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Ricardo A Verdugo,
Tanja Zeller, Maxime Rotival,
Philipp S Wild,
Thomas Münzel,
Karl J Lackner,
Henri Weidmann,
Ewa Ninio,
David-Alexandre Trégouët,
François Cambien,
Stefan Blankenberg,
Laurence Tiret
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ABSTRACT: 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.
PLoS ONE 01/2013; 8(1):e50888. · 4.09 Impact Factor
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Chris Wallace, Maxime Rotival,
Jason D Cooper,
Catherine M Rice,
Jennie H M Yang,
Mhairi McNeill,
Deborah J Smyth,
David Niblett,
François Cambien,
Laurence Tiret,
John A Todd,
David G Clayton,
Stefan Blankenberg
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ABSTRACT: One mechanism by which disease-associated DNA variation can alter disease risk is altering gene expression. However, linkage disequilibrium (LD) between variants, mostly single-nucleotide polymorphisms (SNPs), means it is not sufficient to show that a particular variant associates with both disease and expression, as there could be two distinct causal variants in LD. Here, we describe a formal statistical test of colocalization and apply it to type 1 diabetes (T1D)-associated regions identified mostly through genome-wide association studies and expression quantitative trait loci (eQTLs) discovered in a recently determined large monocyte expression data set from the Gutenberg Health Study (1370 individuals), with confirmation sought in an additional data set from the Cardiogenics Transcriptome Study (558 individuals). We excluded 39 out of 60 overlapping eQTLs in 49 T1D regions from possible colocalization and identified 21 coincident eQTLs, representing 21 genes in 14 distinct T1D regions. Our results reflect the importance of monocyte (and their derivatives, macrophage and dendritic cell) gene expression in human T1D and support the candidacy of several genes as causal factors in autoimmune pancreatic beta-cell destruction, including AFF3, CD226, CLECL1, DEXI, FKRP, PRKD2, RNLS, SMARCE1 and SUOX, in addition to the recently described GPR183 (EBI2) gene.
Human Molecular Genetics 03/2012; 21(12):2815-24. · 7.64 Impact Factor
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Nicolas Greliche,
Tanja Zeller,
Philipp S Wild, Maxime Rotival,
Arne Schillert,
Andreas Ziegler,
Panos Deloukas,
Jeanette Erdmann,
Christian Hengstenberg,
Willem H Ouwehand,
Nilesh J Samani,
Heribert Schunkert,
Thomas Munzel,
Karl J Lackner,
François Cambien,
Alison H Goodall,
Laurence Tiret,
Stefan Blankenberg,
David-Alexandre Trégouët
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ABSTRACT: 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.
PLoS ONE 01/2012; 7(9):e45863. · 4.09 Impact Factor
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Maxime Rotival,
Tanja Zeller,
Philipp S Wild,
Seraya Maouche,
Silke Szymczak,
Arne Schillert,
Raphaele Castagné,
Arne Deiseroth,
Carole Proust,
Jessy Brocheton, [......],
Gilles Montalescot,
Willem H Ouwehand,
Nilesh J Samani,
Heribert Schunkert,
David-Alexandre Tregouet,
Andreas Ziegler,
Alison H Goodall,
François Cambien,
Laurence Tiret,
Stefan Blankenberg
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ABSTRACT: One major expectation from the transcriptome in humans is to characterize the biological basis of associations identified by genome-wide association studies. So far, few cis expression quantitative trait loci (eQTLs) have been reliably related to disease susceptibility. Trans-regulating mechanisms may play a more prominent role in disease susceptibility. We analyzed 12,808 genes detected in at least 5% of circulating monocyte samples from a population-based sample of 1,490 European unrelated subjects. We applied a method of extraction of expression patterns-independent component analysis-to identify sets of co-regulated genes. These patterns were then related to 675,350 SNPs to identify major trans-acting regulators. We detected three genomic regions significantly associated with co-regulated gene modules. Association of these loci with multiple expression traits was replicated in Cardiogenics, an independent study in which expression profiles of monocytes were available in 758 subjects. The locus 12q13 (lead SNP rs11171739), previously identified as a type 1 diabetes locus, was associated with a pattern including two cis eQTLs, RPS26 and SUOX, and 5 trans eQTLs, one of which (MADCAM1) is a potential candidate for mediating T1D susceptibility. The locus 12q24 (lead SNP rs653178), which has demonstrated extensive disease pleiotropy, including type 1 diabetes, hypertension, and celiac disease, was associated to a pattern strongly correlating to blood pressure level. The strongest trans eQTL in this pattern was CRIP1, a known marker of cellular proliferation in cancer. The locus 12q15 (lead SNP rs11177644) was associated with a pattern driven by two cis eQTLs, LYZ and YEATS4, and including 34 trans eQTLs, several of them tumor-related genes. This study shows that a method exploiting the structure of co-expressions among genes can help identify genomic regions involved in trans regulation of sets of genes and can provide clues for understanding the mechanisms linking genome-wide association loci to disease.
PLoS Genetics 12/2011; 7(12):e1002367. · 8.69 Impact Factor
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Raphaële Castagné,
Tanja Zeller, Maxime Rotival,
Silke Szymczak,
Vinh Truong,
Arne Schillert,
David-Alexandre Trégouët,
Thomas Münzel,
Andreas Ziegler,
François Cambien,
Stefan Blankenberg,
Laurence Tiret
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ABSTRACT: In humans, the fraction of X-linked genes with higher expression in females has been estimated to be 5% from microarray studies, a proportion lower than the 25% of genes thought to escape X inactivation. We analyzed 715 X-linked transcripts in circulating monocytes from 1,467 subjects and found an excess of female-biased transcripts on the X compared to autosomes (9.4% vs 5.5%, p<2×10(-5)). Among the genes not previously known to escape inactivation, the most significant one was EFHC2 whose 20% of variability was explained by sex. We also investigated cis expression quantitative trait loci (eQTLs) by analyzing 15,703 X-linked SNPs. The frequency and magnitude of X-linked cis eQTLs were quite similar in males and females. Few genes exhibited a stronger genetic effect in females than in males (ARSD, DCX, POLA1 and ITM2A). These genes would deserve further investigation since they may contribute to sex pathophysiological differences.
Genomics 07/2011; 98(5):320-6. · 3.02 Impact Factor
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Raphaële Castagné, Maxime Rotival,
Tanja Zeller,
Philipp S Wild,
Vinh Truong,
David-Alexandre Trégouët,
Thomas Munzel,
Andreas Ziegler,
François Cambien,
Stefan Blankenberg,
Laurence Tiret
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ABSTRACT: The 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.
To 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.
This 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.
PLoS ONE 01/2011; 6(9):e23956. · 4.09 Impact Factor
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Matthias Heinig,
Enrico Petretto,
Chris Wallace,
Leonardo Bottolo, Maxime Rotival,
Han Lu,
Yoyo Li,
Rizwan Sarwar,
Sarah R Langley,
Anja Bauerfeind, [......],
Andreas Ziegler,
Laurence Tiret,
Deborah J Smyth,
Michal Pravenec,
Timothy J Aitman,
Francois Cambien,
David Clayton,
John A Todd,
Norbert Hubner,
Stuart A Cook
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ABSTRACT: Combined analyses of gene networks and DNA sequence variation can provide new insights into the aetiology of common diseases that may not be apparent from genome-wide association studies alone. Recent advances in rat genomics are facilitating systems-genetics approaches. Here we report the use of integrated genome-wide approaches across seven rat tissues to identify gene networks and the loci underlying their regulation. We defined an interferon regulatory factor 7 (IRF7)-driven inflammatory network (IDIN) enriched for viral response genes, which represents a molecular biomarker for macrophages and which was regulated in multiple tissues by a locus on rat chromosome 15q25. We show that Epstein-Barr virus induced gene 2 (Ebi2, also known as Gpr183), which lies at this locus and controls B lymphocyte migration, is expressed in macrophages and regulates the IDIN. The human orthologous locus on chromosome 13q32 controlled the human equivalent of the IDIN, which was conserved in monocytes. IDIN genes were more likely to associate with susceptibility to type 1 diabetes (T1D)-a macrophage-associated autoimmune disease-than randomly selected immune response genes (P = 8.85 × 10(-6)). The human locus controlling the IDIN was associated with the risk of T1D at single nucleotide polymorphism rs9585056 (P = 7.0 × 10(-10); odds ratio, 1.15), which was one of five single nucleotide polymorphisms in this region associated with EBI2 (GPR183) expression. These data implicate IRF7 network genes and their regulatory locus in the pathogenesis of T1D.
Nature 09/2010; 467(7314):460-4. · 36.28 Impact Factor
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Alfonso Buil,
David-Alexandre Trégouët,
Juan Carlos Souto,
Noémie Saut,
Marine Germain, Maxime Rotival,
Laurence Tiret,
Françcois Cambien,
Mark Lathrop,
Tanja Zeller, [......],
Santiago Rodriguez de Cordoba,
Thomas Münzel,
Philipp Wild,
Jordi Fontcuberta,
France Gagnon,
Joseph Emmerich,
Laura Almasy,
Stefan Blankenberg,
José-Manuel Soria,
Pierre-Emmanuel Morange
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ABSTRACT: Through its binding with protein S (PS), a key element of the coagulation/fibrinolysis cascade, the C4b-binding protein (C4BP) has been hypothesized to be involved in the susceptibility to venous thrombosis (VT). To identify genetic factors that may influence the plasma levels of the 3 C4BP existing isoforms, alpha(7)beta(1), alpha(6)beta(1), and alpha(7)beta(0), we conducted a genome-wide association study by analyzing 283 437 single nucleotide polymorphisms (SNPs) in the Genetic Analysis of Idiopathic Thrombophilia (GAIT) study composed of 352 persons. Three SNPs at the C4BPB/C4BPA locus were found genome-wide significantly associated with alpha(7)beta(0) levels. One of these SNPs was further found to explain approximately 11% of the variability of mRNA C4BPA expression in the Gutenberg Heart Study composed of 1490 persons, with no effect on C4BPB mRNA expression. The allele associated with increased alpha(7)beta(0) plasma levels and increased C4BPA expression was further found associated with increased risk of VT (odds ratio [OR] = 1.24 [1.03-1.53]) in 2 independent case-control studies (MARseille THrombosis Association study [MARTHA] and FActeurs de RIsque et de récidives de la maladie thromboembolique VEineuse [FARIVE]) gathering 1706 cases and 1379 controls. This SNP was not associated with free PS or total PS. In conclusion, we observed strong evidence that the C4BPB/C4BPA locus is a new susceptibility locus for VT through a PS-independent mechanism that remains to be elucidated.
Blood 03/2010; 115(23):4644-50. · 9.90 Impact Factor
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Tanja Zeller,
Philipp Wild,
Silke Szymczak, Maxime Rotival,
Arne Schillert,
Raphaele Castagne,
Seraya Maouche,
Marine Germain,
Karl Lackner,
Heidi Rossmann, [......],
Carole Proust,
Viviane Nicaud,
Joseph Loscalzo,
Norbert Hübner,
David Tregouet,
Thomas Münzel,
Andreas Ziegler,
Laurence Tiret,
Stefan Blankenberg,
François Cambien
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ABSTRACT: Variability of gene expression in human may link gene sequence variability and phenotypes; however, non-genetic variations, alone or in combination with genetics, may also influence expression traits and have a critical role in physiological and disease processes.
To get better insight into the overall variability of gene expression, we assessed the transcriptome of circulating monocytes, a key cell involved in immunity-related diseases and atherosclerosis, in 1,490 unrelated individuals and investigated its association with >675,000 SNPs and 10 common cardiovascular risk factors. Out of 12,808 expressed genes, 2,745 expression quantitative trait loci were detected (P<5.78x10(-12)), most of them (90%) being cis-modulated. Extensive analyses showed that associations identified by genome-wide association studies of lipids, body mass index or blood pressure were rarely compatible with a mediation by monocyte expression level at the locus. At a study-wide level (P<3.9x10(-7)), 1,662 expression traits (13.0%) were significantly associated with at least one risk factor. Genome-wide interaction analyses suggested that genetic variability and risk factors mostly acted additively on gene expression. Because of the structure of correlation among expression traits, the variability of risk factors could be characterized by a limited set of independent gene expressions which may have biological and clinical relevance. For example expression traits associated with cigarette smoking were more strongly associated with carotid atherosclerosis than smoking itself.
This study demonstrates that the monocyte transcriptome is a potent integrator of genetic and non-genetic influences of relevance for disease pathophysiology and risk assessment.
PLoS ONE 01/2010; 5(5):e10693. · 4.09 Impact Factor
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[show abstract]
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ABSTRACT: En génétique, l'utilisation de données haut débit (mesure simultanée de l'expression de dizaines de milliers de gènes, et de plusieurs centaines de milliers de polymorphismes) pour tester les liens entre patrimoine génétique et les différences phénotypiques à l'échelle cellulaire, conduit à une augmentation drastique du nombre de tests statistiques effectués. Dès lors, le contrôle de l'erreur de type I impose des seuils de significativité extrêmement faibles, se traduisant par une importante perte de puissance. Nous proposons une méthode visant à utiliser les phénomènes de co-régulation de l'expression des gènes pour faciliter la recherche d'effets génotypiques à grande échelle. La méthode décrite ici repose sur l'extraction non supervisée de motifs pertinents par l'analyse en composantes indépendantes et la recherche de motifs d'expression affectés par le génotype. La connaissance des polymorphismes ayant des effets à grande échelle, permet dans un deuxième temps d'affiner la recherche afin d'identifier avec précision les gènes impliqués dans les processus biologiques affectés par le polymorphisme. Une étude par simulations montre que cette approche permet d'augmenter considérablement la puissance des études d'association pour la recherche de polymorphismes affectant 'expression d'un grand nombre de gènes co-régulés. Une application à des données de la Gutenberg Heart Study est proposée.
