Influence of Immune Cell Subtypes on Mitochondrial Measurements in Peripheral Blood Mononuclear Cells From Children with Sepsis.

2022

630-638

05/2022

1540-0514

INTRODUCTION: Peripheral blood mononuclear cells (PBMCs) are commonly used to compare mitochondrial function in patients with versus without sepsis, but how these measurements in this mixed cell population vary by composition of immune cell subtypes is not known, especially in children. We determined the effect of changing immune cell composition on PBMC mitochondrial respiration and content in children with and without sepsis.

METHODS: PBMC mitochondrial respiration and citrate synthase (CS) activity, a marker of mitochondrial content, were measured in 167 children with sepsis at three timepoints (day 1-2, 3-5, and 8-14) and once in 19 nonseptic controls. The proportion of lymphocytes and monocytes and T, B, and NK cells was measured using flow cytometry. More specific CD4+ and CD8+ T cell subsets were measured from 13 sepsis patients and 6 controls. Spearman's correlation and simple and mixed effects linear regression were used to determine the association of PBMC mitochondrial measures with proportion of immune cell subtypes.

RESULTS: PBMC mitochondrial respiration and CS activity were correlated with proportion of monocytes, lymphocytes, T B, and NK cells in controls, but not in sepsis patients. PBMC mitochondrial respiration was correlated with CD4+ and CD8+ T cell subsets in both groups. After controlling for differences in immune cell composition between groups using linear regression models, PBMC respiration and CS activity remained lower in sepsis patients than controls.

CONCLUSIONS: Mitochondrial measurements from PBMCs varied with changes in immune cell composition in children with and without sepsis. However, differences in PBMC mitochondrial measurements between sepsis patients and controls were at least partially attributable to the effects of sepsis rather than solely an epiphenomena of variable immune cell composition.

10.1097/SHK.0000000000001903

Shock

34966070

Temperature Trajectory Sub-Phenotypes and The Immuno-Inflammatory Response In Pediatric Sepsis.

2021

2021 Dec 27

1540-0514

<p><strong>OBJECTIVE: </strong>Heterogeneity has hampered sepsis trials, and sub-phenotyping may assist with enrichment strategies. However, biomarker-based strategies are difficult to operationalize. Four sub-phenotypes defined by distinct temperature trajectories in the first 72 hours have been reported in adult sepsis. Given the distinct epidemiology of pediatric sepsis, the existence and relevance of temperature trajectory-defined sub-phenotypes in children is unknown. We aimed to classify septic children into de novo sub-phenotypes derived from temperature trajectories in the first 72 hours, and compare cytokine, immune function, and immunometabolic markers across subgroups.</p>

<p><strong>METHODS: </strong>This was a secondary analysis of a prospective cohort of 191 critically ill septic children recruited from a single academic pediatric intensive care unit. We performed group-based trajectory modeling using temperatures over the first 72 hours of sepsis to identify latent profiles. We then used mixed effects regression to determine if temperature trajectory-defined sub-phenotypes were associated with cytokine levels, immune function, and mitochondrial respiration.</p>

<p><strong>RESULTS: </strong>We identified four temperature trajectory-defined sub-phenotypes: hypothermic, normothermic, hyperthermic fast-resolvers, and hyperthermic slow-resolvers. Hypothermic patients were less often previously healthy and exhibited lower levels of pro- and anti-inflammatory cytokines and chemokines. Hospital mortality did not differ between hypothermic children (17%) and other sub-phenotypes (3 to 11%; p = 0.26).</p>

<p><strong>CONCLUSIONS: </strong>Critically ill septic children can be categorized into temperature trajectory-defined sub-phenotypes that parallel adult sepsis. Hypothermic children exhibit a blunted cytokine and chemokine profile. Group-based trajectory modeling has utility for identifying subtypes of clinical syndromes by incorporating readily available longitudinal data, rather than relying on inputs from a single timepoint.</p>

10.1097/SHK.0000000000001906

Shock

35066512