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Understanding Pain and Trauma Symptoms in Veterans From Resting-State Connectivity: Unsupervised Modeling
Trauma and posttraumatic stress are highly comorbid with chronic pain and are often antecedents to developing chronic pain conditions. Pain and trauma are associated with greater utilization of medical services, greater use of psychiatric medication, and increased total cost of treatment. Despite th...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9127988/ https://www.ncbi.nlm.nih.gov/pubmed/35620636 http://dx.doi.org/10.3389/fpain.2022.871961 |
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author | Strigo, Irina A. Spadoni, Andrea D. Simmons, Alan N. |
author_facet | Strigo, Irina A. Spadoni, Andrea D. Simmons, Alan N. |
author_sort | Strigo, Irina A. |
collection | PubMed |
description | Trauma and posttraumatic stress are highly comorbid with chronic pain and are often antecedents to developing chronic pain conditions. Pain and trauma are associated with greater utilization of medical services, greater use of psychiatric medication, and increased total cost of treatment. Despite the high overlap in the clinic, the neural mechanisms of pain and trauma are often studied separately. In this study, resting-state functional magnetic resonance imaging (rs-fMRI) scans were completed among a diagnostically heterogeneous sample of veterans with a range of back pain and trauma symptoms. Using Group Iterative Multiple Model Estimation (GIMME), an effective functional connectivity analysis, we explored an unsupervised model deriving subgroups based on path similarity in a priori defined regions of interest (ROIs) from brain regions implicated in the experience of pain and trauma. Three subgroups were identified by patterns in functional connection and differed significantly on several psychological measures despite similar demographic and diagnostic characteristics. The first subgroup was highly connected overall, was characterized by functional connectivity from the nucleus accumbens (NAc), the anterior cingulate cortex (ACC), and the posterior cingulate cortex (PCC) to the insula and scored low on pain and trauma symptoms. The second subgroup did not significantly differ from the first subgroup on pain and trauma measures but was characterized by functional connectivity from the ACC and NAc to the thalamus and from ACC to PCC. The third subgroup was characterized by functional connectivity from the thalamus and PCC to NAc and scored high on pain and trauma symptoms. Our results suggest that, despite demographic and diagnostic similarities, there may be neurobiologically dissociable biotypes with different mechanisms for managing pain and trauma. These findings may have implications for the determination of appropriate biotype-specific interventions that target these neurological systems. |
format | Online Article Text |
id | pubmed-9127988 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91279882022-05-25 Understanding Pain and Trauma Symptoms in Veterans From Resting-State Connectivity: Unsupervised Modeling Strigo, Irina A. Spadoni, Andrea D. Simmons, Alan N. Front Pain Res (Lausanne) Pain Research Trauma and posttraumatic stress are highly comorbid with chronic pain and are often antecedents to developing chronic pain conditions. Pain and trauma are associated with greater utilization of medical services, greater use of psychiatric medication, and increased total cost of treatment. Despite the high overlap in the clinic, the neural mechanisms of pain and trauma are often studied separately. In this study, resting-state functional magnetic resonance imaging (rs-fMRI) scans were completed among a diagnostically heterogeneous sample of veterans with a range of back pain and trauma symptoms. Using Group Iterative Multiple Model Estimation (GIMME), an effective functional connectivity analysis, we explored an unsupervised model deriving subgroups based on path similarity in a priori defined regions of interest (ROIs) from brain regions implicated in the experience of pain and trauma. Three subgroups were identified by patterns in functional connection and differed significantly on several psychological measures despite similar demographic and diagnostic characteristics. The first subgroup was highly connected overall, was characterized by functional connectivity from the nucleus accumbens (NAc), the anterior cingulate cortex (ACC), and the posterior cingulate cortex (PCC) to the insula and scored low on pain and trauma symptoms. The second subgroup did not significantly differ from the first subgroup on pain and trauma measures but was characterized by functional connectivity from the ACC and NAc to the thalamus and from ACC to PCC. The third subgroup was characterized by functional connectivity from the thalamus and PCC to NAc and scored high on pain and trauma symptoms. Our results suggest that, despite demographic and diagnostic similarities, there may be neurobiologically dissociable biotypes with different mechanisms for managing pain and trauma. These findings may have implications for the determination of appropriate biotype-specific interventions that target these neurological systems. Frontiers Media S.A. 2022-05-10 /pmc/articles/PMC9127988/ /pubmed/35620636 http://dx.doi.org/10.3389/fpain.2022.871961 Text en Copyright © 2022 Strigo, Spadoni and Simmons. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Pain Research Strigo, Irina A. Spadoni, Andrea D. Simmons, Alan N. Understanding Pain and Trauma Symptoms in Veterans From Resting-State Connectivity: Unsupervised Modeling |
title | Understanding Pain and Trauma Symptoms in Veterans From Resting-State Connectivity: Unsupervised Modeling |
title_full | Understanding Pain and Trauma Symptoms in Veterans From Resting-State Connectivity: Unsupervised Modeling |
title_fullStr | Understanding Pain and Trauma Symptoms in Veterans From Resting-State Connectivity: Unsupervised Modeling |
title_full_unstemmed | Understanding Pain and Trauma Symptoms in Veterans From Resting-State Connectivity: Unsupervised Modeling |
title_short | Understanding Pain and Trauma Symptoms in Veterans From Resting-State Connectivity: Unsupervised Modeling |
title_sort | understanding pain and trauma symptoms in veterans from resting-state connectivity: unsupervised modeling |
topic | Pain Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9127988/ https://www.ncbi.nlm.nih.gov/pubmed/35620636 http://dx.doi.org/10.3389/fpain.2022.871961 |
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