Cerebrospinal fluid biomarkers in human genetic transmissible spongiform encephalopathies

The 14-3-3 protein test has been shown to support the clinical diagnosis of sporadic Creutzfeldt-Jakob disease (CJD) when associated with an adequate clinical context, and a high differential potential for the diagnosis of sporadic CJD has been attributed to other cerebrospinal fluid (CSF) proteins such as tau protein, S100b and neuron specific enolase (NSE). So far there has been only limited information available about biochemical markers in genetic transmissible spongiform encephalopathies (gTSE), although they represent 10–15% of human TSEs. In this study, we analyzed CSF of 174 patients with gTSEs for 14-3-3 (n = 166), tau protein (n = 78), S100b (n = 46) and NSE (n = 50). Levels of brain-derived proteins in CSF varied in different forms of gTSE. Biomarkers were found positive in the majority of gCJD (81%) and insert gTSE (69%), while they were negative in most cases of fatal familial insomnia (13%) and Gerstmann-Sträussler-Scheinker syndrome (10%). Disease duration and codon 129 genotype influence the findings in a different way than in sporadic CJD

Plasma levels of soluble TREM2 and neurofilament light chain in TREM2 rare variant carriers

Background: Results from recent clinical studies suggest that cerebrospinal fluid (CSF) biomarkers that are indicative of Alzheimer’s disease (AD) can be replicated in blood, e.g. amyloid-beta peptides (Aβ42 and Aβ40) and neurofilament light chain (NFL). Such data proposes that blood is a rich source of potential biomarkers reflecting central nervous system pathophysiology and should be fully explored for biomarkers that show promise in CSF. Recently, soluble fragments of the triggering receptor expressed on myeloid cells 2 (sTREM2) protein in CSF have been reported to be increased in prodromal AD and also in individuals with TREM2 rare genetic variants that increase the likelihood of developing dementia. / Methods: In this study, we measured the levels of plasma sTREM2 and plasma NFL using the MesoScale Discovery and single molecule array platforms, respectively, in 48 confirmed TREM2 rare variant carriers and 49 non-carriers. / Results: Our results indicate that there are no changes in plasma sTREM2 and NFL concentrations between TREM2 rare variant carriers and non-carriers. Furthermore, plasma sTREM2 is not different between healthy controls, mild cognitive impairment (MCI) or AD. / Conclusion: Concentrations of plasma sTREM2 do not mimic the recent changes found in CSF sTREM2

CSF glial biomarkers YKL40 and sTREM2 are associated with longitudinal volume and diffusivity changes in cognitively unimpaired individuals

Cerebrospinal fluid (CSF) YKL40 and sTREM2 are astroglial and microglial activity biomarkers, respectively. We assessed whether CSF YKL40 and sTREM2 baseline levels are associated with longitudinal brain volume and diffusivity changes in cognitively unimpaired adults. Two brain MRI scans of 36 participants (57 to 78-years old, 12 male) were acquired in a 2-year interval. A beta(42), p-tau, YKL40 and sTREM2 concentrations in CSF were determined at baseline. We calculated gray and white matter volume changes per year maps (Delta GM and Delta WM, respectively) by means of longitudinal pairwise registration, and mean diffusivity variation per year (Delta MD) by subtraction. We checked voxel-wise for associations between Delta GM, Delta WM and Delta MD and baseline CSF level of YKL40 and sTREM2 and verified to what extent these associations were modulated by age (YKL40xAGE and sTREM2xAGE interactions). We found a positive association between Delta GM and YKL40 in the left inferior parietal region and no association between sTREM2 and Delta GM. Negative associations were also observed between Delta GM and YKL40xAGE (bilateral frontal areas, left precuneus and left postcentral and supramarginal gyri) and sTREM2xAGE (bilateral temporal and frontal cortex, putamen and left middle cingulate gyrus). We found negative associations between Delta WM and YKL40xAGE (bilateral superior longitudinal fasciculus) and sTREM2xAGE (bilateral superior longitudinal fasciculus, left superior corona radiata, retrolenticular external capsule and forceps minor, among other regions) but none between Delta WM and neither YKL40 nor sTREM2. Delta MD was positively correlated with YKL40 in right orbital region and negatively with sTREM2 in left lingual gyrus and precuneus. In addition, significant associations were found between Delta MD and YKL40xAGE (tail of left hippocampus and surrounding areas and right anterior cingulate gyrus) and sTREM2xAGE (right superior temporal gyrus). Areas showing statistically significant differences were disjoint in analyses involving YKL40 and sTREM2. These results suggest that glial biomarkers exert a relevant and distinct influence in longitudinal brain macro- and microstructural changes in cognitively unimpaired adults, which appears to be modulated by age. In younger subjects increased glial markers (both YKL40 and sTREM2) predict a better outcome, as indicated by a decrease in Delta GM and Delta WM and an increase in Delta MD, whereas in older subjects this association is inverted and higher levels of glial markers are associated with a poorer neuroimaging outcome

Bio-Based Fire Retardant for Coco Lumber using Aloe barbadensis miller (Aloe Vera), Mangifera indica (Mango), or Persea americana (Avocado) and Boron Additives

Accidental fires are prevalent in low-income communities and one of the solutions to decrease fire risk is to apply fire retardants on combustible materials. While extensive research was available in creating fire retardants with inorganic chemicals, further studies are needed for bio-based fire retardants. The development of bio-based fire retardants involves testing organic matter for the presence of fire-retardant compounds such as nitrogen, phosphorus, and polyphenols. This study sought to determine the effectiveness of the peels of Aloe barbadensis miller (aloe vera), Mangifera indica (mangoes), and Persea americana (avocados) in creating bio-based fire retardants for coco lumber. Maceration was used to get the fruit and plant extracts. Boric acid and borax were also added as additives to boost fire retarding properties. The burning behavior of the lumber was observed in a modified horizontal flammability test and a modified flame spread test and measured in terms of mass loss, smoke density, char yield, and charring rate. The results revealed that among the fruits, the mango-based fire-retardant inhibited mass loss the most (M = 0.006, SD = 0.003), while the avocado-based fire-retardant inhibited smoke the most (M = 0.036, SD = 0.016). No significant difference was found among the groups as determined by One-way ANOVA and MANOVA (p \u3e 0.05). An indirect relationship was found between smoke density and char yield, which may be examined to improve the smoke suppressing ability of commercial fire retardants. Future studies may also refine the plant extracts and use standard flammability tests

Adsorción de átomos de hidrógeno y oxígeno en superficies de Cu (100) y Ag(100) mediante DFT, simulación de Monte Carlo y Aproximación de Racimo

Se sabe que los sólidos tienen la capacidad de retener grandes cantidades de gases o vapores condensables, motivo por el cual la físicoquímica de superficies encuentra aplicación en nuevas tecnologías y diversas ramas industriales. De no ser controlados estos gases traerían aparejados problemas al medio ambiente como la lluvia ácida, corrosión, disminución de la capa de ozono e incremento de la toxicidad del aire. Es por esto que es de vital importancia contar con herramientas, tanto experimentales como teóricas, para comprender las interacciones sólido-gas. Es por todo esto que se hace imprescindible el desarrollo de modelos novedosos y nuevas herramientas computacionales que den cuenta de este fenómeno. En particular la adsorción de hidrógeno en superficies de Cu(100) y de Ag(100) y de oxígeno en superficies de Cu(100) puede ser estudiada mediante diferentes herramientas computacionales. Para representar este sistema real se realizaron cálculos de DFT con los cuales se obtuvieron las energías de adsorción de un átomo de hidrógeno en diferentes entornos, de acuerdo con el número de primeros vecinos presentes en cada sitio de adsorción. Esta información se empleó luego en simulaciones de Monte Carlo y en la Aproximación de Racimo para diferentes temperaturas. Se observó un comportamiento interesante de la fase adsorbida que se evidencia en los resultados obtenidos para las isotermas de adsorción, además concluimos que ambos métodos utilizados concuerdan en gran medida para los valores energéticos calculados.Fil: Sanchez Varretti, Fabricio Orlando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Física Aplicada "Dr. Jorge Andrés Zgrablich". Universidad Nacional de San Luis. Facultad de Ciencias Físico Matemáticas y Naturales. Instituto de Física Aplicada "Dr. Jorge Andrés Zgrablich"; ArgentinaFil: Gómez, Elizabeth del Valle. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Avalleb, Lucía B.. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; ArgentinaFil: Bulnes, Fernando Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Física Aplicada "Dr. Jorge Andrés Zgrablich". Universidad Nacional de San Luis. Facultad de Ciencias Físico Matemáticas y Naturales. Instituto de Física Aplicada "Dr. Jorge Andrés Zgrablich"; ArgentinaFil: Gimenez, M. C.. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; ArgentinaFil: Ramirez Pastor, Antonio Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Física Aplicada "Dr. Jorge Andrés Zgrablich". Universidad Nacional de San Luis. Facultad de Ciencias Físico Matemáticas y Naturales. Instituto de Física Aplicada "Dr. Jorge Andrés Zgrablich"; Argentina104a Reunión de la Asociación Física ArgentinaSanta FeArgentinaUniversidad Nacional del LitoralAsociación Física Argentin

Digital biomarker-based individualized prognosis for people at risk of dementia

Background: Research investigating treatments and interventions for cognitive decline fail due to difficulties in accurately recognizing behavioral signatures in the presymptomatic stages of the disease. For this validation study, we took our previously constructed digital biomarker-based prognostic models and focused on generalizability and robustness of the models. Method: We validated prognostic models characterizing subjects using digital biomarkers in a longitudinal, multi-site, 40-month prospective study collecting data in memory clinics, general practitioner offices, and home environments. Results: Our models were able to accurately discriminate between healthy subjects and individuals at risk to progress to dementia within 3 years. The model was also able to differentiate between people with or without amyloid neuropathology and classify fast and slow cognitive decliners with a very good diagnostic performance. Conclusion: Digital biomarker prognostic models can be a useful tool to assist large-scale population screening for the early detection of cognitive impairment and patient monitoring over time

Comparison of Pittsburgh compound B and florbetapir in cross-sectional and longitudinal studies.

IntroductionQuantitative in vivo measurement of brain amyloid burden is important for both research and clinical purposes. However, the existence of multiple imaging tracers presents challenges to the interpretation of such measurements. This study presents a direct comparison of Pittsburgh compound B-based and florbetapir-based amyloid imaging in the same participants from two independent cohorts using a crossover design.MethodsPittsburgh compound B and florbetapir amyloid PET imaging data from three different cohorts were analyzed using previously established pipelines to obtain global amyloid burden measurements. These measurements were converted to the Centiloid scale to allow fair comparison between the two tracers. The mean and inter-individual variability of the two tracers were compared using multivariate linear models both cross-sectionally and longitudinally.ResultsGlobal amyloid burden measured using the two tracers were strongly correlated in both cohorts. However, higher variability was observed when florbetapir was used as the imaging tracer. The variability may be partially caused by white matter signal as partial volume correction reduces the variability and improves the correlations between the two tracers. Amyloid burden measured using both tracers was found to be in association with clinical and psychometric measurements. Longitudinal comparison of the two tracers was also performed in similar but separate cohorts whose baseline amyloid load was considered elevated (i.e., amyloid positive). No significant difference was detected in the average annualized rate of change measurements made with these two tracers.DiscussionAlthough the amyloid burden measurements were quite similar using these two tracers as expected, difference was observable even after conversion into the Centiloid scale. Further investigation is warranted to identify optimal strategies to harmonize amyloid imaging data acquired using different tracers

A panel of CSF proteins separates genetic frontotemporal dementia from presymptomatic mutation carriers: a GENFI study

Background A detailed understanding of the pathological processes involved in genetic frontotemporal dementia is critical in order to provide the patients with an optimal future treatment. Protein levels in CSF have the potential to reflect different pathophysiological processes in the brain. We aimed to identify and evaluate panels of CSF proteins with potential to separate symptomatic individuals from individuals without clinical symptoms (unaffected), as well as presymptomatic individuals from mutation non-carriers. Methods A multiplexed antibody-based suspension bead array was used to analyse levels of 111 proteins in CSF samples from 221 individuals from families with genetic frontotemporal dementia. The data was explored using LASSO and Random forest. Results When comparing affected individuals with unaffected individuals, 14 proteins were identified as potentially important for the separation. Among these, four were identified as most important, namely neurofilament medium polypeptide (NEFM), neuronal pentraxin 2 (NPTX2), neurosecretory protein VGF (VGF) and aquaporin 4 (AQP4). The combined profile of these four proteins successfully separated the two groups, with higher levels of NEFM and AQP4 and lower levels of NPTX2 in affected compared to unaffected individuals. VGF contributed to the models, but the levels were not significantly lower in affected individuals. Next, when comparing presymptomatic GRN and C9orf72 mutation carriers in proximity to symptom onset with mutation non-carriers, six proteins were identified with a potential to contribute to a separation, including progranulin (GRN). Conclusion In conclusion, we have identified several proteins with the combined potential to separate affected individuals from unaffected individuals, as well as proteins with potential to contribute to the separation between presymptomatic individuals and mutation non-carriers. Further studies are needed to continue the investigation of these proteins and their potential association to the pathophysiological mechanisms in genetic FTD

Maerl grounds : habitats of high biodiversity in European seas

The BIOMAERL programme is a 3-year collaborative programme between laboratories in UK, Spain, France and Malta which began in February 1996. Its main plans are described in the workplan. A full inventory of the biological composition (biodiversity) of maerl bed assemblages in these regions therefore has yet to be completed, but progress is outlined below.peer-reviewe

Development of international consensus recommendations using a modified Delphi approach

Funding Information: This work was supported by BioMarin Pharmaceutical Inc . Funding Information: The content of this manuscript was based on preparatory pre-meeting activities and presentations and discussions during two advisory board meetings that were coordinated and funded by BioMarin Pharmaceutical Inc. All authors or their institutions received funding from BioMarin to attend at least one or both meetings. Additional disclosures: BKB received consulting payments from BioMarin, Shire, Genzyme, Alexion, Horizon Therapeutics, Denali Therapeutics, JCR Pharma, Moderna, Aeglea BioTherapeutics, SIO Gene Therapies, Taysha Gene Therapy, Ultragenyx, and Inventiva Pharma, participated as clinical trial investigator for BioMarin, Shire, Denali Therapeutics, Homology Medicines, Ultragenyx, and Moderna as well as received speaker fees from BioMarin, Shire, Genzyme, and Horizon Therapeutics. AH received consulting payments from BioMarin, Chiesi, Shire, Genzyme, Amicus, and Ultragenyx, participated as clinical trial investigator for Ultragenyx as well as received speaker fees from Alexion, Amicus, BioMarin, Genzyme, Nutricia, Sobi, and Takeda. ABQ received consulting payments from BioMarin, speaker fees from BioMarin, Nutricia, Vitaflo, Sanofi, Takeda, Recordati, and travel support from Vitaflo . SEC received consulting payments and speaker fees from BioMarin as well as consulting payments from Synlogic Therapeutics. COH was clinical trial investigator for BioMarin and received consulting and speaker payments from BioMarin. SCJH received consulting payments and travel support from BioMarin and Homology Medicines. NL received consulting payments from Alnylam, Amicus, Astellas, BioMarin, BridgeBio, Chiesi, Genzyme/Sanofi, HemoShear, Horizon Therapeutics, Jaguar, Moderna, Nestle, PTC Therapeutics, Reneo, Shire, Synlogic, and Ultragenyx, participated as clinical trial investigator for Aeglea, Amicus, Astellas, BioMarin, Genzyme/Sanofi, Homology, Horizon, Moderna, Pfizer, Protalix, PTC Therapeutics, Reneo, Retrophin/Travere therapeutics, Shire, and Ultragenyx, as well as received speaker fees from Cycle Pharmaceuticals, Leadiant and Recordati. MCM II received consulting payments from BioMarin, Horizon Therapeutics, Rhythm Pharmaceuticals, Applied Therapeutics, Cycle Therapeutics, and Ultragenyx. ALSP received speaker fees from BioMarin. JCR received consulting payments from Applied Pharma Research, Merck Serono, BioMarin, Vitaflo, and Nutricia, speaker fees from Applied Pharma Research, Merck Serono, BioMarin Pharmaceutical, Vitaflo, Cambrooke, PIAM, LifeDiet, and Nutricia, as well as travel support from Applied Pharma Research, Merck Serono, BioMarin, Vitaflo, Cambrooke, PIAM, and Nutricia. SS received consulting payments, research grants, speaker fees, and travel support from BioMarin and participated as clinical trials investigator for BioMarin. ASV received consulting payments from BioMarin, Horizon Therapeutics, and Ultragenyx and participated as clinical trial investigator for Acadia, Alexion, BioMarin, Genzyme, Homology Medicines, Kaleido, Mallinckrodt, and Ultragenyx. JV received consulting payments from BioMarin, LogicBio Pharmaceuticals, Sangamo Therapeutics, Orphan Labs, Synlogic Therapeutics, Sanofi, Axcella Health, Agios Pharmaceuticals, and Applied Therapeutics as well as travel grants from BioMarin and LogicBio Pharmaceuticals. MW received consulting payments, speaker fees, and travel support from BioMarin, and participated as clinical trial investigator for Mallinckrodt, Roche, Wave, Cycle Therapeutics, and Intrabio. ACM participated in strategic advisory boards and received honoraria as a consultant and as a speaker for Merck Serono, BioMarin, Nestlé Health Science (SHS), Applied Pharma Research, Actelion, Retrophin, Censa, PTC Therapeutics, and Arla Food. Funding Information: Ideally, access to (neuro)psychological/psychiatric support should assist adolescents with identifying, understanding, and reporting of PKU-specific challenges (Table 3), offering individualized recommendations on managing these challenges. Although there is no replacement for mental health services for patients with identified needs, psychosocial support from PKU peers, e.g., through PKU camps, virtual social events, etc., can at least in the short-term help to improve metabolic control by providing individuals an opportunity to participate in supportive PKU-related educational activities potentially reducing perceived social isolation [91]. In addition to PKU camps, which may be very specific to certain regions or countries, HCPs should consider encouraging involvement in local, regional, national and international PKU patient/family advocacy and social support organizations, introducing adolescents and young adults to national/international patient registries [92,93]. Besides support from PKU peers, patients can benefit from non-PKU peer support, although some adolescents and young adults with PKU may not disclose to others and may avoid eating in with others or eating in public due to potential feelings of anxiety or feelings of being ashamed of their disease. In addition, patients with PKU of all ages, but particularly vulnerable adolescents and young adults, can benefit from having the opportunity to learn about and practice strategies that help promote feelings of empowerment and self-efficacy that can be used in both familiar and unfamiliar environments where they may experience peer pressure and feel the need to ‘fit in’. For example, a role-play approach involving behavioral rehearsal, self-monitoring, goal setting, and training in problem-solving skills with emphasis on initiation and inhibition (i.e., how to say no) could be provided by parents, PKU peers, or even members of the PKU team. These types of activities can be used to teach adolescents with PKU how to react in social situations, such as dining out, helping to avoid indulging and increased risk-taking behavior, a hallmark of the adolescent period [94].This work was supported by BioMarin Pharmaceutical Inc.The content of this manuscript was based on preparatory pre-meeting activities and presentations and discussions during two advisory board meetings that were coordinated and funded by BioMarin Pharmaceutical Inc. All authors or their institutions received funding from BioMarin to attend at least one or both meetings. Additional disclosures: BKB received consulting payments from BioMarin, Shire, Genzyme, Alexion, Horizon Therapeutics, Denali Therapeutics, JCR Pharma, Moderna, Aeglea BioTherapeutics, SIO Gene Therapies, Taysha Gene Therapy, Ultragenyx, and Inventiva Pharma, participated as clinical trial investigator for BioMarin, Shire, Denali Therapeutics, Homology Medicines, Ultragenyx, and Moderna as well as received speaker fees from BioMarin, Shire, Genzyme, and Horizon Therapeutics. AH received consulting payments from BioMarin, Chiesi, Shire, Genzyme, Amicus, and Ultragenyx, participated as clinical trial investigator for Ultragenyx as well as received speaker fees from Alexion, Amicus, BioMarin, Genzyme, Nutricia, Sobi, and Takeda. ABQ received consulting payments from BioMarin, speaker fees from BioMarin, Nutricia, Vitaflo, Sanofi, Takeda, Recordati, and travel support from Vitaflo. SEC received consulting payments and speaker fees from BioMarin as well as consulting payments from Synlogic Therapeutics. COH was clinical trial investigator for BioMarin and received consulting and speaker payments from BioMarin. SCJH received consulting payments and travel support from BioMarin and Homology Medicines. NL received consulting payments from Alnylam, Amicus, Astellas, BioMarin, BridgeBio, Chiesi, Genzyme/Sanofi, HemoShear, Horizon Therapeutics, Jaguar, Moderna, Nestle, PTC Therapeutics, Reneo, Shire, Synlogic, and Ultragenyx, participated as clinical trial investigator for Aeglea, Amicus, Astellas, BioMarin, Genzyme/Sanofi, Homology, Horizon, Moderna, Pfizer, Protalix, PTC Therapeutics, Reneo, Retrophin/Travere therapeutics, Shire, and Ultragenyx, as well as received speaker fees from Cycle Pharmaceuticals, Leadiant and Recordati. MCM II received consulting payments from BioMarin, Horizon Therapeutics, Rhythm Pharmaceuticals, Applied Therapeutics, Cycle Therapeutics, and Ultragenyx. ALSP received speaker fees from BioMarin. JCR received consulting payments from Applied Pharma Research, Merck Serono, BioMarin, Vitaflo, and Nutricia, speaker fees from Applied Pharma Research, Merck Serono, BioMarin Pharmaceutical, Vitaflo, Cambrooke, PIAM, LifeDiet, and Nutricia, as well as travel support from Applied Pharma Research, Merck Serono, BioMarin, Vitaflo, Cambrooke, PIAM, and Nutricia. SS received consulting payments, research grants, speaker fees, and travel support from BioMarin and participated as clinical trials investigator for BioMarin. ASV received consulting payments from BioMarin, Horizon Therapeutics, and Ultragenyx and participated as clinical trial investigator for Acadia, Alexion, BioMarin, Genzyme, Homology Medicines, Kaleido, Mallinckrodt, and Ultragenyx. JV received consulting payments from BioMarin, LogicBio Pharmaceuticals, Sangamo Therapeutics, Orphan Labs, Synlogic Therapeutics, Sanofi, Axcella Health, Agios Pharmaceuticals, and Applied Therapeutics as well as travel grants from BioMarin and LogicBio Pharmaceuticals. MW received consulting payments, speaker fees, and travel support from BioMarin, and participated as clinical trial investigator for Mallinckrodt, Roche, Wave, Cycle Therapeutics, and Intrabio. ACM participated in strategic advisory boards and received honoraria as a consultant and as a speaker for Merck Serono, BioMarin, Nestlé Health Science (SHS), Applied Pharma Research, Actelion, Retrophin, Censa, PTC Therapeutics, and Arla Food. Publisher Copyright: © 2022 The AuthorsBackground: Early treated patients with phenylketonuria (PKU) often become lost to follow-up from adolescence onwards due to the historical focus of PKU care on the pediatric population and lack of programs facilitating the transition to adulthood. As a result, evidence on the management of adolescents and young adults with PKU is limited. Methods: Two meetings were held with a multidisciplinary international panel of 25 experts in PKU and comorbidities frequently experienced by patients with PKU. Based on the outcomes of the first meeting, a set of statements were developed. During the second meeting, these statements were voted on for consensus generation (≥70% agreement), using a modified Delphi approach. Results: A total of 37 consensus recommendations were developed across five areas that were deemed important in the management of adolescents and young adults with PKU: (1) general physical health, (2) mental health and neurocognitive functioning, (3) blood Phe target range, (4) PKU-specific challenges, and (5) transition to adult care. The consensus recommendations reflect the personal opinions and experiences from the participating experts supported with evidence when available. Overall, clinicians managing adolescents and young adults with PKU should be aware of the wide variety of PKU-associated comorbidities, initiating screening at an early age. In addition, management of adolescents/young adults should be a joint effort between the patient, clinical center, and parents/caregivers supporting adolescents with gradually gaining independent control of their disease during the transition to adulthood. Conclusions: A multidisciplinary international group of experts used a modified Delphi approach to develop a set of consensus recommendations with the aim of providing guidance and offering tools to clinics to aid with supporting adolescents and young adults with PKU.publishersversionpublishe