Unsupervised Analysis of Transcriptomics in Bacterial Sepsis Across Multiple Datasets Reveals Three Robust Clusters

Sweeney, Timothy E.; Azad, Tej D.; Donato, Michèle; Haynes, Winston; Perumal, Thanneer M.; Henao, Ricardo; Bermejo-Martín, Jesús F.; Almansa, Raquel; Tamayo, Eduardo; Howrylak, Judith A.; Choi, Augustine M.K.; Parnell, Grant P; Tang, Benjamin; Nichols, Marshall; Woods, Christopher W.; Ginsburg, Geoffrey S.; Kingsmore, Stephen F.; Omberg, Larsson; Mangravite, Lara M.; Wong, Hector R.; Tsalik, Ephraim L.; Langley, Raymond J.; Khatri, Purvesh

doi:10.1097/ccm.0000000000003084

Cited by 247 publications

(261 citation statements)

References 51 publications

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“…These "hyperthermic, slow resolvers" may represent the hyperinflammatory subphenotype. Sweeny et al also identified an "inflammopathic" subtype from sepsis datasets, which included high disease severity, high bandemia, and high mortality [46]. In the present study, we identified a hyperinflammatory subphenotype (group A patients) that was accompanied by elevated baseline values for temperature and white blood cell count.…”

Section: Discussionsupporting

confidence: 51%

Subphenotypes in Patients with Septic Shock Receiving Vitamin C, Hydrocortisone, and Thiamine: A Retrospective Cohort Analysis

et al. 2019

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This study aimed to identify septic phenotypes in patients receiving vitamin C, hydrocortisone, and thiamine using temperature and white blood cell count. Data were obtained from septic shock patients who were also treated using a vitamin C protocol in a medical intensive care unit. Patients were divided into groups according to the temperature measurements as well as white blood cell counts within 24 h before starting the vitamin C protocol. In the study, 127 patients included who met the inclusion criteria. In the cohort, four groups were identified: “Temperature ≥37.1 °C, white blood cell count ≥15.0 1000/mm3” (group A; n = 27), “≥37.1 °C, <15.0 1000/mm3” (group B; n = 30), “<37.1 °C, ≥15.0 1000/mm3” (group C; n = 35) and “<37.1 °C, <15.0 1000/mm3” (group D; n = 35). The intensive care unit mortality rates were 15% for group A, 33% for group B, 34% for group C, and 49% for group D (p = 0.051). The temporal improvement in organ dysfunction and vasopressor dose seemed more apparent in group A patients. Our results suggest that different subphenotypes exist among sepsis patients treated using a vitamin C protocol, and clinical outcomes might be better for patients with the hyperinflammatory subphenotype.

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Section: Discussionsupporting

confidence: 51%

Subphenotypes in Patients with Septic Shock Receiving Vitamin C, Hydrocortisone, and Thiamine: A Retrospective Cohort Analysis

et al. 2019

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“…3). Some of this residual heterogeneity is expected, owing to the clinical heterogeneity inherent across sepsis cohorts [40][41][42] , but highlighted the need for a robust training procedure 43 .…”

Section: Resultsmentioning

confidence: 99%

A generalizable 29-mRNA neural-network classifier for acute bacterial and viral infections

Mayhew¹,

Buturović²,

Luethy³

et al. 2020

Nat Commun

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124

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Improved identification of bacterial and viral infections would reduce morbidity from sepsis, reduce antibiotic overuse, and lower healthcare costs. Here, we develop a generalizable hostgene-expression-based classifier for acute bacterial and viral infections. We use training data (N = 1069) from 18 retrospective transcriptomic studies. Using only 29 preselected host mRNAs, we train a neural-network classifier with a bacterial-vs-other area under the receiver-operating characteristic curve (AUROC) 0.92 (95% CI 0.90-0.93) and a viral-vsother AUROC 0.92 (95% CI 0.90-0.93). We then apply this classifier, inflammatix-bacterialviral-noninfected-version 1 (IMX-BVN-1), without retraining, to an independent cohort (N = 163). In this cohort, IMX-BVN-1 AUROCs are: bacterial-vs.-other 0.86 (95% CI 0.77-0.93), and viral-vs.-other 0.85 (95% CI 0.76-0.93). In patients enrolled within 36 h of hospital admission (N = 70), IMX-BVN-1 AUROCs are: bacterial-vs.-other 0.92 (95% CI 0.83-0.99), and viral-vs.-other 0.91 (95% CI 0.82-0.98). With further study, IMX-BVN-1 could provide a tool for assessing patients with suspected infection and sepsis at hospital admission.

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“…Although the particular genes that best discriminated the high-risk cohort varied by study, this may be due to high correlation among many dysregulated genes, rather than a failure to replicate. Indeed, a metaanalysis by Sweeney et al [123] that included mortality data from 14 diverse datasets of bacterial infection, including both adult and child cohorts, identified three clusters (a high-mortality "inflammopathic" cluster, a low-mortality "adaptive" cluster, and an additional "coagulopathic" cluster characterized by abnormal coagulation profiles) that could be distinguished with an 11-gene signature. They assessed overlap of their signature-based clusters with the high-mortality clusters identified in the MARS and Wong et al pediatric cohorts, and they found substantial overlap in patients identified by each cohort's high-mortality/high-inflammation endotype.…”

Section: Sepsis Gene Expression Studies: Ready For Clinical Launch?mentioning

confidence: 99%

Precision Medicine in Critical Illness: Sepsis and Acute Respiratory Distress Syndrome

Rogers

Meyer

2020

Precision in Pulmonary, Critical Care, and Sleep Medicine

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Unsupervised Analysis of Transcriptomics in Bacterial Sepsis Across Multiple Datasets Reveals Three Robust Clusters

Abstract: The three sepsis subtypes may represent a unifying framework for understanding the molecular heterogeneity of the sepsis syndrome. Further study could potentially enable a precision medicine approach of matching novel immunomodulatory therapies with septic patients most likely to benefit.

Cited by 247 publications

References 51 publications

Subphenotypes in Patients with Septic Shock Receiving Vitamin C, Hydrocortisone, and Thiamine: A Retrospective Cohort Analysis

Subphenotypes in Patients with Septic Shock Receiving Vitamin C, Hydrocortisone, and Thiamine: A Retrospective Cohort Analysis

A generalizable 29-mRNA neural-network classifier for acute bacterial and viral infections

Precision Medicine in Critical Illness: Sepsis and Acute Respiratory Distress Syndrome

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