ZSCAN1 Autoantibodies Are Associated with Pediatric Paraneoplastic ROHHAD.

OBJECTIVE: Rapid-onset Obesity with Hypothalamic Dysfunction, Hypoventilation and Autonomic Dysregulation (ROHHAD), is a severe pediatric disorder of uncertain etiology resulting in hypothalamic dysfunction and frequent sudden death. Frequent co-occurrence of neuroblastic tumors have fueled suspicion of an autoimmune paraneoplastic neurological syndrome (PNS); however, specific anti-neural autoantibodies, a hallmark of PNS, have not been identified. Our objective is to determine if an autoimmune paraneoplastic etiology underlies ROHHAD. METHODS: Immunoglobulin G (IgG) from pediatric ROHHAD patients (n = 9), non-inflammatory individuals (n = 100) and relevant pediatric controls (n = 25) was screened using a programmable phage display of the human peptidome (PhIP-Seq). Putative ROHHAD-specific autoantibodies were orthogonally validated using radioactive ligand binding and cell-based assays. Expression of autoantibody targets in ROHHAD tumor and healthy brain tissue was assessed with immunohistochemistry and mass spectrometry, respectively. RESULTS: Autoantibodies to ZSCAN1 were detected in ROHHAD patients by PhIP-Seq and orthogonally validated in 7/9 ROHHAD patients and 0/125 controls using radioactive ligand binding and cell-based assays. Expression of ZSCAN1 in ROHHAD tumor and healthy human brain tissue was confirmed. INTERPRETATION: Our results support the notion that tumor-associated ROHHAD syndrome is a pediatric PNS, potentially initiated by an immune response to peripheral neuroblastic tumor. ZSCAN1 autoantibodies may aid in earlier, accurate diagnosis of ROHHAD syndrome, thus providing a means toward early detection and treatment. This work warrants follow-up studies to test sensitivity and specificity of a novel diagnostic test. Last, given the absence of the ZSCAN1 gene in rodents, our study highlights the value of human-based approaches for detecting novel PNS subtypes. ANN NEUROL 2022;92:279-291.

Central Nervous System Virus Infection in African Children with Cerebral Malaria.

We aimed to identify the contribution of central nervous system (CNS) viral coinfection to illness in African children with retinopathy-negative or retinopathy-positive cerebral malaria (CM). We collected cerebrospinal fluid (CSF) from 272 children with retinopathy-negative or retinopathy-positive CM and selected CSF from 111 of these children (38 retinopathy positive, 71 retinopathy negative, 2 retinopathy unknown) for analysis by metagenomic next-generation sequencing. We found CSF viral coinfections in 7/38 (18.4%) retinopathy-positive children and in 18/71 (25.4%) retinopathy-negative children. Excluding HIV-1, human herpesviruses (HHV) represented 61% of viruses identified. Excluding HIV-1, CNS viral coinfection was equally likely in children who were retinopathy positive and retinopathy negative (P = 0.1431). Neither mortality nor neurological morbidity was associated with the presence of virus (odds ratio [OR] = 0.276, 95% CI: 0.056-1.363). Retinopathy-negative children with a higher temperature, lower white blood cell count, or being dehydrated were more likely to have viral coinfection. Level of consciousness at admission was not associated with CNS viral coinfection in retinopathy-negative children. Viral CNS coinfection is unlikely to contribute to coma in children with CM. The herpesviruses other than herpes simplex virus may represent incidental bystanders in CM, reactivating during acute malaria infection.

Genomic and serologic characterization of enterovirus A71 brainstem encephalitis.

OBJECTIVE: In 2016, Catalonia experienced a pediatric brainstem encephalitis outbreak caused by enterovirus A71 (EV-A71). Conventional testing identified EV in the periphery but rarely in CSF. Metagenomic next-generation sequencing (mNGS) and CSF pan-viral serology (VirScan) were deployed to enhance viral detection and characterization. METHODS: RNA was extracted from the CSF (n = 20), plasma (n = 9), stool (n = 15), and nasopharyngeal samples (n = 16) from 10 children with brainstem encephalitis and 10 children with meningitis or encephalitis. Pathogens were identified using mNGS. Available CSF from cases (n = 12) and pediatric other neurologic disease controls (n = 54) were analyzed with VirScan with a subset (n = 9 and n = 50) validated by ELISA. RESULTS: mNGS detected EV in all samples positive by quantitative reverse transcription polymerase chain reaction (qRT-PCR) (n = 25). In qRT-PCR-negative samples (n = 35), mNGS found virus in 23% (n = 8, 3 CSF samples). Overall, mNGS enhanced EV detection from 42% (25/60) to 57% (33/60) (p-value = 0.013). VirScan and ELISA increased detection to 92% (11/12) compared with 46% (4/12) for CSF mNGS and qRT-PCR (p-value = 0.023). Phylogenetic analysis confirmed the EV-A71 strain clustered with a neurovirulent German EV-A71. A single amino acid substitution (S241P) in the EVA71 VP1 protein was exclusive to the CNS in one subject. CONCLUSION: mNGS with VirScan significantly increased the CNS detection of EVs relative to qRT-PCR, and the latter generated an antigenic profile of the acute EV-A71 immune response. Genomic analysis confirmed the close relation of the outbreak EV-A71 and neuroinvasive German EV-A71. A S241P substitution in VP1 was found exclusively in the CSF.

Unbiased Metagenomic Sequencing for Pediatric Meningitis in Bangladesh Reveals Neuroinvasive Chikungunya Virus Outbreak and Other Unrealized Pathogens.

The burden of meningitis in low-and-middle-income countries remains significant, but the infectious causes remain largely unknown, impeding institution of evidence-based treatment and prevention decisions. We conducted a validation and application study of unbiased metagenomic next-generation sequencing (mNGS) to elucidate etiologies of meningitis in Bangladesh. This RNA mNGS study was performed on cerebrospinal fluid (CSF) specimens from patients admitted in the largest pediatric hospital, a World Health Organization sentinel site, with known neurologic infections (n = 36), with idiopathic meningitis (n = 25), and with no infection (n = 30), and six environmental samples, collected between 2012 and 2018. We used the IDseq bioinformatics pipeline and machine learning to identify potentially pathogenic microbes, which we then confirmed orthogonally and followed up through phone/home visits. In samples with known etiology and without infections, there was 83% concordance between mNGS and conventional testing. In idiopathic cases, mNGS identified a potential bacterial or viral etiology in 40%. There were three instances of neuroinvasive Chikungunya virus (CHIKV), whose genomes were >99% identical to each other and to a Bangladeshi strain only previously recognized to cause febrile illness in 2017. CHIKV-specific qPCR of all remaining stored CSF samples from children who presented with idiopathic meningitis in 2017 (n = 472) revealed 17 additional CHIKV meningitis cases, exposing an unrecognized meningitis outbreak. Orthogonal molecular confirmation, case-based clinical data, and patient follow-up substantiated the findings. Case-control CSF mNGS surveys can complement conventional diagnostic methods to identify etiologies of meningitis, conduct surveillance, and predict outbreaks. The improved patient- and population-level data can inform evidence-based policy decisions.IMPORTANCE Globally, there are an estimated 10.6 million cases of meningitis and 288,000 deaths every year, with the vast majority occurring in low- and middle-income countries. In addition, many survivors suffer from long-term neurological sequelae. Most laboratories assay only for common bacterial etiologies using culture and directed PCR, and the majority of meningitis cases lack microbiological diagnoses, impeding institution of evidence-based treatment and prevention strategies. We report here the results of a validation and application study of using unbiased metagenomic sequencing to determine etiologies of idiopathic (of unknown cause) cases. This included CSF from patients with known neurologic infections, with idiopathic meningitis, and without infection admitted in the largest children's hospital of Bangladesh and environmental samples. Using mNGS and machine learning, we identified and confirmed an etiology (viral or bacterial) in 40% of idiopathic cases. We detected three instances of Chikungunya virus (CHIKV) that were >99% identical to each other and to a strain previously recognized to cause systemic illness only in 2017. CHIKV qPCR of all remaining stored 472 CSF samples from children who presented with idiopathic meningitis in 2017 at the same hospital uncovered an unrecognized CHIKV meningitis outbreak. CSF mNGS can complement conventional diagnostic methods to identify etiologies of meningitis, and the improved patient- and population-level data can inform better policy decisions.

Pan-viral serology implicates enteroviruses in acute flaccid myelitis.

Since 2012, the United States of America has experienced a biennial spike in pediatric acute flaccid myelitis (AFM)1-6. Epidemiologic evidence suggests non-polio enteroviruses (EVs) are a potential etiology, yet EV RNA is rarely detected in cerebrospinal fluid (CSF)2. CSF from children with AFM (n = 42) and other pediatric neurologic disease controls (n = 58) were investigated for intrathecal antiviral antibodies, using a phage display library expressing 481,966 overlapping peptides derived from all known vertebrate and arboviruses (VirScan). Metagenomic next-generation sequencing (mNGS) of AFM CSF RNA (n = 20 cases) was also performed, both unbiased sequencing and with targeted enrichment for EVs. Using VirScan, the viral family significantly enriched by the CSF of AFM cases relative to controls was Picornaviridae, with the most enriched Picornaviridae peptides belonging to the genus Enterovirus (n = 29/42 cases versus 4/58 controls). EV VP1 ELISA confirmed this finding (n = 22/26 cases versus 7/50 controls). mNGS did not detect additional EV RNA. Despite rare detection of EV RNA, pan-viral serology frequently identified high levels of CSF EV-specific antibodies in AFM compared with controls, providing further evidence for a causal role of non-polio EVs in AFM.

Kelch-like Protein 11 Antibodies in Seminoma-Associated Paraneoplastic Encephalitis.

A 37-year-old man with a history of seminoma presented with vertigo, ataxia, and diplopia. An autoantibody specific for kelch-like protein 11 (KLHL11) was identified with the use of programmable phage display. Immunoassays were used to identify KLHL11 IgG in 12 other men with similar neurologic features and testicular disease. Immunostaining of the patient's IgG on mouse brain tissue showed sparse but distinctive points of staining in multiple brain regions, with enrichment in perivascular and perimeningeal tissues. The onset of the neurologic syndrome preceded the diagnosis of seminoma in 9 of the 13 patients. An age-adjusted estimate of the prevalence of autoimmune KLHL11 encephalitis in Olmsted County, Minnesota, was 2.79 cases per 100,000 men. (Funded by the Rochester Epidemiology Project and others.).

Miniaturization and optimization of 384-well compatible RNA sequencing library preparation.

Preparation of high-quality sequencing libraries is a costly and time-consuming component of metagenomic next generation sequencing (mNGS). While the overall cost of sequencing has dropped significantly over recent years, the reagents needed to prepare sequencing samples are likely to become the dominant expense in the process. Furthermore, libraries prepared by hand are subject to human variability and needless waste due to limitations of manual pipetting volumes. Reduction of reaction volumes, combined with sub-microliter automated dispensing of reagents without consumable pipette tips, has the potential to provide significant advantages. Here, we describe the integration of several instruments, including the Labcyte Echo 525 acoustic liquid handler and the iSeq and NovaSeq Illumina sequencing platforms, to miniaturize and automate mNGS library preparation, significantly reducing the cost and the time required to prepare samples. Through the use of External RNA Controls Consortium (ERCC) spike-in RNAs, we demonstrated the fidelity of the miniaturized preparation to be equivalent to full volume reactions. Furthermore, detection of viral and microbial species from cell culture and patient samples was also maintained in the miniaturized libraries. For 384-well mNGS library preparations, we achieved cost savings of over 80% in materials and reagents alone, and reduced preparation time by 90% compared to manual approaches, without compromising quality or representation within the library.

Integrating host response and unbiased microbe detection for lower respiratory tract infection diagnosis in critically ill adults.

Lower respiratory tract infections (LRTIs) lead to more deaths each year than any other infectious disease category. Despite this, etiologic LRTI pathogens are infrequently identified due to limitations of existing microbiologic tests. In critically ill patients, noninfectious inflammatory syndromes resembling LRTIs further complicate diagnosis. To address the need for improved LRTI diagnostics, we performed metagenomic next-generation sequencing (mNGS) on tracheal aspirates from 92 adults with acute respiratory failure and simultaneously assessed pathogens, the airway microbiome, and the host transcriptome. To differentiate pathogens from respiratory commensals, we developed a rules-based model (RBM) and logistic regression model (LRM) in a derivation cohort of 20 patients with LRTIs or noninfectious acute respiratory illnesses. When tested in an independent validation cohort of 24 patients, both models achieved accuracies of 95.5%. We next developed pathogen, microbiome diversity, and host gene expression metrics to identify LRTI-positive patients and differentiate them from critically ill controls with noninfectious acute respiratory illnesses. When tested in the validation cohort, the pathogen metric performed with an area under the receiver-operating curve (AUC) of 0.96 (95% CI, 0.86-1.00), the diversity metric with an AUC of 0.80 (95% CI, 0.63-0.98), and the host transcriptional classifier with an AUC of 0.88 (95% CI, 0.75-1.00). Combining these achieved a negative predictive value of 100%. This study suggests that a single streamlined protocol offering an integrated genomic portrait of pathogen, microbiome, and host transcriptome may hold promise as a tool for LRTI diagnosis.

Chronic Meningitis Investigated via Metagenomic Next-Generation Sequencing.

Importance: Identifying infectious causes of subacute or chronic meningitis can be challenging. Enhanced, unbiased diagnostic approaches are needed. Objective: To present a case series of patients with diagnostically challenging subacute or chronic meningitis using metagenomic next-generation sequencing (mNGS) of cerebrospinal fluid (CSF) supported by a statistical framework generated from mNGS of control samples from the environment and from patients who were noninfectious. Design, Setting, and Participants: In this case series, mNGS data obtained from the CSF of 94 patients with noninfectious neuroinflammatory disorders and from 24 water and reagent control samples were used to develop and implement a weighted scoring metric based on z scores at the species and genus levels for both nucleotide and protein alignments to prioritize and rank the mNGS results. Total RNA was extracted for mNGS from the CSF of 7 participants with subacute or chronic meningitis who were recruited between September 2013 and March 2017 as part of a multicenter study of mNGS pathogen discovery among patients with suspected neuroinflammatory conditions. The neurologic infections identified by mNGS in these 7 participants represented a diverse array of pathogens. The patients were referred from the University of California, San Francisco Medical Center (n = 2), Zuckerberg San Francisco General Hospital and Trauma Center (n = 2), Cleveland Clinic (n = 1), University of Washington (n = 1), and Kaiser Permanente (n = 1). A weighted z score was used to filter out environmental contaminants and facilitate efficient data triage and analysis. Main Outcomes and Measures: Pathogens identified by mNGS and the ability of a statistical model to prioritize, rank, and simplify mNGS results. Results: The 7 participants ranged in age from 10 to 55 years, and 3 (43%) were female. A parasitic worm (Taenia solium, in 2 participants), a virus (HIV-1), and 4 fungi (Cryptococcus neoformans, Aspergillus oryzae, Histoplasma capsulatum, and Candida dubliniensis) were identified among the 7 participants by using mNGS. Evaluating mNGS data with a weighted z score-based scoring algorithm reduced the reported microbial taxa by a mean of 87% (range, 41%-99%) when taxa with a combined score of 0 or less were removed, effectively separating bona fide pathogen sequences from spurious environmental sequences so that, in each case, the causative pathogen was found within the top 2 scoring microbes identified using the algorithm. Conclusions and Relevance: Diverse microbial pathogens were identified by mNGS in the CSF of patients with diagnostically challenging subacute or chronic meningitis, including a case of subarachnoid neurocysticercosis that defied diagnosis for 1 year, the first reported case of CNS vasculitis caused by Aspergillus oryzae, and the fourth reported case of C dubliniensis meningitis. Prioritizing metagenomic data with a scoring algorithm greatly clarified data interpretation and highlighted the problem of attributing biological significance to organisms present in control samples used for metagenomic sequencing studies.

A novel cause of chronic viral meningoencephalitis: Cache Valley virus.

OBJECTIVE: Immunodeficient patients are particularly vulnerable to neuroinvasive infections that can be challenging to diagnose. Metagenomic next generation sequencing can identify unusual or novel microbes and is therefore well suited for investigating the etiology of chronic meningoencephalitis in immunodeficient patients. METHODS: We present the case of a 34-year-old man with X-linked agammaglobulinemia from Australia suffering from 3 years of meningoencephalitis that defied an etiologic diagnosis despite extensive conventional testing, including a brain biopsy. Metagenomic next generation sequencing of his cerebrospinal fluid and brain biopsy tissue was performed to identify a causative pathogen. RESULTS: Sequences aligning to multiple Cache Valley virus genes were identified via metagenomic next generation sequencing. Reverse transcription polymerase chain reaction and immunohistochemistry subsequently confirmed the presence of Cache Valley virus in the brain biopsy tissue. INTERPRETATION: Cache Valley virus, a mosquito-borne orthobunyavirus, has only been identified in 3 immunocompetent North American patients with acute neuroinvasive disease. The reported severity ranges from a self-limiting meningitis to a rapidly fatal meningoencephalitis with multiorgan failure. The virus has never been known to cause a chronic systemic or neurologic infection in humans. Cache Valley virus has also never previously been detected on the Australian continent. Our research subject traveled to North and South Carolina and Michigan in the weeks prior to the onset of his illness. This report demonstrates that metagenomic next generation sequencing allows for unbiased pathogen identification, the early detection of emerging viruses as they spread to new locales, and the discovery of novel disease phenotypes. Ann Neurol 2017;82:105-114.

Illuminating uveitis: metagenomic deep sequencing identifies common and rare pathogens.

BACKGROUND: Ocular infections remain a major cause of blindness and morbidity worldwide. While prognosis is dependent on the timing and accuracy of diagnosis, the etiology remains elusive in ~50 % of presumed infectious uveitis cases. The objective of this study is to determine if unbiased metagenomic deep sequencing (MDS) can accurately detect pathogens in intraocular fluid samples of patients with uveitis. METHODS: This is a proof-of-concept study, in which intraocular fluid samples were obtained from five subjects with known diagnoses, and one subject with bilateral chronic uveitis without a known etiology. Samples were subjected to MDS, and results were compared with those from conventional diagnostic tests. Pathogens were identified using a rapid computational pipeline to analyze the non-host sequences obtained from MDS. RESULTS: Unbiased MDS of intraocular fluid produced results concordant with known diagnoses in subjects with (n = 4) and without (n = 1) uveitis. Samples positive for Cryptococcus neoformans, Toxoplasma gondii, and herpes simplex virus 1 as tested by a Clinical Laboratory Improvement Amendments-certified laboratory were correctly identified with MDS. Rubella virus was identified in one case of chronic bilateral idiopathic uveitis. The subject's strain was most closely related to a German rubella virus strain isolated in 1992, one year before he developed a fever and rash while living in Germany. The pattern and the number of viral identified mutations present in the patient's strain were consistent with long-term viral replication in the eye. CONCLUSIONS: MDS can identify fungi, parasites, and DNA and RNA viruses in minute volumes of intraocular fluid samples. The identification of chronic intraocular rubella virus infection highlights the eye's role as a long-term pathogen reservoir, which has implications for virus eradication and emerging global epidemics.