Search

The segmental organization of the vertebral column is established early in embryogenesis, when pairs of somites are rhythmically produced by the presomitic mesoderm (PSM). The tempo of somite formation is controlled by a molecular oscillator known as the segmentation clock1,2. Although this oscillator has been well-characterized in model organisms1,2, whether a similar oscillator exists in humans remains unknown. Genetic analyses of patients with severe spine segmentation defects have implicated several human orthologues of cyclic genes that are associated with the mouse segmentation clock, suggesting that this oscillator might be conserved in humans3. Here we show that human PSM cells derived in vitro-as well as those of the mouse4-recapitulate the oscillations of the segmentation clock. Human PSM cells oscillate with a period two times longer than that of mouse cells (5 h versus 2.5 h), but are similarly regulated by FGF, WNT, Notch and YAP signalling5. Single-cell RNA sequencing reveals that mouse and human PSM cells in vitro follow a developmental trajectory similar to that of mouse PSM in vivo. Furthermore, we demonstrate that FGF signalling controls the phase and period of oscillations, expanding the role of this pathway beyond its classical interpretation in 'clock and wavefront' models1. Our work identifying the human segmentation clock represents an important milestone in understanding human developmental biology.

Autism spectrum disorder (ASD) is a complex neurological and developmental disorder, and a growing body of literature suggests the presence of autonomic nervous system (ANS) dysfunction in individuals with ASD. ANS is part of the "gut brain axis", which consists of an intricate interplay between the gut microbiome, mucosal immune system, enteric nervous system, ANS, and central processes receiving input from the vagus nerve. Measurements of the gut microbiome and the autonomic indices can serve as non-invasive markers of the status of the gut-brain axis in ASD. To our knowledge, no previous studies have explored the relationship between ANS and gut microbiome in individuals with ASD. Furthermore, while previous studies investigated the use of autonomic indices and gut microbiome independently as markers of ASD-related comorbidities, such as anxiety, cardiovascular issues, and gastrointestinal dysfunction, the use of combined autonomic indices and gut microbiome factors to classify ASD and control subjects has not been explored. In this study, we characterized autonomic function of a group of individuals with ASD in comparison to their paired, first-degree relative controls. Second, we explored the ASD gut-brain-axis through the relationship between gut microbiome markers and autonomic indices, as well as the correlation between the gut-brain-axis and clinical presentation of ASD. Lastly, this study explores the predictive capability of gut-brain-axis biomarkers (including autonomic and microbiome indices) in subtyping ASD cases, serving as a starting point to investigate the possibility of assisting in ASD screening and diagnosis that still heavily relies on psychological testing, which may be based on highly subjective standards.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with strong genetic influences. There is an increasing demand for ASD genetic testing beyond the traditionally recommended microarray and syndromic autism testing; however, the current whole genome sequencing (WGS) and whole exome sequencing (WES) methods are lacking an academic standard for WGS variant annotation, reporting, and interpretation, tailored towards patients with ASD and offer very limited interpretation for clinical significance. Using WGS data from six family trios, we demonstrate the clinical feasibility and technical implementation of an evidence-based, fully transparent bioinformatics pipeline and report framework for an ASD-focused WGS genetic report. We confirmed a portion of the key variants with Sanger sequencing and provided interpretation with consideration of patients' clinical symptoms and detailed literature review. Furthermore, we showed that identification of the genetic contributions of ASD core symptoms and comorbidities may promote a better understanding of the ASD pathophysiology, lead to early detection of associated comorbidities, and facilitate pharmacologic intervention based on pathological pathways inferred from the genetic information. We will make the bioinformatics pipeline and interpretation framework publicly available, in an easily accessible format, after validation with a larger cohort. We hope that the present proposed protocol can serve as a starting point to invite discourse and debate to further improve approaches in WGS-based genetic consultation for patients with ASD. [ABSTRACT FROM AUTHOR]