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Updated: Oct 29, 2026

Rapid Detection of Neurodevelopmental Phenotypes in Human Neural Precursor Cells (NPCs)
Published on: March 2, 2018
Altered developmental trajectories in neurodevelopmental disorders: mechanisms, human models and translational
Florence Desprez1, Dévina C Ung2
1Université de Tours, INSERM, Imaging Brain & Neuropsychiatry iBraiN U1253, 37032, Tours, France.
Abstract:
Neurodevelopmental disorders (NDDs) are clinically and genetically heterogeneous conditions often studied through diagnostic categories, causal genes, synaptic dysfunction or end-stage phenotypes. Although these approaches remain essential, they do not fully capture the developmental nature of NDD pathophysiology. This review proposes a trajectory-first framework in which NDDs are interpreted as disorders of altered developmental progression. From this perspective, the key question is not only which gene, pathway, cell type, or synapse is affected, but when, where and how neurodevelopment begins to diverge. We discuss mechanisms of trajectory divergence, including altered developmental timing, cell-state and lineage disruption, selective cellular vulnerability, epigenetic and signaling dysregulation, cytoskeletal and morphogenetic abnormalities, synaptic maturation defects, excitability changes and network-level alterations. We then examine how human systems, including fetal and post-mortem atlases, iPSC-derived models, cortical organoids, assembloids, functional readouts and patient-level phenotypes, can be integrated to reconstruct developmental trajectories across biological scales. Representative NDD genes and syndromes illustrate that distinct divergence points may later converge on shared functional or clinical outcomes, including altered excitation/inhibition balance, abnormal network activity, epilepsy, language delay, intellectual disability, autism spectrum disorder features or motor dysfunction. Finally, we discuss limitations and perspectives for trajectory-based stratification and biomarker discovery. Rather than acting as static diagnostic readouts, future biomarkers should aim to capture developmental state, timing, divergence, convergence, compensation and response to intervention.
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