Citations

AbstractINTRODUCTIONAs the number of biomarkers used to study Alzheimer's disease (AD) continues to increase, it is important to understand the utility of any given biomarker, as well as what additional information a biomarker provides when compared to others.METHODSWe used hierarchical clustering to group 19 cross‐sectional biomarkers in autosomal dominant AD. Feature selection identified biomarkers that were the strongest predictors of mutation status and estimated years from symptom onset (EYO). Biomarkers identified included clinical assessments, neuroimaging, cerebrospinal fluid amyloid, and tau, and emerging biomarkers of neuronal integrity and inflammation.RESULTSThree primary clusters were identified: neurodegeneration, amyloid/tau, and emerging biomarkers. Feature selection identified amyloid and tau measures as the primary predictors of mutation status and EYO. Emerging biomarkers of neuronal integrity and inflammation were relatively weak predictors.DISCUSSIONThese results provide novel insight into our understanding of the relationships among biomarkers and the staging of biomarkers based on disease progression.

AbstractBackgroundThough pathogenic variations in PSEN1 leading to Autosomal Dominant Alzheimer's disease (ADAD) are all highly penetrant, there is substantial inter‐individual variability in the rates of cognitive decline and biomarker change observed in ADAD. We hypothesized that this inter‐individual variability may be associated with the location of the pathogenic variant within PSEN1. We tested this hypothesis using biomarker and cognitive data from the Dominantly Inherited Alzheimer Network (DIAN) observational study.MethodPSEN1 pathogenic variant carriers [grouped based on whether their ADAD genotype affected transmembrane (PSEN1 TM; N = 125) or cytoplasmic (PSEN1 CY; N = 62) domains] and non‐carriers [NC; N = 176] enrolled in DIAN underwent clinical evaluation, multimodal neuroimaging, and lumbar puncture for collection of cerebrospinal fluid (CSF). Linear mixed effects models with a restricted cubic spline were used to determine cross‐sectional differences in clinical and biomarker measures between NC, PSEN1 TM, and PSEN1 CY groups, across the disease course (estimated years to symptom onset; EYO).ResultBackground characteristics are reported in Table 1. PSEN1 CY and PSEN1 TM groups had elevated β‐amyloid (PiB‐PET) and phosphorylated‐tau levels (CSF pTauT181) compared to NC, but these biomarker measures were not different between PSEN1 TM and CY groups (Figure 1a‐b). Additionally, the PSEN1 TM group had decreased glucose metabolism compared to NC but was similar to the PSEN1 CY group (Figure 1c). However, we observed that PSEN1 TM carriers had significantly smaller hippocampal volume, greater lateral ventricle volume, and greater cognitive impairment (Figure 1d‐f) across EYO as compared to PSEN1 CY carriers.ConclusionDespite similar β‐amyloid PET and CSF pTauT181 levels across EYO, individuals with pathogenic variants affecting transmembrane domains in PSEN1 may have more rapid progression of disease as measured by cognitive function and neurodegeneration as compared to those with variants affecting cytoplasmic domains. These results have implications both for understanding the heterogeneity in ongoing ADAD clinical trials and for better understanding the pathobiology of ADAD.

AbstractBackgroundRecent advances in the development of novel Alzheimer’s disease (AD) measures of amyloid, tau, and neurodegeneration in cerebrospinal fluid (CSF) and blood have enabled a better understanding of the links between amyloid‐beta (Aβ), tau species and neurodegeneration in the brain, CSF, and blood. The discoveries of novel tau species in CSF and blood, including specific phospho‐tau (p‐tau) and truncated species containing the microtubule binding region of tau (MTBR‐tau) which aggregates in tau tangles, have greatly expanded our understanding of tau biology and tau target development. The longitudinal Aβ, tau, and neurofilament light chain (NfL) changes previously measured in CSF are now being measured accurately in blood, enabling interpretation and understanding of AD progression in much larger and more robust populations.MethodWe analyzed longitudinal CSF and/or blood plasma mass spectrometry measures of Aβ42/Aβ40, multiple p‐tau species (including p‐tau217, 231, 181, 205, etc.), total tau, MTBR‐tau (e.g., MTBR‐tau243, MTBR‐tau299, and MTBR‐tau354), and NfL in sporadic AD and dominantly inherited AD cohorts. Mass spectrometry results were compared to amyloid and tau aggregation measures by Positron Emission Tomography (PET) scans and clinical and cognitive measures in local and international clinical cohorts including ADNI, AIBL, BioFINDER, Mayo Clinic, the Knight ADRC, and the DIAN.ResultThe longitudinal results indicate that a pathophysiological cascade of events begin with altered CSF and blood plasma Aβ42/Aβ40 ratio, followed by increases in amyloid plaques as measured by amyloid PET, associated with increased phosphorylation of specific CSF tau species (e.g., p‐tau217, p‐tau181, etc.), before increases in p‐tau205, NfL, total tau concentrations, hypometabolism, and atrophy. Finally, some species of MTBR‐tau increase before or with tau aggregation by tau PET and onset of clinical symptoms and correlate with longitudinal tau aggregation and clinical progression.ConclusionThese findings indicate that CSF and blood plasma Aβ, p‐tau, MTBR‐tau and NfL measures are highly precise biomarkers of brain amyloidosis, tauopathy, and neurodegeneration and can accurately identify stages of preclinical and clinical AD.

AbstractBackgroundAmyloid‐related imaging abnormalities (ARIA), edema (E) or hemorrhagic (H) type, have been reported in trials of anti‐β‐amyloid passive immunotherapies in sporadic and dominantly inherited Alzheimer Disease (DIAD). However, beyond APOE‐ɛ4 the risk factors and clinical implications of ARIA are not well understood, especially in DIAD populations. Here we characterize ARIA, focusing on ARIA‐E in the DIAN‐TU‐001 trial evaluating gantenerumab and solanezumab in DIAD.MethodThe DIAN‐TU‐001 trial enrolled 194 participants, including 144 DIAD mutation‐carriers receiving gantenerumab (n=52), solanezumab (n=52), or a placebo (n=40). Clinical assessments included the Clinical Dementia Rating (CDR). Imaging assessments included PiB‐PET and safety MR, including T2‐FLAIR and T2*‐GRE. Treatment dosage and APOE‐ɛ4 status were also reported.ResultEleven participants developed a total of 14 ARIA‐E episodes (discovered on scheduled safety MR) and three had associated mild symptoms reported in retrospect (e.g. headache, imbalance disorder). Though one ARIA‐E case was observed in the solanezumab arm, the following results focus on the gantenerumab arm to prevent unblinding. Recipients of gantenerumab were more likely to develop ARIA‐E compared to placebo (odds ratio (OR)=9.29, 95% confidence interval (CI)=[1.1,75.9], p‐value<0.05). ARIA‐E participants were PiB‐PET+ and 60% were CDR>0. APOE‐ɛ4 tends to be associated with risk for developing ARIA‐E (OR=5.0, 95%CI=[1.0,30.4], p‐value=0.055). ARIA‐E were not observed at initial 225mg dose and were first observed after a titration step (within 4‐24 weeks, after 1‐6 injections, Table 1). Time‐to‐resolution of ARIA‐E was 10.4±6.2weeks. Seven of ten ARIA‐E patients paused/reduced dose escalation and three discontinued treatment. Overall, developing ARIA‐E did not increase the odds of trial discontinuation (OR=1.57, 95%CI=[0.34,7.33], p‐value=0.57). ARIA‐E occurred primarily in the occipital lobe (71%) with associated incident ARIA‐H (microhemorrhages or superficial siderosis) in 60% of ARIA‐E participants. ARIA‐E size was associated with microhemorrhage count (Spearman’s rho=0.72, p‐value<0.05), rate of change (rho=0.78, p‐value<0.01), and baseline PiB‐PET (rho=0.68, p‐value<0.05). Normalizing by baseline, PiB‐PET decreased similarly in ARIA‐E+ (‐0.21±0.20) and ARIA‐E‐ (‐0.16±0.20) participants.ConclusionIn DIAD, gantenerumab dose over 225mg increased ARIA‐E risk, possibly more for APOE‐ɛ4 carriers. ARIA‐E was reversible, generally asymptomatic, and without increased odds of trial discontinuation. These aspects of drug response give insights for managing ARIA‐E occurrence in future trials.

Abstract Introduction Asymptomatic and mildly symptomatic dominantly inherited Alzheimer's disease mutation carriers (DIAD‐MC) are ideal candidates for preventative treatment trials aimed at delaying or preventing dementia onset. Brain atrophy is an early feature of DIAD‐MC and could help predict risk for dementia during trial enrollment. Methods We created a dementia risk score by entering standardized gray‐matter volumes from 231 DIAD‐MC into a logistic regression to classify participants with and without dementia. The score's predictive utility was assessed using Cox models and receiver operating curves on a separate group of 65 DIAD‐MC followed longitudinally. Results Our risk score separated asymptomatic versus demented DIAD‐MC with 96.4% (standard error = 0.02) and predicted conversion to dementia at next visit (hazard ratio = 1.32, 95% confidence interval [CI: 1.15, 1.49]) and within 2 years (area under the curve = 90.3%, 95% CI [82.3%–98.2%]) and improved prediction beyond established methods based on familial age of onset. Discussion Individualized risk scores based on brain atrophy could be useful for establishing enrollment criteria and stratifying DIAD‐MC participants for prevention trials.

Abstract Cognitive resilience is an important modulating factor of cognitive decline in Alzheimer’s disease, but the functional brain mechanisms that support cognitive resilience remain elusive. Given previous findings in normal ageing, we tested the hypothesis that higher segregation of the brain’s connectome into distinct functional networks represents a functional mechanism underlying cognitive resilience in Alzheimer’s disease. Using resting-state functional MRI, we assessed both resting-state functional MRI global system segregation, i.e. the balance of between-network to within-network connectivity, and the alternate index of modularity Q as predictors of cognitive resilience. We performed all analyses in two independent samples for validation: (i) 108 individuals with autosomal dominantly inherited Alzheimer’s disease and 71 non-carrier controls; and (ii) 156 amyloid-PET-positive subjects across the spectrum of sporadic Alzheimer’s disease and 184 amyloid-negative controls. In the autosomal dominant Alzheimer’s disease sample, disease severity was assessed by estimated years from symptom onset. In the sporadic Alzheimer’s sample, disease stage was assessed by temporal lobe tau-PET (i.e. composite across Braak stage I and III regions). In both samples, we tested whether the effect of disease severity on cognition was attenuated at higher levels of functional network segregation. For autosomal dominant Alzheimer’s disease, we found higher functional MRI-assessed system segregation to be associated with an attenuated effect of estimated years from symptom onset on global cognition (P = 0.007). Similarly, for patients with sporadic Alzheimer’s disease, higher functional MRI-assessed system segregation was associated with less decrement in global cognition (P = 0.001) and episodic memory (P = 0.004) per unit increase of temporal lobe tau-PET. Confirmatory analyses using the alternate index of modularity Q revealed consistent results. In conclusion, higher segregation of functional connections into distinct large-scale networks supports cognitive resilience in Alzheimer’s disease.

AbstractIntroductionMachine learning models were used to discover novel disease trajectories for autosomal dominant Alzheimer's disease.MethodsLongitudinal structural magnetic resonance imaging, amyloid positron emission tomography (PET), and fluorodeoxyglucose PET were acquired in 131 mutation carriers and 74 non‐carriers from the Dominantly Inherited Alzheimer Network; the groups were matched for age, education, sex, and apolipoprotein ε4 (APOE ε4). A deep neural network was trained to predict disease progression for each modality. Relief algorithms identified the strongest predictors of mutation status.ResultsThe Relief algorithm identified the caudate, cingulate, and precuneus as the strongest predictors among all modalities. The model yielded accurate results for predicting future Pittsburgh compound B (R2 = 0.95), fluorodeoxyglucose (R2 = 0.93), and atrophy (R2 = 0.95) in mutation carriers compared to non‐carriers.DiscussionResults suggest a sigmoidal trajectory for amyloid, a biphasic response for metabolism, and a gradual decrease in volume, with disease progression primarily in subcortical, middle frontal, and posterior parietal regions.