Teresa D. Douglas

Updated, web-based nutrition management guideline for PKU: An evidence and consensus based approach

BACKGROUND In 2014, recommendations for the nutrition management of phenylalanine hydroxylase deficiency were published as a companion to the concurrently published American College of Medical Genetics and Genomics guideline for the medical treatment of phenylketonuria (PKU). These were developed primarily from a summary of findings from the PKU scientific review conference sponsored by the National Institutes of Health and Agency for Healthcare Research & Quality along with additional systematic literature review. Since that time, the Genetic Metabolic Dietitians International and the Southeast Regional Newborn Screening and Genetics Collaborative have partnered to create a web-based technology platform for the update and development of nutrition management guidelines for inherited metabolic disorders. OBJECTIVE The purpose of this PKU guideline is to establish harmonization in treatment and monitoring, to guide the integration of nutrition therapy in the medical management of PKU, and to improve outcomes (nutritional, cognitive, and developmental) for individuals with PKU in all life stages while reducing associated medical, educational, and social costs. METHODS Six research questions critical to PKU nutrition management were formulated to support guideline development: Review, critical appraisal, and abstraction of peer-reviewed studies and unpublished practice literature, along with expert Delphi survey feedback, nominal group process, and external review from metabolic physicians and dietitians were utilized for development of recommendations relevant to each question. Recommendations address nutrient intake, including updated protein requirements, optimal blood phenylalanine concentrations, nutrition interventions, monitoring parameters specific to life stages, adjunct therapies, and pregnancy and lactation. Recommendations were graded using a rigorous system derived from the Academy of Nutrition and Dietetics. RESULTS AND CONCLUSION These guidelines, updated utilizing a thorough and systematic approach to literature analysis and national consensus process, are now easily accessible to the global community via the newly developed digital platform. For additional details on specific topics, readers are encouraged to review materials on the online portal: https://GMDI.org/.

The effects of sapropterin on urinary monoamine metabolites in phenylketonuria

BACKGROUND Sapropterin dihydrochloride (BH4, tetrahydrobiopterin) can lower plasma phenylalanine (Phe) concentrations for a subset of patients with phenylketonuria (PKU), an inborn error of metabolism. Studies suggest that monoamine neurotransmitter concentrations are low in PKU patients. Sapropterin functions as a cofactor for hydroxylases specific to Phe, tyrosine, and tryptophan metabolism, pathways essential for catecholamine and serotonin synthesis. OBJECTIVE The objective of this study is to determine the impact of sapropterin on monoamine neurotransmitter status in patients with PKU. DESIGN 58 PKU subjects were provided 20 mg/kg of sapropterin for 1 month. Those who responded with at least a 15% decrease in plasma Phe received sapropterin for 1 year, while Non-responders discontinued it. After an additional 3 months, Responders who demonstrated increased Phe tolerance and decreased medical food dependence were classified as Definitive, whereas Responders unable to liberalize their diet without compromising plasma Phe control were identified as Provisional. At study visits, patients provided blood for plasma amino acids, 3-day diet records, and 12-hour urine samples analyzed for epinephrine (E), dopamine (DA), dihydroxyphenylacetate (DOPAC), homovanillic acid (HVA), 3-methoxytyramine (3MT), serotonin (5HT), and 5-hydroxyindole acetic acid (5HIAA) using HPLC with electrochemical detection. RESULTS Compared with healthy non-PKU controls, subjects with PKU had significantly lower baseline concentrations of DA, HVA, 3MT, 5HT, and 5HIAA (p < 0.001 for all). Medical food protein intake had a direct association with DA, HVA, 5HT, and 5HIAA during the study (p < 0.05 for all), while plasma Phe had an inverse association with these markers (p < 0.01 for all). DOPAC was also associated with plasma Phe throughout the year (p = 0.035), although not at baseline. Patients with PKU had a significant increase in HVA (p = 0.015) after 1 month of sapropterin. When stratifying by Responder and Non-Responder status, significance of HVA increase in Non-responders (p = 0.041) was confirmed, but not in Responders (p = 0.081). A declining trend in urinary 5HIAA, significant only after controlling for plasma Phe (p = 0.019), occurred for Definitive Responders during the 1-year study. CONCLUSION Urinary monoamine concentrations are low in patients with PKU and are influenced by oral sapropterin and medical food intake, highlighting the importance of these therapies to neurotransmitter metabolism in phenylketonuria.

Accuracy of Six Anthropometric Skinfold Formulas Versus Air Displacement Plethysmography for Estimating Percent Body Fat in Female Adolescents with Phenylketonuria

BACKGROUND The reliability of studies investigating biological and therapeutic factors that influence body composition in PKU patients depends on accurate anthropometric measurements. OBJECTIVE To determine the precision of six anthropometric skinfold equations versus air displacement plethysmography (ADP) for predicting body fat (BF) percentage in female adolescents with PKU. DESIGN Skinfold and ADP measurements were recorded from a cross section of 59 female patients with PKU, ages 10-19 years. Anthropometric measures were used to calculate percent BF using equations published by Peterson et al., Loftin et al. (TAAG), Slaughter et al., Wilmore and Behnke, Durnin and Womersley, and Jackson et al. Bland-Altman agreement analysis and Lins concordance correlation coefficient (ρ c) were used to determine the precision of each equation compared with percent BF determined by ADP. RESULTS Adolescent females with PKU had a mean BF content of 33% measured by ADP, with an inverse association to birth cohort (r = -0.3, P = 0.016). Based on the Bland-Altman method for evaluating agreement, only Petersons equation did not differ significantly from ADP percent BF results (P = 0.23). Petersons skinfold equation yielded percent BF estimates with the smallest mean difference from ADP and the smallest standard deviation (0.76 ± 4.8), whereas Slaughters equation had the largest (-7.7 ± 7.4). Loftins TAAG equation had the least mean percent error (2.2%), while Slaughters equation had the highest (19%). Both TAAG and Petersons equations had the highest concordance correlation coefficients (ρ c = 0.8, ρ c = 0.8), while Slaughters equation had the lowest (ρ c = 0.3). CONCLUSIONS Petersons equation is a precise surrogate for ADP when estimating percent BF in female adolescents with PKU, though Loftins TAAG equation is also effective. Observed decreases in adiposity correlating with birth cohort could reflect steady improvements in patient nutrition care.

Protein intake and physical activity are associated with body composition in individuals with phenylalanine hydroxylase deficiency

OBJECTIVE Determine whether body composition as it relates to dietary protein in patients with phenylalanine hydroxylase (PAH) deficiency is associated with genotype, dietary factors, and lifestyle choices. METHODS We examined associations between protein intake (intact and medical foods: MF) and body composition in PAH-deficient patients along with, physical activity, and genotype. Protein intakes (total, intact, and MF) were analysed from three-day food records with Nutrition Data System for Research (NDSR) in 59 children and 27 adults (N=86, median age=16.0years). The severity of PAH deficiency was classified using the genotype assigned value method (AV sum). Physical activity was assessed using a study-developed question (light vs. intense activity). Body composition was measured by DXA, including android:gynoid ratio (A:G), fat-free mass index (FFMI), fat mass index (FMI), and FMI:FFMI ratio. RESULTS High intact protein intake was associated with high FFMI (rs=0.75, p=0.008) and low FMI:FFMI (rs=-0.59, p=0.04) in adults. Only in children, MF protein (rs=0.38, p=0.04) was directly proportional to FFMI. Median intact protein intakes of adults (25.1 vs. 9.9g/d, p<0.001) and children (11 vs. 6g/d, p<0.001) were higher than prescribed. Only in adults, the actual median MF protein intake was lower than prescribed (53 vs. 60g/d, p=0.03). In adults and children, light activity was associated with higher fat mass indices compared to intense activity (adults: FMI:FFMI: β=1.1, p=0.001, children: FMI:FFMI: β=1.1, p=0.007; FMI β=2.1, p=0.01; A:G β=1.1, p=0.04). All associations remained significant after covariate adjustment. Genotype was not associated with body composition. CONCLUSIONS Although fat-free mass in adults was positively associated with intact protein intake, it should be consumed as prescribed per individual tolerance to maintain plasma Phe concentrations within treatment range. In children, total protein maximized with MF should be encouraged to promote lean mass. Nutrition counselling could be complemented with physical activity recommendations for optimal clinical outcomes.