Long-read sequencing resolves complex CYP21A2 variants and identifies 2+0 carriers in 21-hydroxylase deficiency.

Authors

Yanjie Xia, Di Cui, Danhua Li, Libao Chen, Xiaohang Chen, Shitong Wu, Aiping Mao, Xiangdong Kong

Published in

The Journal of molecular diagnostics : JMD. Sep 11, 2026. Epub Sep 11, 2026.

Abstract

The complex CYP21A2 variants arising from high homology with its pseudogene CYP21A1P challenge the diagnosis of 21-hydroxylase deficiency (21-OHD). This study systematically evaluated long-read sequencing (LRS) for identifying complex structural variants of the CYP21A2 gene in 21-OHD in comparison with conventional molecular diagnostic methods, including multiplex ligation-dependent probe amplification (MLPA), CNVplex, and SNaPshot. Twenty patients with suspected 21-OHD and defined CYP21A2 structural variants identified via initial MLPA screening were enrolled. Variants were further analyzed using CNVplex and SNaPshot, then all samples underwent LRS for comprehensive variant detection, breakpoint mapping, and haplotype resolution. LRS overcame key limitations of conventional methods. It reliably identified a novel large-fragment deletion and defined its boundaries. Notably, LRS identified "2+0" carriers, where deletions masked by duplications cause false-negatives with standard techniques. Moreover, LRS accurately distinguished CYP21A1P/CYP21A2_CH-4 and CH-9 chimera subtypes which were indistinguishable by the combined conventional assays. Furthermore, LRS enabled the precise identification and characterization of TNXA/TNXB chimeric deletions. These are frequently misclassified as CYP21A1P/CYP21A2 chimeras by conventional methods but are critical for diagnosing associated conditions such as CAH-X syndrome. LRS provides a superior, integrated solution for the molecular diagnosis of 21-OHD, offering precise structural variant characterization, accurate carrier detection, and reliable breakpoint mapping. Its application enhances diagnostic accuracy, supports advanced genetic counseling, and paves the way for genotype-informed clinical management.

PMID:
42727689
Bibliographic data and abstract were imported from PubMed on 12 Sep 2026.

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