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Egyptian Journal of Medical Human Genetics
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In silico analysis and the pathogenicity classification of PTS gene variants among Iranian population

Egyptian Journal of Medical Human Genetics volume 23, Article number: 139 (2022) Cite this article

Abstract

Background

6-Pyruvoyl-tetrahydropterin synthase (PTPS) deficiency is an autosomal recessive disorder caused by PTS gene mutations. The aim of this study was to collect all PTS gene variants detected among Iranian patients with PTPS deficiency as well as in the Iranome project and classify them based on American College of Medical Genetics and Genomics (ACMG-AMP) guidelines.

Results

The number of PTS gene variants reported among Iranian PTPS patients and in the Iranome project were 19 and 36, respectively. Given that one variant was reported in both of our sources, the total number of variants was 54. These variants were classified as pathogenic (n = 11), likely pathogenic (n = 7), VUS (n = 23), likely benign (n = 1), and benign (n = 12). Out of 19 variants reported among Iranian PTPS patients, c.155A>G (p.Asn52Ser, rs104894275) and c.317C>T (p.Thr106Met, rs200712908) were the most frequent ones, each with a frequency of 10%. c.84-3C>G (rs1230781262) (7.5%) and c.281A>T (p.Asp94Val) (5%) were in the next ranks of the list of variants.

Conclusions

The ACMG-AMP criteria need to be updated depending on the type of disease. In addition, to the best of our knowledge, no template has been described for classifying the variants identified in PTPS deficiency. Therefore, this study can be a good reference for future studies in this subject.

Introduction

Phenylalanine hydroxylase (PAH) deficiency, with an autosomal recessive inheritance, is known to be the main cause of hyperphenylalaninemia (HPA). On the other hand, 6R-L-erythro-5,6,7,8-tetrahydrobiopterin (BH4) is an essential cofactor for phenylalanine, tyrosine and tryptophan hydroxylases. There are two pathways for generating this cofactor, including de novo synthesis and recycling, in which different enzymes are involved in each pathway [1].

Patients with BH4 deficiency may develop nervous system symptoms, including intellectual disability. It has been estimated that the frequency of BH4 deficiency is about 1 to 2% of all patients with HPA [1, 2]. 6-Pyruvoyl-tetrahydropterin synthase (PTPS) deficiency (MIM #261640) is a main cause of BH4 deficient HPA; out of 1161 cases with BH4 disorders registered in BIODEF database (last update: September 13, 2019) (available at http://www.biopku.org), 735 cases had PTPS deficiency (63.3%). HPA, higher levels of neopterin and lower levels of biopterin are among the biochemical characteristics of patients with PTPS deficiency [1, 3]. As an autosomal recessive disorder, PTPS deficiency is caused by PTS gene mutations. This gene has been mapped on chromosome 11 (11q23.1) and comprises six exons [1]. According to PND database (available at http://www.biopku.org), 198 variants have been recorded in this gene, most of them are missense variants.

Although the exact frequency of BH4 deficiency among HPA patients from Iran is unknown, it seems that it has a higher frequency than the global rate. For example, based on a study performed in western Iran, its frequency was calculated to be 6.25% [4]. In another study performed on HPA patients from all over of the country, this rate was estimated to be 12.3% [5]. In addition, out of 123 patients with BH4 deficiency, 60 cases had been reported with PTPS deficiency (48.8%) [5, 6].

The Iranome project (http://www.iranome.ir/) is a valuable recent project implemented in Iran. In the Iranome project, the genetics of 800 healthy Iranians with different ethnicities have been analyzed using the whole exome sequencing technique. The aim of this study was to collect all PTS gene variants detected among Iranian patients with PTPS deficiency as well as in the Iranome project, predict their effects using in silico predictive tools, and classify them based on American College of Medical Genetics and Genomics (ACMG-AMP) guidelines.

Methods

Our strategy in this study is as follows step by step.

Systematic collection of PTS gene variants

Two different sources including the Iranome project and scientific reports were used to extract all reported PTS gene variants in Iran.

Verification of variants

The GenBank entry NM_000317.3 and UniProtKB/SwissProt Q03393 were used to determine the genetic and protein variant positions, respectively. The unique properties associated with each variant, including HGVS nomenclature and reference SNP ID (RSID), were obtained from Varsome database (https://varsome.com); variants whose nucleotide or amino acid changes were incorrectly reported were excluded from the study. In the next step, all variants reported in the Iranome project were searched in various databases including BioPKU (http://www.biopku.org/home/pnddb.asp), Leiden Open Variation Database (LOVD) (https://www.lovd.nl/), the Human Gene Mutation Database (HGMD) (http://www.hgmd.cf.ac.uk/ac/index.php), dbSNP (https://www.ncbi.nlm.nih.gov/snp/), ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/), Genome Aggregation Database (gnomAD) (available at https://varsome.com), 1000 Genomes Project (1KGP) (available at http://grch37.ensembl.org/Homo_sapiens/Info/Index), as well as the literature scientific reports to determine if they were novel or previously reported. gnomAD and 1KGP were used as the reference to obtain population data.

In silico analysis

To apply PP3/BP4 criteria in the classification of missense variants, 10 predictive tools including: CADD (https://cadd.gs.washington.edu/), Mutation Taster (http://www.mutationtaster.org/), Polyphen-2 (http://genetics.bwh.harvard.edu/pph2/), I-Mutant disease (http://gpcr.biocomp.unibo.it/cgi/predictors/I-Mutant3.0/I-Mutant3.0.cgi), PROVEAN and SIFT (both available at: http://provean.jcvi.org/index.php), SNPs&GO (https://snps.biofold.org/snps-and-go/), FATHMM-XF (http://fathmm.biocompute.org.uk/fathmm-xf/), PhD-SNPg (https://snps.biofold.org/phd-snpg/#), and PANTHER PSEP (http://pantherdb.org/), were used. On the other hand, seven splicing predictive tools including VarSEAK and MaxEntScan (both available at: https://varseak.bio/), ASSP (http://wangcomputing.com/assp/index.html), NetGene2 (http://www.cbs.dtu.dk/services/NetGene2/), NNSplice (https://www.fruitfly.org/seq_tools/splice.html), CRYP-SKIP (https://cryp-skip.img.cas.cz/), and GENSCAN (http://pbil.univ-lyon1.fr/members/duret/cours/tmp/results/GenScan.html) were used to predict the splicing effects of all missense, synonymous and intronic variants outside the canonical splice acceptor (− 1 and − 2) and donor (+ 1 and + 2) regions. In the next step, the outcome of variants was examined.

Application of ACMG-AMP guidelines

Each of the 28 ACMG-AMP criteria is shown with a code and each code is assigned a weight and direction [7]. Accordingly, the final classification of variants would be as: pathogenic (P), likely pathogenic (LP), variant of uncertain significance (VUS), likely benign (LB), or benign (B). To the best of our knowledge, no template has been defined for classifying the variants identified in PTPS deficiency based on ACMG-AMP guidelines. In the present study, while we used the recommendations defined by expert groups [7,8,9,10], some adjustments were made to classify variants.

To assign PP3/BP4 criteria, Ellard et al. study [9] was used as a template and adapted based on the type and number of tools used here. Accordingly, deleterious results of missense variants in ≥ 7 or ≤ 4 out of 10 tools was accepted as a supporting criterion of PP3 or BP4, respectively. Otherwise, none of them were considered. To accept the effect of a variant on splicing process, three situations were considered: (a) reduction in the score of acceptor or donor splice sites (ASS of DSS, respectively) by 15% or more relative to reference sequence, (b) creating a new ASS or DSS, or c) activation of a cryptic splice site. If ≥ 5 or ≤ 3 out of 7 tools showed each of these situations, PP3 or BP4 was assigned, respectively. Otherwise, neither PP3 nor BP4 was triggered. For synonymous variants with no effect on splicing process, BP7 was used.

PM2 criterion was assigned when a variant was absent in population databases. To assign PM2, BS1, or BA1 for other variants, the results of Varsome database were used. Although PM3 has a moderate weight in its original form, it was upgraded (PM3_strong: PM3_S or PM3_very strong: PM3_VS) or downgraded (PM3_supporting: PM3_Su) based on Zastrow et al. study [8]. PP4 was defined as a supporting criterion when the biochemical phenotype of a patient was consistent with PTPS deficiency (higher neopterin and lower biopterin). With adaptation from Zastrow et al. study [8], PS3 criterion was assigned for variants with PTPS enzyme activity of < 50% or RT-PCR confirming mis-splicing due to non-canonical intronic variants. In addition, with adaptation from Ellard et al. study [9], if there were two or only one related references, PS3 was downgraded to PS3_moderate (PS3_M) or PS3_supporting (PS3_Su), respectively. Moreover, the PTPS enzyme activity of > 85% was used for assigning of BS3 criterion. In situations that PVS1 or PS3 were assigned, PP3 was not used [9]. Finally, BS2 was applied when a variant was observed in homozygous form in a healthy adult [8].

Results

Scientific reports and the Iranome project were our sources to collect all PTS gene variants in Iran. Our literature review revealed two studies in which the mutational spectrum of a total of 60 Iranian patients with PTPS deficiency had been examined [5, 6]. The ratio of male to female, the rate of consanguineous marriages among the patients’ parents, and the age range at the time of diagnosis were 1.00 (30/30), 73.34%, and 13-days to 12-years, respectively. Out of 19 variants reported, six variants were novel at the time of these studies (Table 1A). On the other hand, a total of 36 variants had been recorded in the Iranome project (Table 1B). Given that one variant, c.373G>A (p.Gly125Arg), was reported in both of our sources, the total number of variants collected in this study was 54 (Fig. 1 and Table 1). Variants were classified as exonic (missense: n = 15, synonymous: n = 4, and nonsense: n = 1), intronic (n = 32), and untranslated region (UTR) (n = 2) (Tables 2 and 3). Two variants were excluded from the study because they did not match to NM_000317.3 [5].

Table 1 PTS gene variants reported among Iranian population
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Fig. 1
figure 1

Position of PTS gene variants reported among Iranian population (the genomic structure of PTS gene was adapted from Himmelreich et al., 2021)

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Table 2 Pathogenicity prediction of PTS gene missense variants
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Table 3 Pathogenicity prediction of PTS gene intronic and synonymous variants. AASS: authentic acceptor splice site, ADSS: authentic donor splice site
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Missense and nonsense variants

A total of 15 missense variants were identified; all of them, except for c.351C>A (p.Asn117Lys), had deleterious effects in seven or more predictive tools (Table 2). The ACMG-AMP criteria assigned to each variant are shown in Table 4; accordingly, except for c.70C>G (p.His24Asp) and c.351C>A (p.Asn117Lys) with VUS classification, other missense variants were classified as P or LP (Table 4). On the other hand, only one nonsense variant, c.297C>A (p.Tyr99Ter, rs145882709), was identified; based on ACMG-AMP criteria, it was classified as P (Table 4).

Table 4 ACMG-AMP classification of PTS gene variants reported among Iranian population
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Splicing variants

Using splicing predictive tools, all intronic and synonymous variants were evaluated to find their possible effects on splicing process. Out of 36 variants in this group (Table 3), only four variants including c.84-3C>G, c.163+2T>C, c.164-1G>C, and c.315-1G>A (rs776543880) showed significant effects on splicing process (Table 3); according to ACMG-AMP guidelines, they were classified as P (Table 4). BP4 or BP7 criteria were assigned to the remaining 32 variants and their final classification was B, LB, or VUS (Table 4).

Discussion

To collect all reported PTS gene variants reported in Iran and analyze their pathogenicity, a literature search was performed and a total of 54 variants were identified (Table 1). So far, only a small number of studies on the genetics of patients with PTPS deficiency have been performed in Iran, and only 800 healthy individuals have been studied in the Iranome project. On the other hand, Iran is a country with a population of about 85 million people as well as a high ethnic diversity [11,12,13,14,15,16,17,18]. In fact, recent studies have shown high mutational diversity of single-gene disorders in Iran [19,20,21,22,23]. From all the above issues, it is possible that the number of PTS gene variants in Iran increase in the future.

A total of 19 variants had been reported among Iranian patients with PTPS deficiency. c.155A>G (p.Asn52Ser) and c.317C>T (p.Thr106Met) were the most frequent variants, each with a frequency of 10% (Table 1). c.155A>G (p.Asn52Ser) has been known as a common variant in East Asia [1], especially in Taiwan [24]. In its homozygous form, c.155A>G (p.Asn52Ser) causes sever PTPS deficiency [25]. On the other hand, c.317C>T (p.Thr106Met) has a high frequency of 32% in Russia [26]. Both of these variants were reported repeatedly in combination with P/LP variants, as well as in the form of homozygous [5, 6, 24,25,26,27,28,29,30,31]. Therefore, the two ACMG-AMP criteria, PM3_VS and PP4, were assigned for these variants. Although no functional studies were found in the literature for these variants, in silico analysis revealed that both are deleterious in all 10 predictive tools, therefore, PP3 was met (Table 2). Finally, based on the assigned criteria, c.155A>G (p.Asn52Ser) and c.317C>T (p.Thr106Met) were classified as P (Table 4).

c.84-3C>G, with a frequency of 7.5%, was the third most frequent variant in Iranian patients with PTPS deficiency (Table 1). It seems that this is the highest frequency reported to date for this variant. c.84-3C>G was reported for the first time in 1997 [32]. Subsequently, it was detected with low frequencies in homozygous form or in combination with P/LP variants in at least five other studies (consistent with PM3_VS and PP4 criteria) [5, 6, 26, 31, 33]. In silico analysis of this variant showed loss of function or a strong decrease of score for authentic ASS; accordingly, exon skipping was predicted to be the final outcome (Fig. 2 and Table 3). However, according to Oppliger et al. functional analysis on this variant [32], the use of a cryptic splicing site would result in a 12 nucleotides deletion at the beginning of exon 2 and finally, a deletion of four amino acids (p.Lys29_Ser32del) (Fig. 2). These authors also reported a complete inactivity of PTPS enzyme encoded by this allele (consistent with PS3_Su criterion). Due to the assigning of PS3, PP3 was not applied for c.84-3C>G [9]. As shown in Table 4, this variant was classified as P according to ACMG-AMP guidelines.

Fig. 2
figure 2

In silico analysis of PTS:c.84-3C>G variant using splicing predictive tools. Although exon skipping was predicted by these tools, according to Oppliger et al. (1997) functional study, the use of a cryptic splicing site would result in a deletion of 12 nucleotides at the beginning of exon 2 and finally, a deletion of four amino acids (p.Lys29_Ser32del)

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c.281A>T (p.Asp94Val), c.331G>A (p.Ala111Thr, rs1367077861), and c.351C>A (p.Asn117Lys) had the allele frequencies of 5, 3.3, and 3.3% among Iranian PTPS patients. These variants were only reported in homozygous form and to the best of our knowledge, there is no report of their combination with P/LP variants in the literature [5, 6, 24, 34]; accordingly, along with PP4, PM3_Su was also applied [8]. Moreover, none of them were reported in gnomAD and 1KGP databases (consistent with PM2 criterion). While PP3 criterion was assigned to c.281A>T (p.Asp94Val) and c.331G>A (p.Ala111Thr) variants, c.351C>A (p.Asp117Lys) failed to reach the threshold defined by us in the Methods section (neither PP3 nor BP4 was used) (Table 2). Finally, according to ACMG-AMP guidelines, while the first two variants were classified as LP, the last one was classified as VUS (Table 4).

Nine other variants, each with a frequency of 1.67%, including c.400G>A (p.Glu134Lys, rs779681799), c.259C>T (p.Pro87Ser, rs104894276), c.286G>A (p.Asp96Asn, rs104894280), c.367C>T (p.Pro123Ser, rs141163668), c.412A>C (p.Asn138His, rs1329239489), c.293C>T (p.Pro98Leu, rs748040027), c.70C>G (p.His24Asp), c.407A>T (p.Asp136Val), and c.164-36A>G were also reported among Iranian PTPS patients. c.400G>A (p.Glu134Lys) was first identified in 2017 in an Iranian patient [5], and has subsequently been reported in Omani [30] and Russian [26] patients. Although c.259C>T (p.Pro87Ser) is a common variant in East Asia [27, 29, 35,36,37,38], it also has been detected in Iran [5] and Russia [26]. Similarly, c.286G>A (p.Asp96Asn) is common in East Asian populations [29, 35,36,37]. According to Imamura et al. study [35], the PTPS enzyme activities of p.Pro87Ser and p.Asp96Asn proteins in COS cells was 52 and 10%, respectively; therefore, PS3_Su was only applied for c.286G>A (p.Asp96Asn) (Table 4).

Oppliger et al. reported that the overexpression of c.407A>T (p.Asp136Val) in COS-1 cells would reduce PTPS activity to 31% compared to the wild-type enzyme (consistent with PS3 criterion) [32]. This variant has been found in Italian, Polish, Turkish, German, and Iranian patients so far [6, 32, 33, 39, 40]. Khatami et al. reported c.164-36A>G in homozygous form in an Iranian patient with PTPS deficiency [5] and to the best of our knowledge, there is no other report for this variant in the literature. Our analysis showed that this variant has no effect on splicing process (Table 3) and was classified as a VUS variant (Table 4). Four variants of c.200C>T (p.Thr67Met, rs370340361), c.297C>A (p.Tyr99Ter), c.163+2T>C, and c.373G>A (p.Gly125Arg) had the lowest frequencies in this study (Table 1). With the exception of c.200C>T (p.Thr67Met) [6, 32, 36, 41, 42], the other three variants have been reported in only a few studies [5, 6].

Out of 36 variants identified in the Iranome project, only three variants including c.164-1G>C, c.315-1G>A, and c.373G>A (p.Gly125Arg) were classified in the category of P/LP. c.373G>A (p.Gly125Arg) had also been reported among Iranian PTPS patients (the above paragraph) (Table 1). Both of c.164-1G>C and c.315-1G>A are rare splicing variants [26, 31]. Both of these variants cause loss of function of ASS (Table 3), however, because of assigning of PVS1 criterion, PP3 was not applied [9]. The other intronic or synonymous variants had no effect on splicing process (Tables 1 and 3) and were classified as B, LB, or VUS (Table 4). The splicing effect analysis of some of these variants are shown in Table 3.

In conclusion, the collection of all reported PTS gene variants in the Iranian population, their analysis using in silico predictive tools, and their classification according to ACMG-AMP criteria were the three main areas in the present study. The ACMG-AMP criteria need to be updated depending on the type of disease. In addition, to the best of our knowledge, no template has been described for classifying the variants identified in PTPS deficiency. Therefore, this study can be a good reference for future studies in this area.

Availability of data and materials

Not applicable.

References

  1. Himmelreich N, Blau N, Thöny B (2021) Molecular and metabolic bases of tetrahydrobiopterin (BH4) deficiencies. Mol Genet Metab 133(2):123–136

    CAS  PubMed  Article  Google Scholar 

  2. Bozaci AE, Er E, Yazici H, Canda E, Kalkan Uçar S, Güvenc Saka M et al (2021) Tetrahydrobiopterin deficiencies: lesson from clinical experience. JIMD Rep 59(1):42–51

    PubMed  PubMed Central  Article  Google Scholar 

  3. Fernández-Lainez C, Ibarra-González I, Alcántara-Ortigoza MÁ, Fernández-Hernández L, Enríquez-Flores S, González-del Ángel A et al (2018) Mutational spectrum of PTS gene and in silico pathological assessment of a novel variant in Mexico. Brain Dev 40(7):530–536

    PubMed  Article  Google Scholar 

  4. Moradi K, Alibakhshi R, Khatami S (2013) The proportion of tetrahydrobiopterin deficiency and PAH gene deficiency variants among cases with hyperphenyalaninemia in Western Iran. Indian J Hum Genet 19(4):454–458

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  5. Khatami S, Dehnabeh SR, Zeinali S, Thöny B, Alaei M, Salehpour S et al (2017) Four years of diagnostic challenges with tetrahydrobiopterin deficiencies in Iranian patients. JIMD Rep 32:7–14

    PubMed  Article  Google Scholar 

  6. Khani S, Barzegari M, Esmaeilizadeh Z, Farsian P, Alaei M, Salehpour S et al (2021) The treatment and clinical follow-up outcome in Iranian patients with tetrahydrobiopterin deficiency. J Pediatr Endocrinol Metab 34(9):1157–1167

    PubMed  Article  Google Scholar 

  7. Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J et al (2015) Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med 17(5):405–423

    PubMed  PubMed Central  Article  Google Scholar 

  8. Zastrow DB, Baudet H, Shen W, Thomas A, Si Y, Weaver MA et al (2018) Unique aspects of sequence variant interpretation for inborn errors of metabolism (IEM): the ClinGen IEM Working Group and the Phenylalanine Hydroxylase Gene. Hum Mutat 39(11):1569–1580

    PubMed  PubMed Central  Article  Google Scholar 

  9. Ellard S, Baple E, Berry I, Forrester N, Turnbull C, Owens M, ACGS Best Practice Guidelines for Variant Classification et al (2019) Association for Clinical Genomic Science. Br Soc Genet Med Lond 2019:1–32

    Google Scholar 

  10. Zhang J, Yao Y, He H, Shen J (2020) Clinical interpretation of sequence variants. Curr Protoc Hum Genet 106(1):e98

    PubMed  PubMed Central  Google Scholar 

  11. Alibakhshi R, Moradi K, Aznab M, Azimi A, Shafieenia S, Biglari M (2019) The spectrum of β-thalassemia mutations in Hamadan Province, West Iran. Hemoglobin 43(1):18–22

    CAS  PubMed  Article  Google Scholar 

  12. Moradi K, Aznab M, Tahmasebi S, Dastafkan Z, Omidniakan L, Ahmadi M et al (2019) The spectrum of α-thalassemia mutations in the Lak population of Iran. Hemoglobin 43(2):107–111

    CAS  PubMed  Article  Google Scholar 

  13. Moradi K, Aznab M, Biglari M, Shafieenia S, Azimi A, Bijari N et al (2020) Molecular genetic analysis of α-thalassemia in Hamadan province, West Iran. Hemoglobin 44(5):319–324

    CAS  PubMed  Article  Google Scholar 

  14. Moradi K, Aznab M, Tahmasebi S, Omidniakan L, Bijari N, Alibakhshi R (2020) Distribution of HBB gene mutations in the Kurdish population of Ilam province, West Iran. Hemoglobin 44(4):244–248

    CAS  PubMed  Article  Google Scholar 

  15. Pouranfard J, Vafaei F, Afrouz S, Rezaeian M (2020) Thalassemia gene mutations in Kohgiluyeh and Boyer-Ahmad Province. Iran J Blood Cancer 12(1):18–23

    Google Scholar 

  16. Moradi K, Aznab M, Azimi A, Biglari M, Shafieenia S, Alibakhshi R (2020) α-Thalassemia mutations in Ilam Province, West Iran. Hemoglobin 19:1–6

    Article  CAS  Google Scholar 

  17. Galehdari H, Salehi B, Azmoun S, Keikhaei B, Zandian KM, Pedram M (2010) Comprehensive spectrum of the β-thalassemia mutations in Khuzestan, Southwest Iran. Hemoglobin 34(5):461–468

    CAS  PubMed  Article  Google Scholar 

  18. Miri-Moghaddam E, Zadeh-Vakili A, Rouhani Z, Naderi M, Eshghi P, Feizabad AK (2011) Molecular basis and prenatal diagnosis of β-thalassemia among Balouch population in Iran. Prenat Diagn 31(8):788–791

    CAS  PubMed  Article  Google Scholar 

  19. Bazi A, Miri-Moghaddam E (2016) Spectrum of β-thalassemia Mutations in Iran, an Update. Iran J Ped Hematol Oncol 6(3):190–202

    Google Scholar 

  20. Mahdieh N, Rabbani B (2016) Beta thalassemia in 31,734 cases with HBB gene mutations: pathogenic and structural analysis of the common mutations; Iran as the crossroads of the Middle East. Blood Rev 30(6):493–508

    CAS  PubMed  Article  Google Scholar 

  21. Valaei A, Karimipoor M, Kordafshari A, Zeinali S (2018) Molecular basis of α-thalassemia in Iran. Iran Biomed J 22(1):6–14

    PubMed  PubMed Central  Google Scholar 

  22. Alibakhshi R, Mohammadi A, Khamooshian S, Kazeminia M, Moradi K (2021) CFTR gene mutation spectrum among 735 Iranian patients with cystic fibrosis: a comprehensive systematic review. Pediatr Pulmonol 56(12):3644–3656

    PubMed  Article  Google Scholar 

  23. Alibakhshi R, Mohammadi A, Salari N, Khamooshian S, Kazeminia M, Moradi K (2021) Spectrum of PAH gene mutations in 1547 phenylketonuria patients from Iran: a comprehensive systematic review. Metab Brain Dis 36:767–780

    CAS  PubMed  Article  Google Scholar 

  24. Chiu Y-H, Chang Y-C, Chang Y-H, Niu D-M, Yang Y-L, Ye J et al (2012) Mutation spectrum of and founder effects affecting the PTS gene in East Asian populations. J Hum Genet 57(2):145–152

    CAS  PubMed  Article  Google Scholar 

  25. Leuzzi V, Carducci C, Carducci C, Pozzessere S, Burlina A, Cerone R et al (2010) Phenotypic variability, neurological outcome and genetics background of 6-pyruvoyl-tetrahydropterin synthase deficiency. Clin Genet 77(3):249–257

    CAS  PubMed  Article  Google Scholar 

  26. Gundorova P, Kuznetcova IA, Baydakova GV, Stepanova AA, Itkis YS, Kakaulina VS et al (2021) BH4-deficient hyperphenylalaninemia in Russia. PLoS ONE 16(4):e0249608

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  27. Wang X, He Y, Jiang Y, Feng X, Zhang G, Xia Z et al (2019) Screening and mutation analysis of hyperphenylalaninemia in newborns from Xiamen, China. Clin Chim Acta 498:161–166

    CAS  PubMed  Article  Google Scholar 

  28. Hong F, Yang R, Huang C, Tong F (2015) Case report genotype of mild 6-pyruvoyl-tetrahydropterin synthase deficiency: three case reports and a literature review. HK J Paediatr (new series) 20(3):163–168

    Google Scholar 

  29. Han B, Zou H, Han B, Zhu W, Cao Z, Liu Y (2015) Diagnosis, treatment and follow-up of patients with tetrahydrobiopterin deficiency in Shandong province, China. Brain Dev 37(6):592–598

    PubMed  Article  Google Scholar 

  30. Almannai M, Felemban R, Saleh MA, Faqeih EA, Alasmari A, AlHashem A et al (2019) 6-Pyruvoyltetrahydropterin synthase deficiency: Review and report of 28 Arab subjects. Pediatr Neurol 96:40–47

    PubMed  Article  Google Scholar 

  31. Manti F, Nardecchia F, Banderali G, Burlina A, Carducci C, Carducci C et al (2020) Long-term clinical outcome of 6-pyruvoyl-tetrahydropterin synthase-deficient patients. Mol Genet Metab 131(1–2):155–162

    CAS  PubMed  Article  Google Scholar 

  32. Oppliger T, Thöny B, Kluge C, Matasovic A, Heizmann CW, Ponzone A et al (1997) Identification of mutations causing 6-pyruvoyl-tetrahydropterin synthase deficiency in four Italian families. Hum Mutat 10(1):25–35

    CAS  PubMed  Article  Google Scholar 

  33. Romstad A, Guldberg P, Blau N, Guttler F (1999) Single-step mutation scanning of the 6-pyruvoyltetrahydropterin synthase gene in patients with hyperphenylalaninemia. Clin Chem 45(12):2102–2108

    CAS  PubMed  Article  Google Scholar 

  34. Li N, Yu P, Rao B, Deng Y, Guo Y, Huang Y et al (2018) Molecular genetics of tetrahydrobiopterin deficiency in Chinese patients. J Pediatr Endocrinol Metab 31(8):911–916

    PubMed  Article  CAS  Google Scholar 

  35. Imamura T, Okano Y, Shintaku H, Hase Y, Isshiki G (1999) Molecular characterization of 6-pyruvoyl-tetrahydropterin synthase deficiency in Japanese patients. J Hum Genet 44(3):163–168

    CAS  PubMed  Article  Google Scholar 

  36. Liu TT, Chang YH, Chiang SH, Yang YL, Yu WM, Hsiao KJ (2001) Identification of three novel 6-pyruvoyl-tetrahydropterin synthase gene mutations (226C> T, IVS3+ 1G> A, 116–119delTGTT) in Chinese hyperphenylalaninemia caused by tetrahydrobiopterin synthesis deficiency. Hum Mutat 18(1):83

    CAS  PubMed  Article  Google Scholar 

  37. Cao Y, Qu Y, Song F, Zhang T, Bai J, Jin Y et al (2014) Fast clinical molecular diagnosis of hyperphenylalaninemia using next-generation sequencing-based on a custom AmpliSeq™ panel and Ion Torrent PGM sequencing. Mol Genet Metab 113(4):261–266

    CAS  PubMed  Article  Google Scholar 

  38. Gu Y, Lu K, Yang G, Cen Z, Yu L, Lin L et al (2014) Mutation spectrum of six genes in Chinese phenylketonuria patients obtained through next-generation sequencing. PLoS ONE 9(4):e94100

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  39. Żekanowski C, Nowacka M, Sendecka E, Słowik M, Cabalska B, Bal J (1998) Identification of mutations causing 6-pyruvoyl-tetrahydrobiopterin synthase deficiency in polish patients with variant hyperphenylalaninemia. Mol Diagn Ther 3(4):237–239

    Article  Google Scholar 

  40. Dudešek A, Röschinger W, Muntau AC, Seidel J, Leupold D, Thöny B et al (2001) Molecular analysis and long-term follow-up of patients with different forms of 6-pyruvoyl-tetrahydropterin synthase deficiency. Eur J Pediatr 160(5):267–276

    PubMed  Article  Google Scholar 

  41. Pangkanon S, Charoensiriwatana W, Liamsuwan S (2006) 6-Pyruvoyltetrahydropterin synthase deficiency two-case report. J Med Assoc Thai 89(6):872–877

    PubMed  Google Scholar 

  42. Chaiyasap P, Ittiwut C, Srichomthong C, Sangsin A, Suphapeetiporn K, Shotelersuk V (2017) Massive parallel sequencing as a new diagnostic approach for phenylketonuria and tetrahydrobiopterin-deficiency in Thailand. BMC Med Genet 18(1):102

    PubMed  PubMed Central  Article  CAS  Google Scholar 

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Acknowledgements

We hereby express our gratitude and appreciation to the Student Research Committee and Deputy for Research and Technology, Kermanshah University of Medical Sciences, Kermanshah, Iran, for reviewing, transferring to the ethics research committee and final approval of the project.

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Authors and Affiliations

  1. Student Research Committee, Kermanshah University of Medical Sciences, Kermanshah, Iran

    Sahand Khamooshian & Mohsen Kazeminia

  2. Infectious Diseases Research Center, Health Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran

    Keivan Moradi

Authors
  1. Sahand Khamooshian
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  2. Mohsen Kazeminia
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  3. Keivan Moradi
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Contributions

KM had the idea of the topic. Literature search and data collection was performed by KM, SK and MK. Data analysis was performed by KM. The first draft of the manuscript was written by KM and critically revision of the manuscript was performed by all authors. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Keivan Moradi.

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Ethics approval and consent to participate

This study was approved by the Ethics Committee of Kermanshah University of Medical Sciences, Kermanshah, Iran (Ethics code: IR.KUMS.REC.1400.635, project number: 4000706).

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The authors report no conflicts of interest. The authors alone are responsible for the content and writing of this article.

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Khamooshian, S., Kazeminia, M. & Moradi, K. In silico analysis and the pathogenicity classification of PTS gene variants among Iranian population. Egypt J Med Hum Genet 23, 139 (2022). https://doi.org/10.1186/s43042-022-00351-4

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  • DOI: https://doi.org/10.1186/s43042-022-00351-4

Keywords

  • PTPS deficiency
  • Variant interpretation
  • PTS gene
  • ACMG-AMP guidelines
  • Iran