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The evolutionary origins of Middle East respiratory syndrome (MERS) coronavirus (MERS-CoV) are unknown. Current evidence suggests that insectivorous bats are likely to be the original source, as several 2c CoVs have been described from various species in the family Vespertilionidae Here, we describe a MERS-like CoV identified from a Pipistrellus cf. hesperidus bat sampled in Uganda (strain PREDICT/PDF-2180), further supporting the hypothesis that bats are the evolutionary source of MERS-CoV. Phylogenetic analysis showed that PREDICT/PDF-2180 is closely related to MERS-CoV across much of its genome, consistent with a common ancestry; however, the spike protein was highly divergent (46% amino acid identity), suggesting that the two viruses may have different receptor binding properties. Indeed, several amino acid substitutions were identified in key binding residues that were predicted to block PREDICT/PDF-2180 from attaching to the MERS-CoV DPP4 receptor. To experimentally test this hypothesis, an infectious MERS-CoV clone expressing the PREDICT/PDF-2180 spike protein was generated. Recombinant viruses derived from the clone were replication competent but unable to spread and establish new infections in Vero cells or primary human airway epithelial cells. Our findings suggest that PREDICT/PDF-2180 is unlikely to pose a zoonotic threat. Recombination in the S1 subunit of the spike gene was identified as the primary mechanism driving variation in the spike phenotype and was likely one of the critical steps in the evolution and emergence of MERS-CoV in humans.IMPORTANCE Global surveillance efforts for undiscovered viruses are an important component of pandemic prevention initiatives. These surveys can be useful for finding novel viruses and for gaining insights into the ecological and evolutionary factors driving viral diversity; however, finding a viral sequence is not sufficient to determine whether it can infect people (i.e., poses a zoonotic threat). Here, we investigated the specific zoonotic risk of a MERS-like coronavirus (PREDICT/PDF-2180) identified in a bat from Uganda and showed that, despite being closely related to MERS-CoV, it is unlikely to pose a threat to humans. We suggest that this approach constitutes an appropriate strategy for beginning to determine the zoonotic potential of wildlife viruses. By showing that PREDICT/PDF-2180 does not infect cells that express the functional receptor for MERS-CoV, we further show that recombination was likely to be the critical step that allowed MERS to emerge in humans.

Since the emergence of Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) and Middle East Respiratory Syndrom Coronavirus (MERS-CoV) it has become increasingly clear that bats are important reservoirs of CoVs. Despite this, only 6% of all CoV sequences in GenBank are from bats. The remaining 94% largely consist of known pathogens of public health or agricultural significance, indicating that current research effort is heavily biased towards describing known diseases rather than the 'pre-emergent' diversity in bats. Our study addresses this critical gap, and focuses on resource poor countries where the risk of zoonotic emergence is believed to be highest. We surveyed the diversity of CoVs in multiple host taxa from twenty countries to explore the factors driving viral diversity at a global scale. We identified sequences representing 100 discrete phylogenetic clusters, ninety-one of which were found in bats, and used ecological and epidemiologic analyses to show that patterns of CoV diversity correlate with those of bat diversity. This cements bats as the major evolutionary reservoirs and ecological drivers of CoV diversity. Co-phylogenetic reconciliation analysis was also used to show that host switching has contributed to CoV evolution, and a preliminary analysis suggests that regional variation exists in the dynamics of this process. Overall our study represents a model for exploring global viral diversity and advances our fundamental understanding of CoV biodiversity and the potential risk factors associated with zoonotic emergence.

A nosocomial outbreak of disease involving 5 patients, 4 of whom died, occurred in South Africa during September-October 2008. The first patient had been transferred from Zambia to South Africa for medical management. Three cases involved secondary spread of infection from the first patient, and 1 was a tertiary infection. A novel arenavirus was identified. The source of the first patient's infection remains undetermined. [ABSTRACT FROM AUTHOR]

Background: Human infection with avian influenza H5N1 is an emerging infectious disease characterised by respiratory symptoms and a high fatality rate. Previous studies have shown that the human infection with avian influenza H5N1 could also target organs apart from the lungs.Methods: We studied post-mortem tissues of two adults (one man and one pregnant woman) infected with H5N1 influenza virus, and a fetus carried by the woman. In-situ hybridisation (with sense and antisense probes to haemagglutinin and nucleoprotein) and immunohistochemistry (with monoclonal antibodies to haemagglutinin and nucleoprotein) were done on selected tissues. Reverse-transcriptase (RT) PCR, real-time RT-PCR, strand-specific RT-PCR, and nucleic acid sequence-based amplification (NASBA) detection assays were also undertaken to detect viral RNA in organ tissue samples.Findings: We detected viral genomic sequences and antigens in type II epithelial cells of the lungs, ciliated and non-ciliated epithelial cells of the trachea, T cells of the lymph node, neurons of the brain, and Hofbauer cells and cytotrophoblasts of the placenta. Viral genomic sequences (but no viral antigens) were detected in the intestinal mucosa. In the fetus, we found viral sequences and antigens in the lungs, circulating mononuclear cells, and macrophages of the liver. The presence of viral sequences in the organs and the fetus was also confirmed by RT-PCR, strand-specific RT-PCR, real-time RT-PCR, and NASBA.Interpretation: In addition to the lungs, H5N1 influenza virus infects the trachea and disseminates to other organs including the brain. The virus could also be transmitted from mother to fetus across the placenta. [ABSTRACT FROM AUTHOR]

The generalisability of critical illness molecular phenotypes to low- and middle-income countries (LMICs) is unknown. We show that molecular phenotypes derived in high-income countries (hyperinflammatory and hypoinflammatory, reactive and uninflamed) stratify sepsis patients in Uganda by physiological severity, mortality risk and dysregulation of key pathobiological domains. A classifier model including data available at the LMIC bedside modestly discriminated phenotype assignment (area under the receiver operating characteristic curve (AUROC) 0.80, 95% CI 0.71 to 0.90 for hyperinflammatory vs hypoinflammatory; AUROC 0.74, 95% CI 0.65 to 0.83 for reactive vs uninflamed). Our findings highlight the potential for a globally relevant, clinicomolecular classification of critical illness and may support the inclusion of diverse populations in phenotype-targeted critical care trials. Improved laboratory capacity and access to rapid biomarker assays are likely necessary to optimise phenotype stratification in LMIC settings., Competing Interests: Competing interests: MJC and MRO’D were investigators for clinical trials evaluating the efficacy and safety of remdesivir, convalescent plasma, and anti-SARS-CoV-2 hyperimmune globulin in hospitalised patients with COVID-19, sponsored by Gilead Sciences, Amazon and the NIH, respectively. Compensation for this work was paid to Columbia University. MJC reports consulting fees from Vertex Pharmaceuticals and Veracyte unrelated to the submitted work. The remaining authors declare no conflicts of interest., (© Author(s) (or their employer(s)) 2025. No commercial re-use. See rights and permissions. Published by BMJ Group.)

Objectives: Globally, the burden of sepsis is highest in malaria endemic areas of sub-Saharan Africa. The influence of malaria on biological heterogeneity inherent to sepsis in this setting is poorly understood. We sought to determine shared and distinct features of the host response in malarial and non-malarial sepsis in sub-Saharan Africa., Design and Setting: Analysis of Olink proteomic data from prospective observational cohort studies of sepsis conducted at public hospitals in Uganda (discovery cohort [Entebbe, urban], n = 238; validation cohort [Tororo, rural], n = 253)., Patients: Adults (age ≥ 18 yr) hospitalized with sepsis., Interventions: None., Measurements and Main Results: The frequency of malaria-associated (malarial) sepsis was 20% in the discovery cohort and 28% in the validation cohort. In both cohorts, a shared host response was predominant, with less than or equal to 8% of proteins differentially expressed (Benjamini-Hochberg-adjusted p ≤ 0.05) between malarial and non-malarial sepsis, after adjustment for demographic variables and HIV and tuberculosis coinfection. In both cohorts, malarial sepsis was associated with increased expression of immunosuppressive proteins (interleukin-10, leukocyte immunoglobulin-like receptor B1, killer cell immunoglobulin-like receptor 3DL1), including those associated with Tcell exhaustion and apoptosis (lymphocyte activation gene 3, T cell immunoglobulin and mucin domain containing 4). A classifier model including these immunosuppressive proteins showed reasonable discrimination (area under the receiver operating characteristic curves, 0.73 [95% CI, 0.65-0.81] and 0.72 [0.65-0.79]) and calibration (Brier scores 0.14 and 0.18) for stratification of malarial sepsis in the discovery and validation cohorts, respectively., Conclusions: Host responses are largely conserved in malarial and non-malarial sepsis but may be distinguished by a signature of relative immunosuppression in the former. Further investigations are needed to differentiate mechanisms of malarial and non-malarial sepsis, with the goal of informing pathogen-stratified and pathogen-agnostic treatment strategies., Competing Interests: Drs. Cummings and O’Donnell were investigators for clinical trials evaluating the efficacy and safety of remdesivir, convalescent plasma, and anti-severe acute respiratory syndrome coronavirus 2 hyperimmune globulin in hospitalized patients with COVID-19, sponsored by Gilead Sciences, Amazon, and the National Institutes of Health, respectively. Compensation for this work was paid to Columbia University. Dr. Cummings reports consulting fees from Vertex Pharmaceuticals and Veracyte unrelated to the submitted work. The remaining authors have disclosed that they do not have any potential conflicts of interest., (Copyright © 2025 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.)

Unexplained fever poses significant diagnostic challenges in resource-limited settings like Bamako, Mali, where overlapping endemic diseases include malaria, HIV/AIDS, yellow fever, typhoid, and others. This study aimed to elucidate the infectious etiologies of acute febrile illnesses in this context. Acute febrile patients of any age were enrolled after informed consent or assent. Baseline clinical and demographic data were collected, and samples were analyzed by using rapid diagnostic tests, reverse transcriptase polymerase chain reaction, ELISA, and virus-targeted metagenomic sequencing (virome capture sequencing platform for vertebrate viruses [VirCapSeq-VERT]). Among 108 enrolled subjects, most were male (51.9%) and under 15 years old (56.5%). Measles virus was identified in 39.8% of cases, primarily among children. Other findings included Plasmodium spp. (12%), Salmonella spp. (13%), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; 8.7%). The virome capture sequencing platform for vertebrate viruses was used for 101 subjects, corroborating many routine test results and identifying additional cases of measles virus (1), SARS-CoV-2 (5), and numerous other agents. Notably, nearly all subjects showed evidence of herpesviruses (90%) and anelloviruses (98%). Hemorrhagic fever viruses were not observed. With the inclusion of VirCapSeq-VERT, identifiable pathogens were found in 79.6% of cases, leaving 20.4% without a clear etiology. The identification of more than one concurrent pathogen was common (41.5%). Integrating metagenomic sequencing with routine laboratory diagnostic testing enhances the detection of pathogens in acute febrile illnesses, highlighting its potential value in identifying infectious etiologies in resource-limited settings.

Measles is vaccine-preventable extremely contagious disease caused by the measles virus. High vaccination coverage is needed to prevent outbreaks of disease. Although molecular surveillance of measles is critical to characterize outbreaks and track viral evolution, few whole-genome sequences of measles virus from West Africa are available despite continual outbreaks in the region. Using VirCapSeq-VERT, an enhanced and comprehensive metagenomic sequencing technique that allows for simultaneous identification of all vertebrate viruses, 23 wild-type near-complete genomes of measles virus from across Mali were obtained from samples collected between January 2012 to October 2022. Other febrile rash illnesses were also identified by VirCapSeq-VERT, demonstrating the advantage of using broad detection agnostic methods when the clinical diagnosis is unclear. Whereas one measles virus sequence was consistent with measles vaccine-associated rash illness (VARI), the remaining 38 were classified within the B3.1 genotype. Broad surveillance throughout Mali reveals regional measles virus transmission across West and Central Africa into Mali, while local clinical testing in Bamako shows stable sequence conservation within genotype B3.1 evolving from Nigerian sequences. The genomic information generated in this study is critical in addressing the lack of whole genome sequences available in West Africa and these findings show the importance of phylogenetically tracking measles outbreaks given recent increases in measles cases globally., Competing Interests: Declaration of competing interest Any competing interests were declared. All authors read and approved the final version., (Copyright © 2024. Published by Elsevier B.V.)

Rationale: The global burden of sepsis is concentrated in sub-Saharan Africa, where inciting pathogens are diverse and HIV co-infection is a major driver of poor outcomes. Biological heterogeneity inherent to sepsis in this setting is poorly defined., Objectives: To identify dominant pathobiological signatures of sepsis in sub-Saharan Africa and their relationship to clinical phenotypes, patient outcomes, and biological classifications of sepsis identified in high-income-countries (HICs)., Methods: We analyzed two prospective cohorts of adults hospitalized with sepsis (severe infection with qSOFA score≥1) at disparate settings in Uganda (discovery cohort [Entebbe,urban], N=242; validation cohort [Tororo,rural], N=253). To identify pathobiological signatures in the discovery cohort, we applied unsupervised clustering to 173 soluble proteins reflecting key domains of the host response to severe infection. A random forest-derived classifier was used to predict signature assignment in the validation cohort., Measurements and Main Results: Two signatures (Uganda Sepsis Signature [USS]-1 and USS-2) were identified in the discovery cohort, distinguished by expression of proteins involved in myeloid cell and inflammasome activation, T cell co-stimulation and exhaustion, and endothelial barrier dysfunction. A five-protein classifier (AUROC 0.97) reproduced two signatures in the validation cohort with similar biological profiles. In both cohorts, USS-2 mapped to a more severe clinical phenotype associated with HIV and related immunosuppression, severe tuberculosis, and increased risk of 30-day mortality. Substantial biological overlap was observed between USS-2 and hyperinflammatory and reactive sepsis phenotypes identified in HICs., Conclusions: We identified prognostically-enriched pathobiological signatures among sepsis patients with diverse infections and high HIV prevalence in Uganda. Globally inclusive investigations are needed to define generalizable and context-specific mechanisms of sepsis pathobiology, with the goal of improving access to precision medicine treatment strategies.

Borrelia burgdorferi, the agent of Lyme disease, is estimated to cause >400,000 annual infections in the United States. Serology is the primary laboratory method to support the diagnosis of Lyme disease, but current methods have intrinsic limitations that require alternative approaches or targets. We used a high-density peptide array that contains >90,000 short overlapping peptides to catalog immunoreactive linear epitopes from >60 primary antigens of B. burgdorferi . We then pursued a machine learning approach to identify immunoreactive peptide panels that provide optimal Lyme disease serodiagnosis and can differentiate antibody responses at various stages of disease. We examined 226 serum samples from the Lyme Biobank and the National Institutes of Health, which included sera from 110 individuals diagnosed with Lyme disease, 31 probable cases from symptomatic individuals, and 85 healthy controls. Cases were grouped based on disease stage and presentation and included individuals with early localized, early disseminated, and late Lyme disease. We identified a peptide panel originating from 14 different epitopes that differentiated cases versus controls, whereas another peptide panel built from 12 unique epitopes differentiated subjects with various disease manifestations. Our method demonstrated an improvement in B. burgdorferi antibody detection over the current two-tiered testing approach and confirmed the key diagnostic role of VlsE and FlaB antigens at all stages of Lyme disease. We also uncovered epitopes that triggered a temporal antibody response that was useful for differentiation of early and late disease. Our findings can be used to streamline serologic targets and improve antibody-based diagnosis of Lyme disease., Importance: Serology is the primary method of Lyme disease diagnosis, but this approach has limitations, particularly early in disease. Currently employed antibody detection assays can be improved by the identification of alternative immunodominant epitopes and the selection of optimal diagnostic targets. We employed high-density peptide arrays that enabled precise epitope mapping for a wide range of B. burgdorferi antigens. In combination with machine learning, this approach facilitated the selection of serologic targets early in disease and the identification of serological indicators associated with different manifestations of Lyme disease. This study provides insights into differential antibody responses during infection and outlines a new approach for improved serologic diagnosis of Lyme disease., Competing Interests: The authors declare no conflict of interest.

Abstract: Background: Understanding of immune cell phenotypes associated with inflammatory and immunosuppressive host responses in sepsis is imprecise, particularly in low- and middle-income countries, where the global sepsis burden is concentrated. In these settings, elucidation of clinically relevant immunophenotypes is necessary to determine the relevance of emerging therapeutics and refine mechanistic investigations of sepsis immunopathology. Methods: In a prospective cohort of adults hospitalized with suspected sepsis in Uganda (N = 43; median age 46 years [IQR 36-59], 24 [55.8%] living with HIV, 16 [37.2%] deceased at 60 days), we combined high-dimensional flow cytometry with unsupervised machine learning and manual gating to define peripheral immunophenotypes associated with increased risk of 60-day mortality. Results: Patients who died showed heterogeneous expansion of polymorphonuclear myeloid-derived suppressor cells, with increased and decreased abundance of CD16 - PD-L1 dim and CD16 bright PD-L1 bright subsets, respectively, significantly associated with mortality. While differences between CD16 - PD-L1 dim cell abundance and mortality risk appeared consistent throughout the course of illness, those for the CD16 bright PD-L1 bright subset were more pronounced early after illness onset. Independent of HIV co-infection, depletion of CD4 + T cells, dendritic cells, and CD56 - CD16 bright NK cells were significantly associated with mortality risk, as was expansion of immature, CD56 + CD16 - CD11c + NK cells. Abundance of T cells expressing inhibitory checkpoint proteins (PD-1, CTLA-4, LAG-3) was similar between patients who died versus those who survived. Conclusions: This is the first study to define high-risk immunophenotypes among adults with sepsis in sub-Saharan Africa, an immunologically distinct region where biologically informed treatment strategies are needed. More broadly, our findings highlight the clinical importance and complexity of myeloid derived suppressor cell expansion during sepsis and support emerging data that suggest a host-protective role for PD-L1 myeloid checkpoints in acute critical illness., Competing Interests: The authors report no conflicts of interest., (Copyright © 2024 by the Shock Society.)

Background: Delays and loss of early-emerging social-communication skills are often discussed as unique to autism. However, most studies of regression have relied on retrospective recall and clinical samples. Here, we examine attainment and loss of social-communication skills in the population-based Norwegian Mother, Father and Child Cohort Study (MoBa)., Methods: Mothers rated their child's attainment of 10 early-emerging social-communication skills at ages 18 and 36 months (N = 40,613, 50.9% male). Prospectively reported loss was defined as skill presence at 18 months but absence at 36 months. At 36 months, mothers also recalled whether the child had lost social-communication skills. The Norwegian Patient Registry was used to capture diagnoses of Autism Spectrum Disorder (autism) and other neurodevelopmental disabilities (NDDs)., Results: Delay in at least one skill was observed in 14% of the sample and loss in 5.4%. Recalled loss of social-communication skills was rare (0.86%) and showed low convergence with prospectively reported loss. Delay and especially loss were associated with elevated odds of an autism diagnosis (n = 383) versus no autism diagnosis (n = 40,230; ≥3 skills delayed: OR = 7.09[4.15,12.11]; ≥3 skills lost: OR = 30.66[17.30,54.33]). They were also associated with an increased likelihood of autism compared to some other NDDs. Delay (relative risk [RR] = 4.16[2.08, 8.33]) and loss (RR = 10.00[3.70, 25.00]) associated with increased likelihood of autism versus ADHD, and loss (RR = 4.35[1.28,14.29]), but not delay (RR = 2.00[0.78,5.26]), associated with increased likelihood of autism compared to language disability. Conversely, delay conferred decreased likelihood of autism versus intellectual disability (RR = 0.11[0.06,0.21]), and loss was not reliably associated with likelihood of autism versus intellectual disability (RR = 1.89[0.44,8.33])., Conclusions: This population-based study suggests that loss of early social communication skills is more common than studies using retrospective reports have indicated and is observed across several NDD diagnoses (not just autism). Nevertheless, most children with NDD diagnoses showed no reported delay or loss in these prospectively measured skills., (© 2023 The Authors. Journal of Child Psychology and Psychiatry published by John Wiley & Sons Ltd on behalf of Association for Child and Adolescent Mental Health.)

Objectives: In high-income countries (HICs), sepsis endotypes defined by distinct pathobiological mechanisms, mortality risks, and responses to corticosteroid treatment have been identified using blood transcriptomics. The generalizability of these endotypes to low-income and middle-income countries (LMICs), where the global sepsis burden is concentrated, is unknown. We sought to determine the prevalence, prognostic relevance, and immunopathological features of HIC-derived transcriptomic sepsis endotypes in sub-Saharan Africa., Design: Prospective cohort study., Setting: Public referral hospital in Uganda., Patients: Adults ( n = 128) hospitalized with suspected sepsis., Interventions: None., Measurements and Main Results: Using whole-blood RNA sequencing data, we applied 19-gene and 7-gene classifiers derived and validated in HICs (SepstratifieR) to assign patients to one of three sepsis response signatures (SRS). The 19-gene classifier assigned 30 (23.4%), 92 (71.9%), and 6 (4.7%) patients to SRS-1, SRS-2, and SRS-3, respectively, the latter of which is designed to capture individuals transcriptionally closest to health. SRS-1 was defined biologically by proinflammatory innate immune activation and suppressed natural killer-cell, T-cell, and B-cell immunity, whereas SRS-2 was characterized by dampened innate immune activation, preserved lymphocyte immunity, and suppressed transcriptional responses to corticosteroids. Patients assigned to SRS-1 were predominantly (80.0% [24/30]) persons living with HIV with advanced immunosuppression and frequent tuberculosis. Mortality at 30-days differed significantly by endotype and was highest (48.1%) in SRS-1. Agreement between 19-gene and 7-gene SRS assignments was poor (Cohen's kappa 0.11). Patient stratification was suboptimal using the 7-gene classifier with 15.1% (8/53) of individuals assigned to SRS-3 deceased at 30-days., Conclusions: Sepsis endotypes derived in HICs share biological and clinical features with those identified in sub-Saharan Africa, with major differences in host-pathogen profiles. Our findings highlight the importance of context-specific sepsis endotyping, the generalizability of conserved biological signatures of critical illness across disparate settings, and opportunities to develop more pathobiologically informed sepsis treatment strategies in LMICs., Competing Interests: This work was supported by the National Center for Advancing Translational Sciences (UL1TR001873 to Columbia University, subaward to Dr. O’Donnell), the National Institute of Allergy and Infectious Diseases (K23AI163364 to Dr. Cummings), and the MakCHS-Berkeley-Yale Pulmonary Complications of AIDS Research Training Program (D43TW009607, subaward to Dr. Bakamutumaho) from the Fogarty International Center, National Institutes of Health (NIH). Additional support was provided by the Stony Wold-Herbert Fund (Dr. Cummings), Potts Memorial Foundation (Dr. Cummings), Thrasher Research Fund (Dr. Cummings), Burroughs Wellcome Fund/American Society of Tropical Medicine and Hygiene (Dr. Cummings), and DELTAS Africa Initiative (subaward to Drs. Cummings and Bakamutumaho; grant no. 107743). Drs. Cummings, Bakamutumaho, Owor, Namulondo, Nayiga, Kyebambe, Lutwama, and Lipkin received support for article research from the NIH. Dr. Lipkin disclosed government work. The remaining authors have disclosed that they do not have any potential conflicts of interest., (Copyright © 2023 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.)

Little is known about the pathobiology of SARS-CoV-2 infection in sub-Saharan Africa, where severe COVID-19 fatality rates are among the highest in the world and the immunological landscape is unique. In a prospective cohort study of 306 adults encompassing the entire clinical spectrum of SARS-CoV-2 infection in Uganda, we profile the peripheral blood proteome and transcriptome to characterize the immunopathology of COVID-19 across multiple phases of the pandemic. Beyond the prognostic importance of myeloid cell-driven immune activation and lymphopenia, we show that multifaceted impairment of host protein synthesis and redox imbalance define core biological signatures of severe COVID-19, with central roles for IL-7, IL-15, and lymphotoxin-α in COVID-19 respiratory failure. While prognostic signatures are generally consistent in SARS-CoV-2/HIV-coinfection, type I interferon responses uniquely scale with COVID-19 severity in persons living with HIV. Throughout the pandemic, COVID-19 severity peaked during phases dominated by A.23/A.23.1 and Delta B.1.617.2/AY variants. Independent of clinical severity, Delta phase COVID-19 is distinguished by exaggerated pro-inflammatory myeloid cell and inflammasome activation, NK and CD8 + T cell depletion, and impaired host protein synthesis. Combining these analyses with a contemporary Ugandan cohort of adults hospitalized with influenza and other severe acute respiratory infections, we show that activation of epidermal and platelet-derived growth factor pathways are distinct features of COVID-19, deepening translational understanding of mechanisms potentially underlying SARS-CoV-2-associated pulmonary fibrosis. Collectively, our findings provide biological rationale for use of broad and targeted immunotherapies for severe COVID-19 in sub-Saharan Africa, illustrate the relevance of local viral and host factors to SARS-CoV-2 immunopathology, and highlight underemphasized yet therapeutically exploitable immune pathways driving COVID-19 severity., (© 2024. The Author(s).)

Importance: Broad range assay for accurate and sensitive diagnostics., Competing Interests: The authors declare no conflict of interest.

Unbiased high-throughput sequencing (HTS) has enabled new insights into the diversity of agents implicated in central nervous system (CNS) infections. The addition of positive selection capture methods to HTS has enhanced the sensitivity while reducing sequencing costs and the complexity of bioinformatic analysis. Here we report the use of virus capture-based sequencing for vertebrate viruses (VirCapSeq-VERT) and bacterial capture sequencing (BacCapSeq) in investigating CNS infections. Thirty-four samples were categorized: (1) patients with definitive CNS infection by routine testing; (2) patients meeting clinically the Brighton criteria (BC) for meningoencephalitis; (3) patients with presumptive infectious etiology highest on the differential. RNA extracts from cerebrospinal fluid (CSF) were used for VirCapSeq-VERT, and DNA extracts were used for BacCapSeq analysis. Among 8 samples from known CNS infections in group 1, VirCapSeq and BacCapSeq confirmed 3 expected diagnoses (42.8%), were negative in 2 (25%), yielded an alternative result in 1 (11.1%), and did not detect 2 expected negative pathogens. The confirmed cases identified HHV-6, HSV-2, and VZV while the negative samples included JCV and HSV-2. In groups 2 and 3, 11/26 samples (42%) were positive for at least one pathogen; however, 27% of the total samples (7/26) were positive for commensal organisms. No microbial nucleic acids were detected in negative control samples. HTS showed limited promise for pathogen identification in presumed CNS infectious diseases in our small sample. Before conducting larger-scale prospective studies to assess the clinical value of this novel technique, clinicians should understand the benefits and limitations of using this modality., (© 2023. The Author(s) under exclusive licence to The Journal of NeuroVirology, Inc.)

Univariate analyses of metabolomics data currently follow a frequentist approach, using p -values to reject a null hypothesis. We here propose the use of Bayesian statistics to quantify evidence supporting different hypotheses and discriminate between the null hypothesis versus the lack of statistical power. We used metabolomics data from three independent human cohorts that studied the plasma signatures of subjects with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). The data are publicly available, covering 84-197 subjects in each study with 562-888 identified metabolites of which 777 were common between the two studies and 93 were compounds reported in all three studies. We show how Bayesian statistics incorporates results from one study as "prior information" into the next study, thereby improving the overall assessment of the likelihood of finding specific differences between plasma metabolite levels. Using classic statistics and Benjamini-Hochberg FDR-corrections, Study 1 detected 18 metabolic differences and Study 2 detected no differences. Using Bayesian statistics on the same data, we found a high likelihood that 97 compounds were altered in concentration in Study 2, after using the results of Study 1 as the prior distributions. These findings included lower levels of peroxisome-produced ether-lipids, higher levels of long-chain unsaturated triacylglycerides, and the presence of exposome compounds that are explained by the difference in diet and medication between healthy subjects and ME/CFS patients. Although Study 3 reported only 92 compounds in common with the other two studies, these major differences were confirmed. We also found that prostaglandin F2alpha, a lipid mediator of physiological relevance, was reduced in ME/CFS patients across all three studies. The use of Bayesian statistics led to biological conclusions from metabolomic data that were not found through frequentist approaches. We propose that Bayesian statistics is highly useful for studies with similar research designs if similar metabolomic assays are used.

Astroviruses (AstVs) can cause of severe infection of the central nervous system (CNS) in immunocompromised individuals. Here, we identified a human AstV of the VA1 genotype, HAstV-NIH, as the cause of fatal encephalitis in an immunocompromised adult. We investigated the cells targeted by AstV, neurophysiological changes, and host responses by analyzing gene expression, protein expression, and cellular morphology in brain tissue from three cases of AstV neurologic disease (AstV-ND). We demonstrate that neurons are the principal cells targeted by AstV in the brain and that the cerebellum and brainstem have the highest burden of infection. Detection of VA1 AstV in interconnected brain structures such as thalamus, deep cerebellar nuclei, Purkinje cells, and pontine nuclei indicates that AstV may spread between connected neurons transsynaptically. We found transcriptional dysregulation of neural functions and disruption of both excitatory and inhibitory synaptic innervation of infected neurons. Importantly, transcriptional dysregulation of neural functions occurred in fatal cases, but not in a patient that survived AstV-ND. We show that the innate, but not adaptive immune response was transcriptionally driving host defense in the brain of immunocompromised patients with AstV-ND. Both transcriptome and molecular pathology studies showed that most of the cellular changes were associated with CNS-intrinsic cells involved in phagocytosis and injury repair (microglia, perivascular/parenchymal border macrophages, and astrocytes), but not CNS-extrinsic cells (T and B cells), suggesting an imbalance of innate and adaptive immune responses to AstV infection in the brain as a result of the underlying immunodeficiencies. These results show that VA1 AstV infection of the brain in immunocompromised humans is associated with imbalanced host defense responses, disruption of neuronal somatodendritic compartments and synapses and increased phagocytic cellular activity. Improved understanding of the response to viral infections of the human CNS may provide clues for how to manipulate these processes to improve outcomes., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

Some patients remain unwell for months after "recovering" from acute COVID-19. They develop persistent fatigue, cognitive problems, headaches, disrupted sleep, myalgias and arthralgias, post-exertional malaise, orthostatic intolerance and other symptoms that greatly interfere with their ability to function and that can leave some people housebound and disabled. The illness (Long COVID) is similar to myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) as well as to persisting illnesses that can follow a wide variety of other infectious agents and following major traumatic injury. Together, these illnesses are projected to cost the U.S. trillions of dollars. In this review, we first compare the symptoms of ME/CFS and Long COVID, noting the considerable similarities and the few differences. We then compare in extensive detail the underlying pathophysiology of these two conditions, focusing on abnormalities of the central and autonomic nervous system, lungs, heart, vasculature, immune system, gut microbiome, energy metabolism and redox balance. This comparison highlights how strong the evidence is for each abnormality, in each illness, and helps to set priorities for future investigation. The review provides a current road map to the extensive literature on the underlying biology of both illnesses., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Komaroff and Lipkin.)

The discovery of prenatal and neonatal molecular biomarkers has the potential to yield insights into autism spectrum disorder (ASD) and facilitate early diagnosis. We characterized metabolomic profiles in ASD using plasma samples collected in the Norwegian Autism Birth Cohort from mothers at weeks 17-21 gestation (maternal mid-gestation, MMG, n = 408) and from children on the day of birth (cord blood, CB, n = 418). We analyzed associations using sex-stratified adjusted logistic regression models with Bayesian analyses. Chemical enrichment analyses (ChemRICH) were performed to determine altered chemical clusters. We also employed machine learning algorithms to assess the utility of metabolomics as ASD biomarkers. We identified ASD associations with a variety of chemical compounds including arachidonic acid, glutamate, and glutamine, and metabolite clusters including hydroxy eicospentaenoic acids, phosphatidylcholines, and ceramides in MMG and CB plasma that are consistent with inflammation, disruption of membrane integrity, and impaired neurotransmission and neurotoxicity. Girls with ASD have disruption of ether/non-ether phospholipid balance in the MMG plasma that is similar to that found in other neurodevelopmental disorders. ASD boys in the CB analyses had the highest number of dysregulated chemical clusters. Machine learning classifiers distinguished ASD cases from controls with area under the receiver operating characteristic (AUROC) values ranging from 0.710 to 0.853. Predictive performance was better in CB analyses than in MMG. These findings may provide new insights into the sex-specific differences in ASD and have implications for discovery of biomarkers that may enable early detection and intervention., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)