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Urine metabolome profiling of immune-mediated inflammatory diseases

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ABSTRACT

Background: Immune-mediated inflammatory diseases (IMIDs) are a group of complex and prevalent diseases where disease diagnostic and activity monitoring is highly challenging. The determination of the metabolite profiles of biological samples is becoming a powerful approach to identify new biomarkers of clinical utility. In order to identify new metabolite biomarkers of diagnosis and disease activity, we have performed the first large-scale profiling of the urine metabolome of the six most prevalent IMIDs: rheumatoid arthritis, psoriatic arthritis, psoriasis, systemic lupus erythematosus, Crohn’s disease, and ulcerative colitis.

Methods: Using nuclear magnetic resonance, we analyzed the urine metabolome in a discovery cohort of 1210 patients and 100 controls. Within each IMID, two patient subgroups were recruited representing extreme disease activity (very high vs. very low). Metabolite association analysis with disease diagnosis and disease activity was performed using multivariate linear regression in order to control for the effects of clinical, epidemiological, or technical variability. After multiple test correction, the most significant metabolite biomarkers were validated in an independent cohort of 1200 patients and 200 controls.

Results: In the discovery cohort, we identified 28 significant associations between urine metabolite levels and disease diagnosis and three significant metabolite associations with disease activity (PFDR < 0.05). Using the validation cohort, we validated 26 of the diagnostic associations and all three metabolite associations with disease activity (PFDR < 0.05). Combining all diagnostic biomarkers using multivariate classifiers we obtained a good disease prediction accuracy in all IMIDs and particularly high in inflammatory bowel diseases. Several of the associated metabolites were found to be commonly altered in multiple IMIDs, some of which can be considered as hub biomarkers. The analysis of the metabolic reactions connecting the IMID-associated metabolites showed an over-representation of citric acid cycle, phenylalanine, and glycine-serine metabolism pathways.

Conclusions: This study shows that urine is a source of biomarkers of clinical utility in IMIDs. We have found that IMIDs show similar metabolic changes, particularly between clinically similar diseases and we have found, for the first time, the presence of hub metabolites. These findings represent an important step in the development of more efficient and less invasive diagnostic and disease monitoring methods in IMIDs.

Electronic supplementary material: The online version of this article (doi:10.1186/s12916-016-0681-8) contains supplementary material, which is available to authorized users.

No MeSH data available.


Metabolic reaction network illustrating metabolic signatures associated to IMIDs. Red-shaded metabolites have been associated to IMIDs in the current study. The associated IMIDs are displayed in a text box next to the corresponding metabolite. Disease associations meeting multiple test correction (FDR < 0.05) at the discovery and validation stages are displayed in green letters. Nominal disease associations (P < 0.05) at the discovery and validation stages are displayed in red letters. The metabolite reaction linking hippurate and glycine is only conducted through the activity of the gut microbiota
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Fig1: Metabolic reaction network illustrating metabolic signatures associated to IMIDs. Red-shaded metabolites have been associated to IMIDs in the current study. The associated IMIDs are displayed in a text box next to the corresponding metabolite. Disease associations meeting multiple test correction (FDR < 0.05) at the discovery and validation stages are displayed in green letters. Nominal disease associations (P < 0.05) at the discovery and validation stages are displayed in red letters. The metabolite reaction linking hippurate and glycine is only conducted through the activity of the gut microbiota

Mentions: In the discovery stage, the comparison between the urine metabolite profiles between patients and controls identified a total of 28 significant associations (FDR < 0.05). In the validation stage, n = 26 of these metabolite associations (93 %) were significantly replicated (FDR < 0.05, Table 2). In a secondary analysis, we found n = 13 metabolite associations to be significant at the nominal level in both stages of study (P < 0.05, same direction of change, Table 2). Using MetaboNetworks to analyze the associated metabolite profiles [39] we found a overrepresentation of metabolites from the citric acid cycle, phenylalanine metabolism and glycine-serine metabolism pathways (Fig. 1).Table 2


Urine metabolome profiling of immune-mediated inflammatory diseases
Metabolic reaction network illustrating metabolic signatures associated to IMIDs. Red-shaded metabolites have been associated to IMIDs in the current study. The associated IMIDs are displayed in a text box next to the corresponding metabolite. Disease associations meeting multiple test correction (FDR < 0.05) at the discovery and validation stages are displayed in green letters. Nominal disease associations (P < 0.05) at the discovery and validation stages are displayed in red letters. The metabolite reaction linking hippurate and glycine is only conducted through the activity of the gut microbiota
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC5016926&req=5

Fig1: Metabolic reaction network illustrating metabolic signatures associated to IMIDs. Red-shaded metabolites have been associated to IMIDs in the current study. The associated IMIDs are displayed in a text box next to the corresponding metabolite. Disease associations meeting multiple test correction (FDR < 0.05) at the discovery and validation stages are displayed in green letters. Nominal disease associations (P < 0.05) at the discovery and validation stages are displayed in red letters. The metabolite reaction linking hippurate and glycine is only conducted through the activity of the gut microbiota
Mentions: In the discovery stage, the comparison between the urine metabolite profiles between patients and controls identified a total of 28 significant associations (FDR < 0.05). In the validation stage, n = 26 of these metabolite associations (93 %) were significantly replicated (FDR < 0.05, Table 2). In a secondary analysis, we found n = 13 metabolite associations to be significant at the nominal level in both stages of study (P < 0.05, same direction of change, Table 2). Using MetaboNetworks to analyze the associated metabolite profiles [39] we found a overrepresentation of metabolites from the citric acid cycle, phenylalanine metabolism and glycine-serine metabolism pathways (Fig. 1).Table 2

View Article: PubMed Central - PubMed

ABSTRACT

Background: Immune-mediated inflammatory diseases (IMIDs) are a group of complex and prevalent diseases where disease diagnostic and activity monitoring is highly challenging. The determination of the metabolite profiles of biological samples is becoming a powerful approach to identify new biomarkers of clinical utility. In order to identify new metabolite biomarkers of diagnosis and disease activity, we have performed the first large-scale profiling of the urine metabolome of the six most prevalent IMIDs: rheumatoid arthritis, psoriatic arthritis, psoriasis, systemic lupus erythematosus, Crohn&rsquo;s disease, and ulcerative colitis.

Methods: Using nuclear magnetic resonance, we analyzed the urine metabolome in a discovery cohort of 1210 patients and 100 controls. Within each IMID, two patient subgroups were recruited representing extreme disease activity (very high vs. very low). Metabolite association analysis with disease diagnosis and disease activity was performed using multivariate linear regression in order to control for the effects of clinical, epidemiological, or technical variability. After multiple test correction, the most significant metabolite biomarkers were validated in an independent cohort of 1200 patients and 200 controls.

Results: In the discovery cohort, we identified 28 significant associations between urine metabolite levels and disease diagnosis and three significant metabolite associations with disease activity (PFDR&thinsp;&lt;&thinsp;0.05). Using the validation cohort, we validated 26 of the diagnostic associations and all three metabolite associations with disease activity (PFDR&thinsp;&lt;&thinsp;0.05). Combining all diagnostic biomarkers using multivariate classifiers we obtained a good disease prediction accuracy in all IMIDs and particularly high in inflammatory bowel diseases. Several of the associated metabolites were found to be commonly altered in multiple IMIDs, some of which can be considered as hub biomarkers. The analysis of the metabolic reactions connecting the IMID-associated metabolites showed an over-representation of citric acid cycle, phenylalanine, and glycine-serine metabolism pathways.

Conclusions: This study shows that urine is a source of biomarkers of clinical utility in IMIDs. We have found that IMIDs show similar metabolic changes, particularly between clinically similar diseases and we have found, for the first time, the presence of hub metabolites. These findings represent an important step in the development of more efficient and less invasive diagnostic and disease monitoring methods in IMIDs.

Electronic supplementary material: The online version of this article (doi:10.1186/s12916-016-0681-8) contains supplementary material, which is available to authorized users.

No MeSH data available.