More than chronic pain: behavioural and psychosocial protective factors predict lower brain age in adults with/at risk of knee osteoarthritis over two years.

IF 4.5 Q1 CLINICAL NEUROLOGY
Brain communications Pub Date : 2025-09-11 eCollection Date: 2025-01-01 DOI:10.1093/braincomms/fcaf344
Jared J Tanner, Angela Mickle, Udell Holmes, Brittany Addison, Kenia Rangel, Cynthia Garvan, Roland Staud, Song Lai, David Redden, Burel R Goodin, Catherine C Price, Roger B Fillingim, Kimberly T Sibille
{"title":"More than chronic pain: behavioural and psychosocial protective factors predict lower brain age in adults with/at risk of knee osteoarthritis over two years.","authors":"Jared J Tanner, Angela Mickle, Udell Holmes, Brittany Addison, Kenia Rangel, Cynthia Garvan, Roland Staud, Song Lai, David Redden, Burel R Goodin, Catherine C Price, Roger B Fillingim, Kimberly T Sibille","doi":"10.1093/braincomms/fcaf344","DOIUrl":null,"url":null,"abstract":"<p><p>The interplay between chronic musculoskeletal pain and brain ageing is complex. Studies employing machine learning models to assess relationships between brain age and chronic pain generally show that higher chronic pain severity associates with older brain age. Analyses to date have not considered individual and community-level socioenvironmental risk factors or behavioural/psychosocial protective factors as potential modifiers of cross-sectional and longitudinal brain age. This study aimed to elucidate the relationships between chronic pain, socioenvironmental risk, behavioural/psychosocial protective factors, and brain ageing. The sample comprised 197 adults (Men:Women = 68:129) from a prospective observational cohort study. Most individuals reported knee pain and were with/at risk of osteoarthritis. A subset of 128 participants (Men:Women = 41:87) completed a follow-up MRI session at 2 years and were included in the longitudinal analysis (Aim 2). Participants were 45-85 years of age and self-identified as non-Hispanic Black or non-Hispanic White. Data collected included demographics, health history, pain assessments, individual and community-level socioenvironmental factors (education, income, household size, marital and insurance status, and area deprivation index) coded as a summative socioenvironmental risk variable, and behavioural/psychosocial factors (tobacco use, waist circumference, optimism, positive and negative affect, perceived stress, perceived social support, sleep) coded as a summative behavioural/psychosocial protective factor variable. Structural MRI data were used to estimate brain age by applying a machine learning approach (DeepBrainNet). Cross-sectional analyses utilized regression and analysis of variance, while longitudinal analyses utilized a linear mixed model. Higher chronic pain stage and socioenvironmental risk are associated with an increased brain age gap (the difference between chronological age and predicted brain age). Participants who had higher socioenvironmental risk had brains that were about three years older than those of participants with lower risk. Having more behavioural/psychosocial protective factors correlated with a lower brain age gap; participants with higher behavioural/psychosocial protective factors had brains that were over three years younger than participants with fewer behavioural/psychosocial protective factors. Longitudinally, higher baseline behavioural/psychosocial protective factors are associated with lower brain age over the 2-year span, beyond the effects of chronic pain stage and socioenvironmental risk. Our findings show behavioural/psychosocial protective factors may counteract neurobiological ageing and help buffer the brain from chronic pain.</p>","PeriodicalId":93915,"journal":{"name":"Brain communications","volume":"7 5","pages":"fcaf344"},"PeriodicalIF":4.5000,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12465110/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Brain communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/braincomms/fcaf344","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

The interplay between chronic musculoskeletal pain and brain ageing is complex. Studies employing machine learning models to assess relationships between brain age and chronic pain generally show that higher chronic pain severity associates with older brain age. Analyses to date have not considered individual and community-level socioenvironmental risk factors or behavioural/psychosocial protective factors as potential modifiers of cross-sectional and longitudinal brain age. This study aimed to elucidate the relationships between chronic pain, socioenvironmental risk, behavioural/psychosocial protective factors, and brain ageing. The sample comprised 197 adults (Men:Women = 68:129) from a prospective observational cohort study. Most individuals reported knee pain and were with/at risk of osteoarthritis. A subset of 128 participants (Men:Women = 41:87) completed a follow-up MRI session at 2 years and were included in the longitudinal analysis (Aim 2). Participants were 45-85 years of age and self-identified as non-Hispanic Black or non-Hispanic White. Data collected included demographics, health history, pain assessments, individual and community-level socioenvironmental factors (education, income, household size, marital and insurance status, and area deprivation index) coded as a summative socioenvironmental risk variable, and behavioural/psychosocial factors (tobacco use, waist circumference, optimism, positive and negative affect, perceived stress, perceived social support, sleep) coded as a summative behavioural/psychosocial protective factor variable. Structural MRI data were used to estimate brain age by applying a machine learning approach (DeepBrainNet). Cross-sectional analyses utilized regression and analysis of variance, while longitudinal analyses utilized a linear mixed model. Higher chronic pain stage and socioenvironmental risk are associated with an increased brain age gap (the difference between chronological age and predicted brain age). Participants who had higher socioenvironmental risk had brains that were about three years older than those of participants with lower risk. Having more behavioural/psychosocial protective factors correlated with a lower brain age gap; participants with higher behavioural/psychosocial protective factors had brains that were over three years younger than participants with fewer behavioural/psychosocial protective factors. Longitudinally, higher baseline behavioural/psychosocial protective factors are associated with lower brain age over the 2-year span, beyond the effects of chronic pain stage and socioenvironmental risk. Our findings show behavioural/psychosocial protective factors may counteract neurobiological ageing and help buffer the brain from chronic pain.

超过慢性疼痛:行为和社会心理保护因素预测患有/有患膝骨关节炎风险的成年人两年内脑年龄较低。
慢性肌肉骨骼疼痛和大脑老化之间的相互作用是复杂的。利用机器学习模型评估脑龄和慢性疼痛之间关系的研究通常表明,慢性疼痛严重程度越高,脑龄越大。迄今为止的分析还没有考虑到个人和社区水平的社会环境风险因素或行为/社会心理保护因素是横断面和纵向脑年龄的潜在调节因素。本研究旨在阐明慢性疼痛、社会环境风险、行为/心理社会保护因素与脑老化之间的关系。样本包括来自前瞻性观察队列研究的197名成年人(男性:女性= 68:129)。大多数人报告膝关节疼痛,并有骨关节炎的风险。128名参与者(男性:女性= 41:87)在随访2年后完成了MRI随访,并纳入了纵向分析(目的2)。参与者年龄在45-85岁之间,自我认定为非西班牙裔黑人或非西班牙裔白人。收集的数据包括人口统计、健康史、疼痛评估、个人和社区层面的社会环境因素(教育、收入、家庭规模、婚姻和保险状况以及地区剥夺指数)编码为总结性社会环境风险变量,以及行为/社会心理因素(烟草使用、腰围、乐观、积极和消极影响、感知压力、感知社会支持、睡眠)编码为总结性行为/社会心理保护因素变量。结构MRI数据通过应用机器学习方法(DeepBrainNet)来估计大脑年龄。横断面分析采用回归和方差分析,而纵向分析采用线性混合模型。较高的慢性疼痛阶段和社会环境风险与脑年龄差距(实际年龄与预测脑年龄之间的差异)的增加有关。社会环境风险较高的参与者的大脑年龄比风险较低的参与者大3岁左右。行为/社会心理保护因素越多,大脑年龄差距越小;行为/社会心理保护因素较高的参与者的大脑比行为/社会心理保护因素较少的参与者年轻3岁以上。纵向上,较高的基线行为/社会心理保护因素与2年内较低的脑年龄相关,超出了慢性疼痛阶段和社会环境风险的影响。我们的研究结果表明,行为/社会心理保护因素可能会抵消神经生物学老化,并有助于缓冲大脑的慢性疼痛。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
7.00
自引率
0.00%
发文量
0
审稿时长
6 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信