Is the gut important in multiple joint osteoarthritis? A multimodal investigation in humans and pet dogs

Univ Of North Carolina Chapel Hill, Chapel Hill NC

Investigators

Linked publications, trials & patents

Abstract

PROJECT SUMMARY The parent project (Is the gut important in multiple joint osteoarthritis? A multimodal investigation in humans and pet dogs, R01AR080733) integrates serum biomarkers and radiographic measures of the burden of the disease of OA with measures of intestinal permeability and microbiome assessments in both humans and dogs. It will significantly advance our understanding of the role of a hitherto ignored driving etiology in MJOA – altered intestinal permeability – and create a novel transspecies model platform for testing therapeutics. This proposed supplement effectively synergizes with the parent project by adding a focus on a clinically critical dimension – pain associated with multi-joint osteoarthritis (MJOA). Pain associated with OA is what patients care about. This supplement will generate data that will help us better understand the multiple factors that drive pain and uncover novel therapeutic opportunities. We will expand and enhance our existing innovative work to include novel biomarkers of pain and pain assays relevant to the pain experience in humans and in dogs. There are two core features of this integration and enhancement: 1) to extend the analysis of samples in already being collected to include promising serum biomarkers for musculoskeletal pain and enhance pain phenotyping in the human cohort; 2) to apply advanced analytical techniques to the entire data set (parent and supplemental data) allowing us to perform elegant and innovative pain phenotyping in relation to intestinal permeability, gut microbiome and burden of OA. To advance our understanding of musculoskeletal pain, we will use cutting-edge machine learning analytical approaches to understand how pain phenotype(s), microbiome enterotype(s) and biomarker endotype(s) vary together and individually to advance our understanding of the complex multi-modal and multi-dimensional pain experience of OA patients. This supplement proposal is not a stand-alone project, rather it enriches the parent project and expands the opportunities for discovery of potential pain therapeutic strategies. The combined expertise of the two PIs and teams (OA, musculoskeletal pain, application of machine learning) makes us ideally suited to perform the proposed work. Integrating the supplement work at this stage is fiscally efficient, and scientifically it will accelerate the generation of data to support new investigative strategies that will lead to a better understanding of how to mitigate musculoskeletal pain.