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Updated: Jul 21, 2025

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
Published on: June 21, 2018
Identification by Exome Sequencing of Predisposing Variants in Familial Cases of Autoinflammatory Recurrent Fevers
Eugenio Sangiorgi1, Alessia Azzarà2, Roberto Rumore1
1Dipartimento di Scienze della Vita e Sanità Pubblica, Sezione di Medicina Genomica, Università Cattolica del Sacro Cuore-Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Roma, Italy.
Abstract:
Periodic fever syndromes include autoinflammatory disorders (AID) that involve innate immunity. These disorders are characterized by recurrent fevers and aberrant multi-organ inflammation, without any involvement of T or B cells or the presence of autoantibodies. A complex genetic architecture has been recognized for many AID. However, this complexity has only been partially uncovered for familial Mediterranean fever and other conditions that have a classical monogenic origin and Mendelian transmission. Several gene panels are currently available for molecular diagnosis in patients suspected of having AID. However, even when an extensive number of genes (up to 50-100) are tested in a cohort of clinically selected patients, the diagnostic yield of AID ranges between 15% and 25%, depending on the clinical criteria used for patient selection. In the remaining 75-85% of cases, it is conceivable that the causative gene or genes responsible for a specific condition are still elusive. In these cases, the disease could be explained by variants, either recessive or dominant, that have a major effect on unknown genes, or by the cumulative impact of different variants in more than one gene, each with minor additive effects. In this study, we focused our attention on five familial cases of AID presenting with classical autosomal dominant transmission. To identify the probable monogenic cause, we performed exome sequencing. Through prioritization, filtering, and segregation analysis, we identified a few variants for each family. Subsequent bioinformatics evaluation and pathway analysis helped to narrow down the best candidate genes for each family to FCRL6, PKN1, STAB1, PTDGR, and VCAM1. Future studies on larger cohorts of familial cases will help confirm the pathogenic role of these genes in the pathogenesis of these complex disorders.
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