Publicação
Environmental Exposure Index for Early Life Exposure Assessment Tool
| Resumo: | Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by a highly heterogeneous clinical presentation. Multiple genetic factors explain 40% of ASD etiology. However, recent studies indicate a substantial effect of environmental factors on the onset of ASD. To further understand the role of the environment in ASD, the Early Life Exposures Assessment Tool (ELEAT) was designed to collect detailed data on environmental exposure during early development. The ELEAT was administered to a sample of 102 children with ASD and 23 typically developing controls. The aim was to create an exposure index algorithm, enabling the analysis of gene-environment interactions. The Exposure Index was developed through a logical sequence of steps. This process began with the selection of variables for the basic dataset, achieved by categorizing the questions into three subsets (A, B and C), based on specific criteria. To manage the extensive variable set, the ClustOfVar method was applied to subsets A and B. Variables from subset C were excluded from the analysis. Subsequently, a Factor Analysis of Mixed Data (FAMD) was conducted on the variables selected as those that most discriminate children with ASD from typically developing children. In this step, a set of orthogonal factors was extracted from these variables, factors that were then transformed back into weighted original variables to create an aggregated index, termed the environmental exposure index. Finally, we proceeded with the validation of the index scores, using multiple regression analysis of the orthogonal factors from the FAMD, and with the removal of redundant variables, using multiple regression analysis of the selected variables. Although the index has been statistically validated and is considered a reliable measure for assessing exposure, it requires further refinement to enable the precise identification, in the future, of the elevated risk of a child developing autism associated with specific factors. |
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| Autores principais: | Costa, Beatriz Isabel Santos |
| Assunto: | Perturbação do Espetro do Autismo ClustOfVar ELEAT Índice de Exposição Ambiental Análise Fatorial de Dados Mistos Trabalhos de projeto de mestrado - 2024 |
| Ano: | 2024 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso embargado |
| Instituição associada: | Universidade de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório da Universidade de Lisboa |
| Resumo: | Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by a highly heterogeneous clinical presentation. Multiple genetic factors explain 40% of ASD etiology. However, recent studies indicate a substantial effect of environmental factors on the onset of ASD. To further understand the role of the environment in ASD, the Early Life Exposures Assessment Tool (ELEAT) was designed to collect detailed data on environmental exposure during early development. The ELEAT was administered to a sample of 102 children with ASD and 23 typically developing controls. The aim was to create an exposure index algorithm, enabling the analysis of gene-environment interactions. The Exposure Index was developed through a logical sequence of steps. This process began with the selection of variables for the basic dataset, achieved by categorizing the questions into three subsets (A, B and C), based on specific criteria. To manage the extensive variable set, the ClustOfVar method was applied to subsets A and B. Variables from subset C were excluded from the analysis. Subsequently, a Factor Analysis of Mixed Data (FAMD) was conducted on the variables selected as those that most discriminate children with ASD from typically developing children. In this step, a set of orthogonal factors was extracted from these variables, factors that were then transformed back into weighted original variables to create an aggregated index, termed the environmental exposure index. Finally, we proceeded with the validation of the index scores, using multiple regression analysis of the orthogonal factors from the FAMD, and with the removal of redundant variables, using multiple regression analysis of the selected variables. Although the index has been statistically validated and is considered a reliable measure for assessing exposure, it requires further refinement to enable the precise identification, in the future, of the elevated risk of a child developing autism associated with specific factors. |
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