Amyloid Positron Emission Tomography Research Articles

Deep learning model for individualized trajectory prediction of clinical outcomes in mild cognitive impairment

ObjectivesAccurately predicting when patients with mild cognitive impairment (MCI) will progress to dementia is a formidable challenge. This work aims to develop a predictive deep learning model to accurately predict future cognitive decline and magnetic resonance imaging (MRI) marker changes over time at the individual level for patients with MCI.MethodsWe recruited 657 amnestic patients with MCI from the Samsung Medical Center who underwent cognitive tests, brain MRI scans, and amyloid-β (Aβ) positron emission tomography (PET) scans. We devised a novel deep learning architecture by leveraging an attention mechanism in a recurrent neural network. We trained a predictive model by inputting age, gender, education, apolipoprotein E genotype, neuropsychological test scores, and brain MRI and amyloid PET features. Cognitive outcomes and MRI features of an MCI subject were predicted using the proposed network.ResultsThe proposed predictive model demonstrated good prediction performance (AUC = 0.814 ± 0.035) in five-fold cross-validation, along with reliable prediction in cognitive decline and MRI markers over time. Faster cognitive decline and brain atrophy in larger regions were forecasted in patients with Aβ (+) than with Aβ (−).ConclusionThe proposed method provides effective and accurate means for predicting the progression of individuals within a specific period. This model could assist clinicians in identifying subjects at a higher risk of rapid cognitive decline by predicting future cognitive decline and MRI marker changes over time for patients with MCI. Future studies should validate and refine the proposed predictive model further to improve clinical decision-making.

Antibody engagement with amyloid-beta does not inhibit [11C]PiB binding for PET imaging.

The elimination of amyloid-beta (Aβ) plaques in Alzheimer's disease patients after treatment with anti-Aβ antibodies such as lecanemab and aducanumab is supported by a substantially decreased signal in amyloid positron emission tomography (PET) imaging. However, this decreased PET signal has not been matched by a similar substantial effect on cognitive function. There may be several reasons for this, including short treatment duration and advanced disease stages among the patients. However, one aspect that has not been investigated, and the subject of this study, is whether antibody engagement with amyloid plaques inhibits the binding of amyloid-PET ligands, leading to a false impression of Aβ removal from the brain. In the present study, tg-ArcSwe mice received three injections of RmAb158, the murine version of lecanemab or phosphate-buffered saline (PBS) before the administration of the amyloid-PET radioligand [11C]PiB, followed by isolation of brain tissue. Autoradiography showed that RmAb158- and PBS-treated mice displayed similar [11C]PiB binding. Moreover, the total Aβ1-40 levels, representing the major Aβ species of plaques in the tg-ArcSwe model, as well as soluble triggering receptor on myeloid cells 2 (sTREM2) levels, were similar in both groups. Interestingly, the concentration of soluble Aβ aggregates was decreased in the RmAb158-treated group, along with a small but significant decrease in the total Aβ1-42 levels. In conclusion, this study indicates that the binding of [11C]PiB to Aβ accurately mirrors the load of Aβ plaques in the brain, aligning with how amyloid-PET is interpreted in clinical studies of anti-Aβ antibodies. However, early treatment effects on soluble Aβ aggregates and Aβ1-42 levels were not detected.

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

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

APOE ε4 is associated with decreased synaptic density in cognitively impaired participants.

We aimed to investigate the effect of apolipoprotein E4 (APOE) ε4 on synaptic density in cognitively impaired (CI) participants. One hundred ten CI participants underwent amyloid positron emission tomography (PET) with 18F-florbetapir and synaptic density PET with 18F-SynVesT-1. We evaluated the influence of APOE ε4allele on synaptic density and investigated the effects of ε4 genotype on the associations of synaptic density with Alzheimer's disease (AD) biomarkers. The mediation effects of AD biomarkers on ε4-associated synaptic density loss were analyzed. Compared with non-carriers, APOE ε4 allele carriers exhibited significant synaptic loss in the medial temporal lobe. Amyloid beta (Aβ) and tau pathology mediated the effects of APOE ε4 on synaptic density to different extents. The associations between synaptic density and tau pathology were regulated by the APOE ε4 genotype. The APOE ε4 allele was associated with decreased synaptic density in CI individuals and may be driven by AD biomarkers.

Association between neuropsychological assessment and amyloid status in a clinical setting.

Large research cohorts show robust associations between neuropsychological tests and Alzheimer's disease (AD) biomarkers, but studies in clinical settings are limited. The increasing availability of AD biomarkers to the practicing clinician makes it important to understand the relationship between comprehensive clinical neuropsychological assessment and biomarker status. This study examined concordance between practicing clinical neuropsychologists' diagnostic impressions and AD biomarker status in patients seen at an outpatient medical center, with a secondary aim of defining the characteristics of discordant cases. Participants (N = 79) seen for clinical neuropsychological assessment who subsequently underwent lumbar puncture or amyloid positron emission tomography imaging were identified via retrospective chart review. Concordance between clinical neuropsychological diagnosis (non-AD, indeterminate, possible/probable AD) and AD biomarker status (negative, indeterminate, positive) was determined. Individual test score data were used to examine between-group differences based on amyloid status. AD biomarker positive and negative patients did not differ on individual neuropsychological tests after correcting for multiple comparisons, though the small number of AD biomarker indeterminate individuals performed better than biomarker positive patients. However, there was 76.7% concordance between neuropsychologists' diagnostic impressions and AD biomarker status (88% sensitivity and 55% specificity of neuropsychological assessment in detecting AD biomarker status). AD biomarker negative patients diagnosed as possible/probable AD (discordant) versus non-AD (concordant) had significantly lower Neuropsychological Assessment Battery Story Delayed Recall, higher Wechsler Adult Intelligence Scale-Fourth Edition Coding, and higher Trail-Making A (i.e., an amnestic memory profile). Comprehensive neuropsychological assessment showed modest concordance with AD biomarker status in patients seen in an outpatient medical center for routine clinical care. Low specificity for the clinical diagnosis of AD could be explained by the multiplicity of etiologies that cause memory impairment (i.e., TAR DNA-binding protein 43, suspected non-AD pathology). (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Linking white matter hyperintensities to regional cortical thinning, amyloid deposition, and synaptic density loss in Alzheimer's disease.

We investigated the association between white matter hyperintensities (WMH) and regional cortical thickness, amyloid and tau deposition, and synaptic density in the WMH-connected cortex using multimodal images. We included 107 participants (59 with Alzheimer's disease [AD]; 27 with mild cognitive impairment; 21 cognitively normal controls) with amyloid beta (Aβ) positivity on amyloid positron emission tomography (PET). The cortex connected to WMH was identified using probabilistic tractography. We found that WMH connected to the cortex with more severe regional degeneration as measured by cortical thickness, Aβ and tau deposition, and synaptic vesicle glycoprotein 2 A (SV2A) density using 18F-SynVesT-1 PET. In addition, higher ratios of Aβ in the deep WMH-connected versus WMH-unconnected cortex were significantly related to lower cognitive scores. Last, the cortical thickness of WMH-connected cortex reduced more than WMH-unconnected cortex over 12 months. Our results suggest that WMH may be associated with AD-intrinsic processes of degeneration, in addition to vascular mechanisms. We studied white matter hyperintensities (WMHs) and WMH-connected cortical changes. WMHs are associated with more severe regional cortical degeneration. Findings suggest WMHs may be associated with Alzheimer's disease-intrinsic processes of degeneration.

Combining Blood-Based Biomarkers and Structural MRI Measurements to Distinguish Persons with and without Significant Amyloid Plaques.

Amyloid-β (Aβ) plaques play a pivotal role in Alzheimer's disease. The current positron emission tomography (PET) is expensive and limited in availability. In contrast, blood-based biomarkers (BBBMs) show potential for characterizing Aβ plaques more affordably. We have previously proposed an MRI-based hippocampal morphometry measure to be an indicator of Aβ plaques. To develop and validate an integrated model to predict brain amyloid PET positivity combining MRI feature and plasma Aβ42/40 ratio. We extracted hippocampal multivariate morphometry statistics from MR images and together with plasma Aβ42/40 trained a random forest classifier to perform a binary classification of participant brain amyloid PET positivity. We evaluated the model performance using two distinct cohorts, one from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the other from the Banner Alzheimer's Institute (BAI), including prediction accuracy, precision, recall rate, F1 score, and AUC score. Results from ADNI (mean age 72.6, Aβ+ rate 49.5%) and BAI (mean age 66.2, Aβ+ rate 36.9%) datasets revealed the integrated multimodal (IMM) model's superior performance over unimodal models. The IMM model achieved prediction accuracies of 0.86 in ADNI and 0.92 in BAI, surpassing unimodal models based solely on structural MRI (0.81 and 0.87) or plasma Aβ42/40 (0.73 and 0.81) predictors. Our IMM model, combining MRI and BBBM data, offers a highly accurate approach to predict brain amyloid PET positivity. This innovative multiplex biomarker strategy presents an accessible and cost-effective avenue for advancing Alzheimer's disease diagnostics, leveraging diverse pathologic features related to Aβ plaques and structural MRI.

Diagnostic value of isolated plasma biomarkers and its combination in neurodegenerative dementias: A multicenter cohort study

BackgroundPlasma amyloid-β (Aβ), phosphorylated tau-181 (p-tau181), neurofilament light (NfL) and glial fibrillary acidic protein (GFAP) potentially aid in the diagnosis of neurodegenerative dementias. We aim to conduct a comprehensive comparison between different biomarkers and their combination, which is lacking, in a multicenter Chinese dementia cohort consisting of Alzheimer’s disease (AD), frontotemporal dementia (FTD), and progressive supranuclear palsy (PSP). MethodsWe enrolled 92 demented patients [64 AD, 16 FTD, and 12 PSP with dementia] and 20 healthy controls (HC). Their plasma Αβ, p-tau181, NfL, and GFAP were detected by highly sensitive-single molecule immunoassays. Αβ pathology in patients was measured by cerebrospinal fluid or/and amyloid positron emission tomography. ResultsAll plasma biomarkers tested were significantly altered in dementia patients compared with HC, especially Aβ42/Aβ40 and NfL showed significant performance in distinguishing AD from HC. A combination of plasma Aβ42/Aβ40, p-tau181, NfL, and GFAP could discriminate FTD or PSP well from HC and was able to distinguish AD and non-AD (FTD/PSP). ConclusionsOur results confirmed the diagnostic performance of individual plasma biomarkers Aβ42/Aβ40, p-tau181, NfL, and GFAP in Chinese dementia patients and noted that a combination of these biomarkers may be more accurate in identifying FTD/PSP patients and distinguishing AD from non-AD dementia.

Where Should I Draw the Line: PET-Driven, Data-Driven, or Manufacturer Cut-Off?

The optimal cut-off for Alzheimer's disease (AD) CSF biomarkers remains controversial. To analyze the performance of cut-off points standardized by three methods: one that optimized the agreement between 11C-Pittsburgh compound B PET (a-PET) and CSF biomarkers (Aβ1-42, pTau, tTau, and Aβ1-42/Aβ1-40 ratio) in our population, called PET-driven; an unbiased cut-off using data from a healthy research cohort, called data-driven, and that provided by the manufacturer. We also compare changes in ATN classification. CSF biomarkers measured by the LUMIPULSE G600II platform and qualitative visualization of amyloid positron emission tomography (a-PET) were performed in all the patients. We established a cut-off for each single biomarker and Aβ1-42/Aβ1-40 ratio that optimized their agreement with a-PET using ROC curves. Sensitivity, Specificity, and Overall Percent of Agreement are assessed using a-PET or clinical diagnosis as gold standard for every cut-off. Also, we established a data-driven cut-off from our cognitively unimpaired cohort. We then analyzed changes in ATN classification. One hundred and ten patients were recruited. Sixty-six (60%) were a-PET positive. PET-driven cut-offs were: pTau > 57, tTau > 362.62, Aβ1-42/Aβ1-40 < 0.069. For a single biomarker, pTau showed the highest accuracy (AUC 0.926). New PET-driven cut-offs classified patients similarly to manufacturer cut-offs (only two patients changed). However, 20 patients (18%) changed when data-driven cut-offs were used. We established our sample's best CSF biomarkers cut-offs using a-PET as the gold standard. These cut-offs categorize better symptomatic subjects than data-driven in ATN classification, but they are very similar to the manufacturer's.

Subsequent correlated changes in complement component 3 and amyloid beta oligomers in the blood of patients with Alzheimer's disease.

Alzheimer's disease (AD) involves the complement cascade, with complement component 3 (C3) playing a key role. However, the relationship between C3 and amyloid beta (Aβ) in blood is limited. Plasma C3 and Aβ oligomerization tendency (AβOt) were measured in 35 AD patients and 62 healthy controls. Correlations with cerebrospinal fluid (CSF) biomarkers, cognitive impairment, and amyloid positron emission tomography (PET) were analyzed. Differences between biomarkers were compared in groups classified by concordances of biomarkers. Plasma C3 and AβOt were elevated in AD patients and in CSF or amyloid PET-positive groups. Weak positive correlation was found between C3 and AβOt, while both had strong negative correlations with CSF Aβ42 and cognitive performance. Abnormalities were observed for AβOt and CSF Aβ42 followed by C3 changes. Increased plasma C3 in AD are associated with amyloid pathology, possibly reflecting a defense response for Aβ clearance. Further studies on Aβ-binding proteins will enhance understanding of Aβ mechanisms in blood.

The AUstralian multidomain Approach to Reduce dementia Risk by prOtecting brain health With lifestyle intervention study (AU-ARROW): A study protocol for a single-blind, multi-site, randomized controlled trial.

The Finnish Geriatric Intervention Study (FINGER) led to the global dementia risk reduction initiative: World-Wide FINGERS (WW-FINGERS). As part of WW-FINGERS, the Australian AU-ARROW study mirrors aspects of FINGER, as well as US-POINTER. AU-ARROW is a randomized, single-blind, multisite, 2-year clinical trial (n = 600; aged 55-79). The multimodal lifestyle intervention group will engage in aerobic exercise, resistance training and stretching, dietary advice to encourage MIND diet adherence, BrainHQ cognitive training, and medical monitoring and health education. The Health Education and Coaching group will receive occasional health education sessions. The primary outcome measure is the change in a global composite cognitive score. Extra value will emanate from blood biomarker analysis, positron emission tomography (PET) imaging, brain magnetic resonance imaging (MRI), and retinal biomarker tests. The finalized AU-ARROW protocol is expected to allow development of an evidence-based innovative treatment plan to reduce cognitive decline and dementia risk, and effective transfer of research outcomes into Australian health policy. Study protocol for a single-blind, randomized controlled trial, the AU-ARROW Study.The AU-ARROW Study is a member of the World-Wide FINGERS (WW-FINGERS) initiative.AU-ARROW's primary outcome measure is change in a global composite cognitive score.Extra significance from amyloid PET imaging, brain MRI, and retinal biomarker tests.Leading to development of an innovative treatment plan to reduce cognitive decline.

Use of a Blood Biomarker Test Improves Economic Utility in the Evaluation of Older Patients Presenting with Cognitive Impairment.

More than 16 million Americans living with cognitive impairment warrant a diagnostic evaluation to determine the cause of this disorder. The recent availability of disease-modifying therapies for Alzheimer's disease (AD) is expected to significantly drive demand for such diagnostic testing. Accurate, accessible, and affordable methods are needed. Blood biomarkers (BBMs) offer advantages over usual care amyloid positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarkers in these regards. This study used a budget impact model to assess the economic utility of the PrecivityAD® blood test, a clinically validated BBM test for the evaluation of brain amyloid, a pathological hallmark of AD. The model compared 2 scenarios: (1) baseline testing involving usual care practice, and (2) early use of a BBM test before usual care CSF and PET biomarker use. At a modest 40% adoption rate, the BBM test scenario had comparable sensitivity and specificity to the usual care scenario and showed net savings in the diagnostic work-up of $3.57 million or $0.30 per member per month in a 1 million member population, translating to over $1B when extrapolated to the US population as a whole and representing a 11.4% cost reduction. Savings were driven by reductions in the frequency and need for CSF and PET testing. Additionally, BBM testing was associated with a cost savings of $643 per AD case identified. Use of the PrecivityAD blood test in the clinical care pathway may prevent unnecessary testing, provide cost savings, and reduce the burden on both patients and health plans.

Alterations in Gut Microbiota and Their Correlation with Brain Beta-Amyloid Burden Measured by 18F-Florbetaben PET in Mild Cognitive Impairment Due to Alzheimer's Disease.

(1) Background: This study investigated changes in the gut microbial composition of individuals with mild cognitive impairment (MCI) due to Alzheimer's disease (AD) and their relationship with positron emission tomography (PET) amyloid accumulation. (2) Methods: In total, 17 cognitively normal individuals without amyloid-beta (Aβ) accumulation (Aβ-NC) and 24 with Aβ-positive mild cognitive impairment (Aβ+MCI) who underwent 18F-florbetaben PET and fecal bacterial 16S ribosomal RNA gene sequencing were enrolled. The taxonomic compositions of the Aβ-NC and Aβ+MCI groups were compared. The abundance of taxa was correlated with the standardized uptake value ratio (SUVR), using generalized linear models. (3) Results: There were significant differences in microbiome richness (ACE, p = 0.034 and Chao1, p = 0.024), alpha diversity (Shannon, p = 0.039), and beta diversity (Bray-Curtis, p = 0.018 and Generalized UniFrac, p = 0.034) between the Aβ-NC and Aβ+MCI groups. The global SUVR was positively correlated with the genus Intestinibacter (q = 0.006) and negatively correlated with the genera Roseburia (q = 0.008) and Agathobaculum (q = 0.029). (4) Conclusions: In this study, we identified significant changes in the gut microbiota composition that occur in individuals with MCI due to AD. In particular, the correlation analysis results between PET amyloid burden and gut microbial abundance showed that amyloid deposition is associated with a reduction in specific taxa involved in butyrate production.

Comparison of consistency in centiloid scale among different analytical methods in amyloid PET: the CapAIBL, VIZCalc, and Amyquant methods.

The Centiloid (CL) scale is a standardized measure for quantifying amyloid deposition in amyloid positron emission tomography (PET) imaging. We aimed to assess the agreement among 3 CL calculation methods: CapAIBL, VIZCalc, and Amyquant. This study included 192 participants (mean age: 71.5years, range: 50-87years), comprising 55 with Alzheimer's disease, 65 with mild cognitive impairment, 13 with non-Alzheimer's dementia, and 59 cognitively normal participants. All the participants were assessed using the three CL calculation methods. Spearman's rank correlation, linear regression, Friedman tests, Wilcoxon signed-rank tests, and Bland-Altman analysis were employed to assess data correlations, linear associations, method differences, and systematic bias, respectively. Strong correlations (rho = 0.99, p < .001) were observed among the CL values calculated using the three methods. Scatter plots and regression lines visually confirmed these strong correlations and met the validation criteria. Despite the robust correlations, a significant difference in CL value between CapAIBL and Amyquant was observed (36.1 ± 39.7 vs. 34.9 ± 39.4; p < .001). In contrast, no significant differences were found between CapAIBL and VIZCalc or between VIZCalc and Amyquant. The Bland-Altman analysis showed no observable systematic bias between the methods. The study demonstrated strong agreement among the three methods for calculating CL values. Despite minor variations in the absolute values of the Centiloid scores obtained using these methods, the overall agreement suggests that they are interchangeable.

Glymphatic system dysfunction predicts amyloid deposition, neurodegeneration, and clinical progression in Alzheimer's disease.

Although glymphatic function is involved in Alzheimer's disease (AD), its potential for predicting the pathological and clinical progression of AD and its sequential association with core AD biomarkers is poorly understood. Whole-brain glymphatic activity was measured by diffusion tensor image analysis along the perivascular space (DTI-ALPS) in participants with AD dementia (n=47), mild cognitive impairment (MCI; n=137), and normal controls (n=235) from the Alzheimer's Disease Neuroimaging Initiative. ALPS index was significantly lower in AD dementia than in MCI or controls. Lower ALPS index was significantly associated with faster changes in amyloid positron emission tomography (PET) burden and AD signature region of interest volume, higher risk of amyloid-positive transition and clinical progression, and faster rates of amyloid- and neurodegeneration-related cognitive decline. Furthermore, the associations of the ALPS index with cognitive decline were fully mediated by amyloid PET and brain atrophy. Glymphatic failure may precede amyloid pathology, and predicts amyloid deposition, neurodegeneration, and clinical progression in AD. The analysis along the perivascular space (ALPS) index is reduced in patients with Alzheimer's disease (AD) dementia, prodromal AD, and preclinical AD. Lower ALPS index predicted accelerated amyloid beta (Aβ) positron emission tomography (PET) burden and Aβ-positive transition. The decrease in the ALPS index occurs before cerebrospinal fluid Aβ42 reaches the positive threshold. ALPS index predicted brain atrophy, clinical progression, and cognitive decline. Aβ PET and brain atrophy mediated the link of ALPS index with cognitive decline.

Plasma oligomer beta-amyloid is associated with disease severity and cerebral amyloid deposition in Alzheimer’s disease spectrum

BackgroundMultimer detection system-oligomeric amyloid-β (MDS-OAβ) is a measure of plasma OAβ, which is associated with Alzheimer’s disease (AD) pathology. However, the relationship between MDS-OAβ and disease severity of AD is not clear. We aimed to investigate MDS-OAβ levels in different stages of AD and analyze the association between MDS-OAβ and cerebral Aβ deposition, cognitive function, and cortical thickness in subjects within the AD continuum.MethodsIn this cross-sectional study, we analyzed a total 126 participants who underwent plasma MDS-OAβ, structural magnetic resonance image of brain, and neurocognitive measures using Korean version of the Consortium to Establish a Registry for Alzheimer’s Disease, and cerebral Aβ deposition or amyloid positron emission tomography (A-PET) assessed by [18F] flutemetamol PET. Subjects were divided into 4 groups: N = 39 for normal control (NC), N = 31 for A-PET-negative mild cognitive impairment (MCI) patients, N = 30 for A-PET-positive MCI patients, and N = 22 for AD dementia patients. The severity of cerebral Aβ deposition was expressed as standard uptake value ratio (SUVR).ResultsCompared to the NC (0.803 ± 0.27), MDS-OAβ level was higher in the A-PET-negative MCI group (0.946 ± 0.137) and highest in the A-PET-positive MCI group (1.07 ± 0.17). MDS-OAβ level in the AD dementia group was higher than in the NC, but it fell to that of the A-PET-negative MCI group level (0.958 ± 0.103). There were negative associations between MDS-OAβ and cognitive function and both global and regional cerebral Aβ deposition (SUVR). Cortical thickness of the left fusiform gyrus showed a negative association with MDS-OAβ when we excluded the AD dementia group.ConclusionsThese findings suggest that MDS-OAβ is not only associated with neurocognitive staging, but also with cerebral Aβ burden in patients along the AD continuum.

Current Trends and Applications of PET/MRI Hybrid Imaging in Neurodegenerative Diseases and Normal Aging.

Dementia is a significant global health issue that is exacerbated by an aging population. Imaging plays an established role in the evaluation of patients with neurocognitive disorders such as dementia. In current clinical practice, magnetic resonance imaging (MRI) and positron emission tomography (PET) are primary imaging modalities used separately but in concert to help diagnose and classify dementia. The clinical applications of PET/MRI hybrid imaging in dementia are an active area of research, particularly given the continued emergence of functional MRI (fMRI) and amyloid PET tracers. This narrative review provides a comprehensive overview of the rationale and current evidence for PET/MRI hybrid dementia imaging from 2018 to 2023. Hybrid imaging offers advantages in the accuracy of characterizing neurodegenerative disorders, and future research will need to address the cost of integrated PET/MRI systems compared to stand-alone scanners, the development of new biomarkers, and image correction techniques.

CSF Biomarkers in Longitudinal Alzheimer Disease Cohorts: Pre-Analytic Challenges.

The sensitivity of amyloid to pre-analytic factors complicates cerebrospinal fluid (CSF) diagnostics for Alzheimer disease. We report reliability and validity evidence for automated immunoassays from frozen and fresh CSF samples in an ongoing, single-site research program. CSF samples were obtained from 2 Wisconsin cohorts (1256 measurements; 727 participants). Levels of amyloid beta 1-42 (Aβ42), phosphorylated tau 181 (pTau181), and total tau (tTau) were obtained using an Elecsys cobas e 601 platform. Repeatability and fixed effects of storage tube type, extraction method, and freezing were assessed via mixed models. Concordance with amyloid positron emission tomography (PET) was investigated with 238 participants having a temporally proximal PET scan. Repeatability was high with intraclass correlation (ICC) ≥0.9, but tube type strongly affected measurements. Discriminative accuracy for PET amyloid positivity was strong across tube types (area under the curve [AUC]: Aβ42, 0.87; pTau181Aβ42 , 0.96), although optimal thresholds differed. Under real-world conditions, the Elecsys platform had high repeatability. However, strong effects of pre-analytic factors suggest caution in drawing longitudinal inferences.

Timing of Biomarker Changes in Sporadic Alzheimer's Disease in Estimated Years from Symptom Onset.

A clock relating amyloid positron emission tomography (PET) to time was used to estimate the timing of biomarker changes in sporadic Alzheimer disease (AD). Research participants were included who underwent cerebrospinal fluid (CSF) collection within 2 years of amyloid PET. The ages at amyloid onset and AD symptom onset were estimated for each individual. The timing of change for plasma, CSF, imaging, and cognitive measures was calculated by comparing restricted cubic splines of cross-sectional data from the amyloid PET positive and negative groups. The amyloid PET positive sub-cohort (n = 118) had an average age of 70.4 ± 7.4 years (mean ± standard deviation) and 16% were cognitively impaired. The amyloid PET negative sub-cohort (n = 277) included individuals with low levels of amyloid plaque burden at all scans who were cognitively unimpaired at the time of the scans. Biomarker changes were detected 15-19 years before estimated symptom onset for CSF Aβ42/Aβ40, plasma Aβ42/Aβ40, CSF pT217/T217, and amyloid PET; 12-14 years before estimated symptom onset for plasma pT217/T217, CSF neurogranin, CSF SNAP-25, CSF sTREM2, plasma GFAP, and plasma NfL; and 7-9 years before estimated symptom onset for CSF pT205/T205, CSF YKL-40, hippocampal volumes, and cognitive measures. The use of an amyloid clock enabled visualization and analysis of biomarker changes as a function of estimated years from symptom onset in sporadic AD. This study demonstrates that estimated years from symptom onset based on an amyloid clock can be used as a continuous staging measure for sporadic AD and aligns with findings in autosomal dominant AD. ANN NEUROL 2024;95:951-965.

Examining amyloid reduction as a surrogate endpoint through latent class analysis using clinical trial data for dominantly inherited Alzheimer's disease.

Increasing evidence suggests that amyloid reduction could serve as a plausible surrogate endpoint for clinical and cognitive efficacy. The double-blind phase 3 DIAN-TU-001 trial tested clinical and cognitive declines with increasing doses of solanezumab or gantenerumab. We used latent class (LC) analysis on data from the Dominantly Inherited Alzheimer Network Trials Unit 001 trial to test amyloid positron emission tomography (PET) reduction as a potential surrogate biomarker. LC analysis categorized participants into three classes: amyloid no change, amyloid reduction, and amyloid growth, based on longitudinal amyloid Pittsburgh compound B PET standardized uptake value ratio data. The amyloid-no-change class was at an earlier disease stage for amyloid amounts and dementia. Despite similar baseline characteristics, the amyloid-reduction class exhibited reductions in the annual decline rates compared to the amyloid-growth class across multiple biomarker, clinical, and cognitive outcomes. LC analysis indicates that amyloid reduction is associated with improved clinical outcomes and supports its use as a surrogate biomarker in clinical trials. We used latent class (LC) analysis to test amyloid reduction as a surrogate biomarker. Despite similar baseline characteristics, the amyloid-reduction class exhibited remarkably better outcomes compared to the amyloid-growth class across multiple measures. LC analysis proves valuable in testing amyloid reduction as a surrogate biomarker in clinical trials lacking significant treatment effects.