Targeting immune-fibroblast cell communication in heart failure.

Inflammation and tissue fibrosis co-exist and are causally linked to organ dysfunction1,2. However, the molecular mechanisms driving immune-fibroblast cell communication in human cardiac disease remain unexplored and there are at present no approved treatments that directly target cardiac fibrosis3,4. Here we performed multiomic single-cell gene expression, epitope mapping and chromatin accessibility profiling in 45 healthy donor, acutely infarcted and chronically failing human hearts. We identified a disease-associated fibroblast trajectory that diverged into distinct populations reminiscent of myofibroblasts and matrifibrocytes, the latter expressing fibroblast activator protein (FAP) and periostin (POSTN). Genetic lineage tracing of FAP+ fibroblasts in vivo showed that they contribute to the POSTN lineage but not the myofibroblast lineage. We assessed the applicability of experimental systems to model cardiac fibroblasts and demonstrated that three different in vivo mouse models of cardiac injury were superior compared with cultured human heart and dermal fibroblasts in recapitulating the human disease phenotype. Ligand-receptor analysis and spatial transcriptomics predicted that interactions between C-C chemokine receptor type 2 (CCR2) macrophages and fibroblasts mediated by interleukin-1ß (IL-1ß) signalling drove the emergence of FAP/POSTN fibroblasts within spatially defined niches. In vivo, we deleted the IL-1 receptor on fibroblasts and the IL-1ß ligand in CCR2+ monocytes and macrophages, and inhibited IL-1ß signalling using a monoclonal antibody, and showed reduced FAP/POSTN fibroblasts, diminished myocardial fibrosis and improved cardiac function. These findings highlight the broader therapeutic potential of targeting inflammation to treat tissue fibrosis and preserve organ function.

Semi-supervised machine learning method for predicting homogeneous ancestry groups to assess Hardy-Weinberg equilibrium in diverse whole-genome sequencing studies.

Large-scale, multi-ethnic whole-genome sequencing (WGS) studies, such as the National Human Genome Research Institute Genome Sequencing Program's Centers for Common Disease Genomics (CCDG), play an important role in increasing diversity for genetic research. Before performing association analyses, assessing Hardy-Weinberg equilibrium (HWE) is a crucial step in quality control procedures to remove low quality variants and ensure valid downstream analyses. Diverse WGS studies contain ancestrally heterogeneous samples; however, commonly used HWE methods assume that the samples are homogeneous. Therefore, directly applying these to the whole dataset can yield statistically invalid results. To account for this heterogeneity, HWE can be tested on subsets of samples that have genetically homogeneous ancestries and the results aggregated at each variant. To facilitate valid HWE subset testing, we developed a semi-supervised learning approach that predicts homogeneous ancestries based on the genotype. This method provides a convenient tool for estimating HWE in the presence of population structure and missing self-reported race and ethnicities in diverse WGS studies. In addition, assessing HWE within the homogeneous ancestries provides reliable HWE estimates that will directly benefit downstream analyses, including association analyses in WGS studies. We applied our proposed method on the CCDG dataset, predicting homogeneous genetic ancestry groups for 60,545 multi-ethnic WGS samples to assess HWE within each group.

Mapping and characterization of structural variation in 17,795 human genomes.

A key goal of whole-genome sequencing for studies of human genetics is to interrogate all forms of variation, including single-nucleotide variants, small insertion or deletion (indel) variants and structural variants. However, tools and resources for the study of structural variants have lagged behind those for smaller variants. Here we used a scalable pipeline1 to map and characterize structural variants in 17,795 deeply sequenced human genomes. We publicly release site-frequency data to create the largest, to our knowledge, whole-genome-sequencing-based structural variant resource so far. On average, individuals carry 2.9 rare structural variants that alter coding regions; these variants affect the dosage or structure of 4.2 genes and account for 4.0-11.2% of rare high-impact coding alleles. Using a computational model, we estimate that structural variants account for 17.2% of rare alleles genome-wide, with predicted deleterious effects that are equivalent to loss-of-function coding alleles; approximately 90% of such structural variants are noncoding deletions (mean 19.1 per genome). We report 158,991 ultra-rare structural variants and show that 2% of individuals carry ultra-rare megabase-scale structural variants, nearly half of which are balanced or complex rearrangements. Finally, we infer the dosage sensitivity of genes and noncoding elements, and reveal trends that relate to element class and conservation. This work will help to guide the analysis and interpretation of structural variants in the era of whole-genome sequencing.

Integrating transcriptomics, metabolomics, and GWAS helps reveal molecular mechanisms for metabolite levels and disease risk.

Transcriptomics data have been integrated with genome-wide association studies (GWASs) to help understand disease/trait molecular mechanisms. The utility of metabolomics, integrated with transcriptomics and disease GWASs, to understand molecular mechanisms for metabolite levels or diseases has not been thoroughly evaluated. We performed probabilistic transcriptome-wide association and locus-level colocalization analyses to integrate transcriptomics results for 49 tissues in 706 individuals from the GTEx project, metabolomics results for 1,391 plasma metabolites in 6,136 Finnish men from the METSIM study, and GWAS results for 2,861 disease traits in 260,405 Finnish individuals from the FinnGen study. We found that genetic variants that regulate metabolite levels were more likely to influence gene expression and disease risk compared to the ones that do not. Integrating transcriptomics with metabolomics results prioritized 397 genes for 521 metabolites, including 496 previously identified gene-metabolite pairs with strong functional connections and suggested 33.3% of such gene-metabolite pairs shared the same causal variants with genetic associations of gene expression. Integrating transcriptomics and metabolomics individually with FinnGen GWAS results identified 1,597 genes for 790 disease traits. Integrating transcriptomics and metabolomics jointly with FinnGen GWAS results helped pinpoint metabolic pathways from genes to diseases. We identified putative causal effects of UGT1A1/UGT1A4 expression on gallbladder disorders through regulating plasma (E,E)-bilirubin levels, of SLC22A5 expression on nasal polyps and plasma carnitine levels through distinct pathways, and of LIPC expression on age-related macular degeneration through glycerophospholipid metabolic pathways. Our study highlights the power of integrating multiple sets of molecular traits and GWAS results to deepen understanding of disease pathophysiology.

Exome sequencing of Finnish isolates enhances rare-variant association power.

Exome-sequencing studies have generally been underpowered to identify deleterious alleles with a large effect on complex traits as such alleles are mostly rare. Because the population of northern and eastern Finland has expanded considerably and in isolation following a series of bottlenecks, individuals of these populations have numerous deleterious alleles at a relatively high frequency. Here, using exome sequencing of nearly 20,000 individuals from these regions, we investigate the role of rare coding variants in clinically relevant quantitative cardiometabolic traits. Exome-wide association studies for 64 quantitative traits identified 26 newly associated deleterious alleles. Of these 26 alleles, 19 are either unique to or more than 20 times more frequent in Finnish individuals than in other Europeans and show geographical clustering comparable to Mendelian disease mutations that are characteristic of the Finnish population. We estimate that sequencing studies of populations without this unique history would require hundreds of thousands to millions of participants to achieve comparable association power.

Author Correction: Exome sequencing of Finnish isolates enhances rare-variant association power.

An Amendment to this paper has been published and can be accessed via a link at the top of the paper.

ANGPTL3 deficiency impairs lipoprotein production and produces adaptive changes in hepatic lipid metabolism.

Angiopoietin-like protein 3 (ANGPTL3) is a hepatically secreted protein and therapeutic target for reducing plasma triglyceride-rich lipoproteins and low-density lipoprotein (LDL) cholesterol. Although ANGPTL3 modulates the metabolism of circulating lipoproteins, its role in triglyceride-rich lipoprotein assembly and secretion remains unknown. CRISPR-associated protein 9 (CRISPR/Cas9) was used to target ANGPTL3 in HepG2 cells (ANGPTL3-/-) whereupon we observed ∼50% reduction of apolipoprotein B100 (ApoB100) secretion, accompanied by an increase in ApoB100 early presecretory degradation via a predominantly lysosomal mechanism. Despite defective particle secretion in ANGPTL3-/- cells, targeted lipidomic analysis did not reveal neutral lipid accumulation in ANGPTL3-/- cells; rather ANGPTL3-/- cells demonstrated decreased secretion of newly synthesized triglycerides and increased fatty acid oxidation. Furthermore, RNA sequencing demonstrated significantly altered expression of key lipid metabolism genes, including targets of peroxisome proliferator-activated receptor α, consistent with decreased lipid anabolism and increased lipid catabolism. In contrast, CRISPR/Cas9 LDL receptor (LDLR) deletion in ANGPTL3-/- cells did not result in a secretion defect at baseline, but proteasomal inhibition strongly induced compensatory late presecretory degradation of ApoB100 and impaired its secretion. Additionally, these ANGPTL3-/-;LDLR-/- cells rescued the deficient LDL clearance of LDLR-/- cells. In summary, ANGPTL3 deficiency in the presence of functional LDLR leads to the production of fewer lipoprotein particles due to early presecretory defects in particle assembly that are associated with adaptive changes in intrahepatic lipid metabolism. In contrast, when LDLR is absent, ANGPTL3 deficiency is associated with late presecretory regulation of ApoB100 degradation without impaired secretion. Our findings therefore suggest an unanticipated intrahepatic role for ANGPTL3, whose function varies with LDLR status.

ANGPTL3 Deficiency and Risk of Hepatic Steatosis.

BACKGROUND: ANGPTL3 (angiopoietin-like 3) is a therapeutic target for reducing plasma levels of triglycerides and low-density lipoprotein cholesterol. A recent trial with vupanorsen, an antisense oligonucleotide targeting hepatic production of ANGPTL3, reported a dose-dependent increase in hepatic fat. It is unclear whether this adverse effect is due to an on-target effect of inhibiting hepatic ANGPTL3. METHODS: We recruited participants with ANGPTL3 deficiency related to ANGPTL3 loss-of-function (LoF) mutations, along with wild-type (WT) participants from 2 previously characterized cohorts located in Campodimele, Italy, and St. Louis, MO. Magnetic resonance spectroscopy and magnetic resonance proton density fat fraction were performed to measure hepatic fat fraction and the distribution of extrahepatic fat. To estimate the causal relationship between ANGPTL3 and hepatic fat, we generated a genetic instrument of plasma ANGPTL3 levels as a surrogate for hepatic protein synthesis and performed Mendelian randomization analyses with hepatic fat in the UK Biobank study. RESULTS: We recruited participants with complete (n=6) or partial (n=32) ANGPTL3 deficiency related to ANGPTL3 LoF mutations, as well as WT participants (n=92) without LoF mutations. Participants with ANGPTL3 deficiency exhibited significantly lower total cholesterol (complete deficiency, 78.5 mg/dL; partial deficiency, 172 mg/dL; WT, 188 mg/dL; P<0.05 for both deficiency groups compared with WT), along with plasma triglycerides (complete deficiency, 26 mg/dL; partial deficiency, 79 mg/dL; WT, 88 mg/dL; P<0.05 for both deficiency groups compared with WT) without any significant difference in hepatic fat (complete deficiency, 9.8%; partial deficiency, 10.1%; WT, 9.9%; P>0.05 for both deficiency groups compared with WT) or severity of hepatic steatosis as assessed by magnetic resonance imaging. In addition, ANGPTL3 deficiency did not alter the distribution of extrahepatic fat. Results from Mendelian randomization analyses in 36 703 participants from the UK Biobank demonstrated that genetically determined ANGPTL3 plasma protein levels were causally associated with low-density lipoprotein cholesterol (P=1.7×10-17) and triglycerides (P=3.2×10-18) but not with hepatic fat (P=0.22). CONCLUSIONS: ANGPTL3 deficiency related to LoF mutations in ANGPTL3, as well as genetically determined reduction of plasma ANGPTL3 levels, is not associated with hepatic steatosis. Therapeutic approaches to inhibit ANGPTL3 production in hepatocytes are not necessarily expected to result in the increased risk for hepatic steatosis that was observed with vupanorsen.

Association of structural variation with cardiometabolic traits in Finns.

The contribution of genome structural variation (SV) to quantitative traits associated with cardiometabolic diseases remains largely unknown. Here, we present the results of a study examining genetic association between SVs and cardiometabolic traits in the Finnish population. We used sensitive methods to identify and genotype 129,166 high-confidence SVs from deep whole-genome sequencing (WGS) data of 4,848 individuals. We tested the 64,572 common and low-frequency SVs for association with 116 quantitative traits and tested candidate associations using exome sequencing and array genotype data from an additional 15,205 individuals. We discovered 31 genome-wide significant associations at 15 loci, including 2 loci at which SVs have strong phenotypic effects: (1) a deletion of the ALB promoter that is greatly enriched in the Finnish population and causes decreased serum albumin level in carriers (p = 1.47 × 10-54) and is also associated with increased levels of total cholesterol (p = 1.22 × 10-28) and 14 additional cholesterol-related traits, and (2) a multi-allelic copy number variant (CNV) at PDPR that is strongly associated with pyruvate (p = 4.81 × 10-21) and alanine (p = 6.14 × 10-12) levels and resides within a structurally complex genomic region that has accumulated many rearrangements over evolutionary time. We also confirmed six previously reported associations, including five led by stronger signals in single nucleotide variants (SNVs) and one linking recurrent HP gene deletion and cholesterol levels (p = 6.24 × 10-10), which was also found to be strongly associated with increased glycoprotein level (p = 3.53 × 10-35). Our study confirms that integrating SVs in trait-mapping studies will expand our knowledge of genetic factors underlying disease risk.

Functional assays reveal the pathogenic mechanism of a de novo tropomyosin variant identified in patient with dilated cardiomyopathy.

Dilated cardiomyopathy (DCM) is a leading cause of heart failure and a major indicator for heart transplant. Human genetic studies have identified over a thousand causal mutations for DCM in genes involved in a variety of cellular processes, including sarcomeric contraction. A substantial clinical challenge is determining the pathogenicity of novel variants in disease-associated genes. This challenge of connecting genotype and phenotype has frustrated attempts to develop effective, mechanism-based treatments for patients. Here, we identified a de novo mutation (T237S) in TPM1, the gene that encodes the thin filament protein tropomyosin, in a patient with DCM and conducted in vitro experiments to characterize the pathogenicity of this novel variant. We expressed recombinant mutant protein, reconstituted it into thin filaments, and examined the effects of the mutation on thin filament function. We show that the mutation reduces the calcium sensitivity of thin filament activation, as previously seen for known pathogenic mutations. Mechanistically, this shift is due to mutation-induced changes in tropomyosin positioning along the thin filament. We demonstrate that the thin filament activator omecamtiv mecarbil restores the calcium sensitivity of thin filaments regulated by the mutant tropomyosin, which lays the foundation for additional experiments to explore the therapeutic potential of this drug for patients harboring the T237S mutation. Taken together, our results suggest that the TPM1 T237S mutation is likely pathogenic and demonstrate how functional in vitro characterization of pathogenic protein variants in the lab might guide precision medicine in the clinic.

Non-parametric Polygenic Risk Prediction via Partitioned GWAS Summary Statistics.

In complex trait genetics, the ability to predict phenotype from genotype is the ultimate measure of our understanding of genetic architecture underlying the heritability of a trait. A complete understanding of the genetic basis of a trait should allow for predictive methods with accuracies approaching the trait's heritability. The highly polygenic nature of quantitative traits and most common phenotypes has motivated the development of statistical strategies focused on combining myriad individually non-significant genetic effects. Now that predictive accuracies are improving, there is a growing interest in the practical utility of such methods for predicting risk of common diseases responsive to early therapeutic intervention. However, existing methods require individual-level genotypes or depend on accurately specifying the genetic architecture underlying each disease to be predicted. Here, we propose a polygenic risk prediction method that does not require explicitly modeling any underlying genetic architecture. We start with summary statistics in the form of SNP effect sizes from a large GWAS cohort. We then remove the correlation structure across summary statistics arising due to linkage disequilibrium and apply a piecewise linear interpolation on conditional mean effects. In both simulated and real datasets, this new non-parametric shrinkage (NPS) method can reliably allow for linkage disequilibrium in summary statistics of 5 million dense genome-wide markers and consistently improves prediction accuracy. We show that NPS improves the identification of groups at high risk for breast cancer, type 2 diabetes, inflammatory bowel disease, and coronary heart disease, all of which have available early intervention or prevention treatments.

Low LDL Cholesterol Is Not an Independent Risk Factor for Hepatic Steatosis.

BACKGROUND: Genetic mutations causing defective VLDL secretion and low LDL cholesterol are associated with hepatic steatosis and nonalcoholic fatty liver disease (NAFLD). AIMS: Determine if low LDL cholesterol (< 5th percentile) was an independent predictor of hepatic steatosis. METHODS: Secondary data analysis of the Dallas Heart study (an urban, multiethnic, probability-based sample), we defined hepatic steatosis utilizing intrahepatic triglyceride (IHTG) analyzed using magnetic resonance spectroscopy in conjunction and available demographic, serological and genetic information. We exclude patients on lipid lowering medications. RESULTS: Of the 2094 subjects that met our exclusion criteria, 86 had a low LDL cholesterol, of whom 19 (22%) exhibited hepatic steatosis. After matching for age, sex, BMI, and alcohol consumption, low LDL cholesterol was not a risk factor for hepatic steatosis compared to those with normal (50-180 mg/dL) or high (> 180 mg/dL) LDL. When analyzed as a continuous variable, we observed lower IHTG in the low LDL group compared to the normal or high LDL groups (2.2%, 3.5%, 4.6%; all pairwise comparisons p < 0.001). Subjects with both hepatic steatosis and low LDL cholesterol exhibited a more favorable lipid profile but similar insulin resistance and hepatic fibrosis risk compared to other subjects with hepatic steatosis. The distribution of variant alleles associated with NAFLD, including PNPLA3, GCKR, and MTTP was indistinguishable between subjects with hepatic steatosis and low versus high LDL cholesterol. CONCLUSION: These findings suggest that low serum LDL levels are not a useful predictor of hepatic steatosis and NAFLD. Moreover, subjects with low LDL exhibit a more favorable lipid profile and lower IHTG.

Mitochondrial genome copy number measured by DNA sequencing in human blood is strongly associated with metabolic traits via cell-type composition differences.

BACKGROUND: Mitochondrial genome copy number (MT-CN) varies among humans and across tissues and is highly heritable, but its causes and consequences are not well understood. When measured by bulk DNA sequencing in blood, MT-CN may reflect a combination of the number of mitochondria per cell and cell-type composition. Here, we studied MT-CN variation in blood-derived DNA from 19184 Finnish individuals using a combination of genome (N = 4163) and exome sequencing (N = 19034) data as well as imputed genotypes (N = 17718). RESULTS: We identified two loci significantly associated with MT-CN variation: a common variant at the MYB-HBS1L locus (P = 1.6 × 10-8), which has previously been associated with numerous hematological parameters; and a burden of rare variants in the TMBIM1 gene (P = 3.0 × 10-8), which has been reported to protect against non-alcoholic fatty liver disease. We also found that MT-CN is strongly associated with insulin levels (P = 2.0 × 10-21) and other metabolic syndrome (metS)-related traits. Using a Mendelian randomization framework, we show evidence that MT-CN measured in blood is causally related to insulin levels. We then applied an MT-CN polygenic risk score (PRS) derived from Finnish data to the UK Biobank, where the association between the PRS and metS traits was replicated. Adjusting for cell counts largely eliminated these signals, suggesting that MT-CN affects metS via cell-type composition. CONCLUSION: These results suggest that measurements of MT-CN in blood-derived DNA partially reflect differences in cell-type composition and that these differences are causally linked to insulin and related traits.

Capitalizing on Insights from Human Genetics to Identify Novel Therapeutic Targets for Coronary Artery Disease.

Coronary artery disease (CAD) is a major cause of morbidity and mortality. Unfortunately, despite decades of research focused on disease pathogenesis, we still lack a sufficient pharmacopeia for preventing CAD. The failure of many novel cardiovascular drugs to improve clinical outcomes reflects the major substantial challenge of drug development: identifying causal mechanisms that can be therapeutically manipulated to lower disease risk. Identifying genetic variants that are associated with risk of CAD has emerged as a clear path toward improving our understanding of the underlying mechanisms that lead to disease and to the development of new therapies. Here, we review the potential utility and limitations of using human genetics to guide the identification of therapeutic targets for CAD.

Exome sequencing identifies rare LDLR and APOA5 alleles conferring risk for myocardial infarction.

Myocardial infarction (MI), a leading cause of death around the world, displays a complex pattern of inheritance. When MI occurs early in life, genetic inheritance is a major component to risk. Previously, rare mutations in low-density lipoprotein (LDL) genes have been shown to contribute to MI risk in individual families, whereas common variants at more than 45 loci have been associated with MI risk in the population. Here we evaluate how rare mutations contribute to early-onset MI risk in the population. We sequenced the protein-coding regions of 9,793 genomes from patients with MI at an early age (≤50 years in males and ≤60 years in females) along with MI-free controls. We identified two genes in which rare coding-sequence mutations were more frequent in MI cases versus controls at exome-wide significance. At low-density lipoprotein receptor (LDLR), carriers of rare non-synonymous mutations were at 4.2-fold increased risk for MI; carriers of null alleles at LDLR were at even higher risk (13-fold difference). Approximately 2% of early MI cases harbour a rare, damaging mutation in LDLR; this estimate is similar to one made more than 40 years ago using an analysis of total cholesterol. Among controls, about 1 in 217 carried an LDLR coding-sequence mutation and had plasma LDL cholesterol > 190 mg dl(-1). At apolipoprotein A-V (APOA5), carriers of rare non-synonymous mutations were at 2.2-fold increased risk for MI. When compared with non-carriers, LDLR mutation carriers had higher plasma LDL cholesterol, whereas APOA5 mutation carriers had higher plasma triglycerides. Recent evidence has connected MI risk with coding-sequence mutations at two genes functionally related to APOA5, namely lipoprotein lipase and apolipoprotein C-III (refs 18, 19). Combined, these observations suggest that, as well as LDL cholesterol, disordered metabolism of triglyceride-rich lipoproteins contributes to MI risk.

Functional Characterization of LIPA (Lysosomal Acid Lipase) Variants Associated With Coronary Artery Disease.

OBJECTIVE: LIPA (lysosomal acid lipase) mediates cholesteryl ester hydrolysis, and patients with rare loss-of-function mutations develop hypercholesterolemia and severe disease. Genome-wide association studies of coronary artery disease have identified several tightly linked, common intronic risk variants in LIPA which unexpectedly associate with increased mRNA expression. However, an exonic variant (rs1051338 resulting in T16P) in linkage with intronic variants lies in the signal peptide region and putatively disrupts trafficking. We sought to functionally investigate the net impact of this locus on LIPA and whether rs1051338 could disrupt LIPA processing and function to explain coronary artery disease risk. Approach and Results: In monocytes isolated from a large cohort of healthy individuals, we demonstrate both exonic and intronic risk variants are associated with increased LIPA enzyme activity coincident with the increased transcript levels. To functionally isolate the impact of rs1051338, we studied several in vitro overexpression systems and consistently observed no differences in LIPA expression, processing, activity, or secretion. Further, we characterized a second common exonic coding variant (rs1051339), which is predicted to alter LIPA signal peptide cleavage similarly to rs1051338, yet is not linked to intronic variants. rs1051339 also does not impact LIPA function in vitro and confers no coronary artery disease risk. CONCLUSIONS: Our findings show that common LIPA exonic variants in the signal peptide are of minimal functional significance and suggest coronary artery disease risk is instead associated with increased LIPA function linked to intronic variants. Understanding the mechanisms and cell-specific contexts of LIPA function in the plaque is necessary to understand its association with cardiovascular risk.

Phenotypic Consequences of a Genetic Predisposition to Enhanced Nitric Oxide Signaling.

BACKGROUND: Nitric oxide signaling plays a key role in the regulation of vascular tone and platelet activation. Here, we seek to understand the impact of a genetic predisposition to enhanced nitric oxide signaling on risk for cardiovascular diseases, thus informing the potential utility of pharmacological stimulation of the nitric oxide pathway as a therapeutic strategy. METHODS: We analyzed the association of common and rare genetic variants in 2 genes that mediate nitric oxide signaling (Nitric Oxide Synthase 3 [NOS3] and Guanylate Cyclase 1, Soluble, Alpha 3 [GUCY1A3]) with a range of human phenotypes. We selected 2 common variants (rs3918226 in NOS3 and rs7692387 in GUCY1A3) known to associate with increased NOS3 and GUCY1A3 expression and reduced mean arterial pressure, combined them into a genetic score, and standardized this exposure to a 5 mm Hg reduction in mean arterial pressure. Using individual-level data from 335 464 participants in the UK Biobank and summary association results from 7 large-scale genome-wide association studies, we examined the effect of this nitric oxide signaling score on cardiometabolic and other diseases. We also examined whether rare loss-of-function mutations in NOS3 and GUCY1A3 were associated with coronary heart disease using gene sequencing data from the Myocardial Infarction Genetics Consortium (n=27 815). RESULTS: A genetic predisposition to enhanced nitric oxide signaling was associated with reduced risks of coronary heart disease (odds ratio, 0.37; 95% confidence interval [CI], 0.31-0.45; P=5.5*10-26], peripheral arterial disease (odds ratio 0.42; 95% CI, 0.26-0.68; P=0.0005), and stroke (odds ratio, 0.53; 95% CI, 0.37-0.76; P=0.0006). In a mediation analysis, the effect of the genetic score on decreased coronary heart disease risk extended beyond its effect on blood pressure. Conversely, rare variants that inactivate the NOS3 or GUCY1A3 genes were associated with a 23 mm Hg higher systolic blood pressure (95% CI, 12-34; P=5.6*10-5) and a 3-fold higher risk of coronary heart disease (odds ratio, 3.03; 95% CI, 1.29-7.12; P=0.01). CONCLUSIONS: A genetic predisposition to enhanced nitric oxide signaling is associated with reduced risks of coronary heart disease, peripheral arterial disease, and stroke. Pharmacological stimulation of nitric oxide signaling may prove useful in the prevention or treatment of cardiovascular disease.

Coding Variation in ANGPTL4, LPL, and SVEP1 and the Risk of Coronary Disease.

BACKGROUND: The discovery of low-frequency coding variants affecting the risk of coronary artery disease has facilitated the identification of therapeutic targets. METHODS: Through DNA genotyping, we tested 54,003 coding-sequence variants covering 13,715 human genes in up to 72,868 patients with coronary artery disease and 120,770 controls who did not have coronary artery disease. Through DNA sequencing, we studied the effects of loss-of-function mutations in selected genes. RESULTS: We confirmed previously observed significant associations between coronary artery disease and low-frequency missense variants in the genes LPA and PCSK9. We also found significant associations between coronary artery disease and low-frequency missense variants in the genes SVEP1 (p.D2702G; minor-allele frequency, 3.60%; odds ratio for disease, 1.14; P=4.2×10(-10)) and ANGPTL4 (p.E40K; minor-allele frequency, 2.01%; odds ratio, 0.86; P=4.0×10(-8)), which encodes angiopoietin-like 4. Through sequencing of ANGPTL4, we identified 9 carriers of loss-of-function mutations among 6924 patients with myocardial infarction, as compared with 19 carriers among 6834 controls (odds ratio, 0.47; P=0.04); carriers of ANGPTL4 loss-of-function alleles had triglyceride levels that were 35% lower than the levels among persons who did not carry a loss-of-function allele (P=0.003). ANGPTL4 inhibits lipoprotein lipase; we therefore searched for mutations in LPL and identified a loss-of-function variant that was associated with an increased risk of coronary artery disease (p.D36N; minor-allele frequency, 1.9%; odds ratio, 1.13; P=2.0×10(-4)) and a gain-of-function variant that was associated with protection from coronary artery disease (p.S447*; minor-allele frequency, 9.9%; odds ratio, 0.94; P=2.5×10(-7)). CONCLUSIONS: We found that carriers of loss-of-function mutations in ANGPTL4 had triglyceride levels that were lower than those among noncarriers; these mutations were also associated with protection from coronary artery disease. (Funded by the National Institutes of Health and others.).

Loss of function mutation in LOX causes thoracic aortic aneurysm and dissection in humans.

Thoracic aortic aneurysms and dissections (TAAD) represent a substantial cause of morbidity and mortality worldwide. Many individuals presenting with an inherited form of TAAD do not have causal mutations in the set of genes known to underlie disease. Using whole-genome sequencing in two first cousins with TAAD, we identified a missense mutation in the lysyl oxidase (LOX) gene (c.893T > G encoding p.Met298Arg) that cosegregated with disease in the family. Using clustered regularly interspaced short palindromic repeats (CRISPR)/clustered regularly interspaced short palindromic repeats-associated protein-9 nuclease (Cas9) genome engineering tools, we introduced the human mutation into the homologous position in the mouse genome, creating mice that were heterozygous and homozygous for the human allele. Mutant mice that were heterozygous for the human allele displayed disorganized ultrastructural properties of the aortic wall characterized by fragmented elastic lamellae, whereas mice homozygous for the human allele died shortly after parturition from ascending aortic aneurysm and spontaneous hemorrhage. These data suggest that a missense mutation in LOX is associated with aortic disease in humans, likely through insufficient cross-linking of elastin and collagen in the aortic wall. Mutation carriers may be predisposed to vascular diseases because of weakened vessel walls under stress conditions. LOX sequencing for clinical TAAD may identify additional mutation carriers in the future. Additional studies using our mouse model of LOX-associated TAAD have the potential to clarify the mechanism of disease and identify novel therapeutics specific to this genetic cause.

Polygenic Risk Score Identifies Subgroup With Higher Burden of Atherosclerosis and Greater Relative Benefit From Statin Therapy in the Primary Prevention Setting.

BACKGROUND: Relative risk reduction with statin therapy has been consistent across nearly all subgroups studied to date. However, in analyses of 2 randomized controlled primary prevention trials (ASCOT [Anglo-Scandinavian Cardiac Outcomes Trial-Lipid-Lowering Arm] and JUPITER [Justification for the Use of Statins in Prevention: An Intervention Trial Evaluating Rosuvastatin]), statin therapy led to a greater relative risk reduction among a subgroup at high genetic risk. Here, we aimed to confirm this observation in a third primary prevention randomized controlled trial. In addition, we assessed whether those at high genetic risk had a greater burden of subclinical coronary atherosclerosis. METHODS: We studied participants from a randomized controlled trial of primary prevention with statin therapy (WOSCOPS [West of Scotland Coronary Prevention Study]; n=4910) and 2 observational cohort studies (CARDIA [Coronary Artery Risk Development in Young Adults] and BioImage; n=1154 and 4392, respectively). For each participant, we calculated a polygenic risk score derived from up to 57 common DNA sequence variants previously associated with coronary heart disease. We compared the relative efficacy of statin therapy in those at high genetic risk (top quintile of polygenic risk score) versus all others (WOSCOPS), as well as the association between the polygenic risk score and coronary artery calcification (CARDIA) and carotid artery plaque burden (BioImage). RESULTS: Among WOSCOPS trial participants at high genetic risk, statin therapy was associated with a relative risk reduction of 44% (95% confidence interval [CI], 22-60; P<0.001), whereas in all others, the relative risk reduction was 24% (95% CI, 8-37; P=0.004) despite similar low-density lipoprotein cholesterol lowering. In a study-level meta-analysis across the WOSCOPS, ASCOT, and JUPITER primary prevention, relative risk reduction in those at high genetic risk was 46% versus 26% in all others (P for heterogeneity=0.05). Across all 3 studies, the absolute risk reduction with statin therapy was 3.6% (95% CI, 2.0-5.1) among those in the high genetic risk group and 1.3% (95% CI, 0.6-1.9) in all others. Each 1-SD increase in the polygenic risk score was associated with 1.32-fold (95% CI, 1.04-1.68) greater likelihood of having coronary artery calcification and 9.7% higher (95% CI, 2.2-17.8) burden of carotid plaque. CONCLUSIONS: Those at high genetic risk have a greater burden of subclinical atherosclerosis and derive greater relative and absolute benefit from statin therapy to prevent a first coronary heart disease event. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifiers: NCT00738725 (BioImage) and NCT00005130 (CARDIA). WOSCOPS was carried out and completed before the requirement for clinical trial registration.