Citations

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.

AbstractBackgroundAlzheimer’s disease (AD) prevention trials aim to intervene prior to significant neuronal loss, brain damage, and symptom onset to delay or slow cognitive decline. In dominantly inherited AD (DIAD), mutation carriers develop symptomatic AD at predictable ages with near 100% penetrance. In 2012, the Dominantly Inherited Alzheimer Network Trials Unit Adaptive Prevention Trial (DIAN‐TU APT) platform launched a double‐blind, randomized, placebo‐controlled, parallel group trial of two anti‐amyloid‐beta monoclonal antibodies with two different antigenic targets, gantenerumab and solanezumab (NCT01760005). The DIAN‐TU scientific development, implementation of the first AD prevention trial, trial challenges and opportunities, including dose escalation, and top‐line results will be presented.MethodDIAN was established in 2008 in response to a call from the National Institute of Aging to establish a network to study DIAD and enable future clinical trials. Successive breakthroughs in understanding disease processes enabled the launch of the DIAN‐TU adaptive prevention trial, a global adaptive platform trial supporting testing multiple drugs in parallel. The DIAN‐TU partners include patients and families at risk for DIAD, global academic researchers, the NIH, Alzheimer’s Association, philanthropic supporters, the DIAN‐TU Pharma Consortium, and pharmaceutical companies with drugs being tested. Important milestones include developing a platform to enable a comprehensive efficient treatment trial for this rare population, adding tau PET as part of AMP AD, adapting dosing mid‐trial and extending the original biomarker trial to continue randomized dosing to test a cognitive endpoint until the last patient reaches 4 years, developing a disease progression statistical model and inclusion of DIAN observational data to increase the power to determine drug effects.ResultThe primary and key secondary outcomes of the DIAN‐TU trial will be presented for each therapy in the context of targeting amyloid‐beta at pre‐clinical and clinically symptomatic stages of disease.ConclusionThese results inform about AD hypotheses, timing of treatment and the prospect of slowing, or preventing AD in DIAD and sporadic AD.

AbstractBackgroundGantenerumab is a humanized anti‐amyloid‐beta monoclonal antibody in clinical development for the treatment of several stages of Alzheimer disease (AD). Gantenerumab was evaluated in a phase 2/3 clinical trial program designed to evaluate its efficacy in autosomal dominant AD based on a combination of clinical and biomarker evidence.MethodThe study enrolled both mutation carriers (n=69 with 3:1 randomization of treatment (n=52) vs placebo (n=17)) and non‐carriers (n=28, all on placebo) from 15 years before to 10 years after the expected age of onset inclusive. Patients were both asymptomatic (CDR 0 and MMSE >25) and symptomatic (CDR 0.5‐1 and MMSE >16). There were 41 asymptomatic and 28 symptomatic mutation carriers. The initial dose of gantenerumab was 225 mg monthly administered subcutaneously. The dose was titrated to 1200 mg/month following a protocol amendment based on the increased amyloid lowering seen at higher doses in the gantenerumab program in symptomatic AD. The treatment duration was a minimum of 4 years (range 48‐80 months). The primary outcome was change from baseline in the DIAN‐TU multivariate cognitive endpoint. Secondary clinical outcomes included the DIAN‐TU cognitive composite, Cogstate multivariate cognitive endpoint, CDR SB, and time to CDR progression of >0.5 points. Change from baseline in amyloid PET was the primary biomarker outcome. Other biomarker outcomes included MRI, tau PET, CSF amyloid, tau and phosphotau, and CSF and plasma neurofilament light (NfL). Safety outcomes including ARIA were compared between drug and placebo groups.ResultWe will report change from baseline on the DIAN‐TU multivariate cognitive endpoint, DIAN‐TU cognitive composite, CDR‐SB and other secondary efficacy endpoints. We expect significant lowering on amyloid PET with PIB and florbetapir based on the results from recent anti‐amyloid antibodies, including Gantenerumab, in sporadic AD. We will also present the results of change in other key imaging and fluid biomarkers. The frequency, duration, and severity of ARIA will be reported and compared with studies in sporadic AD.ConclusionThis clinical trial was designed to inform future for ADAD and will provide new insights on the role of amyloid reduction in both pre‐symptomatic and clinical AD.

AbstractBackgroundSolanezumab is a monoclonal antibody targeting soluble forms of β‐amyloid protein important in the pathogenesis of Alzheimer’s disease (AD). Three previous 18‐month double‐blind placebo‐controlled trials of low‐dose solanezumab in late‐onset sporadic AD found inconsistent benefits on cognitive and functional assessments. Dominantly‐inherited mutation‐associated AD subjects both before and after onset of symptoms form an ideal population to study potential benefits of solanezumab therapy.MethodMutation‐carrying asymptomatic (CDR 0, N=41) or mildly symptomatic (CDR 0.5 – 1, N=28) patients were treated for a minimum of 4 years and up to 7 years in a double‐blind 3 to 1 active versus placebo randomized clinical trial that measured disease progression by clinical, neuropsychological and biomarker evaluations. The trial was initiated with a dose of 400 mg every 4 weeks and escalated to 1600 mg when low dose trials in sporadic AD did not meet their primary endpoints. The primary cognitive outcome measure was DIAN‐MCE, composed of Delayed Recall Score of the International Shopping List Test, the Delayed Recall score of the Logical Memory IIa subtest from the Wechsler Memory Scale‐Revised, the Digit Symbol Substitution Test total score from the WAIS‐R and the MMSE total score. Secondary outcomes included a battery of other cognitive and functional measures. The study was powered to detect delay of cognitive disease progression in the DIAN‐MCE. Biomarkers include imaging modalities (volumetric MRI, FDG, amyloid and Tau PET). CSF markers included β‐amyloid, Tau and PhosphoTau species. NfL was measured in both CSF and plasma. The study used a pre‐specified Bayesian multivariate disease progression model, which included dynamic borrowing of control subjects from the DIAN Observational study.ResultThe topline efficacy, safety and biomarker results will be reported.ConclusionThis study provides the first test of targeting soluble abeta forms in DIAD. It addresses the efficacy of early initiation of higher doses of solanezumab targeting soluble forms of amyloid as a disease modifying therapy. While these results are specific to DIAD, they have the potential to inform the application of anti‐amyloid therapy in sporadic AD.

Abstract INTRODUCTION A biphasic model for brain structural changes in preclinical Alzheimer's disease (AD) could reconcile some conflicting and paradoxical findings in observational studies and anti‐amyloid clinical trials. METHODS In this study we tested this model fitting linear versus quadratic trajectories and computed the timing of the inflection points vertexwise of cortical thickness and cortical diffusivity—a novel marker of cortical microstructure—changes in 389 participants from the Dominantly Inherited Alzheimer Network. RESULTS In early preclinical AD, between 20 and 15 years before estimated symptom onset, we found increases in cortical thickness and decreases in cortical diffusivity followed by cortical thinning and cortical diffusivity increases in later preclinical and symptomatic stages. The inflection points 16 to 19 years before estimated symptom onset are in agreement with the start of tau biomarker alterations. DISCUSSION These findings confirm a biphasic trajectory for brain structural changes and have direct implications when interpreting magnetic resonance imaging measures in preventive AD clinical trials.

Background and Purpose: Stroke is a complex disease with multiple genetic and environmental risk factors. Blacks endure a nearly 2-fold greater risk of stroke and are 2× to 3× more likely to die from stroke than European Americans. Methods: The COMPASS (Consortium of Minority Population Genome-Wide Association Studies of Stroke) has conducted a genome-wide association meta-analysis of stroke in >22 000 individuals of African ancestry (3734 cases, 18 317 controls) from 13 cohorts. Results: In meta-analyses, we identified one single nucleotide polymorphism (rs55931441) near the HNF1A gene that reached genome-wide significance ( P =4.62×10 −8 ) and an additional 29 variants with suggestive evidence of association ( P <1×10 −6 ), representing 24 unique loci. For validation, a look-up analysis for a 100 kb region flanking the COMPASS single nucleotide polymorphism was performed in SiGN (Stroke Genetics Network) Europeans, SiGN Hispanics, and METASTROKE (Europeans). Using a stringent Bonferroni correction P value of 2.08×10 −3 (0.05/24 unique loci), we were able to validate associations at the HNF1A locus in both SiGN ( P =8.18×10 −4 ) and METASTROKE ( P =1.72×10 −3 ) European populations. Overall, 16 of 24 loci showed evidence for validation across multiple populations. Previous studies have reported associations between variants in the HNF1A gene and lipids, C-reactive protein, and risk of coronary artery disease and stroke. Suggestive associations with variants in the SFXN4 and TMEM108 genes represent potential novel ischemic stroke loci. Conclusions: These findings represent the most thorough investigation of genetic determinants of stroke in individuals of African descent, to date.

Abstract Structural grey matter covariance networks provide an individual quantification of morphological patterns in the brain. The network integrity is disrupted in sporadic Alzheimer’s disease, and network properties show associations with the level of amyloid pathology and cognitive decline. Therefore, these network properties might be disease progression markers. However, it remains unclear when and how grey matter network integrity changes with disease progression. We investigated these questions in autosomal dominant Alzheimer’s disease mutation carriers, whose conserved age at dementia onset allows individual staging based upon their estimated years to symptom onset. From the Dominantly Inherited Alzheimer Network observational cohort, we selected T1-weighted MRI scans from 269 mutation carriers and 170 non-carriers (mean age 38 ± 15 years, mean estimated years to symptom onset −9 ± 11), of whom 237 had longitudinal scans with a mean follow-up of 3.0 years. Single-subject grey matter networks were extracted, and we calculated for each individual the network properties which describe the network topology, including the size, clustering, path length and small worldness. We determined at which time point mutation carriers and non-carriers diverged for global and regional grey matter network metrics, both cross-sectionally and for rate of change over time. Based on cross-sectional data, the earliest difference was observed in normalized path length, which was decreased for mutation carriers in the precuneus area at 13 years and on a global level 12 years before estimated symptom onset. Based on longitudinal data, we found the earliest difference between groups on a global level 6 years before symptom onset, with a greater rate of decline of network size for mutation carriers. We further compared grey matter network small worldness with established biomarkers for Alzheimer disease (i.e. amyloid accumulation, cortical thickness, brain metabolism and cognitive function). We found that greater amyloid accumulation at baseline was associated with faster decline of small worldness over time, and decline in grey matter network measures over time was accompanied by decline in brain metabolism, cortical thinning and cognitive decline. In summary, network measures decline in autosomal dominant Alzheimer’s disease, which is alike sporadic Alzheimer’s disease, and the properties show decline over time prior to estimated symptom onset. These data suggest that single-subject networks properties obtained from structural MRI scans form an additional non-invasive tool for understanding the substrate of cognitive decline and measuring progression from preclinical to severe clinical stages of Alzheimer’s disease.