Cargando…
Spatial analyzes of HLA data in Rio Grande do Sul, south Brazil: genetic structure and possible correlation with autoimmune diseases
BACKGROUND: HLA genes are the most polymorphic of the human genome and have distinct allelic frequencies in populations of different geographical regions of the world, serving as genetic markers in ancestry studies. In addition, specific HLA alleles may be associated with various autoimmune and infe...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6137739/ https://www.ncbi.nlm.nih.gov/pubmed/30217207 http://dx.doi.org/10.1186/s12942-018-0154-8 |
_version_ | 1783355229046046720 |
---|---|
author | Boquett, Juliano André Zagonel-Oliveira, Marcelo Jobim, Luis Fernando Jobim, Mariana Gonzaga, Luiz Veronez, Maurício Roberto Fagundes, Nelson Jurandi Rosa Schüler-Faccini, Lavínia |
author_facet | Boquett, Juliano André Zagonel-Oliveira, Marcelo Jobim, Luis Fernando Jobim, Mariana Gonzaga, Luiz Veronez, Maurício Roberto Fagundes, Nelson Jurandi Rosa Schüler-Faccini, Lavínia |
author_sort | Boquett, Juliano André |
collection | PubMed |
description | BACKGROUND: HLA genes are the most polymorphic of the human genome and have distinct allelic frequencies in populations of different geographical regions of the world, serving as genetic markers in ancestry studies. In addition, specific HLA alleles may be associated with various autoimmune and infectious diseases. The bone marrow donor registry in Brazil is the third largest in the world, and it counts with genetic typing of HLA-A, -B, and -DRB1. Since 1991 Brazil has maintained the DATASUS database, a system fed with epidemiological and health data from compulsory registration throughout the country. METHODS: In this work, we perform spatial analysis and georeferencing of HLA genetic data from more than 86,000 bone marrow donors from Rio Grande do Sul (RS) and data of hospitalization for rheumatoid arthritis, multiple sclerosis and Crohn’s disease in RS, comprising the period from 1995 to 2016 obtained through the DATASUS system. The allele frequencies were georeferenced using Empirical Bayesian Kriging; the diseases prevalence were georeferenced using Inverse Distance Weighted and cluster analysis for both allele and disease were performed using Getis-Ord Gi* method. Spearman’s test was used to test the correlation between each allele and disease. RESULTS: The results indicate a HLA genetic structure compatible with the history of RS colonization, where it is possible to observe differentiation between regions that underwent different colonization processes. Spatial analyzes of autoimmune disease hospitalization data were performed revealing clusters for different regions of the state for each disease analyzed. The correlation test between allelic frequency and the occurrence of autoimmune diseases indicated a significant correlation between the HLA-B*08 allele and rheumatoid arthritis. CONCLUSIONS: Genetic mapping of populations and the spatial analyzes such as those performed in this work have great economic relevance and can be very useful in the formulation of public health campaigns and policies, contributing to the planning and adjustment of clinical actions, as well as informing and educating professionals and the population. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12942-018-0154-8) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6137739 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-61377392018-09-15 Spatial analyzes of HLA data in Rio Grande do Sul, south Brazil: genetic structure and possible correlation with autoimmune diseases Boquett, Juliano André Zagonel-Oliveira, Marcelo Jobim, Luis Fernando Jobim, Mariana Gonzaga, Luiz Veronez, Maurício Roberto Fagundes, Nelson Jurandi Rosa Schüler-Faccini, Lavínia Int J Health Geogr Research BACKGROUND: HLA genes are the most polymorphic of the human genome and have distinct allelic frequencies in populations of different geographical regions of the world, serving as genetic markers in ancestry studies. In addition, specific HLA alleles may be associated with various autoimmune and infectious diseases. The bone marrow donor registry in Brazil is the third largest in the world, and it counts with genetic typing of HLA-A, -B, and -DRB1. Since 1991 Brazil has maintained the DATASUS database, a system fed with epidemiological and health data from compulsory registration throughout the country. METHODS: In this work, we perform spatial analysis and georeferencing of HLA genetic data from more than 86,000 bone marrow donors from Rio Grande do Sul (RS) and data of hospitalization for rheumatoid arthritis, multiple sclerosis and Crohn’s disease in RS, comprising the period from 1995 to 2016 obtained through the DATASUS system. The allele frequencies were georeferenced using Empirical Bayesian Kriging; the diseases prevalence were georeferenced using Inverse Distance Weighted and cluster analysis for both allele and disease were performed using Getis-Ord Gi* method. Spearman’s test was used to test the correlation between each allele and disease. RESULTS: The results indicate a HLA genetic structure compatible with the history of RS colonization, where it is possible to observe differentiation between regions that underwent different colonization processes. Spatial analyzes of autoimmune disease hospitalization data were performed revealing clusters for different regions of the state for each disease analyzed. The correlation test between allelic frequency and the occurrence of autoimmune diseases indicated a significant correlation between the HLA-B*08 allele and rheumatoid arthritis. CONCLUSIONS: Genetic mapping of populations and the spatial analyzes such as those performed in this work have great economic relevance and can be very useful in the formulation of public health campaigns and policies, contributing to the planning and adjustment of clinical actions, as well as informing and educating professionals and the population. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12942-018-0154-8) contains supplementary material, which is available to authorized users. BioMed Central 2018-09-14 /pmc/articles/PMC6137739/ /pubmed/30217207 http://dx.doi.org/10.1186/s12942-018-0154-8 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Boquett, Juliano André Zagonel-Oliveira, Marcelo Jobim, Luis Fernando Jobim, Mariana Gonzaga, Luiz Veronez, Maurício Roberto Fagundes, Nelson Jurandi Rosa Schüler-Faccini, Lavínia Spatial analyzes of HLA data in Rio Grande do Sul, south Brazil: genetic structure and possible correlation with autoimmune diseases |
title | Spatial analyzes of HLA data in Rio Grande do Sul, south Brazil: genetic structure and possible correlation with autoimmune diseases |
title_full | Spatial analyzes of HLA data in Rio Grande do Sul, south Brazil: genetic structure and possible correlation with autoimmune diseases |
title_fullStr | Spatial analyzes of HLA data in Rio Grande do Sul, south Brazil: genetic structure and possible correlation with autoimmune diseases |
title_full_unstemmed | Spatial analyzes of HLA data in Rio Grande do Sul, south Brazil: genetic structure and possible correlation with autoimmune diseases |
title_short | Spatial analyzes of HLA data in Rio Grande do Sul, south Brazil: genetic structure and possible correlation with autoimmune diseases |
title_sort | spatial analyzes of hla data in rio grande do sul, south brazil: genetic structure and possible correlation with autoimmune diseases |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6137739/ https://www.ncbi.nlm.nih.gov/pubmed/30217207 http://dx.doi.org/10.1186/s12942-018-0154-8 |
work_keys_str_mv | AT boquettjulianoandre spatialanalyzesofhladatainriograndedosulsouthbrazilgeneticstructureandpossiblecorrelationwithautoimmunediseases AT zagoneloliveiramarcelo spatialanalyzesofhladatainriograndedosulsouthbrazilgeneticstructureandpossiblecorrelationwithautoimmunediseases AT jobimluisfernando spatialanalyzesofhladatainriograndedosulsouthbrazilgeneticstructureandpossiblecorrelationwithautoimmunediseases AT jobimmariana spatialanalyzesofhladatainriograndedosulsouthbrazilgeneticstructureandpossiblecorrelationwithautoimmunediseases AT gonzagaluiz spatialanalyzesofhladatainriograndedosulsouthbrazilgeneticstructureandpossiblecorrelationwithautoimmunediseases AT veronezmauricioroberto spatialanalyzesofhladatainriograndedosulsouthbrazilgeneticstructureandpossiblecorrelationwithautoimmunediseases AT fagundesnelsonjurandirosa spatialanalyzesofhladatainriograndedosulsouthbrazilgeneticstructureandpossiblecorrelationwithautoimmunediseases AT schulerfaccinilavinia spatialanalyzesofhladatainriograndedosulsouthbrazilgeneticstructureandpossiblecorrelationwithautoimmunediseases |