This case highlights the diagnostic value of comprehensive genomic analysis and subsequent RNA sequencing for identifying and analyzing deep intronic variants in genetically unexplained cases of XLH and underscores the importance of re-evaluating patients with a strong clinical diagnosis but previously negative genetic results.
Abstract
X-linked hypophosphatemia (XLH) is a rare, genetically determined disorder of phosphate metabolism, most commonly caused by mutations in the PHEX gene. These mutations lead to overexpression of the phosphaturic hormone FGF23, resulting in renal phosphate wasting and impaired bone mineralization. In up to 16% of clinically diagnosed cases, no causative variant can be identified using standard sequencing approaches. We report on a female patient with a clearly defined clinical XLH phenotype, in whom no causative mutation had been detected over several years despite extensive genetic testing. The aim was to identify a previously undetected genetic cause using extended DNA and RNA methods. After unremarkable short-read whole exome sequencing (WES), short-read whole genome sequencing (WGS) was performed. For confirmation of splice effect, RNA was extracted from peripheral blood, amplified via RT-PCR, and analyzed using Nanopore long-read sequencing. A novel deep intronic variant in the PHEX gene (c.2070 + 601C>T) was identified and confirmed as de novo. The variant caused two aberrant transcripts with pseudoexon inclusions, each leading to a premature stop codon. This aberrant splicing supports the pathogenicity of the variant in the context of a loss-of-function mechanism. Following molecular diagnosis, the patient was successfully initiated on Burosumab therapy, resulting in clinical improvement. This case highlights the diagnostic value of comprehensive genomic analysis and subsequent RNA sequencing for identifying and analyzing deep intronic variants in genetically unexplained cases of XLH. The findings expand the known PHEX mutation spectrum and emphasize the importance of re-evaluating patients with a strong clinical diagnosis but previously negative genetic results. In the future, such technologies may play a crucial role in improving diagnostics for rare monogenic diseases.
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