Brain Aging and Chronic Pain: A Replication Study in Knee Osteoarthritis

Abstract

We have previously reported that older adults with chronic musculoskeletal pain had significantly older-appearing brains compared to older controls in a small, mainly Non-Hispanic white sample of individuals. We employed a machine-learning derived brain aging biomarker that compares voxel-wise gray and white matter volume images to a statistical model that accurately predicts chronological age from neuroimaging data in healthy people. The present study aimed to extend our previous findings to a larger, younger, and more racially diverse sample of individuals with knee osteoarthritis (OA) pain. Participants (mean age=58 years) with severe (n=100) and mild knee pain (n=51) as well as age-matched controls (n=54) completed demographic, psychological and self-reported and experimental pain assessments along with a T1-weighted MRI scan. We estimated a brain-predicted age difference (brain-PAD) calculated as brain-predicted age minus chronological age. Analyses of covariances and correlations were used to determine associations of brain-PAD with pain and psychological variables. Age-matched controls had significantly younger brains for their age compared to individuals with the most severe knee pain (Bonferroni-p=0.023). Lower self-reported pain intensity and disability were significantly associated with a younger brain (p's