Changes in pediatric plasma acylcarnitines upon fasting for refined interpretation of metabolic stress

Personalised modelling of clinical heterogeneity between medium-chain acyl-CoA dehydrogenase patients

BACKGROUND

Monogenetic inborn errors of metabolism cause a wide phenotypic heterogeneity that may even differ between family members carrying the same genetic variant. Computational modelling of metabolic networks may identify putative sources of this inter-patient heterogeneity. Here, we mainly focus on medium-chain acyl-CoA dehydrogenase deficiency (MCADD), the most common inborn error of the mitochondrial fatty acid oxidation (mFAO). It is an enigma why some MCADD patients-if untreated-are at risk to develop severe metabolic decompensations, whereas others remain asymptomatic throughout life. We hypothesised that an ability to maintain an increased free mitochondrial CoA (CoASH) and pathway flux might distinguish asymptomatic from symptomatic patients.

RESULTS

We built and experimentally validated, for the first time, a kinetic model of the human liver mFAO. Metabolites were partitioned according to their water solubility between the bulk aqueous matrix and the inner membrane. Enzymes are also either membrane-bound or in the matrix. This metabolite partitioning is a novel model attribute and improved predictions. MCADD substantially reduced pathway flux and CoASH, the latter due to the sequestration of CoA as medium-chain acyl-CoA esters. Analysis of urine from MCADD patients obtained during a metabolic decompensation showed an accumulation of medium- and short-chain acylcarnitines, just like the acyl-CoA pool in the MCADD model. The model suggested some rescues that increased flux and CoASH, notably increasing short-chain acyl-CoA dehydrogenase (SCAD) levels. Proteome analysis of MCADD patient-derived fibroblasts indeed revealed elevated levels of SCAD in a patient with a clinically asymptomatic state. This is a rescue for MCADD that has not been explored before. Personalised models based on these proteomics data confirmed an increased pathway flux and CoASH in the model of an asymptomatic patient compared to those of symptomatic MCADD patients.

CONCLUSIONS

We present a detailed, validated kinetic model of mFAO in human liver, with solubility-dependent metabolite partitioning. Personalised modelling of individual patients provides a novel explanation for phenotypic heterogeneity among MCADD patients. Further development of personalised metabolic models is a promising direction to improve individualised risk assessment, management and monitoring for inborn errors of metabolism.

Instability of Acylcarnitines in Stored Dried Blood Spots: The Impact on Retrospective Analysis of Biomarkers for Inborn Errors of Metabolism

Stored dried blood spots (DBS) can provide valuable samples for the retrospective diagnosis of inborn errors of metabolism, and for validation studies for newborn blood spot screening programs. Acylcarnitine species are subject to degradation upon long-term storage at room temperature, but limited data are available on the stability in original samples and the impact on acylcarnitine ratios. We analysed complete acylcarnitine profiles by flow-injection tandem mass spectrometry in 598 anonymous DBS stored from 2013 to 2017, at +4 °C during the first year and thereafter at room temperature. The concentrations of C2-, C3-, C4-, C5-, C6-, C8-, C10:1-, C10-, C12:1-, C12-, C14:1-, C14-, C16:1-, C16-, C18:2-, C18:1-, C18-, C5OH+C4DC-, C18:1OH-, and C16DC-carnitine decreased significantly, whereas a positive trend was found for free carnitine. Only the C4/C8-, C8/C10-, C14:1/C10- and C14:1/C16-carnitine ratios appeared robust for the metabolite instability. The metabolite instability may provoke the wrong interpretation of test results in the case of retrospective studies and risk the inaccurate estimation of cut-off targets in validation studies when only stored control DBS are used. We recommend including control DBS in diagnostic, retrospective cohort studies, and, for validation studies, we recommend using fresh samples and repeatedly re-evaluating cut-off targets.

Altered Serum Amino Acid and Acylcarnitine Profiles in Hyperinsulinemic Hypoglycemia and Ketotic Hypoglycemia

BACKGROUND

In addition to inborn metabolic disorders, altered metabolic profiles were reported to be associated with the risk and prognosis of some non-metabolic diseases, while as a rare metabolic disease, the overall secondary metabolic spectrum in congenital hyperinsulinemic hypoglycemia (HH) is largely undetermined. Therefore, we investigated metabolic profiles in HH patients and used ketotic hypoglycemia (KH) patients as a control cohort to unveil their distinct metabolic features.

METHODS

A total of 97 hypoglycemia children, including 74 with hyperinsulinemic hypoglycemia and 23 with ketotic hypoglycemia, and 170 euglycemia control subjects were studied retrospectively. Clinical and biochemical data were collected. The normoglycemic spectra of amino acids and acylcarnitines were determined by liquid chromatography tandem mass spectrometry. The serum insulin and fatty acid concentrations during standardized fasting tests in hypoglycemia patients were also collected. Receiver operating characteristic curve analysis was performed to screen potential biomarkers.

RESULTS

Among the normoglycemic spectra of amino acids, blood valine (p < 0.001), arginine (p < 0.001), threonine (p = 0.001), glutamate (p = 0.002), methionine (p = 0.005), ornithine (p = 0.008), leucine (p = 0.014), alanine (p = 0.017), proline (p = 0.031), citrulline (p = 0.042), aspartate (p = 0.046), and glycine (p = 0.048) levels differed significantly among the three groups. Significantly decreased levels of long- (C14:1, p < 0.001; C18, p < 0.001), medium- (C8, p < 0.001; C10, p < 0.001; C10:1, p < 0.001), and short-chain (C4-OH, p < 0.001; C5OH, p < 0.001) acylcarnitines were found in the hyperinsulinemic hypoglycemia group. Hyperinsulinemic hypoglycemia children with focal lesions and diffuse lesions had similar amino acid and acylcarnitine spectra. C10:1 < 0.09 μmol/L, threonine > 35 μmol/L, and threonine/C10:1 > 440 showed sensitivities of 81.1, 66.2, and 81.1% and specificities of 72.7, 78.3, and 81.8%, respectively, in distinguishing HH from KH.

CONCLUSIONS

We found significantly different altered serum amino acid and acylcarnitine profiles at normoglycemia, especially decreased C10:1 and increased threonine levels, between HH and KH children, which may reflect the insulin ketogenesis inhibition effect in HH patients; however, the detailed mechanisms and physiological roles remain to be studied in the future.