Publicação
Analysis of gene expression in adipocytes of individuals with metabolic syndrome by multivariate statistical methods
| Resumo: | Metabolic syndrome is defined as a cluster of cardiovascular risk factors. Its presence is associated with the occurrence of many biologic phenomena, diseases and conditions, as insulin resistance, inflammation, oxidative stress, diabetes, mental diseases and increased severity of health problems. It is also very prevalent in modern societies due to lifestyle choices and due to the ageing of the populations. Due to human variability in behaviors, food choices, chosen environments, genetic and epigenetic traits, amongst other factors, the working definition of metabolic syndrome must be adapted to the population under study. Some previous work from other researchers suggests that a definition of metabolic syndrome as a continuous variable can be better suitable to the clinical and ambulatory settings, to effective interventions in the population and to the progress in the scientific knowledge. Besides that, it is our believe that gene expression studies (and generally genomics studies) can also benefit greatly from this redefinition. In this work, for a male Finnish population, from whom we have clinical measures, we have redefined the metabolic syndrome as a continuous variable. This result can be used to improve the knowledge in the diagnostics and prognostics of this syndrome, in this population. Even more, with the data of the gene expression in abdominal adipocytes of these men, we have used multivariate statistical methods, as principal component analysis, non-negative matrix factorization and independent component analysis to create components/factors that are associated with the continuous variable mentioned. In this way, by annotation of the genes that have the major contributions in these components/factors, we expect to ag genes as good candidates to further research. |
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| Autores principais: | Combadão, Jaime Manuel Pinto |
| Assunto: | Síndrome Metabólica Análise factorial confirmatória Análise em componentes principais Análise em componentes independentes Trabalhos de projeto de mestrado - 2017 |
| Ano: | 2017 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório da Universidade de Lisboa |
| Resumo: | Metabolic syndrome is defined as a cluster of cardiovascular risk factors. Its presence is associated with the occurrence of many biologic phenomena, diseases and conditions, as insulin resistance, inflammation, oxidative stress, diabetes, mental diseases and increased severity of health problems. It is also very prevalent in modern societies due to lifestyle choices and due to the ageing of the populations. Due to human variability in behaviors, food choices, chosen environments, genetic and epigenetic traits, amongst other factors, the working definition of metabolic syndrome must be adapted to the population under study. Some previous work from other researchers suggests that a definition of metabolic syndrome as a continuous variable can be better suitable to the clinical and ambulatory settings, to effective interventions in the population and to the progress in the scientific knowledge. Besides that, it is our believe that gene expression studies (and generally genomics studies) can also benefit greatly from this redefinition. In this work, for a male Finnish population, from whom we have clinical measures, we have redefined the metabolic syndrome as a continuous variable. This result can be used to improve the knowledge in the diagnostics and prognostics of this syndrome, in this population. Even more, with the data of the gene expression in abdominal adipocytes of these men, we have used multivariate statistical methods, as principal component analysis, non-negative matrix factorization and independent component analysis to create components/factors that are associated with the continuous variable mentioned. In this way, by annotation of the genes that have the major contributions in these components/factors, we expect to ag genes as good candidates to further research. |
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