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Spatial analyzes of HLA data in Rio Grande do Sul, south Brazil: genetic structure and possible correlation with autoimmune diseases

Overview of attention for article published in International Journal of Health Geographics, September 2018
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Title
Spatial analyzes of HLA data in Rio Grande do Sul, south Brazil: genetic structure and possible correlation with autoimmune diseases
Published in
International Journal of Health Geographics, September 2018
DOI 10.1186/s12942-018-0154-8
Pubmed ID
Authors

Juliano André Boquett, Marcelo Zagonel-Oliveira, Luis Fernando Jobim, Mariana Jobim, Luiz Gonzaga, Maurício Roberto Veronez, Nelson Jurandi Rosa Fagundes, Lavínia Schüler-Faccini

Abstract

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. 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. 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. 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.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 41 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 17%
Researcher 6 15%
Student > Bachelor 4 10%
Other 2 5%
Lecturer 2 5%
Other 3 7%
Unknown 17 41%
Readers by discipline Count As %
Medicine and Dentistry 5 12%
Biochemistry, Genetics and Molecular Biology 2 5%
Nursing and Health Professions 2 5%
Agricultural and Biological Sciences 2 5%
Computer Science 2 5%
Other 7 17%
Unknown 21 51%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 September 2018.
All research outputs
#20,533,782
of 23,103,903 outputs
Outputs from International Journal of Health Geographics
#552
of 633 outputs
Outputs of similar age
#293,713
of 337,433 outputs
Outputs of similar age from International Journal of Health Geographics
#7
of 8 outputs
Altmetric has tracked 23,103,903 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 633 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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