Tetrahydrobiopterin treatment in phenylketonuria:A repurposing approach

In phenylketonuria (PKU) patients, early diagnosis by neonatal screening and immediate institution of a phenylalanine-restricted diet can prevent severe intellectual impairment. Nevertheless, outcome remains suboptimal in some patients asking for additional treatment strategies. Tetrahydrobiopterin (BH4) could be one of those treatment options, as it may not only increase residual phenylalanine hydroxylase activity in BH4-responsive PKU patients, but possibly also directly improves neurocognitive functioning in both BH4-responsive and BH4-unresponsive PKU patients. In the present review, we aim to further define the theoretical working mechanisms by which BH4 might directly influence neurocognitive functioning in PKU having passed the blood-brain barrier. Further research should investigate which of these mechanisms are actually involved, and should contribute to the development of an optimal BH4 treatment regimen to directly improve neurocognitive functioning in PKU. Such possible repurposing approach of BH4 treatment in PKU may improve neuropsychological outcome and mental health in both BH4-responsive and BH4-unresponsive PKU patients

Does the 48-hour BH4 loading test miss responsive PKU patients?

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Centriole movements in mammalian epithelial cells during cytokinesis

<p>Abstract</p> <p>Background</p> <p>In cytokinesis, when the cleavage furrow has been formed, the two centrioles in each daughter cell separate. It has been suggested that the centrioles facilitate and regulate cytokinesis to some extent. It has been postulated that termination of cytokinesis (abscission) depends on the migration of a centriole to the intercellular bridge and then back to the cell center. To investigate the involvement of centrioles in cytokinesis, we monitored the movements of centrioles in three mammalian epithelial cell lines, HeLa, MCF 10A, and the p53-deficient mouse mammary tumor cell line KP-7.7, by time-lapse imaging. Centrin1-EGFP and α-Tubulin-mCherry were co-expressed in the cells to visualize respectively the centrioles and microtubules.</p> <p>Results</p> <p>Here we report that separated centrioles that migrate from the cell pole are very mobile during cytokinesis and their movements can be characterized as 1) along the nuclear envelope, 2) irregular, and 3) along microtubules forming the spindle axis. Centriole movement towards the intercellular bridge was only seen occasionally and was highly cell-line dependent.</p> <p>Conclusions</p> <p>These findings show that centrioles are highly mobile during cytokinesis and suggest that the repositioning of a centriole to the intercellular bridge is not essential for controlling abscission. We suggest that centriole movements are microtubule dependent and that abscission is more dependent on other mechanisms than positioning of centrioles.</p

The Genetic Landscape and Epidemiology of Phenylketonuria

Phenylketonuria (PKU), caused by variants in the phenylalanine hydroxylase (PAH) gene, is the most common autosomal-recessive Mendelian phenotype of amino acid metabolism. We estimated that globally 0.45 million individuals have PKU, with global prevalence 1:23,930 live births (range 1:4,500 [Italy]-1:125,000 [Japan]). Comparing genotypes and metabolic phenotypes from 16,092 affected subjects revealed differences in disease severity in 51 countries from 17 world regions, with the global phenotype distribution of 62% classic PKU, 22% mild PKU, and 16% mild hyperphenylalaninemia. A gradient in genotype and phenotype distribution exists across Europe, from classic PKU in the east to mild PKU in the southwest and mild hyperphenylalaninemia in the south. The c.1241A gt G (p.Tyr414Cys)-associated genotype can be traced from Northern to Western Europe, from Sweden via Norway, to Denmark, to the Netherlands. The frequency of classic PKU increases from Europe (56%) via Middle East (71%) to Australia (80%). Of 758 PAH variants, c.1222C gt T (p.Arg408Trp) (22.2%), c.1066-11G gt A (IVS10-11G gt A) (6.4%), and c.782G gt A (p.Arg261Gln) (5.5%) were most common and responsible for two prevalent genotypes: p.[Arg408Trp];[Arg408Trp] (11.4%) and c.[1066-11G gt A];[1066-11G gt A] (2.6%). Most genotypes (73%) were compound heterozygous, 27% were homozygous, and 55% of 3,659 different genotypes occurred in only a single individual. PAH variants were scored using an allelic phenotype value and correlated with pre-treatment blood phenylalanine concentrations (n = 6,115) and tetrahydrobiopterin loading test results (n = 4,381), enabling prediction of both a genotype-based phenotype (88%) and tetrahydrobiopterin responsiveness (83%). This study shows that large genotype databases enable accurate phenotype prediction, allowing appropriate targeting of therapies to optimize clinical outcome

Dietary Liberalization in Tetrahydrobiopterin-Treated PKU Patients: Does It Improve Outcomes?

Purpose: this systematic review aimed to assess the effects of dietary liberalization following tetrahydrobiopterin (BH4) treatment on anthropometric measurements, nutritional biomarkers, quality of life, bone density, mental health and psychosocial functioning, and burden of care in PKU patients. Methods: the PubMed, Cochrane, and Embase databases were searched on 7 April 2022. We included studies that reported on the aforementioned domains before and after dietary liberalization as a result of BH4 treatment in PKU patients. Exclusion criteria were: studies written in a language other than English; studies that only included data of a BH4 loading test; insufficient data for the parameters of interest; and wrong publication type. Both within-subject and between-subject analyses were assessed, and meta-analyses were performed if possible. Results: twelve studies containing 14 cohorts and 228 patients were included. Single studies reported few significant differences. Two out of fifteen primary meta-analyses were significant; BMI was higher in BH4-treated patients versus controls (p = 0.02; standardized mean difference (SMD) (95% confidence interval (CI)) = &minus;0.37 (&minus;0.67, &minus;0.06)), and blood cholesterol concentrations increased after starting BH4 treatment (p = 0.01; SMD (CI) = &minus;0.70 (&minus;1.26, &minus;0.15)). Conclusion: there is no clear evidence that dietary liberalization after BH4 treatment has a positive effect on anthropometric measurements, nutritional biomarkers, or quality of life. No studies could be included for bone density, mental health and psychosocial functioning, and burden of care

Anthropomorphic measurements and nutritional biomarkers after 5 years of BH4 treatment in phenylketonuria patients

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The first European guidelines on phenylketonuria: Usefulness and implications for BH 4 responsiveness testing

OBJECTIVE: This study aimed to investigate and improve the usefulness of the 48-hour BH4 loading test and to assess genotype for BH4 responsiveness prediction, using the new definition of BH4 responsiveness from the European guidelines, as well as an amended definition. METHOD: Applying the definition of the European guidelines (>/= 100% increase in natural protein tolerance) and an amended definition (>/= 100% increase in natural protein tolerance or tolerating a safe natural protein intake) to a previous dataset (Anjema et al 2013), we firstly assessed the positive predictive value (PPV) of the 48-hour BH4 loading test using a cutoff value of 30%. Then, we tried to improve this PPV by using different cutoff values and separate time points. Lastly, using the BIOPKU database, we compared predicted BH4 responsiveness (according to genotype) and genotypic phenotype values (GPVs) in BH4 -responsive and BH4 -unresponsive patients. RESULTS: The PPV of the 48-hour loading test was 50.0% using the definition of the European guidelines, and 69.4% when applying the amended definition of BH4 responsiveness. Higher cutoff values led to a higher PPV, but resulted in an increase in false-negative tests. Parameters for genotype overlapped between BH4 -responsive and BH4 -unresponsive patients, although BH4 responsiveness was not observed in patients with a GPV below 2.4. CONCLUSION: The 48-hour BH4 loading test is not as useful as previously considered and cannot be improved easily, whereas genotype seems mainly helpful in excluding BH4 responsiveness. Overall, the definition of BH4 responsiveness and BH4 responsiveness testing require further attention. This article is protected by copyright. All rights reserved

Back/joint Pain, Illness Perceptions and Coping are Important Predictors of Quality of Life and Work Productivity in Patients with Inflammatory Bowel Disease: a 12-month Longitudinal Study

BACKGROUND AND AIMS: Back and joint pain are the most common extraintestinal symptoms reported by patients with inflammatory bowel disease (IBD). We assessed the impact of back/joint pain, illness perceptions, and coping on quality of life (QOL) and work productivity in patients with IBD. METHODS: Our cohort included 155 IBD patients with and 100 without arthropathy. Arthropathy was defined as daily back pain for ≥3 months and/or peripheral joint pain and/or joint swelling over the last year. At baseline and at 12 months, patients completed questionnaires on the extent of back/joint pain, IBD disease activity, illness perceptions, coping, QOL, and work productivity. The impact of back/joint pain, illness perceptions and coping on QOL and work productivity was determined, using linear mixed models. RESULTS: In total, 204 IBD patients (72% Crohn's disease, 40% male, mean age 44 ± 14 years) completed questionnaires at both time points. At both time points, IBD patients with back/joint pain reported a significantly lower QOL and work productivity compared with IBD patients without back/joint pain. Predictors of low QOL were back/joint pain (β = -1.04, 95% confidence interval [CI] -1.40, -0.68), stronger beliefs about the illness consequences (β = -0.39, 95% CI -0.59, -0.18) and emotional impact of IBD (β = -0.47, 95% CI -0.66, -0.28), and the coping strategy 'decreasing activity' (β = -0.26, 95% CI -0.48, -0.03). Predictors of work productivity were back/joint pain (β = 0.22, 95% CI 0.07, 0.37) and illness consequences (β = 0.14, 95% CI 0.06, 0.22). CONCLUSION: Back/joint pain, illness perceptions, and coping are significant predictors of QOL and work productivity, after controlling for disease activity