Complex Inheritance of Rare Missense Variants in PAK2, TAP2, and PLCL1 Genes in a Consanguineous Arab Family With Multiple Autoimmune Diseases Including Celiac Disease

Abstract

BackgroundAutoimmune diseases (AIDs) share a common molecular etiology and often present overlapping clinical presentations. Thus, this study aims to explore the complex molecular basis of AID by whole exome sequencing and computational biology analysis.MethodsMolecular screening of the consanguineous AID family and the computational biology characterization of the potential variants were performed. The potential variants were searched against the exome data of 100 healthy individuals and 30 celiac disease patients.ResultA complex inheritance pattern of PAK2 (V43A), TAP2 (F468Y), and PLCL1 (V473I) genetic variants was observed in the three probands of the AID family. The PAK2 variant (V43A) is a novel one, but TAP2 (F468Y) and PLCL1 (V473I) variants are extremely rare in local Arab (SGHP and GME) and global (gnomAD) databases. All these variants were localized in functional domains, except for the PAK2 variant (V43A) and were predicted to alter the structural (secondary structure elements, folding, active site confirmation, stability, and solvent accessibility) and functional (gene expression) features. Therefore, it is reasonable to postulate that the dysregulation of PAK2, TAP2, and PLCL1 genes is likely to elicit autoimmune reactions by altering antigen processing and presentation, T cell receptor signaling, and immunodeficiency pathways.ConclusionOur findings highlight the importance of exploring the alternate inheritance patterns in families presenting complex autoimmune diseases, where classical genetic models often fail to explain their molecular basis. These findings may have potential implications for developing personalized therapies for complex disease patients.

Structural characterization and conformational dynamics of alpha-1 antitrypsin pathogenic variants causing alpha-1-antitrypsin deficiency

“…In this study, six tools, including Combined Annotation Dependent Depletion (CADD), Scale-invariant Feature Transform (SIFT) ( Ng and Henikoff, 2003 ), Polymorphism Phenotyping (PolyPhen) ( Adzhubei et al, 2013 ), Mendelian Clinically Applicable Pathogenicity (M-CAP) ( Jagadeesh et al, 2016 ), and Functional Analysis through Hidden Markov Models (FATHMM) ( Rogers et al, 2018 ), REVEL (rare exome variant ensemble learner) were used to evaluate the pathogenicity of variants ( Ioannidis et al, 2016 ). SIFT predicts pathogenicity based on alteration in conserved regions of the nucleotide sequence ( Shaik et al, 2020b ; Shaik et al, 2021 ; Alharthi et al, 2022 ; Bima et al, 2022 ). PolyPhen predicts the variant effects based on the nucleotide sequence and changes in protein structure.…”

Molecular Level Atomistic and Structural Insights on Biological Macromolecules, Inhibition, and Dynamics Studies

“…In this study, six tools, including Combined Annotation Dependent Depletion (CADD), Scale-invariant Feature Transform (SIFT) (Ng and Henikoff, 2003), Polymorphism Phenotyping (PolyPhen) (Adzhubei et al, 2013), Mendelian Clinically Applicable Pathogenicity (M-CAP) (Jagadeesh et al, 2016), and Functional Analysis through Hidden Markov Models (FATHMM) (Rogers et al, 2018), REVEL (rare exome variant ensemble learner) were used to evaluate the pathogenicity of variants (Ioannidis et al, 2016). SIFT predicts pathogenicity based on alteration in conserved regions of the nucleotide sequence (Shaik et al, 2020b;Shaik et al, 2021;Alharthi et al , 2022;. PolyPhen predicts the variant effects based on the nucleotide sequence and changes in protein structure.…”