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      Genetic Analysis of 400 Patients Refines Understanding and Implicates a New Gene in Atypical Hemolytic Uremic Syndrome

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          Abstract

          <div class="section"> <a class="named-anchor" id="d413643e284"> <!-- named anchor --> </a> <h5 class="section-title" id="d413643e285">Background</h5> <p id="d413643e287">Genetic variation in complement genes is a predisposing factor for atypical hemolytic uremic syndrome (aHUS), a life-threatening thrombotic microangiopathy, however interpreting the effects of genetic variants is challenging and often ambiguous. </p> </div><div class="section"> <a class="named-anchor" id="d413643e289"> <!-- named anchor --> </a> <h5 class="section-title" id="d413643e290">Methods</h5> <p id="d413643e292"> We analyzed 93 complement and coagulation genes in 400 patients with aHUS, using as controls 600 healthy individuals from Iowa and 63,345 non-Finnish European individuals from the Genome Aggregation Database. After adjusting for population stratification, we then applied the Fisher exact, modified Poisson exact, and optimal unified sequence kernel association tests to assess gene-based variant burden. We also applied a sliding-window analysis to define the frequency range over which variant burden was significant. </p> </div><div class="section"> <a class="named-anchor" id="d413643e294"> <!-- named anchor --> </a> <h5 class="section-title" id="d413643e295">Results</h5> <p id="d413643e297">We found that patients with aHUS are enriched for ultrarare coding variants in the <i>CFH</i>, <i>C3</i>, <i>CD46</i>, <i>CFI</i>, <i>DGKE</i>, and <i>VTN</i> genes. The majority of the significance is contributed by variants with a minor allele frequency of &lt;0.1%. Disease-related variants tend to occur in specific complement protein domains of FH, CD46, and C3. We observed no enrichment for multiple rare coding variants in gene-gene combinations. </p> </div><div class="section"> <a class="named-anchor" id="d413643e318"> <!-- named anchor --> </a> <h5 class="section-title" id="d413643e319">Conclusions</h5> <p id="d413643e321">In known aHUS-associated genes, variants with a minor allele frequency &gt;0.1% should not be considered pathogenic unless valid enrichment and/or functional evidence are available. <i>VTN</i>, which encodes vitronectin, an inhibitor of the terminal complement pathway, is implicated as a novel aHUS-associated gene. Patients with aHUS are not enriched for multiple rare variants in complement genes. In aggregate, these data may help in directing clinical management of aHUS. </p> </div><p id="d413643e329"> <div class="fig panel" id="absf1"> <a class="named-anchor" id="absf1"> <!-- named anchor --> </a> <div class="figure-container so-text-align-c"> <img alt="" class="figure" src="/document_file/16de2f09-2136-4393-82b5-fab38067deb2/PubMedCentral/image/ASN.2018070759absf1"/> </div> <div class="panel-content"/> </div> </p>

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          Most cited references36

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          A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data.

          Heng Li (2011)
          Most existing methods for DNA sequence analysis rely on accurate sequences or genotypes. However, in applications of the next-generation sequencing (NGS), accurate genotypes may not be easily obtained (e.g. multi-sample low-coverage sequencing or somatic mutation discovery). These applications press for the development of new methods for analyzing sequence data with uncertainty. We present a statistical framework for calling SNPs, discovering somatic mutations, inferring population genetical parameters and performing association tests directly based on sequencing data without explicit genotyping or linkage-based imputation. On real data, we demonstrate that our method achieves comparable accuracy to alternative methods for estimating site allele count, for inferring allele frequency spectrum and for association mapping. We also highlight the necessity of using symmetric datasets for finding somatic mutations and confirm that for discovering rare events, mismapping is frequently the leading source of errors. http://samtools.sourceforge.net. hengli@broadinstitute.org.
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            Atypical hemolytic uremic syndrome and C3 glomerulopathy: conclusions from a "Kidney Disease: Improving Global Outcomes" (KDIGO) Controversies Conference.

            In both atypical hemolytic uremic syndrome (aHUS) and C3 glomerulopathy (C3G) complement plays a primary role in disease pathogenesis. Herein we report the outcome of a 2015 Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference where key issues in the management of these 2 diseases were considered by a global panel of experts. Areas addressed included renal pathology, clinical phenotype and assessment, genetic drivers of disease, acquired drivers of disease, and treatment strategies. In order to help guide clinicians who are caring for such patients, recommendations for best treatment strategies were discussed at length, providing the evidence base underpinning current treatment options. Knowledge gaps were identified and a prioritized research agenda was proposed to resolve outstanding controversial issues.
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              Testing for an Unusual Distribution of Rare Variants

              Introduction High throughput sequencing of the human genome is now a reality: recent advances in sequencing technology now permit near complete ascertainment of genetic variation, including rare variants ( p0), some neutral, and some protective (pi
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                Author and article information

                Journal
                Journal of the American Society of Nephrology
                JASN
                American Society of Nephrology (ASN)
                1046-6673
                1533-3450
                November 30 2018
                December 2018
                December 2018
                October 30 2018
                : 29
                : 12
                : 2809-2819
                Article
                10.1681/ASN.2018070759
                6287871
                30377230
                39b4eb1a-0e63-4508-9443-6d7dd6887b26
                © 2018
                History

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