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      Current genetic landscape in common variable immune deficiency

      1 , 2 , 1 , 3 , 4
      Blood
      American Society of Hematology

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          Abstract

          Using whole-exome sequencing to examine the genetic causes of immune deficiency in 235 common variable immunodeficiency (CVID) patients seen in the United States (Mount Sinai, New York), 128 patients from Sweden, and 208 from Iran revealed 68 known disease-causing genes underlying this heterogeneous immune defect. The patients at the time of study ranged from 4 to 90 years of age. Overall, 31%, 36%, and 54% of the patients in the US, Swedish, or Iranian cohorts had mutations. The multiplicity of genes identified in the 571 subjects reflects the complex requirements of B-cell antigen signaling, activation, survival, migration, maturation, and maintenance of antibody-secreting memory B-cell populations to the plasma cell stage. For the US and Swedish cohorts, CVID subjects with noninfectious complications, lymphoid infiltrations, inflamatory conditions, or autoimmunity were somewhat more likely to have an identifiable gene, but in both cohorts, numerous subjects with these medical conditions had no potential gene that could be assigned. Specific clinical patterns of illnesses were also not linked to any given gene defect as there was considerable overlap in clinical presentations. These observations led to a new perspective on the complexity of the immunologic phenotype found in CVID syndrome.

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          Most cited references49

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          Is Open Access

          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            Fast and accurate short read alignment with Burrows–Wheeler transform

            Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
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              Standards and Guidelines for the Interpretation of Sequence Variants: A Joint Consensus Recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology

              The American College of Medical Genetics and Genomics (ACMG) previously developed guidance for the interpretation of sequence variants. 1 In the past decade, sequencing technology has evolved rapidly with the advent of high-throughput next generation sequencing. By adopting and leveraging next generation sequencing, clinical laboratories are now performing an ever increasing catalogue of genetic testing spanning genotyping, single genes, gene panels, exomes, genomes, transcriptomes and epigenetic assays for genetic disorders. By virtue of increased complexity, this paradigm shift in genetic testing has been accompanied by new challenges in sequence interpretation. In this context, the ACMG convened a workgroup in 2013 comprised of representatives from the ACMG, the Association for Molecular Pathology (AMP) and the College of American Pathologists (CAP) to revisit and revise the standards and guidelines for the interpretation of sequence variants. The group consisted of clinical laboratory directors and clinicians. This report represents expert opinion of the workgroup with input from ACMG, AMP and CAP stakeholders. These recommendations primarily apply to the breadth of genetic tests used in clinical laboratories including genotyping, single genes, panels, exomes and genomes. This report recommends the use of specific standard terminology: ‘pathogenic’, ‘likely pathogenic’, ‘uncertain significance’, ‘likely benign’, and ‘benign’ to describe variants identified in Mendelian disorders. Moreover, this recommendation describes a process for classification of variants into these five categories based on criteria using typical types of variant evidence (e.g. population data, computational data, functional data, segregation data, etc.). Because of the increased complexity of analysis and interpretation of clinical genetic testing described in this report, the ACMG strongly recommends that clinical molecular genetic testing should be performed in a CLIA-approved laboratory with results interpreted by a board-certified clinical molecular geneticist or molecular genetic pathologist or equivalent.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Blood
                American Society of Hematology
                0006-4971
                1528-0020
                February 27 2020
                February 27 2020
                : 135
                : 9
                : 656-667
                Affiliations
                [1 ]Division of Clinical Immunology, Department of Laboratory Medicine, Karolinska Institutet at Karolinska Hospital Huddinge, Stockholm, Sweden;
                [2 ]Research Center for Immunodeficiencies, Pediatric Center of Excellence, Children’s Medical Center Hospital, Tehran University of Medical Sciences, Tehran, Iran; and
                [3 ]Division of Clinical Immunology, Departments of Medicine and Pediatrics and
                [4 ]Graduate School of Biomedical Sciences, Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY
                Article
                10.1182/blood.2019000929
                7046605
                31942606
                438d1728-9d8a-4bf9-8bfd-adaffa3d03d4
                © 2020
                History

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