Uncovering associations between data-driven learned qMRI biomarkers and chronic pain
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ABSTRACT:
SUBMITTER: Morales A
PROVIDER: S-EPMC8578418 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe triallelic serotonin transporter gene linked polymorphic region (5-HTTLPR) has been associated with alterations in thermal pain perception. The primary aim of this study was to investigate the associations between heat pain (HP) perception and the triallelic 5-HTTLPR in a large cohort of adults with chronic pain.MethodsThe cohort included 277 adults with chronic pain who met inclusion criteria, and were consecutively admitted to an outpatient pain rehabilitation program from March 2009 through March 2010. Individuals were genotyped for the triallelic 5-HTTLPR (including rs25531) and categorized as high, intermediate, or low expressors of the serotonin transporter. Standardized measures of HP perception were obtained using a validated quantitative sensory test method of levels.ResultsThe distribution of the high, intermediate, and low expressing genotypes was 61 (22%), 149 (54%) and 67 (24%), respectively. The Hardy-Weinberg P-value was 0.204 which indicated no departure from equilibrium. A significant effect of genotype was observed for values of HP threshold (P = 0.029). Individual group comparisons showed that values of HP threshold were significantly greater in the intermediate compared to the high expressing group (P = 0.009) but not the low expressing group (P > 0.1). In a multiple variable linear regression model, the intermediate group (P = 0.034) and male sex (P = 0.021) were associated with significantly greater values of HP 0.5, but no significant genotype-by-sex interaction effect was observed.ConclusionsIn this study that involved adults with chronic pain, the intermediate triallelic 5-HTTLPR expressing group, but not the low expressing group, was associated with greater HP thresholds compared to the high expressing group.
| S-EPMC3737051 | biostudies-literature
Project description:Elevated inflammatory cytokines and chronic pain are associated with shorter leukocyte telomere length (LTL), a measure of cellular aging. Micronutrients, such as 25-hydroxyvitamin D (vitamin D) and omega 3, have anti-inflammatory properties. Little is known regarding the relationships between vitamin D, omega 6:3 ratio, LTL, inflammation, and chronic pain. We investigate associations between vitamin D, omega 6:3 ratio, LTL, and C-reactive protein (CRP) in people living with/without chronic pain overall and stratified by chronic pain status. A cross-sectional analysis of 402 individuals (63% women, 79.5% with chronic pain) was completed. Demographic and health information was collected. Chronic pain was assessed as pain experienced for at least three months. LTL was measured in genomic DNA isolated from blood leukocytes, and micronutrients and CRP were measured in serum samples. Data were analyzed with general linear regression. Although an association between the continuous micronutrients and LTL was not observed, a positive association between omega 6:3 ratio and CRP was detected. In individuals with chronic pain, based on clinical categories, significant associations between vitamin D, omega 6:3 ratio, and CRP were observed. Findings highlight the complex relationships between anti-inflammatory micronutrients, inflammation, cellular aging, and chronic pain.
| S-EPMC8779718 | biostudies-literature
Project description:Several cognitive-affective constructs, including pain catastrophizing and pain-related anxiety, have been implicated in the onset and progression of chronic pain, and both constructs have been identified as key targets for multidisciplinary pain treatment. Both neuroticism and depression have been linked to these constructs (and to each other), but how each may contribute to the pain experience is unknown. This study tested associations between neuroticism, depression, and indices of catastrophizing and pain-related anxiety among persons seeking treatment for chronic non-malignant pain. We hypothesized, as a higher-order personality trait, neuroticism would remain uniquely associated with both pain catastrophizing and pain-related anxiety, even after accounting for current symptoms of depression. A retrospective study design assessed depression (as measured by the Centers for Epidemiologic Studies-Depression scale), neuroticism (measured with the Neuroticism-Extraversion-Openness Personality Inventory), the Pain Catastrophizing Scale, and the Pain Anxiety Symptom Score in a consecutive series of patients (n=595) admitted to a 3-week outpatient pain treatment program from March 2009 through January 2011. Hierarchical regression indicated that neuroticism was independently associated with greater pain catastrophizing and pain-related anxiety, above-and-beyond the contributions of sociodemographic characteristics, pain severity, and depression. A depression by neuroticism interaction was not observed, suggesting that associations between neuroticism and cognitive-affective pain constructs remained stable across varying levels of current depression. These findings represent an early but important step towards the clarification of complex associations between trait neuroticism, current depression, and tendencies toward catastrophic and anxiety-provoking appraisals of pain among persons seeking treatment for chronic pain.
| S-EPMC4406532 | biostudies-other
Project description:BackgroundMounting evidence highlights the importance of combined modifiable lifestyle factors in reducing risk of cognitive decline and dementia. Several a priori additive scoring approaches have been established; however, limited research has employed advanced data-driven approaches to explore this association. This study aimed to examine the association between data-driven lifestyle profiles and cognitive function in community-dwelling Australian adults.MethodsA cross-sectional study of 4561 Australian adults (55.3% female, mean age 60.9 ± 11.3 years) was conducted. Questionnaires were used to collect self-reported data on diet, physical activity, sedentary time, smoking status, and alcohol consumption. Cognitive testing was undertaken to assess memory, processing speed, and vocabulary and verbal knowledge. Latent Profile Analysis (LPA) was conducted to identify subgroups characterised by similar patterns of lifestyle behaviours. The resultant subgroups, or profiles, were then used to further explore associations with cognitive function using linear regression models and an automatic Bolck, Croon & Hagenaars (BCH) approach.ResultsThree profiles were identified: (1) "Inactive, poor diet" (76.3%); (2) "Moderate activity, non-smokers" (18.7%); and (3) "Highly active, unhealthy drinkers" (5.0%). Profile 2 "Moderate activity, non-smokers" exhibited better processing speed than Profile 1 "Inactive, poor diet". There was also some evidence to suggest Profile 3 "Highly active, unhealthy drinkers" exhibited poorer vocabulary and verbal knowledge compared to Profile 1 and poorer processing speed and memory scores compared to Profile 2.ConclusionIn this population of community-dwelling Australian adults, a sub-group characterised by moderate activity levels and higher rates of non-smoking had better cognitive function compared to two other identified sub-groups. This study demonstrates how LPA can be used to highlight sub-groups of a population that may be at increased risk of dementia and benefit most from lifestyle-based multidomain intervention strategies.
| S-EPMC9707000 | biostudies-literature
Project description:The prevalence of chronic pain has reached epidemic levels. In addition to personal suffering chronic pain is associated with psychiatric and medical co-morbidities, notably substance misuse, and a huge a societal cost amounting to hundreds of billions of dollars annually in medical cost, lost wages, and productivity. Chronic pain does not have a cure or quantitative diagnostic or prognostic tools. In this manuscript we provide evidence that this situation is about to change. We first start by summarizing our current understanding of the role of the brain in the pathogenesis of chronic pain. We particularly focus on the concept of learning in the emergence of chronic pain, and the implication of the limbic brain circuitry and dopaminergic signaling, which underly emotional learning and decision making, in this process. Next, we summarize data from our labs and from other groups on the latest brain imaging findings in different chronic pain conditions focusing on results with significant potential for translation into clinical applications. The gaps in the study of chronic pain and brain imaging are highlighted in throughout the overview. Finally, we conclude by discussing the costs and benefits of using brain biomarkers of chronic pain and compare to other potential markers.
| S-EPMC8763372 | biostudies-literature
Project description:Psychological sciences have identified a wealth of cognitive processes and behavioral phenomena, yet struggle to produce cumulative knowledge. Progress is hamstrung by siloed scientific traditions and a focus on explanation over prediction, two issues that are particularly damaging for the study of multifaceted constructs like self-regulation. Here, we derive a psychological ontology from a study of individual differences across a broad range of behavioral tasks, self-report surveys, and self-reported real-world outcomes associated with self-regulation. Though both tasks and surveys putatively measure self-regulation, they show little empirical relationship. Within tasks and surveys, however, the ontology identifies reliable individual traits and reveals opportunities for theoretic synthesis. We then evaluate predictive power of the psychological measurements and find that while surveys modestly and heterogeneously predict real-world outcomes, tasks largely do not. We conclude that self-regulation lacks coherence as a construct, and that data-driven ontologies lay the groundwork for a cumulative psychological science.
| S-EPMC6534563 | biostudies-literature
Project description:BACKGROUND:To foster responsible data sharing in health research, ethical governance complementary to the EU General Data Protection Regulation is necessary. A governance framework for Big Data-driven research platforms will at least need to consider the conditions as specified a priori for individual datasets. We aim to identify and analyze these conditions for the Innovative Medicines Initiative's (IMI) BigData@Heart platform. METHODS:We performed a unique descriptive case study into the conditions for data sharing as specified for datasets participating in BigData@Heart. Principle investigators of 56 participating databases were contacted via e-mail with the request to send any kind of documentation that possibly specified the conditions for data sharing. Documents were qualitatively reviewed for conditions pertaining to data sharing and data access. RESULTS:Qualitative content analysis of 55 relevant documents revealed overlap on the conditions: (1) only to share health data for scientific research, (2) in anonymized/coded form, (3) after approval from a designated review committee, and while (4) observing all appropriate measures for data security and in compliance with the applicable laws and regulations. CONCLUSIONS:Despite considerable overlap, prespecified conditions give rise to challenges for data sharing. At the same time, these challenges inform our thinking about the design of an ethical governance framework for data sharing platforms. We urge current data sharing initiatives to concentrate on: (1) the scope of the research questions that may be addressed, (2) how to deal with varying levels of de-identification, (3) determining when and how review committees should come into play, (4) align what policies and regulations mean by "data sharing" and (5) how to deal with datasets that have no system in place for data sharing.
| S-EPMC6936121 | biostudies-literature
Project description:Current analgesics predominately modulate pain transduction and transmission in neurons and have limited success in controlling disease progression. Accumulating evidence suggests that neuroinflammation, which is characterized by infiltration of immune cells, activation of glial cells and production of inflammatory mediators in the peripheral and central nervous system, has an important role in the induction and maintenance of chronic pain. This Review focuses on emerging targets - such as chemokines, proteases and the WNT pathway - that promote spinal cord neuroinflammation and chronic pain. It also highlights the anti-inflammatory and pro-resolution lipid mediators that act on immune cells, glial cells and neurons to resolve neuroinflammation, synaptic plasticity and pain. Targeting excessive neuroinflammation could offer new therapeutic opportunities for chronic pain and related neurological and psychiatric disorders.
| S-EPMC4228377 | biostudies-literature
Project description:The classification of non-specific chronic low back pain (CLBP) according to multidimensional data could guide clinical management; yet recent systematic reviews show this has not been attempted. This was a prospective cross-sectional study of participants with CLBP (n = 21) and age-, sex- and height-matched pain-free controls (n = 21). Nervous system, lumbar spinal tissue and psychosocial factors were collected. Dimensionality reduction was followed by fuzzy c-means clustering to determine sub-groups. Machine learning models (Support Vector Machine, k-Nearest Neighbour, Naïve Bayes and Random Forest) were used to determine the accuracy of classification to sub-groups. The primary analysis showed that four factors (cognitive function, depressive symptoms, general self-efficacy and anxiety symptoms) and two clusters (normal versus impaired psychosocial profiles) optimally classified participants. The error rates in classification models ranged from 4.2 to 14.2% when only CLBP patients were considered and increased to 24.2 to 37.5% when pain-free controls were added. This data-driven pilot study classified participants with CLBP into sub-groups, primarily based on psychosocial factors. This contributes to the literature as it was the first study to evaluate data-driven machine learning CLBP classification based on nervous system, lumbar spinal tissue and psychosocial factors. Future studies with larger sample sizes should validate these findings.
| S-EPMC10423241 | biostudies-literature
Project description:Chronic pain is a prevalent and debilitating condition with significant impacts on individuals and society. While the role of diet in chronic pain is well-known, the relationship between special dietary choices and chronic pain remains unclear. This study investigates the causal associations between 20 dietary habits and chronic pain using a Mendelian randomization (MR) approach. Publicly available genome-wide association study data from the UK Biobank dataset were utilized for secondary analysis, and genetic instrumental variables strongly correlated with 20 different dietary habits were selected. Multisite chronic pain (MCP) scores were used as the primary outcome, with site-specific chronic pain (SSCP) including back pain, headache, knee pain, neck pain, and hip pain as secondary outcomes. The inverse-variance-weighted (IVW) method was the primary method used in the MR. The weighted median (WM) and Mendelian randomization pleiotropy residual sum and outlier test (MR-PRESSO) methods were used as sensitivity analyses. This study identified causal associations between specific dietary habits and chronic pain. A high intake of cheese, cereal, dried fruits, and fresh fruits was associated with lower MCP scores. Conversely, high alcohol, salt, pork, and poultry intakes were associated with higher MCP scores. Similar associations between special dietary habits and some types of SSCP, such as back and neck pain, were also observed. The findings were consistent across different statistical methods, and sensitivity analyses confirmed the reliability of the results. In conclusion, our study provides evidence of a causal relationship between various dietary habits and different types of chronic pain based on secondary analysis of the UK Biobank dataset. Adhering to an anti-inflammatory diet, including increased consumption of fruits and cereal while reducing salt and pork intake, may potentially alleviate chronic pain symptoms.
| S-EPMC10490345 | biostudies-literature