Novel Insights From In Silico Analysis of Biallelic ALPL (c.1001G/A and c.571G/A) in Two Mennonite Families Leading to Hypophosphatasia

TL;DR

This study explores how two specific ALPL gene mutations cause hypophosphatasia in Mennonite families and identifies related genes and pathways that may explain disease variability.

Contribution

The study provides novel in silico insights into the functional impact of biallelic ALPL mutations and their associated pathways in hypophosphatasia.

Findings

In silico analysis identified 10 genes interacting with ALPL, potentially affecting bone formation and metabolism.

Variants associated with the ALPL mutations were linked to metabolic and transcriptional disruptions in hypophosphatasia.

Phenotypic variability was observed among patients with the same ALPL genotype.

Abstract

This report aimed to describe two families of Mennonite heritage affected with hypophosphatasia (HPP) and biallelic ALPL c.1001G>A/c.571G>A in four individuals. Additionally, we conduct a systematic review of studies considering the above compound heterozygous genotype and present novel insights and evidence inferred from in silico predictions using Ensembl's Variant Effect Predictor (VEP) platform and STRING protein-protein interaction (PPI) network analysis to explore these genetic variations and plausible interacting pathways for the disorder that remain for consideration in future studies. Intrafamilial and interfamilial variability of phenotypes was observed in the four patients affected with the identical ALPL c.1001G>A/c.571G>A mutation. In contrast, in the seven unaffected family members, a specific genotype was not available. Seven eligible studies exploring ALPL c.1001G>A/c.571G>A were identified, and significant heterogeneity (P < 0.05) was observed across four studies. Ensembl VEP inferred a dual effect for rs121918007 and rs121918009, involving 17 variants located in the exome and four classified as non-coding associated with all HPP presentations, as well as serum alkaline phosphatase levels, choline phosphate levels, osteogenesis imperfecta, and inborn genetic diseases. PPI network modeling predicted 10 genes (PTS, NBPF3, SLC30A7, TPK1, NTPCR, BGLAP, RUNX2, ENPP1, SLC30A6, GCH1) interacting with ALPL, highlighting their potential impact on bone formation and homeostasis, metabolism, and gene expression. These results may shed light on HPP variability by disrupting key metabolic and transcriptional pathways and provide a comprehensive view of their functional relevance, which suggests a complex genetic etiology for HPP.

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