Introduction
Familial hypercholesterolaemia (FH) is an autosomal co-dominant monogenic disorder of lipoprotein metabolism. It is characterised by severely elevated levels of low-density lipoprotein cholesterol (LDL-C) from birth onwards, clinically leading to premature atherosclerosis and cardiovascular disease (CVD). The estimated prevalence of heterozygous FH is 1 per 400 in the Dutch population [
1,
2]. Homozygosity is rare with an average frequency of 1:640,000.
FH is mainly caused by mutations in the LDL receptor (
LDLR) gene, encoding for a receptor that removes LDL-C particles from the circulation and facilitates uptake by the liver cell [
3]. In approximately 7% of cases, the clinical phenotype of FH is the result of mutations in the region of the gene encoding for the LDLR-binding domain of apolipoprotein B (
APOB) [
4]. Also, gain-of-function mutations in the gene encoding for proprotein convertase subtilisin–kexin type 9 (
PCSK9), a protein that regulates LDL receptor degradation, are a rare cause (<1%) of the FH phenotype.
More than 1000 different mutations, assumed to cause an FH phenotype, have been identified worldwide [
5]. In the Netherlands, 552 different mutations have been identified so far. The specific mutations can vary with respect to clinical severity, as observed by LDL-C levels [
6], atherosclerosis as assessed by carotid intima-media thickness [
7] as well as by prevalence of CVD [
8]. In some populations, the majority of cases of FH can be explained by only a few mutations, and a founder effect usually underlies a higher than expected frequency of certain mutations.
The importance of early diagnosis and management of FH is well established, and therefore, screening for FH is advocated [
9]. In the Netherlands, approximately 20,000 subjects have been identified with a pathogenic FH mutation so far, mostly through a nationwide genetic cascade screening programme. Because FH has been studied this extensively in our country, this enables us to study some interesting aspects with regard to geographical distribution and prevalence of homozygous patients not directly related to consanguinity. In this study, we explored the geographical distribution, possible founder effects and clinical phenotype with regard to LDL-C levels of the 12 most prevalent FH mutations in the Netherlands.
Discussion
In the Netherlands, a national screening programme for FH is ongoing and has yielded the largest genotyped FH population worldwide. For this study, we determined the geographical distribution of the 12 most common mutations, which represent 64% of all Dutch FH patients. We demonstrated that almost all common mutations showed a clearly marked region of preference, suggesting the existence of a founder effect. This can be explained by the occurrence of a local founder mutation in combination with limited migration, possibly attributable to the geographical isolation in the past, as in West Friesland and the islands of Noord and Zuid Beveland, the two regions with the highest prevalence of mutations per se. The phenomenon of geographical preference of FH causing mutations can have several clinical implications.
Firstly, knowledge of the prevalence of a certain mutation can be used in strategies for molecular testing; when a mutation predominates in a region, molecular tests can be designed to identify these specific variant alleles first. Secondly, knowledge of mutation distribution may explain the identification of homozygous patients in non-consanguineous families. This has been confirmed by our finding that most of the true homozygous patients are found in regions with a high prevalence of that specific mutation and the fact that the total number of identified homozygous patients (51) is higher than the expected number of 26 (1:640,000 in 16.5 million people in the Netherlands). Thirdly, our observations can influence the perception of physicians in different regions with regard to the prevalence of FH and the severity of the FH phenotype in their region. It is not unlikely that physicians in the north-western region where the relatively mild N543H/2393del9bp mutation is most prevalent have a different perception of CVD risk attributable to FH than colleagues in the south of the Netherlands where the severe 1359-1 mutation predominates. The latter is known for its significantly higher LDL-C levels and higher incidence of premature CVD. The relative risk of coronary artery disease in FH patients compared with unaffected relatives was found to be 7.83 (95% CI, 3.11–19.67) for carriers of the N543H/2393del9 mutation and 15.95 (95% CI, 5.52–46.14) for carriers of the 1359-1 mutation [
16].
Dutch FH patients share mutations with FH populations in other countries, as discussed by Fouchier et al. [
3,
17]. This can be partly explained by the migration of individuals over Europe during the last centuries, demonstrated by large numbers of similar mutations in neighbouring countries such as Germany, the UK, Belgium and Denmark [
3]. However, detection rates of mutations depend on the intensity of screening in different countries, and the global array of mutations is therefore not complete.
Towns with harbours that served as an outpost for trading with other coastal communities may have been the source of the spread of the prevalent mutations in those regions. A mutation of special interest in that respect is the V408M mutation, which is most commonly found in West Friesland, close to the former Zuiderzee (now a lake, but it used to be connected to the North Sea). This is one of the regions from where settlers to South Africa departed in the seventeenth century, with important port towns as Hoorn and Enkhuizen. The V408M mutation is one of the founder mutations in South Africa, present in 15–20% of the South African Afrikaner FH patients [
18]. It has been suggested that this was the result of Dutch migration, in times of the expeditions of the Dutch colonial administrator Jan Van Riebeeck, the founder of Cape Town in the seventeenth century. It was indeed established that some of the Dutch FH patients shared the same haplotype with an Afrikaner, who was homozygous for this mutation [
19]. Furthermore, it has been suggested that this mutation was also introduced in Canada at the beginning of the twentieth century by the large immigration waves from (the northern part of) the Netherlands. The founder of a Canadian FH family with the V408M mutation was traced back to Andijk [
20], which is also situated in West Friesland.
By comparing mutation frequencies within and between populations, insight into the evolutionary history of genes and populations can be gained. It has been found that almost all FH patients with R3500Q (showing no founder effect in the Netherlands and present in different populations over the world) share the same rare haplotype. Therefore, it is postulated that the first original R3500Q mutation occurred approximately 6750 years ago [
21,
22]. However, it is also possible that some mutations occurred on multiple occasions, referred to as recurrent mutations. For instance, ‘Dutch’ mutations are also found in countries as Japan, which is geographically isolated and Japanese people are believed to be uniracial [
23]. The same applies for some mutations found in rural China [
24].
Currently, more than 550 different FH mutations have been identified in the Netherlands, from which 471 have been used in cascade screening. These numbers are different because not all patients had given consent for family screening. In populations where one or two mutations predominate, founder effects are much more pronounced than in the Netherlands. In Finland, four different mutations are responsible for 75% of FH patients, which can be explained by the unique geographical position of Finland between Eastern and Western cultures as well as by linguistic barriers [
25]. Other examples of populations with a clear founder effect are the French-Canadians, with the 10-kb deletion in 60% of patients and a total FH prevalence of about 1:200 [
26], and the earlier mentioned South African Afrikaners, where three founder mutations are responsible for 95% of all Afrikaner FH patients (including the ‘Dutch’ V408M mutation), and an estimated prevalence for FH of 1:72 [
27]. As in these populations, this study showed that also in the Dutch population, founder effects result in high prevalence in certain regions, in particular in the area of West Friesland, where a prevalence of 1:280 was found, which is higher than the overall estimated prevalence for the Netherlands [
2]. It has to be taken into account that patients without a known postal code were excluded from our analysis (approximately 7% for index cases and 12% for other patients), that only the data of the 12 most frequent mutations were used, and that all patients might not have been traced yet, so in fact the real prevalence for this area could be considerably higher. For instance, the area with the highest prevalence of index cases (825 per million) is the islands of Noord and Zuid Beveland. From the experience of the screening programme, we know that through one index case, approximately eight family members with FH can be traced [
14]. This would mean that by adding up the 7% with an unknown postal code, the prevalence for the 12 most common mutations in this area can be estimated to be 1:142.
Efficacy of identification of FH patients through a cascade screening programme such as in the Netherlands is dependent on several factors: regional referral rate, regional coverage of the screening programme, family size and willingness of relatives to participate. All these factors may have influenced the results of our study. We attempted to reduce referral bias of physicians by analysing index cases and identified family members separately, but as almost similar patterns can be observed in the two figures, this appears to play a minor role. Our results show different distributions for all 12 mutations with dense areas in all parts of the country, which reflects nationwide coverage. Estimations of the percentage of traced FH patients differ among provinces [
14], but these are based on a presumed even distribution. Furthermore, we assume that family size and willingness for screening are similar for different mutations. Although these assumptions may not be completely correct and therefore may have biased our results to some extent, we have found a clear, unique distribution for the 12 most prevalent mutations.