Proteomic and Metabolomic Correlates of Healthy Dietary Patterns: The Framingham Heart Study

Abstract

Data on proteomic and metabolomic signatures of healthy dietary patterns are limited. We evaluated the cross-sectional association of serum proteomic and metabolomic markers with three dietary patterns: the Alternative Healthy Eating Index (AHEI), the Dietary Approaches to Stop Hypertension (DASH) diet; and a Mediterranean-style (MDS) diet. We examined participants from the Framingham Offspring Study (mean age; 55 years; 52% women) who had complete proteomic (n = 1713) and metabolomic (n = 2284) data; using food frequency questionnaires to derive dietary pattern indices. Proteins and metabolites were quantified using the SomaScan platform and liquid chromatography/tandem mass spectrometry; respectively. We used multivariable-adjusted linear regression models to relate each dietary pattern index (independent variables) to each proteomic and metabolomic marker (dependent variables). Of the 1373 proteins; 103 were associated with at least one dietary pattern (48 with AHEI; 83 with DASH; and 8 with MDS; all false discovery rate [FDR] ≤ 0.05). We identified unique associations between dietary patterns and proteins (17 with AHEI; 52 with DASH; and 3 with MDS; all FDR ≤ 0.05). Significant proteins enriched biological pathways involved in cellular metabolism/proliferation and immune response/inflammation. Of the 216 metabolites; 65 were associated with at least one dietary pattern (38 with AHEI; 43 with DASH; and 50 with MDS; all FDR ≤ 0.05). All three dietary patterns were associated with a common signature of 24 metabolites (63% lipids). Proteins and metabolites associated with dietary patterns may help characterize intermediate phenotypes that provide insights into the molecular mechanisms mediating diet-related disease. Our findings warrant replication in independent populations

Gut Microbiota Functional Dysbiosis Relates to Individual Diet in Subclinical Carotid Atherosclerosis

“…Finally, we did not perform a complete analysis of circulating proteomic and metabolomics markers validating the metagenomics pathways that emerged from our data. Since multiple circulating proteins and metabolites (the majority of which are of lipid origin) have been recently associated with different types of dietary patterns [ 72 ], this aspect is of relevance and will be analyzed in the near future.…”

Towards a biochemical approach to occupational stress management

“…These included studies of aging [ 70 ], suboptimal health [ 71 , 72 ], PTSD [ 67 ], Ayurvedic Therapy [ 69 ] and weight management [ 68 ]. Other confounding factors may also need to be controlled in occupational stress studies of real-world stressors, including smoking [ 110 ], alcohol, drug abuse and pharmaceutical usage [ 54 ], diet or dietary changes [ 111 ], exercise [ 112 ], environmental factors and infection [ 55 , 113 ]. Therefore, analysis of detailed time courses, made possible with blood spot or saliva sampling, will greatly enhance interpretation of occupational stress responses.…”

Metabolomic profiling of the Dietary Approaches to Stop Hypertension diet provides novel insights for the nutritional epidemiology of type 2 diabetes mellitus

“…This included an 83 protein signature which enriched pathways involved in cellular metabolism, hypoxia, inflammation, and atherosclerosis (16) . The metabolite signature included 43 biomarkers mainly consisting of lipids (55%) with long-chain fatty acids (16) . However, as is highlighted by this Accepted manuscript study, additional work is required to identify determinants of dietary correlates and examine how they may relate to the progression of modifiable chronic disease (16) .…”

“…Metabolomics can be similarly informative in identifying metabolite profiles characterizing adherence to different dietary patterns (11,12) . However, to date information regarding the metabolomic signature of DASH adherence is sparse as, to our knowledge, only a limited Accepted manuscript number of previous studies have determined metabolite profiles associated with adherence to this dietary pattern in human subjects (13)(14)(15)(16) . Thus, there is currently an important knowledge gap regarding the metabolomic profile of DASH diet adherence in free-living, multiethnic, and disease-free populations.…”