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University of Groningen
Application of molecular techniques in population genetic studies of cystic fibrosis in theNetherlandsde Vries, Hendrik Gerardus
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Application of molecular techniques in population
genetic studies of cystic fibrosis in The Netherlands
Stichting Drukkerij Regenboog, Groningen
This study was supported by a grant from The Netherlands Organization for Scientific
Research (NWO). Financial support to publish this thesis was provided by the NWO and
by the "Stichting voor erfelijkheidsvoorlichting te Groningen".
RIJKSUNIVERSITEIT GRONINGEN
Application of molecular techniques in population
genetic studies of cystic fibrosis in The Netherlands
Proefschrift
ter verkrijging van het doctoraat in de
Geneeskunde
aan de Rijksuniversiteit Groningen
op gezag van de
Rector Magnificus Dr. F. van der Woude
in het openbaar te verdedigen op
woensdag 31 januari 1996
des namiddags te 2.45 uur precies
door
Hendrik Gerardus de Vries
geboren op 14 april 1965
te Roosendaal
Promotores: Prof.dr. L.P. ten Kate
Prof.dr. C.H.C.M. Buys
Referent: Dr. H. Scheffer
’Kom verder,’ zei hij (professor Sickbock) vriendelijk. ’U treft het. Ik ben net bezig
aan een onderzoek van de mutaties in de genen.’
’Van de wat?’ vroeg heer Ollie, bedremmeld om zich heen kijkend.
’Laat maar,’ hernam de professor. ’Ik heb ontdekt, dat alles wat de natuur ons
voorschotelt beuzelachtig is. Er bestaat niets, dat door een scherp geleerde niet kan
worden verbeterd. Volgt u me?’
(Marten Toonder; Een heer moet alles alleen doen; De toornviolen. De Bezige Bij,
Amsterdam, 1969)
Promotiekommissie: Prof.dr. J.J. Cassiman
Prof.dr. A. Hofman
Prof.dr. H.S.A. Heymans
Contents
Outline of this thesis
Chapter 1. General introduction
1.1 Delineation of and research into cystic fibrosis 11
1.2 The CFTR gene and its mutations 12
1.3 Possibilities for genetic modification
A. Mouse models 15
B. Somatic gene therapy for cystic fibrosis 17
1.4 Cystic fibrosis prevalence at birth 18
1.5 What causes the high frequency of cystic fibrosis ? 19
1.6 Screening for cystic fibrosis carriers 20
1.7 Identity By Descent (IBD) analysis 21
References 23
Chapter 2 Validation of determination of∆F508 mutations of the cystic 33
fibrosis gene in over 11,000 mouthwashes.
Chapter 3 Prevalence of∆F508 cystic fibrosis carriers in The Netherlands: 41
region of residence, age, and number of offspring as explanatory
variables.
Chapter 4 Relative frequencies of CFTR mutations in The Netherlands: 57
Regional variation is present even in a small country.
Chapter 5 Number and sex of offspring of∆F508 carriers outside cystic 67
fibrosis families
Chapter 6 Haplotype identity between individuals who share a CFTR 71
mutation allele Identical By Descent: demonstration of the
usefulness of the haplotype sharing concept for gene mapping
in real populations
Summary 85
Samenvatting 89
Curriculum vitae 94
Dankwoord 95
Outline of this thesis
Cystic fibrosis (CF) is a common autosomal recessive disease with an estimated
birth prevalence of about one in 2500 in Caucasian populations. Since the cloning
and characterizing of the CF gene in 1989, numerous reports have been published
on the detection of new mutations. Till now more then 500 mutations have been
described and this number is still increasing. The most common CF mutation is the
∆F508 mutation with an estimated relative frequency of 70% in Europe. The
median life expectancy of CF patients has strongly increased to 28-40 years. Since
1991 the genetic modification is intensively investigated in mouse-models and in
somatic gene therapy studies.
The birth prevalences of CF in European populations and populations of
European descent elsewhere show a range from 1 in 1700 to 1 in 7700 (excluding
Finland where CF is extremely rare). Heterozygote advantage is the most likely
explanation for the maintenance of the high CF gene frequency at current levels.
The feasibility and appropriateness of offering carrier testing to the general
population was and still is the topic for extensive discussions. This resulted in a
number of arguments against and in favour of population screening. The American
Society of Human Genetics and the National Institutes of Health stated that carrier
screening would be desirable only if 90-95% of the mutations can be detected.
The distribution of numerous less common CF mutations is limited to certain
countries or even population groups within countries. It has been well described that
some specific mutations have achieved a high frequency in certain founder
populations. An example is the A455E mutation in a French Canadian population. It
is very likely that patients with this mutation have a common not to far predecessor.
The study of the DNA of patients with this mutation has been used to demonstrate
the general feasibility of an Identity By Descent (IBD) approach.
The application of molecular techniques strongly enhances the identification of
CF patients. Direct mutation detection can also be used for epidemiologic studies
and population-based carrier screening. One of the purposes of this study was to
analyse the usefulness of a mouthwash procedure for the detection of a large
numbers of CF carriers. Chapter 2 describes the determination of the failure rate,
specificity and sensitivity of the mouthwash procedure. The samples collected for
9
Chapter 1
General introduction
1.1 Delineation of and research into cystic fibrosis
Cystic fibrosis (CF) is the most common lethal autosomal recessive disorder
affecting Caucasian populations, with a generally quoted birth prevalence of one in
2500 [1].
Table 1. Historical perspectives of cystic fibrosis research.
1936 Report of a child with the clinical features of cystic fibrosis. [2]
1938 First detailed description of the clinical features and pathology of CF: "Cystic fibrosis" [3]of the pancreas.
1945 Recognition of the role of sticky mucus as a cause of many of the symptoms: "Mucoviscidosis". [4]
1946 Suggestion of an autosomal recessive inheritance pattern for CF. [5]
1953 Investigation of acute salt loss caused by excessive sweating in babies with CF, during a [6]heat-wave.
1959 Development of the pilocarpine iontophoresis method for sweat testing. [7]
1981 Description of altered electrical properties of CF respiratory epithelium associated with [8]abnormalities of both sodium and chloride transport.
1983 Documentation of chloride impermeability of CF sweat gland ducts. [9]
1985 Mapping of the CF gene to a small segment of the long arm of chromosome 7q, using [10]restriction fragment length polymorphisms (RFLP).
1987 Linkage disequilibrium between the markers XV2C/KM19 and cystic fibrosis was observed. [11]
1989 Cloning of the CF gene and description of a cDNA sequence. [12]
1989 Identification of the∆F508 mutation in approximately 70 percent of the mutations. [13]
1991 Report of the total genomic sequence of the CFTR gene. [14]
1994 Description of more then 500 different CF mutations. [15]
11
The disease is characterized by abnormal secretions of the exocrine glands which
cause chronic obstruction and infection of the respiratory tract, meconium ileus,
pancreatic insufficiency, and elevated levels of sweat electrolytes. Rochholz
(Almanac of Children’s Songs and Games from Switzerland, 1857) described " The
child will soon die whose brows tastes salty when kissed". Table 1 shows important
data on the delineation of and research into CF during the past 60 years.
1.2 The CFTR gene and its mutations
The gene responsible for cystic fibrosis (CF) has been identified in 1989 [12,13,16].
It is located on the long arm of chromosome 7, region 7q31.2 [17]. The gene is
approximately 230,000 kb in size and contains 27 exons [14]. The encoded mRNA
is about 6.5 Kb long. The gene codes for the 1480 amino acid cystic fibrosis
transmembrane conductance regulator (CFTR) protein, with a molecular mass of
168,138 dalton. CFTR is a cAMP-induced chloride channel [18-30], which is
located in epithelial tissues, including pancreatic ductal cells, salivary glands,
intestine, lung, testis and endometrium [31-34]. Defective regulation of the chloride
channel, caused by different mutations in the CF gene, results in desiccation of
secretions, increase in the viscosity of mucus and a decrease in mucociliary clear-
ance. The primary sequence of CFTR suggests that it is a transmembrane protein
which consists of five domains (Figure 1): two membrane-spanning domains, each
composed of six putative transmembrane segments; two nucleotide-binding
domains; and a unique regulatory (R) domain [35,36]. The membrane-spanning
domains contribute to the formation of the Cl- channel pore. The nucleotide-binding
domains and the regulatory domain control the channel activity through an
interaction with cytosolic nucleotides. Phosphorylation of the regulator domain by
cAMP-dependent kinase is required for the channel to open [37-39]. In addition to
this function, the complex expression pattern of the gene and the varied degree of
the clinical manifestations in different organs and tissues suggest that CFTR may
have other activities [40-45].
Thus far more then 500 presumed mutations have been identified in the CFTR
gene in the past 5 years [15]. These mutations can be divided in missense- (42%),
frameshift- (23%), nonsense- (16%), splice defect- (16%) and deletion mutations
12
(4%). The distribution of mutations over the gene is nonrandom, with the highest
density in NBF1 (14.4%) and to a lesser extent in NBF2 (10.8%) (Figure 1). Most
of the CF mutations have been identified among patients of Caucasian ancestry. The
population variation of CF mutations in Europe has been well documented by the
Cystic Fibrosis Consortium [46].
Figure 2 shows four different mechanisms by which CF mutations disrupt the
CFTR function [36].Class 1 mutations: Mutations (G542X, 621+G->T, etc) that
cause defective protein production by premature termination signals as a
consequence of affected splice sites, frameshifts or nonsense mutations [35,47,48].
These mutations result in a shortage of CFTR Cl- channels in affected epithelia
since little or no full-length protein is produced.Class 2 mutations:Several mutant
forms of CFTR fail to be transported correctly, which results in defective protein
processing. Experiments with other proteins suggest that class 2 mutations (∆F508,
S559T, N1303K, etc) cause an incorrect folding of CFTR. Cellular mechanisms
recognise mutant CFTR as abnormal and mark the protein for degradation
Figure 1. CFTR contains 27 exons and consists of five domains: two membrane-spanning domains (MSD),two nucleotide-binding domains (NBF1 and 2), and a regulatory (R) domain. (Adapted from Tsui andBuchwald)
13
which only one has been identified. The state of pancreatic function allows
discrimination of different phenotypes. Class 1 and 2 mutations are associated with
a severe pancreatic-insufficient phenotype, while class 3 and 4 mutations show a
normal pancreas function.
Approximately 70% of the CF chromosomes harbour a three basepair deletion
in CFTR, which removes the phenylalanine residue at amino acid 508 of the
predicted CFTR polypeptide (∆F508) [46]. The estimates of the age of the∆F508
mutation vary from 3,000 to 52,000 years [52-55]. According to the latter study, in
which microsatellites were used in different CF populations in Europe, the∆F508
mutation arose at least 52,000 years ago in a population genetically distinct from
the present European population. The mutation was introduced in Europe in
different periods. The first spread was during the Palaeolithic period. The Basque
population is believed to be a Palaeolithic population [56], and has a high relative
frequency of∆F508 (88%) [53]. Later introduction of∆F508 in Central and Nor-
thern Europe (Neolithic period) increased the frequency of this mutation in these
regions. The relative∆F508 frequencies are shown in Figure 3 [46]. The highest
frequency per country can be found in Denmark (0.88), while the frequency
decreases in Southern and Eastern directions.
1.3 Possibilities for genetic modification
A. Mouse models
The mouse homolog of the human CFTR gene was cloned in 1991 [57]. The mouse
protein is 78% identical to the human CFTR, with a high conservation in the
transmembrane and nucleotide-binding domains. A mouse model for cystic fibrosis
made by gene targeting was first described in 1992 [58]. The murine CFTR gene in
embryonic stem cells was inactivated by targeted insertion of a neomycin gene. This
resulted in a frame stop codon in exon 10. Numerous mutant mice have been
produced using this strategy [59-63]. Almost all mutant CF/CF mice displayed
many features common to young CF patients, including failure to thrive, meconium
ileus, alteration of mucous and serous glands. This resulted in death due to
intestinal obstruction before 40 days of age.
15
B. Somatic gene therapy for cystic fibrosis
The clinical expressions of CF are very broad, although the manifestations in the
airways account for more then 95% of the morbidity in CF patients [1]. It is
therefore that gene transfer strategies are focused on delivery to the airways. A
variety of gene transfer techniques have been used effectively in vitro and in
animals: adenoviral vectors, liposome-mediated gene transfer, DNA-ligand
complexes and adeno-associated viral (AAV) vectors [64]. The first two therapies
are being used in phase I clinical trials involving CF patients.
Several studies indicate that even a low expression (10%) of the CF gene in airway
epithelium may provide clinical benefit [65,66]. Healthy CF carriers will have half-
normal levels of expression. There are some compound heterozygotes which show
mild or normal phenotypes, while they have very low levels of expression [47,67].
This means that there is no necessity to correct all cells and even low levels of
expression per cell may be beneficial.
The major goals for somatic gene therapy for cystic fibrosis are (1) to show
that the expression of the CF gene in airways epithelium will alleviate lung disease
in CF patients and (2) to achieve a lasting expression of the transferred gene.
Table 3. Major advantages and disadvantages of gene transfer systems.
Advantages Disadvantages
Adenoviral 1. Highly efficient gene transfer 1. Transient nature of the expressionvectors 2. Transfection of many cell types 2. Pathogenicity of the wild type virus
3. No evidence for save and effectivereadministration.
DNA-liposome 1. Standardized production of 1. No persistent expressioncomplexes large amounts of vector 2. Low gene expression
2. No risks of viruses3. Readministrations with minimal
host response
DNA ligand 1. See DNA-liposome complexes 1. See DNA-liposome complexescomplexes 2. Large size of complexes may complicate
escape from the vascular space3. Peptides can induce immune responses
AAV vectors 1. Stable virus preparations 1. Possibility for immune responses2. Lack of pathogenicity 2. No adequate system to produce virus3. High-efficiency integration at present 3. Limitation of insert size to 4.8 kb
17
This can be performed through a single delivery with persistent expression or by
use of a save and effective repetitive delivery system. The biological aspects of
various gene transfer systems have been reviewed elsewhere [68,69]. The
advantages and disadvantages of these strategies are summarized in table 3.
1.4 Cystic fibrosis prevalence at birth
Cystic fibrosis is the most common autosomal recessive disease in caucasian
populations. Birth prevalences have been determined by surveys and range from 1
in 1700 to 1 in 40,000 in various European countries (Table 2). Thus far, estimates
based on molecular screening for heterozygotes have not been described in
European populations.
The estimates of the birth prevalences show a variability which as a whole or
in part may be due to under- or overdiagnosis and under- or overreporting.
Alternatively this variability may be due to mechanisms such as foundereffect and
genetic drift.
Table 2. Birth prevalences of cystic fibrosis determined in European populations
Czechoslovakia 1 in 2600 1962 [ 70]1 in 2800 1964 [ 71]1 in 2700 1967 [ 72]1 in 3400 1970 [ 73]1 in 3300 1970 [ 74]1 in 5440 1972 [ 75]
Denmark 1 in 4500 1972 [ 76]1 in 4760 1988 [ 77]
England 1 in 3000 1967 [ 78]1 in 4100 1967 [ 79]1 in 2000 1968 [ 80]1 in 3000 1972 [ 81]1 in 2500 1988 [ 82]
Finland 1 in 40000 1972 [ 83]France 1 in 3300 1961 [ 84]
1 in 1700-2000 1971 [ 85]1 in 2000 1973 [ 86]1 in 1800 1974 [ 87]1 in 3200 1978 [ 88]
Germany 1 in 3300 1963 [ 89]1 in 3000 1968 [ 90]1 in 2000 1975 [ 91]
18
Table 2. (Continued)
Ireland 1 in 1800 1976 [ 92]Italy 1 in 1100-3500 1973 [ 93]
1 in 2700 1976 [ 94]1 in 2000 1985 [ 95]
Netherlands 1 in 3600 1975 [ 96]N-Ireland 1 in 1700 1959 [Cited by Clarke, 97]
1 in 1900 1979 [ 98]Poland 1 in 900-2500 1970 [ 99]Sweden 1 in 7700 1962 [100]
1 in 4000 1970 [101]1 in 3500 1976 [102]1 in 2200-4500 1982 [103]
Switzerland 1 in 2900 1976 [104]Turkey 1 in 3000 1973 [105]
1.5 What causes the high frequency of cystic fibrosis ?
The high birth prevalence of cystic fibrosis of about one in 2500 in the Caucasian
population [1] has been discussed in many papers. A variety of mechanisms has
been suggested to account for this high frequency: genetic drift [106], high mutation
rate [107], meiotic drive and increased fertility of CF carriers [108], genetic
heterogeneity [109], heterozygote advantage [109-113] and segregation distortion of
CF alleles [108,114,115] . Heterozygote advantage is the most likely explanation. A
positive selection of approximately 2% [113] would be sufficient to maintain the CF
gene frequency at current levels.
The best understood example of heterozygote advantage remains sickle cell
haemoglobin, and the protection it confers against malaria. In case of CF,
abnormally functioning chloride channels could lead to increased protection against
bacterial toxin-mediated diarrhoea. Some of the diseases which have been suggested
as the balancing agent for CF are: influenza [116,117], syphilis [118], malaria
[119], bubonic plaque [112] and cholera [119-122]. Gabriel et al. [123] showed
reduced diarrhoea in the cystic fibrosis heterozygote mouse compared with the
normal mouse after exposure to cholera toxin. This effect, however, has not been
studied in human populations sofar.
19
1.6 Screening for cystic fibrosis carriers
The investigation of the validation of a mouthwash procedure and of the
determination of the carrier prevalence in the Netherlands (Chapters 2 and 3) can
partially be considered as preparatory studies for possible population-based
screening programmes. Immediately upon the cloning of the CF gene in 1989,
intensive discussions began regarding the feasibility and appropriateness of offering
carrier testing to the general population. Wilfond and Fost [124] have reviewed
many of the concerns in detail. The following arguments against population
screening have been raised. (1) It is too expensive and not cost-effective. (2) It is
not possible to identify all at-risk couples. (3) Families do not wish to avoid the
disease. (4) Prevention through abortion is morally objectionable. (5) A cure for the
disease is possible. (6) The personnel needed for genetic counselling are not
available. (7) Many couples are left at slightly increased risk. (8) There is a risk of
discrimination regarding insurance or employment. The following arguments in
favour of carrier testing have been raised. (1) Testing will become less expensive
and be cost-effective. (2) The majority of couples at-risk can be identified. (3)
Many couples wish to avoid the disease through various reproductive options. (4)
There is an obligation to inform the public about the availability of carrier testing.
Pilot studies for CF testing can address some of this issues.
Investigations in different groups of people revealed a positive attitude
toward carrier screening [125-128]. The American Society of Human Genetics and
the National Institutes of Health stated that carrier screening would be desirable
only if 90-95% of mutations can be detected. Present data suggest that the
sensitivity can be well above 90% in some Northern European populations, for
instance 98% in Belgium [129], 98% in a Celtic population in Brittany [130] and
99% in Wales [131]. The∆F508 mutation can be detected by simple gel
electrophoresis in material like blood samples, dried blood spots, mouthwashes,
mouthbrushes or fetal cells. The application and validation of the mouthwash
procedure for the DNA isolation out of buccal cells is described in Chapter 2. Most
laboratories now test routinely for from 10 to over 30 common CF mutations using
forward or reverse ASO methods [132] and the Amplification Refractory Mutation
System [133]. Solid-phase methods based on ligation detection, single base
sequencing and other tests offer great promise for the development of highly
20
automated procedures for the economical analysis of dozens of mutations
simultaneously [134]. An economic two-step laboratory approach can be used for
mutation detection [135]. In the first step only a few mutations will be determined
and only the partners of identified carriers will be tested for additional mutations.
The development of economic highly automated procedures for mutation analysis
and the positive attitude toward carrier testing will strongly increase the demand for
population based screening.
1.7 Identity By Descend (IBD) analysis
Haplotype sharing analysis is based on linkage disequilibrium of polymorphic loci
with a disease gene. In previous investigations extensive linkage studies have been
applied for the mapping of rare disease alleles. Although these studies provided
valuable contributions toward the mapping of mutated genes, a few disadvantages
can be observed using the traditional gene localization methods. (1) It is difficult to
obtain adequate family material and large pedigrees. (2) After the selection of
families all members should be examined concerning clinical features. (3) Hundreds
of markers should be involved in a complete genome search. (4) Costs of material
and manpower are high.
Identity by descent (IBD) analysis is an alternative association study method,
in which unrelated patients in a founder population can be selected for gene
mapping. Patients with identical genetic diseases are likely to share the disease gene
and an area around that gene from a common ancestor. The size of the expected
shared area depends on the number of meioses connecting the different persons,
because in time the size of the region will be reduced by crossovers. The larger the
shared area the closer the connection with a common predecessor from whom the
gene originates [136]. The size of the shared regions allows IBD to be used in the
genetic mapping of genes. Gruis et al. [137] described haplotype sharing in
presumedly unrelated patients from a founder population. This sharing was
determined by identity by descent of an area surrounding the disease gene. Houwen
et al. [138] showed that mapping within 2 cM was possible using only three
affected persons.
There are some points of importance which must be taken into consideration
21
when using IBD mapping. (1) The patients samples have to be collected in an
established founder population. (2) For the assignment of haplotypes it is necessary
to analyze also DNA of the parents. In case the phase is unknown it is possible to
assign haplotypes according to their frequency. This, however, will reduce the
power of the test drastically. (3) The allele frequency of the various markers used
with IBD mapping has to be established in a control group within the same founder
population.
A two step IBD approach can be used for gene mapping. In the first step a
few not too far related patients with an identical genetic disorder can be haplotyped
for a rough mapping of the disease gene. Markers can be selected with intervals of
about 20 cM. This means that 100-200 markers will cover the whole genome. Fine
mapping can be performed on the shared regions in a group of seemingly unrelated
patients within a restricted area. These regions will be haplotyped then with highly
polymorphic markers with relative distances of about 2 cM. This method allows fast
and relative cheap gene mapping. A pooling strategy has been described [139] in
which DNA from affected individuals were pooled and used as a PCR template for
microsatellite primers. The amplification product of pooled DNA samples reflects
all alleles represented in the pooled population. The relative frequency of the alleles
correlates with the intensity of each allelic band in the gel after electrophoresis. In
case of linkage disequilibrium of the microsatellite with a disease genotype there
will be a shift in allele frequencies towards a homozygous allele pattern in the
affected DNA pool. The use of the pooling strategy facilitates the identification of
the disease loci by reducing the number of amplification products and gel lanes.
Differences between control and affected pools can easily be examined, without the
need of assigning individual genotypes.
IBD analysis can also be used for determination of the origins of certain
mutations or the relationships of patients with identical genetic diseases. In case of
cystic fibrosis, mutations have been reported which occur predominantly in certain
countries [46]. The mutations may have originated in these countries not very long
ago. An example is the A455E CF mutation, which is mainly detected in Southern-
Holland and in Canada among certain French Canadians. It is likely that patients
with this mutation have a common not too far predecessor. Chapter 6 describes the
IBD analysis in Dutch and French Canadian patients.
22
24
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Chapter 2
Validation of determination of ∆F508 mutations of the cystic
fibrosis gene in over 11,000 mouthwashes.
Hendrik G. de Vries1, J. Margriet Collée2, Marjan H.R. van Veldhuizen2, Leny
Achterhof 3, Cees Th. Smit Sibinga3, Hans Scheffer1, Charles H.C.M. Buys1, Leo
P. ten Kate2.
1 Department of Medical Genetics, University of Groningen, The Netherlands2 Department of Human Genetics, Free University of Amsterdam, The Netherlands3 Blood bank Groningen-Drenthe, Groningen, The Netherlands
Hum. Genet (in press).
Abstract
Mouthwashes can be used as DNA resource for mutation detection. Because
collection and DNA isolation is simple and cheap, it could especially be used for
large numbers of samples. To determine the failure rate (the proportion of
mouthsamples in which no PCR product was obtained) and the specificity of buccal
epithelial cell mutation detection in large numbers of samples, we collected mouth-
washes and blood samples from 11,413 blood donors and tested the mouthwashes
for the ∆F508 mutation, which has an estimated frequency of 75% among cystic
fibrosis chromosomes in The Netherlands. Blood samples were tested for the∆F508
mutations only if the mutation was identified in the mouthwash or in case of a
failure to obtain PCR products. The sensitivity of the test was determined in
mouthwashes of 75∆F508 carriers known from earlier family studies. These
samples were offered blindly between the mouthwashes of the blood donors. Both
specificity and sensitivity of the mouthwash procedure were 100%. The overall
failure rate was 5.6 %. This large figure was caused mainly by insufficient rinsing
of the mouth in one particular blood bank. Exclusion of the results of this blood
33
bank reduced the failure rate to 1.8%. Our results confirm that also for large
number of samples the mouthwash procedure is suitable for mutation detection and
with proper instructions can be used in community screening.
Introduction
White blood cells are the main source of DNA used for gene analysis (Miller et
al.1980). Blood sampling and DNA isolation from great numbers of such samples,
however, have a few disadvantages: medical supervision is necessary for blood
collection, people may shrink from venopuncture, there is a risk of exposure to
blood pathogens for the donor as well as for the investigator, and costs of DNA
isolation are high. An alternative is sampling of mouthwashes followed by DNA
isolation from buccal cells (Lench et al.1988). This procedure is much simpler and
cheaper than existing methods, especially with large numbers of samples. There is
no need for medical supervision of sample collection, and the risk of infections is
eliminated.
To determine the failure rate (the proportion of mouthwash samples in which
no PCR product was obtained), the specificity and the sensitivity of the mouthwash
procedure, we studied the presence of the∆F508 mutation of the cystic fibrosis
(CF) gene in a large number of mouthwash samples with known or unknown
carrierstatus.
Materials and Methods
Recruitment and sampling
11,413 blood donors from 15 blood banks were approached in a study to determine
the prevalence of carriers of the∆F508 mutation in the CFTR gene in this country
and the failure rate and specificity of the mouthwash procedure. The design was
approved by the ethical committee of the Groningen University Hospital. Blood
bank officials were instructed how to recruit volunteers among the blood donors.
After informed consent, the blood donors were asked to rinse their mouth with 15
34
ml of 0.9% sterile saline for 10 seconds. The samples were collected in sputum
containers (Emergo, Landsmeer, The Netherlands). Matched blood samples of the
blood donors were collected in 10 ml heparin tubes. Samples were stored at 4° C
until shipment to either one of the two participating laboratories. Here all
mouthwash samples were analyzed. In order to determine the proportion of false
positives mutations detected in mouthwash DNA were checked in the matched
blood samples. Sensitivity was determined in mouthwash samples of 75 known
∆F508 carriers detected in earlier studies of CF families. The samples of these
carriers were offered blindly to the investigator among the mouthwashes of the
blood donors.
DNA isolation and (mutation) analysis
DNA isolation out of buccal samples was performed according to a procedure
modified from Lench et al.(1988). Buccal cells were pelleted by centrifugation at
1500 g for 10 minutes. The cell pellet was resuspended in 100 µl 50 mM sodiumhy-
droxide and boiled for 10 minutes. Samples were neutralised with 14 µl 1 M TRIS
(pH 7.5) and 5 µl was taken for PCR analysis. Genomic DNA was extracted from
heparin blood according to Miller et al.(1980).
The ∆F508 mutation was determined in the following way. PCR was
performed with primers according to Scheffer et al.(1989) in a Pharmacia LKB-
Gene ATAQ controller with denaturation temperatures decreasing from 94°C to
88°C in three steps of 10 cycles. The∆F508 mutation was detected directly on a 13
% polyacrylamide gel (50 samples per gel). Mutations detected in mouthwashes
were checked in the matched blood samples.
Results
Out of 11,413 mouthwashes we were able to analyse PCR products in 10,772
samples. A total number of 254∆F508 carriers were detected in this group. All 254
positive results could be confirmed by DNA analysis in matched blood samples.
The specificity of the mouthwash procedure was 10501/10501 or 100% (95% CI=
99.96-100%, assuming a sensitivity of 100%, see below).
35
DNA isolation failures occurred in 641 cases, due to insufficient mouthwas-
hings, leaking containers and food rest contamination. The overall failure rate of
mouthwashes therefore was 5.6%. In the matched blood samples of these cases an
additional 17∆F508 carriers were detected. The difference in the carrier frequencies
detected in mouthwashes and blood samples was not statistically significant.
The samples (492) collected from one particular blood bank yielded few
successful DNA isolations, with a failure rate of 90 percent. This probably has been
caused by insufficient rinsing of the mouth. Exclusion of these data resulted in a
total yield of 98.2 % successful DNA analyses (failure rate 1.8%).
Of the failures remaining after excluding those samples of the above
mentioned blood bank, almost 40% was caused by containers leaking during
transport of the mouthwash samples to the laboratories. Another 40% was caused by
insufficient rinsing and 20% by foodrest contamination.
More then 1,000 samples were sent from the blood banks to the laboratories
after storage for 14 days at 4°C. DNA isolation from these mouthwashes has the
same success rate of over 98%.
We were able to obtain PCR products from 74 out of 75 mouthwash samples
of known ∆F508 carriers. In all 74 samples we confirmed carriership of this
mutation. This gives a sensitivity of 100% (95 % CI= 95.1-100%). In one case we
were unable to isolate DNA due to contamination with food remains. The
percentage of successfully analysed mouthwashes of known carriers, therefore, was
98.2% (failure rate 1.8%).
Discussion
We detected a total of 271∆F508 carriers out of 11,413 unrelated individuals. Since
∆F508 represents 75% of the CF mutations in The Netherlands (Scheffer et al.
submitted), this is in keeping with a prevalence of the CF carrierstatus (all
mutations) of about 1 in 30 in The Netherlands (Ten Kate 1977). The specificity
and sensitivity of the mouthwash
procedure were both 100%.
The validation of DNA isolation out of buccal cells
(mouthwashes/mouthbrushes) has been described before (Richard et al. 1993;
36
Gilfillan et al. 1994;). These studies applied multiplex PCR amplifications to detect
the most frequent CFTR mutations. The success rates of these studies were
comparable with our results. The present study is the first to present data on the
sensitivity of the mouthwash procedure as well as effects of storage and transport.
Determination of the failure rate and the specificity of the procedure are based upon
a substantially larger number of samples than in the previous studies.
Our analysis of 11,413 mouthwashes showed a PCR success rate of 94.4%.
After exclusion of the samples from one particular blood bank this percentage
increased to 98.2%. Because mutation detection was comparable among the other
14 blood banks, the failures to obtain PCR-products in the samples of one blood
bank seem to represent an isolated case.
We did not collect mouthwashes under optimum conditions, because blood
donors generally are advised to eat before donating blood. Excluding the one
particular blood bank, this resulted in 30 PCR failures out of 10,921 (0.27%).
For the application of the mouthwash procedure one should be aware of the
above mentioned problems. The need for giving good instructions should not be
underestimated, even with simple collection procedures. If this condition is fulfilled,
mouthwashes can easily be used for single mutation detections with a large number
of samples, like in carrier screening programmes.
Acknowledgements
The authors want to thank the following persons and blood banks for making
mouthwashes and bloodsamples available: Th.M. Brouwers, director of blood bank
Apeldoorn-Deventer-Zutphen; G.C. van der Plas, director of blood bank Arnhem
e.o.; H.J.C. de Wit, director of blood bank Friesland; Mrs J.H. Barmentloo, director
of blood bank Gooi en Eemland; Dr. J.A. van der Does, director of blood bank ’s-
Gravenhage e.o.; R.C. Schaap, director of blood bank Kennemerland; Mrs dr. A.
Brand, director of blood bank Leiden e.o.; Dr. L.H. Siegenbeek van Heukelom,
director of blood bank Noord-Holland-Noord; Dr. H.J.A. Sonderkamp, director of
blood bank Noord-Limburg; F.H.M. Welle, director of blood bank Noord-Oost
Brabant; H.P. Olthuis, director of blood bank Nijmegen; Dr. A.C.J.M. Holdrinet,
director of blood bank West-Brabant; Dr. J.Ph.H.B. Sybesma, director of blood
37
bank Zuid-West Nederland and Dr. M. Bins, director of blood bank Zwolle. This
study was made possible by a grant from The Netherlands Organization for
Scientific Research (NWO).
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Miller SA, Dykes DD, Polesky HF (1980) A simple salting out procedure for extracting DNA from humannucleated cells. Nucleic Acids Res 10:1845
Richards B, Skoletsky J, Shuber AP, Balfour R, Stern RC, Dorkin HL, Parad RB, Witt D, Klinger KW(1993) Multiplex PCR amplification from the CFTR gene using DNA prepared from buccal brushes/swabs.Hum Mol Genet 2:159-163
Scheffer H, Verlind E, Penninga D, Te Meerman G, Ten Kate LP, Buys CHCM (1989) Rapid screening for∆F508 deletion in cystic fibrosis. Lancet:1345-1346
Scheffer H, Mol B, Dijkstra D-J W, Buys CHCM. Allele-specific tests for the CFTR-missense mutationsA455E and A1251N flanking a similar conserved motif in the two nucleotide binding folds with differentclinical phenotypes and occuring relatively frequent in The Netherlands (submitted)
Ten Kate LP (1977) Cystic fibrosis in The Netherlands. Int J Epidem 6:23-35
38
Chapter 3
Prevalence of∆F508 cystic fibrosis carriers in The Netherlands:
region of residence, age, and number of offspring as explanatory
variables
H.G. de Vriesa, J.M. Colléeb, H.E.K. de Wallea, M.H.R. van Veldhuizenb, C.Th.
Smit Sibingac, H. Scheffera, C.H.C.M. Buysa, L.P. ten Kateb.
a Department of Medical Genetics, University of Groningen, The Netherlandsb Department of Human Genetics, Free University of Amsterdam, The Netherlandsc Blood bank Groningen-Drenthe, Groningen, The Netherlands
(submitted)
Abstract
An average cystic fibrosis (CF) carrier frequency of 1 in 25 in Europe is cited in
numerous reports, although a great variability in estimated prevalences has been
found in different European populations. The estimates of these frequencies were
based on numbers of CF patients before identification of the gene in 1989. Here we
report the results of a study to determine the carrier frequency of the∆F508
mutation in The Netherlands by analyzing mouthwashes and matched bloodsamples
from 11,654 blood donors all over the country. In informed consent forms the blood
donors were asked to fill in their age, sex, and number of children. Twenty six
percent of the blood donors did not know that we were looking for a CF mutation.
We analyzed possible relationships between a number of theoretically
explanatory variables and the∆F508 carrier frequency by means of univariate and
multivariate logistic regression. These variables were: 1. Distance of the blood
banks to the northeastern part of the country (distance). This variable was chosen
because a positive correlation between distance and prevalence of CF at birth had
been reported before in this country. 2. Whether the blood donors knew that we
were looking for a CF mutation (CFinfo). 3. Sex of the donor. 4. Age of the donor.
41
5. Number of children of the donor (family size).
We detected a∆F508 carrier frequency of 1 in 42 (95% CI 1/37-1/47) in The
Netherlands. This gives an estimated overall CF carrier frequency of 1 in 31 (95%
CI 1/27-1/35), significantly less than 1 in 25.
The univariate logistic regression analysis of the effects of the explanatory
variables on the carrier frequency revealed no significant relationships, except for an
increase in carrier frequency with increasing distance to the northeastern region. In
the multivariate analysis with all 5 independent variables distance, age and family
size were significantly related to the carrier frequency, but sex and CFinfo were not.
There was a significant interaction between age and family size. In our final model
distance, age and family size were positively related to the carrier frequency, while
the interaction of age with family size showed a negative relation. These results
confirm that there is a gradient in gene frequency with low frequencies in the
northeastern part of the country and high frequencies in the southern part. They also
suggest a relation of age and family size with carrier frequency. This relation,
however, is too complex to be explained by heterozygote advantage.
Introduction
Cystic fibrosis (CF) is the most common fatal autosomal recessive disease in
caucasoid populations. The clinical expression of the disease is variable, but most
patients show chronic pulmonary disease and pancreatic insufficiency. The median
life expectancy for newborns with CF is between 25 and 40 years at the moment
[1].
Generally, in persons of European descent, a prevalence at birth of 1 in 2500
is quoted, which conforms to a carrier frequency of 1 in 25. In reality, however,
previous studies in European populations and populations of European descent
elsewhere have shown a range of birth prevalences from 1 in 1700 to 1 in 6500 [2-
4]. Finland forms an exception with a birthprevalence of 1 in 40,000. Differences
were not only observed between countries but also between regions within countries
[3,5,6]. In The Netherlands for instance a birth prevalence of 1 in 3600 was found
in the seventies, conforming to a carrier frequency of 1 in 30 [3]. Within the
country a gradient was observed with lower frequencies in the northeastern part of
42
the country. It is not clear whether the differences found in previous studies
between countries and between regions are real or were caused by variations in
diagnosis and reporting.
Almost all epidemiologic studies on the prevalence of CF were performed
before the identification of the CFTR-gene in 1989 [7-9]. The present availability of
PCR-based mutation detection methods offers an opportunity for an accurate
determination of carrier frequencies and a reevaluation of the old data.
We here report on a search for∆F508 carriers among 11,654 blood donors in
The Netherlands. We also analyzed the relationship between the∆F508 carrier
frequency and a number of possible explanatory variables: distance of the blood
banks to the northeastern part of the country, whether the blood donors knew that
we were looking for a CF mutation, sex and age of the blood donors and their
number of children. The study also produced data on the validity of testing large
numbers of mouthwash samples. The results of the validity study have been
reported elsewhere [10].
Material and Methods
recruitment and sampling
We approached directors of all 22 blood banks in the country to obtain mouthwash
samples and matched blood samples. Each blood bank serves a geographically
defined region without overlap between them. Out of the 22 blood banks 15 were
willing to co-operate. Blood bank officials were instructed how to recruit volunteers
among the blood donors. 13 of the 15 blood banks adhered to the following
protocol. Informed consent forms consisted of two sticked papers. On the frontpage
readers were asked to participate in a study on the validity of a method to detect a
"genetic trait" in mouthwashes and on the frequency of the trait. Readers then were
given the options of obtaining more information on the trait sought after first or to
join the study anonymously without being informed further and without getting the
test result. In case they wanted further information the sticked paperborders of the
consent form had to be stripped off and data concerning cystic fibrosis, carriership
and genetic counselling were presented at the reverse side of the frontpage. Readers
43
coming this far then had the following options: 1) to participate in the test either
with or without being informed about the results of the test, or 2) not to participate
at all. In all cases the blood donors were asked to fill in their age, sex and number
of children. The design was approved by the ethical committee of the Groningen
University Hospital. This design allowed us to see whether knowledge of the
identity of the trait sought after would influence the participation. For instance if
family members of CF-patients would be more likely to participate, this would bias
our results.
Out of the 15 blood banks two followed a different protocol, approved by
their own ethical committee. Blood donors from these 2 blood banks were not
informed about the identity of the trait which was searched for, and participated
anonymously. In addition blood spots were obtained from the CLB Blood bank.
This blood bank functions as a central facility and receives blood donations from all
regional blood banks. At the time of the sampling only blood spots originating in
one region could be obtained.
We did not give any publicity in the media or elsewhere about this
investigation, first to avoid overrepresentation of donors who have a family member
with CF, and secondly to prevent that people, who already joined this study but
opted not to read the information on the identity of the trait, would obtain
information against their wish after all.
Subjects participating in the mouthwash study were asked to rinse their
mouth with 15 ml of 0.9% sterile saline for 10 seconds. The material then was
collected in sputum containers (Emergo, Landsmeer, The Netherlands). Matched
blood samples were collected in 10 ml heparin tubes.
DNA isolation and (mutation) analysis
Mutation detection was performed on mouthwash DNA. In order to determine the
proportion of false positives, the mutations detected in mouthwash DNAs were
checked for confirmation in the matched blood samples. In case no PCR product
was obtained in mouthwash DNA or no mouthwash DNA was available, mutation
detection was performed on blood samples only. The specificity and sensitivity of
the mouthwash procedure were both 100% (95% CI specificity= 99.96-100%; 95%
44
CI sensitivity= 95.1-100%) [10].
Statistics
The number of participants in each blood bank was not proportional to the
size of the population in the region served by the blood bank. Regional frequencies,
therefore, were adjusted for the size of the population in each region in order to
obtain the average∆F508 carrier frequency in the country. The formula used was as
follows:
Cfreq=∑(Wreg*Creg/Nreg)
with Cfreq = mean carrier frequency of the country, Wreg = regional weight:
proportion of the population in the region with respect to the national population
size, Creg = number of carriers in the region, and Nreg = number of participants in
the region.
An estimate of the overall CF carrier frequency is obtained by dividing the
∆F508 carrier frequency by its relative frequency among CF chromosomes. The
estimated relative frequency of the∆F508 mutation, detected in a total of 532 CF
chromosomes, is 73.3% in The Netherlands (personal communication Hans
Scheffer). The equation used for the calculation of the confidence interval, when
some carriers are not detected, is described by Parker and Phillips [11].
In order to represent possible differences in∆F508 carrier frequencies
between regions, the regional frequencies were represented as standard deviation
scores. The formula of the standard deviation score is:
SDreg = (Creg-Ctot*N reg/Ntot)/(Ctot*N reg/Ntot)1/2
with SDreg = regional standard deviation score, Creg = regional number of carriers,
Ctot = total number of carriers found in this study, Nreg = regional number of
participants, and Ntot = total number of participants in The Netherlands. Areas with
SDreg scores <-2 or >2 accommodate significantly less or more CF carriers
respectively compared with the national average.
45
In view of the number of variables and because the dependent variable was
binary (carrier yes/no) we used the logistic regression model to describe the
relationship between this outcome and a set of independent or explanatory variables.
The independent variables in our model were: 1. Distance of each blood bank to the
northeastern region in km/25 (calculated from latitude and longitude). 2. Whether
the blood donors knew that we were looking for a CF mutation (yes/no). 3. Sex of
the blood donors (male/female). 4. Number of children of blood donors (0,1,2...). 5.
Age of the blood donors (in years). To examine these possible relations we tested
the variables first in a univariate way and after that we used multivariate logistic
regression. The formula of the multiple logistic regression model to calculate the
chance of being a∆F508 carrier is as follows:
p = e[b0+b1x1+b2x2+...+bnxn]/(1+e[b0+b1x1+b2x2+...+bnxn])
p = chance to be a∆F508 carrier
b0= constant regression coefficient
b1 to bn= regression coefficients of the related variables
x1 to xn= (coded) values of the related variables
The statistical package we used was Statistix 4.0.
Results
A total of 11,654 subjects was examined for∆F508 carriership in the various blood
bank regions in The Netherlands (table 1). We were able to obtain and analyze PCR
products from 10,772 out of 11,413 mouthwashes. The failure rate of the
mouthwash procedure is described elsewhere [10]. A total of 254∆F508 carriers
was detected in this group. The remaining 882 analyses were performed on blood
samples only ( 244 from the CLB blood bank). We detected 22∆F508 carriers in
this group. So 276∆F508 carriers were detected among 11,654 subjects.
The overall∆F508 carrier frequency in the country, after adjustment for the
size of the regional population, was 1 in 42 (95% CI 1/37-1/47). The total CF
carrier frequency, including other mutations, therefore, can be estimated at 1 in 31
46
(95% CI 1/27-1/35), based on an estimated relative∆F508 frequency of 73.3%.
The regional distribution of carrier frequencies is shown in figure 1. The
lightshaded areas, which are predominantly located in the northeastern part of the
country harbour less∆F508 carriers than the darkshaded regions in the southern
parts of The Netherlands.
On average 74% of the participants of the 13 blood banks who sticked to the
original protocol read the information on CF (range of 52% to 95%). So 26%
participated without being informed about the identity of the trait that was searched
for. The age of the blood donors ranged from 17 to 69 years, with an average of
40.5 years. The ratio male/female blood donors was 1.5, and the mean number of
their children was 1.6.
The univariate logistic regression analysis of the effects of the explanatory
variables on the carrier frequency revealed a significant relationship for the distance
to the northeastern region (table 2).
Table 1. Number of subjects investigated and number of∆F508 carriers found per blood bank region in TheNetherlands and proportion of the regional population with respect to the national population size.
blood bank regionsa subjects ∆F508 proportioncarriers of population
1. Groningen-Drenthe 2013 34 0.1042. Friesland 770 18 0.0613. Zwolle e.o. 617 9 0.0614. Apeldoorn-Deventer-Zutphen 407 8 0.0455. Noord-Holland-Noord 490 9 0.0566. Arnhem e.o. 705 23 0.0827. Gooi en Eemland 591 12 0.0618. Utrecht 144 3 0.0739. Kennemerland 397 10 0.040
10. Nijmegen 412 13 0.04311. Leiden e.o. 409 9 0.04712. Noord-Oost Brabant 492 14 0.05313. ’s-Gravenhage 603 16 0.09614. Zuid-West Nederland 2024 53 0.07415. Noord-Limburg 424 11 0.04016. West-Brabant 1156 34 0.064
Total 11654 276 1.000
a Blood banks ordered according to distance to the northeastern region
47
Before running the multivariate model we checked the continuous variables if they
were linear in the logit and they were. The results of the multivariate model with all
5 independent variables are shown in table 3a. This full model shows a positive
relation of distance and age with the carrier frequency, while the family size
shows a negative relation. The variables sex and CFinfo were not statistically
significant, so they were omitted in a reduced model (table 3b). The likelihood ratio
test comparing the two models indicated that the reduced model was as good as the
full model. In neither model we made allowance for possible interactions between
variables. There was, however, a significant interaction between age and family size
with respect to being a carrier. Table 3c shows our final model which contains the
variables distance, family size, age and the interaction between age and family size
(age in years * number of children). The goodness-of-fit, calculated with the
Hosmer-Lemeshow statistic [13], of this model revealed a p-value of 0.56. This
indicates that the model seems to fit quite well since the difference between the
expected and the observed results is not significant. Distance, age and family size
all showed a positive affect on carrier frequency, while the interaction showed a
negative effect. The variables age and family size cannot be analyzed separately.
Because of the interaction the odds ratio of family size is not constant over age.
The odds ratios of age, family size and interaction are therefore not shown.
Table 2. Univariate logistic regression analysis relating the∆F508 carrier frequency to the distance to thenortheastern region (distance), whether the blood donors knew that we were looking for a CF mutation(CFinfo), sex of the blood donors (sex), number of their children (family size) and age of the blood donors(age).
variables number ofsubjectsanalyzed
regressioncoefficient (b)
standard error
Se(b)
p odds ratio 95% CIodds ratio
distanceCFinfosexfamily sizeage
11654116549259
1051010501
0.0546-0.1592-0.0230-0.0748
0.0080
0.02050.12650.13510.05000.0058
0.00760.20830.86470.13520.1702
1.060.850.980.931.01
1.01 - 1.100.67 - 1.090.75 - 1.270.84 - 1.021.00 - 1.02
The relation of age and family size with the carrier frequency is also shown
in table 4. For the non-carriers there is a positive correlation between age and
number of children. The relation is different in the carrier group. In this group the
49
family size decreases in the last two age categories, while the carrier frequency
increases with age. These results give an impression of the different associations
between family size and carrier frequency with respect to age.
Table 3. Multivariate logistic regression analysis relating the∆F508 carrier frequency to the distance to thenortheastern region (distance), whether the blood donors knew that we were looking for a CF mutation(CFinfo), sex of the blood donors (sex), number of their children (family size) and age of the blood donors(age).
(a) Full model
variablesa regressioncoefficient (b)
standard errorSe(b)
p odds ratio 95% CIodds ratio
constantdistanceCFinfosexfamily sizeage
-4.54690.0566
-0.12600.0787
-0.12450.0182
0.40410.02070.15040.14050.06010.0069
0.00630.40200.57550.03840.0085
1.060.881.080.881.02
1.02 - 1.100.66 - 1.180.82 - 1.420.78 - 0.991.00 - 1.03
a Analyzed in 9247 subjects
(b) Omitting CFinfo and sex
variablesa regressioncoefficient (b)
standard errorSe(b)
p odds ratio 95% CIodds ratio
constantdistancefamily sizeage
-4.41010.0517
-0.12750.0145
0.27620.02040.05820.0065
0.01130.02860.0258
1.050.881.01
1.01 - 1.100.79 - 0.991.00 - 1.03
a Analyzed in 10488 subjects
(c) Final model
variablesa regressioncoefficient (b)
standard errorSe(b)
p odds ratio 95% CIodds ratio
constantdistance (x1)family size (x2)age (x3)age*family size (x4)
-5.19510.05060.61750.0353
-0.0176
0.36500.02040.22150.00870.0051
0.01300.00530.00010.0006
1.05 1.01 - 1.09
a Analyzed in 10488 subjects
50
Table 4. The relation of the family size and carrier frequency with the age in 10 years categories.
non-carriers ∆F508 carriers
age subjects family size subjects family size carrier frequency
=<2021-3031-4041-5051-60>60
170 0.011799 0.303098 1.623222 1.991487 2.28462 2.62
3 0 1.7%37 0.49 2.0%77 1.59 2.4%87 1.80 2.6%31 1.68 2.0%15 1.60 3.1%
Discussion
A total of 11,654 blood donors was examined for∆F508 carriership in The
Netherlands. Seventy four percent of the donors knew that we were looking for
carriers of the∆F508 mutation. We did not find a difference in carrier frequency
between the groups of informed and non-informed blood donors. This indicates that
we did not introduce a selection bias by giving the blood donors information about
the trait that was searched for.
We have found a∆F508 carrier frequency of 1 in 42 in the Dutch
population. This corresponds with an estimated total CF carrier prevalence of 1 in
31, based on an estimated relative∆F508 frequency of 73.3%. The estimated overall
CF carrier frequency of 1 in 31 is significantly different from the generally quoted
carrier frequency of 1 in 25 (p<0.005). This supports the results of an earlier study
[3] in which an estimated birth prevalence of one CF patient in 3600 newborns was
obtained, conforming to a carrier frequency of one in 30. Because of the observed
biological variation it is incorrect to refer to a common carrier frequency of 1 in 25
for all European populations. The carrier frequencies have to be established
separately for each population. Our study also shows that results of old but properly
performed studies on the birth prevalence of CF may be dependable.
The estimate of the relative frequency of the∆F508 mutation on CF
chromosomes (73.3%) is mainly based on prevalent cases in stead of incident cases.
The DNA of Dutch patients with the clinical manifestations of CF has been
collected for the last 6-10 years. Because of the high infant mortality rate of CF
patients in the past, which was possibly predominantly correlated with the presence
51
of a ∆F508 mutation, samples of these patients may be underrepresented.
Chromosomes with non-∆F508 mutations, often associated with less severe
phenotypes, therefore may have accumulated in the surviving patients. This would
lead to an underestimation of the∆F508 mutation in the present patient population.
There is, however, also a possibility of underdiagnosis of CF patients with non-
∆F508 mutations associated with a mild phenotype. These arguments indicate that
there may be some variance in the estimate of the relative∆F508 frequency on CF
chromosomes.
In our study the variable distance shows a significant positive relation with
the carrier frequency, in both the univariate and multivariate logistic regression
analyses. This geographical gradient in the∆F508 carrier frequency with high
prevalences in the southern part and low prevalences in the northeastern part also
confirms a previous finding of a lower birth prevalence of CF in the north-east of
the country [3].
It is not possible as yet to give a detailed description of the geographic
distribution of the total CF carrier frequency, including non-∆F508 mutations,
because not all non-∆F508 mutations are randomly distributed in the Dutch
population; especially the A455E mutation is very concentrated in the southern parts
of The Netherlands (unpublished results), and the identity of 15% of all CF
mutations is unknown in this country at the moment.
In the multivariate logistic regression analysis we found a positive effect of
age and family size on carrier frequency, while there was an interaction term
involving the same variables which was negatively correlated with carrier
frequency. A possible explanation for a positive effect of age and family size on
carrier frequency is heterozygote advantage either at present or in the past [14]. If
heterozygote advantage is still effective today, this would result in a higher life
expectancy and a larger number of children of carriers and therefore in their
overrepresentation in older people and people with more children (selection effect).
Alternatively, if heterozygote advantage was only effective until recently but no
more today (e.g. by disappearance of an environmental threat) carrier frequency
would decrease in time, resulting in a lower carrier frequency among younger
people than among older ones (cohort effect). In a cross-sectional study it is not
possible to differentiate between these two alternatives.
It is generally assumed that a positive selection of heterozygotes of about 2%
52
would be sufficient to maintain the CF carrier frequency at present levels.
Relaxation of selection also would result in relatively small changes in carrier
frequency. One would not expect to be able to demonstrate such small effects in a
study of this scale. In both cases, however, existing differences in carrier
frequencies between age groups might be exaggerated by studying blood donors,
because they are selected for their health.
There is another phenomenon in our data which we cannot explain by
heterozygote advantage, viz. the negative effect of the interaction between age and
number of children. This effect is so strong that carrier frequency increases with age
only for persons with less then 3 children. Likewise it increases with family size
only for persons below 40 years of age. So, for people of 40 years and over or with
3 or more children the negative effect of the interaction is stronger than the positive
effect of age and family size, resulting in a decrease in carrier frequency. This
phenomenon does not fit in with expectations from the heterozygote advantage
hypothesis and we have not been able to advance a coherent explanation. The
findings are unexpected and should first be confirmed in independent studies before
we can draw firm conclusions.
Acknowledgements
The authors want to thank the following persons and blood banks for making
mouthwashes and blood samples available: Th.M. Brouwers, director of blood bank
Apeldoorn-Deventer-Zutphen; G.C. van der Plas, director of blood bank Arnhem
e.o.; H.J.C. de Wit, director of blood bank Friesland; Mrs J.H. Barmentloo, director
of blood bank Gooi en Eemland; Dr. J.A. van der Does, director of blood bank ’s-
Gravenhage e.o.; R.C. Schaap, director of blood bank Kennemerland; Mrs dr. A.
Brand, director of blood bank Leiden e.o.; Dr. L.H. Siegenbeek van Heukelom,
director of blood bank Noord-Holland-Noord; Dr. H.J.A. Sonderkamp, director of
blood bank Noord-Limburg; F.H.M. Welle, director of blood bank Noord-Oost
Brabant; H.P. Olthuis, director of blood bank Nijmegen; Dr. A.C.J.M. Holdrinet,
director of blood bank West-Brabant; Dr. J.Ph.H.B. Sybesma, director of blood
bank Zuid-West Nederland; Dr. M. Bins, director of blood bank Zwolle and Dr.
L.P. de Waal, director of the CLB Blood bank, Amsterdam. The authors are also
53
very grateful to the blood donors for their spontaneous co-operaration.
This study was made possible by a grant from The Netherlands Organization for
Scientific Research (NWO).
References
1. Welsh MJ, Tsui L-C, Boat TF, Beaudet AL: Cystic fibrosis; in Scriver CR, Beaudet AL, Sly WS,Valle MD (eds): The Metabolic and Molecular Basis of Inherited Disease. New York, McGraw-Hill,1994,vol 3,pp 3799-3876.
2. Wood RE, Boat TF, Doershuk CF: Cystic fibrosis. Am Rev Respir Dis 1976;113:833-878.
3. Ten Kate LP: Cystic fibrosis in The Netherlands. Int J Epidem 1977;6:23-35.
4. Warwick WJ: The incidence of cystic fibrosis in Caucasian populations. Helv Paediat Acta 1978;33:117-125.
5. Brunecky Z: The incidence and genetics of cystic fibrosis. J Med Genetics 1972;9:33-37.
6. Cystic fibrosis Genetic Analysis Consortium: Population variation of common cystic fibrosis mutations.Hum Mut 1994;4:167-177.
7. Rommens JM, Iannuzi MC, Kerem B, Drumm ML, Meimer G, Dean M, Rozmahel R, Cole JL, KennedyD, Hidaka N, Zsiga M, Buchwald M, Riordan JR, Tsui L-C, Collins FS: Identification of the cysticfibrosis gene: chromosome walking and jumping. Science 1989;245:1059-1065.
8. Riordan JR, Rommens JM, Kerem B, Alon N, Rozmahel R, Grzelczak Z, Zielenski J, Lok S, Plavsic N,Chou J-L, Drumm ML, Iannuzzi MC, Collins FS, Tsui L-C: Identification of the cystic fibrosis gene:cloning and characterization of complementary DNA. Science 1989;245:1066-1073.
9. Kerem B, Rommens JM, Buchanan JA, Markiewicz D, Cox TK, Chakravarti A, Buchwald M, Tsui L-C:Identification of the cystic fibrosis gene: genetic analysis. Science 1989;245:1073-1080.
10. De Vries HG, Collée JM, Veldhuizen MHR, Scheffer H, Ten Kate LP: Validation of determination of∆F508 mutations of the cystic fibrosis gene in almost 11,500 mouthwashes. Hum Genet (in press).
11. Parker RA, Phillips III JA: Population screening for carrier status: Effects of test limitations on precisionof carrier prevalence rates. Am J Hum Genet 1994;49:317-322.
12. Micky J, Greenland S: A study of the impact of confounder selection criteria on effect estimation. Am Jepidem 1989;129:125-137.
13. Hosmer DW, Lemeshow S: Applied logistic regression. A Wiley-Interscience
14. Jorde LB, Lathrop GM: A test of the heterozygote advantage hypothesis in cystic fibrosis carriers. Am JHum Genet 1988;42:808-815.
54
Chapter 4
Relative frequencies of CFTR mutations in The Netherlands:
Regional variation is present even in a small country
J. Margriet Collée1, Hendrik G. de Vries2, Hans Scheffer2, Dicky J.J. Halley3, Leo
P. ten Kate1
1 Department of Human Genetics, Free University of Amsterdam, The Netherlands2 Department of Medical Genetics, University of Groningen, The Netherlands3 Department of Clinical Genetics, Erasmus University, Rotterdam, The Netherlands
(submitted)
Abstract
Cystic fibrosis (CF) is one of the most common autosomal recessive disorders in
white populations. Significant regional differences of CF mutations among affected
individuals have been reported.
We studied the geographic distribution of the relative frequencies of the three
most common Dutch CF mutations,∆F508, A455E, and G542X, by analyzing data
on residences of CF patients.
Significantly higher relative frequencies of the A455E mutation and the G542X
mutation were observed in the South-west and the South-east, respectively. For the
∆F508 mutation a rather uniform distribution of relative frequencies was found. The
results of our study show that even in a small country like The Netherlands certain
CF mutations may be more common in one region than in another.
Introduction
Cystic fibrosis (CF) is one of the most common autosomal recessive disorders in
white populations. The classic clinical picture is characterised by chronic pulmonary
57
disease, pancreatic insufficiency and elevated concentrations of sweat electrolytes
[1]. In The Netherlands the birth prevalence of CF has been estimated to be 1 in
3600, corresponding to a carrier frequency of 1 in 30 [2].
Since the identification of the CF gene and its major mutation∆F508 in 1989
[3,4,5], over 500 mutations have been described. In a recent study we found a
∆F508 carrier frequency of one in 42 in the Dutch population. This corresponds
with an estimated total CF carrier prevalence of 1 in 31, based on an estimated
relative ∆F508 frequency of 73.3% [6]. The second and third most common
mutations, A455E and G542X, represent approximately 3 and 2%, respectively [7].
All other identified mutations were detected in less than two percent of all CF
chromosomes each.
As significant regional differences in the relative frequencies of CF mutations
have been reported -with France as an example [8,9]- and migration from one to
another part of the country used to be uncommon in The Netherlands until only a
few decades ago, we studied regional differences in relative frequencies of Dutch
cystic fibrosis mutations. In view of the small numbers of other mutations only
∆F508, A455E and G542X were treated individually.
Patients and methods
In The Netherlands DNA testing for CF mutations is performed in two centres for
Clinical Genetics, one located in the west (Erasmus University Rotterdam) and one
in the North (University of Groningen). Both laboratories receive blood samples
from patients throughout the country. In the summer of 1994 samples from 634
independent Dutch CF patients (i.e. 1268 alleles) had been analyzed for diagnostic
purposes. Of the patients studied we collected data on the results of CF mutation
detection, on the residential area (residence and province), and on the age of the
patient at receipt of the blood specimen. Patients were excluded if no information
on their residence was available.
DNA testing
The detection of the∆F508, A455E, and G542X mutations in Rotterdam was
58
performed as described by Kerem et al. [10]. In Groningen the∆F508 mutation
detection was carried out according to Scheffer et al. [11] and the analysis for the
G542X mutation as described by Ferrie et al. [12]. The A455E mutation was
detected with a specific amplification refractory mutation system (ARMS)(HS,
unpublished).
Data analysis
The Netherlands consists of 12 provinces. First, the distribution of the∆F508
mutation over the 12 provinces was compared with the distribution of the non-
∆F508 mutations. Departure from a random distribution was tested for by means of
the chi-square test (with 11 degrees of freedom). Next, in view of the small
expected numbers of the A455E and G542X mutations in most provinces, provinces
were combined in three groups. Group 1 consisted of the Northern and Eastern
provinces (1-6 in figure 1), group 2 comprised the provinces called Noord-Holland,
Zuid-Holland and Utrecht (7-9 in figure 1) which contain the major cities of the
country, and group 3 included the remaining Southern provinces (10-12 in figure 1).
This grouping may seem rather arbitrary but takes account of some natural barriers:
the former Zuider Zee between group 1 and group 2, and the major rivers of Rhine
and Meuse between group 3 and the rest of the country. The distribution of the
∆F508, A455E, G542X, other known mutations and unknown mutations over the
three groups of provinces was then analyzed (chi-square test with 8 degrees of
freedom). To study the distribution of the∆F508, A455E and G542X in more
detail, we calculated standard deviation (SD) scores for the proportion of the
particular mutation in each of the 12 Dutch provinces. The expression used for the
SD score was as follows:
Dx = (Ax-At*nx/nt)/(At*nx/nt)½
Dx = standard deviation score per province x
Ax = number of CF chromosomes with a particular mutation found in province x
At = number of CF chromosomes with a particular mutation found in The
Netherlands
nx = number of CF chromosomes studied in province x
59
nt = number of CF chromosomes studied in The Netherlands
In provinces with standard deviation scores of <-2 or >2, the mutation under
study forms a significantly lesser or greater proportion of CF chromosomes in that
area when compared to the national average.
The major CF clinics, which have integrated DNA diagnostics for CF more
routinely in patient care (unpublished results, Dutch CF registry), are not randomly
distributed throughout The Netherlands. We, therefore, did not calculate frequencies
relative to the size of the population of the region.
Results
Of the 634 CF patients we were able to retrieve information on places of
residence in all but 36 (5.7%) cases. This resulted in a total of 1196 CF
chromosomes that were included in the analysis. In this study population the∆F508
mutation was present in 75% of the CF chromosomes. The relative frequencies of
the A455E and G542X mutations were 3.7% and 2.2% respectively. Other identified
mutations accounted for 7.4% of CF chromosomes. In 11.5% of the CF
chromosomes no known mutation was found.
The relative frequencies of∆F508, A455E, G542X, other identified CF
mutations, and unknown CF mutations by region are shown in table 1. When
comparing the distribution of∆F508 over the 12 provinces to the distribution of
non-∆F508 mutations (all together), no significant differences were seen indicating
that its relative frequency is rather uniformly distributed. When comparing the
distributions of the∆F508, A455E, G542X, other known mutations, and unknown
mutations over the three groups of provinces a significant deviation from a random
distribution was observed (chi2 = 22.1, p<0.01). This high score is caused mainly by
an abnormal distribution of the A455E and G542X mutations, while the∆F508 and
the other mutations contributed much less to the chi-square. SD scores of the
relative frequencies of∆F508, A455E and G542X were calculated by province, and
are shown in figure 1. The∆F508 mutation was uniformly distributed without SD
values more or less than 2. However, significantly more CF chromosomes in the
South-West of The Netherlands carried the A455E mutation: in the provinces Zuid-
60
Holland and Zeeland this mutation was identified in 6.2% (SD= 2.45) and 11.1%
(SD=2.84) of the chromosomes, respectively. The only other province in which the
A455E mutation was relatively frequent was Utrecht (SD=1.38), a central region
that flanks Zuid-Holland.
For the G542X mutation a significantly larger proportion when compared
with the national average was observed in Limburg (8.6%, SD=3.33), in the South-
east of the country. In the adjacent province Noord-Brabant this mutation was also
relatively frequent (SD=1.27).
When looking at the ages of CF patients at the time of DNA analysis a
remarkable dissimilarity was observed between patients with different mutations.
The mean age for patients with a double∆F508 mutation or a∆F508 mutation and
a G542X mutation (only three homozygotes for G542X were found) was 11.5 years
and 8.9 years respectively. The mean age for patients with a∆F508 and an A455E
mutation (no homozygotes for A455E were found) was 23.3 years. No patients were
identified who were compound heterozygotes of an A455E and a G542X mutation.
Table 1. Numbers of∆F508, A455E, G542X, and other mutations by province in Dutch CF patients
Provincea ∆F508 A455E G542X Otherknownmutations
Unknownmutations
Total numberof CFchromosomes
Group 1
Groningen (1)Friesland (2)Drenthe (3)Overijssel (4)Flevoland (5)Gelderland (6)
Group 2
Utrecht (7)Noord-Holland (8)Zuid-Holland (9)
Group 3
Zeeland (10)Noord-Brabant (11)Limburg (12)
282025551368
63142251
3615445
100100
53
22
651
000001
067
075
403328
31624
6154
34431
11
32952
6193
362432621688
74196356
5420058
The Netherlands 900 44 26 43 138 1196
61
Discussion
The results of our study show that in The Netherlands certain CF mutations among
CF patients are more common in one area than in another. We observed this for the
A455E and the G542X mutation, but not for the∆F508 mutation.
With respect to the∆F508 mutation we earlier performed a study on the
frequency of∆F508 carriers among blood donors which showed a lower prevalence
of carriers in the North of the country [6]. As in the present study no differences
were observed in relative frequencies for the∆F508 mutation between the Dutch
provinces, this suggests a lower prevalence of CF and CF carriership (all mutations
together) in the North. In fact this phenomenon has been suggested before in other
studies on the prevalence of CF in the Netherlands [2,13].
The A455E mutation has mainly been described in The Netherlands and in
Canada [7]. In the latter it has been introduced during the period 1650-1900 [14,15).
Some of the Canadian and Dutch patients share a common haplotype over distances
up to 25 cM surrounding the A455E mutation [16], which suggests that this
mutation has been derived from a not too distant common predecessor. Furthermore,
it is associated with a less severe CF phenotype [17], which results in a higher
prevalence among adult CF patients. In this study this is reflected by the higher age
of patients with a A455E mutation when compared to those with a∆F508 mutation.
As one of the major clinics for adult CF patients is located in the province Zuid-
Holland, in the west of the country, this confronted us with a possible confounding
factor. In order to distinguish between a truly high prevalence of the A455E
mutation in the South-West and a confounder effect, we repeated the data analysis
by calculating standard deviation scores for CF patients under 16 years of age (706
CF chromosomes, A455E in 1.4%). This resulted again in significantly higher
frequencies and deviation scores for Zuid-Holland (3.5%, SD=2.28) and Zeeland
(9.4%, SD= 3.78), while the relative frequencies of the A455E mutation in other
provinces were not different from the results in the total group, thus confirming our
first observation. Similarly analysis of the distribution of the∆F508 and the G542X
mutations in patients under 16 years of age confirmed the results in the total group.
The G542X mutation has been detected in various populations [7] with a
tendency to be more frequent in South European countries. While the A455E
mutation gives rise to mild disease, the G542X mutation is associated with more
63
severe symptoms and pancreatic insufficiency [18]. In this study we found a higher
frequency of this mutation in the South, predominantly in the province of Limburg.
In conclusion, the results of this study show that even in a relatively small
country like The Netherlands regional differences of CF mutations among affected
individuals can be observed.
Acknowledgements
This study was made possible by a grant from The Netherlands Organization for
Scientific Research (NWO).
References
1. Welsh MJ, Tsui L-C, Boat TF, Beaudet AL: Cystic fibrosis; in Scriver CR, BeaudetAL, Sly WS, ValleMD (eds): The Metabolic and Molecular Basis of Inherited Disease. New York, McGraw-Hill,1994,vol3,pp 3799-3876.
2. Ten Kate LP. Cystic fibrosis in The Netherlands. Int J Epidem 1977;6:23-35.
3. Rommens JM, Iannuzzi MC, Kerem B, et al. Identification of the cystic fibrosis gene: chromosomewalking and jumping. Science 1989;245:1059-1065.
4. Riordan JR, Rommens JM, Kerem B, et al. Identification of the cystic fibrosis gene: cloning andcharacterization of complementary DNA. Science 1989;245:1066-1073.
5. Kerem B, Rommens JM, Buchanan JA, et al. Identification of the cystic fibrosis gene: genetic analysis.Science 1989;245:1073-1080.
6. De Vries HG, Collée JM, Van Veldhuizen MHR, Smit Sibinga CTh, Scheffer H, Buys CHCM, Ten KateLP. Prevalence of∆F508 cystic fibrosis carriers in The Netherlands: region of residence, age, and numberof offspring as explanatory variables (submitted)
7. Cystic Fibrosis Genetic Analysis Consortium. Population variation of common cystic fibrosis mutations.Hum Mut 1994;4:167-177.
8. Férec C, Audrezet MP, Mercier B, Guillermit H, Moullier P, Quere I, Verlingue C. Detection of over 98%cystic fibrosis mutations in a Celtic population. Nature Genet 1992;1:188-191.
9. Claustres M, Laussel M, Desgeorges M, Giansily M, Culard JF, Razakatsara G, Demaille J. Analysis ofthe 27 exons and flanking regions of the cystic fibrosis gene: 40 different mutations account for 91.2% ofthe mutant alleles in Southern France. Hum Mol Genet 1993;2:1209-1213.
10. Kerem B, Zielenski J, Markiewicz D, Bozon D, Gazit E, Yahav J, Kennedy D, Riordan JR, Collins FS,Rommens JM, Tsui L-C. Identification of mutations in regions corresponding to the two putative
64
nucleotide (ATP)-binding folds of the cystic fibrosis gene. Proc Natl Sci USA 1990;87:8447-8451.
11. Scheffer H, Verlind E, Penninga D, Te Meerman G, Ten Kate LP, Buys CHCM. Rapid screening for the∆F508 deletion in cystic fibrosis. Lancet 1989;1345-1346.
12. Ferrie RM, Schwartz MJ, Robertson NH, Vaudin S, Super M, Malone G, Little S. Development,multiplexing, and application of ARMS tests for common mutations in the CFTR gene. Am J HumGenet 1992;51:251-262.
13. Cornel MC, Te Meerman GJ, Ten Kate LP. Jaarlijkse inventarisatie van kystische fibrose in Nederland.T Soc Gezondheidsz 1985;63:266-269.
14. Rozen R, Schwartz RH, Hilman BC, Stanislovitis P, Horn GT, Klinger K, Daigneault J, De BraekeleerM, Kerem B-S, Tsui L-C, Fujiwara TM, Morgan K. Cystic fibrosis mutations in North Americanpopulations of French ancestry: analysis of Quebec French Canadian and Louisiana Acadian families.Am J Hum Genet 1990;47:606-610.
15. Rozen R, De Braekeleer M, Daigneault J, Ferreira-Rajabi L, Gerdes M, Lamoureux L, Aubin G, SimardF, Fujiwara TM, Morgan K. Cystic fibrosis mutations in French Canadians: Three mutations arerelatively frequent in a Quebec population with an elevated incidence of cystic fibrosis. Am J Med Genet1992;42:360-364.
16. De Vries HG, Van der Meulen MA, Rozen R, Halley DJJ, Scheffer H, Ten Kate LP, Buys CHCM, TeMeerman GJ. Haplotype identity between individuals who share a CFTR mutation allele Identical ByDescent: demonstration of the usefulness of the haplotype sharing concept for gene mapping in realpopulations (submitted)
17. Gan KH, Veeze HJ, Van den Ouweland AMW, Halley DJJ, Scheffer H, Van der Hout A, Overbeek SE,De Jongste JC, Bakker W, Heijerman HGM. Evidence for a cystic fibrosis mutation associated with mildlung disease. N Engl J Med 1995:333:95-99.
18. Kristidis P, Bozon D, Corey M, Markiewitcz D, Rommens J, Tsui L-C, Durie P. Genetic determinationof exocrine pancreatic function in cystic fibrosis. Am J Hum Genet 1992;50:1178-1184.
65
Chapter 5
Number and sex of offspring of ∆F508 carriers outside CF
families
HG de Vries1, JM Collée2, WP Meeuwsen1, H Scheffer1, LP ten Kate2
1 Department of Medical Genetics, University of Groningen, The Netherlands.2 Department of Human Genetics, Free University, Amsterdam, The Netherlands.
Hum. Genet. (1995) 95:575-576
Abstract
The number and sex of offspring was determined in a group of 7,841 random
selected blood donors who were screened for the∆F508 mutation. We did not find
evidence for differences in number or sex ratio of offspring between∆F508 carriers
and non-carriers.
In previous studies there have been indications of increased fertility of cystic
fibrosis (CF) carriers (Danks et al. 1965) and sex ratio distortion in their offspring
(Gloria-Bottini et al. 1980, Pritchard et al. 1983 ), which could be causally related
to the high birth prevalence of CF. Part of these observations may however have
resulted from ascertainment biasses (Ten Kate 1977; Jorde and Lathrop 1988).
The characterisation of the gene in 1989 (Kerem et al. 1990) enables a new
approach to be used in offspring studies by collecting data of subjects without a
family history of CF. To illustrate this possibility we determined number and sex of
offspring in blood donors who were screened for the∆F508 mutation (77% of CF
mutations in The Netherlands) by mouthwash Polymerase chain reaction (PCR) and
compared this data in carriers and non-carriers. Mouthwashes and data on offspring
were sampled simultaneously. The presence of∆F508 in mouthwashes was
confirmed by analysis in matched blood-samples.
So far 186∆F508 carriers have been identified in a group of 7,841 blood
67
donors. To determine sibship-size we here show data of the 4,116 blood donors
who were 40 years old and over. Most of them will have completed their families.
Data on the sex of children was determined in the total sample.
As shown in table 1, the number of offspring of CF carriers is 1.83 against
2.12 for non-carriers. The average number of children of female carriers is 1.86
against 1.82 for male carriers. In both comparisons the differences are not signifi-
cant. The sex ratio (male/female) in the offspring of carriers and in children of non-
carriers is 1.01. The sex ratio in offspring of male carriers does not differ signifi-
cantly from sexratio in children of female carriers (1.00 and 1.05 respectively).
Table 1. Number and sex of offspring of∆F508 carriers
Subject Number of Sex ofchildren children
Type Number Total Mean Number Male Female Ratio
Carrier
Male 771,2 140 1.82 1103 93 93 1.00
Female 291,2 54 1.86 673 46 44 1.05
Total 1062 194 1.83 1863 139 137 1.01
non-carrier
total 4,010 8,490 2.12 7,655 6,493 6,441 1.01
1 Male/female ratio in all 7,841 blood donors was 2.3/12 Blood donors 40 years and over3 Sex unknown in 9 blood donors
So far we have no evidence for differences in number or sex ratio of
offspring of ∆F508 carriers and non-carriers. As the project continues data will
accumulate until approximately 14,000 blood donors will have been screened
(expected number of carriers 325).
68
References
Danks DM, Allan J, Anderson CM. A genetic study of fibrocystic disease of the pancreas. Ann hum Genet1965;28:323-356.
Gloria-Bottini F, Antonelli M, Quattrucci S. et al. Is there a relationship between sex of cystic fibrosiscarriers and sex ratio of their offspring? Hum Genet 1980;54:79-82.
Jorde LB, Lathrop GM. A test of heterozygote-advantage hypothesis in cystic fibrosis carriers. Am J HumGenet 1988;42:808-815.
Kerem B-S, Rommens JM, Buchanan JA et al. Identification of the cystic fibrosis gene: genetic analysis.Science 1989;245:1073-1080
Pritchard DJ, Hickman GR, Nelson R. Sex ratio and heterozygote advantage in cystic fibrosis families. ArchDis Child 1983;58:290-293.
Ten Kate LP. A method for analysing fertility of heterozygotes for autosomal recessive disorders, withspecial reference to cystic fibrosis, Tay-Sachs disease and phenylketonuria. Ann hum Genet 1977;40:287-297.
69
Chapter 6
Haplotype identity between individuals who share a CFTR
mutation allele Identical By Descent: demonstration of the
usefulness of the haplotype sharing concept for gene mapping in
real populations
Hendrik G. de Vries1, Martin A. van der Meulen1, Rima Rozen2, Dickie J.J. Halley3,
Hans Scheffer1, Leo P. ten Kate4, Charles H.C.M. Buys1 and Gerard J. te Meerman1
1 Department of Medical Genetics, University of Groningen, The Netherlands2 Departments of Human Genetics, Pediatrics and Biology, Montreal, Canada3 Department of Clinical Genetics, Erasmus University, Rotterdam, The Netherlands4 Department of Human Genetics, Free University of Amsterdam, The Netherlands
(submitted)
Abstract
Cystic fibrosis (CF) patients with the A455E mutation, both in the French Canadian
and in the Dutch population, share a common haplotype over distances up to 25
cM. French Canadian patients with the 621+1G→T mutation share a common
haplotype of more than 14 cM. In contrast, haplotypes containing the∆F508
mutation show haplotype identity over a much shorter genomic distance within and
between populations, probably due to multiple introduction of this most common
mutation.
Haplotype analysis for specific mutations in CF or in other recessive diseases
is a model for studying the occurrence of genetic drift conditional on gene
frequencies. Moreover, from our results it can be inferred that analysis of shared
haplotypes is a suitable method for genetic mapping in general.
71
Introduction
In recent times it has been repeatedly observed that haplotypes surrounding rare
alleles of a gene are quite large [1-9]. Sharing of large genomic areas can be used
as a method to map disease genes: Identity By Descent (IBD) Mapping [4,10]. An
empirical question is whether haplotype sharing can be observed in real populations
to an extent where IBD mapping using haplotype sharing is feasible.
As an empirical model for high and low frequency disease alleles weakly
associated with a disease or with dominance and low penetrance, we have chosen to
study mutations leading to the recessive disease cystic fibrosis (CF). Only a very
small fraction of the disease alleles present in the population can be observed in
diseased individuals. Thusfar more than 500 presumed mutations have been
identified in the CFTR gene. The most common mutation (∆F508) has a high
frequency in Caucasian populations (up to 1.5%). A less frequent mutation is the
A455E missense mutation. According to data from the cystic fibrosis consortium
[11] this mutation is mainly detected among French Canadian and Dutch CF
patients. The A455E mutation comprises 8% of all CF mutations in the French
Canadian population of the Saguenay-Lac St. Jean region of Quebec [12] and 3% in
The Netherlands [unpublished data]. The overall CF carrier frequency is 1 in 15 in
the particular French Canadian population [12] and 1 in 30 in the Netherlands [13].
This results in allele frequencies of 1/400 (8% of 1/30) and 1/2000 (3% of 1/60)
respectively. The concentrated geographical distribution indicates that this mutation
has been introduced not very long ago.
In models for multifactorial disease the mutated gene concept is not directly
applicable since alleles act as risk factors in combination with other factors.
However, if gene/gene or gene/environment interactions are modelled in founder
populations, where the multifactorial background is more in common than in mixed
populations, specific alleles of genes may be involved, leading to association at the
population level. The implication is that such alleles show increased frequencies in
affected individuals. It cannot be ruled out that multifactorial diseases are
determined by only very few genes, which would make an increased frequency of
specific alleles in affected individuals even more likely [14]. By studying haplotype
sharing in two populations, one with a very late origin (French Canadians) and one
with a longer history (Southern part of The Netherlands) we demonstrate the
72
usefulness of the haplotype sharing concept for gene mapping in real populations.
Materials and methods
Recruitment of CF patients
The A455E mutation, which is associated with a less severe CF phenotype, has
mainly been detected in Canada and in The Netherlands [11]. In Canada this
mutation has been introduced by French immigrants during the period 1650-1900
[8,12]. The Dutch patients with an A455E mutation all come from the southern
parts of The Netherlands (unpublished results). Bloodsamples from 15 independent
Dutch CF patients with the A455E mutation were collected in Groningen and
Rotterdam. Samples from 10 French Canadian CF patients with the A455E muta-
tion, from a subpopulation in north-eastern Quebec-the Saguenay-Lac St.Jean region
[8,12], were collected in Montreal. The father of proband 3 and the mother of
proband 6, which are both carriers of the 621+1G→T mutation, were sibs. Because
all patients were compound heterozygotes, haplotype sharing could also be
determined around two other CF mutations (∆F508, 621+1G→T). In all patients
clinical diagnosis was confirmed by demonstrating the∆F508 [15], A455E [16] and
621+1G→T [17] mutations. In all cases DNA from one of the parents was used for
phase determination.
Microsatellite analysis
Three intragenic microsatellites, IVS8CA (intron 8), IVS17BTA, and IVS17BCA
(intron 17b) [18] and 7 extragenic microsatellites, D7S518, D7S501, D7S523,
D7S486, D7S480, D7S490, D7S635 [19], were analyzed by single amplification.
The primer sequences are shown in Table 1. PCR was performed with 400 ng of
DNA, 50 mM KCl, 10 mM Tris (pH 9.0), 1.5 mM MgCl2, 0.01% gelatin, 0.1%
Triton X-100, 0.5 µM of each microsatellite primer (biotinylated) and 0.25 U of
Super Taq (SphearoQ), in a total volume of 50 µl. Part of the PCR product was
diluted to 1:20 and mixed with formamide solution. Absolute PCR product sizes
73
Table 1. PCR primers of microsatellites at and flanking the CF locus. Data have been derived from Zielenskiet al [18] and Gyapay et al [19].
Marker Primersequences 5’→3’ Heterozygosity Distance toCFTR gene (cM)
D7S518 CAGTAGGCAGGGGTGG 0.87 15GGGTGTGTCTGTGTGACAAC
D7S501 CACCGTTGTGATGGCAGAG 0.81 7ATTTCTTACCAGGCAGACTGCT
D7S523 CTGATTCATAGCAGCACTTG 0.80 1AAAACATTTCCATTACCACTG
D7S486 AAAGGCCAATGGTATATCCC 0.81 0.2GCCAGGTGATTGATAGTGC
IVS8BTA TCTATCTCATGTTAATGCTG 0.41 0GTTTCTAGAGGACATGATC
IVS17BTA GACAATCTGTGTGCATCG 0.89 0GCTGCATTCTATAGGTTATC
IVS17BCA AAACTTACCGACAAGAGGA 0.38 0TGTCACCTCTTCATACTCAT
D7S480 CTTGGGGACTGAACCATCTT 0.86 2AGCTACCATAGGGCTGGAGG
D7S490 CCTTGGGCCAATAAGGTAAG 0.78 5AGCTACTTGCAGTGTAACAGCATTT
D7S635 CCAGGCCATGTGGAAC 0.81 10AGTTCTTGGCTTGCGTCAGT
were determined by adding standard size markers (generated from Pharmacia
m13mp18) to each sample. The reaction products were detected in a 6% denaturing
polyacrylamide gel with an Automated Laser Fluorescent system (Pharmacia LKB).
In total a region of 25 cM flanking the CF gene was genotyped. For certain
microsatellite alleles it was not possible to establish phase. In these cases, haploty-
pes have been assigned by comparing alleles of flanking microsatellites between the
CF patients.
74
Results
Table 2 shows the results of the haplotype analysis of the Canadian and Dutch CF
patients with a A455E mutation. The haplotype of the intragenic markers on the
A455E chromosome of the 10 French Canadian patients was identical in all cases,
namely 22-35-13, in which the numbers represent the numbers of repeats of the
IVS8CA, IVS17BTA and IVS17BCA respectively. The extragenic alleles are
numbered according to the relative length of the PCR product.
Table 2. Microsatellite haplotypes for independent A455E chromosomes from a French Canadian and aDutch population.
5 3 2 Intragenic 1 6 8 (cM)^ ^ ^ / \ ^ ^ ^
D7S-635 490 480 8CA 17BTA 17BCA 486 523 501 518
French Canadianchromosomes
1 7! 1 3 22! 35! 13 8 4 5 102 7 1 3 22 35! 13 8 4! 5 103 7 1 3 22 35 13 8 4 5! 104 3! 4 3 22! 35 13 8 4 5 105 3 4 3 22! 35 13 8 4 5 106 3 4 3! 22 35 13 8 4 5! 107 1! 1 2 22! 35 13 8 4 5 28 1 1 2 22 35 13 8 4! 4 109 4! 2 2 22 35 13 8 4 5 10
10 7 1! 3 22 35 13 8 3 3 2
Dutchchromosomes
1 7 1 3 22 35! 13 8 4 3 22 1 1 3 22! 35 13 8 4 1 123 1 4 6 22 35 13 8 4 1! 4!4 6 1 3 22 35 13 8 5 7 25 6 1 3 22 35 13 8 5 7 96 6 1 3 22! 35 13 8 5 5 27 6 1! 3 22 35 13 10 5 5 28 1 1 3! 22 35 13 8 5! 3 119 4 1 3 22 37 13 8 5 3 10
10 3 1 3 22! 35 13 8 3 3 12!11 5 6 3 22 35 13 8 5 6 212 8 2 3 22! 35 13 8 5 7 213 5! 6 3 22 35 13 8 3 7! 1014 10 2 3 22 35 13 8! 2 3 315 1 4 5 22 35! 13 8 5 7 3
! phase unknown
75
Of the 10 Canadian patients, 9 share a region of at least 5 cM, surrounding the
A455E mutation (Figure 1). The patients 1, 2 and 3 share a region of more than 25
cM. With a different haplotype this is also the case for patients 4, 5 and 6. The
haplotype of the intragenic markers of 14 of the 15 Dutch patients are identical to
the Canadian patients. They share a region of more than 4 cM surrounding A455E
(Figure 2). The remaining patient showed a different intragenic haplotype (22-37-
13). The haplotypes of the non-A455E chromosomes of the Canadian and Dutch
patients are shown in Table 3.
Table 3. Microsatellite haplotypes for independent∆F508 and 621+1G→T chromosomes from a FrenchCanadian and a Dutch population.
5 3 2 Intragenic 1 6 8 (cM)^ ^ ^ / \ ^ ^ ^
D7S-635 490 480 8CA 17BTA 17BCA 486 523 501 518
French Canadianchromosomes
2 621+1G→T 1 4 5 21 31! 13 8 5! 7 33 621+1G→T 1 4 5 21 31 13 8 5 1! 66 621+1G→T 1 4 5! 21 31 13 8 5 7! 59 621+1G→T 1! 4 5 21 31 13 8 5 5 21 DF508 9! 3 1 17! 32! 13 8 7 1 37 DF508 9! 3 1 17! 32 13 8 1 5 24 DF508 7! 4 1 17! 32 13 8 7 1 45 DF508 9 6 7 17! 32 13 5 5 7 58 DF508 2 4 3 17 35 17 3 5! 8 7
10 DF508 8 4! 2 23 31 13 11 5 3 4
Dutchchromosomes
5 DF508 6 1 6 17 31 13 10 4 3 27 DF508 1 6! 8 17 31 13 10 6 5 98 DF508 4 2 7! 17 31 13 10 3! 6 11
15 DF508 1 6 5 17 31! 13 10 2 7 41 DF508 4 1 3 17 31! 13 3 3 4 29 DF508 9 6 3 17 31 13 8 4 1 76 DF508 7 3 3 17! 32 13 8 2 1 2
11 DF508 1 4 7 17 32 13 8 6 5 914 DF508 1 2 1 17 32 13 5! 3 7 74 DF508 3 3 2 17 35 17 10 5 4 2
12 DF508 8 1 2 17! 35 17 10 2 7 413 DF508 4! 1 5 17 47 13 10 4 8! 33 DF508 1 2 1 23 31 13 8 5 5! 10!
! phase unknown
76
Dystrophia and rickettsia genes has been demonstrated [20]. The only aberrant
dutch haplotype (22-37-13) can best be explained by independent introduction,
although there is also a possibility of a mutation in the original haplotype.
The ∆F508 mutation is a very old mutation, which has been introduced at
least 52,000 years ago in Europe [21]. Much variation is observed in intragenic
markers, which is probably due to repeat length mutations subsequent to the dF508
mutation. This most frequent CF mutation has been widely distributed in especially
Caucasian populations over a long period of time. In the Saquenay-Lac St.Jean
region we detected three different intragenic haplotypes in only six patients with a
∆F508 mutation. This means that there were most likely multiple independent
introductions of the∆F508 mutations in this population. Sharing of DNA regions
surrounding∆F508 mutations is limited to individuals with the same haplotype of
intragenic markers. The observed intragenic haplotypes are also the most common
haplotypes in Europe [21]. To detect haplotype sharing surrounding∆F508
mutations, more observations with identical intragenic haplotypes are necessary.
If the size of a shared haplotype is large, the common predecessor must be
quite recent. The difference in the extent of sharing found for the∆F508 mutation
and for the other mutations, shows that haplotype sharing can be expected to occur
only if there are not too many independent introductions of a gene in the
population. Haplotype sharing and other association studies can therefore be
expected to be successful in founder populations of a proper size relative to the
gene frequency. Independent introduction of about 10-20 copies will because of
genetic drift lead to perhaps 1-4 copies remaining in widely varying numbers of
individuals after 8 or more generations. This is in agreement with the theoretical
expectation according to Fisher [22], who computed that the probability of survival
of a single gene after 10 generations in a stable population is about 10%. It appears
from the French Canadian genealogical data, that gene flow cannot be traced back
to unique predecessors, even if all genealogical data are complete. The informativity
of genealogical data seems therefore limited in comparison to what is being learned
from direct haplotype comparison.
The similarity in intragenic ∆F508 haplotypes in the two populations
suggests multiple introduction of the same intragenic haplotypes, of which some
have survived. In Finland genetic drift has by this process led to a low CF
frequency and to a distribution of mutations different from that of the rest of
79
Europe [23].
The suitability of a population for haplotype sharing studies will increase if
there is a larger population with which the founder population is connected. Once a
genomic region has been identified which possibly contains an allele predisposing
to a disease, it is easy to perform a genome screening in affected individuals at the
1 cM level. This situation seems to exist both for the French Canadians and in The
Netherlands, where more isolated areas are connected with larger populations. At
the genomic distances of 1 cM association and linkage disequilibrium can be
detected in populations much larger than the one originally investigated. At the
same time, a large number of meioses is being observed implicitly, thus narrowing
the region where the gene must be located. This is well illustrated from the
consistent overlap shown in and between Figures 1 and 2. In The Netherlands, the
A455E data come from an unselected population, which shows that for rare genes,
such as the A455E mutation, founder effects are present at the population level. A
complication in haplotype comparison is marker allele mutation. In this dataset we
probably observe two such mutations (the Dutch patients number 7 and 9 show an
allele mutation in the microsatellites D7S486 and IVS17BTA, respectively) where
the haplotype for surrounding markers seems to be conserved.
The present study shows that the suitability of populations for gene mapping
through direct haplotype comparison can be investigated using some of the well
known recessive disease mutations that can easily be detected at the level of
carriers. These mutations have generally a quite high frequency, as would be
expected for alleles of genes involved in multifactorial diseases. By relating the
gene frequency to the size of the shared haplotypes, an impression can be obtained
whether haplotype sharing analysis can be used to find the map location of other
genes.
Acknowledgements
The authors thank Dr. J.P. Heyerman (Leyenborg Hospital, The Hague) for sending
DNA of the parents of Dutch CF patients. This study was made possible by a grant
from The Netherlands Organization for Scientific Research (NWO).
80
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9. Heyer E and Tremblay M: Variability of the genetic contribution of Quebec population foundersassociated to some deleterious genes. Am J Hum Genet 1995;56:970-978.
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13. Ten Kate LP: Cystic fibrosis in The Netherlands. Int J Epidem 1977;6:23-35.
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15. Scheffer H, Verlind E, Penninga D, Te Meerman G, Ten Kate LP, Buys CHCM: Rapid screening for∆F508 deletion in cystic fibrosis. Lancet 1989:1345-1346.
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17. Zielenski J, Bozon D, Kerem B, Markiewicz D, Durie P, Rommens JM, Tsui L-C: Identification ofmutations in exons 1 through 8 of the cystic fibrosis transmembrane conductance regulator (CFTR) gene.Genomics 1991;10:229-235.
18. Zielenski J, Markiewicz D, Rininsland F, Rommens JM and Tsui L-C: A cluster of highly polymorphicdinucleotide repeats in intron 17b of the CFTR gene. Am J Hum Genet 1991;49:1256-1262.
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20. Bétard, C, Raeymaekers P, Ouellette G, Jomphe M, Labuda M, Glorieux F, Mathieu J, Laberge C,Cassiman J-J, Sandkuijl LA and Gauvreau D: The validation of a novel linkage disequilibrium mappingtechnique on Steinert myotonic dystrophy and pseudovitamin D deficient rickets in a founder population.Med Genetik 1995;2:238 (abstract).
21. Morral N, Bertranpetit J, Estivill X, Nunes V, Casals T, Giménez J, Reis A, Varon-Mateeva R, Macek JrM, Kalaydjieva L, Angelicheva D, Dancheva R, Romeo G, Russo MP, Garnerone S, Restagno G,Ferrari M, Magnani C, Claustres M, Desgeorges M, Schwartz M, Schwartz M, Novelli G, Ferec C, DeArce M, Nemeti M, Kere J, Anvret M, Dahl N and Kadasi L: The origin of the major cystic fibrosismutation (∆F508) in European populations. Nature Genet 1994;7:169-175.
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82
Summary
This thesis describes the application of molecular techniques in population genetic
studies of cystic fibrosis (CF), the most common serious autosomal recessive
disorder affecting Caucasian populations. Birth prevalences in European countries
range from 1 in 1700 to 1 in 40,000. The disease is characterized mainly by chronic
obstruction and infection of the respiratory tract, meconium ileus, pancreatic
insufficiency, and elevated levels of sweat electrolytes (Chapter 1). The gene
responsible for CF has been identified in 1989. It has been named cystic fibrosis
transmembrane conductance regulator (CFTR) gene, is located on the long arm of
chromosome 7, is approximately 230,000 kb in size, and contains 27 exons. Thus
far more then 500 mutations have been identified in the CFTR gene. A variety of
mechanisms has been suggested to account for the high CF carrier frequency of 1 in
21 to 1 in 100 in the Caucasian population: genetic heterogeneity, high mutation
rate, genetic drift, meiotic drive, increased fertility of CF carriers, heterozygote
advantage and segregation distortion of CF alleles.
Approximately 75% of the CF chromosomes in The Netherlands harbour a
three basepair deletion in CFTR, which removes the phenylalanine residue at amino
acid position 508 of the CFTR polypeptide (∆F508). This mutation can easily be
detected by the polymerase chain reaction (PCR) - amplification of the flanking
DNA-sequence - and subsequent gel electrophoresis of the amplfied product. In
most laboratories blood is used as the source for DNA isolation. Blood sampling
and DNA isolation in great numbers have, however, a few disadvantages: costs of
DNA isolation are high, (para)medical personnel is necessary for blood collection,
people may shrink from venapuncture, and there is a risk of exposure to blood
pathogens. An alternative is sampling of mouthwashes followed by DNA isolation
from buccal cells. This procedure is much simpler and cheaper than existing
methods, especially with large numbers of samples. There is no need for medical
supervision of sample collection, and the risk of infections is eliminated.
For the validation of the mouthwash procedure, we collected a total of over
11,000 mouthwashes and matched blood samples from 15 blood banks and also 75
mouthwashes of known CF carriers (Chapter 2). Both the specificity and the
sensitivity of the mouthwash procedure were 100%. The overall failure rate was 1.8
85
% (excluding the results of one particular blood bank with a markedly high failure
rate). These results indicate that for large numbers of samples the mouthwash
procedure is suitable for mutation detection and can be used in community
screening.
We used the samples above to determine the prevalence of carriers of the
∆F508 mutation. The∆F508 carrier frequency in The Netherlands turned out to be
1 in 42, which gives an estimated overall CF carrier frequency of 1 in 31. This CF
carrier frequency is significantly less than the generally quoted frequency for
Europe of 1 in 25. Logistic regression analysis revealed possitive relationships
between the∆F508 carrier frequency and the region of residence, age of the blood
donors, and number of children of the blood donors. The distribution of the carrier
frequency displayed a geographical gradient in the∆F508 carrier frequency with
high prevalences in the southern part and low prevalences in the north-east of the
country. The positive relation of age and family size with the carrier frequency may
be explained as a consequence of hetrozugote advantage, but should be confirmed
in further studies.
Chapter 4 describes the frequency and distribution of the non-∆F508
mutations in The Netherlands. Thusfar, 17 less frequent mutations have been
detected. The A455E mutation with a relative frequency of about 2.8 % has
predominantly been detected in the south-western parts of The Netherlands.
A possible explanation for the high prevalence of cystic fibrosis in the
Caucasian population is a high fertility of CF carriers. We collected data from more
than 7000 blood donors to determine the sex ratio and number of offspring of
∆F508 carriers and non-carriers (Chapter 5). We were unable to detect significant
differences between both groups. This means that we cannot support the hypothesis
of increased fertility of CF carriers.
The A455E mutation, which is associated with a less severe CF phenotype,
has mainly been detected in Canada (in a subpopulation in northeastern Quebec -the
Saguenay-Lac St.Jean region) and in The Netherlands (south-western parts). The
concentration of the mutation indicates that it has been introduced not very long
ago. The A455E mutation therefore, may be suitable for a haplotype sharing
analysis between ’unrelated’ CF patients. DNA of 15 independent Dutch and 10
French Canadian CF patients with the A455E mutation were collected for haplotype
analysis. Each group of CF patients with the A455E mutation, shared a common
86
haplotype both intragenic and extragenic over distances up to 25 cM. In contrast,
the haplotypes of the∆F508 mutation showed much shorter haplotype identity
within and between these populations, probably due to multiple introduction of this
very old, but common mutation. The method of haplotype comparison for CF is a
model for studying the occurrence of genetic drift conditional on gene frequencies,
and indirectly demonstrates the suitability of empirical populations for genetic
mapping by haplotype sharing analysis.
87
Samenvatting
In elke menselijke cel met een kern bevinden zich 23 paar chromosomen.
Chromosomen bestaan voor een groot gedeelte uit DNA. Maar een klein gedeelte
(3%) van dit DNA komt in eiwitten tot expressie. Het DNA is een keten van
bouwstenen. Er zijn vier verschillende bouwstenen en de volgorde hiervan in het
DNA is bepalend voor de eigenschappen van ons lichaam. Elk chromosomenpaar
bevat een chromosoom van de moeder en één van de vader. De aanleg voor elke
eigenschap op de autosomen is daardoor in tweevoud aanwezig. Een stuk DNA met
de informatie voor een erfelijke eigenschap noemen we een gen. Bij de mens
komen 50.000 - 100.000 genen voor. In bepaalde gevallen kunnen er veranderingen
(mutaties) optreden in de DNA volgorde van de genen. Als deze mutaties
voorkomen in de voortplantingscellen, dan kunnen ze doorgegeven worden aan de
volgende generatie.
Cystic fibrosis (CF), ook wel taaislijmziekte genoemd, is een erfelijke
aandoening die zich meestal in de eerste levensjaren openbaart. De ziekte gaat ge-
paard met herhaalde longontstekingen, spijsverteringsproblemen en een te zout
zweet. Deze aandoening komt voornamelijk voor bij blanken (de Caucasische
volkeren). CF is een ernstige en nog niet te genezen ziekte. Door een zorgvuldige
behandeling kunnen de symptomen van CF steeds beter bestreden worden. Het
aantal patiënten in de volwassen leeftijd neemt dan ook toe, hoewel nog steeds pati-
enten op jeugdige leeftijd overlijden. In Nederland komt CF voor bij ongeveer 1 op
de 3600 kinderen. CF is een recessieve aandoening. Dit wil zeggen dat de ziekte
zich pas openbaart als zowel van de vader als van de moeder een chromosoom met
een mutatie in het CF-gen wordt verkregen. Er wordt gesproken van dragerschap
voor CF wanneer een CF mutatie in enkelvoud aanwezig is (ook deze is weer af-
komstig van de vader óf van de moeder). Dragers hebben naast de afwijkende
aanleg een normale aanleg die sterker is dan de afwijkende. Dragerschap voor CF
heeft dan ook geen gevolgen voor de eigen gezondheid. In Nederland is ongeveer 1
op de 30 mensen drager van CF.
In 1989 hebben onderzoekers de bouwsteen volgorde van het CF gen kunnen
bepalen. Hierdoor is het mogelijk geworden om mutaties in dit gen aan te tonen.
Dit is van groot belang voor het opsporen van CF patiënten en dragers. Het CF gen
is een relatief groot gen. Tot nu toe zijn er al meer dan 500 verschillende mutaties
89
in dit gen gevonden. De meest voorkomende mutatie is de∆F508 (spreek uit delta
F508) mutatie die in Nederland bij ongeveer 75% van de afwijkende CF-genen
wordt gevonden. De verschillende mutaties, maar ook andere invloeden, kunnen
voor een van patiënt tot patiënt wisselend ziektebeeld zorgen. Hierdoor is het voor
artsen soms zeer lastig om louter op grond van symptomen vast te kunnen stellen of
iemand CF heeft. Met behulp van DNA technieken is het veelal mogelijk om in
twijfelgevallen de diagnose CF te bevestigen of ontkrachten. Tevens kan door
middel van DNA onderzoek dragerschap vastgesteld worden. Er kan dan bekeken
worden of een (echt)paar dat kinderen wil, een risico (25%) op CF bij hun
kind(eren) heeft. In geval van een risico-zwangerschap is het mogelijk om door
middel van een vruchtwater punctie of een vlokkentest te onderzoeken of het kind
wel of niet CF zal krijgen.
In een in dit proefschrift beschreven onderzoek is gekeken naar het vó-
órkomen van CF dragers en patiënten in Nederland. Het onderzoek kan opgesplitst
worden in vijf delen. 1) Bepaling van de betrouwbaarheid van DNA isolatie uit
mondspoelsels. 2) Vaststellen van het aantal dragers van de∆F508 mutatie in
verschillende regio’s in Nederland. 3) Onderzoek naar de verspreiding van niet-
∆F508 mutaties. 4) Vergelijking van het aantal en het geslacht van kinderen van
∆F508 dragers en niet dragers. 5) Vergelijking van stukken DNA van Nederlandse
en Frans Canadese CF patiënten met een A455E mutatie.
1) DNA wordt gewoonlijk uit bloed geïsoleerd. Er zijn echter enige nadelen
verbonden aan het nemen van bloedmonsters voor het onderzoeken van grote
aantallen personen: de kosten voor de DNA isolatie zijn relatief hoog, de
bloedafname moet plaatsvinden door (para) medisch personeel, mensen zien er
tegenop om geprikt te worden, en er is een klein gevaar van besmetting voor zowel
de donor als de onderzoeker. Een alternatief voor bloedmonsters is de
mondspoelselprocedure. Door middel van het spoelen van de mond met zout water
worden wangslijmvlies cellen verkregen, waaruit DNA geïsoleerd kan worden. In
dit onderzoek werden meer dan 11.000 bloeddonoren bereid gevonden een
mondspoelsel af te staan. In 94.4% van alle gevallen was het mogelijk DNA hieruit
te isoleren. Het relatief grote aantal mislukte DNA isolaties was voor het merendeel
het gevolg van het onvoldoende spoelen bij één bepaalde bloedbank. Na het
weglaten van deze resultaten van die bloedbank steeg het percentage succesvolle
DNA isolaties naar 98.2%. In die gevallen waarin de∆F508 mutatie werd
90
aangetoond in mondspoelsel DNA, werd de uitslag gecontroleerd door DNA isolatie
uit een bijbehorend bloedmonster. In al deze gevallen was het mogelijk om de
dragerschap te bevestigen. Tevens werden 75 mondspoelsels van bekende∆F508
dragers onderzocht om te bepalen of in alle gevallen deze mutatie ook aan te tonen
was. In 73 mondspoelsels werd dragerschap bevestigd. Uit twee mondspoelsel kon
geen DNA worden geïsoleerd. Hieruit blijkt dat de mondspoelsel procedure een
betrouwbare en geschikte methode is voor DNA bepalingen bij grote aantallen
personen (hoofdstuk 2).
2) Met behulp van deze mondspoelsels was het mogelijk om voor het hele
land en per provincie het aantal dragers voor de∆F508 mutatie te bepalen. In heel
Nederland bleek 1 op de 42 personen deze mutatie te hebben. Als dit omgerekend
wordt naar de totale dragerschapsfrequentie, dus ook de dragers meerekenend die
een andere CF mutatie hebben, dan komt dit neer op 1 op 31. Met behulp van een
statistisch reken programma werd aangetoond dat de dragerschapsfrequentie in het
zuiden hoger was dan in het noorden van Nederland. Tevens werd gevonden dat
leeftijd en aantal kinderen positief gerelateerd was met de dragerschapsfrequentie.
Dit wil zeggen dat oudere personen met een gezin een grotere kans hebben om
drager te zijn van de∆F508 mutatie dan jongere mensen zonder kinderen. Deze
resultaten zouden kunnen wijzen op een heterozygoot voordeel. Heterozygoot
voordeel wil zeggen dat dragers van de mutatie beter beschermd zijn tegen
bijvoorbeeld het (ver)krijgen van bepaalde besmettelijke ziektes. Voordat er echter
voorbarige conclusies getrokken worden uit deze resultaten is het van belang om ze
eerst te bevestigen in onafhankelijk onderzoeken (hoofdstuk 3).
3) Hierboven werd al vermeld dat in eerder onderzoek in Nederland in 75 %
van alle CF mutaties de∆F508 werd aangetoond. Tot nu toe zijn 17 andere mutaties
in Nederland aangetoond met elk een relatieve frequentie van minder dan 3%. Om
de verspreiding van deze mutaties in Nederland te onderzoeken, werden gegevens
over de woonplaatsen van de CF patiënten verzameld (hoofdstuk 4). Deze gegevens
vormden tevens een aanvulling op de verspreiding van CF dragers in Nederland. Uit
dit onderzoek bleek dat ook andere niet-∆F508 mutaties niet willekeurig over
Nederland verspreid waren. Met name de A455E mutatie, met een frequentie van
2.8% werd voornamelijk in Zeeland en Zuid-Holland aangetoond. De geringe ver-
spreiding leverde een vervolg onderzoek op naar de oorsprong van deze mutatie, dat
beschreven wordt in hoofdstuk 6.
91
4) Er is veel onderzoek uitgevoerd om een verklaring te vinden voor de hoge
frequentie van CF bij de Caucasische bevolking. Twee mogelijke theorieën zijn: a)
een heterozygoot voordeel en b) een verhoogde fertiliteit van dragers. Een bekend
voorbeeld van heterozygoot voordeel is dragerschap voor sikkelcel-anemie, wat
bescherming biedt tegen malaria. In geval van CF zouden de dragers mogelijk
minder kans hebben op het krijgen van cholera. Dit voordeel is echter bij de mens
nog niet aangetoond. Verhoogde fertiliteit (vruchtbaarheid) van dragers betekent dat
CF dragers meer kinderen zouden krijgen dan niet-dragers. In hoofdstuk 5 is een
onderzoek beschreven waarin het geslacht en het aantal kinderen van∆F508 dragers
en niet-dragers met elkaar vergeleken worden. Er werd geen verschil aangetoond
tussen beide groepen. Dit betekent dat de tweede theorie met dit onderzoek niet
ondersteund kan worden. Voor het verwerpen ervan zijn echter grotere aantallen
nodig.
5) Uit een onderzoek waarbij gegevens werden verzameld van CF patiënten
uit heel Europa kwam naar voren dat de∆F508 mutatie waarschijnlijk minstens
52,000 jaar oud was. De mutatie zou zijn geïntroduceerd in Europa vanuit Klein
Azië. De minder frequente mutaties zijn waarschijnlijk veel minder oud. Dit is te
zien aan de geringere verspreiding van deze mutaties in verschillende landen. De
A455E mutatie is bijvoorbeeld alleen veelvuldig aangetoond in het zuiden van
Nederland en in een Frans-Canadese populatie in Canada. Om uit te zoeken of
patiënten met deze mutatie in de verre verte familie van elkaar zijn, werd het DNA
in de regio rondom het CF gen bij deze patiënten onderling vergeleken. Personen
die nauw met elkaar verwant zijn zullen namelijk een groter stuk DNA
overeenkomstig hebben dan personen waarbij dit niet het geval is. De methode
waarbij DNA regio’s vergeleken worden bij patiënten met een identieke erfelijke
aandoening wordt IBD mapping genoemd. IBD staat voor "Identity By Descent" en
betekent "overeenkomst door afstamming". Deze methode kan ook gebruikt worden
voor het opsporen van nog onbekende genen. Hiervoor is DNA nodig van patiënten
met een één en dezelfde erfelijke aandoening, die afkomstig zijn uit eenzelfde
gebied. Alle chromosomen worden dan onderzocht om vergelijkbare DNA regio’s te
vinden. In deze regio’s kan het verantwoordelijke gen zich bevinden. Omdat de
A455E mutatie bijna uitsluitend in de bovengenoemde populaties is gevonden, zijn
patiënten met deze mutatie uit die populaties zeer geschikt om de IBD methode te
testen. Uit het onderzoek bij 15 Nederlandse en 10 Frans-Canadese patiënten bleek
92
dat een klein stukje DNA rondom het CF gen in alle gevallen identiek was. Bij een
aantal Frans Canadese patiënten werden zelfs vrij grote overeenkomstige stukken
DNA aangetoond. Bij de Nederlandse patiënten waren deze DNA regio’s iets korter,
maar er was wel een duidelijke verwantschap met de Canadese patiënten. Mogelijk
hebben deze patiënten dan ook dezelfde voorouder en is de mutatie vanuit Frankrijk
in Nederland en in Canada terecht gekomen. Uit de resultaten blijkt dat de IBD
methode in founderpopulaties, dat wil zeggen geïsoleerde kolonies die ontstaan zijn
uit fracties van grotere oorspronkelijke populaties, goed toepasbaar is (hoofdstuk 6).
93
Curriculum vitae
Name: Hendrik Gerardus de Vries
Date of birth: April 14, 1965
Place of birth: Roosendaal
1978-1984 HAVO, Leeuwarden
1984-1988 Hogere Laboratorium Opleiding, Leeuwarden
Specialization: medical microbiology
1988-1991 Medical biology, University of Groningen
1991-1995 PhD student on a project funded by the Netherlands
Organization for Scientific Research (NWO). Validity and yield
of a screeningtest for the detection of carriers of the cystic
fibrosis gene. Department of Medical Genetics, University of
Groningen, The Netherlands.
94
Dankwoord
In de afgelopen vier jaar hebben een groot aantal personen er voor gezorgd dat mijn
onderzoek geresulteerd heeft in dit proefschrift. Al deze personen wil ik hartelijk
bedanken voor hun aandeel. Een aantal van hen wil ik bij name noemen. In de
eerste plaats Leo ten Kate. Hoewel jij in Amsterdam niet altijd even goed te
bereiken was, heb je wel de tijd gevonden voor de evaluaties van dit project en de
kritische beschouwingen van de manuscripten. Tot mijn grote spijt ben ik er niet
aan toe gekomen om oude botten te onderzoeken. Charles Buys, nadat jij positief
had gereageerd op het verzoek om als co-promotor op te treden, was jij bereid om
mij met raad terzijde te staan. Hans Scheffer wil ik bedanken voor de praktische
begeleiding van dit project. Hierdoor was ik in staat om mijn onderzoek in
Groningen voort te zetten.
Dit project was geheel afhankelijk van de spontane medewerking van alle
bloedbanken, het CLB en alle bloeddonoren. In het b zonder wil ik Dr C.Th. Smit
Sibinga, directeur van de bloedbank Noord-Nederland, bedanken voor zijn bijdrage
aan de opzet van deze studie.
Zonder de hulp van een aantal analisten was ik nooit in staat geweest om dit
project tot een goede einde te brengen. Bart Mol, wiens muziek keuze toch niet de
mijne was; Marjan van Veldhuizen, die als echte Friezin in het verre Amsterdam
haar experimenten uitvoerde; Wilma Meeuwsen, die vol enthousiasme over haar
kinderen kon vertellen en Jolanda Kliphuis, met wie ik veel gesprekken heb gehad
op ons labzaaltje. Hoewel dit project praktisch niet altijd even interessant was,
hebben jullie mij een hoop werk uit handen genomen. Hiervoor mijn hartelijke
dank.
Margriet Collée, ik ben jou zeer erkentelijk voor jouw aandeel in dit project.
Je hebt heel wat afgereisd om alle bloedbanken te benaderen en her en der praatjes
te verzorgen. Jij hebt mij doen inzien dat er met artsen toch een goede
samenwerking mogelijk is. Gerard en Martin kwamen met het idee om IBD toe te
passen op CF patiënten en dragers. Deze samenwerking resulteerde in een inte-
ressant artikel. Rima Rozen en Dicky Halley waren bereid om DNA’s van CF
patiënten naar mij op te sturen. Edwin wil ik bedanken voor de ALF resultaten.
Mentje en Tinke W ben ik zeer erkentelijk voor het feit dat ze niet geërgerd waren
(of dat althans niet lieten merken) wanneer ik zo’n tien maal per dag hun kamer
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binnen stormde. Ze waren ook altijd spontaan bereid om een onwetende OIO te
helpen met zijn problemen. Menke wil ik bedanken voor het in no time klaarmaken
van mooie dia’s. Hermien was bereid om in de laatste fase "multiple logistische
regressie" los te laten op mijn resultaten. De term alleen al misstaat niet in een
artikel. Ik wil je hierbij van harte bedanken voor deze bijdrage. Eva Pliester bedank
ik voor het invoeren van de onderzoeksgegevens in de computer.
Gerrit, ik vond het bijzonder leuk om "de meest populaire collega" als
kamergenoot te hebben. Dank zij jou heb ik niet alleen meer inzicht gekregen in
"the never ending story" van SMA, maar mijn bridge spel is nu ook sterk verbeterd.
Verder wil ik alle collega’s van de vakgroep Medische Genetica bedanken
voor de prettige tijd die ik hier heb doorgebracht.
De leden van de promotie commissie Prof J.J. Cassiman, Prof A. Hofman en
Prof H.S.A. Heymans wil ik bedanken voor het lezen van de thesis.
Mijn ouders hebben mij altijd gestimuleerd om te gaan studeren. Zonder die
steun had ik die stap waarschijnlijk niet genomen. Ook voor hun betrokkenheid
tijdens mijn promotie project ben ik hen bijzonder dankbaar.
Regina (Ient), je weet het.
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