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Meningitis and encephalitis are leading global causes of central nervous system (CNS) disability and mortality. Current diagnostic workflows remain inefficient, requiring costly pathogen-specific assays and sometimes invasive surgical procedures. Meningitis and encephalitis are leading causes of central nervous system (CNS) disease and often result in severe neurological compromise or death. Traditional diagnostic workflows largely rely on pathogen-specific tests, sometimes over days to weeks, whereas metagenomic next-generation sequencing (mNGS) profiles all nucleic acid in a sample. In this single-center, prospective study, 68 hospitalized patients with known ( n  = 44) or suspected ( n  = 24) CNS infections underwent mNGS from RNA and DNA to identify potential pathogens and also targeted sequencing of viruses using hybrid capture. Using a computational metagenomic classification pipeline based on KrakenUniq and BLAST, we detected pathogen nucleic acid in cerebrospinal fluid (CSF) from 22 subjects, 3 of whom had no clinical diagnosis by routine workup. Among subjects diagnosed with infection by serology and/or peripheral samples, we demonstrated the utility of mNGS to detect pathogen nucleic acid in CSF, importantly for the Ixodes scapularis tick-borne pathogens Powassan virus, Borrelia burgdorferi , and Anaplasma phagocytophilum . We also evaluated two methods to enhance the detection of viral nucleic acid, hybrid capture and methylated DNA depletion. Hybrid capture nearly universally increased viral read recovery. Although results for methylated DNA depletion were mixed, it allowed the detection of varicella-zoster virus DNA in two samples that were negative by standard mNGS. Overall, mNGS is a promising approach that can test for multiple pathogens simultaneously, with efficacy similar to that of pathogen-specific tests, and can uncover geographically relevant infectious CNS disease, such as tick-borne infections in New England. With further laboratory and computational enhancements, mNGS may become a mainstay of workup for encephalitis and meningitis. IMPORTANCE Meningitis and encephalitis are leading global causes of central nervous system (CNS) disability and mortality. Current diagnostic workflows remain inefficient, requiring costly pathogen-specific assays and sometimes invasive surgical procedures. Despite intensive diagnostic efforts, 40 to 60% of people with meningitis or encephalitis have no clear cause of CNS disease identified. As diagnostic uncertainty often leads to costly inappropriate therapies, the need for novel pathogen detection methods is paramount. Metagenomic next-generation sequencing (mNGS) offers the unique opportunity to circumvent these challenges using unbiased laboratory and computational methods. Here, we performed comprehensive mNGS from 68 prospectively enrolled patients with known ( n  = 44) or suspected ( n  = 24) CNS viral infection from a single center in New England and evaluated enhanced methods to improve the detection of CNS pathogens, including those not traditionally identified in the CNS by nucleic acid detection. Overall, our work helps elucidate how mNGS can become integrated into the diagnostic toolkit for CNS infections.

Trillions of microbes such as bacteria, fungi, and viruses exist in the healthy human gut microbiome. Although gut bacterial dysbiosis has been extensively studied in multiple sclerosis (MS), the significance of the fungal microbiome (mycobiome) is an understudied and neglected part of the intestinal microbiome in MS. The aim of this study was to characterize the gut mycobiome of patients with relapsing-remitting multiple sclerosis (RRMS), compare it to healthy controls, and examine its association with changes in the bacterial microbiome. We characterized and compared the mycobiome of 20 RRMS patients and 33 healthy controls (HC) using Internal Transcribed Spacer 2 (ITS2) and compared mycobiome interactions with the bacterial microbiome using 16S rRNA sequencing. Our results demonstrate an altered mycobiome in RRMS patients compared with HC. RRMS patients showed an increased abundance of Basidiomycota and decreased Ascomycota at the phylum level with an increased abundance of Candida and Epicoccum genera along with a decreased abundance of Saccharomyces compared to HC. We also observed an increased ITS2/16S ratio, altered fungal and bacterial associations, and altered fungal functional profiles in MS patients compared to HC. This study demonstrates that RRMS patients had a distinct mycobiome with associated changes in the bacterial microbiome compared to HC. There is an increased fungal to bacterial ratio as well as more diverse fungal-bacterial interactions in RRMS patients compared to HC. Our study is the first step towards future studies in delineating the mechanisms through which the fungal microbiome can influence MS disease.

Although gut microbiome dysbiosis is implicated in the pathobiology of multiple sclerosis (MS), the role of the oral microbiome (OM), the second largest microbiome, remains poorly understood. Additionally, while the salivary metabolome has been linked to other neurodegenerative diseases; its role in people with Relapsing-Remitting MS (pwRRMS), the most prevalent form of MS, is unknown. Combining shotgun metagenomics with untargeted metabolomics, we identified a reduced abundance of several early colonizing species including Streptococcus and Actinomyces in pwRRMS and an enrichment of bacteria with pathogenic potential including Fusobacterium nucleatum, Porphyromonas gingivalis , and several Prevotella species. pwRRMS had an altered metabolite profile including a decreased hypotaurine compared to healthy controls. Thus we report altered oral microbiome and metabolome in pwRRMS which might contribute to MS pathobiology. These findings offer potential microbiome-metabolome based diagnostic biomarkers for MS and pave the way for novel therapeutic interventions to improve disease management and patient outcomes.

Immune checkpoint inhibitors (ICIs) are an important class of cancer treatment. Endocrine immune-related adverse events (E-irAEs) account for a significant proportion of irAEs in ICI-treated patients. Diagnosing E-irAEs accurately and timely can be challenging in the absence of clear categorization and standardization across oncology, endocrinology and other specialties. While existing guidelines provide some broad directions to diagnosis and management, they lack clarity on irAE-specific symptom evaluation and work-up, as well as assessment of severity. These limitations can then impact triage, time-sensitive management and care escalation to specialists such as oncoendocrinologists. The objective of this study was to develop consensus-based statements on disease definitions for E-irAEs.A core working group of endocrinologists with expertise in the oncoendocrinology field drafted a survey with statements outlining the general approach to E-irAEs, disease definition and management approach of six specific diagnoses: ir-thyroiditis thyrotoxic phase, ir-thyroiditis hypothyroidism, ir-Graves’ disease, ir-hypophysitis, ir-adrenalitis and ir-type 1 diabetes mellitus. Severity grading tables were drafted for three disease categories—“thyroid”, “pituitary and adrenal”, and “diabetes mellitus”. A two-round modified Delphi process, using the RAND/University of California Los Angeles (RAND/UCLA) Appropriateness Method, was employed. In this process, a 25-member voting panel consisting of endocrinologists, oncologists and other specialists and healthcare providers with experience in management of ICI-treated patients and irAEs was recruited. The panel rated anonymously on usability, accuracy, appropriateness or agreement of 41 items on a 9-point scale in Survey 1, after which a meeting was convened. Statements were modified based on voting results from Survey 1 and Meeting 1, and the process was repeated in Survey 2 and Meeting 2. At the end of this process, consensus was achieved for all statements.Our study findings address the gap in standardized nomenclature, clinical, laboratory and radiological evaluations, and management principles of E-irAEs. With consensus achieved from a panel of experts from a variety of disciplines, we anticipate that the statements can form the basis for standardization of the diagnostic process and improvement of patient care.

A 57-year-old-woman with a history of gastric bypass presented with hypoesthesia, paresthesia, and weakness in the arms and legs. Studies for somatosensory evoked potentials were consistent with disruption of central conduction. A diagnostic test was performed.

A 76-year-old man was admitted to the hospital because of weakness and fever. Seventeen days earlier, he had presented with fatigue, weight loss, and guaiac-positive stool. Within 12 hours after admission, altered mental status developed. A diagnostic test was performed.

Factors regulating self-antigen directed immune-responses in autoimmunity are poorly understood. Signal regulatory protein gamma (SIRPγ) is a human T-cell specific protein with genetic variants associated with type 1 diabetes (T1D). SIRPγ's function in the immune system remains unclear. We show that T1D and relapsing remitting multiple sclerosis (RRMS) subjects have significantly greater frequency of rs2281808 T genetic variant, that correlates with reduced SIRPγ-expression in T-cells. Importantly, reduced SIRPγ-expression in RRMS and T1D subjects was not restricted to T variant, suggesting SIRPγ-expression is also regulated by disease specific factors in autoimmunity. Interestingly, increased frequencies of SIRPγlow T-cells in RRMS and T1D positively correlated with proinflammatory molecules from T-cells. Finally, we show that SIRPγlow T-cells have enhanced pathogenecity in vivo in a GVHD model. These findings suggest that decreased-SIRPγ expression, either determined by genetic variants or through peripherally acquired processes, may have a mechanistic link to autoimmunity through induction of hyperactive T-cells.

The optimal treatment for neurosarcoidosis myelitis is uncertain. We characterize incident neurosarcoidosis myelitis and assess treatment response by MRI and clinical scales. Incident probable or definite neurosarcoidosis myelitis in adults was retrospectively identified from 13 academic medical centers. Cases were analyzed by initial treatment. The primary outcome was T1 post-contrast gadolinium enhancement resolution at 6 months post-treatment. Secondary outcomes were changes in modified Rankin scale (mRS) and Expanded Disability Status Scale (EDSS) from nadir to final follow-up. Two hundred two patients were identified (median diagnosis age: 47 years (IQR 39-55); male: female 1.3:1). Median nadir mRS and EDSS were 2 (IQR 2-3) and 4 (IQR 2.5-6). At initial treatment, 129 (63.9%) received prolonged corticosteroids ≥ 4 weeks (group A ), 36 (17.8%) received corticosteroids < 4 weeks (B ), 21 (10.4%) received corticosteroids plus sarcoidosis-directed immunosuppressant (E), and 16 (7.9%) received corticosteroids plus non-sarcoidosis-directed agents (F). In 167 cases with sufficient imaging, there were no significant differences in contrast enhancement resolution at 6 months (A 27/106 (25.5%), B 9/28 (32.1%), E 5/19 (26.3%), F 5/14 (35.7%); Fisher's exact p = 0.76). There were no significant differences in changes in mRS or EDSS among treatment groups (Kruskal-Wallis p = 0.69 and 0.63, respectively) after median follow-up of 46.5 months (IQR 18-91.3). Different initial immunosuppression strategies did not correlate with MRI contrast enhancement resolution at 6 months or clinical scales (mRS, EDSS). However, conclusions are limited by retrospective design, imbalanced cohorts, and insensitivity of binary MRI outcomes and available clinical scales for treatment response in neurosarcoidosis.

Encephalitis has various etiologies, but viral infections and autoimmune disorders are the most commonly identified. Clinical signs, geographical clues, and diagnostic testing—including cerebrospinal fluid abnormalities and magnetic resonance imaging abnormalities—can be helpful in identifying the cause. Certain forms of encephalitis have specific treatments; hence, establishing a diagnosis rapidly and accurately is crucial. Here, we describe the clinical approach to diagnosing several common etiologies of encephalitis as well as treatment strategies.

Objective Multiple sclerosis (MS) is a chronic autoimmune disorder characterized by inflammation, demyelination, and neurological impairment. While the gut microbiota's role in MS is extensively studied, the association between the oral microbiota and MS remains underexplored, particularly in North American cohorts. This study aimed to investigate the microbiota (bacterial) composition as well as functional pathways and immune profiles of the oral cavity in 60 patients with relapsing–remitting MS (RRMS), stratified by treatment status, compared to 44 healthy controls (HC). Methods Unstimulated saliva was collected for genomic DNA extraction and salivary cytokine quantification. Oral bacterial composition and diversity were analyzed using 16S rRNA sequencing, with functional pathways inferred using PICRUSt2. Salivary cytokine levels were measured via multiplex immunoassays. LEfSe and random forest models identified key discriminatory taxa, and correlations between microbiota and cytokines were assessed using Spearman's rank analysis. Results RRMS patients exhibited distinct microbial communities compared to HC and a higher Bacteroidota to Firmicutes ratio. Key taxa such as Campylobacter, Lachnoanaerobaculum, and Porphyromonas were enriched in RRMS. Functional profiling revealed 49 differentially abundant pathways, including the enrichment of lipopolysaccharide biosynthesis in MS. Elevated levels of IFN‐γ, IL‐6, and other cytokines correlated with the altered microbiome. IL‐21, elevated in HC, correlated with anti‐inflammatory pathways, suggesting a protective role in immune homeostasis. Interpretation This study provides, for the first time, insights into oral microbiome‐host interactions in North American RRMS patients, underscoring the interplay between microbial dysbiosis, functional pathways, and immune dysregulation. The oral microbiome shows potential as a biomarker for MS‐related immune alterations.