Alzheimer's disease: The next frontier—Special Report 2017

Karlawish, Jason; Jack, Clifford R.; Rocca, Walter A.; Snyder, Heather M.; Carrillo, María C.

doi:10.1016/j.jalz.2017.02.006

Cited by 93 publications

(56 citation statements)

References 61 publications

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“…Results are the mean ± SD of spines measured from 13 different neurons. One-way ANOVA (effector: treatment) with a F (1,26) mouse astrocytes (SI Appendix, Fig. S2B).…”

Section: Resultsmentioning

confidence: 99%

“…These findings highlight a property of aspirin: stimulating hippocampal plasticity via direct interaction with PPARα. aspirin | PPARα | plasticity | memory and learning A lzheimer's disease (AD) is the predominantly fatal form of dementia that affects up to 1 in 10 American age 65 y and older (1). In 2017, total annual primary care payments for individuals living with AD or other dementias in the United States was estimated at approximately $259 billion, and this is expected to rise to $1.1 trillion by 2050 (2).…”

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confidence: 99%

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Aspirin binds to PPARα to stimulate hippocampal plasticity and protect memory

Patel

Roy

Kundu

et al. 2018

Proc. Natl. Acad. Sci. U.S.A.

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Despite its long history, until now, no receptor has been identified for aspirin, one of the most widely used medicines worldwide. Here we report that peroxisome proliferator-activated receptor alpha (PPARα), a nuclear hormone receptor involved in fatty acid metabolism, serves as a receptor of aspirin. Detailed proteomic analyses including cheminformatics, thermal shift assays, and TR-FRET revealed that aspirin, but not other structural homologs, acts as a PPARα ligand through direct binding at the Tyr314 residue of the PPARα ligand-binding domain. On binding to PPARα, aspirin stimulated hippocampal plasticity via transcriptional activation of cAMP response element-binding protein (CREB). Finally, hippocampus-dependent behavioral analyses, calcium influx assays in hippocampal slices and quantification of dendritic spines demonstrated that low-dose aspirin treatment improved hippocampal plasticity and memory in FAD5X mice, but not in FAD5X/-null mice. These findings highlight a property of aspirin: stimulating hippocampal plasticity via direct interaction with PPARα.

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“…Results are the mean ± SD of spines measured from 13 different neurons. One-way ANOVA (effector: treatment) with a F (1,26) mouse astrocytes (SI Appendix, Fig. S2B).…”

Section: Resultsmentioning

confidence: 99%

mentioning

confidence: 99%

Aspirin binds to PPARα to stimulate hippocampal plasticity and protect memory

Patel

Roy

Kundu

et al. 2018

Proc. Natl. Acad. Sci. U.S.A.

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“…As a cause for Alzheimer's disease, neuronal death correlated with aggregated proteins has previously been suspected [1]. The finding of an effective pharmacological treatment for cognitive impairment and the development of biomarkers are top research priorities [1,2].…”

Section: Introductionmentioning

confidence: 99%

Spermidine in dementia

Pekar

Wendzel²,

Flak³

et al. 2019

Wien Klin Wochenschr

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Previous studies have highlighted that spermidine has the ability to trigger the important process of dissolving amyloid-beta plaques by autophagy. This manuscript focuses on the correlation of serum spermidine levels between age and between performance in mini-mental state examinations. It will serve as a premise for an ongoing multicentric placebo-controlled study, which focuses on the effect of oral spermidine supplementation on memory performance. Memory tests were carried out on 80 subjects aged 60-96 years old in 6 nursing homes in Styria. Blood samples were taken for the determination of spermidine concentration. The results showed a significant correlation between the spermidine concentration and the mini-mental state

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“…One would use L-GoM to determine expected progression in drug and placebo groups in clinical trials evaluating the effectiveness of randomization prior to the trial and comparing modeled vs. actual progression in the drug group after the trial [ 47 ]. Alternatively, L-GoM could be used to explore how the clinical symptoms/signs captured by it correlate with measured AD biomarkers, such as by testing concurrent and lagged associations of biomarkers and time-varying GoM scores, associations that could elucidate the connections between DFLE/DLE and the neuropathology of AD [ 48 , 49 ]. With such applications, the model and its results have the potential to stimulate rapid progress in the fight against AD.…”

Section: Discussionmentioning

confidence: 99%

Personalized predictive modeling for patients with Alzheimer’s disease using an extension of Sullivan’s life table model

2017

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BackgroundAlzheimer’s disease (AD) progression varies substantially among patients, hindering calculation of residual total life expectancy (TLE) and its decomposition into disability-free life expectancy (DFLE) and disabled life expectancy (DLE) for individual patients with AD. The objective of the present study was to assess the accuracy of a new synthesis of Sullivan’s life table (SLT) and longitudinal Grade of Membership (L-GoM) models that estimates individualized TLEs, DFLEs, and DLEs for patients with AD. If sufficiently accurate, such information could enhance the quality of important decisions in AD treatment and patient care.MethodsWe estimated a new SLT/L-GoM model of the natural history of AD over 10 years in the Predictors 2 Study cohort: N = 229 with 6 fixed and 73 time-varying covariates over 21 examinations covering 11 measurement domains including cognitive, functional, behavioral, psychiatric, and other symptoms/signs. Total remaining life expectancy was censored at 10 years. Disability was defined as need for full-time care (FTC), the outcome most strongly associated with AD progression. All parameters were estimated via weighted maximum likelihood using data-dependent weights designed to ensure that the estimates of the prognostic subtypes were of high quality. Goodness of fit was tested/confirmed for survival and FTC disability for five relatively homogeneous subgroups defined to cover the range of patient outcomes over the 21 examinations.ResultsThe substantial heterogeneity in initial patient presentation and AD progression was captured using three clinically meaningful prognostic subtypes and one terminal subtype exhibiting highly differentiated symptom severity on 7 of the 11 measurement domains. Comparisons of the observed and estimated survival and FTC disability probabilities demonstrated that the estimates were accurate for all five subgroups, supporting their use in AD life expectancy calculations. Mean 10-year TLE differed widely across subgroups: range 3.6–8.0 years, average 6.1 years. Mean 10-year DFLE differed relatively even more widely across subgroups: range 1.2–6.5 years, average 4.0 years. Mean 10-year DLE was relatively much closer: range 1.5–2.3 years, average 2.1 years.ConclusionsThe SLT/L-GoM model yields accurate maximum likelihood estimates of TLE, DFLE, and DLE for patients with AD; it provides a realistic, comprehensive modeling framework for endpoint and resource use/cost calculations.Electronic supplementary materialThe online version of this article (doi:10.1186/s13195-017-0302-6) contains supplementary material, which is available to authorized users.

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Alzheimer's disease: The next frontier—Special Report 2017

Cited by 93 publications

References 61 publications

Aspirin binds to PPARα to stimulate hippocampal plasticity and protect memory

Aspirin binds to PPARα to stimulate hippocampal plasticity and protect memory

Spermidine in dementia

Personalized predictive modeling for patients with Alzheimer’s disease using an extension of Sullivan’s life table model

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