Functional characterization of 105 Factor H variants associ-ated with atypical HUS: lessons for variant classification
| Autor: | Héctor Martín Merinero, Zhang, Yuzhou, Bolanos, Emilia Arjona, Goodfellow, Renee, Michelena, Malkoa, Smith, Richard J. H., Cordoba, Santiago Rodriguez |
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| Přispěvatelé: | Martín Merinero, Héctor, Arjona, Emilia, Rodríguez de Córdoba, Santiago, Martín Merinero, Héctor [0000-0002-9094-5934], Arjona, Emilia [0000-0002-0753-3657], Rodríguez de Córdoba, Santiago [0000-0001-6401-1874] |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Zdroj: | Web of Science Digital.CSIC. Repositorio Institucional del CSIC instname |
| Popis: | 1 p. Background: Atypical hemolytic uremic syndrome (aHUS) isa life-threatening thrombotic microangiopathy that can progress,when untreated, to end-stage renal disease. Most frequently, aHUSis caused by complement dysregulation due to pathogenic vari-ants in genes that encode complement components and regulators.Amongst these genes, the Factor H (FH) gene, CFH, presents withthe highest frequency (15-20%) of variants and is associated withthe poorest prognosis. Correct classification of CFH variants aspathogenic or benign is essential to clinical care but remains chal-lenging owing to the dearth of functional studies. As a result,significant numbers of variants are reported as variants of uncertainsignificance. Methods: To address this knowledge gap, we expressed andfunctionally characterized 105 aHUS-associated FH variants witha battery of hemolytic and plate-based assays to determine theirimpact on its regulatory and binding properties. We used 26 pre-viously characterized FH variants to validate the robustness of thefunctional assays used. Results: All FH variants were categorized as pathogenic orbenign, and for each, we fully documented the nature of thepathogenicity. Among the 79 uncharacterized variants, only 29(36.7%) alter FH in vitro expression or function and are thereforeproposed to be pathogenic. We show that rarity in control databasesis not informative for variant classification, and we identify impor-tant limitations in applying prediction algorithms to FH variants.Based on structural and functional data, we suggest ways to circum-vent these difficulties and thereby improve variant classification. Conclusions: Our work reveals limitations of routinely usedvariant classification methods. Rarity in control databases can bemisleading and prediction algorithms fails classifying up to 17%of the variants. This highlights the need for functional assays tointerpret FH variants accurately if clinical care of patients withaHUS is to be individualized and optimized. |
| Databáze: | OpenAIRE |
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