Longitudinal profiling of plasma cytokines in melioidosis and their association with mortality: a prospective cohort study

Kaewarpai, Taniya; Ekchariyawat, Peeraya; Phunpang, Rungnapa; Wright, Shelton W.; Dulsuk, Adul; Moonmueangsan, B; Morakot, Chumpol; Thiansukhon, Ekkachai; Day, Nicholas P. J.; Lertmemongkolchai, Ganjana; West, T. Eoin; Chantratita, Narisara

doi:10.1016/j.cmi.2019.10.032

Cited by 22 publications

(31 citation statements)

References 28 publications

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“…This study was part of a multi-centre study of patients aged ≥15 years who were culture-positive for B. pseudomallei from any type of clinical samples and admitted to the hospitals between January 2015 and December 2019. The inclusion and exclusion criteria were described previously [ 12 ]. B. pseudomallei were identified by biochemical tests and latex agglutination [ 13 ] at the microbiology laboratories of the hospitals and further confirmed by Matrix-Assisted Laser Desorption Ionization Mass Spectrometry (MALDI-TOF MS) as previously described [ 14 ].…”

Section: Methodsmentioning

confidence: 99%

Blood transcriptomics to characterize key biological pathways and identify biomarkers for predicting mortality in melioidosis

Yimthin

Cliff

Phunpang

et al. 2021

Emerging Microbes & Infections

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Melioidosis is a tropical infectious disease caused by the Gram-negative bacillus, Burkholderia pseudomallei that is often lethal in many endemic areas. The objective of this study was to characterize the transcriptome in melioidosis patients and identify genes associated with outcome. RNA-seq was performed on whole blood RNA in a discovery set of 29 melioidosis patients and 3 healthy controls using Ion AmpliSeq Transcriptome. Transcriptomic profiles of patients who did not survive to 28 days were compared with patients who survived and healthy controls. RT-qPCR of 28 differentially expressed genes was performed in a validation set of 60 melioidosis patients and 20 healthy controls. In RNAseq analysis, 65 genes were significantly up-regulated and 218 were down-regulated in nonsurvivors compared to survivors. Up-regulated genes were involved in myeloid leukocyte activation, Toll-like receptor cascades and reactive oxygen species metabolic processes. Down-regulated genes were hematopoietic cell lineage, adaptive immune system and lymphocyte activation pathways. RT-qPCR in the validation set of patients confirmed differential expression of a subset of genes. IL1R2, GAS7, S100A9, IRAK3, and NFKBIA were significantly higher in non-survivors compared with survivors (P < 0.005) and healthy controls (P < 0.0001). The AUROCC of these genes for mortality discrimination ranged from 0.80-0.88. In survivors, expression of IL1R2, S100A9 and IRAK3 genes decreased significantly over 28 days (P < 0.05). Whole blood transcriptomics characterizes the host response in melioidosis. Expression levels of specific genes are potential biomarkers to predict outcomes. These findings augment our understanding of this severe infection.

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Section: Methodsmentioning

confidence: 99%

Blood transcriptomics to characterize key biological pathways and identify biomarkers for predicting mortality in melioidosis

Yimthin

Cliff

Phunpang

et al. 2021

Emerging Microbes & Infections

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“…Enrollment occurred at the time of pathogen identification. This cohort has been described previously [ 21 ]. Plasma samples were obtained at the time of enrollment and clinical data were obtained from patient interview, medical records, and telephone calls.…”

Section: Methodsmentioning

confidence: 99%

A 2-Biomarker Model Augments Clinical Prediction of Mortality in Melioidosis

Wright

Kaewarpai

Lovelace-Macon

et al. 2020

Clinical Infectious Diseases

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Background Melioidosis, infection caused by Burkholderia pseudomallei, is a common cause of sepsis with high associated mortality in Southeast Asia. Identification of patients at high likelihood of clinical deterioration is important for guiding decisions about resource allocation and management. We sought to develop a biomarker-based model for 28-day mortality prediction in melioidosis. Methods In a derivation set (N = 113) of prospectively enrolled, hospitalized Thai patients with melioidosis, we measured concentrations of interferon-γ, interleukin-1β, interleukin-6, interleukin-8, interleukin-10, tumor necrosis factor-ɑ, granulocyte-colony stimulating factor, and interleukin-17A. We used least absolute shrinkage and selection operator (LASSO) regression to identify a subset of predictive biomarkers and performed logistic regression and receiver operating characteristic curve analysis to evaluate biomarker-based prediction of 28-day mortality compared with clinical variables. We repeated select analyses in an internal validation set (N = 78) and in a prospectively enrolled external validation set (N = 161) of hospitalized adults with melioidosis. Results All 8 cytokines were positively associated with 28-day mortality. Of these, interleukin-6 and interleukin-8 were selected by LASSO regression. A model consisting of interleukin-6, interleukin-8, and clinical variables significantly improved 28-day mortality prediction over a model of only clinical variables [AUC (95% confidence interval [CI]): 0.86 (.79–.92) vs 0.78 (.69–.87); P = .01]. In both the internal validation set (0.91 [0.84–0.97]) and the external validation set (0.81 [0.74–0.88]), the combined model including biomarkers significantly improved 28-day mortality prediction over a model limited to clinical variables. Conclusions A 2-biomarker model augments clinical prediction of 28-day mortality in melioidosis.

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“…Three of the upregulated proteins (CD40, TNFRSF1B and TRAF1) are involved in the expression of tumor necrosis factor-alpha (TNF-α), a major stimulator of apoptosis. Nevertheless, the pleiotrophic TNF-α is also an important proinflammatory cytokine produced in higher abundance in individuals with melioidosis as compared with uninfected healthy individuals [39]. Furthermore the only proteins typically associated with apoptosis and which were notably altered in expression were the enzyme caspase 6 and the caspase recruitment domain family protein CARD9.…”

Section: Two Hundred Seventy-four Host Proteins Were Exclusively Presmentioning

confidence: 99%

A DUF4148 family protein produced inside RAW264.7 cells is a critical Burkholderia pseudomallei virulence factor

et al. 2020

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Burkholderia pseudomallei: is the etiological agent of the disease melioidosis and is a Tier 1 select agent. It survives and replicates inside phagocytic cells by escaping from the endocytic vacuole, replicating in the cytosol, spreading to other cells via actin polymerization and promoting the fusion of infected and uninfected host cells to form multinucleated giant cells. In this study, we utilized a proteomics approach to identify bacterial proteins produced inside RAW264.7 murine macrophages and host proteins produced in response to B. pseudomallei infection. Cells infected with B. pseudomallei strain K96243 were lysed and the lysate proteins digested and analyzed using nanoflow reversed-phase liquid chromatography and tandem mass spectrometry. Approximately 160 bacterial proteins were identified in the infected macrophages, including BimA, TssA, TssB, Hcp1 and TssM. Several previously uncharacterized B. pseudomallei proteins were also identified, including BPSS1996 and BPSL2748. Mutations were constructed in the genes encoding these novel proteins and their relative virulence was assessed in BALB/c mice. The 50% lethal dose for the BPSS1996 mutant was approximately 55-fold higher than that of the wild type, suggesting that BPSS1996 is required for full virulence. Sera from B. pseudomallei-infected animals reacted with BPSS1996 and it was found to localize to the bacterial surface using indirect immunofluorescence. Finally, we identified 274 host proteins that were exclusively present or absent in infected RAW264.7 cells, including chemokines and cytokines involved in controlling the initial stages of infection.

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Longitudinal profiling of plasma cytokines in melioidosis and their association with mortality: a prospective cohort study

Cited by 22 publications

References 28 publications

Blood transcriptomics to characterize key biological pathways and identify biomarkers for predicting mortality in melioidosis

Blood transcriptomics to characterize key biological pathways and identify biomarkers for predicting mortality in melioidosis

A 2-Biomarker Model Augments Clinical Prediction of Mortality in Melioidosis

A DUF4148 family protein produced inside RAW264.7 cells is a critical Burkholderia pseudomallei virulence factor

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