Targeted next-generation sequencing to diagnose disorders of HDL cholesterol[S]

A low level of HDL cholesterol (HDL-C) is a common clinical scenario and an important marker for increased cardiovascular risk. Many patients with very low or very high HDL-C have a rare mutation in one of several genes, but identification of the molecular abnormality in patients with extreme HDL-C is rarely performed in clinical practice. We investigated the accuracy and diagnostic yield of a targeted next-generation sequencing (NGS) assay for extreme levels of HDL-C. We developed a targeted NGS panel to capture the exons, intron/exon boundaries, and untranslated regions of 26 genes with highly penetrant effects on plasma lipid levels. We sequenced 141 patients with extreme HDL-C levels and prioritized variants in accordance with medical genetics guidelines. We identified 35 pathogenic and probably pathogenic variants in HDL genes, including 21 novel variants, and performed functional validation on a subset of these. Overall, a molecular diagnosis was established in 35.9% of patients with low HDL-C and 5.2% with high HDL-C, and all prioritized variants identified by NGS were confirmed by Sanger sequencing. Our results suggest that a molecular diagnosis can be identified in a substantial proportion of patients with low HDL-C using targeted NGS.


Biochemical assays
ABCA1 cDNA sequences were cloned into the pCDNA3.1 vector and the W590L and R2200* mutations generated by sitedirected mutagenesis. Immunoblotting and immunofl uorescence in transiently transfected HEK293 cells were carried out as previously described ( 15 ). Cholesterol effl ux assays were performed, as previously described ( 15 ), in transiently transfected HEK293 cells. Data represent the mean ± SD of at least three independent experiments, each performed in triplicate.
LCAT assays were performed as recommended by the manufacturer (Calbiochem) using 5 l of human plasma. The fl uorescent intensities at 390 nm and 470 nm were measured at time = 0, 2, 4, and 8 h. LCAT activity was calculated as the rate of change in the ratio of fl uorescent intensities at 470 nm and 390 nm. Data represent the mean ± SD of three independent experiments, each performed in triplicate.

Statistical analyses
Results are presented as mean ± SD. Differences between groups were compared with two-tailed Student's t -test, or one-way ANOVA for three or more groups, or for comparison between proportions, chi-squared test. Calculations were performed in GraphPad Prism software. P < 0.05 was considered statistically signifi cant.

Sequencing extreme HDL-C patients
We generated a customized NGS panel to capture the exons, intron/exon boundaries, and fl anking untranslated regions (UTRs) of 26 genes with known roles in plasma lipid metabolism based on data from the HGMD and manual curation of the literature ( Table 1 ). We included genes in which rare variants are known to cause highly penetrant effects on plasma levels of HDL-C, LDL-C, TG, and lipoprotein (a), as well as on the response to lipid-lowering therapy. We generated a probe library using Nimblegen SeqCap technology to capture these targets.
To assess the accuracy and diagnostic yield of this panel, we sequenced 141 patients with extreme levels of HDL-C, including 64 patients with extremely low HDL-C and 77 patients with extremely high HDL-C. This patient population was hypothesized to harbor a substantial percentage of damaging variants in HDL-related genes (5)(6)(7)(8)(9)(10)(11)(12). The clinical characteristics of these patients are shown in Table 2 . Patients with low HDL-C also had lower total plasma cholesterol and LDL-C, as well as higher TGs, higher BMI, and a higher frequency of diabetes mellitus, consistent with previous observations ( 17 ). Most patients in both groups were of self-reported European ancestry.
We performed high-throughput sequencing of this cohort to a mean depth of 1,559 ± 290 reads per base after quality and diagnostic yield of a targeted NGS panel to establish the molecular diagnosis of abnormal HDL-C in a range of patients with extreme HDL phenotypes visiting a specialty lipid clinic. Our results indicate that this approach can reliably and accurately identify pathogenic variants in a substantial proportion of patients with low levels of HDL-C.

Patients
We recruited consecutive patients with HDL-C levels below the 10th percentile or greater than the 90th percentile using ageand gender-adjusted population data from the Lipid Research Clinics ( 14 ), hereafter referred to as "extreme HDL-C," regardless of other lipid parameters, from the Healthy Heart Program Prevention Clinic at St. Paul's Hospital, Vancouver, Canada, a large specialty lipid clinic serving a multi-ethnic patient population. We did not attempt to exclude patients with potential secondary causes of low HDL-C (e.g., hypertriglyceridemia) or high HDL-C (e.g., alcohol use). Related individuals were not specifically recruited. Patients were excluded if they could not speak English or were unable or unwilling to provide written informed consent. As a positive control, we included patients in whom a molecular diagnosis of a Mendelian disorder of HDL had previously been established by Sanger sequencing ( 15 ). Clinical data were abstracted from the patients' medical records. In cases where multiple sets of laboratory values were available, we used the most recent values. All subjects provided written informed consent. This study was approved by the Clinical Research Ethics Board of the University of British Columbia.

DNA sequencing
DNA was isolated from venous blood samples using DNeasy kits (Qiagen) or saliva using Oragene kits (DNA Genotek) and quantifi ed using the Quant-iT PicoGreen assay (Life Technologies). Sequencing libraries were prepared according to the manufacturer's instructions (Illumina, San Diego, CA). In-solution hybridization capture was performed with SeqCap EZ library reagents (Roche-Nimblegen). Captured DNA was quantifi ed by the KAPA system (Kapa Biosystems) and diluted to a fi nal concentration of 5 nM. Sequencing was performed on an Illumina MiSeq instrument in 2 × 151 bp mode. Reads were mapped to the reference human genome (hg19) using Burrows-Wheeler alignment tool v0.5.9 in paired read mode (maximal exact match algorithm) and processed following the recommended guidelines by the Genome Analysis Toolkit "Best Practices for Variant Calling" (available at http://www.broadinstitute.org/genome-analysis-toolkit) . Variants were called using the Genome Analysis Toolkit v3 Unifi ed Genotyper. We applied the following variant-level and genotype-level quality fi lters for variant calling: quality by depth (QD) < 2.0; root mean square of mapping quality (MQ) < 40.0; rank sum test of mapping quality (MQRankSum) < Ϫ 12.5; rank sum test of read position (ReadPosRankSum) < Ϫ 8.0, <20 times base coverage; <Q20 genotype quality; and allele balance <0.15 for heterozygous calls and <0.85 for homozygous calls. All single nucleotide variants and indels that passed these quality control fi lters were annotated with the SIFT, Polyphen 2 [HumDiv], Polyphen 2 [HumVar], PROVEAN, and Condel tools, and matched against public databases of variants (1000 Genomes, HapMap, and National Heart, Lung, and Blood Institute exome variant server) . We then prioritized variants in HDL genes according to the following criteria: 1 ) variants that are reported to be disease-causing in the Human Gene Mutation Database three novel variants in LCAT , two novel variants in each of APOA1 , NPC1 , LIPG , and one novel variant in each of CETP and SCARB1 ( Table 3 ).
Of note, three patients with extremely low HDL-C were found to harbor homozygous or compound heterozygous mutations in the APOA1 , ABCA1 , and LCAT genes ( Table 4 ). This included a 43-year-old female subject [patient identifi cation number (ID) 114] with extremely low HDL-C (0.1 mmol/l) and ApoA-I (0.05 g/l), found to be homozygous for a novel premature truncation in the APOA1 gene (p.Arg34*); a 21-year-old male subject (patient ID 18301) with near undetectable HDL-C (0.1 mmol/l) found to be fi ltering. Ninety-three percent of target bases were covered by 20 or more reads. Ninety-four percent of targeted exons had у 50% of bases covered with an average of 15 or more reads. The mean GC (guanine-cytosine) content of exons with <50% of bases covered with 15 or more reads was 70.8 ± 4% compared with 52.0 ± 8% for exons with у 50% of bases covered with 15 or more reads, suggesting that local genomic features interfered with the capture of these loci .
We identifi ed 668 variants that met quality fi ltering criteria, including 357 exonic variants, 37 intronic variants, 212 3 ′ UTR variants, 37 5 ′ UTR variants, 18 variants downstream of the 3 ′ UTR, and 7 variants upstream of 5 ′ UTR. We then prioritized these variants (supplementary Fig. 1) based on established medical genetics recommendations ( 18 ), as follows. Variants known to be disease-causing for abnormalities of HDL-C in HGMD were designated as "pathogenic." Novel or rare variants (MAF <1% in public databases and MAF <4% in study samples) in HDL-related genes were designated as "probably pathogenic" if they resulted in a premature stop, indel, or splice site alteration, or for missense variants, if they were predicted to be deleterious by fi ve different variant prediction algorithms (SIFT, Polyphen 2 [HumDiv], Polyphen 2 [HumVar], PROVEAN, and Condel).
Thirty-fi ve variants in 38 individuals met these prioritization criteria, including 29 variants in low HDL-C genes and 6 variants in high HDL-C genes ( Table 3 ). Among the 35 patients with prioritized variants, 10 patients (28.5%) had >1 variant. Variants in the ABCA1 gene were most frequent, followed by variants in LCAT . No variants that met our prioritization criteria were identifi ed in APOA2 , GALNT2 , APOC3 , or PLTP . Twenty-one of the prioritized variants we identifi ed were novel, including ten novel variants in ABCA1 ,  CETP , a known high HDL-C-causing variant that is present in 2-3% of individuals of Asian ancestry, but absent in individuals of European ancestry (http://www.1000genomes. org) . One patient with low HDL-C (0.52 mmol/l) was heterozygous for both a novel 2 bp insertion in ABCA1 leading to premature protein truncation (p.Glu1902Ilefs*1912) and a novel predicted damaging mutation in SCARB1 (p.Gly239Arg). This observation is consistent with previous data that mutations in ABCA1 are dominant to the effects of mutations in SCARB1 ( 21 ).
The distribution of prioritized alleles in genes known to cause low HDL-C was highly skewed toward patients with low HDL-C, with 44/50 (88%) of such alleles occurring in patients with low HDL-C and only 6/50 (12%) in patients with high HDL-C. Similarly, 83% of prioritized alleles in genes known to cause high HDL-C were observed in patients with high HDL-C. Among patients with low HDL-C, 34/35 (97.1%) of the prioritized alleles observed were in genes known to cause low HDL-C, and only 2.9% were in genes known to cause high HDL-C. These observations suggest that our prioritization criteria were effective, in general, at identifying variants with penetrant effects on compound heterozygous for one known disease-causing mutation in ABCA1 (p.Trp590Leu) and one novel premature truncation in ABCA1 (p.Arg2200*); and a 21-year-old male subject (patient ID 34) with extremely low HDL-C (0.1 mmol/l) and less severely reduced ApoA-I levels (0.9 g/l), found to be homozygous for a novel predicted deleterious missense variant in LCAT (p.Thr348Ile), as well as heterozygous for a previously identifi ed variant in ABCA1 (p.Val2244Ile) ( 19 ). These results established molecular diagnoses of the rare Mendelian disorders ApoA-I deficiency, Tangier disease, and familial LCAT defi ciency, respectively, in these three individuals. Another individual (patient ID 35) who is the sibling of patient ID 34 and had a less dramatic reduction in HDL-C (0.5 mmol/l) was found to be heterozygous for the same LCAT variant (p.Thr348Ile), establishing a gene-dosage relationship for this variant with HDL-C levels.
One individual with extremely high HDL-C (3.2 mmol/l) was compound heterozygous for two known disease-causing variants in LIPG , p.Arg476Trp, and p.Ile239Thr ( 20 ). One individual of self-reported Japanese ancestry with high HDL-C (1.9 mmol/l) was heterozygous for p.Asp459Gly in  MAF is based on 1000 Genomes CEU (Utah residents with ancestry from northern and western Europe) data. Functional prediction based on SIFT. DM, disease-causing mutation in HGMD; DP, disease-associated polymorphism in HGMD; Ref. Seq., reference sequence; Nuc., nulceotide; rsID, reference SNP identifi cation. Phenotype refers to whether the variant was detected in a patient (or patients) with low HDL-C, high HDL-C, or in both groups of patients .
with low HDL-C and vice versa). We excluded variants in NPC1 from this analysis because of the observation that a similar proportion of patients with high versus low HDL-C had variants in this gene. Overall, a molecular diagnosis was established in 23 out of 64 patients with low HDL-C (35.9%) and 4 out of 77 patients with high HDL-C (5.2%) ( Table 4 ). The percentage of patients in whom a molecular diagnosis was made did not appreciably change when we excluded patients of non-European ancestry [patients with a molecular diagnosis 15/46 (32.6%) with low HDL-C and 3/63 (4.8%) with high HDL-C], suggesting that these results were not substantially affected by population stratifi cation.
Within the low HDL-C group of patients, HDL-C levels were signifi cantly lower among those in whom a molecular diagnosis was made compared with those in whom no molecular diagnosis was made (0.51 ± 0.2 mmol/l vs. 0.74 ± 0.1 mmol/l, P < 0.0001) ( Fig. 1 ). Similarly, within the low HDL-C group, patients in whom a molecular diagnosis was made had lower TG levels (2.44 ± 1.6 mmol/l vs. 4.52 ± 3.9 mmol/l, P = 0.02) and a trend toward a lower prevalence of type 2 diabetes (13.0% vs. 36.6%, P = 0.08), compared with those in whom no molecular diagnosis was made. In contrast, among patients with high HDL-C, the HDL-C level the lipid phenotypes in question. A notable exception is the NPC1 gene, in which we detected pathogenic or probably pathogenic variants in two individuals with low HDL-C (3.1% of low HDL-C patients) and two individuals with high HDL-C (2.6% of high HDL-C patients), all in the heterozygous state, suggesting that these variants may not contribute to the differences in HDL-C in these patients.
We performed Sanger sequencing of PCR amplicons to confi rm the 35 prioritized variants, present as 50 genotypes. All 50 of these genotypes were bi-directionally confi rmed by Sanger sequencing, indicating that the NGS assay had 100% concordance with the gold standard (95% confi dence interval 92.9-100.0%). We also assessed the reproducibility of the NGS assay by performing technical replication of one sample in two independent NGS runs. After quality fi ltering was performed, we observed 100% concordance in quality fi ltered variant calls between runs .

Diagnostic yield for extreme HDL-C
We considered a molecular diagnosis to have been made if a patient had a pathogenic or probably pathogenic variant detected in a gene known to cause the phenotype present in that patient (i.e., in a low HDL-C gene in a patient known disease-causing rare mutations in the ABCA1 gene previously identifi ed by Sanger sequencing ( 15 ). This included fi ve individuals heterozygous for missense mutations in ABCA1 and one individual compound heterozygous for mutations in ABCA1 . All seven genotypes were correctly identifi ed by NGS. However, it is noteworthy that one of these mutations, c.4176-11T>G, previously shown to be pathogenic ( 15 ), would not have passed conservative prioritization criteria based on its distance from the intron/exon junction (11 nucleotides upstream of the exon start site).

Functional signifi cance of pathogenic variants
To investigate the functional signifi cance of variants identifi ed by our prioritization approach, we performed functional validation of a subset of these variants. We generated the ABCA1 p.Trp590Leu and p.Arg2200* variants, identifi ed in patient ID 18301, and transiently expressed them in HEK293 cells. Both variants displayed similar levels of protein expression by Western blot ( Fig. 2A ) and similar patterns of subcellular localization by immunofl uorescence ( Fig. 2B ), as compared with wild-type ABCA1. We then tested the ability of cells transfected with these variants to effl ux radiolabeled cholesterol in response to ApoA-I. The p.Arg2200* variant displayed complete abrogation of ApoA-I-dependent cholesterol effl ux activity, whereas the p.Trp590Leu variant displayed an ‫ف‬ 50% reduction in effl ux compared with wild-type ABCA1 ( Fig. 2C ), indicating that these two variants represent complete and did not differ between those with or without a molecular diagnosis (2.42 ± 0.5 mmol/l vs. 2.47 ± 0.4 mmol/l, P = 0.8).

Identifi cation of known mutations
To assess the sensitivity of our assay to detect previously identifi ed mutations, we sequenced six patients with Fig. 1. HDL-C levels in patients with or without a molecular diagnosis of low HDL. Each patient is represented by one column in order of increasing HDL-C level from left to right. Red columns indicate patients in whom a molecular diagnosis of low HDL-C was made by NGS, and blue columns indicate those in whom no molecular diagnosis of low HDL-C was made.

Fig. 2. Functional characterization of variants in ABCA1.
A: Western blot analysis showing normal protein expression of wild-type and mutant ABCA1. The two ABCA1 variants, as well as wild-type ABCA1, were generated in vitro and expressed in HEK293 cells. Cell lysates were probed with antibodies to ABCA1 and calnexin (as loading control). Neg, negative control. B: Immunofl uorescence results showing normal subcellular localization of wild-type, W590L, and R2200* ABCA1 proteins. C: HEK293 cells were transiently transfected with wild-type, W590L, and R2200* ABCA1, and cholesterol effl ux measured in the presence or absence of ApoA-I. # Indicates a statistically significant difference compared with mock transfected and * indicates a statistically signifi cant difference compared with wild-type ABCA1 at P < 0.05 using a oneway ANOVA. pathogenic variants that impact HDL-C; 2 ) the report of several novel variants in HDL-related genes with associated clinical phenotypes and functional validation of a subset of these; and 3 ) that a molecular diagnosis can be established in a substantial percentage of patients with extremely low HDL-C visiting a specialty lipid clinic.
Our results showed high analytic accuracy of this assay to detect pathogenic variants. It is noteworthy that while our assay accurately detected a known pathogenic mutation in the ABCA1 gene (c.4176-11T>G) ( 15 ) with high levels of confi dence (Q > 30, 3,188 depth of coverage), the location of this mutation, 11 nucleotides 5 ′ of the start of an exon, means that it would have been excluded by most conservative prioritization approaches that generally identify splice site variants two nucleotides up-or downstream of the intron/exon junction . This example highlights the ongoing challenge of determining pathogenicity by computational approaches.
We showed that the NGS assay could successfully identify the molecular causes of rare Mendelian disorders of HDL-C, namely, ApoA-I defi ciency, Tangier disease, and familial LCAT defi ciency. Notably, none of these three patients displayed the classical physical examination fi ndings associated with these conditions (i.e., enlarged yellow tonsils in Tangier disease or corneal opacities in familial LCAT defi ciency). This suggests that the sequencing-based approach described here may be more sensitive to identify patients with rare Mendelian disorders of HDL-C compared with an approach based on classical stigmata of these conditions. Previously, we have employed Sanger sequencing to identify pathogenic mutations in patients with Mendelian disorders of HDL-C ( 15 ). For large genes such as ABCA1 (50 exons), this approach is costly, laborintensive, time-consuming, and generally requires sequential testing of candidate genes if no pathogenic mutation is identifi ed in the initial screening. In contrast, the targeted resequencing strategy we describe here allows processing of multiple samples and multiple genes in parallel, thus substantially reducing both the cost and time on a per-patient and per-gene basis.
While our study was designed primarily to detect known pathogenic variants, it is noteworthy that 21 of the prioritized variants we detected were novel. Importantly, we confi rmed functionality of some of these variants by demonstrating either reduced activity in vitro or reduced enzyme activity ex vivo. These results highlight the research and discovery potential of targeted gene panels for both known disease genes and important candidate genes. In this regard, we included NPC1 as a candidate gene based on the observation that patients with the autosomal recessive disorder, Niemann-Pick disease, have reduced levels of plasma HDL-C ( 24-26 ). Our results showing a similar proportion of patients with low versus high HDL-C carrying predicted damaging variants in NPC1 (3.1% vs. 2.6%) do not support a role for heterozygous variants in this gene causing low HDL-C in the general population. For this reason, we did not consider the fi nding of a pathogenic or probably pathogenic variant in NPC1 to constitute a molecular diagnosis of low HDL-C. Larger sample sizes and partial loss-of-function alleles, respectively. Similar results have been reported previously for another mutation in ABCA1 (p.Trp590Ser) that affects the same amino acid position ( 22 ).
We measured LCAT activity in plasma from six individuals with variants in the LCAT gene compared with four patients with wild-type LCAT and similar HDL-C levels. This included the novel variant p.Thr348Ile, observed in one patient in the homozygous state and in one patient in the heterozygous state. We also included the p.Ser232Thr and p.Gly368Val variants, both of which have been previously reported to cause low HDL-C ( 5, 23 ), but have not been functionally characterized. We observed p.Ser232Thr in three patients and p.Gly368Val in one patient, all in the heterozygous state. Relative to patients with wild-type LCAT and similar HDL-C levels, heterozygotes for either p.Ser232Thr or p.Thr348Ile variants had signifi cant reductions in plasma LCAT activity, with some residual activity ( Fig. 3 ). The patient homozygous for p.Thr348Ile, as well as the patient heterozygous for p.Gly368Val, had complete abrogation of LCAT activity with residual activity that was not signifi cantly different than the negative control sample . These data indicate that patients with these variants in LCAT have impaired plasma LCAT activity, consistent with the concept that these variants represent loss-of-function alleles.

DISCUSSION
We have described a targeted NGS panel for molecular diagnosis of disorders of lipid metabolism. We assessed the performance of this panel in a population of patients with extreme HDL-C levels without previously identifi ed mutations, as well as a collection of patients with known rare mutations that impact HDL-C. The major fi ndings of this study are: 1 ) that this panel is highly accurate and has high analytic sensitivity to identify pathogenic and probably Fig. 3. LCAT activity in plasma from patients with wild-type or variant LCAT genes. LCAT activity was determined in plasma using a fl uorescent assay. Values represent the mean ± SD of triplicate samples from individual patients unless otherwise indicated. # Indicates a statistically signifi cant difference compared with negative control and * indicates a statistically signifi cant difference compared with wild-type, both at P < 0.05 using a one-way ANOVA. despite applying stringent prioritization criteria, it is not possible to conclusively determine the pathogenicity of novel variants by computational methods alone. This is particularly the case for missense variants, and it is likely that some of the novel missense variants detected in our study that were predicted to be damaging are in fact benign. We used a relatively stringent bioinformatics approach, by requiring that fi ve different computational algorithms all agreed in their predictions that a novel missense variant was deleterious, for us to classify it as probably pathogenic . Notwithstanding the limitations of bioinformatics approaches to predict functionality, our functional validation of a subset of novel variants provides confi dence that many of the variants detected in this study are functional. In addition, the prioritized variants showed strong enrichment with the associated phenotype: 88% of prioritized alleles in low HDL genes were in patients with low HDL-C. In contrast, analysis of all rare coding variants in low HDL-C genes without prioritization displayed a more equal distribution: 60% of rare nonprioritized coding alleles in low HDL genes were in patients with low HDL-C. This indicates that our prioritization approach selected variants with penetrant effects on these lipid phenotypes. Lastly, we biochemically characterized only a subset of the variants detected. While our functional data is consistent with the concept that many of the variants we detected do impair the function of the encoded proteins, we did not perform exhaustive functional characterization of all novel variants detected. This also refl ects the reality of clinical practice, in which novel variants are frequently discovered but functional characterization may not be possible.
Identifying the molecular cause of HDL-C or other lipid or lipoprotein parameters provides diagnostic closure and allows rapid cascade screening in the family members of affected individuals. In patients with mutations causing elevated LDL-C, introduction of a molecular diagnostic program has been shown to signifi cantly increase the appropriate use of lipid-lowering therapy ( 28,29 ). Similarly, identifi cation of molecular abnormalities in patients with low HDL-C could guide personalized cardiovascular prevention and risk-reduction strategies, and may improve patient compliance with therapeutic lifestyle modifi cation or pharmacological interventions. Moreover, targeted therapies for specifi c disorders of HDL metabolism are in development ( 30,31 ), and the identifi cation of specifi c molecular defects in patients with abnormal HDL-C levels may identify candidates for these future therapies.
In summary, we have described a novel targeted NGS panel for disorders of lipid metabolism. Our validation study in patients with extreme levels of HDL-C indicates that this assay is highly accurate for the identifi cation of pathogenic variants and that the diagnostic yield of such an approach is high, particularly among patients with very low HDL-C. Targeted sequencing approaches hold the promise to refi ne diagnostic categories and may lead to new opportunities for personalized treatment and prevention strategies in patients with abnormalities of plasma lipid levels.
The authors thank the patients who participated in this study. functional testing may help to clarify the impact of rare heterozygous variants in NPC1 on HDL-C levels.
One previous study evaluated the use of a targeted NGS panel for lipid disorders in patients with abnormal TG or LDL-C levels and in patients with lipodystrophy and maturityonset diabetes of the young ( 27 ). That study also reported a high level of analytic accuracy in detecting known mutations (95.2%). The mean depth of coverage achieved by that assay (345.1×) was substantially less than was achieved by our assay (1,559×), which relates to the smaller genomic capture region of our assay. Together with these previous results on disorders of TG and LDL-C, the current study, demonstrating high accuracy to identify pathogenic variants causing abnormalities of HDL-C, suggest that targeted NGS panels can accurately identify pathogenic variants across the entire range of clinical dyslipidemias.
We identifi ed a pathogenic or probably pathogenic variant in 35.9% of patients with low HDL-C, suggesting a high diagnostic yield in this patient population. Notably, among patients with low HDL-C, the HDL-C level was signifi cantly lower among those in whom a pathogenic variant was identifi ed compared with those in whom no such variant was identifi ed ( Fig. 1 ). This suggests that identifi cation of a molecular defect in patients with low HDL-C may identify a more extreme subpopulation of patients, and likewise, that the diagnostic yield will be highest among patients with the lowest levels of HDL-C. Indeed, had we included only patients with an HDL-C of less than or equal to 0.7, 0.6, or 0.5 mmol/l, the molecular diagnosis rate would have increased to 51.2, 65.2, or 91.7%, respectively. This further indicates that these established HDL genes account for the vast majority of cases of extremely low HDL-C, and that there are likely to be few additional major genes causing this phenotype that remain to be discovered. The observation that patients with low HDL-C in whom no pathogenic variant was identifi ed had higher TG levels and a trend toward a higher prevalence of diabetes mellitus is consistent with the concept that the low HDL-C phenotype in these patients may be secondary to other metabolic factors, rather than being primarily due to a major genetic cause.
In contrast to the low HDL-C group, the diagnostic yield in patients with extremely high HDL-C was lower in our cohort (5.2%), suggesting that there may be additional unknown genetic or nongenetic factors that impact this phenotype, or alternatively, that a greater proportion of such patients have multiple variants in genes with more modest effect sizes that may not have been detected by our approach ( 12 ).
There are several limitations of our study. Our assay was primarily designed to detect single nucleotide variants and small indels. As such, larger indels or complex rearrangements may not have been detected. As bioinformatics approaches to identifying structural and copy number variants improve, it is expected that detection of this category of variant will increase. Importantly, out of the 200 curated mutations in the ABCA1 gene, only 6 (3%) are large indels or complex rearrangements, suggesting that the majority of pathogenic variants will be detected by our assay. Second,