Taub Institute: Genomics Core
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TaubCONNECT Research Perspectives:
May 2016

White Matter Integrity as a Mediator in the Relationship between Dietary Nutrients and Cognition in the Elderly

Yian Gu, PhD    Adam M. Brickman, PhD

Mounting evidence suggests that dietary factors are associated with risk for Alzheimer’s disease and cognitive decline among the elderly. Previous work from Dr. Gu and others have shown that dietary factors are also implicated in maintaining brain macrostructures, such as brain volumes assessed by magnetic resonance imaging (MRI). Diffusion tensor imaging (DTI) is a sensitive MRI-based neuroimaging technique that assesses the integrity of white matter microstructure by measuring diffusion properties of water in the brain, and studies have shown that DTI metrics predict dementia or cognitive impairment. However, little is known about the association of dietary patterns with microstructural brain imaging markers such as white matter integrity.

Fig. 1. Mediation model for composite memory score. Models were analyzed using Preacher and Hayes's (Preacher and Hayes 2008) PROCESS SPSS macro. β indicate standardized beta weights and were estimated from models adjusted for age, sex, education, ethnicity, APOE, and caloric intake. The 95%CI indicates the 10000 sample bootstrapped 95% confidence intervals for the indirect effects. A 95%CI not including 0 indicates statistic significance. R2 indicates the fit of the mediation model. Acronyms: fractional anisotropy (FA); confidence interval (CI).

Recently published in the Annals of Neurology, Dr. Gu, Dr. Adam Brickman, and colleagues investigated the association between dietary nutrient intake and white matter integrity among 239 elderly (≥65 years) participants of the Washington Heights-Hamilton Heights-Inwood Columbia Aging Project (WHICAP). The study also evaluated the extent to which the association between nutrient intake and cognition is due to the variability in white matter microstructure. The white matter integrity in the study was assessed using DTI, and the most widely used metric derived from DTI, fractional anisotropy (FA), was used in the analysis. Higher FA values indicate greater directionality of diffusion and preserved microstructure. Dietary data were collected using food frequency questionnaire, and nutrient patterns were derived from principal component analysis based on energy-adjusted intake of 24 selected nutrients. Generalized linear models were used to assess the association between nutrient patterns and mean FA of 26 white matter tracts. Mediation analysis was used to determine if FA mediates the nutrient-cognition relationship. All models were adjusted for age at time of scan, gender, ethnicity, education, caloric intake, and Apolipoprotein genotype.

In the current study, results showed that there was a positive association between a principal component analysis-derived nutrient pattern (omega-3 and omega-6 poly-unsaturated fatty acids and vitamin E) and better white matter integrity, indicated by higher value of DTI metric FA. Those with the highest tertile of nutrient pattern score had a mean of 0.01 (p=0.01) higher FA value than those with the lowest tertile, similar to the effect of a ten-year decrease in age (b for age=−0.001, p=0.01). In addition, the study also found that FA mediated the relationship between this nutrient pattern and memory, language, visuospatial and speed/executive function, and mean cognitive scores. This study offers important evidence to support a positive association between consumption of poly-unsaturated fatty acids and vitamin E rich foods and white matter integrity in the elderly, as well as the role brain white matter plays in the relationship between diet and cognition.

Yian Gu, PhD
Assistant Professor of Neurological Sciences (in Neurology, Epidemiology and the Taub Institute)

Adam M. Brickman, PhD
Associate Professor of Neuropsychology

Dementia Risk and Protective Factors Differ in the Context of Memory Trajectory Groups

Laura Zahodne, PhD     Jennifer J. Manly, PhD

There is great heterogeneity in the trajectories of memory performance in late life. Some adults enter late life with above average memory performance but experience steep declines, while some enter late life with below average memory performance and enjoy many years of cognitive stability. Dr. Laura Zahodne and colleagues from the Taub Institute previously used the data-driven approach of growth mixture modeling to identify four distinct subgroups of older adults in the Washington Heights-Inwood Columbia Aging Project (WHICAP) based on repeated memory assessments: "Stable-High," "Stable-Low," "Decline," and "Rapid Decline." While individuals showing memory decline were more likely to develop incident dementia, each of the four subgroups contained individuals who converted to dementia.

In a recent follow-up study published in the Journal of Alzheimer's Disease, Zahodne et al. showed that the predictive value of several well-known dementia risk and protective factors differed across the four memory trajectory subgroups. For example, higher educational attainment did not protect against incident dementia for older adults showing the steepest memory declines, in whom stroke and APOE genotype were most predictive of conversion. These findings suggest that there are different pathways to dementia in older adults, and resilience or vulnerability factors may modify the influence of specific dementia risk/protective factors. Dementia risk profiles may be improved by considering interactions between risk/protective factors and a patient's unique cognitive history.

Laura Zahodne, PhD
Associate Research Scientist

Jennifer J. Manly, PhD
Professor of Neuropsychology (in Neurology, the Gertrude H. Sergievsky Center and the Taub Institute)

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