37 research outputs found

    Widespread white matter and conduction defects in PSEN1-related spastic paraparesis

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    The mechanisms underlying PSEN1 mutation-associated spastic paraparesis (SP) are not clear. We compared diffusion and volumetric magnetic resonance measures between 3 persons with SP associated with the A431E mutation and 7 symptomatic persons with PSEN1 mutations without SP matched for symptom duration. We performed amyloid imaging and central motor and somatosensory conduction studies in one subject with SP. We found decreases in fractional anisotropy and increases in mean diffusivity in widespread white matter areas including the corpus callosum, occipital, parietal, and frontal lobes in PSEN1 mutation carriers with SP. Volumetric measures were not different and amyloid imaging showed low signal in sensorimotor cortex and other areas in a single subject with SP. Electrophysiological studies demonstrated both slowed motor and sensory conduction in the lower extremities in this same subject. Our results suggest that SP in carriers of the A431E PSEN1 mutation is a manifestation of widespread white matter abnormalities not confined to the corticospinal tract that is at most indirectly related to the mutation’s effect on APP processing and amyloid deposition

    Comparing amyloid-β plaque burden with antemortem PiB PET in autosomal dominant and late-onset Alzheimer disease

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    Pittsburgh compound B (PiB) radiotracer for positron emission tomography (PET) imaging can bind to different types of amyloid-β plaques and blood vessels (cerebral amyloid angiopathy). However, the relative contributions of different plaque subtypes (diffuse versus cored/compact) to in vivo PiB PET signal on a region-by-region basis is incompletely understood. Of particular interest is whether the same staging schemes for summarizing amyloid-β burden are appropriate for both late-onset and autosomal dominant forms of Alzheimer disease (LOAD and ADAD). Here we compared antemortem PiB PET with follow-up postmortem estimation of amyloid-β burden using stereologic methods to estimate the relative area fraction of diffuse and cored/compact amyloid-β plaques across 16 brain regions in 15 individuals with ADAD and 14 individuals with LOAD. In ADAD, we found that PiB PET correlated with diffuse plaques in the frontal, parietal, temporal, and striatal regions commonly used to summarize amyloid-β burden in PiB PET, and correlated with both diffuse and cored/compact plaques in the occipital lobe and parahippocampal gyrus. In LOAD, we found that PiB PET correlated with both diffuse and cored/compact plaques in the anterior cingulate, frontal lobe (middle frontal gyrus), and parietal lobe, and showed additional correlations with diffuse plaque in the amygdala and occipital lobe, and with cored/compact plaque in the temporal lobe. Thus, commonly used PiB PET summary regions predominantly reflect diffuse plaque burden in ADAD and a mixture of diffuse and cored/compact plaque burden in LOAD. In direct comparisons of ADAD and LOAD, postmortem stereology identified much greater mean amyloid-β plaque burdens in ADAD versus LOAD across almost all brain regions studied. However, standard PiB PET did not recapitulate these stereologic findings, likely due to non-trivial amyloid-β plaque burdens in ADAD within the cerebellum and brainstem – commonly used reference regions in PiB PET. Our findings suggest that PiB PET summary regions correlate with amyloid-β plaque burden in both ADAD and LOAD; however, they might not be reliable in direct comparisons of regional amyloid-β plaque burden between the two forms of AD

    Evaluation of dose-dependent treatment effects after mid-trial dose escalation in biomarker, clinical, and cognitive outcomes for gantenerumab or solanezumab in dominantly inherited Alzheimer's disease

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    Introduction: While the Dominantly Inherited Alzheimer Network Trials Unit (DIAN-TU) was ongoing, external data suggested higher doses were needed to achieve targeted effects; therefore, doses of gantenerumab were increased 5-fold, and solanezumab was increased 4-fold. We evaluated to what extent mid-trial dose increases produced a dose-dependent treatment effect. Methods: Using generalized linear mixed effects (LME) models, we estimated the annual low- and high-dose treatment effects in clinical, cognitive, and biomarker outcomes. Results: Both gantenerumab and solanezumab demonstrated dose-dependent treatment effects (significant for gantenerumab, non-significant for solanezumab) in their respective target amyloid biomarkers (Pittsburgh compound B positron emission tomography standardized uptake value ratio and cerebrospinal fluid amyloid beta 42), with gantenerumab demonstrating additional treatment effects in some downstream biomarkers. No dose-dependent treatment effects were observed in clinical or cognitive outcomes. Conclusions: Mid-trial dose escalation can be implemented as a remedy for an insufficient initial dose and can be more cost effective and less burdensome to participants than starting a new trial with higher doses, especially in rare diseases. Highlights: We evaluated the dose-dependent treatment effect of two different amyloid-specific immunotherapies. Dose-dependent treatment effects were observed in some biomarkers. No dose-dependent treatment effects were observed in clinical/cognitive outcomes, potentially due to the fact that the modified study may not have been powered to detect such treatment effects in symptomatic subjects at a mild stage of disease exposed to high (or maximal) doses of medication for prolonged durations

    T1 and FLAIR signal intensities are related to tau pathology in dominantly inherited Alzheimer disease

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    Carriers of mutations responsible for dominantly inherited Alzheimer disease provide a unique opportunity to study potential imaging biomarkers. Biomarkers based on routinely acquired clinical MR images, could supplement the extant invasive or logistically challenging) biomarker studies. We used 1104 longitudinal MR, 324 amyloid beta, and 87 tau positron emission tomography imaging sessions from 525 participants enrolled in the Dominantly Inherited Alzheimer Network Observational Study to extract novel imaging metrics representing the mean (μ) and standard deviation (σ) of standardized image intensities of T1-weighted and Fluid attenuated inversion recovery (FLAIR) MR scans. There was an exponential decrease in FLAIR-μ in mutation carriers and an increase in FLAIR and T1 signal heterogeneity (T1-σ and FLAIR-σ) as participants approached the symptom onset in both supramarginal, the right postcentral and right superior temporal gyri as well as both caudate nuclei, putamina, thalami, and amygdalae. After controlling for the effect of regional atrophy, FLAIR-μ decreased and T1-σ and FLAIR-σ increased with increasing amyloid beta and tau deposition in numerous cortical regions. In symptomatic mutation carriers and independent of the effect of regional atrophy, tau pathology demonstrated a stronger relationship with image intensity metrics, compared with amyloid pathology. We propose novel MR imaging intensity-based metrics using standard clinical T1 and FLAIR images which strongly associates with the progression of pathology in dominantly inherited Alzheimer disease. We suggest that tau pathology may be a key driver of the observed changes in this cohort of patients

    Variant-dependent heterogeneity in amyloid β burden in autosomal dominant Alzheimer's disease: cross-sectional and longitudinal analyses of an observational study

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    Background: Insights gained from studying individuals with autosomal dominant Alzheimer's disease have broadly influenced mechanistic hypotheses, biomarker development, and clinical trials in both sporadic and dominantly inherited Alzheimer's disease. Although pathogenic variants causing autosomal dominant Alzheimer's disease are highly penetrant, there is substantial heterogeneity in levels of amyloid β (Aβ) between individuals. We aimed to examine whether this heterogeneity is related to disease progression and to investigate the association with mutation location within PSEN1, PSEN2, or APP. Methods: We did cross-sectional and longitudinal analyses of data from the Dominantly Inherited Alzheimer's Network (DIAN) observational study, which enrols individuals from families affected by autosomal dominant Alzheimer's disease. 340 participants in the DIAN study who were aged 18 years or older, had a history of autosomal dominant Alzheimer's disease in their family, and who were enrolled between September, 2008, and June, 2019, were included in our analysis. 206 participants were carriers of pathogenic mutations in PSEN1, PSEN2, or APP, and 134 were non-carriers. 62 unique pathogenic variants were identified in the cohort and were grouped in two ways. First, we sorted variants in PSEN1, PSEN2, or APP by the affected protein domain. Second, we divided PSEN1 variants according to position before or after codon 200. We examined variant-dependent variability in Aβ biomarkers, specifically Pittsburgh-Compound-B PET (PiB-PET) signal, levels of CSF Aβ1-42 (Aβ42), and levels of Aβ1-40 (Aβ40). Findings: Cortical and striatal PiB-PET signal showed striking variant-dependent variability using both grouping approaches (p0·7), and CSF Aβ42 levels (codon-based grouping: p=0·49; domain-based grouping: p=0·095). Longitudinal PiB-PET signal also varied across codon-based groups, mirroring cross-sectional analyses. Interpretation: Autosomal dominant Alzheimer's disease pathogenic variants showed highly differential temporal and regional patterns of PiB-PET signal, despite similar functional progression. These findings suggest that although increased PiB-PET signal is generally seen in autosomal dominant Alzheimer's disease, higher levels of PiB-PET signal at an individual level might not reflect more severe or more advanced disease. Our results have high relevance for ongoing clinical trials in autosomal dominant Alzheimer's disease, including those using Aβ PET as a surrogate marker of disease progression. Additionally, and pertinent to both sporadic and autosomal dominant Alzheimer's disease, our results suggest that CSF and PET measures of Aβ levels are not interchangeable and might reflect different Aβ-driven pathobiological processes. Funding: National Institute on Aging, Doris Duke Charitable Foundation, German Center for Neurodegenerative Diseases, Japanese Agency for Medical Research and Development

    Pattern and degree of individual brain atrophy predicts dementia onset in dominantly inherited Alzheimer's disease

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    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.Fil: Keret, Ophir. University of California; Estados UnidosFil: Staffaroni, Adam M.. University of California; Estados UnidosFil: Ringman, John M.. University of Southern California; Estados UnidosFil: Cobigo, Yann. University of California; Estados UnidosFil: Goh, Sheng Yang M.. University of California; Estados UnidosFil: Wolf, Amy. University of California; Estados UnidosFil: Allen, Isabel Elaine. University of California; Estados UnidosFil: Salloway, Stephen. Brown University; Estados UnidosFil: Chhatwal, Jasmeer. Harvard Medical School; Estados UnidosFil: Brickman, Adam M.. Columbia University; Estados UnidosFil: Reyes Dumeyer, Dolly. Columbia University; Estados UnidosFil: Bateman, Randal J.. University of Washington; Estados UnidosFil: Benzinger, Tammie L.S.. University of Washington; Estados UnidosFil: Morris, John C.. University of Washington; Estados UnidosFil: Ances, Beau M.. University of Washington; Estados UnidosFil: Joseph Mathurin, Nelly. University of Washington; Estados UnidosFil: Perrin, Richard J.. University of Washington; Estados UnidosFil: Gordon, Brian A.. University of Washington; Estados UnidosFil: Levin, Johannes. German Center for Neurodegenerative Diseases; Alemania. Ludwig Maximilians Universitat; AlemaniaFil: Vöglein, Jonathan. Ludwig Maximilians Universitat; Alemania. German Center for Neurodegenerative Diseases; AlemaniaFil: Jucker, Mathias. German Center for Neurodegenerative Diseases; Alemania. Eberhard Karls Universität Tübingen; AlemaniaFil: la Fougère, Christian. Eberhard Karls Universität Tübingen; Alemania. German Center for Neurodegenerative Diseases; AlemaniaFil: Martins, Ralph N.. Cooperative Research Centres Australia; Australia. University of Western Australia; Australia. Edith Cowan University; Australia. Australian Alzheimer's Research Foundation; Australia. Macquarie University; AustraliaFil: Sohrabi, Hamid R.. University of Western Australia; Australia. Macquarie University; Australia. Australian Alzheimer's Research Foundation; Australia. Cooperative Research Centres Australia; Australia. Edith Cowan University; AustraliaFil: Taddei, Kevin. Australian Alzheimer's Research Foundation; Australia. Edith Cowan University; AustraliaFil: Villemagne, Victor L.. Austin Health; AustraliaFil: Schofield, Peter R.. Neuroscience Research Australia; Australia. Unsw Medicine; AustraliaFil: Brooks, William S.. Neuroscience Research Australia; Australia. Unsw Medicine; AustraliaFil: Fulham, Michael. Royal Prince Alfred Hospital; AustraliaFil: Masters, Colin L.. University of Melbourne; AustraliaFil: Allegri, Ricardo Francisco. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia. Instituto de Neurociencias - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Neurociencias; Argentin

    Pattern and degree of individual brain atrophy predicts dementia onset in dominantly inherited Alzheimer's disease

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    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

    Serum neurofilament light chain levels are associated with white matter integrity in autosomal dominant Alzheimer's disease

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    Neurofilament light chain (NfL) is a protein that is selectively expressed in neurons. Increased levels of NfL measured in either cerebrospinal fluid or blood is thought to be a biomarker of neuronal damage in neurodegenerative diseases. However, there have been limited investigations relating NfL to the concurrent measures of white matter (WM) decline that it should reflect. White matter damage is a common feature of Alzheimer's disease. We hypothesized that serum levels of NfL would associate with WM lesion volume and diffusion tensor imaging (DTI) metrics cross-sectionally in 117 autosomal dominant mutation carriers (MC) compared to 84 non-carrier (NC) familial controls as well as in a subset (N = 41) of MC with longitudinal NfL and MRI data. In MC, elevated cross-sectional NfL was positively associated with WM hyperintensity lesion volume, mean diffusivity, radial diffusivity, and axial diffusivity and negatively with fractional anisotropy. Greater change in NfL levels in MC was associated with larger changes in fractional anisotropy, mean diffusivity, and radial diffusivity, all indicative of reduced WM integrity. There were no relationships with NfL in NC. Our results demonstrate that blood-based NfL levels reflect WM integrity and supports the view that blood levels of NfL are predictive of WM damage in the brain. This is a critical result in improving the interpretability of NfL as a marker of brain integrity, and for validating this emerging biomarker for future use in clinical and research settings across multiple neurodegenerative diseases

    Location of pathogenic variants in PSEN1 impacts progression of cognitive, clinical, and neurodegenerative measures in autosomal-dominant Alzheimer's disease

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    Although pathogenic variants in PSEN1 leading to autosomal-dominant Alzheimer disease (ADAD) are highly penetrant, substantial interindividual variability in the rates of cognitive decline and biomarker change are observed in ADAD. We hypothesized that this interindividual variability may be associated with the location of the pathogenic variant within PSEN1. PSEN1 pathogenic variant carriers participating in the Dominantly Inherited Alzheimer Network (DIAN) observational study were grouped based on whether the underlying variant affects a transmembrane (TM) or cytoplasmic (CY) protein domain within PSEN1. CY and TM carriers and variant non-carriers (NC) who completed clinical evaluation, multimodal neuroimaging, and lumbar puncture for collection of cerebrospinal fluid (CSF) as part of their participation in DIAN were included in this study. Linear mixed effects models were used to determine differences in clinical, cognitive, and biomarker measures between the NC, TM, and CY groups. While both the CY and TM groups were found to have similarly elevated Aβ compared to NC, TM carriers had greater cognitive impairment, smaller hippocampal volume, and elevated phosphorylated tau levels across the spectrum of pre-symptomatic and symptomatic phases of disease as compared to CY, using both cross-sectional and longitudinal data. As distinct portions of PSEN1 are differentially involved in APP processing by γ-secretase and the generation of toxic β-amyloid species, these results have important implications for understanding the pathobiology of ADAD and accounting for a substantial portion of the interindividual heterogeneity in ongoing ADAD clinical trials

    Modeling autosomal dominant Alzheimer's disease with machine learning

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    INTRODUCTION: Machine learning models were used to discover novel disease trajectories for autosomal dominant Alzheimer's disease. METHODS: Longitudinal 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. RESULTS: The 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. DISCUSSION: Results 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
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