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      Physical Activity, Mediterranean Diet and Biomarkers-Assessed Risk of Alzheimer’s: A Multi-Modality Brain Imaging Study

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          Abstract

          Increased physical activity and higher adherence to a Mediterranean-type diet (MeDi) have been independently associated with reduced risk of Alzheimer’s disease (AD). Their association has not been investigated with the use of biomarkers. This study examines whether, among cognitively normal (NL) individuals, those who are less physically active and show lower MeDi adherence have brain biomarker abnormalities consistent with AD.

          Methods

          Forty-five NL individuals (age 54 ± 11, 71% women) with complete leisure time physical activity (LTA), dietary information, and cross-sectional 3D T1-weigthed MRI, 11C-Pittsburgh Compound B (PiB) and 18F-fluorodeoxyglucose (FDG) Positron Emission Tomography (PET) scans were examined. Voxel-wise multivariate partial least square (PLS) regression was used to examine the effects of LTA, MeDi and their interaction on brain biomarkers. Age, gender, ethnicity, education, caloric intake, BMI, family history of AD, Apolipoprotein E (APOE) genotype, presence of hypertension and insulin resistance were examined as confounds. Subjects were dichotomized into more and less physically active (LTA+ vs. LTA−; n = 21 vs. 24), and into higher vs. lower MeDi adherence groups (n = 18 vs. 27) using published scoring methods. Spatial patterns of brain biomarkers that represented the optimal association between the images and the groups were generated for all modalities using voxel-wise multivariate Partial Least Squares (PLS) regression.

          Results

          Groups were comparable for clinical and neuropsychological measures. Independent effects of LTA and MeDi factors were observed in AD-vulnerable brain regions for all modalities (p < 0.001). Increased AD-burden (in particular higher A β load and lower glucose metabolism) were observed in LTA− compared to LTA+ subjects, and in MeDi− as compared to MeDi+ subjects. A gradient effect was observed for all modalities so that LTA−/MeDi− subjects had the highest and LTA+/MeDi+ subjects had the lowest AD-burden (p < 0.001), although the LTA × MeDi interaction was significant only for FDG measures (p < 0.03). Adjusting for covariates did not attenuate these relationships.

          Conclusion

          Lower physical activity and MeDi adherence were associated with increased brain AD-burden among NL individuals, indicating that lifestyle factors may modulate AD risk. Studies with larger samples and longitudinal evaluations are needed to determine the predictive power of the observed associations

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          Most cited references40

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          Partial Least Squares (PLS) methods for neuroimaging: a tutorial and review.

          Partial Least Squares (PLS) methods are particularly suited to the analysis of relationships between measures of brain activity and of behavior or experimental design. In neuroimaging, PLS refers to two related methods: (1) symmetric PLS or Partial Least Squares Correlation (PLSC), and (2) asymmetric PLS or Partial Least Squares Regression (PLSR). The most popular (by far) version of PLS for neuroimaging is PLSC. It exists in several varieties based on the type of data that are related to brain activity: behavior PLSC analyzes the relationship between brain activity and behavioral data, task PLSC analyzes how brain activity relates to pre-defined categories or experimental design, seed PLSC analyzes the pattern of connectivity between brain regions, and multi-block or multi-table PLSC integrates one or more of these varieties in a common analysis. PLSR, in contrast to PLSC, is a predictive technique which, typically, predicts behavior (or design) from brain activity. For both PLS methods, statistical inferences are implemented using cross-validation techniques to identify significant patterns of voxel activation. This paper presents both PLS methods and illustrates them with small numerical examples and typical applications in neuroimaging. Copyright © 2010 Elsevier Inc. All rights reserved.
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            Partial least squares analysis of neuroimaging data: applications and advances.

            Partial least squares (PLS) analysis has been used to characterize distributed signals measured by neuroimaging methods like positron emission tomography (PET), functional magnetic resonance imaging (fMRI), event-related potentials (ERP) and magnetoencephalography (MEG). In the application to PET, it has been used to extract activity patterns differentiating cognitive tasks, patterns relating distributed activity to behavior, and to describe large-scale interregional interactions or functional connections. This paper reviews the more recent extension of PLS to the analysis of spatiotemporal patterns present in fMRI, ERP, and MEG data. We present a basic mathematical description of PLS and discuss the statistical assessment using permutation testing and bootstrap resampling. These two resampling methods provide complementary information of the statistical strength of the extracted activity patterns (permutation test) and the reliability of regional contributions to the patterns (bootstrap resampling). Simulated ERP data are used to guide the basic interpretation of spatiotemporal PLS results, and examples from empirical ERP and fMRI data sets are used for further illustration. We conclude with a discussion of some caveats in the use of PLS, including nonlinearities, nonorthogonality, and interpretation difficulties. We further discuss its role as an important tool in a pluralistic analytic approach to neuroimaging.
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              Mediterranean diet and risk for Alzheimer's disease.

              Previous research in Alzheimer's disease (AD) has focused on individual dietary components. There is converging evidence that composite dietary patterns such as the Mediterranean diet (MeDi) is related to lower risk for cardiovascular disease, several forms of cancer, and overall mortality. We sought to investigate the association between MeDi and risk for AD. A total of 2,258 community-based nondemented individuals in New York were prospectively evaluated every 1.5 years. Adherence to the MeDi (zero- to nine-point scale with higher scores indicating higher adherence) was the main predictor in models that were adjusted for cohort, age, sex, ethnicity, education, apolipoprotein E genotype, caloric intake, smoking, medical comorbidity index, and body mass index. There were 262 incident AD cases during the course of 4 (+/-3.0; range, 0.2-13.9) years of follow-up. Higher adherence to the MeDi was associated with lower risk for AD (hazard ratio, 0.91; 95% confidence interval, 0.83-0.98; p=0.015). Compared with subjects in the lowest MeDi tertile, subjects in the middle MeDi tertile had a hazard ratio of 0.85 (95% confidence interval, 0.63-1.16) and those at the highest tertile had a hazard ratio of 0.60 (95% confidence interval, 0.42-0.87) for AD (p for trend=0.007). We conclude that higher adherence to the MeDi is associated with a reduction in risk for AD. Ann Neurol 2006.
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                Author and article information

                Journal
                101632146
                42572
                Adv J Mol Imaging
                Adv J Mol Imaging
                Advances in molecular imaging
                2161-6728
                2161-6752
                5 December 2014
                October 2014
                14 January 2015
                : 4
                : 4
                : 43-57
                Affiliations
                [1 ]ADM Diagnostics, Chicago, USA
                [2 ]Department of Psychiatry, New York University School of Medicine, New York, USA
                [3 ]Citigroup Biomedical Imaging Center, Weill Cornell Medical College, New York, USA
                Author notes
                [* ]Corresponding author lisa.mosconi@ 123456nyumc.org
                Article
                NIHMS646686
                10.4236/ami.2014.44006
                4294269
                25599008
                4cf4109d-c677-4d0e-aeae-fb048008fc5d
                Copyright © 2014 by authors and Scientific Research Publishing Inc.

                This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/

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                Categories
                Article

                alzheimer’s disease,mediterranean diet,physical activity,pet imaging,amyloid,glucose metabolism,mri,early detection,brain aging

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