Browsing by Author "Tsalik, Ephraim L"
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Item Open Access 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 WBACKGROUND: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.Item Open Access A community approach to mortality prediction in sepsis via gene expression analysis.(Nature communications, 2018-02) Sweeney, Timothy E; Perumal, Thanneer M; Henao, Ricardo; Nichols, Marshall; Howrylak, Judith A; Choi, Augustine M; Bermejo-Martin, Jesús F; Almansa, Raquel; Tamayo, Eduardo; Davenport, Emma E; Burnham, Katie L; Hinds, Charles J; Knight, Julian C; Woods, Christopher W; Kingsmore, Stephen F; Ginsburg, Geoffrey S; Wong, Hector R; Parnell, Grant P; Tang, Benjamin; Moldawer, Lyle L; Moore, Frederick E; Omberg, Larsson; Khatri, Purvesh; Tsalik, Ephraim L; Mangravite, Lara M; Langley, Raymond JImproved risk stratification and prognosis prediction in sepsis is a critical unmet need. Clinical severity scores and available assays such as blood lactate reflect global illness severity with suboptimal performance, and do not specifically reveal the underlying dysregulation of sepsis. Here, we present prognostic models for 30-day mortality generated independently by three scientific groups by using 12 discovery cohorts containing transcriptomic data collected from primarily community-onset sepsis patients. Predictive performance is validated in five cohorts of community-onset sepsis patients in which the models show summary AUROCs ranging from 0.765-0.89. Similar performance is observed in four cohorts of hospital-acquired sepsis. Combining the new gene-expression-based prognostic models with prior clinical severity scores leads to significant improvement in prediction of 30-day mortality as measured via AUROC and net reclassification improvement index These models provide an opportunity to develop molecular bedside tests that may improve risk stratification and mortality prediction in patients with sepsis.Item Open Access 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 LObjectives
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.Item Open Access A cross-sectional analysis of HIV and hepatitis C clinical trials 2007 to 2010: the relationship between industry sponsorship and randomized study design.(Trials, 2014-01) Goswami, Neela D; Tsalik, Ephraim L; Naggie, Susanna; Miller, William C; Horton, John R; Pfeiffer, Christopher D; Hicks, Charles BBackground
The proportion of clinical research sponsored by industry will likely continue to expand as federal funds for academic research decreases, particularly in the fields of HIV/AIDS and hepatitis C (HCV). While HIV and HCV continue to burden the US population, insufficient data exists as to how industry sponsorship affects clinical trials involving these infectious diseases. Debate exists about whether pharmaceutical companies undertake more market-driven research practices to promote therapeutics, or instead conduct more rigorous trials than their non-industry counterparts because of increased resources and scrutiny. The ClinicalTrials.gov registry, which allows investigators to fulfill a federal mandate for public trial registration, provides an opportunity for critical evaluation of study designs for industry-sponsored trials, independent of publication status. As part of a large public policy effort, the Clinical Trials Transformation Initiative (CTTI) recently transformed the ClinicalTrials.gov registry into a searchable dataset to facilitate research on clinical trials themselves.Methods
We conducted a cross-sectional analysis of 477 HIV and HCV drug treatment trials, registered with ClinicalTrials.gov from 1 October 2007 to 27 September 2010, to study the relationship of study sponsorship with randomized study design. The likelihood of using randomization given industry (versus non-industry) sponsorship was reported with prevalence ratios (PR). PRs were estimated using crude and stratified tabular analysis and Poisson regression adjusting for presence of a data monitoring committee, enrollment size, study phase, number of study sites, inclusion of foreign study sites, exclusion of persons older than age 65, and disease condition.Results
The crude PR was 1.17 (95% CI 0.94, 1.45). Adjusted Poisson models produced a PR of 1.13 (95% CI 0.82, 1.56). There was a trend toward mild effect measure modification by study phase, but this was not statistically significant. In stratified tabular analysis the adjusted PR was 1.14 (95% CI 0.78, 1.68) among phase 2/3 trials and 1.06 (95% CI 0.50, 2.22) among phase 4 trials.Conclusions
No significant relationship was found between industry sponsorship and use of randomization in trial design in this cross-sectional study. Prospective studies evaluating other aspects of trial design may shed further light on the relationship between industry sponsorship and appropriate trial methodology.Item Open Access 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 KThe 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.Item Open Access A Decade On: Systematic Review of ClinicalTrials.gov Infectious Disease Trials, 2007-2017.(Open forum infectious diseases, 2019-06) Jaffe, Ian S; Chiswell, Karen; Tsalik, Ephraim LBackground:Registration of interventional trials of Food and Drug Administration-regulated drug and biological products and devices became a legal requirement in 2007; the vast majority of these trials are registered in ClinicalTrials.gov. An analysis of ClinicalTrials.gov offers an opportunity to define the clinical research landscape; here we analyze 10 years of infectious disease (ID) clinical trial research. Methods:Beginning with 166 415 interventional trials registered in ClinicalTrials.gov from 2007-2017, ID trials were selected by study conditions and interventions. Relevance to ID was confirmed through manual review, resulting in 13 707 ID trials and 152 708 non-ID trials. Results:ID-related trials represented 6.9%-9.9% of all trials with no significant trend over time. ID trials tended to be more focused on treatment and prevention, with a focus on testing drugs, biologics, and vaccines. ID trials tended to be large, randomized, and nonblinded with a greater degree of international enrollment. Industry was the primary funding source for 45.2% of ID trials. Compared with the global burden of disease, human immunodeficiency virus/AIDS and hepatitis C trials were overrepresented, and lower respiratory tract infection trials were underrepresented. Hepatitis C trials fluctuated, keeping with a wave of new drug development. Influenza vaccine trials peaked during the 2009 H1N1 swine influenza outbreak. Conclusions:This study presents the most comprehensive characterization of ID clinical trials over the past decade. These results help define how clinical research aligns with clinical need. Temporal trends reflect changes in disease epidemiology and the impact of scientific discovery and market forces. Periodic review of ID clinical trials can help identify gaps and serve as a mechanism to realign resources.Item Open Access 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 WEarly, 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.Item Open Access 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 LRATIONALE: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.Item Open Access 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 LBackground: 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.Item Open Access Access to COVID-19 testing by individuals with housing insecurity during the early days of the COVID-19 pandemic in the United States: a scoping review.(Frontiers in public health, 2023-01) Johannesson, Jon M; Glover, William A; Petti, Cathy A; Veldman, Timothy H; Tsalik, Ephraim L; Taylor, Donald H; Hendren, Stephanie; Neighbors, Coralei E; Tillekeratne, L Gayani; Kennedy, Scott W; Harper, Barrie; Kibbe, Warren A; Corbie, Giselle; Cohen-Wolkowiez, Michael; Woods, Christopher W; Lee, Mark JIntroduction
The COVID-19 pandemic focused attention on healthcare disparities and inequities faced by individuals within marginalized and structurally disadvantaged groups in the United States. These individuals bore the heaviest burden across this pandemic as they faced increased risk of infection and difficulty in accessing testing and medical care. Individuals experiencing housing insecurity are a particularly vulnerable population given the additional barriers they face. In this scoping review, we identify some of the barriers this high-risk group experienced during the early days of the pandemic and assess novel solutions to overcome these barriers.Methods
A scoping review was performed following PRISMA-Sc guidelines looking for studies focusing on COVID-19 testing among individuals experiencing housing insecurity. Barriers as well as solutions to barriers were identified as applicable and summarized using qualitative methods, highlighting particular ways that proved effective in facilitating access to testing access and delivery.Results
Ultimately, 42 studies were included in the scoping review, with 143 barriers grouped into four categories: lack of cultural understanding, systemic racism, and stigma; medical care cost, insurance, and logistics; immigration policies, language, and fear of deportation; and other. Out of these 42 studies, 30 of these studies also suggested solutions to address them.Conclusion
A paucity of studies have analyzed COVID-19 testing barriers among those experiencing housing insecurity, and this is even more pronounced in terms of solutions to address those barriers. Expanding resources and supporting investigators within this space is necessary to ensure equitable healthcare delivery.Item Open Access 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 CBackground
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 .Item Open Access 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 FBACKGROUND: 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.Item Open Access Analytical Evaluation of the Abbott RealTime CT/NG Assay for Detection of Chlamydia trachomatis and Neisseria gonorrhoeae in Rectal and Pharyngeal Swabs.(The Journal of molecular diagnostics : JMD, 2020-06) Adamson, Paul C; Pandori, Mark W; Doernberg, Sarah B; Komarow, Lauren; Sund, Zoe; Tran, Thuy Tien T; Jensen, David; Tsalik, Ephraim L; Deal, Carolyn D; Chambers, Henry F; Fowler, Vance G; Evans, Scott R; Patel, Robin; Klausner, Jeffrey D; Antibacterial Resistance Leadership GroupChlamydia trachomatis and Neisseria gonorrhoeae infections in the rectum and pharynx are important extragenital reservoirs of infection. Few assays approved by the US Food and Drug Administration are commercially available to diagnose pharyngeal or rectal infections. The current study reports on the analytical performance of the Abbott RealTime CT/NG assay, including the limit of detection, inclusivity, and analytical specificity for C. trachomatis and N. gonorrhoeae in rectal and pharyngeal specimens. The limit of detection was performed using known concentrations of organisms, elementary bodies per milliliter (EB/mL) for C. trachomatis and colony-forming units per milliliter (CFU/mL) for N. gonorrhoeae, in clinical rectal and pharyngeal swab matrices. Inclusivity was performed against 12 serovars of C. trachomatis and seven strains of N. gonorrhoeae. The analytical specificity was performed using 28 different bacteria and viruses. The limit of detection for C. trachomatis was 2.56 EB/mL in pharyngeal specimens and 12.8 EB/mL in rectal specimens. The limit of detection for N. gonorrhoeae was 0.0256 CFU/mL for both pharyngeal and rectal specimens. The inclusivity and analytical specificity were 100% for both rectal and pharyngeal specimens. These analytical performance data demonstrate that the Abbott CT/NG RealTime assay is an accurate, sensitive, and specific assay in rectal and pharyngeal specimens, supporting the potential of the assay for detection of rectal and pharyngeal C. trachomatis and N. gonorrhoeae infections.Item Open Access Antibacterial Resistance Leadership Group 2.0: Back to Business.(Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2021-08) Chambers, Henry F; Evans, Scott R; Patel, Robin; Cross, Heather R; Harris, Anthony D; Doi, Yohei; Boucher, Helen W; van Duin, David; Tsalik, Ephraim L; Holland, Thomas L; Pettigrew, Melinda M; Tamma, Pranita D; Hodges, Kathryn R; Souli, Maria; Fowler, Vance GIn December 2019, the Antibacterial Resistance Leadership Group (ARLG) was awarded funding for another 7-year cycle to support a clinical research network on antibacterial resistance. ARLG 2.0 has 3 overarching research priorities: infections caused by antibiotic-resistant (AR) gram-negative bacteria, infections caused by AR gram-positive bacteria, and diagnostic tests to optimize use of antibiotics. To support the next generation of AR researchers, the ARLG offers 3 mentoring opportunities: the ARLG Fellowship, Early Stage Investigator seed grants, and the Trialists in Training Program. The purpose of this article is to update the scientific community on the progress made in the original funding period and to encourage submission of clinical research that addresses 1 or more of the research priority areas of ARLG 2.0.Item Open Access 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, JessilynImportance
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.Item Open Access Average Weighted Accuracy: Pragmatic Analysis for a Rapid Diagnostics in Categorizing Acute Lung Infections (RADICAL) Study.(Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2020-06) Liu, Ying; Tsalik, Ephraim L; Jiang, Yunyun; Ko, Emily R; Woods, Christopher W; Henao, Ricardo; Evans, Scott RPatient management relies on diagnostic information to identify appropriate treatment. Standard evaluations of diagnostic tests consist of estimating sensitivity, specificity, positive/negative predictive values, likelihood ratios, and accuracy. Although useful, these metrics do not convey the tests' clinical value, which is critical to informing decision-making. Full appreciation of the clinical impact of a diagnostic test requires analyses that integrate sensitivity and specificity, account for the disease prevalence within the population of test application, and account for the relative importance of specificity vs sensitivity by considering the clinical implications of false-positive and false-negative results. We developed average weighted accuracy (AWA), representing a pragmatic metric of diagnostic yield or global utility of a diagnostic test. AWA can be used to compare test alternatives, even across different studies. We apply the AWA methodology to evaluate a new diagnostic test developed in the Rapid Diagnostics in Categorizing Acute Lung Infections (RADICAL) study.Item Open Access 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 GAssays 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.Item Open Access Candidate genes on murine chromosome 8 are associated with susceptibility to Staphylococcus aureus infection in mice and are involved with Staphylococcus aureus septicemia in humans.(PloS one, 2017-01) Yan, Qin; Ahn, Sun Hee; Medie, Felix Mba; Sharma-Kuinkel, Batu K; Park, Lawrence P; Scott, William K; Deshmukh, Hitesh; Tsalik, Ephraim L; Cyr, Derek D; Woods, Christopher W; Yu, Chen-Hsin Albert; Adams, Carlton; Qi, Robert; Hansen, Brenda; Fowler, Vance GWe previously showed that chromosome 8 of A/J mice was associated with susceptibility to S. aureus infection. However, the specific genes responsible for this susceptibility are unknown. Chromosome substitution strain 8 (CSS8) mice, which have chromosome 8 from A/J but an otherwise C57BL/6J genome, were used to identify the genetic determinants of susceptibility to S. aureus on chromosome 8. Quantitative trait loci (QTL) mapping of S. aureus-infected N2 backcross mice (F1 [C8A] × C57BL/6J) identified a locus 83180780-88103009 (GRCm38/mm10) on A/J chromosome 8 that was linked to S. aureus susceptibility. All genes on the QTL (n~ 102) were further analyzed by three different strategies: 1) different expression in susceptible (A/J) and resistant (C57BL/6J) mice only in response to S. aureus, 2) consistently different expression in both uninfected and infected states between the two strains, and 3) damaging non-synonymous SNPs in either strain. Eleven candidate genes from the QTL region were significantly differently expressed in patients with S. aureus infection vs healthy human subjects. Four of these 11 genes also exhibited significantly different expression in S. aureus-challenged human neutrophils: Ier2, Crif1, Cd97 and Lyl1. CD97 ligand binding was evaluated within peritoneal neutrophils from A/J and C57BL/6J. CD97 from A/J had stronger CD55 but weaker integrin α5β1 ligand binding as compared with C57BL/6J. Because CD55/CD97 binding regulates immune cell activation and cytokine production, and integrin α5β1 is a membrane receptor for fibronectin, which is also bound by S. aureus, strain-specific differences could contribute to susceptibility to S. aureus. Down-regulation of Crif1 with siRNA was associated with increased host cell apoptosis among both naïve and S. aureus-infected bone marrow-derived macrophages. Specific genes in A/J chromosome 8, including Cd97 and Crif1, may play important roles in host defense against S. aureus.Item Open Access 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, XilingSARS-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.Item Open Access Clinically Adjudicated Reference Standards for Evaluation of Infectious Diseases Diagnostics.(Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2023-03) Patel, Robin; Tsalik, Ephraim L; Evans, Scott; Fowler, Vance G; Doernberg, Sarah B; Antibacterial Resistance Leadership GroupLack of a gold standard can present a challenge for evaluation of diagnostic test accuracy of some infectious diseases tests, particularly when the test's accuracy potentially exceeds that of its predecessors. This approach may measure agreement with an imperfect reference, rather than correctness, because the right answer is unknown. Solutions consist of multitest comparators, including those that involve a test under evaluation if multiple new tests are being evaluated together, using latent class modeling, and clinically adjudicated reference standards. Clinically adjudicated reference standards may be considered as comparator methods when no predefined test or composite of tests is sufficiently accurate; they emulate clinical practice in that multiple data pieces are clinically assessed together.
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