Mediterranean vs. Western diet effects on the primate cerebral cortical pre-synaptic proteome: Relationships with the transcriptome and multi-system phenotypes

Abstract

Introduction: Diet quality mediates aging-related risks of cognitive decline, neurodegeneration, and Alzheimer's disease (AD) through poorly defined mechanisms.

Methods: The effects of diet on the presynaptic proteome of the temporal cortex were assessed in 36 female cynomolgus macaques randomized to Mediterranean or Western diets for 31 months. Associations between the presynaptic proteome, determined by synaptometry by time-of-flight (SynTOF) mass spectrometry, adjacent cortex transcriptome, and multi-system phenotypes were assessed using a machine learning approach.

Results: Six presynaptic proteins (DAT, Aβ42, calreticulin, LC3B, K48-Ubiquitin, SLC6A8) were elevated in the presynaptic proteome in Mediterranean diet consumers (p < 0.05). Transcriptomic data and multi-system phenotypes significantly predicted SynTOF markers. Selected SynTOF markers were correlated with changes in white matter volumes, hepatosteatosis, and behavioral and physiological measures of psychosocial stress.

Discussion: These observations demonstrate that diet composition drives cortical presynaptic protein composition, that transcriptional profiles strongly predict the presynaptic proteomic profile, and that presynaptic proteins were closely associated with peripheral metabolism, stress responsivity, neuroanatomy, and socio-emotional behavior.

Highlights: Mediterranean and Western diets differentially altered the cortical presynaptic proteome, which is strongly associated with neurodegeneration and cognitive decline. Presynaptic proteomic markers were predicted by transcriptomic profiles in the adjacent cortex, and by multi-system anatomical, physiologic, and behavioral phenotypes. The data demonstrate that brain phenotypes and brain-body interactions are influenced by common dietary patterns, suggesting that improving diet quality may be an effective means to maintain brain health.

Keywords: Alzheimer's disease; Mediterranean diet; brain; inflammation; nonhuman primates; synaptometry by time‐of‐flight (SynTOF) mass spectrometry.

FIGURE 1

Experimental design. Design of this randomized, controlled preclinical trial of 36 middle‐aged, female cynomolgus macaques (Macaca fascicularis) to determine the impacts of long‐term consumption (31 months, equivalent to ∼9 years for humans) of either a Western or Mediterranean diet. The phenotypes collected across the course of the study shown here are described in Table S2 and more detail in the referenced publications. CSF, cerebrospinal fluid; CT, computed tomography; HPA, hypothalamic‐pituitary‐adrenal; IVGTT, intravenous glucose tolerance test.

FIGURE 2

Effects of diet on NHP presynaptic proteome. Results of a randomized, controlled preclinical trial of middle‐aged, female cynomolgus macaques to determine the impact of long‐term consumption of Western vs. Mediterranean diets. Data presented here represent presynaptic proteomic phenotypes in the lateral temporal cortex determined by SynTOF mass spectrometry. (A) Differential effects of diet were assessed using pseudo‐bulk presynaptic relative contents of SynTOF targets. The SynTOF‐detected levels that were significantly different between the two diet groups are annotated (multi‐testing adjusted Wilcoxon's p < 0.05, fold‐change > 0.1). (B) Box plot illustrating effects of diet on SynTOF‐detected presynaptic levels. **p < 0.01 ***p < 0.001. (C) SynTOF markers predicted the diet group with a cross‐validated AUROC of 0.87 using a linear model (Ridge regression). (D) UMAP visualization of single‐presynapse organization in NHP brain illustrating 15 individual clusters based on results from 30 SynTOF probes. (E) Heat map illustrating relative concentrations of SynTOF peptides in individual presynaptic clusters. AUROC, area under the receiver operating characteristic curve; NHP, nonhuman primate; SynTOF, synaptometry by time‐of‐flight.

FIGURE 3

Transcript correlations with SynTOF markers. Results of a randomized, controlled preclinical trial of middle‐aged, female cynomolgus macaques to determine the impact of long‐term consumption (31 months, equivalent to ∼9 years for humans) of either a Western or Mediterranean diet. Data presented are from the lateral temporal cortex using SynTOF mass spectrometry and RNAseq transcriptomics. (A) Cross‐validated performance of diet‐adjusted machine learning models predicting SynTOF marker expression from the transcriptional profile (p < 0.05) using a feature selection algorithm. Only the best models per SynTOF marker are shown here (see the Methods section). (B) Distribution of SynTOF marker model prediction p values by the number of selected transcripts. Only a few transcripts are needed to enable the prediction of all the SynTOF markers (30/30 SynTOF markers p < 0.05, 22/30 p < 0.001). (C) Associations between individual transcripts and SynTOF markers. Transcript contribution to the model prediction was quantified using the SHAP algorithm. Node sizes are proportional to the importance of the transcript in SynTOF marker prediction. Node colors represent the Spearman correlation between SynTOF markers and corresponding gene expression. SynTOF, synaptometry by time‐of‐flight.

FIGURE 4

Associations of SynTOF markers with multi‐system phenotypes. Data presented are multi‐system phenotypes previously described (see Table S2), and lateral temporal cortex proteomic data determined by SynTOF mass spectrometry. (A) Cross‐validated performance of diet‐adjusted machine learning models predicted 26 of 30 SynTOF marker expressions from the multi‐system phenotypes (p < 0.05), with and without feature selection. Only the best nested cross‐validated models per marker are shown (see the Methods section). (B) Correlation network between multi‐system phenotypes and SynTOF markers. Node size represents the strength of the univariate association of the covariate with diet (−log(p‐value)). Edges represent the top 10% of the correlation between different covariates. (C) Association of SynTOF markers with behavioral, physical, neuroimaging, and physiologic characteristics. Horizontal dotted lines represent major clusters of SynTOF markers; vertical dotted lines delineate classes of phenotypes (e.g., behavior, stress, CSF biomarkers etc.). Node sizes are proportional to the importance of the phenotype in SynTOF prediction determined using the SHAP algorithm (39). Node colors represent the Spearman univariate correlation between SynTOF markers and phenotypes. Clustering was performed on the univariate correlation expression matrix using pair‐wise Euclidian distance. SynTOF, synaptometry by time‐of‐flight.