Browsing by Author "McClain, Micah T"

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    A blood-based host gene expression assay for early detection of respiratory viral infection: an index-cluster prospective cohort study.
    (The Lancet. Infectious diseases, 2020-09-24) McClain, Micah T; Constantine, Florica J; Nicholson, Bradly P; Nichols, Marshall; Burke, Thomas W; Henao, Ricardo; Jones, Daphne C; Hudson, Lori L; Jaggers, L Brett; Veldman, Timothy; Mazur, Anna; Park, Lawrence P; Suchindran, Sunil; Tsalik, Ephraim L; Ginsburg, Geoffrey S; Woods, Christopher W
    BACKGROUND:Early and accurate identification of individuals with viral infections is crucial for clinical management and public health interventions. We aimed to assess the ability of transcriptomic biomarkers to identify naturally acquired respiratory viral infection before typical symptoms are present. METHODS:In this index-cluster study, we prospectively recruited a cohort of undergraduate students (aged 18-25 years) at Duke University (Durham, NC, USA) over a period of 5 academic years. To identify index cases, we monitored students for the entire academic year, for the presence and severity of eight symptoms of respiratory tract infection using a daily web-based survey, with symptoms rated on a scale of 0-4. Index cases were defined as individuals who reported a 6-point increase in cumulative daily symptom score. Suspected index cases were visited by study staff to confirm the presence of reported symptoms of illness and to collect biospecimen samples. We then identified clusters of close contacts of index cases (ie, individuals who lived in close proximity to index cases, close friends, and partners) who were presumed to be at increased risk of developing symptomatic respiratory tract infection while under observation. We monitored each close contact for 5 days for symptoms and viral shedding and measured transcriptomic responses at each timepoint each day using a blood-based 36-gene RT-PCR assay. FINDINGS:Between Sept 1, 2009, and April 10, 2015, we enrolled 1465 participants. Of 264 index cases with respiratory tract infection symptoms, 150 (57%) had a viral cause confirmed by RT-PCR. Of their 555 close contacts, 106 (19%) developed symptomatic respiratory tract infection with a proven viral cause during the observation window, of whom 60 (57%) had the same virus as their associated index case. Nine viruses were detected in total. The transcriptomic assay accurately predicted viral infection at the time of maximum symptom severity (mean area under the receiver operating characteristic curve [AUROC] 0·94 [95% CI 0·92-0·96]), as well as at 1 day (0·87 [95% CI 0·84-0·90]), 2 days (0·85 [0·82-0·88]), and 3 days (0·74 [0·71-0·77]) before peak illness, when symptoms were minimal or absent and 22 (62%) of 35 individuals, 25 (69%) of 36 individuals, and 24 (82%) of 29 individuals, respectively, had no detectable viral shedding. INTERPRETATION:Transcriptional biomarkers accurately predict and diagnose infection across diverse viral causes and stages of disease and thus might prove useful for guiding the administration of early effective therapy, quarantine decisions, and other clinical and public health interventions in the setting of endemic and pandemic infectious diseases. FUNDING:US Defense Advanced Research Projects Agency.
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    A comparison of host response strategies to distinguish bacterial and viral infection.
    (PloS one, 2021-01) Ross, Melissa; Henao, Ricardo; Burke, Thomas W; Ko, Emily R; McClain, Micah T; Ginsburg, Geoffrey S; Woods, Christopher W; Tsalik, Ephraim L

    Objectives

    Compare three host response strategies to distinguish bacterial and viral etiologies of acute respiratory illness (ARI).

    Methods

    In this observational cohort study, procalcitonin, a 3-protein panel (CRP, IP-10, TRAIL), and a host gene expression mRNA panel were measured in 286 subjects with ARI from four emergency departments. Multinomial logistic regression and leave-one-out cross validation were used to evaluate the protein and mRNA tests.

    Results

    The mRNA panel performed better than alternative strategies to identify bacterial infection: AUC 0.93 vs. 0.83 for the protein panel and 0.84 for procalcitonin (P<0.02 for each comparison). This corresponded to a sensitivity and specificity of 92% and 83% for the mRNA panel, 81% and 73% for the protein panel, and 68% and 87% for procalcitonin, respectively. A model utilizing all three strategies was the same as mRNA alone. For the diagnosis of viral infection, the AUC was 0.93 for mRNA and 0.84 for the protein panel (p<0.05). This corresponded to a sensitivity and specificity of 89% and 82% for the mRNA panel, and 85% and 62% for the protein panel, respectively.

    Conclusions

    A gene expression signature was the most accurate host response strategy for classifying subjects with bacterial, viral, or non-infectious ARI.
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    A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection.
    (Nature communications, 2018-10-24) Fourati, Slim; Talla, Aarthi; Mahmoudian, Mehrad; Burkhart, Joshua G; Klén, Riku; Henao, Ricardo; Yu, Thomas; Aydın, Zafer; Yeung, Ka Yee; Ahsen, Mehmet Eren; Almugbel, Reem; Jahandideh, Samad; Liang, Xiao; Nordling, Torbjörn EM; Shiga, Motoki; Stanescu, Ana; Vogel, Robert; Respiratory Viral DREAM Challenge Consortium; Pandey, Gaurav; Chiu, Christopher; McClain, Micah T; Woods, Christopher W; Ginsburg, Geoffrey S; Elo, Laura L; Tsalik, Ephraim L; Mangravite, Lara M; Sieberts, Solveig K
    The response to respiratory viruses varies substantially between individuals, and there are currently no known molecular predictors from the early stages of infection. Here we conduct a community-based analysis to determine whether pre- or early post-exposure molecular factors could predict physiologic responses to viral exposure. Using peripheral blood gene expression profiles collected from healthy subjects prior to exposure to one of four respiratory viruses (H1N1, H3N2, Rhinovirus, and RSV), as well as up to 24 h following exposure, we find that it is possible to construct models predictive of symptomatic response using profiles even prior to viral exposure. Analysis of predictive gene features reveal little overlap among models; however, in aggregate, these genes are enriched for common pathways. Heme metabolism, the most significantly enriched pathway, is associated with a higher risk of developing symptoms following viral exposure. This study demonstrates that pre-exposure molecular predictors can be identified and improves our understanding of the mechanisms of response to respiratory viruses.
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    A Genomic Signature of Influenza Infection Shows Potential for Presymptomatic Detection, Guiding Early Therapy, and Monitoring Clinical Responses.
    (Open Forum Infect Dis, 2016-01) McClain, Micah T; Nicholson, Bradly P; Park, Lawrence P; Liu, Tzu-Yu; Hero, Alfred O; Tsalik, Ephraim L; Zaas, Aimee K; Veldman, Timothy; Hudson, Lori L; Lambkin-Williams, Robert; Gilbert, Anthony; Burke, Thomas; Nichols, Marshall; Ginsburg, Geoffrey S; Woods, Christopher W
    Early, presymptomatic intervention with oseltamivir (corresponding to the onset of a published host-based genomic signature of influenza infection) resulted in decreased overall influenza symptoms (aggregate symptom scores of 23.5 vs 46.3), more rapid resolution of clinical disease (20 hours earlier), reduced viral shedding (total median tissue culture infectious dose [TCID50] 7.4 vs 9.7), and significantly reduced expression of several inflammatory cytokines (interferon-γ, tumor necrosis factor-α, interleukin-6, and others). The host genomic response to influenza infection is robust and may provide the means for early detection, more timely therapeutic interventions, a meaningful reduction in clinical disease, and an effective molecular means to track response to therapy.
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    A host gene expression approach for identifying triggers of asthma exacerbations.
    (PloS one, 2019-01) Lydon, Emily C; Bullard, Charles; Aydin, Mert; Better, Olga M; Mazur, Anna; Nicholson, Bradly P; Ko, Emily R; McClain, Micah T; Ginsburg, Geoffrey S; Woods, Chris W; Burke, Thomas W; Henao, Ricardo; Tsalik, Ephraim L
    RATIONALE:Asthma exacerbations often occur due to infectious triggers, but determining whether infection is present and whether it is bacterial or viral remains clinically challenging. A diagnostic strategy that clarifies these uncertainties could enable personalized asthma treatment and mitigate antibiotic overuse. OBJECTIVES:To explore the performance of validated peripheral blood gene expression signatures in discriminating bacterial, viral, and noninfectious triggers in subjects with asthma exacerbations. METHODS:Subjects with suspected asthma exacerbations of various etiologies were retrospectively selected for peripheral blood gene expression analysis from a pool of subjects previously enrolled in emergency departments with acute respiratory illness. RT-PCR quantified 87 gene targets, selected from microarray-based studies, followed by logistic regression modeling to define bacterial, viral, or noninfectious class. The model-predicted class was compared to clinical adjudication and procalcitonin. RESULTS:Of 46 subjects enrolled, 7 were clinically adjudicated as bacterial, 18 as viral, and 21 as noninfectious. Model prediction was congruent with clinical adjudication in 15/18 viral and 13/21 noninfectious cases, but only 1/7 bacterial cases. None of the adjudicated bacterial cases had confirmatory microbiology; the precise etiology in this group was uncertain. Procalcitonin classified only one subject in the cohort as bacterial. 47.8% of subjects received antibiotics. CONCLUSIONS:Our model classified asthma exacerbations by the underlying bacterial, viral, and noninfectious host response. Compared to clinical adjudication, the majority of discordances occurred in the bacterial group, due to either imperfect adjudication or model misclassification. Bacterial infection was identified infrequently by all classification schemes, but nearly half of subjects were prescribed antibiotics. A gene expression-based approach may offer useful diagnostic information in this population and guide appropriate antibiotic use.
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    A host transcriptional signature for presymptomatic detection of infection in humans exposed to influenza H1N1 or H3N2.
    (PLoS One, 2013) Woods, Christopher W; McClain, Micah T; Chen, Minhua; Zaas, Aimee K; Nicholson, Bradly P; Varkey, Jay; Veldman, Timothy; Kingsmore, Stephen F; Kingsmore, Stephen F; Huang, Yongsheng; Lambkin-Williams, Robert; Gilbert, Anthony G; Hero, Alfred O; Ramsburg, Elizabeth; Glickman, Seth; Lucas, Joseph E; Carin, Lawrence; Ginsburg, Geoffrey S
    There is great potential for host-based gene expression analysis to impact the early diagnosis of infectious diseases. In particular, the influenza pandemic of 2009 highlighted the challenges and limitations of traditional pathogen-based testing for suspected upper respiratory viral infection. We inoculated human volunteers with either influenza A (A/Brisbane/59/2007 (H1N1) or A/Wisconsin/67/2005 (H3N2)), and assayed the peripheral blood transcriptome every 8 hours for 7 days. Of 41 inoculated volunteers, 18 (44%) developed symptomatic infection. Using unbiased sparse latent factor regression analysis, we generated a gene signature (or factor) for symptomatic influenza capable of detecting 94% of infected cases. This gene signature is detectable as early as 29 hours post-exposure and achieves maximal accuracy on average 43 hours (p = 0.003, H1N1) and 38 hours (p-value = 0.005, H3N2) before peak clinical symptoms. In order to test the relevance of these findings in naturally acquired disease, a composite influenza A signature built from these challenge studies was applied to Emergency Department patients where it discriminates between swine-origin influenza A/H1N1 (2009) infected and non-infected individuals with 92% accuracy. The host genomic response to Influenza infection is robust and may provide the means for detection before typical clinical symptoms are apparent.
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    A miRNA Host Response Signature Accurately Discriminates Acute Respiratory Infection Etiologies.
    (Frontiers in microbiology, 2018-01) Poore, Gregory D; Ko, Emily R; Valente, Ashlee; Henao, Ricardo; Sumner, Kelsey; Hong, Christopher; Burke, Thomas W; Nichols, Marshall; McClain, Micah T; Huang, Erich S; Ginsburg, Geoffrey S; Woods, Christopher W; Tsalik, Ephraim L
    Background: Acute respiratory infections (ARIs) are the leading indication for antibacterial prescriptions despite a viral etiology in the majority of cases. The lack of available diagnostics to discriminate viral and bacterial etiologies contributes to this discordance. Recent efforts have focused on the host response as a source for novel diagnostic targets although none have explored the ability of host-derived microRNAs (miRNA) to discriminate between these etiologies. Methods: In this study, we compared host-derived miRNAs and mRNAs from human H3N2 influenza challenge subjects to those from patients with Streptococcus pneumoniae pneumonia. Sparse logistic regression models were used to generate miRNA signatures diagnostic of ARI etiologies. Generalized linear modeling of mRNAs to identify differentially expressed (DE) genes allowed analysis of potential miRNA:mRNA relationships. High likelihood miRNA:mRNA interactions were examined using binding target prediction and negative correlation to further explore potential changes in pathway regulation in response to infection. Results: The resultant miRNA signatures were highly accurate in discriminating ARI etiologies. Mean accuracy was 100% [88.8-100; 95% Confidence Interval (CI)] in discriminating the healthy state from S. pneumoniae pneumonia and 91.3% (72.0-98.9; 95% CI) in discriminating S. pneumoniae pneumonia from influenza infection. Subsequent differential mRNA gene expression analysis revealed alterations in regulatory networks consistent with known biology including immune cell activation and host response to viral infection. Negative correlation network analysis of miRNA:mRNA interactions revealed connections to pathways with known immunobiology such as interferon regulation and MAP kinase signaling. Conclusion: We have developed novel human host-response miRNA signatures for bacterial and viral ARI etiologies. miRNA host response signatures reveal accurate discrimination between S. pneumoniae pneumonia and influenza etiologies for ARI and integrated analyses of the host-pathogen interface are consistent with expected biology. These results highlight the differential miRNA host response to bacterial and viral etiologies of ARI, offering new opportunities to distinguish these entities.
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    An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility.
    (Genome medicine, 2021-05) Wang, Liuyang; Balmat, Thomas J; Antonia, Alejandro L; Constantine, Florica J; Henao, Ricardo; Burke, Thomas W; Ingham, Andy; McClain, Micah T; Tsalik, Ephraim L; Ko, Emily R; Ginsburg, Geoffrey S; DeLong, Mark R; Shen, Xiling; Woods, Christopher W; Hauser, Elizabeth R; Ko, Dennis C

    Background

    While genome-wide associations studies (GWAS) have successfully elucidated the genetic architecture of complex human traits and diseases, understanding mechanisms that lead from genetic variation to pathophysiology remains an important challenge. Methods are needed to systematically bridge this crucial gap to facilitate experimental testing of hypotheses and translation to clinical utility.

    Results

    Here, we leveraged cross-phenotype associations to identify traits with shared genetic architecture, using linkage disequilibrium (LD) information to accurately capture shared SNPs by proxy, and calculate significance of enrichment. This shared genetic architecture was examined across differing biological scales through incorporating data from catalogs of clinical, cellular, and molecular GWAS. We have created an interactive web database (interactive Cross-Phenotype Analysis of GWAS database (iCPAGdb)) to facilitate exploration and allow rapid analysis of user-uploaded GWAS summary statistics. This database revealed well-known relationships among phenotypes, as well as the generation of novel hypotheses to explain the pathophysiology of common diseases. Application of iCPAGdb to a recent GWAS of severe COVID-19 demonstrated unexpected overlap of GWAS signals between COVID-19 and human diseases, including with idiopathic pulmonary fibrosis driven by the DPP9 locus. Transcriptomics from peripheral blood of COVID-19 patients demonstrated that DPP9 was induced in SARS-CoV-2 compared to healthy controls or those with bacterial infection. Further investigation of cross-phenotype SNPs associated with both severe COVID-19 and other human traits demonstrated colocalization of the GWAS signal at the ABO locus with plasma protein levels of a reported receptor of SARS-CoV-2, CD209 (DC-SIGN). This finding points to a possible mechanism whereby glycosylation of CD209 by ABO may regulate COVID-19 disease severity.

    Conclusions

    Thus, connecting genetically related traits across phenotypic scales links human diseases to molecular and cellular measurements that can reveal mechanisms and lead to novel biomarkers and therapeutic approaches. The iCPAGdb web portal is accessible at http://cpag.oit.duke.edu and the software code at https://github.com/tbalmat/iCPAGdb .
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    An integrated transcriptome and expressed variant analysis of sepsis survival and death.
    (Genome Med, 2014) Tsalik, Ephraim L; Langley, Raymond J; Dinwiddie, Darrell L; Miller, Neil A; Yoo, Byunggil; van Velkinburgh, Jennifer C; Smith, Laurie D; Thiffault, Isabella; Jaehne, Anja K; Valente, Ashlee M; Henao, Ricardo; Yuan, Xin; Glickman, Seth W; Rice, Brandon J; McClain, Micah T; Carin, Lawrence; Corey, G Ralph; Ginsburg, Geoffrey S; Cairns, Charles B; Otero, Ronny M; Fowler, Vance G; Rivers, Emanuel P; Woods, Christopher W; Kingsmore, Stephen F
    BACKGROUND: Sepsis, a leading cause of morbidity and mortality, is not a homogeneous disease but rather a syndrome encompassing many heterogeneous pathophysiologies. Patient factors including genetics predispose to poor outcomes, though current clinical characterizations fail to identify those at greatest risk of progression and mortality. METHODS: The Community Acquired Pneumonia and Sepsis Outcome Diagnostic study enrolled 1,152 subjects with suspected sepsis. We sequenced peripheral blood RNA of 129 representative subjects with systemic inflammatory response syndrome (SIRS) or sepsis (SIRS due to infection), including 78 sepsis survivors and 28 sepsis non-survivors who had previously undergone plasma proteomic and metabolomic profiling. Gene expression differences were identified between sepsis survivors, sepsis non-survivors, and SIRS followed by gene enrichment pathway analysis. Expressed sequence variants were identified followed by testing for association with sepsis outcomes. RESULTS: The expression of 338 genes differed between subjects with SIRS and those with sepsis, primarily reflecting immune activation in sepsis. Expression of 1,238 genes differed with sepsis outcome: non-survivors had lower expression of many immune function-related genes. Functional genetic variants associated with sepsis mortality were sought based on a common disease-rare variant hypothesis. VPS9D1, whose expression was increased in sepsis survivors, had a higher burden of missense variants in sepsis survivors. The presence of variants was associated with altered expression of 3,799 genes, primarily reflecting Golgi and endosome biology. CONCLUSIONS: The activation of immune response-related genes seen in sepsis survivors was muted in sepsis non-survivors. The association of sepsis survival with a robust immune response and the presence of missense variants in VPS9D1 warrants replication and further functional studies. TRIAL REGISTRATION: ClinicalTrials.gov NCT00258869. Registered on 23 November 2005.
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    Assessment of the Feasibility of Using Noninvasive Wearable Biometric Monitoring Sensors to Detect Influenza and the Common Cold Before Symptom Onset.
    (JAMA network open, 2021-09) Grzesiak, Emilia; Bent, Brinnae; McClain, Micah T; Woods, Christopher W; Tsalik, Ephraim L; Nicholson, Bradly P; Veldman, Timothy; Burke, Thomas W; Gardener, Zoe; Bergstrom, Emma; Turner, Ronald B; Chiu, Christopher; Doraiswamy, P Murali; Hero, Alfred; Henao, Ricardo; Ginsburg, Geoffrey S; Dunn, Jessilyn

    Importance

    Currently, there are no presymptomatic screening methods to identify individuals infected with a respiratory virus to prevent disease spread and to predict their trajectory for resource allocation.

    Objective

    To evaluate the feasibility of using noninvasive, wrist-worn wearable biometric monitoring sensors to detect presymptomatic viral infection after exposure and predict infection severity in patients exposed to H1N1 influenza or human rhinovirus.

    Design, setting, and participants

    The cohort H1N1 viral challenge study was conducted during 2018; data were collected from September 11, 2017, to May 4, 2018. The cohort rhinovirus challenge study was conducted during 2015; data were collected from September 14 to 21, 2015. A total of 39 adult participants were recruited for the H1N1 challenge study, and 24 adult participants were recruited for the rhinovirus challenge study. Exclusion criteria for both challenges included chronic respiratory illness and high levels of serum antibodies. Participants in the H1N1 challenge study were isolated in a clinic for a minimum of 8 days after inoculation. The rhinovirus challenge took place on a college campus, and participants were not isolated.

    Exposures

    Participants in the H1N1 challenge study were inoculated via intranasal drops of diluted influenza A/California/03/09 (H1N1) virus with a mean count of 106 using the median tissue culture infectious dose (TCID50) assay. Participants in the rhinovirus challenge study were inoculated via intranasal drops of diluted human rhinovirus strain type 16 with a count of 100 using the TCID50 assay.

    Main outcomes and measures

    The primary outcome measures included cross-validated performance metrics of random forest models to screen for presymptomatic infection and predict infection severity, including accuracy, precision, sensitivity, specificity, F1 score, and area under the receiver operating characteristic curve (AUC).

    Results

    A total of 31 participants with H1N1 (24 men [77.4%]; mean [SD] age, 34.7 [12.3] years) and 18 participants with rhinovirus (11 men [61.1%]; mean [SD] age, 21.7 [3.1] years) were included in the analysis after data preprocessing. Separate H1N1 and rhinovirus detection models, using only data on wearble devices as input, were able to distinguish between infection and noninfection with accuracies of up to 92% for H1N1 (90% precision, 90% sensitivity, 93% specificity, and 90% F1 score, 0.85 [95% CI, 0.70-1.00] AUC) and 88% for rhinovirus (100% precision, 78% sensitivity, 100% specificity, 88% F1 score, and 0.96 [95% CI, 0.85-1.00] AUC). The infection severity prediction model was able to distinguish between mild and moderate infection 24 hours prior to symptom onset with an accuracy of 90% for H1N1 (88% precision, 88% sensitivity, 92% specificity, 88% F1 score, and 0.88 [95% CI, 0.72-1.00] AUC) and 89% for rhinovirus (100% precision, 75% sensitivity, 100% specificity, 86% F1 score, and 0.95 [95% CI, 0.79-1.00] AUC).

    Conclusions and relevance

    This cohort study suggests that the use of a noninvasive, wrist-worn wearable device to predict an individual's response to viral exposure prior to symptoms is feasible. Harnessing this technology would support early interventions to limit presymptomatic spread of viral respiratory infections, which is timely in the era of COVID-19.
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    Blood RNA alternative splicing events as diagnostic biomarkers for infectious disease
    (Cell Reports Methods, 2023-01-01) Zhang, Zijun; Sauerwald, Natalie; Cappuccio, Antonio; Ramos, Irene; Nair, Venugopalan D; Nudelman, German; Zaslavsky, Elena; Ge, Yongchao; Gaitas, Angelo; Ren, Hui; Brockman, Joel; Geis, Jennifer; Ramalingam, Naveen; King, David; McClain, Micah T; Woods, Christopher W; Henao, Ricardo; Burke, Thomas W; Tsalik, Ephraim L; Goforth, Carl W; Lizewski, Rhonda A; Lizewski, Stephen E; Weir, Dawn L; Letizia, Andrew G; Sealfon, Stuart C; Troyanskaya, Olga G
    Assays detecting blood transcriptome changes are studied for infectious disease diagnosis. Blood-based RNA alternative splicing (AS) events, which have not been well characterized in pathogen infection, have potential normalization and assay platform stability advantages over gene expression for diagnosis. Here, we present a computational framework for developing AS diagnostic biomarkers. Leveraging a large prospective cohort of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and whole-blood RNA sequencing (RNA-seq) data, we identify a major functional AS program switch upon viral infection. Using an independent cohort, we demonstrate the improved accuracy of AS biomarkers for SARS-CoV-2 diagnosis compared with six reported transcriptome signatures. We then optimize a subset of AS-based biomarkers to develop microfluidic PCR diagnostic assays. This assay achieves nearly perfect test accuracy (61/62 = 98.4%) using a naive principal component classifier, significantly more accurate than a gene expression PCR assay in the same cohort. Therefore, our RNA splicing computational framework enables a promising avenue for host-response diagnosis of infection.
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    Chromatin remodeling in peripheral blood cells reflects COVID-19 symptom severity.
    (bioRxiv, 2020-12-05) Giroux, Nicholas S; Ding, Shengli; McClain, Micah T; Burke, Thomas W; Petzold, Elizabeth; Chung, Hong A; Palomino, Grecia R; Wang, Ergang; Xi, Rui; Bose, Shree; Rotstein, Tomer; Nicholson, Bradly P; Chen, Tianyi; Henao, Ricardo; Sempowski, Gregory D; Denny, Thomas N; Ko, Emily R; Ginsburg, Geoffrey S; Kraft, Bryan D; Tsalik, Ephraim L; Woods, Christopher W; Shen, Xiling
    SARS-CoV-2 infection triggers highly variable host responses and causes varying degrees of illness in humans. We sought to harness the peripheral blood mononuclear cell (PBMC) response over the course of illness to provide insight into COVID-19 physiology. We analyzed PBMCs from subjects with variable symptom severity at different stages of clinical illness before and after IgG seroconversion to SARS-CoV-2. Prior to seroconversion, PBMC transcriptomes did not distinguish symptom severity. In contrast, changes in chromatin accessibility were associated with symptom severity. Furthermore, single-cell analyses revealed evolution of the chromatin accessibility landscape and transcription factor motif occupancy for individual PBMC cell types. The most extensive remodeling occurred in CD14+ monocytes where sub-populations with distinct chromatin accessibility profiles were associated with disease severity. Our findings indicate that pre-seroconversion chromatin remodeling in certain innate immune populations is associated with divergence in symptom severity, and the identified transcription factors, regulatory elements, and downstream pathways provide potential prognostic markers for COVID-19 subjects.
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    Comparing the Diagnostic Accuracy of Clinician Judgment to a Novel Host Response Diagnostic for Acute Respiratory Illness.
    (Open forum infectious diseases, 2021-12) Jaffe, Ian S; Jaehne, Anja K; Quackenbush, Eugenia; Ko, Emily R; Rivers, Emanuel P; McClain, Micah T; Ginsburg, Geoffrey S; Woods, Christopher W; Tsalik, Ephraim L

    Background

    Difficulty discriminating bacterial from viral infections drives antibacterial misuse. Host gene expression tests discriminate bacterial and viral etiologies, but their clinical utility has not been evaluated.

    Methods

    Host gene expression and procalcitonin levels were measured in 582 emergency department participants with suspected infection. We also recorded clinician diagnosis and clinician-recommended treatment. These 4 diagnostic strategies were compared with clinical adjudication as the reference. To estimate the clinical impact of host gene expression, we calculated the change in overall Net Benefit (∆NB; the difference in Net Benefit comparing 1 diagnostic strategy with a reference) across a range of prevalence estimates while factoring in the clinical significance of false-positive and -negative errors.

    Results

    Gene expression correctly classified bacterial, viral, or noninfectious illness in 74.1% of subjects, similar to the other strategies. Clinical diagnosis and clinician-recommended treatment revealed a bias toward overdiagnosis of bacterial infection resulting in high sensitivity (92.6% and 94.5%, respectively) but poor specificity (67.2% and 58.8%, respectively), resulting in a 33.3% rate of inappropriate antibacterial use. Gene expression offered a more balanced sensitivity (79.0%) and specificity (80.7%), which corresponded to a statistically significant improvement in average weighted accuracy (79.9% vs 71.5% for procalcitonin and 76.3% for clinician-recommended treatment; P<.0001 for both). Consequently, host gene expression had greater Net Benefit in diagnosing bacterial infection than clinician-recommended treatment (∆NB=6.4%) and procalcitonin (∆NB=17.4%).

    Conclusions

    Host gene expression-based tests to distinguish bacterial and viral infection can facilitate appropriate treatment, improving patient outcomes and mitigating the antibacterial resistance crisis.
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    Differential chromatin accessibility in peripheral blood mononuclear cells underlies COVID-19 disease severity prior to seroconversion.
    (Scientific reports, 2022-07-09) Giroux, Nicholas S; Ding, Shengli; McClain, Micah T; Burke, Thomas W; Petzold, Elizabeth; Chung, Hong A; Rivera, Grecia O; Wang, Ergang; Xi, Rui; Bose, Shree; Rotstein, Tomer; Nicholson, Bradly P; Chen, Tianyi; Henao, Ricardo; Sempowski, Gregory D; Denny, Thomas N; De Ussel, Maria Iglesias; Satterwhite, Lisa L; Ko, Emily R; Ginsburg, Geoffrey S; Kraft, Bryan D; Tsalik, Ephraim L; Shen, Xiling; Woods, Christopher W
    SARS-CoV-2 infection triggers profound and variable immune responses in human hosts. Chromatin remodeling has been observed in individuals severely ill or convalescing with COVID-19, but chromatin remodeling early in disease prior to anti-spike protein IgG seroconversion has not been defined. We performed the Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) and RNA-seq on peripheral blood mononuclear cells (PBMCs) from outpatients with mild or moderate symptom severity at different stages of clinical illness. Early in the disease course prior to IgG seroconversion, modifications in chromatin accessibility associated with mild or moderate symptoms were already robust and included severity-associated changes in accessibility of genes in interleukin signaling, regulation of cell differentiation and cell morphology. Furthermore, single-cell analyses revealed evolution of the chromatin accessibility landscape and transcription factor motif accessibility for individual PBMC cell types over time. The most extensive remodeling occurred in CD14+ monocytes, where sub-populations with distinct chromatin accessibility profiles were observed prior to seroconversion. Mild symptom severity was marked by upregulation of classical antiviral pathways, including those regulating IRF1 and IRF7, whereas in moderate disease, these classical antiviral signals diminished, suggesting dysregulated and less effective responses. Together, these observations offer novel insight into the epigenome of early mild SARS-CoV-2 infection and suggest that detection of chromatin remodeling in early disease may offer promise for a new class of diagnostic tools for COVID-19.
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    Differential chromatin accessibility in peripheral blood mononuclear cells underlies COVID-19 disease severity prior to seroconversion.
    (Res Sq, 2022-04-07) Giroux, Nicholas S; Ding, Shengli; McClain, Micah T; Burke, Thomas W; Petzold, Elizabeth; Chung, Hong A; Rivera, Grecia O; Wang, Ergang; Xi, Rui; Bose, Shree; Rotstein, Tomer; Nicholson, Bradly P; Chen, Tianyi; Henao, Ricardo; Sempowski, Gregory D; Denny, Thomas N; De Ussel, Maria Iglesias; Satterwhite, Lisa L; Ko, Emily R; Ginsburg, Geoffrey S; Kraft, Bryan D; Tsalik, Ephraim L; Shen, Xiling; Woods, Christopher
    SARS-CoV-2 infection triggers profound and variable immune responses in human hosts. Chromatin remodeling has been observed in individuals severely ill or convalescing with COVID-19, but chromatin remodeling early in disease prior to anti-spike protein IgG seroconversion has not been defined. We performed the Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) and RNA-seq on peripheral blood mononuclear cells (PBMCs) from outpatients with mild or moderate symptom severity at different stages of clinical illness. Early in the disease course prior to IgG seroconversion, modifications in chromatin accessibility associate with mild or moderate symptoms are already robust and include severity-associated changes in accessibility of genes in interleukin signaling, regulation of cell differentiation and cell morphology. Furthermore, single-cell analyses revealed evolution of the chromatin accessibility landscape and transcription factor motif accessibility for individual PBMC cell types over time. The most extensive remodeling occurred in CD14+ monocytes, where sub-populations with distinct chromatin accessibility profiles were observed prior to seroconversion. Mild symptom severity is marked by upregulation classical antiviral pathways including those regulating IRF1 and IRF7, whereas in moderate disease these classical antiviral signals diminish suggesting dysregulated and less effective responses. Together, these observations offer novel insight into the epigenome of early mild SARS-CoV-2 infection and suggest that detection of chromatin remodeling in early disease may offer promise for a new class of diagnostic tools for COVID-19.
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    Discriminating Bacterial and Viral Infection Using a Rapid Host Gene Expression Test.
    (Critical care medicine, 2021-10) Tsalik, Ephraim L; Henao, Ricardo; Montgomery, Jesse L; Nawrocki, Jeff W; Aydin, Mert; Lydon, Emily C; Ko, Emily R; Petzold, Elizabeth; Nicholson, Bradly P; Cairns, Charles B; Glickman, Seth W; Quackenbush, Eugenia; Kingsmore, Stephen F; Jaehne, Anja K; Rivers, Emanuel P; Langley, Raymond J; Fowler, Vance G; McClain, Micah T; Crisp, Robert J; Ginsburg, Geoffrey S; Burke, Thomas W; Hemmert, Andrew C; Woods, Christopher W; Antibacterial Resistance Leadership Group

    Objectives

    Host gene expression signatures discriminate bacterial and viral infection but have not been translated to a clinical test platform. This study enrolled an independent cohort of patients to describe and validate a first-in-class host response bacterial/viral test.

    Design

    Subjects were recruited from 2006 to 2016. Enrollment blood samples were collected in an RNA preservative and banked for later testing. The reference standard was an expert panel clinical adjudication, which was blinded to gene expression and procalcitonin results.

    Setting

    Four U.S. emergency departments.

    Patients

    Six-hundred twenty-three subjects with acute respiratory illness or suspected sepsis.

    Interventions

    Forty-five-transcript signature measured on the BioFire FilmArray System (BioFire Diagnostics, Salt Lake City, UT) in ~45 minutes.

    Measurements and main results

    Host response bacterial/viral test performance characteristics were evaluated in 623 participants (mean age 46 yr; 45% male) with bacterial infection, viral infection, coinfection, or noninfectious illness. Performance of the host response bacterial/viral test was compared with procalcitonin. The test provided independent probabilities of bacterial and viral infection in ~45 minutes. In the 213-subject training cohort, the host response bacterial/viral test had an area under the curve for bacterial infection of 0.90 (95% CI, 0.84-0.94) and 0.92 (95% CI, 0.87-0.95) for viral infection. Independent validation in 209 subjects revealed similar performance with an area under the curve of 0.85 (95% CI, 0.78-0.90) for bacterial infection and 0.91 (95% CI, 0.85-0.94) for viral infection. The test had 80.1% (95% CI, 73.7-85.4%) average weighted accuracy for bacterial infection and 86.8% (95% CI, 81.8-90.8%) for viral infection in this validation cohort. This was significantly better than 68.7% (95% CI, 62.4-75.4%) observed for procalcitonin (p < 0.001). An additional cohort of 201 subjects with indeterminate phenotypes (coinfection or microbiology-negative infections) revealed similar performance.

    Conclusions

    The host response bacterial/viral measured using the BioFire System rapidly and accurately discriminated bacterial and viral infection better than procalcitonin, which can help support more appropriate antibiotic use.
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    Dysregulated transcriptional responses to SARS-CoV-2 in the periphery support novel diagnostic approaches.
    (medRxiv, 2020-07-26) McClain, Micah T; Constantine, Florica J; Henao, Ricardo; Liu, Yiling; Tsalik, Ephraim L; Burke, Thomas W; Steinbrink, Julie M; Petzold, Elizabeth; Nicholson, Bradly P; Rolfe, Robert; Kraft, Bryan D; Kelly, Matthew S; Sempowski, Gregory D; Denny, Thomas N; Ginsburg, Geoffrey S; Woods, Christopher W
    In order to elucidate novel aspects of the host response to SARS-CoV-2 we performed RNA sequencing on peripheral blood samples across 77 timepoints from 46 subjects with COVID-19 and compared them to subjects with seasonal coronavirus, influenza, bacterial pneumonia, and healthy controls. Early SARS-CoV-2 infection triggers a conserved transcriptomic response in peripheral blood that is heavily interferon-driven but also marked by indicators of early B-cell activation and antibody production. Interferon responses during SARS-CoV-2 infection demonstrate unique patterns of dysregulated expression compared to other infectious and healthy states. Heterogeneous activation of coagulation and fibrinolytic pathways are present in early COVID-19, as are IL1 and JAK/STAT signaling pathways, that persist into late disease. Classifiers based on differentially expressed genes accurately distinguished SARS-CoV-2 infection from other acute illnesses (auROC 0.95). The transcriptome in peripheral blood reveals unique aspects of the immune response in COVID-19 and provides for novel biomarker-based approaches to diagnosis.
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    ItemOpen Access
    Dysregulated transcriptional responses to SARS-CoV-2 in the periphery.
    (Nature communications, 2021-02-17) McClain, Micah T; Constantine, Florica J; Henao, Ricardo; Liu, Yiling; Tsalik, Ephraim L; Burke, Thomas W; Steinbrink, Julie M; Petzold, Elizabeth; Nicholson, Bradly P; Rolfe, Robert; Kraft, Bryan D; Kelly, Matthew S; Saban, Daniel R; Yu, Chen; Shen, Xiling; Ko, Emily M; Sempowski, Gregory D; Denny, Thomas N; Ginsburg, Geoffrey S; Woods, Christopher W
    SARS-CoV-2 infection has been shown to trigger a wide spectrum of immune responses and clinical manifestations in human hosts. Here, we sought to elucidate novel aspects of the host response to SARS-CoV-2 infection through RNA sequencing of peripheral blood samples from 46 subjects with COVID-19 and directly comparing them to subjects with seasonal coronavirus, influenza, bacterial pneumonia, and healthy controls. Early SARS-CoV-2 infection triggers a powerful transcriptomic response in peripheral blood with conserved components that are heavily interferon-driven but also marked by indicators of early B-cell activation and antibody production. Interferon responses during SARS-CoV-2 infection demonstrate unique patterns of dysregulated expression compared to other infectious and healthy states. Heterogeneous activation of coagulation and fibrinolytic pathways are present in early COVID-19, as are IL1 and JAK/STAT signaling pathways, which persist into late disease. Classifiers based on differentially expressed genes accurately distinguished SARS-CoV-2 infection from other acute illnesses (auROC 0.95 [95% CI 0.92-0.98]). The transcriptome in peripheral blood reveals both diverse and conserved components of the immune response in COVID-19 and provides for potential biomarker-based approaches to diagnosis.
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    Efficacy and safety of azithromycin versus placebo to treat lower respiratory tract infections associated with low procalcitonin: a randomised, placebo-controlled, double-blind, non-inferiority trial.
    (The Lancet. Infectious diseases, 2023-04) Tsalik, Ephraim L; Rouphael, Nadine G; Sadikot, Ruxana T; Rodriguez-Barradas, Maria C; McClain, Micah T; Wilkins, Dana M; Woods, Christopher W; Swamy, Geeta K; Walter, Emmanuel B; El Sahly, Hana M; Keitel, Wendy A; Mulligan, Mark J; Tuyishimire, Bonifride; Serti, Elisavet; Hamasaki, Toshimitsu; Evans, Scott R; Ghazaryan, Varduhi; Lee, Marina S; Lautenbach, Ebbing; TRAP-LRTI Study Group; Antibacterial Resistance Leadership Group

    Background

    Lower respiratory tract infections are frequently treated with antibiotics, despite a viral cause in many cases. It remains unknown whether low procalcitonin concentrations can identify patients with lower respiratory tract infection who are unlikely to benefit from antibiotics. We aimed to compare the efficacy and safety of azithromycin versus placebo to treat lower respiratory tract infections in patients with low procalcitonin.

    Methods

    We conducted a randomised, placebo-controlled, double-blind, non-inferiority trial at five health centres in the USA. Adults aged 18 years or older with clinically suspected non-pneumonia lower respiratory tract infection and symptom duration from 24 h to 28 days were eligible for enrolment. Participants with a procalcitonin concentration of 0·25 ng/mL or less were randomly assigned (1:1), in blocks of four with stratification by site, to receive over-encapsulated oral azithromycin 250 mg or matching placebo (two capsules on day 1 followed by one capsule daily for 4 days). Participants, non-study clinical providers, investigators, and study coordinators were masked to treatment allocation. The primary outcome was efficacy of azithromycin versus placebo in terms of clinical improvement at day 5 in the intention-to-treat population. The non-inferiority margin was -12·5%. Solicited adverse events (abdominal pain, vomiting, diarrhoea, allergic reaction, or yeast infections) were recorded as a secondary outcome. This trial is registered with ClinicalTrials.gov, NCT03341273.

    Findings

    Between Dec 8, 2017, and March 9, 2020, 691 patients were assessed for eligibility and 499 were enrolled and randomly assigned to receive azithromycin (n=249) or placebo (n=250). Clinical improvement at day 5 was observed in 148 (63%, 95% CI 54 to 71) of 238 participants with full data in the placebo group and 155 (69%, 61 to 77) of 227 participants with full data in the azithromycin group in the intention-to-treat analysis (between-group difference -6%, 95% CI -15 to 2). The 95% CI for the difference did not meet the non-inferiority margin. Solicited adverse events and the severity of solicited adverse events were not significantly different between groups at day 5, except for increased abdominal pain associated with azithromycin (47 [23%, 95% CI 18 to 29] of 204 participants) compared with placebo (35 [16%, 12 to 21] of 221; between-group difference -7% [95% CI -15 to 0]; p=0·066).

    Interpretation

    Placebo was not non-inferior to azithromycin in terms of clinical improvement at day 5 in adults with lower respiratory tract infection and a low procalcitonin concentration. After accounting for both the rates of clinical improvement and solicited adverse events at day 5, it is unclear whether antibiotics are indicated for patients with lower respiratory tract infection and a low procalcitonin concentration.

    Funding

    National Institute of Allergy and Infectious Diseases, bioMérieux.
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    Epigenetic and transcriptional responses in circulating leukocytes are associated with future decompensation during SARS-CoV-2 infection.
    (iScience, 2024-01) McClain, Micah T; Zhbannikov, Ilya; Satterwhite, Lisa L; Henao, Ricardo; Giroux, Nicholas S; Ding, Shengli; Burke, Thomas W; Tsalik, Ephraim L; Nix, Christina; Balcazar, Jorge Prado; Petzold, Elizabeth A; Shen, Xiling; Woods, Christopher W
    To elucidate host response elements that define impending decompensation during SARS-CoV-2 infection, we enrolled subjects hospitalized with COVID-19 who were matched for disease severity and comorbidities at the time of admission. We performed combined single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) on peripheral blood mononuclear cells (PBMCs) at admission and compared subjects who improved from their moderate disease with those who later clinically decompensated and required invasive mechanical ventilation or died. Chromatin accessibility and transcriptomic immune profiles were markedly altered between the two groups, with strong signals in CD4+ T cells, inflammatory T cells, dendritic cells, and NK cells. Multiomic signature scores at admission were tightly associated with future clinical deterioration (auROC 1.0). Epigenetic and transcriptional changes in PBMCs reveal early, broad immune dysregulation before typical clinical signs of decompensation are apparent and thus may act as biomarkers to predict future severity in COVID-19.