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. 2020 May 19;12(5):1476.
doi: 10.3390/nu12051476.

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

Maura E Walker  1 , Rebecca J Song  2 , Xiang Xu  3 , Robert E Gerszten  4 , Debby Ngo  4 , Clary B Clish  5 , Laura Corlin  1   6 , Jiantao Ma  7   8 , Vanessa Xanthakis  1   7   9 , Paul F Jacques  8   10 , Ramachandran S Vasan  1   2   7   11   12
Affiliations

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

Maura E Walker et al. Nutrients. .

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.

Keywords: biomarker; diet quality; dietary patterns; metabolomic; proteomic.

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Conflict of interest statement

All authors declare no conflict of interest.

Figures

Figure 1
Figure 1
The number of protein (A) and metabolite (B) markers associated with dietary pattern indices. Venn diagrams illustrate the overlap of significant proteins (FDR q ≤ 0.05) and metabolites across the AHEI, DASH, and MDS dietary patterns. Significant proteins and metabolites were based on a false discovery rate threshold ≤ 0.05 from multivariable models adjusted for age, sex, total caloric intake, current smoking, physical activity index, lipid lowering medication, anti-hypertensive medication, and body mass index. Abbreviations: AHEI, Alternative Healthy Eating Index; DASH, Dietary Approaches to Stop Hypertension; FDR, false discovery rate; MDS, Mediterranean-style Diet Score.
Figure 2
Figure 2
Protein (A) and metabolite (B) markers associated with dietary pattern indices. Colored points (red, green, blue) indicate statistical significance (FDR q ≤ 0.05) by the respective dietary pattern indices. Multivariable regression models are adjusted for age, sex, total caloric intake, current smoking, physical activity index, lipid lowering medication, anti-hypertensive medication, and body mass index. β estimates represent the change in marker per one-unit increase in the respective dietary pattern indices. Eleven metabolites with β coefficients < −0.50 or >0.50 are excluded from the figure. Abbreviations: AHEI, Alternative Healthy Eating Index; CE, cholesterol ester; DASH, Dietary Approaches to Stop Hypertension; FDR, false discovery rate; LPC, lysophosphatidylcholine; LPE, lysophosphatidylethanolamine; MDS, Mediterranean-style Diet Score. PC, phosphatidylcholine; SM, sphingomyelin; TAG, triacylglycerol.
Figure 3
Figure 3
Heatmap depicting Spearman’s partial correlation coefficients adjusted for age and sex between proteins that were statistically significant (FDR p ≤ 0.05) in multivariable models adjusting for age, sex, total caloric intake, current smoking, physical activity index, lipid lowering medication, anti-hypertensive medication, and body mass index.
Figure 4
Figure 4
Heatmap depicting Spearman’s partial correlation coefficients adjusted for age and sex between metabolites that were statistically significant (FDR p ≤ 0.05) in multivariable models adjusting for age, sex, total caloric intake, current smoking, physical activity index, lipid lowering medication, anti-hypertensive medication, and body mass index. CE, cholesterol ester; FDR, false discovery rate; LPC, lysophosphatidylcholine; LPE, lysophosphatidylethanolamine; PC, phosphatidylcholine; SM, sphingomyelin; TAG, triacylglycerol.
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