CSF neurofilament light chain profiling and quantitation in neurological diseases.

Neurofilament light chain is an established marker of neuroaxonal injury that is elevated in CSF and blood across various neurological diseases. It is increasingly used in clinical practice to aid diagnosis and monitor progression and as an outcome measure to assess safety and efficacy of disease-modifying therapies across the clinical translational neuroscience field. Quantitative methods for neurofilament light chain in human biofluids have relied on immunoassays, which have limited capacity to describe the structure of the protein in CSF and how this might vary in different neurodegenerative diseases. In this study, we characterized and quantified neurofilament light chain species in CSF across neurodegenerative and neuroinflammatory diseases and healthy controls using targeted mass spectrometry. We show that the quantitative immunoprecipitation-tandem mass spectrometry method developed in this study strongly correlates to single-molecule array measurements in CSF across the broad spectrum of neurodegenerative diseases and was replicable across mass spectrometry methods and centres. In summary, we have created an accurate and cost-effective assay for measuring a key biomarker in translational neuroscience research and clinical practice, which can be easily multiplexed and translated into clinical laboratories for the screening and monitoring of neurodegenerative disease or acute brain injury.

Neuroimaging and plasma evidence of early white matter loss in Parkinson's disease with poor outcomes.

Parkinson's disease is a common and debilitating neurodegenerative disorder, with over half of patients progressing to postural instability, dementia or death within 10 years of diagnosis. However, the onset and rate of progression to poor outcomes is highly variable, underpinned by heterogeneity in underlying pathological processes. Quantitative and sensitive measures predicting poor outcomes will be critical for targeted treatment, but most studies to date have been limited to a single modality or assessed patients with established cognitive impairment. Here, we used multimodal neuroimaging and plasma measures in 98 patients with Parkinson's disease and 28 age-matched controls followed up over 3 years. We examined: grey matter (cortical thickness and subcortical volume), white matter (fibre cross-section, a measure of macrostructure; and fibre density, a measure of microstructure) at whole-brain and tract level; structural and functional connectivity; and plasma levels of neurofilament light chain and phosphorylated tau 181. We evaluated relationships with subsequent poor outcomes, defined as development of mild cognitive impairment, dementia, frailty or death at any time during follow-up, in people with Parkinson's disease. We show that extensive white matter macrostructural changes are already evident at baseline assessment in people with Parkinson's disease who progress to poor outcomes (n = 31): with up to 19% reduction in fibre cross-section in multiple tracts, and a subnetwork of reduced structural connectivity strength, particularly involving connections between right frontoparietal and left frontal, right frontoparietal and left parietal and right temporo-occipital and left parietal modules. In contrast, grey matter volumes and functional connectivity were preserved in people with Parkinson's disease with poor outcomes. Neurofilament light chain, but not phosphorylated tau 181 levels were increased in people with Parkinson's disease with poor outcomes, and correlated with white matter loss. These findings suggest that imaging sensitive to white matter macrostructure and plasma neurofilament light chain may be useful early markers of poor outcomes in Parkinson's disease. As new targeted treatments for neurodegenerative disease are emerging, these measures show important potential to aid patient selection for treatment and improve stratification for clinical trials.

Serum Neurofilament Light Chain in Replication Factor Complex Subunit 1 CANVAS and Disease Spectrum.

BACKGROUND: Biallelic intronic AAGGG repeat expansions in the replication factor complex subunit 1 (RFC1) gene were identified as the leading cause of cerebellar ataxia, neuropathy, vestibular areflexia syndrome. Patients exhibit significant clinical heterogeneity and variable disease course, but no potential biomarker has been identified to date. OBJECTIVES: In this multicenter cross-sectional study, we aimed to evaluate neurofilament light (NfL) chain serum levels in a cohort of RFC1 disease patients and to correlate NfL serum concentrations with clinical phenotype and disease severity. METHODS: Sixty-one patients with genetically confirmed RFC1 disease and 48 healthy controls (HCs) were enrolled from six neurological centers. Serum NfL concentration was measured using the single molecule array assay technique. RESULTS: Serum NfL concentration was significantly higher in patients with RFC1 disease compared to age- and-sex-matched HCs (P < 0.0001). NfL level showed a moderate correlation with age in both HCs (r = 0.4353, P = 0.0020) and patients (r = 0.4092, P = 0.0011). Mean NfL concentration appeared to be significantly higher in patients with cerebellar involvement compared to patients without cerebellar dysfunction (27.88 vs. 21.84 pg/mL, P = 0.0081). The association between cerebellar involvement and NfL remained significant after controlling for age and sex (ß = 0.260, P = 0.034). CONCLUSIONS: Serum NfL levels are significantly higher in patients with RFC1 disease compared to HCs and correlate with cerebellar involvement. Longitudinal studies are warranted to assess its change over time.

Quantitative MRI outcome measures in CMT1A using automated lower limb muscle segmentation.

BACKGROUND: Lower limb muscle magnetic resonance imaging (MRI) obtained fat fraction (FF) can detect disease progression in patients with Charcot-Marie-Tooth disease 1A (CMT1A). However, analysis is time-consuming and requires manual segmentation of lower limb muscles. We aimed to assess the responsiveness, efficiency and accuracy of acquiring FF MRI using an artificial intelligence-enabled automated segmentation technique. METHODS: We recruited 20 CMT1A patients and 7 controls for assessment at baseline and 12 months. The three-point-Dixon fat water separation technique was used to determine thigh-level and calf-level muscle FF at a single slice using regions of interest defined using Musclesense, a trained artificial neural network for lower limb muscle image segmentation. A quality control (QC) check and correction of the automated segmentations was undertaken by a trained observer. RESULTS: The QC check took on average 30 seconds per slice to complete. Using QC checked segmentations, the mean calf-level FF increased significantly in CMT1A patients from baseline over an average follow-up of 12.5 months (1.15%±1.77%, paired t-test p=0.016). Standardised response mean (SRM) in patients was 0.65. Without QC checks, the mean FF change between baseline and follow-up, at 1.15%±1.68% (paired t-test p=0.01), was almost identical to that seen in the corrected data, with a similar overall SRM at 0.69. CONCLUSIONS: Using automated image segmentation for the first time in a longitudinal study in CMT, we have demonstrated that calf FF has similar responsiveness to previously published data, is efficient with minimal time needed for QC checks and is accurate with minimal corrections needed.

Transcriptomic analysis of cutaneous squamous cell carcinoma reveals a multigene prognostic signature associated with metastasis.

BACKGROUND: Metastasis of cutaneous squamous cell carcinoma (cSCC) is uncommon. Current staging methods are reported to have sub-optimal performances in metastasis prediction. Accurate identification of patients with tumors at high risk of metastasis would have a significant impact on management. OBJECTIVE: To develop a robust and validated gene expression profile signature for predicting primary cSCC metastatic risk using an unbiased whole transcriptome discovery-driven approach. METHODS: Archival formalin-fixed paraffin-embedded primary cSCC with perilesional normal tissue from 237 immunocompetent patients (151 nonmetastasizing and 86 metastasizing) were collected retrospectively from four centers. TempO-seq was used to probe the whole transcriptome and machine learning algorithms were applied to derive predictive signatures, with a 3:1 split for training and testing datasets. RESULTS: A 20-gene prognostic model was developed and validated, with an accuracy of 86.0%, sensitivity of 85.7%, specificity of 86.1%, and positive predictive value of 78.3% in the testing set, providing more stable, accurate prediction than pathological staging systems. A linear predictor was also developed, significantly correlating with metastatic risk. LIMITATIONS: This was a retrospective 4-center study and larger prospective multicenter studies are now required. CONCLUSION: The 20-gene signature prediction is accurate, with the potential to be incorporated into clinical workflows for cSCC.

Plasma biomarkers of neurodegeneration in mild cognitive impairment with Lewy bodies.

BACKGROUND: Blood biomarkers of Alzheimer's disease (AD) may allow for the early detection of AD pathology in mild cognitive impairment (MCI) due to AD (MCI-AD) and as a co-pathology in MCI with Lewy bodies (MCI-LB). However not all cases of MCI-LB will feature AD pathology. Disease-general biomarkers of neurodegeneration, such as glial fibrillary acidic protein (GFAP) or neurofilament light (NfL), may therefore provide a useful supplement to AD biomarkers. We aimed to compare the relative utility of plasma Aß42/40, p-tau181, GFAP and NfL in differentiating MCI-AD and MCI-LB from cognitively healthy older adults, and from one another. METHODS: Plasma samples were analysed for 172 participants (31 healthy controls, 48 MCI-AD, 28 possible MCI-LB and 65 probable MCI-LB) at baseline, and a subset (n = 55) who provided repeated samples after ≥1 year. Samples were analysed with a Simoa 4-plex assay for Aß42, Aß40, GFAP and NfL, and incorporated previously-collected p-tau181 from this same cohort. RESULTS: Probable MCI-LB had elevated GFAP (p < 0.001) and NfL (p = 0.012) relative to controls, but not significantly lower Aß42/40 (p = 0.06). GFAP and p-tau181 were higher in MCI-AD than MCI-LB. GFAP discriminated all MCI subgroups, from controls (AUC of 0.75), but no plasma-based marker effectively differentiated MCI-AD from MCI-LB. NfL correlated with disease severity and increased with MCI progression over time (p = 0.011). CONCLUSION: Markers of AD and astrocytosis/neurodegeneration are elevated in MCI-LB. GFAP offered similar utility to p-tau181 in distinguishing MCI overall, and its subgroups, from healthy controls.

Seed amplification and neurodegeneration marker trajectories in individuals at risk of prion disease.

Human prion diseases are remarkable for long incubation times followed typically by rapid clinical decline. Seed amplification assays and neurodegeneration biofluid biomarkers are remarkably useful in the clinical phase, but their potential to predict clinical onset in healthy people remains unclear. This is relevant not only to the design of preventive strategies in those at-risk of prion diseases, but more broadly, because prion-like mechanisms are thought to underpin many neurodegenerative disorders. Here, we report the accrual of a longitudinal biofluid resource in patients, controls and healthy people at risk of prion diseases, to which ultrasensitive techniques such as real-time quaking-induced conversion (RT-QuIC) and single molecule array (Simoa) digital immunoassays were applied for preclinical biomarker discovery. We studied 648 CSF and plasma samples, including 16 people who had samples taken when healthy but later developed inherited prion disease (IPD) ('converters'; range from 9.9 prior to, and 7.4 years after onset). Symptomatic IPD CSF samples were screened by RT-QuIC assay variations, before testing the entire collection of at-risk samples using the most sensitive assay. Glial fibrillary acidic protein (GFAP), neurofilament light (NfL), tau and UCH-L1 levels were measured in plasma and CSF. Second generation (IQ-CSF) RT-QuIC proved 100% sensitive and specific for sporadic Creutzfeldt-Jakob disease (CJD), iatrogenic and familial CJD phenotypes, and subsequently detected seeding activity in four presymptomatic CSF samples from three E200K carriers; one converted in under 2 months while two remain asymptomatic after at least 3 years' follow-up. A bespoke HuPrP P102L RT-QuIC showed partial sensitivity for P102L disease. No compatible RT-QuIC assay was discovered for classical 6-OPRI, A117V and D178N, and these at-risk samples tested negative with bank vole RT-QuIC. Plasma GFAP and NfL, and CSF NfL levels emerged as proximity markers of neurodegeneration in the typically slow IPDs (e.g. P102L), with significant differences in mean values segregating healthy control from IPD carriers (within 2 years to onset) and symptomatic IPD cohorts; plasma GFAP appears to change before NfL, and before clinical conversion. In conclusion, we show distinct biomarker trajectories in fast and slow IPDs. Specifically, we identify several years of presymptomatic seeding positivity in E200K, a new proximity marker (plasma GFAP) and sequential neurodegenerative marker evolution (plasma GFAP followed by NfL) in slow IPDs. We suggest a new preclinical staging system featuring clinical, seeding and neurodegeneration aspects, for validation with larger prion at-risk cohorts, and with potential application to other neurodegenerative proteopathies.

Acceptability and feasibility of plasma phosphorylated-tau181 in two memory services.

BACKGROUND: Plasma phosphorylated-tau181 (p-tau181) represents a novel blood-based biomarker of Alzheimer's disease pathology. We explored clinicians' experience of the utility of plasma p-tau181 in Camden and Islington Memory Services. METHODS: Patients were identified by their clinician as appropriate for p-tau181. Their p-tau181 result was plotted on a reference range graph provided to clinicians. This was discussed with the patient at diagnostic feedback appointment. RESULTS: Twenty-nine participants' plasma p-tau181 samples were included (mean age 74 SD 8.5, 65% female). Nine clinicians participated in the study. Eighty-six percent of clinicians found the p-tau181 result to be helpful and in 93% of cases it was clearly understandable. The p-tau181 result was useful in making the diagnosis in 44% of cases. CONCLUSIONS: Plasma p-tau181 is a feasible test for use in memory services and acceptable to clinicians. Clinician feedback on utility in dementia diagnoses was mixed. Further work is required to provide education and training in understanding and interpreting ambiguity in biomarker results.