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Updated: Dec 26, 2025

Identification and Classification of Position-specific GABAA Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons
Published on: June 6, 2025
From bedside-to-bench: What disease-associated variants are teaching us about the NMDA receptor
Johansen B Amin1,2, Gabrielle R Moody2, Lonnie P Wollmuth3,4,5
1Medical Scientist Training Program (MSTP), Stony Brook University, Stony Brook, NY, 11794-5230.
Abstract:
NMDA receptors (NMDARs) are glutamate-gated ion channels that contribute to nearly all brain processes. Not surprisingly then, genetic variations in the genes encoding NMDAR subunits can be associated with neurodevelopmental, neurological and psychiatric disorders. These disease-associated variants (DAVs) present challenges, such as defining how DAV-induced alterations in receptor function contribute to disease progression and how to treat the affected individual clinically. As a starting point to overcome these challenges, we need to refine our understanding of the complexity of NMDAR structure function. In this regard, DAVs have expanded our knowledge of NMDARs because they do not just target well-known structure-function motifs, but rather give an unbiased view of structural elements that are important to the biology of NMDARs. Indeed, established NMDAR structure-function motifs have been validated by the appearance of disorders in patients where these motifs have been altered, and DAVs have identified novel structural features in NMDARs such as gating triads and hinges in the gating machinery. Still, the majority of DAVs remain unexplored and occur at sites in the protein with unidentified function or alter receptor properties in multiple and unanticipated ways. Detailed mechanistic and structural investigations are required of both established and novel motifs to develop a highly refined pathomechanistic model that accounts for the complex machinery that regulates NMDARs. Such a model would provide a template for rational drug design and a starting point for personalized medicine.
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