Salmaninejad, Arash

ABSTRACT Background A rare autosomal recessive disorder known as hyperphosphatasia with impaired intellectual development syndrome (HPMRS), also referred to as Mabry syndrome, is caused by a deficiency in glycosylphosphatidylinositol (GPI). Elevated blood alkaline phosphatase (ALP) levels, cognitive impairment, and epileptic seizures are among its key features. These pathways are involved in the synthesis of GPI and the transfer of GPI anchor to the proteins, fatty acid remodeling, and transport of GPI‐anchored proteins (GPI‐APs). Methods Using exome sequencing (ES), the cause of hyperphosphatasia and ID of an 11‐year‐old girl from non‐consanguineous parents was solved, and the results confirmed by direct Sanger sequencing method. Results ES identified a novel homozygous pathogenic variant, PGAP3 (NM_033419.5: c.202dupT, p.Cys68fs*2) that segregated within the family members. To the best of our knowledge at the time of writing this manuscript, this variant has not been reported in HPMRS in the literature. Conclusion Our findings indicate that the p.Cys68fs*2 variant may disrupt normal protein function and likely disrupt its interaction with its associated partner proteins, potentially leading to disruption of GPI biosynthesis. We present a novel pathogenic variant thus expanding the phenotypic and mutational spectrum of this extremely rare disorder. Elevated ALP assays and ES are valuable diagnostic tools for HPMRS. Additionally, a comprehensive literature review was conducted to expand the phenotypic and genotypic spectrum within the PGAP3 gene responsible for HPMRS.

ABSTRACT Background LINS1 , the human homolog of the Drosophila segment polarity gene, encodes a key regulator of the Wingless/Wnt signaling pathway. While numerous genes have been implicated in intellectual disability (ID), only a limited number have been conclusively associated with autosomal recessive intellectual disability (ARID). Variants in LINS1 have been identified as one such cause. Methods In this study, we employed exome sequencing (ES) to investigate the genetic basis of ID in two consanguineous Iranian families. This variant was confirmed by Sanger sequencing, and segregation analysis supported its pathogenicity. Additionally, in silico analyses were conducted to explore the protein–protein interaction network of LINS1 and its functional connections to ID‐associated proteins. Results We identified a novel homozygous missense variant in LINS1 (c.1354G>C), leading to an alanine‐to‐proline substitution (p.Ala452Pro) in exon six. Conclusion Our findings provide new molecular and clinical insights into the role of LINS1 in ARID, expanding the genetic landscape of ID. This discovery has significant implications for genetic counseling and prenatal diagnosis, aiding in the identification of at‐risk couples.

Abstract Motivation The American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines represent the gold standard for clinical variant interpretation. Despite the widespread adoption of ACMG/AMP guidelines, a comprehensive comparison of the software tools designed to implement them has been lacking. This represents a significant gap, as clinicians require evidence-based guidance on which tools to use in their practice. Results We benchmarked four ACMG/AMP-based tools (Franklin, InterVar, TAPES, Genebe) selected from 22 tools, and compared their performance with LIRICAL, a top-performing phenotype-driven tool, using 151 expert-curated datasets from Mendelian disorders. Selection criteria included free availability, VCF compatibility, operational reliability, and not being disease-specific. Our evaluation framework assessed top-N accuracy (N = 1, 5, 10, 20, 50), retention rates, precision, recall, F1 scores, and area under the curve (AUC). Statistical validation employed bootstrap confidence intervals (n = 1000) and Friedman tests. LIRICAL (68.21%) and Franklin (61.59%) demonstrated superior top-10 variant prioritization accuracy in Mendelian disorders, significantly outperforming other tools (P = .0000). Results demonstrate that tools with advanced phenotypic integration significantly outperform those relying primarily on genomic features. Availability and implementation All data and source code required to reproduce the findings of this study are openly available in the Code Ocean repository at https://doi.org/10.24433/CO.6562438.v1.