Targeted next-generation sequencing to diagnose disorders of HDL cholesterol

Rare and common coding variants in lipid metabolism-related genes and their association with coronary artery disease

BACKGROUND

Coronary artery disease (CAD) is a complex disease that is influenced by environmental and genetic factors. In this study, we aimed to investigate the relationship between coding variants in lipid metabolism-related genes and CAD in a Chinese Han population.

METHODS

A total of 252 individuals were recruited for this study, including 120 CAD patients and 132 healthy control individuals. Rare and common coding variants in 12 lipid metabolism-related genes (ANGPTL3, ANGPTL4, APOA1, APOA5, APOC1, APOC3, CETP, LDLR, LIPC, LPL, PCSK9 and SCARB1) were detected via next-generation sequencing (NGS)-based targeted sequencing. Associations between common variants and CAD were evaluated by Fisher's exact test. A gene-based association test of rare variants was performed by the sequence kernel association test-optimal (SKAT-O test).

RESULTS

We found 51 rare variants and 17 common variants in this study. One common missense variant, LIPC rs6083, was significantly associated with CAD after Bonferroni correction (OR = 0.47, 95% CI = 0.29-0.76, p = 1.9 × 10- 3). Thirty-three nonsynonymous rare variants were identified, including two novel variants located in the ANGPTL4 (p.Gly47Glu) and SCARB1 (p.Leu233Phe) genes. We did not find a significant association between rare variants and CAD via gene-based analysis via the SKAT-O test.

CONCLUSIONS

Targeted sequencing is a powerful tool for identifying rare and common variants in CAD. The common missense variant LIPC rs6083 confers protection against CAD. The clinical relevance of rare variants in CAD aetiology needs to be investigated in larger sample sizes in the future.

Functional characterization of missense variants affecting the extracellular domains of ABCA1 using a fluorescence-based assay

Excess cholesterol originating from nonhepatic tissues is transported within HDL particles to the liver for metabolism and excretion. Cholesterol efflux is initiated by lipid-free or lipid-poor apolipoprotein A1 interacting with the transmembrane protein ABCA1, a key player in cholesterol homeostasis. Defective ABCA1 results in reduced serum levels of HDL cholesterol, deposition of cholesterol in arteries, and an increased risk of early onset CVD. Over 300 genetic variants in ABCA1 have been reported, many of which are associated with reduced HDL cholesterol levels. Only a few of these have been functionally characterized. In this study, we have analyzed 51 previously unclassified missense variants affecting the extracellular domains of ABCA1 using a sensitive, easy, and low-cost fluorescence-based assay. Among these, only 12 variants showed a distinct loss-of-function phenotype, asserting their direct association with severe HDL disorders. These findings emphasize the crucial role of functional characterization of genetic variants in pathogenicity assessment and precision medicine. The functional rescue of ABCA1 loss-of-function variants through proteasomal inhibition or by the use of the chemical chaperone 4-phenylbutyric acid was genotype specific. Genotype-specific responses were also observed for the ability of apolipoprotein A1 to stabilize the different ABCA1 variants. In view of personalized medicine, this could potentially form the basis for novel therapeutic strategies.

Rare Variants in Genes of the Cholesterol Pathway Are Present in 60% of Patients with Acute Myocardial Infarction

Acute myocardial infarction (AMI) is a pandemic in which conventional risk factors are inadequate to detect who is at risk early in the asymptomatic stage. Although gene variants in genes related to cholesterol, which may increase the risk of AMI, have been identified, no studies have systematically screened the genes involved in this pathway. In this study, we included 105 patients diagnosed with AMI with an elevation of the ST segment (STEMI) and treated with primary percutaneous coronary intervention (PPCI). Using next-generation sequencing, we examined the presence of rare variants in 40 genes proposed to be involved in lipid metabolism and we found that 60% of AMI patients had a rare variant in the genes involved in the cholesterol pathway. Our data show the importance of considering the wide scope of the cholesterol pathway in order to assess the genetic risk related to AMI.

Genetic Analysis of Japanese Children Clinically Diagnosed with Familial Hypercholesterolemia

AIM

This study aimed to elucidate the gene and lipid profiles of children clinically diagnosed with familial hypercholesterolemia (FH).

METHODS

A total of 21 dyslipidemia-related Mendelian genes, including FH causative genes (LDLR, APOB, and PCSK9) and LDL-altering genes (APOE, LDLRAP1, and ABCG5/8), were sequenced in 33 Japanese children (mean age, 9.7±4.2 years) with FH from 29 families.

RESULTS

Fifteen children (45.5%) with pathogenic variants in LDLR (eight different heterozygous variants) and one child (3.0%) with the PCSK9 variant were found. Among 17 patients without FH causative gene variants, 3 children had variants in LDL-altering genes, an APOE variant and two ABCG8 variants. The mean serum total cholesterol (280 vs 246 mg/dL), LDL-cholesterol (LDL-C, 217 vs 177 mg/dL), and non-HDL cholesterol (228 vs 188 mg/dL) levels were significantly higher in the pathogenic variant-positive group than in the variant-negative group. In the variant-positive group, 81.3% of patients had LDL-C levels ≥ 180 mg/dL but 35.3% in the variant-negative group. The mean LDL-C level was significantly lower in children with missense variants, especially with the p.Leu568Val variant, than in children with other variants in LDLR, whereas the LDL-altering variants had similar effects on the increase in serum LDL-C to LDLR p.Leu568Val.

CONCLUSION

Approximately half of the children clinically diagnosed with FH had pathogenic variants in FH causative genes. The serum LDL-C levels tend to be high in FH children with pathogenic variations, and the levels are by the types of variants. Genetic analysis is useful; however, further study on FH without any variants is required.

The design and rationale of the Advancing Cardiac Care Unit-based Rapid Assessment and Treatment of hypErcholesterolemia (ACCURATE) study

Familial hypercholesterolemia (FH) is an inherited condition characterized by elevated low-density lipoprotein cholesterol (LDL-C) levels and premature atherosclerotic cardiovascular disease (ASCVD). Despite being the most common inherited cardiovascular disorder, it is still highly underdiagnosed and undertreated worldwide. We designed the Advancing Cardiac Care Unit-based Rapid Assessment and Treatment of hypErcholesterolemia (ACCURATE) study to test the hypothesis that opportunistic genetic testing for FH among patients hospitalized for acute coronary syndrome (ACS) will increase the diagnosis of FH and improve patient outcomes. ACCURATE is a non-randomized, controlled trial of patients <60 years old admitted to an acute cardiac unit with ACS and elevated LDL-C levels. The first cohort will consist of a control group of patients presenting with ACS who will be treated according to usual standard-of-care. The second cohort will consist of patients presenting with ACS in whom research-based genetic testing for FH will be performed during hospitalization and the results returned to the treating physicians. The primary endpoint will be the number of patients with a new diagnosis of FH. The secondary endpoints will be the proportion of patients who undergo intensification of lipid-lowering therapy, the lowest LDL-C level achieved, and the proportion of patients reaching guideline recommended lipid targets in the 12 months after the index ACS. To our knowledge, ACCURATE represents the first clinical trial of genetic testing for FH in the acute cardiac care setting and is expected to help identify optimal approaches to increase the diagnosis and treatment of FH.

Omics technologies in personalized combination therapy for cardiovascular diseases: challenges and opportunities

The primary purpose of 'omics' technologies is to understand the intricacy of genomics, proteomics, metabolomics and other molecular mechanisms to reveal the complex traits of human diseases. The significant use of omics technologies and their applications in medicine gear up the study of the pathogenesis of several disorders. The detection of biomarkers in the early onset of diseases is challenging; still, omics can discover novel molecular mechanisms and biomarkers. In this review, the different types of omics and their technologies are explicated and aimed to provide their emerging applications in cardiovascular precision medicine. These technologies significantly impact optimizing medical treatment for individuals to reach a higher level in precision medicine.

Genetics and regulation of HDL metabolism

The inverse association between plasma HDL cholesterol (HDL-C) levels and risk for cardiovascular disease (CVD) has been demonstrated by numerous epidemiological studies. However, efforts to reduce CVD risk by pharmaceutically manipulating HDL-C levels failed and refused the HDL hypothesis. HDL-C levels in the general population are highly heterogeneous and are determined by a combination of genetic and environmental factors. Insights into the causes of HDL-C heterogeneity came from the study of monogenic HDL deficiency syndromes but also from genome wide association and Μendelian randomization studies which revealed the contribution of a large number of loci to low or high HDL-C cases in the general or in restricted ethnic populations. Furthermore, HDL-C levels in the plasma are under the control of transcription factor families acting primarily in the liver including members of the hormone nuclear receptors (PPARs, LXRs, HNF-4) and forkhead box proteins (FOXO1-4) and activating transcription factors (ATFs). The effects of certain lipid lowering drugs used today are based on the modulation of the activity of specific members of these transcription factors. During the past decade, the roles of small or long non-coding RNAs acting post-transcriptionally on the expression of HDL genes have emerged and provided novel insights into HDL regulation and new opportunities for therapeutic interventions. In the present review we summarize recent progress made in the genetics and the regulation (transcriptional and post-transcriptional) of HDL metabolism.

Chromosome 1q21.2 and additional loci influence risk of spontaneous coronary artery dissection and myocardial infarction

Spontaneous coronary artery dissection (SCAD) is a non-atherosclerotic cause of myocardial infarction (MI), typically in young women. We undertook a genome-wide association study of SCAD (N_cases = 270/N_controls = 5,263) and identified and replicated an association of rs12740679 at chromosome 1q21.2 (P_{discovery+replication} = 2.19 × 10⁻¹², OR = 1.8) influencing ADAMTSL4 expression. Meta-analysis of discovery and replication samples identified associations with P < 5 × 10⁻⁸ at chromosome 6p24.1 in PHACTR1, chromosome 12q13.3 in LRP1, and in females-only, at chromosome 21q22.11 near LINC00310. A polygenic risk score for SCAD was associated with (1) higher risk of SCAD in individuals with fibromuscular dysplasia (P = 0.021, OR = 1.82 [95% CI: 1.09–3.02]) and (2) lower risk of atherosclerotic coronary artery disease and MI in the UK Biobank (P = 1.28 × 10⁻¹⁷, HR = 0.91 [95% CI :0.89–0.93], for MI) and Million Veteran Program (P = 9.33 × 10⁻³⁶, OR = 0.95 [95% CI: 0.94–0.96], for CAD; P = 3.35 × 10⁻⁶, OR = 0.96 [95% CI: 0.95–0.98] for MI). Here we report that SCAD-related MI and atherosclerotic MI exist at opposite ends of a genetic risk spectrum, inciting MI with disparate underlying vascular biology.

Spontaneous coronary artery dissection (SCAD) is a cause of myocardial infarction Here, the authors present a genome-wide association study of SCAD, finding an association at 1q21.2 which potentially affects expression of ADAMTSL4.

Risk of Premature Atherosclerotic Disease in Patients With Monogenic Versus Polygenic Familial Hypercholesterolemia

BACKGROUND

A pathogenic variant in LDLR, APOB, or PCSK9 can be identified in 30% to 80% of patients with clinically-diagnosed familial hypercholesterolemia (FH). Alternatively, ∼20% of clinical FH is thought to have a polygenic cause. The cardiovascular disease (CVD) risk associated with polygenic versus monogenic FH is unclear.

OBJECTIVES

This study evaluated the effect of monogenic and polygenic causes of FH on premature (age <55 years) CVD events in patients with clinically diagnosed FH.

METHODS

Targeted sequencing of genes known to cause FH as well as common genetic variants was performed to calculate polygenic scores in patients with "possible," "probable," or "definite" FH, according to Dutch Lipid Clinic Network Criteria (n = 626). Patients with a polygenic score ≥80th percentile were considered to have polygenic FH. We examined the risk of unstable angina, myocardial infarction, coronary revascularization, or stoke.

RESULTS

A monogenic cause of FH was associated with significantly greater risk of CVD (adjusted hazard ratio: 1.96; 95% confidence interval: 1.24 to 3.12; p = 0.004), whereas the risk of CVD in patients with polygenic FH was not significantly different compared with patients in whom no genetic cause of FH was identified. However, the presence of an elevated low-density lipoprotein cholesterol (LDL-C) polygenic risk score further increased CVD risk in patients with monogenic FH (adjusted hazard ratio: 3.06; 95% confidence interval: 1.56 to 5.99; p = 0.001).

CONCLUSIONS

Patients with monogenic FH and superimposed elevated LDL-C polygenic risk scores have the greatest risk of premature CVD. Genetic testing for FH provides important prognostic information that is independent of LDL-C levels.

Cholesteryl Ester Transfer Protein Influences High-Density Lipoprotein Levels and Survival in Sepsis

RATIONALE

High-density lipoprotein (HDL) cholesterol (HDL-C) levels decline during sepsis, and lower levels are associated with worse survival. However, the genetic mechanisms underlying changes in HDL-C during sepsis, and whether the relationship with survival is causative, are largely unknown.

OBJECTIVES

We hypothesized that variation in genes involved in HDL metabolism would contribute to changes in HDL-C levels and clinical outcomes during sepsis.

METHODS

We performed targeted resequencing of HDL-related genes in 200 patients admitted to an emergency department with sepsis (Early Infection cohort). We examined the association of genetic variants with HDL-C levels, 28-day survival, 90-day survival, organ dysfunction, and need for vasopressor or ventilatory support. Candidate variants were further assessed in the VASST (Vasopressin versus Norepinephrine Infusion in Patients with Septic Shock Trial) cohort (n = 632) and St. Paul's Hospital Intensive Care Unit 2 (SPHICU2) cohort (n = 203).

MEASUREMENTS AND MAIN RESULTS

We identified a rare missense variant in CETP (cholesteryl ester transfer protein gene; rs1800777-A) that was associated with significant reductions in HDL-C levels during sepsis. Carriers of the A allele (n = 10) had decreased survival, more organ failure, and greater need for organ support compared with noncarriers. We replicated this finding in the VASST and SPHICU2 cohorts, in which carriers of rs1800777-A (n = 35 and n = 12, respectively) had significantly reduced 28-day survival. Mendelian randomization was consistent with genetically reduced HDL levels being a causal factor for decreased sepsis survival.

CONCLUSIONS

Our results identify CETP as a critical regulator of HDL levels and clinical outcomes during sepsis. These data point toward a critical role for HDL in sepsis.

CETP, LIPC, and SCARB1 variants in individuals with extremely high high-density lipoprotein-cholesterol levels

The concentration of high-density lipoprotein-cholesterol (HDL-C) in humans is partially determined by genetic factors; however, the role of these factors is incompletely understood. The aim of this study was to examine the prevalence and characteristics of CETP, LIPC, and SCARB1 variants in Korean individuals with extremely high HDL-C levels. We also analysed associations between these variants and cholesterol efflux capacity (CEC), reactive oxygen species (ROS) generation, and vascular cell adhesion molecule-1 (VCAM-1) expression. Of 13,545 participants in the cardiovascular genome cohort, 42 subjects with HDL-C levels >100 mg/dL were analysed. The three target genes were sequenced by targeted next-generation sequencing, the functional effects of detected variants were predicted, and CEC was assessed using a radioisotope and apolipoprotein B-depleted sera. We observed two rare variants of CETP in 13 individuals (rare variant c.A1196G [p.D399G] of CETP was discovered in 12 subjects) and one rare variant of SCARB1 in one individual. Furthermore, all subjects had at least one of four common variants (one CETP and three LIPC variants). Two additional novel CETP variants of unknown frequency were found in two subjects. However, the identified variants did not show significant associations with CEC, ROS generation, or VCAM-1 expression. Our study provides additional insights into the role of genetics in individuals with extremely high HDL-C.

Genetics, Dyslipidemia, and Cardiovascular Disease: New Insights

PURPOSE OF REVIEW

The cardiovascular (CV) risk related to lipid disorders is well established and is based on a robust body of evidence from well-designed randomized clinical trials, as well as prospective observational studies. In the last two decades, significant advances have been made in understanding the genetic basis of dyslipidemias. The present review is intended as a comprehensive discussion of current knowledge about the genetics and pathophysiology of disorders that predispose to dyslipidemia. We also focus on issues related to statins and the proprotein convertase subtilisin/kexin type 9 (PCSK9) and some of its polymorphisms, as well as new cholesterol-lowering medications, including PCSK9 inhibitors.

RECENT FINDING

Cholesterol is essential for the proper functioning of several body systems. However, dyslipidemia-especially elevated low-density lipoprotein (LDL-c) and triglyceride levels, as well as reduced lipoprotein lipase activity-is associated with an increased risk of coronary artery disease (CAD). High-density lipoprotein (HDL-c), however, seems to play a role as a risk marker rather than as a causal factor of the disease, as suggested by Mendelian randomization studies. Several polymorphisms in the lipoprotein lipase locus have been described and are associated with variations in the activity of this enzyme, producing high concentrations of triglycerides and increased risk of CAD. Dyslipidemia, especially increased LDL-c and triglyceride levels, continues to play a significant role in CV risk. The combination of genetic testing and counseling is important in the management of patients with dyslipidemia of genetic etiology. Strategies focused on primary prevention can offer an opportunity to reduce CV events.

CETP genetic variant rs1800777 (allele A) is associated with abnormally low HDL-C levels and increased risk of AKI during sepsis

High-density cholesterol (HDL-C) levels are influenced by genetic variation in several genes. Low levels of HDL-C have been associated with increased risk of acute kidney injury (AKI). We investigated whether genetic polymorphisms in ten genes known to regulate HDL-C levels are associated with both HDL-C levels and AKI development during sepsis. Two cohorts were retrospectively analyzed: Derivation Cohort (202 patients with sepsis enrolled at the Emergency Department from 2011 to 2014 in Vancouver, Canada); Validation Cohort (604 septic shock patients enrolled into the Vasopressin in Septic Shock Trial (VASST)). Associations between HDL-related genetic polymorphisms and both HDL-C levels, and risk for clinically significant sepsis-associated AKI (AKI KDIGO stages 2 and 3) were evaluated. In the Derivation Cohort, one genetic variant in the Cholesteryl Ester Transfer Protein (CETP) gene, rs1800777 (allele A), was strongly associated with lower HDL-C levels (17.4 mg/dL vs. 32.9 mg/dL, P = 0.002), greater CETP mass (3.43 µg/mL vs. 1.32 µg/mL, P = 0.034), and increased risk of clinically significant sepsis-associated AKI (OR: 8.28, p = 0.013). Moreover, the same allele was a predictor of sepsis-associated AKI in the Validation Cohort (OR: 2.38, p = 0.020). Our findings suggest that CETP modulates HDL-C levels in sepsis. CETP genotype may identify patients at high-risk of sepsis-associated AKI.

Large-scale deletions of the ABCA1 gene in patients with hypoalphalipoproteinemia

Copy-number variations (CNVs) have been studied in the context of familial hypercholesterolemia but have not yet been evaluated in patients with extreme levels of HDL cholesterol. We evaluated targeted, next-generation sequencing data from patients with very low levels of HDL cholesterol (i.e., hypoalphalipoproteinemia) with the VarSeq-CNV^® caller algorithm to screen for CNVs that disrupted the ABCA1, LCAT, or APOA1 genes. In four individuals, we found three unique deletions in ABCA1: a heterozygous deletion of exon 4, a heterozygous deletion that spanned exons 8 to 31, and a heterozygous deletion of the entire ABCA1 gene. Breakpoints were identified with Sanger sequencing, and the full-gene deletion was confirmed by using exome sequencing and the Affymetrix CytoScan HD array. Previously, large-scale deletions in candidate HDL genes had not been associated with hypoalphalipoproteinemia; our findings indicate that CNVs in ABCA1 may be a previously unappreciated genetic determinant of low levels of HDL cholesterol. By coupling bioinformatic analyses with next-generation sequencing data, we can successfully assess the spectrum of genetic determinants of many dyslipidemias, including hypoalphalipoproteinemia.

Polygenic influences on dyslipidemias

PURPOSE OF REVIEW

Rare large-effect genetic variants underlie monogenic dyslipidemias, whereas common small-effect genetic variants - single nucleotide polymorphisms (SNPs) - have modest influences on lipid traits. Over the past decade, these small-effect SNPs have been shown to cumulatively exert consistent effects on lipid phenotypes under a polygenic framework, which is the focus of this review.

RECENT FINDINGS

Several groups have reported polygenic risk scores assembled from lipid-associated SNPs, and have applied them to their respective phenotypes. For lipid traits in the normal population distribution, polygenic effects quantified by a score that integrates several common polymorphisms account for about 20-30% of genetic variation. Among individuals at the extremes of the distribution, that is, those with clinical dyslipidemia, the polygenic component includes both rare variants with large effects and common polymorphisms: depending on the trait, 20-50% of susceptibility can be accounted for by this assortment of genetic variants.

SUMMARY

Accounting for polygenic effects increases the numbers of dyslipidemic individuals who can be explained genetically, but a substantial proportion of susceptibility remains unexplained. Whether documenting the polygenic basis of dyslipidemia will affect outcomes in clinical trials or prospective observational studies remains to be determined.

Next generation sequencing applications for cardiovascular disease

The Human Genome Project (HGP), as the primary sequencing of the human genome, lasted more than one decade to be completed using the traditional Sanger's method. At present, next-generation sequencing (NGS) technology could provide the genome sequence data in hours. NGS has also decreased the expense of sequencing; therefore, nowadays it is possible to carry out both whole-genome (WGS) and whole-exome sequencing (WES) for the variations detection in patients with rare genetic diseases as well as complex disorders such as common cardiovascular diseases (CVDs). Finding new variants may contribute to establishing a risk profile for the pathology process of diseases. Here, recent applications of NGS in cardiovascular medicine are discussed; both Mendelian disorders of the cardiovascular system and complex genetic CVDs including inherited cardiomyopathy, channelopathies, stroke, coronary artery disease (CAD) and are considered. We also state some future use of NGS in clinical practice for increasing our information about the CVDs genetics and the limitations of this new technology. Key messages Traditional Sanger's method was the mainstay for Human Genome Project (HGP); Sanger sequencing has high fidelity but is slow and costly as compared to next generation methods. Within cardiovascular medicine, NGS has been shown to be successful in identifying novel causative mutations and in the diagnosis of Mendelian diseases which are caused by a single variant in a single gene. NGS has provided the opportunity to perform parallel analysis of a great number of genes in an unbiased approach (i.e. without knowing the underlying biological mechanism) which probably contribute to advance our knowledge regarding the pathology of complex diseases such as CVD.

NGS Technologies as a Turning Point in Rare Disease Research , Diagnosis and Treatment

Approximately 25-50 million Americans, 30 million Europeans, and 8% of the Australian population have a rare disease. Rare diseases are thus a common problem for clinicians and account for enormous healthcare costs worldwide due to the difficulty of establishing a specific diagnosis. In this article, we review the milestones achieved in our understanding of rare diseases since the emergence of next-generation sequencing (NGS) technologies and analyze how these advances have influenced research and diagnosis. The first half of this review describes how NGS has changed diagnostic workflows and provided an unprecedented, simple way of discovering novel disease-associated genes. We focus particularly on metabolic and neurodevelopmental disorders. NGS has enabled cheap and rapid genetic diagnosis, highlighted the relevance of mosaic and de novo mutations, brought to light the wide phenotypic spectrum of most genes, detected digenic inheritance or the presence of more than one rare disease in the same patient, and paved the way for promising new therapies. In the second part of the review, we look at the limitations and challenges of NGS, including determination of variant causality, the loss of variants in coding and non-coding regions, and the detection of somatic mosaicism variants and epigenetic mutations, and discuss how these can be overcome in the near future.

Increased prevalence of clinical and subclinical atherosclerosis in patients with damaging mutations in ABCA1 or APOA1

BACKGROUND

A low level of high-density lipoprotein cholesterol (HDL-C) is a common clinical scenario and poses challenges for management. Many patients with low HDL-C harbor a damaging mutation in ABCA1 or APOA1, but the clinical implications of genetic testing for these mutations are unclear.

OBJECTIVE

The purpose of this study was to investigate the prevalence of clinical or subclinical atherosclerosis among patients with low HDL-C due to a mutation in ABCA1 or APOA1, compared with patients with low HDL-C without such a mutation.

METHODS

We performed targeted next-generation sequencing to identify mutations in ABCA1 and APOA1 in 72 patients with HDL-C levels below the 10^th percentile. We examined the prevalence of clinical atherosclerosis and subclinical atherosclerosis in these patients. We also measured cholesterol efflux capacity (CEC) in plasma.

RESULTS

We identified a known disease-causing or likely pathogenic variant in the ABCA1 or APOA1 genes in 22% of patients with low HDL-C. Eighty-three percent of patients with a damaging mutation in ABCA1 or APOA1 had evidence of atherosclerosis compared with 38.6% with low HDL-C without such a mutation (P = .04). Patients with damaging mutations in ABCA1 or APOA1 had lower CEC compared with patients without a mutation (25.9% vs 30.1%).

CONCLUSION

The presence of a damaging mutation in ABCA1 or APOA1 confers an increased risk of atherosclerosis relative to patients without such a mutation at a comparable level of HDL cholesterol, possibly because of a reduction in CEC.

Polygenic determinants in extremes of high-density lipoprotein cholesterol

HDL cholesterol (HDL-C) remains a superior biochemical predictor of CVD risk, but its genetic basis is incompletely defined. In patients with extreme HDL-C concentrations, we concurrently evaluated the contributions of multiple large- and small-effect genetic variants. In a discovery cohort of 255 unrelated lipid clinic patients with extreme HDL-C levels, we used a targeted next-generation sequencing panel to evaluate rare variants in known HDL metabolism genes, simultaneously with common variants bundled into a polygenic trait score. Two additional cohorts were used for validation and included 1,746 individuals from the Montréal Heart Institute Biobank and 1,048 individuals from the University of Pennsylvania. Findings were consistent between cohorts: we found rare heterozygous large-effect variants in 18.7% and 10.9% of low- and high-HDL-C patients, respectively. We also found common variant accumulation, indicated by extreme polygenic trait scores, in an additional 12.8% and 19.3% of overall cases of low- and high-HDL-C extremes, respectively. Thus, the genetic basis of extreme HDL-C concentrations encountered clinically is frequently polygenic, with contributions from both rare large-effect and common small-effect variants. Multiple types of genetic variants should be considered as contributing factors in patients with extreme dyslipidemia.

Identification of a novel LMF1 nonsense mutation responsible for severe hypertriglyceridemia by targeted next-generation sequencing

BACKGROUND

Severe hypertriglyceridemia (HTG) may result from mutations in genes affecting the intravascular lipolysis of triglyceride (TG)-rich lipoproteins.

OBJECTIVE

The aim of this study was to develop a targeted next-generation sequencing panel for the molecular diagnosis of disorders characterized by severe HTG.

METHODS

We developed a targeted customized panel for next-generation sequencing Ion Torrent Personal Genome Machine to capture the coding exons and intron/exon boundaries of 18 genes affecting the main pathways of TG synthesis and metabolism. We sequenced 11 samples of patients with severe HTG (TG>885 mg/dL-10 mmol/L): 4 positive controls in whom pathogenic mutations had previously been identified by Sanger sequencing and 7 patients in whom the molecular defect was still unknown.

RESULTS

The customized panel was accurate, and it allowed to confirm genetic variants previously identified in all positive controls with primary severe HTG. Only 1 patient of 7 with HTG was found to be carrier of a homozygous pathogenic mutation of the third novel mutation of LMF1 gene (c.1380C>G-p.Y460X). The clinical and molecular familial cascade screening allowed the identification of 2 additional affected siblings and 7 heterozygous carriers of the mutation.

CONCLUSIONS

We showed that our targeted resequencing approach for genetic diagnosis of severe HTG appears to be accurate, less time consuming, and more economical compared with traditional Sanger resequencing. The identification of pathogenic mutations in candidate genes remains challenging and clinical resequencing should mainly intended for patients with strong clinical criteria for monogenic severe HTG.

GWAS as a Driver of Gene Discovery in Cardiometabolic Diseases

Cardiometabolic diseases represent a common complex disorder with a strong genetic component. Currently, genome-wide association studies (GWAS) have yielded some 755 single-nucleotide polymorphisms (SNPs) encompassing 366 independent loci that may help to decipher the molecular basis of cardiometabolic diseases. Going from a disease SNP to the underlying disease mechanisms is a huge challenge because the associated SNPs rarely disrupt protein function. Many disease SNPs are located in noncoding regions, and therefore attention is now focused on linking genetic SNP variation to effects on gene expression levels. By integrating genetic information with large-scale gene expression data, and with data from epigenetic roadmaps revealing gene regulatory regions, we expect to be able to identify candidate disease genes and the regulatory potential of disease SNPs.