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Background: Assessing dietary phenylalanine (Phe) tolerance is crucial for managing hyperphenylalaninemia (HPA) in children. However, traditionally, adjusting the diet requires significant time from clinicians and parents. This study aims to investigate the development of a machine-learning model that predicts a range of dietary Phe intake tolerance for children with HPA over 10 years following diagnosis. Methods: In this multicenter retrospective observational study, we collected the genotypes of phenylalanine hydroxylase (PAH), metabolic profiles at screening and diagnosis, and blood Phe concentrations corresponding to dietary Phe intake from over 10 years of follow-up data for 204 children with HPA. To incorporate genetic information, allelic phenotype value (APV) was input for 2965 missense variants in the PAH gene using a predicted APV (pAPV) model. This model was trained on known pheno-genotype relationships from the BioPKU database, utilizing 31 features. Subsequently, a multiclass classification model was constructed and trained on a dataset featuring metabolic data, genetic data, and follow-up data from 3177 events. The final model was fine-tuned using tenfold validation and validated against three independent datasets. Results: The pAPV model achieved a good predictive performance with root mean squared error (RMSE) of 1.53 and 2.38 on the training and test datasets, respectively. The variants that cause amino acid changes in the region of 200–300 of PAH tend to exhibit lower pAPV. The final model achieved a sensitivity range of 0.77 to 0.91 and a specificity range of 0.8 to 1 across all validation datasets. Additional assessment metrics including positive predictive value (0.68–1), negative predictive values (0.8–0.98), F1 score (0.71–0.92), and balanced accuracy (0.8–0.92) demonstrated the robust performance of our model. Conclusions: Our model integrates metabolic and genetic information to accurately predict age-specific Phe tolerance, aiding in the precision management of patients with HPA. This study provides a potential framework that could be applied to other inborn errors of metabolism. [ABSTRACT FROM AUTHOR]

Background: The GCH1 gene encodes the enzyme guanosine triphosphate cyclohydrolase I (GTPCH), which catalyzes the rate‐limiting step in the biosynthesis of tetrahydrobiopterin (BH4), a critical cofactor in the production of monoamine neurotransmitters. Autosomal dominant GTPCH (adGTPCH) deficiency is the most common cause of dopa‐responsive dystonia (DRD), whereas the recessive form (arGTPCH) is an ultrarare and poorly characterized disorder with earlier and more complex presentation that may disrupt neurodevelopmental processes. Here, we delineated the phenotypic spectrum of ARGTPCHD and investigated the predictive value of biochemical and genetic correlates for disease outcome. Objectives: The aim was to study 4 new cases of arGTPCH deficiency and systematically review patients reported in the literature. Methods: Clinical, biochemical, and genetic data and treatment response of 45 patients are presented. Results: Three phenotypes were outlined: (1) early‐infantile encephalopathic phenotype with profound disability (24 of 45 patients), (2) dystonia‐parkinsonism phenotype with infantile/early‐childhood onset of developmental stagnation/regression preceding the emergence of movement disorder (7 of 45), and (3) late‐onset DRD phenotype (14 of 45). All 3 phenotypes were responsive to pharmacological treatment, which for the first 2 must be initiated early to prevent disabling neurodevelopmental outcomes. A gradient of BH4 defect and genetic variant severity characterizes the 3 clinical subgroups. Hyperphenylalaninemia was not observed in the second and third groups and was associated with a higher likelihood of intellectual disability. Conclusions: The clinical spectrum of arGTPCH deficiency is a continuum from early‐onset encephalopathies to classical DRD. Genotype and biochemical alterations may allow early diagnosis and predict clinical severity. Early treatment remains critical, especially for the most severe patients. [ABSTRACT FROM AUTHOR]

Characterization of Kuvan tablets involved thorough analysis of physical, chemical, and dissolution properties. Formulation development encompassed pre-formulation studies, feasibility trials, and process optimization. Kuvan tablets demonstrated variability in sapropterin dihydrochloride concentration but rapid dissolution across different media. Consistent mechanical strength, low impurity levels, and appropriate pH values were observed, ensuring efficacy, safety, and reliability. [ABSTRACT FROM AUTHOR]

Abstract Background Assessing dietary phenylalanine (Phe) tolerance is crucial for managing hyperphenylalaninemia (HPA) in children. However, traditionally, adjusting the diet requires significant time from clinicians and parents. This study aims to investigate the development of a machine-learning model that predicts a range of dietary Phe intake tolerance for children with HPA over 10 years following diagnosis. Methods In this multicenter retrospective observational study, we collected the genotypes of phenylalanine hydroxylase (PAH), metabolic profiles at screening and diagnosis, and blood Phe concentrations corresponding to dietary Phe intake from over 10 years of follow-up data for 204 children with HPA. To incorporate genetic information, allelic phenotype value (APV) was input for 2965 missense variants in the PAH gene using a predicted APV (pAPV) model. This model was trained on known pheno-genotype relationships from the BioPKU database, utilizing 31 features. Subsequently, a multiclass classification model was constructed and trained on a dataset featuring metabolic data, genetic data, and follow-up data from 3177 events. The final model was fine-tuned using tenfold validation and validated against three independent datasets. Results The pAPV model achieved a good predictive performance with root mean squared error (RMSE) of 1.53 and 2.38 on the training and test datasets, respectively. The variants that cause amino acid changes in the region of 200–300 of PAH tend to exhibit lower pAPV. The final model achieved a sensitivity range of 0.77 to 0.91 and a specificity range of 0.8 to 1 across all validation datasets. Additional assessment metrics including positive predictive value (0.68–1), negative predictive values (0.8–0.98), F1 score (0.71–0.92), and balanced accuracy (0.8–0.92) demonstrated the robust performance of our model. Conclusions Our model integrates metabolic and genetic information to accurately predict age-specific Phe tolerance, aiding in the precision management of patients with HPA. This study provides a potential framework that could be applied to other inborn errors of metabolism.

Phenylalanine hydroxylase (PAH) is predominantly a hepatic enzyme that catalyzes phenylalanine (Phe) into tyrosine, which is the rate-limiting step in Phe catabolism. Biallelic variants in the PAH gene cause PAH enzyme deficiency. Phenylketonuria (PKU) is an autosomal recessive disorder that causes neurologic, behavioral, and dermatological findings. PKU could be divided clinically into three types based on the blood Phe levels: classic phenylketonuria (cPKU), mild-moderate phenylketonuria (mPKU), and mild hyperphenylalaninemia (MHP). This study aimed to determine the phenotypic and genotypic characteristics of Turkish PKU patients in the eastern region of Türkiye. Demographic characteristics, serum Phe levels, treatments, and PAH variants of 163 patients with PKU and hyperphenylalaninemia (HPA) were retrospectively evaluated. Blood Phe levels of the patients were analyzed with the high-performance liquid chromatography method. For PAH gene analysis, next-generation sequencing was performed. Of the 163 patients included in the study, 38 (23.3 %) had cPKU, 16 (9.8 %) had mPKU, and 109 (66.9 %) had MHP. Homozygous variants in the PAH gene were detected in 66 (40.5 %) of the patients, while compound heterozygous variants were detected in 97 (59.5 %) patients. Two novel and 35 recurrent variants in the PAH gene were detected. Of the two novel variants, one was missense (p.Phe351Leu) and the other was frameshift (p.Met276Cysfs*65). The most frequently detected variants were p.Thr380Met (18 %), p.Arg261Gln (16.8 %), and p.Ala300Ser (12.8 %). All patients with the homozygous c.1066-11G>A variant exhibited cPKU phenotype. The c.898G>T (p.Ala300Ser), c.1139C>T (p.Thr380Met), and c.1208C>T (p.Ala403Val) variants were statistically related to mild phenotype. On the other hand, c.592_613del (p.Tyr198Serfs*136), c.1028A>G (p.Tyr343Cys), and c.782G>A (p.Arg261Gln) variants were more frequently detected in the cPKU group. Our study, conducted with patients from the eastern region of Türkiye, demonstrates the genetic heterogeneity in the Turkish population. Simultaneously, our research contributes to genotype–phenotype correlation and expands the genotypic spectrum by identifying novel variants. [ABSTRACT FROM AUTHOR]

ObjectiveSapropterin dihydrochloride is the first drug for the therapy of phenylketonuria, which is a rare disease that occurs one of 10,000–15,000 newborns. As a result, detailed and comprehensive reports on the safety of sapropterin in large, real-world populations are required. The purpose of this study is to undertake a complete analysis of sapropterin’s adverse events (AEs) using the FDA Adverse Event Reporting System (FAERS) database.MethodsWe retrieved reports of adverse events with sapropterin as the principal suspect from FAERS between the first quarter of 2008 and the first quarter of 2024. The Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), and Bayesian Confidence Propagation Neural Network (BCPNN) were utilized to detect AE signals.ResultsThe study collected 4,953 suspected AE cases from the FAERS database, with sapropterin as the major suspect. A total of 130 positive signals were obtained utilizing the ROR, PRP, and BCPNN. The FAERS database revealed that common clinical AEs of sapropterin included vomiting, upper respiratory infection, rhinorrhea, and a reduction in amino acid concentrations. Furthermore, we detected probable unexpected adverse events (AEs) using disproportionality analysis, including gastroesophageal reflux disease, flatulence, influenza, ear infection, viral infection, pharyngitis streptococcal, spontaneous abortion, and nephrolithiasis.ConclusionBy analyzing huge amounts of real-world data from the FAERS database, we found potential novel AEs of sapropterin using disproportionate analysis. It is advantageous for healthcare professionals and pharmacists to focus on efficiently managing sapropterin’s high-risk adverse events, improving drug levels in clinical settings, and ensuring patient medication safety.

This study, conducted in the Republic of North Ossetia-Alania (RNOA), aimed to explore the genetic landscape of hyperphenylalaninemia (HPA) and phenylketonuria (PKU) in the Ossetian population using data from newborn screening (NBS). Through comprehensive molecular genetic analysis of 29 patients with HPA from diverse ethnic backgrounds, two major genetic variants in the PAH gene, P281L and P211T, were identified, constituting 50% of all detected pathogenic alleles in Ossetian patients. Remarkably, these variants exhibited an exceptionally high frequency in the Ossetian population, surpassing global prevalence rates. This study unveiled a notable prevalence of mild forms of HPA (78%), underscoring the importance of genetic counseling for carriers of pathogenic variants in the PAH gene. Moreover, the findings emphasized the necessity for ongoing monitoring of patients with mild forms, as they may lack significant symptoms for diagnosis, potentially impacting offspring. Overall, this research offers valuable insights into the genetic landscape of HPA and PKU in the Ossetian population. [ABSTRACT FROM AUTHOR]

Women with phenylketonuria (PKU) should maintain blood phenylalanine (phe) concentration within the recommended range before and during pregnancy to prevent maternal PKU syndrome (MPKUS) in their offspring. Women who gave birth to children with MPKUS symptoms were more likely to report elevated phe concentration before pregnancy, and barriers to accessing components of their dietary management during pregnancy, including blood phe testing, medical food, modified low-protein foods, and healthcare visits with PKU specialists.

This study, conducted in the Republic of North Ossetia-Alania (RNOA), aimed to explore the genetic landscape of hyperphenylalaninemia (HPA) and phenylketonuria (PKU) in the Ossetian population using data from newborn screening (NBS). Through comprehensive molecular genetic analysis of 29 patients with HPA from diverse ethnic backgrounds, two major genetic variants in the PAH gene, P281L and P211T, were identified, constituting 50% of all detected pathogenic alleles in Ossetian patients. Remarkably, these variants exhibited an exceptionally high frequency in the Ossetian population, surpassing global prevalence rates. This study unveiled a notable prevalence of mild forms of HPA (78%), underscoring the importance of genetic counseling for carriers of pathogenic variants in the PAH gene. Moreover, the findings emphasized the necessity for ongoing monitoring of patients with mild forms, as they may lack significant symptoms for diagnosis, potentially impacting offspring. Overall, this research offers valuable insights into the genetic landscape of HPA and PKU in the Ossetian population.

DNAJC12-deficient hyperphenylalaninemia is a recently described inborn error of metabolism associated with hyperphenylalaninemia, neurotransmitter deficiency, and developmental delay caused by biallelic pathogenic variants of the DNAJC12 gene. The loss of the DNAJC12-encoded chaperone results in the destabilization of the biopterin-dependent aromatic amino acid hydroxylases, resulting in deficiencies in dopamine, norepinephrine, and serotonin. We present the case of a patient who screened positive for hyperphenylalaninemia on newborn screening and was discovered to be homozygous for a likely pathogenic variant of DNAJC12. Here, we review the management of DNAJC12-related hyperphenylalaninemia and compare our patient to other reported cases in the literature to investigate how early detection and management may impact clinical outcomes.

Phenylketonuria (PKU) is a genetic disorder caused by variations in the phenylalanine hydroxylase (PAH) gene. Among the 3369 reported PAH variants, 33.7% are missense alterations. Unfortunately, 30% of these missense variants are classified as variants of unknown significance (VUS), posing challenges for genetic risk assessment. In our study, we focused on analyzing 836 missense PAH variants following the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines specified by ClinGen PAH Variant Curation Expert Panel (VCEP) criteria. We utilized and compared variant annotator tools like Franklin and Varsome, conducted 3D structural analysis of PAH, and examined active and regulatory site hotspots. In addition, we assessed potential splicing effect of apparent missense variants. By evaluating phenotype data from 22962 PKU patients, our aim was to reassess the pathogenicity of missense variants. Our comprehensive approach successfully reclassified 309 VUSs out of 836 missense variants as likely pathogenic or pathogenic (37%), upgraded 370 likely pathogenic variants to pathogenic, and reclassified one previously considered likely benign variant as likely pathogenic. Phenotypic information was available for 636 missense variants, with 441 undergoing 3D structural analysis and active site hotspot identification for 180 variants. After our analysis, only 6% of missense variants were classified as VUSs, and three of them (c.23A>C/p.Asn8Thr, c.59_60delinsCC/p.Gln20Pro, and c.278A >T/p.Asn93Ile) may be influenced by abnormal splicing. Moreover, a pathogenic variant (c.168G>T/p.Glu56Asp) was identified to have a risk exceeding 98% for modifications of the consensus splice site, with high scores indicating a donor loss of 0.94. The integration of ACMG/AMP guidelines with in silico structural analysis and phenotypic data significantly reduced the number of missense VUSs, providing a strong basis for genetic counseling and emphasizing the importance of metabolic phenotype information in variant curation. This study also sheds light on the current landscape of PAH variants. [ABSTRACT FROM AUTHOR]

The present study aimed to conduct a comprehensive meta-analysis to assess the diagnostic value of fluorometric assays and tandem mass spectrometry (MS/MS) for hyperphenylalaninemia (HPA) and its subtypes. The PubMed, Embase and Cochrane Library databases were searched from inception to October 2023. The present study included studies that reported the newborn screening and genetic features of patients with HPA and excluded duplicate publications, studies without full text, studies with incomplete information, studies from which it was not possible to extract data, animal experiments, reviews and systematic reviews. STATA 15.1 was used to analyze the data. The pooled results revealed that 0.04% [95% confidence interval (CI): 0.019-0.069] of neonatal HPA fluorometric assays and MS/MS. The positive predictive value (PPV) of neonatal HPA screening using fluorometric assays and tandem mass spectrometry was 31.7% (95% CI: 19.6-45.2). Notably, the PPV of neonatal HPA screening using fluorometric assays was 8.3% (95% CI: 7.1-9.6), while the PPV of neonatal HPA screening using tandem mass spectrometry was 31.8% (95% CI: 16.4-49.4). Additionally, the pooled results showed that the incidence of tetrahydrobiopterin deficiency (BH4D) in HPA patients was 12.43% (95% CI: 3.28-25.75) and the incidence of phenylalanine hydroxylase deficiency (PAHD) in HPA patients was 88.65% (95% CI: 78.84-95.86). Newborn screening is an effective method for the early detection of HPA and MS/MS has a greater PPA than fluorometric assays for diagnosing HPA. In addition, in the screening of HPA, the proportion of HPA patients with PAHD was significantly higher than that of patients with BH4D. [ABSTRACT FROM AUTHOR]

• In this review, we have discussed about an autosomal recessive metabolic disorder, Phenylketonuria (PKU), resulting from deficient phenylalanine hydroxylase (PAH) enzyme activity, leading to impaired phenylalanine (Phe) metabolism. • This review provides insights into pathophysiology, current treatment and diagnostic approaches. • We have further explored the wide array of sensors used till date for diagnosis of PKU. Phenylketonuria (PKU) is an autosomal recessive metabolic disorder resulting from deficient phenylalanine hydroxylase (PAH) enzyme activity, leading to impaired phenylalanine (Phe) metabolism. This condition can lead to intellectual disability, epilepsy, and behavioural issues. Treatment typically involves strict dietary restrictions on natural protein intake, supplemented with chemically manufactured protein substitutes containing amino acids other than Phe. Various approaches, including casein glycomacropeptide (GMP), tetrahydrobiopterin (BH 4), phenylalanine ammonia-lyase (PAL) therapy, large neutral amino acid (LNAA) supplementation, enzyme therapy, gene therapy, and medical therapies, aim to prevent Phe transport in the brain to potentially treat PKU. Although newborn screening programs and early dietary interventions have enhanced outcomes of the potential treatment strategies, limitations still persist in this direction. These involve potent accuracy concerns in diagnosis due to the existence of antibiotics in blood of PKU patients, affecting growth of the bacteria in the bacterial inhibition assay. Monitoring involves complex methods for instance, mass spectrometry and high-pressure liquid chromatography, which involve shortcomings such as lengthy protocols and the need for specialized equipment. To address these limitations, adaptable testing formats like bio/nano sensors are emerging with their cost-effectiveness, biodegradability, and rapid, accurate, and sensitive detection capabilities, offering promising alternatives for PKU diagnosis. This review provides insights into current treatment and diagnostic approaches, emphasizing on the potential applications of the diverse sensors intended for PKU diagnosis. [ABSTRACT FROM AUTHOR]

Background: Hyperphenylalaninemia (HPA) is defined as blood phenylalanine (Phe) levels exceeding the normal values (>120 μmol/L or >2 mg/dL) and is caused by a deficiency in the enzyme phenylalanine hydroxylase (PAH). The widespread screening of Phe levels in newborn screening programs has led to a very high number of patients with HPA., Methods: The samples were collected at various ages, not at the point of diagnosis. Nine pterin derivatives, including isoxanthopterin, sepiapterin, xanthopterin, primapterin, biopterin, neopterin, 7,8-dihydrobiopterin, 7,8-dihydroneopterin, and tetrahydrobiopterin (BH4), were analyzed in different HPA classes in serum, dried blood spots (DBS), and urine samples. A total of 18 patients, including six classical phenylketonuria (PKU), eight BH4-responsive PKU, and four mild HPA patients, were included in the study., Results: Among the nine pterin derivatives measured, a significant increase was observed in the levels of isoxanthopterin, biopterin, and 7,8-dihydrobiopterin in serum, dried blood spots (DBS), and urine samples of patients with HPA compared to the control group. However, elevations in isoxanthopterin, biopterin, and 7,8-dihydrobiopterin were observed in all HPA groups, although the extent of elevation varied among the different disease groups. There were also significant differences between HPA subgroups among these high values., Conclusion: In this study, it might be suggested that pterin profiling shows promising potential for its effective utilization in the differential diagnosis of HPA. Pterin profiling demonstrated its efficacy in accurately categorizing patients into distinct subtypes. This approach offers several notable advantages, including the ability to simultaneously screen multiple HPA subtypes through a single test, establish disease decision limits for pterins, shorten the time required for HPA differential diagnosis, reduce the risk of misdiagnosis, and increase overall diagnostic accuracy. This study is the most comprehensive study examining the association between HPA pterin in the literature. In our study, samples obtained from BH4-responsive PKU patients were on treatment. This may have affected the results. Preliminary findings on pterin profiles may need to be replicated in a prospective cohort of samples collected at the time of diagnosis to confirm the results., Competing Interests: The authors have no conflicts of interest to declare., (© 2024 S. Karger AG, Basel.)

Women with phenylketonuria (PKU) should maintain blood phenylalanine (phe) concentration within the recommended range before and during pregnancy to prevent maternal PKU syndrome (MPKUS) in their offspring. Women who gave birth to children with MPKUS symptoms were more likely to report elevated phe concentration before pregnancy, and barriers to accessing components of their dietary management during pregnancy, including blood phe testing, medical food, modified low-protein foods, and healthcare visits with PKU specialists., Competing Interests: The authors declare no conflicts of interest., (© 2024 The Authors.)