Abstract
Chronic musculoskeletal pain (CMP), a prevalent and heterogeneous condition characterized by persistent pain in various body parts, is a leading cause of disability worldwide and greatly affects a patient’s brain. Apart from experiencing pain, older adults with CMP also have accelerated cognitive decline and higher dementia risk with limited understanding of biological mechanism underlying the associations between CMP and dementia risk. A multiscale study to disentangle pathological brain aging from normal brain aging may reveal the underlying mechanisms. Using large-scale, cross-sectional and longitudinal cohorts (N = 9,344), we have developed an MRI-based brain age model (N = 6,725) to evaluate the difference between brain age and chronological age, termed ‘predicted age difference’ (PAD), across several common types of CMP (N = 2,427). Our study unveils significantly increased PAD in knee osteoarthritis (KOA) cohorts versus healthy controls, and validates it in an independent dataset (N = 192), suggesting a pattern of brain-aging acceleration in KOA. This acceleration was contributed by the hippocampus in both datasets and predicted memory decline and dementia incidents during follow-up. The SLC39A8 gene showed pleiotropy between brain-aging accelerations and KOA and exhibited spatially transcriptional associations with the regional contributions to brain-aging accelerations. The genes exhibiting spatially strong transcriptional associations with regional contributions were highly expressed in microglial cells and astrocytes, and were mainly enriched in synaptic structure and neurodevelopment. These findings highlight a heterogeneous pattern of brain aging in CMP and reveal a heritable morphological pattern that links brain-aging acceleration to cognitive decline and an elevated risk of dementia in KOA.
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Data availability
The MRI data are from multiple sources. The data acquired from UKB are publicly available upon third-party authorization (https://www.ukbiobank.ac.uk/register-apply). The GWAS summary statistics of KOA were downloaded from https://www.ebi.ac.uk/gwas/publications/30664745. The GWAS summary statistics for chronic hip pain, chronic back pain and chronic neck pain were downloaded from https://gwas.mrcieu.ac.uk/datasets with the category codes as ukb-b-133, ukb-b-8463 and ukb-b-16118, respectively. Human brain gene expression data in AHBA can be downloaded from http://human.brain-map.org/static/download. Individual data used to estimate brain age in dataset 2 can be accessed via ScienceDB (https://doi.org/10.57760/sciencedb.psych.00120).
Code availability
The publicly available software for the analyses has been described in the Methods of our manuscript. Our custom analysis code and the developed brain age model can be accessed at https://github.com/tulab-brain/BrainAgeCP.
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Acknowledgements
The present study utilized the UK Biobank Resource under application no. 71901. We sincerely thank all participants and researchers from the UK Biobank. The study was supported by the STI-2030 Major Project (2022ZD0206400, Y.T.), the National Natural Science Foundation of China (32171078, 32322035, Y.T.), the Scientific Foundation of the Institute of Psychology, Chinese Academy of Sciences (E0CX52 and E2CX4015, Y.T.) and the Young Elite Scientist Sponsorship Program by the China Association for Science and Technology (E1KX0210, Y.T.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
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Y.T. and J.L. conceived and designed the study. L.Z., W.Z., J.C., T.G. and J.F. analyzed and interpreted the data. J.L. was involved in data collection. L.Z. and Y.T. wrote the initial manuscript. L.Z., Y.T. and T.G. were involved in writing, reviewing and editing the manuscript. Y.T. supervised the project. All authors edited and contributed to the final version of the manuscript.
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Zhao, L., Liu, J., Zhao, W. et al. Morphological and genetic decoding shows heterogeneous patterns of brain aging in chronic musculoskeletal pain. Nat. Mental Health 2, 435–449 (2024). https://doi.org/10.1038/s44220-024-00223-3
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DOI: https://doi.org/10.1038/s44220-024-00223-3