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56 Chronic Musculoskeletal Pain, Biobehavioral and Psychosocial Resilience Index, and Brain Age Gap
- Udell Holmes III, Jared Tanner, Brittany Addison, Kenia Rangel, Angela M Mickle, Cynthia S Garvan, Emily J Bartley, Amber K Brooks, Lai Song, Roland Staud, Burel Goodin, Roger B Fillingim, Catherine C Price, Kimberly T Sibille
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, p. 465
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Objective:
Chronic musculoskeletal pain is associated with neurobiological, physiological, and cellular measures. Importantly, we have previously demonstrated that a biobehavioral and psychosocial resilience index appears to have a protective relationship on the same biomarkers. Less is known regarding the relationships between chronic musculoskeletal pain, protective factors, and brain aging. This study investigates the relationships between clinical pain, a resilience index, and brain age. We hypothesized that higher reported chronic pain would correlate with older appearing brains, and the resilience index will attenuate the strength of the relationship between chronic pain and brain age.
Participants and Methods:Participants were drawn from an ongoing observational multisite study and included adults with chronic pain who also reported knee pain (N = 135; age = 58.3 ± 8.1; 64% female; 49% non-Hispanic Black, 51% non-Hispanic White; education Mdn = some college; income level Mdn = $30,000 - $40,000; MoCA M = 24.27 ± 3.49). Measures included the Graded Chronic Pain Scale (GCPS), characteristic pain intensity (CPI) and disability, total pain body sites; and a cognitive screening (MoCA). The resilience index consisted of validated biobehavioral (e.g., smoking, waist/hip ratio, and active coping) and psychosocial measures (e.g., optimism, positive affect, negative affect, perceived stress, and social support). T1-weighted MRI data were obtained. Surface area metrics were calculated in FreeSurfer using the Human Connectome Project's multi-modal cortical parcellation scheme. We calculated brain age in R using previously validated and trained machine learning models. Chronological age was subtracted from predicted brain age to generate a brain age gap (BAG). With higher scores of BAG indicating predicated age is older than chronological age. Three parallel hierarchical regression models (each containing one of three pain measures) with three blocks were performed to assess the relationships between chronic pain and the resilience index in relation to BAG, adjusting for covariates. For each model, Block 1 entered the covariates, Block 2 entered a pain score, and Block 3 entered the resilience index.
Results:GCPS CPI (R2 change = .033, p = .027) and GCPS disability (R2 change = 0.038, p = 0.017) significantly predicted BAG beyond the effects of the covariates, but total pain sites (p = 0.865) did not. The resilience index was negatively correlated and a significant predictor of BAG in all three models (p < .05). With the resilience index added in Block 3, both GCPS CPI (p = .067) and GCPS disability (p = .066) measures were no longer significant in their respective models. Additionally, higher education/income (p = 0.016) and study site (p = 0.031) were also significant predictors of BAG.
Conclusions:In this sample, higher reported chronic pain correlated with older appearing brains, and higher resilience attenuated this relationship. The biobehavioral and psychosocial resilience index was associated with younger appearing brains. While our data is cross-sectional, findings are encouraging that interventions targeting both chronic pain and biobehavioral and psychosocial factors (e.g., coping strategies, positive and negative affect, smoking, and social support) might buffer brain aging. Future directions include assessing if chronic pain and resilience factors can predict brain aging over time.
Avera Twin Register Growing Through Online Consenting and Survey Collection
- Julie M. Kittelsrud, Erik A. Ehli, Vikki Petersen, Tammy Jung, Jeffrey J. Beck, Noah Kallsen, Patricia Huizenga, Brittany Holm, Gareth E. Davies
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- Journal:
- Twin Research and Human Genetics / Volume 22 / Issue 6 / December 2019
- Published online by Cambridge University Press:
- 14 October 2019, pp. 686-690
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The aim of the Avera Twin Register (ATR) is to establish a prospective longitudinal repository of twins, multiples, siblings and family members’ biological samples to study environmental and genetic influences on health and disease. Also, it is our intention to contribute to international genome-wide association study (GWAS) twin consortia when appropriate sample size is achieved within the ATR. The ATR is young compared with existing registers and continues to collect a longitudinal repository of biological specimens, survey data and health information. Data and biological specimens were originally collected via face-to-face appointments or the postal department and consisted of paper-informed consents and questionnaires. Enrollment of the ATR began on May 18, 2016 and is located in Sioux Falls, South Dakota, a rural and frontier area in the Central United States with a regional population of approximately 880,000. The original target area for the ATR was South Dakota and the four surrounding states: Minnesota, Iowa, North Dakota and Nebraska. The ATR has found a need to expand that area based on twin and multiple siblings who live in various areas surrounding these states. A description of the state of the ATR today and its transition to online data collection and informed consent will be presented. The ATR collects longitudinal data on lifestyle, including diet and activity levels, aging, plus complex traits and diseases. All twins and multiples participating in the ATR are genotyped on the Illumina Global Screening Array and receive zygosity results.
Relationships between Ligustrum sinense Invasion, Biodiversity, and Development in a Mixed Bottomland Forest
- Justin L. Hart, Brittany N. Holmes
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- Journal:
- Invasive Plant Science and Management / Volume 6 / Issue 1 / March 2013
- Published online by Cambridge University Press:
- 20 January 2017, pp. 175-186
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Invasion of closed canopy forests by shade-tolerant alien plants has the potential to modify species composition, stand structure, ecosystem function, and long-term forest development patterns. Ligustrum sinense is a shade-tolerant alien shrub that has invaded bottomland forests throughout the southeastern United States. This species has received comparatively little attention in the literature despite its potential to drastically alter invaded sites. The overarching goal of our study was to document the relationships between Ligustrum sinense invasion and woody plant biodiversity and development patterns in an intact southeastern U.S. bottomland forest. The forest was dominated by Quercus nigra and Liquidambar styraciflua. Ligustrum sinense ranked fifth in basal area contribution, occurred in 97% of our plots, and represented 95% of all understory stems. Spearman's rho for dominance (based on basal area of stems > 5 cm diameter at breast height [dbh]) of L. sinense and woody plant species richness for each plot revealed a significant negative relationship (rs = −0.69, P < 0.01). A similar relationship was revealed between L. sinense density and woody plant species diversity (rs = −0.78, P < 0.01) and evenness (rs = −0.82, P < 0.01). Spearman's rho for L. sinense density and native understory stem density (individuals ≥ 1 m height, < 5 cm dbh) also revealed a significant negative association (rs = −0.48, P < 0.01). Under the current disturbance regime and without active management, we projected the forest would shift to support a stronger component of L. sinense and that structure would transition from tree to shrub dominance for sites within the forest.