Influencing factors of brain alterations in chronic pain

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Associations of clinical parameters and imaging data as well as predictive biomarkers have enabled valuable insights into the neurobiology of chronic pain in recent years. The brains of patients with chronic back pain show characteristic volume reductions in the gray matter of the brain in the medial prefrontal cortex, the cingulate gyrus, and the anterior insula. However, the results for various pain syndromes are still very inconsistent, which can largely be attributed to group sizes that are too small in the individual studies.In the case of frequent pain disorders, analyzes from population-based studies can also be used that can provide the necessary group sizes. With the proposed project we intend to close this gap. We analyze the volume of the gray matter volume (GMV) based on voxels in two longitudinal population-based cohorts of the SHIP study (Study of health in Pomerania) and in longitudinal clinical data sets. The overall goal of this project is to characterize the neurobiology of chronic pain by using existing information on various pain syndromes in two extensive population-based cohorts. In addition, we supplement the observations made in population-based cohorts with clinical studies. These include patients with craniomandibular pain and patients with upper extremity pain associated with complex regional pain syndrome (CRPS), which is a neuropathic pain syndrome. The advantage of the population-based cohort studies lies in the comprehensive collection of data, which in the case of frequently occurring diseases also enables the recording of biomarkers that can predict who will develop these syndromes in the post-survey period. The advantage of the patient examinations lies in the specific surveys with an evidence-based therapy method. This in turn makes it possible to determine longitudinal predictors for therapy responders. What is specific about both cohorts is that they were measured on the same MRI together with a large number of matched controls free of acute and chronic pain. This enables a unique homogeneity of the data pool. In addition, both cohorts enable a closer look at the common changes in GMV in all syndromes, a look at specific changes for each individual syndrome, but also a comparison of the specific changes to other mental illnesses that show large overlaps with chronic pain with regard to individual symptoms (depression and anxiety). Ultimately, with the large number of parameters recorded, relations with changes in gray matter can also be calculated by means of mediation analyzes. In summary, the project applied for with the longitudinally available data sets offers a unique opportunity to identify biomarkers for chronic pain and to test their specificity- especially with respect to GMV alterations.