Seizures in Alzheimer's disease are highly recurrent and associated with a poor disease course

BACKGROUND Seizures are an important comorbidity in Alzheimer's disease (AD). Conflicting results regarding clinical parameters associated with seizures in AD were previously reported. Data on seizure recurrence risk, a crucial parameter for treatment decisions, are lacking. METHODS National Alzheimer's Coordinating Center data were analyzed. Seizure prevalence in AD and an association with disease duration were investigated. Associations of seizures with age of AD onset and with cognitive and functional performance, and seizure recurrence risk were studied. RESULTS 20,745 individuals were investigated. In AD dementia, seizure recurrence risk was 70.4% within 7.5 months. Seizure history was associated with an earlier age of onset of cognitive symptoms (seizures vs. no seizures: 64.7 vs. 70.4 years; p < 0.0001) and worse cognitive and functional performance (mean MMSE score: 16.6 vs. 19.6; mean CDR-sum of boxes score: 9.3 vs. 6.8; p < 0.0001; adjusted for disease duration and age). Seizure prevalence increased with duration of AD dementia (standardized OR = 1.55, 95% CI = 1.39–1.73, p < 0.0001), rising from 1.51% at 4.8 years to 5.43% at 11 years disease duration. Seizures were more frequent in AD dementia compared to normal controls (active seizures: 1.51% vs. 0.35%, p < 0.0001, OR = 4.34, 95% CI = 3.01–6.27; seizure history: 3.14% vs. 1.57%, p < 0.0001, OR = 2.03, 95% CI = 1.67–2.46). CONCLUSION Seizures in AD dementia feature an exceptionally high recurrence risk and are associated with a poor course of cognitive symptoms. AD patients are at an increased risk for seizures, particularly in later disease stages. Our findings emphasize a need for seizure history assessment in AD, inform individual therapeutic decisions and underline the necessity of systematic treatment studies of AD-associated epilepsy

Differentiating amyloid beta spread in autosomal dominant and sporadic Alzheimer\u27s disease

Amyloid-beta deposition is one of the hallmark pathologies in both sporadic Alzheimer\u27s disease and autosomal-dominant Alzheimer\u27s disease, the latter of which is caused by mutations in genes involved in amyloid-beta processing. Despite amyloid-beta deposition being a centrepiece to both sporadic Alzheimer\u27s disease and autosomal-dominant Alzheimer\u27s disease, some differences between these Alzheimer\u27s disease subtypes have been observed with respect to the spatial pattern of amyloid-beta. Previous work has shown that the spatial pattern of amyloid-beta in individuals spanning the sporadic Alzheimer\u27s disease spectrum can be reproduced with high accuracy using an epidemic spreading model which simulates the diffusion of amyloid-beta across neuronal connections and is constrained by individual rates of amyloid-beta production and clearance. However, it has not been investigated whether amyloid-beta deposition in the rarer autosomal-dominant Alzheimer\u27s disease can be modelled in the same way, and if so, how congruent the spreading patterns of amyloid-beta across sporadic Alzheimer\u27s disease and autosomal-dominant Alzheimer\u27s disease are. We leverage the epidemic spreading model as a data-driven approach to probe individual-level variation in the spreading patterns of amyloid-beta across three different large-scale imaging datasets (2 sporadic Alzheimer\u27s disease, 1 autosomal-dominant Alzheimer\u27s disease). We applied the epidemic spreading model separately to the Alzheimer\u27s Disease Neuroimaging initiative (n = 737), the Open Access Series of Imaging Studies (n = 510) and the Dominantly Inherited Alzheimer\u27s Network (n = 249), the latter two of which were processed using an identical pipeline. We assessed inter-and intra-individual model performance in each dataset separately and further identified the most likely subject-specific epicentre of amyloid-beta spread. Using epicentres defined in previous work in sporadic Alzheimer\u27s disease, the epidemic spreading model provided moderate prediction of the regional pattern of amyloid-beta deposition across all three datasets. We further find that, whilst the most likely epicentre for most amyloid-beta-positive subjects overlaps with the default mode network, 13% of autosomal-dominant Alzheimer\u27s disease individuals were best characterized by a striatal origin of amyloid-beta spread. These subjects were also distinguished by being younger than autosomal-dominant Alzheimer\u27s disease subjects with a default mode network amyloid-beta origin, despite having a similar estimated age of symptom onset. Together, our results suggest that most autosomal-dominant Alzheimer\u27s disease patients express amyloid-beta spreading patterns similar to those of sporadic Alzheimer\u27s disease, but that there may be a subset of autosomal-dominant Alzheimer\u27s disease patients with a separate, striatal phenotype

Serum neurofilament dynamics predicts neurodegeneration and clinical progression in presymptomatic Alzheimer's disease

Neurofilament light chain (NfL) is a promising fluid biomarker of disease progression for various cerebral proteopathies. Here we leverage the unique characteristics of the Dominantly Inherited Alzheimer Network and ultrasensitive immunoassay technology to demonstrate that NfL levels in the cerebrospinal fluid (n = 187) and serum (n = 405) are correlated with one another and are elevated at the presymptomatic stages of familial Alzheimer's disease. Longitudinal, within-person analysis of serum NfL dynamics (n = 196) confirmed this elevation and further revealed that the rate of change of serum NfL could discriminate mutation carriers from non-mutation carriers almost a decade earlier than cross-sectional absolute NfL levels (that is, 16.2 versus 6.8 years before the estimated symptom onset). Serum NfL rate of change peaked in participants converting from the presymptomatic to the symptomatic stage and was associated with cortical thinning assessed by magnetic resonance imaging, but less so with amyloid-β deposition or glucose metabolism (assessed by positron emission tomography). Serum NfL was predictive for both the rate of cortical thinning and cognitive changes assessed by the Mini-Mental State Examination and Logical Memory test. Thus, NfL dynamics in serum predict disease progression and brain neurodegeneration at the early presymptomatic stages of familial Alzheimer's disease, which supports its potential utility as a clinically useful biomarker

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

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

Patterns and implications of neurological examination findings in autosomal dominant Alzheimer disease

Introduction: As knowledge about neurological examination findings in autosomal dominant Alzheimer disease (ADAD) is incomplete, we aimed to determine the frequency and significance of neurological examination findings in ADAD. Methods: Frequencies of neurological examination findings were compared between symptomatic mutation carriers and non mutation carriers from the Dominantly Inherited Alzheimer Network (DIAN) to define AD neurological examination findings. AD neurological examination findings were analyzed regarding frequency, association with and predictive value regarding cognitive decline, and association with brain atrophy in symptomatic mutation carriers. Results: AD neurological examination findings included abnormal deep tendon reflexes, gait disturbance, pathological cranial nerve examination findings, tremor, abnormal finger to nose and heel to shin testing, and compromised motor strength. The frequency of AD neurological examination findings was 65.1 %. Cross-sectionally, mutation carriers with AD neurological examination findings showed a more than two-fold faster cognitive decline and had greater parieto-temporal atrophy, including hippocampal atrophy. Longitudinally, AD neurological examination findings predicted a significantly greater decline over time. Discussion: ADAD features a distinct pattern of neurological examination findings that is useful to estimate prognosis and may inform clinical care and therapeutic trial designs

Positron emission tomography and magnetic resonance imaging methods and datasets within the dominantly inherited Alzheimer network (DIAN)

The Dominantly Inherited Alzheimer Network (DIAN) is an international collaboration studying autosomal dominant Alzheimer disease (ADAD). ADAD arises from mutations occurring in three genes. Offspring from ADAD families have a 50% chance of inheriting their familial mutation, so non-carrier siblings can be recruited for comparisons in case–control studies. The age of onset in ADAD is highly predictable within families, allowing researchers to estimate an individual’s point in the disease trajectory. These characteristics allow candidate AD biomarker measurements to be reliably mapped during the preclinical phase. Although ADAD represents a small proportion of AD cases, understanding neuroimaging-based changes that occur during the preclinical period may provide insight into early disease stages of ‘sporadic’ AD also. Additionally, this study provides rich data for research in healthy aging through inclusion of the non-carrier controls. Here we introduce the neuroimaging dataset collected and describe how this resource can be used by a range of researchers