In patients with phenylketonuria (PKU), a low-phenylalanine (Phe) diet supplemented with low-protein foods and a Phe-free amino acid mixture favors a dietary intake rich in carbohydrates, but little is known about how these molecules are metabolized in this setting. The objective of the present study was to analyze carbohydrate metabolism in patients with hyperphenylalaninemia. We conducted a multicenter cross-sectional study to investigate biochemical markers of basal and postprandial carbohydrate metabolism in PKU patients according to age, Phe tolerance, waist circumference and body mass index (BMI), diet, tetrahydrobiopterin (BH4) supplementation, and adherence to treatment. Basal biomarkers and anthropometric parameters were also evaluated in patients with mild hyperphenylalaninemia (MHPA) and in healthy controls. A total of 83 patients aged 4–52 years were studied; 68.7% had PKU and 31.3% had MHPA. 68 healthy controls of similar sex and age were also evaluated Metabolic control was adequate in 71.9% of PKU patients. Fasting glucose levels (mean 80.77 ± 8.06 mg/dL) were high in just one patient, but fasting insulin levels, with a mean of 12.74 ± 8.4 mIU/L, were altered in 15 PKU patients (26.3%) and markedly higher than in patients with MPHA (p = 0.035). Fasting insulin levels and Homeostasis Model Assessment Insulin Resistance (HOMA-IR) were significantly higher than in healthy controls and correlated with body mass index, waist circumference, age, and also showed statistically significant differences according to diagnosis and Phe tolerance (p < 0.05). Patients under BH4 therapy had lower insulin levels and HOMA-IR. A higher mean carbohydrate intake from AA mixtures was observed in classic PKU patients. The caloric intake in the form of carbohydrates was also higher in PKU than MHPA patients (p = 0.038) and it was correlated with basal insulin (rho = 0.468, p = 0.006), HOMA-IR (rho = 0.423, p = 0.02), BMI (rho 0.533, p = 0.002), and waist circumference (rho 0.584, p = 0.0007). This study shows that PKU patients are at risk of carbohydrate intolerance and insulin resistance, more evident in adults and overweight patients, probably related to their higher caloric intake in form carbohydrate content. A higher dependency of AA mixtures was demonstrated in PKU patients.

Treatment of fatty acid oxidation disorders is based on dietary, pharmacological and metabolic decompensation measures. It is essential to provide the patient with sufficient glucose to prevent lipolysis and to avoid the use of fatty acids as fuel as far as possible. Dietary management consists of preventing periods of fasting and restricting fat intake by increasing carbohydrate intake, while maintaining an adequate and uninterrupted caloric intake. In long-chain deficits, long-chain triglyceride restriction should be 10% of total energy, with linoleic acid and linolenic acid intake of 3–4% and 0.5–1% (5/1–10/1 ratio), with medium-chain triglyceride supplementation at 10–25% of total energy (total MCT+LCT ratio = 20–35%). Trihepatnoin is a new therapeutic option with a good safety and efficacy profile. Patients at risk of rhabdomyolysis should ingest MCT or carbohydrates or a combination of both 20 min before exercise. In medium- and short-chain deficits, dietary modifications are not advised (except during exacerbations), with MCT contraindicated and slow sugars recommended 20 min before any significant physical exertion. Parents should be alerted to the need to increase the amount and frequency of carbohydrate intake in stressful situations. The main measure in emergency hospital treatment is the administration of IV glucose. The use of carnitine remains controversial and new therapeutic options are under investigation.

Background and objectives: Glycerol phenylbutyrate (GPB) has demonstrated safety and efficacy in patients with urea cycle disorders (UCDs) by means of its clinical trial program, but there are limited data in clinical practice. In order to analyze the efficacy and safety of GPB in clinical practice, here we present a national Spanish experience after direct switching from another nitrogen scavenger to GPB. Methods: This observational, retrospective, multicenter study was performed in 48 UCD patients (age 11.7 ± 8.2 years) switching to GPB in 13 centers from nine Spanish regions. Clinical, biochemical, and nutritional data were collected at three different times: prior to GPB introduction, at first follow-up assessment, and after one year of GPB treatment. Number of related adverse effects and hyperammonemic crisis 12 months before and after GPB introduction were recorded. Results: GPB was administered at a 247.8 ± 102.1 mg/kg/day dose, compared to 262.6 ± 126.1 mg/kg/day of previous scavenger (46/48 Na-phenylbutyrate). At first follow-up (79 ± 59 days), a statistically significant reduction in ammonia (from 40.2 ± 17.3 to 32.6 ± 13.9 μmol/L, p < 0.001) and glutamine levels (from 791.4 ± 289.8 to 648.6 ± 247.41 μmol/L, p < 0.001) was observed. After one year of GPB treatment (411 ± 92 days), we observed an improved metabolic control (maintenance of ammonia and glutamine reduction, with improved branched chain amino acids profile), and a reduction in hyperammonemic crisis rate (from 0.3 ± 0.7 to less than 0.1 ± 0.3 crisis/patients/year, p = 0.02) and related adverse effects (RAE, from 0.5 to less than 0.1 RAEs/patients/year p < 0.001). Conclusions: This study demonstrates the safety of direct switching from other nitrogen scavengers to GPB in clinical practice, which improves efficacy, metabolic control, and RAE compared to previous treatments.

Human milk (HM) offers important nutritional benefits. However, except for phenylketonuria (PKU), there are little data on optimal levels of consumption of HM and a special formula free of disease-related amino acids (SF-AA) in infants with inborn errors of metabolism of amino acids and proteins (IEM-AA-P). We designed a spreadsheet to calculate the amounts of SF-AA and HM required to cover amino acid, protein, and energy needs in patients with the nine main IEM-AA-P in infants aged under 6 months. Upon entering the infant’s weight and the essential amino acid or intact protein requirements for the specific IEM, the spreadsheet calculates the corresponding required volume of HM based on the amino acid concentration in HM. Next, the theoretical daily fluid intake (typical range, 120–200 mL/kg/day) is entered, and the estimated daily fluid intake is calculated. The required daily volume of SF-AA is calculated as the difference between the total fluid intake value and the calculated volume of HM. The spreadsheet allows for the introduction of a range of requirements based on the patient’s metabolic status, and includes the option to calculate the required volume of expressed HM, which may be necessary in certain conditions such as MMA/PA and UCD. In cases in which breastfeeding on demand is feasible, the spreadsheet determines the daily amount of SF-AA divided over 6–8 feeds, assuming that SF-AA is administered first, followed by HM as needed. Intake data calculated by the spreadsheet should be evaluated in conjunction with data from clinical and nutritional analyses, which provide a comprehensive understanding of the patient’s nutritional status and help guide individualized dietary management for the specific IEM.

Inborn errors of metabolism (IEM) constitute a huge group of rare diseases affecting 1 in every 1000 newborns. Next-generation sequencing has transformed the diagnosis of IEM, leading to its proposed use as a second-tier technology for confirming cases detected by clinical/biochemical studies or newborn screening. The diagnosis rate is, however, still not 100%. This paper reports the use of a personalized multi-omics (metabolomic, genomic and transcriptomic) pipeline plus functional genomics to aid in the genetic diagnosis of six unsolved cases, with a clinical and/or biochemical diagnosis of galactosemia, mucopolysaccharidosis type I (MPS I), maple syrup urine disease (MSUD), hyperphenylalaninemia (HPA), citrullinemia, or urea cycle deficiency. Eight novel variants in six genes were identified: six (four of them deep intronic) located in GALE, IDUA, PTS, ASS1 and OTC, all affecting the splicing process, and two located in the promoters of IDUA and PTS, thus affecting these genes’ expression. All the new variants were subjected to functional analysis to verify their pathogenic effects. This work underscores how the combination of different omics technologies and functional analysis can solve elusive cases in clinical practice.

The determination of acylcarnitines (AC) in dried blood spots (DBS) by tandem mass spectrometry in newborn screening (NBS) programs has enabled medium-chain acyl-coA dehydrogenase deficiency (MCADD) to be identified in presymptomatic newborns. Nevertheless, different confirmatory tests must be performed to confirm the diagnosis. In this work, we have collected and analyzed the NBS results and confirmatory test results (plasma AC, molecular findings, and lymphocyte MCAD activity) of forty individuals, correlating them with clinical outcomes and treatment, with the aim of obtaining useful diagnostic information that could be applied in the follow-up of the patients. Our results led us to classify patients into two groups. The first group (14 cases) had high increased octanoylcarnitine (C8) levels, biallelic pathogenic variants, and severe impaired enzyme activity (<10% of the intra-assay control (IAC)); all of these cases received nutritional therapy and required carnitine supplementation during follow-up, representing the most severe form of the disease. The second group (16 patients) was a heterogeneous group presenting moderate increases in C8, biallelic likely pathogenic/pathogenic variants, and intermediate activity (<41% IAC). All of them are currently asymptomatic and could be considered as having a milder form of the disease. Finally, eight cases presented a normal–mild increase in plasma C8, with only one pathogenic variant detected, and high–intermediate residual activity (15–100%). Based on our results, we confirm that combined evaluation of acylcarnitine profiles, genetic findings, and residual enzyme activities proves useful in predicting the risk of future metabolic decompensation, in making decisions regarding future treatment or follow-up, and also in confirming the clinical effects of unknown clinical variants.