Adaptive immune changes associate with clinical progression of Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is the most frequent cause of dementia. Recent evidence suggests the involvement of peripheral immune cells in the disease, but the underlying mechanisms remain unclear.

METHODS

We comprehensively mapped peripheral immune changes in AD patients with mild cognitive impairment (MCI) or dementia compared to controls, using cytometry by time-of-flight (CyTOF).

RESULTS

We found an adaptive immune signature in AD, and specifically highlight the accumulation of PD1+ CD57+ CD8+ T effector memory cells re-expressing CD45RA in the MCI stage of AD. In addition, several innate and adaptive immune cell subsets correlated to cerebrospinal fluid (CSF) biomarkers of AD neuropathology and measures for cognitive decline. Intriguingly, subsets of memory T and B cells were negatively associated with CSF biomarkers for tau pathology, neurodegeneration and neuroinflammation in AD patients. Lastly, we established the influence of the APOE ε4 allele on peripheral immunity.

CONCLUSIONS

Our findings illustrate significant peripheral immune alterations associated with both early and late clinical stages of AD, emphasizing the necessity for further investigation into how these changes influence underlying brain pathology.

Fully automated measurement of plasma Aβ42/40 and p-tau181: Analytical robustness and concordance with cerebrospinal fluid profile along the Alzheimer's disease continuum in two independent cohorts

INTRODUCTION

For routine clinical implementation of Alzheimer's disease (AD) plasma biomarkers, fully automated random-access platforms are crucial to ensure reproducible measurements. We aimed to perform an analytical validation and to establish cutoffs for AD plasma biomarkers measured with Lumipulse.

METHODS

Two cohorts were included. UNIPG: n = 450 paired cerebrospinal fluid (CSF)/plasma samples from subjects along the AD-continuum, subjects affected by other neurodegenerative diseases, and controls with known CSF profile; AMS: n = 40 plasma samples from AD and n = 40 controls. Plasma amyloid β (Aβ)42, Aβ40, and p-tau181 were measured with Lumipulse. We evaluated analytical and diagnostic performance.

RESULTS

Lumipulse assays showed high analytical performance. Plasma p-tau181 levels accurately reflected CSF A+/T+ profile in AD-dementia and mild cognitive impairment (MCI)-AD, but not in asymptomatic-AD. Plasma and CSF Aβ42/40 values were concordant across clinical AD stages. Cutoffs and probability-based models performed satisfactorily in both cohorts.

DISCUSSION

The identified cutoffs and probability-based models represent a significant step toward plasma AD molecular diagnosis.

Plasma Markers of Alzheimer's Disease Pathology, Neuronal Injury, and Astrocytic Activation and MRI Load of Vascular Pathology and Neurodegeneration: The SMART-MR Study

BACKGROUND

Two of the main causes for dementia are Alzheimer's disease (AD) and vascular pathology, with most patients showing mixed pathology. Plasma biomarkers for Alzheimer's disease-related pathology have recently emerged, including Aβ (amyloid-beta), p-tau (phosphorylated tau), NfL (neurofilament light), and GFAP (glial fibrillary acidic protein). There is a current gap in the literature regarding whether there is an association between these plasma biomarkers with vascular pathology and neurodegeneration.

METHODS AND RESULTS

Cross-sectional data from 594 individuals (mean [SD] age: 64 [8] years; 17% female) were included from the SMART-MR (Second Manifestations of Arterial Disease-Magnetic Resonance) study, a prospective cohort study of individuals with a history of arterial disease. Plasma markers were assessed using single molecular array assays (Quanterix). Magnetic resonance imaging markers included white matter hyperintensity volume, presence of infarcts (yes/no), total brain volume, and hippocampal volume assessed on 1.5T magnetic resonance imaging. Linear regressions were performed for each standardized plasma marker with white matter hyperintensity volume, total brain volume, and hippocampal volume as separate outcomes, correcting for age, sex, education, and intracranial volume. Logistic regressions were performed for the presence of lacunar and cortical infarcts. Higher p-tau181 was associated with larger white matter hyperintensity volume (b per SD increase=0.16 [95% CI, 0.06-0.26], P=0.015). Higher NfL (b=-5.63, [95% CI, -8.95 to -2.31], P=0.015) was associated with lower total brain volume and the presence of infarcts (odds ratio [OR], 1.42 [95% CI, 1.13-1.78], P=0.039). Higher GFAP levels were associated with cortical infarcts (OR, 1.45 [95% CI, 1.09-1.92], P=0.010).

CONCLUSIONS

Plasma biomarkers that have been associated with tau pathology, axonal injury, and astrocytic activation are related to magnetic resonance imagingmarkers of vascular pathology and neurodegeneration in patients with manifest arterial disease.

The use of synaptic biomarkers in cerebrospinal fluid to differentiate behavioral variant of frontotemporal dementia from primary psychiatric disorders and Alzheimer's disease

BACKGROUND

Lack of early molecular biomarkers in sporadic behavioral variants of frontotemporal dementia (bvFTD) and its clinical overlap with primary psychiatric disorders (PPD) hampers its diagnostic distinction. Synaptic dysfunction is an early feature in bvFTD and identification of specific biomarkers might improve its diagnostic accuracy. Our goal was to understand the differential diagnostic potential of cerebrospinal fluid (CSF) synaptic biomarkers in bvFTD versus PPD and their specificity towards bvFTD compared with Alzheimer's disease (AD) and controls. Additionally, we explored the association of CSF synaptic biomarkers with social cognition, cognitive performance, and disease severity in these clinical groups.

METHODS

Participants with probable bvFTD (n = 57), PPD (n = 71), AD (n = 60), and cognitively normal controls (n = 39) with available CSF, cognitive tests, and disease severity as frontotemporal lobar degeneration-modified clinical dementia rating scale (FTLD-CDR) were included. In a subset of bvFTD and PPD cases, Ekman 60 faces test scores for social cognition were available. CSF synaptosomal-associated protein 25 (SNAP25), neurogranin (Ng), neuronal pentraxin 2 (NPTX2), and glutamate receptor 4 (GluR4) were measured, along with neurofilament light (NfL), and compared between groups using analysis of covariance (ANCOVA) and logistic regression. Diagnostic accuracy was assessed using ROC analyses, and biomarker panels were selected using Wald's backward selection. Correlations with cognitive measures were performed using Pearson's partial correlation analysis.

RESULTS

NPTX2 concentrations were lower in the bvFTD group compared with PPD (p < 0.001) and controls (p = 0.003) but not compared with AD. Concentrations of SNAP25 (p < 0.001) and Ng (p < 0.001) were elevated in patients with AD versus those with bvFTD and controls. The modeled panel for differential diagnosis of bvFTD versus PPD consisted of NfL and NPTX2 (AUC = 0.96, CI: 0.93-0.99, p < 0.001). In bvFTD versus AD, the modeled panel consisted of NfL, SNAP25, Ng, and GluR4 (AUC = 0.86, CI: 0.79-0.92, p < 0.001). In bvFTD, lower NPTX2 (Pearson's r = 0.29, p = 0.036) and GluR4 (Pearson's r = 0.34, p = 0.014) concentrations were weakly associated with worse performance of total cognitive score. Lower GluR4 concentrations were also associated with worse MMSE scores (Pearson's r = 0.41, p = 0.002) as well as with worse executive functioning (Pearson's r = 0.36, p = 0.011) in bvFTD. There were no associations between synaptic markers and social cognition or disease severity in bvFTD.

CONCLUSION

Our findings of involvement of NTPX2 in bvFTD but not PPD contribute towards better understanding of bvFTD disease pathology.

Cognitive and Functional Change Over Time in Cognitively Healthy Individuals According to Alzheimer Disease Biomarker-Defined Subgroups

BACKGROUND AND OBJECTIVES

It is unclear to what extent cognitive outcome measures are sensitive to capture decline in Alzheimer disease (AD) prevention trials. We aimed to analyze the sensitivity to changes over time of a range of neuropsychological tests in several cognitively unimpaired, biomarker-defined patient groups.

METHODS

Cognitively unimpaired individuals from the Amsterdam Dementia Cohort and the SCIENCe project with available AD biomarkers, obtained from CSF, PET scans, and plasma at baseline, were followed over time (4.5 ± 3.1 years, range 0.6-18.9 years). Based on common inclusion criteria for clinical trials, we defined groups (amyloid, phosphorylated tau [p-tau], APOE ε4). Linear mixed models, adjusted for age, sex, and education, were used to estimate change over time in neuropsychological tests, a functional outcome, and 2 cognitive composite measures. Standardized regression coefficients of time in years (βtime) were reported as outcome of interest. We analyzed change over time with full follow-up, as well as with follow-up limited to 1.5 and 3 years.

RESULTS

We included 387 individuals (aged 61.7 ± 8.6 years; 44% female) in the following (partly overlapping) biomarker groups: APOE ε4 carriers (n = 212), amyloid-positive individuals (n = 109), amyloid-positive APOE ε4 carriers (n = 66), CSF p-tau-positive individuals (n = 127), plasma p-tau-positive individuals (n = 71), and amyloid and CSF p-tau-positive individuals (n = 50), or in a control group (normal biomarkers; n = 65). An executive functioning task showed most decline in all biomarker groups (βtime range -0.30 to -0.71), followed by delayed word list recognition (βtime range -0.18 to -0.50). Functional decline (βtime range -0.17 to -0.63) was observed in all, except the CSF and plasma tau-positive groups. Both composites showed comparable amounts of change (βtime range -0.12 to -0.62) in all groups, except plasma p-tau-positive individuals. When limiting original follow-up duration, many effects disappeared or even flipped direction.

DISCUSSION

In conclusion, functional, composite, and neuropsychological outcome measures across all cognitive domains detect changes over time in various biomarker-defined groups, with changes being most evident among individuals with more AD pathology. AD prevention trials should use sufficiently long follow-up duration and/or more sensitive outcome measures to optimally capture subtle cognitive changes over time.

Neurofilament light protein as a biomarker for spinal muscular atrophy: a review and reference ranges

Spinal muscular atrophy (SMA) is the leading genetic cause of infant mortality, characterized by progressive neuromuscular degeneration resulting from mutations in the survival motor neuron (SMN1) gene. The availability of disease-modifying therapies for SMA therapies highlights the pressing need for easily accessible and cost-effective blood biomarkers to monitor treatment response and for better disease management. Additionally, the wide implementation of newborn genetic screening programs in Western countries enables presymptomatic diagnosis of SMA and immediate treatment administration. However, the absence of monitoring and prognostic blood biomarkers for neurodegeneration in SMA hinders effective disease management. Neurofilament light protein (NfL) is a promising biomarker of neuroaxonal damage in SMA and reflects disease progression in children with SMA undergoing treatment. Recently, the European Medicines Agency issued a letter of support endorsing the potential utilization of NfL as a biomarker of pediatric neurological diseases, including SMA. Within this review, we comprehensively assess the potential applications of NfL as a monitoring biomarker for disease severity and treatment response in pediatric-onset SMA. We provide reference ranges for normal levels of serum based NfL in neurologically healthy children aged 0-18 years. These reference ranges enable accurate interpretation of NfL levels in children and can accelerate the implementation of NfL into clinical practice.

Alzheimer's Disease and Cognitive Decline in Patients with Cardiovascular Diseases Along the Heart-Brain Axis

Background

We hypothesize that Alzheimer's disease (AD)-related pathology may accelerate cognitive decline in patients with cardiovascular diseases.

Objective

To investigate the association between blood-based biomarkers of AD, astrocyte activation, and neurodegeneration and cognitive decline.

Methods

From the multi-center Heart-Brain study, we included 412 patients with heart failure, carotid occlusive disease or vascular cognitive impairment (age:68.6±9.0) and 128 reference participants (65.7±7.5). Baseline amyloid-β42/40 (Aβ42/40), phosphorylated-tau181 (pTau181), glial fibrillary acidic protein (GFAP), and neurofilament light (NfL) were determined using SiMoA (Quanterix). Memory, attention, language, and executive functioning were evaluated (follow-up:2.1±0.3 years). We applied linear mixed models with terms for biomarker, time and biomarker*time interactions, adjusted for age, sex, education, and site, to assess associations between biomarkers and cognitive decline.

Results

Among patients, Aβ42/40 was not associated with cognitive performance at baseline. However, lower Aβ42/40 was associated with steeper decline in global cognition (β±SE:0.04±0.02). Higher pTau181 was associated with worse baseline performance on global cognition (-0.14±0.04) and memory (-0.31±0.09) and with steeper decline in global cognition (-0.07±0.02), memory (-0.09±0.04), attention (-0.05±0.02), and language (-0.10±0.03). Higher GFAP was associated with worse baseline performance on global cognition (-0.22±0.05), memory (-0.43±0.10), attention (-0.14±0.06), language (-0.15±0.05), and executive functioning (-0.15±0.05) and steeper decline in global cognition (-0.05±0.01). Higher NfL was associated with worse baseline performance on global cognition (-0.16±0.04), memory (-0.28±0.09), attention (-0.20±0.06), and executive functioning (-0.10±0.04), but was not associated with performance over time. In reference participants, no associations were found.

Conclusions

Our findings suggest that blood-based biomarkers of AD-related pathology predict cognitive decline in patients with cardiovascular diseases.

Methods to Discover and Validate Biofluid-Based Biomarkers in Neurodegenerative Dementias

Neurodegenerative dementias are progressive diseases that cause neuronal network breakdown in different brain regions often because of accumulation of misfolded proteins in the brain extracellular matrix, such as amyloids or inside neurons or other cell types of the brain. Several diagnostic protein biomarkers in body fluids are being used and implemented, such as for Alzheimer's disease. However, there is still a lack of biomarkers for co-pathologies and other causes of dementia. Such biofluid-based biomarkers enable precision medicine approaches for diagnosis and treatment, allow to learn more about underlying disease processes, and facilitate the development of patient inclusion and evaluation tools in clinical trials. When designing studies to discover novel biofluid-based biomarkers, choice of technology is an important starting point. But there are so many technologies to choose among. To address this, we here review the technologies that are currently available in research settings and, in some cases, in clinical laboratory practice. This presents a form of lexicon on each technology addressing its use in research and clinics, its strengths and limitations, and a future perspective.

Association of plasma biomarkers with cognitive function in persons with dementia and cognitively healthy in the Democratic Republic of Congo

Introduction

This study investigates whether plasma biomarkers (Aβ42/40 and p-tau 181), APS, as well as apolipoprotein E (APOE) proteotype predict cognitive deficits in elderly adults from the Democratic Republic of Congo.

Methods

Forty-four with possible AD (pAD) and 41 healthy control (HC) subjects were screened using CSID and AQ, underwent cognitive assessment with the African Neuropsychology Battery (ANB), and provided blood samples for plasma Aβ42, Aβ40, Aβ42/40, and APOE proteotype. Linear and logistic regression were used to evaluate the associations of plasma biomarkers with ANB tests and the ability of biomarkers to predict cognitive status.

Results

Patients with pAD had significantly lower plasma Aβ42/40 levels, higher APS, and higher prevalence of APOE E4 allele compared to HC. Groups did not differ in levels of Aβ40, Aβ42, or P-tau 181. Results showed that Aβ42/40 ratio and APS were significantly associated with African Naming Test (ANT), African List Memory Test (ALMT), and African Visuospatial Memory Test (AVMT) scores, while the presence of APOE E4 allele was associated with ANT, ALMT, AVMT, and APT scores. P-tau 181 did not show any significant associations while adjusting for age, education, and gender. APS showed the highest area under the curve (AUC) value (AUC = 0.78, 95% confidence interval [CI]: 0.68-0.88) followed by Aβ42/40 (AUC = 0.75, 95% CI: 0.66-0.86) and APOE E4 (AUC = 0.69 (CI 0.57-0.81) in discriminating pAD from HC.

Discussion

These results demonstrate associations between select plasma biomarker of AD pathology (Aβ42/40), APS, and APOE E4 allele) and ANB test scores and the ability of these biomarkers to differentiate pAD from cognitively normal SSA individuals, consistent with findings reported in other settings.

Elevated plasma sclerostin is associated with high brain amyloid-β load in cognitively normal older adults

Osteoporosis and Alzheimer's disease (AD) mainly affect older individuals, and the possibility of an underlying link contributing to their shared epidemiological features has rarely been investigated. In the current study, we investigated the association between levels of plasma sclerostin (SOST), a protein primarily produced by bone, and brain amyloid-beta (Aβ) load, a pathological hallmark of AD. The study enrolled participants meeting a set of screening inclusion and exclusion criteria and were stratified into Aβ- (n = 65) and Aβ+ (n = 35) according to their brain Aβ load assessed using Aβ-PET (positron emission tomography) imaging. Plasma SOST levels, apolipoprotein E gene (APOE) genotype and several putative AD blood-biomarkers including Aβ40, Aβ42, Aβ42/Aβ40, neurofilament light (NFL), glial fibrillary acidic protein (GFAP), total tau (t-tau) and phosphorylated tau (p-tau181 and p-tau231) were detected and compared. It was found that plasma SOST levels were significantly higher in the Aβ+ group (71.49 ± 25.00 pmol/L) compared with the Aβ- group (56.51 ± 22.14 pmol/L) (P < 0.01). Moreover, Spearman's correlation analysis showed that plasma SOST concentrations were positively correlated with brain Aβ load (ρ = 0.321, P = 0.001). Importantly, plasma SOST combined with Aβ42/Aβ40 ratio significantly increased the area under the curve (AUC) when compared with using Aβ42/Aβ40 ratio alone (AUC = 0.768 vs 0.669, P = 0.027). In conclusion, plasma SOST levels are elevated in cognitively unimpaired older adults at high risk of AD and SOST could complement existing plasma biomarkers to assist in the detection of preclinical AD.

Deciphering Protein Secretion from the Brain to Cerebrospinal Fluid for Biomarker Discovery

Cerebrospinal fluid (CSF) is an essential matrix for the discovery of neurological disease biomarkers. However, the high dynamic range of protein concentrations in CSF hinders the detection of the least abundant protein biomarkers by untargeted mass spectrometry. It is thus beneficial to gain a deeper understanding of the secretion processes within the brain. Here, we aim to explore if and how the secretion of brain proteins to the CSF can be predicted. By combining a curated CSF proteome and the brain elevated proteome of the Human Protein Atlas, brain proteins were classified as CSF or non-CSF secreted. A machine learning model was trained on a range of sequence-based features to differentiate between CSF and non-CSF groups and effectively predict the brain origin of proteins. The classification model achieves an area under the curve of 0.89 if using high confidence CSF proteins. The most important prediction features include the subcellular localization, signal peptides, and transmembrane regions. The classifier generalized well to the larger brain detected proteome and is able to correctly predict novel CSF proteins identified by affinity proteomics. In addition to elucidating the underlying mechanisms of protein secretion, the trained classification model can support biomarker candidate selection.

A Head-to-Head Comparison Between Plasma pTau181 and Tau PET Along the Alzheimer's Disease Continuum

Both plasma tau phosphorylated at threonine-181 (pTau181) and tau PET show potential for detecting Alzheimer's disease (AD) pathology and predicting clinical progression. In this study, we performed a head-to-head comparison between plasma pTau181 and tau PET along the AD continuum. Methods: We included participants from the Amsterdam Dementia Cohort who underwent ¹⁸F-flortaucipir (tau) PET and had a plasma sample biobanked within 12 mo from tau PET. Fifty subjective cognitive decline (SCD) participants (31 Aβ-negative and 19 Aβ-positive) and 60 Aβ-positive participants with mild cognitive impairment (MCI) or dementia due to AD were included. A subset had 2-y longitudinal plasma pTau181 and tau PET available (n = 40). Longitudinal neuropsychological test data covering 3.2 ± 2.7 y from both before and after tau PET were available. Plasma pTau181 and tau PET were compared in their accuracies in discriminating between cognitive stage (MCI/AD vs. SCD) and preclinical Aβ status (SCD Aβ-positive vs. SCD Aβ-negative), their associations with cross-sectional and longitudinal neuropsychological test performance, and their longitudinal changes over time. Results: When discriminating between preclinical Aβ status, the area under the curve (AUC) for plasma pTau181 (0.83) and tau PET (entorhinal, 0.87; temporal, 0.85; neocortical, 0.67) were equally high (all DeLong P > 0.05), but tau PET outperformed plasma pTau181 in discriminating MCI/AD from SCD (AUC for plasma pTau181: 0.74; AUCs for tau PET: entorhinal, 0.89; temporal, 0.92; neocortical, 0.89) (all P < 0.01). Overall, tau PET showed stronger associations with cognitive decline and was associated with a wider variety of cognitive tests than plasma pTau181 (plasma pTau181, -0.02 > β < -0.12; tau PET, -0.01 > β < -0.22). Both plasma pTau181 and tau PET increased more steeply over time in MCI/AD than in SCD (P < 0.05), but only tau PET annual changes were associated with cognitive decline. Conclusion: Our results suggest that plasma pTau181 and tau PET perform equally well in identifying Aβ pathology but that tau PET better monitors disease stage and clinical progression.

Plasma biomarkers predict amyloid pathology in cognitively normal monozygotic twins after 10 years

Blood-based biomarkers could prove useful to predict Alzheimer's disease core pathologies in advance of clinical symptoms. Implementation of such biomarkers requires a solid understanding of their long-term dynamics and the contribution of confounding to their association with Alzheimer's disease pathology. Here we assess the value of plasma amyloid-β_1-42/1-40, phosphorylated-tau181 and glial fibrillary acidic protein to detect early Alzheimer's disease pathology, accounting for confounding by genetic and early environmental factors. Participants were 200 monozygotic twins, aged ≥60 years with normal cognition from the european medical information framework for Alzheimer's disease study. All twins had amyloid-β status and plasma samples available at study enrolment. For 80 twins, additional plasma samples were available that had been collected approximately 10 years prior to amyloid-β status assessment. Single-molecule array assays were applied to measure amyloid-β_1-42/1-40, phosphorylated-tau181 and glial fibrillary acidic protein. Predictive value of and longitudinal change in these biomarkers were assessed using receiver operating characteristic curve analysis and linear mixed models. Amyloid pathology could be predicted using blood-based biomarkers obtained at the time of amyloid status assessment (amyloid-β_1-42/1-40: area under the curve = 0.65, P = 0.01; phosphorylated-tau181: area under the curve = 0.84, P < 0.001; glial fibrillary acidic protein: area under the curve = 0.74, P < 0.001), as well as using those obtained 10 years prior to amyloid status assessment (amyloid-β_1-42/1-40: area under the curve = 0.69, P = 0.03; phosphorylated-tau181: area under the curve = 0.92, P < 0.001; glial fibrillary acidic protein: area under the curve = 0.84, P < 0.001). Longitudinally, amyloid-β_1-42/1-40 levels decreased [β (SE) = -0.12 (0.01), P < 0.001] and phosphorylated-tau181 levels increased [β (SE) = 0.02 (0.01), P = 0.004]. Amyloid-β-positive individuals showed a steeper increase in phosphorylated-tau181 compared with amyloid-β-negative individuals [β (SE) = 0.06 (0.02), P = 0.004]. Also amyloid-β-positive individuals tended to show a steeper increase in glial fibrillary acidic protein [β (SE) = 0.04 (0.02), P = 0.07]. Within monozygotic twin pairs, those with higher plasma phosphorylated-tau181 and lower amyloid-β_1-42/1-40 levels were more likely to be amyloid-β positive [β (SE) = 0.95 (0.26), P < 0.001; β (SE) = -0.28 (0.14), P < 0.05] indicating minimal contribution of confounding by genetic and early environmental factors. Our data support the use of amyloid-β_1-42/1-40, phosphorylated-tau181 and glial fibrillary acidic protein as screening tools for Alzheimer's disease pathology in the normal aging population, which is of importance for enrolment of high-risk subjects in secondary, or even primary, prevention trials. Furthermore, these markers show potential as low-invasive monitoring tool of disease progression and possibly treatment effects in clinical trials.

Age- and disease-specific reference values for neurofilament light presented in an online interactive support interface

Interpretation of axonal damage biomarker Neurofilament Light chain (NfL) concentrations is difficult due to the lack of age-specific and disease-specific reference values. We here developed an interactive interface to support interpretation of NfL results in human body fluids. We used NfL values of 1698 individuals without a neurological disorder, aged 19-85 years, and patients with MS and dementias. Percentile regression estimates per diagnosis populate interactive graphs, alongside NfL background information (available on: https://mybiomarkers.shinyapps.io/Neurofilament). This accessible interface provides reference for interpretation of the individual patient results for clinicians. It showcases an adaptable method to support interpretation of age-dependent biomarkers in neurology.

Differential diagnostic performance of a panel of plasma biomarkers for different types of dementia

Introduction

We explored what combination of blood‐based biomarkers (amyloid beta [Aβ]_{1‐42/1‐40}, phosphorylated tau [p‐tau]181, neurofilament light [NfL], glial fibrillary acidic protein [GFAP]) differentiates Alzheimer's disease (AD) dementia, frontotemporal dementia (FTD), and dementia with Lewy bodies (DLB).

Methods

We measured the biomarkers with Simoa in two separate cohorts (n = 160 and n = 152). In one cohort, Aβ_{1‐42/1‐40} was also measured with mass spectrometry (MS). We assessed the differential diagnostic value of the markers, by logistic regression with Wald's backward selection.

Results

MS and Simoa Aβ_{1‐42/1‐40} similarly differentiated AD from controls. The Simoa panel that optimally differentiated AD from FTD consisted of NfL and p‐tau181 (area under the curve [AUC] = 0.94; cohort 1) or NfL, GFAP, and p‐tau181 (AUC = 0.90; cohort 2). For AD from DLB, the panel consisted of NfL, p‐tau181, and GFAP (AUC = 0.88; cohort 1), and only p‐tau181 (AUC = 0.81; cohort 2).

Discussion

A combination of plasma p‐tau181, NfL, and GFAP, but not Aβ_{1‐42/1‐40}, might be useful to discriminate AD, FTD, and DLB.

Pre-analytical stability of serum biomarkers for neurological disease: neurofilament-light, glial fibrillary acidic protein and contactin-1

OBJECTIVES

Neurofilament-light (NfL), glial fibrillary acidic protein (GFAP) and contactin-1 (CNTN1) are blood-based biomarkers that could contribute to monitoring and prediction of disease and treatment outcomes in neurological diseases. Pre-analytical sample handling might affect results, which could be disease-dependent. We tested common handling variations in serum of volunteers as well as in a defined group of patients with multiple sclerosis (pwMS).

METHODS

Sample sets from 5 pwMS and 5 volunteers at the outpatient clinic were collected per experiment. We investigated the effect of the following variables: collection tube type, delayed centrifugation, centrifugation temperature, delayed storage after centrifugation and freeze-thawing. NfL and GFAP were measured by Simoa and CNTN1 by Luminex. A median recovery of 90-110% was considered stable.

RESULTS

For most pre-analytical variables, serum NfL and CNTN1 levels remained unaffected. In the total group, NfL levels increased (121%) after 6 h of delay at 2-8 °C until centrifugation, while no significant changes were observed after 24 h delay at room temperature (RT). In pwMS specifically, CNTN1 levels increased from additional freeze-thaw cycles number 2 to 4 (111%-141%), whereas volunteer levels remained stable. GFAP showed good stability for all pre-analytical variables.

CONCLUSIONS

Overall, the serum biomarkers tested were relatively unaffected by variations in sample handling. For serum NfL, we recommend storage at RT before centrifugation at 2-8 °C up to 6 h or at RT up to 24 h. For serum CNTN1, we advise a maximum of two freeze-thaw cycles. Our results confirm and expand on recently launched consensus standardized operating procedures.

Association of CSF, Plasma, and Imaging Markers of Neurodegeneration With Clinical Progression in People With Subjective Cognitive Decline

Background and Objectives

Multiple biomarkers have been suggested to measure neurodegeneration (N) in the AT(N) framework, leading to inconsistencies between studies. We investigated the association of 5 N biomarkers with clinical progression and cognitive decline in individuals with subjective cognitive decline (SCD).

Methods

We included individuals with SCD from the Amsterdam Dementia Cohort and SCIENCe project, a longitudinal cohort study (follow-up 4±3 years). We used the following N biomarkers: CSF total tau (t-tau), medial temporal atrophy visual rating on MRI, hippocampal volume (HV), serum neurofilament light (NfL), and serum glial fibrillary acidic protein (GFAP). We determined correlations between biomarkers. We assessed associations between N biomarkers and clinical progression to mild cognitive impairment or dementia (Cox regression) and Mini-Mental State Examination (MMSE) over time (linear mixed models). Models included age, sex, CSF β-amyloid (Aβ) (A), and CSF p-tau (T) as covariates, in addition to the N biomarker.

Result

We included 401 individuals (61±9 years, 42% female, MMSE 28 ± 2, vascular comorbidities 8%–19%). N biomarkers were modestly to moderately correlated (range r −0.28 – 0.58). Serum NfL and GFAP correlated most strongly (r 0.58, p < 0.01). T-tau was strongly correlated with p-tau (r 0.89, p < 0.01), although these biomarkers supposedly represent separate biomarker groups. All N biomarkers individually predicted clinical progression, but only HV, NfL, and GFAP added predictive value beyond Aβ and p-tau (hazard ratio 1.52 [95% CI 1.11–2.09]; 1.51 [1.05–2.17]; 1.50 [1.04–2.15]). T-tau, HV, and GFAP individually predicted MMSE slope (range β −0.17 to −0.11, p < 0.05), but only HV remained associated beyond Aβ and p-tau (β −0.13 [SE 0.04]; p < 0.05).

Discussion

In cognitively unimpaired older adults, correlations between different N biomarkers were only moderate, indicating they reflect different aspects of neurodegeneration and should not be used interchangeably. T-tau was strongly associated with p-tau (T), which makes it less desirable to use as a measure for N. HV, NfL, and GFAP predicted clinical progression beyond A and T. Our results do not allow to choose one most suitable biomarker for N, but illustrate the added prognostic value of N beyond A and T.

Classification of Evidence

This study provides Class II evidence that HV, NfL, and GFAP predicted clinical progression beyond A and T in individuals with SCD.

Detecting amyloid positivity in early Alzheimer's disease using combinations of plasma Aβ42/Aβ40 and p-tau

INTRODUCTION

We studied usefulness of combining blood amyloid beta (Aβ)42/Aβ40, phosphorylated tau (p-tau)217, and neurofilament light (NfL) to detect abnormal brain Aβ deposition in different stages of early Alzheimer's disease (AD).

METHODS

Plasma biomarkers were measured using mass spectrometry (Aβ42/Aβ40) and immunoassays (p-tau217 and NfL) in cognitively unimpaired individuals (CU, N = 591) and patients with mild cognitive impairment (MCI, N = 304) from two independent cohorts (BioFINDER-1, BioFINDER-2).

RESULTS

In CU, a combination of plasma Aβ42/Aβ40 and p-tau217 detected abnormal brain Aβ status with area under the curve (AUC) of 0.83 to 0.86. In MCI, the models including p-tau217 alone or Aβ42/Aβ40 and p-tau217 had similar AUCs (0.86-0.88); however, the latter showed improved model fit. The models were implemented in an online application providing individualized risk assessments (https://brainapps.shinyapps.io/PredictABplasma/).

DISCUSSION

A combination of plasma Aβ42/Aβ40 and p-tau217 discriminated Aβ status with relatively high accuracy, whereas p-tau217 showed strongest associations with Aβ pathology in MCI but not in CU.

Clinical and analytical comparison of six Simoa assays for plasma P-tau isoforms P-tau181, P-tau217, and P-tau231

INTRODUCTION

Studies using different assays and technologies showed highly promising diagnostic value of plasma phosphorylated (P-)tau levels for Alzheimer's disease (AD). We aimed to compare six P-tau Simoa assays, including three P-tau181 (Eli Lilly, ADx, Quanterix), one P-tau217 (Eli Lilly), and two P-tau231 (ADx, Gothenburg).

METHODS

We studied the analytical (sensitivity, precision, parallelism, dilution linearity, and recovery) and clinical (40 AD dementia patients, age 66±8years, 50%F; 40 age- and sex-matched controls) performance of the assays.

RESULTS

All assays showed robust analytical performance, and particularly P-tau217 Eli Lilly; P-tau231 Gothenburg and all P-tau181 assays showed robust clinical performance to differentiate AD from controls, with AUCs 0.936-0.995 (P-tau231 ADx: AUC = 0.719). Results obtained with all P-tau181 assays, P-tau217 Eli Lilly assay, and P-tau231 Gothenburg assay strongly correlated (Spearman's rho > 0.86), while correlations with P-tau231 ADx results were moderate (rho < 0.65).

DISCUSSION

P-tau isoforms can be measured robustly by several novel high-sensitive Simoa assays.

Blood-based biomarkers for Alzheimer's disease: towards clinical implementation

For many years, blood-based biomarkers for Alzheimer's disease seemed unattainable, but recent results have shown that they could become a reality. Convincing data generated with new high-sensitivity assays have emerged with remarkable consistency across different cohorts, but also independent of the precise analytical method used. Concentrations in blood of amyloid and phosphorylated tau proteins associate with the corresponding concentrations in CSF and with amyloid-PET or tau-PET scans. Moreover, other blood-based biomarkers of neurodegeneration, such as neurofilament light chain and glial fibrillary acidic protein, appear to provide information on disease progression and potential for monitoring treatment effects. Now the question emerges of when and how we can bring these biomarkers to clinical practice. This step would pave the way for blood-based biomarkers to support the diagnosis of, and development of treatments for, Alzheimer's disease and other dementias.

Characterization of pre-analytical sample handling effects on a panel of Alzheimer's disease-related blood-based biomarkers: Results from the Standardization of Alzheimer's Blood Biomarkers (SABB) working group

Introduction

Pre‐analytical sample handling might affect the results of Alzheimer's disease blood‐based biomarkers. We empirically tested variations of common blood collection and handling procedures.

Methods

We created sample sets that address the effect of blood collection tube type, and of ethylene diamine tetraacetic acid plasma delayed centrifugation, centrifugation temperature, aliquot volume, delayed storage, and freeze–thawing. We measured amyloid beta (Aβ)42 and 40 peptides with six assays, and Aβ oligomerization‐tendency (OAβ), amyloid precursor protein (APP)_699‐711, glial fibrillary acidic protein (GFAP), neurofilament light (NfL), total tau (t‐tau), and phosphorylated tau181.

Results

Collection tube type resulted in different values of all assessed markers. Delayed plasma centrifugation and storage affected Aβ and t‐tau; t‐tau was additionally affected by centrifugation temperature. The other markers were resistant to handling variations.

Discussion

We constructed a standardized operating procedure for plasma handling, to facilitate introduction of blood‐based biomarkers into the research and clinical settings.

Head-to-Head Comparison of 8 Plasma Amyloid-β 42/40 Assays in Alzheimer Disease

Importance

Blood-based tests for brain amyloid-β (Aβ) pathology are needed for widespread implementation of Alzheimer disease (AD) biomarkers in clinical care and to facilitate patient screening and monitoring of treatment responses in clinical trials.

Objective

To compare the performance of plasma Aβ42/40 measured using 8 different Aβ assays when detecting abnormal brain Aβ status in patients with early AD.

Design, Setting, and Participants

This study included 182 cognitively unimpaired participants and 104 patients with mild cognitive impairment from the BioFINDER cohort who were enrolled at 3 different hospitals in Sweden and underwent Aβ positron emission tomography (PET) imaging and cerebrospinal fluid (CSF) and plasma collection from 2010 to 2014. Plasma Aβ42/40 was measured using an immunoprecipitation-coupled mass spectrometry developed at Washington University (IP-MS-WashU), antibody-free liquid chromatography MS developed by Araclon (LC-MS-Arc), and immunoassays from Roche Diagnostics (IA-Elc); Euroimmun (IA-EI); and Amsterdam University Medical Center, ADx Neurosciences, and Quanterix (IA-N4PE). Plasma Aβ42/40 was also measured using an IP-MS-based method from Shimadzu in 200 participants (IP-MS-Shim) and an IP-MS-based method from the University of Gothenburg (IP-MS-UGOT) and another immunoassay from Quanterix (IA-Quan) among 227 participants. For validation, 122 participants (51 cognitively normal, 51 with mild cognitive impairment, and 20 with AD dementia) were included from the Alzheimer Disease Neuroimaging Initiative who underwent Aβ-PET and plasma Aβ assessments using IP-MS-WashU, IP-MS-Shim, IP-MS-UGOT, IA-Elc, IA-N4PE, and IA-Quan assays.

Main Outcomes and Measures

Discriminative accuracy of plasma Aβ42/40 quantified using 8 different assays for abnormal CSF Aβ42/40 and Aβ-PET status.

Results

A total of 408 participants were included in this study. In the BioFINDER cohort, the mean (SD) age was 71.6 (5.6) years and 49.3% of the cohort were women. When identifying participants with abnormal CSF Aβ42/40 in the whole cohort, plasma IP-MS-WashU Aβ42/40 showed significantly higher accuracy (area under the receiver operating characteristic curve [AUC], 0.86; 95% CI, 0.81-0.90) than LC-MS-Arc Aβ42/40, IA-Elc Aβ42/40, IA-EI Aβ42/40, and IA-N4PE Aβ42/40 (AUC range, 0.69-0.78; P < .05). Plasma IP-MS-WashU Aβ42/40 performed significantly better than IP-MS-UGOT Aβ42/40 and IA-Quan Aβ42/40 (AUC, 0.84 vs 0.68 and 0.64, respectively; P < .001), while there was no difference in the AUCs between IP-MS-WashU Aβ42/40 and IP-MS-Shim Aβ42/40 (0.87 vs 0.83; P = .16) in the 2 subcohorts where these biomarkers were available. The results were similar when using Aβ-PET as outcome. Plasma IPMS-WashU Aβ42/40 and IPMS-Shim Aβ42/40 showed highest coefficients for correlations with CSF Aβ42/40 (r range, 0.56-0.65). The BioFINDER results were replicated in the Alzheimer Disease Neuroimaging Initiative cohort (mean [SD] age, 72.4 [5.4] years; 43.4% women), where the IP-MS-WashU assay performed significantly better than the IP-MS-UGOT, IA-Elc, IA-N4PE, and IA-Quan assays but not the IP-MS-Shim assay.

Conclusions and Relevance

The results from 2 independent cohorts indicate that certain MS-based methods performed better than most of the immunoassays for plasma Aβ42/40 when detecting brain Aβ pathology.

The global Alzheimer's Association round robin study on plasma amyloid β methods

INTRODUCTION

Blood-based assays to measure brain amyloid beta (Aβ) deposition are an attractive alternative to the cerebrospinal fluid (CSF)-based assays currently used in clinical settings. In this study, we examined different blood-based assays to measure Aβ and how they compare among centers and assays.

METHODS

Aliquots from 81 plasma samples were distributed to 10 participating centers. Seven immunological assays and four mass-spectrometric methods were used to measure plasma Aβ concentrations.

RESULTS

Correlations were weak for Aβ42 while Aβ40 correlations were stronger. The ratio Aβ42/Aβ40 did not improve the correlations and showed weak correlations.

DISCUSSION

The poor correlations for Aβ42 in plasma might have several potential explanations, such as the high levels of plasma proteins (compared to CSF), sensitivity to pre-analytical sample handling and specificity, and cross-reactivity of different antibodies. Different methods might also measure different pools of plasma Aβ42. We, however, hypothesize that greater correlations might be seen in future studies because many of the methods have been refined during completion of this study.

BDNF-Met polymorphism and amyloid-beta in relation to cognitive decline in cognitively normal elderly: the SCIENCe project

Brain-derived neurotrophic factor (BNDF) plays a role in synapse integrity. We investigated in 398 cognitively normal adults (60±8years, 41% female, MMSE=28±1) the joint association of the Val66Met polymorphism of the BDNF gene (Met+/-) and plasma BDNF levels and abnormal cerebrospinal fluid (CSF) amyloid-beta status (A+/-) with cognitive decline and dementia risk. Age-, sex- and education-adjusted linear mixed models showed that compared to Met-A-, Met+A+ showed steeper decline on tests of global cognition, memory, language, attention and executive functioning, while Met-A+ showed steeper decline on a smaller number of tests. There were no associations between Met+A- and cognitive decline. Cox models showed that compared to Met-A-, Met+A+ participants were at increased risk of dementia (HR=8.8, 95%CI: 2.8-27.9), as were Met-A+ participants (HR=6.5, 95%CI: 2.2-19.5). Lower plasma BDNF was associated with an increased risk of progression to dementia in the A+ participants. Our results imply that Met-carriage on top of amyloid-beta pathology might increase rate of cognitive decline to dementia.

Ultrasensitive immunoassay allows measurement of serum neurofilament heavy in multiple sclerosis

BACKGROUND

Neurofilament heavy (NfH) is a promising biomarker for neuro-axonal damage in Multiple Sclerosis (MS). We compared the performance of high-sensitivity serum-NfH immunoassays, with as aim to investigate the value of serum-NfH as biomarker for MS.

METHODS

We measured serum-NfH in 76 MS patients with Simoa (one commercial, one in-house) or Luminex assays. Serum-NfH measured by the immunoassay with greatest sensitivity was related to clinical and radiological outcomes with age and sex-adjusted linear regression analysis, and to biological outcomes cerebrospinal fluid (CSF)-NfH, serum neurofilament light (NfL) and CSF-NfL with Spearman's correlation analysis.

RESULTS

With the commercial Simoa assay, we obtained 100% serum-NfH detectability (in-house Simoa: 70%, Luminex: 61%), with lowest coefficient of variation (CV) between duplicates of 11%CV (in-house Simoa: 22%CV, Luminex: 30%CV). Serum-NfH quantified with the commercial Simoa assay was associated with disease duration (standardized beta (sβ) = 0.28, p = 0.034), T2 lesion volume (sβ = 0.23, p = 0.041), and tended to associate with black hole count (sβ = 0.21, p = 0.084) but not with Expanded Disease Disability Score (EDSS) or normalized brain volume (all: p>0.10). Furthermore, serum-NfH showed correlations with CSF-NfH (rho = 0.27, p = 0.018) and serum-NfL (rho=0.44, p < 0.001), but not with CSF-NfL.

CONCLUSIONS

Serum-NfH can be quantified with high-sensitivity technology. Cross-sectionally, we observed some weak correlations of serum-NfH with MS disease burden parameters, suggesting there might be some utility for serum-NfH as biomarker for MS disease burden.

Plasma glial fibrillary acidic protein is elevated in cognitively normal older adults at risk of Alzheimer's disease

Glial fibrillary acidic protein (GFAP), an astrocytic cytoskeletal protein, can be measured in blood samples, and has been associated with Alzheimer's disease (AD). However, plasma GFAP has not been investigated in cognitively normal older adults at risk of AD, based on brain amyloid-β (Aβ) load. Cross-sectional analyses were carried out for plasma GFAP and plasma Aβ1-42/Aβ1-40 ratio, a blood-based marker associated with brain Aβ load, in participants (65-90 years) categorised into low (Aβ-, n = 63) and high (Aβ+, n = 33) brain Aβ load groups via Aβ positron emission tomography. Plasma GFAP, Aβ1-42, and Aβ1-40 were measured using the Single molecule array (Simoa) platform. Plasma GFAP levels were significantly higher (p < 0.00001), and plasma Aβ1-42/Aβ1-40 ratios were significantly lower (p < 0.005), in Aβ+ participants compared to Aβ- participants, adjusted for covariates age, sex, and apolipoprotein E-ε4 carriage. A receiver operating characteristic curve based on a logistic regression of the same covariates, the base model, distinguished Aβ+ from Aβ- (area under the curve, AUC = 0.78), but was outperformed when plasma GFAP was added to the base model (AUC = 0.91) and further improved with plasma Aβ1-42/Aβ1-40 ratio (AUC = 0.92). The current findings demonstrate that plasma GFAP levels are elevated in cognitively normal older adults at risk of AD. These observations suggest that astrocytic damage or activation begins from the pre-symptomatic stage of AD and is associated with brain Aβ load. Observations from the present study highlight the potential of plasma GFAP to contribute to a diagnostic blood biomarker panel (along with plasma Aβ1-42/Aβ1-40 ratios) for cognitively normal older adults at risk of AD.

Amyloid-β misfolding as a plasma biomarker indicates risk for future clinical Alzheimer's disease in individuals with subjective cognitive decline

Background

We evaluated Aβ misfolding in combination with Aβ_42/40 ratio as a prognostic tool for future clinical progression to mild cognitive impairment (MCI) or dementia due to Alzheimer’s disease (AD) in individuals with subjective cognitive decline (SCD).

Methods

Baseline plasma samples (n = 203) from SCD subjects in the SCIENCe project and Amsterdam Dementia Cohort (age 61 ± 9 years; 57% male, mean follow-up time 2.7 years) were analyzed using immuno-infrared-sensor technology. Within 6 years of follow-up, 22 (11%) individuals progressed to MCI or dementia due to AD. Sensor readout values > 1646 cm^− 1 reflected normal Aβ folding; readouts at ≤ 1646 cm^− 1 reflected low and at < 1644 cm^− 1 high misfolding. We used Cox proportional hazard models to quantify Aβ misfolding as a prognostic biomarker for progression to MCI and dementia due to AD. The accuracy of the predicted development of MCI/AD was determined by time-dependent receiver operating characteristic (t-ROC) curve analyses that take individual follow-up and conversion times into account. Statistical models were adjusted for age, sex, and APOEε4 status. Additionally, plasma Aβ_42/40 data measured by SIMOA were statistically analyzed and compared.

Results

All 22 patients who converted to MCI or AD-dementia within 6 years exhibited Aβ misfolding at baseline. Cox analyses revealed a hazard ratio (HR) of 19 (95% confidence interval [CI] 2.2–157.8) for future conversion of SCD subjects with high misfolding and of 11 (95% CI 1.0–110.1) for those with low misfolding. T-ROC curve analyses yielded an area under the curve (AUC) of 0.94 (95% CI 0.86–1.00; 6-year follow-up) for Aβ misfolding in an age, sex, and APOEε4 model. A similar model with plasma Aβ_42/40 ratio yielded an AUC of 0.92 (95% CI, 0.82–1.00). The AUC increased to 0.99 (95% CI, 0.99–1.00) after inclusion of both Aβ misfolding and the Aβ_42/40 ratio.

Conclusions

A panel of structure- and concentration-based plasma amyloid biomarkers may predict conversion to clinical MCI and dementia due to AD in cognitively unimpaired subjects. These plasma biomarkers provide a noninvasive and cost-effective alternative for screening early AD pathological changes. Follow-up studies and external validation in larger cohorts are in progress for further validation of our findings.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-020-00738-8.

Comparison of ELISA- and SIMOA-based quantification of plasma Aβ ratios for early detection of cerebral amyloidosis

BACKGROUND

Blood-based amyloid biomarkers may provide a non-invasive, cost-effective and scalable manner for detecting cerebral amyloidosis in early disease stages.

METHODS

In this prospective cross-sectional study, we quantified plasma Aβ1-42/Aβ1-40 ratios with both routinely available ELISAs and novel SIMOA Amyblood assays, and provided a head-to-head comparison of their performances to detect cerebral amyloidosis in a nondemented elderly cohort (n = 199). Participants were stratified according to amyloid-PET status, and the performance of plasma Aβ1-42/Aβ1-40 to detect cerebral amyloidosis was assessed using receiver operating characteristic analysis. We additionally investigated the correlations of plasma Aβ ratios with amyloid-PET and CSF Alzheimer's disease biomarkers, as well as platform agreement using Passing-Bablok regression and Bland-Altman analysis for both Aβ isoforms.

RESULTS

ELISA and SIMOA plasma Aβ1-42/Aβ1-40 detected cerebral amyloidosis with identical accuracy (ELISA: area under curve (AUC) 0.78, 95% CI 0.72-0.84; SIMOA: AUC 0.79, 95% CI 0.73-0.85), and both increased the performance of a basic demographic model including only age and APOE-ε4 genotype (p ≤ 0.02). ELISA and SIMOA had positive predictive values of respectively 41% and 36% in cognitively normal elderly and negative predictive values all exceeding 88%. Plasma Aβ1-42/Aβ1-40 correlated similarly with amyloid-PET for both platforms (Spearman ρ = - 0.32, p <  0.0001), yet correlations with CSF Aβ1-42/t-tau were stronger for ELISA (ρ = 0.41, p = 0.002) than for SIMOA (ρ = 0.29, p = 0.03). Plasma Aβ levels demonstrated poor agreement between ELISA and SIMOA with concentrations of both Aβ1-42 and Aβ1-40 measured by SIMOA consistently underestimating those measured by ELISA.

CONCLUSIONS

ELISA and SIMOA demonstrated equivalent performances in detecting cerebral amyloidosis through plasma Aβ1-42/Aβ1-40, both with high negative predictive values, making them equally suitable non-invasive prescreening tools for clinical trials by reducing the number of necessary PET scans for clinical trial recruitment.

TRIAL REGISTRATION

EudraCT 2009-014475-45 (registered on 23 Sept 2009) and EudraCT 2013-004671-12 (registered on 20 May 2014, https://www.clinicaltrialsregister.eu/ctr-search/trial/2013-004671-12/BE ).

Variations in consecutive serum neurofilament light levels in healthy controls and multiple sclerosis patients

Background Neurofilament light is a neuronal protein detectable in serum (sNfL), with high potential as disease activity biomarker in multiple sclerosis (MS). To date, little is known about sNfL fluctuations between 2 consecutive measurements in healthy controls (HC) and MS patients. Yet this information is critical, as it will help define a clinically significant variation. Methods sNfL was measured at 2 consecutive time points in a cohort of 90 MS patients (untreated relapsing remitting MS (uRRMS), n=35; treated relapsing remitting MS (tRRMS), n= 21; secondary progressive MS, SPMS, n=21; primary progressive MS, PPMS, n=13), and 90 age-matched HC, using the Simoa NfL light® assay. Results Mean sNfL was elevated in all MS subtypes compared to HC (p<0.0001), and positively associated with age in HC (r=0.70, p<0.001), confirming previous reports. Mean sNfL was higher at follow-up compared to baseline in HC (p<0.001), and lower in uRRMS(p=0.036) and tRRMS (p=0.008). At follow-up, a similar proportion of HC (50.0%), untreated RRMS (51.4%), treated RRMS (33.3%), SPMS (45.0%) and PPMS (46.2%) had variations in sNfL levels exceeding 20% of baseline levels. Conclusions Our data suggest variations in sNfL occur both in HC and MS populations to a similar extent and magnitude. Variations between two consecutive sNfL measurements may reflect natural variations and not necessarily variations in inflammatory disease activity.

Combination of plasma amyloid beta(1-42/1-40) and glial fibrillary acidic protein strongly associates with cerebral amyloid pathology

BACKGROUND

Blood-based biomarkers for Alzheimer's disease (AD) might facilitate identification of participants for clinical trials targeting amyloid beta (Abeta) accumulation, and aid in AD diagnostics. We examined the potential of plasma markers Abeta_(1-42/1-40), glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) to identify cerebral amyloidosis and/or disease severity.

METHODS

We included individuals with a positive (n = 176: 63 ± 7 years, 87 (49%) females) or negative (n = 76: 61 ± 9 years, 27 (36%) females) amyloid PET status, with syndrome diagnosis subjective cognitive decline (18 PET+, 25 PET-), mild cognitive impairment (26 PET+, 24 PET-), or AD-dementia (132 PET+). Plasma Abeta_(1-42/1-40), GFAP, and NfL were measured by Simoa. We applied two-way ANOVA adjusted for age and sex to investigate the associations of the plasma markers with amyloid PET status and syndrome diagnosis; logistic regression analysis with Wald's backward selection to identify an optimal panel that identifies amyloid PET positivity; age, sex, and education-adjusted linear regression analysis to investigate associations between the plasma markers and neuropsychological test performance; and Spearman's correlation analysis to investigate associations between the plasma markers and medial temporal lobe atrophy (MTA).

RESULTS

Abeta_(1-42/1-40) and GFAP independently associated with amyloid PET status (p = 0.009 and p < 0.001 respectively), and GFAP and NfL independently associated with syndrome diagnosis (p = 0.001 and p = 0.048 respectively). The optimal panel identifying a positive amyloid status included Abeta_(1-42/1-40) and GFAP, alongside age and APOE (AUC = 88% (95% CI 83-93%), 82% sensitivity, 86% specificity), while excluding NfL and sex. GFAP and NfL robustly associated with cognitive performance on global cognition and all major cognitive domains (GFAP: range standardized β (sβ) = - 0.40 to - 0.26; NfL: range sβ = - 0.35 to - 0.18; all: p < 0.002), whereas Abeta_(1-42/1-40) associated with global cognition, memory, attention, and executive functioning (range sβ = 0.22 - 0.11; all: p < 0.05) but not language. GFAP and NfL showed moderate positive correlations with MTA (both: Spearman's rho> 0.33, p < 0.001). Abeta_(1-42/1-40) showed a moderate negative correlation with MTA (Spearman's rho = - 0.24, p = 0.001).

DISCUSSION AND CONCLUSIONS

Combination of plasma Abeta_(1-42/1-40) and GFAP provides a valuable tool for the identification of amyloid PET status. Furthermore, plasma GFAP and NfL associate with various disease severity measures suggesting potential for disease monitoring.

High efavirenz levels but not neurofilament light plasma levels are associated with poor neurocognitive functioning in asymptomatic HIV patients

The aim of this study is to assess the effect of efavirenz exposure on neurocognitive functioning and investigate plasma neurofilament light (Nfl) as a biomarker for neurocognitive damage. Sub-analysis of the ESCAPE-study, a randomised controlled trial where virologically suppressed, cognitively asymptomatic HIV patients were randomised (2:1) to switch to rilpivirine or continue on efavirenz. At baseline and week 12, patients underwent an extensive neuropsychological assessment (NPA), and serum efavirenz concentration and plasma Nfl levels were measured. Subgroups of elevated (≥ 4.0 mg/L) and therapeutic (0.74 to< 4.0 mg/L) baseline efavirenz concentration were made. Differences between these groups in baseline NPA Z-scores and in delta scores after efavirenz discontinuation were assessed. Nfl level was measured using an ELISA analysis using single molecule array (Simoa) technology. Correlation of plasma NFL with NPA Z-scores was evaluated using a linear mixed model. The elevated group consisted of 6 patients and the therapeutic group of 48. At baseline, the elevated group showed lower composite Z-scores (median - 1.03; IQR 0.87 versus 0.27; 0.79. p 0.02). This effect was also seen on the subdomains verbal (p 0.01), executive functioning (p 0.02), attention (p < 0.01) and speed (p 0.01). In the switch group, the elevated group improved more on composite scores after discontinuing efavirenz (mean 0.58; SD 0.32 versus 0.22; 0.54, p 0.15). No association between plasma Nfl and composite Z-score was found. High efavirenz exposure is associated with worse cognitive functioning compared with patients with therapeutic concentrations. Plasma Nfl is not a suitable biomarker to measure cognitive damage in this group.

ATN classification and clinical progression in subjective cognitive decline: The SCIENCe project

Objective

To investigate the relationship between the ATN classification system (amyloid, tau, neurodegeneration) and risk of dementia and cognitive decline in individuals with subjective cognitive decline (SCD).

Methods

We classified 693 participants with SCD (60 ± 9 years, 41% women, Mini-Mental State Examination score 28 ± 2) from the Amsterdam Dementia Cohort and Subjective Cognitive Impairment Cohort (SCIENCe) project according to the ATN model, as determined by amyloid PET or CSF β-amyloid (A), CSF p-tau (T), and MRI-based medial temporal lobe atrophy (N). All underwent extensive neuropsychological assessment. For 342 participants, follow-up was available (3 ± 2 years). As a control population, we included 124 participants without SCD.

Results

Fifty-six (n = 385) participants had normal Alzheimer disease (AD) biomarkers (A–T–N–), 27% (n = 186) had non-AD pathologic change (A–T–N+, A–T+N–, A–T+N+), 18% (n = 122) fell within the Alzheimer continuum (A+T–N–, A+T–N+, A+T+N–, A+T+N+). ATN profiles were unevenly distributed, with A–T+N+, A+T–N+, and A+T+N+ containing very few participants. Cox regression showed that compared to A–T–N–, participants in A+ profiles had a higher risk of dementia with a dose–response pattern for number of biomarkers affected. Linear mixed models showed participants in A+ profiles showed a steeper decline on tests addressing memory, attention, language, and executive functions. In the control group, there was no association between ATN and cognition.

Conclusions

Among individuals presenting with SCD at a memory clinic, those with a biomarker profile A–T+N+, A+T–N–, A+T+N–, and A+T+N+ were at increased risk of dementia, and showed steeper cognitive decline compared to A–T–N– individuals. These results suggest a future where biomarker results could be used for individualized risk profiling in cognitively normal individuals presenting at a memory clinic.

Plasma amyloid is associated with the rate of cognitive decline in cognitively normal elderly: the SCIENCe project

Plasma biomarkers are promising prognostic tools in individuals with subjective cognitive decline (SCD). We aimed to investigate the relationships of baseline plasma amyloid beta (Aβ)42/Aβ40 and total Tau (tTau) with rate of cognitive decline, in comparison to relationships of baseline cerebrospinal fluid (CSF) Aβ42, tTau, and phosphorylated tau181 (pTau181) with rate of cognitive decline. We included 241 subjects with SCD (age = 61 ± 9, 40% female, Mini-Mental State Examination = 28 ± 2) with follow-up (average: 2 ± 2 years, median visits: 3 [range: 1-11]) for re-evaluation of neuropsychological test performance (attention, memory, language, and executive functioning domains). Using age, gender and education-adjusted linear mixed models, we found that lower plasma Aβ42/Aβ40 was associated with steeper rate of decline on tests for attention, memory, and executive functioning, but not language. Lower CSF Aβ42 was associated with steeper decline on tests covering all domains. Associations for plasma amyloid and cognitive decline mirror those of CSF amyloid. Plasma tTau was not associated with rate of cognitive decline, whereas CSF tTau and pTau181 were on multiple tests covering all domains.

Serum neurofilament light chain in genetic frontotemporal dementia: a longitudinal, multicentre cohort study

BACKGROUND

Neurofilament light chain (NfL) is a promising blood biomarker in genetic frontotemporal dementia, with elevated concentrations in symptomatic carriers of mutations in GRN, C9orf72, and MAPT. A better understanding of NfL dynamics is essential for upcoming therapeutic trials. We aimed to study longitudinal NfL trajectories in people with presymptomatic and symptomatic genetic frontotemporal dementia.

METHODS

We recruited participants from 14 centres collaborating in the Genetic Frontotemporal Dementia Initiative (GENFI), which is a multicentre cohort study of families with genetic frontotemporal dementia done across Europe and Canada. Eligible participants (aged ≥18 years) either had frontotemporal dementia due to a pathogenic mutation in GRN, C9orf72, or MAPT (symptomatic mutation carriers) or were healthy at-risk first-degree relatives (either presymptomatic mutation carriers or non-carriers), and had at least two serum samples with a time interval of 6 months or more. Participants were excluded if they had neurological comorbidities that were likely to affect NfL, including cerebrovascular events. We measured NfL longitudinally in serum samples collected between June 8, 2012, and Dec 8, 2017, through follow-up visits annually or every 2 years, which also included MRI and neuropsychological assessments. Using mixed-effects models, we analysed NfL changes over time and correlated them with longitudinal imaging and clinical parameters, controlling for age, sex, and study site. The primary outcome was the course of NfL over time in the various stages of genetic frontotemporal dementia.

FINDINGS

We included 59 symptomatic carriers and 149 presymptomatic carriers of a mutation in GRN, C9orf72, or MAPT, and 127 non-carriers. Nine presymptomatic carriers became symptomatic during follow-up (so-called converters). Baseline NfL was elevated in symptomatic carriers (median 52 pg/mL [IQR 24-69]) compared with presymptomatic carriers (9 pg/mL [6-13]; p<0·0001) and non-carriers (8 pg/mL [6-11]; p<0·0001), and was higher in converters than in non-converting carriers (19 pg/mL [17-28] vs 8 pg/mL [6-11]; p=0·0007; adjusted for age). During follow-up, NfL increased in converters (b=0·097 [SE 0·018]; p<0·0001). In symptomatic mutation carriers overall, NfL did not change during follow-up (b=0·017 [SE 0·010]; p=0·101) and remained elevated. Rates of NfL change over time were associated with rate of decline in Mini Mental State Examination (b=-94·7 [SE 33·9]; p=0·003) and atrophy rate in several grey matter regions, but not with change in Frontotemporal Lobar Degeneration-Clinical Dementia Rating scale score (b=-3·46 [SE 46·3]; p=0·941).

INTERPRETATION

Our findings show the value of blood NfL as a disease progression biomarker in genetic frontotemporal dementia and suggest that longitudinal NfL measurements could identify mutation carriers approaching symptom onset and capture rates of brain atrophy. The characterisation of NfL over the course of disease provides valuable information for its use as a treatment effect marker.

FUNDING

ZonMw and the Bluefield project.

CSF or serum neurofilament light added to α-Synuclein panel discriminates Parkinson's from controls

BACKGROUND

Neurofilament light chain is a marker of axonal damage and is of interest as a biofluid biomarker for PD. The objective of this study was to investigate whether CSF or serum neurofilament contributes to a combination of CSF biomarkers in defining the optimal biomarker panel for discriminating PD patients from healthy controls. In addition, we aimed to assess whether CSF and/or serum neurofilament levels are associated with clinical measures of disease severity.

METHODS

We measured neurofilament light chain levels in CSF and/or serum of 139 PD patients and 52 age-matched healthy controls. We used stepwise logistic regression analyses to test whether neurofilament contributes to a biomarker CSF panel including total, oligomeric, and phosphorylated α-synuclein and Alzheimer's disease biomarkers. Measures of disease severity included disease duration, UPDRS-III, Hoehn & Yahr stage, and MMSE.

RESULTS

After correcting for age, CSF neurofilament levels were 42% higher in PD patients compared with controls (P < 0.01), whereas serum neurofilament levels were 37% higher (P = 0.08). Combining CSF neurofilament, phosphorylated-/total α-synuclein, and oligomeric-/total α-synuclein yielded the best-fitting model for discriminating PD patients from controls (area under the curve 0.92). The discriminatory potential of serum neurofilament in the CSF biomarker panel was similar (area under the curve 0.90). Higher serum neurofilament was associated with a lower MMSE score. There were no other associations between CSF and/or serum neurofilament levels and clinical disease severity.

CONCLUSIONS

CSF neurofilament contributes to a panel of CSF α-synuclein species in differentiating PD patients from healthy controls. Serum neurofilament may have added value to a biofluid biomarker panel for differentiating PD patients from controls. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Serum Neurofilament light correlates with CADASIL disease severity and survival

Objective

To validate whether serum Neurofilament Light‐chain (NfL) levels correlate with disease severity in CADASIL, and to determine whether serum NfL predicts disease progression and survival.

Methods

Fourty‐one (pre‐) manifest individuals with CADASIL causing NOTCH3 mutations and 22 healthy controls were recruited from CADASIL families. At baseline, MRI‐lesion load and clinical severity was determined and serum was stored. Disease progression was measured in 30/41 patients at 7‐year follow‐up, and survival of all individuals was determined at 17‐year follow‐up. Serum NfL levels were quantified using an ultra‐sensitive molecule array. Generalized estimated equation regression (GEE) was used to analyze association between serum NfL, MRI‐lesion load, disease severity, and disease progression. With GEE‐based Cox regression, survival was analyzed.

Results

At baseline, serum NfL levels correlated with MRI‐lesion load [lacune count (s = 0.64, P = 0.002), brain atrophy (r = −0.50, P = 0.001), and microbleed count (s = 0.48, P = 0.044)], cognition [CAMCOG (s = −0.45, P = 0.010), MMSE (r = −0.61, P = 0.003), GIT (r = −0.61, P < 0.001), TMT‐A (r = 0.70, P < 0.001)) and disability (mRS (r = 0.70, P = 0.002)]. Baseline serum NfL predicted 7‐year changes in disability (B = 0.34, P < 0.001) and cognition (CAMCOG B = −4.94, P = 0.032), as well as 17‐year survival. Higher NfL levels were associated with increased mortality (HR=1.8 per twofold increase in NfL levels, P = 0.006).

Interpretation

Serum NfL levels correlate with disease severity, disease progression and 17‐year survival in CADASIL patients. Serum NfL is a promising biomarker to monitor and predict disease course in CADASIL, as well as potentially assessing therapeutic response in future clinical trials.

Plasma Amyloid as Prescreener for the Earliest Alzheimer Pathological Changes

Objective

We investigated the association of plasma amyloid beta (Abeta)40, Abeta42, and total tau (tTau) with the presence of Alzheimer pathological changes in cognitively normal individuals with subjective cognitive decline (SCD).

Methods

We included 248 subjects with SCD (61 ± 9 years, 42% female, Mini‐Mental State Examination = 28 ± 2) from the SCIENCe project and Amsterdam Dementia Cohort. Subjects were dichotomized as amyloid abnormal by cerebrospinal fluid (CSF) and positron emission tomography (PET). Baseline plasma Abeta40, Abeta42, and tTau were measured using Simoa technology. Associations between plasma levels and amyloid status were assessed using logistic regression analyses and receiver operating characteristic analyses. Association of plasma levels with risk of clinical progression to mild cognitive impairment (MCI) or dementia was assessed using Cox proportional hazard models.

Results

Fifty‐seven (23%) subjects were CSF‐amyloid abnormal. Plasma Abeta42/Abeta40 ratio and plasma Abeta42 alone, but not tTau, identified abnormal CSF‐amyloid status (plasma ratio: area under the curve [AUC] = 77%, 95% confidence interval [CI] = 69–84%; plasma Abeta42: AUC = 66%, 95% CI: 58–74%). Combining plasma ratio with age and apolipoprotein E resulted in AUC = 83% (95% CI = 77–89%). The Youden cutoff of the plasma ratio gave a sensitivity of 76% and specificity of 75%, and applying this as a prescreener would reduce the number of lumbar punctures by 51%. Using PET as outcome, a comparable reduction in number of PET scans would be achieved when applying the plasma ratio as prescreener. In addition, low plasma ratio was associated with clinical progression to MCI or dementia (hazard ratio = 2.0, 95% CI = 1.4–2.3).

Interpretation

Plasma Abeta42/Abeta40 ratio has potential as a prescreener to identify Alzheimer pathological changes in cognitively normal individuals with SCD. Ann Neurol 2018;84:656–666