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

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

The Early Perfusion Image Is Useful to Support the Visual Interpretation of Brain Amyloid-PET With 18F-Flutemetamol in Borderline Cases.

PURPOSE: Visual interpretation of brain amyloid-ß (Aß) PET can be difficult in individuals with borderline Aß burden. Coregistration with individual MRI is recommended in these cases, which, however, is not always available. This study evaluated coregistration with the early perfusion frames acquired immediately after tracer injection to support the visual interpretation of the late Aß-frames in PET with 18F-flutemetamol (FMM). PATIENTS AND METHODS: Fifty dual-time-window FMM-PET scans of cognitively normal subjects with 0 to 60 Centiloids were included retrospectively (70.1 ± 6.9 years, 56% female, MMSE score 28.9 ± 1.3, 42% APOE ɛ4 carrier). Regional Aß load was scored with respect to a 6-point Likert scale by 3 independent raters in the 10 regions of interest recommended for FMM reading using 3 different settings: Aß image only, Aß image coregistered with MRI, and Aß image coregistered with the perfusion image. The impact of setting, within- and between-readers variability, region of interest, and Aß-status was tested by repeated-measure analysis of variance of the Likert score. RESULTS: The Centiloid scale ranged between 2 and 52 (interquartile range, 7-19). Support of visual scoring by the perfusion image resulted in the best discrimination between Aß-positive and Aß-negative cases, mainly by improved certainty of excluding Aß plaques in Aß-negative cases (P = 0.030). It also resulted in significantly higher between-rater agreement. The setting effect was most pronounced in the frontal lobe and in the posterior cingulate cortex/precuneus area (P = 0.005). CONCLUSIONS: The early perfusion image is a suitable alternative to T1-weighted MRI to support the visual interpretation of the late Aß image in FMM-PET.

Digital remote assessment of speech acoustics in cognitively unimpaired adults: feasibility, reliability and associations with amyloid pathology.

BACKGROUND: Digital speech assessment has potential relevance in the earliest, preclinical stages of Alzheimer's disease (AD). We evaluated the feasibility, test-retest reliability, and association with AD-related amyloid-beta (Aß) pathology of speech acoustics measured over multiple assessments in a remote setting. METHODS: Fifty cognitively unimpaired adults (Age 68 ± 6.2 years, 58% female, 46% Aß-positive) completed remote, tablet-based speech assessments (i.e., picture description, journal-prompt storytelling, verbal fluency tasks) for five days. The testing paradigm was repeated after 2-3 weeks. Acoustic speech features were automatically extracted from the voice recordings, and mean scores were calculated over the 5-day period. We assessed feasibility by adherence rates and usability ratings on the System Usability Scale (SUS) questionnaire. Test-retest reliability was examined with intraclass correlation coefficients (ICCs). We investigated the associations between acoustic features and Aß-pathology, using linear regression models, adjusted for age, sex and education. RESULTS: The speech assessment was feasible, indicated by 91.6% adherence and usability scores of 86.0 ± 9.9. High reliability (ICC ≥ 0.75) was found across averaged speech samples. Aß-positive individuals displayed a higher pause-to-word ratio in picture description (B = -0.05, p = 0.040) and journal-prompt storytelling (B = -0.07, p = 0.032) than Aß-negative individuals, although this effect lost significance after correction for multiple testing. CONCLUSION: Our findings support the feasibility and reliability of multi-day remote assessment of speech acoustics in cognitively unimpaired individuals with and without Aß-pathology, which lays the foundation for the use of speech biomarkers in the context of early AD.

Amyloid PET disclosure in subjective cognitive decline: Patient experiences over time.

INTRODUCTION: We disclosed amyloid positron emission tomography (PET) results in individuals with subjective cognitive decline (SCD) and studied patient experiences and outcomes over a 6-month period. METHODS: Fifty-seven participants from the Subjective Cognitive Impairment Cohort (SCIENCe) (66 ± 8 years, 21 [37%] F, Mini-Mental State Examination 29 ± 1, 15 [26%] amyloid positive [A+]) completed questionnaires 1 week prior (T0), 1 day after (T1), and 6 months after amyloid PET disclosure (T2). Questionnaires addressed patient-reported experiences and outcomes. RESULTS: Independent of amyloid status, participants were satisfied with the consultation (scale 1-10; 7.9 ± 1.7) and information provided (scale 1-4; T1: 3.3 ± 0.9, T2: 3.2 ± 0.8). After 6 months, A+ participants reported more information needs (45% vs. 12%, p = 0.02). Independent of amyloid status, decision regret (scale 1-5; A+: 1.5 ± 0.9, A-: 1.4 ± 0.6, p = 0.53) and negative emotions (negative affect, uncertainty, anxiety) were low (all p > 0.15 and Pinteraction > 0.60). DISCUSSION: Participants with SCD valued amyloid PET disclosure positively, regardless of amyloid status. The need for information after 6 months, which was stronger in A+ individuals, underscores the importance of follow-up. HIGHLIGHTS: Participants with subjective cognitive decline (SCD) positively valued amyloid positron emission tomography (PET) disclosure. Participants with SCD experienced low levels of decision regret. We did not observe an increase in negative emotions. After 6 months, amyloid-positive individuals wanted more information.

Rationale and design of the BeyeOMARKER study: prospective evaluation of blood- and eye-based biomarkers for early detection of Alzheimer's disease pathology in the eye clinic.

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

Prediction of future cognitive decline among cognitively unimpaired individuals using measures of soluble phosphorylated tau or tau tangle pathology.

Plasma p-tau217 and Tau-PET are strong prognostic biomarkers in Alzheimer's disease (AD), but their relative performance in predicting future cognitive decline among cognitively unimpaired (CU) individuals is unclear. In this head-to-head comparison study including 9 cohorts and 1534 individuals, we found that plasma p-tau217 and medial temporal lobe Tau-PET signal showed similar associations with cognitive decline on a global cognitive composite test (R2 PET=0.32 vs R2 PLASMA=0.32, pdifference=0.812) and with progression to mild cognitive impairment (Hazard ratio[HR]PET=1.56[1.43-1.70] vs HRPLASMA=1.63[1.50-1.77], pdifference=0.627). Combined plasma and PET models were superior to the single biomarker models (R2=0.36, p<0.01). Furthermore, sequential selection using plasma p-tau217 and then Tau-PET reduced the number of participants required for a clinical trial by 94%, compared to a 75% reduction when using plasma p-tau217 alone. We conclude that plasma p-tau217 and Tau-PET showed similar performance for predicting future cognitive decline in CU individuals, and their sequential use (i.e., plasma p-tau217 followed by Tau-PET in a subset with high plasma p-tau217) is useful for screening in clinical trials in preclinical AD.

Predicting Cognitive Decline in Amyloid-Positive Patients With Mild Cognitive Impairment or Mild Dementia.

BACKGROUND AND OBJECTIVES: Cognitive decline rates in Alzheimer disease (AD) vary greatly. Disease-modifying treatments may alter cognitive decline trajectories, rendering their prediction increasingly relevant. We aimed to construct clinically applicable prediction models of cognitive decline in amyloid-positive patients with mild cognitive impairment (MCI) or mild dementia. METHODS: From the Amsterdam Dementia Cohort, we selected amyloid-positive participants with MCI or mild dementia and at least 2 longitudinal Mini-Mental State Examination (MMSE) measurements. Amyloid positivity was based on CSF AD biomarker concentrations or amyloid PET. We used linear mixed modeling to predict MMSE over time, describing trajectories using a cubic time curve and interactions between linear time and the baseline predictors age, sex, baseline MMSE, APOE ε4 dose, CSF ß-amyloid (Aß) 1-42 and pTau, and MRI total brain and hippocampal volume. Backward selection was used to reduce model complexity. These models can predict MMSE over follow-up or the time to an MMSE value. MCI and mild dementia were modeled separately. Internal 5-fold cross-validation was performed to calculate the explained variance (R2). RESULTS: In total, 961 participants were included (age 65 ± 7 years, 49% female), 310 had MCI (MMSE 26 ± 2) and 651 had mild dementia (MMSE 22 ± 4), with 4 ± 2 measurements over 2 (interquartile range 1-4) years. Cognitive decline rates increased over time for both MCI and mild dementia (model comparisons linear vs squared vs cubic time fit; p < 0.05 favoring a cubic fit). For MCI, backward selection retained age, sex, and CSF Aß1-42 and pTau concentrations as time-varying effects altering the MMSE trajectory. For mild dementia, retained time-varying effects were Aß1-42, age, APOE ε4, and baseline MMSE. R2 was 0.15 for the MCI model and 0.26 for mild dementia in internal cross-validation. A hypothetical patient with MCI, baseline MMSE 28, and CSF Aß1-42 of 925 pg/mL was predicted to reach an MMSE of 20 after 6.0 years (95% CI 5.4-6.7) and after 8.6 years with a hypothetical treatment reducing decline by 30%. DISCUSSION: We constructed models for MCI and mild dementia that predict MMSE over time. These models could inform patients about their potential cognitive trajectory and the remaining uncertainty and aid in conversations about individualized potential treatment effects.

The association of tobacco smoking and metabolite levels in the anterior cingulate cortex of first-episode psychosis patients: A case-control and 6-month follow-up 1H-MRS study.

Tobacco smoking is highly prevalent among patients with psychosis and associated with worse clinical outcomes. Neurometabolites, such as glutamate and choline, are both implicated in psychosis and tobacco smoking. However, the specific associations between smoking and neurometabolites have yet to be investigated in patients with psychosis. The current study examines associations of chronic smoking and neurometabolite levels in the anterior cingulate cortex (ACC) in first-episode psychosis (FEP) patients and controls. Proton magnetic resonance spectroscopy (1H MRS) data of 59 FEP patients and 35 controls were analysed. Associations between smoking status (i.e., smoker yes/no) or cigarettes per day and Glx (glutamate + glutamine, as proxy for glutamate) and total choline (tCh) levels were assessed at baseline in both groups separately. For patients, six months follow-up data were acquired for multi-cross-sectional analysis using linear mixed models. No significant differences in ACC Glx levels were found between smoking (n = 28) and non-smoking (n = 31) FEP patients. Smoking patients showed lower tCh levels compared to non-smoking patients at baseline, although not surving multiple comparisons correction, and in multi-cross-sectional analysis (pFDR = 0.08 and pFDR = 0.044, respectively). Negative associations were observed between cigarettes smoked per day, and ACC Glx (pFDR = 0.02) and tCh levels (pFDR = 0.02) in controls. Differences between patients and controls regarding Glx might be explained by pre-existing disease-related glutamate deficits or alterations at nicotine acetylcholine receptor level, resulting in differences in tobacco-related associations with neurometabolites. Additionally, observed alterations in tCh levels, suggesting reduced cellular proliferation processes, might result from exposure to the neurotoxic effects of smoking.

Computerized decision support is an effective approach to select memory clinic patients for amyloid-PET.

BACKGROUND: The use of amyloid-PET in dementia workup is upcoming. At the same time, amyloid-PET is costly and limitedly available. While the appropriate use criteria (AUC) aim for optimal use of amyloid-PET, their limited sensitivity hinders the translation to clinical practice. Therefore, there is a need for tools that guide selection of patients for whom amyloid-PET has the most clinical utility. We aimed to develop a computerized decision support approach to select patients for amyloid-PET. METHODS: We included 286 subjects (135 controls, 108 Alzheimer's disease dementia, 33 frontotemporal lobe dementia, and 10 vascular dementia) from the Amsterdam Dementia Cohort, with available neuropsychology, APOE, MRI and [18F]florbetaben amyloid-PET. In our computerized decision support approach, using supervised machine learning based on the DSI classifier, we first classified the subjects using only neuropsychology, APOE, and quantified MRI. Then, for subjects with uncertain classification (probability of correct class (PCC) < 0.75) we enriched classification by adding (hypothetical) amyloid positive (AD-like) and negative (normal) PET visual read results and assessed whether the diagnosis became more certain in at least one scenario (PPC≥0.75). If this was the case, the actual visual read result was used in the final classification. We compared the proportion of PET scans and patients diagnosed with sufficient certainty in the computerized approach with three scenarios: 1) without amyloid-PET, 2) amyloid-PET according to the AUC, and 3) amyloid-PET for all patients. RESULTS: The computerized approach advised PET in n = 60(21%) patients, leading to a diagnosis with sufficient certainty in n = 188(66%) patients. This approach was more efficient than the other three scenarios: 1) without amyloid-PET, diagnostic classification was obtained in n = 155(54%), 2) applying the AUC resulted in amyloid-PET in n = 113(40%) and diagnostic classification in n = 156(55%), and 3) performing amyloid-PET in all resulted in diagnostic classification in n = 154(54%). CONCLUSION: Our computerized data-driven approach selected 21% of memory clinic patients for amyloid-PET, without compromising diagnostic performance. Our work contributes to a cost-effective implementation and could support clinicians in making a balanced decision in ordering additional amyloid PET during the dementia workup.

Developing blood-brain barrier arterial spin labelling as a non-invasive early biomarker of Alzheimer's disease (DEBBIE-AD): a prospective observational multicohort study protocol.

INTRODUCTION: Loss of blood-brain barrier (BBB) integrity is hypothesised to be one of the earliest microvascular signs of Alzheimer's disease (AD). Existing BBB integrity imaging methods involve contrast agents or ionising radiation, and pose limitations in terms of cost and logistics. Arterial spin labelling (ASL) perfusion MRI has been recently adapted to map the BBB permeability non-invasively. The DEveloping BBB-ASL as a non-Invasive Early biomarker (DEBBIE) consortium aims to develop this modified ASL-MRI technique for patient-specific and robust BBB permeability assessments. This article outlines the study design of the DEBBIE cohorts focused on investigating the potential of BBB-ASL as an early biomarker for AD (DEBBIE-AD). METHODS AND ANALYSIS: DEBBIE-AD consists of a multicohort study enrolling participants with subjective cognitive decline, mild cognitive impairment and AD, as well as age-matched healthy controls, from 13 cohorts. The precision and accuracy of BBB-ASL will be evaluated in healthy participants. The clinical value of BBB-ASL will be evaluated by comparing results with both established and novel AD biomarkers. The DEBBIE-AD study aims to provide evidence of the ability of BBB-ASL to measure BBB permeability and demonstrate its utility in AD and AD-related pathologies. ETHICS AND DISSEMINATION: Ethics approval was obtained for 10 cohorts, and is pending for 3 cohorts. The results of the main trial and each of the secondary endpoints will be submitted for publication in a peer-reviewed journal.

Validation of image-derived input function using a long axial field of view PET/CT scanner for two different tracers.

BACKGROUND: Accurate image-derived input function (IDIF) from highly sensitive large axial field of view (LAFOV) PET/CT scanners could avoid the need of invasive blood sampling for kinetic modelling. The aim is to validate the use of IDIF for two kinds of tracers, 3 different IDIF locations and 9 different reconstruction settings. METHODS: Eight [18F]FDG and 10 [18F]DPA-714 scans were acquired respectively during 70 and 60 min on the Vision Quadra PET/CT system. PET images were reconstructed using various reconstruction settings. IDIFs were taken from ascending aorta (AA), descending aorta (DA), and left ventricular cavity (LV). The calibration factor (CF) extracted from the comparison between the IDIFs and the manual blood samples as reference was used for IDIFs accuracy and precision assessment. To illustrate the effect of various calibrated-IDIFs on Patlak linearization for [18F]FDG and Logan linearization for [18F]DPA-714, the same target time-activity curves were applied for each calibrated-IDIF. RESULTS: For [18F]FDG, the accuracy and precision of the IDIFs were high (mean CF ≥ 0.82, SD ≤ 0.06). Compared to the striatum influx (Ki) extracted using calibrated AA IDIF with the updated European Association of Nuclear Medicine Research Ltd. standard reconstruction (EARL2), Ki mean differences were < 2% using the other calibrated IDIFs. For [18F]DPA714, high accuracy of the IDIFs was observed (mean CF ≥ 0.86) except using absolute scatter correction, DA and LV (respectively mean CF = 0.68, 0.47 and 0.44). However, the precision of the AA IDIFs was low (SD ≥ 0.10). Compared to the distribution volume (VT) in a frontal region obtained using calibrated continuous arterial sampler input function as reference, VT mean differences were small using calibrated AA IDIFs (for example VT mean difference = -5.3% using EARL2), but higher using calibrated DA and LV IDIFs (respectively + 12.5% and + 19.1%). CONCLUSIONS: For [18F]FDG, IDIF do not need calibration against manual blood samples. For [18F]DPA-714, AA IDIF can replace continuous arterial sampling for simplified kinetic quantification but only with calibration against arterial blood samples. The accuracy and precision of IDIF from LAFOV PET/CT system depend on tracer, reconstruction settings and IDIF VOI locations, warranting careful optimization.

Neuromelanin-Sensitive MRI as Candidate Marker for Treatment Resistance in First-Episode Schizophrenia.

OBJECTIVE: Markers for treatment resistance in schizophrenia are needed to reduce delays in effective treatment. Nigrostriatal hyperdopaminergic function plays a critical role in the pathology of schizophrenia, yet antipsychotic nonresponders do not show increased dopamine function. Neuromelanin-sensitive MRI (NM-MRI), which indirectly measures dopamine function in the substantia nigra, has potential as a noninvasive marker for nonresponders. Increased NM-MRI signal has been shown in psychosis, but has not yet been assessed in nonresponders. In this study, the authors investigated whether nonresponders show lower NM-MRI signal than responders. METHODS: NM-MRI scans were acquired in 79 patients with first-episode psychosis and 20 matched healthy control subjects. Treatment response was assessed at a 6-month follow-up. An a priori voxel-wise analysis within the substantia nigra tested the relation between NM-MRI signal and treatment response in patients. RESULTS: Fifteen patients were classified as nonresponders and 47 patients as responders. Seventeen patients were excluded, primarily because of medication nonadherence or change in diagnosis. Voxel-wise analysis revealed 297 significant voxels in the ventral tier of the substantia nigra that were negatively associated with treatment response. Nonresponders and healthy control subjects had significantly lower NM-MRI signal than responders. Receiver operating characteristic curve analysis showed that NM-MRI signal separated nonresponders with areas under the curve between 0.62 and 0.85. In addition, NM-MRI signal in patients did not change over 6 months. CONCLUSIONS: These findings provide further evidence for dopaminergic differences between medication responders and nonresponders and support the potential of NM-MRI as a clinically applicable marker for treatment resistance in schizophrenia.

Endocannabinoid levels in plasma and neurotransmitters in the brain: a preliminary report on patients with a psychotic disorder and healthy individuals.

BACKGROUND: Interactions between the endocannabinoid system (ECS) and neurotransmitter systems might mediate the risk of developing a schizophrenia spectrum disorder (SSD). Consequently, we investigated in patients with SSD and healthy controls (HC) the relations between (1) plasma concentrations of two prototypical endocannabinoids (N-arachidonoylethanolamine [anandamide] and 2-arachidonoylglycerol [2-AG]) and (2) striatal dopamine synthesis capacity (DSC), and glutamate and y-aminobutyric acid (GABA) levels in the anterior cingulate cortex (ACC). As anandamide and 2-AG might reduce the activity of these neurotransmitters, we hypothesized negative correlations between their plasma levels and the abovementioned neurotransmitters in both groups. METHODS: Blood samples were obtained from 18 patients and 16 HC to measure anandamide and 2-AG plasma concentrations. For all subjects, we acquired proton magnetic resonance spectroscopy scans to assess Glx (i.e. glutamate plus glutamine) and GABA + (i.e. GABA plus macromolecules) concentrations in the ACC. Ten patients and 14 HC also underwent [18F]F-DOPA positron emission tomography for assessment of striatal DSC. Multiple linear regression analyses were used to investigate the relations between the outcome measures. RESULTS: A negative association between 2-AG plasma concentration and ACC Glx concentration was found in patients (p = 0.008). We found no evidence of other significant relationships between 2-AG or anandamide plasma concentrations and dopaminergic, glutamatergic, or GABAergic measures in either group. CONCLUSIONS: Our preliminary results suggest an association between peripheral 2-AG and ACC Glx levels in patients.

Visual associative learning to detect early episodic memory deficits and distinguish Alzheimer's disease from other types of dementia.

OBJECTIVE: We investigated how well a visual associative learning task discriminates Alzheimer's disease (AD) dementia from other types of dementia and how it relates to AD pathology. METHODS: 3,599 patients (63.9 ± 8.9 years old, 41% female) from the Amsterdam Dementia Cohort completed two sets of the Visual Association Test (VAT) in a single test session and underwent magnetic resonance imaging. We performed receiver operating curve analysis to investigate the VAT's discriminatory ability between AD dementia and other diagnoses and compared it to that of other episodic memory tests. We tested associations between VAT performance and medial temporal lobe atrophy (MTA), and amyloid status (n = 2,769, 77%). RESULTS: Patients with AD dementia performed worse on the VAT than all other patients. The VAT discriminated well between AD and other types of dementia (area under the curve range 0.70-0.86), better than other episodic memory tests. Six-hundred forty patients (17.8%) learned all associations on VAT-A, but not on VAT-B, and they were more likely to have higher MTA scores (odds ratios range 1.63 (MTA 0.5) through 5.13 for MTA ≥ 3, all p < .001) and to be amyloid positive (odds ratio = 3.38, 95%CI = [2.71, 4.22], p < .001) than patients who learned all associations on both sets. CONCLUSIONS: Performance on the VAT, especially on a second set administered immediately after the first, discriminates AD from other types of dementia and is associated with MTA and amyloid positivity. The VAT might be a useful, simple tool to assess early episodic memory deficits in the presence of AD pathology.

Cognitive and Functional Change Over Time in Cognitively Healthy Individuals According to Alzheimer Disease Biomarker-Defined Subgroups.

BACKGROUND AND OBJECTIVES: It is unclear to what extent cognitive outcome measures are sensitive to capture decline in Alzheimer disease (AD) prevention trials. We aimed to analyze the sensitivity to changes over time of a range of neuropsychological tests in several cognitively unimpaired, biomarker-defined patient groups. METHODS: Cognitively unimpaired individuals from the Amsterdam Dementia Cohort and the SCIENCe project with available AD biomarkers, obtained from CSF, PET scans, and plasma at baseline, were followed over time (4.5 ± 3.1 years, range 0.6-18.9 years). Based on common inclusion criteria for clinical trials, we defined groups (amyloid, phosphorylated tau [p-tau], APOE ε4). Linear mixed models, adjusted for age, sex, and education, were used to estimate change over time in neuropsychological tests, a functional outcome, and 2 cognitive composite measures. Standardized regression coefficients of time in years (ßtime) were reported as outcome of interest. We analyzed change over time with full follow-up, as well as with follow-up limited to 1.5 and 3 years. RESULTS: We included 387 individuals (aged 61.7 ± 8.6 years; 44% female) in the following (partly overlapping) biomarker groups: APOE ε4 carriers (n = 212), amyloid-positive individuals (n = 109), amyloid-positive APOE ε4 carriers (n = 66), CSF p-tau-positive individuals (n = 127), plasma p-tau-positive individuals (n = 71), and amyloid and CSF p-tau-positive individuals (n = 50), or in a control group (normal biomarkers; n = 65). An executive functioning task showed most decline in all biomarker groups (ßtime range -0.30 to -0.71), followed by delayed word list recognition (ßtime range -0.18 to -0.50). Functional decline (ßtime range -0.17 to -0.63) was observed in all, except the CSF and plasma tau-positive groups. Both composites showed comparable amounts of change (ßtime range -0.12 to -0.62) in all groups, except plasma p-tau-positive individuals. When limiting original follow-up duration, many effects disappeared or even flipped direction. DISCUSSION: In conclusion, functional, composite, and neuropsychological outcome measures across all cognitive domains detect changes over time in various biomarker-defined groups, with changes being most evident among individuals with more AD pathology. AD prevention trials should use sufficiently long follow-up duration and/or more sensitive outcome measures to optimally capture subtle cognitive changes over time.

Glutamate and GABA levels in the anterior cingulate cortex in treatment resistant first episode psychosis patients.

BACKGROUND: Around 30 % of schizophrenia patients do not respond sufficiently to conventional antipsychotic treatment. Glutamate and γ-aminobutyric acid (GABA) may be implicated in treatment resistant (TR) patients. Some data indicate that TR patients show increased glutamate levels compared to responders, but findings are inconclusive and limited in the early disease stage. Furthermore, the two neurotransmitters have rarely been assessed in conjunction. We therefore aimed to investigate the role of GABA+ and glutamate in first episode TR patients and explore whether these neurometabolites could be potential predictive markers for TR schizophrenia. STUDY DESIGN: We used proton magnetic resonance spectroscopy (MRS) to assess glutamate + glutamine (Glx) and GABA including macromolecules (GABA+) in the anterior cingulate cortex (ACC) of 58 first episode psychosis patients. At six months follow-up treatment response was determined and in a subgroup of 33 patients a follow-up MRS scan was acquired. STUDY RESULTS: Glx and GABA+ levels were not significantly different between TR patients and responders at baseline and the levels did not change at six months follow-up. The groups differed in voxel fractions, which could have influenced our results even though we corrected for these differences. CONCLUSIONS: Our findings do not provide evidence that ACC Glx or GABA+ levels are potential biomarkers for TR in first episode psychosis. Future research needs to take in to account voxel fractions and report potential differences. Comparison with previous literature suggests that illness duration, clozapine responsiveness and medication effects may partly explain the heterogeneous results on Glx and GABA+ levels in TR.

Contributions of amyloid beta and cerebral small vessel disease in clinical decline.

INTRODUCTION: We assessed whether co-morbid small vessel disease (SVD) has clinical predictive value in preclinical or prodromal Alzheimer's disease. METHODS: In 1090 non-demented participants (65.4 ± 10.7 years) SVD was assessed with magnetic resonance imaging and amyloid beta (Aß) with lumbar puncture and/or positron emission tomography scan (mean follow-up for cognitive function 3.1 ± 2.4 years). RESULTS: Thirty-nine percent had neither Aß nor SVD (A-V-), 21% had SVD only (A-V+), 23% Aß only (A+V-), and 17% had both (A+V+). Pooled cohort linear mixed model analyses demonstrated that compared to A-V- (reference), A+V- had a faster rate of cognitive decline. Co-morbid SVD (A+V+) did not further increase rate of decline. Cox regression showed that dementia risk was modestly increased in A-V+ (hazard ratio [95% confidence interval: 1.8 [1.0-3.2]) and most strongly in A+ groups. Also, mortality risk was increased in A+ groups. DISCUSSION: In non-demented persons Aß was predictive of cognitive decline, dementia, and mortality. SVD modestly predicts dementia in A-, but did not increase deleterious effects in A+. HIGHLIGHTS: Amyloid beta (Aß; A) was predictive for cognitive decline, dementia, and mortality. Small vessel disease (SVD) had no additional deleterious effects in A+. SVD modestly predicted dementia in A-. Aß should be assessed even when magnetic resonance imaging indicates vascular cognitive impairment.

Clinical outcomes up to 9 years after [18F]flutemetamol amyloid-PET in a symptomatic memory clinic population.

BACKGROUND: Previous studies demonstrated increases in diagnostic confidence and change in patient management after amyloid-PET. However, studies investigating longitudinal outcomes over an extended period of time are limited. Therefore, we aimed to investigate clinical outcomes up to 9 years after amyloid-PET to support the clinical validity of the imaging technique. METHODS: We analyzed longitudinal data from 200 patients (Mage = 61.8, 45.5% female, MMMSE = 23.3) suspected of early-onset dementia that underwent [18F]flutemetamol-PET. Baseline amyloid status was determined through visual read (VR). Information on mortality was available with a mean follow-up of 6.7 years (range = 1.1-9.3). In a subset of 108 patients, longitudinal cognitive scores and clinical etiological diagnosis (eDx) at least 1 year after amyloid-PET acquisition were available (M = 3.06 years, range = 1.00-7.02). VR - and VR + patients were compared on mortality rates with Cox Hazard's model, prevalence of stable eDx using chi-square test, and longitudinal cognition with linear mixed models. Neuropathological data was available for 4 patients (mean delay = 3.59 ± 1.82 years, range = 1.2-6.3). RESULTS: At baseline, 184 (92.0%) patients were considered to have dementia. The majority of VR + patients had a primary etiological diagnosis of AD (122/128, 95.3%), while the VR - group consisted mostly of non-AD etiologies, most commonly frontotemporal lobar degeneration (30/72, 40.2%). Overall mortality rate was 48.5% and did not differ between VR - and VR + patients. eDx at follow-up was consistent with baseline diagnosis for 92/108 (85.2%) patients, with most changes observed in VR - cases (VR - = 14/35, 40% vs VR + = 2/73, 2.7%, χ2 = 26.03, p < 0.001), who at no time received an AD diagnosis. VR + patients declined faster than VR - patients based on MMSE (ß = - 1.17, p = 0.004), episodic memory (ß = - 0.78, p = 0.003), fluency (ß = - 1.44, p < 0.001), and attention scores (ß = 16.76, p = 0.03). Amyloid-PET assessment was in line with post-mortem confirmation in all cases; two cases were VR + and showed widespread AD pathology, while the other two cases were VR - and showed limited amyloid pathology. CONCLUSION: In a symptomatic population, we observed that amyloid-status did not impact mortality rates, but is predictive of cognitive functioning over time across several domains. Also, we show particular validity for a negative amyloid-PET assessment, as these patients did not receive an AD diagnosis at follow-up.

The association between clinical, sociodemographic, familial, and environmental factors and treatment resistance in schizophrenia: A machine-learning-based approach.

BACKGROUND: Prediction of treatment resistance in schizophrenia (TRS) would be helpful to reduce the duration of ineffective treatment and avoid delays in clozapine initiation. We applied machine learning to identify clinical, sociodemographic, familial, and environmental variables that are associated with TRS and could potentially predict TRS in the future. STUDY DESIGN: Baseline and follow-up data on trait(-like) variables from the Genetic Risk and Outcome of Psychosis (GROUP) study were used. For the main analysis, we selected patients with non-affective psychotic disorders who met TRS (n = 200) or antipsychotic-responsive criteria (n = 423) throughout the study. For a sensitivity analysis, we only selected patients who met TRS (n = 76) or antipsychotic-responsive criteria (n = 123) at follow-up but not at baseline. Random forest models were trained to predict TRS in both datasets. SHapley Additive exPlanation values were used to examine the variables' contributions to the prediction. STUDY RESULTS: Premorbid functioning, age at onset, and educational degree were most consistently associated with TRS across both analyses. Marital status, current household, intelligence quotient, number of moves, and family loading score for substance abuse also consistently contributed to the prediction of TRS in the main or sensitivity analysis. The diagnostic performance of our models was modest (area under the curve: 0.66-0.69). CONCLUSIONS: We demonstrate that various clinical, sociodemographic, familial, and environmental variables are associated with TRS. Our models only showed modest performance in predicting TRS. Prospective large multi-centre studies are needed to validate our findings and investigate whether the model's performance can be improved by adding data from different modalities.

Performance of a [18F]Flortaucipir PET Visual Read Method Across the Alzheimer Disease Continuum and in Dementia With Lewy Bodies.

BACKGROUND AND OBJECTIVES: Recently, the US Food and Drug Administration approved the tau-binding radiotracer [18F]flortaucipir and an accompanying visual read method to support the diagnostic process in cognitively impaired patients assessed for Alzheimer disease (AD). Studies evaluating this visual read method are limited. In this study, we evaluated the performance of the visual read method in participants along the AD continuum and dementia with Lewy bodies (DLB) by determining its reliability, accordance with semiquantitative analyses, and associations with clinically relevant variables. METHODS: We included participants who underwent tau-PET at Amsterdam University Medical Center. A subset underwent follow-up tau-PET. Two trained nuclear medicine physicians visually assessed all scans. Inter-reader agreement was calculated using Cohen κ. To examine the concordance of visual read tau positivity with semiquantification, we defined standardized uptake value ratio (SUVr) positivity using different threshold approaches. To evaluate the prognostic value of tau-PET visual read, we performed linear mixed models with longitudinal Mini-Mental State Examination (MMSE). RESULTS: We included 263 participants (mean age 68.5 years, 45.6% female), including 147 cognitively unimpaired (CU) participants, 97 amyloid-positive participants with mild cognitive impairment or AD dementia (AD), and 19 participants with DLB. The visual read inter-reader agreement was excellent (κ = 0.95, CI 0.91-0.99). None of the amyloid-negative CU participants (0/92 [0%]) and 1 amyloid-negative participant with DLB (1/12 [8.3%]) were tau-positive. Among amyloid-positive participants, 13 CU participants (13/52 [25.0%]), 85 with AD (85/97 [87.6%]), and 3 with DLB (3/7 [42.9%]) were tau-positive. Two-year follow-up visual read status was identical to baseline. Tau-PET visual read corresponded strongly to SUVr status, with up to 90.4% concordance. Visual read tau positivity was associated with a decline on the MMSE in CU participants (ß = -0.52, CI -0.74 to -0.30, p < 0.001) and participants with AD (ß = -0.30, CI -0.58 to -0.02, p = 0.04). DISCUSSION: The excellent inter-reader agreement, strong correspondence with SUVr, and longitudinal stability indicate that the visual read method is reliable and robust, supporting clinical application. Furthermore, visual read tau positivity was associated with prospective cognitive decline, highlighting its additional prognostic potential. Future studies in unselected cohorts are needed for a better generalizability to the clinical population. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that [18F]flortaucipir visual read accurately distinguishes patients with low tau-tracer binding from those with high tau-tracer binding and is associated with amyloid positivity and cognitive decline.