OBJECTIVE: Progress in basic neuroscience has led to identification of molecular targets for treatment in fragile X syndrome (FXS) and other neurodevelopmental disorders; however, there is a gap in translation to targeted therapies in humans. One major obstacle to the demonstration of efficacy in human trials has been the lack of generally accepted endpoints to assess improvement in function in individuals with FXS. To address this problem, the National Institutes of Health convened a meeting of leading scientists and clinicians with the goal of identifying and standardizing outcome measures for use as potential endpoints in clinical trials in FXS. METHODS: Participants in the meeting included FXS experts, experts in the design and implementation of clinical trials and measure development, and representatives from advocacy groups, industry, and federal agencies. RESULTS: The group generated recommendations for optimal outcome measures in cognitive, behavioral, and biomarker/medical domains, including additional testing and validation of existing measures and development of new measures in areas of need. Although no one endpoint or set of endpoints could be identified that met all criteria as an optimal measure, recommendations are presented in this report. CONCLUSION: The report is expected to guide the selection of measures in clinical trials and lead to the use of a more consistent battery of measures across trials. Furthermore, this will help to direct research toward gaps in the development of validated FXS-specific outcome measures and to assist with interpretation of clinical trial data by creating templates for measurement of treatment efficacy.

Objective

Progress in basic neuroscience has led to identification of molecular targets for treatment in fragile X syndrome (FXS) and other neurodevelopmental disorders; however, there is a gap in translation to targeted therapies in humans. One major obstacle to the demonstration of efficacy in human trials has been the lack of generally accepted endpoints to assess improvement in function in individuals with FXS. To address this problem, the National Institutes of Health convened a meeting of leading scientists and clinicians with the goal of identifying and standardizing outcome measures for use as potential endpoints in clinical trials in FXS.

Methods

Participants in the meeting included FXS experts, experts in the design and implementation of clinical trials and measure development, and representatives from advocacy groups, industry, and federal agencies.

Results

The group generated recommendations for optimal outcome measures in cognitive, behavioral, and biomarker/medical domains, including additional testing and validation of existing measures and development of new measures in areas of need. Although no one endpoint or set of endpoints could be identified that met all criteria as an optimal measure, recommendations are presented in this report.

Conclusion

The report is expected to guide the selection of measures in clinical trials and lead to the use of a more consistent battery of measures across trials. Furthermore, this will help to direct research toward gaps in the development of validated FXS-specific outcome measures and to assist with interpretation of clinical trial data by creating templates for measurement of treatment efficacy.

Recent research on disparate psychiatric disorders has implicated rare variants in genes involved in global gene regulation and chromatin modification, as well as many common variants located primarily in regulatory regions of the genome. Understanding precisely how these variants contribute to disease will require a deeper appreciation for the mechanisms of gene regulation in the developing and adult human brain. The PsychENCODE project aims to produce a public resource of multidimensional genomic data using tissue- and cell type–specific samples from approximately 1,000 phenotypically well-characterized, high-quality healthy and disease-affected human post-mortem brains, as well as functionally characterize disease-associated regulatory elements and variants in model systems. We are beginning with a focus on autism spectrum disorder, bipolar disorder and schizophrenia, and expect that this knowledge will apply to a wide variety of psychiatric disorders. This paper outlines the motivation and design of PsychENCODE.