12 research outputs found

    Detection of regulator genes and eQTLs in gene networks

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    Genetic differences between individuals associated to quantitative phenotypic traits, including disease states, are usually found in non-coding genomic regions. These genetic variants are often also associated to differences in expression levels of nearby genes (they are "expression quantitative trait loci" or eQTLs for short) and presumably play a gene regulatory role, affecting the status of molecular networks of interacting genes, proteins and metabolites. Computational systems biology approaches to reconstruct causal gene networks from large-scale omics data have therefore become essential to understand the structure of networks controlled by eQTLs together with other regulatory genes, and to generate detailed hypotheses about the molecular mechanisms that lead from genotype to phenotype. Here we review the main analytical methods and softwares to identify eQTLs and their associated genes, to reconstruct co-expression networks and modules, to reconstruct causal Bayesian gene and module networks, and to validate predicted networks in silico.Comment: minor revision with typos corrected; review article; 24 pages, 2 figure

    Different prognostic impact of recurrent gene mutations in chronic lymphocytic leukemia depending on IGHV gene somatic hypermutation status: a study by ERIC in HARMONY

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    Recent evidence suggests that the prognostic impact of gene mutations in patients with chronic lymphocytic leukemia (CLL) may differ depending on the immunoglobulin heavy variable (IGHV) gene somatic hypermutation (SHM) status. In this study, we assessed the impact of nine recurrently mutated genes (BIRC3, EGR2, MYD88, NFKBIE, NOTCH1, POT1, SF3B1, TP53, and XPO1) in pre-treatment samples from 4580 patients with CLL, using time-to-first-treatment (TTFT) as the primary end-point in relation to IGHV gene SHM status. Mutations were detected in 1588 (34.7%) patients at frequencies ranging from 2.3-9.8% with mutations in NOTCH1 being the most frequent. In both univariate and multivariate analyses, mutations in all genes except MYD88 were associated with a significantly shorter TTFT. In multivariate analysis of Binet stage A patients, performed separately for IGHV-mutated (M-CLL) and unmutated CLL (U-CLL), a different spectrum of gene alterations independently predicted short TTFT within the two subgroups. While SF3B1 and XPO1 mutations were independent prognostic variables in both U-CLL and M-CLL, TP53, BIRC3 and EGR2 aberrations were significant predictors only in U-CLL, and NOTCH1 and NFKBIE only in M-CLL. Our findings underscore the need for a compartmentalized approach to identify high-risk patients, particularly among M-CLL patients, with potential implications for stratified management

    Network analysis of coronary artery disease risk genes elucidates disease mechanisms and druggable targets

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    Genome-wide association studies (GWAS) have identified over two hundred chromosomal loci that modulate risk of coronary artery disease (CAD). The genes affected by variants at these loci are largely unknown and an untapped resource to improve our understanding of CAD pathophysiology and identify potential therapeutic targets. Here, we prioritized 68 genes as the most likely causal genes at genome-wide significant loci identified by GWAS of CAD and examined their regulatory roles in 286 metabolic and vascular tissue gene-protein sub-networks ("modules"). The modules and genes within were scored for CAD druggability potential. The scoring enriched for targets of cardiometabolic drugs currently in clinical use and in-depth analysis of the top-scoring modules validated established and revealed novel target tissues, biological processes, and druggable targets. This study provides an unprecedented resource of tissue-defined gene-protein interactions directly affected by genetic variance in CAD risk loci

    Expression Quantitative Trait Loci Acting Across Multiple Tissues Are Enriched in Inherited Risk for Coronary Artery Disease.

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    -Despite recent discoveries of new genetic risk factors, the majority of risk for coronary artery disease (CAD) remains elusive. As the most proximal sensor of DNA variation, RNA abundance can help identify subpopulations of genetic variants active in and across tissues mediating CAD risk through gene expression

    Variants in ALOX5, ALOX5AP and LTA4H are not associated with atherosclerotic plaque phenotypes : The Athero-Express Genomics Study

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    Background: The eicosanoid genes ALOX5, ALOX5AP and LTA4H have been implicated in atherosclerosis. We assessed the impact of common variants in these genes on gene expression, circulating protein levels, and atherosclerotic plaque phenotypes. Methods: We included patients from the Stockholm Atherosclerosis Gene Expression study (STAGE, N=109), and the Athero-Express Biobank Study (AE, N=1443). We tested 1453 single-nucleotide variants (SNVs) in ALOX5, ALOX5AP and LTA4H for association with gene expression in STAGE. We also tested these SNVs for association with seven histologically defined plaque phenotypes in the AE (which included calcification, collagen, cellular content, atheroma size, and intraplaque vessel density and hemorrhage). Results: We replicate a known cis-eQTL (rs6538697, p=1.96×10-6) for LTA4H expression in whole blood of patients from STAGE. We found no significant association for any of the SNVs tested with serum levels of ALOX5 or ALOX5AP (p>5.79×10-4). For atherosclerotic plaque phenotypes the strongest associations were found for intraplaque vessel density and smooth muscle cells in the ALOX5AP locus (p>1.67×10-4). Conclusions: We replicate a known eQTL for LTA4H expression in whole blood using STAGE data. We found no associations of variants in and around ALOX5, ALOX5AP and LTA4H with serum ALOX5 or ALOX5AP levels, or plaque phenotypes. On the supposition that these genes play a causal role in atherosclerosis, these results suggest that common variants in these loci play a limited role (if any) in influencing advanced atherosclerotic plaque morphology to the extent that it impacts atherosclerotic disease

    Smoking is Associated to DNA Methylation in Atherosclerotic Carotid Lesions

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    Background: Tobacco smoking is a major risk factor for atherosclerotic disease and has been associated with DNA methylation (DNAm) changes in blood cells. However, whether smoking influences DNAm in the diseased vascular wall is unknown but may prove crucial in understanding the pathophysiology of atherosclerosis. In this study, we associated current tobacco smoking to epigenome-wide DNAm in atherosclerotic plaques from patients undergoing carotid endarterectomy. Methods: DNAm at commonly methylated sites (cytosine-guanine nucleotide pairs separated by a phospho-group [CpGs]) was assessed in atherosclerotic plaque samples and peripheral blood samples from 485 carotid endarterectomy patients. We tested the association of current tobacco smoking with DNAm corrected for age and sex. To control for bias and inflation because of cellular heterogeneity, we applied a Bayesian method to estimate an empirical null distribution as implemented by the R package bacon. Replication of the smoking-associated methylated CpGs in atherosclerotic plaques was executed in the second sample of 190 carotid endarterectomy patients, and results were meta-analyzed using a fixed-effects model. Results: Tobacco smoking was significantly associated to differential DNAm in atherosclerotic lesions of 4 CpGs (false discovery rate <0.05) mapped to 2 different genes (AHRR, ITPK1) and 17 CpGs mapped to 8 genes and RNAs in blood. The strongest associations were found for CpGs mapped to the gene AHRR, a repressor of the aryl hydrocarbon receptor transcription factor involved in xenobiotic detoxification. One of these methylated CpGs were found to be regulated by local genetic variation. Conclusions: The risk factor tobacco smoking associates with DNAm at multiple loci in carotid atherosclerotic lesions. These observations support further investigation of the relationship between risk factors and epigenetic regulation in atherosclerotic disease

    Genetic Susceptibility Loci for Cardiovascular Disease and Their Impact on Atherosclerotic Plaques.

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    BACKGROUND: Atherosclerosis is a chronic inflammatory disease in part caused by lipid uptake in the vascular wall, but the exact underlying mechanisms leading to acute myocardial infarction and stroke remain poorly understood. Large consortia identified genetic susceptibility loci that associate with large artery ischemic stroke and coronary artery disease. However, deciphering their underlying mechanisms are challenging. Histological studies identified destabilizing characteristics in human atherosclerotic plaques that associate with clinical outcome. To what extent established susceptibility loci for large artery ischemic stroke and coronary artery disease relate to plaque characteristics is thus far unknown but may point to novel mechanisms. METHODS: We studied the associations of 61 established cardiovascular risk loci with 7 histological plaque characteristics assessed in 1443 carotid plaque specimens from the Athero-Express Biobank Study. We also assessed if the genotyped cardiovascular risk loci impact the tissue-specific gene expression in 2 independent biobanks, Biobank of Karolinska Endarterectomy and Stockholm Atherosclerosis Gene Expression. RESULTS: A total of 21 established risk variants (out of 61) nominally associated to a plaque characteristic. One variant (rs12539895, risk allele A) at 7q22 associated to a reduction of intraplaque fat, P=5.09×10-6 after correction for multiple testing. We further characterized this 7q22 Locus and show tissue-specific effects of rs12539895 on HBP1 expression in plaques and COG5 expression in whole blood and provide data from public resources showing an association with decreased LDL (low-density lipoprotein) and increase HDL (high-density lipoprotein) in the blood. CONCLUSIONS: Our study supports the view that cardiovascular susceptibility loci may exert their effect by influencing the atherosclerotic plaque characteristics

    BTK and PLCG2 remain unmutated in one-third of patients with CLL relapsing on ibrutinib

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    Patients with chronic lymphocytic leukemia (CLL) progressing on ibrutinib constitute an unmet need. Though Bruton tyrosine kinase (BTK) and PLCG2 mutations are associated with ibrutinib resistance, their frequency and relevance to progression are not fully understood. In this multicenter retrospective observational study, we analyzed 98 patients with CLL on ibrutinib (49 relapsing after an initial response and 49 still responding after ≥1 year of continuous treatment) using a next-generation sequencing (NGS) panel (1% sensitivity) comprising 13 CLL-relevant genes including BTK and PLCG2. BTK hotspot mutations were validated by droplet digital polymerase chain reaction (ddPCR) (0.1% sensitivity). By integrating NGS and ddPCR results, 32 of 49 relapsing cases (65%) carried at least 1 hotspot BTK and/or PLCG2 mutation(s); in 6 of 32, BTK mutations were only detected by ddPCR (variant allele frequency [VAF] 0.1% to 1.2%). BTK/PLCG2 mutations were also identified in 6 of 49 responding patients (12%; 5/6 VAF <10%), of whom 2 progressed later. Among the relapsing patients, the BTK-mutated (BTKmut) group was enriched for EGR2 mutations, whereas BTK-wildtype (BTKwt) cases more frequently displayed BIRC3 and NFKBIE mutations. Using an extended capture-based panel, only BRAF and IKZF3 mutations showed a predominance in relapsing cases, who were enriched for del(8p) (n = 11; 3 BTKwt). Finally, no difference in TP53 mutation burden was observed between BTKmut and BTKwt relapsing cases, and ibrutinib treatment did not favor selection of TP53-aberrant clones. In conclusion, we show that BTK/PLCG2 mutations were absent in a substantial fraction (35%) of a real-world cohort failing ibrutinib, and propose additional mechanisms contributing to resistance

    Multiethnic genome-wide meta-analysis of ectopic fat depots identifies loci associated with adipocyte development and differentiation

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    Variation in body fat distribution contributes to the metabolic sequelae of obesity. The genetic determinants of body fat distribution are poorly understood. The goal of this study was to gain new insights into the underlying genetics of body fat distribution by conducting sample-size-weighted fixed-effects genome-wide association meta-analyses in up to 9,594 women and 8,738 men of European, African, Hispanic and Chinese ancestry, with and without sex stratification, for six traits associated with ectopic fat (hereinafter referred to as ectopic-fat traits). In total, we identified seven new loci associated with ectopic-fat traits (ATXN1, UBE2E2, EBF1, RREB1, GSDMB, GRAMD3 and ENSA; P &lt; 5 × 10(-8); false discovery rate &lt; 1%). Functional analysis of these genes showed that loss of function of either Atxn1 or Ube2e2 in primary mouse adipose progenitor cells impaired adipocyte differentiation, suggesting physiological roles for ATXN1 and UBE2E2 in adipogenesis. Future studies are necessary to further explore the mechanisms by which these genes affect adipocyte biology and how their perturbations contribute to systemic metabolic disease
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