Longitudinal cognitive and biomarker changes in dominantly inherited Alzheimer disease

McDade, Eric; Wang, Guoqiao; Gordon, Brian A.; Hassenstab, Jason; Benzinger, Tammie L.S.; Buckles, Virginia; Fagan, Anne M.; Holtzman, David M.; Cairns, Nigel J.; Goate, Alison; Marcus, Daniel S.; Morris, John C.; Paumier, Katrina L.; Allegri, Ricardo; Berman, Sarah B.; Klunk, William E.; Noble, James M.; Ringman, John M.; Ghetti, Bernardino; Farlow, Martin R.; Sperling, Reisa A.; Chhatwal, Jasmeer P.; Salloway, Stephen; Graff‐Radford, Neill R.; Schofield, Peter R.; Masters, Colin L.; Rossor, Martin N.; Fox, Nick C.; Xiong, Chengjie; Jucker, Mathias; Bateman, Randall J.

doi:10.1212/wnl.0000000000006277

Cited by 214 publications

(254 citation statements)

References 34 publications

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“…Findings to date from this PSEN1 E280A kindred generally support the prevailing models of AD pathogenesis and largely align with research from other ADAD groups, such as the Dominantly Inherited Alzheimer’s Network (DIAN), which suggest that CSF markers of amyloid-beta change earliest in the disease process, followed by decline in brain metabolism, and lastly by atrophy in memory-related brain structures (e.g., the hippocampus) which is closer to the age of onset of cognitive decline [54]. Reports from the Colombian kindred also generally align with studies of sporadic AD [55,56].…”

Section: Discussionmentioning

confidence: 54%

Biological and Cognitive Markers of Presenilin1 E280a Autosomal Dominant Alzheimer’s Disease: A Comprehensive Review of the Colombian Kindred

et al. 2019

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The study of individuals with autosomal dominant Alzheimer’s disease affords one of the best opportunities to characterize the biological and cognitive changes of Alzheimer’s disease that occur over the course of the preclinical and symptomatic stages. Unifying the knowledge gained from the past three decades of research in the world’s largest single-mutation autosomal dominant Alzheimer’s disease kindred — a family in Antioquia, Colombia with the E280A mutation in the Presenilin1 gene — will provide new directions for Alzheimer’s research and a framework for generalizing the findings from this cohort to the more common sporadic form of Alzheimer’s disease. As this specific mutation is virtually 100% penetrant for the development of the disease by midlife, we use a previously defined median age of onset for mild cognitive impairment for this cohort to examine the trajectory of the biological and cognitive markers of the disease as a function of the carriers’ estimated years to clinical onset. Studies from this cohort suggest that structural and functional brain abnormalities — such as cortical thinning and hyperactivation in memory networks — as well as differences in biofluid and in vivo measurements of Alzheimer’s-related pathological proteins distinguish Presenilin1 E280A mutation carriers from non-carriers as early as childhood, or approximately three decades before the median age of onset of clinical symptoms. We conclude our review with discussion on future directions for Alzheimer’s disease research, with specific emphasis on ways to design studies that compare the generalizability of research in autosomal dominant Alzheimer’s disease to the larger sporadic Alzheimer’s disease population.

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Section: Discussionmentioning

confidence: 54%

Biological and Cognitive Markers of Presenilin1 E280a Autosomal Dominant Alzheimer’s Disease: A Comprehensive Review of the Colombian Kindred

et al. 2019

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“…Third, we trained the model on EYO in ADAD, which is only a cross‐sectional proxy of future cognitive decline 27 . Computing actual cognitive decline in ADAD would have drastically reduced the sample size to those with available longitudinal cognitive data.…”

Section: Discussionmentioning

confidence: 99%

“…the emergence of cognitive symptoms in ADAD is driven by AD pathology rather than age-related comorbidities, and thus, provides a good model for AD-related cognitive decline. 27,42 The most predictive features in amyloid-PET included almost the entire neocortex, sparing primary sensorimotor, and medial temporal regions that develop amyloid very late in AD. 43,44 Further, predictive regions included posterior parietal and medial temporal regions for MRI and posterior parietal and lateral frontal regions for FDG-PET, that is, AD-typical predilection sites.…”

Section: Discussionmentioning

confidence: 99%

“…ADAD constitutes a unique training sample as the disease onset is at a relatively young age and the development of AD pathology and cognitive decline are not confounded by age‐related comorbidities (eg, TDP‐43, small‐vessel disease) 26 . Because in ADAD the time course of the development of dementia symptoms is strongly genetically driven, EYO can be used as a surrogate marker of AD‐related cognitive decline 27–29 . Here, we first trained biomarker‐based machine‐learning models for predicting EYO in ADAD.…”

Section: Introductionmentioning

confidence: 99%

“…26 Because in ADAD the time course of the development of dementia symptoms is strongly genetically driven, EYO can be used as a surrogate marker of AD-related cognitive decline. [27][28][29] Here, we first trained biomarker-based machinelearning models for predicting EYO in ADAD. After model training and…”

Section: Introductionmentioning

confidence: 99%

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Predicting sporadic Alzheimer's disease progression via inherited Alzheimer's disease‐informed machine‐learning

Franzmeier

Koutsouleris

Benzinger

et al. 2020

Alzheimer's & Dementia

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Introduction Developing cross‐validated multi‐biomarker models for the prediction of the rate of cognitive decline in Alzheimer's disease (AD) is a critical yet unmet clinical challenge. Methods We applied support vector regression to AD biomarkers derived from cerebrospinal fluid, structural magnetic resonance imaging (MRI), amyloid‐PET and fluorodeoxyglucose positron‐emission tomography (FDG‐PET) to predict rates of cognitive decline. Prediction models were trained in autosomal‐dominant Alzheimer's disease (ADAD, n = 121) and subsequently cross‐validated in sporadic prodromal AD (n = 216). The sample size needed to detect treatment effects when using model‐based risk enrichment was estimated. Results A model combining all biomarker modalities and established in ADAD predicted the 4‐year rate of decline in global cognition (R2 = 24%) and memory (R2 = 25%) in sporadic AD. Model‐based risk‐enrichment reduced the sample size required for detecting simulated intervention effects by 50%–75%. Discussion Our independently validated machine‐learning model predicted cognitive decline in sporadic prodromal AD and may substantially reduce sample size needed in clinical trials in AD.

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Association of Longitudinal Changes in Cerebrospinal Fluid Total Tau and Phosphorylated Tau 181 and Brain Atrophy With Disease Progression in Patients With Alzheimer Disease

Llibre‐Guerra

Schindler

et al. 2019

JAMA Netw Open

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IMPORTANCE The amyloid/tau/neurodegeneration (A/T/N) framework uses cerebrospinal fluid (CSF) levels of total tau (tTau) as a marker of neurodegeneration and CSF levels of phosphorylated tau 181 (pTau181) as a marker of tau tangles. However, it is unclear whether CSF levels of tTau and pTau181 have similar or different trajectories over the course of Alzheimer disease. OBJECTIVES To examine the rates of change in CSF levels of tTau and pTau181 across the Alzheimer disease course and how the rates of change are associated with brain atrophy as measured by magnetic resonance imaging. DESIGN, SETTING, AND PARTICIPANTS This cohort study was set in tertiary research clinics. Each participant was a member of a pedigree with a known mutation for dominantly inherited Alzheimer disease. Participants were divided into 3 groups on the basis of the presence of a mutation and their Clinical Dementia Rating score. Data analysis was performed in June 2019. MAIN OUTCOMES AND MEASURES Rates of change of CSF tTau and pTau181 levels and their association with the rate of change of brain volume. RESULTS Data from 465 participants (283 mutation carriers and 182 noncarriers) were analyzed. The mean (SD) age of the cohort was 37.8 (11.3) years, and 262 (56.3%) were women. The mean (SD) follow-up duration was 2.7 (1.5) years. Two or more longitudinal CSF and magnetic resonance imaging assessments were available for 160 and 247 participants, respectively. Sixty-five percent of mutation carriers (183) did not have symptoms at baseline (Clinical Dementia Rating score, 0). For mutation carriers, the annual rates of change for CSF tTau and pTau181 became significantly different from 0 approximately 10 years before the estimated year of onset (mean [SE] rates of change, 5.5 [2.8] for tTau [P = .05] and 0.7 [0.3] for pTau 181 [P = .04]) and 15 years before onset (mean [SE] rates of change, 5.4 [3.9] for tTau [P = .17] and 1.1 [0.5] for pTau181 [P = .03]), respectively. The rate of change of pTau181 was positive and increased at the early stages of the disease, showing a positive rate of change starting at 15 estimated years before onset until 5 estimated years before onset (mean [SE], 0.4 [0.3]), followed by a positive but decreasing rate of change at year 0 (mean [SE], 0.1 [0.3]) and then negative rates of change at 5 years (mean [SE], −0.3 [0.4]) and 10 years (mean [SE], −0.6 [0.6]) after symptom onset. In individuals without symptoms (Clinical Dementia Rating score, 0), the rates of change of CSF tTau and pTau181 were negatively associated with brain atrophy (high rates of change in CSF measures were associated with low rates of change in brain volume in asymptomatic stages). After symptom onset (Clinical Dementia Rating score, >0), an increased rate of brain atrophy was not associated with rates of change of levels of both CSF tTau and pTau181. (continued) Key Points Question How do different proposed measurements of tau brain pathologic abnormalities (ie, levels of phosphorylated tau 181 in the cerebrospinal fluid [CSF]) and neurodegenera...

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Longitudinal cognitive and biomarker changes in dominantly inherited Alzheimer disease

Cited by 214 publications

References 34 publications

Biological and Cognitive Markers of Presenilin1 E280a Autosomal Dominant Alzheimer’s Disease: A Comprehensive Review of the Colombian Kindred

Biological and Cognitive Markers of Presenilin1 E280a Autosomal Dominant Alzheimer’s Disease: A Comprehensive Review of the Colombian Kindred

Predicting sporadic Alzheimer's disease progression via inherited Alzheimer's disease‐informed machine‐learning

Association of Longitudinal Changes in Cerebrospinal Fluid Total Tau and Phosphorylated Tau 181 and Brain Atrophy With Disease Progression in Patients With Alzheimer Disease

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