Background
In recent years, blood‐based biomarkers have become key measures in the study of dementia, including frontotemporal dementia (FTD), with use in diagnosis and clinical trial outcomes. ...Remote collection of blood samples provides a more accessible and cost‐effective alternative to regular clinic visits and allows for more frequent measures to be taken. This is particularly relevant as we progress into an era of clinical trials in FTD. The aim of this current study was to assess whether neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP), markers previously shown be increased in genetic forms of FTD, can be measured using dried blood cards and to optimise the protocol for this.
Method
10 participants from the University College London GENFI study (three C9orf72 mutation carriers, four GRN mutation carriers and three mutation negative controls) were included in this pilot study. Blood samples were collected by venepuncture from each participant: one sample for plasma analysis and one sample which was used to pipette whole blood on to a blood card. NfL and GFAP concentrations were subsequently quantified using the Simoa multiplex Neurology 4‐Plex A (N4PA) assay in both plasma and the dried blood card. Total protein concentration was measured with the Bradford protein assay and used to correct for variable concentrations of blood card spots. The effect of incubation temperature and time as well as freeze thaw cycles were also assessed as part of the optimisation process.
Result
In this pilot cohort, blood card GFAP concentration (BSA corrected) very strongly correlated with matched plasma GFAP (r = 0.897, p = 0.0004), whilst blood card NfL concentration (BSA corrected) strongly correlated with matched plasma NfL (r = 0.721, p = 0.0234). Incubation temperature impacted total protein concentration in the blood cards, but freeze‐thaw and incubation time did not.
Conclusion
This pilot study shows that NfL and GFAP concentrations can be successfully quantified using dried blood cards and results strongly correlate with plasma measures. Future work will involve investigating whether these biomarkers can be measured in blood cards obtained with capillary blood through lancet‐based fingerprick collection and assessing the feasibility of home collection.
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 A
42/40,
-tau181, GFAP and NfL in differentiating MCI-AD and MCI-LB from cognitively healthy older adults, and from one another.
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 (
= 55) who provided repeated samples after ≥1 year. Samples were analysed with a Simoa 4-plex assay for A
42, A
40, GFAP and NfL, and incorporated previously-collected
-tau181 from this same cohort.
Probable MCI-LB had elevated GFAP (
< 0.001) and NfL (
= 0.012) relative to controls, but not significantly lower A
42/40 (
= 0.06). GFAP and
-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 (
= 0.011).
Markers of AD and astrocytosis/neurodegeneration are elevated in MCI-LB. GFAP offered similar utility to
-tau181 in distinguishing MCI overall, and its subgroups, from healthy controls.
Background
In 2012‐2014, an observational cohort study of postoperative delirium (POD) in an elective arthroplasty population recruited 315 individuals aged over 65 without a diagnosis of dementia. ...This follow‐up study aims to determine what effect POD has on cognitive function eight years later.
Method
Preoperatively, participants underwent cognitive assessments and sampling of blood and cerebrospinal fluid (CSF) which were analysed for amyloid‐beta (Aβ)40, Aβ42, glial fibrillary acidic protein (GFAP), neurofilament light (NFL) and interleukin (IL)‐6.
In 2021, n = 172 of n = 264 surviving participants completed virtual cognitive assessments and agreed to have their medical records reviewed. For those who had died (n = 50), death certificates were obtained to determine if the participant died with a diagnosis of dementia. Univariate analyses and binary logistic regression were undertaken to investigate factors associated with mild cognitive impairment (MCI)/dementia in this cohort at eight years (Table 1). In cases when MCI or dementia was suspected, an expert consensus panel reviewed medical notes, cognitive test scores and informant reports to determine if a participant had MCI or dementia.
Result
Of the n = 222 participants, n = 30 had POD in 2012‐2014 and n = 22 had developed dementia or MCI. On univariate analyses, those who developed MCI/dementia at eight years were significantly older at the time of surgery (p = .02), had greater preoperative functional impairment (p = .02), and depression (p = .03) and performed worse on a number of cognitive tasks pre‐operatively (p<.05). Rates of POD were significantly greater in those who subsequently developed MCI/dementia (p = .03). In those who developed MCI/dementia, preoperative plasma and CSF measures of Aβ42 were significantly lower (p<.01), while CSF neurofilament light (NFL) and plasma IL‐6, GFAP and NFL were significantly higher (p<.05). On multivariate analyses, CSF Aβ42 (p = .02) and preoperative phonemic fluency (p = .01) remained significant predictors of MCI/dementia, while POD did not (Table 1).
Conclusion
This study did not find an independent association between delirium following elective arthroplasty and the development of MCI/dementia eight years later. The results of our study indicate preoperative CSF Aβ42 and cognitive function predict longer‐term outcomes and that the association between delirium and subsequent MCI and dementia is not independent of these factors.
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.
Key points
Results from this study show that plasma phosphorylated‐tau181 (p‐tau181) is feasible to incorporate in the diagnostic assessment of patients in a memory service and acceptable to clinicians.
Clinicians require education and training in understanding and interpreting ambiguity in biomarker results.
Further work is needed to establish the clinical utility of such a blood biomarker in UK Memory Services and to investigate the impact of p‐tau181 results for Alzheimer's disease diagnoses, clinicians' diagnostic confidence and patient management.
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.
To develop a robust and validated gene expression profile signature for predicting primary cSCC metastatic risk using an unbiased whole transcriptome discovery-driven approach.
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.
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.
This was a retrospective 4-center study and larger prospective multicenter studies are now required.
The 20-gene signature prediction is accurate, with the potential to be incorporated into clinical workflows for cSCC.
Background
Blood‐based biomarkers of Alzheimer’s disease (AD) may help to rule AD in, with particular promise at the mild cognitive impairment (MCI) stage when potential disease‐modifying treatments ...may be most effective. However, AD is not the only common cause of cognitive impairment: Lewy body disease and other non‐AD pathologies are common and under‐recognised. Reliance on AD‐specific biomarkers alone may therefore contribute to missed diagnosis of non‐AD aetiologies. We aimed to examine the utility of emerging AD plasma biomarkers in identifying disease‐specific MCI due to AD (MCI‐AD), MCI with Lewy bodies (MCI‐LB) and in disease‐general MCI. We also aimed to compare these with alternative disease‐general biomarkers of neurodegeneration, and examined any change over time.
Method
In a longitudinal study, plasma samples were collected 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 Simoa assays for Alzheimer’s disease (Aβ42, Aβ40, ptau‐181) and neurodegeneration (GFAP and NfL) biomarkers.
MCI cases were differentially classified as MCI‐AD or MCI‐LB by an expert panel of old age psychiatrists, based on current consensus diagnostic criteria, and including Lewy body disease‐specific imaging biomarkers.
Age‐adjusted mixed effects models assessed any longitudinal changes over time in each biomarker, and associations with severity of cognitive impairment as assessed by the Addenbrooke’s Cognitive Examination – Revised.
Result
GFAP performed comparably to AD‐specific biomarkers in identifying any‐cause MCI (GFAP AUC = 0.75; ptau‐181 = 0.73), while maintaining good accuracy in identifying MCI‐AD specifically. AD biomarkers did not reliably distinguish MCI‐AD from MCI‐LB. Severity of cognitive impairment in any‐cause MCI and MCI‐AD was most strongly correlated with the disease‐nonspecific neurodegenerative biomarker NfL (r = 0.48, p = 0.005; cf. GFAP r = 0.23, p = 0.121), which progressively increased over time.
Conclusion
Given the high prevalence of unrecognised non‐AD pathologies at autopsy (>1/3 cases in UK brain banks), blood biomarkers of neurodegeneration may be a useful alternative to AD‐specific biomarkers in screening for neurodegenerative disease in MCI. As AD biomarkers do not reliably differentiate MCI‐AD from MCI‐LB, there is a need for disease‐specific biomarkers of synucleinopathies.
Abstract
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.
Mok et al. present longitudinal biofluid RT-QuIC and neurodegenerative biomarker analyses of individuals at risk of and symptomatic for prion disease. RT-QuIC can detect seeding activity up to almost 4 years before disease onset, while neurodegenerative marker trajectories differ between fast and slow inherited prion diseases.
See Minikel and Vallabh (https://doi.org/10.1093/brain/awad143) for a scientific commentary on this article.
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.
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.
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.
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.
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 (β = 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.
Background
Cerebrospinal fluid (CSF) neurofilament light (NfL) is a dynamic biomarker of neurodegeneration that is used for supporting clinical diagnosis and monitoring disease‐modifying therapies. ...Development of new analytical tests has been limited, with quantitation of NfL in biomarker studies largely restricted to immunoassay methods. Targeted mass spectrometry is a highly specific technique that can be easily translated into existing proteomic and clinical pathology laboratories. In this multi‐centre study, we have developed two targeted mass spectrometry assays which were compared to Simoa, the gold standard method for NfL quantitation. The developed methods included immunocapture of intact NfL protein or specific peptides (immune‐peptide capture) prior to targeted proteomic analyses. We discuss the development, validation and merits of each technology to quantitate NfL in CSF from healthy controls and several neurodegenerative diseases.
Method
CSF was collected from patients with a range of neurological diseases at the National Hospital for Neurology and Neurosurgery (London, UK). Clinical diagnosis was determined by their treating clinician according to consensus clinical criteria. NfL concentrations were measured by Simoa (Quanterix, USA) and two immunoprecipitation‐targeted mass spectrometry (IP‐MS) assays developed by a collaboration between UCL and Washington University in St Louis. To evaluate replication of results across centres and mass spectrometry approaches, results were compared using Spearman’s correlation analysis and Bland‐Altman testing.
Results
A high correlation was observed for CSF NfL levels between Simoa and both IP‐MS assays (immune‐peptide capture, r = 0.90, P<0.0001 and immune‐protein capture, r = 0.88, P<0.0001). Relative differences in mean NfL concentration between clinical groups remained the same across the analytical methods, with the highest and lowest NfL concentrations observed in the Huntington’s disease and the healthy control groups respectively. Interestingly, differences in the extent of correlation between Simoa and IP‐MS were observed between the different clinical groups (r = 0.37 ‐ 0.94).
Conclusion
Immunoprecipitation‐targeted mass spectrometry quantitation of NfL correlates highly with NfL Simoa measures across a range of neurodegenerative and neuroinflammatory diseases, and is replicable between laboratories using different immunoprecipitation‐targeted mass spectrometry approaches.
