scholarly journals Precision Medicine Approach to Alzheimer's Disease: Successful Proof-of-Concept Trial

Author(s):  
Kat Toups ◽  
Ann Hathaway ◽  
Deborah Gordon ◽  
Henrianna Chung ◽  
Cyrus Raji ◽  
...  

Abstract Importance: Effective therapeutics for Alzheimer's disease and mild cognitive impairment are needed. Objective: To determine whether a precision medicine approach to Alzheimer's disease and mild cognitive impairment, in which potential contributors to cognitive decline are identified and targeted therapeutically, is effective enough in a proof-of-concept trial to warrant a larger, randomized, controlled clinical trial. Rationale: Previous clinical trials for Alzheimer's disease have pre-determined a single treatment modality, such as a drug candidate or therapeutic procedure, that may be unrelated to the primary drivers of the neurodegenerative process. Therefore, increasing data set size to include the potential contributors to cognitive decline for each patient, and addressing the identified potential contributors, may represent a more effective therapeutic strategy. Hypothesis: Alzheimer's disease is a multi-factorial network dysfunction that results from a chronic or repeated insufficiency of support for a neuroplasticity network; thus factors that increase demand — such as infections or toxin exposure — or reduce support — such as reduced energetics or trophic support — may contribute to the neurodegenerative process. Rectifying this hypothesized network dysfunction represents a rational approach to the treatment of the cognitive decline associated with Alzheimer's disease and mild cognitive impairment. Design: Twenty-five patients with Alzheimer's disease or mild cognitive impairment, with Montreal Cognitive Assessment (MoCA) scores of 19 or higher, were evaluated for markers of inflammation, chronic infection, dysbiosis, insulin resistance, protein glycation, vascular disease, nocturnal hypoxemia, hormone insufficiency or dysregulation, nutrient deficiency, toxin or toxicant exposure (metals, organic toxicants, and biotoxins), genetic predisposition to cognitive decline, and other biochemical parameters associated with cognitive decline. Brain magnetic resonance imaging with volumetrics was performed at baseline and study conclusion. Patients were treated for nine months with a personalized, precision medicine protocol that addressed each patient's identified potentially contributory factors, and cognition was assessed at t = 0, 3, 6, and 9 months. Trial registration and IRB approval: The clinical trial was registered at clinicaltrials.gov (NCT03883633), 1 and approved by the Advarra IRB. Support for the trial: The trial was supported by a grant from the Four Winds Foundation via Evanthea, LLC, and we are grateful to Diana Merriam and Gayle Brown for their interest, discussions, and support. Main Outcome Measures: Trained external raters evaluated the study subjects with the Montreal Cognitive Assessment (MoCA), CNS Vital Signs (a computerized cognitive assessment battery), AQ-21 (a subjective scale completed by the significant other or study partner), and AQ-C change scale (a subjective scale of cognitive improvement or decline, completed by the significant other or study partner). Follow-up brain MRI with volumetrics was carried out at the completion of the trial. Results: All outcome measures revealed improvement: statistically highly significant improvement in MoCA scores, CNS Vital Signs Neurocognitive Index, and AQ-C were documented. No serious adverse events were recorded. Conclusions and Relevance: Based on the cognitive improvements observed in this study of patients with Alzheimer's disease or mild cognitive impairment, a larger, randomized, controlled trial of the precision medicine therapeutic approach described herein is warranted.

2014 ◽  
Vol 8 (2) ◽  
pp. 112-116 ◽  
Author(s):  
Maira Okada de Oliveira ◽  
Sonia Maria Dozzi Brucki

ABSTRACT Currently, computerized batteries are of great value in detecting cognitive impairment. This aim of this review was to compare the computerized neurocognitive batteries used in most studies with cognitive decline over the last 10 years. Using the search words computerized cognitive assessment with: dementia, mild cognitive impairment, and Alzheimer's disease, the CogState, CNS Vital Sings, COGDRAS and Mindstreams batteries were retrieved.


2018 ◽  
Vol 15 (3) ◽  
pp. 219-228 ◽  
Author(s):  
Jiri Cerman ◽  
Ross Andel ◽  
Jan Laczo ◽  
Martin Vyhnalek ◽  
Zuzana Nedelska ◽  
...  

Background: Great effort has been put into developing simple and feasible tools capable to detect Alzheimer's disease (AD) in its early clinical stage. Spatial navigation impairment occurs very early in AD and is detectable even in the stage of mild cognitive impairment (MCI). Objective: The aim was to describe the frequency of self-reported spatial navigation complaints in patients with subjective cognitive decline (SCD), amnestic and non-amnestic MCI (aMCI, naMCI) and AD dementia and to assess whether a simple questionnaire based on these complaints may be used to detect early AD. Method: In total 184 subjects: patients with aMCI (n=61), naMCI (n=27), SCD (n=63), dementia due to AD (n=20) and normal controls (n=13) were recruited. The subjects underwent neuropsychological examination and were administered a questionnaire addressing spatial navigation complaints. Responses to the 15 items questionnaire were scaled into four categories (no, minor, moderate and major complaints). Results: 55% of patients with aMCI, 64% with naMCI, 68% with SCD and 72% with AD complained about their spatial navigation. 38-61% of these complaints were moderate or major. Only 33% normal controls expressed complaints and none was ranked as moderate or major. The SCD, aMCI and AD dementia patients were more likely to express complaints than normal controls (p's<0.050) after adjusting for age, education, sex, depressive symptoms (OR for SCD=4.00, aMCI=3.90, AD dementia=7.02) or anxiety (OR for SCD=3.59, aMCI=3.64, AD dementia=6.41). Conclusion: Spatial navigation complaints are a frequent symptom not only in AD, but also in SCD and aMCI and can potentially be detected by a simple and inexpensive questionnaire.


2021 ◽  
Author(s):  
Noel Valencia ◽  
Johann Lehrner

Summary Background Visuo-Constructive functions have considerable potential for the early diagnosis and monitoring of disease progression in Alzheimer’s disease. Objectives Using the Vienna Visuo-Constructional Test 3.0 (VVT 3.0), we measured visuo-constructive functions in subjective cognitive decline (SCD), mild cognitive impairment (MCI), Alzheimer’s disease (AD), and healthy controls to determine whether VVT performance can be used to distinguish these groups. Materials and methods Data of 671 participants was analyzed comparing scores across diagnostic groups and exploring associations with relevant clinical variables. Predictive validity was assessed using Receiver Operator Characteristic curves and multinomial logistic regression analysis. Results We found significant differences between AD and the other groups. Identification of cases suffering from visuo-constructive impairment was possible using VVT scores, but these did not permit classification into diagnostic subgroups. Conclusions In summary, VVT scores are useful indicators for visuo-constructive impairment but face challenges when attempting to discriminate between several diagnostic groups.


2017 ◽  
Vol 29 (6) ◽  
pp. 1105-1111 ◽  
Author(s):  
Mehmet Yuruyen ◽  
Fundan Engin Akcan ◽  
Gizem Cetiner Batun ◽  
Gozde Gultekin ◽  
Mesut Toprak ◽  
...  

2016 ◽  
Vol 10 (3) ◽  
pp. 170-177 ◽  
Author(s):  
Adalberto Studart Neto ◽  
Ricardo Nitrini

ABSTRACT Background: Mild cognitive impairment is considered as the first clinical manifestation of Alzheimer's disease (AD), when the individual exhibits below performance on standardized neuropsychological tests. However, some subjects before having a lower performance on cognitive assessments already have a subjective memory complaint. Objective: A review about subjective cognitive decline, the association with AD biomarkers and risk of conversion to dementia. Methods: We performed a comprehensive non-systematic review on PubMed. The keywords used in the search were terms related to subjective cognitive decline. Results: Subjective cognitive decline is characterized by self-experience of deterioration in cognitive performance not detected objectively through formal neuropsychological testing. However, various terms and definitions have been used in the literature and the lack of a widely accepted concept hampers comparison of studies. Epidemiological data have shown that individuals with subjective cognitive decline are at increased risk of progression to AD dementia. In addition, there is evidence that this group has a higher prevalence of positive biomarkers for amyloidosis and neurodegeneration. However, Alzheimer's disease is not the only cause of subjective cognitive decline and various other conditions can be associated with subjective memory complaints, such as psychiatric disorders or normal aging. The features suggestive of a neurodegenerative disorder are: onset of decline within the last five years, age at onset above 60 years, associated concerns about decline and confirmation by an informant. Conclusion: These findings support the idea that subjective cognitive complaints may be an early clinical marker that precedes mild cognitive impairment due to Alzheimer's disease.


2017 ◽  
Vol 28 (7) ◽  
pp. 2112-2124 ◽  
Author(s):  
Kai Kang ◽  
Jingheng Cai ◽  
Xinyuan Song ◽  
Hongtu Zhu

Alzheimer’s disease is a firmly incurable and progressive disease. The pathology of Alzheimer’s disease usually evolves from cognitive normal, to mild cognitive impairment, to Alzheimer’s disease. The aim of this paper is to develop a Bayesian hidden Markov model to characterize disease pathology, identify hidden states corresponding to the diagnosed stages of cognitive decline, and examine the dynamic changes of potential risk factors associated with the cognitive normal–mild cognitive impairment–Alzheimer’s disease transition. The hidden Markov model framework consists of two major components. The first one is a state-dependent semiparametric regression for delineating the complex associations between clinical outcomes of interest and a set of prognostic biomarkers across neurodegenerative states. The second one is a parametric transition model, while accounting for potential covariate effects on the cross-state transition. The inter-individual and inter-process differences are taken into account via correlated random effects in both components. Based on the Alzheimer’s Disease Neuroimaging Initiative data set, we are able to identify four states of Alzheimer’s disease pathology, corresponding to common diagnosed cognitive decline stages, including cognitive normal, early mild cognitive impairment, late mild cognitive impairment, and Alzheimer’s disease and examine the effects of hippocampus, age, gender, and APOE-[Formula: see text] on degeneration of cognitive function across the four cognitive states.


2009 ◽  
Vol 17 (4) ◽  
pp. 761-772 ◽  
Author(s):  
Flavio Nobili ◽  
Fabrizio De Carli ◽  
Giovanni B. Frisoni ◽  
Florence Portet ◽  
Frans Verhey ◽  
...  

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