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ObjectivesDetermine the role of apolipoprotein M (ApoM) in anthracycline (Dox) cardiotoxicity.BackgroundApoM binds the cardioprotective sphingolipid sphingosine-1-phosphate (S1P). Circulating ApoM is inversely associated with mortality in human heart failure (HF).MethodsIn the Penn HF Study (PHFS), we tested the relationship between ApoM and mortality in a subset with anthracycline-induced cardiomyopathy. We measured ApoM in humans and mice treated with Dox and utilized hepatic ApoM transgenic (ApomTG), ApoM knockout (ApomKO), ApoM knock-in mice with impaired S1P binding, and S1P receptor 3 (S1PR3) knockout mice in Dox cardiotoxicity. We assayed autophagy in left ventricular tissue from anthracycline-induced HF patients versus donor controls.ResultsApoM was inversely associated with mortality in PHFS, and Dox reduced circulating ApoM in mice and breast cancer patients.ApomTGmice were protected from Dox-induced cardiac dysfunction and loss of left ventricular mass.ApomTGattenuated Dox-induced impairment in autophagic flux in vivo and accumulation of insoluble p62, which was also observed in the myocardium of patients with anthracycline-induced HF. In vehicle-treated mice, ApoM negatively regulated transcription factor EB (TFEB), a master regulator of autophagy and lysosomal biogenesis. The effect of ApoM on TFEB required both S1P binding and S1PR3. In the presence of Dox, ApoM preserved TFEB and cardiomyocyte lysosomal abundance assessed as lysosomal associated membrane protein 1 positive structures in vivo, while S1P mimetic pretreatment of cardiomyocytes prevented Dox-induced changes in lysosomal pH.ConclusionsApoM attenuates Dox cardiotoxicity via the autophagy-lysosome pathway. The association between ApoM and reduced mortality may be explained by its role in sustaining autophagy.HighlightsCirculating ApoM is inversely associated with survival in human anthracycline-induced cardiomyopathyAnthracycline treatment reduces circulating ApoM in humans and miceIncreasing ApoM attenuates doxorubicin cardiotoxicity, lysosomal injury and preserves myocardial autophagic flux, but does not impact doxorubicin anti-neoplastic efficacyAutophagic impairment is characteristic of human anthracycline cardiomyopathy

Sushi, von Willebrand factor type A, EGF pentraxin domain-containing 1 (SVEP1), an extracellular matrix protein, is a human coronary artery disease locus that promotes atherosclerosis. We previously demonstrated that SVEP1 induces vascular smooth muscle cell (VSMC) proliferation and an inflammatory phenotype in the arterial wall to enhance the development of atherosclerotic plaque. The only receptor known to interact with SVEP1 is integrin α9β1, a cell surface receptor that is expressed by VSMCs and myeloid lineage-derived monocytes and macrophages. Our previous in vitro studies suggested that integrin α9β1 was necessary for SVEP1-induced VSMC proliferation and inflammation; however, the underlying mechanisms mediated by integrin α9β1 in these cell types during the development of atherosclerosis remain poorly understood.Here, using cell-specific gene targeting, we investigated the effects of the integrin α9β1 receptor on VSMCs and myeloid cells in mouse models of atherosclerosis. Interestingly, we found that depleting integrin α9β1 in either VSMCs or myeloid cells did not affect the formation or complexity of atherosclerotic plaque in vessels after either 8 or 16 weeks of high fat diet feeding.Our results indicate that integrin α9β1 in these two cell types does not mediate the in vivo effect of SVEP1 in the development of atherosclerosis. Instead, our results suggest either the presence of other potential receptor(s) or alternative integrin α9β1-expressing cell types responsible for SVEP1 induced signaling in the development of atherosclerosis.

Cardiac fibrosis is causally linked to heart failure pathogenesis and adverse clinical outcomes. However, the precise fibroblast populations that drive fibrosis in the human heart and the mechanisms that govern their emergence remain incompletely defined. Here, we performed Cellular Indexing of Transcriptomes and Epitomes by sequencing (CITE-seq) in 22 explanted human hearts from healthy donors, acute myocardial infarction (MI), and chronic ischemic and non-ischemic cardiomyopathy patients. We identified a fibroblast trajectory marked by fibroblast activator protein (FAP) and periostin (POSTN) expression that was independent of myofibroblasts, peaked early after MI, remained elevated in chronic heart failure, and displayed a transcriptional signature consistent with fibrotic activity. We assessed the applicability of cardiac fibrosis models and demonstrated that mouse MI, angiotensin II/phenylephrine infusion, and pressure overload models were superior compared to cultured human heart and dermal fibroblasts in recapitulating cardiac fibroblast diversity including pathogenic cell states. Ligand-receptor analysis and spatial transcriptomics predicted interactions between macrophages, T cells, and fibroblasts within spatially defined niches. CCR2+monocyte and macrophage states were the dominant source of ligands targeting fibroblasts. Inhibition of IL-1β signaling to cardiac fibroblasts was sufficient to suppress fibrosis, emergence, and maturation of FAP+POSTN+fibroblasts. Herein, we identify a human fibroblast trajectory marked by FAP and POSTN expression that is associated with cardiac fibrosis and identify macrophage-fibroblast crosstalk mediated by IL-1β signaling as a key regulator of pathologic fibroblast differentiation and fibrosis.

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.

ANGPTL3 has emerged as a therapeutic target whose inhibition results in profound reductions of plasma lipids, including atherogenic triglyceride-rich lipoproteins and low-density lipoprotein cholesterol. The identification of ANGPTL3 deficiency as a cause of familial combined hypolipidemia in humans hastened the development of anti-ANGPTL3 therapeutic agents, including evinacumab (a monoclonal antibody inhibiting circulating ANGPTL3), vupanorsen (an antisense oligonucleotide [ASO] targeting hepatic ANGPTL3 mRNA for degradation), and others. Advances have also been made in ANGPTL3 vaccination and gene editing strategies, with the former still in preclinical phases and the latter in preparation for Phase 1 trials. Here, we review the discovery of ANGPTL3 as an important regulator of lipoprotein metabolism, molecular characteristics of the protein, mechanisms by which it regulates plasma lipids, and the clinical development of anti-ANGPTL3 agents. The clinical success of therapies inhibiting ANGPTL3 highlights the importance of this target as a novel approach in treating refractory hypertriglyceridemia and hypercholesterolemia.

Background: Angiopoietin-like protein 3 (ANGPTL3 ) is a hepatically secreted protein and therapeutic target for reducing plasma triglyceride-rich lipoproteins and low-density lipoprotein cholesterol (LDL). Although ANGPTL3 modulates lipolytic pathways in lipoprotein metabolism, its potential intra-hepatocyte role in very low-density lipoprotein (VLDL) assembly and secretion remains unknown. Furthermore, although ANGPTL3 inhibition reduces low-density lipoprotein cholesterol (LDL), humans with complete LDL receptor (LDLR) deficiency exhibit LDLR-independent LDL lowering. Methods: We established hepatocyte cell culture systems, including CRISPR/Cas9-edited HepG2 cells with ANGPTL3 “knocked out” (KO). We also generated hepatocyte-like cells from patient-derived isogenic pluripotent stem cells (iPSCs) with and without ANGPTL3 KO. Radiolabeling was used to quantify apolipoprotein and triglyceride synthesis. Negative stain electron microscopy (NS-EM) was used to quantify the size of secreted lipoproteins. Results: We observed reduction of both apolipoprotein B100 and triglyceride synthesis and secretion in ANGPTL3 KO HepG2 cells. NS-EM demonstrated ANGPTL3-deficient HepG2 cells secrete significantly smaller lipoprotein particles compared to WT control cells. Together, these three findings suggest ANGPTL3 deficiency in hepatocytes results in the production of fewer, smaller, underlipidated lipoprotein particles. Conclusion: Our results point to an important intracellular role for ANGPTL3 within hepatocytes, suggesting that ANGPTL3 modifies the assembly and remodeling, as well as clearance, of hepatically secreted lipoproteins. Further experiments are planned to identify and characterize mechanistic mediators of this process. These studies have potential to identify additional targets for reducing plasma lipids via LDLR-independent pathways.

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.

Structural variants in more than 17,000 human genomes are mapped and characterized using whole-genome sequencing, showing how this type of variation contributes to rare deleterious coding and noncoding alleles. 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 pipeline(1)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.

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.

Few studies have explored the impact of rare variants (minor allele frequency, MAF

Previous human genetic studies have provided insight into the genes and pathways involved in atherosclerotic CAD, however, there remains an incomplete understanding of the precise cell types that drive disease pathogenesis. To generate a cellular atlas for CAD, we performed CITE-seq on left human coronary arteries with obstructive CAD (n=5), CAD with coronary stenting (n=4), or controls without CAD (n=5); single-nuclei RNA sequencing was performed on a subset (n=4) of these samples. Standard histopathology was used to assess the degree of atherosclerotic plaque burden and annotate disease status (Fig b). Sequencing yielded 65,437 cells with 23 distinct cell types (Fig a) and canonical marker genes (Fig c). Within the stroma we found prominent transcriptional changes in endothelial cells and fibroblasts along with the emergence of a modulated smooth muscle cell (SMC) state in CAD tissue. The modulated SMC cells were enriched with fibroblast activator protein surface expression. Additionally, we noted the emergence of a proliferative SMC population in stented arteries. Two distinct fibroblast populations were present: one was specific to coronary arteries in GTEx and this population was enriched for SVEP1 expression in the CAD samples. Furthermore, pseudotime analysis and integration of published single-cell SMC lineage tracing data in atherosclerotic mice show that this population is SMC-derived. Within the immune cells, we find expansion of B- and T-cell populations with transcriptional changes within myeloid subsets. We found 4 distinct macrophage populations: inflammatory, TREM2, HLA-II high, and resident-like macrophages. CAD macrophages had enriched inflammatory and foam-cell like signatures compared to controls. Furthermore, foam cell genes were localized to the inflammatory and TREM2 macrophages. Together, our results provide the first multi-omic single cell atlas of human coronary artery tissue with insights into disease pathogenesis.

Few studies have explored the impact of rare variants (minor allele frequency 1%) on highly heritable plasma metabolites identified in metabolomic screens. The Finnish population provides an ideal opportunity for such explorations, given the multiple bottlenecks and expansions that have shaped its history, and the enrichment for many otherwise rare alleles that has resulted. Here, we report genetic associations for 1391 plasma metabolites in 6136 men from the late-settlement region of Finland. We identify 303 novel association signals, more than one third at variants rare or enriched in Finns. Many of these signals identify genes not previously implicated in metabolite genome-wide association studies and suggest mechanisms for diseases and disease-related traits.

A surprising and well-replicated result in genetic studies of human longevity is that centenarians appear to carry disease-associated variants in numbers similar to the general population. With the proliferation of large genome-wide association studies (GWAS) in recent years, investigators have turned to polygenic scores to leverage GWAS results into a measure of genetic risk that can better predict risk of disease than individual significant variants alone.We selected 54 polygenic risk scores (PRSs) developed for a variety of outcomes and we calculated their values in individuals from the New England Centenarian Study (NECS, N = 4886) and the Long Life Family Study (LLFS, N = 4577). We compared the distribution of these PRSs among exceptionally long-lived individuals (ELLI), their offspring and controls and we also examined their predictive values, using t-tests and regression models adjusting for sex and principal components reflecting ancestral background of the individuals (PCs). In our analyses we controlled for multiple testing using a Bonferroni-adjusted threshold for 54 traits.We found that only 4 of the 54 PRSs differed between ELLIs and controls in both cohorts. ELLIs had significantly lower mean PRSs for Alzheimer’s disease (AD), coronary artery disease (CAD) and systemic lupus than controls, suggesting genetic predisposition to extreme longevity may be mediated by reduced susceptibility to these traits. ELLIs also had significantly higher mean PRSs for improved cognitive function. In addition, the PRS for AD was associated with higher risk of dementia among controls but not ELLIs (p = 0.0004, 0.3 in NECS, p = 0.03, 0.93 in LLFS respectively). Interestingly, ELLIs did not have a larger number of homozygous risk genotypes for AD (TNECS = -1.72, TLLFs = 0.83) and CAD (TNECS = -5.08, TLLFs = -0.31) in both cohorts, but did have significantly larger number of homozygous protective genotypes than controls for the two traits (AD: TNECS =3.10, TLLFs = 2.2, CAD: TNECS = 6.57, TLLFs =2.36, respectively).ELLIs have a similar burden of genetic disease risk as the general population for most traits, but have significantly lower genetic risk of AD, CAD, and lupus. The lack of association between AD PRS and dementia among ELLIs suggests that their genetic risk for AD is somehow buffered by protective genetic or environmental factors.

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.

The Nordic region, comprising primarily Denmark, Estonia, Finland, Iceland, Norway and Sweden, has many of the necessary characteristics for being at the forefront of genome-based precision medicine. These include egalitarian and universal healthcare, expertly curated patient and population registries, biobanks, large population-based prospective cohorts linked to registries and biobanks, and a widely embraced sense of social responsibility that motivates public engagement in biomedical research. However, genome-based precision medicine can be achieved only through coordinated action involving all actors in the healthcare sector. Now is an opportune time to organize scientists in the Nordic region, together with other stakeholders including patient representatives, governments, pharmaceutical companies, academic institutions and funding agencies, to initiate a Nordic Precision Medicine Initiative. We present a roadmap for how this organization can be created. The Initiative should facilitate research, clinical trials and knowledge transfer to meet regional and global health challenges.

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.

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.

A low-frequency variant of sushi, von Willebrand factor type A, EGF and pentraxin domain containing protein 1 (SVEP1), an extracellular matrix protein, is associated with risk of coronary disease in humans independent of plasma lipids. Despite a robust statistical association, if and how SVEP1 might contribute to atherosclerosis remained unclear. Here, using Mendelian randomization and complementary mouse models, we provide evidence that SVEP1 promotes atherosclerosis in humans and mice and is expressed by vascular smooth muscle cells (VSMCs) within the atherosclerotic plaque. VSMCs also interact with SVEP1, causing proliferation and dysregulation of key differentiation pathways, including integrin and Notch signaling. Fibroblast growth factor receptor transcription increases in VSMCs interacting with SVEP1, and is further increased by the coronary disease-associated SVEP1 variant p.D2702G. These effects ultimately drive inflammation and promote atherosclerosis. Taken together, our results suggest that VSMC-derived SVEP1 is a pro-atherogenic factor, and support the concept that pharmacological inhibition of SVEP1 should protect against atherosclerosis in humans.

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 two novel loci at which SVs have strong phenotypic effects: (1) a deletion of the ALB gene 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 multiallelic 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.

Mitochondrial copy number is known to vary among humans and across tissues, and a population-based study of mitochondrial genome copy number (MT-CN) in blood – as estimated from genome sequencing data – observed strong (∼54%) heritability. However, the genetic causes and phenotypic consequences of MT-CN variation in humans are not well-studied. Here, we studied MT-CN variation in blood-derived DNA from 19,184 Finnish individuals with deep cardiometabolic trait measurements using a combination of whole genome (N = 4,163) and exome sequencing (N = 19,034) data as well as imputed array genotypes (N = 17,718). We confirmed that MT-CN in blood is highly heritable (31% by GREML). We identified two loci in the nuclear genome that are 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 TMB1M1 gene (P = 3.0×10−8), which has been reported to protect against non-alcoholic fatty liver disease in model organisms. We also found that MT-CN is strongly associated with insulin levels (P = 2.0×10−21), fat mass (P = 4.5×10−16), and other related traits. Using a Mendelian randomization framework, we constructed a genetic instrument for MT-CN using penalized regression with adjustment for potentially confounding covariates and found a significant association with insulin levels, which suggests that our MT-CN measurement in blood may be causally related to metabolic syndrome. Finally, we computed our genetic instrument in UK Biobank participants and tested it against a set of cell count and cardiometabolic traits. We found significant associations between MT-CN and both neutrophil and platelet counts (P = 1.8×10−8 and P = 1.2×10−3). While the association between MT-CN and metabolic syndrome traits was replicated in the UK Biobank, adjusting for cell counts largely eliminated these signals, suggesting that MT-CN is actually a proxy measurement for neutrophil and platelet counts in its effect on metabolic syndrome. Taken together, these results suggest that measurements of MT-CN in blood-derived DNA may primarily reflect differences in cell-type composition, and that these differences may be causally linked to insulin and related traits. Author summary The number of mitochondria per cell is variable between tissues and between individuals, and prior studies have shown that mitochondrial genome copy number in blood (MT-CN) – as estimated indirectly from sequencing of blood-derived DNA – is a genetically determined trait that varies among humans. We studied genetic data from approximately 19,000 Finnish individuals and showed that MT-CN is significantly associated with insulin and related metabolic traits, providing evidence that MT-CN levels play a role in determining these traits. Consistent with a previous study, we showed that genetics play a significant role in determining blood-derived MT-CN. We also found new evidence linking several regions of the genome to MT-CN, including a gene known to be associated with non-alcoholic fatty liver disease. Finally, we found that in the link between blood-derived MT-CN and metabolic syndrome, MT-CN likely represents the relative quantities of circulating immune cells, providing further evidence for the role of inflammation in metabolic syndrome.

SummaryA low-frequency variant of SVEP1, an extracellular matrix protein, is associated with risk of coronary disease in humans independent of plasma lipids. Despite a robust statistical association, however, it was unclear if and how SVEP1 might contribute to atherosclerosis. Here, using Mendelian randomization and complementary mouse models, we provide evidence that SVEP1 promotes atherosclerosis in humans and mice. We find that SVEP1 is expressed by vascular smooth muscle cells (VSMCs) within the atherosclerotic plaque. VSMCs also interact with SVEP1, causing proliferation and dysregulation of key differentiation pathways, including integrin and Notch signaling. Fibroblast growth factor receptor transcription increases in VSMCs interacting with SVEP1, and is further increased by the coronary disease-associated SVEP1 variant. These effects ultimately drive inflammation and promote atherosclerosis. Taken together, our results suggest that VSMC-derived SVEP1 is a pro-atherogenic factor, and support the concept that pharmacological inhibition of SVEP1 should protect against atherosclerosis in humans.

High protein diets are commonly utilized for weight loss, yet have been reported to raise cardiovascular risk. The mechanisms underlying this risk are unknown. Here, we show that dietary protein drives atherosclerosis and lesion complexity. Protein ingestion acutely elevates amino acid levels in blood and atherosclerotic plaques, stimulating macrophage mTOR signaling. This is causal in plaque progression as the effects of dietary protein are abrogated in macrophage-specific Raptor-null mice. Mechanistically, we find amino acids exacerbate macrophage apoptosis induced by atherogenic lipids, a process that involves mTORC1-dependent inhibition of mitophagy, accumulation of dysfunctional mitochondria, and mitochondrial apoptosis. Using macrophage-specific mTORC1- and autophagy-deficient mice we confirm this amino acid-mTORC1-autophagy signaling axis in vivo. Our data provide the first insights into the deleterious impact of excessive protein ingestion on macrophages and atherosclerotic progression. Incorporation of these concepts in clinical studies will be important to define the vascular effects of protein-based weight loss regimens.

Aortic aneurysms are morbid conditions that can lead to rupture or dissection and are categorized as thoracic (TAA) or abdominal aortic aneurysms (AAA) depending on their location. While AAA shares overlapping risk factors with atherosclerotic cardiovascular disease, TAA exhibits strong heritability. Human genetic studies in the past two decades have successfully identified numerous genes involved in both familial and sporadic forms of aortic aneurysm. In this review we will discuss the genetic basis of aortic aneurysm, focusing on the extracellular matrix and how insights from these studies have informed our understanding of human biology and disease pathogenesis.

Type 1 and type 2 diabetes mellitus (T1DM and T2DM) increase the risk of atherosclerotic cardiovascular disease (CVD), resulting in acute cardiovascular events, such as heart attack and stroke. Recent clinical trials point toward new treatment and prevention strategies for cardiovascular complications of T2DM. New antidiabetic agents show unexpected cardioprotective benefits. Moreover, genetic and reverse translational strategies have revealed potential novel targets for CVD prevention in diabetes, including inhibition of apolipoprotein C3 (APOC3). Modeling and pharmacology-based approaches to improve insulin action provide additional potential strategies to combat CVD. The development of new strategies for improved diabetes and lipid control fuels hope for future prevention of CVD associated with diabetes.

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.

Although awareness of familial hypercholesterolemia (FH) is increasing, this common, potentially fatal, treatable condition remains underdiagnosed. Despite FH being a genetic disorder, genetic testing is rarely used. The Familial Hypercholesterolemia Foundation convened an international expert panel to assess the utility of FH genetic testing. The rationale includes the following: 1) facilitation of definitive diagnosis; 2) pathogenic variants indicate higher cardiovascular risk, which indicates the potential need for more aggressive lipid lowering; 3) increase in initiation of and adherence to therapy; and 4) cascade testing of at-risk relatives. The Expert Consensus Panel recommends that FH genetic testing become the standard of care for patients with definite or probable FH, as well as for their at-risk relatives. Testing should include the genes encoding the low-density lipoprotein receptor (LDLR), apolipoprotein B (APOB), and proprotein convertase subtilisin/kexin 9 (PCSK9); other genes may also need to be considered for analysis based on patient phenotype. Expected outcomes include greater diagnoses, more effective cascade testing, initiation of therapies at earlier ages, and more accurate risk stratification.

Heterozygous missense mutations in lysyl oxidase (LOX) are associated with thoracic aortic aneurysms and dissections. To assess how LOX mutations modify protein function and lead to aortic disease, we studied the factors that influence the onset and progression of vascular aneurysms in mice bearing a Lox mutation (p.M292R) linked to aortic dilation in humans. We show that mice heterozygous for the M292R mutation did not develop aneurysmal disease unless challenged with increased hemodynamic stress. Vessel dilation was confined to the ascending aorta although both the ascending and descending aortae showed changes in vessel wall structure, smooth muscle cell number and inflammatory cell recruitment that differed between wild-type and mutant animals. Studies with isolated cells found that M292R-mutant Lox is retained in the endoplasmic reticulum and ultimately cleared through an autophagy/proteasome pathway. Because the mutant protein does not transit to the Golgi where copper incorporation occurs, the protein is never catalytically active. These studies show that the M292R mutation results in LOX loss-of-function due to a secretion defect that predisposes the ascending aorta in mice (and by extension humans with similar mutations) to arterial dilation when exposed to risk factors that impart stress to the arterial wall.

Background We asked whether, after excluding familial hypercholesterolemia, individuals with high low‐density lipoprotein cholesterol ( LDL ‐C) or triacylglyceride levels and a family history of the same hyperlipidemia have greater coronary artery disease risk or different lipidomic profiles compared with population‐based hyperlipidemias. Methods and Results We determined incident coronary artery disease risk for 755 members of 66 hyperlipidemic families (≥2 first‐degree relatives with similar hyperlipidemia) and 19 644 Finnish FINRISK population study participants. We quantified 151 circulating lipid species from 550 members of 73 hyperlipidemic families and 897 FINRISK participants using mass spectrometric shotgun lipidomics. Familial hypercholesterolemia was excluded using functional LDL receptor testing and genotyping. Hyperlipidemias ( LDL ‐C or triacylglycerides >90th population percentile) associated with increased coronary artery disease risk in meta‐analysis of the hyperlipidemic families and the population cohort (high LDL ‐C: hazard ratio, 1.74 [95% CI, 1.48–2.04]; high triacylglycerides: hazard ratio, 1.38 [95% CI, 1.09–1.74]). Risk estimates were similar in the family and population cohorts also after adjusting for lipid‐lowering medication. In lipidomic profiling, high LDL ‐C associated with 108 lipid species, and high triacylglycerides associated with 131 lipid species in either cohort (at 5% false discovery rate; P ‐value range 0.038–2.3×10 −56 ). Lipidomic profiles were highly similar for hyperlipidemic individuals in the families and the population ( LDL ‐C: r =0.80; triacylglycerides: r =0.96; no lipid species deviated between the cohorts). Conclusions Hyperlipidemias with family history conferred similar coronary artery disease risk as population‐based hyperlipidemias. We identified distinct lipidomic profiles associated with high LDL ‐C and triacylglycerides. Lipidomic profiles were similar between hyperlipidemias with family history and population‐ascertained hyperlipidemias, providing evidence of similar and overlapping underlying mechanisms.

A key goal of whole genome sequencing (WGS) for human genetics studies is to interrogate all forms of variation, including single nucleotide variants (SNV), small insertion/deletion (indel) variants and structural variants (SV). However, tools and resources for the study of SV have lagged behind those for smaller variants. Here, we used a cloud-based pipeline to map and characterize SV in 17,795 deeply sequenced human genomes from common disease trait mapping studies. We publicly release site-frequency information to create the largest WGS-based SV resource to date. On average, individuals carry 2.9 rare SVs that alter coding regions, which affect the dosage or structure of 4.2 genes and account for 4.0-11.2% of rare high-impact coding alleles. Based on a computational model, we estimate that SVs account for 17.2% of rare alleles genome-wide whose predicted deleterious effects are equivalent to loss-of-function (LoF) coding alleles; ~90% of such SVs are non-coding deletions (mean 19.1 per genome). We report 158,991 ultra-rare SVs and show that ~2% of individuals carry ultra-rare megabase-scale SVs, nearly half of which are balanced and/or complex rearrangements. Finally, we exploit this resource to infer the dosage sensitivity of genes and non-coding elements, revealing strong trends related to regulatory element class, conservation and cell-type specificity. This work will help guide SV analysis and interpretation in the era of WGS.

Background— The burden of subclinical atherosclerosis in asymptomatic individuals is heritable and associated with elevated risk of developing clinical coronary heart disease. We sought to identify genetic variants in protein-coding regions associated with subclinical atherosclerosis and the risk of subsequent coronary heart disease. Methods and Results— We studied a total of 25 109 European ancestry and African ancestry participants with coronary artery calcification (CAC) measured by cardiac computed tomography and 52 869 participants with common carotid intima–media thickness measured by ultrasonography within the CHARGE Consortium (Cohorts for Heart and Aging Research in Genomic Epidemiology). Participants were genotyped for 247 870 DNA sequence variants (231 539 in exons) across the genome. A meta-analysis of exome-wide association studies was performed across cohorts for CAC and carotid intima–media thickness. APOB p.Arg3527Gln was associated with 4-fold excess CAC ( P =3×10 − 10 ). The APOE ε2 allele (p.Arg176Cys) was associated with both 22.3% reduced CAC ( P =1×10 − 12 ) and 1.4% reduced carotid intima–media thickness ( P =4×10 − 14 ) in carriers compared with noncarriers. In secondary analyses conditioning on low-density lipoprotein cholesterol concentration, the ε2 protective association with CAC, although attenuated, remained strongly significant. Additionally, the presence of ε2 was associated with reduced risk for coronary heart disease (odds ratio 0.77; P =1×10 − 11 ). Conclusions— Exome-wide association meta-analysis demonstrates that protein-coding variants in APOB and APOE associate with subclinical atherosclerosis. APOE ε2 represents the first significant association for multiple subclinical atherosclerosis traits across multiple ethnicities, as well as clinical coronary heart disease.

Meta-analyses of association results for blood pressure using exome-centric single-variant and gene-based tests identified 31 new loci in a discovery stage among 146,562 individuals, with follow-up and meta-analysis in 180,726 additional individuals (total n = 327,288). These blood pressure-associated loci are enriched for known variants for cardiometabolic traits. Associations were also observed for the aggregation of rare and low-frequency missense variants in three genes, NPR1, DBH, and PTPMT1. In addition, blood pressure associations at 39 previously reported loci were confirmed. The identified variants implicate biological pathways related to cardiometabolic traits, vascular function, and development. Several new variants are inferred to have roles in transcription or as hubs in protein-protein interaction networks. Genetic risk scores constructed from the identified variants were strongly associated with coronary disease and myocardial infarction. This large collection of blood pressure-associated loci suggests new therapeutic strategies for hypertension, emphasizing a link with cardiometabolic risk.

AimGenetic investigation of human plasma lipidome to get insights into lipid-related disorders beyond traditional lipid measures.Methods and ResultsWe performed a genome-wide association study (GWAS) of 141 lipid species (n=2,181 individuals), followed by phenome-wide scans (PheWAS) with 44 clinical endpoints related to cardiometabolic, psychiatric and gastrointestinal disorders (n=456,941 individuals). SNP-based heritability for lipid species ranged from 0.10-0.54. Lipids with long-chain polyunsaturated fatty acids showed higher heritability and genetic sharing, suggesting considerable genetic regulation at acyl chains levels. We identified 35 genomic regions associated with at least one lipid species (P−8), revealing 37 new SNP-lipid species pair associations e.g. new association between ABCG5/8 and CE(20:2;0). PheWAS of lipid-species-associated loci suggested new associations of BLK with obesity, FADS2 with thrombophlebitis, and BLK and SPTLC3 with gallbladder disease (false discovery rate SYNGR1, MIR100HG, and PTPRN2 in desaturation and/or elongation of fatty acids. At known lipid loci (FADS2, APOA5 and LPL), genetic associations provided detailed insights to their roles in lipid biology and diseases. We also show that traditional lipid measures may fail to capture lipids such as lysophospatidylcholines (LPCs) and phosphatidylcholines (PCs) that are potential disease risk factors, but are not included in routine screens. The full genome-wide association statistics are available on the web-based database (http://35.205.141.92).ConclusionOur study reveals genetic regulation of plasma lipidome and highlights the potential of lipidomic profiling in disease gene mapping.

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 trait9s 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 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 a set of 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 correct for linkage disequilibrium in summary statistics of 5 million dense genome-wide markers and consistently improves prediction accuracy. We show that NPS significantly 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. The NPS software is available at http://github.com/sgchun/nps/.

Autosomal dominant hypercholesterolemia (ADH) is characterized by elevated LDL-C levels leading to coronary heart disease. Four genes are implicated in ADH: LDLR, APOB, PCSK9 and APOE. Our aim was to identify new mutations in known genes, or in new genes implicated in ADH. Thirteen French families with ADH were recruited and studied by exome sequencing after exclusion, in their probands, of mutations in the LDLR, PCSK9 and APOE genes and fragments of exons 26 and 29 of APOB gene. We identified in one family a p.Arg50Gln mutation in the APOB gene, which occurs in a region not usually associated with ADH. Segregation and in-silico analysis suggested that this mutation is disease causing in the family. We identified in another family with the p.Ala3396Thr mutation of APOB, one patient with a severe phenotype carrying also a mutation in PCSK9: p.Arg96Cys. This is the first compound heterozygote reported with a mutation in APOB and PCSK9. Functional studies proved that the p.Arg96Cys mutation leads to increased LDL receptor degradation. This work shows that Next-Generation Sequencing (exome, genome or targeted sequencing) are powerful tools to find new mutations and identify compound heterozygotes, which will lead to better diagnosis and treatment of ADH.