The impact of routine next generation sequencing testing for familial hypercholesterolaemia – 5 months service experience

The effect of adjusting LDL-cholesterol for Lp(a)-cholesterol on the diagnosis of familial hypercholesterolaemia

BACKGROUND

Familial hypercholesterolaemia (FH) diagnostic tools help prioritise patients for genetic testing and include LDL-C estimates commonly calculated using the Friedewald equation. However, cholesterol contributions from lipoprotein(a) (Lp(a)) can overestimate 'true' LDL-C, leading to potentially inappropriate clinical FH diagnosis.

OBJECTIVE

To assess how adjusting LDL-C for Lp(a)-cholesterol affects FH diagnoses using Simon Broome (SB) and Dutch Lipid Clinic Network (DLCN) criteria.

METHODS

Adults referred to a tertiary lipid clinic in London, UK were included if they had undergone FH genetic testing based on SB or DLCN criteria. LDL-C was adjusted for Lp(a)-cholesterol using estimated cholesterol contents of 17.3%, 30% and 45%, and the effects of these adjustments on reclassification to 'unlikely' FH and diagnostic accuracy were determined.

RESULTS

Depending on the estimated cholesterol content applied, LDL-C adjustment reclassified 8-23% and 6-17% of patients to 'unlikely' FH using SB and DLCN criteria, respectively. The highest reclassification rates were observed following 45% adjustment in mutation-negative patients with higher Lp(a) levels. This led to an improvement in diagnostic accuracy (46% to 57% with SB, and 32% to 44% with DLCN following 45% adjustment) through increased specificity. However all adjustment factors led to erroneous reclassification of mutation-positive patients to 'unlikely' FH.

CONCLUSION

LDL-C adjustment for Lp(a)-cholesterol improves the accuracy of clinical FH diagnostic tools. Adopting this approach would reduce unnecessary genetic testing but also incorrectly reclassify mutation-positive patients. Health economic analysis is needed to balance the risks of over- and under-diagnosis before LDL-C adjustments for Lp(a) can be recommended.

Genetic testing for familial hypercholesterolemia-past, present, and future

In the early 1980s, the Nobel Prize winning cellular and molecular work of Mike Brown and Joe Goldstein led to the identification of the LDL receptor gene as the first gene where mutations cause the familial hypercholesterolemia (FH) phenotype. We now know that autosomal dominant monogenic FH can be caused by pathogenic variants of three additional genes (APOB/PCSK9/APOE) and that the plasma LDL-C concentration and risk of premature coronary heart disease differs according to the specific locus and associated molecular cause. It is now possible to use next-generation sequencing to sequence all exons of all four genes, processing 96 patient samples in one sequencing run, increasing the speed of test results, and reducing costs. This has resulted in the identification of not only many novel FH-causing variants but also some variants of unknown significance, which require further evidence to classify as pathogenic or benign. The identification of the FH-causing variant in an index case can be used as an unambiguous and rapid test for other family members. An FH-causing variant can be found in 20-40% of patients with the FH phenotype, and we now appreciate that in the majority of patients without a monogenic cause, a polygenic etiology for their phenotype is highly likely. Compared with those with a monogenic cause, these patients have significantly lower risk of future coronary heart disease. The use of these molecular genetic diagnostic methods in the characterization of FH is a prime example of the utility of precision or personalized medicine.

Clinical utility of the polygenic LDL-C SNP score in familial hypercholesterolemia

Mutations in any of three genes (LDLR, APOB and PCSK9) are known to cause autosomal dominant FH, but a mutation can be found in only ∼40% of patients with a clinical diagnosis of FH. In the remainder, a polygenic aetiology may be the cause of the phenotype, due to the co-inheritance of common LDL-C raising variants. In 2013, we reported the development of a 12-SNP LDL-C "SNP-Score" based on common variants identified as LDL-C raising from genome wide association consortium studies, and have confirmed the validity of this score in samples of no-mutation FH adults and children from more than six countries with European-Caucasian populations. In more than 80% of those with a clinical diagnosis of FH but with no detectable mutation in LDLR/APOB/PCSK9, the polygenic explanation is the most likely for their hypercholesterolaemia. Those with a low score (in the bottom two deciles) may have a mutation in a novel gene, and further research including whole exome or whole genome sequencing is warranted. Only in families where the index case has a monogenic cause should cascade testing be carried out, using DNA tests for an unambiguous identification of affected relatives. The clinical utility of the polygenic explanation is that it supports a more conservative (less aggressive) treatment care pathway for those with no mutation. The ability to distinguish those with a clinical diagnosis of FH who have a monogenic or a polygenic cause of their hypercholesterolaemia is a paradigm example of the use of genomic information to inform Precision Medicine using lipid lowering agents with different efficacy and costs.

Improving the cost-effectiveness equation of cascade testing for familial hypercholesterolaemia

PURPOSE OF REVIEW

Many international recommendations for the management of familial hypercholesterolaemia propose the use of cascade testing using the family mutation to unambiguously identify affected relatives. In the current economic climate DNA information is often regarded as too expensive. Here, we review the literature and suggest strategies to improve cost-effectiveness of cascade testing.

RECENT FINDINGS

Advances in next-generation sequencing have both speeded up the time taken for a genetic diagnosis and reduced costs. Also, it is now clear that, in the majority of patients with a clinical diagnosis of familial hypercholesterolaemia in whom no mutation can be found, the most likely cause of their elevated LDL-cholesterol (LDL-C) is because they have inherited a greater number than average of common LDL-C raising variants in many different genes. The major cost driver for cascade testing is not DNA testing but treatment over the remaining lifetime of the identified relative. With potent statins now off-patent, the overall cost has reduced considerably, and combining these three factors, a familial hypercholesterolaemia service based around DNA-cascade testing is now less than 25% of that estimated by NICE in 2008.

SUMMARY

Although all patients with a clinical diagnosis of familial hypercholesterolaemia need to have their LDL-C lowered, cascade testing should be focused on those with the monogenic form and not the polygenic form.

Would raising the total cholesterol diagnostic cut-off from 7.5 mmol/L to 9.3 mmol/L improve detection rate of patients with monogenic familial hypercholesterolaemia?

A previous report suggested that 88% of individuals in the general population with total cholesterol (TC) > 9.3 mmol/L have familial hypercholesterolaemia (FH). We tested this hypothesis in a cohort of 4896 UK civil servants, mean (SD) age 44 (±6) years, using next generation sequencing to achieve a comprehensive genetic diagnosis. 25 (0.5%) participants (mean age 49.2 years) had baseline TC > 9.3 mmol/L, and overall we found an FH-causing mutation in the LDLR gene in seven (28%) subjects. The detection rate increased to 39% by excluding eight participants with triglyceride levels over 2.3 mmol/L, and reached 75% in those with TC > 10.4 mmol/L. By extrapolation, the detection rate would be ∼25% by including all participants with TC > 8.6 mmol/L (2.5 standard deviations from the mean). Based on the 1/500 FH frequency, 30% of all FH-cases in this cohort would be missed using the 9.3 mmol/L cut-off. Given that an overall detection rate of 25% is considered economically acceptable, these data suggest that a diagnostic TC cut-off of 8.6 mmol/L, rather than 9.3 mmol/L would be clinically useful for FH in the general population.

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28% of sequenced UK individuals with total cholesterol >9.3 mmol/L were found to have an FH mutation using NGS.

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Detection rate was higher (39%) in individuals with triglycerides lower than 2.3 mmol/L.

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By extrapolation, a 8.6 mmol/L (2.5 SD from the mean) cholesterol cut-off may be most economically sustainable.