The Foundation for Prader-Willi Research announces our first round of Research Awards in 2018 totaling $615,000. FPWR is dedicated to supporting research that advances the understanding and treatment of Prader-Willi syndrome (PWS) and to that end, has awarded over $10,000,000 to research since 2003.
FPWR PWS Research Grant Recipients, Spring 2018
A transcriptome-wide approach to identifying RNA targets of the Prader-Willi locus snoRNAs (year 2)
Tomaz Bratkovic, PhD University of Ljubljana, Slovenia
Dr. Bratkovic has been working to identify the RNA targets of SNORD116 gene, a critical gene cluster in the PWS region of chromosome 15.. His group is applying advanced techniques to examine the full complement of RNAs that interact with SNORD116 transcripts. This study will further define how the loss of the SNORD116 gene results in the symptoms of PWS and may identify targets for therapeutic interventions.
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The gut microbiome in Prader-Willi syndrome
Dr. Mauro Costa-Mattioli, Baylor College of Medicine
Dr.Costa-Mattioli has shown that the composition of the gut microbiome can influence autistic behaviors in mouse models, and that this influence acts through the oxytocin system. This study will examine the gut microbiome of a PWS mouse model, and determine whether altering the microbiome can impact social behaviors.
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Evaluating endosomal recycling pathways in primary neurons from PWS individuals
Ryan Potts, PhD. St. Jude’s
Dr. Potts has identified a defect in vesicle recycling in cells that have mutations in the MAGEL2 gene, as in Schaaf-Yang syndrome. Here, he will collaborate Dr. Larry Reiter, who has produced stem cell-based neurons from PWS ‘baby teeth’, to evaluate whether these same cellular changes are present in PWS. He will also examine ways to ‘rescue’ the defects in cellular vesicle function and receptor recycling in PWS neurons.
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Improving social functioning in Prader-willi syndrome (year 2)
Elizabeth Roof, Vanderbilt University
The Vanderbilt team has developed a web-based intervention curriculum designed to improve the social skills of adolescents and young adults with PWS. They are evaluating whether this program reduces social isolation and improves social functioning. Their ultimate goal is to develop a social intervention program, tailored towards those with PWS, which can be widely disseminated.
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The molecular mechanism of SNORD116 action (year 2)
Stefan Stamm, PhD University of Kentucky
Dr. Stamm has been studying the normal function of the SNORD116 genes in PWS. In year 1, he determined that SNORD116 plays a role in RNA stability, which may be important in controlling circadian rhythm and hormone release. In year 2 his group will examine how SNORD116 binds to these RNAs and controls their stability, as a first step to identify ways to replace their function.
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Cellular role of MAGEL2 in Prader-Willi and Schaaf-Yang syndromes
Rachel Wevrick, PhD, University of Alberta
Dr. Wevrick’s group has been studying the function of MAGEL2, one of the genes in the PWS region. This project focuses on one part of the MAGEL2 protein, which the lab has recently found interacts with complexes that include specialized mRNAs. They will determine how MAGEL2 binding to these complexes influences the stability and location of these RNAs in the cell, setting the stage for evaluating therapeutic interventions to compensate for MAGEL2 loss.
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Consequences of targeted SNORD116 deletion in human and mouse neurons (year 2)
Giles Yeo, University of Cambridge
Without environmental controls, individuals with PWS will become morbidly obese. However, certain mouse models of PWS have been unable to replicate this symptom, hampering the development of new drugs for PWS. With FPWR funding, Dr. Yeo’s group has developed a mouse model of PWS that is based on loss of Snord116 after the newborn period, which results in an animal that more closely mimics the human condition, developing hyperphagia and obesity. Such an animal model will be important for testing new drugs. Here, they are using a genetic approach to make this model more robust and usable, and will characterize the features of the model.
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