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Review
. 2022 Feb 18;11(4):1061.
doi: 10.3390/jcm11041061.

The Utility of Genomic Testing for Hyperphenylalaninemia

Affiliations
Review

The Utility of Genomic Testing for Hyperphenylalaninemia

Elisabetta Anna Tendi et al. J Clin Med. .

Abstract

Hyperphenylalaninemia (HPA), the most common amino acid metabolism disorder, is caused by defects in enzymes involved in phenylalanine metabolism, with the consequent accumulation of phenylalanine and its secondary metabolites in body fluids and tissues. Clinical manifestations of HPA include mental retardation, and its early diagnosis with timely treatment can improve the prognosis of affected patients. Due to the genetic complexity and heterogeneity of HPA, high-throughput molecular technologies, such as next-generation sequencing (NGS), are becoming indispensable tools to fully characterize the etiology, helping clinicians to promptly identify the exact patients' genotype and determine the appropriate treatment. In this review, after a brief overview of the key enzymes involved in phenylalanine metabolism, we represent the wide spectrum of genes and their variants associated with HPA and discuss the utility of genomic testing for improved diagnosis and clinical management of HPA.

Keywords: genomics; hyperphenylalaninemia; inherited metabolic disorders.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Metabolic pathway of Phe and BH4. Phe metabolism is crucial for protein synthesis, as well as for the synthesis of Tyr and its derivatives. The major catabolic pathway involves Phe hydroxylation to Tyr by PAH. In one of the minor pathways, Phe may undergo conversion to Phenylpyruvic acid. An essential cofactor and regulator of PAH is BH4, whose biosynthesis and regeneration depend by different enzymes. Abbreviations: AATC, Aspartate aminotransferase, cytoplasmic; AATM, Aspartate aminotransferase, mitochondrial; DCoH, Pterin-4-alpha-carbinolamine dehydratase; DHPR, Dihydropteridine reductase; DNAJC12, DNAJ homolog subfamily C member 12; GCH1, Guanosine triphosphate (GTP) cyclohydrolase 1; KAT1, Kynurenine-oxoglutarate transaminase 1; PAH, Phenylalanine-4-hydroxylase; PTS, 6-pyruvoyl tetrahydrobiopterin synthase; SPR, Sepiapterin reductase; TPH1, Tryptophan 5-hydroxylase 1; TPH2, Tryptophan 5-hydroxylase 2; PCBD1, Pterin-4a-carbinolamine dehydratase; EC number 1.5.1.34: Dihydrobiopterin + NADH = NAD+ + Tetrahydrobiopterin; EC number 1.14.16.1: O2 + Tetrahydrobiopterin + S-Methylcysteine = S-Methylcysteine-sulfoxide + H2O + Dihydrobiopterin; EC number: 1.14.16.4 L-Tryptophan + O2 + Tetrahydrobiopterin = 5-Hydroxyl-L-Tryptophan+4alpha-Hydroxytetrahydrobiopterin; EC number 2.6.1.5-2.6.1.64: L-Phenylalanine + 2-Oxoglutaric acid = L-Glutamic acid + Phenylpyruvic acid.
Figure 2
Figure 2
Analytical workflow of targeted sequencing for the Ion Torrent and Illumina methods. (A) Panel design: the Designer software helps to create custom assays based on PCR target selection. (B) Library preparation: library construction is the preparation of the nucleic acid target into a form compatible with the sequencing system to be used. (C) Template preparation and chip loading: target enrichment is used in NGS workflows to capture only genomic DNA regions of interest. (D) Sequencing and data generation: IonTorrent platform: microwells of the chip is flooded by nucleotides that when binding to the complementary nucleotide on a template, release an ion. At each flow, the electrical signal at each well is measured, indicating that a reaction has occurred; Illumina platform: the fragments are clonally amplified on the slide utilizing fluorescently labeled reversible-terminator nucleotides; (E) Read assembly and annotation: starting from Binary Alignment Map (BAM) and Variant Call Format (VCF) files, variants are prioritized based on localization, functional effect, mode of inheritance, coverage and Minor Allelic Frequency (MAF) to obtain disease-correlated variants.
Figure 3
Figure 3
Sequencing performance of Ion Torrent. Metrics, such as Raw Accuracy, Aligned Bases, and Total Reads, can be used to determine the performance of a run.

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