RESUMO
Glucocorticoid-induced osteonecrosis is a common and severe adverse event. We conducted a meta-analysis to investigate whether polymorphisms in target genes were associated with the risk of corticosteroid-induced osteonecrosis. Published literature from PubMed and EMBASE were searched for eligible publications. Pooled odds ratio (OR) and 95% confidence interval (CI) were calculated using a fixed- or random-effects model. There were 23 articles with 35 genes described the relationship between polymorphisms and glucocorticoid-induced osteonecrosis. Meta-analyses were carried out for those SNPs with three or more eligible studies, which included four SNPs located in three genes (PAI-1, MTHFR, ABCB1). The meta-analysis revealed that the PAI-1 4G allele was associated with an increased risk of osteonecrosis compared with the 5G allele (combined studies: OR=1.932, 95% CI=1.145-3.261). The OR for the 4G/4G vs. 5G/5G genotype of PAI-1 was 3.217 (95% CI 1.667-6.209 with combined studies), The relative risk of osteonecrosis was increased in the 4G allele vs. 5G/5G and 4G/4G genotype vs. 5G allele, with odds ratios of 2.304 (95% CI=1.235-4.299) and 2.307 (95% CI=1.527-3.485) in combined studies, respectively. The ABCB1 C3435T genotype distributions available confirmed that the C allele increased osteonecrosis risk compared with the T allele (OR 1.668, 95% CI=1.214-2.293) and TT genotype (OR 2.946, 95% CI=1.422-6.101). There was no evidence for significant association between MTHFR C677T and ABCB1 G2677T/A polymorphisms and risk of osteonecrosis. Results of this meta-analysis indicate that the PAI-1 4G/5G and ABCB1 C3435T polymorphisms may be risk factors for osteonecrosis.
Assuntos
Glucocorticoides/efeitos adversos , Osteonecrose/induzido quimicamente , Osteonecrose/genética , Alelos , Genótipo , Humanos , Polimorfismo de Nucleotídeo Único/genética , Fatores de RiscoRESUMO
INTRODUCTION: To investigate whether t-PA Alu repeat insertion/deletion (I/D) and PAI-1 4G/5G genetic variations are associated with the risk of MI. METHODS: We conducted a meta-analysis to assess the association between the t-PA I/D and PAI-1 4G/5G polymorphisms and risk of MI. We also performed subgroup analyses based on ethnicity (Caucasian, Asian, and African), gender and age. Forty one eligible studies including 12,461 cases and 14,993 controls were identified to evaluate the impact of PAI-1 4G/5G polymorphism on MI. Seven studies investigated the relationship between t-PA I/D and MI. RESULTS: This meta-analysis revealed that the PAI-1 4G allele (4G/4G and 4G/5G genotype) was associated with an increased risk of MI compared with the 5G allele in the overall population (OR=1.094, 95% CI=1.021 - 1.172, p=0.011). The relative risks of MI for 4G/4G genotype was increased when compared to 5G/5G genotype and 5G allele, with odds ratio at 1.157 (95% CI 1.015 - 1.320, p=0.029) and 1.126 (95% CI =1.015 - 1.249, p=0.025). However, the results show that the 4G/5G polymorphism risk for MI was not associated with ethnicity stratification as Caucasian, Asian or African population. No substantial differences in the genotype distributions were observed in the MI group and control group along the lines of gender and age. After multivariable analysis t-PA I/D polymorphism showed no consistent association with MI. CONCLUSIONS: This study suggests that the 4G/5G polymorphism of PAI-1 may be a risk factor for MI in overall populations.
Assuntos
Predisposição Genética para Doença/etnologia , Predisposição Genética para Doença/genética , Infarto do Miocárdio/etnologia , Infarto do Miocárdio/genética , Inativadores de Plasminogênio/genética , Polimorfismo de Nucleotídeo Único/genética , Ativador de Plasminogênio Tecidual/genética , Distribuição por Idade , Feminino , Estudos de Associação Genética , Humanos , Masculino , Pessoa de Meia-Idade , Prevalência , Fatores de Risco , Distribuição por SexoRESUMO
Rho-kinase inhibitors are effective candidates for the treatment of neural and cardiovascular disorders. The present paper reports the discovery of a novel class of ROCK-I inhibitors by integrating virtual screening with high-throughput screening methods. We developed common-feature pharmacophore models based on known representative ROCK inhibitors and employed them to screen a database of 12,280 compounds. We then applied a LigandFit model to reduce the number of hits. A new high-throughput screening model based on Kinase-Glo Luminescent Kinase Assay was established to identify inhibitors observed among the virtual screening models. Ten hits were found to have larger than 70% inhibition at 10 micromol l(-1) and were worthy of further investigation.
