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.
SNAREopathies. This post continues the series on SNAREopathies, a group of neurodevelopmental conditions caused by variants in genes encoding components that form the SNARE complex and regulatory proteins. As previously described, the SNARE complex is the molecular machinery driving synaptic vesicle release in the presynapse, which enables communication between neurons. Here, we expand the discussion to the second t-SNARE protein of the SNARE core complex, STX1A, and provide a brief review of the recent paper implicating STX1A in epilepsy and neurodevelopmental disorders.
Multi-omics. An emerging avenue of research for investigating the underlying architecture of human disease is the development of multi-omics approaches. Integration and analysis of large-scale data generated from genome sequencing alongside other -omics technologies including transcriptomics, proteomics, and metabolomics, enable a more comprehensive and nuanced insight into biological systems that underlie disease. However, in contrast to genomic data, the generation of multi-omics data remains expensive, time-consuming, and is typically limited in large-scale population studies. In a recent publication, Xu and collaborators developed a model predicting >17,000 multi-omic traits from genomic profiles across 50,000 people. Here is a brief review of their paper, with a focus on the relevance of developing multi-omics resources in 2023.
GLUT1DS. Disease-causing variants in SLC2A1 are associated with a rare genetic neurometabolic condition known as GLUT1 Deficiency Syndrome (GLUT1DS). While GLUT1DS is typically diagnosed through molecular genetic testing, the diagnostic strategy in some cases includes lumbar puncture to measure cerebrospinal fluid (CSF) glucose to confirm the diagnosis. In a recent study, Mochel and collaborators performed a multicenter validation study of a blood-based biomarker for GLUT1DS. Here is a brief review on their publication and the utility of molecular biomarkers in GLUT1DS and genetic epilepsies more broadly.
Genome sequencing. Despite continual progress in understanding the genetic etiology of human disease, more than half of rare disorders remain unsolved. Resolving the remaining etiologies in rare disease are a major focus of ongoing efforts in the field, including a shift towards standardized analysis of large-scale genome sequencing data from large patient cohorts. In a recent study, Greene and collaborators aimed to identify associations between genes and rare disease subgroups, leveraging genomes of 77,539 people including 29,741 probands. Here is a brief review on their publication in the context of etiological resolution in rare disease.
Language. In the recent years, there has been an emerging focus on the phenotypic characterization of genetic epilepsies and neurodevelopmental disorders. With a rise in large-scale studies leveraging massive and complex genetic and phenotypic datasets, understanding how we make sense of big data becomes critical. However, determining what are clinically meaningful findings and communicating the conclusions we make from these datasets remain a challenge. While we typically think about data in the scope of ‘n’s, probabilities, and p-values, there is understated value in the visualization of information. Here is a different way of how we think about scientific communication and how we can “make data speak in childhood epilepsies.”
CNS Biomarkers. In the last two days, our team attended the Workshop for Multimodal Biomarkers in CNS Disorders held at the National Academies of Sciences, Engineering, and Medicine in Washington, DC. This conference provided a needed review of the current state of multimodal biomarker discovery and development. While most of the speakers focused on more common CNS disorders such as Alzheimer’s disease and neuropsychiatric disorders, there stands to be important lessons that can be translated into the rare disease field. Here is what we learned about the clinical utility of biomarkers and their potential as we move towards precision medicine in rare disease.
FIRES. As a rare and severe epilepsy syndrome, febrile-infection related epilepsy syndrome (FIRES) is characterized by refractory status epilepticus (RSE) preceded by a febrile illness and often leads to prolonged hospitalizations, cognitive impairment, and intractable epilepsy. There are currently no clear causative etiologies identified in FIRES, and the underlying genetic architecture remains elusive. Here is a brief summary of our recent manuscript on the genetics of FIRES and refractory status epilepticus. This is what we learned about one of the most enigmatic conditions in child neurology.
Precision medicine. This post continues the discussion on how we can make sense of clinical data in the absence of outcomes in the context of precision medicine – a concept that drives much of what we do on a research basis. The fundamental idea is that clinical care in pediatric epilepsies can be personalized and tailored to underlying etiologies. With continual progress in gene curation and variant interpretation alongside clinical knowledge, we typically expect that treatment suggestions are immediately implemented after the discovery of the causative genetic etiology. For example, a child with early onset epileptic encephalopathy is found to have a gain-of-function variant in SCN8A and is almost immediately started on a sodium channel blocker such as Trileptal. However, to what extent is this the case? In the context of precision medicine, how precise are we exactly?
Phenotypic bottleneck. This is another post in the “phenotypic atomism series,” what has become our lab’s philosophy in how we think about and work with longitudinal clinical data. However, before we introduce another dimension to the phenotypic atom, let me first revisit the idea of the “phenotypic bottleneck” – a concept that had piqued my interest three years ago and led me to join the lab. In brief, in contrast to established pipelines for large-scale analysis of sequencing data, our ability to analyze clinical data at scale remains more limited. As a result, phenotypic characterization lags behind gene discovery, even with tremendous progress in the last few years. A major challenge stems from the inherent nature of working with multi-dimensional longitudinal clinical data: it can be sparse and incomplete at times. However, how much of the unknown is truly unknown?