Background Blood-based amyloid biomarkers may provide a non-invasive, cost-effective and scalable manner for detecting cerebral amyloidosis in early disease stages. Methods In this prospective cross-sectional study, we quantified plasma Aβ1–42/Aβ1–40 ratios with both routinely available ELISAs and novel SIMOA Amyblood assays, and provided a head-to-head comparison of their performances to detect cerebral amyloidosis in a nondemented elderly cohort (n = 199). Participants were stratified according to amyloid-PET status, and the performance of plasma Aβ1–42/Aβ1–40 to detect cerebral amyloidosis was assessed using receiver operating characteristic analysis. We additionally investigated the correlations of plasma Aβ ratios with amyloid-PET and CSF Alzheimer’s disease biomarkers, as well as platform agreement using Passing-Bablok regression and Bland-Altman analysis for both Aβ isoforms. Results ELISA and SIMOA plasma Aβ1–42/Aβ1–40 detected cerebral amyloidosis with identical accuracy (ELISA: area under curve (AUC) 0.78, 95% CI 0.72–0.84; SIMOA: AUC 0.79, 95% CI 0.73–0.85), and both increased the performance of a basic demographic model including only age and APOE-ε4 genotype (p ≤ 0.02). ELISA and SIMOA had positive predictive values of respectively 41% and 36% in cognitively normal elderly and negative predictive values all exceeding 88%. Plasma Aβ1–42/Aβ1–40 correlated similarly with amyloid-PET for both platforms (Spearman ρ = − 0.32, p <  0.0001), yet correlations with CSF Aβ1–42/t-tau were stronger for ELISA (ρ = 0.41, p = 0.002) than for SIMOA (ρ = 0.29, p = 0.03). Plasma Aβ levels demonstrated poor agreement between ELISA and SIMOA with concentrations of both Aβ1–42 and Aβ1–40 measured by SIMOA consistently underestimating those measured by ELISA. Conclusions ELISA and SIMOA demonstrated equivalent performances in detecting cerebral amyloidosis through plasma Aβ1–42/Aβ1–40, both with high negative predictive values, making them equally suitable non-invasive prescreening tools for clinical trials by reducing the number of necessary PET scans for clinical trial recruitment. Trial registration EudraCT 2009-014475-45 (registered on 23 Sept 2009) and EudraCT 2013-004671-12 (registered on 20 May 2014, https://www.clinicaltrialsregister.eu/ctr-search/trial/2013-004671-12/BE).

The extent to which deficits in non-verbal auditory processing contribute to the clinical phenotype of primary progressive aphasia (PPA) is unclear. Grube et al. reveal impairments in processing the timing of brief sequences of non-linguistic stimuli, particularly in the non-fluent variant, indicative of a core central auditory impairment in PPA.

IMPORTANCE Corticolimbic patterns of neurofibrillary tangle (NFT) accumulation define neuropathologic subtypes of Alzheimer disease (AD), which underlie the clinical heterogeneity observed antemortem. The cholinergic system, which is the target of acetylcholinesterase inhibitor therapy, is selectively vulnerable in AD.OBJECTIVE To investigate the major source of cholinergic innervation, the nucleus basalis of Meynert (nbM), in order to determine whether there is differential involvement of NFT accumulation or neuronal loss among AD subtypes. DESIGN, SETTING, AND PARTICIPANTSIn this cross-sectional study, retrospective abstraction of clinical records and quantitative assessment of NFTs and neuron counts in the nbM was completed in January 2019 at the Mayo Clinic using the Florida Autopsied Multi-Ethnic (FLAME) cohort, which had been accessioned from 1991 until 2015. The FLAME cohort is derived from the deeded autopsy program funded throughout the State of Florida's memory disorder clinic referral services. Of the 2809 consecutively accessioned FLAME cohort, 1464 were identified as neuropathologically diagnosed AD cases and nondemented normal controls available for clinicopathologic assessment. Quantification of NFTs and neuronal density in the anterior nbM was performed blinded to neuropathologic groupings.MAIN OUTCOMES AND MEASURES Demographic and clinical characteristics, including cognitive decline measured using the Mini-Mental State Examination score (range, 0-30), were evaluated. The anterior nbM was investigated quantitatively for neuronal loss and NFT accumulation. RESULTSIn total, 1361 AD subtypes and 103 nondemented controls were assessed. The median (interquartile range) age at death was 72 (66-80) years in hippocampal sparing (HpSp) AD, 81 (76-86) years in typical AD, and 86 (82-90) years in limbic predominant AD. The median (interquartile range) count per 0.125 mm 2 of thioflavin S-positive NFTs was highest in the nbM of HpSp AD (14 [9-20]; n = 163), lower in typical AD (10 [5-16]; n = 937), and lowest in limbic predominant AD (8 [5-11], n = 163) (P < .001). The median (interquartile range) neuronal density per millimeters squared was lowest in HpSp AD cases (22 [17-28]; n = 148), higher in typical AD (25 [19-30]; n = 727), and highest in limbic predominant AD (26 [19-32]; n = 127) (P = .002). Multivariable regression modeling of clinical and demographic variables was performed to assess overlap in NFT accumulation and neuronal density differences among AD subtypes. Higher NFT accumulation in the nbM was associated with younger age at onset for HpSp AD (β, −1.5; 95% CI, −2.9 to −0.15; P = .03) and typical AD (β, −3.2; 95% CI, −3.9 to −2.4; P < .001). In addition, higher NFT accumulation in the nbM of typical AD cases was associated with female sex (β, 2.5; 95% CI, 1.4-3.5; P < .001), apolipoprotein E ε4 allele (β, 1.3; 95% CI, 0.15-2.5; P = .03), and lower Mini-Mental State Examination scores (β, −1.8; 95% CI, −3.2 to −0.31; P = .02). Demographic and clinical progression variables were not associated ...

BackgroundWith the shift of research focus towards the pre-dementia stage of Alzheimer’s disease (AD), there is an urgent need for reliable, non-invasive biomarkers to predict amyloid pathology. The aim of this study was to assess whether easily obtainable measures from structural MRI, combined with demographic data, cognitive data and apolipoprotein E (APOE) ε4 genotype, can be used to predict amyloid pathology using machine-learning classification.MethodsWe examined 810 subjects with structural MRI data and amyloid markers from the European Medical Information Framework for Alzheimer’s Disease Multimodal Biomarker Discovery study, including subjects with normal cognition (CN, n = 337, age 66.5 ± 7.2, 50% female, 27% amyloid positive), mild cognitive impairment (MCI, n = 375, age 69.1 ± 7.5, 53% female, 63% amyloid positive) and AD dementia (n = 98, age 67.0 ± 7.7, 48% female, 97% amyloid positive). Structural MRI scans were visually assessed and Freesurfer was used to obtain subcortical volumes, cortical thickness and surface area measures. We first assessed univariate associations between MRI measures and amyloid pathology using mixed models. Next, we developed and tested an automated classifier using demographic, cognitive, MRI and APOE ε4 information to predict amyloid pathology. A support vector machine (SVM) with nested 10-fold cross-validation was applied to identify a set of markers best discriminating between amyloid positive and amyloid negative subjects.ResultsIn univariate associations, amyloid pathology was associated with lower subcortical volumes and thinner cortex in AD-signature regions in CN and MCI. The multi-variable SVM classifier provided an area under the curve (AUC) of 0.81 ± 0.07 in MCI and an AUC of 0.74 ± 0.08 in CN. In CN, selected features for the classifier included APOE ε4, age, memory scores and several MRI measures such as hippocampus, amygdala and accumbens volumes and cortical thickness in temporal and parahippocampal regions. In MCI, the classifier including demographic and APOE ε4 information did not improve after additionally adding imaging measures.ConclusionsAmyloid pathology is associated with changes in structural MRI measures in CN and MCI. An automated classifier based on clinical, imaging and APOE ε4 data can identify the presence of amyloid pathology with a moderate level of accuracy. These results could be used in clinical trials to pre-screen subjects for anti-amyloid therapies.Electronic supplementary materialThe online version of this article (10.1186/s13195-018-0428-1) contains supplementary material, which is available to authorized users.

BackgroundBiomarkers such as amyloid imaging are increasingly used for diagnosis in the early stages of Alzheimer’s disease. Very few studies have examined this from the perspective of the patient. To date, there is only limited evidence about how patients experience and value disclosure in an early disease stage.MethodsSemistructured interviews were carried out with 38 patients with amnestic mild cognitive impairment as part of an investigator-driven diagnostic trial (EudraCT, 2013-004671-12; registered on 20 June 2014) in which participants could opt to know the binary outcome (positive/negative) result of their amyloid positron emission tomography (PET) scan. Verbatim transcripts of the interviews were evaluated using qualitative content analysis and NVivo 11 software.ResultsEight of 38 patients received a positive amyloid PET scan result, and the remaining 30 patients received a negative amyloid PET scan result. After disclosure of the result to the patients, we interviewed each patient twice: 2 weeks after disclosure and 6 months after disclosure. Patients had difficulties in repeating the exact words used during disclosure of their amyloid PET scan result by the neurologist; yet, they could recall the core message of the result in their own words. Some patients were confused by the terminology of an amyloid-positive/negative test result. At 6 months, two of eight patients with a positive amyloid PET scan result experienced emotional difficulties (sadness, feeling worried). Three of 30 patients with a negative amyloid PET scan result started to doubt whether they had received the correct result. Patients reported that they experienced advantages after the disclosure, such as information about their health status, the possibility of making practical arrangements, medication, enjoying life more, and a positive impact on relationships. They also reported disadvantages following disclosure, such as having emotional difficulties, feeling worried about when their symptoms might worsen, the risk of a more patronizing attitude by relatives, and the possibility of a wrong diagnosis.ConclusionsThis exploratory study shows that the majority of patients can accurately recall the information received during disclosure. The experienced advantages and disadvantages reported by our patients depended on the outcome of the result (positive or negative) and the interval of the conducted interview (2 weeks or 6 months after amyloid PET disclosure). Discrepancies were found between patients’ expectations according to the interview prior to amyloid PET disclosure (Vanderschaeghe et al. [Neuroethics. 2017;10:281–97]) and their actual experiences after their amyloid PET disclosure.

BackgroundResearchers currently are not obligated to share individual research results (IRR) with participants. This non-disclosure policy has been challenged on the basis of participants’ rights to be aware and in control of their personal medical information. Here, we determined how patients view disclosure of research PET results of brain amyloid and why they believe it is advantageous or disadvantageous to disclose.MethodAs a part of a larger diagnostic trial, we conducted semi-structured interviews with patients with amnestic Mild Cognitive Impairment (aMCI). Participants had the option to receive their brain amyloid PET scan result (i.e., their IRR). Interviews were conducted before they received their IRR.ResultsA total of 38 aMCI patients (100% of study participants) wanted to know their IRR. The two most frequently mentioned reasons for choosing IRR disclosure were to better understand their brain health status and to be better able to make informed decisions about future personal arrangements (e.g., inheritance tax, moving into a smaller house, end-of-life decisions, etc.). Emotional risk was mentioned as the primary disadvantage of knowing one’s IRR. On the other hand, non-disclosure was considered to be emotionally difficult also, as patients would be uncertain about their future health condition.ConclusionsMany patients diagnosed clinically with aMCI want to know their brain amyloid test results, even though this knowledge may be disadvantageous to them. Knowing what is going on with their health and the ability to make informed decisions about their future were the two principal advantages mentioned for obtaining their amyloid PET results. Because of the overwhelming consensus of aMCI patients was to disclose their brain amyloid PET scan results, researchers should strongly consider releasing this information to research subjects.

Purpose: Preclinical, or asymptomatic, Alzheimer's disease (AD) refers to the presence of positive AD biomarkers in the absence of cognitive deficits. This research concept is being applied to define target populations for clinical drug development. In a prospective communityrecruited cohort of cognitively intact older adults, we compared two amyloid imaging markers within subjects: 18 F-flutemetamol and 11 C-Pittsburgh compound B ( 11 C-PIB). Methods:In 32 community-recruited cognitively intact older adults aged between 65 and 80 years, we determined the concordance between binary classification based on 18 Fflutemetamol versus 11 C-PIB according to semiquantitative assessment (standardized uptake value ratio in composite cortical volume, SUVRcomp) and, alternatively, according to visual reads.We also determined the correlation between 18 F-flutemetamol and 11 C-PIB SUVR and evaluated Correlations in neocortical regions were significantly lower with pons as reference region. PVC improved the correlation in striatum and medial temporal cortex.

Alzheimer’s disease (AD) is the most prevalent neurodegenerative disorder and the most common form of dementia in the elderly. Susceptibility to AD is considerably determined by genetic factors which hitherto were primarily identified using case–control designs. Elucidating the genetic architecture of additional AD-related phenotypic traits, ideally those linked to the underlying disease process, holds great promise in gaining deeper insights into the genetic basis of AD and in developing better clinical prediction models. To this end, we generated genome-wide single-nucleotide polymorphism (SNP) genotyping data in 931 participants of the European Medical Information Framework Alzheimer’s Disease Multimodal Biomarker Discovery (EMIF-AD MBD) sample to search for novel genetic determinants of AD biomarker variability. Specifically, we performed genome-wide association study (GWAS) analyses on 16 traits, including 14 measures derived from quantifications of five separate amyloid-beta (Aβ) and tau-protein species in the cerebrospinal fluid (CSF). In addition to confirming the well-established effects of apolipoprotein E (APOE) on diagnostic outcome and phenotypes related to Aβ42, we detected novel potential signals in the zinc finger homeobox 3 (ZFHX3) for CSF-Aβ38 and CSF-Aβ40 levels, and confirmed the previously described sex-specific association between SNPs in geminin coiled-coil domain containing (GMNC) and CSF-tau. Utilizing the results from independent case–control AD GWAS to construct polygenic risk scores (PRS) revealed that AD risk variants only explain a small fraction of CSF biomarker variability. In conclusion, our study represents a detailed first account of GWAS analyses on CSF-Aβ and -tau-related traits in the EMIF-AD MBD dataset. In subsequent work, we will utilize the genomics data generated here in GWAS of other AD-relevant clinical outcomes ascertained in this unique dataset.