Food insecurity and epigenetic aging in middle-aged and older adults.

BACKGROUND: Food insecurity is recognized as a key social determinant of health for older adults. While food insecurity has been associated with morbidity and mortality, few studies have examined how it may contribute to accelerated biological aging. A potential mechanism by which food insecurity may contribute to aging is via epigenetic alterations. We examined the relationship between food insecurity and epigenetic aging, a novel measure of biological aging, in a nationally representative sample of middle-aged and older adults in the United States. METHODS: Cross-sectional analysis of adults 50 years of age and older from the 2016 Health and Retirement Study (HRS). Financial food insecurity was self-reported via two questions that ascertained having enough money for food or eating less than they felt they should. Epigenetic aging was measured via epigenetic clocks based on DNA methylation patterns that predict aging correlates of morbidity and mortality. Linear regressions were performed to test for differences in the epigenetic clocks, adjusting for biological, socioeconomic, and behavioral factors. RESULTS: The analysis consisted of 3875 adults with mean age of 68.5 years. A total of 8.1% reported food insecurity. Food insecurity was associated with several characteristics, including younger age, race/ethnic minority, lower income, total wealth, and educational attainment, higher BMI, and less physical activity. Food insecurity was associated with accelerated epigenetic aging compared to food security, as measured via second (Zhang, PhenoAge, GrimAge) and third (DunedinPoAm) generation epigenetic clocks. In particular, food insecurity remained significantly associated with accelerated Zhang (B = 0.09, SE = 0.03, p = 0.011) and GrimAge (B = 0.57, SE = 0.24, p = 0.022) in the fully adjusted models. CONCLUSIONS: Food insecurity is associated with accelerated epigenetic aging among middle-aged and older adults in the United States. Food insecurity may contribute to DNA methylation alterations across the genome and biological age acceleration. These findings add to a growing understanding of the influence of socioeconomic status on the epigenome and health in aging.

Addressing Pain Using a Mediterranean Ketogenic Nutrition Program in Older Adults with Mild Cognitive Impairment.

Chronic pain has negative physical and cognitive consequences in older adults and may lead to a poorer quality of life. Mediterranean ketogenic nutrition (MKN) is a promising nonpharmacological intervention for pain management, but long-term adherence is challenging due to the carbohydrate restrictive diet regimen. The main objective of this study was to evaluate the effects of the pilot MKN Adherence (MKNA) Program on pain in older adults with mild cognitive impairment and to assess whether improvements in self-reported pain were associated with adherence to MKN. Older adults (N = 58) aged 60-85 with possible mild cognitive impairment were randomized to a 6-week MKNA arm or an MKN Education (MKNE) program arm. Both arms received the same nutrition education and group format; however, the MKNA arm received additional motivational interviewing and cognitive behavioral skills to enhance adherence. Changes in self-reported pain (Brief Pain Inventory, Roland Morris, Patient's Global Impression of Change) and adherence to MKN (ketone levels, self-reported adherence) were assessed at baseline, 6-weeks, and 3-months post intervention. Both arms showed clinically significant reductions in pain. Greater adherence to MKN across the 6-week intervention was associated with higher ratings of pain-related changes on the Patient's Global Impression of Change scale. Based on these findings, adherence to MKN may promote improvements in self-reported pain in older adults with mild cognitive impairment and findings support the need for future full-scale randomized clinical trials evaluating MKN programs on pain. Trial Registration: Clinicaltrials.gov ID: NCT04817176.

Beyond numbers: integrating qualitative analysis into quantitative sensory testing for neuropathic pain.

This article investigates the benefits of adopting qualitative and quantitative sensory testing (QQST) in sensory assessment, with a focus on understanding neuropathic pain. The innovative QQST method combines participant qualitative experiences with quantitative psychophysical measurements, offering a more varied interpretation of sensory abnormalities and normal sensory function. This article also explores the steps for the optimization of the method by identifying qualitative signs of sensory abnormalities and standardizing data collection. By leveraging the inherent subjectivity in the test design and participant responses, the QQST method contributes to a more holistic exploration of both normal and abnormal sensory experiences. This article positions the QQST approach as a foundational element within the Sensory Evaluation Network, uniting international experts to harmonize qualitative and quantitative sensory evaluation methods.

Association of Muscle Quality and Pain in Adults With Symptomatic Knee Osteoarthritis, Independent of Muscle Strength: Findings From a Cross-Sectional Study.

OBJECTIVE: Knee osteoarthritis (OA) is a leading cause of chronic pain in adults and shows wide interindividual variability, with peripheral and central factors contributing to the pain experience. Periarticular factors, such as muscle quality (eg, echo intensity [EI] and shear wave velocity [SWV]), may contribute to knee OA pain; however, the role of muscle quality in OA symptoms has yet to be fully established. METHODS: Twenty-six adults (age >50 years) meeting clinical criteria for knee OA were included in this cross-sectional study. Quantitative ultrasound imaging was used to quantify EI and SWV in the rectus femoris of the index leg. Pearson correlations followed by multiple linear regression was used to determine associations between muscle quality and pain, controlling for strength, age, sex, and body mass index. RESULTS: EI and SWV were significantly associated with movement-evoked pain (b = 0.452-0.839, P = 0.024-0.029). Clinical pain intensity was significantly associated with SWV (b = 0.45, P = 0.034), as were pressure pain thresholds at the medial (b = -0.41, P = 0.025) and lateral (b = -0.54, P = 0.009) index knee joint line, adjusting for all covariates. Pain interference was significantly associated with knee extension strength (b = -0.51, P = 0.041). CONCLUSION: These preliminary findings suggest that EI and SWV may impact knee OA pain and could serve as malleable treatment targets. Findings also demonstrate that muscle quality is a unique construct, distinct from muscle strength, which may impact pain and treatment outcomes. More research is needed to fully understand the role of muscle quality in knee OA.

Socioeconomic Status, Knee Pain, and Epigenetic Aging in Community-Dwelling Middle-to-Older Age Adults.

Chronic musculoskeletal pain is often associated with lower socioeconomic status (SES). SES correlates with psychological and environmental conditions that could contribute to the disproportionate burden of chronic stress. Chronic stress can induce changes in global DNA methylation and gene expression, which increases risk of chronic pain. We aimed to explore the association of epigenetic aging and SES in middle-to-older age individuals with varying degrees of knee pain. Participants completed self-reported pain, a blood draw, and answered demographic questions pertaining to SES. We used an epigenetic clock previously associated with knee pain (DNAmGrimAge) and the subsequent difference of predicted epigenetic age (DNAmGrimAge-Diff). Overall, the mean DNAmGrimAge was 60.3 (±7.6), and the average DNAmGrimAge-diff was 2.4 years (±5.6 years). Those experiencing high-impact pain earned less income and had lower education levels compared to both low-impact and no pain groups. Differences in DNAmGrimAge-diff across pain groups were found, whereby individuals with high-impact pain had accelerated epigenetic aging (∼5 years) compared to low-impact pain and no pain control groups (both ∼1 year). Our main finding was that epigenetic aging mediated the associations of income and education with pain impact, as such the relationship between SES and pain outcomes may occur through potential interactions with the epigenome reflective of accelerated cellular aging. PERSPECTIVE: Socioeconomic status (SES) has previously been implicated in the pain experience. The present manuscript aims to present a potential social-biological link between SES and pain via accelerated epigenetic aging.

Lower individual alpha frequency in individuals with chronic low back pain and fear of movement.

ABSTRACT: Significant progress has been made in linking measures of individual alpha frequency (IAF) and pain. A lower IAF has been associated with chronic neuropathic pain and with an increased sensitivity to pain in healthy young adults. However, the translation of these findings to chronic low back pain (cLBP) are sparse and inconsistent. To address this limitation, we assessed IAFs in a cohort of 70 individuals with cLBP, implemented 3 different IAF calculations, and separated cLBP subjects based on psychological variables. We hypothesized that a higher fear movement in cLBP is associated with a lower IAF at rest. A total of 10 minutes of resting data were collected from 128 electroencephalography channels. Our results offer 3 novel contributions to the literature. First, the high fear group had a significantly lower peak alpha frequency. The high fear group also reported higher pain and higher disability. Second, we calculated individual alpha frequency using 3 different but established methods; the effect of fear on individual alpha frequency was robust across all methods. Third, fear of movement, pain intensity, and disability highly correlated with each other and together significantly predicted IAF. Our findings are the first to show that individuals with cLBP and high fear have a lower peak alpha frequency.

Chronic Pain Among Middle-Aged and Older Adults in the United States: The Role of Everyday Discrimination and Racial/Ethnic Identity.

Chronic pain disproportionately affects middle-aged and older adults in the United States. Everyday discrimination is associated with worse pain outcomes and is more prevalent among adults from racial/ethnic minoritized groups. Yet, there is limited evidence on relationships between everyday discrimination and chronic pain among middle-aged and older adults, as well as how discrimination and racial/ethnic identity may interact to influence this relationship. We used the 2018 Health and Retirement study to evaluate associations between exposure to everyday discrimination and odds to experience any, severe, and high-impact chronic pain among 5,314 Hispanic, non-Hispanic Black, and non-Hispanic White adults over the age of 50. Logistic regression was used to evaluate the main and interaction effects of everyday discrimination on the odds of chronic pain (any, severe, and high-impact) across racial/ethnic groups. Results showed that Hispanic and non-Hispanic Black middle-aged and older adults had a higher, unadjusted prevalence of severe and high-impact chronic pain and reported more exposure to everyday discrimination compared to non-Hispanic White middle-aged and older adults. In fully adjusted models, exposure to everyday discrimination predicted higher odds to experience each type of chronic pain. In addition, study findings showed that exposure to everyday discrimination significantly raised pain risk among Hispanic and non-Hispanic White, but not non-Hispanic Black, middle-aged, and older adults. Findings underscore the influential role of everyday discrimination on the chronic pain experiences of middle-aged and older adults, as well as differential effects across racial/ethnic groups. PERSPECTIVE: Using national data, we examined associations between discrimination and chronic pain among middle-aged and older adults, including interactions between discrimination and race/ethnicity. Exposure to discrimination predicted a higher chronic pain burden, overall. Differential effects within racial/ethnic groups underscored a need for more nuanced investigations into pain disparities among this population.

A Secondary Analysis: Comparison of Experimental Pain and Psychological Impact in Individuals with Carpometacarpal and Knee Osteoarthritis.

Purpose: Evaluate sensory and psychological differences in individuals with thumb carpometacarpal (CMC) and/or knee osteoarthritis (OA) pain. This secondary analysis focuses on comparing the effects of OA at large and small joints in community-dwelling adults. Patients and Methods: A total of 434 individuals were recruited from communities in Gainesville, FL and Birmingham, AL. Each participant completed health and clinical history questionnaires, quantitative sensory testing, and physical functional tests. Participants were divided into four groups based on their pain ("CMC pain" (n = 33), "knee pain" (n = 71), "CMC + knee pain" (n = 81), and "pain-free" controls (n = 60)). ANCOVAs were performed to identify significant differences in experimental pain and psychological variables across groups. Results: The "CMC + knee pain" group had lower pressure pain thresholds (lateral knee site, p < 0.01) and higher temporal summation of mechanical pain (knee, p < 0.01) when compared to "CMC pain" and "pain-free" groups. The "knee pain" group had lower heat pain tolerance at the forearm site (p = 0.02) and higher mechanical pain (p < 0.01) at both tested sites in comparison to the "CMC pain" group. Lastly, the "CMC + knee pain" group had the highest self-reported pain (p < 0.01) and disability (p < 0.01) compared to all other groups. Conclusion: Results suggest knee OA compounded with CMC OA increases disease impact and decreases emotional health compared to OA at either the CMC or knee joint alone. Results also support a relationship between the number of painful joints and enhanced widespread pain sensitivity. Measuring pain at sites other than the primary OA location is important and could contribute to more holistic treatment and prevention of OA progression.

Food insecurity is associated with chronic pain and high-impact chronic pain in the USA.

OBJECTIVE: This study evaluated whether food insecurity (US Adult Food Security Survey) was associated with chronic pain (≥ 3 months) and high-impact chronic pain (i.e. pain that limits work and life) among US adults. DESIGN: Cross-sectional analysis. SETTING: Nationally representative sample of non-institutionalised adults in the USA. PARTICIPANTS: 79 686 adults from the National Health Interview Survey (2019-2021). RESULTS: Marginal, low and very low food security were associated with increased prevalence odds of chronic pain (OR: 1·58 (95 % CI 1·44, 1·72), 2·28 (95 % CI 2·06, 2·52) and 3·37 (95 % CI 3·01, 3·78), respectively) and high-impact chronic pain (OR: 1·28 (95 % CI 1·14, 1·42), 1·55 (95 % CI 1·37, 1·75) and 1·90 (95 % CI 1·65, 2·18), respectively) in a dose-response fashion (P-trend < 0·0001 for both), adjusted for sociodemographic, socio-economic and clinically relevant factors. Participation in Supplemental Nutrition Assistance Program (SNAP) and age modified the association between food insecurity and chronic pain. CONCLUSIONS: These findings illustrate the impact of socio-economic factors on chronic pain and suggest that food insecurity may be a social determinant of chronic pain. Further research is needed to better understand the complex relationship between food insecurity and chronic pain and to identify targets for interventions. Moreover, the consideration of food insecurity in the clinical assessment of pain and pain-related conditions among socio-economically disadvantaged adults may be warranted.

Accelerated Brain Aging Mediates the Association Between Psychological Profiles and Clinical Pain in Knee Osteoarthritis.

Chronic pain is driven by factors across the biopsychosocial spectrum. Previously, we demonstrated that magnetic resonance images (MRI)-based brain-predicted age differences (brain-PAD: brain-predicted age minus chronological age) were significantly associated with pain severity in individuals with chronic knee pain. We also previously identified four distinct, replicable, multidimensional psychological profiles significantly associated with clinical pain. The brain aging-psychological characteristics interface in persons with chronic pain promises elucidating factors contributing to their poor health outcomes, yet this relationship is barely understood. That is why we examined the interplay between the psychological profiles in participants having chronic knee pain impacting function, brain-PAD, and clinical pain severity. Controlling for demographics and MRI scanner, we compared the brain-PAD among psychological profiles at baseline (n = 164) and over two years (n = 90). We also explored whether profile-related differences in pain severity were mediated by brain-PAD. Brain-PAD differed significantly between profiles (ANOVA's omnibus test, P = .039). Specifically, participants in the profile 3 group (high negative/low positive emotions) had an average brain-PAD ∼4 years higher than those in profile- (low somatic reactivity), with P = .047, Bonferroni-corrected, and than those in profile 2 (high coping), with P = .027, uncorrected. Repeated measures ANOVA revealed no significant change in profile-related brain-PAD differences over time, but there was a significant decrease in brain-PAD for profile 4 (high optimism/high positive affect), with P = .045. Moreover, profile-related differences in pain severity at baseline were partly explained by brain-PAD differences between profile 3 and 1, or 2; but brain-PAD did not significantly mediate the influence of variations in profiles on changes in pain severity over time. PERSPECTIVE: Accelerated brain aging could underlie the psychological-pain relationship, and psychological characteristics may predispose individuals with chronic knee pain to worse health outcomes via neuropsychological processes.

Feasibility of brain age predictions from clinical T1-weighted MRIs.

An individual's brain predicted age minus chronological age (brain-PAD) obtained from MRIs could become a biomarker of disease in research studies. However, brain age reports from clinical MRIs are scant despite the rich clinical information hospitals provide. Since clinical MRI protocols are meant for specific clinical purposes, performance of brain age predictions on clinical data need to be tested. We explored the feasibility of using DeepBrainNet, a deep network previously trained on research-oriented MRIs, to predict the brain ages of 840 patients who visited 15 facilities of a health system in Florida. Anticipating a strong prediction bias in our clinical sample, we characterized it to propose a covariate model in group-level regressions of brain-PAD (recommended to avoid Type I, II errors), and tested its generalizability, a requirement for meaningful brain age predictions in new single clinical cases. The best bias-related covariate model was scanner-independent and linear in age, while the best method to estimate bias-free brain ages was the inverse of a scanner-independent and quadratic in brain age function. We demonstrated the feasibility to detect sex-related differences in brain-PAD using group-level regression accounting for the selected covariate model. These differences were preserved after bias correction. The Mean-Average Error (MAE) of the predictions in independent data was ∼8 years, 2-3 years greater than reports for research-oriented MRIs using DeepBrainNet, whereas an R2 (assuming no bias) was 0.33 and 0.76 for the uncorrected and corrected brain ages, respectively. DeepBrainNet on clinical populations seems feasible, but more accurate algorithms or transfer-learning retraining is needed.

Toward MR protocol-agnostic, unbiased brain age predicted from clinical-grade MRIs.

The difference between the estimated brain age and the chronological age ('brain-PAD') could become a clinical biomarker. However, most brain age models were developed for research-grade high-resolution T1-weighted MRIs, limiting their applicability to clinical-grade MRIs from various protocols. We adopted a dual-transfer learning strategy to develop a model agnostic to modality, resolution, or slice orientation. We retrained a convolutional neural network (CNN) using 6281 clinical MRIs from 1559 patients, among 7 modalities and 8 scanner models. The CNN was trained to estimate brain age from synthetic research-grade magnetization-prepared rapid gradient-echo MRIs (MPRAGEs) generated by a 'super-resolution' method. The model failed with T2-weighted Gradient-Echo MRIs. The mean absolute error (MAE) was 5.86-8.59 years across the other modalities, still higher than for research-grade MRIs, but comparable between actual and synthetic MPRAGEs for some modalities. We modeled the "regression bias" in brain age, for its correction is crucial for providing unbiased summary statistics of brain age or for personalized brain age-based biomarkers. The bias model was generalizable as its correction eliminated any correlation between brain-PAD and chronological age in new samples. Brain-PAD was reliable across modalities. We demonstrate the feasibility of brain age predictions from arbitrary clinical-grade MRIs, thereby contributing to personalized medicine.

More Problems, More Pain: The Role of Chronic Life Stressors and Racial/Ethnic Identity on Chronic Pain Among Middle-Aged and Older Adults in the United States.

There is a high prevalence of chronic pain among middle-aged and older adults in the United States. Chronic life stressors have been shown to have detrimental consequences for myriad health conditions, including chronic pain. However, there is limited evidence on the types of chronic life stressors that affect middle-aged and older adults and how these stressors influence the chronic pain burden in this population. Moreover, the interaction between chronic life stressors and racial/ethnic identity remains poorly understood as it relates to chronic pain. The current analysis used the 2018 Health and Retirement Study to investigate relationships between chronic life stressors and odds to experience any chronic pain and high-impact chronic pain. Chronic life stressors were characterized, overall and by racial/ethnic identity, and the main and interaction effects were calculated to evaluate relationships between chronic life stressors, racial/ethnic identity, and odds of experiencing any chronic pain and high-impact chronic pain. Results indicate that in 2018, the most common chronic life stressor among middle-aged and older adults was dealing with their own health problems (68%), followed by dealing with the physical or emotional issues affecting a spouse or child (46%). Adjusted analyses showed that a higher total of chronic life stressors increased the odds of middle-aged and older adults experiencing any chronic pain and high-impact chronic pain. There were no significant interactions between the overall chronic life stress burden and racial/ethnic identity as a predictor of odds to experience any chronic pain or high-impact chronic pain, but significant interaction effects were found related to specific chronic life stressors. Findings underscore the significant impact of chronic life stressors on the chronic pain burden among middle-aged and older adults in the United States, which cut across racial/ethnic identity.

Weight-cycling over 6 years is associated with pain, physical function and depression in the Osteoarthritis Initiative cohort.

Body weight significantly impacts health and quality of life, and is a leading risk factor for the development of knee osteoarthritis (OA). Weight cycling may have more negative health consequences compared to steady high or low weight. Using the Osteoarthritis Initiative dataset, we investigated the effects of weight cycling on physical function, quality of life, and depression over 72-months compared to stable or unidirectional body weight trajectories. Participants (n = 731) had knee OA and were classified as: (1) stable-low (BMI < 25), (2) stable-overweight (BMI = 25-29.9), and (3) stable-obese (BMI ≥ 30); (4) steady-weight-loss; (5) steady-weight-gain (weight loss/gain ≥ 2.2 kg every 2-years); (6) gain-loss-gain weight cycling, and (7) loss-gain-loss weight cycling (weight loss/gain with return to baseline), based on bi-annual assessments. We compared Knee Injury and Osteoarthritis Outcome Knee-Related Quality of Life, Function in Sports and Recreation, Physical Activity in the Elderly, Short Form SF-12, repeated chair rise, 20-m gait speed, and Center for Epidemiological Studies Depression using repeated-measures ANOVA. The steady weight loss group demonstrated the worst pain, physical function, and depressive symptoms over time (p's < 0.05). More research is needed to confirm these findings, and elucidate the mechanisms by which steady weight loss is associated with functional decline in knee OA.

Toward MR protocol-agnostic, bias-corrected brain age predicted from clinical-grade MRIs.

The predicted brain age minus the chronological age ('brain-PAD') could become a clinical biomarker. However, most brain age methods were developed to use research-grade high-resolution T1-weighted MRIs, limiting their applicability to clinical-grade MRIs from multiple protocols. To overcome this, we adopted a double transfer learning approach to develop a brain age model agnostic to modality, resolution, or slice orientation. Using 6,224 clinical MRIs among 7 modalities, scanned from 1,540 patients using 8 scanners among 15 + facilities of the University of Florida's Health System, we retrained a convolutional neural network (CNN) to predict brain age from synthetic research-grade magnetization-prepared rapid gradient-echo MRIs (MPRAGEs) generated by a deep learning-trained 'super-resolution' method. We also modeled the "regression dilution bias", a typical overestimation of younger ages and underestimation of older ages, which correction is paramount for personalized brain age-based biomarkers. This bias was independent of modality or scanner and generalizable to new samples, allowing us to add a bias-correction layer to the CNN. The mean absolute error in test samples was 4.67-6.47 years across modalities, with similar accuracy between original MPRAGEs and their synthetic counterparts. Brain-PAD was also reliable across modalities. We demonstrate the feasibility of clinical-grade brain age predictions, contributing to personalized medicine.

Electrical Brain Activity during Human Walking with Parametric Variations in Terrain Unevenness and Walking Speed.

Mobile brain imaging with high-density electroencephalography (EEG) can provide insight into the cortical processes involved in complex human walking tasks. While uneven terrain is common in the natural environment and poses challenges to human balance control, there is limited understanding of the supraspinal processes involved with traversing uneven terrain. The primary objective of this study was to quantify electrocortical activity related to parametric variations in terrain unevenness for neurotypical young adults. We used high-density EEG to measure brain activity when thirty-two young adults walked on a novel custom-made uneven terrain treadmill surface with four levels of difficulty at a walking speed tailored to each participant. We identified multiple brain regions associated with uneven terrain walking. Alpha (8 - 13 Hz) and beta (13 - 30 Hz) spectral power decreased in the sensorimotor and posterior parietal areas with increasing terrain unevenness while theta (4 - 8 Hz) power increased in the mid/posterior cingulate area with terrain unevenness. We also found that within stride spectral power fluctuations increased with terrain unevenness. Our secondary goal was to investigate the effect of parametric changes in walking speed (0.25 m/s, 0.5m/s, 0.75 m/s, 1.0 m/s) to differentiate the effects of walking speed from uneven terrain. Our results revealed that electrocortical activities only changed substantially with speed within the sensorimotor area but not in other brain areas. Together, these results indicate there are distinct cortical processes contributing to the control of walking over uneven terrain versus modulation of walking speed on smooth, flat terrain. Our findings increase our understanding of cortical involvement in an ecologically valid walking task and could serve as a benchmark for identifying deficits in cortical dynamics that occur in people with mobility deficits.

Brain-predicted age difference mediates the association between PROMIS sleep impairment, and self-reported pain measure in persons with knee pain.

Knee pain, the most common cause of musculoskeletal pain (MSK), constitutes a severe public health burden. Its neurobiological causes, however, remain poorly understood. Among many possible causes, it has been proposed that sleep problems could lead to an increase in chronic pain symptomatology, which may be driven by central nervous system changes. In fact, we previously found that brain cortical thickness mediated the relationship between sleep qualities and pain severity in older adults with MSK. We also demonstrated a significant difference in a machine-learning-derived brain-aging biomarker between participants with low-and high-impact knee pain. Considering this, we examined whether brain aging was associated with self-reported sleep and pain measures, and whether brain aging mediated the relationship between sleep problems and knee pain. Exploratory Spearman and Pearson partial correlations, controlling for age, sex, race and study site, showed a significant association of brain aging with sleep related impairment and self-reported pain measures. Moreover, mediation analysis showed that brain aging significantly mediated the effect of sleep related impairment on clinical pain and physical symptoms. Our findings extend our prior work demonstrating advanced brain aging among individuals with chronic pain and the mediating role of brain-aging on the association between sleep and pain severity. Future longitudinal studies are needed to further understand whether the brain can be a therapeutic target to reverse the possible effect of sleep problems on chronic pain.