Development of a Genomic Metric That Can Be Rapidly Used to Predict Clinical Outcome in Severely Injured Trauma Patients*

Cuenca, Alex G.; Gentile, Lori F.; López, María Cecilia; Ungaro, Ricardo; Liu, Huazhi; Xiao, Wenzhong; Seok, Junhee; Mindrinos, Michael; Ang, Darwin; Baslanti, Tezcan Ozrazgat; Bïhorac, Azra; Efron, Philip A.; Cuschieri, Joseph; Warren, H. Shaw; Tompkins, Ronald G.; Maier, Ronald V.; Baker, Henry V.; Moldawer, Lyle L.

doi:10.1097/ccm.0b013e318277131c

Cited by 90 publications

(107 citation statements)

References 26 publications

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“…For instance, upregulation of THBS1 (thrombospondin 1), to which 3/14 of the biomarker probe sets were mapped, has been associated with complicated recovery in blunt trauma patients, 29 supporting the broad applicability of our approach and findings. The discovery of THBS1 also supports the potential biological relevance of our biomarkers.…”

Section: Discussionsupporting

confidence: 66%

“…As trauma promotes susceptibility to infection and genomic signatures appear to play an increasingly promising role in prognosis, 26,29 we analyzed the blood transcriptome and clinical characteristics data of 113 patients from the 573 thermally injured patients enrolled in the Inflammation and the Host Response to Injury study. Using clinical characteristics available upon admission and early genomic signatures, we developed novel predictive models that would permit early identification of burn patients at high risk of developing repeated infection indicative of an early hyper-susceptible state.…”

Section: Introductionmentioning

confidence: 99%

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Prediction of Multiple Infections After Severe Burn Trauma

et al. 2015

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Objective To develop predictive models for early triage of burn patients based on hyper-susceptibility to repeated infections. Background Infection remains a major cause of mortality and morbidity after severe trauma, demanding new strategies to combat infections. Models for infection prediction are lacking. Methods Secondary analysis of 459 burn patients (≥16 years old) with ≥20% total body surface area burns recruited from six US burn centers. We compared blood transcriptomes with a 180-h cut-off on the injury-to-transcriptome interval of 47 patients (≤1 infection episode) to those of 66 hyper-susceptible patients (multiple [≥2] infection episodes [MIE]). We used LASSO regression to select biomarkers and multivariate logistic regression to built models, accuracy of which were assessed by area under receiver operating characteristic curve (AUROC) and cross-validation. Results Three predictive models were developed covariates of: (1) clinical characteristics; (2) expression profiles of 14 genomic probes; (3) combining (1) and (2). The genomic and clinical models were highly predictive of MIE status (AUROCGenomic = 0.946 [95% CI, 0.906–0.986]); AUROCClinical = 0.864 [CI, 0.794–0.933]; AUROCGenomic/AUROCClinical P = 0.044). Combined model has an increased AUROCCombined of 0.967 (CI, 0.940–0.993) compared to the individual models (AUROCCombined/AUROCClinical P = 0.0069). Hyper-susceptible patients show early alterations in immune-related signaling pathways, epigenetic modulation and chromatin remodeling. Conclusions Early triage of burn patients more susceptible to infections can be made using clinical characteristics and/or genomic signatures. Genomic signature suggests new insights into the pathophysiology of hyper-susceptibility to infection may lead to novel potential therapeutic or prophylactic targets.

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Section: Discussionsupporting

confidence: 66%

Section: Introductionmentioning

confidence: 99%

Prediction of Multiple Infections After Severe Burn Trauma

et al. 2015

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“…Expression measurement of the entire genome would not be required once a suitable set of predictive genes (<100) is identified. The identification of molecular endotypes that identify classes of infants via modern multiplex messenger RNA (mRNA) quantification platforms can be obtained rapidly (8)(9)(10)(11)(12) h) (38,39). Integration of these techniques into intensive care environments has great potential to benefit patient populations with diverse clinical presentations of infection such as preterm neonates.…”

Section: Discussionmentioning

confidence: 99%

Postnatal Age Is a Critical Determinant of the Neonatal Host Response to Sepsis

Wynn

Guthrie

Wong

et al. 2015

Mol Med

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Neonates manifest a unique host response to sepsis even among other children. Preterm neonates may experience sepsis soon after birth or during often-protracted birth hospitalizations as they attain physiologic maturity. We examined the transcriptome using genome-wide expression profiling on prospectively collected peripheral blood samples from infants evaluated for sepsis within 24 h after clinical presentation. Simultaneous plasma samples were examined for alterations in inflammatory mediators. Group designation (sepsis or uninfected) was determined retrospectively on the basis of clinical exam and laboratory results over the next 72 h from the time of evaluation. Unsupervised analysis showed the major node of separation between groups was timing of sepsis episode relative to birth (early, <3 d, or late, ≥3 d). Principal component analyses revealed significant differences between patients with early or late sepsis despite the presence of similar key immunologic pathway aberrations in both groups. Unique to neonates, the uninfected state and host response to sepsis is significantly affected by timing relative to birth. Future therapeutic approaches may need to be tailored to the timing of the infectious event based on postnatal age.

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“…[88,89]), trauma (9 studies, e.g. [90,91]), pregnancy (7 studies, e.g. [92][93][94]), allergy (6 studies, e.g.…”

Section: Blood Transcriptome Profiling Studies In Health and Diseasementioning

confidence: 99%

Assessment of immune status using blood transcriptomics and potential implications for global health

Chaussabel¹

2015

Seminars in Immunology

102

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The immune system plays a key role in health maintenance and pathogenesis of a wide range of diseases. Leukocytes that are present in the blood convey valuable information about the status of the immune system. Blood transcriptomics, which consists in profiling blood transcript abundance on genome-wide scales, has gained in popularity over the past several years. Indeed, practicality and simplicity largely makes up for what this approach may lack in terms of cell population-level resolution. An extensive survey of the literature reveals increasingly widespread use across virtually all fields of medicine as well as across a number of different animal species, including model organisms but also animals of economical importance. Dissemination across such a wide range of disciplines holds the promise of adding a new perspective, breadth or context, to the considerable depth afforded by whole genome profiling of blood transcript abundance. Indeed, it is only through such contextualization that a truly global perspective will be gained from the use of systems approaches. Also discussed are opportunities that may arise for the fields of immunology and medicine from using blood transcriptomics as a common denominator for developing interactions and cooperation across fields of research that have traditionally been and largely remain compartmentalized. Finally, an argument is made for building immunology research capacity using blood transcriptomics platforms in low-resource and high-disease burden settings.

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Development of a Genomic Metric That Can Be Rapidly Used to Predict Clinical Outcome in Severely Injured Trauma Patients*

Cited by 90 publications

References 26 publications

Prediction of Multiple Infections After Severe Burn Trauma

Prediction of Multiple Infections After Severe Burn Trauma

Postnatal Age Is a Critical Determinant of the Neonatal Host Response to Sepsis

Assessment of immune status using blood transcriptomics and potential implications for global health

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