Author: Joana Barroso1,2,3,4, Kenta Wakaizumi5,6, Ana Mafalda Reis7, Marwan Baliki3,5, Thomas J Schnitzer3,8,9, Vasco Galhardo1,2, Apkar Vania Apkarian3,4,9
1 Departamento de Biomedicina, Faculdade de Medicina, Universidade do Porto, Porto, Portugal.
2 Instituto de Investigação e Inovação em Saúde - i3S, Universidade do Porto, Porto, Portugal.
3 Department of Physical Medicine and Rehabilitation, Northwestern University, Feinberg School of Medicine, Chicago, Illinois, USA.
4 Department of Physiology, Northwestern University, Feinberg School of Medicine, Chicago, Illinois, USA.
5 Shirley Ryan Ability Lab, Chicago, Illinois, USA.
6 Department of Anesthesiology, Keio University School of Medicine, Tokyo, Japan.
7 Unilabs Boavista, Porto, Portugal.
8 Department of Internal Medicine/Rheumatology, Northwestern University, Feinberg School of Medicine, Chicago, Illinois, USA.
9 Department of Anesthesia, Northwestern University, Feinberg School of Medicine, Chicago, Illinois, USA.
Conference/Journal: Hum Brain Mapp
Date published: 2020 Nov 19
Other: Special Notes: doi: 10.1002/hbm.25287. , Word Count: 264
Osteoarthritis (OA) manifests with chronic pain, motor impairment, and proprioceptive changes. However, the role of the brain in the disease is largely unknown. Here, we studied brain networks using the mathematical properties of graphs in a large sample of knee and hip OA (KOA, n = 91; HOA, n = 23) patients. We used a robust validation strategy by subdividing the KOA data into discovery and testing groups and tested the generalizability of our findings in HOA. Despite brain global topological properties being conserved in OA, we show there is a network wide pattern of reorganization that can be captured at the subject-level by a single measure, the hub disruption index. We localized reorganization patterns and uncovered a shift in the hierarchy of network hubs in OA: primary sensory and motor regions and parahippocampal gyrus behave as hubs and insular cortex loses its central placement. At an intermediate level of network structure, frontoparietal and cingulo-opercular modules showed preferential reorganization. We examined the association between network properties and clinical correlates: global disruption indices and isolated degree properties did not reflect clinical parameters; however, by modeling whole brain nodal degree properties, we identified a distributed set of regions that reliably predicted pain intensity in KOA and generalized to hip OA. Together, our findings reveal that while conserving global topological properties, brain network architecture reorganizes in OA, at both global and local scale. Network connectivity related to OA pain intensity is dissociated from the major hub disruptions, challenging the extent of dependence of OA pain on nociceptive signaling.
Keywords: brain networks; brain topology; chronic pain; graph properties; osteoarthritis.
PMID: 33210801 DOI: 10.1002/hbm.25287