The new england journal of medicine

Review Article

Frontiers in Medicine Next-Generation to Diagnose Suspected Genetic Disorders

David R. Adams, M.D., Ph.D., and Christine M. Eng, M.D.​​

linical next-generation sequencing is being used frequently in From the Office of the Clinical Director, medical practices in which genetic testing has traditionally taken place — National Human Research In- stitute, and the Undiagnosed Diseases for example, medical and medical subspecialties such as neuroge- Program, National Institutes of Health, C Bethesda, MD (D.R.A.); and the Depart- netics. Emerging diagnostic applications include rapid-reporting approaches in intensive care settings (especially neonatal and pediatric)1 and use early in the course ment of Molecular and Human Genetics, 2 Baylor College of Medicine, and Baylor of complex disease. Large-scale projects in the United States, China, and else- Genetics — both in Houston (C.M.E.). where are exploring and developing the role of clinical next-generation sequencing Address reprint requests to Dr. Adams at in precision medicine.3,4 This suggests a future in which genomic data will influence the Undiagnosed Diseases Program, Na- tional Institutes of Health, Bldg. 10, Rm. medical decision making for a diverse and growing group of patients (see video). 10C103E, 10 Center Dr., Bethesda, MD 20892, or at ­david​.­adams@​­nih​.­gov. Clinical Next-Generation Sequencing N Engl J Med 2018;379:1353-62. as a Diagnostic Tool DOI: 10.1056/NEJMra1711801 Copyright © 2018 Massachusetts Medical Society. The laboratory techniques that are used in clinical next-generation sequencing have been described in numerous reviews5; proposed guidelines for their application to diagnostic testing have been published.6 The technology generates accurate and reliable sequence information for most parts of the genome. In a comparison of data from and Sanger sequencing (considered the standard of sequenc- ing) for 684 participants in five , the validation rate for the exome sequencing results was 99.97%. Furthermore, discrepant results in high-quality exome sequenc- An illustrated glossary and a ing regions were more likely to be correct in the exome sequencing data than in the video overview of first round of Sanger sequencing data.7 next-generation A clinical next-generation sequencing test can be designed to target a panel of se- sequencing are lected genes, the exome (all known genes, or approximately 1 to 2% of the genome), available at NEJM.org or the entire genome. panels target curated sets of genes associated with specific clinical phenotypes. Phenotypes may be narrow, with 4 genes in the panel for familial hypercholesterolemia, or broad, with more than 1000 genes in the panel for intellectual disability. Clinical exome sequencing targets approximately 22,000 protein-coding genes. Clinical genome sequencing is untargeted, generating se- quence data from a region that is 50 to 100 times as large as that covered by exome sequencing and that includes regulatory, intronic, and intergenic regions (Fig. 1). Clinical decision making about which test to order is an area of active research. Genome sequencing generates more uniform sequencing in some regions than does exome sequencing. Emerging analytic approaches can use genome sequencing to detect structural variants and expansion of short repeats associated with disease. However, bioinformatic tools for genome sequencing are overall less devel- oped than those available for exome sequencing. In addition, the cost of genome sequencing remains higher than that of exome sequencing, partly because of the cost of data management and analysis.

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Gene 1 Gene 2 Gene 3 DNA Exon Exon Exon Exon Exon Exon

Intergenic Difficult-to- region sequence region

Sanger Sequencing

NGS Gene Panel (only a selection of genes are targeted)

Depth-of-coverage graph

Aligned reads at base resolution: Gene 2 not targeted for sequencing

... AATCTGACA ...

... AATCTGACA ...... AATCTGACA AATCAGACA Aligned NGS ... fragments ... AATCAGACA... (“reads”)

Exome Sequencing

Depth-of-coverage graph

Aligned NGS fragments (“reads”)

Genome Sequencing

Intergenic Depth-of-coverage graph Exon region Intron

Aligned NGS fragments (“reads”)

The primary goal for any diagnostic genetic test tify potential risk variants for genetic disease that is the identification of DNA sequence variants that is absent or has not been diagnosed at the time of may be confidently associated with the presenting testing; these results are referred to as secondary, signs and symptoms. Other test results may iden- incidental, or medically actionable findings. Pa-

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Figure 1 (facing page). Clinical Next-Generation ment categories: pathogenic, likely pathogenic, Sequencing (NGS) Test Types. likely benign, benign, and variant of unknown Exome, genome, and panel NGS tests have different significance. Databases of previously assessed vari- genomic coverage characteristics. NGS gene panel ants, such as ClinVar, have been established to tests cover a set of genes defined by the clinical diag- collect and distribute information about previous­ nostic laboratory. The panel will typically cover genes ly interpreted variants.14 ClinVar uses a categorical associated with a set of related medical conditions (e.g., heritable epilepsy disorders). Exome sequencing rating system to indicate the level of evidence for covers the majority of known genes, including genes submitted interpretations. Variants are also priori- that have not yet been associated with human disease. tized on the basis of association with the pheno- Genome sequencing covers a majority of both genes type of the patient, although the possibility of and intergenic regions. Each test type has an associat- phenotypic heterogeneity and blended phenotypes ed pattern of false negative results. For instance, a gene panel may not include a mutated gene and an (more than one mendelian disorder manifesting 15 exome may miss deep intronic splice . In ad- in an individual patient) must be considered. dition, some regions of the genome are difficult to se- Clinical laboratories primarily report variants quence with any existing method. in genes for which the gene–disease association is well established. In other cases, the proposed association will be novel, creating an “N = 1” situa- tients with these risk variants may benefit from tion (in which the diagnosis cannot be claimed early screening and management efforts. Guide- to be definitive) and the opportunity to establish lines for the clinical reporting of this category of a new gene–disease association.10 The risk of findings have been published.8 falsely associating diseases with genes and vari- ants is regularly illustrated by the reclassification Variant Classification of previously established pathogenic variants as the result of improvements in frequency databas- Next-generation sequencing generates thousands es.16 One innovative way to locate additional cases of sequence variants that must be filtered and pri- is through the use of matching databases. Gene- oritized for clinical interpretation, which results in Matcher (https://genematcher.org/), DECIPHER the reporting of a limited number of variants per (https://decipher.sanger.ac.uk/), and Phenome- report. This process may differ slightly among Central (https://www.phenomecentral.org/) iden- individual laboratories, but it generally includes tify matching cases with the use of deidentified annotation of variants, application of frequency data, such as gene names or disease features.17-19 filters and database searches to enrich for rare The Matchmaker Exchange protocol allows match- variants and eliminate common variants, and pre- es between such databases.20 These tools are pub- diction of functional effect. Clinical evaluation of licly available and do not require computational a DNA sequence variant includes an assessment of expertise. potential effects on the function of one or more genes and an assessment of the evidence support- Diagnostic R ate ing attribution of the illness at presentation to the and Testing Strategy affected gene or genes.9 Both assessments benefit from strong association information (e.g., variant Gene Panels to disease and absence of variant to absence of Gene panels (selected genes sequenced by a next- disease).10 However, such evidence may be difficult generation sequencing method) often have higher to obtain for rare variants or diseases. diagnostic rates than exome sequencing or ge- Variants are evaluated according to evolution- nome sequencing, being designed to maximize ary conservation, population frequency, and mod- coverage, sensitivity, and specificity for the includ- eled (or measured) effect on protein function. ed genes. An exception may occur in the context of Large-scale genomic sequencing databases, includ- greater diagnostic uncertainty, for which modeled ing the Genome Aggregation Database (gnomAD), data suggest that exome sequencing can have a are powerful tools for distinguishing common and higher diagnostic rate.21 For example, in a study rare variants.11 Variant evaluation criteria have been involving 50 patients with peripheral neuropathy, published,12 with subsequent proposed refine- a virtual panel was derived from a subset of exome ments.13 These criteria include widely used assess- sequencing data. With the use of this panel, 11 of

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50 diagnoses were made successfully. A subse- ents, and an expected pattern of segregation can quent analysis with the full set of exome data be confirmed for recessive diseases; this kind yielded 8 additional diagnoses.22 of information strengthens confidence in the di- Panels are often used in the context of a spe- agnosis. cific suspected disease or group of diseases. Di- The actual diagnostic rate is highly dependent agnostic rates vary among gene panels. For ex- on the tested population, the availability of ad- ample, a 222-gene panel designed for inherited ditional family members, and the definition of a retinal diseases yielded a diagnosis in 98 of 192 high-likelihood diagnosis; rates of up to 60% have patients (51%) with inherited retinal disorders.23 been reported in selected disease cohorts.32 Di- A more genetically heterogeneous phenotype, early- agnostic sensitivity may differ according to the onset epilepsy, had a diagnostic rate of approxi- affected organ system.26 The remaining unex- mately 30% with the use of a targeted panel of 172 plained cases suggest that new genetic disorders genes associated with the phenotype.24 A total of are yet to be discovered and characterized. Po- 156 of the 172 genes in the panel showed no ab- tential biologic mechanisms for these disorders normalities, which highlights the fact that the may include new mendelian disorders, gene inter- diagnostic rate may not increase linearly with the actions, epistasis, epigenetic mechanisms, uncap- number of included genes.25 tured genetic variation (such as copy-number The cost of next-generation sequencing gene variation), and environmental contributions. Fi- panels is variable but is often lower than that of nal clinical decisions about the appropriate test- exome sequencing. More expensive panels may ing strategy to use in a given context requires incorporate other sequencing techniques to im- the incorporation of information about diagnos- prove the reliability of detection of nucleotide tic uncertainty, panel design, cost, and the nature repeat or add procedures for detecting of any predictable disease-causing mutations deletions and duplications. (Table 1).

Clinical Genome and Exome Sequencing Implementation of Clinical Clinical genome and exome sequencing is often Next-Generation Sequencing used for patients with previous negative panel studies or complex phenotypes for which the dif- Clinicians who routinely use clinical next-gener- ferential diagnosis is broad. These approaches ation sequencing have developed infrastructures have the benefit of assessing all known disease for obtaining consent from patients and counsel- genes, while simultaneously providing a substrate ing them and their family members before and for future reanalysis as variant classification and after testing. Testing begins with sample collec- new gene discovery proceed. When clinical ge- tion — typically, a blood sample (saliva, buccal nome and exome sequencing is used in a patient swab, or blood spot may be acceptable, depending with a suspected but without a on the laboratory used) — and proceeds through a diagnosis, the rate at which testing reveals a complex laboratory and analytic workflow (Fig. 2). molecular diagnosis that is probably explanatory Final reports include DNA sequence variants in ranges from 25 to 52%.26-29 Depending on the in- genes known to be associated with the presenting dication, this diagnostic rate may exceed that of illness, along with an assessment of potentially other widely used genetic diagnostic tools such pathogenic variants (including those of uncer- as chromosome microarray analysis.30 tain significance). Variants in genes that are not An improvement in diagnostic rates, in one associated with the presenting illness may also example by 16 percentage points,31 has been re- be included, such as predicted pathogenic variants ported when sequencing in the affected person in novel genes not currently associated with a (proband) is performed concurrently with sequenc- specific disease. ing in the biologic parents (trio testing). This ap- There may be differences in reporting practices proach highlights the importance of communicat- that may be specific to the particular test or di- ing the clinical phenotype of all tested persons to agnostic laboratory; thus, careful review of test the testing laboratory. With accurate information, characteristics and limitations is important for a new (de novo) mutation in the proband can be the ordering physician. A mock example report is confirmed to be absent from the unaffected par- shown in the Supplementary Appendix, available

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Challenges to Diagnosis by Clinical Genome and Exome Sequencing Example

bb Bb Initial Testing Strategy BRCA1 Mutation for Breast Cancer Unaffected Breast • Affected or unaffected status may be assigned incorrectly cancer Phenotypically unaffected daughter possesses at-risk genotype; any • More common for disorders with incomplete penetrance genetic variants may be mistakenly • Sequence variants detected in family members labeled as bb Bb Bb discarded unaffected may be mistakenly discarded Unaffected Breast Unaffected cancer

DNA Generation of Sequencing Data Alignment • Source of false negative results • Regions that cannot be sequenced will not generate variants for downstream analysis Difficult-to-sequence region Massively parallel (e.g., regions within BRCA2) sequencing

Highly similar region 1 Highly similar region 2 Short-Read Alignment Reference DNA ... ACAAGTGAAGCTGAGTCATACTTAGCCAGAGAAACTGAGTCATAGTA... • Source of false positive results TGAAGCTGAGT AGAAACTGA • If a short read is aligned to an incorrect position, any AGTGAAGCTGAGT GAGAAACTGAGTC Aligned reads GTGAAGCTGAGTCA AGAAACTGAGTCAT difference between the short read and the reference (at base resolution) sequence at the new position may be incorrectly GAGAAACTGAGTCAT GAGAAACTGAG identified as a mutation Misaligned read may be interpreted as a mutation

Region of low coverage

Reference DNA ... ATCTGACTCCTGAGGAGAAGTCTGCC... Genotyping ACTCCTGAGGAGAAGTCTGC • Certainty decreases in regions with low coverage, which TGACTCCTGAGGAGAAGTCT Genotype: A/T heterozygote Aligned causes low-confidence genotype calls that are discarded ATCTGACTCCTGAGGAGAAGTCTG Position: Chromosome 11, during analysis reads 5248232 (GRCh37) GACTCCTGTGGAGAAGTCTGCC ATCTGACTCCTGTGGAGAA

Two population assessment tools wrongly predict that the mutation associated with sickle cell anemia is benign: Annotation Gene: HBB (hemoglobin locus) Pathogenicity Prediction: Complementary DNA: c.20A→T (longest transcript) PolyPhen-2: Benign • Errors may occur owing to outdated information Protein: p.Glu7Val MutationTaster: Polymorphism Identifier: rs334 (dbSNP) • Some annotations are based on errors in software predictions Frequency Known Disease Associations: Sickle cell anemia ExAC: 0.0044 (aggregated populations)

dbSNP: 0.0000 (1000 European) 0.0998 (1000 genomes African)

Filtration Ruleset: Variant Filtration Rule 1 would incorrectly discard the (Essential for reducing large number of variants generated p.Cys282Tyr hemochromatosis 1. Exclude all variants with a frequency of >5% mutation, which occurs in 11% of in any human population by clinical genome and exome sequencing to an analytically North Americans tractable number) 2. Exclude all variants for which an unaffected family member is homozygous • Errors occur when filtration assumptions are violated

Assessment Categories Used by the American College of Medical Reference ...ACTCCTGA GGAGAAG... Interpretation DNA Genetics and Genomics: • Often incorporates a considerable amount of judgment CCTGT GGAGAAG 1. Pathogenic and extrapolation, which is particularly true for rare and Aligned CTCCTGT GGAGA 2. Likely pathogenic newly discovered variants reads CTGT GGAGAAG 3. Variant of unknown significance CCTGT GGA 4. Likely benign 5. Benign

Figure 2. Laboratory and Analytic Workflow of Clinical NGS. The term dbSNP denotes Database of Single-Nucleotide Polymorphisms, ExAC Exome Aggregation Consortium, and PolyPhen-2 Poly- morphism Phenotyping, version 2.

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with the full text of this article at NEJM.org. Coverage decisions are generally based on wheth- Most commercial testing laboratories have some er the use of the test in clinical practice is consid- means by which individual patients can request ered to be experimental, investigational, or medi- the release of their raw test data for reanalysis, cally necessary. second opinion, or research study. Reimbursement for diagnostic testing by means Genetic results can provide support for clini- of next-generation sequencing gene panels, exome cal diagnoses, modify future disease risk, and in- sequencing, and genome sequencing may differ form the customization of a variety of therapies. according to carrier and specific plan. Preautho- Ongoing studies that incorporate results obtained rization by the payer is typically required. The by next-generation sequencing into point-of-care ordering physician must provide clinical notes clinical practice may serve to illuminate the chal- justifying the testing, including details of how lenges of future widespread use of such sequenc- medical management will be affected by the test ing, including the patient’s right to decline receipt results. Appeals of claim denials and peer-to-peer of certain types of results.33 Informed consent is discussions with a payer medical director can be an important component of testing by clinical expected. Appeals of claim denials may incorpo- next-generation sequencing. A proper consent- rate diagnostic rates and other data obtainable ing process gathers information about second- from the clinical diagnostic laboratory. Self-pay ary results that the patient would like to receive options and financial-assistance plans offered by (if any) and provides counseling about the possi- some testing laboratories can help improve access bility of unanticipated risk variants being found. when coverage is denied. In addition, there has The American College of Medical Genetics and been an overall decline in the cost of genomic Genomics (ACMGG) has published a list of genes sequencing in recent years. Ultimately, studies of with both a clinically significant health associa- clinical usefulness and cost-effectiveness will be tion and a potential to modify therapeutic deci- needed to improve coverage and access for pa- sion making.8 Most current laboratories use this tients and families. as a minimum set of secondary-result offerings. The consideration and return of other results, such Studies of Clinical Usefulness as carrier status for recessive diseases, risk-modi- fying variants, and pharmacogenomic variants, are Timely diagnoses can alter medical management, less standardized. provide accurate information about recurrence The consent process should also address poten- risk for family planning, and may result in health tial risks of genetic testing, such as privacy and care savings by ending diagnostic odysseys. In a discrimination concerns. The Genetic Information study involving 44 children who were selected by Act of 2008 prohibits genetic discrimination in clinical geneticists, a diagnosis was achieved in employment and health insurance, but the abil- 23 (52%) by proband-only exome sequencing. ity to obtain life, disability, or long-term care in- Clinical management was altered in 25%. The surance is not protected against genetic discrimi- mean time to diagnosis was 6 years, with the in- nation.34 curring of costs that would have been saved had exome sequencing been carried out earlier.27 Reimbursement In another study, exome sequencing in 63 criti- cally ill infants yielded a diagnostic rate of 51% Coverage of the cost of clinical next-generation at a mean age of 33.1 days of life and had an effect sequencing (and analysis of the results) by both on medical management in 72%.1 In the same public and private payers lags behind the tech- study, 39 of 81 deceased infants received a diagno- nological advances that have brought next-gener- sis by exome sequencing. ation sequencing into clinical use.35 Payers often A study in which genome sequencing was consider several factors when making coverage compared with a standard battery of genetic tests decisions. These include the analytic and clinical in 42 patients showed diagnostic yields of 43% validity of the test, guidelines from professional and 10%, respectively.36 Clinical usefulness was societies, and evidence-based scientific literature. shown in 31%, and the estimated savings due to

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changes in management approached $1 to 2 mil- biomarkers are included in current drug label- lion total for a group of 6 patients. The perfor- ing,43 but the literature regarding the usefulness mance of genome sequencing in patients for of pharmacogenomic data for individual variants whom exome sequencing is nondiagnostic has been mixed. Most persons have one or more has been reported to show some additional use- such variants, with an eMERGE Network study fulness.37 showing a median of two per person in a 5000-person cohort.44 However, studies of geno- Challenges and Opportunities type-guided warfarin dosing — arguably one of the best-known pharmacogenomic examples — Clinical next-generation sequencing technology have not yielded clear guidance.45 has evolved rapidly, frequently outpacing available Assessment of common-disease risk and other resources for generating standards, guidelines, uses of genomic data in healthy persons needs to and resources. Examples include the storage of be performed with the use of high-quality scien- genomic data in electronic medical records (EMRs), tific methods despite the temptation to move data reanalysis, and the creation of databases of rapidly toward implementation.46 In a study of genomic variation in global populations. genome involving healthy pa- Storage practices for genomic data in EMRs tients, 22% had a monogenic disease risk result are heterogeneous. Models for integration into with uncertain clinical usefulness.47 Ongoing and the EMR for ongoing patient care are being stud- future studies are needed to expand characteriza- ied, such as in the Electronic Medical Records and tion of genomic variation in diverse populations. Genomics (eMERGE) and Implementing Genom- A mismatch between the ancestry or ethnic group ics in Practice (IGNITE) networks.38 of the tested person and that of the available popu- A clinical sequencing report is usually pre- lation (“control”) data can negatively affect test pared with the best evidence available at the time. performance. As new information accrues, reanalysis of the test data may result in the reclassification of DNA Future Directions variants of previously unclear clinical significance. In a recent study, exome reanalysis 12 months The field of clinical genome and exome sequenc- after the initial interpretation yielded additional ing is evolving rapidly, with numerous projects fo- diagnoses and was found to be a cost-effective cused on the expansion of diagnostic yield. Current diagnostic approach.39 For the ordering physician, areas of interest include the integration of RNA reanalysis may continue to produce new results testing,48 detection of structural variants,49,50 and over time but has its own risks and benefits, the improvement of decision making related to including loss of contact with patients for whom testing alternatives (gene panels, exomes, and ge- new results become available. nome testing).51 Ongoing and planned genomics and health studies are adding to our under- Healthy Persons standing of the relationship between genomic variation and disease.52,53 Future clinical initia- Genomic data are a potential component of pre- tives that incorporate clinical next-generation cision medicine, and exome and genome sequenc- sequencing into routine medical care are likely es have been described as a lifelong clinical re- to herald a major increase in the total number source.40,41 In addition to the uses described above, of existing and exome sequenc- these data can potentially produce refinement of es. Cost, ethics, and standards development will risk estimates for common diseases, pharmaco­ help to shape the trajectory of broader incorpo- genomic data, and diagnoses for late-onset dis- ration of clinical next-generation sequencing and orders. Exome-sequencing studies detect one to related forms of technology into routine medical seven carrier variants on average, and one trial42 practice. Given the rapid pace of changes during showed that 2% of studies produce potentially the past 5 years, all medical providers should An audio actionable pathogenic or likely pathogenic vari- keep a weather eye open for changes in this trans- interview with Dr. Adams ants in at least one of the genes recommended by formative field. is available the ACMGG for mandatory secondary-result re- Disclosure forms provided by the authors are available with at NEJM.org porting.8 Approximately 130 pharmacogenomic the full text of this article at NEJM.org.

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We thank William Gahl, M.D., Ph.D., Thomas Markello, M.D., sion of the manuscript, discussions, and contributions to earlier Ph.D., and Vito Oliveri, M.B.A., for their review of an earlier ver- versions of the figures.

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