Treelet transform analysis to identify clusters of systemic inflammatory variance in a population with moderate-to-severe traumatic brain injury

•We utilized treelet transform to identify 5 clusters of biomarkers post-TBI.•The adaptive immunity cluster contributed the most variance to the treelet.•Innate and soluble receptor clusters were associated with poor long-term outcome.•Our results explore the intersection of inflammation and outcome...

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Veröffentlicht in:Brain, behavior, and immunity behavior, and immunity, 2021-07, Vol.95, p.45-60
Hauptverfasser: Vijapur, Sushupta M., Vaughan, Leah E., Awan, Nabil, DiSanto, Dominic, McKernan, Gina P., Wagner, Amy K.
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container_end_page 60
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container_start_page 45
container_title Brain, behavior, and immunity
container_volume 95
creator Vijapur, Sushupta M.
Vaughan, Leah E.
Awan, Nabil
DiSanto, Dominic
McKernan, Gina P.
Wagner, Amy K.
description •We utilized treelet transform to identify 5 clusters of biomarkers post-TBI.•The adaptive immunity cluster contributed the most variance to the treelet.•Innate and soluble receptor clusters were associated with poor long-term outcome.•Our results explore the intersection of inflammation and outcomes post-TBI.•We show a methodology which may enhance future studies on immunity post-TBI. Inflammatory cascades following traumatic brain injury (TBI) can have both beneficial and detrimental effects on recovery. Single biomarker studies do not adequately reflect the major arms of immunity and their relationships to long-term outcomes. Thus, we applied treelet transform (TT) analysis to identify clusters of interrelated inflammatory markers reflecting major components of systemic immune function for which substantial variation exists among individuals with moderate-to-severe TBI. Serial blood samples from 221 adults with moderate-to-severe TBI were collected over 1–6 months post-injury (n = 607 samples). Samples were assayed for 33 inflammatory markers using Millipore multiplex technology. TT was applied to standardized mean biomarker values generated to identify latent patterns of correlated markers. Treelet clusters (TC) were characterized by biomarkers related to adaptive immunity (TC1), innate immunity (TC2), soluble molecules (TC3), allergy immunity (TC4), and chemokines (TC5). For each TC, a score was generated as the linear combination of standardized biomarker concentrations and cluster load for each individual in the cohort. Ordinal logistic or linear regression was used to test associations between TC scores and 6- and 12-month Glasgow Outcome Scale (GOS), Disability Rating Scale (DRS), and covariates. When adjusting for clinical covariates, TC5 was significantly associated with 6-month GOS (odds ratio, OR = 1.44; p-value, p = 0.025) and 6-month DRS scores (OR = 1.46; p = 0.013). TC5 relationships were attenuated when including all TC scores in the model (GOS: OR = 1.29, p = 0.163; DRS: OR = 1.33, p = 0.100). When adjusting for all TC scores and covariates, only TC3 was associated with 6- and 12-month GOS (OR = 1.32, p = 0.041; OR = 1.39, p = 0.002) and also 6- and 12-month DRS (OR = 1.38, p = 0.016; OR = 1.58, p = 0.0002). When applying TT to inflammation markers significantly associated with 6-month GOS, multivariate modeling confirmed that TC3 remained significantly associated with GOS. Biomarker cluster membership remained consistent between the GOS
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Inflammatory cascades following traumatic brain injury (TBI) can have both beneficial and detrimental effects on recovery. Single biomarker studies do not adequately reflect the major arms of immunity and their relationships to long-term outcomes. Thus, we applied treelet transform (TT) analysis to identify clusters of interrelated inflammatory markers reflecting major components of systemic immune function for which substantial variation exists among individuals with moderate-to-severe TBI. Serial blood samples from 221 adults with moderate-to-severe TBI were collected over 1–6 months post-injury (n = 607 samples). Samples were assayed for 33 inflammatory markers using Millipore multiplex technology. TT was applied to standardized mean biomarker values generated to identify latent patterns of correlated markers. Treelet clusters (TC) were characterized by biomarkers related to adaptive immunity (TC1), innate immunity (TC2), soluble molecules (TC3), allergy immunity (TC4), and chemokines (TC5). For each TC, a score was generated as the linear combination of standardized biomarker concentrations and cluster load for each individual in the cohort. Ordinal logistic or linear regression was used to test associations between TC scores and 6- and 12-month Glasgow Outcome Scale (GOS), Disability Rating Scale (DRS), and covariates. When adjusting for clinical covariates, TC5 was significantly associated with 6-month GOS (odds ratio, OR = 1.44; p-value, p = 0.025) and 6-month DRS scores (OR = 1.46; p = 0.013). TC5 relationships were attenuated when including all TC scores in the model (GOS: OR = 1.29, p = 0.163; DRS: OR = 1.33, p = 0.100). When adjusting for all TC scores and covariates, only TC3 was associated with 6- and 12-month GOS (OR = 1.32, p = 0.041; OR = 1.39, p = 0.002) and also 6- and 12-month DRS (OR = 1.38, p = 0.016; OR = 1.58, p = 0.0002). When applying TT to inflammation markers significantly associated with 6-month GOS, multivariate modeling confirmed that TC3 remained significantly associated with GOS. Biomarker cluster membership remained consistent between the GOS-specific dendrogram and overall dendrogram. TT effectively characterized chronic, systemic immunity among a cohort of individuals with moderate-to-severe TBI. We posit that chronic chemokine levels are effector molecules propagating cellular immune dysfunction, while chronic soluble receptors are inflammatory damage readouts perpetuated, in part, by persistent dysfunctional cellular immunity to impact neuro-recovery.</description><identifier>ISSN: 0889-1591</identifier><identifier>EISSN: 1090-2139</identifier><identifier>DOI: 10.1016/j.bbi.2021.01.026</identifier><identifier>PMID: 33524553</identifier><language>eng</language><publisher>Netherlands: Elsevier Inc</publisher><subject>Adaptive immunity ; Adult ; Biomarker ; Biomarkers ; Brain Injuries, Traumatic ; Chemokine ; Cohort Studies ; Cytokine ; Glasgow Outcome Scale ; Humans ; Inflammation ; Innate immunity ; Soluble receptor ; Traumatic brain injury ; Treelet transform analysis</subject><ispartof>Brain, behavior, and immunity, 2021-07, Vol.95, p.45-60</ispartof><rights>2021 Elsevier Inc.</rights><rights>Copyright © 2021 Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c451t-dcd94c9d69a62b9cc2a6741355fb9e78b93e9de0e44a219ca8c7f116794518ab3</citedby><cites>FETCH-LOGICAL-c451t-dcd94c9d69a62b9cc2a6741355fb9e78b93e9de0e44a219ca8c7f116794518ab3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0889159121000301$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,314,776,780,881,3537,27901,27902,65534</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33524553$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Vijapur, Sushupta M.</creatorcontrib><creatorcontrib>Vaughan, Leah E.</creatorcontrib><creatorcontrib>Awan, Nabil</creatorcontrib><creatorcontrib>DiSanto, Dominic</creatorcontrib><creatorcontrib>McKernan, Gina P.</creatorcontrib><creatorcontrib>Wagner, Amy K.</creatorcontrib><title>Treelet transform analysis to identify clusters of systemic inflammatory variance in a population with moderate-to-severe traumatic brain injury</title><title>Brain, behavior, and immunity</title><addtitle>Brain Behav Immun</addtitle><description>•We utilized treelet transform to identify 5 clusters of biomarkers post-TBI.•The adaptive immunity cluster contributed the most variance to the treelet.•Innate and soluble receptor clusters were associated with poor long-term outcome.•Our results explore the intersection of inflammation and outcomes post-TBI.•We show a methodology which may enhance future studies on immunity post-TBI. 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Treelet clusters (TC) were characterized by biomarkers related to adaptive immunity (TC1), innate immunity (TC2), soluble molecules (TC3), allergy immunity (TC4), and chemokines (TC5). For each TC, a score was generated as the linear combination of standardized biomarker concentrations and cluster load for each individual in the cohort. Ordinal logistic or linear regression was used to test associations between TC scores and 6- and 12-month Glasgow Outcome Scale (GOS), Disability Rating Scale (DRS), and covariates. When adjusting for clinical covariates, TC5 was significantly associated with 6-month GOS (odds ratio, OR = 1.44; p-value, p = 0.025) and 6-month DRS scores (OR = 1.46; p = 0.013). TC5 relationships were attenuated when including all TC scores in the model (GOS: OR = 1.29, p = 0.163; DRS: OR = 1.33, p = 0.100). When adjusting for all TC scores and covariates, only TC3 was associated with 6- and 12-month GOS (OR = 1.32, p = 0.041; OR = 1.39, p = 0.002) and also 6- and 12-month DRS (OR = 1.38, p = 0.016; OR = 1.58, p = 0.0002). When applying TT to inflammation markers significantly associated with 6-month GOS, multivariate modeling confirmed that TC3 remained significantly associated with GOS. Biomarker cluster membership remained consistent between the GOS-specific dendrogram and overall dendrogram. TT effectively characterized chronic, systemic immunity among a cohort of individuals with moderate-to-severe TBI. We posit that chronic chemokine levels are effector molecules propagating cellular immune dysfunction, while chronic soluble receptors are inflammatory damage readouts perpetuated, in part, by persistent dysfunctional cellular immunity to impact neuro-recovery.</description><subject>Adaptive immunity</subject><subject>Adult</subject><subject>Biomarker</subject><subject>Biomarkers</subject><subject>Brain Injuries, Traumatic</subject><subject>Chemokine</subject><subject>Cohort Studies</subject><subject>Cytokine</subject><subject>Glasgow Outcome Scale</subject><subject>Humans</subject><subject>Inflammation</subject><subject>Innate immunity</subject><subject>Soluble receptor</subject><subject>Traumatic brain injury</subject><subject>Treelet transform analysis</subject><issn>0889-1591</issn><issn>1090-2139</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kcGKFDEQhoMo7uzqA3iRHL30mKSTng6CIIuuwoKX9Ryqk2o3Q7ozJumRfgsf2QyzLnoRChIq__9Xko-QV5xtOePd2_12GPxWMMG3rJbonpANZ5o1grf6KdmwvtcNV5pfkMuc94wx1fL-ObloWyWkUu2G_LpLiAELLQnmPMY0UZghrNlnWiL1Dufix5XasOSCKdM40rzW7eQt9fMYYJqgxLTSIyQPs8XapUAP8bAEKD7O9Kcv93SKDhMUbEpsMh4x4WniUr01Z0hQTX7eL2l9QZ6NEDK-fFivyLdPH--uPze3X2--XH-4baxUvDTOOi2tdp2GTgzaWgHdTvJWqXHQuOsH3aJ2yFBKEFxb6O1u5Lzb6WrvYWivyPtz7mEZJnS2vjNBMIfkJ0irieDNvyezvzff49FoxqTsdQ148xCQ4o8FczGTzxZDgBnjko2QvVJcVFBVys9Sm2LOCcfHMZyZE0mzN5WkOZE0rJboquf13_d7dPxBVwXvzgKsv3T0mEy2HisA5xPaYlz0_4n_DfSntEo</recordid><startdate>20210701</startdate><enddate>20210701</enddate><creator>Vijapur, Sushupta M.</creator><creator>Vaughan, Leah E.</creator><creator>Awan, Nabil</creator><creator>DiSanto, Dominic</creator><creator>McKernan, Gina P.</creator><creator>Wagner, Amy K.</creator><general>Elsevier Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20210701</creationdate><title>Treelet transform analysis to identify clusters of systemic inflammatory variance in a population with moderate-to-severe traumatic brain injury</title><author>Vijapur, Sushupta M. ; Vaughan, Leah E. ; Awan, Nabil ; DiSanto, Dominic ; McKernan, Gina P. ; Wagner, Amy K.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c451t-dcd94c9d69a62b9cc2a6741355fb9e78b93e9de0e44a219ca8c7f116794518ab3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Adaptive immunity</topic><topic>Adult</topic><topic>Biomarker</topic><topic>Biomarkers</topic><topic>Brain Injuries, Traumatic</topic><topic>Chemokine</topic><topic>Cohort Studies</topic><topic>Cytokine</topic><topic>Glasgow Outcome Scale</topic><topic>Humans</topic><topic>Inflammation</topic><topic>Innate immunity</topic><topic>Soluble receptor</topic><topic>Traumatic brain injury</topic><topic>Treelet transform analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Vijapur, Sushupta M.</creatorcontrib><creatorcontrib>Vaughan, Leah E.</creatorcontrib><creatorcontrib>Awan, Nabil</creatorcontrib><creatorcontrib>DiSanto, Dominic</creatorcontrib><creatorcontrib>McKernan, Gina P.</creatorcontrib><creatorcontrib>Wagner, Amy K.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Brain, behavior, and immunity</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Vijapur, Sushupta M.</au><au>Vaughan, Leah E.</au><au>Awan, Nabil</au><au>DiSanto, Dominic</au><au>McKernan, Gina P.</au><au>Wagner, Amy K.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Treelet transform analysis to identify clusters of systemic inflammatory variance in a population with moderate-to-severe traumatic brain injury</atitle><jtitle>Brain, behavior, and immunity</jtitle><addtitle>Brain Behav Immun</addtitle><date>2021-07-01</date><risdate>2021</risdate><volume>95</volume><spage>45</spage><epage>60</epage><pages>45-60</pages><issn>0889-1591</issn><eissn>1090-2139</eissn><abstract>•We utilized treelet transform to identify 5 clusters of biomarkers post-TBI.•The adaptive immunity cluster contributed the most variance to the treelet.•Innate and soluble receptor clusters were associated with poor long-term outcome.•Our results explore the intersection of inflammation and outcomes post-TBI.•We show a methodology which may enhance future studies on immunity post-TBI. Inflammatory cascades following traumatic brain injury (TBI) can have both beneficial and detrimental effects on recovery. Single biomarker studies do not adequately reflect the major arms of immunity and their relationships to long-term outcomes. Thus, we applied treelet transform (TT) analysis to identify clusters of interrelated inflammatory markers reflecting major components of systemic immune function for which substantial variation exists among individuals with moderate-to-severe TBI. Serial blood samples from 221 adults with moderate-to-severe TBI were collected over 1–6 months post-injury (n = 607 samples). Samples were assayed for 33 inflammatory markers using Millipore multiplex technology. TT was applied to standardized mean biomarker values generated to identify latent patterns of correlated markers. Treelet clusters (TC) were characterized by biomarkers related to adaptive immunity (TC1), innate immunity (TC2), soluble molecules (TC3), allergy immunity (TC4), and chemokines (TC5). For each TC, a score was generated as the linear combination of standardized biomarker concentrations and cluster load for each individual in the cohort. Ordinal logistic or linear regression was used to test associations between TC scores and 6- and 12-month Glasgow Outcome Scale (GOS), Disability Rating Scale (DRS), and covariates. When adjusting for clinical covariates, TC5 was significantly associated with 6-month GOS (odds ratio, OR = 1.44; p-value, p = 0.025) and 6-month DRS scores (OR = 1.46; p = 0.013). TC5 relationships were attenuated when including all TC scores in the model (GOS: OR = 1.29, p = 0.163; DRS: OR = 1.33, p = 0.100). When adjusting for all TC scores and covariates, only TC3 was associated with 6- and 12-month GOS (OR = 1.32, p = 0.041; OR = 1.39, p = 0.002) and also 6- and 12-month DRS (OR = 1.38, p = 0.016; OR = 1.58, p = 0.0002). When applying TT to inflammation markers significantly associated with 6-month GOS, multivariate modeling confirmed that TC3 remained significantly associated with GOS. Biomarker cluster membership remained consistent between the GOS-specific dendrogram and overall dendrogram. TT effectively characterized chronic, systemic immunity among a cohort of individuals with moderate-to-severe TBI. We posit that chronic chemokine levels are effector molecules propagating cellular immune dysfunction, while chronic soluble receptors are inflammatory damage readouts perpetuated, in part, by persistent dysfunctional cellular immunity to impact neuro-recovery.</abstract><cop>Netherlands</cop><pub>Elsevier Inc</pub><pmid>33524553</pmid><doi>10.1016/j.bbi.2021.01.026</doi><tpages>16</tpages><oa>free_for_read</oa></addata></record>
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subjects Adaptive immunity
Adult
Biomarker
Biomarkers
Brain Injuries, Traumatic
Chemokine
Cohort Studies
Cytokine
Glasgow Outcome Scale
Humans
Inflammation
Innate immunity
Soluble receptor
Traumatic brain injury
Treelet transform analysis
title Treelet transform analysis to identify clusters of systemic inflammatory variance in a population with moderate-to-severe traumatic brain injury
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