Minimally invasive (13)C-breath test to examine phenylalanine metabolism in children with phenylketonuria

European guideline on indications, performance and clinical impact of 13 C-breath tests in adult and pediatric patients: An EAGEN, ESNM, and ESPGHAN consensus, supported by EPC

Introduction

¹³C‐breath tests are valuable, noninvasive diagnostic tests that can be widely applied for the assessment of gastroenterological symptoms and diseases. Currently, the potential of these tests is compromised by a lack of standardization regarding performance and interpretation among expert centers.

Methods

This consensus‐based clinical practice guideline defines the clinical indications, performance, and interpretation of ¹³C‐breath tests in adult and pediatric patients. A balance between scientific evidence and clinical experience was achieved by a Delphi consensus that involved 43 experts from 18 European countries. Consensus on individual statements and recommendations was established if ≥ 80% of reviewers agreed and <10% disagreed.

Results

The guideline gives an overview over general methodology of ¹³C‐breath testing and provides recommendations for the use of ¹³C‐breath tests to diagnose Helicobacter pylori infection, measure gastric emptying time, and monitor pancreatic exocrine and liver function in adult and pediatric patients. Other potential applications of ¹³C‐breath testing are summarized briefly. The recommendations specifically detail when and how individual ¹³C‐breath tests should be performed including examples for well‐established test protocols, patient preparation, and reporting of test results.

Conclusion

This clinical practice guideline should improve pan‐European harmonization of diagnostic approaches to symptoms and disorders, which are very common in specialist and primary care gastroenterology practice, both in adult and pediatric patients. In addition, this guideline identifies areas of future clinical research involving the use of ¹³C‐breath tests.

Stable Isotope Abundance and Fractionation in Human Diseases

The natural abundance of heavy stable isotopes (¹³C, ¹⁵N, ¹⁸O, etc.) is now of considerable importance in many research fields, including human physiology. In fact, it varies between tissues and metabolites due to isotope effects in biological processes, that is, isotope discriminations between heavy and light isotopic forms during enzyme or transporter activity. The metabolic deregulation associated with many diseases leads to alterations in metabolic fluxes, resulting in changes in isotope abundance that can be identified easily with current isotope ratio technologies. In this review, we summarize the current knowledge on changes in natural isotope composition in samples (including various tissues, hair, plasma, saliva) found in patients compared to controls, caused by human diseases. We discuss the metabolic origin of such isotope fractionations and highlight the potential of using isotopes at natural abundance for medical diagnosis and/or prognostic.

A Multiplatform Metabolomics Approach to Characterize Plasma Levels of Phenylalanine and Tyrosine in Phenylketonuria

BACKGROUND

Different pathophysiological mechanisms have been described in phenylketonuria (PKU) but the indirect metabolic consequences of metabolic disorders caused by elevated Phe or low Tyr concentrations remain partially unknown. We used a multiplatform metabolomics approach to evaluate the metabolic signature associated with Phe and Tyr.

MATERIAL AND METHODS

We prospectively included 10 PKU adult patients and matched controls. We analysed the metabolome profile using GC-MS (urine), amino-acid analyzer (urine and plasma) and nuclear magnetic resonance spectroscopy (urine). We performed a multivariate analysis from the metabolome (after exclusion of Phe, Tyr and directly derived metabolites) to explain plasma Phe and Tyr concentrations, and the clinical status. Finally, we performed a univariate analysis of the most discriminant metabolites and we identified the associated metabolic pathways.

RESULTS

We obtained a metabolic pattern from 118 metabolites and we built excellent multivariate models to explain Phe, Tyr concentrations and PKU diagnosis. Common metabolites of these models were identified: Gln, Arg, succinate and alpha aminobutyric acid. Univariate analysis showed an inverse correlation between Arg, alpha aminobutyric acid and Phe and a positive correlation between Arg, succinate, Gln and Tyr (p < 0.0003). Thus, we highlighted the following pathways: Arg and Pro, Ala, Asp and Glu metabolism.

DISCUSSION

We obtain a specific metabolic signature related to Tyr and Phe concentrations. We confirmed the involvement of different pathophysiological mechanisms previously described in PKU such as protein synthesis, energetic metabolism and oxidative stress. The metabolomics approach is relevant to explore PKU pathogenesis.