceland, of critical importance for the identification of protein biomarkers and validation of genetic findings respectively. Our work with brain imaging has thus far mainly focused on isolating grey and white matter volumes from brain scans, making them suitable for further analysis. In parallel PainFACT, has assessed a broad range of health outcomes in a large cohort of mice, including pain, anxiety, depression, fatigue, blood pressure, atherosclerosis and blood levels of glucose and cholesterol. These mice have undergone MRI imaging thereby providing a bridge to corresponding data in humans. A unique feature of this mouse cohort is that it is comprised of outbred mice, meaning that each mouse is genetically unique. This mouse cohort therefore mirrors the human situation, in ways that other animal studies, which typically employ genetically identical subjects, do not. Indeed, one of the most striking findings thus far is the huge variance between animals in all assessed outcomes.
Analysis of data from humans and animals is ongoing and it will still be some time before the major findings can be reported. In total the project has produced 10 papers, with an additional paper in press. Among these, was a study of the genetics of back-pain (Bjornsdottir, et al. 2022, Nature Communications), identifying 41 genetic variants. Aside from migraine, the genetics of pain has lagged behind other fields, and getting a grip on the genetics of well-defined common pain outcomes is of central importance for understanding the molecular mechanisms of pain.
Currently PainFACT’s major ongoing effort directed towards the analysis of relationships between health outcomes. In humans this includes relationships between pain sensitivity and chronic pain, between chronic pain and selected comorbid conditions, such as depression, and more broadly the clustering of diseases in the general population. Our approach includes mapping comorbidity between conditions, the predictive value of one condition for the future development of another, as well as the genetic overlap between conditions. In mice, similar analyses are being conducted to map the patterns of comorbidity. Results from these analyses are expected in the next reporting period.
Analysis of data from humans and animals is ongoing and it will still be some time before the major findings can be reported. In total the project has produced 10 papers, with an additional paper in press. Among these, was a study of the genetics of back-pain (Bjornsdottir, et al. 2022, Nature Communications), identifying 41 genetic variants. Aside from migraine, the genetics of pain has lagged behind other fields, and getting a grip on the genetics of well-defined common pain outcomes is of central importance for understanding the molecular mechanisms of pain.
Currently PainFACT’s major ongoing effort directed towards the analysis of relationships between health outcomes. In humans this includes relationships between pain sensitivity and chronic pain, between chronic pain and selected comorbid conditions, such as depression, and more broadly the clustering of diseases in the general population. Our approach includes mapping comorbidity between conditions, the predictive value of one condition for the future development of another, as well as the genetic overlap between conditions. In mice, similar analyses are being conducted to map the patterns of comorbidity. Results from these analyses are expected in the next reporting period.
Given the limited knowledge of the causes of chronic pain and pain comorbidity, it is expected that PainFACT will yield a number of novel results with long term impact on the field.
1. PainFACT will identify patterns of pain comorbidity and the order with which diseases occur within these disease clusters. Furthermore, PainFACT will develop and validate biomarker panels and genetic risk scores for pain and pain comorbidity clusters. Taken together, it is expected that this will lead to prognostic algorithms and screening methods of importance for prioritizing patients and tailoring treatment to the individual patient (precision medicine).
2. PainFACT will identify biomarkers that are associated with pain, yielding insight into the root causes of chronic pain. This is expected to yield novel targets for pharmacological research, ultimately paving the way for the development of new analgesic treatments.
3. PainFACT will identify biomarkers that are associated clusters of diseases that co-occur with pain, yielding insight into the root causes comorbidity and multimorbidity. This will open a window of opportunity for developing treatments targeting patterns of disease, rather than individual diseases. With an ageing population and an increasing number of individuals suffering from many diseases, polypharmacy and drug-drug interactions is an increasing problem, and there is a pressing need to move beyond the one-disease-one-drug approach to treatment.
4. PainFACT will characterize structural characteristics of the brain that are associated with pain and pain comorbidity. This is a key to understanding how pain impacts central nervous system (i.e. cognition and emotion) and can potentially be developed as method for monitoring the impact of pain on central nervous functions.
The focus of PainFACT is on mechanisms and basic science, and as such the project is not directed at creating change at a societal level. However, as chronic pain is the leading cause of disability and arguably the single most expensive health care problem, it is to be expected that PainFACT will have major indirect positive impact at the societal level. For instance: The ability to predict which patients will develop severe pain and multiple comorbid health problems, would be of major value in prioritizing patients for more extensive treatment in health care systems that is pressed for resources. Should PainFACT eventually lead to development of improved analgesic treatments, this would be of immense value for reducing the suffering and societal costs associated with pain. Though such outcomes lie outside the scope of the project itself, PainFACT was nevertheless designed to provide the foundation further exploitation by e.g. the pharmacological industry and will engage in close dialogue to ensure the further exploitation of project results.
1. PainFACT will identify patterns of pain comorbidity and the order with which diseases occur within these disease clusters. Furthermore, PainFACT will develop and validate biomarker panels and genetic risk scores for pain and pain comorbidity clusters. Taken together, it is expected that this will lead to prognostic algorithms and screening methods of importance for prioritizing patients and tailoring treatment to the individual patient (precision medicine).
2. PainFACT will identify biomarkers that are associated with pain, yielding insight into the root causes of chronic pain. This is expected to yield novel targets for pharmacological research, ultimately paving the way for the development of new analgesic treatments.
3. PainFACT will identify biomarkers that are associated clusters of diseases that co-occur with pain, yielding insight into the root causes comorbidity and multimorbidity. This will open a window of opportunity for developing treatments targeting patterns of disease, rather than individual diseases. With an ageing population and an increasing number of individuals suffering from many diseases, polypharmacy and drug-drug interactions is an increasing problem, and there is a pressing need to move beyond the one-disease-one-drug approach to treatment.
4. PainFACT will characterize structural characteristics of the brain that are associated with pain and pain comorbidity. This is a key to understanding how pain impacts central nervous system (i.e. cognition and emotion) and can potentially be developed as method for monitoring the impact of pain on central nervous functions.
The focus of PainFACT is on mechanisms and basic science, and as such the project is not directed at creating change at a societal level. However, as chronic pain is the leading cause of disability and arguably the single most expensive health care problem, it is to be expected that PainFACT will have major indirect positive impact at the societal level. For instance: The ability to predict which patients will develop severe pain and multiple comorbid health problems, would be of major value in prioritizing patients for more extensive treatment in health care systems that is pressed for resources. Should PainFACT eventually lead to development of improved analgesic treatments, this would be of immense value for reducing the suffering and societal costs associated with pain. Though such outcomes lie outside the scope of the project itself, PainFACT was nevertheless designed to provide the foundation further exploitation by e.g. the pharmacological industry and will engage in close dialogue to ensure the further exploitation of project results.