Journal of Alzheimer's Disease - Volume 50, issue 1

Authors: Quintana-Hernández, Domingo J. | Miró-Barrachina, María T. | Ibáñez-Fernández, Ignacio J. | Pino, Angelo Santana-del | Quintana-Montesdeoca, María P. | Rodríguez-de Vera, Bienvenida | Morales-Casanova, David | Pérez-Vieitez, María del Carmen | Rodríguez-García, Javier | Bravo-Caraduje, Noelia

Article Type: Research Article

Abstract: Background: The Canary Islands longitudinal study on non-pharmacological treatments showed the overall effectiveness of mindfulness in Alzheimer’s disease (AD). However, no specific data on the maintenance of cognitive capacities were presented. Objective: To determine whether the practice of mindfulness modifies the course of cognitive impairment in AD. Methods: Design: Longitudinal, non-inferiority and equivalence, randomized clinical trial, repeated-measures design, with three experimental groups and one control group. Participants: Patients with AD who voluntarily attended the Lidia García Foundation (n  = 502). Only those who were treated with donepezil and MMSE ≥18 were included (n  = 120). Intervention: Over a …two-year period, each group carried out three weekly sessions of stimulation based on mindfulness, cognitive stimulation therapy, and progressive muscle relaxation. Measures: Cognitive assessment CAMDEX-R (MMSE and CAMCOG). Statistical analysis: Repeated-measures ANOVA (p  <  0.05) and the effect size Cohen’s d were performed. Results: The mindfulness group showed significant scores compared with the control and muscle relaxation groups (p  <  0.05), while mindfulness and cognitive stimulation therapy were equivalent (p ≥0.05). Group cognitive stimulation evolved better than the control (p  <  0.05) group but not better than the muscle relaxation group (p ≥0.05). The effect size compared over two years was large for the mindfulness group (p ≥0.80), moderate for the relaxation group (p ≥0.50), and low for the cognitive stimulation group (p ≥0.20). Conclusion: The practice of mindfulness maintained cognitive function over a period of two years. This longitudinal study suggests that mindfulness can be used as a non-pharmacological treatment to slow cognitive impairment in AD. Show more

Keywords: Alzheimer’s disease, cognitive impairment, cognitive stimulation therapy, mindfulness, non-pharmacological treatments, progressive muscle relaxation

DOI: 10.3233/JAD-143009

Citation: Journal of Alzheimer's Disease, vol. 50, no. 1, pp. 217-232, 2016

Authors: Wang, Shuihua | Zhang, Yudong | Liu, Ge | Phillips, Preetha | Yuan, Ti-Fei

Article Type: Research Article

Abstract: Background: Within the past decade, computer scientists have developed many methods using computer vision and machine learning techniques to detect Alzheimer’s disease (AD) in its early stages. Objective: However, some of these methods are unable to achieve excellent detection accuracy, and several other methods are unable to locate AD-related regions. Hence, our goal was to develop a novel AD brain detection method. Methods: In this study, our method was based on the three-dimensional (3D) displacement-field (DF) estimation between subjects in the healthy elder control group and AD group. The 3D-DF was treated with AD-related features. The …three feature selection measures were used in the Bhattacharyya distance, Student’s t -test, and Welch’s t -test (WTT). Two non-parallel support vector machines, i.e., generalized eigenvalue proximal support vector machine and twin support vector machine (TSVM), were then used for classification. A 50 × 10-fold cross validation was implemented for statistical analysis. Results: The results showed that “3D-DF+WTT+TSVM” achieved the best performance, with an accuracy of 93.05 ± 2.18, a sensitivity of 92.57 ± 3.80, a specificity of 93.18 ± 3.35, and a precision of 79.51 ± 2.86. This method also exceled in 13 state-of-the-art approaches. Additionally, we were able to detect 17 regions related to AD by using the pure computer-vision technique. These regions include sub-gyral, inferior parietal lobule, precuneus, angular gyrus, lingual gyrus, supramarginal gyrus, postcentral gyrus, third ventricle, superior parietal lobule, thalamus, middle temporal gyrus, precentral gyrus, superior temporal gyrus, superior occipital gyrus, cingulate gyrus, culmen, and insula. These regions were reported in recent publications. Conclusions: The 3D-DF is effective in AD subject and related region detection. Show more

Keywords: Alzheimer’s disease, computer vision, displacement field, generalized eigenvalue proximal support vector machine, machine learning, magnetic resonance imaging, pattern recognition, twin support vector machine

DOI: 10.3233/JAD-150848

Citation: Journal of Alzheimer's Disease, vol. 50, no. 1, pp. 233-248, 2016

Authors: Malishkevich, Anna | Marshall, Gad A. | Schultz, Aaron P. | Sperling, Reisa A. | Aharon-Peretz, Judith | Gozes, Illana

Article Type: Research Article

Abstract: Biomarkers for Alzheimer’s disease (AD) are vital for disease detection in the clinical setting. Discovered in our laboratory, activity-dependent neuroprotective protein (ADNP) is essential for brain formation and linked to cognitive functions. Here, we revealed that blood borne expression of ADNP and its paralog ADNP2 is correlated with premorbid intelligence, AD pathology, and clinical stage. Age adjustment showed significant associations between: 1) higher premorbid intelligence and greater serum ADNP, and 2) greater cortical amyloid and lower ADNP and ADNP2 mRNAs. Significant increases in ADNP mRNA levels were observed in patients ranging from mild cognitive impairment (MCI) to AD dementia. ADNP2 …transcripts showed high correlation with ADNP transcripts, especially in AD dementia lymphocytes. ADNP plasma/serum and lymphocyte mRNA levels discriminated well between cognitively normal elderly, MCI, and AD dementia participants. Measuring ADNP blood-borne levels could bring us a step closer to effectively screening and tracking AD. Show more

Keywords: Activity-dependent neuroprotective protein (ADNP), Alzheimer’s disease, amyloid-beta, blood-borne biomarkers, cognitively normal, mild cognitive impairment, premorbid intelligence

DOI: 10.3233/JAD-150799

Citation: Journal of Alzheimer's Disease, vol. 50, no. 1, pp. 249-260, 2016

Authors: Rhodius-Meester, Hanneke F.M. | Koikkalainen, Juha | Mattila, Jussi | Teunissen, Charlotte E. | Barkhof, Frederik | Lemstra, Afina W. | Scheltens, Philip | Lötjönen, Jyrki | van der Flier, Wiesje M.

Article Type: Research Article

Abstract: Background: Recent criteria allow biomarkers to provide evidence of Alzheimer’s disease (AD) pathophysiology. How they should be implemented in daily practice remains unclear, especially in mild cognitive impairment (MCI) patients. Objective: We evaluated how a clinical decision support system such as the PredictAD tool can aid clinicians to integrate biomarker evidence to support AD diagnosis. Methods: With available data on demographics, cerebrospinal fluid (CSF), and MRI, we trained the PredictAD tool on a reference population of 246 controls and 491 AD patients. We then applied the identified algorithm to 211 MCI patients. For comparison, we also …classified patients based on individual biomarkers (MRI; CSF) and the NIA-AA criteria. Progression to dementia was used as outcome measure. Results: After a median follow up of 3 years, 72 (34%) MCI patients remained stable and 139 (66%) progressed to AD. The PredictAD tool assigned a likelihood of underlying AD to each patient (AUC 0.82). Excluding patients with missing data resulted in an AUC of 0.87. According to the NIA-AA criteria, half of the MCI patients had uninformative biomarkers, precluding an assignment of AD likelihood. A minority (41%) was assigned to high or low AD likelihood with good predictive value. The individual biomarkers showed best value for CSF total tau (AUC 0.86). Conclusion: The ability of the PredictAD tool to identify AD pathophysiology was comparable to individual biomarkers. The PredictAD tool has the advantage that it assigns likelihood to all patients, regardless of missing or conflicting data, allowing clinicians to integrate biomarker data in daily practice. Show more

Keywords: KeywordsAlzheimer’s disease, clinical decision support system, diagnostic test assessment, mild cognitive impairment, prognosis

DOI: 10.3233/JAD-150548

Citation: Journal of Alzheimer's Disease, vol. 50, no. 1, pp. 261-270, 2016

Authors: Hochstetler, Helen | Trzepacz, Paula T. | Wang, Shufang | Yu, Peng | Case, Michael | Henley, David B. | Degenhardt, Elisabeth | Leoutsakos, Jeannie-Marie | Lyketsos, Constantine G.

Article Type: Research Article

Abstract: Background: Alzheimer’s disease (AD) is associated with variable cognitive and functional decline, and it is difficult to predict who will develop the disease and how they will progress. Objective: This exploratory study aimed to define latent classes from participants in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database who had similar growth patterns of both cognitive and functional change using Growth Mixture Modeling (GMM), identify characteristics associated with those trajectories, and develop a decision tree using clinical predictors to determine which trajectory, as determined by GMM, individuals will most likely follow. Methods: We used ADNI early mild …cognitive impairment (EMCI), late MCI (LMCI), AD dementia, and healthy control (HC) participants with known amyloid-β status and follow-up assessments on the Alzheimer’s Disease Assessment Scale - Cognitive Subscale or the Functional Activities Questionnaire (FAQ) up to 24 months postbaseline. GMM defined trajectories. Classification and Regression Tree (CART) used certain baseline variables to predict likely trajectory path. Results: GMM identified three trajectory classes (C): C1 (n  = 162, 13.6%) highest baseline impairment and steepest pattern of cognitive/functional decline; C3 (n  = 819, 68.7%) lowest baseline impairment and minimal change on both; C2 (n  = 211, 17.7%) intermediate pattern, worsening on both, but less steep than C1. C3 had fewer amyloid- or apolipoprotein-E ɛ 4 (APOE4) positive and more healthy controls (HC) or EMCI cases. CART analysis identified two decision nodes using the FAQ to predict likely class with 82.3% estimated accuracy. Conclusions: Cognitive/functional change followed three trajectories with greater baseline impairment and amyloid and APOE4 positivity associated with greater progression. FAQ may predict trajectory class. Show more

Keywords: Alzheimer’s disease, disease progression, amyloid, longitudinal studies, ADNI, function, cognition, MCI

DOI: 10.3233/JAD-150563

Citation: Journal of Alzheimer's Disease, vol. 50, no. 1, pp. 271-282, 2016

Authors: Fischer, Corinne E. | Qian, Winnie | Schweizer, Tom A. | Millikin, Colleen P. | Ismail, Zahinoor | Smith, Eric E. | Lix, Lisa M. | Shelton, Paul | Munoz, David G.

Article Type: Research Article

Abstract: Background: The neuropathological correlates of psychosis in Alzheimer’s disease (AD) is unclear, with some studies reporting a correlation between psychosis and increased AD pathology while others have found no association. Objective: To determine the demographic, clinical, and neuropathological features associated with psychotic symptoms in clinically attributed and neuropathologically proven AD. Method: We separately reviewed two overlapping groups of clinically diagnosed (cAD) AD patients with neuropathology data and neuropathologically definite (npAD) cases (regardless of clinical diagnosis) from the NACC database, and explored the relationships between psychosis and clinical variables, neuropathologic correlates, and vascular risk factors. Delusions and …hallucinations, defined according to the NPI-Q, were analyzed separately. Results: 1,073 subjects in the database fulfilled our criteria (890 cAD and 728 npAD patients). 34% of cAD and 37% of npAD had psychotic symptoms during their illness. Hallucinations were associated with greater cognitive and functional impairments on the MMSE and CDR, while delusional patients showed less impairment on CDR, consistent across cAD and npAD groups. Burden of AD pathology appears to relate to presence of psychotic symptoms in the clinical AD group, but this result is not confirmed in the neuropathologically confirmed group suggesting the findings in the clinical group were due to misdiagnosis of AD. Lewy body pathology, subcortical arteriosclerotic leukoencephalopathy, and vascular risk factors, including a history of hypertension and diabetes, were associated with the development of psychosis. Method: Vascular and Lewy body pathologies and vascular risk factors are important modifiers of the risk of psychosis in AD. Show more

Keywords: Alzheimer’s disease, arteriosclerotic leukoencephalopathy, delusion, hallucination, neuropathology, psychosis, vascular pathology

DOI: 10.3233/JAD-150606

Citation: Journal of Alzheimer's Disease, vol. 50, no. 1, pp. 283-295, 2016

Article Type: Other

DOI: 10.3233/JAD-151014

Citation: Journal of Alzheimer's Disease, vol. 50, no. 1, pp. 297-300, 2016