フェニルケトン尿症

Phenylketonuria (PKU) is an autosomal recessive inherited metabolic disorder (IMD) characterized by elevated phenylalanine (Phe) levels, requiring a low-protein diet and low-Phe amino acid supplementation from birth to prevent cognitive impairment. Despite early and continuous treatment, emerging evidence indicates that adults with PKU may experience subtle cognitive deficits and features consistent with accelerated aging. This narrative review synthesizes the current evidence on accelerated aging in PKU, describes its clinical manifestations, and explores potential underlying mechanisms. Adults with PKU exhibit greater cardiovascular aging, including arterial stiffness and dyslipidaemia, alongside higher rates of obesity, diabetes, and hypertension compared to adults without PKU. They also tend to demonstrate lower bone mineral density, more extensive white matter changes, and poorer cognitive performance alongside a higher prevalence of mood disorders and reduced quality of life, despite treatment. These physiological differences are thought to be primarily driven by oxidative stress (OS), which appears to be inherent to the pathophysiology of PKU. OS leads to secondary mitochondrial dysfunction and DNA damage, which are also implicated in accelerated aging in PKU, along with epigenetic changes. This review explores in detail the mechanisms implicated in premature aging in PKU and proposes potential aging biomarkers and treatment targets.

OBJECTIVE: Inherited metabolic disorders (IMDs) are heterogeneous genetic diseases whose observed spectrum is influenced by population characteristics, newborn screening (NBS), and diagnostic pathways.This study aimed to characterize confirmed IMDs diagnosed through NBS and symptomatic referrals at a tertiary center in Eastern Türkiye and estimate the regional burden of selected disorders. METHODS: This retrospective study included patients evaluated between September 2022 and September 2024. IMDs were confirmed by biochemical and/or molecular genetic analyses. Population and live-birth data from the defined referral region were used to estimate regional and NBS-based birth prevalence. RESULTS: Among 9603 patients evaluated, 828 (8.6%) had a confirmed IMDs; 580 (70.0%) were identified through NBS, 230 (27.8%) through symptomatic referral, and 18 (2.2%) through family screening. Vitamin and cofactor metabolism (43.8%) and amino acid metabolism disorders (35.7%) predominated. Biotinidase deficiency was the most frequent disorder (n = 360, 43.4%), including 316 (87.8%) partial and 44 (12.2%) profound cases. Neurological manifestations were the most frequent presentation among symptomatic patients (23.2%). Based on 61,409 estimated live births, estimated birth prevalence was 1:627 for the hyperphenylalaninemia/phenylketonuria spectrum and 1:543 for biotinidase deficiency. Minimum estimated regional prevalence was 1.07 and 0.97 per 100,000 for mucopolysaccharidoses and alkaptonuria, respectively. CONCLUSION: NBS and symptom-based evaluation are complementary diagnostic pathways for IMDs. The observed disease spectrum reflects the influence of screening strategies, while symptomatic referrals reveal broader clinical and genetic heterogeneity.

Background: Inherited metabolic disorders (IMDs) are a heterogeneous group of genetic diseases, some of which require lifelong disease-specific dietary management. Children with phenylketonuria (PKU), organic acidemias (OAs), and glycogen storage diseases (GSDs) are particularly susceptible to nutritional imbalances and metabolic disturbances that may adversely affect bone metabolism and skeletal health. However, data regarding bone turnover markers and bone health in these pediatric IMD populations remain limited. Objective: This study aimed to evaluate bone metabolism by assessing biochemical parameters, bone turnover markers, and bone mineral density in children with PKU, OA, and GSD receiving long-term dietary treatment. Methods: This cross-sectional study included 95 children, comprising 25 patients with PKU, 20 patients with organic acidemias, 20 patients with glycogen storage diseases, and 30 healthy age-matched controls. Demographic characteristics, anthropometric measurements, and dietary intake were recorded. Biochemical evaluation included serum calcium, phosphorus, alkaline phosphatase (ALP), parathyroid hormone (PTH), and 25-hydroxyvitamin D levels. Bone turnover was assessed using C-terminal telopeptide of type I collagen (CTX), procollagen type I N-terminal propeptide (P1NP), and osteocalcin (OC) levels. Bone mineral density was evaluated by dual-energy X-ray absorptiometry (DXA). Results: Age and sex distributions were similar among the groups. Height was lower in OA than in controls and PKU, and in GSD than in PKU; weight and BMI were lower in both OA and GSD than in controls and PKU (p < 0.05). Significant differences were observed in dietary energy and macronutrient intake according to disease-specific nutritional regimens. Serum calcium, phosphorus, and 25-hydroxyvitamin D levels were significantly lower in all IMD groups compared with healthy controls (p < 0.001). ALP and PTH levels were significantly higher in PKU, OA, and GSD patients than in controls (p < 0.001). Among bone turnover markers, P1NP and osteocalcin levels significantly differed among groups, with the highest values observed in PKU patients (p = 0.006 and p = 0.028, respectively). CTX levels did not significantly differ among the groups (p = 0.183). DXA Z-scores were significantly lower in all IMD groups than in controls, with the lowest mean Z-scores observed in GSD patients. Conclusions: Children with PKU, OA, and GSD receiving long-term dietary treatment exhibited significant alterations in bone metabolism, characterized by lower vitamin D, calcium, and phosphorus levels, higher ALP and PTH concentrations, differences in bone formation markers, and lower DXA Z-scores compared with controls. Significant differences were observed in the bone formation markers P1NP and osteocalcin, whereas CTX levels remained comparable among the study groups. These findings underscore the importance of regular assessment of bone health and optimization of nutritional management in children under dietary treatment, while acknowledging that disease-specific mechanisms of skeletal involvement may differ among these conditions.

OBJECTIVE: Artificial intelligence (AI)-based large language models (LLMs) are increasingly used to support nutrition-related decision-making; however, their ability to generate clinically appropriate dietary plans for inherited protein metabolism disorders remains largely unexplored. This study aimed to perform an exploratory simulation-based benchmarking analysis of AI-generated dietary plans for phenylketonuria (PKU), maple syrup urine disease (MSUD), and propionic acidemia (PPA) using disease-specific metabolic nutrition guidelines. METHODS: Standardized pediatric case scenarios were developed for PKU, MSUD, and PPA. Using identical English-language prompts, ChatGPT-5.3 Pro and Gemini 3 Pro Advanced each generated 3-day dietary plans. Nutrient composition was analyzed using the BeBiS Nutrition Information System and evaluated against Dietary Reference Intakes (DRIs). Disease-specific nutritional targets, including amino acid intake, protein distribution, and energy provision, were benchmarked against recommendations from Genetic Metabolic Dietitians International (GMDI). Nutritional characteristics of the dietary plans generated by the two AI models were compared using exploratory statistical analyses. RESULTS: Both LLMs generated structured dietary plans with generally acceptable overall nutritional characteristics; however, clinically relevant deviations from disease-specific nutritional targets were identified across all three disorders. In the PKU case, both models achieved the recommended phenylalanine range, but neither simultaneously met protein and tyrosine recommendations. In the MSUD case, differences were primarily related to energy provision and branched-chain amino acid targets, while in the PPA case neither model achieved the recommended balance between intact protein and total protein. These findings demonstrated that conventional measures of nutritional adequacy alone were insufficient to determine the clinical appropriateness of AI-generated dietary plans for inherited protein metabolism disorders. CONCLUSION: General-purpose LLMs can generate structured dietary plans for inherited protein metabolism disorders; however, disease-specific metabolic targets are not consistently achieved. Evaluation of AI-generated dietary plans should therefore extend beyond conventional nutritional assessment and incorporate disease-specific benchmarking against established metabolic nutrition guidelines. This study provides a disease-specific benchmarking framework for evaluating AI-generated dietary plans in inherited protein metabolism disorders.

BACKGROUND: Children with inherited metabolic disorders (IMDs) receiving natural protein-restricted diets may be at risk of micronutrient imbalance. However, data on dietary supplement practices in this population are limited. This study aimed to determine the prevalence of current dietary supplement use and to evaluate supplement types and factors associated with their use. METHODS: In this cross-sectional study, 50 children with IMDs receiving natural protein-restricted diets were included. Parents completed a structured 50-item questionnaire during face-to-face interviews. Information on dietary supplement use, reasons for supplementation, and clinical and sociodemographic characteristics was collected. RESULTS: The prevalence of current dietary supplement use was 36.0% (95% CI, 22.9-50.8). Vitamin-mineral preparations were the most commonly used supplements. Current supplement use was more frequent among children with phenylketonuria who had high dietary adherence than among those with low dietary adherence (50.0% vs. 13.3%, p = 0.034). No significant associations were found with diagnosis, growth status, or sociodemographic characteristics. When dietary supplements were used, they were most often recommended by pediatric metabolic specialists according to individual clinical needs. CONCLUSIONS: Approximately one-third of children with IMDs receiving natural protein-restricted diets were current dietary supplement users. These findings support individualized nutritional assessment and the use of dietary supplements based on clinical evaluation rather than routine supplementation.