87 research outputs found

    Nomenclature for the human Arf family of GTP-binding proteins: ARF, ARL, and SAR proteins

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    The Ras superfamily is comprised of at least four large families of regulatory guanosine triphosphate–binding proteins, including the Arfs. The Arf family includes three different groups of proteins: the Arfs, Arf-like (Arls), and SARs. Several Arf family members have been very highly conserved throughout eukaryotic evolution and have orthologues in evolutionally diverse species. The different means by which Arf family members have been identified have resulted in an inconsistent and confusing array of names. This confusion is further compounded by differences in nomenclature between different species. We propose a more consistent nomenclature for the human members of the Arf family that may also serve as a guide for nomenclature in other species

    ARF GTPases and their GEFs and GAPs: concepts and challenges

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    Detailed structural, biochemical, cell biological, and genetic studies of any gene/protein are required to develop models of its actions in cells. Studying a protein family in the aggregate yields additional information, as one can include analyses of their coevolution, acquisition or loss of functionalities, structural pliability, and the emergence of shared or variations in molecular mechanisms. An even richer understanding of cell biology can be achieved through evaluating functionally linked protein families. In this review, we summarize current knowledge of three protein families: the ARF GTPases, the guanine nucleotide exchange factors (ARF GEFs) that activate them, and the GTPase-activating proteins (ARF GAPs) that have the ability to both propagate and terminate signaling. However, despite decades of scrutiny, our understanding of how these essential proteins function in cells remains fragmentary. We believe that the inherent complexity of ARF signaling and its regulation by GEFs and GAPs will require the concerted effort of many laboratories working together, ideally within a consortium to optimally pool information and resources. The collaborative study of these three functionally connected families ( \u3e /=70 mammalian genes) will yield transformative insights into regulation of cell signaling

    Extensive alterations of the whole-blood transcriptome are associated with body mass index: results of an mRNA profiling study involving two large population-based cohorts

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    Background: Obesity, defined as pathologically increased body mass index (BMI),is strongly related to an increased risk for numerous common cardiovascular and metabolic diseases. It is particularly associated with insulin resistance, hyperglycemia, and systemic oxidative stress and represents the most important risk factor for type 2 diabetes (T2D). However, the pathophysiological mechanisms underlying these associations are still not completely understood. Therefore, in order to identify potentially disease-relevant BMI-associated gene expression signatures, a transcriptome-wide association study (TWAS) on BMI was performed. Methods: Whole-blood mRNA levels determined by array-based transcriptional profiling were correlated with BMI in two large independent population-based cohort studies (KORA F4 and SHIP-TREND) comprising a total of 1977 individuals. Results: Extensive alterations of the whole-blood transcriptome were associated with BMI: More than 3500 transcripts exhibited significant positive or negative BMI-correlation. Three major whole-blood gene expression signatures associated with increased BMI were identified. The three signatures suggested: i) a ratio shift from mature erythrocytes towards reticulocytes, ii) decreased expression of several genes essentially involved in the transmission and amplification of the insulin signal, and iii) reduced expression of several key genes involved in the defence against reactive oxygen species (ROS). Conclusions: Whereas the first signature confirms published results, the other two provide possible mechanistic explanations for well-known epidemiological findings under conditions of increased BMI, namely attenuated insulin signaling and increased oxidative stress. The putatively causative BMI-dependent down-regulation of the expression of numerous genes on the mRNA level represents a novel finding. BMI-associated negative transcriptional regulation of insulin signaling and oxidative stress management provide new insights into the pathogenesis of metabolic syndrome and T2D

    A whole-blood transcriptome meta-analysis identifies gene expression signatures of cigarette smoking

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    Cigarette smoking is a leading modifiable cause of death worldwide. We hypothesized that cigarette smoking induces extensive transcriptomic changes that lead to target-organ damage and smoking-related diseases. We performed a metaanalysis of transcriptome-wide gene expression using whole blood-derived RNA from 10,233 participants of European ancestry in six cohorts (including 1421 current and 3955 former smokers) to identify associations between smoking and altered gene expression levels. At a false discovery rate (FDR) < 0.1, we identified 1270 differentially expressed genes in current vs. never smokers, and 39 genes in former vs. never smokers. Expression levels of 12 genes remained elevated up to 30 years after smoking cessation, suggesting that the molecular consequence of smoking may persist for decades. Gene ontology analysis revealed enrichment of smoking-related genes for activation of platelets and lymphocytes, immune response, and apoptosis. Many of the top smoking-related differentially expressed genes, including LRRN3 and GPR15, have DNA methylation loci in promoter regions that were recently reported to be hypomethylated among smokers. By linking differential gene expression with smoking-related disease phenotypes, we demonstrated that stroke and pulmonary function show enrichment for smoking-related gene expression signatures. Mediation analysis revealed the expression of several genes (e.g. ALAS2) to be putative mediators of the associations between smoking and inflammatory biomarkers (IL6 and C-re

    A meta-analysis of gene expression signatures of blood pressure and hypertension.

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    Genome-wide association studies (GWAS) have uncovered numerous genetic variants (SNPs) that are associated with blood pressure (BP). Genetic variants may lead to BP changes by acting on intermediate molecular phenotypes such as coded protein sequence or gene expression, which in turn affect BP variability. Therefore, characterizing genes whose expression is associated with BP may reveal cellular processes involved in BP regulation and uncover how transcripts mediate genetic and environmental effects on BP variability. A meta-analysis of results from six studies of global gene expression profiles of BP and hypertension in whole blood was performed in 7017 individuals who were not receiving antihypertensive drug treatment. We identified 34 genes that were differentially expressed in relation to BP (Bonferroni-corrected p<0.05). Among these genes, FOS and PTGS2 have been previously reported to be involved in BP-related processes; the others are novel. The top BP signature genes in aggregate explain 5%-9% of inter-individual variance in BP. Of note, rs3184504 in SH2B3, which was also reported in GWAS to be associated with BP, was found to be a trans regulator of the expression of 6 of the transcripts we found to be associated with BP (FOS, MYADM, PP1R15A, TAGAP, S100A10, and FGBP2). Gene set enrichment analysis suggested that the BP-related global gene expression changes include genes involved in inflammatory response and apoptosis pathways. Our study provides new insights into molecular mechanisms underlying BP regulation, and suggests novel transcriptomic markers for the treatment and prevention of hypertension

    A meta-analysis of gene expression signatures of blood pressure and hypertension

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    Genome-wide association studies (GWAS) have uncovered numerous genetic variants (SNPs) that are associated with blood pressure (BP). Genetic variants may lead to BP changes by acting on intermediate molecular phenotypes such as coded protein sequence or gene expression, which in turn affect BP variability. Therefore, characterizing genes whose expression is associated with BP may reveal cellular processes involved in BP regulation and uncover how transcripts mediate genetic and environmental effects on BP variability. A meta-analysis of results from six studies of global gene expression profiles of BP and hypertension in whole blood was performed in 7017 individuals who were not receiving antihypertensive drug treatment. We identified 34 genes that were differentially expressed in relation to BP (Bonferroni-corrected p<0.05). Among these genes, FOS and PTGS2 have been previously reported to be involved in BP-related processes; the others are novel. The top BP signature genes in aggregate explain 5%-9% of inter-individual variance in BP. Of note, rs3184504 in SH2B3, which was also reported in GWAS to be associated with BP, was found to be a trans regulator of the expression of 6 of the transcripts we found to be associated with BP (FOS, MYADM, PP1R15A, TAGAP, S100A10, and FGBP2). Gene set enrichment analysis suggested that the BP-related global gene expression changes include genes involved in inflammatory response and apoptosis pathways. Our study provides new insights into molecular mechanisms underlying BP regulation, and suggests novel transcriptomic markers for the treatment and prevention of hypertension

    Large-scale analyses of common and rare variants identify 12 new loci associated with atrial fibrillation

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    Atrial fibrillation affects more than 33 million people worldwide and increases the risk of stroke, heart failure, and death. Fourteen genetic loci have been associated with atrial fibrillation in European and Asian ancestry groups. To further define the genetic basis of atrial fibrillation, we performed large-scale, trans-ancestry meta-analyses of common and rare variant association studies. The genome-wide association studies (GWAS) included 17,931 individuals with atrial fibrillation and 115,142 referents; the exome-wide association studies (ExWAS) and rare variant association studies (RVAS) involved 22,346 cases and 132,086 referents. We identified 12 new genetic loci that exceeded genome-wide significance, implicating genes involved in cardiac electrical and structural remodeling. Our results nearly double the number of known genetic loci for atrial fibrillation, provide insights into the molecular basis of atrial fibrillation, and may facilitate the identification of new potential targets for drug discovery

    Genetic analyses of the QT interval and its components in over 250K individuals identifies new loci and pathways affecting ventricular depolarization and repolarization

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    Genetic analyses of the electrocardiographic QT interval and its components identify additional loci and pathways

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    The QT interval is an electrocardiographic measure representing the sum of ventricular depolarization and repolarization, estimated by QRS duration and JT interval, respectively. QT interval abnormalities are associated with potentially fatal ventricular arrhythmia. Using genome-wide multi-ancestry analyses (&gt;250,000 individuals) we identify 177, 156 and 121 independent loci for QT, JT and QRS, respectively, including a male-specific X-chromosome locus. Using gene-based rare-variant methods, we identify associations with Mendelian disease genes. Enrichments are observed in established pathways for QT and JT, and previously unreported genes indicated in insulin-receptor signalling and cardiac energy metabolism. In contrast for QRS, connective tissue components and processes for cell growth and extracellular matrix interactions are significantly enriched. We demonstrate polygenic risk score associations with atrial fibrillation, conduction disease and sudden cardiac death. Prioritization of druggable genes highlight potential therapeutic targets for arrhythmia. Together, these results substantially advance our understanding of the genetic architecture of ventricular depolarization and repolarization
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