A physiometric investigation of inflammatory composites: Comparison of “a priori” aggregates, empirically-identified factors, and individual proteins

Most research testing the association between inflammation and health outcomes (e.g., heart disease, diabetes, depression) has focused on individual proteins; however, some studies have used summed composites of inflammatory markers without first investigating dimensionality. Using two different sam...

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Autores principales:	Daniel P. Moriarity, Lauren M. Ellman, Christopher L. Coe, Thomas M. Olino, Lauren B. Alloy
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Inflammation Cytokines Inflammatory composites Inflammatory aggregates Physiometrics Structural equation modeling Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
Acceso en línea:	https://doaj.org/article/8a75ef43c45f43a49fef478b8b00ddb6
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spelling	oai:doaj.org-article:8a75ef43c45f43a49fef478b8b00ddb62021-11-26T04:40:59ZA physiometric investigation of inflammatory composites: Comparison of “a priori” aggregates, empirically-identified factors, and individual proteins2666-354610.1016/j.bbih.2021.100391https://doaj.org/article/8a75ef43c45f43a49fef478b8b00ddb62021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2666354621001940https://doaj.org/toc/2666-3546Most research testing the association between inflammation and health outcomes (e.g., heart disease, diabetes, depression) has focused on individual proteins; however, some studies have used summed composites of inflammatory markers without first investigating dimensionality. Using two different samples (MIDUS-2: N = 1255 adults, MIDUS-R: N = 863 adults), this study investigates the dimensionality of eight inflammatory proteins (C-reactive protein (CRP), interleukin (IL)-6, IL-8, IL-10, tumor necrosis factor-α (TNF-α), fibrinogen, E-selectin, and intercellular adhesion molecule (ICAM)-1) and compared the resulting factor structure to a) an “a priori”/tau-equivalent factor structure in which all inflammatory proteins equally load onto a single dimension (comparable to the summed composites) and b) proteins modeled individually (i.e., no latent variable) in terms of model fit, replicability, reliability, and their associations with health outcomes. An exploratory factor analysis indicated a two-factor structure (Factor 1: CRP and fibrinogen; Factor 2: IL-8 and IL-10) in MIDUS-2 and was replicated in MIDUS-R. Results did not clearly indicate whether the empirically-identified factor structure or the individual proteins modeled without a latent variable had superior model fit, but both strongly outperformed the “a priori”/tau-equivalent structure (which did not achieve acceptable model fit in any models). Modeling the empirically-identified factors and individual proteins (without a latent factor) as outcomes of medical diagnoses resulted in comparable conclusions. However, modeling individual proteins resulted in findings more robust to correction for multiple comparisons despite more conservative adjustments. Further, reliability for all latent variables was poor. These results indicate that modeling inflammation as a unidimensional construct equally associated with all available proteins does not fit the data well. Instead, individual inflammatory proteins or, potentially (if empirically supported and biologically-plausible) empirically-identified inflammatory factors should be used in accordance with theory.Daniel P. MoriarityLauren M. EllmanChristopher L. CoeThomas M. OlinoLauren B. AlloyElsevierarticleInflammationCytokinesInflammatory compositesInflammatory aggregatesPhysiometricsStructural equation modelingNeurosciences. Biological psychiatry. NeuropsychiatryRC321-571ENBrain, Behavior, & Immunity - Health, Vol 18, Iss , Pp 100391- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Inflammation Cytokines Inflammatory composites Inflammatory aggregates Physiometrics Structural equation modeling Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
spellingShingle	Inflammation Cytokines Inflammatory composites Inflammatory aggregates Physiometrics Structural equation modeling Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 Daniel P. Moriarity Lauren M. Ellman Christopher L. Coe Thomas M. Olino Lauren B. Alloy A physiometric investigation of inflammatory composites: Comparison of “a priori” aggregates, empirically-identified factors, and individual proteins
description	Most research testing the association between inflammation and health outcomes (e.g., heart disease, diabetes, depression) has focused on individual proteins; however, some studies have used summed composites of inflammatory markers without first investigating dimensionality. Using two different samples (MIDUS-2: N = 1255 adults, MIDUS-R: N = 863 adults), this study investigates the dimensionality of eight inflammatory proteins (C-reactive protein (CRP), interleukin (IL)-6, IL-8, IL-10, tumor necrosis factor-α (TNF-α), fibrinogen, E-selectin, and intercellular adhesion molecule (ICAM)-1) and compared the resulting factor structure to a) an “a priori”/tau-equivalent factor structure in which all inflammatory proteins equally load onto a single dimension (comparable to the summed composites) and b) proteins modeled individually (i.e., no latent variable) in terms of model fit, replicability, reliability, and their associations with health outcomes. An exploratory factor analysis indicated a two-factor structure (Factor 1: CRP and fibrinogen; Factor 2: IL-8 and IL-10) in MIDUS-2 and was replicated in MIDUS-R. Results did not clearly indicate whether the empirically-identified factor structure or the individual proteins modeled without a latent variable had superior model fit, but both strongly outperformed the “a priori”/tau-equivalent structure (which did not achieve acceptable model fit in any models). Modeling the empirically-identified factors and individual proteins (without a latent factor) as outcomes of medical diagnoses resulted in comparable conclusions. However, modeling individual proteins resulted in findings more robust to correction for multiple comparisons despite more conservative adjustments. Further, reliability for all latent variables was poor. These results indicate that modeling inflammation as a unidimensional construct equally associated with all available proteins does not fit the data well. Instead, individual inflammatory proteins or, potentially (if empirically supported and biologically-plausible) empirically-identified inflammatory factors should be used in accordance with theory.
format	article
author	Daniel P. Moriarity Lauren M. Ellman Christopher L. Coe Thomas M. Olino Lauren B. Alloy
author_facet	Daniel P. Moriarity Lauren M. Ellman Christopher L. Coe Thomas M. Olino Lauren B. Alloy
author_sort	Daniel P. Moriarity
title	A physiometric investigation of inflammatory composites: Comparison of “a priori” aggregates, empirically-identified factors, and individual proteins
title_short	A physiometric investigation of inflammatory composites: Comparison of “a priori” aggregates, empirically-identified factors, and individual proteins
title_full	A physiometric investigation of inflammatory composites: Comparison of “a priori” aggregates, empirically-identified factors, and individual proteins
title_fullStr	A physiometric investigation of inflammatory composites: Comparison of “a priori” aggregates, empirically-identified factors, and individual proteins
title_full_unstemmed	A physiometric investigation of inflammatory composites: Comparison of “a priori” aggregates, empirically-identified factors, and individual proteins
title_sort	physiometric investigation of inflammatory composites: comparison of “a priori” aggregates, empirically-identified factors, and individual proteins
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/8a75ef43c45f43a49fef478b8b00ddb6
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A physiometric investigation of inflammatory composites: Comparison of “a priori” aggregates, empirically-identified factors, and individual proteins

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