Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2015 Mar;47(3):589-601.
doi: 10.1007/s00726-014-1893-x. Epub 2014 Dec 21.

Metabolome-wide Association Study of Phenylalanine in Plasma of Common Marmosets

Affiliations
Free PMC article

Metabolome-wide Association Study of Phenylalanine in Plasma of Common Marmosets

Young-Mi Go et al. Amino Acids. .
Free PMC article

Abstract

Little systematic knowledge exists concerning the impacts of cumulative lifelong exposure, termed the exposome, on requirements for nutrients. Phenylalanine (Phe) is an essential dietary amino acid with an aromatic ring structure similar to endogenous metabolites, dietary compounds and environmental agents. Excess plasma Phe in genetic disease or nutritional deficiency of Phe has adverse health consequences. In principle, structurally similar chemicals interfering with Phe utilization could alter Phe requirement at an individual level. As a strategy to identify components of the exposome that could interfere with Phe utilization, we tested for metabolites correlating with Phe concentration in plasma of a non-human primate species, common marmosets (Callithrix jacchus). The results of tests for more than 5,000 chemical features detected by high-resolution metabolomics showed 17 positive correlations with Phe metabolites and other amino acids. Positive and negative correlations were also observed for 33 other chemicals, which included matches to endogenous metabolites and dietary, microbial and environmental chemicals in database searches. Chemical similarity analysis showed many of the matches had high structural similarity to Phe. Together, the results show that chemicals in marmoset plasma could impact Phe utilization. Such chemicals could contribute to early lifecycle developmental disorders when neurological development is vulnerable to Phe levels.

Figures

Fig. 1
Fig. 1
Workflow to test for dietary, microbiome and environmental metabolite correlations with Phe. Fifty marmoset plasma samples were analyzed by liquid chromatography-mass spectrometry (LCMS) resulting in selection of 5,345 m/z features for Phe analysis. Following metabolome-wide association study (MWAS) of 5,345 LCMS features shows 50 features were correlated with Phe (q ≤ 0.2). These features were then used with the Metlin metabolomics database to obtain metabolites that matched the accurate mass within 10 ppm. The Kyoto Encyclopedia of Genes and Genomes (KEGG) identifiers from the Metlin search were then used to classify metabolites with KEGG Brite and KEGG Pathway mapping. KEGG and CAS identifiers from Metlin were converted to CID and used with PubChem Matrix Score Service to obtain structural similarity scores.
Fig. 2
Fig. 2
Phe concentrations in marmoset plasma. There was no anticipation of sex or age differences in Phe concentration so study design was to use an approximately balanced population of young females (n=12), older females (n=12), young males (n=12) and older males (n=14) and analyze data without consideration of sex or age effects. Statistical analyses showed differences (*p<0.05) in Phe concentration between respective age groups of females and males.
Fig. 3
Fig. 3
Metabolome-Wide Association Study (MWAS) of metabolites in marmoset plasma correlated with Phe. a. Type 1 Manhattan plot showing the negative log p (−log p) for correlation of each metabolite (m/z feature) as a function of the m/z (mass/charge). b. Type 2 Manhattan plot showing −log p for each metabolite as a function of chromatographic retention time. False discovery rate (FDR) thresholds are shown by broken lines. Positive correlations are shown in blue and negative correlations are shown in red.
Fig. 4
Fig. 4
Correlations of amino acids in marmoset plasma with plasma phenylalanine. Intensity values for ions (identified by m/z and chromatographic retention time) for individual marmoset plasma samples plotted as a function of the Phe concentration in the sample. Data for Tyr (a, r=0.62), Met (b, r=0.59), His (c, r=0.50), and citrulline (d, r=0.53) were significant at FDR 0.05. Thr was significant at FDR 0.2 (e, r=0.45). Pearson correlation and p for correlation are provided in Online Resource 1.
Fig. 5
Fig. 5
Classification of 50 plasma metabolites correlated with plasma Phe at FDR <0.2. Seventeen of the features correlated with Phe had confirmed identities as Phe, metabolites of Phe or other amino acids. Other features were manually annotated by searching the Metlin database and selecting likely matches. Where multiple matches were present, a single count was used, i.e., multiple matches for a single m/z feature to multiple dietary compounds were given a single count. Most of the correlations were positive, so only these are shown as separate segments. Negatively associated features mostly matched complex lipids (blue symbols in Fig. 3b with retention times >200 s). The detailed information of 50 metabolites is provided in Online Resource 1.
Fig. 6
Fig. 6
Histogram of metabolites correlated with Phe in marmoset plasma as a function of structural similarity score. PubChem Compound identifiers (CID) were available for 125 metabolites matching the 50 m/z features correlated with Phe; these were used to calculate chemical similarity scores using the PubChem Score Matrix Service (http://pubchem.ncbi.nlm.nih.gov/score_matrix). CID were similarly derived for 50 randomly selected m/z features not correlated with Phe, and the 112 resulting metabolites were used to calculate similarity scores. For each similarity score threshold indicated, the total number of metabolite matches is indicated by the height of the bar, with the hatched component of the bar representing the number derived from the randomly selected metabolites, the black component representing those due to redundant detection of Phe, and the white component representing the number of non-randomly detected metabolites correlated with Phe.
Fig. 7
Fig. 7
KEGG Pathway Mapping of plasma metabolites associated with Phe in younger (2-7 y old) and older (8-15 y old) marmosets. Metabolites were separated according to positive (+r) and negative (−r) associations according to Pearson correlation. Mass spectrometry features were matched to metabolites within 10 ppm using the Metlin metabolomics database. Respective KEGG identifiers were used with the KEGG Pathway Mapping function to obtain pathway classifications. Results show differences in the classes of metabolites correlated with Phe in younger and older marmosets. The analysis is imprecise because of inclusion of multiple isobaric chemical species matching to a single m/z feature and some features not being represented due to lack of metabolite match and/or KEGG identifier. Symbols (*, +) are used to facilitate distinction of pathways differing between positive and negative associations in younger marmosets.

Similar articles

See all similar articles

Cited by 23 articles

See all "Cited by" articles

Publication types

LinkOut - more resources

Feedback