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INTRODUCTIONT ree years ago, the Medical College of Wis-consin launched a Genomics Medicine clinic in collaboration with Children’s Hospital of Wisconsin and Froedtert Hospital with the goal of using whole-genome sequencing (WGS) to elucidate the etiology of undiag-nosed diseases in patients who had exhausted all standard care options. We used exome sequencing for our f rst pediatric case, Nic Volker, and had to develop analytical tools to evaluate ~18,000 variants. Subsequently, 23 pediatric patients and 2 adult patients have had their genomes sequenced, requiring that we develop a strategy to manage >400,000 variants. So far, we have been able to obtain a def nitive diagnosis in 27% of cases (7/26)

(Table 1). Our initial concerns were cost and data accuracy, but the major challenges turned out to be the logistics of delivering genome sequence information to clinicians, how clinicians use the data, and how patients and their families deal with the secondary (incidental) f ndings. Here, we discuss the challenges of building our clinical genomic medicine program and the lessons we have learned. We hope this Commentary will help other groups to implement their own clinical programs or, at a minimum, help to initiate a conversation about the application of WGS in clinical care.

GETTING CLINICIAN BUY-INToday, in clinical medicine, elucidating ge-netic causation is commonly pursued for rare diseases. In contrast, risk assessment for common diseases is based on family history even though this is of en incomplete or inac-curate (1, 2). Genetic diagnosis and risk as-sessment can be achieved through traditional genetic testing (at the individual gene or gene panel level), but there are limitations. WGS is a more comprehensive approach but is not regularly used because testing is perceived as expensive, of en is not covered by insurance companies, and is not always thought neces-sary based on clinical decision-making guide-lines. As a result, most clinicians are unlikely to view WGS as a useful clinical tool. When considering WGS, clinicians may ask: If I f nd the gene mutation and there is nothing I can do that will change the clinical course, why do the test? In other words, are the results from gene tests or WGS clinically actionable?

e term “clinically actionable” has a wide range of def nitions (3); this lack of clarity

has the potential to limit viable clinical use and complicates the development of uniform policies. At the strict def nitional level, action-able is “information that allows a decision to be made or action to be taken” (www.thefree-dictionary.com/actionable). In this regard, us-ing WGS to make the diagnosis, or a better diagnosis, can be considered “actionable”. Our clinical program is built around the principal idea that making a diagnosis is essential, even in cases where the results may not lead to bet-ter treatment. e long-standing experience of clinical genetics has been that a diagnosis can change the management plan for a patient even in the absence of specif c therapeutic choices (4).

For example, our group was consider-ing a liver transplant for a critically ill child with severe liver disease (5). To aid in di-agnosis, next-generation sequencing was performed and the clinical team learned that the child carried two mutations in the TWINKLE gene and that the liver manifes-tations were likely to be the result of a newly identif ed gene variant. TWINKLE muta-tions are known to cause progressive neu-rological deterioration (6), and the patient was beginning to show neurological symp-toms. In consultation with the parents and the clinical team, a liver transplant was not performed, given the poor long-term prog-nosis, and the child died at 6 months of age (5). In this case, although there was no im-proved measured clinical outcome, the par-ents were reassured that the disease was in-curable and that a liver transplant would not have prevented the child’s death. e po-tential donor liver was available for another child and our patient did not suf er from a futile liver transplant. In another case, WGS uncovered a rare autosomal recessive gas-trointestinal (GI) syndrome and, although there is no cure for the disease, the diagnosis allowed us to improve the patient’s quality of life by providing anticipatory guidance. e information also enabled us to provide an accurate recurrence risk to the parents and options for prenatal testing, and the parents derived comfort from knowing the diag-nosis. Although physicians and insurance companies have traditionally used clinical utility to determine the value of a test, the concept of personal utility is now being ap-plied to genomic information (7) and, we believe, has a role in clinical medicine.

MAKING CLINICAL DECISIONSClinical decision-making is especially chal-lenging when there are no data to support

G E N O M I C S

Genomics in Clinical Practice: Lessons from the Front LinesHoward J. Jacob,1,5,6* Kelly Abrams,12 David P. Bick,1,5,10 Kent Brodie,1 David P. Dimmock,1,5,10 Michael Farrell,3 Jennifer Geurts,1,7 Jeremy Harris,1,5 Daniel Helbling,1,5 Barbara J. Joers,12 Robert Kliegman,5 George Kowalski,1 Jozef Lazar,1,2 David A. Margolis,5 Paula North,4,9,11 Jill Northup,1 Altheia Roquemore-Goins,11 Gunter Scharer,1,5,10 Mary Shimoyama,1,7 Kimberly Strong,1,8 Bradley Taylor,1 Shirng-Wern Tsaih,1 Michael R. Tschannen,1 Regan L. Veith,1,10 Jaime Wendt-Andrae,1 Brandon Wilk,1,5 Elizabeth A. Worthey1,5,9

*Corresponding author. E-mail: jacob@mcw.edu

1Human and Molecular Genetic Center, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. 2Department of Dermatology, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. 3Department of Medicine, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. 4Department of Pa-thology, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. 5Department of Pediatrics, Medical College of Wisconsin, 8701 Water-town Plank Road, Milwaukee, WI 53226, USA. 6Depart-ment of Physiology, Medical College of Wisconsin, 8701, Watertown Plank Road, Milwaukee, WI 53226, USA. 7Department of Surgery, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. 8The Institute of Health and Society, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. 9Children’s Research Institute, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. 10Genomics Medicine Clinic, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. 11Clinical Laboratory, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. 12Operations, Chil-dren’s Hospital of Wisconsin, 9000 W. Wisconsin Avenue, Milwaukee, WI 53226, USA.

The price of whole-genome and -exome sequencing has fallen to the point where these methods can be applied to clinical medicine. Here, we outline the lessons we have learned in converting a sequencing laboratory designed for research into a fully func-tional clinical program.

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the role of a specif c genetic variant in a par-ticular disease phenotype (so-called vari-ants of uncertain signif cance, VUS). Our f rst pediatric patient, Nic Volker, had se-vere GI disease and had undergone multiple procedures under anesthetic. Whole-exome sequencing revealed a mutation in the XIAP gene. XIAP mutations are associated with an increased risk of lymphoproliferative disease (LPD) (8), but no scientif c evidence linked these mutations to Nic’s GI symptoms. Al-though reconstituting Nic’s immune sys-

tem with a bone marrow transplant (BMT) would reduce the risk of LPD, this interven-tion carried signif cant risks and it was not clear whether it would improve Nic’s GI dis-ease. Fortuitously, while we and the family were considering the decision, molecular research was published supporting an asso-ciation between XIAP and a gene in a sig-naling pathway known to be altered in GI disease (8). We proceeded with a cord blood transplant that resulted in resolution of Nic’s GI symptoms. It is uncertain what course we

would have taken if there had not been the compelling need for a BMT based on the molecular diagnosis or what other clinicians would have done with the same data we had. ere have been two other cases in which a VUS was found to be a clear contributor to disease etiology af er the publication of new research data. With WGS, we have improved our rate of diagnosis to 27% for rare or undi-agnosed diseases (Table 1). We wonder how many of the 73% of unsolved cases af er WGS have the correct VUS but no supporting data

The fi rst column lists the order in which patient samples were sent to Illumina for whole-genome sequencing (WGS). Nic Volker is not listed because his diagnosis was made using whole-exome sequencing. Clinical indication denotes the broad category of disease the patient initially presented with. The ACMG guidelines were used to classify variants as either pathogenic or variant of uncertain signifi cance (VUS). N/A, not analyzed. Children’s Hospital of Wisconsin (CHW), Froedtert Hospital (FH), Medical College of Wisconsin (MCW).

Table 1. Results of WGS at the MCW Genomics Medicine Clinic for 23 Pediatric (CHW) and 2 Adult (FH) Cases.

Pediatric case # Clinical indication Variants Diagnosis

1 T cell immune defi ciency 4 pathogenic, 1 VUS No

2 Multiple congenital anomalies, lactic acidosis, leukodystrophy and seizure disorder 3 pathogenic, 11 VUS Maybe

3 Immune defi ciency 1 pathogenic, 1 VUS No

4 Leukodystrophy 3 pathogenic, 4 VUS Maybe

5 Intrauterine growth retardation, hair abnormalities, vomiting, chronic diarrhea, developmental delay, facial dysmorphism

2 pathogenic, 5 VUS Yes

6 Recurrent stroke, polymositis, chronic infl ammation, recurrent unexplained fever 5 pathogenic, 5 VUS No

7 Infantile spasms, dystonia, sensorineural hearing loss, optic nerve abnormalities 5 pathogenic, 10 VUS No

8 Ataxia, seizures, regression 1 pathogenic, 4 VUS No

9 Malignant nerve sheath tumor, plexiform neurofi broma 1 VUS No

10 Dilated cardiomyopathy with recurrent hypoglycemic events 2 VUS Maybe

11 Atypical hemolytic uremic syndrome 1 VUS No

12 Dystonia, chorea, mental retardation, retinal and neurotransmitter abnormalities 2 pathogenic, 14 VUS Maybe

13 Recurrent rhabdomyolysis 1 pathogenic, 6 VUS Yes

14 Long QT syndrome, arrhythmia, neurogenic myopathy 2 pathogenic, 5 VUS Yes

15 Seizures with combined white and grey matter degeneration 3 pathogenic, 1 VUS No

16 Methyl malonic acidemia and spherocytosis 1 pathogenic Yes

17 Congenital myofi bromatosis 1 pathogenic, 5 VUS No

18 Poor growth, vomiting, mental retardation, facial dysmorphism, seizure disorder 2 pathogenic, 2 VUS Yes

19 Connective tissue disorder, aortic root dilatation, short stature, developmental delay, hypermobility

analysis in process N/A

20 Neurological condition (microcephaly, epilepsy, mental retardation, autism) and endocrine syndrome (primary ovarian failure)

4 pathogenic, 1 VUS Maybe

21 Neurological condition (microcephaly, epilepsy, mental retardation, autism) and endocrine syndrome (primary ovarian failure)

9 pathogenic, 2 VUS Maybe

22 Metabolic condition, liver and renal failure, bilateral cataracts, short stature 3 pathogenic, 2 VUS Maybe

23 Neurological condition, neurodegeneration analysis in process N/A

Adult case #

24 Hypertension of unclear etiology (Executive Medicine Program) 2 pathogenic, 3 VUS Yes

25 Colon cancer, secondary fi nding of Marfan syndrome 1 pathogenic, 8 VUS Yes for Marfan syndrome; Maybe for cancer

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C O M M E N TA R Y “ ”to prove causality. ere is an urgent need to solve this problem. One simple solution, at least for rare diseases, is to increase sharing of sequenced human genomes (7). A recent White Paper from the Broad Institute creates a potential framework (www.broadinstitute.org/files/news/pdfs/GAWhitePaperJune3.pdf) for making this happen. Of course, many complex issues remain to be resolved, including release of clinical data from hospi-tal sites, compliance with HIPAA regulations, and informed consent. An alternative would be to share data in a federated rather than a centralized manner, which would make it easier for hospitals and clinics to share sensi-tive patient data.

RETURN OF RESULTS TO PATIENTSA key consideration is what types of data will be returned to the clinician and to the patient (or patient’s family). Once the clinic or laboratory determines what data they will return, an analysis pipeline (consisting of dif erent analysis tools, algorithms, and computational steps) can be built. However, because the data sets are so large (up to 1 terabyte per genome) the bulk of the work must be automated (computer-assisted analysis, CAA). Currently, there is no stan-dard platform, thus requiring institutions to establish their own CAA or link together a variety of commercial and open-source sof ware packages and data sets that contain information about disease-causing variants. Genomics laboratories new to the clinical arena need to identify state and local laws and hospital guidelines that af ect storage of clinical and laboratory data and samples and the types of genomic sequence data that need to be disclosed to the patient.

ere remains no clear consensus about what data must be stored from WGS and exome sequencing, nor are there clear guidelines about the storage of secondary (incidental) or tertiary data. Several groups are working on guidelines. e American College of Medical Genetics (ACMG) re-cently published guidelines regarding the return of secondary (incidental) f ndings to patients and their physicians (www.acmg.net; see also Editorial by S. Kingsmore, this issue). ese guidelines def ne what results a clinical laboratory should return to a physician ordering a test for whole-exome sequencing or WGS. e guidelines state that certain secondary results should be re-ported “without reference to patient prefer-ences” (9). ese guidelines have not been uniformly accepted (10–12) but do set the

standard that certain secondary f ndings should be returned to the patient’s physician and patient. In our opinion, the issue of the return of secondary results should be deter-mined by the physician and patient before ordering the test.

e following questions are particularly important to consider as they will have a profound impact on how the genomic medi-cine program and CAA pipelines will be de-veloped and on cost. What types of data will be returned to the patient or to the parents in the case of children? For example, should parents receive information about their child’s status for the Alzheimer’s disease-associated allele ApoE4? If the only data to be returned are directly related to the disease for which the patient is being treated, then CAA pipelines and data storage are simpli-f ed. In our clinic, the patient or parents (in the case of minors) are given the choice re-garding what type of results they would like disclosed in addition to data directly related to the patient’s illness (7). We acknowledge that this approach, to incorporate patient preferences into data return, is not universal-ly supported (13). We also of er to provide an annual follow-up clinical visit, where the pa-tient returns and we reanalyze the genomic data. If patients and parents express an in-terest, we will conf rm the types of results that they are interested in and reanalyze the data from the nucleotide-called sequence. ese choices have had a signif cant impact on our CAA pipelines and data storage deci-sions and have increased our overhead costs. Many have suggested that the easy alterna-tive is to resequence the patient’s genome in the future as sequencing costs decrease and analytical tools improve, but genome rese-quencing is not without its problems.

THE LIMITATIONS OF TECHNOLOGYTechnology is not without its limitations. ere are errors or uncertainties introduced into the sequence from the sequencing ma-chines and analytical algorithms, and there are errors in the reference data we align the new sequence against. Rosenfeld et al. report that dif erences in the generation and analy-sis of genome sequences result in a 4–14% range in the number of variants called in the same sample (14). is has implications for clinical use. If the original sequence data are not stored, it will be impossible to determine the source of error in the future. Hopefully, future storage formats will retain key data elements, enabling far less data per sample to be stored. Given the dif erences among

variant calling programs, some groups have chosen to use a combination of programs. But what should be done with the variants called by a single program, many of which are likely to be accurate (14)? In a clinical setting, each analytical process requires a documented validation step (15); whenever any process is altered, there has to be revali-dation. Our tertiary analysis platform devel-oped in house, CarpeNovo, is updated and revalidated every 6 months (a process that takes 4 to 6 weeks). We had to develop and write standard operating procedures (1192 pages) for all parts of the process in order to obtain CLIA (Clinical Laboratory Improve-ment Amendment) certif cation and CAP (College of American Pathology) accredita-tion, a legal requirement for the reporting of clinical results.

Given the challenges outlined, it may seem that WGS should be outsourced to a few expert centers. However, as the cost of WGS decreases and the speed of sequenc-ing and analysis increases, it is likely that most hospitals and diagnostic laboratories will implement WGS. Local implementation has the advantages of speed, compliant data storage, easier interactions with the clinical team, and the availability of other types of data—e.g., gene expression (RNAseq) data and genomic sequencing of the gut and skin microbiota.

CLINICAL DATA WORKFLOW AND RE-IMBURSEMENT ere is a critical, unmet need for a compre-hensive clinical and phenotype prof le for each patient that can be integrated with the variants discovered in the patient’s genome. Current electronic health records (EHRs) are not designed to handle the complex medical data for patients with rare or undiagnosed diseases, who have visited many dif erent clinicians and hospitals and have numerous clinician reports on paper, laboratory print-outs, and other communications. We have developed an in-house sof ware (ClinMiner) to integrate data from multiple sources, both paper and electronic, and to standardize the data using SNOMED CT, LOINC, and Rx-Norm ontologies. Data entry, query systems, and patient reports with timelines and charts provide the clinician with easy access to comprehensive clinical prof les. Until EHRs are designed to meet these needs, sequenc-ing groups along with their clinical partners will need to develop similar tools.

Af er variants are called, the genom-ics data must be integrated into the clinical

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workf ow (Fig. 1). Simple questions become incredibly complex, for example: (i) What results will go into the medical record? (ii) How will the report be generated? (iii) What can be billed and how will this be paid for? (iv) What is the clinical oversight for a pro-gram that incorporates genetic counselors, clinical geneticists, pathologists, clinical lab-

oratory personnel, bioinformaticians, data analysts, and the ordering clinician? In our opinion, the solution is to develop a service line that crosses departments and integrates the various personnel with the appropriate expertise to improve patient care. Develop-ing a reimbursement strategy is also a major challenge, as Medicaid, Medicare, and many

insurance companies will not pay for WGS,leaving patients or their providers with the bill. How each provider manages this chal-lenge in the face of an evolving health care system requires careful consideration. We have had some success by demonstrating that the cost of sequencing one whole ge-nome is more economical than ordering multiple genetic tests.

DEMONSTRATING AN ECONOMIC ADVANTAGEFor rare diseases and undiagnosed diseases, the economic case for WGS is relatively easy,as the patient and their family have gone from clinician to clinician, hospital to hospi-tal, looking for an answer, while accumulat-ing huge bills. What about the use of WGS for common diseases such as type 2 diabetes, heart disease, cancer, or for pharmacoge-nomic testing to determine which patients will have a benef cial or adverse reaction to a drug? Given the potential development of disease in everyone and the probabilistic nature of genomic data, there is a concern that follow-up analysis for secondary f nd-ings will increase the cost of clinical WGS. As was the case for MRI, the clinical teams, the hospitals, and the insurance companies will need to learn to balance deployment of new technologies, including WGS (16). Economic considerations should not be the dominant reason for delaying implementation of WGS in the clinic.

What about WGS for preventive care? Dis-ease prevention is not considered economical because many people have to be screened to f nd the few at risk (17). Because everyone has a risk for developing at least one disease and WGS can expand the accuracy of fam-ily history, we think that WGS is economical in preventive care. Every genome sequenced of ers value, as it provides a reference for an individual’s family, as well as for the general population. In our opinion, as medical and genomic information becomes better inte-grated, the combined data set will be of even greater value to the patient, their family, and society. However, the economic advantages of WGS still need to be clearly demonstrated, and the delay may have spurred the appeal of direct-to-consumer genetic testing.

OTHER BARRIERS TO CLINICAL DEPLOYMENTWe need to continue to explore and test how WGS f ndings can be conveyed to patients and their families and how follow-up stud-ies should be conducted. e ethical, legal,

Fig. 1. The long and winding road. Shown is the linear fl ow for a patient undergoing WGS in our genomic medicine clinic. Patients can enter the program at several points. A typical patient is re-ferred by their clinician or is already in our hospital system. The fi rst steps are collecting data from their records, a visit (outpatient or inpatient), genetic counseling, and discussion and determina-tion of what data they would like returned to them. Once the patient has consented to clinical care, their genome is sequenced. Subsequent analysis focuses on the primary clinical reason the patient was admitted. Any secondary fi ndings that the patient has requested are returned later. We then invite patients to come back annually for clinical follow-up. Ongoing care depends on the clinical presentation, severity of symptoms, and the outcome of our assessment. We also allow patients to enter the system with their own genome sequence in hand as long as the sequence was generated in a CLIA/CAP-accredited laboratory.

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C O M M E N TA R Y “ ”and social implications could be limiting factors for the general uptake of genomic medicine and require considerable atten-tion. Early reports from direct-to-consumer genetic testing (18) show that there has not been extensive psychological harm done by the information provided to customers. But will these f ndings hold, particularly for people who have not actively pursued results from their genome, unlike those us-ing direct-to-consumer testing. Consider-ing the known gaps in existing legislation (19), uncertainty remains about the ways in which life, disability, and long-term care insurers might use genetic information. Fi-nally, privacy concerns legitimized in recent publications (20) require additional atten-tion when contextualizing genomic data as “anonymous.” Engaging the public is an es-sential element for the success of genomic medicine. Public conf dence regarding the management of genomic data and clarity regarding how such data can be used and shared will continue to be crucial as adop-tion of WGS increases.

Becoming a fully integrated genomic medicine clinic has many steps within care delivery that are specif c to each institu-tion, such as departmental boundaries, lo-cal politics, or silos that could be the big-gest barriers to implementation. Education of providers about the use of genomic data is also a challenge. Although we have estab-lished a fully integrated genomic medicine clinical program, not every patient with a rare disease will benef t. We have had our share of successes (27% successful diagno-ses), potential diagnoses (34%), and fail-ures (39%).

We believe that WGS will improve the practice of medicine. Yet, despite the clear advantages it provides over other tests, a ge-nome sequence is still just another data set. What we can extract from this data set will require further integration of genomic and phenotypic data and clinical trial results. Our f rst 26 clinical cases have been vital for def n-

ing and ref ning our program. We encourage other institutions to set up their own genomic medicine clinics because there is clear medi-cal value in the human genome sequence that can be excavated to improve the diagnosis and treatment of human disease. e use of WGS in the clinic may still be debated, but we challenge the fence sitters to do 20 cases of their own and see whether WGS adds value to clinical decision-making.

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Citation: H. J. Jacob, K. Abrams, D. P. Bick, K. Brodie, D. P. Dimmock, M. Farrell, J. Geurts, J. Harris, D. Helbling, B. J. Joers, R. Kliegman, G. Kowalski, J. Lazar, D. A. Margolis, P. North, J. Northup, A. Roquemore-Goins, G. Scharer, M. Shimoyama, K. Strong, B. Taylor, S.-W. Tsaih, M. R. Tschannen, R. L. Veith, J. Wendt-Andrae, B. Wilk, E. A Worthey, Genomics in clinical prac-tice: Lessons from the front lines. Sci. Transl. Med. 5, 194cm5 (2013).

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Genomics in Clinical Practice: Lessons from the Front Lines

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DOI: 10.1126/scitranslmed.3006468, 194cm5194cm5.5Sci Transl Med

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REFERENCES

http://stm.sciencemag.org/content/5/194/194cm5#BIBLThis article cites 19 articles, 3 of which you can access for free

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