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      Catalytically Impaired TYK2 Variants are Protective Against Childhood- and Adult-Onset Systemic Lupus Erythematosus in Mexicans

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          Abstract

          Type I interferon (IFN-I) pathway plays a central role in the systemic lupus erythematosus (SLE) pathogenesis. Recent data suggest that SLE is associated with variants in IFN-I genes, such as tyrosine kinase 2 ( TYK2), which is crucial in anti-viral immunity. Here, five TYK2 single nucleotide polymorphisms (SNPs) were genotyped in 368 childhood-onset SLE Mexican patients and 516 sex-matched healthy controls. Allele frequencies were also estimated in four indigenous groups. SLE protection was associated with TYK2 risk infection variants affecting residually its catalytic domain, rs12720356 (OR = 0.308; p = 0.041) and rs34536443 (OR = 0.370; p = 0.034), but not with rs2304256, rs12720270, and rs280500. This association was replicated in a 506 adult-onset SLE patients sample (OR = 0.250; p = 0.005, and OR = 0.277; p = 0.008, respectively). The minor alleles of both associated SNPs had a lower frequency in Mestizos than in Spaniards and were absent or rare in indigenous, suggesting that the presence of these alleles in the Mexican Mestizo population was derived from the Spaniards. For the first time, we report genetic variants with a protective effect in childhood- and adult-onset SLE Mexican population. Our results suggest that the frequency of IFN-I alleles associated with SLE, may have been shaped in populations exposed to infectious diseases for long periods, and this could be an explanation why Native American ancestry is associated with a higher SLE prevalence and an earlier onset.

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          Most cited references 33

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          PLINK: a tool set for whole-genome association and population-based linkage analyses.

          Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.
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            Haploview: analysis and visualization of LD and haplotype maps.

            Research over the last few years has revealed significant haplotype structure in the human genome. The characterization of these patterns, particularly in the context of medical genetic association studies, is becoming a routine research activity. Haploview is a software package that provides computation of linkage disequilibrium statistics and population haplotype patterns from primary genotype data in a visually appealing and interactive interface. http://www.broad.mit.edu/mpg/haploview/ jcbarret@broad.mit.edu
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              An integrated map of genetic variation from 1,092 human genomes

              Summary Through characterising the geographic and functional spectrum of human genetic variation, the 1000 Genomes Project aims to build a resource to help understand the genetic contribution to disease. We describe the genomes of 1,092 individuals from 14 populations, constructed using a combination of low-coverage whole-genome and exome sequencing. By developing methodologies to integrate information across multiple algorithms and diverse data sources we provide a validated haplotype map of 38 million SNPs, 1.4 million indels and over 14 thousand larger deletions. We show that individuals from different populations carry different profiles of rare and common variants and that low-frequency variants show substantial geographic differentiation, which is further increased by the action of purifying selection. We show that evolutionary conservation and coding consequence are key determinants of the strength of purifying selection, that rare-variant load varies substantially across biological pathways and that each individual harbours hundreds of rare non-coding variants at conserved sites, such as transcription-factor-motif disrupting changes. This resource, which captures up to 98% of accessible SNPs at a frequency of 1% in populations of medical genetics focus, enables analysis of common and low-frequency variants in individuals from diverse, including admixed, populations.
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                Author and article information

                Contributors
                lorozco@inmegen.gob.mx
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                21 August 2019
                21 August 2019
                2019
                : 9
                Affiliations
                [1 ]ISNI 0000 0004 0627 7633, GRID grid.452651.1, Immunogenomics and Metabolic Diseases Laboratory, National Institute of Genomic Medicine, ; SS Mexico City, Mexico
                [2 ]GRID grid.414788.6, Servicio de Reumatología del Hospital Juárez de México, ; Mexico City, Mexico
                [3 ]GRID grid.414788.6, Unidad de Investigación en Enfermedades Metabólicas y Endócrinas del Hospital Juárez de México, ; Mexico City, Mexico
                [4 ]ISNI 0000 0001 0698 4037, GRID grid.416850.e, Department of Genetics, , Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, ; Mexico City, Mexico
                [5 ]ISNI 0000 0001 1091 9430, GRID grid.419157.f, Department of Rheumatology, , Pediatric Hospital Medical Center SXXI, IMSS, ; Mexico City, Mexico
                Article
                48451
                10.1038/s41598-019-48451-3
                6704113
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                Funding
                Funded by: FundRef https://doi.org/10.13039/501100003141, Consejo Nacional de Ciencia y Tecnología (National Council of Science and Technology, Mexico);
                Award ID: CB 2014-243394
                Award ID: CB 2010-135155
                Award Recipient :
                Categories
                Article
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                © The Author(s) 2019

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                systemic lupus erythematosus, genetics research

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