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

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Background Familial Hypercholesterolemia (FH) is an autosomal-dominant disorder caused by mutations in one of three 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-C-raising alleles using a 12-SNP score. The aims of the study were to improve the selection of SNPs, and to replicate the results in additional samples. Methods Receiver-operating characteristic curves were used to determine the optimum number of LDL-C SNPs. For replication analysis, we genotyped patients with a clinical diagnosis of FH from six countries for six 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 an 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, while sequential removal of SNPs with smaller effects/lower frequency showed a weighted score of six SNPs performed as well as the 12-SNP score. Meta-analysis of the weighted 6-SNP score, based on polymorphisms in CELSR2, APOB, ABCG5/8, LDLR and APOE 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 quarters of the score distribution, indicated a >95% likelihood of a polygenic explanation of their increased LDL-C. Conclusion A 6-SNP LDL-C score consistently distinguishes FH/M- patients from healthy subjects. The hypercholesterolemia in 88% of mutation-negative patients is likely to have a polygenic basis.

Purpose of ReviewFamilial 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 FindingsMutations 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.SummaryNew genotyping methods such as next-generation sequencing will provide us with better understanding of the genetic architecture of FH.

BackgroundFamilial 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 resultsExomes 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.ConclusionsNo 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.

AimTo determine the frequency and spectrum of mutations causing Familial Hypercholesterolaemia (FH) in patients attending a single UK specialist hospital lipid clinic in Oxford and to identify characteristics contributing to a high mutation detection rate.Methods289 patients (272 probands) were screened sequentially over a 2-year period for mutations in LDLR, APOB and PCSK9 using standard molecular genetic techniques. The Simon Broome (SB) clinical diagnostic criteria were used to classify patients and a separate cohort of 409 FH patients was used for replication.ResultsAn FH-causing mutation was found in 101 unrelated patients (LDLR = 54 different mutations, APOB p.(Arg3527Gln) = 10, PCSK9 p.(Asp374Tyr) = 0). In the 60 SB Definite FH patients the mutation detection rate was 73% while in the 142 with Possible FH the rate was significantly lower (27%, p < 0.0001), but similar (14%, p = 0.06) to the 70 in whom there was insufficient data to make a clinical diagnosis. The mutation detection rate varied significantly (p = 9.83 × 10−5) by untreated total cholesterol (TC) levels (25% in those <8.1 mmol/l and 74% in those >10.0 mmol/l), and by triglyceride levels (20% in those >2.16 mmol/l and 60% in those <1.0 mmol/l (p = 0.0005)), with both effects confirmed in the replication sample (p for trend = 0.0001 and p = 1.8 × 10−6 respectively). There was no difference in the specificity or sensitivity of the SB criteria versus the Dutch Lipid Clinic Network score in identifying mutation carriers (AROC respectively 0.73 and 0.72, p = 0.68).ConclusionsIn this genetically heterogeneous cohort of FH patients the mutation detection rate was significantly dependent on pre-treatment TC and triglyceride levels.

The analysis of rich catalogues of genetic variation from population-based sequencing provides an opportunity to screen for functional effects. Here we report a rare variant in APOC3 (rs138326449-A, minor allele frequency ~0.25% (UK)) associated with plasma triglyceride (TG) levels (−1.43 standard deviations (standard error (s.e.=0.27) per minor allele (p-value=8.0×10−8)) discovered in 3202 individuals with low read-depth, whole genome sequence. We replicate this in 12831 participants from five additional samples of Northern and Southern European origin (−1.0 standard deviation (s.e.=0.173), p-value=7.32×10−9). This is consistent with an effect between 0.5 and 1.5mmol/L dependent on population. We show that a single predicted splice donor variant is responsible for association signals and is independent of known common variants. Analyses suggest an independent relationship between rs138326449 and high-density lipoprotein (HDL) levels. This represents one of the first examples of a rare, large effect variant identified from whole-genome sequencing at a population scale.

BackgroundFamilial 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.MethodsPubMed 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.ResultsThe 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.ConclusionsThis 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.