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Abstract This preclinical AD CSF proteome study identified a panel of 12-CSF markers detecting amyloid positivity and clinical progression to AD with high accuracy; some of these CSF proteins related to immune function, neurotrophic processes, energy metabolism and endolysosomal functioning (e.g., ITGB2, CLEC5A, IGFBP-1, CST3) changed before amyloid positivity is established.

Abstract Background Alzheimer’s disease (AD) is a common, complex and multifactorial disease that may require screening across multiple routes of referral to enable early detection and subsequent future implementation of tailored interventions. Blood- and eye-based biomarkers show promise as low-cost, scalable and patient-friendly tools for early AD detection given their ability to provide information on AD pathophysiological changes and manifestations in the retina, respectively. Eye clinics provide an intriguing real-world proof-of-concept setting to evaluate the performance of these potential AD screening tools given the intricate connections between the eye and brain, presumed enrichment for AD pathology in the aging population with eye disorders, and the potential for an accelerated diagnostic pathway for under-recognized patient groups. Methods The BeyeOMARKER study is a prospective, observational, longitudinal cohort study aiming to include individuals visiting an eye-clinic. Inclusion criteria entail being ≥ 50 years old and having no prior dementia diagnosis. Excluded eye-conditions include traumatic insults, superficial inflammation, and conditions in surrounding structures of the eye that are not engaged in vision. The BeyeOMARKER cohort (n = 700) will undergo blood collection to assess plasma p-tau217 levels and a brief cognitive screening at the eye clinic. All participants will subsequently be invited for annual longitudinal follow-up including remotely administered cognitive screening and questionnaires. The BeyeOMARKER + cohort (n = 150), consisting of 100 plasma p-tau217 positive participants and 50 matched negative controls selected from the BeyeOMARKER cohort, will additionally undergo Aβ-PET and tau-PET, MRI, retinal imaging including hyperspectral imaging (primary), widefield imaging, optical coherence tomography (OCT) and OCT-Angiography (secondary), and cognitive and cortical vision assessments. Results We aim to implement the current protocol between April 2024 until March 2027. Primary outcomes include the performance of plasma p-tau217 and hyperspectral retinal imaging to detect AD pathology (using Aβ- and tau-PET visual read as reference standard) and to detect cognitive decline. Initial follow-up is ~ 2 years but may be extended with additional funding. Conclusions We envision that the BeyeOMARKER study will demonstrate the feasibility of early AD detection based on blood- and eye-based biomarkers in alternative screening settings, and will improve our understanding of the eye-brain connection. Trial registration The BeyeOMARKER study (Eudamed CIV ID: CIV-NL-23–09-044086; registration date: 19th of March 2024) is approved by the ethical review board of the Amsterdam UMC.

Abstract 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.

Abstract 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.

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.

Abstract 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.

Abstract 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.

Abstract 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

Abstract Plasma biomarkers that reflect specific amyloid beta (Abeta) proteoforms provide an insight in the treatment effects of Alzheimer’s disease (AD) therapies. Our aim was to develop and validate ready-to-use Simoa ‘Amyblood’ assays that measure full length Abeta1-42 and Abeta1-40 and compare their performance with two commercial assays. Linearity, intra- and inter-assay %CV were compared between Amyblood, Quanterix Simoa triplex, and Euroimmun ELISA. Sensitivity and selectivity were assessed for Amyblood and the Quanterix triplex. Clinical performance was assessed in CSF biomarker confirmed AD (n = 43, 68 ± 6 years) and controls (n = 42, 62 ± 5 years). Prototype and Amyblood showed similar calibrator curves and differentiation (20 AD vs 20 controls, p

Abstract 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

Abstract 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

Abstract Background We evaluated Aβ misfolding in combination with Aβ42/40 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

Abstract 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 0.33, p

An amendment to this paper has been published and can be accessed via the original article.

Abstract 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.

In early-stage Parkinson′s disease (PD), cognitive impairment is common, and a variety of cognitive domains including memory, attention, and executive functioning may be affected. Cerebrospinal fluid (CSF) biomarkers are potential markers of cognitive functioning. We aimed to explore whether CSF α-synuclein species, neurofilament light chain, amyloid-β42, and tau are associated with cognitive performance in early-stage PD patients. CSF levels of total-α-synuclein and phosphorylated-α-synuclein, neurofilament light chain, amyloid-β42, and total-tau and phosphorylated-tau were measured in 26 PD patients (disease duration ≤5 years and Hoehn and Yahr stage 1–2.5). Multivariable linear regression models, adjusted for age, gender, and educational level, were used to assess the relationship between CSF biomarker levels and memory, attention, executive and visuospatial function, and language performance scores. In 26 early-stage PD patients, attention and memory were the most commonly affected domains. A higher CSF phosphorylated-α-synuclein/total-α-synuclein ratio was associated with better executive functioning (sβ = 0.40). Higher CSF neurofilament light was associated with worse memory (sβ = −0.59), attentional (sβ = −0.32), and executive functioning (sβ = −0.35). Reduced CSF amyloid-β42 levels were associated with poorer attentional functioning (sβ = 0.35). Higher CSF phosphorylated-tau was associated with worse language functioning (sβ = −0.33). Thus, CSF biomarker levels, in particular neurofilament light, were related to the most commonly affected cognitive domains in early-stage PD. This indicates that CSF biomarker levels may identify early-stage PD patients who are at an increased risk of developing cognitive impairment.

Abstract Background The accumulation of amyloid-β (Aβ) peptide in the brain is a hallmark of Alzheimer’s disease (AD), occurring years before symptom onset. Current methods for quantifying in vivo amyloid load involve invasive or costly procedures, limiting accessibility. Early detection of amyloid positivity in non-demented individuals is crucial for aiding early AD diagnosis and for initiating anti-amyloid immunotherapies at early stages. This study aimed to develop and validate predictive models to identify brain amyloid positivity in non-demented patients, using routinely collected clinical data. Methods Predictive models for amyloid positivity were developed using data from 853 non-demented participants in the MEMENTO cohort. Amyloid levels were measured potentially repeatedly during study course through Positron Emision Tomography or CerebroSpinal Fluid analysis. The probability of amyloid positivity was modelled using mixed-effects logistic regression. Predictors included demographic information, cognitive assessments, visual brain MRI evaluations of hippocampal atrophy and lobar microbleeds, AD-related blood biomarkers (Aβ42/40 and P-tau181), and ApoE4 status. Models were subjected to internal cross-validation and external validation using data from the Amsterdam Dementia Cohort. Performance also was evaluated in a subsample that met the main criteria of the Appropriate Use Recommendations (AUR) for lecanemab. Results The most effective model incorporated demographic data, cognitive assessments, ApoE status, and AD-related blood biomarkers, achieving AUCs of 0.82 [95%CI 0.81-0.82] in MEMENTO sample and 0.90 [95%CI 0.86-0.94] in the external validation sample. This model significantly outperformed a reference model based solely on demographic and cognitive data, with an AUC difference in MEMENTO of 0.10 [95%CI 0.10-0.11]. A similar model without ApoE genotype achieved comparable discriminatory performance. MRI markers did not improve model performance. Performances in AUR of lecanemab subsample were comparable. Conclusion A predictive model integrating demographic, cognitive, and blood biomarker data offers a promising method to help identify amyloid status in non-demented patients. ApoE genotype and brain MRI data were not necessary for strong discriminatory ability, suggesting that ApoE genotyping may be deferred when assessing the risk-benefit ratio of immunotherapies in amyloid-positive patients who desire treatment. The integration of this model into clinical practice could reduce the need for lumbar puncture or PET examinations to confirm amyloid status.

Summary: Background: Serum glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) are putative non-amyloid blood-based biomarkers indicative of ongoing inflammatory and neurodegenerative disease processes. We aimed to assess their prognostic and monitoring value for progression to dementia in individuals presenting at a memory clinic who are cognitively normal. Methods: For this prospective cohort study, we included individuals who were cognitively normal from the Amsterdam Dementia Cohort and received screening for dementia at first visit and annual follow-up visits. Participants without a serum sample stored in the Amsterdam Dementia Biobank within 6 months of baseline visit and without a follow-up diagnosis after a minimum of 6 months were excluded. We measured serum GFAP and NfL levels at baseline for all participants and at follow-up for a subset of participants. Using Cox proportional hazard models, we investigated associations of biomarker levels (Z-transformed) with incident dementia (adjusted for age and sex), by entering the markers first separately and then simultaneously, to test independent associations. We also assessed longitudinal performance of the markers on a standardised neuropsychological test battery covering global cognition, memory, language, executive functioning, and attention (adjusted for age, sex, and education). Finally, we evaluated the association of slopes of biomarker levels with incident dementia (adjusted for age and sex). Findings: Between July 13, 2001, and Aug 17, 2016, 300 individuals were included in the study. Mean baseline age was 61 years (SD 9), 125 (42%) of participants were women, and mini-mental state examination was 29 (IQR 27–29). Median follow-up time was 3·0 years (IQR 1·9–4·2), with a median of three visits per participant (range 2–12; 1010 total neuropsychological evaluations). During follow-up, 27 (9%) of 300 individuals developed dementia. Both high baseline GFAP (hazard ratio 3·6, 95% CI 2·2–5·7; p