An ANXA11 P93S variant dysregulates TDP-43 and causes corticobasal syndrome.

As genetic testing has become more accessible and affordable, variants of uncertain significance (VUS) are increasingly identified, and determining whether these variants play causal roles in disease is a major challenge. The known disease-associated Annexin A11 (ANXA11) mutations result in ANXA11 aggregation, alterations in lysosomal-RNA granule co-trafficking, and TDP-43 mis-localization and present as amyotrophic lateral sclerosis or frontotemporal dementia. We identified a novel VUS in ANXA11 (P93S) in a kindred with corticobasal syndrome and unique radiographic features that segregated with disease. We then queried neurodegenerative disorder clinic databases to identify the phenotypic spread of ANXA11 mutations. Multi-modal computational analysis of this variant was performed and the effect of this VUS on ANXA11 function and TDP-43 biology was characterized in iPSC-derived neurons. Single-cell sequencing and proteomic analysis of iPSC-derived neurons and microglia were used to determine the multiomic signature of this VUS. Mutations in ANXA11 were found in association with clinically diagnosed corticobasal syndrome, thereby establishing corticobasal syndrome as part of ANXA11 clinical spectrum. In iPSC-derived neurons expressing mutant ANXA11, we found decreased colocalization of lysosomes and decreased neuritic RNA as well as decreased nuclear TDP-43 and increased formation of cryptic exons compared to controls. Multiomic assessment of the P93S variant in iPSC-derived neurons and microglia indicates that the pathogenic omic signature in neurons is modest compared to microglia. Additionally, omic studies reveal that immune dysregulation and interferon signaling pathways in microglia are central to disease. Collectively, these findings identify a new pathogenic variant in ANXA11, expand the range of clinical syndromes caused by ANXA11 mutations, and implicate both neuronal and microglia dysfunction in ANXA11 pathophysiology. This work illustrates the potential for iPSC-derived cellular models to revolutionize the variant annotation process and provides a generalizable approach to determining causality of novel variants across genes.

Prognostic performance of blood neurofilament light chain protein in hospitalized COVID-19 patients without major central nervous system manifestations: an individual participant data meta-analysis.

BACKGROUND AND AIMS: To investigate the prognostic value of blood neurofilament light chain protein (NfL) levels in the acute phase of coronavirus disease 2019 (COVID-19). METHODS: We conducted an individual participant data (IPD) meta-analysis after screening on MEDLINE and Scopus to May 23rd 2022. We included studies with hospitalized adult COVID-19 patients without major COVID-19-associated central nervous system (CNS) manifestations and with a measurement of blood NfL in the acute phase as well as data regarding at least one clinical outcome including intensive care unit (ICU) admission, need of mechanical ventilation (MV) and death. We derived the age-adjusted measures NfL Z scores and conducted mixed-effects modelling to test associations between NfL Z scores and other variables, encompassing clinical outcomes. Summary receiver operating characteristic curves (SROCs) were used to calculate the area under the curve (AUC) for blood NfL. RESULTS: We identified 382 records, of which 7 studies were included with a total of 669 hospitalized COVID-19 cases (mean age 66.2 ± 15.0 years, 68.1% males). Median NfL Z score at admission was elevated compared to the age-corrected reference population (2.37, IQR: 1.13-3.06, referring to 99th percentile in healthy controls). NfL Z scores were significantly associated with disease duration and severity. Higher NfL Z scores were associated with a higher likelihood of ICU admission, need of MV, and death. SROCs revealed AUCs of 0.74, 0.80 and 0.71 for mortality, need of MV and ICU admission, respectively. CONCLUSIONS: Blood NfL levels were elevated in the acute phase of COVID-19 patients without major CNS manifestations and associated with clinical severity and poor outcome. The marker might ameliorate the performance of prognostic multivariable algorithms in COVID-19.

Chromosomal microarray analysis supplements exome sequencing to diagnose children with suspected inborn errors of immunity.

Purpose: Though copy number variants (CNVs) have been suggested to play a significant role in inborn errors of immunity (IEI), the precise nature of this role remains largely unexplored. We sought to determine the diagnostic contribution of CNVs using genome-wide chromosomal microarray analysis (CMA) in children with IEI. Methods: We performed exome sequencing (ES) and CMA for 332 unrelated pediatric probands referred for evaluation of IEI. The analysis included primary, secondary, and incidental findings. Results: Of the 332 probands, 134 (40.4%) received molecular diagnoses. Of these, 116/134 (86.6%) were diagnosed by ES alone. An additional 15/134 (11.2%) were diagnosed by CMA alone, including two likely de novo changes. Three (2.2%) participants had diagnostic molecular findings from both ES and CMA, including two compound heterozygotes and one participant with two distinct diagnoses. Half of the participants with CMA contribution to diagnosis had CNVs in at least one non-immune gene, highlighting the clinical complexity of these cases. Overall, CMA contributed to 18/134 diagnoses (13.4%), increasing the overall diagnostic yield by 15.5% beyond ES alone. Conclusion: Pairing ES and CMA can provide a comprehensive evaluation to clarify the complex factors that contribute to both immune and non-immune phenotypes. Such a combined approach to genetic testing helps untangle complex phenotypes, not only by clarifying the differential diagnosis, but in some cases by identifying multiple diagnoses contributing to the overall clinical presentation.

Neurofilament light chain in cerebrospinal fluid as a novel biomarker in evaluating both clinical severity and therapeutic response in Niemann-Pick disease type C1.

PURPOSE: Niemann-Pick disease type C1 (NPC1) is a neurodegenerative lysosomal disorder caused by pathogenic variants in NPC1. Disease progression is monitored using the NPC Neurological Severity Scale, but there are currently no established validated or qualified biomarkers. Neurofilament light chain (NfL) is being investigated as a biomarker in multiple neurodegenerative diseases. METHODS: Cross-sectional and longitudinal cerebrospinal fluid (CSF) samples were obtained from 116 individuals with NPC1. NfL levels were measured using a solid-phase sandwich enzyme-linked immunosorbent assay and compared with age-appropriate non-NPC1 comparison samples. RESULTS: Median levels of NfL were elevated at baseline (1152 [680-1840] pg/mL) in NPC1 compared with controls (167 [82-372] pg/mL; P < .001). Elevated NfL levels were associated with more severe disease as assessed by both the 17-domain and 5-domain NPC Neurological Severity Score. Associations were also observed with ambulation, fine motor, speech, and swallowing scores. Although treatment with the investigational drug 2-hydroxypropyl-ß-cyclodextrin (adrabetadex) did not decrease CSF NfL levels, miglustat therapy over time was associated with a decrease (odds ratio = 0.77, 95% CI = 0.62-0.96). CONCLUSION: CSF NfL levels are increased in individuals with NPC1, associated with clinical disease severity, and decreased with miglustat therapy. These data suggest that NfL is a biomarker that may have utility in future therapeutic trials.

Molecular models of multiple sclerosis severity identify heterogeneity of pathogenic mechanisms.

While autopsy studies identify many abnormalities in the central nervous system (CNS) of subjects dying with neurological diseases, without their quantification in living subjects across the lifespan, pathogenic processes cannot be differentiated from epiphenomena. Using machine learning (ML), we searched for likely pathogenic mechanisms of multiple sclerosis (MS). We aggregated cerebrospinal fluid (CSF) biomarkers from 1305 proteins, measured blindly in the training dataset of untreated MS patients (N = 129), into models that predict past and future speed of disability accumulation across all MS phenotypes. Healthy volunteers (N = 24) data differentiated natural aging and sex effects from MS-related mechanisms. Resulting models, validated (Rho 0.40-0.51, p < 0.0001) in an independent longitudinal cohort (N = 98), uncovered intra-individual molecular heterogeneity. While candidate pathogenic processes must be validated in successful clinical trials, measuring them in living people will enable screening drugs for desired pharmacodynamic effects. This will facilitate drug development making, it hopefully more efficient and successful.

Current Status and Future Opportunities in Modeling Clinical Characteristics of Multiple Sclerosis.

Development of effective treatments requires understanding of disease mechanisms. For diseases of the central nervous system (CNS), such as multiple sclerosis (MS), human pathology studies and animal models tend to identify candidate disease mechanisms. However, these studies cannot easily link the identified processes to clinical outcomes, such as MS severity, required for causality assessment of candidate mechanisms. Technological advances now allow the generation of thousands of biomarkers in living human subjects, derived from genes, transcripts, medical images, and proteins or metabolites in biological fluids. These biomarkers can be assembled into computational models of clinical value, provided such models are generalizable. Reproducibility of models increases with the technical rigor of the study design, such as blinding, control implementation, the use of large cohorts that encompass the entire spectrum of disease phenotypes and, most importantly, model validation in independent cohort(s). To facilitate the growth of this important research area, we performed a meta-analysis of publications (n = 302) that model MS clinical outcomes extracting effect sizes, while also scoring the technical quality of the study design using predefined criteria. Finally, we generated a Shiny-App-based website that allows dynamic exploration of the data by selective filtering. On average, the published studies fulfilled only one of the seven criteria of study design rigor. Only 15.2% of the studies used any validation strategy, and only 8% used the gold standard of independent cohort validation. Many studies also used small cohorts, e.g., for magnetic resonance imaging (MRI) and blood biomarker predictors, the median sample size was <100 subjects. We observed inverse relationships between reported effect sizes and the number of study design criteria fulfilled, expanding analogous reports from non-MS fields, that studies that fail to limit bias overestimate effect sizes. In conclusion, the presented meta-analysis represents a useful tool for researchers, reviewers, and funders to improve the design of future modeling studies in MS and to easily compare new studies with the published literature. We expect that this will accelerate research in this important area, leading to the development of robust models with proven clinical value.

Enhancing the clinical value of serum neurofilament light chain measurement.

BACKGROUNDSerum neurofilament light chain (sNFL) is becoming an important biomarker of neuro-axonal injury. Though sNFL correlates with CSF NFL (cNFL), 40% to 60% of variance remains unexplained. We aimed to mathematically adjust sNFL to strengthen its clinical value.METHODSWe measured NFL in a blinded fashion in 1138 matched CSF and serum samples from 571 patients. Multiple linear regression (MLR) models constructed in the training cohort were validated in an independent cohort.RESULTSAn MLR model that included age, blood urea nitrogen, alkaline phosphatase, creatinine, and weight improved correlations of cNFL with sNFL (from R2 = 0.57 to 0.67). Covariate adjustment significantly improved the correlation of sNFL with the number of contrast-enhancing lesions (from R2 = 0.18 to 0.28; 36% improvement) in the validation cohort of patients with multiple sclerosis (MS). Unexpectedly, only sNFL, but not cNFL, weakly but significantly correlated with cross-sectional MS severity outcomes. Investigating 2 nonoverlapping hypotheses, we showed that patients with proportionally higher sNFL to cNFL had higher clinical and radiological evidence of spinal cord (SC) injury and probably released NFL from peripheral axons into blood, bypassing the CSF.CONCLUSIONsNFL captures 2 sources of axonal injury, central and peripheral, the latter reflecting SC damage, which primarily drives disability progression in MS.TRIAL REGISTRATIONClinicalTrials.gov NCT00794352.FUNDINGDivision of Intramural Research, National Institute of Allergy and Infectious Diseases, NIH (AI001242 and AI001243).

Prognostic value of serum/plasma neurofilament light chain for COVID-19-associated mortality.

OBJECTIVE: Given the continued spread of coronavirus 2, the early predictors of coronavirus disease 19 (COVID-19) associated mortality might improve patients' outcomes. Increased levels of circulating neurofilament light chain (NfL), a biomarker of neuronal injury, have been observed in severe COVID-19 patients. We investigated whether NfL provides non-redundant clinical value to previously identified predictors of COVID-19 mortality. METHODS: We measured serum or plasma NfL concentrations in a blinded fashion in 3 cohorts totaling 338 COVID-19 patients. RESULTS: In cohort 1, we found significantly elevated NfL levels only in critically ill COVID-19 patients. Longitudinal cohort 2 data showed that NfL is elevated late in the course of the disease, following the two other prognostic markers of COVID-19: decrease in absolute lymphocyte count (ALC) and increase in lactate dehydrogenase (LDH). Significant correlations between ALC and LDH abnormalities and subsequent rise of NfL implicate that the multi-organ failure is the most likely cause of neuronal injury in severe COVID-19 patients. The addition of NfL to age and gender in cohort 1 significantly improved the accuracy of mortality prediction and these improvements were validated in cohorts 2 and 3. INTERPRETATION: A substantial increase in serum/plasma NfL reproducibly enhanced COVID-19 mortality prediction. Combined with other prognostic markers, such as ALC and LDH that are routinely measured in ICU patients, NfL measurements might be useful to identify the patients at a high risk of COVID-19-associated mortality, who might still benefit from escalated care.

Drug library screen identifies inhibitors of toxic astrogliosis.

BACKGROUND: Multiple sclerosis (MS) is a chronic neuroinflammatory disorder, in which activated immune cells directly or indirectly induce demyelination and axonal degradation. Inflammatory stimuli also change the phenotype of astrocytes, making them neurotoxic. The resulting 'toxic astrocyte' phenotype has been observed in animal models of neuroinflammation and in MS lesions. Proteins secreted by toxic astrocytes are elevated in the cerebrospinal fluid (CSF) of MS patients and reproducibly correlate with the rates of accumulation of neurological disability and brain atrophy. This suggests a pathogenic role for neurotoxic astrocytes in MS. METHODS: Here, we applied a commercially available library of small molecules that are either Food and Drug Administration-approved or in clinical development to an in vitro model of toxic astrogliosis to identify drugs and signaling pathways that inhibit inflammatory transformation of astrocytes to a neurotoxic phenotype. RESULTS: Inhibitors of three pathways related to the endoplasmic reticulum stress: (1) proteasome, (2) heat shock protein 90 and (3) mammalian target of rapamycin reproducibly decreased inflammation-induced conversion of astrocytes to toxic phenotype. Dantrolene, an anti-spasticity drug that inhibits calcium release through ryanodine receptors expressed in the endoplasmic reticulum of central nervous system cells, also exerted inhibitory effect at in vivo achievable concentrations. Finally, we established CSF SERPINA3 as a relevant pharmacodynamic marker for inhibiting toxic astrocytes in clinical trials. CONCLUSION: Drug library screening provides mechanistic insight into the generation of toxic astrocytes and identifies candidates for immediate proof-of-principle clinical trial(s).

Prognostic Value of Serum/Plasma Neurofilament Light Chain for COVID-19 Associated Mortality.

Given the continued spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), early predictors of coronavirus disease 19 (COVID-19) mortality might improve patients’ outcomes. Increased levels of circulating neurofilament light chain (NfL), a biomarker of neuro-axonal injury, have been observed in patients with severe COVID-19. We investigated whether NfL provides non-redundant clinical value to previously identified predictors of COVID-19 mortality. We measured serum or plasma NfL concentrations in a blinded fashion in 3 cohorts totaling 338 COVID-19 patients. In cohort 1, we found significantly elevated NfL levels only in critically ill COVID-19 patients compared to healthy controls. Longitudinal cohort 2 data showed that NfL is elevated late in the course of the disease, following two other prognostic markers of COVID-19: decrease in absolute lymphocyte count (ALC) and increase in lactate dehydrogenase (LDH). Significant correlations between LDH and ALC abnormalities and subsequent rise of NfL implicate multi-organ failure as a likely cause of neuronal injury at the later stages of COVID-19. Addition of NfL to age and gender in cohort 1 significantly improved the accuracy of mortality prediction and these improvements were validated in cohorts 2 and 3. In conclusion, although substantial increase in serum/plasma NfL reproducibly enhances COVID-19 mortality prediction, NfL has clinically meaningful prognostic value only close to death, which may be too late to alter medical management. When combined with other prognostic biomarkers, rising longitudinal NfL measurements triggered by LDH and ALC abnormalities would identify patients at risk of COVID-19 associated mortality who might still benefit from escalated care.

Machine learning-optimized Combinatorial MRI scale (COMRISv2) correlates highly with cognitive and physical disability scales in Multiple Sclerosis patients.

Composite MRI scales of central nervous system tissue destruction correlate stronger with clinical outcomes than their individual components in multiple sclerosis (MS) patients. Using machine learning (ML), we previously developed Combinatorial MRI scale (COMRISv1) solely from semi-quantitative (semi-qMRI) biomarkers. Here, we asked how much better COMRISv2 might become with the inclusion of quantitative (qMRI) volumetric features and employment of more powerful ML algorithm. The prospectively acquired MS patients, divided into training (n = 172) and validation (n = 83) cohorts underwent brain MRI imaging and clinical evaluation. Neurological examination was transcribed to NeurEx™ App that automatically computes disability scales. qMRI features were computed by lesion-TOADS algorithm. Modified random forest pipeline selected biomarkers for optimal model(s) in the training cohort. COMRISv2 models validated moderate correlation with cognitive disability [Spearman Rho = 0.674; Lin's concordance coefficient (CCC) = 0.458; p < 0.001] and strong correlations with physical disability (Spearman Rho = 0.830-0.852; CCC = 0.789-0.823; p < 0.001). The NeurEx led to the strongest COMRISv2 model. Addition of qMRI features enhanced performance only of cognitive disability model, likely because semi-qMRI biomarkers measure infratentorial injury with greater accuracy. COMRISv2 models predict most granular clinical scales in MS with remarkable criterion validity, expanding scientific utilization of cohorts with missing clinical data.

Confounder-adjusted MRI-based predictors of multiple sclerosis disability.

Introduction: Both aging and multiple sclerosis (MS) cause central nervous system (CNS) atrophy. Excess brain atrophy in MS has been interpreted as "accelerated aging." Current paper tests an alternative hypothesis: MS causes CNS atrophy by mechanism(s) different from physiological aging. Thus, subtracting effects of physiological confounders on CNS structures would isolate MS-specific effects. Methods: Standardized brain MRI and neurological examination were acquired prospectively in 646 participants enrolled in ClinicalTrials.gov Identifier: NCT00794352 protocol. CNS volumes were measured retrospectively, by automated Lesion-TOADS algorithm and by Spinal Cord Toolbox, in a blinded fashion. Physiological confounders identified in 80 healthy volunteers were regressed out by stepwise multiple linear regression. MS specificity of confounder-adjusted MRI features was assessed in non-MS cohort (n = 158). MS patients were randomly split into training (n = 277) and validation (n = 131) cohorts. Gradient boosting machine (GBM) models were generated in MS training cohort from unadjusted and confounder-adjusted CNS volumes against four disability scales. Results: Confounder adjustment highlighted MS-specific progressive loss of CNS white matter. GBM model performance decreased substantially from training to cross-validation, to independent validation cohorts, but all models predicted cognitive and physical disability with low p-values and effect sizes that outperform published literature based on recent meta-analysis. Models built from confounder-adjusted MRI predictors outperformed models from unadjusted predictors in the validation cohort. Conclusion: GBM models from confounder-adjusted volumetric MRI features reflect MS-specific CNS injury, and due to stronger correlation with clinical outcomes compared to brain atrophy these models should be explored in future MS clinical trials.

Cerebrospinal Fluid Biomarkers of Myeloid and Glial Cell Activation Are Correlated With Multiple Sclerosis Lesional Inflammatory Activity.

Multiple sclerosis (MS)-related inflammation can be divided into lesional activity, mediated by immune cells migrating from the periphery to the central nervous system (CNS) and non-lesional activity, mediated by inflammation compartmentalized to CNS tissue. Lesional inflammatory activity, reflected by contrast-enhancing lesions (CELs) on the magnetic resonance imaging (MRI), is effectively inhibited by current disease modifying therapies (DMTs). While, the effect of DMTs on non-lesional inflammatory activity is currently unknown. Reliable and simultaneous measurements of both lesional and non-lesional MS activity is necessary to understand their contribution to CNS tissue destruction in individual patients. We previously demonstrated that CNS compartmentalized inflammation can be measured by combined quantification of cerebrospinal fluid (CSF) immune cells and cell-specific soluble markers. The goal of this study is to develop and validate a CSF-biomarker-based molecular surrogate of MS lesional activity. The training cohort was dichotomized into active (CELs > 1 or clinical relapse) and inactive lesional activity (no CELs or relapse) groups. Matched CSF and serum samples were analyzed for 20 inflammatory and axonal damage biomarkers in a blinded fashion. Only the findings from the training cohort with less than 0.1% probability of false positive (i.e., p < 0.001) were validated in an independent validation cohort. MS patients with lesional activity have elevated IL-12p40, CHI3L1, TNFα, TNFß, and IL-10, with the first two having the strongest effects and validated statistically-significant association with lesional activity in an independent validation cohort. Marker of axonal damage, neurofilament light (NfL), measured in CSF (cNfL) was also significantly elevated in MS patients with active lesions. NfL measured in serum (sNfL) did not differentiate the two MS subgroups with pre-determined significance, (p = 0.0690) even though cCSF and sNfL correlated (Rho = 0.66, p < 0.0001). Finally, the additive model of IL12p40 and CHI3L1 outperforms any biomarker discretely. IL12p40 and CHI3L1, released predominantly by immune cells of myeloid lineage are reproducibly the best CSF biomarkers of MS lesional activity. The residuals from the IL12p40/CHI3L1-cNfL correlations may identify MS patients with more destructive inflammation or contributing neurodegeneration.

Seizure phenotype in CLN3 disease and its relation to other neurologic outcome measures.

CLN3 disease is a pediatric neurodegenerative condition wherein seizures are common. The most common disease-causing variant is an ~1-kb deletion in CLN3. We investigated seizure phenotype in relation to genotype and to adaptive behavior, MR spectroscopy and CSF biochemical markers in a CLN3 cohort. We performed seizure phenotyping using clinical history, EEG, and the Unified Batten Disease Rating Scale (UBDRS) seizure score. We assessed correlations of seizure severity with disease severity (UBDRS capability), adaptive behavior composite score (ABC; Vineland-3), glutamate+glutamine+GABA and N-acetylaspartate+N-acetylaspartyl glutamate (MR spectroscopy), and CSF neurofilament light chain (NEFL) levels. In 20 participants, median age was 10.7 years (IQR = 7.8). Eighteen completed baseline EEG; 12 had a 1-year follow-up. Seizures were reported in 14 (8 1-kb deletion homozygotes), with median age at onset of 10.0 (IQR = 6.8). Epileptiform discharges were noted in 15 (9 homozygotes). Bilateral tonic clonic (n = 11) and nonmotor seizures (n = 7) were most common. UBDRS seizure score correlated with age (rp = 0.50; [0.08,0.77]; P = .02), UBDRS capability (rp = -0.57; [-0.81,-0.17]; P = .009) and ABC (rp = -0.66; [-0.85,-0.31]; P = .001) scores, glutamate+glutamine+GABA (rp = -0.54; [-0.80,-0.11]; P = .02) and N-acetylaspartate+N-acetylaspartyl glutamate (rp = -0.54; [-0.80,-0.11]; P = .02), and CSF NEFL (rp = 0.65; [0.29,0.85]; P = .002) levels. After controlling for age, correlations with ABC and CSF NEFL remained significant. In our CLN3 cohort, seizures and epileptiform discharges were frequent and often started by age 10 years without significant difference between genotypes. ABC and CSF NEFL correlate with UBDRS seizure score, reflecting the role of seizures in the neurodegenerative process. Longitudinal evaluations in a larger cohort are needed to confirm these findings.

Smartphone-based symbol-digit modalities test reliably captures brain damage in multiple sclerosis.

As the burden of neurodegenerative diseases increases, time-limited clinic encounters do not allow quantification of complex neurological functions. Patient-collected digital biomarkers may remedy this, if they provide reliable information. However, psychometric properties of digital tools remain largely un-assessed. We developed a smartphone adaptation of the cognitive test, the Symbol-Digit Modalities Test (SDMT) by randomizing the test's symbol-number codes and testing sequences. The smartphone SDMT showed comparable psychometric properties in 154 multiple sclerosis (MS) patients and 39 healthy volunteers (HV). E.g., smartphone SDMT achieved slightly higher correlations with cognitive subscores of neurological examinations and with brain injury measured by MRI (R2 = 0.75, Rho = 0.83, p < 0.0001) than traditional SDMT. Mathematical adjustment for motoric disability of the dominant hand, measured by another smartphone test, compensates for the disadvantage of touch-based test. Averaging granular home measurements of the digital biomarker also increases accuracy of identifying true neurological decline.

Assessment of Smartphone-Based Spiral Tracing in Multiple Sclerosis Reveals Intra-Individual Reproducibility as a Major Determinant of the Clinical Utility of the Digital Test.

Technological advances, lack of medical professionals, high cost of face-to-face encounters, and disasters such as the COVID-19 pandemic fuel the telemedicine revolution. Numerous smartphone apps have been developed to measure neurological functions. However, their psychometric properties are seldom determined. It is unclear which designs underlie the eventual clinical utility of the smartphone tests. We have developed the smartphone Neurological Function Tests Suite (NeuFun-TS) and are systematically evaluating their psychometric properties against the gold standard of complete neurological examination digitalized into the NeurExTM app. This article examines the fifth and the most complex NeuFun-TS test, the "Spiral tracing." We generated 40 features in the training cohort (22 healthy donors [HD] and 89 patients with multiple sclerosis [MS]) and compared their intraclass correlation coefficient, fold change between HD and MS, and correlations with relevant clinical and imaging outcomes. We assembled the best features into machine-learning models and examined their performance in the independent validation cohort (45 patients with MS). We show that by involving multiple neurological functions, complex tests such as spiral tracing are susceptible to intra-individual variations, decreasing their reproducibility and clinical utility. Simple tests, reproducibly measuring single function(s) that can be aggregated to increase sensitivity, are preferable in app design.

Neurofilament light chain levels correlate with clinical measures in CLN3 disease.

PURPOSE: CLN3 disease is a neurodegenerative disorder with onset in childhood. It affects multiple functions at different developmental stages. Incomplete understanding of the pathophysiology hampers identification of cell and tissue biochemical compounds reflective of the disease process. As treatment approaches are being explored, more sensitive, objective, quantifiable, and clinically relevant biomarkers are needed. METHODS: We collected prospective biosamples from 21 phenotyped individuals with CLN3. We measured neurofilament light chain (NEFL) levels, a marker of neuronal damage, in cross-sectional CSF and serum samples from individuals with CLN3 and in pediatric non-CLN3 controls using two different assays. RESULTS: Cerebrospinal fluid (CSF) and serum NEFL levels are significantly higher in CLN3 (CSF: 2096 ± 1202; serum: 29.0 ± 18.0 pg/mL) versus similarly aged non-CLN3 (CSF: 345 ± 610; serum: 6.7 ± 3.2 pg/mL) samples. NEFL levels correlate with Unified Batten Disease Rating Scale and adaptive behavior composite scores, and magnetic resonance (MR) spectroscopy markers. NEFL levels from CSF and serum are strongly correlated (rp = 0.83; p < 0.0001). CONCLUSION: CSF and serum NEFL levels increase in multiple neurologic conditions. Here, we show that CSF and serum NEFL levels also increase in CLN3 (versus non-CLN3) and correlate with other disease-relevant measures. These findings suggest NEFL as a relevant and feasible biomarker for applications in CLN3 clinical trials and management.

Outcomes in Previously Healthy Cryptococcal Meningoencephalitis Patients Treated With Pulse Taper Corticosteroids for Post-infectious Inflammatory Syndrome.

BACKGROUND: Cryptococcal meningoencephalitis (CM) is a major cause of mortality in immunosuppressed patients and previously healthy individuals. In the latter, a post-infectious inflammatory response syndrome (PIIRS) is associated with poor clinical response despite antifungal therapy and negative cerebrospinal fluid (CSF) cultures. Data on effective treatment are limited. METHODS: Between March 2015 and March 2020, 15 consecutive previously healthy patients with CM and PIIRS were treated with adjunctive pulse corticosteroid taper therapy (PCT) consisting of intravenous methylprednisolone 1 gm daily for 1 week followed by oral prednisone 1 mg/kg/day, tapered based on clinical and radiological response plus oral fluconazole. Montreal cognitive assessments (MOCA), Karnofsky performance scores, magnetic resonance imaging (MRI) brain scanning, ophthalmic and audiologic exams, and CSF parameters including cellular and soluble immune responses were compared at PIIRS diagnosis and after methylprednisolone completion. RESULTS: The median time from antifungal treatment to steroid initiation was 6 weeks. The most common symptoms at PIIRS diagnosis were altered mental status and vision changes. All patients demonstrated significant improvements in MOCA and Karnofsky scores at 1 month (P < .0003), which was accompanied by improvements in CSF glucose, white blood cell (WBC) count, protein, cellular and soluble inflammatory markers 1 week after receiving corticosteroids (CS) (P < .003). All patients with papilledema and visual field deficits also exhibited improvement (P < .0005). Five out of 7 patients who underwent audiological testing demonstrated hearing improvement. Brain MRI showed significant improvement of radiological findings (P = .001). CSF cultures remained negative. CONCLUSIONS: PCT in this small cohort of PIIRS was associated with improvements in CM-related complications with minimal toxicity in the acute setting.

Extensive Healthy Donor Age/Gender Adjustments and Propensity Score Matching Reveal Physiology of Multiple Sclerosis Through Immunophenotyping.

Quantifying cell subpopulations in biological fluids aids in diagnosis and understanding of the mechanisms of injury. Although much has been learned from cerebrospinal fluid (CSF) flow cytometry in neuroimmunological disorders, such as multiple sclerosis (MS), previous studies did not contain enough healthy donors (HD) to derive age- and gender-related normative data and sufficient heterogeneity of other inflammatory neurological disease (OIND) controls to identify MS specific changes. The goals of this blinded training and validation study of MS patients and embedded controls, representing 1,240 prospectively acquired paired CSF/blood samples from 588 subjects was (1) to define physiological age-/gender-related changes in CSF cells, (2) to define/validate cellular abnormalities in blood and CSF of untreated MS through disease duration (DD) and determine which are MS-specific, and (3) to compare effect(s) of low-efficacy (i.e., interferon-beta [IFN-beta] and glatiramer acetate [GA]) and high-efficacy drugs (i.e., natalizumab, daclizumab, and ocrelizumab) on MS-related cellular abnormalities using propensity score matching. Physiological gender differences are less pronounced in the CSF compared to blood, and age-related changes suggest decreased immunosurveillance of CNS by activated HLA-DR+T cells associated with natural aging. Results from patient samples support the concept of MS being immunologically single disease evolving in time. Initially, peripherally activated innate and adaptive immune cells migrate into CSF to form MS lesions. With progression, T cells (CD8+ > CD4+), NK cells, and myeloid dendritic cells are depleted from blood as they continue to accumulate, together with B cells, in the CSF and migrate to CNS tissue, forming compartmentalized inflammation. All MS drugs inhibit non-physiological accumulation of immune cells in the CSF. Although low-efficacy drugs tend to normalize it, high-efficacy drugs overshoot some aspects of CSF physiology, suggesting impairment of CNS immunosurveillance. Comparable inhibition of MS-related CSF abnormalities advocates changes within CNS parenchyma responsible for differences in drug efficacy on MS disability progression. Video summarizing all results may become useful educational tool.

Idebenone does not inhibit disability progression in primary progressive MS.

BACKGROUND: Multiple sclerosis (MS) is a chronic, immune-mediated neurodegenerative disorder of the central nervous system (CNS). While current MS therapies target the inflammatory processes, no treatment explicitly targets mitochondrial dysfunction and resulting axonal loss. Therefore, the aim of this study was to determine whether idebenone inhibits mitochondrial dysfunction and accumulation of disability in primary progressive MS (PPMS) and to enhance understanding of pathogenic mechanisms of PPMS progression using cerebrospinal fluid (CSF) biomarkers. METHODS: The double-blind, placebo-controlled Phase I/II clinical trial of Idebenone in patients with Primary Progressive MS (IPPoMS; NCT00950248) was an adaptively designed, baseline-versus-treatment, placebo-controlled, CSF-biomarker-supported trial. Based on interim analysis of the 1-year pre-treatment data, change in the area under the curve of Combinatorial Weight-Adjusted Disability Score (CombiWISE) became the primary outcome, with >80% power to detect ≥40% efficacy with 28 patients/arm treated for 2 years in baseline versus treatment paradigm. Changes in traditional disability scales and in brain ventricular volume were secondary outcomes. Exploratory outcomes included CSF biomarkers of mitochondrial dysfunction (Growth/differentiation factor 15 [GDF15] and lactate), axonal damage (neurofilament light chain [NFL]), innate immunity (sCD14), blood brain barrier leakage (albumin quotient) and retinal nerve fiber layer thinning. RESULTS: Idebenone was well tolerated but did not inhibit disability progression or CNS tissue destruction. Concentrations of GDF15, secreted predominantly by astrocytes and choroid plexus epithelium in vitro, increased after exposure to mitochondrial toxin rotenone, validating the ability of this biomarker to measure intrathecal mitochondrial damage. CSF GDF15 levels correlated strongly with age and MS patients had CSF levels of GDF15 significantly above age-adjusted healthy volunteers, with highest levels measured in PPMS. Idebenone did not change CSF GDF15 levels. CONCLUSION: Mitochondrial dysfunction exceeding normal aging reflected by age-adjusted CSF GDF15 is present in the majority of PPMS patients, but it is not inhibited by idebenone.