Back

Gene Portals: A Framework for Integrating Clinical, Functional, and Structural Evidence into Rare Disease Variant Classification

Brünger, T.; Krey, I.; Kim, S.; Klöckner, C.; Myers, S. J. A.; Johannesen, K. M.; Stefanski, A.; Taylor, G.; Perez-Palma, E.; Macnee, M.; Schorge, S.; Dahl, R. S.; Yuan, H.; Perszyk, R. E.; Kim, S.; Bajaj, S.; Helbig, I.; Pan, J. Q.; Farrant, M.; Wollmuth, L.; Wyllie, D. J. A.; Kurganov, E.; Baez, D.; Zuberi, S.; Bosselmann, C. M.; Lerche, H.; Mantegazza, M.; Cestele, S.; May, P.; Ivaniuk, A.; Meskis, M. A.; Hood, V.; Schust, L.; Goodspeed, K.; Kang, J.-Q.; Freed, A.; Gati, C.; Montanucci, L.; Wuster, A.; Trinidad, M.; Froelich, S.; Deng, A. T.; Aledo-Serrano, A.; Borovikov, A.; Sharkov, A.;

2026-03-06 genetic and genomic medicine
10.64898/2026.03.05.26347086 medRxiv
Show abstract

Rare Mendelian disorders affect 300-400 million people globally. Although genetic testing has become widely adopted, gene-specific evidence for tailored variant interpretation remains scattered across resources. We present Gene Portals, a framework for gene-centered multimodal knowledge bases that co-localize expert-harmonized clinical data, functional assays, population variation, structural annotations and gene-specific ACMG/AMP specifications within a single resource. A modular interface integrates this unified evidence with VCEP-refined ACMG specifications to enable automated gene-specific variant classification, infer molecular mechanisms, and support cross-gene analyses. We demonstrate the frameworks utility across five Gene portals spanning eleven neurodevelopmental disorder-associated genes, integrating data from 4,423 individuals with 2,838 unique variants, 36,149 ClinVar submissions, and 1,044 expert-curated molecular readouts. By organizing evidence that is otherwise dispersed across multiple sources into a unified, queryable framework, the SCN, GRIN, CACNA1A, SATB2 and SLC6A1 Gene Portals became widely used community resources and provide an extensible template for standardized rare-disease variant interpretation and mechanism-aware discovery.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.