ArticleNeurology. Genetics2026
Leveraging Next-Generation Phenotyping in Dysmorphology to Support Variant Interpretation in Mowat-Wilson Syndrome.
Article in Neurology. Genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- AI-Driven Multidimensional Phenotyping for Variant Classification in Rare Neurogenetic Disorders.Neurology. Genetics · 2026Article
Corrections and comments
- Commented on by
Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and Objectives: Next-generation phenotyping (NGP) tools, such as GestaltMatcher, have revolutionized the diagnosis of rare genetic disorders through computational facial analysis. While NGP has been widely integrated into differential diagnosis workflows, its application in variant reclassification within the ACMG framework remains underexplored. Methods: We applied GestaltMatcher to a 4-year-old patient with an undiagnosed neurodevelopmental disorder, suspected Mowat-Wilson syndrome (MWS), and a de novo Results: GestaltMatcher ranked MWS as the top differential diagnosis, and PEDIA integration further confirmed Discussion: This study highlights the potential of NGP-driven facial phenotyping and multimodal integration in dysmorphology. The results support the broader application of AI-assisted phenotyping to improve diagnostic accuracy, particularly in neurodevelopmental disorders with distinct facial features.
Identifiers
What OpenQuestion holds
Registered trials
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.