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Background Factor V (FV) is a key molecular player in the coagulation cascade. FV plasma levels have been associated with several human diseases, including thrombosis, bleeding, and diabetic complications. So far, 2 genes have been robustly found through genome‐wide association analyses to contribute to the inter‐individual variability of plasma FV levels: structural F5 gene and PLXDC2. Methods and Results The authors used the underestimated Brown‐Forsythe methodology implemented in the QuickTest software to search for non‐additive genetic effects that could contribute to the inter‐individual variability of FV plasma activity. QUICKTEST was applied to 4 independent genome‐wide association studies studies (LURIC [Ludwigshafen RIsk and Cardiovascular Health Study], MARTHA [Marseille Thrombosis Association], MEGA [Multiple Environmental and Genetic Assessment], and RETROVE [Riesgo de Enfermedad Tromboembolica Venosa]) totaling 4505 participants of European ancestry with measured FV plasma levels. Results obtained in the 4 cohorts were meta‐analyzed using a fixed‐effect model. Additional analyses involved exploring haplotype and gene×gene interactions in downstream investigations. A genome‐wide significant signal at the PSKH2 locus on chr8q21.3 with lead variant rs75463553 with no evidence for heterogeneity across cohorts was observed (P=0.518). Although rs75463553 did not show an association with mean FV levels (P=0.49), it demonstrated a robust significant (P=3.38x10−9) association with the variance of FV plasma levels. Further analyses confirmed the reported association of PSKH2 with neutrophil biology and revealed that rs75463553 likely interacts with two loci, GRIN2A and POM121L12, known for their involvement in smoking biology. Conclusions This comprehensive approach identifies the role of PSKH2 as a novel molecular player in the genetic regulation of FV, shedding light on the contribution of neutrophils to FV biology.

Abstract Background Thrombo-inflammation and neutrophil extracellular traps (NETs) are exacerbated in severe cases of COVID-19, potentially contributing to disease exacerbation. However, the mechanisms underpinning this dysregulation remain elusive. We hypothesised that lower DNase activity may be associated with higher NETosis and clinical worsening in patients with COVID-19. Methods Biological samples were obtained from hospitalized patients (15 severe, 37 critical at sampling) and 93 non-severe ambulatory cases. Our aims were to compare NET biomarkers, functional DNase levels, and explore mechanisms driving any imbalance concerning disease severity. Results Functional DNase levels were diminished in the most severe patients, paralleling an imbalance between NET markers and DNase activity. DNase1 antigen levels were higher in ambulatory cases but lower in severe patients. DNase1L3 antigen levels remained consistent across subgroups, not rising alongside NET markers. DNASE1 polymorphisms correlated with reduced DNase1 antigen levels. Moreover, a quantitative deficiency in plasmacytoid dendritic cells (pDCs), which primarily express DNase1L3, was observed in critical patients. Analysis of public single-cell RNAseq data revealed reduced DNase1L3 expression in pDCs from severe COVID-19 patient. Conclusion Severe and critical COVID-19 cases exhibited an imbalance between NET and DNase functional activity and quantity. Early identification of NETosis imbalance could guide targeted therapies against thrombo-inflammation in COVID-19-related sepsis, such as DNase administration, to avert clinical deterioration. Trial registration: COVERAGE trial (NCT04356495) and COLCOV19-BX study (NCT04332016). Graphical Abstract

Summary: Background: Two important questions regarding the genetics of pancreatic adenocarcinoma (PDAC) are 1. Which germline genetic variants influence the incidence of this cancer; and 2. Whether PDAC causally predisposes to associated non-malignant phenotypes, such as type 2 diabetes (T2D) and venous thromboembolism (VTE). Methods: In this study of 8803 patients with PDAC and 67,523 controls, we first performed a large-scale transcriptome-wide association study to investigate the association between genetically determined gene expression in normal pancreas tissue and PDAC risk. Secondly, we used Mendelian Randomization (MR) to analyse the causal relationships among PDAC, T2D (74,124 cases and 824,006 controls) and VTE (30,234 cases and 172,122 controls). Findings: Sixteen genes showed an association with PDAC risk (FDR

Abstract Hereditary Hemorrhagic Telangiectasia (HHT) is a rare, autosomal dominant, vascular disorder. About 80% of cases are caused by pathogenic variants in ACVRL1 (also known as ALK1) and ENG, with the remaining cases being unexplained. We identified two variants, c.-79C>T and c.-68G>A, in the 5’UTR of ENG in two unrelated patients. They create upstream AUGs at the origin of upstream overlapping open reading frames (uoORFs) ending at the same stop codon. To assess the pathogenicity of these variants, we performed functional assays based on the expression of wild-type and mutant constructs in human cells and evaluated their effect on ALK1 activity in a BMP-response element assay. This assay is mandatory for molecular diagnosis and has been so far only applied to coding ENG variants. These variants were associated with a decrease of protein levels in HeLa and HUVEC cells and a decreased ability to activate ALK1. We applied the same experiments on three additional uoORF-creating variants (c.-142A>T, c.-127C>T and c.-10C>T) located in the 5’UTR of ENG and previously reported in HHT patients. We found that all the analyzed variants alter protein levels and function. Additional experiments relying on an artificial deletion in our mutated constructs show that identified uAUGs could initiate the translation indicating that the associated effect is translation-dependent. Overall, we have identified two 5’UTR ENG variations in HHT patients and shed new light on the role of upstream ORFs on ENG regulation. Our findings contribute to the amelioration of molecular diagnosis in HHT.

Abstract Venous thromboembolism (VTE) is a common, multi-causal disease with potentially serious short- and long-term complications. In clinical practice, there is a need for improved plasma biomarker-based tools for VTE diagnosis and risk prediction. Here we show, using proteomics profiling to screen plasma from patients with suspected acute VTE, and several case-control studies for VTE, how Complement Factor H Related 5 protein (CFHR5), a regulator of the alternative pathway of complement activation, is a VTE-associated plasma biomarker. In plasma, higher CFHR5 levels are associated with increased thrombin generation potential and recombinant CFHR5 enhanced platelet activation in vitro. GWAS analysis of ~52,000 participants identifies six loci associated with CFHR5 plasma levels, but Mendelian randomization do not demonstrate causality between CFHR5 and VTE. Our results indicate an important role for the regulation of the alternative pathway of complement activation in VTE and that CFHR5 represents a potential diagnostic and/or risk predictive plasma biomarker.

Abstract Background In studies of time-to-events, it is common to collect information about events that occurred before the inclusion in a prospective cohort. When the studied risk factors are independent of time, including both pre- and post-inclusion events in the analyses, generally referred to as relying on an ambispective design, increases the statistical power but may lead to a selection bias. In the field of venous thromboembolism (VT), ABO blood groups have been the subject of extensive research due to their substantial effect on VT risk. However, few studies have investigated their effect on the risk of VT recurrence. Motivated by the study of the association of genetically determined ABO blood groups with VT recurrence, we propose a methodology to include pre-inclusion events in the analysis of ambispective studies while avoiding the selection bias due to mortality. Methods This work relies on two independent cohorts of VT patients, the French MARTHA study built on an ambispective design and the Dutch MEGA study built on a standard prospective design. For the analysis of the MARTHA study, a weighted Cox model was developed where weights were defined by the inverse of the survival probability at the time of data collection about the events. Thanks to the collection of information on the vital status of patients, we could estimate the survival probabilities using a delayed-entry Cox model on the death risk. Finally, results obtained in both studies were then meta-analysed. Results In the combined sample totalling 2,752 patients including 993 recurrences, the A1 blood group has an increased risk (Hazard Ratio (HR) of 1.18, p = 4.2 × 10–3) compared with the O1 group, homogeneously in MARTHA and in MEGA. The same trend (HR = 1.19, p = 0.06) was observed for the less frequent A2 group. Conclusion The proposed methodology increases the power of studies relying on an ambispective design which is frequent in epidemiologic studies about recurrent events. This approach allowed to clarify the association of ABO blood groups with the risk of VT recurrence. Besides, this methodology has an immediate field of application in the context of genome wide association studies.

AimRare genetic variants in the CUBN gene encoding the main albumin-transporter in the proximal tubule of the kidneys have previously been associated with microalbuminuria and higher urine albumin levels, also in diabetes. Sequencing studies in isolated proteinuria suggest that these variants might not affect kidney function, despite proteinuria. However, the relation of these CUBN missense variants to the estimated glomerular filtration rate (eGFR) is largely unexplored. We hereby broadly examine the associations between four CUBN missense variants and eGFRcreatinine in Europeans with Type 1 (T1D) and Type 2 Diabetes (T2D). Furthermore, we sought to deepen our understanding of these variants in a range of single- and aggregate- variant analyses of other kidney-related traits in individuals with and without diabetes mellitus.MethodsWe carried out a genetic association-based linear regression analysis between four CUBN missense variants (rs141640975, rs144360241, rs45551835, rs1801239) and eGFRcreatinine (ml/min/1.73 m2, CKD-EPIcreatinine(2012), natural log-transformed) in populations with T1D (n ~ 3,588) or T2D (n ~ 31,155) from multiple European studies and in individuals without diabetes from UK Biobank (UKBB, n ~ 370,061) with replication in deCODE (n = 127,090). Summary results of the diabetes-group were meta-analyzed using the fixed-effect inverse-variance method.ResultsAlbeit we did not observe associations between eGFRcreatinine and CUBN in the diabetes-group, we found significant positive associations between the minor alleles of all four variants and eGFRcreatinine in the UKBB individuals without diabetes with rs141640975 being the strongest (Effect=0.02, PeGFR_creatinine=2.2 × 10-9). We replicated the findings for rs141640975 in the Icelandic non-diabetes population (Effect=0.026, PeGFR_creatinine=7.7 × 10-4). For rs141640975, the eGFRcreatinine-association showed significant interaction with albuminuria levels (normo-, micro-, and macroalbuminuria; p = 0.03). An aggregated genetic risk score (GRS) was associated with higher urine albumin levels and eGFRcreatinine. The rs141640975 variant was also associated with higher levels of eGFRcreatinine-cystatin C (ml/min/1.73 m2, CKD-EPI2021, natural log-transformed) and lower circulating cystatin C levels.ConclusionsThe positive associations between the four CUBN missense variants and eGFR in a large population without diabetes suggests a pleiotropic role of CUBN as a novel eGFR-locus in addition to it being a known albuminuria-locus. Additional associations with diverse renal function measures (lower cystatin C and higher eGFRcreatinine-cystatin C levels) and a CUBN-focused GRS further suggests an important role of CUBN in the future personalization of chronic kidney disease management in people without diabetes.

Rare variant association tests (RVAT) have been developed to study the contribution of rare variants widely accessible through high-throughput sequencing technologies. RVAT require to aggregate rare variants in testing units and to filter variants to retain only the most likely causal ones. In the exome, genes are natural testing units and variants are usually filtered based on their functional consequences. However, when dealing with whole-genome sequence (WGS) data, both steps are challenging. No natural biological unit is available for aggregating rare variants. Sliding windows procedures have been proposed to circumvent this difficulty, however they are blind to biological information and result in a large number of tests. We propose a new strategy to perform RVAT on WGS data: "RAVA-FIRST" (RAre Variant Association using Functionally-InfoRmed STeps) comprising three steps. (1) New testing units are defined genome-wide based on functionally-adjusted Combined Annotation Dependent Depletion (CADD) scores of variants observed in the gnomAD populations, which are referred to as "CADD regions". (2) A region-dependent filtering of rare variants is applied in each CADD region. (3) A functionally-informed burden test is performed with sub-scores computed for each genomic category within each CADD region. Both on simulations and real data, RAVA-FIRST was found to outperform other WGS-based RVAT. Applied to a WGS dataset of venous thromboembolism patients, we identified an intergenic region on chromosome 18 enriched for rare variants in early-onset patients. This region that was missed by standard sliding windows procedures is included in a TAD region that contains a strong candidate gene. RAVA-FIRST enables new investigations of rare non-coding variants in complex diseases, facilitated by its implementation in the R package Ravages.

Abstract Venous thromboembolism is the third common cardiovascular disease and is composed of two entities, deep vein thrombosis (DVT) and its potential fatal form, pulmonary embolism (PE). While PE is observed in ~ 40% of patients with documented DVT, there is limited biomarkers that can help identifying patients at high PE risk. To fill this need, we implemented a two hidden-layers artificial neural networks (ANN) on 376 antibodies and 19 biological traits measured in the plasma of 1388 DVT patients, with or without PE, of the MARTHA study. We used the LIME algorithm to obtain a linear approximate of the resulting ANN prediction model. As MARTHA patients were typed for genotyping DNA arrays, a genome wide association study (GWAS) was conducted on the LIME estimate. Detected single nucleotide polymorphisms (SNPs) were tested for association with PE risk in MARTHA. Main findings were replicated in the EOVT study composed of 143 PE patients and 196 DVT only patients. The derived ANN model for PE achieved an accuracy of 0.89 and 0.79 in our training and testing sets, respectively. A GWAS on the LIME approximate identified a strong statistical association peak (rs1424597: p = 5.3 × 10–7) at the PLXNA4 locus. Homozygote carriers for the rs1424597-A allele were then more frequently observed in PE than in DVT patients from the MARTHA (2% vs. 0.4%, p = 0.005) and the EOVT (3% vs. 0%, p = 0.013) studies. In a sample of 112 COVID-19 patients known to have endotheliopathy leading to acute lung injury and an increased risk of PE, decreased PLXNA4 levels were associated (p = 0.025) with worsened respiratory function. Using an original integrated proteomics and genetics strategy, we identified PLXNA4 as a new susceptibility gene for PE whose exact role now needs to be further elucidated.

White matter hyperintensities (WMH) are a common brain-imaging feature of cerebral small vessel disease. Here, the authors carry out a GWAS and followup analyses for WMH-volume, implicating several variants with potential for risk stratification and drug targeting.

Vascular homeostasis is impaired in various diseases thereby contributing to the progression of their underlying pathologies. The endothelial immediate early gene Apolipoprotein L domain-containing 1 (APOLD1) helps to regulate endothelial function. However, its precise role in endothelial cell biology remains unclear. We have localized APOLD1 to endothelial cell contacts and to Weibel-Palade bodies (WPB) where it associates with von Willebrand factor (VWF) tubules. Silencing of APOLD1 in primary human endothelial cells disrupted the cell junction-cytoskeletal interface, thereby altering endothelial permeability accompanied by spontaneous release of WPB contents. This resulted in an increased presence of WPB cargoes, notably VWF and angiopoietin-2 in the extracellular medium. Autophagy flux, previously recognized as an essential mechanism for the regulated release of WPB, was impaired in the absence of APOLD1. In addition, we report APOLD1 as a candidate gene for a novel inherited bleeding disorder across three generations of a large family in which an atypical bleeding diathesis was associated with episodic impaired microcirculation. A dominant heterozygous nonsense APOLD1:p.R49* variant segregated to affected family members. Compromised vascular integrity resulting from an excess of plasma angiopoietin-2, and locally impaired availability of VWF may explain the unusual clinical profile of APOLD1:p.R49* patients. In summary, our findings identify APOLD1 as an important regulator of vascular homeostasis and raise the need to consider testing of endothelial cell function in patients with inherited bleeding disorders without apparent platelet or coagulation defects.

High-throughput sequencing (HTS) technologies are revolutionizing the research and molecular diagnosis landscape by allowing the exploration of millions of nucleotide sequences at an unprecedented scale. These technologies are of particular interest in the identification of genetic variations contributing to the risk of rare (Mendelian) and common (multifactorial) human diseases. So far, they have led to numerous successes in identifying rare disease-causing mutations in coding regions, but few in non-coding regions that include introns, untranslated (UTR), and intergenic regions. One class of neglected non-coding variations is that of 5′UTR variants that alter upstream open reading frames (upORFs) of the coding sequence (CDS) of a natural protein coding transcript. Following a brief summary of the molecular bases of the origin and functions of upORFs, we will first review known 5′UTR variations altering upORFs and causing rare cardiovascular disorders (CVDs). We will then investigate whether upORF-affecting single nucleotide polymorphisms could be good candidates for explaining association signals detected in the context of genome-wide association studies for common complex CVDs.

Advances in genomics and molecular biology have revealed an abundance of small open reading frames (sORFs) across all types of transcripts. While these sORFs are often assumed to be non-functional, many have been implicated in physiological functions and a significant number of sORFs have been described in human diseases. Thus, sORFs may represent a hidden repository of functional elements that could serve as therapeutic targets. Unlike protein-coding genes, it is not necessarily the encoded peptide of an sORF that enacts its function, sometimes simply the act of translating an sORF might have a regulatory role. Indeed, the most studied sORFs are located in the 5′UTRs of coding transcripts and can have a regulatory impact on the translation of the downstream protein-coding sequence. However, sORFs have also been abundantly identified in non-coding RNAs including lncRNAs, circular RNAs and ribosomal RNAs suggesting that sORFs may be diverse in function. Of the many different experimental methods used to discover sORFs, the most commonly used are ribosome profiling and mass spectrometry. These can confirm interactions between transcripts and ribosomes and the production of a peptide, respectively. Extensions to ribosome profiling, which also capture scanning ribosomes, have further made it possible to see how sORFs impact the translation initiation of mRNAs. While high-throughput techniques have made the identification of sORFs less difficult, defining their function, if any, is typically more challenging. Together, the abundance and potential function of many of these sORFs argues for the necessity of including sORFs in gene annotations and systematically characterizing these to understand their potential functional roles. In this review, we will focus on the high-throughput methods used in the detection and characterization of sORFs and discuss techniques for validation and functional characterization.

Rare variants outside the classical coagulation cascade might cause inherited thrombosis. We aimed to identify the variant(s) causing venous thromboembolism (VTE) in a family with multiple relatives affected with unprovoked VTE and no thrombophilia defects. We identified by whole exome sequencing an extremely rare Arg to Gln variant (Arg89Gln) in the Microtubule Associated Serine/Threonine Kinase 2 (MAST2) gene that segregates with VTE in the family. Free-tissue factor pathway inhibitor (f-TFPI) plasma levels were significantly decreased in affected family members compared to healthy relatives. Conversely, plasminogen activator inhibitor-1 (PAI-1) levels were significantly higher in affected members than in healthy relatives. RNA sequencing analysis of RNA interference experimental data conducted in endothelial cells revealed that, of the 13,387 detected expressed genes, 2,354 have their level of expression modified by MAST2 knockdown, including SERPINE1 coding for PAI-1 and TFPI. In HEK293 cells overexpressing the MAST2 Gln89 variant, TFPI and SERPINE1 promoter activities were respectively lower and higher than in cells overexpressing the MAST2 wild type. This study identifies a novel thrombophilia-causing Arg89Gln variant in the MAST2 gene that is here proposed as a new molecular player in the etiology of VTE by interfering with hemostatic balance of endothelial cells.

Abstract Background Patients with type 1 diabetes are more at risk of coronary artery disease than the general population. Although evidence points to a genetic risk there have been no study investigating genetic risk factors of coronary artery disease specific to individuals with type 1 diabetes. To identify low frequency and common genetic variations associated with coronary artery disease in populations of individuals with type 1 diabetes. Methods A two-stage genome wide association study was conducted. The discovery phase involved the meta-analysis of three genome-wide association cohorts totaling 434 patients with type 1 diabetes and coronary artery disease (cases) and 3123 T1D individuals with no evidence of coronary artery disease (controls). Replication of the top association signals (p

Background Systemic iron status has been implicated in atherosclerosis and thrombosis. The aim of this study was to investigate the effect of genetically determined iron status on carotid intima‐media thickness, carotid plaque, and venous thromboembolism using Mendelian randomization. Methods and Results Genetic instrumental variables for iron status were selected from a genome‐wide meta‐analysis of 48 972 subjects. Genetic association estimates for carotid intima‐media thickness and carotid plaque were obtained using data from 71 128 and 48 434 participants, respectively, and estimates for venous thromboembolism were obtained using data from a study incorporating 7507 cases and 52 632 controls. Conventional 2‐sample summary data Mendelian randomization was performed for the main analysis. Higher genetically determined iron status was associated with increased risk of venous thromboembolism. Odds ratios per SD increase in biomarker levels were 1.37 (95% CI 1.14‐1.66) for serum iron, 1.25 (1.09‐1.43) for transferrin saturation, 1.92 (1.28‐2.88) for ferritin, and 0.76 (0.63‐0.92) for serum transferrin (with higher transferrin levels representing lower iron status). In contrast, higher iron status was associated with lower risk of carotid plaque. Corresponding odds ratios were 0.85 (0.73‐0.99) for serum iron and 0.89 (0.80‐1.00) for transferrin saturation, with concordant trends for serum transferrin and ferritin that did not reach statistical significance. There was no Mendelian randomization evidence of an effect of iron status on carotid intima‐media thickness. Conclusions These findings support previous work to suggest that higher genetically determined iron status is protective against some forms of atherosclerotic disease but increases the risk of thrombosis related to stasis of blood.

Macrophages are key players involved in numerous pathophysiological pathways and an in-depth characterization of their gene regulatory networks can help in better understanding how their dysfunction may impact on human diseases. We here conducted a cross-species network analysis of macrophage gene expression data between human and mouse to identify conserved networks across both species, and assessed whether such networks could reveal new disease-associated regulatory mechanisms. From a sample of 684 individuals processed for genome-wide macrophage gene expression profiling, we identified 27 groups of coexpressed genes (modules). Six modules were found preserved (P < 10−4) in macrophages from 86 mice of the Hybrid Mouse Diversity Panel. One of these modules was significantly [false discovery rate (FDR) = 8.9 × 10−11] enriched for genes belonging to the oxidative phosphorylation (OXPHOS) pathway. This pathway was also found significantly (FDR < 10−4) enriched in susceptibility genes for Alzheimer, Parkinson, and Huntington diseases. We further conducted an expression quantitative trait loci analysis to identify SNP that could regulate macrophage OXPHOS gene expression in humans. This analysis identified the PARK2 rs192804963 as a trans-acting variant influencing (minimal P-value = 4.3 × 10−8) the expression of most OXPHOS genes in humans. Further experimental work demonstrated that PARK2 knockdown expression was associated with increased OXPHOS gene expression in THP1 human macrophages. This work provided strong new evidence that PARK2 participates to the regulatory networks associated with oxidative phosphorylation and suggested that PARK2 genetic variations could act as a trans regulator of OXPHOS gene macrophage expression in humans.

Prognostic models based on survival data frequently make use of the Cox proportional hazards model. Developing reliable Cox models with few events relative to the number of predictors can be challenging, even in low-dimensional datasets, with a much larger number of observations than variables. In such a setting we examined the performance of methods used to estimate a Cox model, including (i) full model using all available predictors and estimated by standard techniques, (ii) backward elimination (BE), (iii) ridge regression, (iv) least absolute shrinkage and selection operator (lasso), and (v) elastic net. Based on a prospective cohort of patients with manifest coronary artery disease (CAD), we performed a simulation study to compare the predictive accuracy, calibration, and discrimination of these approaches. Candidate predictors for incident cardiovascular events we used included clinical variables, biomarkers, and a selection of genetic variants associated with CAD. The penalized methods, i.e., ridge, lasso, and elastic net, showed a comparable performance, in terms of predictive accuracy, calibration, and discrimination, and outperformed BE and the full model. Excessive shrinkage was observed in some cases for the penalized methods, mostly on the simulation scenarios having the lowest ratio of a number of events to the number of variables. We conclude that in similar settings, these three penalized methods can be used interchangeably. The full model and backward elimination are not recommended in rare event scenarios.

Cardiovascular diseases (CVD) and type 2 diabetes (T2D) are closely interrelated complex diseases likely sharing overlapping pathogenesis driven by aberrant activities in gene networks. However, the molecular circuitries underlying the pathogenic commonalities remain poorly understood. We sought to identify the shared gene networks and their key intervening drivers for both CVD and T2D by conducting a comprehensive integrative analysis driven by five multi-ethnic genome-wide association studies (GWAS) for CVD and T2D, expression quantitative trait loci (eQTLs), ENCODE, and tissue-specific gene network models (both co-expression and graphical models) from CVD and T2D relevant tissues. We identified pathways regulating the metabolism of lipids, glucose, and branched-chain amino acids, along with those governing oxidation, extracellular matrix, immune response, and neuronal system as shared pathogenic processes for both diseases. Further, we uncovered 15 key drivers including HMGCR, CAV1, IGF1 and PCOLCE, whose network neighbors collectively account for approximately 35% of known GWAS hits for CVD and 22% for T2D. Finally, we cross-validated the regulatory role of the top key drivers using in vitro siRNA knockdown, in vivo gene knockout, and two Hybrid Mouse Diversity Panels each comprised of >100 strains. Findings from this in-depth assessment of genetic and functional data from multiple human cohorts provide strong support that common sets of tissue-specific molecular networks drive the pathogenesis of both CVD and T2D across ethnicities and help prioritize new therapeutic avenues for both CVD and T2D.

Congenital macrothrombocytopenia is a family of rare diseases, of which a significant fraction remains to be genetically characterized. To analyze cases of unexplained thrombocytopenia, 27 individuals from a patient cohort of the Bleeding and Thrombosis Exploration Center of the University Hospital of Marseille were recruited for a high-throughput gene sequencing study. This strategy led to the identification of two novel FLI1 variants (c.1010G>A and c.1033A>G) responsible for macrothrombocytopenia. The FLI1 variant carriers’ platelets exhibited a defect in aggregation induced by low-dose adenosine diphosphate (ADP), collagen and thrombin receptor-activating peptide (TRAP), a defect in adenosine triphosphate (ATP) secretion, a reduced mepacrine uptake and release and a reduced CD63 expression upon TRAP stimulation. Precise ultrastructural analysis of platelet content was performed using transmission electron microscopy and focused ion beam scanning electron microscopy. Remarkably, dense granules were nearly absent in the carriers’ platelets, presumably due to a biogenesis defect. Additionally, 25–29% of the platelets displayed giant α-granules, while a smaller proportion displayed vacuoles (7–9%) and autophagosome-like structures (0–3%). In vitro study of megakaryocytes derived from circulating CD34+ cells of the carriers revealed a maturation defect and reduced proplatelet formation potential. The study of the FLI1 variants revealed a significant reduction in protein nuclear accumulation and transcriptional activity properties. Intraplatelet flow cytometry efficiently detected the biomarker MYH10 in FLI1 variant carriers. Overall, this study provides new insights into the phenotype, pathophysiology and diagnosis of FLI1 variant-associated thrombocytopenia.

Variants in ETV6, which encodes a transcription repressor of the E26 transformation-specific family, have recently been reported to be responsible for inherited thrombocytopenia and hematologic malignancy. We sequenced the DNA from cases with unexplained dominant thrombocytopenia and identified six likely pathogenic variants in ETV6, of which five are novel. We observed low repressive activity of all tested ETV6 variants, and variants located in the E26 transformation-specific binding domain (encoding p.A377T, p.Y401N) led to reduced binding to corepressors. We also observed a large expansion of megakaryocyte colony-forming units derived from variant carriers and reduced proplatelet formation with abnormal cytoskeletal organization. The defect in proplatelet formation was also observed in control CD34+ cell-derived megakaryocytes transduced with lentiviral particles encoding mutant ETV6. Reduced expression levels of key regulators of the actin cytoskeleton CDC42 and RHOA were measured. Moreover, changes in the actin structures are typically accompanied by a rounder platelet shape with a highly heterogeneous size, decreased platelet arachidonic response, and spreading and retarded clot retraction in ETV6 deficient platelets. Elevated numbers of circulating CD34+ cells were found in p.P214L and p.Y401N carriers, and two patients from different families suffered from refractory anemia with excess blasts, while one patient from a third family was successfully treated for acute myeloid leukemia. Overall, our study provides novel insights into the role of ETV6 as a driver of cytoskeletal regulatory gene expression during platelet production, and the impact of variants resulting in platelets with altered size, shape and function and potentially also in changes in circulating progenitor levels.

BACKGROUND:Thrombin activatable fibrinolysis inhibitor (TAFI), encoded by the Carboxypeptidase B2 gene (CPB2), is an inhibitor of fibrinolysis and plays a role in the pathogenesis of venous thrombosis. Experimental findings support a functional role of genetic variants in CPB2, while epidemiological studies have been unable to confirm associations with risk of venous thrombosis. Sex-specific effects could underlie the observed inconsistent associations between CPB2 genetic variants and venous thrombosis. METHODS:A comprehensive literature search was conducted for associations between Ala147Thr and Thr325Ile variants with venous thrombosis. Authors were contacted to provide sex-specific genotype counts from their studies. Combined and sex-specific random effects meta-analyses were used to estimate a pooled effect estimate for primary and secondary genetic models. RESULTS:A total of 17 studies met the inclusion criteria. A sex-specific meta-analysis applying a dominant model supported a protective effect of Ala147Thr on venous thrombosis in females (OR = 0.81, 95%CI: 0.68,0.97; p = 0.018), but not in males (OR = 1.06, 95%CI:0.96-1.16; p = 0.263). The Thr325Ile did not show a sex-specific effect but showed variation in allele frequencies by geographic region. A subgroup analysis of studies in European countries showed decreased risk, with a recessive model (OR = 0.83, 95%CI:0.71-0.97, p = 0.021) for venous thrombosis. CONCLUSIONS:A comprehensive literature review, including unpublished data, provided greater statistical power for the analyses and decreased the likelihood of publication bias influencing the results. Sex-specific analyses explained apparent discrepancies across genetic studies of Ala147Thr and venous thrombosis. While, careful selection of genetic models based on population genetics, evolutionary and biological knowledge can increase power by decreasing the need to adjust for testing multiple models.

BACKGROUND:DNA methylation is affected by the activities of the key enzymes and intermediate metabolites of the one-carbon pathway, one of which involves homocysteine. We investigated the effect of the well-known genetic variant associated with mildly elevated homocysteine: MTHFR 677C>T independently and in combination with other homocysteine-associated variants, on genome-wide leukocyte DNA-methylation. METHODS:Methylation levels were assessed using Illumina 450k arrays on 9,894 individuals of European ancestry from 12 cohort studies. Linear-mixed-models were used to study the association of additive MTHFR 677C>T and genetic-risk score (GRS) based on 18 homocysteine-associated SNPs, with genome-wide methylation. RESULTS:Meta-analysis revealed that the MTHFR 677C>T variant was associated with 35 CpG sites in cis, and the GRS showed association with 113 CpG sites near the homocysteine-associated variants. Genome-wide analysis revealed that the MTHFR 677C>T variant was associated with 1 trans-CpG (nearest gene ZNF184), while the GRS model showed association with 5 significant trans-CpGs annotated to nearest genes PTF1A, MRPL55, CTDSP2, CRYM and FKBP5. CONCLUSIONS:Our results do not show widespread changes in DNA-methylation across the genome, and therefore do not support the hypothesis that mildly elevated homocysteine is associated with widespread methylation changes in leukocytes.

Technical variation plays an important role in microarray-based gene expression studies, and batch effects explain a large proportion of this noise. It is therefore mandatory to eliminate technical variation while maintaining biological variability. Several strategies have been proposed for the removal of batch effects, although they have not been evaluated in large-scale longitudinal gene expression data. In this study, we aimed at identifying a suitable method for batch effect removal in a large study of microarray-based longitudinal gene expression. Monocytic gene expression was measured in 1092 participants of the Gutenberg Health Study at baseline and 5-year follow up. Replicates of selected samples were measured at both time points to identify technical variability. Deming regression, Passing-Bablok regression, linear mixed models, non-linear models as well as ReplicateRUV and ComBat were applied to eliminate batch effects between replicates. In a second step, quantile normalization prior to batch effect correction was performed for each method. Technical variation between batches was evaluated by principal component analysis. Associations between body mass index and transcriptomes were calculated before and after batch removal. Results from association analyses were compared to evaluate maintenance of biological variability. Quantile normalization, separately performed in each batch, combined with ComBat successfully reduced batch effects and maintained biological variability. ReplicateRUV performed perfectly in the replicate data subset of the study, but failed when applied to all samples. All other methods did not substantially reduce batch effects in the replicate data subset. Quantile normalization plus ComBat appears to be a valuable approach for batch correction in longitudinal gene expression data.

Plasma fibrinogen is an acute phase protein playing an important role in the blood coagulation cascade having strong associations with smoking, alcohol consumption and body mass index (BMI). Genome-wide association studies (GWAS) have identified a variety of gene regions associated with elevated plasma fibrinogen concentrations. However, little is yet known about how associations between environmental factors and fibrinogen might be modified by genetic variation. Therefore, we conducted large-scale meta-analyses of genome-wide interaction studies to identify possible interactions of genetic variants and smoking status, alcohol consumption or BMI on fibrinogen concentration. The present study included 80,607 subjects of European ancestry from 22 studies. Genome-wide interaction analyses were performed separately in each study for about 2.6 million single nucleotide polymorphisms (SNPs) across the 22 autosomal chromosomes. For each SNP and risk factor, we performed a linear regression under an additive genetic model including an interaction term between SNP and risk factor. Interaction estimates were meta-analysed using a fixed-effects model. No genome-wide significant interaction with smoking status, alcohol consumption or BMI was observed in the meta-analyses. The most suggestive interaction was found for smoking and rs10519203, located in the LOC123688 region on chromosome 15, with a p value of 6.2 × 10(-8). This large genome-wide interaction study including 80,607 participants found no strong evidence of interaction between genetic variants and smoking status, alcohol consumption or BMI on fibrinogen concentrations. Further studies are needed to yield deeper insight in the interplay between environmental factors and gene variants on the regulation of fibrinogen concentrations.

In order to investigate whether DNA methylation marks could contribute to the incomplete penetrance of the FV Leiden mutation, a major genetic risk factor for venous thrombosis (VT), we measured genome-wide DNA methylation levels in peripheral blood samples of 98 VT patients carrying the mutation and 251 VT patients without the mutation using the dedicated Illumina HumanMethylation450 array. The genome-wide analysis of 388,120 CpG probes identified three sites mapping to the SLC19A2 locus whose DNA methylation levels differed significantly (p0.05). In conclusion, our work clearly illustrates some promises and pitfalls of DNA methylation investigations on peripheral blood DNA in large epidemiological cohorts. DNA methylation levels at SLC19A2 are influenced by SNPs in LD with FV Leiden, but these DNA methylation marks do not explain the incomplete penetrance of the FV Leiden mutation.

In order to assess whether gene expression variability could be influenced by several SNPs acting in cis, either through additive or more complex haplotype effects, a systematic genome-wide search for cis haplotype expression quantitative trait loci (eQTL) was conducted in a sample of 758 individuals, part of the Cardiogenics Transcriptomic Study, for which genome-wide monocyte expression and GWAS data were available. 19,805 RNA probes were assessed for cis haplotypic regulation through investigation of ~2,1 × 10(9) haplotypic combinations. 2,650 probes demonstrated haplotypic p-values >10(4)-fold smaller than the best single SNP p-value. Replication of significant haplotype effects were tested for 412 probes for which SNPs (or proxies) that defined the detected haplotypes were available in the Gutenberg Health Study composed of 1,374 individuals. At the Bonferroni correction level of 1.2 × 10(-4) (~0.05/412), 193 haplotypic signals replicated. 1000 G imputation was then conducted, and 105 haplotypic signals still remained more informative than imputed SNPs. In-depth analysis of these 105 cis eQTL revealed that at 76 loci genetic associations were compatible with additive effects of several SNPs, while for the 29 remaining regions data could be compatible with a more complex haplotypic pattern. As 24 of the 105 cis eQTL have previously been reported to be disease-associated loci, this work highlights the need for conducting haplotype-based and 1000 G imputed cis eQTL analysis before commencing functional studies at disease-associated loci.

Smoking is a risk factor for atherosclerosis with reported widespread effects on gene expression in circulating blood cells. We hypothesized that a molecular signature mediating the relation between smoking and atherosclerosis may be found in the transcriptome of circulating monocytes. Genome-wide expression profiles and counts of atherosclerotic plaques in carotid arteries were collected in 248 smokers and 688 non-smokers from the general population. Patterns of co-expressed genes were identified by Independent Component Analysis (ICA) and network structure of the pattern-specific gene modules was inferred by the PC-algorithm. A likelihood-based causality test was implemented to select patterns that fit models containing a path "smoking→gene expression→plaques". Robustness of the causal inference was assessed by bootstrapping. At a FDR ≤0.10, 3,368 genes were associated to smoking or plaques, of which 93% were associated to smoking only. SASH1 showed the strongest association to smoking and PPARG the strongest association to plaques. Twenty-nine gene patterns were identified by ICA. Modules containing SASH1 and PPARG did not show evidence for the "smoking→gene expression→plaques" causality model. Conversely, three modules had good support for causal effects and exhibited a network topology consistent with gene expression mediating the relation between smoking and plaques. The network with the strongest support for causal effects was connected to plaques through SLC39A8, a gene with known association to HDL-cholesterol and cellular uptake of cadmium from tobacco, while smoking was directly connected to GAS6, a gene reported to have anti-inflammatory effects in atherosclerosis and to be up-regulated in the placenta of women smoking during pregnancy. Our analysis of the transcriptome of monocytes recovered genes relevant for association to smoking and atherosclerosis, and connected genes that before, were only studied in separate contexts. Inspection of correlation structure revealed candidates that would be missed by expression-phenotype association analysis alone.

BackgroundMore accurate coronary heart disease (CHD) prediction, specifically in middle-aged men, is needed to reduce the burden of disease more effectively. We hypothesised that a multilocus genetic risk score could refine CHD prediction beyond classic risk scores and obtain more precise risk estimates using a prospective cohort design.MethodsUsing data from nine prospective European cohorts, including 26,221 men, we selected in a case-cohort setting 4,818 healthy men at baseline, and used Cox proportional hazards models to examine associations between CHD and risk scores based on genetic variants representing 13 genomic regions. Over follow-up (range: 5-18 years), 1,736 incident CHD events occurred. Genetic risk scores were validated in men with at least 10 years of follow-up (632 cases, 1361 non-cases). Genetic risk score 1 (GRS1) combined 11 SNPs and two haplotypes, with effect estimates from previous genome-wide association studies. GRS2 combined 11 SNPs plus 4 SNPs from the haplotypes with coefficients estimated from these prospective cohorts using 10-fold cross-validation. Scores were added to a model adjusted for classic risk factors comprising the Framingham risk score and 10-year risks were derived.ResultsBoth scores improved net reclassification (NRI) over the Framingham score (7.5%, p = 0.017 for GRS1, 6.5%, p = 0.044 for GRS2) but GRS2 also improved discrimination (c-index improvement 1.11%, p = 0.048). Subgroup analysis on men aged 50-59 (436 cases, 603 non-cases) improved net reclassification for GRS1 (13.8%) and GRS2 (12.5%). Net reclassification improvement remained significant for both scores when family history of CHD was added to the baseline model for this male subgroup improving prediction of early onset CHD events.ConclusionsGenetic risk scores add precision to risk estimates for CHD and improve prediction beyond classic risk factors, particularly for middle aged men.

By applying an imputation strategy based on the 1000 Genomes project to two genome-wide association studies (GWAS), we detected a susceptibility locus for venous thrombosis on chromosome 11p11.2 that was missed by previous GWAS analyses that had been conducted on the same datasets. A comprehensive linkage disequilibrium and haplotype analysis of the whole locus where twelve SNPs exhibited association p-values lower than 2.23 10(-11) and the use of independent case-control samples demonstrated that the culprit variant was a rare variant located ~1 Mb away from the original hits, not tagged by current genome-wide genotyping arrays and even not well imputed in the original GWAS samples. This variant was in fact the rs1799963, also known as the FII G20210A prothrombin mutation. This work may be of major interest not only for its scientific impact but also for its methodological findings.

In this work, we assessed whether SERPINE1 expression could be under the influence of microRNAs (miRNAs) predicted to bind the SERPINE1 3'UTR region. We specifically focused on the 3'UTR region harboring a common polymorphism, rs1050955, that have been found associated to SERPINE1 monocyte expression, and investigated whether the presence of different alleles at rs1050955 could modify the miRNAs binding efficiency and affect PAI-1 protein levels. We demonstrated that, in human umbilical vein endothelial cells, both miR-421 and miR-30c directly interacted with PAI-1 mRNA to inhibit the expression of the associated protein. However, these inhibitory mechanisms were independent on the allele present at the rs1050955 locus. We further showed that miR-421 levels correlated with PAI-1 activity in the plasma sample of 40 patients with venous thrombosis. Our results strongly suggest that the regulation of PAI-1 molecule could be under the influence of several miRNAs whose measurement in the plasma of patients could be envisaged as a biomarker for inflammatory and thrombotic disorders.

We aimed to assess whether pri-miRNA SNPs (miSNPs) could influence monocyte gene expression, either through marginal association or by interacting with polymorphisms located in 3'UTR regions (3utrSNPs). We then conducted a genome-wide search for marginal miSNPs effects and pairwise miSNPs × 3utrSNPs interactions in a sample of 1,467 individuals for which genome-wide monocyte expression and genotype data were available. Statistical associations that survived multiple testing correction were tested for replication in an independent sample of 758 individuals with both monocyte gene expression and genotype data. In both studies, the hsa-mir-1279 rs1463335 was found to modulate in cis the expression of LYZ and in trans the expression of CNTN6, CTRC, COPZ2, KRT9, LRRFIP1, NOD1, PCDHA6, ST5 and TRAF3IP2 genes, supporting the role of hsa-mir-1279 as a regulator of several genes in monocytes. In addition, we identified two robust miSNPs × 3utrSNPs interactions, one involving HLA-DPB1 rs1042448 and hsa-mir-219-1 rs107822, the second the H1F0 rs1894644 and hsa-mir-659 rs5750504, modulating the expression of the associated genes.As some of the aforementioned genes have previously been reported to reside at disease-associated loci, our findings provide novel arguments supporting the hypothesis that the genetic variability of miRNAs could also contribute to the susceptibility to human diseases.

BackgroundThe hypothesis of dosage compensation of genes of the X chromosome, supported by previous microarray studies, was recently challenged by RNA-sequencing data. It was suggested that microarray studies were biased toward an over-estimation of X-linked expression levels as a consequence of the filtering of genes below the detection threshold of microarrays.Methodology/principal findingsTo investigate this hypothesis, we used microarray expression data from circulating monocytes in 1,467 individuals. In total, 25,349 and 1,156 probes were unambiguously assigned to autosomes and the X chromosome, respectively. Globally, there was a clear shift of X-linked expressions toward lower levels than autosomes. We compared the ratio of expression levels of X-linked to autosomal transcripts (X∶AA) using two different filtering methods: 1. gene expressions were filtered out using a detection threshold irrespective of gene chromosomal location (the standard method in microarrays); 2. equal proportions of genes were filtered out separately on the X and on autosomes. For a wide range of filtering proportions, the X∶AA ratio estimated with the first method was not significantly different from 1, the value expected if dosage compensation was achieved, whereas it was significantly lower than 1 with the second method, leading to the rejection of the hypothesis of dosage compensation. We further showed in simulated data that the choice of the most appropriate method was dependent on biological assumptions regarding the proportion of actively expressed genes on the X chromosome comparative to the autosomes and the extent of dosage compensation.Conclusion/significanceThis study shows that the method used for filtering out lowly expressed genes in microarrays may have a major impact according to the hypothesis investigated. The hypothesis of dosage compensation of X-linked genes cannot be firmly accepted or rejected using microarray-based data.

BACKGROUND: Venous Thrombosis (VT) is a common multifactorial disease associated with a major public health burden. Genetics factors are known to contribute to the susceptibility of the disease but how many genes are involved and their contribution to VT risk still remain obscure. We aimed to identify genetic variants associated with VT risk. METHODOLOGY/PRINCIPAL FINDINGS: We conducted a genome-wide association study (GWAS) based on 551,141 SNPs genotyped in 1,542 cases and 1,110 controls. Twelve SNPs reached the genome-wide significance level of 2.0×10(-8) and encompassed four known VT-associated loci, ABO, F5, F11 and FGG. By means of haplotype analyses, we also provided novel arguments in favor of a role of HIVEP1, PROCR and STAB2, three loci recently hypothesized to participate in the susceptibility to VT. However, no novel VT-associated loci came out of our GWAS. Using a recently proposed statistical methodology, we also showed that common variants could explain about 35% of the genetic variance underlying VT susceptibility among which 3% could be attributable to the main identified VT loci. This analysis additionally suggested that the common variants left to be identified are not uniformly distributed across the genome and that chromosome 20, itself, could contribute to ∼7% of the total genetic variance. CONCLUSIONS/SIGNIFICANCE: This study might also provide a valuable source of information to expand our understanding of biological mechanisms regulating quantitative biomarkers for VT.