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May 21, 2014

Bringing Informed Interpretation to Vexing Variants

An open-access paper in Nature presents the NIH's proposed guidelines for evaluating evidence supporting variant causality.

Bringing Informed Interpretation to Vexing Variants

While sharing data has been a longstanding practice in genomics, the most important data labs and clinicians can share will be the lives they saved through testing. [shutterstock/ Alexander Raths]

  • While the first traffic light flashed 18 years before the first car was built, the rules of the road have long lagged behind technology where genetic testing is concerned, especially in distinguishing functional gene variants from those that cause disease.

    That is starting to change as groups of researchers and clinicians hammer out guidelines for statistically rigorous and evidence-based clinical interpretation of variants found through next-generation sequencing.

    On April 23, a working group of 27 experts in genomic research, analysis, and clinical diagnostic sequencing convened in a 2012 workshop by the NIH’s National Human Genome Research Institute (NHGRI) published an open-access paper in Nature presenting its proposed guidelines for evaluating evidence supporting variant causality.

    Daniel MacArthur, Ph.D., of Massachusetts General Hospital and Chris Gunter, Ph.D., of Marcus Autism Center and Emory University, led the working group in drawing up guidelines that cover evidence assessment for candidate disease genes and candidate pathogenic variants, as well as standards for reporting, publishing, and even sharing data.

    The group listed priorities for research and infrastructure development: Developing standardized, quantitative statistical approaches for assigning probability of causation; large-scale genotyping of reported disease-causing variants; building public databases of those variants, with up-to-date supporting evidence, plus variant and allele frequency data from large, diverse population samples; and greater sharing of data by research and clinical labs.

    “We have seen so many more large cohorts and huge amounts of sequence generated, and we have seen things go wrong as well as right over time,” Dr. Gunther told GEN. “Much more is needed on both the research and infrastructure fronts to stringently assign causality to sequence variants.”

    Teri Manolio, M.D., Ph.D., director of NHGRI’s Division of Genomic Medicine and co-chair of the workshop with Dr. MacArthur, told GEN that the institute will not impose the guidelines on labs.

    “We have no way (nor wish) to force this,” Dr. Manolio said. “We hope labs will adopt these or similar guidelines and use caution about inferring causality without firm evidence.”

  • When Size Matters

    The working group hopes to eliminate the incorrect clinical decisions that have resulted after past studies offered conclusions about the relationship between a specific sequence and disease that turned out to be wrong. Many past studies were underpowered, or researchers may not have taken into account important biological factors like sheer gene size, Dr. Gunter told GEN.

    The paper cited four exome sequencing studies that found independent missense mutations in TTN when they compared genomes between individuals with and without autism. TTN has the largest coding sequence of any gene in the genome—it encodes the largest-known muscle protein, titin—thus, variants are likelier to be found there than in smaller genes. Without applying statistical corrections accounting for gene size, mutation rate, number of trios, and distribution of exome coverage, researchers may have falsely focused on TTN as playing a causal role in autism.

    Tracking data on thousands of genes and their mutations is the function of the U.S. National Center for Biotechnology Information’s ClinVar website. As of April 30, ClinVar recorded data on 18,694 genes with 100,523 variations, within 112,341 submissions from 139 entities.

    ClinVar accepts data based on standard formats developed by the International Collaboration for Clinical Genomics (ICCG)—one of three research groups charged with developing and curating variant information through the Clinical Genomics Resource (ClinGen), funded with $25 million from NHGRI and the Eunice Kennedy Shriver National Institute of Child Health and Human Development.

    Is the challenge one of learning more about the gene, or developing technology capable of finding that knowledge? A Stanford University School of Medicine team in March suggested it may be both after studying data from 12 adults who underwent whole-genome sequencing. Depending on the sequencing platform used, 10% to 19% of inherited disease genes were not covered to accepted standards for single nucleotide variant discovery, the team reported in a paper published March 12 in Journal of the American Medical Association.

    “Highly repetitive gene sequences and the first several base pairs of many gene sequences remain challenging. Ion channel genes contributing to risk for inherited heart rhythm disorders are notable examples of poorly covered genes,” Frederick E. Dewey, M.D., a co-lead author, told GEN.

    Dr. Dewey said physicians who are aware of these coverage gaps will often factor them into their choices of sequencing platform. For patients whose signs and symptoms may be consistent with a number of disease processes, genome or exome sequencing may be quicker and less expensive. But panel testing may provide more certainty for assessing patients whose signs and symptoms are highly characteristic of one or small number of genetically related diseases.

    “Our current practice is to require targeted confirmation of clinically important genetic variants discovered via whole genome or exome sequencing prior to clinical action, and many other centers adhere to this practice,” Dr. Dewey added.

  • Clinically Focused Guidelines

    Another effort at developing variant guidelines has occurred over the past year through a clinically oriented workgroup led by the American College of Medical Genetics (ACMG), with representatives from the Association of Molecular Pathologists (AMP) and College of American Pathologists (CAP).

    The groups focused on interpreting Mendelian variants identified by single gene testing, gene panels, and exome analysis in clinically validated genes. The workgroup developed standard terms for classifying variants, and based the interpretation of a variant on multiple lines of evidence, with a menu approach for scoring.

    “The ACMG/AMP/CAP guidelines give more details in how to use the evidences and are intended as a practical guide for clinical laboratories,” AMP President Elaine Lyon, Ph.D., told GEN. Dr. Lyon is also medical director of molecular genetics, and co-medical director of pharmacogenomics at ARUP Laboratories, and associate professor of pathology at University of Utah School of Medicine.

    “There will always be a level of professional interpretation and professional judgment that goes into assessing a variant. We as laboratory professionals have been interpreting sequence variants in single genes for about 15 years, so this is not new to us. However, the next-generation sequencing gives us so much more data that it is more challenging,” Dr. Lyon added.

    Developing successful guidelines will require consensus on who interprets the torrent of sequencing data. In the Stanford study, physicians referred patients for tests based on annotation of variant to function by three genetic counselors, three physician-informaticists, and a molecular pathologist.

    Though the field’s preferred degree is the MS rather than a doctorate, “It is common for genetic counselors to very thoroughly read the literature before meeting with a patient. Counselors have the skills to search the literature for the relevant references to do the annotation,” Ricki Lewis, Ph.D., a genetic counselor at CareNet Medical Group in Schenectady, NY, told GEN.

    “It is very time-consuming, so I don't think that Ph.D.s who run research labs and M.D.s would have the time to add this to their job description,” added Dr. Lewis, author of "The Forever Fix: Gene Therapy and the Boy Who Saved It" (St. Martin's Press, 2012).

    While sharing data has been a longstanding practice in genomics, as Dr. Gunter noted, the most important data labs and clinicians can share will be the lives they saved through testing. The Stanford study discovered a BRCA1 mutation in a pre-symptomatic woman, which led to life-saving prophylactic surgery.

    As Dr. Dewey correctly concluded, “While formal cost-effectiveness analyses are yet to come, and in spite of the limitations we identified, these technologies do have life-saving potential at reasonable cost.”

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