Evidence map›Paper›PMID 41602908›Full record

ArticleiScience2026

Context-dependent NMDA receptor dysfunction predicts seizure treatment in mice with human GluN1 variant.

Sridevi Venkatesan, Daria Nazarkina, Megan T Sullivan, Yao-Fang Tan, Sarah Qu, Amy J Ramsey, Evelyn K Lambe

Abstract read
In one paragraph

Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Sridevi VenkatesanDepartment of Physiology, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada.
Daria NazarkinaDepartment of Physiology, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada.
Megan T SullivanDepartment of Physiology, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada.
Yao-Fang TanDepartment of Physiology, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada.
Sarah QuDepartment of Physiology, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada.
Amy J RamseyDepartment of Pharmacology and Toxicology, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5G 2C8, Canada.
Evelyn K LambeDepartment of Physiology, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mutations in N-methyl-D-aspartate receptors (NMDARs) cause epilepsy and profound cognitive impairment, though the underlying subunit-specific vulnerabilities remain unclear. We investigate the impact of a severe human variant in the lurcher motif of obligate GluN1 NMDAR subunit using transgenic mice, revealing unexpected context-dependent phenotypes. We show that the GluN1 Y647S variant significantly reduces current flow through pharmacologically isolated synaptic NMDARs in prefrontal neurons. Yet in intact local circuits, this loss-of-function paradoxically extends NMDAR-dependent dendritic integration, causing prolonged circuit-wide excitation that promotes seizures. Mutant receptors appear deficient in engaging opposing dendritic ion channels that normally curtail NMDAR-dependent excitation. Boosting SK channel activity normalizes dendritic integration, whereas slight decreases in extracellular magnesium further extend abnormally prolonged integration in mutant mice. We find that magnesium supplementation successfully treats seizures

Indexed as

geneticsneuroscience

Identifiers

PMID41602908
PMCPMC12834114

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.