4 resultados para CANDIDATE GENES

em Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco


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Background: There is growing evidence that microglia are key players in the pathological process of amyotrophic lateral sclerosis (ALS). It is suggested that microglia have a dual role in motoneurone degeneration through the release of both neuroprotective and neurotoxic factors. Results: To identify candidate genes that may be involved in ALS pathology we have analysed at early symptomatic age (P90), the molecular signature of microglia from the lumbar region of the spinal cord of hSOD1(G93A) mice, the most widely used animal model of ALS. We first identified unique hSOD1(G93A) microglia transcriptomic profile that, in addition to more classical processes such as chemotaxis and immune response, pointed toward the potential involvement of the tumour suppressor gene breast cancer susceptibility gene 1 (Brca1). Secondly, comparison with our previous data on hSOD1(G93A) motoneurone gene profile substantiated the putative contribution of Brca1 in ALS. Finally, we established that Brca1 protein is specifically expressed in human spinal microglia and is up-regulated in ALS patients. Conclusions: Overall, our data provide new insights into the pathogenic concept of a non-cell-autonomous disease and the involvement of microglia in ALS. Importantly, the identification of Brca1 as a novel microglial marker and as possible contributor in both human and animal model of ALS may represent a valid therapeutic target. Moreover, our data points toward novel research strategies such as investigating the role of oncogenic proteins in neurodegenerative diseases.

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Age of onset (AO) of Huntington disease (HD) is mainly determined by the length of the CAG repeat expansion (CAGexp) in exon 1 of the HTT gene. Additional genetic variation has been suggested to contribute to AO, although the mechanism by which it could affect AO is presently unknown. The aim of this study is to explore the contribution of candidate genetic factors to HD AO in order to gain insight into the pathogenic mechanisms underlying this disorder. For that purpose, two AO definitions were used: the earliest age with unequivocal signs of HD (earliest AO or eAO), and the first motor symptoms age (motor AO or mAO). Multiple linear regression analyses were performed between genetic variation within 20 candidate genes and eAO or mAO, using DNA and clinical information of 253 HD patients from REGISTRY project. Gene expression analyses were carried out by RT-qPCR with an independent sample of 35 HD patients from Basque Country Hospitals. We found suggestive association signals between HD eAO and/or mAO and genetic variation within the E2F2, ATF7IP, GRIN2A, GRIN2B, LINC01559, HIP1 and GRIK2 genes. Among them, the most significant was the association between eAO and rs2742976, mapping to the promoter region of E2F2 transcription factor. Furthermore, rs2742976 T allele patient carriers exhibited significantly lower lymphocyte E2F2 gene expression, suggesting a possible implication of E2F2-dependent transcriptional activity in HD pathogenesis. Thus, E2F2 emerges as a new potential HD AO modifier factor.

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Introduction The identification of the genetic risk factors that could discriminate non-thrombotic from thrombotic antiphospholipid antibodies (aPLA) carriers will improve prognosis of these patients. Several human studies have shown the presence of aPLAs associated with atherosclerotic plaque, which is a known risk factor for thrombosis. Hence, in order to determine the implication of atherosclerosis in the risk of developing thrombosis in aPLA positive patients, we performed a genetic association study with 3 candidate genes, APOH, LDLR and PCSK9. Material & Methods For genetic association study we analyzed 190 aPLA carriers -100 with non-thrombotic events and 90 with thrombotic events-and 557 healthy controls. Analyses were performed by chi(2) test and were corrected by false discovery rate. To evaluate the functional implication of the newly established susceptibility loci, we performed expression analyses in 86 aPLA carrier individuals (43 with thrombotic manifestations and 43 without it) and in 45 healthy controls. Results Our results revealed significant associations after correction in SNPs located in LDLR gene with aPLA carriers and thrombotic aPLA carriers, when compared with healthy controls. The most significant association in LDLR gene was found between SNP rs129083082 and aPLA carriers in recessive model (adjusted P-value = 2.55 x 10(-3); OR = 2.18; 95% CI = 1.49-3.21). Furthermore, our work detected significant allelic association after correction between thrombotic aPLA carriers and healthy controls in SNP rs562556 located in PCSK9 gene (adjusted P-value = 1.03 x 10(-2); OR = 1.60; 95% CI = 1.24-2.06). Expression level study showed significantly decreased expression level of LDLR gene in aPLA carriers (P-value < 0.0001; 95% CI 0.16-2.10; SE 0.38-1.27) in comparison to the control group. Discussion Our work has identified LDLR gene as a new susceptibility gene associated with the development of thrombosis in aPLA carriers, describing for the first time the deregulation of LDLR expression in individuals with aPLAs. Besides, thrombotic aPLA carriers also showed significant association with PCSK9 gene, a regulator of LDLR plasma levels. These results highlight the importance of atherosclerotic processes in the development of thrombosis in patients with aPLA.

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The development of techniques for oncogenomic analyses such as array comparative genomic hybridization, messenger RNA expression arrays and mutational screens have come to the fore in modern cancer research. Studies utilizing these techniques are able to highlight panels of genes that are altered in cancer. However, these candidate cancer genes must then be scrutinized to reveal whether they contribute to oncogenesis or are coincidental and non-causative. We present a computational method for the prioritization of candidate (i) proto-oncogenes and (ii) tumour suppressor genes from oncogenomic experiments. We constructed computational classifiers using different combinations of sequence and functional data including sequence conservation, protein domains and interactions, and regulatory data. We found that these classifiers are able to distinguish between known cancer genes and other human genes. Furthermore, the classifiers also discriminate candidate cancer genes from a recent mutational screen from other human genes. We provide a web-based facility through which cancer biologists may access our results and we propose computational cancer gene classification as a useful method of prioritizing candidate cancer genes identified in oncogenomic studies.