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      Regulatory polymorphisms modulate the expression of HLA class II molecules and promote autoimmunity

      research-article
      1 , 1 , 2 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 3 , 4 , 4 , 5 , 6 , 3 , 7 , 8 , 8 , 9 , 10 , 11 , 12 , 13 , 4 , 4 , 14 , 15 , 1 , 16 , 1 , 4 , 1 , *
      eLife
      eLife Sciences Publications, Ltd
      targeted sequencing, HLA, SLE risk, haplotype, risk allele, LD, Human

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          Abstract

          Targeted sequencing of sixteen SLE risk loci among 1349 Caucasian cases and controls produced a comprehensive dataset of the variations causing susceptibility to systemic lupus erythematosus (SLE). Two independent disease association signals in the HLA-D region identified two regulatory regions containing 3562 polymorphisms that modified thirty-seven transcription factor binding sites. These extensive functional variations are a new and potent facet of HLA polymorphism. Variations modifying the consensus binding motifs of IRF4 and CTCF in the XL9 regulatory complex modified the transcription of HLA-DRB1, HLA-DQA1 and HLA-DQB1 in a chromosome-specific manner, resulting in a 2.5-fold increase in the surface expression of HLA-DR and DQ molecules on dendritic cells with SLE risk genotypes, which increases to over 4-fold after stimulation. Similar analyses of fifteen other SLE risk loci identified 1206 functional variants tightly linked with disease-associated SNPs and demonstrated that common disease alleles contain multiple causal variants modulating multiple immune system genes.

          DOI: http://dx.doi.org/10.7554/eLife.12089.001

          eLife digest

          The human immune system defends the body against microbes and other threats. However, if this process goes wrong the immune system can attack the body’s own healthy cells, which can lead to serious autoimmune diseases.

          Systemic lupus erythematosus (SLE) is an autoimmune disease in which immune cells often attack internal organs – including the kidneys, nervous system and heart. Over the past decade, multiple genes have been linked with an increased risk of SLE. However, it is largely unknown how the sequences of these genes differ between individuals with SLE and healthy individuals, and the precise changes that lead to an increased risk of SLE are also not clear.

          Now, Raj, Rai et al. have determined the genetic sequences of over 700 people with SLE and over 500 healthy individuals and looked for differences that influence susceptibility to the disease. The vast majority of differences were discovered in stretches of DNA that regulate the expression of nearby genes, rather than in DNA that encodes the structures of proteins. Notably, extensive differences were found in a region of the human genome that regulates the production of proteins called Human Leukocyte Antigen class II molecules; which are known to play a critical role in activating the immune system. Raj, Rai et al. found that slight changes to the regulatory DNA sequences resulted in an overabundance of these proteins, which led to a hyperactive immune system that is strongly associated with SLE.

          Future studies could now ask if the changes to the regulatory DNA sequences highlighted by Raj, Rai et al. increase susceptibility to other autoimmune disorders as well. It may also be possible to use the increased understanding of how the immune system is regulated to develop new ways to minimize the rejection of organ transplants.

          DOI: http://dx.doi.org/10.7554/eLife.12089.002

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          Efficiency and power in genetic association studies.

          We investigated selection and analysis of tag SNPs for genome-wide association studies by specifically examining the relationship between investment in genotyping and statistical power. Do pairwise or multimarker methods maximize efficiency and power? To what extent is power compromised when tags are selected from an incomplete resource such as HapMap? We addressed these questions using genotype data from the HapMap ENCODE project, association studies simulated under a realistic disease model, and empirical correction for multiple hypothesis testing. We demonstrate a haplotype-based tagging method that uniformly outperforms single-marker tests and methods for prioritization that markedly increase tagging efficiency. Examining all observed haplotypes for association, rather than just those that are proxies for known SNPs, increases power to detect rare causal alleles, at the cost of reduced power to detect common causal alleles. Power is robust to the completeness of the reference panel from which tags are selected. These findings have implications for prioritizing tag SNPs and interpreting association studies.
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            Use and misuse of population attributable fractions.

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              Limitations of the odds ratio in gauging the performance of a diagnostic, prognostic, or screening marker.

              M. S. Pepe (2004)
              A marker strongly associated with outcome (or disease) is often assumed to be effective for classifying persons according to their current or future outcome. However, for this assumption to be true, the associated odds ratio must be of a magnitude rarely seen in epidemiologic studies. In this paper, an illustration of the relation between odds ratios and receiver operating characteristic curves shows, for example, that a marker with an odds ratio of as high as 3 is in fact a very poor classification tool. If a marker identifies 10% of controls as positive (false positives) and has an odds ratio of 3, then it will correctly identify only 25% of cases as positive (true positives). The authors illustrate that a single measure of association such as an odds ratio does not meaningfully describe a marker's ability to classify subjects. Appropriate statistical methods for assessing and reporting the classification power of a marker are described. In addition, the serious pitfalls of using more traditional methods based on parameters in logistic regression models are illustrated.
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                Author and article information

                Contributors
                Role: Reviewing editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                15 February 2016
                2016
                : 5
                : e12089
                Affiliations
                [1 ]deptDepartment of Immunology , University of Texas Southwestern Medical Center , Dallas, United States
                [2 ]deptSchool of Biotechnology , Shri Mata Vaishno Devi University , Katra, India
                [3 ]deptDepartment of Neurology , Yale School of Medicine , New Haven, United States
                [4 ]deptArthritis and Clinical Immunology Program , Oklahoma Medical Research Foundation , Oklahoma City, United States
                [5 ]deptPole de pathologies rhumatismales, Institut de Recherche Expérimentale et Clinique , Université catholique de Louvain , Bruxelles, Belgium
                [6 ]deptDivision of Rheumatology, Department of Medicine , Penn State Medical School , Hershey, United States
                [7 ]deptDepartment of Internal Medicine , University of Texas Southwestern Medical Center , Dallas, United States
                [8 ]deptEugene McDermott Center for Human Growth and Development , University of Texas Southwestern Medical Center , Dallas, United States
                [9 ]deptDepartment of Orthopaedic Surgery , University of Texas Southwestern Medical Center , Dallas, United States
                [10 ]deptSarah M. and Charles E. Seay Center for Musculoskeletal Research , Texas Scottish Rite Hospital for Children , Dallas, United States
                [11 ]deptDepartment of Pediatrics , University of Texas Southwestern Medical Center , Dallas, United States
                [12 ]Cincinnati VA Medical Center , Cincinnati, United States
                [13 ]Cincinnati Children's Hospital Medical Center , Cincinnati, United States
                [14 ]deptDepartment of Medicine , University of Southern California , Los Angeles, United States
                [15 ]deptDepartment of Medicine , University of California, Los Angeles , Los Angeles, United States
                [16 ]deptRheumatic Diseases Division, Department of Medicine , University of Texas Southwestern Medical Center , Dallas, United States
                [17]Wellcome Trust Centre for Human Genetics , United Kingdom
                [18]Wellcome Trust Centre for Human Genetics , United Kingdom
                Author notes
                [†]

                These authors contributed equally to this work.

                Author information
                http://orcid.org/0000-0002-7107-0992
                Article
                12089
                10.7554/eLife.12089
                4811771
                26880555
                e608ddf9-40ac-4bf4-8b33-0f3278c37419
                © 2016, Raj et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 05 October 2015
                : 13 February 2016
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100007820, Alliance for Lupus Research;
                Award Recipient :
                Funded by: Walter M. and Helen D. Bader Center;
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000052, NIH Office of the Director;
                Award ID: AR055503
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000052, NIH Office of the Director;
                Award ID: AI045196
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000052, NIH Office of the Director;
                Award ID: AR058959
                Award Recipient :
                The funding from above listed agencies supported sample collection, data generation, data analysis, etc., and man power for the present study
                Categories
                Research Article
                Genomics and Evolutionary Biology
                Human Biology and Medicine
                Custom metadata
                2.5
                Genetic variations that underlie common autoimmune disease genes are predominantly regulatory and modify the expression of multiple genes within the HLA gene complex and throughout the immune system.

                Life sciences
                targeted sequencing,hla,sle risk,haplotype,risk allele,ld,human
                Life sciences
                targeted sequencing, hla, sle risk, haplotype, risk allele, ld, human

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