Nutrient patterns and brain biomarkers of Alzheimer’s disease in cognitively normal individuals

Objectives: Epidemiological evidence linking diet, one of the most important modifiable lifestyle factors, and risk of Alzheimer's disease (AD) is rapidly increasing. However, there is little or no evidence for a direct association between dietary nutrients and brain biomarkers of AD. This study identifies nutrient patterns associated with major brain AD biomarkers in a cohort of clinically and cognitively normal (NL) individuals at risk for AD. Design: Cross-sectional study. Setting: Manhattan (broader area). Participants: Fifty-two NL individuals age 54+12 y, 70% women, Clinical Dementia Rating=0, MMSE>27, neuropsychological test performance within norms by age and education) with complete dietary information and cross-sectional, 3D T1-weighted Magnetic Resonance Imaging (MRI; gray matter volumes, GMV, a marker of brain atrophy), 11C-Pittsburgh compound-B (PiB; a marker of fibrillar amyloid-beta, A beta) and 18F-fluorodeoxyglucose (FDG; a marker of glucose metabolism, METglc) Positron Emission Tomography (PET) scans were examined. Measurements: Dietary intake of 35 nutrients associated with cognitive function and AD was assessed using the Harvard/Willet Food Frequency Questionnaire. Principal component analysis was used to generate nutrient patterns (NP) from the full nutrient panel. Statistical parametric mapping and voxel based morphometry were used to assess the associations of the identified NPs with AD biomarkers. Results: None of the participants were diabetics, smokers, or met criteria for obesity. Five NPs were identified: NP1 was characterized by most B-vitamins and several minerals [VitB & Minerals]; NP2 by monounsaturated and polyunsaturated fats, including omega-3 and omega-6 PUFA, and vitamin E [VitE & PUFA]; NP3 by vitamin A, vitamin C, carotenoids and dietary fibers [Anti-oxidants & Fibers]; NP4 by vitamin B12, vitamin D and zinc [VitB12& D]; NP5 by saturated, trans- saturated fats, cholesterol and sodium [Fats]. Voxel-based analysis showed that NP4 scores [VitB12&D] were positively associated with METglc and GMV, and negatively associated with PiB retention in AD- vulnerable regions (p<0.001). In addition, both METglc and GMV were positively associated with NP2 scores [VitE&PUFA], and negatively associated with NP5 scores [Fats] (p<0.001), and METglc was positively associated with higher NP3 scores [Anti-oxidants&Fibers] (p<0.001). Adjusting for age, gender, ethnicity, education, caloric intake, BMI, alcohol consumption, family history and Apolipoprotein E (APOE) status did not attenuate these relationships. The identified 'AD-protective' nutrient combination was associated with higher intake of fresh fruit and vegetables, whole grains, fish and low-fat dairies, and lower intake of sweets, fried potatoes, high-fat dairies, processed meat and butter. Conclusion: Specific dietary NPs are associated with brain biomarkers of AD in NL individuals, suggesting that dietary interventions may play a role in the prevention of AD by modulating AD-risk through its effects on A beta and associated neuronal impairment.