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Título: | Functional characterization of 105 Factor H variants associ-ated with atypical HUS: lessons for variant classification |
Autor: | Martín Merinero, Héctor CSIC ORCID; Zhang, Yuzhou; Arjona, Emilia CSIC ORCID ; Goodfellow, Renee; Michelena, Malkoa CSIC; Smith, Richard J.H.; Rodríguez de Córdoba, Santiago | Fecha de publicación: | 2021 | Editor: | Elsevier | Resumen: | 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. |
Descripción: | 1 p. | Versión del editor: | https://doi.org/10.1016/j.molimm.2021.11.020 | URI: | http://hdl.handle.net/10261/257308 | DOI: | 10.1016/j.molimm.2021.11.020 | ISSN: | 0161-5890 |
Aparece en las colecciones: | (CIB) Comunicaciones congresos |
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