Mutation Detection in the LDLR Gene | Genetics | Biology

In this article we will discuss about the mutation analysis of LDLR mutations in patients with familial hypercholesterolaemia.

Introduction to Mutation Detection in the LDLR Gene:

In some families, the risk of early coronary heart disease is considerably raised by the inheritance of a specific mutation, in one of two genes (apolipoprotein B, ApoB [OMIM #107730], or low-density lipoprotein receptor, LDLR [OMIM #143890]), which gives rise to Familial Hypercholesterolaemia (FH).

FH is characterized by an autosomal dominant inheritance, severe hypercholesterolemia, premature onset of atherogenesis and cholesterol deposits in the skin, tendons (tendon xanthoma) or in and around the eyes (corneal arcus and xanthelasma). In the majority of FH patients, the disorder is caused by a mutation in the LDLR gene that destroys or significantly impairs its proper function.

FH is among the most common metabolic genetic disorders, the prevalence being estimated at one in 400 to 500 people for mutations in LDLR, and one in 1000 for ApoB mutations, more frequent than either cystic fibrosis or sickle cell anaemia. Recent reports from the UK and the Netherlands suggest that the vast majority of these individuals remain unidentified and untreated.

In both these countries there is extensive evidence that case finding combined with family screening and mutation detection is a very effective method for increasing the percentage of FH individuals getting effective treatment.

With the exception of a few populations where founder mutations have been reported (French Canadians, Finns, Ashkenazi Jews of Lithuanian descent, Christian Lebanese, Dutch and Afrikaners), a relatively large number of diverse mutations cause FH in most populations, with different mutations prevailing in different populations.

Over 700 LDLR gene mutations have been reported world-wide and new mutations are reported regularly (www(dot)ucl(dot)ac(dot)uk/fh/), as opposed to only three mutations that have been described in the apoB gene that cause FH.

Since the most frequent known LDLR mutations are present only in a small proportion of patients, an initial strategy of testing for specific mutations (such as is routine for Cystic Fibrosis where a single muta­tion accounts for more than 70% of mutations) is precluded as a first step in those countries with heterogeneous populations.

For some heterozygous FH individuals, a clear diagnosis can be made on the basis of grossly increased cho­lesterol and associated clinical features. However, one of the problems of using hypercholesterolemia as a primary criterion for diagnosis of FH is that plasma lipid levels in heterozygous FH patients overlap with those in the general pop­ulation.

The use of DNA tests to confirm the diagnosis of FH in family mem­bers of identified LDLR mutation carriers suggests that between 15-20% of adult relatives and 5-10% of children may be misdiagnosed by cholesterol testing alone.

The LDL receptor is encoded by a large gene comprised of 18 exons span­ning approximately 45 kilobases. Its size, along with the large numbers of mutations found throughout the coding and control regions, means that mutations are not easily detected by simple diagnostic assays and sequencing the patients’ entire LDLR genes on a clinical scale is prohibitive due to cost.

By far the majority of mutations described in this gene are single base substitutions or deletions and insertions of only a few base pairs (approximately 90%), with the remainder deletions of multiple introns and exons. In addition, 35 polymorphisms and a number of silent mutations have been described through­out the LDLR gene.

In particular, the LDLR polymorphisms complicate the screening process as although the allelic frequencies for these polymorphisms within various populations range from 0.5% to 96%, the majority occurs with allelic frequencies from 30-70 %.

Therefore, it is sensible to use a pre-screening method to identify specific small regions of variation for further analysis by sequencing, as has been the case in BRCA1 and BRCA2 gene mutation screen­ing for familial breast cancer.

Methods, such as single strand conformational polymorphism (SSCP), previously used to screen for LDLR mutations, lack sensitivity and are labor intensive. The optimal length of DNA for SSCP analysis appears to be from 150 to 200 nucleotides with mutation detection sensitivity for fragments this size ranging from 70-90%.

The sensitivity of this technique decreases with increasing size of the fragment and it is often necessary to run samples under a number of different experimental conditions, including electrophoresis temperature, in order to detect variants reliably.

DHPLC has been reported to have numerous advantages over SSCP; analysis is rapid, inexpensive and semi-automated. Amplicons from 200 to 500 nucleotides are within the ideal range for heteroduplex detection, with sensitivity and specificity reported to range from 96-100 %. In addition, in most cases elution profiles are distinct for any given sequence variant allowing differentiation of polymorphisms from pathogenic mutations.

Previously we have reported a comparison of SSCP with DHPLC, assessing their effectiveness as prescreening methods for LDLR mutation detection in New Zealand patients with FH in a research setting. Compared with DHPLC, we were able to detect only 64% of mutations by SSCP.

As a result, we have imple­mented diagnostic testing through LDLR mutation screening by DHPLC. We have developed the first LDLR gene diagnostic assay that integrates DHPLC pre­screening with automated PCR setup and DNA sequencing of variants.

LDLR Mutation Detection in a Diagnostic Setting:

A number of factors must be taken into account when implementing a new diagnostic assay to enable timely delivery of an effective service. These include: turnaround time for reporting, automation for greater sample numbers and reduced risk of handling errors, optimization to a single set of PCR param­eters for reduced handling conditions and ease of automated set-up and, per­haps of prime concern, specificity and sensitivity to avoid reporting of false positives and false negatives.

Analysis of the LDLR gene requires amplification of each patient sample in a number of fragments or amplicons to encompass the coding and control regions. Previously, the LDLR gene has been amplified under multiple PCR con­ditions in 21 fragments for analysis by SSCP, ranging in size from 127 to 355 base pairs.

As it was essential that the LDLR diagnostic assay developed met the turnaround time and automation requirements detailed above, the screening process was designed to allow for analysis of patient samples in batch sizes consistent with sample numbers obtained. Therefore, seven patient sam­ples plus controls for all 21 amplicons are screened simultaneously per batch in two microtiter plates (168 wells in total) in a largely automated process.

Samples were obtained from apparently unrelated individuals with clinical­ly probable FH, attending lipid disorders clinics at Christchurch or Dunedin Hospitals. These patients had plasma cholesterol of >8.0 mmol/L and family histories of hypercholesterolaemia and/or classical clinical stigmata of FH. DNA was extracted from patients’ whole blood specimens according to an established method.

The known mutations in the apoB gene (R3500Q, R3531C and R3500W) were excluded by PCR and restriction analysis. After PCR set-up in two microtiter plates by a Tecan robotic workstation (Tecan AG, Switzerland), all exons were amplified under one set of conditions using Roche Taq Polymerase (Germany).

Prior to analysis, heteroduplices were formed by heating the PCR products at 95°C for five minutes and slowly cooling to room temperature over one hour. Samples were analyzed overnight by DHPLC using a WAVE Nucleic Acid Fragment Analysis System including a C18 reversed phase column based on non-porous poly(styrene-divinylbenzene) particles (DNASep Cartridge) from Transgenomic (Omaha, NE, USA). DNA was eluted from the column by an acetonitrile gradient in 0.1 mol/L triethylammonium acetate buffer (TEAA), pH 7, at a constant flow rate of 0.9 ml/min.

The melting profile for each DNA frag­ment, the respective elution profiles and column temperatures were determined using the WAVEMAKER™ software from Transgenomic, with further optimization performed against a positive control.

Every sequence alteration was confirmed in two independently amplified PCR products by direct cycle sequencing of dou­ble-stranded DNA with 33P-labeled terminators and ThermoSequenase according to the manufacturer’s instructions (Amersham Pharmacia Biotech, NZ).

Whilst use of a single set of conditions has greatly improved speed of sam­ple preparation for analysis by DHPLC, there have been some disadvantages. Acceptable products are produced but these are not necessarily optimal in terms of yield or quality of product for DHPLC. Some non-specific pre-peaks are observed during DHPLC for certain amplicons, though these are consistent between samples and runs, allowing the operator to correct for their presence.

Although PCR yield varies between amplicons, variation is also seen to a simi­lar degree between patient samples (at a factor of between one and three) and can be adjusted for by small changes in scaling of traces.

Optimization of DHPLC Screening:

The LDLR gene is similar to many other genes in terms of approach to muta­tion screening by DHPLC. Factors for consideration include: primer selection, size of amplicons, choice of positive controls, presence of multiple melting domains within fragments and optimum temperature for analysis.

However, the LDLR gene is larger than most genes screened routinely in a diagnostic envi­ronment and has a larger number of mutations, with more than 700 described throughout and more being regularly reported.

These mutations are also spread throughout all of the exons and intron/exon boundaries, which are both rela­tively polymorphic. Therefore, there is a distinct chance of DHPLC profiles being similar for different mutations. The influence of these factors on the develop­ment of diagnostic LDLR screening is discussed below.

Selection of Primers:

A number of primer sets have been described for LDLR mutation analysis by both SSCP and by denaturing gradient gel electrophoresis (DGGE) analysis, which is considered to be more sensitive but also more technically challenging and labor intensive than SSCP (www(dot)ucl(dot)ac(dot)uk/fh/primers(dot)html).

As we were interested in comparing SSCP and DHPLC, a primer set was selected for both applications based on SSCP design requirements. Whilst DHPLC melt­ing profiles for some of the amplicons obtained by use of these primers were not ideal, they provided an effective starting point for the screening process.

In some cases primers annealed to sequences within or immediately adjacent to intron/exon boundaries and, as approximately 46 splice site mutations have been described for the LDLR, it was necessary to relocate some of these primers to encompass these regions. For example, the Exon 2 product, ampli­fied using the primers designed by Hobbs and colleagues, encompasses a stretch of six nucleotides containing 17 reported splice mutations clustered in the 5′ donor site.

However, the upstream primer anneals to these nucleotides, ren­dering detection of any of these mutations unlikely. Therefore a new amplicon was designed to allow analysis of this region, with a new primer annealing approximately 50 nucleotides from the intron/exon boundary.

Generation of Positive Controls:

Although various software packages can predict the ‘optimal’ temperature for screening by DHPLC the use of positive controls, containing a single base substitution or small deletion, is essential to verify and refine the temperature used for each amplicon. These controls also provide some security that the dis­criminating conditions are maintained between DHPLC runs.

Non-identification of abnormal traces for the positive control would indicate variation in buffer conditions, column condition or oven calibration, and is essential in controlling for false negatives during diagnostic screening. Calibration of ovens may also vary between instruments, resulting in variation when screening is performed (at slightly different temperatures) on multiple instruments.

This also means that temperatures predicted by the WAVEMAKER software, or as reported in the literature, provide a good guide but may not be directly translatable from instru­ment to instrument. Therefore, temperature optimization and verification by way of positive controls is important and will resolve any issues arising from these differences.

However, obtaining positive controls for each amplicon is a difficult step. Here they were obtained from Professor Steve Humphries (University College London, UK) and Dr. Ros Thiart (University of Stellenbosch), except in the cases of the promoter region and exon 18 (Table 6-1). Positive controls were syn­thesized for the latter two fragments as described below.

A number of methods have been assessed within our laboratory previously for generating positive controls, including: screening of amplicons for polymor­phic restriction enzyme sites, site directed mutagenesis (SDM) using the megaprimer protocol and Ligation During Amplification (LDA) SDM. As no polymorphic restriction sites were identified in either the promoter or exon 18 amplicons, it was necessary to generate positive controls for these amplicons.

Introduction of a specific mutation through SDM by megaprimer protocol involves a multistep PCR and restriction digest protocol, whereas LDA SDM involves a single extension and ligation PCR – allowing more rapid synthesis. Due to rapidity and ease of synthesis, the LDA SDM method was selected as the most suitable method for generation of positive controls and was used to elim­inate a unique restriction site within each amplicon.

In brief, a thermostable ligase and a phosphorylated mutagenic primer, containing a single base mismatch, were included in a standard PCR reaction mix and cycling conditions modified to include a seven-minute extension at 65°C. The mutagenic primer was designed to eliminate a unique restriction site, allowing digestion of wild type product post-amplification.

Digested reactions were then diluted and re-amplified to obtain 100% mutant product. The mutant product was sequenced to confirm the mutation and was mixed in an equal ratio with wild type PCR product in order to obtain heteroduplices for DHPLC analy­sis. The synthesized mutant was analyzed by DHPLC against a wild type (nor­mal) control (Figure 6-1). This method allows the generation of multiple posi­tive controls within one to two days.

Multiple Melting Domains:

The LDLR gene is relatively GC rich, with several exons having long repeti­tive stretches of GCs (Table 6-1). Due to sequence constraints, it may not always be possible to design primers to amplify regions that contain similar GC content and therefore have similar melting profiles across the amplicon for DHPLC. In these cases, with referral to the WAVEMAKER software predictions for melting domains, it is desirable to screen samples at two temperatures to resolve sequence variation in different domains within an amplicon.

Where possible, multiple positive controls were used in order to optimize partial denaturing temperatures for DHPLC. Two Exon 1 positive controls, local­ized to different regions of the amplicon, were used during DHPLC optimization (Table 6- 1) and further patient screening was performed at both 65°C and 66°C.

This example highlights the importance of positive control selection as if only the C>T variant had been used then the optimal screening temperature select­ed would have been 66°C. Therefore, variants localized in the lower melting domain could be potentially missed if those regions are denatured at 65°C (Figure 6-2).

Similarity of DHPLC Profiles:

As discussed previously, a number of factors complicate screening of the LDLR gene for genetic variation that might cause FH. Of considerable impor­tance are the large number of mutations and polymorphisms previously described in the gene and the increasing number of novel mutations being repotted, meaning that any LDLR screening process must be able to potentially target any mutation present rather than solely target known variants. As DHPLC has the capacity to detect all these small variations at the DNA level (substitu­tions, insertions and deletions) without discrimination it is ideally suited to LDLR mutation analysis.

However, unlike other genes that might have fewer mutations more sparsely spaced through coding and control regions, it is unlikely that elution profiles will be distinct for each LDLR sequence variant making the use of these profiles less effective in discriminating deleterious mutations from benign polymorphisms.

This lack of ability to discriminate variation on the basis of DHPLC profiles alone is not so important in a clinical context as all mutations must be con­firmed by a second method, whether the prescreening method used is DHPLC, SSCP or dideoxy fingerprinting (DDF).

However, the use of DHPLC profiles would still remain effective in cases where a mutation has been previously identified in a relative and screening is focused on confirming the presence or absence of that solitary mutation.

Alternatively, in highly polymorphic regions (for exam­ple, Exons 12, 15 and 18), it would be better to sequence the amplicon direct­ly rather than prescreen for variation initially. However, where sequencing capacity is restricted (i.e. in low throughput sequencers or when sequencing is performed manually), this may not be an effective use of resources and DHPLC would remain the best option.

Confirmation by sequencing of variants identified in Exon 10a fragments of New Zealand FH patients has led to the identification of two different mutations with virtually identical profiles within the same amplicon (Figure 6-3). The most common LDLR mutation identified in the New Zealand population is “FH Northern Irish”, or D461N, and this variant is indistinguishable from a splice site mutation, 1359-1G>A, which has been identified in multiple patients in Intron 9.

Conclusion:

On a worldwide basis it has been estimated that more than 10 million peo­ple have FH, of whom as many as 200,000 die of premature coronary heart dis­ease each year. In contrast to most genetic disorders, an effective treatment is available for FH. By using lipid-lowering drugs, a reduction in LDL choles­terol of 50-60% can be achieved, which if started early may be expected to achieve a normal life expectancy.

Recent reports from the UK and the Netherlands suggest that the vast majority people with FH remain unidentified and untreated. In both of these countries there is extensive evidence that case finding combined with family screening and mutation detection is a very effective method for increasing the percentage of FH individuals getting effec­tive treatment.

Therefore an effective means of screening for LDLR mutations, that recognizes that there is a great diversity of LDLR mutations and that tar­gets both known and novel mutations, is needed, especially in heterogeneous populations.

We have shown that DHPLC is an effective tool for the detection of muta­tions within the LDLR. Twenty-nine different LDLR mutations have been iden­tified in 55 New Zealand FH patients by DHPLC. These mutations are localized throughout the gene, occurring in the receptor’s various functional domains (Table 6-2).

The majority of mutations were identified within the EGF precur­sor domain (67.4%), followed by the ligand binding domain (23.6%) and the balance are localized in the signal peptide (1.8%), the sugar-modified domain (3.6%), the membrane-spanning domain (1.8%) and the cytoplasmic domain (1.8%).

In the past, screening programs for LDR mutation analysis have focused on “mutation hot spots” such as the ligand-binding domain, specifically Exons 3 and 4. However, more recently it has been recognized that this tar­geting of “hot spots” has resulted in sampling bias rather than being a true reflection of the localization of mutations. In fact, more novel muta­tions are being identified within the EGF precursor domain than in any other region, now that more comprehensive screening of the LDLR gene is being per­formed.

This is not unexpected, as mutations in this functional domain would affect lipoprotein dissociation from the receptor in endosomes during receptor recycling and receptor positioning at the cell surface. This effect of sampling bias highlights the necessity for a comprehensive screening approach that encompasses all coding and control regions, as well as reported and novel mutations.

Mutations were detected in 20.9% of the patients analyzed. The majority of these patients were selected according to total cholesterol levels, >8.0 mmol/L (300mg/dl), and a suggestive family history of heart disease. Less than one third also displayed clinical stigmata. These patients could be categorized into “probable FH” and “definite FH” according to the absence or presence of stigmata, respectively.

Mutations have been identified in 45% of patients with “definite FH” compared to 8% of those with “probable FH.” These data are con­sistent with those reported for other populations, which range from 18- 27%, reinforcing that hypercholesterolaemia is not sufficient as the primary criterion for making a clinical diagnosis of FH.

The LDLR gene is an ideal candidate for mutation analysis by DHPLC due to its relatively large size, the range of variation identified throughout the gene and also the nature of FH expression. FH is an autosomal dominantly inherit­ed condition with variable phenotypic presentation. Whilst FH heterozygotes are prone to premature coronary artery disease, homozogous individuals are more severely affected and may die before reaching maturity.

However, homozy­gous affected individuals are rare, having a prevalence of one in one million, compared with one in 400 to 500 for heterozygotes. Therefore, FH patients attending lipid clinics will generally be heterozygotes. Thus, unlike those disorders where some samples may be homozygous and must be combined with wild type DNA, mixing of LDLR amplicons is not required for FH.

DHPLC allows a more rapid turnaround time for LDLR mutation screening than SSCP, as amplification of gene fragments and pre-screening by DHPLC is largely automated, less laborious, cheaper and 30% more sensitive than SSCP. Taken together with our finding that it provides sensitive mutation detection of LDLR variants, DHPLC is ideally suited to LDLR mutation analysis in both clini­cal and research settings.