Muscle and Bone Health in Young Chilean Adults with Phenylketonuria and Different Degrees of Compliance with the Phenylalanine Restricted Diet.

There are concerns about muscle and bone health in patients with Phenylketonuria (PKU). Our aim was to compare muscle mass, function, and bone health among young adults with PKU who maintained or suspended dietary treatment. METHODS: Three groups were considered-PKU-1: 10 patients who used a protein substitute (PS) without phenylalanine (Phe); PKU-2: 14 patients who used the PS without Phe until eighteen years old and then practiced mostly a vegan diet; and 24 matched healthy controls. A 24 h recall survey, blood parameters, body composition and bone mineral density through DEXA, rectus femoris thickness by ultrasound, hand grip strength, submaximal exercise test, and walking speed were assessed. RESULTS: PKU-1 patients had lower hand grip strength than their matched controls, but no other differences. Compared to controls, the PKU-2 group had lower fat-free mass (p = 0.01), less spine and femoral bone mineral density (p = 0.04 and p < 0.01, respectively), and peak workload on the incremental test (p = 0.03). When comparing PKU groups, blood Phe levels were significantly lower in the PKU-1 group (p = 0.02). CONCLUSIONS: Among PKU patients, abandoning the dietary treatment and maintaining high blood Phe concentrations could be deleterious for muscles and bones. However, we cannot discard other causes of bone and muscle damage in these patients.

Risk of Developing Insulin Resistance in Adult Subjects with Phenylketonuria: Machine Learning Model Reveals an Association with Phenylalanine Concentrations in Dried Blood Spots.

Phenylketonuria (PKU) is an autosomal recessive inborn error of metabolism where high phenylalanine (Phe) concentrations cause irreversible intellectual disability that can be prevented by newborn screening and early treatment. Evidence suggests that PKU subjects not adherent to treatment could be at risk of insulin resistance (IR). We studied how Phe concentrations (PheCs) relate to IR using machine learning (ML) and derived potential biomarkers. In our cross-sectional study, we analyzed subjects with neonatal diagnoses of PKU, grouped as follows: 10 subjects who adhered to treatment (G1); 14 subjects who suspended treatment (G2); and 24 control subjects (G3). We analyzed plasma biochemical variables, as well as profiles of amino acids and acylcarnitines in dried blood spots (DBSs). Higher PheCs and plasma insulin levels were observed in the G2 group compared to the other groups. Additionally, a positive correlation between the PheCs and homeostatic measurement assessments (HOMA-IRs) was found, as well as a negative correlation between the HOMA-Sensitivity (%) and quantitative insulin sensitivity check index (QUICKI) scores. An ML model was then trained to predict abnormal HOMA-IRs using the panel of metabolites measured from DBSs. Notably, ranking the features' importance placed PheCs as the second most important feature after BMI for predicting abnormal HOMA-IRs. Our results indicate that low adherence to PKU treatment could affect insulin signaling, decrease glucose utilization, and lead to IR.