© 2001 Oxford University PressHuman Molecular Genetics, 2001, Vol. 10, No. 26 2961–2972
Dissecting a population genome for targeted screening
of disease mutations
Tomi Pastinen1, Markus Perola1,2, Jaakko Ignatius3,4, Chiara Sabatti2, Päivi Tainola1,
Minna Levander1, Ann-Christine Syvänen1,5 and Leena Peltonen1,2,4,*
1Department of Molecular Medicine, National Public Health Institute, Biomedicum, 00250 Helsinki, Finland,
2Department of Human Genetics, University of California, Los Angeles, CA 90095-7088, USA, 3Department of Clinical
Neurophysiology, Helsinki University Hospital (Jorvi Hospital), 02740 Espoo, Finland, 4Department of Medical
Genetics, University of Helsinki, 00250 Helsinki, Finland and 5Molecular Medicine, Department of Medical Sciences,
S-751 85 Uppsala, Sweden
Received August 6, 2001; Revised and Accepted October 10, 2001
Compared to mixed populations, population isolates such as Finland show distinct differences in the
prevalence of disease mutations. However, little information exists of the differences on the prevalence of differ-
ent disease alleles in regional populations with different history of multiple bottlenecks. We constructed a
DNA-array and monitored the prevalence of 31 rare and common disease mutations underlying 27 clinical
phenotypes in a large population-based study sample. Over 64 000 genotypes were assigned in 2151 samples
from four geographical areas representing early and late settlement regions of Finland. Each sample was
analyzed in duplicate and a total of 142 000 array-derived genotyping calls were made. On average one in
three individuals was found to be a carrier of one of the 31 monitored mutations. This should remove fears of the
stigmatizing effect of a carrier-screening program monitoring multiple diseases. Regional differences were found in
the prevalence of mutations, providing molecular evidence for the deviating population histories of regional
subisolates. The mutations introduced early into the population revealed relatively even distribution in differ-
ent subregions. More recently introduced rare mutations showed local clustering of disease alleles, indicating
the persistence of population subisolates and the effect of multiple bottlenecks in molding the population gene
pool. Regional differences were observed also for common disease alleles. Such precise information of the carrier
frequencies could form the basis for targeted genetic screens in this population. Our approach describes a
general paradigm for large-scale carrier-screening programs also in other populations.
DNA variants in over 1000, mostly monogenic, traits have
been identified (1). Identification of mutations has not resulted
in immediate DNA diagnosis due to the high heterogeneity of
disease alleles. Isolated populations provide special advantages
for DNA diagnostics and carrier-screening programs due to a
limited spectrum of disease mutations; one test having high
diagnostic specificity and sensitivity (2,3). Targeted screening
of ethnically restricted disease mutations in the appropriate
population subgroups has demonstrated its efficiency in
disease prevention (4). However, for most populations,
rational design of genetic-screening programs requires large
population-based pilot studies to monitor for the diversity and
prevalence of specific disease mutations.
DNA-array technology is a promising approach to monitor
large numbers of sequence variants in one assay (5–8). If a
moderate number of variants in a large number of samples are
to be analyzed, a custom-made, spotted oligonucleotide arrays used
for enzymatic allele discrimination provides a high-throughput
system (8). Such arrays are flexible and can be tailored for
population-specific carrier screening of several disease variants.
Information on the frequency and regional distribution of
individual disease mutations as well as the validation of array-
based assays must exist before such tests can be implemented
population-wide as a standard component of the health care
We constructed a DNA-array for the detection of 31 mutations
in a study sample of 2400 individuals from different geographical
*To whom correspondence should be addressed at: UCLA Department of Human Genetics, Gonda Neuroscience and Genetics Research Center,
Room 6506, 695 Charles E. Young Drive South, Box 708822, Los Angeles, CA 90095-7088, USA. Tel: +1 310 794 5631; Fax: +1 310 794 5446;
Tomi Pastinen, Montreal Genome Centre, Montreal, H3G 1A4 Quebec, Canada
2962 Human Molecular Genetics, 2001, Vol. 10, No. 26
regions of Finland to monitor for the regional differences in the
prevalence of disease alleles. The majority of the mutations
included on the array, ‘the Finnish Chip’, are recessive disease
mutations enriched in the Finnish population, belonging to the
‘Finnish disease heritage’. In addition, we incorporated to the
array some disease mutations common in most Caucasian
populations, like mutations of α-1-antitrypsin, factor V and the
hereditary hemochromatosis gene.
We did not include on the array dominant disease mutations
like those of hereditary breast and ovarian cancer (BRCA1 and 2),
familial non-polypotic colon cancer or familial hypercholes-
terolemia due to their rarity. Recent studies in cancer patients
(9,10) or population-based surveys (11) demonstrate the low
prevalence of these mutations in the Finnish population
The microarray-based primer extension assay proved to be
highly robust and provided reliable genotyping results at a
relatively low cost. Interestingly, we found distinct regional
differences in the carrier frequency of both rare and common
disease mutations within this genetically homogeneous,
isolated population, the findings providing support for multiple
historical population bottle necks. The population-wide
carrier frequency of disease alleles detected by this panel of
31 mutations was 1:3, illustrating the prediction that if a
wider panel of disease mutations were to be included on the
array, every Finn would be a carrier of at least one of the
tested disease mutations. This should alleviate fears of the
stigmatizing effect of carrier-screening programs monitoring
numerous disease mutations.
Mutations screened with the DNA array
The mutation-screening panel on the DNA-array comprised
the known major mutations of Finnish diseases (12), a total of
19 mutations in 16 different genes. Most mutations show a
strong founder effect and the coverage of the mutation detection
varied between 74 and 99% for different diseases. The
common Caucasian mutations consisted of 10 mutations in
nine genes including two common polymorphisms of factor V
(13) and the prothrombin gene (14). A list of the mutations
included on the array as well as the corresponding diseases and
OMIM symbols are provided in Table 1. A pair of allele-specific
detection primers for each of the mutations was spotted on
derivatized microscopic glass-slides (8). Eighty replicate
arrays were spotted onto each slide and custom-made reaction
chambers were used to analyze up to 80 separate samples per
slide. This facilitated the monitoring of 2480 mutations (31
genotypes for 80 individuals) on a single microscopic glass
slide (Fig. 1). The allele-specific primer extension reactions
provided reliable discrimination between the obtained genotypes
We determined the carrier frequencies of disease mutations
by genotyping 2151 anonymous DNA samples from four
geographical regions (Fig. 2). One rural sample was collected
from southern Botnia, representing the ‘early settlement’
region, which was inhabited some 2000 years ago. Another
rural sample was collected from North Karelia, representing
the ‘late settlement’ northeastern region, permanently
inhabited after the 16th century. The two urban community
samples were from Helsinki and from the city of Oulu on the
northwestern coastline. Both of these cities have been targets
for internal population movement during the past eight to nine
decades. However, according to Y chromosomal haplotype
analysis, the influence from early immigration from Western
Europe is much less evident in Oulu region than in southern
Finland (15). Further, immigration to Helsinki, the capital, has
been much more excessive than to Oulu. As positive controls,
212 samples from carriers of the disease mutations were allo-
cated blindly among the study samples.
Quality of the data from the arrays
Each sample was amplified by PCR and assayed in duplicate
on separate microarrays. The genotyping results for each
sample were read and the genotypes were independently
assigned from the two arrays. Moreover, the genotypes were
called on coded samples, without knowledge of the sample
status to serve as quality control of the array-based screening
procedure. The reference methods were systematically used to
verify the genotyping result if a sample indicated a carrier
status, if the results from the duplicate assays were discrepant
or if the signal intensities on a microarray were too low to
assign the genotype. For samples with low signal intensity on
the array, the reference method was performed only once, and
the sample was omitted from further analysis if this reference
assay failed. In the cases of conflicting duplicate genotype
calls and for every carrier genotype sample the reference
method was used to confirm the genotype.
Since each sample was analyzed in duplicate, a total of
142 000 array derived genotyping calls were made. None of
the heterozygous controls was assigned as normal homo-
zygotes. Of the 71 000 genotypes generated, 95% were called
successfully. In 5% of the samples the signal intensities were
too low to make a reliable genotype call, and the reference
methods were used to assign the genotypes. Less than 0.1% of
the samples gave conflicting results in the duplicate array-
based assay, due to inconsistencies resulting from the spotting
of the primer-arrays. The final assignment of genotype in the
study samples was made in 99.15% of cases (64 076 out of
64 625 genotypes were assigned). The genotyping results are
summarized in Tables 2 and 3.
Carrier frequencies of the ‘Finnish disease heritage’
A particularly informative approach to the analysis of the
regional prevalence of the Finnish mutations is to divide them
based on the time of their assumed introduction into the population.
Recent introduction of a disease allele is characterized by the
geographically restricted occurrence of patients, a genealogical
history revealing ancestors in the same communities and a
demonstration of linkage disequilibrium over a wide genetic
interval flanking the disease mutation (12,16). Representative
examples of such mutations in our screen include vLINCL
(17), EPMR (18), Salla disease (19), CCD (20) and two X-linked
retinoschisis (RS) (21) mutations (Table 1). Figure 3 demon-
strates the carrier frequencies of five young mutations in the
four regional samples. Notably, all these mutations show
evidence of local clustering of disease alleles, indicating the
persistence of the subisolates. A striking example of such
clustering is the high frequency (1:44) of the vLINCL mutation
Human Molecular Genetics, 2001, Vol. 10, No. 26 2963
in the southern Botnia sample whereas the carrier frequency in
the ‘mixed’ Helsinki population is only 1:1000. Clustering is
also evident for CCD and Salla disease in which the prevalence
of disease mutation was highest in North Karelia and lowest in
the Helsinki sample. However, the distribution for the Salla
mutation was relatively even across all geographical regions
when compared with vLINCL, which would provide evidence
for a relatively early introduction of Salla mutation to the
Finnish population. Only one of the two major mutations
causing X-linked RS could be detected as one RSOulu carrier
was identified in the Oulu sample. No carriers for the other
mutation, RSPori, were seen in any of our samples, probably
reflecting the fact that the mutation is highly concentrated in a
single community, Noormarkku (21), located in southwestern
Finland and outside the regions sampled for this study. Similar
findings were obtained for EPMR, a rare recessive disease
known to occur in a very restricted region in Kainuu in north-
eastern Finland (18) which was also not covered in the
sampling for the present study.
Somewhat differently from young mutations, the old Finnish
mutations show relatively even distribution of patients and
their carrier frequencies (Fig. 4). The most common of the
Finnish diseases, congenital nephrosis (22), is caused by two
major mutations, CNFmajor and CNFminor, accounting for 78 and
16% of disease alleles, respectively. We found a relatively
even distribution of the CNFmajor allele across all the geographical
Table 1. A list of the mutations included on the array as well as the corresponding OMIM symbols and diseases
aThe reference in which the common Finnish or Caucasian allele included in the mutation-screening panel was described can be found at http://www.ncbi.nlm.nih.gov/
Omim/ [online Mendelian inheritance in man (OMIM). Center for Medical Genetics, Johns Hopkins University (Baltimore, MD) and National Center for Biotechnology
Information, National Library of Medicine (Bethesda, MD); 1999] by using this number.
Mutation Gene name (SYMBOL)OMIM symbola
Common disease name
Autoimmune polyendocrine syndrome, type I
Autoimmune regulator (AIRE)
Down-regulated in adenoma (DRA)
Familial chloride diarrhea
Congenital nephrosis 1, Finnish type
Human sulfate transporter (DTDST)
Ceroid lipofuscinosis, neuronal 8 (CLN8)
Progressive epilepsy with mental retardation
Hyperornithinemia with gyrate atrophy of Choroid and
Aldolase B (ALDOB)
Hereditary fructose intolerance
Tyrosinemia, type I
Infantile neuronal ceroid lipofuscinosis
Fumarylacetoacetate hydrolase (FAH)
Palmitoyl-protein thioesterase (PPT)
Solute carrier family 7, member 7 (SLC7A7)
Lysinuric protein intolerance
Nonketotic hyperglycinemia 1
Hereditary hypergonadotropic ovarian failure
Glycine cleavage system P protein (GCSP)
Follicle-stimulating hormone receptor (FSHR)
Retinoschisis 1 (XLRS1)
X-linked, juvenile RS 1
Sialuria, Finnish type
Variant late infantile neuronal ceroid lipofuscinosis
Solute carrier family 17, member 5 (SLC17A5)
Ceroid lipofuscinosis, neuronal 5 (CLN5)
Common Caucasian mutations
Protease inhibitor 1 (PI)
Cystic fibrosis transmembrane conductance
Coagulation factor V (F5)
227400 Thrombophilia due to deficiency of cofactor for
activated protein C
Neurosensory deafness, autosomal recessive 1
Gap junction protein, β-2 (GJB2)
Phenylalanine hydroxylase (PAH)
Coagulation factor II (F2)
Ceroid lipofuscinosis, neuronal 3
Juvenile neuronal ceroid lipofuscinosis, Batten disease
Long-chain 3-hydroxyacyl-CoA dehydrogenase
Deficiency of medium-chain acyl-CoA dehydrogenase
Hydroxyacyl-CoA dehydrogenase (HADHA)
Acyl-CoA dehydrogenase, medium-chain
252800 Mucopolysaccharidosis type I
2964 Human Molecular Genetics, 2001, Vol. 10, No. 26
regions whereas we saw a significant clustering of the CNF
minor allele in the sample from the early settlement southern
Botnia region (Fig. 4). In this region, the combined carrier
frequency of the two mutations was as high as 1:27 (suggesting
birth incidence of 1:2500), whereas in the other study samples
the combined carrier frequency varied from 1:48 to 1:61. The
second most common Finnish disease is aspartylglucosaminuria,
in which one major mutation (AGUFin) accounts for 98% of
disease alleles (23). Again the carrier frequency varied, the
prevalence being lowest in the old settlement, southern Botnia
region (1:132) and highest in the late settlement North Karelia
(1:63). Diastrophic dysplasia (24), the third most common
representative of Finnish diseases, has a major mutation
identified in 90% of disease alleles. Interestingly we found a
high frequency of the DD major mutation in the regional
samples from North Karelia and Oulu, a finding not expected
based on the results of earlier epidemiological and genealogical
The combined carrier frequency of all tested Finnish mutations
varied between ∼1:11 and ∼1:6 in regional study populations,
being highest in the rural eastern and western study samples.
Mutations common in Caucasian populations
The carrier frequencies for common Caucasian mutations are
shown in Figure 5. The Z-allele of the α-1-antitrypsin gene
revealed a higher prevalence in Helsinki and early settlement
southern Botnia, when compared to the late settlement north-
eastern sample (1:26 versus 1:46). The frequency of the
common mutation of hereditary hemochromatosis, HFEC282Y,
varied across Finland, showing high prevalence in the early
settlement western sample (1:10), with decreasing frequency
in the late settlement northeastern Finland (1:33). An opposite
regional distribution was evident for FVLeiden (13) and
prothrombinG20210A (14), SNPs predisposing to venous thrombo-
embolism. Both were more commonly encountered in the late
settlement sample. Another common disease mutation which
was monitored was a common frameshift mutation in the
connexin 26 gene referred to as GJB2∆35G, resulting in congenital
non-syndromic deafness in several populations (26,27). The
GJB2∆35G mutation had a relatively uniform geographical
distribution across Finland with a carrier frequency of 1:43–1:63.
The combined carrier frequency of the common Caucasian
mutations in Finland varied between ∼1:7 and ∼1:5, being
highest in the rural, early settlement region.
Mutations with exceptionally low prevalence in Finland
We monitored two mutations, ∆F508 and ∆TT394 in the
CFTR gene, reported to account for 45 and 30% of Finnish
CF chromosomes, respectively (28). The carrier rate for the
Figure 1. Examples of screening for Finnish mutations using allele-specific
primer extension on microarrays. A section showing the results from 20 samples
is illustrated. Eighty samples are analyzed per microscope slide with the aid of
rubber grids forming 80 separate reaction wells. On a single slide 2480 genotypes
were scored. Differences in signal patterns indicate mutations, and the six carriers
identified are enlarged with circles around probe pairs with signals indicative of
heterozygosity for the given site. Each array contains a pair of allele-specific
probes for each mutation to be detected, one probe corresponding to the wild-type
allele (odd vertical columns) and another probe corresponding to the mutated
allele (even columns). Carriers are identified by calculating the ratio between
the signal intensities obtained from the wild-type probe sites and the mutant
probe sites for each mutation. The average signal ratios that discriminate
between the genotypes are >10-fold. They vary between the mutations, but are
relatively constant for each mutation. For example, the discrimination against
the z-allele of the α-1-antitrypsin gene is over 20-fold due to the low background
signal for the mutant probe in row four, column six of the array in non-carriers
and high signal intensities at this site in carriers of the mutation. The non-carriers
of the common mutation underlying lysinuric protein intolerance show relatively
high background signals at the mutant probe sites in row eight, column two, but
the very high signal intensity from the wild-type probe in non-carriers discriminates
the carriers from non-carriers by 5-fold differences in signal ratios. The accuracy
of genotype discrimination by our microarray system for this set of mutations was
validated previously in a sample of >400 individuals including known carriers in
Pastinen et al. (8).
Figure 2. Map of Finland. The geographical areas where the study samples
were obtained are shaded in gray.
Human Molecular Genetics, 2001, Vol. 10, No. 26 2965
CF mutations was low in all study samples, the combined
carrier frequency varying from 1:99 in the western to 1:193 in
the eastern study sample. The common PKU mutation, PAH
R408W, accounts for 50% of Finnish PKU alleles (29). The
Table 2. The genotyping results and extrapolated carrier frequencies
Due to the rarity of some mutations, regional differences in carrier frequencies may be affected by random fluctuation. In Table 3 confidence intervals for
binomial proportions on the base of likelihood evaluations (66,67) are provided for more extensive comparisons of allele frequencies.
aEPMR mutation was included on the array screening at a later phase and only 150 samples from each geographic region were included in the analysis.
bThe first design of the reference method produced false negative results due to amplification of a pseudogene with the selected PCR primers, thus the 500 first
samples analyzed in Helenski were omitted from the data.
cOne homozygote for FVLeiden mutation was found in the Helsinki population.
dTwo homozygotes for HFE C282Y mutation were found in the Southern Botnia population.
Rural areas Urban areas
Early settlement Botnia/western Late settlement North Karelia/eastern HelsinkiOulu
AGU 3963 1:1323857 1:551005 161:63 3654 1:91
APECED3965 1:79 3854 1:9610058 1:1263651 1:365
CCD 3962 1:1983854 1:96 10023 1:334 3630–
395 10 1:40 3858 1:48 100518 1:563655 1:73
3965 1:793850– 10053 1:3353651 1:365
3954 1:993859 1:43 1001141:72 3658 1:46
1490– 1500– 1500– 1480–
3960– 3850– 10050– 3651 1:365
3943 1:131 3843 1:128100215 1:673651 1:365
3963 1:1323851 1:38510057 1:143 3652 1:183
3964 1:993850– 10041 1:10043650–
INCL396 13 1:303859 1:43100412 1:84 3654 1:91
LPI3913 1:130 3854 1:96 97251:1943654 1:91
NKH3912 1:1963853 1:128 10011 1:10013654 1:91
ODG 3950– 3852 1:1939962 1:498 3650–
3950– 3850– 10050– 3650–
3960– 3850– 10040– 3651 1:365
3434 1:86 3856 1:649416 1:15736531:122
VLINCL 3969 1:443851 1:38510001 1:1000 36521:183
39614 1:28 34914 1:39 100538 1:263658 1:46
3960– 3840– 10034 1:251 3652 1:183
39641:99 3852 1:193 10026 1:1673651 1:365
3946 1:66 38516 1:241005 39c
3958 1:493859 1:431002 161:63 3658 1:46
1:10 384 19d
BATTEN 31221:15638551:77 82751:16536511:365
39531:132 38521:1934923 1:1643651 1:365
MCAD3962 1:198 3850– 10052 1:503 36511:365
MPS–I3951 1:395 38511:385 9885 1:198 3651 1:365
2966 Human Molecular Genetics, 2001, Vol. 10, No. 26
calculated carrier frequency of PAH mutations was <1:200,
consistent with estimated PKU incidence of less than 1:100
000 in Finland (30). The common deletion in the CLN3 gene,
causing Batten disease (31) and accounting for 90% of Finnish
Batten chromosomes, was surprisingly rare. The carrier
frequency for this mutation was 1:165–1:365 in all regional
samples, except the eastern, late settlement study sample,
which had a frequency of 1:77, being comparable to that
reported from other Caucasian populations (32). The
prevalence of the medium-chain acyl CoA dehydrogenase
(MCAD) mutation was very low, the carrier frequency varying
between 1:503 and 1:198. This would suggest that the MCAD
deficiency represents still another example of a ‘negative
founder effect’ in the Finnish population.
Linkage disequilibrium in common disease alleles
SNPs flanking the common mutations in the HFE (33,34) and
FV (35) genes were selected (Materials and Methods; Table 4)
to monitor for the linkage disequilibrium of common disease
alleles and the haplotypes of disease alleles in regional
samples. After correction for multiple testing, the only significant
departure from linkage equilibrium between the SNP variants
of the HFE allele was observed in the late settlement North
Karelia sample (Table 4). In the case of the factor V gene
SNPs, no regional differences in linkage disequilibrium could
The predicted haplotypes of HFE and FV alleles suggested
that the mutation occurred in the same haplotype background
in all geographic regions. This provided evidence that many of
these are old founder mutations. The old age of mutations is
supported by the fact that for both loci these haplotypes were in
agreement with the previously described haplotypes observed
in other Caucasian populations (33,34,36,37). Allelic information
of these common variants provided no evidence of genetic
distance between regional subpopulations based on the Nei’s
identity estimation (38).
Table 3. Confidence intervals (based on binomial likelihoods) for the allele frequency estimation
DiseaseBotniaNorth KareliaHelsinki Oulu
Human Molecular Genetics, 2001, Vol. 10, No. 26 2967
Our study demonstrates the power of array-based mutation
detection techniques in parallel screening for numerous disease
mutations. Miniaturization and multiplexing resulted in the
low cost for genotyping, the price per genotype being
$0.30USD/mutation/sample (8). Several approaches for
parallel genotyping by DNA-microarrays have been presented
[reviewed by Hacia and Collins (39)], but there is a notable
lack of their application beyond the proof-of-principle level.
ASO-hybridization-based approaches suffer from complicated
array designs and imperfect allelic discrimination (40,41)
rendering them inflexible and costly for custom genotyping
applications. Primer extension-based approaches (7,8,42) with
low complexity array designs provide a better accessibility of
the microarray technology for high-throughput genotyping.
However, dissemination of high-throughput primer extension-
based microarray systems to clinical diagnostics and carrier-
screening programs are currently hindered by the considerable
set-up optimization required for multiplex PCR (8,43). Generic
arrays of ‘tag’ (44) or ‘zip code’ (45) sequences can be used to
capture and visualize primer extension or ligation products
carrying complementary tag- or sequence-sequences at their
5′ ends in a highly parallel manner. These generic arrays will
obviously be more accessible to non-specialized laboratories.
Despite the relatively limited sample size and statistical
power of our pilot study, the obtained carrier frequencies of
‘Finnish diseases’ were generally in very good agreement with
the reported carrier frequencies of the individual diseases,
evidencing for the accuracy of the data (12,25). Furthermore,
for most of the diseases studied, the observed geographic
distribution of the carrier frequencies agreed well with earlier
epidemiological and genealogical data (16,46). It should be
noted that our study samples reflect the effect of at least two
features molding the gene pools of the analyzed regions. First,
the western sample represents the typical early settlement
region with the population history of some 100 generations,
whereas the eastern sample represents the late settlement
communities, permanently inhabited only some 15 generations
ago. Secondly, both western and eastern samples were
collected from rural, isolated communities, whereas Helsinki
and Oulu samples represent more mixed, urban populations.
However, some distinct differences in the population history as
well as in the distinction of Y chromosomal haplotypes
between these urban populations have been shown to exist (15)
and this genetic diversity could explain some of the variation
seen in the carrier frequencies between these two urban areas.
Very low carrier frequencies were seen for many ‘Finnish
mutations’ in rural population samples. An enrichment of these
disease alleles is not obvious at the whole population level but
only in highly restricted communities created by a small
number of founders and by a long-standing isolation.
The regional distribution varied considerably for the rare
mutations that had been recently introduced into the population.
These disease alleles are known to reveal linkage disequilibrium
over a wide genetic interval (12). With regard to the older,
common Finnish mutations, such as CNF, DD and LPI (16), no
dramatic differences could be observed in carrier frequency
between the regional study samples. Interestingly, the INCLFin
mutation (47) as well as the most common APECED mutation
(48) suspected to represent old mutations based on the short
LD interval in disease chromosomes showed enrichment in
both east and west rural populations as compared to the more
mixed Helsinki and Oulu study samples (Tables 2 and 3).
Further, the AGU mutation, otherwise revealing an even prevalence
across the regional samples showed a lower frequency of
carriers in the early settlement region. These findings would be
in agreement with multiple regional bottlenecks in the population
history and suggest that local events mold the gene pool
Figure 3. Frequency of carriers of ‘young’ Finnish disease heritage mutations in different geographical regions of Finland. The carrier frequencies in the
‘subregions’ were compared to those in the Helsinki region.
2968 Human Molecular Genetics, 2001, Vol. 10, No. 26
continuously and can have a significant effect on the frequency
of disease alleles.
It should be noted that although the major mutations of old
Finnish diseases showed a relatively even distribution across
the country, minor alleles of these diseases revealed dramatic
differences in their regional distribution supporting their more
recent introduction into the population, as exemplified by the
prevalence of the CNF minor mutation. This mutation was
found to be highly enriched in the western coastline communities
while being very rare in other parts of Finland. This is in agreement
with the recent study of 2000 Finns from the eastern area (49).
Most probably, the CNF minor mutation has been introduced
to this early settlement region quite recently, possibly after the
major internal migration movement in the 16th century (16).
This illustrates the fact that even in isolated populations with
relatively little immigration several different mutations for a
rare disease may at times be found simultaneously. Further, not
all of these mutations are ‘original’ founder mutations nor are
they of similar age. Finally, CNF also provides a demonstrative
example of how the introduction of a second mutation into the
population can result in patients who are compound hetero-
zygotes, a feature that may markedly increase the incidence of
The data on the common Caucasian mutations revealed
several interesting features. A geographic gradient has been
reported in the prevalence of the deletion mutation of connexin
26 (50). In Europe the carrier frequency is highest (1:31) in
some Mediterranean populations and gradually decreases
towards central and northern Europe (1:79). Despite this, the
Finnish frequency (1:45–1:60) represents an average European
population frequency. There were no distinct differences in the
regional distribution of this mutation providing evidence for its
early introduction and even spreading during the inhabitation of
α-1-Antitrypsin deficient individuals are most commonly
homozygous for a recurrent point mutation referred to as the
Z-allele (51). Nearly 30 years ago a study was conducted
among Finnish students to determine the prevalence of the
Z-allele by protein electrophoresis in different parts of Finland
(52). The carrier frequency of the Z-allele in Helsinki was
reported to be 2.7% (1:38) and a higher frequency was seen in
the western early settlement region when compared to north-
eastern Finland. Our data are in good agreement with these
Table 4. Uncorrected P-values for the linkage disequilibrium analyses
between different pairs of SNPs
Pair of SNPsBotniaNorth
HLA-HIVS2 C282Y0.0283 0.00100.1132 0.4510
C282Y HLA-H55690.6480 1.00000.10260.6994
HLA-HIVS2 HLA-H55690.08380.0043 0.11310.4510
FVLeiden 11091A_C 1.00001.00000.3562 1.0000
FVLeiden 11063G_A 0.6053 0.7379 0.8721 0.2841
11091A_C 11063G_A 0.7432 0.32550.8597 0.6414
FVLeiden 11064G_A 0.60490.6357 0.8662 0.5152
11091A_C 11064G_A0.7431 0.3093 0.86020.6447
11063G_A 11064G_A <0.0001 <0.0001<0.0001<0.0001
FVLeiden 10964A_G1.0000 0.17170.19221.0000
11091A_C 10964A_G1.00000.3236 1.0000 1.0000
11063G_A 10964A_G 0.75940.1595 1.0000 0.3985
11064G_A 10964A_G0.7628 0.20011.0000 0.4574
Figure 4. Frequency of carriers of ‘old’ Finnish disease heritage mututations in different geographical regions of Finland.
Human Molecular Genetics, 2001, Vol. 10, No. 26 2969
findings exposing a similar decreasing gradient (1:26–1:46) of
the Z allele from west to east.
The prevalence of another common disease mutation,
HFEC282Y, causing hereditary hemochromatosis had been
previously studied in two Finnish population-based samples.
The first study reported a carrier frequency of 9.9% (1:10) in
141 Finns (53), whereas a larger study in eastern Finland
reported a carrier frequency of 6.7% (1:15) (54). Our data
exposes differences in tested geographical regions, the
prevalence being highest in the early settlement area of
Finland. The high global prevalence of both of these mutations
is reflected by the high prevalence among founders of the
Finnish population. Further, the mutation has become relatively
evenly distributed, even during the internal migration.
However, later bottlenecks, especially those affecting the
eastern, late settlement region have molded the population
prevalence of the mutations. An opposite regional distribution
was observed in the prevalence of two other common Cauca-
sian mutations: FVLeiden and prothrombinG20210A, both predis-
posing to venous thrombosis. These were most prevalent in the
eastern samples. It remains to be seen if this opposite direction
of increasing gradients in the frequency of common mutations
simply reflects a random drift in regional subisolates or rather
mirrors the dual theory concerning the settlement history of
Finland (15,55). The combined carrier frequency of these
common Caucasian mutations in Finland is slightly higher
(1:5) than or similar to the pooled frequency of recessive
‘Finnish’ mutations (1:6). As expected, population bottlenecks
that have had a distinct effect on rare alleles, have less dramat-
ically influenced the common Caucasian alleles. Even the
recent bottlenecks have resulted in only minor regional differ-
ences in the prevalence of common mutations. However, when
analyzing the SNPs flanking a common mutation (HFE), a
more significant linkage disequilibrium between the SNPs was
detected in the eastern rural sample than in the other
populations. This reflects a younger age and a less mixed
population in the late settlement region when compared to the
rest of Finland. Our finding also emphasizes the importance of
population selection in linkage disequilibrium-based disease
gene mapping studies. The fact that even closely spaced SNPs
were in linkage equilibrium for a clinically important factor V
Leiden mutation, underlines the potential difficulties in
performing and interpretations of possible SNP-based studies
relying on linkage disequilibrium.
The negative founder effect reflecting genetic drift in small
founder populations of Finland has resulted in almost complete
exclusion of some relatively common Caucasian disease
alleles. We found a very low prevalence of CF and PKU
alleles, approximately one-third of the prevalence reported for
other Caucasian populations (56,57). Also, in agreement with
an earlier study the carrier frequency of the common mutation
for MCAD was very low adding another mutation to the list of
disease alleles showing exceptionally low prevalence in
Finland (58). It appears that by chance these mutations had not
been introduced into the Finnish population reflecting the
small number of founders.
Our mutation screen of Finns represents the largest direct
determination of the carrier frequencies of numerous disease
mutations in a representative population sample. Furthermore,
it is thus far the only study considering regional differences in
the mutational spectrum in a population isolate, extensively
studied both genealogically and genetically. Most rare mutations of
Finnish disease heritage showed relatively constant population
frequency indicating the old age of these mutations; however,
some mutations had remarkable high local incidences,
reflecting the distinct effect of recent population bottlenecks.
Although being less affected than rare recessive mutations, the
prevalence of common Caucasian mutations also reflected the
stochastic effect of population bottlenecks, founder effects and
genetic drift: some common mutations showing distinct
Figure 5. Frequency of carriers of Finnish mutations for common Caucasian traits.
2970 Human Molecular Genetics, 2001, Vol. 10, No. 26
regional enrichment such as HFEC282Y in Botnia or FVLeiden in
North Karelia whereas others became significantly under-
represented in Finland (i.e. CF∆F508).
MATERIALS AND METHODS
Four sets of population samples representing different
geographical areas in Finland were analyzed (Fig. 5). A sample
from the city of Helsinki, the capital of Finland and considered
to represent the most genetically heterogeneous subpopulation
of the country consisted of 510 samples of the large epidemi-
ological population-based FINRISKI study (59) and 495 samples
from the Finnish Twin Cohort Study (http://kate.pc.helsinki.fi/
twin/twinhome.html) (60). The sample from the county of
southern Botnia consisted of 396 random blood donors from
the rural counties of Kurikka, Alajärvi and Lapua. The North
Karelia (eastern Finland) sample consisted of 385 random
blood donors from the rural counties of Eno, Ilomantsi, Juuka,
Lieksa and Polvijärvi. The Oulu sample was composed of
365 random inhabitants of the city of Oulu in northern Finland born
in the year of 1966. All samples were analyzed anonymously. In
addition to the study subjects, 212 samples from verified
carriers of the disease mutations studied were included to serve
as blinded positive controls. Following the initial screening,
the remaining positive samples (some DNA-aliquots were
exhausted after the array-based assay and confirmatory geno-
typing) for either the FVLeiden and HFEC282Y mutations from
each geographic region were further analyzed for SNPs in the
FV and HFE genes. Along with these samples approximately
20 negative samples for both mutations were picked from each
geographic region and similarly analyzed for the SNPs. A total
of 218 samples were included for this part of the study.
A system based on allele-specific primer extension in a micro-
array format was used to screen for carriers of the 31 disease
mutations as well as the FV and HFE SNPs as described in
detail previously for these panels (8). Standard solid-phase
minisequencing in a microtiter plate format served as the refer-
ence method (61). For the NKH and LPI mutations PCR-RFLP
digestion was used as the reference method (62,63), and for the
Salla disease mutation an allele-specific PCR reaction (18)
with an internal control amplicon was used. The genotypes of
the carriers identified by the array-based screening were
confirmed using one of the above mentioned reference
methods. Samples yielding signal ratios not falling within
distinct clusters or having low signal intensities were
reanalyzed using a reference method.
Statistically significant differences between carrier frequencies
were assessed using Fisher’s exact test. In cases where, based
on published literature, carriers were expected to cluster in a
particular region one-tailed tests were used, otherwise two-
tailed tests were employed. Hardy–Weinberg proportion and
linkage disequilibrium were assessed using the Genepop web
version 3.1c program (http://wbiomed.curtin.edu.au/genepop/)
(64). Nei’s identity estimation (38) was carried out to compare
genetic distances between different study samples using the
program PopDist (65). In the case of the Factor V gene SNPs
(WIAF-10964 A/G, WIAF-11529 T/G, WIAF-11065 G/A,
WIAF-11064 A/G, WIAF-11063 A/G, WIAF-11091 A/C,
WIAF-11062 C/T) no regional differences in linkage
disequilibrium values could be observed. For the HFE gene,
tests of disequilibrium based on multilocus genotypes were
conducted within each population to avoid spurious results due
to admixture. Fisher exact tests could not reject the hypothesis
of equilibrium between SNPs HHC282Y and HFE5569 in any of
the populations, despite the close positions of the two markers.
Equilibrium could not be rejected between any marker for the
Helsinki and Oulu populations. To correct for multiple
comparisons across populations (4) and marker pairs (three for
each population) using the Bonferroni method, one should
inflate the P-values of each single test by a number between 4
and 12 (corresponding, respectively, to the extreme of total
dependence and independence between marker pairs). This
leaves only one significant departure from equilibrium in the
HFE gene in North Karelian population (the pair 282Y and
HLA-IVS2 has an initial P-value of 0.01 and the pair HLA-H5569
HLA-IVS2 has an initial P-value of 0.004—these P-values are
before the Bonferroni correction).
We owe our deepest gratitude to several researchers and
clinicians for making the control samples available to us. Vlad
Kustanovitsh is appreciated for his advice in grammar and
style. The following grants made this study possible: the
Technology Development Centre of Finland, EC Biomed2
Contract no. BMH4-972013, The Hjelt Fond of the Pediatric
Research Foundation, The Finnish Cultural Foundation, The
Academy of Finland and The Maud Kuistila Foundation.
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