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Abstract Alzheimer’s disease (AD) is a debilitating neurodegenerative disorder characterized by brain aggregation of β-amyloid (Aβ) peptides and phosphorylated tau (P-tau) proteins. Extracellular vesicles (EVs) can be isolated and studied for potential roles in disease. While several studies have tested plasma-derived EVs in AD, few have analyzed EVs from cerebrospinal fluid (CSF), which are potentially more closely related to brain changes. This study included 20 AD patients and 20 cognitively unimpaired (CU) participants. Using a novel EV isolation method based on acoustic trapping, we isolated and purified EVs from minimal CSF volumes. EVs were lysed and analyzed by immunoassays for P-tau217 and P-tau181. Isolation was confirmed through transmission electron microscopy and the presence of EV-specific markers (CD9, CD63, CD81, ATP1A3). Nanoparticle tracking analysis revealed a high variance in EV distribution. AD patients exhibited increased P-tau181 and decreased P-tau217 in EVs, leading to a higher EV P-tau181/P-tau217 ratio compared to CU. No significant differences in EV counts or sizes were observed between AD and CU groups. This study is the first to use acoustic trapping to isolate EVs from CSF and demonstrates differential P-tau content in AD-derived EVs, warranting further research to understand the relationship between these EV changes and brain pathology.

Abstract Background In Alzheimer’s disease (AD), the associations between tau pathology and brain atrophy and cognitive decline are well established, but imperfect. We investigate whether cerebrospinal fluid (CSF) biomarkers of biological processes (vascular, synaptic, and axonal integrity, neuroinflammation, neurotrophic factors) explain the disconnection between tau pathology and brain atrophy (brain resilience), and tau pathology and cognitive decline (cognitive resilience). Methods We included 428 amyloid positive participants (134 cognitively unimpaired (CU), 128 with mild cognitive impairment (MCI), 166 with AD dementia) from the BioFINDER-2 study. At baseline, participants underwent tau positron emission tomography (tau-PET), magnetic resonance imaging (MRI), cognitive testing, and lumbar puncture. Longitudinal data were available for MRI (mean (standard deviation) follow-up 26.4 (10.7) months) and cognition (25.2 (11.4) months). We analysed 18 pre-selected CSF proteins, reflecting vascular, synaptic, and axonal integrity, neuroinflammation, and neurotrophic factors. Stratifying by cognitive status, we performed linear mixed-effects models with cortical thickness (brain resilience) and global cognition (cognitive resilience) as dependent variables to assess whether the CSF biomarkers interacted with tau-PET levels in its effect on cortical atrophy and cognitive decline. Results Regarding brain resilience, interaction effects were observed in AD dementia, with vascular integrity biomarkers (VEGF-A (βinteraction = -0.009, pFDR = 0.047) and VEGF-B (βinteraction = -0.010, pFDR = 0.037)) negatively moderating the association between tau-PET signal and atrophy. In MCI, higher NfL levels were associated with more longitudinal cortical atrophy (β = -0.109, pFDR = 0.033) and lower baseline cortical thickness (β = -0.708, pFDR = 0.033) controlling for tau-PET signal. Cognitive resilience analyses in CU revealed interactions with tau-PET signal for inflammatory (GFAP, IL-15; βinteraction -0.073–-0.069, pFDR 0.001–0.045), vascular (VEGF-A, VEGF-D, PGF; βinteraction -0.099–-0.063, pFDR

Abstract Background The medial temporal lobe (MTL) is hypothesized to be relatively spared in early-onset Alzheimer’s disease (EOAD). Yet, detailed examination of MTL subfields and drivers of atrophy in amnestic EOAD is lacking. Methods BioFINDER-2 participants with memory impairment, abnormal amyloid-β and tau-PET were included. Forty-one amnestic EOAD individuals ≤65 years and, as comparison, late-onset AD (aLOAD, ≥70 years, n = 154) and amyloid-β-negative cognitively unimpaired controls were included. MTL subregions and biomarkers of (co-)pathologies were measured. Results AD groups showed smaller MTL subregions compared to controls. Atrophy patterns were similar across AD groups: aLOAD showed thinner entorhinal cortices than aEOAD; aEOAD showed thinner parietal regions than aLOAD. aEOAD showed lower white matter hyperintensities than aLOAD. No differences in MTL tau-PET or transactive response DNA binding protein 43-proxy positivity were found. Conclusions We found evidence for MTL atrophy in amnestic EOAD and overall similar levels to aLOAD of MTL tau pathology and co-pathologies.

Abstract Background Alzheimer’s disease (AD) is a progressive neurodegenerative disorder where pathophysiological changes begin decades before the onset of clinical symptoms. Analysis of brain atrophy patterns using structural MRI and multivariate data analysis are an effective tool in identifying patients with subjective cognitive decline (SCD) at higher risk of progression to AD dementia. Atrophy patterns obtained from models trained to classify advanced AD versus normal subjects, may not be optimal for subjects at an early stage, like SCD. In this study, we compared the accuracy of the SCD progression prediction using the ‘severity index’ generated using a standard classification model trained on patients with AD dementia versus a new model trained on β-amyloid (Aβ) positive patients with amnestic mild cognitive impairment (aMCI). Methods We used structural MRI data of 504 patients from the Swedish BioFINDER-1 study cohort (cognitively normal (CN), Aβ-negative = 220; SCD, Aβ positive and negative = 139; aMCI, Aβ-positive = 106; AD dementia = 39). We applied multivariate data analysis to create two predictive models trained to discriminate CN individuals from either individuals with Aβ positive aMCI or AD dementia. Models were applied to individuals with SCD to classify their atrophy patterns as either high-risk “disease-like” or low-risk “CN-like”. Clinical trajectory and model accuracy were evaluated using 8 years of longitudinal data. Results In predicting progression from SCD to MCI or dementia, the standard, dementia-based model, reached 100% specificity but only 10.6% sensitivity, while the new, aMCI-based model, reached 72.3% sensitivity and 60.9% specificity. The aMCI-based model was superior in predicting progression from SCD to MCI or dementia, reaching a higher receiver operating characteristic area under curve (AUC = 0.72; P = 0.037) in comparison with the dementia-based model (AUC = 0.57). Conclusion When predicting conversion from SCD to MCI or dementia using structural MRI data, prediction models based on individuals with milder levels of atrophy (i.e. aMCI) may offer superior clinical value compared to standard dementia-based models.

Abstract Background Although several cardiovascular, demographic, genetic and lifestyle factors have been associated with cognitive function, little is known about what type of cognitive impairment they are associated with. The aim was to examine the associations between different risk factors and future memory and attention/executive functions, and their interaction with APOE genotype. Methods Participants from a large, prospective, population-based, Swedish study were included (n = 3,229). Linear regression models were used to examine baseline hypertension, body mass index (BMI), long-term glucose levels (HbA1c), different lipid levels, physical activity, alcohol consumption, smoking, education, APOE genotype, age and sex. All models were adjusted for follow-up time and basic demographics, and, in a second step, all significant predictors were included to examine independent effects. Follow-up outcomes were memory and attention/executive functions. Results The mean age at baseline was 56.1 (SD 5.7) years and 59.7% were women. The mean follow-up time was 17.4 (range 14.3–20.8) years. When examining independent effects, APOE ε4 genotype(p

Abstract Background Studies suggest that cerebrospinal fluid (CSF) levels of amyloid-β (Aβ)42 and Aβ40 present a circadian rhythm. However sustained sampling of large volumes of CSF with indwelling intrathecal catheters used in most of these studies might have affected CSF dynamics and thereby confounded the observed fluctuations in the biomarker levels. Methods We included 38 individuals with either normal (N = 20) or abnormal (N = 18) CSF Aβ42/Aβ40 levels at baseline. CSF and plasma were collected at two visits separated by an average of 53 days with lumbar punctures and venipunctures performed either in the morning or evening. At the first visit, sample collection was performed in the morning for 17 participants and the order was reversed for the remaining 21 participants. CSF and plasma samples were analyzed for Alzheimer’ disease (AD) biomarkers, including Aβ42, Aβ40, GFAP, NfL p-tau181, p-tau217, p-tau231 and t-tau. CSF samples were also tested using mass spectrometry for 22 synaptic and endo-lysosomal proteins. Results CSF Aβ42 (mean difference [MD], 0.21 ng/mL; p = 0.038), CSF Aβ40 (MD, 1.85 ng/mL; p

Abstract 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.

Abstract 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.

Abstract Blood-based biomarkers for screening may guide tau positrion emissition tomography (PET) scan referrals to optimize prognostic evaluation in Alzheimer’s disease. Plasma Aβ42/Aβ40, 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.

Age-related white matter hyperintensities are a common feature and are known to be negatively associated with structural integrity, functional connectivity, and cognitive performance. However, this has yet to be fully understood mechanistically. We analyzed multiple MRI modalities acquired in 465 non-demented individuals from the Swedish BioFINDER study including 334 cognitively normal and 131 participants with mild cognitive impairment. White matter hyperintensities were automatically quantified using fluid-attenuated inversion recovery MRI and parameters from diffusion tensor imaging were estimated in major white matter fibre tracts. We calculated fMRI resting state-derived functional connectivity within and between predefined cortical regions structurally linked by the white matter tracts. How change in functional connectivity is affected by white matter lesions and related to cognition (in the form of executive function and processing speed) was explored. We examined the functional changes using a measure of sample entropy. As expected hyperintensities were associated with disrupted structural white matter integrity and were linked to reduced functional interregional lobar connectivity, which was related to decreased processing speed and executive function. Simultaneously, hyperintensities were also associated with increased intraregional functional connectivity, but only within the frontal lobe. This phenomenon was also associated with reduced cognitive performance. The increased connectivity was linked to increased entropy (reduced predictability and increased complexity) of the involved voxels’ blood oxygenation level-dependent signal. Our findings expand our previous understanding of the impact of white matter hyperintensities on cognition by indicating novel mechanisms that may be important beyond this particular type of brain lesions.

Abstract Background Novel phosphorylated-tau (p-tau) blood biomarkers (e.g., p-tau181, p-tau217 or p-tau231), are highly specific for Alzheimer’s disease (AD), and can track amyloid-β (Aβ) and tau pathology. However, because these biomarkers are strongly associated with the emergence of Aβ pathology, it is difficult to determine the contribution of insoluble tau aggregates to the plasma p-tau signal in blood. Therefore, there remains a need for a biomarker capable of specifically tracking insoluble tau accumulation in brain. Methods NTA is a novel ultrasensitive assay targeting N-terminal containing tau fragments (NTA-tau) in cerebrospinal fluid (CSF) and plasma, which is elevated in AD. Using two well-characterized research cohorts (BioFINDER-2, n = 1,294, and BioFINDER-1, n = 932), we investigated the association between plasma NTA-tau levels and disease progression in AD, including tau accumulation, brain atrophy and cognitive decline. Results We demonstrate that plasma NTA-tau increases across the AD continuum¸ especially during late stages, and displays a moderate-to-strong association with tau-PET (β = 0.54, p

Abstract Background Antibody-based immunoassays have enabled quantification of very low concentrations of phosphorylated tau (p-tau) protein forms in cerebrospinal fluid (CSF), aiding in the diagnosis of AD. Mass spectrometry enables absolute quantification of multiple p-tau variants within a single run. The goal of this study was to compare the performance of mass spectrometry assessments of p-tau181, p-tau217 and p-tau231 with established immunoassay techniques. Methods We measured p-tau181, p-tau217 and p-tau231 concentrations in CSF from 173 participants from the TRIAD cohort and 394 participants from the BioFINDER-2 cohort using both mass spectrometry and immunoassay methods. All subjects were clinically evaluated by dementia specialists and had amyloid-PET and tau-PET assessments. Bland–Altman analyses evaluated the agreement between immunoassay and mass spectrometry p-tau181, p-tau217 and p-tau231. P-tau associations with amyloid-PET and tau-PET uptake were also compared. Receiver Operating Characteristic (ROC) analyses compared the performance of mass spectrometry and immunoassays p-tau concentrations to identify amyloid-PET positivity. Results Mass spectrometry and immunoassays of p-tau217 were highly comparable in terms of diagnostic performance, between-group effect sizes and associations with PET biomarkers. In contrast, p-tau181 and p-tau231 concentrations measured using antibody-free mass spectrometry had lower performance compared with immunoassays. Conclusions Our results suggest that while similar overall, immunoassay-based p-tau biomarkers are slightly superior to antibody-free mass spectrometry-based p-tau biomarkers. Future work is needed to determine whether the potential to evaluate multiple biomarkers within a single run offsets the slightly lower performance of antibody-free mass spectrometry-based p-tau quantification.

Abstract A positron emission tomography (PET) tracer detecting α-synuclein pathology will improve the diagnosis, and ultimately the treatment of α-synuclein-related diseases. Here we show that the PET ligand, [18F]ACI-12589, displays good in vitro affinity and specificity for pathological α-synuclein in tissues from patients with different α-synuclein-related disorders including Parkinson’s disease (PD) and Multiple-System Atrophy (MSA) using autoradiography and radiobinding techniques. In the initial clinical evaluation we include 23 participants with α-synuclein related disorders, 11 with other neurodegenerative disorders and eight controls. In vivo [18F]ACI-12589 demonstrates clear binding in the cerebellar white matter and middle cerebellar peduncles of MSA patients, regions known to be highly affected by α-synuclein pathology, but shows limited binding in PD. The binding statistically separates MSA patients from healthy controls and subjects with other neurodegenerative disorders, including other synucleinopathies. Our results indicate that α-synuclein pathology in MSA can be identified using [18F]ACI-12589 PET imaging, potentially improving the diagnostic work-up of MSA and allowing for detection of drug target engagement in vivo of novel α-synuclein targeting therapies.

The interplay between amyloid and tau pathology in Alzheimer’s disease is still not well understood. Here, the authors show that amyloid-related increased in soluble p-tau is related to subsequent accumulation of tau aggregates and cognitive decline in early stage of the disease.

Abstract Background Cortical atrophy is associated with cognitive decline, but the association is not perfect. We aimed to identify factors explaining the discrepancy between the degree of cortical atrophy and cognitive decline in cognitively unimpaired elderly. Methods The discrepancy between atrophy and cognitive decline was measured using the residuals from a linear regression analysis between change in whole brain cortical thickness over time and change in a cognitive composite measure over time in 395 cognitively unimpaired participants from the Swedish BioFINDER study. We tested for bivariate associations of this residual measure with demographic, imaging, and fluid biomarker variables using Pearson correlations and independent-samples t-tests, and for multivariate associations using linear regression models. Mediation analyses were performed to explore possible paths between the included variables. Results In bivariate analyses, older age (r = −0.11, p = 0.029), male sex (t = −3.00, p = 0.003), larger intracranial volume (r = −0.17, p < 0.001), carrying an APOEe4 allele (t = −2.71, p = 0.007), larger white matter lesion volume (r = −0.16, p = 0.002), lower cerebrospinal fluid (CSF) β-amyloid (Aβ) 42/40 ratio (t = −4.05, p < 0.001), and higher CSF levels of phosphorylated tau (p-tau) 181 (r = −0.22, p < 0.001), glial fibrillary acidic protein (GFAP; r = −0.15, p = 0.003), and neurofilament light (NfL; r = −0.34, p < 0.001) were negatively associated with the residual measure, i.e., associated with worse than expected cognitive trajectory given the level of atrophy. In a multivariate analysis, only lower CSF Aβ42/40 ratio and higher CSF NfL levels explained cognition beyond brain atrophy. Mediation analyses showed that associations between the residual measure and APOEe4 allele, CSF Aβ42/40 ratio, and CSF GFAP and p-tau181 levels were mediated by levels of CSF NfL, as were the associations with the residual measure for age, sex, and WML volume. Conclusions Our results suggest that axonal degeneration and amyloid pathology independently affect the rate of cognitive decline beyond the degree of cortical atrophy. Furthermore, axonal degeneration mediated the negative effects of old age, male sex, and white matter lesions, and in part also amyloid and tau pathology, on cognition over time when accounting for cortical atrophy.

Abstract Introduction The optimal combination of amyloid‐β/tau/neurodegeneration (A/T/N) biomarker profiles for the diagnosis of Alzheimer's disease (AD) dementia is unclear. Methods We examined the discriminative accuracy of A/T/N combinations assessed with neuroimaging biomarkers for the differentiation of AD from cognitively unimpaired (CU) elderly and non‐AD neurodegenerative diseases in the TRIAD, BioFINDER‐1 and BioFINDER‐2 cohorts (total n = 832) using area under the receiver operating characteristic curves (AUC). Results For the diagnosis of AD dementia (vs. CU elderly), T biomarkers performed as well as the complete A/T/N system (AUC range: 0.90–0.99). A and T biomarkers in isolation performed as well as the complete A/T/N system in differentiating AD dementia from non‐AD neurodegenerative diseases (AUC range; A biomarker: 0.84–1; T biomarker: 0.83–1). Discussion In diagnostic settings, the use of A or T neuroimaging biomarkers alone can reduce patient burden and medical costs compared with using their combination, without significantly compromising accuracy.

Abstract Studies of the genetic regulation of cerebrospinal fluid (CSF) proteins may reveal pathways for treatment of neurological diseases. 398 proteins in CSF were measured in 1,591 participants from the BioFINDER study. Protein quantitative trait loci (pQTL) were identified as associations between genetic variants and proteins, with 176 pQTLs for 145 CSF proteins (P

Abstract Cognitive decline in early-stage Alzheimer’s disease (AD) may depend on genetic variability. In the Swedish BioFINDER study, we used polygenic scores (PGS) (for AD, intelligence, and educational attainment) to predict longitudinal cognitive change (measured by mini-mental state examination (MMSE) [primary outcome] and other cognitive tests) over a mean of 4.2 years. We included 260 β-amyloid (Aβ) negative cognitively unimpaired (CU) individuals, 121 Aβ-positive CU (preclinical AD), 50 Aβ-negative mild cognitive impairment (MCI) patients, and 127 Aβ-positive MCI patients (prodromal AD). Statistical significance was determined at Bonferroni corrected p value

Abstract PET, CSF and plasma biomarkers of tau pathology may be differentially associated with Alzheimer's disease (AD)‐related demographic, cognitive, genetic and neuroimaging markers. We examined 771 participants with normal cognition, mild cognitive impairment or dementia from BioFINDER‐2 (n = 400) and ADNI (n = 371). All had tau‐PET ([18F]RO948 in BioFINDER‐2, [18F]flortaucipir in ADNI) and CSF p‐tau181 biomarkers available. Plasma p‐tau181 and plasma/CSF p‐tau217 were available in BioFINDER‐2 only. Concordance between PET, CSF and plasma tau biomarkers ranged between 66 and 95%. Across the whole group, ridge regression models showed that increased CSF and plasma p‐tau181 and p‐tau217 levels were independently of tau PET associated with higher age, and APOEɛ4‐carriership and Aβ‐positivity, while increased tau‐PET signal in the temporal cortex was associated with worse cognitive performance and reduced cortical thickness. We conclude that biofluid and neuroimaging markers of tau pathology convey partly independent information, with CSF and plasma p‐tau181 and p‐tau217 levels being more tightly linked with early markers of AD (especially Aβ‐pathology), while tau‐PET shows the strongest associations with cognitive and neurodegenerative markers of disease progression.

Plasma biomarkers of amyloid, tau and neurodegeneration (ATN) need to be characterized in cognitively unimpaired (CU) elderly individuals. Here, the authors show plasma ATN biomarkers predict clinical deterioration and cognitive decline and show in a simulated clinical trial combining all three biomarkers reduced the required sample size.

Cerebrospinal fluid neurofilament light (NfL) is a biomarker for neurodegeneration that can also be assessed in blood. Here the authors show in a validation study the potential for plasma NfL as a biomarker for several neurodegenerative diseases.

Abstract Alzheimer’s disease is characterized by β‐amyloid plaques and tau tangles. Plasma levels of phospho‐tau217 (P‐tau217) accurately differentiate Alzheimer’s disease dementia from other dementias, but it is unclear to what degree this reflects β‐amyloid plaque accumulation, tau tangle accumulation, or both. In a cohort with post‐mortem neuropathological data (N = 88), both plaque and tangle density contributed independently to higher P‐tau217, but P‐tau217 was not elevated in patients with non‐Alzheimer’s disease tauopathies (N = 9). Several findings were replicated in a cohort with PET imaging (“BioFINDER‐2”, N = 426), where β‐amyloid and tau PET were independently associated with P‐tau217. P‐tau217 concentrations correlated with β‐amyloid PET (but not tau PET) in early disease stages and with both β‐amyloid and (more strongly) tau PET in late disease stages. Finally, P‐tau217 mediated the association between β‐amyloid and tau in both cohorts, especially for tau outside of the medial temporal lobe. These findings support the hypothesis that plasma P‐tau217 concentration is increased by both β‐amyloid plaques and tau tangles and is congruent with the hypothesis that P‐tau is involved in β‐amyloid‐dependent formation of neocortical tau tangles.

Abstract Mild behavioral impairment (MBI) is suggested as risk marker for neurodegenerative diseases, such as Alzheimer’s disease (AD). Recently, pathologic tau deposition in the brain has been shown closely related to clinical manifestations, such as cognitive deficits. Yet, associations between tau pathology and MBI have rarely been investigated. It is further debated if MBI precedes cognitive deficits in AD. Here, we explored potential mechanisms by which MBI is related to AD, this by studying associations between MBI and tau in preclinical AD. In all, 50 amyloid-β-positive cognitively unimpaired subjects (part of the BioFINDER-2 study) underwent MBI-checklist (MBI-C) to assess MBI, and the Alzheimer’s Disease Assessment Scale – Cognitive subscale (ADAS-Cog) delayed word recall (ADAS-DR) to assess episodic memory. Early tau pathology was determined using tau-PET ([18F]RO948 retention in entorhinal cortex/hippocampus) and cerebrospinal fluid (CSF) P-tau181. Regression models were used to test for associations. We found that higher tau-PET signal in the entorhinal cortex/hippocampus and CSF P-tau181 levels were associated with higher MBI-C scores (β = 0.010, SE = 0.003, p = 0.003 and β = 1.263, SE = 0.446, p = 0.007, respectively). When MBI-C and ADAS-DR were entered together in the regression models, tau-PET (β = 0.009, p = 0.009) and CSF P-tau181 (β = 0.408, p = 0.006) were predicted by MBI-C, but not ADAS-DR. We conclude that in preclinical AD, MBI is associated with tau independently from memory deficits. This denotes MBI as an important early clinical manifestation related to tau pathology in AD.

Abstract It is unclear how pathological aging of the inflammatory system relates to Alzheimer’s disease (AD). We tested whether age-related inflammatory changes in cerebrospinal fluid (CSF) and plasma exist across different stages of AD, and whether such changes related to AD pathology. Linear regression was first used model chronological age in amyloid-β negative, cognitively unimpaired individuals (Aβ− CU; n = 312) based on a collection of 73 inflammatory proteins measured in both CSF and plasma. Fitted models were then applied on protein levels from Aβ+ individuals with mild cognitive impairment (Aβ+ MCI; n = 150) or Alzheimer’s disease dementia (Aβ+ AD; n = 139) to test whether the age predicted from proteins alone (“inflammatory age”) differed significantly from true chronological age. Aβ− individuals with subjective cognitive decline (Aβ− SCD; n = 125) or MCI (Aβ− MCI; n = 104) were used as an independent contrast group. The difference between inflammatory age and chronological age (InflammAGE score) was then assessed in relation to core AD biomarkers of amyloid, tau, and cognition. Both CSF and plasma inflammatory proteins were significantly associated with age in Aβ− CU individuals, with CSF-based proteins predicting chronological age better than plasma-based counterparts. Meanwhile, the Aβ− SCD and validation Aβ− CU groups were not characterized by significant inflammatory aging, while there was increased inflammatory aging in Aβ− MCI patients for CSF but not plasma inflammatory markers. Both CSF and plasma inflammatory changes were seen in the Aβ+ MCI and Aβ+ AD groups, with varying degrees of change compared to Aβ− CU and Aβ− SCD groups. Finally, CSF inflammatory changes were highly correlated with amyloid, tau, general neurodegeneration, and cognition, while plasma changes were mostly associated with amyloid and cognition. Inflammatory pathways change during aging and are specifically altered in AD, tracking closely with pathological hallmarks. These results have implications for tracking AD progression and for suggesting possible pathways for drug targeting.

Cerebrospinal fluid (CSF) p-tau181 (tau phosphorylated at threonine 181) is an established biomarker of Alzheimer’s disease (AD) reflecting abnormal tau metabolism in the AD brain. Here the authors demonstrate that CSF p-tau217 shows better performance as an AD biomarker than p-tau181.

Abstract Background As research in treatments for neurocognitive diseases progresses, there is an increasing need to identify cognitive decline in the earliest stages of disease for initiation of treatment in addition to determining the efficacy of treatment. For early identification, accurate cognitive tests cutoff values for cognitive impairment are essential. Methods We conducted a study on 297 cognitively healthy elderly people from the BioFINDER study and created subgroups excluding people with signs of underlying neuropathology, i.e., abnormal cerebrospinal fluid [CSF] β-amyloid or phosphorylated tau, CSF neurofilament light (neurodegeneration), or cerebrovascular pathology. We compared cognitive test results between groups and examined the age effect on cognitive test results. Results In our subcohort without any measurable pathology (n = 120), participants achieved better test scores and significantly stricter cutoffs for cognitive impairment for almost all the examined tests. The age effect in this subcohort disappeared for all cognitive tests, apart from some attention/executive tests, predominantly explained by the exclusion of cerebrovascular pathology. Conclusion Our study illustrates a new approach to establish normative data that could be useful to identify earlier cognitive changes in preclinical dementias. Future studies need to investigate if there is a genuine effect of healthy aging on cognitive tests or if this age effect is a proxy for higher prevalence of preclinical neurodegenerative diseases.

Abstract Failures in Alzheimer's disease (AD) drug trials highlight the need to further explore disease mechanisms and alterations of biomarkers during the development of AD. Using cross‐sectional data from 377 participants in the BioFINDER study, we examined seven cerebrospinal fluid (CSF) and six plasma biomarkers in relation to β‐amyloid (Aβ) PET uptake to understand their evolution during AD. In CSF, Aβ42 changed first, closely followed by Aβ42/Aβ40, phosphorylated‐tau (P‐tau), and total‐tau (T‐tau). CSF neurogranin, YKL‐40, and neurofilament light increased after the point of Aβ PET positivity. The findings were replicated using Aβ42, Aβ40, P‐tau, and T‐tau assays from five different manufacturers. Changes were seen approximately simultaneously for CSF and plasma biomarkers. Overall, plasma biomarkers had smaller dynamic ranges, except for CSF and plasma P‐tau which were similar. In conclusion, using state‐of‐the‐art biomarkers, we identified the first changes in Aβ, closely followed by soluble tau. Only after Aβ PET became abnormal, biomarkers of neuroinflammation, synaptic dysfunction, and neurodegeneration were altered. These findings lend in vivo support of the amyloid cascade hypotheses in humans.

Abstract To date, the development of disease-modifying therapies for Alzheimer’s disease (AD) has largely focused on the removal of amyloid beta Aβ fragments from the CNS. Proteomic profiling of patient fluids may help identify novel therapeutic targets and biomarkers associated with AD pathology. Here, we applied the Olink™ ProSeek immunoassay to measure 270 CSF and plasma proteins across 415 Aβ- negative cognitively normal individuals (Aβ- CN), 142 Aβ-positive CN (Aβ+ CN), 50 Aβ- mild cognitive impairment (MCI) patients, 75 Aβ+ MCI patients, and 161 Aβ+ AD patients from the Swedish BioFINDER study. A validation cohort included 59 Aβ- CN, 23 Aβ- + CN, 44 Aβ- MCI and 53 Aβ+ MCI. To compare protein concentrations in patients versus controls, we applied multiple linear regressions adjusting for age, gender, medications, smoking and mean subject-level protein concentration, and corrected findings for false discovery rate (FDR, q

Abstract Background Widespread implementation of Alzheimer’s disease biomarkers in routine clinical practice requires the establishment of standard operating procedures for pre-analytical handling of cerebrospinal fluid (CSF). Methods Here, CSF collection and storage protocols were optimized for measurements of β-amyloid (Aβ). We investigated the effects of (1) storage temperature, (2) storage time, (3) centrifugation, (4) sample mixing, (5) blood contamination, and (6) collection gradient on CSF levels of Aβ. For each study participant, we used fresh CSF directly collected into a protein low binding (LoB) tube that was analyzed within hours after lumbar puncture (LP) as standard of truth. Aβ42 and Aβ40 were measured in de-identified CSF samples using EUROIMMUN and Mesoscale discovery assays. Results CSF Aβ42 and Aβ40 were stable for at least 72 h at room temperature (RT), 1 week at 4 °C, and 2 weeks at − 20 °C and − 80 °C. Centrifugation of non-blood-contaminated CSF or mixing of samples before the analysis did not affect Aβ levels. Addition of 0.1–10% blood to CSF that was stored at RT without centrifugation led to a dose- and time-dependent decrease in Aβ42 and Aβ40, while Aβ42/Aβ40 did not change. The effects of blood contamination were mitigated by centrifugation and/or storage at 4 °C or − 20 °C. Aβ levels did not differ between the first to fourth 5-ml portions of CSF. Conclusions CSF can be stored for up to 72 h at RT, 1 week at 4 °C, or at least 2 weeks at either − 20 °C or − 80 °C before Aβ measurements. Centrifugation of fresh non-blood-contaminated CSF after LP, or mixing before analysis, is not required. In case of visible blood contamination, centrifugation and storage at 4 °C or − 20 °C is recommended. After discarding the first 2 ml, any portion of up to 20 ml of CSF is suitable for Aβ analysis. These findings will be important for the development of a clinical routine protocol for pre-analytical handling of CSF.

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.

Abstract Introduction General practitioners (GPs) play a key role in early identification of dementia, yet diagnosis is often missed or delayed in primary care. As part of the multinational Models of Patient Engagement for Alzheimer's Disease project, we assess GPs’ attitude toward early and pre‐dementia diagnosis of AD and explore barriers to early diagnosis. Methods Our survey covered general attitude toward early diagnosis, diagnostic procedures, resources, and opinion on present and future treatment options across five European countries. Results In total 343 GPs completed the survey; 74% of GPs indicated that an early diagnosis is valuable. There were country‐specific differences in GPs’ perceptions of reimbursement and time available for the patient. If a drug were available to slow down the progression of AD, 59% of the GPs would change their implementation of early diagnosis. Discussion Our findings provide insight into GPs’ attitudes by exploring differences in perception and management of early diagnosis.

Objectives: Cholinergic dysfunction plays a prominent role in cognitive impairment in Parkinson's disease (PD). The aim of this study was to assess the relationship of baseline and longitudinal basal forebrain atrophy with cognitive decline and dementia in PD. Methods: We included 106 non-demented PD patients, 19 PD dementia (PDD) patients and 42 controls with longitudinal structural MRI and cognitive testing. After 4.2 ± 1.8 years, 20 non-demented PD patients were diagnosed with dementia (PD-dementia converters), whereas the rest of PD patients remained non-demented (stable-PD). We compared MRI volumes of the medial septum/diagonal band (Ch1/Ch2) and nucleus basalis of Meynert (Ch4) between groups. Cox regression analyses were applied to test whether Ch1/Ch2 or Ch4 atrophy could predict future dementia and linear mixed models assessed their association with cognitive decline. Results: Compared to controls, we found reduced Ch4 baseline volumes in PD-dementia converters (p = .003) and those who already had PDD (p

Abstract Introduction We aimed to establish a standardized, routine‐use pre‐analytical protocol for measuring Alzheimer's disease (AD) biomarkers in cerebrospinal fluid (CSF). Methods The effect of pre‐analytical factors (sample collection/handling/storage/transportation) on biomarker levels was assessed using freshly collected CSF. Tube type/sterilization was assessed using previously frozen samples. A low‐bind false‐bottom tube (FBT, Sarstedt) was used for all experiments, except tube types/sterilization experiments. Biomarkers were measured using Elecsys CSF assays. Results Amyloid beta (Aβ)1‐42 levels varied by tube type, using a low‐bind FBT reduced variation. Aβ1‐42 levels were higher with no mixing versus roller/inversion mixing. Aβ1‐42 levels were lower with horizontal versus upright transportation; this was resolved by maximal tube filling and storage at 2°C to 8°C. Aβ1‐40 levels were less strongly affected. Phospho‐tau and total‐tau levels were largely unaffected. Discussion We propose an easy‐to‐use, standardized, routine‐use pre‐analytical protocol, using low‐bind FBTs, for measuring AD CSF biomarkers in clinical practice.

Abstract Background Alzheimer’s disease is characterized by aggregated β-amyloid and tau proteins, but the clinical presentations and patterns of brain atrophy vary substantially. A part of this heterogeneity may be linked to the risk allele APOE ε4. The spread of tau pathology is related to atrophy and cognitive decline, but little data exist on the effects of APOE ε4 on tau. The objective of this preliminary study was therefore to test if tau load and brain structure differ by APOE ε4 in Alzheimer’s disease. Methods Sixty-five β-amyloid-positive patients at the prodromal and dementia stages of Alzheimer’s disease were enrolled, including APOE ε4-positive (n = 46) and APOE ε4-negative (n = 19) patients. 18F-AV-1451 positron emission tomography was used to measure tau and brain magnetic resonance imaging (MRI) was used to measure cortical thickness. Results Compared with their APOE ε4-positive counterparts, APOE ε4-negative patients had greater tau load and reduced cortical thickness, with the most pronounced effects for both in the parietal cortex. Relative to the overall cortical tau load, APOE ε4-positive patients had greater tau load in the entorhinal cortex. APOE ε4-positive patients also had slightly greater cortical β-amyloid load. There was an interaction between APOE ε4 and 18F-AV-1451 on cortical thickness, with greater effects of 18F-AV-1451 on cortical thickness in APOE ε4-negative patients. APOE ε4 and 18F-AV-1451 were independent predictors of cognition, but showed distinct associations with different cognitive tests. Conclusions APOE genotype may be associated with differences in pathways in Alzheimer’s disease, potentially through differential development and spread of tau, as well as through effects on cognitive outcomes involving non-tau-related mechanisms.

Abnormal levels of Aβ42 in the cerebrospinal fluid occur prior to a positive amyloid PET scan in the brain of individuals with Alzheimer’s disease and here the authors use this temporal pattern to identify individuals with very early stage AD. They show that Aβ fibrils start to accumulate in some of the regions of the default mode network and affect brain connectivity before neurodegeneration occurs.

Abstract Introduction Cerebrospinal fluid collection by lumbar puncture (LP) is performed in the diagnostic workup of several neurological brain diseases. Reluctance to perform the procedure is among others due to a lack of standards and guidelines to minimize the risk of complications, such as post‐LP headache or back pain. Methods We provide consensus guidelines for the LP procedure to minimize the risk of complications. The recommendations are based on (1) data from a large multicenter LP feasibility study (evidence level II‐2), (2) systematic literature review on LP needle characteristics and post‐LP complications (evidence level II‐2), (3) discussion of best practice within the Joint Programme Neurodegenerative Disease Research Biomarkers for Alzheimer's disease and Parkinson's Disease and Biomarkers for Multiple Sclerosis consortia (evidence level III). Results Our consensus guidelines address contraindications, as well as patient‐related and procedure‐related risk factors that can influence the development of post‐LP complications. Discussion When an LP is performed correctly, the procedure is well tolerated and accepted with a low complication rate.

Autosomal dominant Alzheimer's disease is thought to be caused by increased amyloidogenic APP processing. Mattson et al.show that association between brain Aβ and cerobrospinal fluid Aβ40 levels is stronger in APOE ɛ4 negative people, suggesting that increased processing may also underlie sporadic disease.

Background: Arterial stiffness reflects the ageing processes in the vascular system, and studies have shown an association between reduced cognitive function and cerebral small vessel disease. Small vessel disease can be visualized as white matter hyperintensities (WMH) and lacunar infarcts but also as cerebral microbleeds on brain magnetic resonance imaging (MRI). We aimed to investigate if arterial stiffness influences the presence of microbleeds, WMH and cognitive function in a population of cognitively healthy elderly. Methods: The study population is part of the Swedish BioFinder study and consisted of 208 individuals without any symptoms of cognitive impairment, who scored >27 points on the Mini-Mental State Examination. The participants (mean age, 72 years; 59% women) underwent MRI of the brain with visual rating of microbleeds and WMH. Arterial stiffness was measured with carotid-femoral pulse wave velocity (cfPWV). Eight cognitive tests covering different cognitive domains were performed. Results: Microbleeds were detected in 12% and WMH in 31% of the participants. Mean (±standard deviation, SD) cfPWV was 10.0 (±2.0) m/s. There was no association between the presence of microbleeds and arterial stiffness. There was a positive association between arterial stiffness and WMH independent of age or sex (odds ratio, 1.58; 95% confidence interval, 1.04-2.40, p 0.05). Cognitive performance was not associated with microbleeds, but individuals with WMH performed slightly worse than those without WMH on the Symbol Digit Modalities Test (mean ± SD, 35 ± 7.8 vs. 39 ± 8.1, p Conclusions: Arterial stiffness was not associated with the presence of cerebral microbleeds or cognitive function in cognitively healthy elderly. However, arterial stiffness was related to the presence of WMH, but the association was attenuated when multiple adjustments were made. There was a weak negative association between WMH and performance in one specific test of attention. Longitudinal follow-up studies are needed to further assess the associations.

Alzheimer’s disease (AD) is associated with atrophy of the cornu ammonis (CA) 1 and the subiculum subfield of the hippocampus (HC), and with deficits in episodic memory and spatial orientation. These deficits are mainly associated with the functionality of the posterior HC. We therefore hypothesized that key AD pathologies, i.e., β-amyloid and tau pathology would be particularly associated with the volume of the posterior subiculum in non-demented individuals. In our study we included 302 cognitively normal elderly participants (CN), 183 patients with subjective cognitive decline (SCD) and 171 patients with amnestic mild cognitive impairment (MCI), all of whom underwent 3T magnetic resonance images (MRI). The subicular subfield was segmented using Freesurfer 5.3 and divided into 10 volumetric segments moving from the most posterior (segment 1) to the most anterior part along the axis of the hippocampal head and body (segment 10). Cerebrospinal fluid (CSF) Aβ42 and phosphorylated tau (P-tau) were quantified using ELISA and were used as biomarkers for β-amyloid and tau pathology, respectively. In the total sample, tau-pathology and Aβ-pathology and (measured by elevated P-tau and low Aβ42 levels in CSF) and mild memory dysfunction were mostly associated with the volume changes of the posterior subiculum. Both SCD and MCI patients with elevated P-tau or low Aβ42 levels displayed predominantly posterior subicular atrophy in comparisons to control subjects with normal CSF biomarker levels. Finally, there was no main effect of Aβ42 or P-tau when comparing SCD with abnormal P-tau or Aβ42 with SCD with normal levels of these CSF-biomarkers. However, in the left subiculum there was a significant interaction revealing atrophy in the left posterior but not the anterior subiculum in participants with low Aβ42 levels. The same pattern was observed on the contralateral side in participants with elevated P-tau levels. In conclusion, AD pathologies and mild memory dysfunction are mainly associated with atrophy of the posterior parts of the subicular subfields of the HC in non-demented individuals. In light of these findings we suggest that segmentation of the HC subfields may benefit from considering the volume of the different anterior-posterior subsections of each subfield.

Diffusion tensor imaging (DTI) has been used to study microstructural white matter alterations in a variety of conditions including normal aging and Alzheimer's disease (AD). White matter hyperintensities (WMH) are common in cognitively healthy elderly as well as in AD and exhibit elevated mean diffusivity (MD) and reduced fractional anisotropy (FA). However, the effect of WMH on statistical analysis of DTI estimates has not been thoroughly studied. In the present study we address this in two ways. First, we investigate the effect of WMH on MD and FA in the dorsal and ventral cingulum, the superior longitudinal fasciculus, and the corticospinal tract, by comparing two matched groups of cognitively healthy elderly (n = 21 + 21) with unequal WMH load. Second, we assess the effects of adjusting for WMH load when comparing MD and FA in prodromal AD subjects (n = 83) to cognitively healthy elderly (n = 132) in the abovementioned white matter tracts. Results showed the WMH in cognitively healthy elderly to have a generally large effect on DTI estimates (Cohen's d = 0.63 to 1.27 for significant differences in MD and -1.06 to -0.69 for FA). These effect sizes were comparable to those of various neurological and psychiatric diseases (Cohen's d = 0.57 to 2.20 for differences in MD and -1.76 to -0.61 for FA). Adjusting for WMH when comparing DTI estimates in prodromal AD subjects to cognitively healthy elderly improved the explanatory power as well as the outcome of the analysis, indicating that some of the differences in MD and FA were largely driven by unequal WMH load between the groups rather than alterations in normal-appearing white matter (NAWM). Thus, our findings suggest that if the purpose of a study is to compare alterations in NAWM between two groups using DTI it may be necessary to adjust the statistical analysis for WMH.

BACKGROUND: The CSF biomarkers tau and Abeta42 can identify patients with AD, even during the preclinical stages. However, previous studies on longitudinal changes of tau and Abeta42 in individual patients with AD and elderly controls report somewhat inconsistent results. METHODOLOGY/PRINCIPAL FINDINGS: We investigated the levels of tau and Abeta42 at baseline and after 1 year in 100 patients with AD. In a second cohort of 45 AD patients we measured the CSF biomarkers at baseline and after 2 years. Moreover, in 34 healthy elderly controls the CSF biomarkers were followed for 4 years. The baseline levels of tau were increased with >60% in AD patients compared to controls (p50% (p