Posttranscriptional Regulation of the Human LDL Receptor by the U2-Spliceosome.

BACKGROUND: The LDLR (low-density lipoprotein receptor) in the liver is the major determinant of LDL-cholesterol levels in human plasma. The discovery of genes that regulate the activity of LDLR helps to identify pathomechanisms of hypercholesterolemia and novel therapeutic targets against atherosclerotic cardiovascular disease. METHODS: We performed a genome-wide RNA interference screen for genes limiting the uptake of fluorescent LDL into Huh-7 hepatocarcinoma cells. Top hit genes were validated by in vitro experiments as well as analyses of data sets on gene expression and variants in human populations. RESULTS: The knockdown of 54 genes significantly inhibited LDL uptake. Fifteen of them encode for components or interactors of the U2-spliceosome. Knocking down any one of 11 out of 15 genes resulted in the selective retention of intron 3 of LDLR. The translated LDLR fragment lacks 88% of the full length LDLR and is detectable neither in nontransfected cells nor in human plasma. The hepatic expression of the intron 3 retention transcript is increased in nonalcoholic fatty liver disease as well as after bariatric surgery. Its expression in blood cells correlates with LDL-cholesterol and age. Single nucleotide polymorphisms and 3 rare variants of one spliceosome gene, RBM25, are associated with LDL-cholesterol in the population and familial hypercholesterolemia, respectively. Compared with overexpression of wild-type RBM25, overexpression of the 3 rare RBM25 mutants in Huh-7 cells led to lower LDL uptake. CONCLUSIONS: We identified a novel mechanism of posttranscriptional regulation of LDLR activity in humans and associations of genetic variants of RBM25 with LDL-cholesterol levels.

Prevalence of FH-Causing Variants and Impact on LDL-C Concentration in European, South Asian, and African Ancestry Groups of the UK Biobank-Brief Report.

BACKGROUND: Familial hypercholesterolemia (FH) is a monogenic disease that causes high low-density lipoprotein cholesterol (LDL-C) and higher risk of premature coronary heart disease. The prevalence of FH-causing variants and their association with LDL-C in non-European populations remains largely unknown. Using DNA diagnosis in a population-based cohort, we aimed to estimate the prevalence of FH across 3 major ancestry groups in the United Kingdom. METHODS: Principal component analysis was used to distinguish genetic ancestry in UK Biobank participants. Whole exome sequencing data were analyzed to provide a genetic diagnosis of FH. LDL-C concentrations were adjusted for statin use. RESULTS: Principal component analysis distinguished 140 439 European, 4067 South Asian, and 3906 African participants with lipid and whole exome sequencing data. There were significant differences between the 3 groups, including total and LDL-C concentrations, and prevalence and incidence of coronary heart disease. We identified 488, 18, and 15 participants of European, South Asian, and African ancestry carrying a likely pathogenic or pathogenic FH-variant. No statistical difference in the prevalence of an FH-causing variant was observed: 1 out of 288 (95% CI, 1/316-1/264) in European, 1 out of 260 (95% CI, 1/526-1/173) in African, and 1 out of 226 (95% CI, 1/419-1/155) in South Asian. Carriers of an FH-causing variant had significantly higher LDL-C concentration than noncarriers in every ancestry group. There was no difference in median (statin-use adjusted) LDL-C concentration in FH-variant carriers depending on their ancestry background. Self-reported statin use was nonsignificantly highest in FH-variant carriers of South Asian ancestry (55.6%), followed by African (40.0%) and European (33.8%; P=0.15). CONCLUSIONS: The prevalence of FH-causing variants in the UK Biobank is similar across the ancestry groups analyzed. Despite overall differences in lipid concentrations, FH-variant carriers across the 3 ancestry groups had similar LDL-C levels. In all ancestry groups, the proportion of FH-variant carriers treated with lipid-lowering therapy should be improved to reduce future risk of premature coronary heart disease.

Alpha-protein kinase 3 (ALPK3) truncating variants are a cause of autosomal dominant hypertrophic cardiomyopathy.

AIMS: The aim of this study was to determine the frequency of heterozygous truncating ALPK3 variants (ALPK3tv) in patients with hypertrophic cardiomyopathy (HCM) and confirm their pathogenicity using burden testing in independent cohorts and family co-segregation studies. METHODS AND RESULTS: In a discovery cohort of 770 index patients with HCM, 12 (1.56%) were heterozygous for ALPK3tv [odds ratio(OR) 16.11, 95% confidence interval (CI) 7.94-30.02, P = 8.05e-11] compared to the Genome Aggregation Database (gnomAD) population. In a validation cohort of 2047 HCM probands, 32 (1.56%) carried heterozygous ALPK3tv (OR 16.17, 95% CI 10.31-24.87, P < 2.2e-16, compared to gnomAD). Combined logarithm of odds score in seven families with ALPK3tv was 2.99. In comparison with a cohort of genotyped patients with HCM (n = 1679) with and without pathogenic sarcomere gene variants (SP+ and SP-), ALPK3tv carriers had a higher prevalence of apical/concentric patterns of hypertrophy (60%, P < 0.001) and of a short PR interval (10%, P = 0.009). Age at diagnosis and maximum left ventricular wall thickness were similar to SP- and left ventricular systolic impairment (6%) and non-sustained ventricular tachycardia (31%) at baseline similar to SP+. After 5.3 ± 5.7 years, 4 (9%) patients with ALPK3tv died of heart failure or had cardiac transplantation (log-rank P = 0.012 vs. SP- and P = 0.425 vs. SP+). Imaging and histopathology showed extensive myocardial fibrosis and myocyte vacuolation. CONCLUSIONS: Heterozygous ALPK3tv are pathogenic and segregate with a characteristic HCM phenotype.

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.

The UK10K project identifies rare variants in health and disease.

The contribution of rare and low-frequency variants to human traits is largely unexplored. Here we describe insights from sequencing whole genomes (low read depth, 7×) or exomes (high read depth, 80×) of nearly 10,000 individuals from population-based and disease collections. In extensively phenotyped cohorts we characterize over 24 million novel sequence variants, generate a highly accurate imputation reference panel and identify novel alleles associated with levels of triglycerides (APOB), adiponectin (ADIPOQ) and low-density lipoprotein cholesterol (LDLR and RGAG1) from single-marker and rare variant aggregation tests. We describe population structure and functional annotation of rare and low-frequency variants, use the data to estimate the benefits of sequencing for association studies, and summarize lessons from disease-specific collections. Finally, we make available an extensive resource, including individual-level genetic and phenotypic data and web-based tools to facilitate the exploration of association results.

The familial hypercholesterolaemia phenotype: Monogenic familial hypercholesterolaemia, polygenic hypercholesterolaemia and other causes.

Familial hypercholesterolaemia (FH) is a monogenic disorder characterised by high low-density lipoprotein cholesterol (LDL-C) concentrations and increased cardiovascular risk. However, in clinically defined FH cohorts worldwide, an FH-causing variant is only found in 40%-50% of the cases. The aim of this work was to characterise the genetic cause of the FH phenotype in Portuguese clinical FH patients. Between 1999 and 2017, 731 index patients (311 children and 420 adults) who met the Simon Broome diagnostic criteria had been referred to our laboratory. LDLR, APOB, PCSK9, APOE, LIPA, LDLRAP1, ABCG5/8 genes were analysed by polymerase chain reaction amplification and Sanger sequencing. The 6-SNP LDL-C genetic risk score (GRS) for polygenic hypercholesterolaemia was validated in the Portuguese population and cases with a GRS over the 25th percentile were considered to have a high likelihood of polygenic hypercholesterolaemia. An FH-causing mutation was found in 39% of patients (94% in LDLR, 5% APOB and 1% PCSK9), while at least 29% have polygenic hypercholesterolaemia and 1% have other lipid disorders. A genetic cause for the FH phenotype was found in 503 patients (69%). All known causes of the FH phenotype should be investigated in FH cohorts to ensure accurate diagnosis and appropriate management.

Polygenic Hypercholesterolemia and Cardiovascular Disease Risk.

PURPOSE OF THE REVIEW: Identification of loci and common single-nucleotide polymorphisms (SNPs) that have modest effects on plasma lipids have been used to confirm or refute the causal role of lipid traits in the development of coronary heart disease (CHD), and as tools to identify individuals with polygenic hypercholesterolemia. RECENT FINDINGS: Several groups have reported on the use of SNP scores in distinguishing individuals with a clinical diagnosis of familial hypercholesterolemia (FH) with a monogenic or polygenic etiology. We review evidence that those with monogenic FH have worse prognosis and discuss the possible mechanisms for this and their management. Individuals with a clinical phenotype of FH and a monogenic cause are at greater risk of CHD than those where no causative mutation can be found. The patients with polygenic hypercholesterolemia would not require elaborate cascade screening or secondary care input for their management.

The UCL low-density lipoprotein receptor gene variant database: pathogenicity update.

BACKGROUND: Familial hypercholesterolaemia (OMIM 143890) is most frequently caused by variations in the low-density lipoprotein receptor (LDLR) gene. Predicting whether novel variants are pathogenic may not be straightforward, especially for missense and synonymous variants. In 2013, the Association of Clinical Genetic Scientists published guidelines for the classification of variants, with categories 1 and 2 representing clearly not or unlikely pathogenic, respectively, 3 representing variants of unknown significance (VUS), and 4 and 5 representing likely to be or clearly pathogenic, respectively. Here, we update the University College London (UCL) LDLR variant database according to these guidelines. METHODS: PubMed searches and alerts were used to identify novel LDLR variants for inclusion in the database. Standard in silico tools were used to predict potential pathogenicity. Variants were designated as class 4/5 only when the predictions from the different programs were concordant and as class 3 when predictions were discordant. RESULTS: The updated database (http://www.lovd.nl/LDLR) now includes 2925 curated variants, representing 1707 independent events. All 129 nonsense variants, 337 small frame-shifting and 117/118 large rearrangements were classified as 4 or 5. Of the 795 missense variants, 115 were in classes 1 and 2, 605 in class 4 and 75 in class 3. 111/181 intronic variants, 4/34 synonymous variants and 14/37 promoter variants were assigned to classes 4 or 5. Overall, 112 (7%) of reported variants were class 3. CONCLUSIONS: This study updates the LDLR variant database and identifies a number of reported VUS where additional family and in vitro studies will be required to confirm or refute their pathogenicity.

Genetic Architecture of Familial Hypercholesterolaemia.

PURPOSE OF REVIEW: Familial hypercholesterolaemia (FH) is an inherited disorder of low-density lipoprotein cholesterol (LDL-C) which is characterised by a raised cholesterol level from birth and a high risk of premature coronary heart disease. In this paper, we review the genetic basis of FH and its impact on the clinical presentation. RECENT FINDINGS: 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 is most likely, due to the co-inheritance of common LDL-C-raising variants. The cardiovascular presentation and management of FH will differ between patients based on their underlying genetic factors. New genotyping methods such as next-generation sequencing will provide us with better understanding of the genetic architecture of FH.

Variants Within TSC2 Exons 25 and 31 Are Very Unlikely to Cause Clinically Diagnosable Tuberous Sclerosis.

Inactivating mutations in TSC1 and TSC2 cause tuberous sclerosis complex (TSC). The 2012 international consensus meeting on TSC diagnosis and management agreed that the identification of a pathogenic TSC1 or TSC2 variant establishes a diagnosis of TSC, even in the absence of clinical signs. However, exons 25 and 31 of TSC2 are subject to alternative splicing. No variants causing clinically diagnosed TSC have been reported in these exons, raising the possibility that such variants would not cause TSC. We present truncating and in-frame variants in exons 25 and 31 in three individuals unlikely to fulfil TSC diagnostic criteria and examine the importance of these exons in TSC using different approaches. Amino acid conservation analysis suggests significantly less conservation in these exons compared with the majority of TSC2 exons, and TSC2 expression data demonstrates that the majority of TSC2 transcripts lack exons 25 and/or 31 in many human adult tissues. In vitro assay of both exons shows that neither exon is essential for TSC complex function. Our evidence suggests that variants in TSC2 exons 25 or 31 are very unlikely to cause classical TSC, although a role for these exons in tissue/stage specific development cannot be excluded.

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.

Refinement of variant selection for the LDL cholesterol genetic risk score in the diagnosis of the polygenic form of clinical familial hypercholesterolemia and replication in samples from 6 countries.

BACKGROUND: Familial hypercholesterolemia (FH) is an autosomal-dominant disorder caused by mutations in 1 of 3 genes. In the 60% of patients who are mutation negative, we have recently shown that the clinical phenotype can be associated with an accumulation of common small-effect LDL cholesterol (LDL-C)-raising alleles by use of a 12-single nucleotide polymorphism (12-SNP) score. The aims of the study were to improve the selection of SNPs and replicate the results in additional samples. METHODS: We used ROC curves to determine the optimum number of LDL-C SNPs. For replication analysis, we genotyped patients with a clinical diagnosis of FH from 6 countries for 6 LDL-C-associated alleles. We compared the weighted SNP score among patients with no confirmed mutation (FH/M-), those with a mutation (FH/M+), and controls from a UK population sample (WHII). RESULTS: Increasing the number of SNPs to 33 did not improve the ability of the score to discriminate between FH/M- and controls, whereas sequential removal of SNPs with smaller effects/lower frequency showed that a weighted score of 6 SNPs performed as well as the 12-SNP score. Metaanalysis of the weighted 6-SNP score, on the basis of polymorphisms in CELSR2 (cadherin, EGF LAG 7-pass G-type receptor 2), APOB (apolipoprotein B), ABCG5/8 [ATP-binding cassette, sub-family G (WHITE), member 5/8], LDLR (low density lipoprotein receptor), and APOE (apolipoprotein E) loci, in the independent FH/M- cohorts showed a consistently higher score in comparison to the WHII population (P < 2.2 × 10(-16)). Modeling in individuals with a 6-SNP score in the top three-fourths of the score distribution indicated a >95% likelihood of a polygenic explanation of their increased LDL-C. CONCLUSIONS: A 6-SNP LDL-C score consistently distinguishes FH/M- patients from healthy individuals. The hypercholesterolemia in 88% of mutation-negative patients is likely to have a polygenic basis.

Whole exome sequencing of familial hypercholesterolaemia patients negative for LDLR/APOB/PCSK9 mutations.

BACKGROUND: Familial hypercholesterolaemia (FH) is an autosomal dominant disease of lipid metabolism, which leads to early coronary heart disease. Mutations in LDLR, APOB and PCSK9 can be detected in 80% of definite FH (DFH) patients. This study aimed to identify novel FH-causing genetic variants in patients with no detectable mutation. METHODS AND RESULTS: Exomes of 125 unrelated DFH patients were sequenced, as part of the UK10K project. First, analysis of known FH genes identified 23 LDLR and two APOB mutations, and patients with explained causes of FH were excluded from further analysis. Second, common and rare variants in genes associated with low-density lipoprotein cholesterol (LDL-C) levels in genome-wide association study (GWAS) meta-analysis were examined. There was no clear rare variant association in LDL-C GWAS hits; however, there were 29 patients with a high LDL-C SNP score suggestive of polygenic hypercholesterolaemia. Finally, a gene-based burden test for an excess of rare (frequency <0.005) or novel variants in cases versus 1926 controls was performed, with variants with an unlikely functional effect (intronic, synonymous) filtered out. CONCLUSIONS: No major novel locus for FH was detected, with no gene having a functional variant in more than three patients; however, an excess of novel variants was found in 18 genes, of which the strongest candidates included CH25H and INSIG2 (p<4.3×10(-4) and p<3.7×10(-3), respectively). This suggests that the genetic cause of FH in these unexplained cases is likely to be very heterogeneous, which complicates the diagnostic and novel gene discovery process.

The genetic architecture of the familial hyperlipidaemia syndromes: rare mutations and common variants in multiple genes.

PURPOSE OF REVIEW: Genome-Wide Association Studies have provided robust identification of approximately 100 genetic loci determining plasma lipid parameters. Using these multiple common genetic lipid-determining variants in a 'gene score' has thrown new light on the mode of inheritance of familial lipid disorders. RECENT FINDINGS: Different hypertriglyceridaemia states have been explained by the polygenic coinheritance of triglyceride-raising alleles. Taking this gene score approach with 12 LDL-cholesterol-raising alleles, we reported that for patients with a clinical diagnosis of familial hypercholesterolaemia, but no identified rare mutation in the familial hypercholesterolaemia-causing genes, LDL receptor, apolipoprotein B and PCSK9, the most likely explanation for their elevated LDL-C levels was a polygenic, not a monogenic, cause of the disease. SUMMARY: These findings have wider implications for understanding complex disorders, and may very well explain the genetic basis of familial combined hyperlipidaemia, another familial lipid disorder in which the genetic cause(s) has remained elusive.

Use of low-density lipoprotein cholesterol gene score to distinguish patients with polygenic and monogenic familial hypercholesterolaemia: a case-control study.

BACKGROUND: Familial hypercholesterolaemia is a common autosomal-dominant disorder caused by mutations in three known genes. DNA-based cascade testing is recommended by UK guidelines to identify affected relatives; however, about 60% of patients are mutation-negative. We assessed the hypothesis that familial hypercholesterolaemia can also be caused by an accumulation of common small-effect LDL-C-raising alleles. METHODS: In November, 2011, we assembled a sample of patients with familial hypercholesterolaemia from three UK-based sources and compared them with a healthy control sample from the UK Whitehall II (WHII) study. We also studied patients from a Belgian lipid clinic (Hôpital de Jolimont, Haine St-Paul, Belgium) for validation analyses. We genotyped participants for 12 common LDL-C-raising alleles identified by the Global Lipid Genetics Consortium and constructed a weighted LDL-C-raising gene score. We compared the gene score distribution among patients with familial hypercholesterolaemia with no confirmed mutation, those with an identified mutation, and controls from WHII. FINDINGS: We recruited 321 mutation-negative UK patients (451 Belgian), 319 mutation-positive UK patients (273 Belgian), and 3020 controls from WHII. The mean weighted LDL-C gene score of the WHII participants (0.90 [SD 0.23]) was strongly associated with LDL-C concentration (p=1.4 x 10(-77); R(2)=0.11). Mutation-negative UK patients had a significantly higher mean weighted LDL-C score (1.0 [SD 0.21]) than did WHII controls (p=4.5 x 10(-16)), as did the mutation-negative Belgian patients (0.99 [0.19]; p=5.2 x 10(-20)). The score was also higher in UK (0.95 [0.20]; p=1.6 x 10(-5)) and Belgian (0.92 [0.20]; p=0.04) mutation-positive patients than in WHII controls. 167 (52%) of 321 mutation-negative UK patients had a score within the top three deciles of the WHII weighted LDL-C gene score distribution, and only 35 (11%) fell within the lowest three deciles. INTERPRETATION: In a substantial proportion of patients with familial hypercholesterolaemia without a known mutation, their raised LDL-C concentrations might have a polygenic cause, which could compromise the efficiency of cascade testing. In patients with a detected mutation, a substantial polygenic contribution might add to the variable penetrance of the disease. FUNDING: British Heart Foundation, Pfizer, AstraZeneca, Schering-Plough, National Institute for Health Research, Medical Research Council, Health and Safety Executive, Department of Health, National Heart Lung and Blood Institute, National Institute on Aging, Agency for Health Care Policy Research, John D and Catherine T MacArthur Foundation Research Networks on Successful Midlife Development and Socio-economic Status and Health, Unilever, and Departments of Health and Trade and Industry.

A systematic evaluation of the performance and properties of the UK Biobank Polygenic Risk Score (PRS) Release.

We assess the UK Biobank (UKB) Polygenic Risk Score (PRS) Release, a set of PRSs for 28 diseases and 25 quantitative traits that has been made available on the individuals in UKB, using a unified pipeline for PRS evaluation. We also release a benchmarking software tool to enable like-for-like performance evaluation for different PRSs for the same disease or trait. Extensive benchmarking shows the PRSs in the UKB Release to outperform a broad set of 76 published PRSs. For many of the diseases and traits we also validate the PRS algorithms in a separate cohort (100,000 Genomes Project). The availability of PRSs for 53 traits on the same set of individuals also allows a systematic assessment of their properties, and the increased power of these PRSs increases the evidence for their potential clinical benefit.

Mutation detection in Croatian patients with familial hypercholesterolemia.

Familial hypercholesterolemia (FH) is caused by mutations in the genes for LDLR, APOB or PCSK9, and identification of the causative mutation provides definitive diagnosis so that the patient can be treated, their relatives tested and, therefore, premature heart disease prevented. DNA of eight unrelated individuals with clinically diagnosed FH were analyzed using a High-Resolution Melting method (HRM) for the LDLR gene (coding region, promoter and intron/exon boundaries), the APOB gene (part exon 26) and the PCSK9 gene (exon7). Variations found were sequenced and the effect on function of confirmed variants examined using predictive algorithms. Gross deletions and insertions were analysed using MLPA. Three novel LDLR variants were found, p.(S470C), p.(C698R) and c.2312-2A>C. All were predicted to be pathogenic using predictive algorithms. Three previously reported disease-causing mutations were identified (p.(G20R), p.(N272T) and p.(S286R); the latter was also carried by a hypercholesterolaemic relative. One patient carried the pathogenic APOB variant p.(R3527Q). No large LDLR deletions nor insertions were found, neither were any PCSK9 variants identified. HRM is a sensitive method for screening for mutations. While the causative mutation has been identified in 88% of these clinically defined FH patients, there appears to be a high degree of allelic heterogeneity in Croatian patients.

Use of targeted exome sequencing as a diagnostic tool for Familial Hypercholesterolaemia.

BACKGROUND: Familial Hypercholesterolaemia (FH) is an autosomal dominant disease, caused by mutations in LDLR, APOB or PCSK9, which results in high levels of LDL-cholesterol (LDL-C) leading to early coronary heart disease. An autosomal recessive form of FH is also known, due to homozygous mutations in LDLRAP1. This study assessed the utility of an exome capture method and deep sequencing in FH diagnosis. METHODS: Exomes of 48 definite FH patients, with no mutation detected by current methods, were captured by Agilent Human All Exon 50Mb assay and sequenced on the Illumina HiSeq 2000 platform. Variants were called by GATK and SAMtools. RESULTS: The mean coverage of FH genes varied considerably (PCSK9=23x, LDLRAP1=36x, LDLR=56x and APOB=93x). Exome sequencing detected 17 LDLR mutations, including three copy number variants, two APOB mutations, missed by the standard techniques, two LDLR novel variants likely to be FH-causing, and five APOB variants of uncertain effect. Two variants called in PCSK9 were not confirmed by Sanger sequencing. One heterozygous mutation was found in LDLRAP1. CONCLUSIONS: High-throughput DNA sequencing demonstrated its efficiency in well-covered DNA regions, in particular LDLR. This highly automated technology is proving to be effective for heterogeneous diseases and may soon replace laborious conventional methods. However, the poor coverage of gene promoters and repetitive, or GC-rich sequences, remains problematic, and validation of all identified variants is currently required.

A Machine Learning Model to Aid Detection of Familial Hypercholesterolemia.

Background: People with monogenic familial hypercholesterolemia (FH) are at an increased risk of premature coronary heart disease and death. With a prevalence of 1:250, FH is relatively common; but currently there is no population screening strategy in place and most carriers are identified late in life, delaying timely and cost-effective interventions. Objectives: The purpose of this study was to derive an algorithm to identify people with suspected monogenic FH for subsequent confirmatory genomic testing and cascade screening. Methods: A least absolute shrinkage and selection operator logistic regression model was used to identify predictors that accurately identified people with FH in 139,779 unrelated participants of the UK Biobank. Candidate predictors included information on medical and family history, anthropometric measures, blood biomarkers, and a low-density lipoprotein cholesterol (LDL-C) polygenic score (PGS). Model derivation and evaluation were performed in independent training and testing data. Results: A total of 488 FH variant carriers were identified using whole-exome sequencing of the low-density lipoprotein receptor, apolipoprotein B, apolipoprotein E, proprotein convertase subtilisin/kexin type 9 genes. A 14-variable algorithm for FH was derived, with an area under the curve of 0.77 (95% CI: 0.71-0.83), where the top 5 most important variables included triglyceride, LDL-C, apolipoprotein A1 concentrations, self-reported statin use, and LDL-C PGS. Excluding the PGS as a candidate feature resulted in a 9-variable model with a comparable area under the curve: 0.76 (95% CI: 0.71-0.82). Both multivariable models (w/wo the PGS) outperformed screening-prioritization based on LDL-C adjusted for statin use. Conclusions: Detecting individuals with FH can be improved by considering additional predictors. This would reduce the sequencing burden in a 2-stage population screening strategy for FH.