Plasma p-tau217 in Alzheimer's disease: Lumipulse and ALZpath SIMOA head-to-head comparison.

Background: Plasma phosphorylated-tau217 (p-tau217) has been shown to be one of the most accurate diagnostic markers for Alzheimer's disease (AD). No studies have compared the clinical performance of p-tau217 as assessed by the fully automated Lumipulse and SIMOA ALZpath p-tau217. Aim: To evaluate the diagnostic accuracy of Lumipulse and SIMOA plasma p-tau217 assays for AD. Methods: The study included 392 participants, 162 with AD, 70 with other neurodegenerative diseases (NDD) with CSF biomarkers and 160 healthy controls. Plasma p-tau217 levels were measured using the Lumipulse and ALZpath SIMOA assays. The ability of p-tau217 assessed by both techniques to discriminate AD from NDD and controls was investigated using ROC analyses. Results: Both techniques showed high internal consistency of p-tau217 with similar correlation with CSF p-tau181 levels. In head-to-head comparison, Lumipulse and SIMOA showed similar diagnostic accuracy for differentiating AD from NDD (area under the curve [AUC] 0.952, 95%CI 0.927-0.978 vs 0.955, 95%CI 0.928-0.982, respectively) and HC (AUC 0.938, 95%CI 0.910-0.966 and 0.937, 95% CI0.907-0.967 for both assays). Conclusions: This study demonstrated the high precision and diagnostic accuracy of p-tau217 for the clinical diagnosis of Alzheimer's disease using either fully automated or semi-automated techniques.

MRI-Derived AD Signature of Cortical Thinning and Plasma P-Tau217 for Predicting Alzheimer Dementia Among Community-Dwelling Older Adults.

Background and Objectives: Structural brain MRI and blood-based phosphorylated tau (p-tau) measures are among the least invasive and least expensive Alzheimer's disease (AD) biomarkers to date. The extent to which these biomarkers may outperform one another in predicting future Alzheimer dementia diagnosis is poorly understood, however. This study investigated 2 specific AD biomarkers, i.e., a cortical thickness signature of AD (AD-CT) and plasma p-tau217, for predicting Alzheimer dementia. Methods: Data came from community-dwelling older participants of the Religious Orders Study or the Rush Memory and Aging Project. AD-CT was obtained from 3T MRI scans using a magnetization-prepared rapid acquisition gradient echo sequence and by averaging thickness from previously identified cortical regions implicated in AD. Plasma p-tau217 was quantified using an immunoassay developed by Lilly Research Laboratories on the MSD platform. Both MRI scans and blood specimens were collected at the same visits, and subsequent diagnoses of Alzheimer dementia were determined through annual detailed clinical evaluations. Cox proportional hazards models examined the associations of the 2 biomarkers with incident Alzheimer dementia, and prediction accuracy was assessed using c-statistics. Results: A total of 198 older adults, on average 84 years of age, were included. Over a mean follow-up of 4 years, 60 (30%) individuals developed Alzheimer dementia. AD-CT (hazard ratio: 1.71, 95% CI 1.26-2.31) and separately plasma p-tau217 (hazard ratio: 2.57, 95% CI 1.83-3.61) were associated with incident Alzheimer dementia. The c-statistic for prediction accuracy was consistently higher for plasma p-tau217 (between 0.74 and 0.81) than AD-CT (between 0.70 and 0.75) across a range of time horizons. Furthermore, with both biomarkers included in the same model, there was only modest improvement in the c-statistic due to AD-CT. Discussion: Plasma p-tau217 outperforms an imaging-based cortical thickness signature of AD in predicting future Alzheimer dementia diagnosis. Furthermore, the AD cortical thickness signature adds little to the prediction accuracy above and beyond plasma p-tau217.

Cerebrospinal fluid reference proteins increase accuracy and interpretability of biomarkers for brain diseases.

Cerebrospinal fluid (CSF) biomarkers reflect brain pathophysiology and are used extensively in translational research as well as in clinical practice for diagnosis of neurological diseases, e.g., Alzheimer's disease (AD). However, CSF biomarker concentrations may be influenced by non-disease related inter-individual variability. Here we use a data-driven approach to demonstrate the existence of inter-individual variability in mean standardized CSF protein levels. We show that these non-disease related differences cause many commonly reported CSF biomarkers to be highly correlated, thereby producing misleading results if not accounted for. To adjust for this inter-individual variability, we identified and evaluated high-performing reference proteins which improved the diagnostic accuracy of key CSF AD biomarkers. Our reference protein method attenuates the risk for false positive findings, and improves the sensitivity and specificity of CSF biomarkers, with broad implications for both research and clinical practice.

Altered empathy processing in frontotemporal dementia A task-based fMRI study.

A lack of empathy, and particularly its affective components, is a core symptom of behavioural variant frontotemporal dementia (bvFTD). Visual exposure to images of a needle pricking a hand (pain condition) and Q-tips touching a hand (control condition) is an established functional magnetic resonance imaging (fMRI) paradigm used to investigate empathy for pain (EFP; pain condition minus control condition). EFP has been associated with increased blood oxygen level dependent (BOLD) signal in regions known to become atrophic in the early stages in bvFTD, including the anterior insula and the anterior cingulate. We therefore hypothesized that patients with bvFTD would display altered empathy processing in the EFP paradigm. Here we examined empathy processing using the EFP paradigm in 28 patients with bvFTD and 28 sex and age matched controls. Participants underwent structural MRI, task-based and resting-state fMRI. The Interpersonal Reactivity Index (IRI) was used as a measure of different facets of empathic function outside the scanner. The EFP paradigm was analysed at a whole brain level and using two regions-of-interest approaches, one based on a metanalysis of affective perceptual empathy versus cognitive evaluative empathy and one based on the controls activation pattern. In controls, EFP was linked to an expected increase of BOLD signal that displayed an overlap with the pattern of atrophy in the bvFTD patients (insula and anterior cingulate). Additional regions with increased signal were the supramarginal gyrus and the occipital cortex. These latter regions were the only ones that displayed increased BOLD signal in bvFTD patients. BOLD signal increase under the affective perceptual empathy but not the cognitive evaluative empathy region of interest was significantly greater in controls than in bvFTD patients. The controls rating on their empathic concern subscale of the IRI was significantly correlated with the BOLD signal in the EFP paradigm, as were an informants ratings of the patients empathic concern subscale. This correlation was not observed on other subscales of the IRI or when using the patient's self-ratings. Finally, controls and patients showed different connectivity patterns in empathy related networks during resting-state fMRI, mainly in nodes overlapping the ventral attention network. Our results indicate that reduced neural activity in regions typically affected by pathology in bvFTD is associated with reduced empathy processing, and a predictor of patients capacity to experience affective empathy.

Large-scale network analysis of the cerebrospinal fluid proteome identifies molecular signatures of frontotemporal lobar degeneration.

The pathophysiological mechanisms driving disease progression of frontotemporal lobar degeneration (FTLD) and corresponding biomarkers are not fully understood. We leveraged aptamer-based proteomics (> 4,000 proteins) to identify dysregulated communities of co-expressed cerebrospinal fluid proteins in 116 adults carrying autosomal dominant FTLD mutations (C9orf72, GRN, MAPT) compared to 39 noncarrier controls. Network analysis identified 31 protein co-expression modules. Proteomic signatures of genetic FTLD clinical severity included increased abundance of RNA splicing (particularly in C9orf72 and GRN) and extracellular matrix (particularly in MAPT) modules, as well as decreased abundance of synaptic/neuronal and autophagy modules. The generalizability of genetic FTLD proteomic signatures was tested and confirmed in independent cohorts of 1) sporadic progressive supranuclear palsy-Richardson syndrome and 2) frontotemporal dementia spectrum syndromes. Network-based proteomics hold promise for identifying replicable molecular pathways in adults living with FTLD. 'Hub' proteins driving co-expression of affected modules warrant further attention as candidate biomarkers and therapeutic targets.

α-Synuclein seed amplification assay detects Lewy body co-pathology in autosomal dominant Alzheimer's disease late in the disease course and dependent on Lewy pathology burden.

INTRODUCTION: Amyloid beta and tau pathology are the hallmarks of sporadic Alzheimer's disease (AD) and autosomal dominant AD (ADAD). However, Lewy body pathology (LBP) is found in ≈ 50% of AD and ADAD brains. METHODS: Using an α-synuclein seed amplification assay (SAA) in cerebrospinal fluid (CSF) from asymptomatic (n = 26) and symptomatic (n = 27) ADAD mutation carriers, including 12 with known neuropathology, we investigated the timing of occurrence and prevalence of SAA positive reactivity in ADAD in vivo. RESULTS: No asymptomatic participant and only 11% (3/27) of the symptomatic patients tested SAA positive. Neuropathology revealed LBP in 10/12 cases, primarily affecting the amygdala or the olfactory areas. In the latter group, only the individual with diffuse LBP reaching the neocortex showed α-synuclein seeding activity in CSF in vivo. DISCUSSION: Results suggest that in ADAD LBP occurs later than AD pathology and often as amygdala- or olfactory-predominant LBP, for which CSF α-synuclein SAA has low sensitivity. HIGHLIGHTS: Cerebrospinal fluid (CSF) real-time quaking-induced conversion (RT-QuIC) detects misfolded α-synuclein in ≈ 10% of symptomatic autosomal dominant Alzheimer's disease (ADAD) patients. CSF RT-QuIC does not detect α-synuclein seeding activity in asymptomatic mutation carriers. Lewy body pathology (LBP) in ADAD mainly occurs as olfactory only or amygdala-predominant variants. LBP develops late in the disease course in ADAD. CSF α-synuclein RT-QuIC has low sensitivity for focal, low-burden LBP.

Associations between structural brain changes and blood neurofilament light chain protein in treatment-resistant schizophrenia.

Background and Hypothesis: Around 30% of people with schizophrenia are refractory to antipsychotic treatment (treatment-resistant schizophrenia; TRS). While abnormal structural neuroimaging findings, in particular volume and thickness reductions, are often observed in schizophrenia, it is anticipated that biomarkers of neuronal injury like neurofilament light chain protein (NfL) can improve our understanding of the pathological basis underlying schizophrenia. The current study aimed to determine whether people with TRS demonstrate different associations between plasma NfL levels and regional cortical thickness reductions compared with controls. Study Design: Measurements of plasma NfL and cortical thickness were obtained from 39 individuals with TRS, and 43 healthy controls. T1-weighted magnetic resonance imaging sequences were obtained and processed via FreeSurfer. General linear mixed models adjusting for age and weight were estimated to determine whether the interaction between diagnostic group and plasma NfL level predicted lower cortical thickness across frontotemporal structures and the insula. Study Results: Significant (false discovery rate corrected) cortical thinning of the left (p = 0.001, η2p = 0.104) and right (p < 0.001, η2p = 0.167) insula was associated with higher levels of plasma NfL in TRS, but not in healthy controls. Conclusions: The association between regional thickness reduction of the insula bilaterally and plasma NfL may reflect a neurodegenerative process during the course of TRS. The findings of the present study suggest that some level of cortical degeneration localised to the bilateral insula may exist in people with TRS, which is not observed in the normal population.

Is GBA1 T369M not a risk factor for Parkinson's disease in the Swedish population?

Variants in GBA1 are important genetic risk factors in Parkinson's disease (PD). GBA1 T369M has been linked to an ~80% increased PD risk but the reports are conflicting and the relevance of GBA1 variants in different populations varies. A lack of association between T369M and PD in the Swedish population was recently reported but needs further validation. We therefore investigated T369M in 1,808 PD patients and 2,183 controls and our results support that T369M is not a risk factor for PD in the Swedish population.

Fixel-Based Analysis Reveals Tau-Related White Matter Changes in Early Stages of Alzheimer's Disease.

Several studies have shown white matter (WM) abnormalities in Alzheimer's disease (AD) using diffusion tensor imaging (DTI). Nonetheless, robust characterization of WM changes has been challenging due to the methodological limitations of DTI. We applied fixel-based analyses (FBA) to examine microscopic differences in fiber density (FD) and macroscopic changes in fiber cross-section (FC) in early stages of AD (N = 393, 212 females). FBA was also compared with DTI, free-water corrected (FW)-DTI and diffusion kurtosis imaging (DKI). We further investigated the correlation of FBA and tensor-derived metrics with AD pathology and cognition. FBA metrics were decreased in the entire cingulum bundle, uncinate fasciculus and anterior thalamic radiations in Aß-positive patients with mild cognitive impairment compared to control groups. Metrics derived from DKI, and FW-DTI showed similar alterations whereas WM degeneration detected by DTI was more widespread. Tau-PET uptake in medial temporal regions was only correlated with reduced FC mainly in the parahippocampal cingulum in Aß-positive individuals. This tau-related WM alteration was also associated with impaired memory. Despite the spatially extensive between-group differences in DTI-metrics, the link between WM and tau aggregation was only revealed using FBA metrics implying high sensitivity but low specificity of DTI-based measures in identifying subtle tau-related WM degeneration. No relationship was found between amyloid load and any diffusion-MRI measures. Our results indicate that early tau-related WM alterations in AD are due to macrostructural changes specifically captured by FBA metrics. Thus, future studies assessing the effects of AD pathology in WM tracts should consider using FBA metrics.

A blood-based biomarker workflow for optimal tau-PET referral in memory clinic settings.

Blood-based biomarkers for screening may guide tau positrion emissition tomography (PET) scan referrals to optimize prognostic evaluation in Alzheimer's disease. Plasma Aß42/Aß40, pTau181, pTau217, pTau231, NfL, and GFAP were measured along with tau-PET in memory clinic patients with subjective cognitive decline, mild cognitive impairment or dementia, in the Swedish BioFINDER-2 study (n = 548) and in the TRIAD study (n = 179). For each plasma biomarker, cutoffs were determined for 90%, 95%, or 97.5% sensitivity to detect tau-PET-positivity. We calculated the percentage of patients below the cutoffs (who would not undergo tau-PET; "saved scans") and the tau-PET-positivity rate among participants above the cutoffs (who would undergo tau-PET; "positive predictive value"). Generally, plasma pTau217 performed best. At the 95% sensitivity cutoff in both cohorts, pTau217 resulted in avoiding nearly half tau-PET scans, with a tau-PET-positivity rate among those who would be referred for a scan around 70%. And although tau-PET was strongly associated with subsequent cognitive decline, in BioFINDER-2 it predicted cognitive decline only among individuals above the referral cutoff on plasma pTau217, supporting that this workflow could reduce prognostically uninformative tau-PET scans. In conclusion, plasma pTau217 may guide selection of patients for tau-PET, when accurate prognostic information is of clinical value.

Biomarker-based staging of Alzheimer disease: rationale and clinical applications.

Disease staging, whereby the spatial extent and load of brain pathology are used to estimate the severity of Alzheimer disease (AD), is pivotal to the gold-standard neuropathological diagnosis of AD. Current in vivo diagnostic frameworks for AD are based on abnormal concentrations of amyloid-ß and tau in the cerebrospinal fluid or on PET scans, and breakthroughs in molecular imaging have opened up the possibility of in vivo staging of AD. Focusing on the key principles of disease staging shared across several areas of medicine, this Review highlights the potential for in vivo staging of AD to transform our understanding of preclinical AD, refine enrolment criteria for trials of disease-modifying therapies and aid clinical decision-making in the era of anti-amyloid therapeutics. We provide a state-of-the-art review of recent biomarker-based AD staging systems and highlight their contributions to the understanding of the natural history of AD. Furthermore, we outline hypothetical frameworks to stage AD severity using more accessible fluid biomarkers. In addition, by applying amyloid PET-based staging to recently published anti-amyloid therapeutic trials, we highlight how biomarker-based disease staging frameworks could illustrate the numerous pathological changes that have already taken place in individuals with mildly symptomatic AD. Finally, we discuss challenges related to the validation and standardization of disease staging and provide a forward-looking perspective on potential clinical applications.

Comparing a pre-defined versus deep learning approach for extracting brain atrophy patterns to predict cognitive decline due to Alzheimer's disease in patients with mild cognitive symptoms.

BACKGROUND: Predicting future Alzheimer's disease (AD)-related cognitive decline among individuals with subjective cognitive decline (SCD) or mild cognitive impairment (MCI) is an important task for healthcare. Structural brain imaging as measured by magnetic resonance imaging (MRI) could potentially contribute when making such predictions. It is unclear if the predictive performance of MRI can be improved using entire brain images in deep learning (DL) models compared to using pre-defined brain regions. METHODS: A cohort of 332 individuals with SCD/MCI were included from the Swedish BioFINDER-1 study. The goal was to predict longitudinal SCD/MCI-to-AD dementia progression and change in Mini-Mental State Examination (MMSE) over four years. Four models were evaluated using different predictors: (1) clinical data only, including demographics, cognitive tests and APOE ε4 status, (2) clinical data plus hippocampal volume, (3) clinical data plus all regional MRI gray matter volumes (N = 68) extracted using FreeSurfer software, (4) a DL model trained using multi-task learning with MRI images, Jacobian determinant images and baseline cognition as input. A double cross-validation scheme, with five test folds and for each of those ten validation folds, was used. External evaluation was performed on part of the ADNI dataset, including 108 patients. Mann-Whitney U-test was used to determine statistically significant differences in performance, with p-values less than 0.05 considered significant. RESULTS: In the BioFINDER cohort, 109 patients (33%) progressed to AD dementia. The performance of the clinical data model for prediction of progression to AD dementia was area under the curve (AUC) = 0.85 and four-year cognitive decline was R2 = 0.14. The performance was improved for both outcomes when adding hippocampal volume (AUC = 0.86, R2 = 0.16). Adding FreeSurfer brain regions improved prediction of four-year cognitive decline but not progression to AD (AUC = 0.83, R2 = 0.17), while the DL model worsened the performance for both outcomes (AUC = 0.84, R2 = 0.08). A sensitivity analysis showed that the Jacobian determinant image was more informative than the MRI image, but that performance was maximized when both were included. In the external evaluation cohort from ADNI, 23 patients (21%) progressed to AD dementia. The results for predicted progression to AD dementia were similar to the results for the BioFINDER test data, while the performance for the cognitive decline was deteriorated. CONCLUSIONS: The DL model did not significantly improve the prediction of clinical disease progression in AD, compared to regression models with a single pre-defined brain region.

Disease staging of Alzheimer's disease using a CSF-based biomarker model.

Biological staging of individuals with Alzheimer's disease (AD) may improve diagnostic and prognostic workup of dementia in clinical practice and the design of clinical trials. In this study, we used the Subtype and Stage Inference (SuStaIn) algorithm to establish a robust biological staging model for AD using cerebrospinal fluid (CSF) biomarkers. Our analysis involved 426 participants from BioFINDER-2 and was validated in 222 participants from the Knight Alzheimer Disease Research Center cohort. SuStaIn identified a singular biomarker sequence and revealed that five CSF biomarkers effectively constituted a reliable staging model (ordered: Aß42/40, pT217/T217, pT205/T205, MTBR-tau243 and non-phosphorylated mid-region tau). The CSF stages (0-5) demonstrated a correlation with increased abnormalities in other AD-related biomarkers, such as Aß-PET and tau-PET, and aligned with longitudinal biomarker changes reflective of AD progression. Higher CSF stages at baseline were associated with an elevated hazard ratio of clinical decline. This study highlights a common molecular pathway underlying AD pathophysiology across all patients, suggesting that a single CSF collection can accurately indicate the presence of AD pathologies and characterize the stage of disease progression. The proposed staging model has implications for enhancing diagnostic and prognostic assessments in both clinical practice and the design of clinical trials.

The Relationship between p-tau217, p-tau231, and p-tau205 in the Human Brain Is Affected by the Cellular Environment and Alzheimer's Disease Pathology.

The levels of p-tau217 and p-tau231 in cerebrospinal fluid (CSF) are associated with early amyloid beta (Aß) changes in the brain, while the CSF levels of p-tau205 are foremost related to tau pathology in the later stages of the disease. To investigate if the three p-tau variants are found to the same degree in different tau structures and if their co-localization is affected by the diagnosis and presence of Aß plaques, we immunostained sections of the entorhinal cortex (EC) and inferior temporal gyrus (ITG) from non-demented controls (NC), patients with Alzheimer's disease (AD), and primary age-related tauopathy (PART) against p-tau217, p-tau231, and p-tau205 together with Methoxi-X04. An analysis using confocal microscopy showed that the co-localization variable, the Pearson correlation coefficient (PCC), was significantly higher between p-tau231 and p-tau205 in neurofibrillary tangles compared to neuropil threads and dystrophic neurites in plaques. The PCC value between all three p-tau variants in the neuropil threads was significantly lower in the ECs of patients with AD compared to the NC and in the ITGs of patients with AD, with a high Aß load compared to PART. The lowered value was associated with proportionally higher amounts of non-colocalized p-tau231 and p-tau217 compared to p-tau205, and the PCC values were negatively correlated with Aß and the tangle loads in patients with AD, but positively correlated with tangles in PART. These results suggest that the proportion of and co-localization between p-tau217, p-tau231, and p-tau205 are dependent on cellular localization and are altered in response to AD pathology in a spatial-temporal manner.

Putaminal T1/T2-weighted ratio is increased in PSP compared to PD and healthy controls, a multi-cohort study.

INTRODUCTION: Differentiating Parkinson's disease (PD) from progressive supranuclear palsy (PSP) and multiple system atrophy (MSA) is a common clinical problem. We aimed to apply the T1-/T2-weighted ratio imaging technique, based on standard clinical MRI, to reveal differences in neurodegeneration in three large cohorts. METHODS: Three cohorts, with a total of 405 participants (269 PD, 44 PSP, 38 MSA, 54 controls), were combined and T1/T2-weighted ratio image analyses were carried out. A combination of automatic segmentation and atlas-based ROI were used in this study. The cohorts were combined using the ComBat batch correction procedure. RESULTS: Group differences were found in the putamen (p = 0.040), with higher T1/T2-weighted ratio in this region in PSP compared to PD and healthy controls (p-values 0.010 and 0.007 respectively). Using putaminal T1/T2-weighted ratio for diagnostic separation, a fair performance was found in separating PSP from healthy controls, with an area under the receiver operating characteristic curve of 0.701. CONCLUSION: Different patterns of T1/T2-weighted ratio, reflecting differences in underlying pathophysiology, were found between the groups. Since T1/T2-weighted ratio can be applied to standard clinical MRI sequences to allow more quantitative analyses, this seems to be a promising biomarker for diagnostics and treatment evaluation of parkinsonian disorders for clinical trials.

Effects of certain pre-analytical factors on the performance of plasma phospho-tau217.

INTRODUCTION: Pre-analytical factors can cause substantial variability in the measurements of cerebrospinal fluid (CSF) and plasma biomarkers of Alzheimer's disease (AD). However, their effects on the performance of one of the most promising plasma AD biomarkers, phosphorylated tau (p-tau)217, are not known. METHODS: We included 50 amyloid-ß positive (Aß+) and 50 Aß- participants from the Swedish BioFINDER-1 study. Plasma and CSF p-tau217 were measured using an immunoassay developed by Lilly Research Laboratories. We examined the effect of four plasma handling conditions, i.e., (1) thawing at room temperature (RT) with no centrifugation, (2) thawing at RT followed by centrifugation, (3) thawing on ice with no centrifugation, and (4) thawing on ice followed by centrifugation. In addition, we also tested the effects of up to 3 freeze-thaw cycles on the associations of plasma p-tau217 with AD-related pathologies measured with CSF p-tau217 and CSF Aß42/Aß40. RESULTS: In the whole cohort (combining Aß+ and Aß- participants), we found significant correlations between plasma p-tau217 and both CSF p-tau217 (Rrange, 0.614-0.717, p < 0.001) and CSF Aß42/Aß40 (Spearman Rrange, - 0.515 to - 0.652, p < 0.001) for each of the four tested conditions. Correlations between plasma and CSF p-tau217 were also significant for all conditions in the Aß+ group (Rrange, 0.506-0.579, p < 0.001). However, in this Aß+ subgroup, correlations with CSF Aß42/Aß40 were only significant for centrifuged samples (thawed at RT, R = - 0.394, p = 0.010; thawed on ice, R = - 0.406; p = 0.007). In Aß- participants, correlations between plasma and CSF p-tau217 were again significant only for centrifuged samples (thawed at RT, R = 0.394, p = 0.007; thawed on ice, R = 0.334; p = 0.022), with no correlations seen between plasma p-tau217 and CSF Aß42/Aß40 for any of the conditions. While the accuracy of plasma p-tau217 to identify individuals with abnormal CSF Aß42/Aß40 or CSF p-tau217 status was high, the AUCs for samples thawed at RT and analyzed without centrifugation were numerically lower than the AUCs of other conditions (CSF Aß42/Aß40 = 0.845 vs 0.872-0.884; CSF p-tau217 = 0.866 vs 0.908-0.924, pdiff > 0.11). P-tau217 concentration was consistently higher in non-centrifuged samples than in centrifuged samples (p ≤ 0.021). There were no differences between samples freeze-thawed once, twice, or three times. CONCLUSION: Centrifugation improved the performance of plasma p-tau217, but thawing temperatures and up to three freeze-thaw cycles did not have a significant impact. These results may inform the future development of standardized sample-handling protocols for AD biomarkers.

Prognostic and Predictive Factors in Early Alzheimer's Disease: A Systematic Review.

Background: Alzheimer's disease (AD) causes progressive decline of cognition and function. There is a lack of systematic literature reviews on prognostic and predictive factors in its early clinical stages (eAD), i.e., mild cognitive impairment due to AD and mild AD dementia. Objective: To identify prognostic factors affecting eAD progression and predictive factors for treatment efficacy and safety of approved and/or under late-stage development disease-modifying treatments. Methods: Databases were searched (August 2022) for studies reporting prognostic factors associated with eAD progression and predictive factors for treatment response. The Quality in Prognostic Factor Studies tool or the Cochrane risk of bias tool were used to assess risk of bias. Two reviewers independently screened the records. A single reviewer performed data extraction and quality assessment. A second performed a 20% check. Content experts reviewed and interpreted the data collected. Results: Sixty-one studies were included. Self-reporting, diagnosis definition, and missing data led to high risk of bias. Population size ranged from 110 to 11,451. Analyses found data indicating that older age was and depression may be associated with progression. Greater baseline cognitive impairment was associated with progression. APOE4 may be a prognostic factor, a predictive factor for treatment efficacy and predicts an adverse response (ARIA). Elevated biomarkers (CSF/plasma p-tau, CSF t-tau, and plasma neurofilament light) were associated with disease progression. Conclusions: Age was the strongest risk factor for progression. Biomarkers were associated with progression, supporting their use in trial selection and aiding diagnosis. Baseline cognitive impairment was a prognostic factor. APOE4 predicted ARIA, aligning with emerging evidence and relevant to treatment initiation/monitoring.

Highly accurate blood test for Alzheimer's disease is similar or superior to clinical cerebrospinal fluid tests.

With the emergence of Alzheimer's disease (AD) disease-modifying therapies, identifying patients who could benefit from these treatments becomes critical. In this study, we evaluated whether a precise blood test could perform as well as established cerebrospinal fluid (CSF) tests in detecting amyloid-ß (Aß) plaques and tau tangles. Plasma %p-tau217 (ratio of phosporylated-tau217 to non-phosphorylated tau) was analyzed by mass spectrometry in the Swedish BioFINDER-2 cohort (n = 1,422) and the US Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC) cohort (n = 337). Matched CSF samples were analyzed with clinically used and FDA-approved automated immunoassays for Aß42/40 and p-tau181/Aß42. The primary and secondary outcomes were detection of brain Aß or tau pathology, respectively, using positron emission tomography (PET) imaging as the reference standard. Main analyses were focused on individuals with cognitive impairment (mild cognitive impairment and mild dementia), which is the target population for available disease-modifying treatments. Plasma %p-tau217 was clinically equivalent to FDA-approved CSF tests in classifying Aß PET status, with an area under the curve (AUC) for both between 0.95 and 0.97. Plasma %p-tau217 was generally superior to CSF tests in classification of tau-PET with AUCs of 0.95-0.98. In cognitively impaired subcohorts (BioFINDER-2: n = 720; Knight ADRC: n = 50), plasma %p-tau217 had an accuracy, a positive predictive value and a negative predictive value of 89-90% for Aß PET and 87-88% for tau PET status, which was clinically equivalent to CSF tests, further improving to 95% using a two-cutoffs approach. Blood plasma %p-tau217 demonstrated performance that was clinically equivalent or superior to clinically used FDA-approved CSF tests in the detection of AD pathology. Use of high-performance blood tests in clinical practice can improve access to accurate AD diagnosis and AD-specific treatments.

Diffusion weighted magnetic resonance spectroscopy revealed neuronal specific microstructural alterations in Alzheimer's disease.

In Alzheimer's disease, reconfiguration and deterioration of tissue microstructure occur before substantial degeneration become evident. We explored the diffusion properties of both water, a ubiquitous marker measured by diffusion MRI, and N-acetyl-aspartate, a neuronal metabolite probed by diffusion-weighted magnetic resonance spectroscopy, for investigating cortical microstructural changes downstream of Alzheimer's disease pathology. To this aim, 50 participants from the Swedish BioFINDER-2 study were scanned on both 7 and 3 T MRI systems. We found that in cognitively impaired participants with evidence of both abnormal amyloid-beta (CSF amyloid-beta42/40) and tau accumulation (tau-PET), the N-acetyl-aspartate diffusion rate was significantly lower than in cognitively unimpaired participants (P < 0.05). This supports the hypothesis that intraneuronal tau accumulation hinders diffusion in the neuronal cytosol. Conversely, water diffusivity was higher in cognitively impaired participants (P < 0.001) and was positively associated with the concentration of myo-inositol, a preferentially astrocytic metabolite (P < 0.001), suggesting that water diffusion is sensitive to alterations in the extracellular space and in glia. In conclusion, measuring the diffusion properties of both water and N-acetyl-aspartate provides rich information on the cortical microstructure in Alzheimer's disease, and can be used to develop new sensitive and specific markers to microstructural changes occurring during the disease course.

European intersocietal recommendations for the biomarker-based diagnosis of neurocognitive disorders.

The recent commercialisation of the first disease-modifying drugs for Alzheimer's disease emphasises the need for consensus recommendations on the rational use of biomarkers to diagnose people with suspected neurocognitive disorders in memory clinics. Most available recommendations and guidelines are either disease-centred or biomarker-centred. A European multidisciplinary taskforce consisting of 22 experts from 11 European scientific societies set out to define the first patient-centred diagnostic workflow that aims to prioritise testing for available biomarkers in individuals attending memory clinics. After an extensive literature review, we used a Delphi consensus procedure to identify 11 clinical syndromes, based on clinical history and examination, neuropsychology, blood tests, structural imaging, and, in some cases, EEG. We recommend first-line and, if needed, second-line testing for biomarkers according to the patient's clinical profile and the results of previous biomarker findings. This diagnostic workflow will promote consistency in the diagnosis of neurocognitive disorders across European countries.