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CHaPTEr 96  Molecular Methods              1307


                                                                  sift/SIFT.html), PolyPhen (http://coot.embl.de/PolyPhen/), and
           Tertiary Data Analysis—Variant Annotation,             several others. CADD represents a class of software that creates
           Interpretation, and Reporting                          a joint model based on integration of many of these methods.
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           The next steps in the analysis involve annotation, filtering, and   All these criteria are put together in a process called gene and
           classification of variants as to their likely role in the disease or   variant curation. Recommendations for scoring variants into
           phenotype for which the test was submitted. The laboratory must   five categories—pathogenic, likely pathogenic, variant of unknown
           ensure that the final report is accurate and complete without   significance, likely benign, and benign—have been given by the
           overinterpretation. Annotation of each variant detected in the   American College of Medical Genetics and  Association for
           sequencing means attaching information about population   Molecular Pathology. 34
           frequency (or lack of previous observation), differences in   The next step in the process is assembly of filtered and classified
           frequency between various ethnic groups, effect of the variant on   variants into the laboratory report. The report must be simple
           protein coding sequence, effect on splicing, and so on. Diagnostic   enough for physicians who are not experts in genomics to
           laboratories must actively use information contained in the public   understand but, at the same time, must document the intermediate
           sequence databases to interpret the biological consequences of   results required to demonstrate analytical accuracy and clinical
           mutations and polymorphisms. There are databases that have   validity. Clinical reports must contain clear nomenclature for
           an important role: (i) GenBank, which contains the reference   the position and consequence of relevant variants along with
           human genome sequences (http://www.ncbi.nlm.nih.gov/entrez);   appropriate indication of test and interpretive limitations. The
           (ii) dbSNP, which contains more than 150 000 000 common   final steps of interpretation and reporting may be facilitated by
           single-nucleotide polymorphisms; (iii) Exome Sequencing Project   communication with the referring clinician so that there is active
           (https://esp.gs.washington.edu/drupal/), which has exome data   collaboration in arriving at a clinical diagnosis.
           on about 6500 individuals from several research projects; (iv) the   The final steps in bioinformatics management of NGS tests
           1000 Genomes Project (http://www.1000genomes.org/), which has   are aggregation and data sharing. Submission of deidentified
           exome and genome data from about 2500 multiethnic controls; and   cases to public-knowledge databases, such as ClinVar, will allow
           the (v) Exome Aggregation Consortium (http://exac.broadinstitute   aggregation of variant data accompanied by sufficient clinical
           .org/), which has assembled variant data on more than 60 000   information to support variant classification. Once this informa-
           subjects from various disease and populations studies.  tion is accumulated in many clinical contexts, the value for patient
             Interpretation of sequence and genotype information is the   care will be magnified beyond what could be inferred from the
           next step in carrying out a molecular diagnostic test. The labora-  case data alone. Data sharing that is consistent, standardized,
           tory must do the following: take into consideration the patient’s   and collected with appropriate protections for confidentiality
           presenting symptoms and other clinical data; examine the strength   will be an invaluable resource for the future.
           of the evidence that specific gene mutations can cause the
           suspected disease; look for variants in genes that might provide   Clinical Performance of Genomics Assays
           a causal explanation; determine whether a candidate variant has   The development of specialized training programs in molecular
           previously been reported to cause a disease; determine whether   genetics and molecular genetic pathology by the  American
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           variants that appear in previous databases have a low frequency   Boards of Medical Genetics and Pathology  highlights the recogni-
           (i.e., compatible with the observed frequency of the rare disease);   tion by professional groups that this area of clinical testing
           determine whether loss-of-function, gain-of-function, dominant   is exceptionally complex.  Although inferences made about
           negative, haploinsufficiency, and so on are known underlying   disease diagnosis and carrier status based on direct detection of
           mechanisms of disease; determine whether variant occurs in an   mutations are inherently categorical, data interpretation should
           exon and/or protein domain compatible with alteration of   incorporate known genotype–phenotype correlations, variable
           function; and summarize whether the candidate variants occur   disease expression/severity, incomplete penetrance, gender-specific
           in similarly affected family members (pattern of inheritance     risk, and other available data. In the future, as DNA testing is
           and cosegregation). If a variant has been observed in the     employed in the assessment of more complex traits such as
           proband and other family members are tested, then the expecta-  autoimmune and neoplastic diseases, genotype data will perhaps
           tion is that it will exactly segregate with the disease. An example   be expressed as “relative risk” and incorporate gene–gene and
           would be testing for a mutation in X-linked SCID in two brothers.   gene–environment interactions. The reliability of these estimates
           The causal variant will be present in both. When the proband   will require standard data acquisition algorithms and constant
           is the only affected individual, then one may look to the literature;   updating of population-based data.
           ClinVar (www.clinicalgenome.org/data-sharing/clinvar/), a
           database of variants with curated interpretations; and locus-  RECOMMENDATIONS FOR USE
           specific public databases (bioinf.uta.fi/base_root/mutationdata
           bases.php) to determine whether the specific variant has previ-
           ously been observed in another affected person. However, it is    KEY CONCEPTS
           routine to find variants that have not previously been observed.
           Assessment of the functional consequence of a newly observed   Principles of Molecular Diagnostics
           sequence variant is problematic, as there is no guarantee that it   •  DNA diagnostics can play an important role in the diagnosis of specific
           is anything more than a rare, but neutral, polymorphism. Loss-  diseases in affected individuals and in genetic risk assessment for
           of-function mutations (e.g., nonsense, frameshift, and conserved   their family members.
           splice site mutations) have clear functional consequences. Missense   •  Genotyping can be used to conduct prenatal diagnoses.
           substitutions  are more difficult. Several methods based on   •  Prenatal diagnosis may be used not only for elective termination of
           sequence conservation and the chemical properties of amino   pregnancy but also for treatment planning.
           acids have been developed. These are available in software, such   •  Provision of genetic testing results to patients and their families carries
                                                                     responsibilities for sensitivity and confidentiality.
           as Sorting Intolerant From Tolerant (SIFT) (http://blocks.fhcrc.org/
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