Histologic and biochemical alterations predict pulmonary mechanical dysfunction in aging mice with chronic lung inflammation

Christopher B Massa, Angela M Groves, Smita U Jaggernauth, Debra L Laskin and Andrew J Gow

PLOS Computational Biology, 2017, vol. 13, issue 8, 1-22

Abstract: Both aging and chronic inflammation produce complex structural and biochemical alterations to the lung known to impact work of breathing. Mice deficient in surfactant protein D (Sftpd) develop progressive age-related lung pathology characterized by tissue destruction/remodeling, accumulation of foamy macrophages and alteration in surfactant composition. This study proposes to relate changes in tissue structure seen in normal aging and in chronic inflammation to altered lung mechanics using a computational model. Alterations in lung function in aging and Sftpd -/- mice have been inferred from fitting simple mechanical models to respiratory impedance data (Zrs), however interpretation has been confounded by the simultaneous presence of multiple coexisting pathophysiologic processes. In contrast to the inverse modeling approach, this study uses simulation from experimental measurements to recapitulate how aging and inflammation alter Zrs. Histologic and mechanical measurements were made in C57BL6/J mice and congenic Sftpd-/- mice at 8, 27 and 80 weeks of age (n = 8/group). An anatomic computational model based on published airway morphometry was developed and Zrs was simulated between 0.5 and 20 Hz. End expiratory pressure dependent changes in airway caliber and recruitment were estimated from mechanical measurements. Tissue elements were simulated using the constant phase model of viscoelasticity. Baseline elastance distribution was estimated in 8-week-old wild type mice, and stochastically varied for each condition based on experimentally measured alteration in elastic fiber composition, alveolar geometry and surfactant composition. Weighing reduction in model error against increasing model complexity allowed for identification of essential features underlying mechanical pathology and their contribution to Zrs. Using a maximum likelihood approach, alteration in lung recruitment and diminished elastic fiber density were shown predictive of mechanical alteration at airway opening, to a greater extent than overt acinar wall destruction. Model-predicted deficits in PEEP-dependent lung recruitment correlate with altered lung lining fluid composition independent of age or genotype.Author summary: Aging and chronic inflammation produce complex changes to the structure of the lung including accumulation of cells and debris, thinning and destruction of air sacs, altered airway size and increased tendency for airway collapse. As these structural changes are observed concurrently, their individual contributions to altered lung function cannot readily be determined by conventional measurement of lung function. Our study employs a novel approach to identifying the age progression of these effects in mice with and without chronic lung inflammation. Histologic changes in lung tissue were incorporated into a computational model of the mouse lung and used to simulate measured changes in lung function. By incorporating experimentally measured factors into the model in a stepwise fashion, the contribution of destructive and remodeling processes to alterations in lung function can be assessed. This modeling approach provides a framework for determining the significance of structural changes to the altered function observed in complex lung pathologies such as emphysema and chronic obstructive pulmonary disease. Such an approach could be utilized to assess mechanisms by which compounds alter lung function and the capacity of specific therapies to produce improvements in lung function at the organ level.

Date: 2017
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005570 (text/html)
https://journals.plos.org/ploscompbiol/article/fil ... 05570&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1005570

DOI: 10.1371/journal.pcbi.1005570

Access Statistics for this article

More articles in PLOS Computational Biology from Public Library of Science
Bibliographic data for series maintained by ploscompbiol ().