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Halder A, Liesenfeld O, Whitfield N, Uhle F, Schenz J, Mehrabi A, Schmitt FCF, Weigand MA, Decker SO. A 29-mRNA host-response classifier identifies bacterial infections following liver transplantation - a pilot study. Langenbecks Arch Surg 2024; 409:185. [PMID: 38865015 PMCID: PMC11169022 DOI: 10.1007/s00423-024-03373-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2024] [Accepted: 06/01/2024] [Indexed: 06/13/2024]
Abstract
PURPOSE Infections are common complications in patients following liver transplantation (LTX). The early diagnosis and prognosis of these infections is an unmet medical need even when using routine biomarkers such as C-reactive protein (CRP) and procalcitonin (PCT). Therefore, new approaches are necessary. METHODS In a prospective, observational pilot study, we monitored 30 consecutive patients daily between days 0 and 13 following LTX using the 29-mRNA host classifier IMX-BVN-3b that determine the likelihood of bacterial infections and viral infections. True infection status was determined using clinical adjudication. Results were compared to the accuracy of CRP and PCT for patients with and without bacterial infection due to clinical adjudication. RESULTS Clinical adjudication confirmed bacterial infections in 10 and fungal infections in 2 patients. 20 patients stayed non-infected until day 13 post-LTX. IMX-BVN-3b bacterial scores were increased directly following LTX and decreased until day four in all patients. Bacterial IMX-BVN-3b scores detected bacterial infections in 9 out of 10 patients. PCT concentrations did not differ between patients with or without bacterial, whereas CRP was elevated in all patients with significantly higher levels in patients with bacterial infections. CONCLUSION The 29-mRNA host classifier IMX-BVN-3b identified bacterial infections in post-LTX patients and did so earlier than routine biomarkers. While our pilot study holds promise future studies will determine whether these classifiers may help to identify post-LTX infections earlier and improve patient management. CLINICAL TRIAL NOTATION German Clinical Trials Register: DRKS00023236, Registered 07 October 2020, https://drks.de/search/en/trial/DRKS00023236.
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Affiliation(s)
- Amelie Halder
- Heidelberg University, Medical Faculty Heidelberg, Department of Anesthesiology, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany
| | | | | | - Florian Uhle
- Heidelberg University, Medical Faculty Heidelberg, Department of Anesthesiology, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany
| | - Judith Schenz
- Heidelberg University, Medical Faculty Heidelberg, Department of Anesthesiology, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany
| | - Arianeb Mehrabi
- Heidelberg University, Medical Faculty Heidelberg, Department of General, Visceral & Transplantation Surgery, Neuenheimer Feld 420, 69120, Heidelberg, Germany
| | - Felix C F Schmitt
- Heidelberg University, Medical Faculty Heidelberg, Department of Anesthesiology, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany
| | - Markus A Weigand
- Heidelberg University, Medical Faculty Heidelberg, Department of Anesthesiology, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany
| | - Sebastian O Decker
- Heidelberg University, Medical Faculty Heidelberg, Department of Anesthesiology, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany.
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2
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Pretorius A, Nefefe T, Thema N, Liebenberg J, Steyn H, van Kleef M. Screening for immune biomarkers associated with infection or protection against Ehrlichia ruminantium by RNA-sequencing analysis. Microb Pathog 2024; 189:106588. [PMID: 38369169 DOI: 10.1016/j.micpath.2024.106588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 01/11/2024] [Accepted: 02/15/2024] [Indexed: 02/20/2024]
Abstract
Heartwater is one of the most economically important tick-borne fatal diseases of livestock. The disease is caused by the bacteria Ehrlichia ruminantium transmitted by Amblyomma ticks. Although there is evidence that interferon-gamma controls E. ruminantium growth and that cellular immune responses are protective, an effective recombinant vaccine for this disease is lacking. Analyses of markers associated with infection as well as protection will lead to a better understanding of the E. ruminantium immune response and corresponding pathways induced in sheep peripheral blood mononuclear cells (PBMC) will assist in development of such a vaccine. In this study, Biomarkers of infection (BMI) were identified as uniquely expressed genes during primary infection and biomarkers of protection (BMP) associated with immune to heartwater were identified post challenge. Sheep were experimentally infected and challenged with E. ruminantium infected ticks. The immune phenotypic and transcriptome profile of their PBMC were compared to their own naïve PBMC collected before infection. The study revealed 305 differentially expressed genes (DEGs) as BMI, of these 17 were upregulated at all three time-points investigated. These DEGs, form part of the bacterial invasion of epithelial cells Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway, and others detected from day 1 post infection and are considered predictive markers for early heartwater infection in ruminants. Similarly, a total of 332 DEGs were identified as BMP, of these 100 were upregulated and 75 were downregulated at all three time-points investigated. However, at D1PC most DEGs were downregulated (n = 1312) that correlated with a reduction in the % CD4 and CD8 T cells detected with flow cytometry. KEGG pathway analyses showed complete down regulation of T cell specific pathways possibly due to homing of immune cells to the site of infection after acquired immunity developed. At D4PC, expression levels of most of these downregulated genes increased and by D6PC they were upregulated. This indicates that the sampling time-point for biomarker analyses is important when results for acquired immune responses are inferred. This data identified DEGs that could be considered as biomarkers of protective immunity that can be used for identification of vaccine antigens and provides a strong foundation to further development of heartwater recombinant vaccines.
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Affiliation(s)
- A Pretorius
- Agricultural Research Council -Onderstepoort Veterinary Research, Private Bag X05, Onderstepoort, 0110, South Africa; Department of Veterinary Tropical Diseases, University of Pretoria, Private Bag X04, Onderstepoort, 0110, South Africa.
| | - T Nefefe
- Agricultural Research Council -Onderstepoort Veterinary Research, Private Bag X05, Onderstepoort, 0110, South Africa; Department of Veterinary Tropical Diseases, University of Pretoria, Private Bag X04, Onderstepoort, 0110, South Africa
| | - N Thema
- Agricultural Research Council -Onderstepoort Veterinary Research, Private Bag X05, Onderstepoort, 0110, South Africa
| | - J Liebenberg
- Agricultural Research Council -Onderstepoort Veterinary Research, Private Bag X05, Onderstepoort, 0110, South Africa
| | - H Steyn
- Agricultural Research Council -Onderstepoort Veterinary Research, Private Bag X05, Onderstepoort, 0110, South Africa
| | - M van Kleef
- Agricultural Research Council -Onderstepoort Veterinary Research, Private Bag X05, Onderstepoort, 0110, South Africa; Department of Veterinary Tropical Diseases, University of Pretoria, Private Bag X04, Onderstepoort, 0110, South Africa
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3
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Marin MJ, van Wijk XMR, Chambliss AB. Advances in sepsis biomarkers. Adv Clin Chem 2024; 119:117-166. [PMID: 38514209 DOI: 10.1016/bs.acc.2024.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2024]
Abstract
Sepsis, a dysregulated host immune response to an infectious agent, significantly increases morbidity and mortality for hospitalized patients worldwide. This chapter reviews (1) the basic principles of infectious diseases, pathophysiology and current definition of sepsis, (2) established sepsis biomarkers such lactate, procalcitonin and C-reactive protein, (3) novel, newly regulatory-cleared/approved biomarkers, such as assays that evaluate white blood cell properties and immune response molecules, and (4) emerging biomarkers and biomarker panels to highlight future directions and opportunities in the diagnosis and management of sepsis.
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Affiliation(s)
- Maximo J Marin
- Department of Pathology, Immunology & Laboratory Medicine, University of Florida, Gainesville, Florida, USA
| | | | - Allison B Chambliss
- Department of Pathology & Laboratory Medicine, University of California Los Angeles, Los Angeles, California, USA
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4
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Dementieva NV, Dysin AP, Shcherbakov YS, Nikitkina EV, Musidray AA, Petrova AV, Mitrofanova OV, Plemyashov KV, Azovtseva AI, Griffin DK, Romanov MN. Risk of Sperm Disorders and Impaired Fertility in Frozen-Thawed Bull Semen: A Genome-Wide Association Study. Animals (Basel) 2024; 14:251. [PMID: 38254422 PMCID: PMC10812825 DOI: 10.3390/ani14020251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Revised: 01/08/2024] [Accepted: 01/11/2024] [Indexed: 01/24/2024] Open
Abstract
Cryopreservation is a widely used method of semen conservation in animal breeding programs. This process, however, can have a detrimental effect on sperm quality, especially in terms of its morphology. The resultant sperm disorders raise the risk of reduced sperm fertilizing ability, which poses a serious threat to the long-term efficacy of livestock reproduction and breeding. Understanding the genetic factors underlying these effects is critical for maintaining sperm quality during cryopreservation, and for animal fertility in general. In this regard, we performed a genome-wide association study to identify genomic regions associated with various cryopreservation sperm abnormalities in Holstein cattle, using single nucleotide polymorphism (SNP) markers via a high-density genotyping assay. Our analysis revealed a significant association of specific SNPs and candidate genes with absence of acrosomes, damaged cell necks and tails, as well as wrinkled acrosomes and decreased motility of cryopreserved sperm. As a result, we identified candidate genes such as POU6F2, LPCAT4, DPYD, SLC39A12 and CACNB2, as well as microRNAs (bta-mir-137 and bta-mir-2420) that may play a critical role in sperm morphology and disorders. These findings provide crucial information on the molecular mechanisms underlying acrosome integrity, motility, head abnormalities and damaged cell necks and tails of sperm after cryopreservation. Further studies with larger sample sizes, genome-wide coverage and functional validation are needed to explore causal variants in more detail, thereby elucidating the mechanisms mediating these effects. Overall, our results contribute to the understanding of genetic architecture in cryopreserved semen quality and disorders in bulls, laying the foundation for improved animal reproduction and breeding.
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Affiliation(s)
- Natalia V. Dementieva
- Russian Research Institute of Farm Animal Genetics and Breeding—Branch of the L. K. Ernst Federal Research Centre for Animal Husbandry, Pushkin, 196601 St. Petersburg, Russia; (A.P.D.); (Y.S.S.); (E.V.N.); (A.A.M.); (A.V.P.); (O.V.M.); (A.I.A.)
| | - Artem P. Dysin
- Russian Research Institute of Farm Animal Genetics and Breeding—Branch of the L. K. Ernst Federal Research Centre for Animal Husbandry, Pushkin, 196601 St. Petersburg, Russia; (A.P.D.); (Y.S.S.); (E.V.N.); (A.A.M.); (A.V.P.); (O.V.M.); (A.I.A.)
| | - Yuri S. Shcherbakov
- Russian Research Institute of Farm Animal Genetics and Breeding—Branch of the L. K. Ernst Federal Research Centre for Animal Husbandry, Pushkin, 196601 St. Petersburg, Russia; (A.P.D.); (Y.S.S.); (E.V.N.); (A.A.M.); (A.V.P.); (O.V.M.); (A.I.A.)
| | - Elena V. Nikitkina
- Russian Research Institute of Farm Animal Genetics and Breeding—Branch of the L. K. Ernst Federal Research Centre for Animal Husbandry, Pushkin, 196601 St. Petersburg, Russia; (A.P.D.); (Y.S.S.); (E.V.N.); (A.A.M.); (A.V.P.); (O.V.M.); (A.I.A.)
| | - Artem A. Musidray
- Russian Research Institute of Farm Animal Genetics and Breeding—Branch of the L. K. Ernst Federal Research Centre for Animal Husbandry, Pushkin, 196601 St. Petersburg, Russia; (A.P.D.); (Y.S.S.); (E.V.N.); (A.A.M.); (A.V.P.); (O.V.M.); (A.I.A.)
| | - Anna V. Petrova
- Russian Research Institute of Farm Animal Genetics and Breeding—Branch of the L. K. Ernst Federal Research Centre for Animal Husbandry, Pushkin, 196601 St. Petersburg, Russia; (A.P.D.); (Y.S.S.); (E.V.N.); (A.A.M.); (A.V.P.); (O.V.M.); (A.I.A.)
| | - Olga V. Mitrofanova
- Russian Research Institute of Farm Animal Genetics and Breeding—Branch of the L. K. Ernst Federal Research Centre for Animal Husbandry, Pushkin, 196601 St. Petersburg, Russia; (A.P.D.); (Y.S.S.); (E.V.N.); (A.A.M.); (A.V.P.); (O.V.M.); (A.I.A.)
| | - Kirill V. Plemyashov
- Federal State Budgetary Educational Institution of Higher Education “St. Petersburg State University of Veterinary Medicine”, 196084 St. Petersburg, Russia;
| | - Anastasiia I. Azovtseva
- Russian Research Institute of Farm Animal Genetics and Breeding—Branch of the L. K. Ernst Federal Research Centre for Animal Husbandry, Pushkin, 196601 St. Petersburg, Russia; (A.P.D.); (Y.S.S.); (E.V.N.); (A.A.M.); (A.V.P.); (O.V.M.); (A.I.A.)
| | | | - Michael N. Romanov
- School of Biosciences, University of Kent, Canterbury CT2 7NJ, UK;
- L. K. Ernst Federal Research Centre for Animal Husbandry, Dubrovitsy, 142132 Podolsk, Moscow Oblast, Russia
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Pandya R, He YD, Sweeney TE, Hasin-Brumshtein Y, Khatri P. A machine learning classifier using 33 host immune response mRNAs accurately distinguishes viral and non-viral acute respiratory illnesses in nasal swab samples. Genome Med 2023; 15:64. [PMID: 37641125 PMCID: PMC10463681 DOI: 10.1186/s13073-023-01216-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 07/27/2023] [Indexed: 08/31/2023] Open
Abstract
BACKGROUND Viral acute respiratory illnesses (viral ARIs) contribute significantly to human morbidity and mortality worldwide, but their successful treatment requires timely diagnosis of viral etiology, which is complicated by overlap in clinical presentation with the non-viral ARIs. Multiple pandemics in the twenty-first century to date have further highlighted the unmet need for effective monitoring of clinically relevant emerging viruses. Recent studies have identified conserved host response to viral infections in the blood. METHODS We hypothesize that a similarly conserved host response in nasal samples can be utilized for diagnosis and to rule out viral infection in symptomatic patients when current diagnostic tests are negative. Using a multi-cohort analysis framework, we analyzed 1555 nasal samples across 10 independent cohorts dividing them into training and validation. RESULTS Using six of the datasets for training, we identified 119 genes that are consistently differentially expressed in viral ARI patients (N = 236) compared to healthy controls (N = 146) and further down-selected 33 genes for classifier development. The resulting locked logistic regression-based classifier using the 33-mRNAs had AUC of 0.94 and 0.89 in the six training and four validation datasets, respectively. Furthermore, we found that although trained on healthy controls only, in the four validation datasets, the 33-mRNA classifier distinguished viral ARI from both healthy or non-viral ARI samples with > 80% specificity and sensitivity, irrespective of age, viral type, and viral load. Single-cell RNA-sequencing data showed that the 33-mRNA signature is dominated by macrophages and neutrophils in nasal samples. CONCLUSION This proof-of-concept signature has potential to be adapted as a clinical point-of-care test ('RespVerity') to improve the diagnosis of viral ARIs.
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Affiliation(s)
| | - Yudong D. He
- Inflammatix Inc., CA 94085 Sunnyvale, USA
- Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, Stanford, CA 94305 USA
- Allen Institute of Immunology, Seattle, WA USA
| | | | | | - Purvesh Khatri
- Inflammatix Inc., CA 94085 Sunnyvale, USA
- Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, Stanford, CA 94305 USA
- Department of Medicine, Center for Biomedical Informatics Research, School of Medicine, Stanford University, Stanford, CA 94305 USA
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Balch JA, Chen UI, Liesenfeld O, Starostik P, Loftus TJ, Efron PA, Brakenridge SC, Sweeney TE, Moldawer LL. Defining critical illness using immunological endotypes in patients with and without sepsis: a cohort study. Crit Care 2023; 27:292. [PMID: 37474944 PMCID: PMC10360294 DOI: 10.1186/s13054-023-04571-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 07/07/2023] [Indexed: 07/22/2023] Open
Abstract
BACKGROUND Sepsis is a heterogenous syndrome with limited therapeutic options. Identifying immunological endotypes through gene expression patterns in septic patients may lead to targeted interventions. We investigated whether patients admitted to a surgical intensive care unit (ICU) with sepsis and with high risk of mortality express similar endotypes to non-septic, but still critically ill patients using two multiplex transcriptomic metrics obtained both on admission to a surgical ICU and at set intervals. METHODS We analyzed transcriptomic data from 522 patients in two single-site, prospective, observational cohorts admitted to surgical ICUs over a 5-year period ending in July 2020. Using an FDA-cleared analytical platform (nCounter FLEX®, NanoString, Inc.), we assessed a previously validated 29-messenger RNA transcriptomic classifier for likelihood of 30-day mortality (IMX-SEV-3) and a 33-messenger RNA transcriptomic endotype classifier. Clinical outcomes included all-cause mortality, development of chronic critical illness, and secondary infections. Univariate and multivariate analyses were performed to assess for true effect and confounding. RESULTS Sepsis was associated with a significantly higher predicted and actual hospital mortality. At enrollment, the predominant endotype for both septic and non-septic patients was adaptive, though with significantly different distributions. Inflammopathic and coagulopathic septic patients, as well as inflammopathic non-septic patients, showed significantly higher frequencies of secondary infections compared to those with adaptive endotypes (p < 0.01). Endotypes changed during ICU hospitalization in 57.5% of patients. Patients who remained adaptive had overall better prognosis, while those who remained inflammopathic or coagulopathic had worse overall outcomes. For severity metrics, patients admitted with sepsis and a high predicted likelihood of mortality showed an inflammopathic (49.6%) endotype and had higher rates of cumulative adverse outcomes (67.4%). Patients at low mortality risk, whether septic or non-septic, almost uniformly presented with an adaptive endotype (100% and 93.4%, respectively). CONCLUSION Critically ill surgical patients express different and evolving immunological endotypes depending upon both their sepsis status and severity of their clinical course. Future studies will elucidate whether endotyping critically ill, septic patients can identify individuals for targeted therapeutic interventions to improve patient management and outcomes.
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Affiliation(s)
- Jeremy A Balch
- Sepsis and Critical Illness Research Center, Department of Surgery, Shands Hospital, University of Florida College of Medicine, Room 6116, 1600 SW Archer Road, P. O. Box 100019, Gainesville, FL, 32610-0019, USA
| | - Uan-I Chen
- Inflammatix, Inc., Sunnyvale, CA, 94085, USA
| | | | - Petr Starostik
- UF Health Medical Laboratory at Rocky Point, Department of Pathology, Immunology and Laboratory Medicine, University of Florida College of Medicine, Gainesville, FL, 32610, USA
| | - Tyler J Loftus
- Sepsis and Critical Illness Research Center, Department of Surgery, Shands Hospital, University of Florida College of Medicine, Room 6116, 1600 SW Archer Road, P. O. Box 100019, Gainesville, FL, 32610-0019, USA
| | - Philip A Efron
- Sepsis and Critical Illness Research Center, Department of Surgery, Shands Hospital, University of Florida College of Medicine, Room 6116, 1600 SW Archer Road, P. O. Box 100019, Gainesville, FL, 32610-0019, USA
| | - Scott C Brakenridge
- Sepsis and Critical Illness Research Center, Department of Surgery, Shands Hospital, University of Florida College of Medicine, Room 6116, 1600 SW Archer Road, P. O. Box 100019, Gainesville, FL, 32610-0019, USA
- Department of Surgery, Harborview Medical Center, University of Washington School of Medicine, Seattle, WA, 63110, USA
| | | | - Lyle L Moldawer
- Sepsis and Critical Illness Research Center, Department of Surgery, Shands Hospital, University of Florida College of Medicine, Room 6116, 1600 SW Archer Road, P. O. Box 100019, Gainesville, FL, 32610-0019, USA.
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Altindiş M, Kahraman Kilbaş EP. Managing Viral Emerging Infectious Diseases via Current and Future Molecular Diagnostics. Diagnostics (Basel) 2023; 13:diagnostics13081421. [PMID: 37189522 DOI: 10.3390/diagnostics13081421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 04/10/2023] [Accepted: 04/14/2023] [Indexed: 05/17/2023] Open
Abstract
Emerging viral infectious diseases have been a constant threat to global public health in recent times. In managing these diseases, molecular diagnostics has played a critical role. Molecular diagnostics involves the use of various technologies to detect the genetic material of various pathogens, including viruses, in clinical samples. One of the most commonly used molecular diagnostics technologies for detecting viruses is polymerase chain reaction (PCR). PCR amplifies specific regions of the viral genetic material in a sample, making it easier to detect and identify viruses. PCR is particularly useful for detecting viruses that are present in low concentrations in clinical samples, such as blood or saliva. Another technology that is becoming increasingly popular for viral diagnostics is next-generation sequencing (NGS). NGS can sequence the entire genome of a virus present in a clinical sample, providing a wealth of information about the virus, including its genetic makeup, virulence factors, and potential to cause an outbreak. NGS can also help identify mutations and discover new pathogens that could affect the efficacy of antiviral drugs and vaccines. In addition to PCR and NGS, there are other molecular diagnostics technologies that are being developed to manage emerging viral infectious diseases. One of these is CRISPR-Cas, a genome editing technology that can be used to detect and cut specific regions of viral genetic material. CRISPR-Cas can be used to develop highly specific and sensitive viral diagnostic tests, as well as to develop new antiviral therapies. In conclusion, molecular diagnostics tools are critical for managing emerging viral infectious diseases. PCR and NGS are currently the most commonly used technologies for viral diagnostics, but new technologies such as CRISPR-Cas are emerging. These technologies can help identify viral outbreaks early, track the spread of viruses, and develop effective antiviral therapies and vaccines.
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Affiliation(s)
- Mustafa Altindiş
- Medical Microbiology Department, Faculty of Medicine, Sakarya University, Sakarya 54050, Türkiye
| | - Elmas Pınar Kahraman Kilbaş
- Medical Laboratory Techniques, Vocational School of Health Services, Fenerbahce University, Istanbul 34758, Türkiye
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Pelaia TM, Shojaei M, McLean AS. The Role of Transcriptomics in Redefining Critical Illness. Crit Care 2023; 27:89. [PMID: 36941625 PMCID: PMC10027592 DOI: 10.1186/s13054-023-04364-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2023] Open
Abstract
This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2023. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2023 . Further information about the Annual Update in Intensive Care and Emergency Medicine is available from https://link.springer.com/bookseries/8901 .
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Affiliation(s)
- Tiana M Pelaia
- Department of Intensive Care Medicine, Nepean Hospital, Kingswood, NSW, Australia.
| | - Maryam Shojaei
- Department of Intensive Care Medicine, Nepean Hospital, Kingswood, NSW, Australia
- Centre for Immunology and Allergy Research, Westmead Institute for Medical Research, Westmead, NSW, Australia
| | - Anthony S McLean
- Department of Intensive Care Medicine, Nepean Hospital, Kingswood, NSW, Australia
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9
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Shojaei M, Chen UI, Midic U, Thair S, Teoh S, McLean A, Sweeney TE, Thompson M, Liesenfeld O, Khatri P, Tang B. Multisite validation of a host response signature for predicting likelihood of bacterial and viral infections in patients with suspected influenza. Eur J Clin Invest 2023; 53:e13957. [PMID: 36692131 DOI: 10.1111/eci.13957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 12/08/2022] [Accepted: 01/05/2023] [Indexed: 01/25/2023]
Abstract
BACKGROUND Indiscriminate use of antimicrobials and antimicrobial resistance is a public health threat. IMX-BVN-1, a 29-host mRNA classifier, provides two separate scores that predict likelihoods of bacterial and viral infections in patients with suspected acute infections. We validated the performance of IMX-BVN-1 in adults attending acute health care settings with suspected influenza. METHOD We amplified 29-host response genes in RNA extracted from blood by NanoString nCounter. IMX-BVN-1 calculated two scores to predict probabilities of bacterial and viral infections. Results were compared against the infection status (no infection; highly probable/possible infection; confirmed infection) determined by clinical adjudication. RESULTS Amongst 602 adult patients (74.9% ED, 16.9% ICU, 8.1% outpatients), 7.6% showed in-hospital mortality and 15.5% immunosuppression. Median IMX-BVN-1 bacterial and viral scores were higher in patients with confirmed bacterial (0.27) and viral (0.62) infections than in those without bacterial (0.08) or viral (0.21) infection, respectively. The AUROC distinguishing bacterial from nonbacterial illness was 0.81 and 0.87 when distinguishing viral from nonviral illness. The bacterial top quartile's positive likelihood ratio (LR) was 4.38 with a rule-in specificity of 88%; the bacterial bottom quartile's negative LR was 0.13 with a rule-out sensitivity of 96%. Similarly, the viral top quartile showed an infinite LR with rule-in specificity of 100%; the viral bottom quartile had a LR of 0.22 and a rule-out sensitivity of 85%. CONCLUSION IMX-BVN-1 showed high accuracy for differentiating bacterial and viral infections from noninfectious illness in patients with suspected influenza. Clinical utility of IMX-BVN will be validated following integration into a point of care system.
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Affiliation(s)
- Maryam Shojaei
- Department of Medicine, Sydney Medical School Nepean, Nepean Hospital, University of Sydney, Penrith, New South Wales, Australia.,Department of Intensive Care Medicine, Nepean Hospital, Penrith, New South Wales, Australia.,Centre for Immunology and Allergy Research, Westmead Institute for Medical Research, Westmead, New South Wales, Australia
| | - Uan-I Chen
- Inflammatix, Inc., Sunnyvale, California, USA
| | - Uros Midic
- Inflammatix, Inc., Sunnyvale, California, USA
| | | | - Sally Teoh
- Department of Intensive Care Medicine, Nepean Hospital, Penrith, New South Wales, Australia
| | - Anthony McLean
- Department of Intensive Care Medicine, Nepean Hospital, Penrith, New South Wales, Australia
| | | | | | | | | | - Benjamin Tang
- Department of Intensive Care Medicine, Nepean Hospital, Penrith, New South Wales, Australia.,Centre for Immunology and Allergy Research, Westmead Institute for Medical Research, Westmead, New South Wales, Australia
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10
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Ram-Mohan N, Rogers AJ, Blish CA, Nadeau KC, Zudock EJ, Kim D, Quinn JV, Sun L, Liesenfeld O, Yang S. Using a 29-mRNA Host Response Classifier To Detect Bacterial Coinfections and Predict Outcomes in COVID-19 Patients Presenting to the Emergency Department. Microbiol Spectr 2022; 10:e0230522. [PMID: 36250865 PMCID: PMC9769905 DOI: 10.1128/spectrum.02305-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Accepted: 09/26/2022] [Indexed: 01/06/2023] Open
Abstract
Clinicians in the emergency department (ED) face challenges in concurrently assessing patients with suspected COVID-19 infection, detecting bacterial coinfection, and determining illness severity since current practices require separate workflows. Here, we explore the accuracy of the IMX-BVN-3/IMX-SEV-3 29 mRNA host response classifiers in simultaneously detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and bacterial coinfections and predicting clinical severity of COVID-19. A total of 161 patients with PCR-confirmed COVID-19 (52.2% female; median age, 50.0 years; 51% hospitalized; 5.6% deaths) were enrolled at the Stanford Hospital ED. RNA was extracted (2.5 mL whole blood in PAXgene blood RNA), and 29 host mRNAs in response to the infection were quantified using Nanostring nCounter. The IMX-BVN-3 classifier identified SARS-CoV-2 infection in 151 patients with a sensitivity of 93.8%. Six of 10 patients undetected by the classifier had positive COVID tests more than 9 days prior to enrollment, and the remaining patients oscillated between positive and negative results in subsequent tests. The classifier also predicted that 6 (3.7%) patients had a bacterial coinfection. Clinical adjudication confirmed that 5/6 (83.3%) of the patients had bacterial infections, i.e., Clostridioides difficile colitis (n = 1), urinary tract infection (n = 1), and clinically diagnosed bacterial infections (n = 3), for a specificity of 99.4%. Two of 101 (2.8%) patients in the IMX-SEV-3 "Low" severity classification and 7/60 (11.7%) in the "Moderate" severity classification died within 30 days of enrollment. IMX-BVN-3/IMX-SEV-3 classifiers accurately identified patients with COVID-19 and bacterial coinfections and predicted patients' risk of death. A point-of-care version of these classifiers, under development, could improve ED patient management, including more accurate treatment decisions and optimized resource utilization. IMPORTANCE We assay the utility of the single-test IMX-BVN-3/IMX-SEV-3 classifiers that require just 2.5 mL of patient blood in concurrently detecting viral and bacterial infections as well as predicting the severity and 30-day outcome from the infection. A point-of-care device, in development, will circumvent the need for blood culturing and drastically reduce the time needed to detect an infection. This will negate the need for empirical use of broad-spectrum antibiotics and allow for antibiotic use stewardship. Additionally, accurate classification of the severity of infection and the prediction of 30-day severe outcomes will allow for appropriate allocation of hospital resources.
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Affiliation(s)
- Nikhil Ram-Mohan
- Department of Emergency Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Angela J. Rogers
- Department of Medicine—Pulmonary, Allergy & Critical Care Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Catherine A. Blish
- Department of Medicine/Infectious Diseases, Stanford University School of Medicine, Stanford, California, USA
| | - Kari C. Nadeau
- Department of Medicine—Pulmonary, Allergy & Critical Care Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Elizabeth J. Zudock
- Department of Emergency Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - David Kim
- Department of Emergency Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - James V. Quinn
- Department of Emergency Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Lixian Sun
- Inflammatix, Inc., Burlingame, California, USA
| | | | - The Stanford COVID-19 Biobank Study Group
- Department of Emergency Medicine, Stanford University School of Medicine, Stanford, California, USA
- Department of Medicine—Pulmonary, Allergy & Critical Care Medicine, Stanford University School of Medicine, Stanford, California, USA
- Department of Medicine/Infectious Diseases, Stanford University School of Medicine, Stanford, California, USA
- Inflammatix, Inc., Burlingame, California, USA
| | - Samuel Yang
- Department of Emergency Medicine, Stanford University School of Medicine, Stanford, California, USA
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11
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Bauer W, Gläser S, Thiemig D, Wanner K, Peric A, Behrens S, Bialas J, Behrens A, Galtung N, Liesenfeld O, Sun L, May L, Mace S, Ott S, Vesenbeckh S. Detection of Viral Infection and Bacterial Coinfection and Superinfection in Coronavirus Disease 2019 Patients Presenting to the Emergency Department Using the 29-mRNA Host Response Classifier IMX-BVN-3: A Multicenter Study. Open Forum Infect Dis 2022; 9:ofac437. [PMID: 36111173 PMCID: PMC9452140 DOI: 10.1093/ofid/ofac437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2022] [Accepted: 08/24/2022] [Indexed: 11/24/2022] Open
Abstract
Background Identification of bacterial coinfection in patients with coronavirus disease 2019 (COVID-19) facilitates appropriate initiation or withholding of antibiotics. The Inflammatix Bacterial Viral Noninfected (IMX-BVN) classifier determines the likelihood of bacterial and viral infections. In a multicenter study, we investigated whether IMX-BVN version 3 (IMX-BVN-3) identifies patients with COVID-19 and bacterial coinfections or superinfections. Methods Patients with polymerase chain reaction-confirmed COVID-19 were enrolled in Berlin, Germany; Basel, Switzerland; and Cleveland, Ohio upon emergency department or hospital admission. PAXgene Blood RNA was extracted and 29 host mRNAs were quantified. IMX-BVN-3 categorized patients into very unlikely, unlikely, possible, and very likely bacterial and viral interpretation bands. IMX-BVN-3 results were compared with clinically adjudicated infection status. Results IMX-BVN-3 categorized 102 of 111 (91.9%) COVID-19 patients into very likely or possible, 7 (6.3%) into unlikely, and 2 (1.8%) into very unlikely viral bands. Approximately 94% of patients had IMX-BVN-3 unlikely or very unlikely bacterial results. Among 7 (6.3%) patients with possible (n = 4) or very likely (n = 3) bacterial results, 6 (85.7%) had clinically adjudicated bacterial coinfection or superinfection. Overall, 19 of 111 subjects for whom adjudication was performed had a bacterial infection; 7 of these showed a very likely or likely bacterial result in IMX-BVN-3. Conclusions IMX-BVN-3 identified COVID-19 patients as virally infected and identified bacterial coinfections and superinfections. Future studies will determine whether a point-of-care version of the classifier may improve the management of COVID-19 patients, including appropriate antibiotic use.
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Affiliation(s)
- Wolfgang Bauer
- Charité–Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Emergency Medicine, Berlin, Germany
| | - Sven Gläser
- Klinik für Innere Medizin–Pneumologie, Vivantes Klinikum Spandau und Klinik für Innere Medizin–Pneumologie und Infektiologie, Vivantes Klinikum Neukölln, Berlin, Germany
- Klinik für Innere Medizin–Pneumologie und Infektiologie, Vivantes Klinikum Neukölln, Berlin, Germany
| | - Dorina Thiemig
- Klinik für Innere Medizin–Pneumologie und Infektiologie, Vivantes Klinikum Neukölln, Berlin, Germany
| | - Katrin Wanner
- Klinik für Innere Medizin–Pneumologie, Vivantes Klinikum Spandau und Klinik für Innere Medizin–Pneumologie und Infektiologie, Vivantes Klinikum Neukölln, Berlin, Germany
| | - Alexander Peric
- Klinik für Innere Medizin–Pneumologie und Infektiologie, Vivantes Klinikum im Friedrichshain, Berlin, Germany
| | - Steffen Behrens
- Klinik für Innere Medizin–Kardiologie, Vivantes–Netzwerk für Gesundheit/Vivantes Humboldt-Klinikum and Klinik für Innere Medizin–Kardiologie und konservative Intensivmedizin, Vivantes–Netzwerk für Gesundheit/Vivantes Klinikum Spandau, Berlin, Germany
| | - Johanna Bialas
- Labor Berlin–Charité Vivantes Services GmbH, Berlin, Germany
| | - Angelika Behrens
- Klinik für Innere Medizin, Gastroenterologie und Pneumologie, Evangelische Elisabeth Klinik Krankenhausbetriebs gGmbH, Berlin, Germany
| | - Noa Galtung
- Charité–Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Emergency Medicine, Berlin, Germany
| | | | - Lisa Sun
- Inflammatix Inc, Burlingame, California, USA
| | - Larissa May
- Department of Emergency Medicine, University of California, Davis School of Medicine, Sacramento, California, USA
| | - Sharron Mace
- Department of Emergency Medicine, Cleveland Clinic, Cleveland, Ohio, USA
| | - Sebastian Ott
- Department of Pulmonary Medicine, St Claraspital AG, Basel, Switzerland
- University of Bern, Bern, Switzerland
| | - Silvan Vesenbeckh
- Department of Pulmonary Medicine, St Claraspital AG, Basel, Switzerland
- Department of Pulmonology, University Hospital Zürich, Zürich, Switzerland
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12
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Kostaki A, Wacker JW, Safarika A, Solomonidi N, Katsaros K, Giannikopoulos G, Koutelidakis IM, Hogan CA, Uhle F, Liesenfeld O, Sweeney TE, Giamarellos-Bourboulis EJ. A 29-MRNA HOST RESPONSE WHOLE-BLOOD SIGNATURE IMPROVES PREDICTION OF 28-DAY MORTALITY AND 7-DAY INTENSIVE CARE UNIT CARE IN ADULTS PRESENTING TO THE EMERGENCY DEPARTMENT WITH SUSPECTED ACUTE INFECTION AND/OR SEPSIS. Shock 2022; 58:224-230. [PMID: 36125356 PMCID: PMC9512237 DOI: 10.1097/shk.0000000000001970] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 03/28/2022] [Accepted: 07/19/2022] [Indexed: 11/25/2022]
Abstract
ABSTRACT Background: Risk stratification of emergency department patients with suspected acute infections and/or suspected sepsis remains challenging. We prospectively validated a 29-messenger RNA host response classifier for predicting severity in these patients. Methods: We enrolled adults presenting with suspected acute infections and at least one vital sign abnormality to six emergency departments in Greece. Twenty-nine target host RNAs were quantified on NanoString nCounter and analyzed with the Inflammatix Severity 2 (IMX-SEV-2) classifier to determine risk scores as low, moderate, and high severity. Performance of IMX-SEV-2 for prediction of 28-day mortality was compared with that of lactate, procalcitonin, and quick sequential organ failure assessment (qSOFA). Results: A total of 397 individuals were enrolled; 38 individuals (9.6%) died within 28 days. Inflammatix Severity 2 classifier predicted 28-day mortality with an area under the receiver operator characteristics curve of 0.82 (95% confidence interval [CI], 0.74-0.90) compared with lactate, 0.66 (95% CI, 0.54-0.77); procalcitonin, 0.67 (95% CI, 0.57-0.78); and qSOFA, 0.81 (95% CI, 0.72-0.89). Combining qSOFA with IMX-SEV-2 improved prognostic accuracy from 0.81 to 0.89 (95% CI, 0.82-0.96). The high-severity (rule-in) interpretation band of IMX-SEV-2 demonstrated 96.9% specificity for predicting 28-day mortality, whereas the low-severity (rule-out) band had a sensitivity of 78.9%. Similarly, IMX-SEV-2 alone accurately predicted the need for day-7 intensive care unit care and further boosted overall accuracy when combined with qSOFA. Conclusions: Inflammatix Severity 2 classifier predicted 28-day mortality and 7-day intensive care unit care with high accuracy and boosted the accuracy of clinical scores when used in combination.
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Affiliation(s)
- Antigone Kostaki
- 4th Department of Internal Medicine, National and Kapodistrian University of Athens, Medical School, Greece
| | | | - Asimina Safarika
- 4th Department of Internal Medicine, National and Kapodistrian University of Athens, Medical School, Greece
| | - Nicky Solomonidi
- 4th Department of Internal Medicine, National and Kapodistrian University of Athens, Medical School, Greece
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Zhang W, Wang W, Hou W, Jiang C, Hu J, Sun L, Hu L, Wu J, Shang A. The diagnostic utility of IL-10, IL-17, and PCT in patients with sepsis infection. Front Public Health 2022; 10:923457. [PMID: 35937269 PMCID: PMC9355284 DOI: 10.3389/fpubh.2022.923457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 07/05/2022] [Indexed: 11/18/2022] Open
Abstract
Objective The purpose of this study is to determine the diagnostic value and net clinical benefit of interleukin-10 (IL-10), interleukin-17 (IL-17), procalcitonin (PCT), and combination tests in patients with sepsis, which will serve as a standard for sepsis early detection. Patients and methods An investigation of 84 sepsis patients and 81 patients with local inflammatory diseases admitted to the ICU of Tongji University Hospital in 2021. In addition to comparing inter-group variability, indicators relevant to sepsis diagnosis and therapy were screened. Results LASSO regression was used to examine PCT, WBC, CRP, IL-10, IFN-, IL-12, and IL-17. Multivariate logistic regression linked IL-10, IL-17, and PCT to sepsis risk. The AUC values of IL-10, IL-17, PCT, and the combination of the three tests were much higher than those of standard laboratory infection indicators. The combined AUC was greater than the sum of IL-10, IL-17, and PCT (P < 0.05). A clinical decision curve analysis of IL-10, IL-17, PCT, and the three combined tests found that the three combined tests outperformed the individual tests in terms of total clinical benefit rate. To predict the risk of sepsis using IL-10, IL-17, and PCT had an AUC of 0.951, and the model's predicted probability was well matched. An examination of the nomogram model's clinical value demonstrated a considerable net therapeutic benefit between 3 and 87%. Conclusion The IL-10, IL-17, and PCT tests all have a high diagnostic value for patients with sepsis, and the combination of the three tests outperforms the individual tests in terms of diagnostic performance, while the combined tests have a higher overall clinical benefit rate.
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Affiliation(s)
- Wei Zhang
- Department of Laboratory Medicine, Shanghai Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
- Department of Laboratory Medicine, Jiaozuo Fifth People's Hospital, Jiaozuo, China
| | - Weiwei Wang
- Department of Laboratory Medicine, Tinghu People's Hospital of Yancheng City, Yancheng, China
| | - Weiwei Hou
- Department of Laboratory Medicine, Shanghai Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Chenfei Jiang
- The College of Medical Technology, Shanghai University of Medicine and Health Sciences, Shanghai, China
| | - Jingwen Hu
- The College of Medical Technology, Shanghai University of Medicine and Health Sciences, Shanghai, China
| | - Li Sun
- Department of Medical Laboratory Technology, School of Medicine, Xiangyang Polytechnic, Xiangyang, China
| | - Liqing Hu
- Department of Laboratory Medicine, Ningbo First Hospital and Ningbo Hospital, Ningbo, China
- Liqing Hu
| | - Jian Wu
- Department of Laboratory Medicine, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China
- Jian Wu
| | - Anquan Shang
- Department of Laboratory Medicine, Shanghai Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
- *Correspondence: Anquan Shang
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14
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Brakenridge SC, Chen UI, Loftus T, Ungaro R, Dirain M, Kerr A, Zhong L, Bacher R, Starostik P, Ghita G, Midic U, Darden D, Fenner B, Wacker J, Efron PA, Liesenfeld O, Sweeney TE, Moldawer LL. Evaluation of a Multivalent Transcriptomic Metric for Diagnosing Surgical Sepsis and Estimating Mortality Among Critically Ill Patients. JAMA Netw Open 2022; 5:e2221520. [PMID: 35819783 PMCID: PMC9277492 DOI: 10.1001/jamanetworkopen.2022.21520] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 05/19/2022] [Indexed: 02/02/2023] Open
Abstract
Importance Rapid and accurate discrimination of sepsis and its potential severity currently require multiple assays with slow processing times that are often inconclusive in discerning sepsis from sterile inflammation. Objective To analyze a whole-blood, multivalent, host-messenger RNA expression metric for estimating the likelihood of bacterial infection and 30-day mortality and compare performance of the metric with that of other diagnostic and prognostic biomarkers and clinical parameters. Design, Setting, and Participants This prospective diagnostic and prognostic study was performed in the surgical intensive care unit (ICU) of a single, academic health science center. The analysis included 200 critically ill adult patients admitted with suspected sepsis (cohort A) or those at high risk for developing sepsis (cohort B) between July 1, 2020, and July 30, 2021. Exposures Whole-blood sample measurements of a custom 29-messenger RNA transcriptomic metric classifier for likelihood of bacterial infection (IMX-BVN-3) or 30-day mortality (severity) (IMX-SEV-3) in a clinical-diagnostic laboratory setting using an analysis platform (510[k]-cleared nCounter FLEX; NanoString, Inc), compared with measurement of procalcitonin and interleukin 6 (IL-6) plasma levels, and maximum 24-hour sequential organ failure assessment (SOFA) scores. Main Outcomes and Measures Estimated sepsis and 30-day mortality performance. Results Among the 200 patients included (124 men [62.0%] and 76 women [38.0%]; median age, 62.5 [IQR, 47.0-72.0] years), the IMX-BVN-3 bacterial infection classifier had an area under the receiver operating characteristics curve (AUROC) of 0.84 (95% CI, 0.77-0.90) for discriminating bacterial infection at ICU admission, similar to procalcitonin (0.85 [95% CI, 0.79-0.90]; P = .79) and significantly better than IL-6 (0.67 [95% CI, 0.58-0.75]; P < .001). For estimating 30-day mortality, the IMX-SEV-3 metric had an AUROC of 0.81 (95% CI, 0.66-0.95), which was significantly better than IL-6 levels (0.57 [95% CI, 0.37-0.77]; P = .006), marginally better than procalcitonin levels (0.65 [95% CI, 0.50-0.79]; P = .06), and similar to the SOFA score (0.76 [95% CI, 0.62-0.91]; P = .48). Combining IMX-BVN-3 and IMX-SEV-3 with procalcitonin or IL-6 levels or SOFA scores did not significantly improve performance. Among patients with sepsis, IMX-BVN-3 scores decreased over time, reflecting the resolution of sepsis. In 11 individuals at high risk (cohort B) who subsequently developed sepsis during their hospital course, IMX-BVN-3 bacterial infection scores did not decline over time and peaked on the day of documented infection. Conclusions and Relevance In this diagnostic and prognostic study, a novel, multivalent, transcriptomic metric accurately estimated the presence of bacterial infection and risk for 30-day mortality in patients admitted to a surgical ICU. The performance of this single transcriptomic metric was equivalent to or better than multiple alternative diagnostic and prognostic metrics when measured at admission and provided additional information when measured over time.
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Affiliation(s)
- Scott C. Brakenridge
- Sepsis and Critical Illness Research Center, Department of Surgery, University of Florida College of Medicine, Gainesville
- Division of Burn, Trauma & Critical Care Surgery, Department of Surgery, University of Washington, Seattle
| | - Uan-I Chen
- Inflammatix, Inc, Burlingame, California
| | - Tyler Loftus
- Sepsis and Critical Illness Research Center, Department of Surgery, University of Florida College of Medicine, Gainesville
| | - Ricardo Ungaro
- Sepsis and Critical Illness Research Center, Department of Surgery, University of Florida College of Medicine, Gainesville
| | - Marvin Dirain
- Sepsis and Critical Illness Research Center, Department of Surgery, University of Florida College of Medicine, Gainesville
| | - Austin Kerr
- Sepsis and Critical Illness Research Center, Department of Surgery, University of Florida College of Medicine, Gainesville
| | - Luer Zhong
- Sepsis and Critical Illness Research Center, Department of Surgery, University of Florida College of Medicine, Gainesville
| | - Rhonda Bacher
- Sepsis and Critical Illness Research Center, Department of Surgery, University of Florida College of Medicine, Gainesville
| | - Petr Starostik
- Molecular Pathology Laboratory at Rocky Point, Department of Pathology, Immunology and Laboratory Medicine, University of Florida College of Medicine, Gainesville
- Clinical and Diagnostic Laboratories, Health Science Center, UF (University of Florida) Health Shands Hospital, Gainesville
| | - Gabriella Ghita
- Sepsis and Critical Illness Research Center, Department of Surgery, University of Florida College of Medicine, Gainesville
| | - Uros Midic
- Inflammatix, Inc, Burlingame, California
| | - Dijoia Darden
- Sepsis and Critical Illness Research Center, Department of Surgery, University of Florida College of Medicine, Gainesville
| | - Brittany Fenner
- Sepsis and Critical Illness Research Center, Department of Surgery, University of Florida College of Medicine, Gainesville
| | | | - Philip A. Efron
- Sepsis and Critical Illness Research Center, Department of Surgery, University of Florida College of Medicine, Gainesville
| | | | | | - Lyle L. Moldawer
- Sepsis and Critical Illness Research Center, Department of Surgery, University of Florida College of Medicine, Gainesville
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Velásquez SY, Coulibaly A, Sticht C, Schulte J, Hahn B, Sturm T, Schefzik R, Thiel M, Lindner HA. Key Signature Genes of Early Terminal Granulocytic Differentiation Distinguish Sepsis From Systemic Inflammatory Response Syndrome on Intensive Care Unit Admission. Front Immunol 2022; 13:864835. [PMID: 35844509 PMCID: PMC9280679 DOI: 10.3389/fimmu.2022.864835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 05/26/2022] [Indexed: 11/13/2022] Open
Abstract
Infection can induce granulopoiesis. This process potentially contributes to blood gene classifiers of sepsis in systemic inflammatory response syndrome (SIRS) patients. This study aimed to identify signature genes of blood granulocytes from patients with sepsis and SIRS on intensive care unit (ICU) admission. CD15+ cells encompassing all stages of terminal granulocytic differentiation were analyzed. CD15 transcriptomes from patients with sepsis and SIRS on ICU admission and presurgical controls (discovery cohort) were subjected to differential gene expression and pathway enrichment analyses. Differential gene expression was validated by bead array in independent sepsis and SIRS patients (validation cohort). Blood counts of granulocyte precursors were determined by flow cytometry in an extension of the validation cohort. Despite similar transcriptional CD15 responses in sepsis and SIRS, enrichment of canonical pathways known to decline at the metamyelocyte stage (mitochondrial, lysosome, cell cycle, and proteasome) was associated with sepsis but not SIRS. Twelve of 30 validated genes, from 100 selected for changes in response to sepsis rather than SIRS, were endo-lysosomal. Revisiting the discovery transcriptomes revealed an elevated expression of promyelocyte-restricted azurophilic granule genes in sepsis and myelocyte-restricted specific granule genes in sepsis followed by SIRS. Blood counts of promyelocytes and myelocytes were higher in sepsis than in SIRS. Sepsis-induced granulopoiesis and signature genes of early terminal granulocytic differentiation thus provide a rationale for classifiers of sepsis in patients with SIRS on ICU admission. Yet, the distinction of this process from noninfectious tissue injury-induced granulopoiesis remains to be investigated.
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Affiliation(s)
- Sonia Y. Velásquez
- Department of Anesthesiology and Surgical Intensive Care Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Anna Coulibaly
- Department of Anesthesiology and Surgical Intensive Care Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Carsten Sticht
- Next Generation Sequencing Core Facility, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Jutta Schulte
- Department of Anesthesiology and Surgical Intensive Care Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Bianka Hahn
- Department of Anesthesiology and Surgical Intensive Care Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Timo Sturm
- Department of Anesthesiology and Surgical Intensive Care Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Roman Schefzik
- Department of Anesthesiology and Surgical Intensive Care Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Manfred Thiel
- Department of Anesthesiology and Surgical Intensive Care Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Mannheim Institute of Innate Immunoscience (MI3), Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Holger A. Lindner
- Department of Anesthesiology and Surgical Intensive Care Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Mannheim Institute of Innate Immunoscience (MI3), Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- *Correspondence: Holger A. Lindner,
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A point-of-need platform for rapid measurement of a host-protein score that differentiates bacterial from viral infection: analytical evaluation. Clin Biochem 2022; 117:39-47. [PMID: 35487256 DOI: 10.1016/j.clinbiochem.2022.04.012] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2021] [Revised: 03/30/2022] [Accepted: 04/24/2022] [Indexed: 12/20/2022]
Abstract
The objective was to evaluate the analytical performance of a new point-of-need platform for rapid and accurate measurement of a host-protein score that differentiates between bacterial and viral infection. The system comprises a dedicated test cartridge (MeMed BV®) and an analyzer (MeMed Key®). In each run, three host proteins (TRAIL, IP-10 and CRP) are measured quantitatively and a combinational score (0-100) computed that indicates the likelihood of Bacterial versus Viral infection (BV score). Serum samples collected from patients with acute infection representing viral (0 ≤ score < 35), equivocal (35 ≤ score ≤ 65), or bacterial (65 < score ≤ 100) scores based on pre-defined score cutoffs were employed for the analytical evaluation studies as well as samples from healthy individuals. To assess reproducibility, triplicate runs were conducted at 3 different sites, on 2 analyzers per site over 5 non-consecutive days. Lower limit of quantitation (LLoQ) and analytical measurement range were established utilizing recombinant proteins. Sample stability was evaluated using patient samples representative of BV score range (0-100). MeMed Key® and MeMed BV® passed the acceptance criteria for each study. In the reproducibility study, TRAIL, IP-10 and CRP measurements ranged with coefficient of variation from 9.7 to 12.7%, 4.6 to 6.2% and 5.0 to 11.6%, respectively. LLoQ concentrations were established as 15 pg/mL, 100 pg/mL and 1 mg/L for TRAIL, IP-10 and CRP, respectively. To date, sample stability when frozen is 14 months. In summary, the analytical performance reported here, along with diagnostic accuracy established in the Apollo clinical validation study (NCT04690569), supports that MeMed BV® run on MeMed Key® can serve as a tool to assist clinicians in differentiating between bacterial and viral infection.
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Ram-Mohan N, Rogers AJ, Blish CA, Nadeau KC, Zudock EJ, Kim D, Quinn JV, Sun L, Liesenfeld O, Yang S. Detection of bacterial co-infections and prediction of fatal outcomes in COVID-19 patients presenting to the emergency department using a 29 mRNA host response classifier. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2022:2022.03.14.22272394. [PMID: 35313598 PMCID: PMC8936113 DOI: 10.1101/2022.03.14.22272394] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Objective Clinicians in the emergency department (ED) face challenges in concurrently assessing patients with suspected COVID-19 infection, detecting bacterial co-infection, and determining illness severity since current practices require separate workflows. Here we explore the accuracy of the IMX-BVN-3/IMX-SEV-3 29 mRNA host response classifiers in simultaneously detecting SARS-CoV-2 infection, bacterial co-infections, and predicting clinical severity of COVID-19. Methods 161 patients with PCR-confirmed COVID-19 (52.2% female, median age 50.0 years, 51% hospitalized, 5.6% deaths) were enrolled at the Stanford Hospital ED. RNA was extracted (2.5 mL whole blood in PAXgene Blood RNA) and 29 host mRNAs in response to the infection were quantified using Nanostring nCounter. Results The IMX-BVN-3 classifier identified SARS-CoV-2 infection in 151 patients with a sensitivity of 93.8%. Six of 10 patients undetected by the classifier had positive COVID tests more than 9 days prior to enrolment and the remaining oscillated between positive and negative results in subsequent tests. The classifier also predicted that 6 (3.7%) patients had a bacterial co-infection. Clinical adjudication confirmed that 5/6 (83.3%) of the patients had bacterial infections, i.e. Clostridioides difficile colitis (n=1), urinary tract infection (n=1), and clinically diagnosed bacterial infections (n=3) for a specificity of 99.4%. 2/101 (2.8%) patients in the IMX-SEV-3 Low and 7/60 (11.7%) in the Moderate severity classifications died within thirty days of enrollment. Conclusions IMX-BVN-3/IMX-SEV-3 classifiers accurately identified patients with COVID-19, bacterial co-infections, and predicted patients’ risk of death. A point-of-care version of these classifiers, under development, could improve ED patient management including more accurate treatment decisions and optimized resource utilization.
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Affiliation(s)
- Nikhil Ram-Mohan
- Department of Emergency Medicine, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Angela J. Rogers
- Department of Medicine-Pulmonary, Allergy & Critical Care Medicine, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Catherine A. Blish
- Department of Medicine/Infectious Diseases, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Kari C. Nadeau
- Department of Medicine-Pulmonary, Allergy & Critical Care Medicine, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Elizabeth J Zudock
- Department of Emergency Medicine, Stanford University School of Medicine, Palo Alto, CA, USA
| | - David Kim
- Department of Emergency Medicine, Stanford University School of Medicine, Palo Alto, CA, USA
| | - James V. Quinn
- Department of Emergency Medicine, Stanford University School of Medicine, Palo Alto, CA, USA
| | | | | | | | - Samuel Yang
- Department of Emergency Medicine, Stanford University School of Medicine, Palo Alto, CA, USA
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Watkins RR, Bonomo RA, Rello J. Managing sepsis in the era of precision medicine: challenges and opportunities. Expert Rev Anti Infect Ther 2022; 20:871-880. [PMID: 35133228 DOI: 10.1080/14787210.2022.2040359] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
INTRODUCTION Precision medicine is a medical model in which decisions, practices, interventions and therapies are tailored to the individual patient based on their predicted response or risk of disease. Sepsis is a life-threatening condition characterized by immune system dysregulation whose pathophysiology remains incompletely understood. There is much hope that precision medicine can lead to better outcomes in patients with sepsis. AREAS COVERED In this review from a comprehensive literature search in PubMed for English-language studies conducted in adults, we highlight recent advances in the diagnosis and treatment of sepsis of bacterial origin in adults using precision medicine approaches including rapid diagnostic tests, predictive biomarkers, genomic methods, rapid antimicrobial susceptibility testing, and monitoring cell mediated immunity. Challenges and directions for future research are also discussed. EXPERT OPINION Current diagnostic testing in sepsis relies primarily on conventional cultures (e.g. blood cultures), which are time-consuming and may delay critical therapeutic decisions. Nonculture-based techniques including nucleic acid amplification technologies (NAAT), other molecular methods (biomarkers), and genomic sequencing offer promise to overcome some of the inherent limitations seen with culture-based techniques.
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Affiliation(s)
- Richard R Watkins
- Department of Medicine, Northeast Ohio Medical University, Rootstown, Ohio, USA
| | - Robert A Bonomo
- Medicine Service, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, Ohio, USA.,Department of Medicine, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA.,Research Service, Veterans Affairs Northeast Ohio Healthcare System, Cleveland, OH, USA.,CWRU-Cleveland VAMC Center for Antimicrobial Resistance and Epidemiology, Cleveland, OH, USA
| | - Jordi Rello
- Clinical Research in Pneumonia and Sepsis, Vall d'Hebron Institute of Research, Barcelona, Spain.,Clinical Research, Centre Hospitalier Universitaire Maribeau, Nimes, France
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