Blood metabolite markers of cognitive performance and brain function in aging

Abstract

We recently showed that Alzheimer's disease patients have lower plasma concentrations of the phosphatidylcholines (PC16:0/20:5; PC16:0/22:6; and PC18:0/22:6) relative to healthy controls. We now extend these findings by examining associations between plasma concentrations of these PCs with cognition and brain function (measured by regional resting state cerebral blood flow; rCBF) in non-demented older individuals. Within the Baltimore Longitudinal Study of Aging neuroimaging substudy, participants underwent cognitive assessments and brain (15)O-water positron emission tomography. Plasma phosphatidylcholines concentrations (PC16:0/20:5, PC16:0/22:6, and PC18:0/22:6), cognition (California Verbal Learning Test (CVLT), Trail Making Test A&B, the Mini-Mental State Examination, Benton Visual Retention, Card Rotation, and Fluencies-Category and Letter), and rCBF were assessed. Lower plasma phosphatidylcholine concentrations were associated with lower baseline memory performance (CVLT long delay recall task-PC16:0/20:5: -2.17-1.39-0.60 p = 0.001 (β with 95% confidence interval subscripts)) and lower rCBF in several brain regions including those associated with memory performance and higher order cognitive processes. Our findings suggest that lower plasma concentrations of PC16:0/20:5, PC16:0/22:6, and PC18:0/22:6 are associated with poorer memory performance as well as widespread decreases in brain function during aging. Dysregulation of peripheral phosphatidylcholine metabolism may therefore be a common feature of both Alzheimer's disease and age-associated differences in cognition.

SPARCL1 Accelerates Symptom Onset in Alzheimer’s Disease and Influences Brain Structure and Function During Aging

“…We first applied a statistical magnitude threshold of p < 0.005, as recommended by the PET Working Group of the NIH/NIA Neuroimaging Initiative. Secondly, we applied a spatial extent threshold of at least 50 voxels within the regions meeting the statistical threshold of p < 0.005, as reported previously [48]. …”

Large-scale proteomic analysis of human prefrontal cortex identifies proteins associated with cognitive trajectory in advanced age

“…For each cohort, we model the annual MMSE score as a longitudinal outcome, follow-up year as the independent variable and sex, age at enrollment, and education as the covariates, with a random intercept and random slope per subject using the lme4 R package (version 1. [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19]. The derived cognitive trajectory for each individual in Banner and BLSA cohorts is listed in supplementary table 1.…”

Metabolic network failures in Alzheimer's disease: A biochemical road map

“…Measurement of large numbers of metabolites enables network analysis approaches and provides means to identify critical metabolic drivers in disease pathophysiology [20]. Initial small-scale metabolomics studies in AD have highlighted metabolic alterations including ceramide–sphingomyelin pathways [10], glycero-phosphatidylcholines ( aa = diacyl, ae = acyl–alkyl) [PC] [15,21], PE plasmalogens [22,23], amines [24], and mitochondrial defects [25] among others [13,14]. Metabolic networks have linked central perturbations in norepinephrine and purines with elevated cerebrospinal fluid (CSF) tau, and changes in tryptophan and methionine to decreased Aβ levels [18].…”