Application of a Machine Learning-Based Classification Approach for Developing Host Protein Diagnostic Models for Infectious Disease.

In recent years, infectious disease diagnosis has increasingly turned to host-centered approaches as a complement to pathogen-directed ones. The former, however, typically requires the interpretation of complex multiple biomarker datasets to arrive at an informative diagnostic outcome. This report describes a machine learning (ML)-based classification workflow that is intended as a template for researchers seeking to apply ML approaches for developing host-based infectious disease biomarker classifiers. As an example, we built a classification model that could accurately distinguish between three disease etiology classes: bacterial, viral, and normal in human sera using host protein biomarkers of known diagnostic utility. After collecting protein data from known disease samples, we trained a series of increasingly complex Auto-ML models until arriving at an optimized classifier that could differentiate viral, bacterial, and non-disease samples. Even when limited to a relatively small training set size, the model had robust diagnostic characteristics and performed well when faced with a blinded sample set. We present here a flexible approach for applying an Auto-ML-based workflow for the identification of host biomarker classifiers with diagnostic utility for infectious disease, and which can readily be adapted for multiple biomarker classes and disease states.

Host response transcriptomic analysis of Crimean-Congo hemorrhagic fever pathogenesis in the cynomolgus macaque model.

Crimean-Congo hemorrhagic fever virus (CCHFV) is a highly pathogenic tick-borne RNA virus prevalent in Asia, Europe, and Africa, and can cause a hemorrhagic disease (CCHF) in humans with mortality rates as high as 60%. A general lack of both effective medical countermeasures and a comprehensive understanding of disease pathogenesis is partly driven by an historical lack of viable CCHF animal models. Recently, a cynomolgous macaque model of CCHF disease was developed. Here, we document the targeted transcriptomic response of non-human primates (NHP) to two different CCHFV strains; Afghan09-2990 and Kosova Hoti that both yielded a mild CCHF disease state. We utilized a targeted gene panel to elucidate the transcriptomic changes occurring in NHP whole blood during CCHFV infection; a first for any primate species. We show numerous upregulated genes starting at 1 day post-challenge through 14 days post-challenge. Early gene changes fell predominantly in the interferon stimulated gene family with later gene changes coinciding with an adaptive immune response to the virus. There are subtle differences between viral strains, namely duration of the differentially expressed gene response and biological pathways enriched. After recovery, NHPs showed no lasting transcriptomic changes at the end of sample collection.

Addressing the Third Epidemic of Retinopathy of Prematurity Through Telemedicine and Technology: A Systematic Review.

The rising prevalence of retinopathy of prematurity (ROP) in low- and middle-income countries has increased the need for screening at-risk infants. The purpose of this article was to review the impact of tele-medicine and technology on ROP screening programs. Adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic review was performed using PubMed, Pro-Quest, and Google Scholar bibliographic search engine. Terms searched included retinopathy of prematurity, telemedicine, and tele-ophthalmology. Data regarding internet access and gross domestic product per capita were obtained from the World Bank. Information was also obtained about internet access, speeds, and costs in low-income countries. There has been increasing integration of telemedicine and technology for ROP screening and management. Low-income countries are using available internet options and information and communications technology for ROP screening, which can aid in addressing the unique challenges faced by low-income countries. This provides a promising solution to the third epidemic of ROP by expanding and improving screening and management. Although telemedicine systems may serve as a cost-effective approach to facilitate delivery of health care, programs (especially in lowand middle-income countries) require national support to maintain its infrastructure. [J Pediatr Ophthalmol Strabismus. 2021;58(4):261-269.].

Transcriptomic Analysis Reveals Host miRNAs Correlated with Immune Gene Dysregulation during Fatal Disease Progression in the Ebola Virus Cynomolgus Macaque Disease Model.

Ebola virus is a continuing threat to human populations, causing a virulent hemorrhagic fever disease characterized by dysregulation of both the innate and adaptive host immune responses. Severe cases are distinguished by an early, elevated pro-inflammatory response followed by a pronounced lymphopenia with B and T cells unable to mount an effective anti-viral response. The precise mechanisms underlying the dysregulation of the host immune system are poorly understood. In recent years, focus on host-derived miRNAs showed these molecules to play an important role in the host gene regulation arsenal. Here, we describe an investigation of RNA biomarkers in the fatal Ebola virus disease (EVD) cynomolgus macaque model. We monitored both host mRNA and miRNA responses in whole blood longitudinally over the disease course in these non-human primates (NHPs). Analysis of the interactions between these classes of RNAs revealed several miRNA markers significantly correlated with downregulation of genes; specifically, the analysis revealed those involved in dysregulated immune pathways associated with EVD. In particular, we noted strong interactions between the miRNAs hsa-miR-122-5p and hsa-miR-125b-5p with immunological genes regulating both B and T-cell activation. This promising set of biomarkers will be useful in future studies of severe EVD pathogenesis in both NHPs and humans and may serve as potential prognostic targets.

Diagnostic targETEd seQuencing adjudicaTion (DETEQT): Algorithms for Adjudicating Targeted Infectious Disease Next-Generation Sequencing Panels.

Next-generation sequencing (NGS) for infectious disease diagnostics is a relatively new and underdeveloped concept. If this technology is to become a regulatory-grade clinical diagnostic, standardization in the form of locked-down assays and firmly established underlying processes is necessary. Targeted sequencing, specifically by amplification of genomic signatures, has the potential to bridge the gap between PCR- and NGS-based diagnostics; however, existing NGS assay panels lack validated analytical techniques to adjudicate high background and error-prone NGS data. Herein, we present the Diagnostic targETEd seQuencing adjudicaTion (DETEQT) software, consisting of an intuitive bioinformatics pipeline entailing a set of algorithms to translate raw sequencing data into positive, negative, and indeterminate diagnostic determinations. After basic read filtering and mapping, the software compares abundance and quality metrics against heuristic and fixed thresholds. A novel generalized quality function provides an amalgamated quality score for the match between sequence reads of an assay and panel targets, rather than considering each component factor independently. When evaluated against numerous assay samples and parameters (mock clinical, human, and nonhuman primate clinical data sets; diverse amplification strategies; downstream applications; and sequence platforms), DETEQT demonstrated improved rejection of false positives and accuracies >95%. Finally, DETEQT was implemented in the user-friendly Empowering the Development of Genomics Expertise (EDGE) bioinformatics platform, providing a complete, end-to-end solution that can be operated by nonexperts in a clinical laboratory setting.

A highly multiplexed broad pathogen detection assay for infectious disease diagnostics.

Rapid pathogen identification during an acute febrile illness is a critical first step for providing appropriate clinical care and patient isolation. Primary screening using sensitive and specific assays, such as real-time PCR and ELISAs, can rapidly test for known circulating infectious diseases. If the initial testing is negative, potentially due to a lack of developed diagnostic assays or an incomplete understanding of the pathogens circulating within a geographic region, additional testing would be required including highly multiplexed assays and metagenomic next generation sequencing. To bridge the gap between rapid point of care diagnostics and sequencing, we developed a highly multiplexed assay designed to detect 164 different viruses, bacteria, and parasites using the NanoString nCounter platform. Included in this assay were high consequence pathogens such as Ebola virus, highly endemic organisms including several Plasmodium species, and a large number of less prevalent pathogens to ensure a broad coverage of potential human pathogens. Evaluation of this panel resulted in positive detection of 113 (encompassing 98 different human pathogen types) of the 126 organisms available to us including the medically important Ebola virus, Lassa virus, dengue virus serotypes 1-4, Chikungunya virus, yellow fever virus, and Plasmodium falciparum. Overall, this assay could improve infectious disease diagnostics and biosurveillance efforts as a quick, highly multiplexed, and easy to use pathogen screening tool.

Comparison of Transcriptomic Platforms for Analysis of Whole Blood from Ebola-Infected Cynomolgus Macaques.

Ebola virus disease (EVD) is a serious illness with mortality rates of 20-90% in various outbreaks. EVD is characterized by robust virus replication and strong host inflammatory response. Analyzing host immune responses has increasingly involved multimodal approaches including transcriptomics to profile gene expression. We studied cynomolgus macaques exposed to Ebola virus Makona via different routes with the intent of comparing RNA-Seq to a NanoString nCounter codeset targeting 769 non-human primate (NHP) genes. RNA-Seq analysis of serial blood samples showed different routes led to the same overall transcriptional response seen in previously reported EBOV-exposed NHP studies. Both platforms displayed a strong correlation in gene expression patterns, including a strong induction of innate immune response genes at early times post-exposure, and neutrophil-associated genes at later time points. A 41-gene classifier was tested in both platforms for ability to cluster samples by infection status. Both NanoString and RNA-Seq could be used to predict relative abundances of circulating immune cell populations that matched traditional hematology. This demonstrates the complementarity of RNA-Seq and NanoString. Moreover, the development of an NHP-specific NanoString codeset should augment studies of filoviruses and other high containment infectious diseases without the infrastructure requirements of RNA-Seq technology.

Influence of Computer-Generated Mosaic Photographs on Retinopathy of Prematurity Diagnosis and Management.

IMPORTANCE: Telemedicine is becoming an increasingly important component of clinical care for retinopathy of prematurity (ROP), but little information exists regarding the role of mosaic photography for ROP telemedicine diagnosis. OBJECTIVE: To examine the potential effect of computer-generated mosaic photographs on the diagnosis and management of ROP. DESIGN, SETTING, AND PARTICIPANTS: In this prospective cohort study performed from July 12, 2011, through September 21, 2015, images were acquired from ROP screening at 8 academic institutions, and ROP experts interpreted 40 sets (20 sets with individual fundus photographs with ≥3 fields and 20 computer-generated mosaic photographs) of wide-angle retinal images from infants with ROP. All experts independently reviewed the 40 sets and provided a diagnosis and management plan for each set presented. MAIN OUTCOMES AND MEASURES: The primary outcome measure was the sensitivity and specificity of the ROP diagnosis by experts that was calculated using a consensus reference standard diagnosis, determined from the diagnosis of fundus photographs by 3 experienced readers in combination with the clinical diagnosis based on ophthalmoscopic examination. Mean unweighted κ statistics were used to analyze the mean intergrader agreement among experts for diagnosis of zone, stage, plus disease, and category. RESULTS: Nine ROP experts (4 women and 5 men) who have been practicing ophthalmology for a mean of 10.8 years (range, 3-24 years) consented to participate. Diagnosis by the mosaic photographs compared with diagnosis by multiple individual photographs resulted in improvements in sensitivity for diagnosis of stage 2 disease or worse (95.9% vs 88.9%; difference, 7.0; 95% CI, 3.5 to 10.5; P = .02), plus disease (85.7% vs 63.5%; difference, 22.2; 95% CI, 7.6 to 36.9; P = .02), and treatment-requiring ROP (84.4% vs 68.5%; difference, 15.9; 95% CI, 0.8 to 31.7; P = .047). With use of the κ statistic, mosaic photographs, compared with multiple individual photographs, resulted in improvements in intergrader agreement for diagnosis of plus disease or not (0.54 vs 0.40; mean κ difference, 0.14; 95% CI, 0.07 to 0.21; P = .004), stage 3 disease or worse or not (0.60 vs 0.52; mean κ difference, 0.06; 95% CI, -0.06 to 0.18; P = .04), and type 2 ROP or not (0.58 vs 0.51; mean κ difference, 0.07; 95% CI, 0.03 to 0.11; P = .04). After viewing the mosaic photographs, experts altered their choice of management in 42 of 180 responses (23.3%; 95% CI, 17.1%-29.5%). CONCLUSIONS AND RELEVANCE: Compared with multiple individual photographs, computer-generated mosaic photographs were associated with improved accuracy of image-based diagnosis for certain categories (eg, plus disease, stage 2 disease or worse, and treatment-requiring ROP) of ROP by experts. It is unclear, however, whether these findings are generalizable, and the results of this study may not be relevant to mosaic grading of other retinal vascular conditions.

Real-time reverse transcriptase polymerase chain reaction assays for Middle East Respiratory Syndrome.

Here we designed and tested two highly specific quantitative TaqMan(®)-MGB-based reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) assays for Middle East Respiratory Syndrome (MERS). The primers and probes for these assays were evaluated and found to have a limit of detection (LOD) of 0.005 plaque-forming units/PCR (pfu/PCR).

Fear extinction learning can be impaired or enhanced by modulation of the CRF system in the basolateral nucleus of the amygdala.

The neuropeptide corticotropin-releasing factor (CRF) is released during periods of anxiety and modulates learning and memory formation. One region with particularly dense concentrations of CRF receptors is the basolateral nucleus of the amygdala (BLA), a critical structure for both Pavlovian fear conditioning and fear extinction. While CRF has the potential to modify amygdala-dependent learning, its effect on fear extinction has not yet been assessed. In the present study, we examined the modulatory role of CRF on within-session extinction and fear extinction consolidation. Intra-BLA infusions of the CRF binding protein ligand inhibitor CRF(6-33) which increases endogenous levels of free CRF, or intra-BLA infusions of exogenous CRF made prior to fear extinction learning did not affect either fear expression or within-session extinction learning. However, when these animals were tested twenty-four hours later, drug free, they showed impairments in extinction memory. Conversely, intra-BLA infusions of the CRF receptor antagonist α-helical CRF(9-41) enhanced memory of fear extinction. These results suggest that increased CRF levels within the BLA at the time of fear extinction learning actively impair the consolidation of long-term fear extinction.