Whole Genome and Whole Exome Sequencing AHS – M2032
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Whole Exome and Whole Genome Sequencing – Oxford Clinical Policy
UnitedHealthcare® Oxford Clinical Policy Whole Exome and Whole Genome Sequencing Policy Number: LABORATORY 024.11 T2 Effective Date: October 1, 2021 Instructions for Use Table of Contents Page Related Policies Coverage Rationale ....................................................................... 1 Chromosome Microarray Testing (Non-Oncology Documentation Requirements ...................................................... 2 Conditions) Definitions ...................................................................................... 2 Molecular Oncology Testing for Cancer Diagnosis, Prior Authorization Requirements ................................................ 3 Prognosis, and Treatment Decisions Applicable Codes .......................................................................... 3 • Preimplantation Genetic Testing Description of Services ................................................................. 4 Clinical Evidence ........................................................................... 4 U.S. Food and Drug Administration ........................................... 22 References ................................................................................... 22 Policy History/Revision Information ........................................... 26 Instructions for Use ..................................................................... 27 Coverage Rationale Whole Exome Sequencing (WES) Whole Exome Sequencing (WES) is proven and Medically Necessary for the following: • Diagnosing or evaluating a genetic disorder -
Whole Exome Sequencing Faqs
WHOLE EXOME SEQUENCING (WES) Whole Exome Sequencing (WES) is generally ordered when a patient’s medical history and physical exam strongly suggest that there is an underlying genetic etiology. In some cases, the patient may have had an extensive evaluation consisting of multiple genetic tests, without identifying an etiology. In other cases, a physician may opt to order one of the Whole Exome Sequencing tests early in the patient’s evaluation in an effort to expedite a possible diagnosis and reduce costs incurred by multiple tests. Whole Exome Sequencing is a highly complex test that is newly developed for the identification of changes in a patient’s DNA that are causative or related to their medical concerns. In contrast to current sequencing tests that analyze one gene or small groups of related genes at a time, Whole Exome Sequencing analyzes the exons or coding regions of thousands of genes simultaneously using next-generation sequencing techniques. The exome refers to the portion of the human genome that contains functionally important sequences of DNA that direct the body to make proteins essential for the body to function properly. These regions of DNA are referred to as exons. There are approximately 180,000 exons in the human genome which represents about 3% of the genome. These 180,000 exons are arranged in about 22,000 genes. It is known that many of the errors that occur in DNA sequences that then lead to genetic disorders are located in the exons. Therefore, sequencing of the exome is thought to be an efficient method of analyzing a patient’s DNA to discover the genetic cause of diseases or disabilities. -
DNA Sequencing and Sorting: Identifying Genetic Variations
BioMath DNA Sequencing and Sorting: Identifying Genetic Variations Student Edition Funded by the National Science Foundation, Proposal No. ESI-06-28091 This material was prepared with the support of the National Science Foundation. However, any opinions, findings, conclusions, and/or recommendations herein are those of the authors and do not necessarily reflect the views of the NSF. At the time of publishing, all included URLs were checked and active. We make every effort to make sure all links stay active, but we cannot make any guaranties that they will remain so. If you find a URL that is inactive, please inform us at [email protected]. DIMACS Published by COMAP, Inc. in conjunction with DIMACS, Rutgers University. ©2015 COMAP, Inc. Printed in the U.S.A. COMAP, Inc. 175 Middlesex Turnpike, Suite 3B Bedford, MA 01730 www.comap.com ISBN: 1 933223 71 5 Front Cover Photograph: EPA GULF BREEZE LABORATORY, PATHO-BIOLOGY LAB. LINDA SHARP ASSISTANT This work is in the public domain in the United States because it is a work prepared by an officer or employee of the United States Government as part of that person’s official duties. DNA Sequencing and Sorting: Identifying Genetic Variations Overview Each of the cells in your body contains a copy of your genetic inheritance, your DNA which has been passed down to you, one half from your biological mother and one half from your biological father. This DNA determines physical features, like eye color and hair color, and can determine susceptibility to medical conditions like hypertension, heart disease, diabetes, and cancer. -
The Bio Revolution: Innovations Transforming and Our Societies, Economies, Lives
The Bio Revolution: Innovations transforming economies, societies, and our lives economies, societies, our and transforming Innovations Revolution: Bio The Executive summary The Bio Revolution Innovations transforming economies, societies, and our lives May 2020 McKinsey Global Institute Since its founding in 1990, the McKinsey Global Institute (MGI) has sought to develop a deeper understanding of the evolving global economy. As the business and economics research arm of McKinsey & Company, MGI aims to help leaders in the commercial, public, and social sectors understand trends and forces shaping the global economy. MGI research combines the disciplines of economics and management, employing the analytical tools of economics with the insights of business leaders. Our “micro-to-macro” methodology examines microeconomic industry trends to better understand the broad macroeconomic forces affecting business strategy and public policy. MGI’s in-depth reports have covered more than 20 countries and 30 industries. Current research focuses on six themes: productivity and growth, natural resources, labor markets, the evolution of global financial markets, the economic impact of technology and innovation, and urbanization. Recent reports have assessed the digital economy, the impact of AI and automation on employment, physical climate risk, income inequal ity, the productivity puzzle, the economic benefits of tackling gender inequality, a new era of global competition, Chinese innovation, and digital and financial globalization. MGI is led by three McKinsey & Company senior partners: co-chairs James Manyika and Sven Smit, and director Jonathan Woetzel. Michael Chui, Susan Lund, Anu Madgavkar, Jan Mischke, Sree Ramaswamy, Jaana Remes, Jeongmin Seong, and Tilman Tacke are MGI partners, and Mekala Krishnan is an MGI senior fellow. -
Genomic Sequencing of Infectious Pathogens
Science, Technology Assessment, MARCH 2021 and Analytics WHY THIS MATTERS Genomic sequencing reveals the genetic code of an infectious disease pathogen, such as SARS-CoV-2, the SCIENCE & TECH SPOTLIGHT: virus that causes COVID-19. Newer, faster, and less costly sequencing can now be used to more quickly track GENOMIC SEQUENCING OF transmission, detect new variants, and develop vaccines and other countermeasures. However, challenges such INFECTIOUS PATHOGENS as high startup costs and privacy concerns remain. /// THE TECHNOLOGY How mature is it? First-generation sequencing is often used to confirm results of NGS. NGS is relatively new to the public health field, but is used What is it? Genomic sequencing technologies decode a pathogen’s to augment surveillance (i.e., data collection and analysis) for SARS- genetic material by identifying the order of chemical “letters” of its DNA CoV-2 in the U.S. and overseas. New technologies are allowing greater (or RNA, its chemical equivalent in some viruses). Each of four letters access to sequencing capabilities by making NGS portable, faster, and represents a chemical unit called a base. The sequence of the bases can more affordable (the cost of one sequence run is now one-millionth of reveal useful information for combatting disease. For example, sequencing what it was two decades ago). Genomic sequencing technologies enable of SARS-CoV-2 is used to track the spread of various strains, known as many different areas of infectious disease study. For example, they enable variants (see fig. 1). genomic epidemiology—the science of using pathogen genomic data to determine the distribution and spread of an infectious disease in a group How does it work? Technologies for sequencing genomes of pathogens of people or animals, and the application of this information to respond to use chemicals to break up the DNA or RNA into small fragments. -
Next-Gen Sequencing Identifies Non-Coding Variation Disrupting
OPEN Molecular Psychiatry (2018) 23, 1375–1384 www.nature.com/mp ORIGINAL ARTICLE Next-gen sequencing identifies non-coding variation disrupting miRNA-binding sites in neurological disorders P Devanna1, XS Chen2,JHo1,2, D Gajewski1, SD Smith3, A Gialluisi2,4, C Francks2,5, SE Fisher2,5, DF Newbury6,7 and SC Vernes1,5 Understanding the genetic factors underlying neurodevelopmental and neuropsychiatric disorders is a major challenge given their prevalence and potential severity for quality of life. While large-scale genomic screens have made major advances in this area, for many disorders the genetic underpinnings are complex and poorly understood. To date the field has focused predominantly on protein coding variation, but given the importance of tightly controlled gene expression for normal brain development and disorder, variation that affects non-coding regulatory regions of the genome is likely to play an important role in these phenotypes. Herein we show the importance of 3 prime untranslated region (3'UTR) non-coding regulatory variants across neurodevelopmental and neuropsychiatric disorders. We devised a pipeline for identifying and functionally validating putatively pathogenic variants from next generation sequencing (NGS) data. We applied this pipeline to a cohort of children with severe specific language impairment (SLI) and identified a functional, SLI-associated variant affecting gene regulation in cells and post-mortem human brain. This variant and the affected gene (ARHGEF39) represent new putative risk factors for SLI. Furthermore, we identified 3′UTR regulatory variants across autism, schizophrenia and bipolar disorder NGS cohorts demonstrating their impact on neurodevelopmental and neuropsychiatric disorders. Our findings show the importance of investigating non-coding regulatory variants when determining risk factors contributing to neurodevelopmental and neuropsychiatric disorders. -
An Efficient and Scalable Analysis Framework for Variant Extraction and Refinement from Population-Scale DNA Sequence Data
Downloaded from genome.cshlp.org on October 4, 2021 - Published by Cold Spring Harbor Laboratory Press Method An efficient and scalable analysis framework for variant extraction and refinement from population-scale DNA sequence data Goo Jun,1,2 Mary Kate Wing,2 Gonçalo R. Abecasis,2 and Hyun Min Kang2 1Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas 77030, USA; 2Center for Statistical Genetics and Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan 48109, USA The analysis of next-generation sequencing data is computationally and statistically challenging because of the massive vol- ume of data and imperfect data quality. We present GotCloud, a pipeline for efficiently detecting and genotyping high- quality variants from large-scale sequencing data. GotCloud automates sequence alignment, sample-level quality control, variant calling, filtering of likely artifacts using machine-learning techniques, and genotype refinement using haplotype in- formation. The pipeline can process thousands of samples in parallel and requires less computational resources than current alternatives. Experiments with whole-genome and exome-targeted sequence data generated by the 1000 Genomes Project show that the pipeline provides effective filtering against false positive variants and high power to detect true variants. Our pipeline has already contributed to variant detection and genotyping in several large-scale sequencing projects, including the 1000 Genomes Project and the NHLBI Exome Sequencing Project. We hope it will now prove useful to many medical sequencing studies. [Supplemental material is available for this article.] The cost of human genome sequencing has declined rapidly, pow- There is a pressing need for software pipelines that support ered by advances in massively parallel sequencing technologies. -
Whole Exome and Whole Genome Sequencing
UnitedHealthcare® Community Plan Medical Policy Whole Exome and Whole Genome Sequencing Policy Number: CS150.J Effective Date: October 1, 2021 Instructions for Use Table of Contents Page Related Community Plan Policies Application ..................................................................................... 1 • Chromosome Microarray Testing (Non-Oncology Coverage Rationale ....................................................................... 1 Conditions) Definitions ...................................................................................... 2 • Molecular Oncology Testing for Cancer Diagnosis, Applicable Codes .......................................................................... 3 Prognosis, and Treatment Decisions Description of Services ................................................................. 4 • Preimplantation Genetic Testing Clinical Evidence ........................................................................... 4 U.S. Food and Drug Administration ........................................... 22 Commercial Policy References ................................................................................... 22 • Whole Exome and Whole Genome Sequencing Policy History/Revision Information ........................................... 26 Medicare Advantage Coverage Summaries Instructions for Use ..................................................................... 26 • Genetic Testing • Laboratory Tests and Services Application This Medical Policy does not apply to the states listed below; refer to -
Clinical Exome Sequencing Tip Sheet – Medicare Item Numbers 73358/73359
Clinical exome sequencing Tip sheet – Medicare item numbers 73358/73359 Glossary Chromosome microarray (CMA or molecular Monogenic conditions (as opposed karyotype): CMA has a Medicare item number to polygenic or multifactorial conditions) are for patients presenting with intellectual caused by variants in a single gene. Variants disability, developmental delay, autism, or at may be inherited (dominant or recessive least two congenital anomalies. CMA is the fashion), or may occur spontaneously (de recommended first line test in these cases as novo) showing no family history. it can exclude a chromosome cause of disease which is unlikely to be detected by Whole exome sequence – sequencing only exome. the protein coding genes (exons). The exome is ~2% of the genome and contains ~85% of Gene panel is a set of genes that are known to disease-causing gene variants. be associated with a phenotype or disorder. They help narrow down the search Whole genome sequence – sequencing the for variants of interest to genes with evidence entire genome (all genes, including coding linking them to particular phenotypes and noncoding regions) Human phenotype ontology (HPO) terms Singleton – Analysis of the child only. describe a phenotypic abnormality using a Trio – analysis of the child and both biological standard nomenclature. Ideally, all clinicians parents. and scientists are using the same terms. Variant - A change in the DNA code that Mendeliome refers to the ~5,000 genes (out of differs from a reference genome. about 20,000 protein coding genes) that are known to be associated with monogenic disease. As variants in new genes are identified with evidence linking them with human disease, they are added to the Mendeliome. -
The Genomics Era: the Future of Genetics in Medicine - Glossary
The Genomics Era: the Future of Genetics in Medicine - Glossary The glossary below provides a list of key terms used throughout the course. You do not need to read them all now; we’ll be linking back to the main glossary step wherever these terms appear, so you may refer back to this list if you are unsure of the terminology being used. Term Definition The process of matching reads back to their original Alignment position in the reference genome. An allele is one of a number of alternative forms of the same gene or genetic locus. We inherit one copy Allele of our genetic code from our mother and one copy of our genetic code from our father. Each copy is known as an allele. Microarray based genomic comparative hybridisation. This is a technique used to detect chromosome imbalances by comparing patient and control DNA and comparing differences between the two sets. It is Array CGH a useful technique for detecting small chromosome deletions and duplications which would not have been detected with more traditional karyotyping techniques. A unit of DNA. There are four bases which form the Base cross links (or rungs) of the DNA double helix: adenine (A), thymine (T), guanine (G) and cytosine (C). Capture see Target enrichment. The process by which a cell becomes specialized in Cell differentiation order to perform a specific function. Centromere The point at which the sister chromatids are joined. #1 FutureLearn A structure located in the nucleus all living cells, comprised of DNA bound around proteins called histones. The normal number of chromosomes in each Chromosome human cell nucleus is 46 and is composed of 22 pairs of autosomes and a pair of sex chromosomes which determine gender: males have an X and a Y chromosome whilst females have two X chromosomes. -
DNA Sequencing) Time Binding Sites and Other Functional Sites Using Sequencing As a Means of Evaluating Chromatin Immunoprecipitation (Chip) Elaine R
COMMENTARY for re-sequencing genomes. With next- generation-based applications, we rapidly A brief history of will begin to annotate the human genome with the positions of regulatory protein- (DNA sequencing) time binding sites and other functional sites using sequencing as a means of evaluating chromatin immunoprecipitation (ChIP) Elaine R. Mardis experiments. A variant of ChIP will eluci- date how genome-wide patterns of histone Each spring, I co-teach a course to under- binding and DNA methylation relate to graduates that aims to introduce them to gene-expression regulation in various cell the brief history of genome sequencing states, such as differentiation or disease. and then immerses them in its current The short read-lengths of next-generation practices. Looking out at their eager faces, platforms also are ideal for discovering the I try (perhaps in vain) to capture for them sequences of non-coding RNA genes that in a 1 hour lecture what has been my life’s cannot be elucidated by in silico methods. focus for the past 20 years or so — DNA Bioinformatics-based analysis of genome- sequencing. If forced to summarize this wide DNA copy number, DNA-sequence time period succinctly, I would say, “Never variation and RNA-expression data sets, all a dull moment!” This is largely owing to the produced by next-generation sequencers, technological advances that have catapulted will be integrated to stitch together the genome sequencing from a cottage industry pieces of the biological ‘story’ being told to a high-throughput enterprise, akin to by genomic data. These stories will, in a factory. -
Exome Sequencing in Early Disease Diagnosis
Diabetes Updates Short Communication ISSN: 2631-5483 Exome Sequencing in early disease diagnosis: Are we on the right track? Musambil M* Department of Genetics, Strategic Center for Diabetes Research, King Saud University, Riyadh, Saudi Arabia Identification of genetic variants associated with monogenic to whole exome sequencing (WES) and targeted gene sequencing. syndromes, complex disorders and related traits opened up an avenue But WGS still remains very much expensive compared with WES and that had not been explored before, which is to translate the genetic targeted sequencing [6] (Tables 1 and 2). screening information into disease predicting tools which could WES could be briefly explained as the process of sequencing provide more efficient management of the disease by improving risk exons or the protein-encoding parts of the genes which represent and its prediction capabilities. The methods to uncover the genetics of these complex disorders have evolved over time. The International the functional part of the genome. WES gives a clear picture of high HapMap Project, carried out as a part of the Human Genome Project, penetrance allelic variation and its relationship to disease phenotype was successful in providing information about more than one million [7]. As WES targets exons and with the knowledge that Mendelian or SNPs (Single Nucleotide Polymorphisms) across the human genome. partly Mendelian variations are mediated by non-synonymous, splice A revolution in SNP genotyping technology had occurred, making it site and frameshift variations, exomes remain the most ideal regions possible to genotype hundreds of thousands of SNPs, opening new to be screened in order to link genetic variation to health and disease.