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      Cortical Thickness Mediates the Association Between Self-Reported Pain and Sleep Quality in Community-Dwelling Older Adults

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          Musculoskeletal pain is prevalent in older adults representing the leading cause of disability in this population. Similarly, nearly half of older adults complain of difficulty sleeping. We aimed to explore the relationship between sleep quality with self-reported musculoskeletal pain, somatosensory and pain thresholds in community-dwelling older adults and further explore brain regions that may contribute to this association.


          Older adults (>60 years old, n=69) from the NEPAL study completed demographic, pain and sleep assessments followed by a quantitative sensory testing battery. A subset (n=49) also underwent a 3T high-resolution, T1-weighted anatomical scan.


          Poorer sleep quality using the Pittsburgh Sleep Quality Index was positively associated with self-reported pain measures (all p’s >0.05), but not somatosensory and pain thresholds (all p’s >0.05). Using a non-parametric threshold-free cluster enhancement (TFCE) approach, worse sleep quality was significantly associated with lower cortical thickness in the precentral, postcentral, precuneus, superior parietal, and lateral occipital regions (TFCE-FWE-corrected at p < 0.05). Further, only postcentral cortical thickness significantly mediated the association between sleep quality and self-reported pain intensity using bootstrapped mediation methods.


          Our findings in older adults are similar to previous studies in younger individuals where sleep is significantly associated with self-reported pain. Specifically, our study implicates brain structure as a significant mediator of this association in aging. Future larger studies are needed to replicate our findings and to further understand if the brain can be a therapeutic target for both improved sleep and pain relief in older individuals.

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          Most cited references 38

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          Cortical thickness and central surface estimation.

          Several properties of the human brain cortex, e.g., cortical thickness and gyrification, have been found to correlate with the progress of neuropsychiatric disorders. The relationship between brain structure and function harbors a broad range of potential uses, particularly in clinical contexts, provided that robust methods for the extraction of suitable representations of the brain cortex from neuroimaging data are available. One such representation is the computationally defined central surface (CS) of the brain cortex. Previous approaches to semi-automated reconstruction of this surface relied on image segmentation procedures that required manual interaction, thereby rendering them error-prone and complicating the analysis of brains that were not from healthy human adults. Validation of these approaches and thickness measures is often done only for simple artificial phantoms that cover just a few standard cases. Here, we present a new fully automated method that allows for measurement of cortical thickness and reconstructions of the CS in one step. It uses a tissue segmentation to estimate the WM distance, then projects the local maxima (which is equal to the cortical thickness) to other GM voxels by using a neighbor relationship described by the WM distance. This projection-based thickness (PBT) allows the handling of partial volume information, sulcal blurring, and sulcal asymmetries without explicit sulcus reconstruction via skeleton or thinning methods. Furthermore, we introduce a validation framework using spherical and brain phantoms that confirms accurate CS construction and cortical thickness measurement under a wide set of parameters for several thickness levels. The results indicate that both the quality and computational cost of our method are comparable, and may be superior in certain respects, to existing approaches.
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            How do sleep disturbance and chronic pain inter-relate? Insights from the longitudinal and cognitive-behavioral clinical trials literature.

            Sleep disturbance is perhaps one of the most prevalent complaints of patients with chronically painful conditions. Experimental studies of healthy subjects and cross-sectional research in clinical populations suggest the possibility that the relationship between sleep disturbance and pain might be reciprocal, such that pain disturbs sleep continuity/quality and poor sleep further exacerbates pain. This suggests that aggressive management of sleep disturbance may be an important treatment objective with possible benefits beyond the improvement in sleep. Little is known, however, about how to effectively treat sleep disturbance associated with pain or whether such treatment might have beneficial effects on reducing pain. A small, but growing literature has applied cognitive-behavioral therapies (CBT) for either pain management or insomnia to patients with chronic pain. In this article, we review the longitudinal literature on sleep disturbance associated with chronic pain and clinical trial literatures of cognitive-behavior therapy for pain management and insomnia secondary to chronic pain with the aim of evaluating whether the relationship between clinical pain and insomnia is reciprocal. While methodological problems are common, the literature suggests that the relationship is reciprocal and CBT treatments for pain or insomnia hold promise in reducing pain severity and improving sleep quality. Directions for future research include the use of validated measures of sleep, longitudinal studies, and larger randomized clinical trials incorporating appropriate attentional controls and longer periods of follow-up.
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              Corticolimbic anatomical characteristics predetermine risk for chronic pain.

              SEE TRACEY DOI101093/BRAIN/AWW147 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE: Mechanisms of chronic pain remain poorly understood. We tracked brain properties in subacute back pain patients longitudinally for 3 years as they either recovered from or transitioned to chronic pain. Whole-brain comparisons indicated corticolimbic, but not pain-related circuitry, white matter connections predisposed patients to chronic pain. Intra-corticolimbic white matter connectivity analysis identified three segregated communities: dorsal medial prefrontal cortex-amygdala-accumbens, ventral medial prefrontal cortex-amygdala, and orbitofrontal cortex-amygdala-hippocampus. Higher incidence of white matter and functional connections within the dorsal medial prefrontal cortex-amygdala-accumbens circuit, as well as smaller amygdala volume, represented independent risk factors, together accounting for 60% of the variance for pain persistence. Opioid gene polymorphisms and negative mood contributed indirectly through corticolimbic anatomical factors, to risk for chronic pain. Our results imply that persistence of chronic pain is predetermined by corticolimbic neuroanatomical factors.

                Author and article information

                J Pain Res
                Journal of Pain Research
                24 September 2020
                : 13
                : 2389-2400
                [1 ]Department of Community Dentistry & Behavioral Sciences, University of Florida , Gainesville, FL, USA
                [2 ]Center for Cognitive Aging and Memory, McKnight Brain Foundation, University of Florida , Gainesville, FL, USA
                [3 ]University of Central , Florida College of Medicine, Orlando, FL, USA
                [4 ]Department of Neuroscience, College of Medicine, University of Florida , Gainesville, FL, USA
                [5 ]Department of Clinical and Health Psychology, College of Health Professions, University of Florida , Gainesville, FL, USA
                [6 ]Department of Biostatistics, College of Public Health and Health Professions College of Medicine, University of Florida , Gainesville, FL, USA
                [7 ]Institute on Aging, University of Florida , Gainesville, FL, USA
                Author notes
                Correspondence: Yenisel Cruz-Almeida Pain Research and Intervention Center of Excellence, University of Florida , PO BOX 112610, Gainesville, FL326010, USATel +1 352-294-5845Fax +1 352-273-5920 Email cryeni@ufl.edu
                © 2020 Montesino-Goicolea et al.

                This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms ( https://www.dovepress.com/terms.php).

                Page count
                Figures: 3, Tables: 7, References: 52, Pages: 12
                Original Research

                Anesthesiology & Pain management

                chronic pain, sleep quality, sleep, brain, aging


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