A genetic association study of circulating coagulation factor VIII and von Willebrand factor levels.

ABSTRACT: Coagulation factor VIII (FVIII) and its carrier protein von Willebrand factor (VWF) are critical to coagulation and platelet aggregation. We leveraged whole-genome sequence data from the Trans-Omics for Precision Medicine (TOPMed) program along with TOPMed-based imputation of genotypes in additional samples to identify genetic associations with circulating FVIII and VWF levels in a single-variant meta-analysis, including up to 45 289 participants. Gene-based aggregate tests were implemented in TOPMed. We identified 3 candidate causal genes and tested their functional effect on FVIII release from human liver endothelial cells (HLECs) and VWF release from human umbilical vein endothelial cells. Mendelian randomization was also performed to provide evidence for causal associations of FVIII and VWF with thrombotic outcomes. We identified associations (P < 5 × 10-9) at 7 new loci for FVIII (ST3GAL4, CLEC4M, B3GNT2, ASGR1, F12, KNG1, and TREM1/NCR2) and 1 for VWF (B3GNT2). VWF, ABO, and STAB2 were associated with FVIII and VWF in gene-based analyses. Multiphenotype analysis of FVIII and VWF identified another 3 new loci, including PDIA3. Silencing of B3GNT2 and the previously reported CD36 gene decreased release of FVIII by HLECs, whereas silencing of B3GNT2, CD36, and PDIA3 decreased release of VWF by HVECs. Mendelian randomization supports causal association of higher FVIII and VWF with increased risk of thrombotic outcomes. Seven new loci were identified for FVIII and 1 for VWF, with evidence supporting causal associations of FVIII and VWF with thrombotic outcomes. B3GNT2, CD36, and PDIA3 modulate the release of FVIII and/or VWF in vitro.

The functional impact of rare variation across the regulatory cascade.

Each human genome has tens of thousands of rare genetic variants; however, identifying impactful rare variants remains a major challenge. We demonstrate how use of personal multi-omics can enable identification of impactful rare variants by using the Multi-Ethnic Study of Atherosclerosis, which included several hundred individuals, with whole-genome sequencing, transcriptomes, methylomes, and proteomes collected across two time points, 10 years apart. We evaluated each multi-omics phenotype's ability to separately and jointly inform functional rare variation. By combining expression and protein data, we observed rare stop variants 62 times and rare frameshift variants 216 times as frequently as controls, compared to 13-27 times as frequently for expression or protein effects alone. We extended a Bayesian hierarchical model, "Watershed," to prioritize specific rare variants underlying multi-omics signals across the regulatory cascade. With this approach, we identified rare variants that exhibited large effect sizes on multiple complex traits including height, schizophrenia, and Alzheimer's disease.

Dyslipidemia.

Dyslipidemia is an important risk factor for coronary artery disease and stroke. All persons with dyslipidemia should be advised to focus on lifestyle interventions, including regular aerobic exercise, a healthy diet, maintenance of a healthy weight, and abstinence from smoking. In addition to lifestyle interventions, lipid-lowering therapy should be considered for persons at moderate to high risk for atherosclerotic cardiovascular disease based on validated risk equations. Statin therapy is the first-line medical treatment for dyslipidemia due to its effectiveness and favorable adverse effect profile, but newer treatments provide additional tools for clinicians to effectively treat dyslipidemia.

High risk oral contraceptive hormones do not directly enhance endothelial cell procoagulant activity in vitro.

BACKGROUND: Oral contraceptive (OC) use increases venous thromboembolism risk 2-5-fold. Procoagulant changes can be detected in plasma from OC users even without thrombosis, but cellular mechanisms that provoke thrombosis have not been identified. Endothelial cell (EC) dysfunction is thought to initiate venous thromboembolism. It is unknown whether OC hormones provoke aberrant procoagulant activity in ECs. OBJECTIVE: Characterize the effect of high-risk OC hormones (ethinyl estradiol [EE] and drospirenone) on EC procoagulant activity and the potential interplay with nuclear estrogen receptors ERα and ERß and inflammatory processes. METHODS: Human umbilical vein and dermal microvascular ECs (HUVEC and HDMVEC, respectively) were treated with EE and/or drospirenone. Genes encoding the estrogen receptors ERα and ERß (ESR1 and ESR2, respectively) were overexpressed in HUVEC and HDMVEC via lentiviral vectors. EC gene expression was assessed by RT-qPCR. The ability of ECs to support thrombin generation and fibrin formation was measured by calibrated automated thrombography and spectrophotometry, respectively. RESULTS: Neither EE nor drospirenone, alone or together, changed expression of genes encoding anti- or procoagulant proteins (TFPI, THBD, F3), integrins (ITGAV, ITGB3), or fibrinolytic mediators (SERPINE1, PLAT). EE and/or drospirenone did not increase EC-supported thrombin generation or fibrin formation, either. Our analyses indicated a subset of individuals express ESR1 and ESR2 transcripts in human aortic ECs. However, overexpression of ESR1 and/or ESR2 in HUVEC and HDMVEC did not facilitate the ability of OC-treated ECs to support procoagulant activity, even in the presence of a pro-inflammatory stimulus. CONCLUSIONS: The OC hormones EE and drospirenone do not directly enhance thrombin generation potential of primary ECs in vitro.

CCRL2 affects the sensitivity of myelodysplastic syndrome and secondary acute myeloid leukemia cells to azacitidine.

Better understanding of the biology of resistance to DNA methyltransferase (DNMT) inhibitors is required to identify therapies that can improve their efficacy for patients with high-risk myelodysplastic syndrome (MDS). CCRL2 is an atypical chemokine receptor that is upregulated in CD34+ cells from MDS patients and induces proliferation of MDS and secondary acute myeloid leukemia (sAML) cells. In this study, we evaluated any role that CCRL2 may have in the regulation of pathways associated with poor response or resistance to DNMT inhibitors. We found that CCRL2 knockdown in TF-1 cells downregulated DNA methylation and PRC2 activity pathways and increased DNMT suppression by azacitidine in MDS/sAML cell lines (MDS92, MDS-L and TF-1). Consistently, CCRL2 deletion increased the sensitivity of these cells to azacitidine in vitro and the efficacy of azacitidine in an MDS-L xenograft model. Furthermore, CCRL2 overexpression in MDS-L and TF-1 cells decreased their sensitivity to azacitidine. Finally, CCRL2 levels were higher in CD34+ cells from MDS and MDS/myeloproliferative neoplasm patients with poor response to DNMT inhibitors. In conclusion, we demonstrated that CCRL2 modulates epigenetic regulatory pathways, particularly DNMT levels, and affects the sensitivity of MDS/sAML cells to azacitidine. These results support CCRL2 targeting as having therapeutic potential in MDS/sAML.

Aggregative trans-eQTL analysis detects trait-specific target gene sets in whole blood.

Large scale genetic association studies have identified many trait-associated variants and understanding the role of these variants in the downstream regulation of gene-expressions can uncover important mediating biological mechanisms. Here we propose ARCHIE, a summary statistic based sparse canonical correlation analysis method to identify sets of gene-expressions trans-regulated by sets of known trait-related genetic variants. Simulation studies show that compared to standard methods, ARCHIE is better suited to identify "core"-like genes through which effects of many other genes may be mediated and can capture disease-specific patterns of genetic associations. By applying ARCHIE to publicly available summary statistics from the eQTLGen consortium, we identify gene sets which have significant evidence of trans-association with groups of known genetic variants across 29 complex traits. Around half (50.7%) of the selected genes do not have any strong trans-associations and are not detected by standard methods. We provide further evidence for causal basis of the target genes through a series of follow-up analyses. These results show ARCHIE is a powerful tool for identifying sets of genes whose trans-regulation may be related to specific complex traits.

Genetic determinants of telomere length from 109,122 ancestrally diverse whole-genome sequences in TOPMed.

Genetic studies on telomere length are important for understanding age-related diseases. Prior GWAS for leukocyte TL have been limited to European and Asian populations. Here, we report the first sequencing-based association study for TL across ancestrally-diverse individuals (European, African, Asian and Hispanic/Latino) from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. We used whole genome sequencing (WGS) of whole blood for variant genotype calling and the bioinformatic estimation of telomere length in n=109,122 individuals. We identified 59 sentinel variants (p-value <5×10-9) in 36 loci associated with telomere length, including 20 newly associated loci (13 were replicated in external datasets). There was little evidence of effect size heterogeneity across populations. Fine-mapping at OBFC1 indicated the independent signals colocalized with cell-type specific eQTLs for OBFC1 (STN1). Using a multi-variant gene-based approach, we identified two genes newly implicated in telomere length, DCLRE1B (SNM1B) and PARN. In PheWAS, we demonstrated our TL polygenic trait scores (PTS) were associated with increased risk of cancer-related phenotypes.

Redefining tissue specificity of genetic regulation of gene expression in the presence of allelic heterogeneity.

Uncovering the functional impact of genetic variation on gene expression is important in understanding tissue biology and the pathogenesis of complex traits. Despite large efforts to map expression quantitative trait loci (eQTLs) across many human tissues, our ability to translate those findings to understanding human disease has been incomplete, and the majority of disease loci are not explained by association with expression of a target gene. Cell-type specificity and the presence of multiple independent causal variants for many eQTLs are potential confounders contributing to the apparent discrepancy with disease loci. In this study, we investigate the tissue specificity of genetic effects on gene expression and the overlap with disease loci while considering the presence of multiple causal variants within and across tissues. We find evidence of pervasive tissue specificity of eQTLs, often masked by linkage disequilibrium that misleads traditional meta-analytic approaches. We propose CAFEH (colocalization and fine-mapping in the presence of allelic heterogeneity), a Bayesian method that integrates genetic association data across multiple traits, incorporating linkage disequilibrium to identify causal variants. CAFEH outperforms previous approaches in colocalization and fine-mapping. Using CAFEH, we show that genes with highly tissue-specific genetic effects are under greater selection, enriched in differentiation and developmental processes, and more likely to be involved in human disease. Last, we demonstrate that CAFEH can efficiently leverage the widespread allelic heterogeneity in genetic regulation of gene expression to prioritize the target tissue in genome-wide association complex trait loci, thereby improving our ability to interpret complex trait genetics.

Linear and Nonlinear Mendelian Randomization Analyses of the Association Between Diastolic Blood Pressure and Cardiovascular Events: The J-Curve Revisited.

BACKGROUND: Recent clinical guidelines support intensive blood pressure treatment targets. However, observational data suggest that excessive diastolic blood pressure (DBP) lowering might increase the risk of myocardial infarction (MI), reflecting a J- or U-shaped relationship. METHODS: We analyzed 47 407 participants from 5 cohorts (median age, 60 years). First, to corroborate previous observational analyses, we used traditional statistical methods to test the shape of association between DBP and cardiovascular disease (CVD). Second, we created polygenic risk scores of DBP and systolic blood pressure and generated linear Mendelian randomization (MR) estimates for the effect of DBP on CVD. Third, using novel nonlinear MR approaches, we evaluated for nonlinearity in the genetic relationship between DBP and CVD events. Comprehensive MR interrogation of DBP required us to also model systolic blood pressure, given that the 2 are strongly correlated. RESULTS: Traditional observational analysis of our cohorts suggested a J-shaped association between DBP and MI. By contrast, linear MR analyses demonstrated an adverse effect of increasing DBP increments on CVD outcomes, including MI (MI hazard ratio, 1.07 per unit mm Hg increase in DBP; P<0.001). Furthermore, nonlinear MR analyses found no evidence for a J-shaped relationship; instead confirming that MI risk decreases consistently per unit decrease in DBP, even among individuals with low values of baseline DBP. CONCLUSIONS: In this analysis of the genetic effect of DBP, we found no evidence for a nonlinear J- or U-shaped relationship between DBP and adverse CVD outcomes; including MI.

sn-spMF: matrix factorization informs tissue-specific genetic regulation of gene expression.

Genetic regulation of gene expression, revealed by expression quantitative trait loci (eQTLs), exhibits complex patterns of tissue-specific effects. Characterization of these patterns may allow us to better understand mechanisms of gene regulation and disease etiology. We develop a constrained matrix factorization model, sn-spMF, to learn patterns of tissue-sharing and apply it to 49 human tissues from the Genotype-Tissue Expression (GTEx) project. The learned factors reflect tissues with known biological similarity and identify transcription factors that may mediate tissue-specific effects. sn-spMF, available at https://github.com/heyuan7676/ts_eQTLs , can be applied to learn biologically interpretable patterns of eQTL tissue-specificity and generate testable mechanistic hypotheses.

Genome-wide association and multi-omic analyses reveal ACTN2 as a gene linked to heart failure.

Heart failure is a major public health problem affecting over 23 million people worldwide. In this study, we present the results of a large scale meta-analysis of heart failure GWAS and replication in a comparable sized cohort to identify one known and two novel loci associated with heart failure. Heart failure sub-phenotyping shows that a new locus in chromosome 1 is associated with left ventricular adverse remodeling and clinical heart failure, in response to different initial cardiac muscle insults. Functional characterization and fine-mapping of that locus reveal a putative causal variant in a cardiac muscle specific regulatory region activated during cardiomyocyte differentiation that binds to the ACTN2 gene, a crucial structural protein inside the cardiac sarcolemma (Hi-C interaction p-value = 0.00002). Genome-editing in human embryonic stem cell-derived cardiomyocytes confirms the influence of the identified regulatory region in the expression of ACTN2. Our findings extend our understanding of biological mechanisms underlying heart failure.

ACE inhibition and cardiometabolic risk factors, lung ACE2 and TMPRSS2 gene expression, and plasma ACE2 levels: a Mendelian randomization study.

Angiotensin-converting enzyme 2 (ACE2) and serine protease TMPRSS2 have been implicated in cell entry for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for coronavirus disease 2019 (COVID-19). The expression of ACE2 and TMPRSS2 in the lung epithelium might have implications for the risk of SARS-CoV-2 infection and severity of COVID-19. We use human genetic variants that proxy angiotensin-converting enzyme (ACE) inhibitor drug effects and cardiovascular risk factors to investigate whether these exposures affect lung ACE2 and TMPRSS2 gene expression and circulating ACE2 levels. We observed no consistent evidence of an association of genetically predicted serum ACE levels with any of our outcomes. There was weak evidence for an association of genetically predicted serum ACE levels with ACE2 gene expression in the Lung eQTL Consortium (p = 0.014), but this finding did not replicate. There was evidence of a positive association of genetic liability to type 2 diabetes mellitus with lung ACE2 gene expression in the Gene-Tissue Expression (GTEx) study (p = 4 × 10-4) and with circulating plasma ACE2 levels in the INTERVAL study (p = 0.03), but not with lung ACE2 expression in the Lung eQTL Consortium study (p = 0.68). There were no associations of genetically proxied liability to the other cardiometabolic traits with any outcome. This study does not provide consistent evidence to support an effect of serum ACE levels (as a proxy for ACE inhibitors) or cardiometabolic risk factors on lung ACE2 and TMPRSS2 expression or plasma ACE2 levels.

Author Correction: Retinal transcriptome and eQTL analyses identify genes associated with age-related macular degeneration.

In the version of this article initially published, in Supplementary Data 5, the logFC, FC, P value and adjusted P value for advanced AMD versus control (DE 4/1) without age correction did not correspond to the correct gene IDs. The errors have been corrected in the HTML version of the article.

Retinal transcriptome and eQTL analyses identify genes associated with age-related macular degeneration.

Genome-wide association studies (GWAS) have identified genetic variants at 34 loci contributing to age-related macular degeneration (AMD)1-3. We generated transcriptional profiles of postmortem retinas from 453 controls and cases at distinct stages of AMD and integrated retinal transcriptomes, covering 13,662 protein-coding and 1,462 noncoding genes, with genotypes at more than 9 million common SNPs for expression quantitative trait loci (eQTL) analysis of a tissue not included in Genotype-Tissue Expression (GTEx) and other large datasets4,5. Cis-eQTL analysis identified 10,474 genes under genetic regulation, including 4,541 eQTLs detected only in the retina. Integrated analysis of AMD-GWAS with eQTLs ascertained likely target genes at six reported loci. Using transcriptome-wide association analysis (TWAS), we identified three additional genes, RLBP1, HIC1 and PARP12, after Bonferroni correction. Our studies expand the genetic landscape of AMD and establish the Eye Genotype Expression (EyeGEx) database as a resource for post-GWAS interpretation of multifactorial ocular traits.

Use of Serum Transthyretin as a Prognostic Indicator and Predictor of Outcome in Cardiac Amyloid Disease Associated With Wild-Type Transthyretin.

BACKGROUND: Wild-type transthyretin amyloidosis (ATTRwt), an underappreciated cause of heart failure in older adults, is challenging to diagnose and monitor in the absence of validated, disease-specific biomarkers. We examined the prognostic use and survival association of serum TTR (transthyretin) concentration in ATTRwt. METHODS AND RESULTS: Patients with biopsy-proven ATTRwt were retrospectively identified. Serum TTR, cardiac biomarkers, and echocardiographic parameters were assessed at baseline and follow-up evaluations. Statistical analyses included Kaplan-Meier method, Cox proportional hazard survival models, and receiver-operating characteristic curve analysis. Median serum TTR concentration at presentation was 23 mg/dL (n=116). Multivariate predictors of shorter overall survival were decreased TTR, left ventricular ejection fraction and elevated cTn-I (cardiac troponin I); an inclusive model demonstrated superior accuracy in 4-year survival prediction by receiver-operating characteristic curve analysis (area under the curve, 0.77). TTR values lower than the normal limit, <18 mg/dL, were associated with shorter survival (2.8 versus 4.1 years; P=0.03). Further, TTR values at 1- and 2-year follow-ups were significantly lower (P<0.001) in untreated patients (n=23) compared with those treated with TTR stabilizer, diflunisal (n=12), after baseline evaluation. During 2-year follow-up, unchanged TTR corresponded to increased cTn-I (P=0.006) in untreated patients; conversely, the diflunisal-treated group showed increased TTR (P=0.001) and stabilized cTn-I and left ventricular ejection fraction at 1 year. CONCLUSIONS: In this series of biopsy-proven ATTRwt, lower baseline serum TTR concentration was associated with shorter survival as an independent predictor of outcome. Longitudinal analysis demonstrated that decreasing TTR corresponded to worsening cardiac function. These data suggest that TTR may be a useful prognostic marker and predictor of outcome in ATTRwt.