Validating the Amyloid Cascade Through the Revised Criteria of Alzheimer's Association Workgroup 2024 for Alzheimer Disease

While clinical disease stages remained largely unchanged in the 2024 update of the Alzheimer disease (AD) criteria, tau-positron emission tomography (PET) was introduced as a core biomarker and its spatial extent was incorporated into the revised biological stages of the disease. It is important to consider both the clinical and the biological stages and understand their discrepancies. To compare individuals who have discrepant biological and clinical stages with those who have congruent stages in terms of copathologies, comorbidities, and demographics. Participants were from the Swedish BioFINDER-2 (inclusion from 2017 through 2023) and the Alzheimer's Disease Neuroimaging Initiative (ADNI) (inclusion from 2015 through 2024). BioFINDER-2 included a prospective population-based (cognitively normal [CN] older adults) and memory clinic-based cohort (participants with subjective cognitive impairment [SCD], mild cognitive impairment [MCI], and dementia). ADNI included a volunteer-based sample. All participants who were amyloid-β positive and had undergone tau-PET were included. In BioFINDER-2, 838 participants of a total of 1979 were included, and of 927 with tau-PET in ADNI, 380 were included. The clinical (CN to dementia) and biological (based on PET; initial [amyloid-β-positive only] to advanced [amyloid-β-positive, elevated, and widespread tau]) stages from the revised AD criteria. Cross-sectional measures of neurodegeneration (cortical thickness, TAR DNA-binding protein 43 [TDP-43] imaging signature, neurofilament light [NfL]), α-synuclein cerebrospinal fluid status, plasma glial fibrillary acidic protein, white matter lesions, infarcts, microbleeds, comorbidities, and demographics. There were 838 BioFINDER-2 participants (mean age, 73.9 [SD, 7.3] years; 431 women [51%]; 407 men [49%]) and 380 ADNI participants (average age, 72.9 [SD, 7.0] years; 194 women [51%]; 186 mean [49%]) included. In BioFINDER-2, 37.7% of the sample had congruent biological and clinical stages (reference group), 51.3% had more advanced clinical impairment compared with their clinical stage (clinical > biological) and 11.0% had the opposite (biological > clinical). The main differences were between the reference group and the clinical > biological group: the latter participants were more often positive for α-synuclein pathology, had higher NfL levels, greater TDP-43-like atrophy, and higher burden of cerebral small vessel disease lesions (all false discovery rate P < .05). The only difference between the biological > clinical and the reference group was that the former had less neurodegeneration (thicker cortex; all false discovery rate P < .001). The main results were replicated in the independent ADNI cohort, where congruent 56.1% of participants had biological and clinical stages; 36.1% were in the category clinical > biological, and 7.9% in biological > clinical. Copathologies play an important role in symptom severity in individuals who harbor less tau-tangle pathology than expected for their clinical impairment. These results highlight the importance of measuring non-AD biomarkers in patients with AD with worse cognitive impairment than expected based on their biological stage, which could impact the clinical diagnosis and prognosis.

Decision letter: Stage-dependent differential influence of metabolic and structural networks on memory across Alzheimer’s disease continuum

Develop a cerebrospinal fluid biomarker signature for mild Alzheimer's disease (AD) in Alzheimer's Disease Neuroimaging Initiative (ADNI) subjects. Amyloid-beta 1 to 42 peptide (A beta(1-42)), total tau (t-tau), and tau phosphorylated at the threonine 181 were measured in (1) cerebrospinal fluid (CSF) samples obtained during baseline evaluation of 100 mild AD, 196 mild cognitive impairment, and 114 elderly cognitively normal (NC) subjects in ADNI; and (2) independent 56 autopsy-confirmed AD cases and 52 age-matched elderly NCs using a multiplex immunoassay. Detection of an AD CSF profile for t-tau and A beta(1-42) in ADNI subjects was achieved using receiver operating characteristic cut points and logistic regression models derived from the autopsy-confirmed CSF data. CSF A beta(1-42) was the most sensitive biomarker for AD in the autopsy cohort of CSF samples: receiver operating characteristic area under the curve of 0.913 and sensitivity for AD detection of 96.4%. In the ADNI cohort, a logistic regression model for A beta(1-42), t-tau, and APO epsilon 4 allele count provided the best assessment delineation of mild AD. An AD-like baseline CSF profile for t-tau/A beta(1-42) was detected in 33 of 37 ADNI mild cognitive impairment subjects who converted to probable AD during the first year of the study. The CSF biomarker signature of AD defined by A beta(1-42) and t-tau in the autopsy-confirmed AD cohort and confirmed in the cohort followed in ADNI for 12 months detects mild AD in a large, multisite, prospective clinical investigation, and this signature appears to predict conversion from mild cognitive impairment to AD.

Safety profile of Alzheimer's disease patient populations over 18 months using ADNI and controlled clinical trial data

The ADNI multicenter study: CSF biomarkers data report

Background and Hypothesis: Magnetic resonance imaging (MRI) has become a useful tool in monitoring the progression of Alzheimer's disease. Previous surface-based analysis has focused on changes in cortical thickness associated with the disease1. The objective of this study is to analyze MRI-derived cortical reconstructions for patterns of atrophy in terms of both cortical thickness and cortical volume. We hypothesize that Alzheimer’s Disease progression will be associated with a more significant change in volume than thickness. Experimental Design or Project Methods: MRI data was obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI). All subjects with baseline and two-year 3T MRI scans were included. Segmentation of MRIs into gray and white matter was performed with FreeSurfer2,3,4,5. Subjects whose scans did not segment accurately were excluded. Surfaces were then registered to a common atlas with Ciftify6, and anatomically-constrained Multimodal Surface Matching (aMSM) was used to analyze longitudinal changes in each subject7. This produced continuous surface maps showing changes in cortical surface area and thickness. These maps were multiplied to create cortical volume maps8. Permutation Analysis of Linear Models (PALM) was used to perform two-sample t-tests comparing the maps of the Alzheimer’s and control groups9. Results: Preliminary analysis of nine Alzheimer’s subjects and nine control subjects produced surface maps displaying patterns that were expected given previous research findings10,11. There was increased volume and thickness loss in Alzheimer’s subjects relative to controls, with relatively high loss in structures of the medial temporal lobe. Future analysis of a larger sample will determine whether statistically significant differences exist between the Alzheimer’s and control groups in terms of thickness loss and volume loss. Conclusion and Potential Impact: If significant results are found, surface-based analysis of cortical volume may allow for detection of atrophy at an earlier stage in disease progression than would be possible based on cortical thickness.

The structural covariance network (SCN) has provided a perspective on the large‐scale brain organization impairment in the Alzheimer's Disease (AD) continuum. However, the successive structural impairment across brain regions, which may underlie the disrupted SCN in the AD continuum, is not well understood. In the current study, we enrolled 446 subjects with AD, mild cognitive impairment (MCI) or normal aging (NA) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The SCN as well as a casual SCN (CaSCN) based on Granger causality analysis were applied to the T1‐weighted structural magnetic resonance images of the subjects. Compared with that of the NAs, the SCN was disrupted in the MCI and AD subjects, with the hippocampus and left middle temporal lobe being the most impaired nodes, which is in line with previous studies. In contrast, according to the 194 subjects with records on CSF amyloid and Tau, the CaSCN revealed that during AD progression, the CaSCN was enhanced. Specifically, the hippocampus, thalamus, and precuneus/posterior cingulate cortex (PCC) were identified as the core regions in which atrophy originated and could predict atrophy in other brain regions. Taken together, these findings provide a comprehensive view of brain atrophy in the AD continuum and the relationships among the brain atrophy in different regions, which may provide novel insight into the progression of AD.

Bayesian latent time joint mixed-effects model of progression in the Alzheimer's Disease Neuroimaging Initiative

Amyloid-β pathology is associated with greater tau pathology and facilitates tau propagation from the medial temporal lobe to the neocortex, where tau is closely associated with local neurodegeneration. The degree of the involvement of amyloid-β versus existing tau pathology in tau propagation and neurodegeneration has not been fully elucidated in human studies. Careful quantification of these effects can inform the development and timing of therapeutic interventions. We conducted causal mediation analyses to investigate the relative contributions of amyloid-β and existing tau to tau propagation and neurodegeneration in two longitudinal studies of individuals without dementia: the Baltimore Longitudinal Study of Aging (N = 103, age range 57-96) and the Alzheimer's Disease Neuroimaging Initiative (N = 122, age range 56-92). As proxies of neurodegeneration, we investigated cerebral blood flow, glucose metabolism, and regional volume. We first confirmed that amyloid-β moderates the association between tau in the entorhinal cortex and in the inferior temporal gyrus, a neocortical region exhibiting early tau pathology (amyloid group × entorhinal tau interaction term β = 0.488, standard error [SE] = 0.126, P < 0.001 in the Baltimore Longitudinal Study of Aging; β = 0.619, SE = 0.145, P < 0.001 in the Alzheimer's Disease Neuroimaging Initiative). In causal mediation analyses accounting for this facilitating effect of amyloid, amyloid positivity had a statistically significant direct effect on inferior temporal tau as well as an indirect effect via entorhinal tau (average direct effect =0.47, P < 0.001 and average causal mediation effect =0.44, P = 0.0028 in Baltimore Longitudinal Study of Aging; average direct effect =0.43, P = 0.004 and average causal mediation effect =0.267, P = 0.0088 in Alzheimer's Disease Neuroimaging Initiative). Entorhinal tau mediated up to 48% of the total effect of amyloid on inferior temporal tau. Higher inferior temporal tau was associated with lower colocalized cerebral blood flow, glucose metabolism, and regional volume, whereas amyloid had only an indirect effect on these measures via tau, implying tau as the primary driver of neurodegeneration (amyloid-cerebral blood flow average causal mediation effect =-0.28, P = 0.021 in Baltimore Longitudinal Study of Aging; amyloid-volume average causal mediation effect =-0.24, P < 0.001 in Alzheimer's Disease Neuroimaging Initiative). Our findings suggest targeting amyloid or medial temporal lobe tau might slow down neocortical spread of tau and subsequent neurodegeneration, but a combination therapy may yield better outcomes.

A workgroup assembled by the Alzheimer's Association recently described a conceptual framework for Alzheimer's disease biological staging based on amyloid and tau positron emission tomography (PET) imaging. However, specific tau PET cut points were left to be determined, a step necessary prior to clinical application. We sought to operationalize and evaluate Alzheimer's disease biological staging by identifying meaningful tau PET cut points to define the four biological stages in a well-characterized participant cohort and describe the features of individuals placed into the different biological stages. The primary analysis included 896 participants in the Mayo Clinic Study of Aging or the Mayo Clinic Alzheimer's Disease Research Center longitudinal cohorts. A validation cohort consisted of 328 participants in the Alzheimer's Disease Neuroimaging Initiative. Both cognitively normal and impaired individuals with positive amyloid PET and evaluable tau PET imaging were included. Tau PET cut points were identified with Gaussian Mixture Models to characterize Alzheimer's disease biological stage in study participants with different clinical diagnoses and objective degrees of cognitive impairment as measured by Mini-Mental State Examination. A tau PET cut point in the medial temporal region and two cut points in the temporoparietal region were identified to collectively produce the four Alzheimer's disease biological stages described in the revised criteria. Increasing stage was associated with greater likelihood of mild cognitive impairment and dementia diagnosis and worsening cognitive performance on Mini-Mental State Examination and Clinical Dementia Rating Sum of Boxes, a result that was reproduced in the independent Alzheimer's Disease Neuroimaging Initiative cohort. This study provided empiric validation for the concept of using amyloid PET and tau PET to separate subjects with biomarker-proven Alzheimer's disease into four biological stages with distinct characteristics.

The screening and enrollment of underrepresented ethnoracial and educational populations in the Alzheimer's Disease Neuroimaging Initiative

Compositional brain scores capture Alzheimer's disease-specific structural brain patterns along the disease continuum.

ContextThere is no rapid and cost effective tool that can be implemented as a front-line screening tool for Alzheimer's disease (AD) at the population level.ObjectiveTo generate and cross-validate a blood-based screener for AD that yields acceptable accuracy across both serum and plasma.Design, Setting, ParticipantsAnalysis of serum biomarker proteins were conducted on 197 Alzheimer's disease (AD) participants and 199 control participants from the Texas Alzheimer's Research Consortium (TARC) with further analysis conducted on plasma proteins from 112 AD and 52 control participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI). The full algorithm was derived from a biomarker risk score, clinical lab (glucose, triglycerides, total cholesterol, homocysteine), and demographic (age, gender, education, APOE*E4 status) data.Major Outcome MeasuresAlzheimer's disease.Results11 proteins met our criteria and were utilized for the biomarker risk score. The random forest (RF) biomarker risk score from the TARC serum samples (training set) yielded adequate accuracy in the ADNI plasma sample (training set) (AUC = 0.70, sensitivity (SN) = 0.54 and specificity (SP) = 0.78), which was below that obtained from ADNI cerebral spinal fluid (CSF) analyses (t-tau/Aβ ratio AUC = 0.92). However, the full algorithm yielded excellent accuracy (AUC = 0.88, SN = 0.75, and SP = 0.91). The likelihood ratio of having AD based on a positive test finding (LR+) = 7.03 (SE = 1.17; 95% CI = 4.49–14.47), the likelihood ratio of not having AD based on the algorithm (LR−) = 3.55 (SE = 1.15; 2.22–5.71), and the odds ratio of AD were calculated in the ADNI cohort (OR) = 28.70 (1.55; 95% CI = 11.86–69.47).ConclusionsIt is possible to create a blood-based screening algorithm that works across both serum and plasma that provides a comparable screening accuracy to that obtained from CSF analyses.

Background and ObjectivesTau-PET is increasingly used in Alzheimer disease (AD) clinical trials, both for participant selection based on disease stage and as an outcome measure. However, the longitudinal patterns of tau accumulation according to AD stages remain unclear. We aimed to examine the patterns of tau-PET accumulation in different AD stages defined by the Alzheimer's Association Workgroup to inform trial design.MethodsThis was a retrospective analysis of data collected from participants in 2 longitudinal observational cohort studies: the Translational Biomarkers in Aging and Dementia (TRIAD) study from Montreal, Canada, and Alzheimer's Disease Neuroimaging Initiative (ADNI), a multisite study in North America. Amyloid-PET–positive participants were biologically staged as one of the following based on tau-PET uptake: A+T2− (initial), A+T2MTL+ (early), A+T2MOD+ (intermediate), and A+T2HIGH+ (advanced). Amyloid-PET–negative participants were included as non-AD controls. All participants underwent amyloid-PET and tau-PET imaging, with longitudinal follow-up (mean: 2.96 ± 1.35 years). Linear mixed-effects models evaluated stage-specific regional longitudinal tau-PET changes; statistical power analyses estimated the sample sizes needed to detect differences in tau-PET accumulation for future AD trials.ResultsThe study included 542 participants (mean age: 67.9 ± 15.3 years; 56.3% female), comprising 321 non-AD controls and 221 individuals with AD. The baseline AD stage determined both the regional distribution and magnitude of tau accumulation. No significant accumulation occurred in A+T2− individuals over 4–6 years. In those with early-stage AD, tau accumulation was localized to early affected regions (TRIAD: β = 0.15, 95% CI 0.09–0.21, p < 0.001; ADNI: β = 0.21, 95% CI 0.03–0.40, p = 0.03). Individuals with intermediate-stage AD showed accumulation in intermediate regions (TRIAD: β = 0.16, 95% CI 0.10–0.22, p < 0.001; ADNI: β = 0.37, 95% CI 0.15–0.59, p = 0.001) while those with advanced-stage AD exhibited accumulation in later affected regions (TRIAD: β = 0.45, 95% CI 0.39–0.50, p < 0.001; ADNI: β = 0.31, 95% CI 0.14–0.49, p < 0.001). Stage-specific tau-PET region-of-interest selection reduced required sample sizes by 30%–93% for detecting hypothetical disease-modifying drug effects.DiscussionStage-specific patterns of tau-PET change highlighted the importance of baseline biological AD staging for selecting outcome regions of interest. Statistical power analyses indicated that aligning outcome regions with disease stage reduced sample size estimates, suggesting potential gains in trial efficiency. While findings were consistent across 2 independent cohorts, differences in tracers and demographic composition represent key limitations.

Regional pattern of cortical microstructural alterations along the AD continuum and association with plasma neurofilament light