Literature DB >> 28356823

Molecular Analysis of Cystic Fibrosis Patients in Hungary - An Update to the Mutational Spectrum.

Gergely Ivády1, Katalin Koczok1, Laszlo Madar1, Eva Gombos1, Izabella Toth1, Klaudia Gyori1, István Balogh1.   

Abstract

BACKGROUND: In this study the authors present an update to the CFTR mutation profile in Hungary, utilizing data from a selected cohort of 45 cystic fibrosis (CF) patients from different regions of the country.
METHODS: Depending on the preceding analysis, four different mutation detection methods were used. A commercial assay targeting the most common CF-causing mutations was performed as the first test followed by an allele specific PCR for CFTRdele2,3(21kb), Sanger sequencing and MLPA analysis of the coding region of the CFTR gene.
RESULTS: In our recent study 27 different mutations were detected, including 2 novel ones (c.1037_1038insA and c.1394C>T). Besides F508del (c.1521_1523delCTT), the following mutations were found at a frequency of ≥ 4.0%: W1282X (c.3846G>A), N1303K (c.3909C>G), CFTRdele2,3(21kb) (c.54-5940_273+10250del21kb) and 2184insA (c.2052_2053insA). In addition, four mutations (G542X, Y1092X, 621+1G>T, and 2143delT) were found in more than one allele.
CONCLUSIONS: The updated database of Hungarian mutations not only enables to increase the efficiency of the existing diagnostic approach, but also provides a further refined basis for the introduction of the molecular newborn screening (NBS) program in Hungary.

Entities:  

Keywords:  cystic fibrosis; mutational spectrum; newborn screening

Year:  2014        PMID: 28356823      PMCID: PMC4922332          DOI: 10.2478/jomb-2014-0055

Source DB:  PubMed          Journal:  J Med Biochem        ISSN: 1452-8266            Impact factor:   3.402


Introduction

Cystic fibrosis (CF) is the most common severe inherited monogenic disease in Caucasians, with an incidence of 1: 2500. Besides the F508del mutation, which accounts for the majority of CF alleles, almost 2000 different rare mutations have been described in the CFTR gene. Although no more than 20 of them occur at a frequency higher than 0.1% worldwide (1), the geographical heterogeneity of CF causing alleles demands the use of population specific mutation detection panels in order to reach reasonably high mutation detection rates. Here, we present the mutational spectrum of CF patients in a Hungarian cohort which supplements the results of our previous study from Eastern Hungary (2).

Materials and Methods

Altogether 45 CF patients (22 males and 23 females, 10.1±8.1 years) were involved in this study. Sample collection and analysis were performed between 2010 and 2014. We selected patients with a clinical picture of classical CF, where both disease-causing mutations were identified. All patient samples were sent by Hungarian care centers (mainly from the regions of Budapest, Szeged and Debrecen). DNA was isolated from peripheral blood leukocytes with the QIAgen Blood Mini Kit (Qiagen, Hilden, Germany). The first line molecular test – if it had not been carried out by another laboratory before – was a commercially available multiplex allele specific PCR assay, which is able to detect 29 mutations and differentiates between hetero- or homozygous forms of F508del (Elucigene™ CF29 v.2 kit, Tepnel Diagnostics Ltd, Abingdon, UK). Any mutation found other than F508del was further examined by sequence analysis of the corresponding region in order to determine if one or both alleles were affected. The first tier assay was complemented by an allele specific PCR to detect the common »Slavic« deletion, CFTRdele2,3(21kb) (3). As a second tier mutation analysis Sanger sequencing of the entire coding region was employed as described before (2) to find small-scale mutations elusive of the commercial assay. According to our previous experience (2), we started sequencing of exons 4, 6, 11, 14, 15 and 20, containing prevalent Hungarian mutations such as 2184insA (c.2052_2053insA), L101X (c.302T>G) and Y1092X (c.3276C>A); if no alteration was detected, the remaining exons were also tested. As a third tier step, MLPA analysis was used to detect large-scale rearrangements (SALSA MLPA KIT P091-B1 CFTR, MRC-Holland, Amsterdam, the Netherlands). If the sending institution had already performed first-line testing, we carried out only the second and/or third level of molecular analysis. One gross rearrangement in the CFTR gene (CFTRdele2, c.54-5811_164+2186del273+6780_273+6961inv) which was detected by MLPA analysis was confirmed by allele specific PCR and bidirectional sequencing of the junction regions, as described in the literature (7–9). The numbering of CFTR exons was done according to the current recommendations (Ensembl ENSG00000001626). In the mutation nomenclature both the legacy names and cDNA based HGVS names were used as proposed (4).

Results

Table I shows the distribution of detected mutations in our recent study compared to Czech (5), Polish (6) and previous Hungarian (2) papers. Altogether 27 different mutations were found. F508del was detected in 53.3%, four mutations (W1282X, N1303K, CFTRdele2,3(21 kb), and 2184insA) were detected in 4.4% of alleles, while another four mutations (G542X, Y1092X, 621+ 1G>T, and 2143delT) were found in more than one allele.
Table I

Mutation distribution in our patient cohort compared to Czech (5), Polish (6) and previous Hungarian (2) publications.

HGVS nomenclatureLegacy name/effect on protein levelHungary 2011 (N=80)Czech Republic 2013 (N=1200)Poland 2014 (N=1476)This study (N=90)
c.1521_1523delCTTF508del70.0%67.4%54.5%53.3%
c.3846G>AW1282X0.0%0.6%0.6%4.4%
c.3909C>GN1303K5.0%2.4%1.2%4.4%
c.54-5940_273+10250del21kbCFTRdele2,3(21kb)5.0%5.8%4.5%4.4%
c.2052_2053insA2184insA5.0%0.4%1.0%4.4%
c.1624G>TG542X3.8%2.0%1.7%2.2%
c.489+1G>T621+1G>T0.0%0.4%0.3%2.2%
c.3276C>AY1092X1.3%0.0%0.1%2.2%
c.302T>GL101X2.5%0.0%0.1%1.1%
c.1397C>GS466X1.3%0.0%0.1%1.1%
c.2012delT2143delT0.0%0.9%1.8%2.2%
c.53+1G>T185+1G>T0.0%0.2%0.0%1.1%
c.1394C>Tp.Thr465Ile0.0%0.0%0.0%1.1%
c.1037_1038insAp.Leu346Hisfs*170.0%0.0%0.0%1.1%
c.2051_2052delAAinsG2183AA>G0.0%0.1%0.7%1.1%
c.2657+5G>A2789+5G>A0.0%0.5%0.0%1.1%
c.3717+12191C>T3849+10kbC>T0.0%1.7%3.9%1.1%
c.215C>AA72D0.0%0.0%0.0%1.1%
c.3454G>CD1152H0.0%0.0%0.1%1.1%
c.3731G>AG1244E0.0%0.0%0.0%1.1%
c.1727G>CG576A0.0%0.0%0.3%1.1%
c.3302T>AM1101K0.0%0.0%0.0%1.1%
c.2591_2592delTT2723delTT0.0%0.0%0.0%1.1%
c.3822G>AW1274X0.0%0.0%0.0%1.1%
c.2002C>TR668C0.0%0.0%0.2%1.1%
c.325_327delTATinsGp.Tyr109Glyfs*40.0%0.0%0.0%1.1%
c.54-5811_164+2186del273+6780_273+6961invCFTRdele20.0%0.2%0.0%1.1%
As shown in Table II, the commercially available assay was able to detect 75.9% of the mutations in our combined mutational database. The allele specific PCR for CFTRdele2,3(21kb) revealed 4.7% of disease-causing alleles. By the sequencing of exon 14 2184insA and two other rare mutations (c.2012delT and c.2002C>T) were found with a frequency of 4.7%, 1.2% and 0.6%, respectively. The remaining mutations were scattered throughout the entire coding region of the CFTR gene. MLPA analysis revealed one deletion affecting exon 2 in one patient in a heterozygous form. Allele specific PCR and sequencing analysis showed that the single exon deletion detected by MLPA was the same as previously described by others (10, 11).
Table II

Allele frequencies and mutation detection rates in the combined mutational database. Novel mutations are in bold.

Exon/intronHGVS nomenclatureLegacy name/effect on protein levelNo. of alleles (N=170)Frequency of allelesMutation in transProportion of detected mutations
e11c.1521_1523delCTTF508del10461.2%various CF mutationsElucigene CF29v.2 75.9%
e23c.3846G>AW1282X42.4%F508del, 2184insA, W1282
e24c.3909C>GN1303K84.7%various CF mutations
e12c.1624G>TG542X52.9%various CF mutations
i11c.1585-1G>A1717-1G>A10.6%F508del
e8c.1040G>CR347P10.6%G542X
e14c.2051_2052delAAinsG2183AA>G10.6%D1152H
i16c.2657+5G>A2789+5G>A10.6%621+1G>T
i4c.489+1G>T621+1G>T21.2%F508del, 2789+5G>A
e21c.3454G>CD1152H10.6%2183AA>G
i22c.3717+12191C>T3849+10kbC>T10.6%F508del
i1-i3c.54-5940_273+ 10250del21kbCFTRdele2,3(21kb)84.7%F508del, N1303K, Y109G“Slavic PCR” 4.7%
e14c.2052_2053insA2184insA84.7%F508del, G542X, W1282Sequencing of e14 6.5%
e14c.2012delT2143delT21.2%F508del
e14c.2002C>TR668C10.6%G576A
e20c.3276C>AY1092X31.8%F508delSequencing of the entire coding region 11.8%
e4c.302T>GL101X31.8%F508del, 2723delTT
e11c.1397C>GS466X21.2%F508del
i1c.53+1G>T185+1G>T10.6%N1303K
e11c.1394C>Tp.Thr465Ile10.6%F508del
e8c.1037_1038insAp.Leu346Hisfs*1710.6%F508del
e3c.215C>AA72D10.6%N1303K
e15c.2491G>TE831X10.6%N1303K
e6c.658C>TQ220X10.6%F508del
e23c.3731G>AG1244E10.6%F508del
e13c.1727G>CG576A10.6%R668C
e20c.3302T>AM1101K10.6%F508del
e15c.2591_2592delTT2723delTT10.6%L101X
e23c.3822G>AW1274X10.6%F508del
e4c.325_327delTATinsGp.Tyr109Glyfs*410.6%CFTRdele2,3(21kb)
i1-i2c.54-5811_164+2186del273 +6780_273+6961invCFTRdele210.6%F508delMLPA 0.6%

Discussion

We updated our existing CF database by merging recently acquired nationwide results with our previous data from Eastern Hungary (2). Allele frequencies and proportion of detected mutations at different levels are listed in Table II. Data of our combined database are discussed below. Altogether, 31 different mutations were identified in our previous and recent studies, two of which were novel (according to the Clinical and Functional Translation of CFTR database, cftr2.org and the Human Gene Mutation Database (HGMD)). These newly described sequence alterations are most likely pathogenic. One of them changes the reading frame, generating a premature stop codon 17 amino acids downstream (c.1037_1038insA, p.Leu346Hisfs*17). Pathogenicity of the detected novel missense mutation c.1394C>T, p.Thr465Ile is supported by the following: 1) the affected residue is located at a phylogenetically highly conserved position according to the orthologs of Bos taurus, Equus caballus, Felis catus, Mus musculus etc.; 2) another pathogenic mutation (T465N) affecting the same amino acid residue has already been described (12); 3) SIFT analysis predicts a damaging effect on the protein function. Eleven mutations reached a frequency higher than 1%. In accordance with the literature (5, 6), the decreasing »North-to-South« gradient (13) stands for the distribution of F508del (104/170 CF alleles) compared to the Czech Republic, but not to Poland. F508del was followed by the Mediterranean mutation N1303K, the »Slavic« mutation CFTRdele2,3(21kb) and the »Galican« mutation 2184insA, each responsible for 4.7% of all CF alleles, which meets our previous observations. G542X was detected in 2.9%, the Israeli mutation W1282X in 2.4%. Other relatively frequent mutations were Y1092X, L101X found in 1.8% and 621+1G>T, S466X, 2143delT found in 1.2% of the patients. One gross rearrangement (0.6%) in the CFTR gene (CFTRdele2, c.54-5811_164+2186del273+6780_273+6961inv) was detected by MLPA analysis and confirmed by allele specific PCR and bidirectional sequencing of the junction regions, as described in the literature (7). The mutation is characterized by a deletion of 8108bp (part of intron 1, the whole exon 2 and part of intron 2) with an inverted insertion of 182 bp from intron 3 (11). As demonstrated in Figure 1, geographical tendencies can be recognized in the distribution of both CFTRdele2,3(21kb) and 2184insA mutations. All but one CFTRdele2,3(21kb) and 2184insA positive samples originate from the northern regions of the country and 2184insA even seems to be restricted to the northeastern territories of Hungary, which is not suprising if we consider the high frequency of this mutation in Western Ukraine (14).
Figure 1

Geographical distribution of CFTRdele2,3(21kb) and 2184insA mutations in Hungary.

Legend: o – CFTRdele2,3(21kb), x – 2184insA, ● – other mutations.

According to the mapped mutation frequencies in patients originating from different regions of Hungary using the commercially available assay 75.9% of the mutations can be identified. The allele specific PCR for the detection of the common »Slavic« deletion, CFTRdele2,3(21kb) adds 4.7%, while the sequencing of exon 14 adds 6.5% to the proportion of detected mutations. MLPA analysis revealed one rearrangement (0.6%), while direct sequencing of the entire coding region of CFTR gene identified 20 CF alleles (11.8%). However, it should be noted that the detection of CFTRdele2,3(21kb) would have been possible by MLPA as well. In conclusion, beside determining mutation distribution in Hungarian CF patients, our study provides a good starting point to the genetic testing following newborn screening. The commercial allele specific mutation detection method detects 75.9% of CFTR mutations. Complementing it with the detection of other two frequent population-specific alterations (i.e. CFTRdele2,3(21kb) and 2184insA) ~85% of mutations can be detected to achieve the required sensitivity (85–90%) in newborn screening (15 and Milan Macek, personal communication). With the growing popularity of the clinical use of next generation sequencing (NGS) methods, one possible solution of the combined (i.e. all tiers) DNA analysis step of NBS programs would be the use of those tests. However, based on our results, it also has to be emphasized that using NGS methods with a high error rate in homopolymer regions (e.g. pyrosequencing or ion semiconductor sequencing) in genetic testing will fail to detect ~5% of CF alleles (2184insA mutation). The frequent »Slavic« mutation (~5%) would be missed as well unless applying a very high coverage not usual in germline mutation detection or using commercially available kits including this mutation, but both of these solutions raise unnecessary financial burdens.
  12 in total

1.  A high frequency of the Cystic Fibrosis 2184insA mutation in Western Ukraine: genotype-phenotype correlations, relevance for newborn screening and genetic testing.

Authors:  Halyna Makukh; Petra Krenková; Marta Tyrkus; Lyudmyla Bober; Miroslava Hancárová; Oleh Hnateyko; Milan Macek
Journal:  J Cyst Fibros       Date:  2010-07-24       Impact factor: 5.482

2.  A new insertion/deletion of the cystic fibrosis transmembrane conductance regulator gene accounts for 3.4% of cystic fibrosis mutations in Sardinia: implications for population screening.

Authors:  Valeria Faà; Pietro Pellegrini Bettoli; Maria Demurtas; Maurizio Zanda; Vincenzina Ferri; Antonio Cao; Maria Cristina Rosatelli
Journal:  J Mol Diagn       Date:  2006-09       Impact factor: 5.568

3.  Gross genomic rearrangements involving deletions in the CFTR gene: characterization of six new events from a large cohort of hitherto unidentified cystic fibrosis chromosomes and meta-analysis of the underlying mechanisms.

Authors:  Claude Férec; Teresa Casals; Nadia Chuzhanova; Milan Macek; Thierry Bienvenu; Andrea Holubova; Caitriona King; Trudi McDevitt; Carlo Castellani; Philip M Farrell; Molly Sheridan; Sarah-Jane Pantaleo; Ourida Loumi; Taieb Messaoud; Harry Cuppens; Francesca Torricelli; Garry R Cutting; Robert Williamson; Maria Jesus Alonso Ramos; Pier Franco Pignatti; Odile Raguénès; David N Cooper; Marie-Pierre Audrézet; Jian-Min Chen
Journal:  Eur J Hum Genet       Date:  2006-05       Impact factor: 4.246

4.  Best practice guidelines for molecular genetic diagnosis of cystic fibrosis and CFTR-related disorders--updated European recommendations.

Authors:  Els Dequeker; Manfred Stuhrmann; Michael A Morris; Teresa Casals; Carlo Castellani; Mireille Claustres; Harry Cuppens; Marie des Georges; Claude Ferec; Milan Macek; Pier-Franco Pignatti; Hans Scheffer; Marianne Schwartz; Michal Witt; Martin Schwarz; Emmanuelle Girodon
Journal:  Eur J Hum Genet       Date:  2008-08-06       Impact factor: 4.246

5.  Geographic distribution and regional origin of 272 cystic fibrosis mutations in European populations. The Biomed CF Mutation Analysis Consortium.

Authors:  X Estivill; C Bancells; C Ramos
Journal:  Hum Mutat       Date:  1997       Impact factor: 4.878

6.  Distribution of CFTR mutations in the Czech population: positive impact of integrated clinical and laboratory expertise, detection of novel/de novo alleles and relevance for related/derived populations.

Authors:  Petra Křenková; Tereza Piskáčková; Andrea Holubová; Miroslava Balaščaková; Veronika Krulišová; Jana Čamajová; Marek Turnovec; Malgorzata Libik; Patricia Norambuena; Alexandra Štambergová; Lenka Dvořáková; Veronika Skalická; Jana Bartošová; Tereza Kučerová; Libor Fila; Dana Zemková; Věra Vávrová; Monika Koudová; Milan Macek; Alice Krebsová; Milan Macek
Journal:  J Cyst Fibros       Date:  2012-12-29       Impact factor: 5.482

7.  Epidemiology and a novel procedure for large scale analysis of CFTR rearrangements in classic and atypical CF patients: a multicentric Italian study.

Authors:  R Tomaiuolo; F Sangiuolo; C Bombieri; A Bonizzato; G Cardillo; V Raia; M R D'Apice; M D Bettin; P F Pignatti; G Castaldo; G Novelli
Journal:  J Cyst Fibros       Date:  2008-02-14       Impact factor: 5.482

8.  European best practice guidelines for cystic fibrosis neonatal screening.

Authors:  Carlo Castellani; Kevin W Southern; Keith Brownlee; Jeannette Dankert Roelse; Alistair Duff; Michael Farrell; Anil Mehta; Anne Munck; Rodney Pollitt; Isabelle Sermet-Gaudelus; Bridget Wilcken; Manfred Ballmann; Carlo Corbetta; Isabelle de Monestrol; Philip Farrell; Maria Feilcke; Claude Férec; Silvia Gartner; Kevin Gaskin; Jutta Hammermann; Nataliya Kashirskaya; Gerard Loeber; Milan Macek; Gita Mehta; Andreas Reiman; Paolo Rizzotti; Alec Sammon; Dorota Sands; Alan Smyth; Olaf Sommerburg; Toni Torresani; Georges Travert; Annette Vernooij; Stuart Elborn
Journal:  J Cyst Fibros       Date:  2009-02-26       Impact factor: 5.482

9.  Comprehensive genetic analysis of the cystic fibrosis transmembrane conductance regulator from dried blood specimens--implications for newborn screening.

Authors:  Anja Kammesheidt; Martin Kharrazi; Steve Graham; Suzanne Young; Michelle Pearl; Charles Dunlop; Steven Keiles
Journal:  Genet Med       Date:  2006-09       Impact factor: 8.822

10.  CFTR mutations spectrum and the efficiency of molecular diagnostics in Polish cystic fibrosis patients.

Authors:  Ewa Ziętkiewicz; Ewa Rutkiewicz; Andrzej Pogorzelski; Barbara Klimek; Katarzyna Voelkel; Michał Witt
Journal:  PLoS One       Date:  2014-02-26       Impact factor: 3.240

View more
  5 in total

1.  Pediatric Laboratory Medicine: Some Aspects of Obesity, Metabolic Syndrome, Neonatal Screening, Reference and Critical Values.

Authors:  Nada Majkić-Singh
Journal:  J Med Biochem       Date:  2014-10-08       Impact factor: 3.402

2.  Analytical parameters and validation of homopolymer detection in a pyrosequencing-based next generation sequencing system.

Authors:  Gergely Ivády; László Madar; Erika Dzsudzsák; Katalin Koczok; János Kappelmayer; Veronika Krulisova; Milan Macek; Attila Horváth; István Balogh
Journal:  BMC Genomics       Date:  2018-02-21       Impact factor: 3.969

3.  Cystic fibrosis presentation in del. F508 and p. Tyr109Glyfs compound heterozygote CFTR state: a case report.

Authors:  Mirjana Turkalj; Vid Matišić; Arijana Šimić; Alen Juginović; Damir Erceg; Dorian Tješić Drinković; Wolfgang Höppner; Dragan Primorac
Journal:  Croat Med J       Date:  2019-06-13       Impact factor: 1.351

4.  Phenotypic spectrum and genetic heterogeneity of cystic fibrosis in Sri Lanka.

Authors:  Neluwa Liyanage Ruwan Indika; Dinesha Maduri Vidanapathirana; Hewa Warawitage Dilanthi; Grace Angeline Malarnangai Kularatnam; Nambage Dona Priyani Dhammika Chandrasiri; Eresha Jasinge
Journal:  BMC Med Genet       Date:  2019-05-24       Impact factor: 2.103

5.  Identification of 99% of CFTR gene mutations in Bulgarian-, Bulgarian Turk-, and Roma cystic fibrosis patients.

Authors:  Guergana Petrova; Nadezhda Yaneva; Jana Hrbková; Malgorzata Libik; Alexey Savov; Milan Macek
Journal:  Mol Genet Genomic Med       Date:  2019-06-27       Impact factor: 2.183

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.