STXBP1. Today is the first day of the 1st European STXBP1 Summit and Research Roundtable, held from May 16-18th in Milan, Italy. This meeting is bringing together voices from academia, industry, organizations, and family foundations to discuss the current state of research – spanning from preclinical efforts investigating mechanisms of disease to moving towards the clinic and the future therapeutic landscape. In 2023, it feels like an understatement to say that STXBP1 is on the map. In spirit of the ongoing momentum in the field, we wanted to refresh the gene page and outline three emerging frameworks to think about STXBP1.
Figure 1. Spectrum of clinical studies and ongoing efforts in STXBP1-related disorders in the lab in the past few years, ranging from large cohort study harmonizing clinical and genetic data across 534 individuals with STXBP1, to longitudinal phenotyping in a subset of individuals for whom clinical data captured from clinical care was used to reconstruct disease histories, and to efforts to identify outcome measures in characterizing the natural history of STXBP1-related disorders and moving towards clinical trial-readiness. Conceptual framework demonstrating the gradient between data complexity and cohort size is adapted from a prior post.
1 – Large-scale phenotyping. First described in human epilepsy in 2008, STXBP1 has since been associated with a perplexing range of clinical presentations. Historically, it was challenging to get a full picture of STXBP1 through a single case-cohort study. To overcome this phenotypic complexity, STXBP1 became the second gene that our lab completely “digitized” – by systematically phenotyping and harmonizing data of all individuals previously reported in the literature in addition to individuals seen at clinical centers around the world. In our study, we analyzed almost 20,000 phenotypic annotations across 534 individuals with STXBP1-related disorders, enabling us to capture the full range of clinical features and identify phenotypic signatures associated with variant and clinical subgroups in STXBP1.
2 – Longitudinal characterization. How can we make trajectories in STXBP1-related disorders predicable? A reoccurring theme that underlies much of our EMR Genomics work is that we may already know more than we think. Despite the high phenotypic variability, we can analyze Real World Data, or data captured from routine clinical care that already spans thousands of patient-years, even in a rare disease, and that is increasing in volume as you read this post. However, predicting trajectories is rooted in accounting for the dimension of time. Forecasting long-term seizure frequencies requires understanding seizure progression over time. Assessment of treatment response is based on looking at changes in seizures in temporal relation to treatment initiation. Developing frameworks and a shared language for making sense of longitudinal clinical data will enable us to characterize the longitudinal landscape in unprecedented detail and enable us to move towards more precise prognostication.
3 – Clinical trial-readiness. Understanding the natural history of STXBP1-related disorders is a prerequisite for meaningful interpretation of the true efficacy of any current or future therapeutic approach. However, the natural history of a neurodevelopmental disorder is multidimensional and requires both identification and validation of standardized outcome measures. On one hand, there is a need to identify and validate scales for developmental and epilepsy outcomes and multimodal biomarkers that serve as objective measurements of the underlying pathophysiology. On the other hand, getting a sense of how to meaningfully “measure” a disorder is rooted in defining the symptoms and domains that describe the impact of a condition in its entirety and that capture the lived experience of affected individuals and their families. Clinical trial-readiness requires intentionality.
Harmonization. Large-scale phenotyping, longitudinal characterization, and clinical trial-readiness frameworks represent different ways of thinking and approaches to understand a condition. Integration of ongoing efforts and frameworks from all three perspectives will provide a more comprehensive understanding of STXBP1-related disorders from multiple angles that will form the basis for improving clinical care and precision medicine approaches for affected individuals.
Julie Xian is a Data Scientist in the Helbig Lab at Children’s Hospital of Philadelphia (CHOP).
