Screening of PAH Common Mutations in Chinese Phenylketonuria Patients Using iPLEX MALDI-TOF MS

Building Minimized Epigenetic Clock by iPlex MassARRAY Platform

Epigenetic clocks are valuable tools for estimating both chronological and biological age by assessing DNA methylation levels at specific CpG dinucleotides. While conventional epigenetic clocks rely on genome-wide methylation data, targeted approaches offer a more efficient alternative. In this study, we explored the feasibility of constructing a minimized epigenetic clock utilizing data acquired through the iPlex MassARRAY technology. The study enrolled a cohort of relatively healthy individuals, and their methylation levels of eight specific CpG dinucleotides in genes SLC12A5, LDB2, FIGN, ACSS3, FHL2, and EPHX3 were evaluated using the iPlex MassARRAY system and the Illumina EPIC array. The methylation level of five studied CpG sites demonstrated significant correlations with chronological age and an acceptable convergence of data obtained by the iPlex MassARRAY and Illumina EPIC array. At the same time, the methylation level of three CpG sites showed a weak relationship with age and exhibited a low concordance between the data obtained from the two technologies. The construction of the epigenetic clock involved the utilization of different machine-learning models, including linear models, deep neural networks (DNN), and gradient-boosted decision trees (GBDT). The results obtained from these models were compared with each other and with the outcomes generated by other well-established epigenetic clocks. In our study, the TabNet architecture (deep tabular data learning architecture) exhibited the best performance (best MAE = 5.99). Although our minimized epigenetic clock yielded slightly higher age prediction errors compared to other epigenetic clocks, it still represents a viable alternative to the genome-wide epigenotyping array.

A capillary electrophoresis-based variant hotspot genotyping method for rapid and reliable analysis of the phenylalanine hydroxylase gene in the Chinese Han population

BACKGROUND AND AIMS

Hyperphenylalaninemia (HPA) is a common autosomal recessive disorder of phenylalanine metabolism, mainly caused by the deficiency of phenylalanine hydroxylase gene (PAH). A simple, fast, and accurate assay to achieve early diagnosis for children with HPA is required.

MATERIALS AND METHODS

In the present study, we established a SNaPshot-based assay that allows the simultaneous genotyping of 96 hotspot variants in the PAH gene. First, 18 Chinese HPA patients were analyzed by next generation sequencing (NGS) and SNaPshot in parallel. Then, the SNaPshot assay was performed to analyze the mutational spectrum of the PAH in 4,276 individuals in Eastern China.

RESULTS

A total of 36 variants in the PAH gene were successfully identified by NGS, while the SNaPshot assay identified 34 PAH variants in these patients. Thus, the SNaPshot assay achieved the sensitivity and specificity of 91.6% and 100.0%, respectively. Furthermore, the carrier rate was approximately 1 in 58 (1.73%) in 4,276 individuals, and c.728G > A was the most common variant.

CONCLUSION

In summary, SNaPshot can accurately and rapidly detect PAH gene variants at a comparable performance and lower cost as compared with NGS. Our results suggest that SNaPshot may serve as a promising approach for a routine genetic test in clinical practice.