The SORL1 p.Y1816C variant causes impaired endosomal dimerization and autosomal dominant Alzheimer's disease.

Truncating genetic variants of SORL1, encoding the endosome recycling receptor SORLA, have been accepted as causal of Alzheimer's disease (AD). However, most genetic variants observed in SORL1 are missense variants, for which it is complicated to determine the pathogenicity level because carriers come from pedigrees too small to be informative for penetrance estimations. Here, we describe three unrelated families in which the SORL1 coding missense variant rs772677709, that leads to a p.Y1816C substitution, segregates with Alzheimer's disease. Further, we investigate the effect of SORLA p.Y1816C on receptor maturation, cellular localization, and trafficking in cell-based assays. Under physiological circumstances, SORLA dimerizes within the endosome, allowing retromer-dependent trafficking from the endosome to the cell surface, where the luminal part is shed into the extracellular space (sSORLA). Our results showed that the p.Y1816C mutant impairs SORLA homodimerization in the endosome, leading to decreased trafficking to the cell surface and less sSORLA shedding. These trafficking defects of the mutant receptor can be rescued by the expression of the SORLA 3Fn-minireceptor. Finally, we find that iPSC-derived neurons with the engineered p.Y1816C mutation have enlarged endosomes, a defining cytopathology of AD. Our studies provide genetic as well as functional evidence that the SORL1 p.Y1816C variant is causal for AD. The partial penetrance of the mutation suggests this mutation should be considered in clinical genetic screening of multiplex early-onset AD families.

Clinical value of plasma pTau181 to predict Alzheimer's disease pathology in a large real-world cohort of a memory clinic.

BACKGROUND: The identification of patients with an elevated risk of developing Alzheimer's disease (AD) dementia and eligible for the disease-modifying treatments (DMTs) in the earliest stages is one of the greatest challenges in the clinical practice. Plasma biomarkers has the potential to predict these issues, but further research is still needed to translate them to clinical practice. Here we evaluated the clinical applicability of plasma pTau181 as a predictive marker of AD pathology in a large real-world cohort of a memory clinic. METHODS: Three independent cohorts (modelling [n = 991, 59.7% female], testing [n = 642, 56.2% female] and validation [n = 441, 55.1% female]) of real-world patients with subjective cognitive decline (SCD), mild cognitive impairment (MCI), AD dementia, and other dementias were included. Paired cerebrospinal fluid (CSF) and plasma samples were used to measure AT(N) CSF biomarkers and plasma pTau181. FINDINGS: CSF and plasma pTau181 showed correlation in all phenotypes except in SCD and other dementias. Age significantly influenced the biomarker's performance. The general Aß(+) vs Aß(-) ROC curve showed an AUC = 0.77 [0.74-0.80], whereas the specific ROC curve of MCI due to AD vs non-AD MCI showed an AUC = 0.89 [0.85-0.93]. A cut-off value of 1.30 pg/ml of plasma pTau181 exhibited a sensitivity of 93.57% [88.72-96.52], specificity of 72.38% [62.51-79.01], VPP of 77.85% [70.61-83.54], and 8.30% false negatives in the subjects with MCI of the testing cohort. The HR of cox regression showed that patients with MCI up to this cut-off value exhibited a HR = 1.84 [1.05-3.22] higher risk to convert to AD dementia than patients with MCI below the cut-off value. INTERPRETATION: Plasma pTau181 has the potential to be used in the memory clinics as a screening biomarker of AD pathology in subjects with MCI, presenting a valuable prognostic utility in predicting the MCI conversion to AD dementia. In the context of a real-world population, a confirmatory test employing gold-standard procedures is still advisable. FUNDING: This study has been mainly funded by Ace Alzheimer Center Barcelona, Instituto de Salud Carlos III (ISCIII), Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Spanish Ministry of Science and Innovation, Fundación ADEY, Fundación Echevarne and Grífols S.A.

Large-scale CSF proteome profiling identifies biomarkers for accurate diagnosis of Frontotemporal Dementia.

Diagnosis of Frontotemporal dementia (FTD) and the specific underlying neuropathologies (frontotemporal lobar degeneration; FTLD- Tau and FTLD-TDP) is challenging, and thus fluid biomarkers are needed to improve diagnostic accuracy. We used proximity extension assays to analyze 665 proteins in cerebrospinal fluid (CSF) samples from a multicenter cohort including patients with FTD (n = 189), Alzheimer's Disease dementia (AD; n = 232), and cognitively unimpaired individuals (n = 196). In a subset, FTLD neuropathology was determined based on phenotype or genotype (FTLD-Tau = 87 and FTLD-TDP = 68). Forty three proteins were differentially regulated in FTD compared to controls and AD, reflecting axon development, regulation of synapse assembly, and cell-cell adhesion mediator activity pathways. Classification analysis identified a 14- and 13-CSF protein panel that discriminated FTD from controls (AUC: 0.96) or AD (AUC: 0.91). Custom multiplex panels confirmed the highly accurate discrimination between FTD and controls (AUCs > 0.96) or AD (AUCs > 0.88) in three validation cohorts, including one with autopsy confirmation (AUCs > 0.90). Six proteins were differentially regulated between FTLD-TDP and FTLD-Tau, but no reproducible classification model could be generated (AUC: 0.80). Overall, this study introduces novel FTD-specific biomarker panels with potential use in diagnostic setting.

Blood DNA methylomic signatures associated with CSF biomarkers of Alzheimer's disease in the EMIF-AD study.

INTRODUCTION: We investigated blood DNA methylation patterns associated with 15 well-established cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) pathophysiology, neuroinflammation, and neurodegeneration. METHODS: We assessed DNA methylation in 885 blood samples from the European Medical Information Framework for Alzheimer's Disease (EMIF-AD) study using the EPIC array. RESULTS: We identified Bonferroni-significant differential methylation associated with CSF YKL-40 (five loci) and neurofilament light chain (NfL; seven loci) levels, with two of the loci associated with CSF YKL-40 levels correlating with plasma YKL-40 levels. A co-localization analysis showed shared genetic variants underlying YKL-40 DNA methylation and CSF protein levels, with evidence that DNA methylation mediates the association between genotype and protein levels. Weighted gene correlation network analysis identified two modules of co-methylated loci correlated with several amyloid measures and enriched in pathways associated with lipoproteins and development. DISCUSSION: We conducted the most comprehensive epigenome-wide association study (EWAS) of AD-relevant CSF biomarkers to date. Future work should explore the relationship between YKL-40 genotype, DNA methylation, and protein levels in the brain. HIGHLIGHTS: Blood DNA methylation was assessed in the EMIF-AD MBD study. Epigenome-wide association studies (EWASs) were performed for 15 Alzheimer's disease (AD)-relevant cerebrospinal fluid (CSF) biomarker measures. Five Bonferroni-significant loci were associated with YKL-40 levels and seven with neurofilament light chain (NfL). DNA methylation in YKL-40 co-localized with previously reported genetic variation. DNA methylation potentially mediates the effect of single-nucleotide polymorphisms (SNPs) in YKL-40 on CSF protein levels.

Blood-based multivariate methylation risk score for cognitive impairment and dementia.

INTRODUCTION: The established link between DNA methylation and pathophysiology of dementia, along with its potential role as a molecular mediator of lifestyle and environmental influences, positions blood-derived DNA methylation as a promising tool for early dementia risk detection. METHODS: In conjunction with an extensive array of machine learning techniques, we employed whole blood genome-wide DNA methylation data as a surrogate for 14 modifiable and non-modifiable factors in the assessment of dementia risk in independent dementia cohorts. RESULTS: We established a multivariate methylation risk score (MMRS) for identifying mild cognitive impairment cross-sectionally, independent of age and sex (P = 2.0 × 10-3). This score significantly predicted the prospective development of cognitive impairments in independent studies of Alzheimer's disease (hazard ratio for Rey's Auditory Verbal Learning Test (RAVLT)-Learning = 2.47) and Parkinson's disease (hazard ratio for MCI/dementia = 2.59). DISCUSSION: Our work shows the potential of employing blood-derived DNA methylation data in the assessment of dementia risk. HIGHLIGHTS: We used whole blood DNA methylation as a surrogate for 14 dementia risk factors. Created a multivariate methylation risk score for predicting cognitive impairment. Emphasized the role of machine learning and omics data in predicting dementia. The score predicts cognitive impairment development at the population level.

Development of thresholds and a visualization tool for use of a blood test in routine clinical dementia practice.

INTRODUCTION: We developed a multimarker blood test result interpretation tool for the clinical dementia practice, including phosphorylated (P-)tau181, amyloid-beta (Abeta)42/40, glial fibrillary acidic protein (GFAP), and neurofilament light (NfL). METHODS: We measured the plasma biomarkers with Simoa (n = 1199), applied LASSO regression for biomarker selection and receiver operating characteristics (ROC) analyses to determine diagnostic accuracy. We validated our findings in two independent cohorts and constructed a visualization approach. RESULTS: P-tau181, GFAP, and NfL were selected. This combination had area under the curve (AUC) = 83% to identify amyloid positivity in pre-dementia stages, AUC = 87%-89% to differentiate Alzheimer's or controls from frontotemporal dementia, AUC = 74%-76% to differentiate Alzheimer's or controls from dementia with Lewy bodies. Highly reproducible AUCs were obtained in independent cohorts. The resulting visualization tool includes UpSet plots to visualize the stand-alone biomarker results and density plots to visualize the biomarker results combined. DISCUSSION: Our multimarker blood test interpretation tool is ready for testing in real-world clinical dementia settings. HIGHLIGHTS: We developed a multimarker blood test interpretation tool for clinical dementia practice. Our interpretation tool includes plasma biomarkers P-tau, GFAP, and NfL. Our tool is particularly useful for Alzheimer's and frontotemporal dementia diagnosis.

Characterization of white matter hyperintensities in Down syndrome.

INTRODUCTION: In Down syndrome (DS), white matter hyperintensities (WMHs) are highly prevalent, yet their topography and association with sociodemographic data and Alzheimer's disease (AD) biomarkers remain largely unexplored. METHODS: In 261 DS adults and 131 euploid controls, fluid-attenuated inversion recovery magnetic resonance imaging scans were segmented and WMHs were extracted in concentric white matter layers and lobar regions. We tested associations with AD clinical stages, sociodemographic data, cerebrospinal fluid (CSF) AD biomarkers, and gray matter (GM) volume. RESULTS: In DS, total WMHs arose at age 43 and showed stronger associations with age than in controls. WMH volume increased along the AD continuum, particularly in periventricular regions, and frontal, parietal, and occipital lobes. Associations were found with CSF biomarkers and temporo-parietal GM volumes. DISCUSSION: WMHs increase 10 years before AD symptom onset in DS and are closely linked with AD biomarkers and neurodegeneration. This suggests a direct connection to AD pathophysiology, independent of vascular risks. HIGHLIGHTS: White matter hyperintensities (WMHs) increased 10 years before Alzheimer's disease symptom onset in Down syndrome (DS). WMHs were strongly associated in DS with the neurofilament light chain biomarker. WMHs were more associated in DS with gray matter volume in parieto-temporal areas.

APP dyshomeostasis in the pathogenesis of Alzheimer's disease: implications for current drug targets.

The Amyloid precursor protein (APP) is a transmembrane glycoprotein from which amyloid-ß (Aß) peptides are generated after proteolytic cleavage. Aß peptides are the main constituent of amyloid plaques in Alzheimer's Disease (AD). The physiological functions of APP in the human adult brain are very diverse including intracellular signaling, synaptic and neuronal plasticity, and cell adhesion, among others. There is growing evidence that APP becomes dysfunctional in AD and that this dyshomeostasis may impact several APP functions beyond Aß generation. The vast majority of current anti-amyloid approaches in AD have focused on reducing the synthesis of Aß or increasing the clearance of brain Aß aggregates following a paradigm in which Aß plays a solo in APP dyshomeostasis. A wider view places APP at the center stage in which Aß is an important, but not the only, factor involved in APP dyshomeostasis. Under this paradigm, APP dysfunction is universal in AD, but with some differences across different subtypes. Little is known about how to approach APP dysfunction therapeutically beyond anti-Aß strategies. In this review, we will describe the role of APP dyshomeostasis in AD beyond Aß and the potential therapeutic strategies targeting APP.

Comparison of the Amyloid Plaque Proteome in Down Syndrome, Early-Onset Alzheimer's Disease and Late-Onset Alzheimer's Disease.

Background: Down syndrome (DS) is strongly associated with Alzheimer's disease (AD), attributable to APP overexpression. DS exhibits Amyloid-ß (Aß) and Tau pathology similar to early-onset AD (EOAD) and late-onset AD (LOAD). The study aimed to evaluate the Aß plaque proteome of DS, EOAD and LOAD. Methods: Using unbiased localized proteomics, we analyzed amyloid plaques and adjacent plaque-devoid tissue ('non-plaque') from post-mortem paraffin-embedded tissues in four cohorts (n = 20/group): DS (59.8 ± 4.99 y/o), EOAD (63 ± 4.07 y/o), LOAD (82.1 ± 6.37 y/o) and controls (66.4 ± 13.04). We assessed functional associations using Gene Ontology (GO) enrichment and protein interaction networks. Results: We identified differentially abundant Aß plaque proteins vs. non-plaques (FDR < 5%, fold-change > 1.5) in DS (n = 132), EOAD (n = 192) and in LOAD (n = 128); there were 43 plaque-associated proteins shared between all groups. Positive correlations (p < 0.0001) were observed between plaque-associated proteins in DS and EOAD (R2 = 0.77), DS and LOAD (R2 = 0.73), and EOAD vs. LOAD (R2 = 0.67). Top Biological process (BP) GO terms (p < 0.0001) included lysosomal transport for DS, immune system regulation for EOAD, and lysosome organization for LOAD. Protein networks revealed a plaque enriched signature across all cohorts involving APP metabolism, immune response, and lysosomal functions. In DS, EOAD and LOAD non-plaque vs. control tissue, we identified 263, 269, and 301 differentially abundant proteins, including 65 altered non-plaque proteins across all cohorts. Differentially abundant non-plaque proteins in DS showed a significant (p < 0.0001) but weaker positive correlation with EOAD (R2 = 0.59) and LOAD (R2 = 0.33) compared to the stronger correlation between EOAD and LOAD (R2 = 0.79). The top BP GO term for all groups was chromatin remodeling (DS p = 0.0013, EOAD p = 5.79×10- 9, and LOAD p = 1.69×10- 10). Additional GO terms for DS included extracellular matrix (p = 0.0068), while EOAD and LOAD were associated with protein-DNA complexes and gene expression regulation (p < 0.0001). Conclusions: We found strong similarities among the Aß plaque proteomes in individuals with DS, EOAD and LOAD, and a robust association between the plaque proteomes and lysosomal and immune-related pathways. Further, non-plaque proteomes highlighted altered pathways related to chromatin structure and extracellular matrix (ECM), the latter particularly associated with DS. We identified novel Aß plaque proteins, which may serve as biomarkers or therapeutic targets.

Associations of Microbleeds and Their Topography With Imaging and CSF Biomarkers of Alzheimer Pathology in Individuals With Down Syndrome.

BACKGROUND AND OBJECTIVES: Cerebral hemorrhages are an exclusion criterion and potential adverse effect of antiamyloid agents. It is, therefore, critical to characterize the natural history of cerebral microbleeds in populations genetically predisposed to Alzheimer disease (AD), such as Down syndrome (DS). We aimed to assess microbleed emergence in adults with DS across the AD spectrum, defining their topography and associations with clinical variables, cognitive outcomes, and fluid and neuroimaging biomarkers. METHODS: This cross-sectional study included participants aged 18 years or older from the Down-Alzheimer Barcelona Neuroimaging Initiative and Sant Pau Initiative on Neurodegeneration with T1-weighted and susceptibility-weighted images. Participants underwent comprehensive assessments, including apolipoprotein E (APOE) genotyping; fluid and plasma determinations of beta-amyloid, tau, and neurofilament light; cognitive outcomes (Cambridge Cognitive Examination and modified Cued Recall Test); and vascular risk factors (hypertension, diabetes mellitus, and dyslipidemia). We manually segmented microbleeds and characterized their topography. Associations between microbleed severity and AD biomarkers were explored using between-group comparisons (none vs 1 vs 2+) and multivariate linear models. RESULTS: We included 276 individuals with DS and 158 healthy euploid controls (mean age = 47.8 years, 50.92% female). Individuals with DS were more likely to have microbleeds than controls (20% vs 8.9%, p < 0.001), with more severe presentation (12% with 2+ vs 1.9%). Microbleeds increased with age (12% 20-30 years vs 60% > 60 years) and AD clinical stage (12.42% asymptomatic, 27.9% prodromal, 35.09% dementia) were more common in APOEε4 carriers (26% vs 18.3% noncarriers, p = 0.008), but not associated with vascular risk factors (p > 0.05). Microbleeds were predominantly posterior (cerebellum 33.66%; occipital 14.85%; temporal 21.29%) in participants with DS. Associations with microbleed severity were found for neuroimaging and fluid AD biomarkers, but only hippocampal volumes (standardized ß = -0.18 [-0.31, -0.06], p < 0.005) and CSF p-tau-181 concentrations (ß = 0.26 [0.12, 0.41], p < 0.005) survived regression controlling for age and disease stage, respectively. Microbleeds had limited effect on cognitive outcomes. DISCUSSION: In participants with DS, microbleeds present with a posterior, lobar predominance, are associated with disease severity, but do not affect cognitive performance. These results suggest an interplay between AD pathology and vascular lesions, implicating microbleeds as a risk factor limiting the use of antiamyloid agents in this population.

Diagnostic performance of plasma pTau217, pTau181, Aß1-42 and Aß1-40 in the LUMIPULSE automated platform for the detection of Alzheimer disease.

BACKGROUND: Recently developed blood markers for Alzheimer's disease (AD) detection have high accuracy but usually require ultra-sensitive analytic tools not commonly available in clinical laboratories, and their performance in clinical practice is unknown. METHODS: We analyzed plasma samples from 290 consecutive participants that underwent lumbar puncture in routine clinical practice in a specialized memory clinic (66 cognitively unimpaired, 130 participants with mild cognitive impairment, and 94 with dementia). Participants were classified as amyloid positive (A +) or negative (A-) according to CSF Aß1-42/Aß1-40 ratio. Plasma pTau217, pTau181, Aß1-42 and Aß1-40 were measured in the fully-automated LUMIPULSE platform. We used linear regression to compare plasma biomarkers concentrations between A + and A- groups, evaluated Spearman's correlation between plasma and CSF and performed ROC analyses to assess their diagnostic accuracy to detect brain amyloidosis as determined by CSF Aß1-42/Aß1-40 ratio. We analyzed the concordance of pTau217 with CSF amyloidosis. RESULTS: Plasma pTau217 and pTau181 concentration were higher in A + than A- while the plasma Aß1-42/Aß1-40 ratio was lower in A + compared to A-. pTau181 and the Aß1-42/Aß1-40 ratio showed moderate correlation between plasma and CSF (Rho = 0.66 and 0.69, respectively). The areas under the ROC curve to discriminate A + from A- participants were 0.94 (95% CI 0.92-0.97) for pTau217, and 0.88 (95% CI 0.84-0.92) for both pTau181 and Aß1-42/Aß1-40. Chronic kidney disease (CKD) was related to increased plasma biomarker concentrations, but ratios were less affected. Plasma pTau217 had the highest fold change (× 3.2) and showed high predictive capability in discriminating A + from A-, having 4-7% misclassification rate. The global accuracy of plasma pTau217 using a two-threshold approach was robust in symptomatic groups, exceeding 90%. CONCLUSION: The evaluation of blood biomarkers on an automated platform exhibited high diagnostic accuracy for AD pathophysiology, and pTau217 showed excellent diagnostic accuracy to identify participants with AD in a consecutive sample representing the routine clinical practice in a specialized memory unit.

Paired plasma lipidomics and proteomics analysis in the conversion from mild cognitive impairment to Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative condition for which there is currently no available medication that can stop its progression. Previous studies suggest that mild cognitive impairment (MCI) is a phase that precedes the disease. Therefore, a better understanding of the molecular mechanisms behind MCI conversion to AD is needed. METHOD: Here, we propose a machine learning-based approach to detect the key metabolites and proteins involved in MCI progression to AD using data from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery Study. Proteins and metabolites were evaluated separately in multiclass models (controls, MCI and AD) and together in MCI conversion models (MCI stable vs converter). Only features selected as relevant by 3/4 algorithms proposed were kept for downstream analysis. RESULTS: Multiclass models of metabolites highlighted nine features further validated in an independent cohort (0.726 mean balanced accuracy). Among these features, one metabolite, oleamide, was selected by all the algorithms. Further in-vitro experiments in rodents showed that disease-associated microglia excreted oleamide in vesicles. Multiclass models of proteins stood out with nine features, validated in an independent cohort (0.720 mean balanced accuracy). However, none of the proteins was selected by all the algorithms. Besides, to distinguish between MCI stable and converters, 14 key features were selected (0.872 AUC), including tTau, alpha-synuclein (SNCA), junctophilin-3 (JPH3), properdin (CFP) and peptidase inhibitor 15 (PI15) among others. CONCLUSIONS: This omics integration approach highlighted a set of molecules associated with MCI conversion important in neuronal and glia inflammation pathways.

APOE4 homozygozity represents a distinct genetic form of Alzheimer's disease.

This study aimed to evaluate the impact of APOE4 homozygosity on Alzheimer's disease (AD) by examining its clinical, pathological and biomarker changes to see whether APOE4 homozygotes constitute a distinct, genetically determined form of AD. Data from the National Alzheimer's Coordinating Center and five large cohorts with AD biomarkers were analyzed. The analysis included 3,297 individuals for the pathological study and 10,039 for the clinical study. Findings revealed that almost all APOE4 homozygotes exhibited AD pathology and had significantly higher levels of AD biomarkers from age 55 compared to APOE3 homozygotes. By age 65, nearly all had abnormal amyloid levels in cerebrospinal fluid, and 75% had positive amyloid scans, with the prevalence of these markers increasing with age, indicating near-full penetrance of AD biology in APOE4 homozygotes. The age of symptom onset was earlier in APOE4 homozygotes at 65.1, with a narrower 95% prediction interval than APOE3 homozygotes. The predictability of symptom onset and the sequence of biomarker changes in APOE4 homozygotes mirrored those in autosomal dominant AD and Down syndrome. However, in the dementia stage, there were no differences in amyloid or tau positron emission tomography across haplotypes, despite earlier clinical and biomarker changes. The study concludes that APOE4 homozygotes represent a genetic form of AD, suggesting the need for individualized prevention strategies, clinical trials and treatments.

Cortical microinfarcts in adults with Down syndrome assessed with 3T-MRI.

BACKGROUND: Cortical microinfarcts (CMI) were attributed to cerebrovascular disease and cerebral amyloid angiopathy (CAA). CAA is frequent in Down syndrome (DS) while hypertension is rare, yet no studies have assessed CMI in DS. METHODS: We included 195 adults with DS, 63 with symptomatic sporadic Alzheimer's disease (AD), and 106 controls with 3T magnetic resonance imaging. We assessed CMI prevalence in each group and CMI association with age, AD clinical continuum, vascular risk factors, vascular neuroimaging findings, amyloid/tau/neurodegeneration biomarkers, and cognition in DS. RESULTS: CMI prevalence was 11.8% in DS, 4.7% in controls, and 17.5% in sporadic AD. In DS, CMI increased in prevalence with age and the AD clinical continuum, was clustered in the parietal lobes, and was associated with lacunes and cortico-subcortical infarcts, but not hemorrhagic lesions. DISCUSSION: In DS, CMI are posteriorly distributed and related to ischemic but not hemorrhagic findings suggesting they might be associated with a specific ischemic CAA phenotype. HIGHLIGHTS: This is the first study to assess cortical microinfarcts (assessed with 3T magnetic resonance imaging) in adults with Down syndrome (DS). We studied the prevalence of cortical microinfarcts in DS and its relationship with age, the Alzheimer's disease (AD) clinical continuum, vascular risk factors, vascular neuroimaging findings, amyloid/tau/neurodegeneration biomarkers, and cognition. The prevalence of cortical microinfarcts was 11.8% in DS and increased with age and along the AD clinical continuum. Cortical microinfarcts were clustered in the parietal lobes, and were associated with lacunes and cortico-subcortical infarcts, but not hemorrhagic lesions. In DS, cortical microinfarcts are posteriorly distributed and related to ischemic but not hemorrhagic findings suggesting they might be associated with a specific ischemic phenotype of cerebral amyloid angiopathy.

Diagnostic Accuracy of a Plasma Phosphorylated Tau 217 Immunoassay for Alzheimer Disease Pathology.

Importance: Phosphorylated tau (p-tau) is a specific blood biomarker for Alzheimer disease (AD) pathology, with p-tau217 considered to have the most utility. However, availability of p-tau217 tests for research and clinical use has been limited. Expanding access to this highly accurate AD biomarker is crucial for wider evaluation and implementation of AD blood tests. Objective: To determine the utility of a novel and commercially available immunoassay for plasma p-tau217 to detect AD pathology and evaluate reference ranges for abnormal amyloid ß (Aß) and longitudinal change across 3 selected cohorts. Design, Setting, and Participants: This cohort study examined data from 3 single-center observational cohorts: cross-sectional and longitudinal data from the Translational Biomarkers in Aging and Dementia (TRIAD) cohort (visits October 2017-August 2021) and Wisconsin Registry for Alzheimer's Prevention (WRAP) cohort (visits February 2007-November 2020) and cross-sectional data from the Sant Pau Initiative on Neurodegeneration (SPIN) cohort (baseline visits March 2009-November 2021). Participants included individuals with and without cognitive impairment grouped by amyloid and tau (AT) status using PET or CSF biomarkers. Data were analyzed from February to June 2023. Exposures: Magnetic resonance imaging, Aß positron emission tomography (PET), tau PET, cerebrospinal fluid (CSF) biomarkers (Aß42/40 and p-tau immunoassays), and plasma p-tau217 (ALZpath pTau217 assay). Main Outcomes and Measures: Accuracy of plasma p-tau217 in detecting abnormal amyloid and tau pathology, longitudinal p-tau217 change according to baseline pathology status. Results: The study included 786 participants (mean [SD] age, 66.3 [9.7] years; 504 females [64.1%] and 282 males [35.9%]). High accuracy was observed in identifying elevated Aß (area under the curve [AUC], 0.92-0.96; 95% CI, 0.89-0.99) and tau pathology (AUC, 0.93-0.97; 95% CI, 0.84-0.99) across all cohorts. These accuracies were comparable with CSF biomarkers in determining abnormal PET signal. The detection of abnormal Aß pathology using a 3-range reference yielded reproducible results and reduced confirmatory testing by approximately 80%. Longitudinally, plasma p-tau217 values showed an annual increase only in Aß-positive individuals, with the highest increase observed in those with tau positivity. Conclusions and Relevance: This study found that a commercially available plasma p-tau217 immunoassay accurately identified biological AD, comparable with results using CSF biomarkers, with reproducible cut-offs across cohorts. It detected longitudinal changes, including at the preclinical stage.

Agreement of cerebrospinal fluid biomarkers and amyloid-PET in a multicenter study.

Core Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers have shown incomplete agreement with amyloid-positron emission tomography (PET). Our goal was to analyze the agreement between AD CSF biomarkers and amyloid-PET in a multicenter study. Retrospective multicenter study (5 centers). Participants who underwent both CSF biomarkers and amyloid-PET scan within 18 months were included. Clinical diagnoses were made according to latest diagnostic criteria by the attending clinicians. CSF Amyloid Beta1-42 (Aß1-42, A), phosphorliated tau 181 (pTau181, T) and total tau (tTau, N) biomarkers were considered normal (-) or abnormal ( +) according to cutoffs of each center. Amyloid-PET was visually classified as positive/negative. Agreement between CSF biomarkers and amyloid-PET was analyzed by overall percent agreement (OPA). 236 participants were included (mean age 67.9 years (SD 9.1), MMSE score 24.5 (SD 4.1)). Diagnoses were mild cognitive impairment or dementia due to AD (49%), Lewy body dementia (22%), frontotemporal dementia (10%) and others (19%). Mean time between tests was 5.1 months (SD 4.1). OPA between single CSF biomarkers and amyloid-PET was 74% for Aß1-42, 75% for pTau181, 73% for tTau. The use of biomarker ratios improved OPA: 87% for Aß1-42/Aß1-40 (n = 155), 88% for pTau181/Aß1-42 (n = 94) and 82% for tTau/Aß1-42 (n = 160). A + T + N + cases showed the highest agreement between CSF biomarkers and amyloid-PET (96%), followed by A-T-N- cases (89%). Aß1-42/Aß1-40 was a better marker of cerebral amyloid deposition, as identified by amyloid tracers, than Aß1-42 alone. Combined biomarkers in CSF predicted amyloid-PET result better than single biomarkers.