Abstract
Background:
Exome and genome sequencing have been demonstrated to increase diagnostic yield in pediatric populations, improving treatment options and providing risk information for relatives. There are limited studies examining the clinical utility of these tests in adults, who currently have limited access to this technology.
Methods:
Patients from adult and cancer genetics clinics across Toronto, Ontario, Canada were recruited into a prospective cohort study evaluating the diagnostic utility of exome and genome sequencing in adults. Eligible patients were ≥18 years of age and suspected of having a hereditary disorder but had received previous uninformative genetic test results. In total, we examined the diagnostic utility of exome and genome sequencing in 47 probands and 34 of their relatives who consented to participate and underwent exome or genome sequencing.
Results:
Overall, 17% (8/47) of probands had a pathogenic or likely pathogenic variant identified in a gene associated with their primary indication for testing. The diagnostic yield for patients with a cancer history was similar to the yield for patients with a non-cancer history [4/18 (22%) vs. 4/29 (14%)]. An additional 24 probands (51%) had an inconclusive result. Secondary findings were identified in 10 patients (21%); three had medically actionable results.
Conclusions:
This study lends evidence to the diagnostic utility of exome or genome sequencing in an undiagnosed adult population. The significant increase in diagnostic yield warrants the use of this technology. The identification and communication of secondary findings may provide added value when using this testing modality as a first line test.
INTRODUCTION
Genetic disorders contribute a significant proportion of morbidity and mortality, cumulatively affecting up to 1-2% of adults[1]. This range may be an underestimate, given that adult genetic diseases can be challenging to diagnose because they present later in life, are often overlooked in the differential diagnosis, and have variable penetrance and clinical features that can overlap with common adult co-morbidities[2–4]. Standard investigations consist of multiple tests and procedures, costing the healthcare system tens of thousands of dollars per patient[5,6]. Despite extensive testing, many patients remain undiagnosed or misdiagnosed and do not receive appropriate management.
Genomic sequencing technologies have been largely successful in diagnosing rare disorders in pediatrics, where they have increased diagnostic yield up to 30-70% in populations with suspected forms of hereditary neurological diseases and seizures[7,8]. Exome sequencing (ES) and genome sequencing (GS) have been shown to alter medical management by informing treatment options for patients and providing reproductive risk information for their families[5,9,10]. The few studies that have assessed ES in adults have reported lower diagnostic yields, ranging from 18% to 27%[11–13] and provide limited evidence on the clinical utility of results.
In Canada, clinical ES is not currently offered by laboratories, lagging behind the United States (US)[14–16]. In the province of Ontario, patients must receive approval for clinical ES through the Ministry of Health and Long Term Care (MOHLTC) on a case by case basis; once approved, testing is paid for by the MOHLTC and performed out of province. The limited evidence of clinical utility of ES and GS in adults has, up until recently, led to reduced access to this technology in this population.
Thousands of Canadian adults are seen annually by medical geneticists, many of whom will not receive a diagnosis using current genetic testing practices and may have no further options for additional genetic investigations. These patients may benefit from ES or GS, which may provide a diagnosis and inform targeted management. We sought to apply ES/GS in a clinically heterogeneous (e.g. cardiovascular, neurological) adult population who were not eligible for clinical ES. We report on the diagnostic yield of ES/GS in this population.
METHODS
Patient Recruitment
We recruited patients from four genetics clinics in Toronto, Ontario; The Fred A. Litwin Family Centre in Genetic Medicine, the Familial Breast Clinic at the Marvelle Koffler Breast Centre, Princess Margaret Cancer Centre, and the Familial Gastrointestinal Cancer Registry. Recruitment began in March 2013 and ended in November 2018. Patients ≥18 years with a suspected hereditary disorder but prior negative or inconclusive genetic test results (e.g. gene panels) were eligible and identified by their clinician. Inclusion of relatives, affected or unaffected, was recommended but not required.
Consent was obtained for access to relevant data including contact information, demographics, family history (pedigree), medical records related to the primary indication, and to conduct ES or GS and analysis. Participants also consented to having their sample, genomic data and health information stored and potentially shared with other researchers in controlled-access databases and also informed that general research results would be available in open-access databases. Participants were given the option to consent for re-contact for return of secondary findings (SF) and participation in future studies. They also completed a questionnaire that evaluated preferences for receiving SF. A blood sample was obtained at time of consent if an aliquot of DNA was unavailable.
Sequencing and Analysis
ES was performed at one of several sequencing platforms in downtown Toronto. All sequencing was performed using next generation sequencing on the Illumina HiSeq 2500 platform (Illumina, San Diego, California, USA). GS was carried out at The Centre for Applied Genomics beginning in 2018. Bioinformatic and data processing from the raw sequence reads were analyzed using the in-house pipeline developed by JLE at MSH (Mount Sinai Hospital). The raw data was also analyzed using third party software - the Variantyx Genomic Intelligence platform V. 2.6.0.2 (https://www.variantyx.com) that uses proprietary algorithms for analysis of sequence variants. Reanalysis from raw data for inconclusive cases was performed for a subset of cases by the Broad Institute. See supplementary information for detailed information on sequencing and capture methods, data processing and analysis tools (online supplementary file 1).
Reporting
A written report was generated for each proband and issued to the referring clinician who returned results to the patient. The report included variants classified as pathogenic, likely pathogenic, or of uncertain significance (VUS) occurring in genes that matched or were related to the clinical phenotype(s), using ACMG/AMP (American College of Medical Genetics and Genomics/Association for Molecular Pathology) guidelines[17]. Cases were classified as positive if the variant identified was likely pathogenic or pathogenic or as inconclusive if a VUS was identified or only one pathogenic/likely pathogenic variant was identified in a gene associated with autosomal recessive (AR) disease. Alternatively, a report was called inconclusive if a pathogenic/likely pathogenic variant was identified in a gene that was not considered diagnostic or related to the patients’ phenotype.
Secondary results
We did not intentionally analyze data for SF. However, if a pathogenic or likely pathogenic variant was identified in a gene within the phenotypic filters but did not directly match the presentation, the results were reported as SF to patients who consented to receiving them (online supplementary table 1). Secondary findings were not limited to the 59 genes recommended by the ACMG[18]. As part of the study, patients also completed a questionnaire on their preferences for receiving SF (online supplementary file 2). They were asked about their interest in receiving SF for diseases with varying levels of penetrance (e.g. <5%, 5-10% and so on) and types of genetic variants/conditions.
Costs
Costs for prior genetic investigations were obtained from MOHLTC documents in clinical charts. If unavailable, laboratories were contacted to obtain the cost of the specific test.
RESULTS
Cohort enrollment and description
In total, 47 probands and 34 relatives were consented, underwent sequencing and received results. ES was performed on 39 probands and GS on 8 probands. GS became available in 2018 and offered to families who were recommended for GS by their referring clinician.
Approximately 77% (36/47) of the probands were female (mean age 47.32). Patients had a wide variety of indications. The most commonly observed phenotypes included cancer, neurological, and cardiovascular/connective tissue abnormalities (table 1 and figure 1).
Table 1:
Clinical characteristics of probands
| Characteristic | No. of probands (%) |
|---|---|
| Sex | |
| Male | 11 (23%) |
| Female | 36 (77%) |
| Age at enrollment | |
| 18-25 | 1 (2.1%) |
| 26-35 | 12 (26%) |
| 36-44 | 9 (19%) |
| >45 | 25 (53%) |
| Main presentation | |
| Cancer | 18 (38%) |
| Neurological | 9 (19%) |
| Connective tissue | 6 (13%) |
| Cardiovascular | 3 (6.4%) |
| Musculoskeletal | 3 (6.4%) |
| Cerebrovascular | 2 (4.3%) |
| Ophthalmological | 1 (2.1%) |
| Renal | 1 (2.1%) |
| Multiple congenital anomalies and gastrointestinal issues | 1 (2.1%) |
| Metabolic | 1 (2.1%) |
| Endocrinological | 1 (2.1%) |
| Immunological | 1 (2.1%) |
| Type of test | |
| Exome | 39 (83%) |
| Genome | 8 (17%) |
| Result | |
| Positive | 8 (17%) |
| Inconclusive | 24 (51%) |
| Negative | 15 (32%) |
| Secondary | 10 (21%) |
Figure 1:
Distribution of primary results by phenotype
In 23 cases, only the proband was sequenced; proband plus one first-degree relative (16 families), trios (6 families) or quartet families (2 families). Out of the 34 relatives included in the study, 22 were affected and 12 were unaffected. On average, 49 760 variants were identified per proband in the ES cases (online supplementary tables 1 and 2).
Diagnostic yield
Overall, 17% (8/47) of probands who underwent ES or GS had a pathogenic or likely pathogenic variant identified in a gene that was consistent with their primary indication (t able 2). The correlation between the pathogenic or likely pathogenic variant and the phenotype was confirmed with the referring clinician.
The diagnostic yield for patients with a cancer history was similar to the yield in patients with a non-cancer history (22% or 4/18 vs. 14% or 4/29) (p=0.46, Fisher’s exact test).
The majority of the findings were associated with pathogenic variants in autosomal dominant (AD) genes (seven out eight positive cases). One patient had one likely pathogenic variant and one VUS in COL6A2, which is associated with autosomal dominant and recessive presentations. Among the nine pathogenic or likely pathogenic variants, four were expected to produce a premature stop codon due to a frameshift or nonsense variant, one patient harbored a variant in the canonical splice donor site and the other four corresponded to missense variants classified as pathogenic or likely pathogenic variants. Of note, 7/8 positive cases were identified by ES and only 1/8 was identified through GS (SCN5A; c.3823G>A), which was a missense variant and therefore would have been identified by ES.
The results from our study can have a broad range of clinical management implications for the patients and their relatives, such as surgical recommendations, regular imaging, reproductive counselling, and medication and diet changes (online supplementary table 3).
Inconclusive cases
Inconclusive cases were defined as those in which a VUS was identified in a gene related to the primary indication or one pathogenic or likely pathogenic variant identified in a gene associated with AR disease. In total, 24 of 47 (51%) probands had an inconclusive result (online supplementary tables 4 and 5).
Secondary or incidental findings
SF were defined as likely pathogenic or pathogenic variants in genes not associated with the primary indication. Ten patients (21%) had a total of 18 SF, of which 3/18 (17%) were in genes associated with diseases considered to be medically actionable (LDLR, APOB and MUTYH) by the ACMG (table 3)[18].
Table 3:
Summary of secondary findings
| ID | Test indication | Sex | Gene; transcript | Variant (cDNA, protein) | Zygosity | Relatives | ACMG class | OMIM phenotypes | |
|---|---|---|---|---|---|---|---|---|---|
| #T | #P | ||||||||
| 019 | Achalasia, HL, corneal/retinal anomalies, delayed growth/puberty, gastric dysmotility, dysmorphism | F | APOB (NM_000384) | c.1315C>T, (p.Arg439*) | Het | 2 | 1 | P | Familial hypercholesterolemia 2 (AD); hypobetalipoproteinemia (AR) |
| 029 | Carotid artery aneurysm; early onset osteoarthritis; scoliosis; widened scars; soft and hyperextensible skin; breast cysts | F | COL7A1 (NM_000094) | c.6501G>A, (p.Pro2167Pro) | Het | 1 | 1 | LP | EBD inversa (AR); EBD, Bart type (AD); EBD, localisata variant; epidermolysis bullosa dystrophica (AR/AD); epidermolysis bullosa pruriginosa (AR/AD); epidermolysis bullosa, pretibial (AD/AR); toenail dystrophy, isolated (AD); transient bullous of the newborn (AR/AD) |
| 031 | Developmental delay, seizures, microcephaly | F | LDLR (NM_000527) | c.1085A>C, (p.Asp362Ala) | Het | 1 | 0 | LP | Familial hypercholesterolemia 1 (AD); LDL cholesterol level QTL2 (AD) |
| 037 | Polyps; epithelioid inflammatory myofibroblastic sarcoma | F | GJB2 (NM_004004) | c.101T>C, (p.Met34Thr) | Het | 1 | 0 | P(RP) | Bart-Pumphrey syndrome (AD); Autosomal dominant deafness 3A (AD); Autosomal recessive deafness 1A (AR/DD); Hystrix-like ichthyosis with deafness (AD); Keratitis-ichthyosis-deafness syndrome (AD); Keratoderma, palmoplantar, with deafness (AD); Vohwinkel syndrome (AD) |
| HADHA (NM_000182) | c.1528G>C, (p.Glu510Gln) | Het | 1 | 0 | P | Long-chain 3-hydroxyacyl-CoA dehydrogenase deficiency (AR); Acute fatty liver of pregnancy (AR); Maternal HELLP syndrome of pregnancy (AR); Trifunctional protein deficiency (AR) | |||
| HFE (NM_000410) | c.845G>A, (p.Cys282Tyr) | Het | 1 | 1 | P (RP) | Hereditary haemochromatosis (AR); Susceptibility to Alzheimer disease (AD); Susceptibility to Porphyria cutanea tarda (AR/AD); Susceptibility torphyria variegata (AD) | |||
| 067 | Clinical diagnosis of Albright hereditary osteodystrophy; pseudpseudohypoparathyrodism; tachycardia; repetitive movements; developmental delay; hypotonic in neonatal period | F | FANCA (NM_000135) | c. 3788_3790 (p.Phe1263del) | Het | 1 | 1 | LP | Fanconi anemia, complementation group A (AR) |
| CNGB3 (NM_019098) | c. 1148del (p.Thr383Ilefs*13) | Het | 1 | 1 | P | Achromatopsia 3 (AR) | |||
| 073 | Undifferentiated connective tissue disorder or possibly fibromuscular dysplasia; query LDS or vascular EDS | F | CEP164 (NM_001271933) | c.381dup (p.Lys128Glnfs*77) | Het | - | - | P | Nephronophthisis 15 (AR) |
| FLG (NM_002016) | c.7487del (p.Thr2496Asnfs*104) | Het | P | Ichthyosis vulgaris (AD); Susceptibility to atopic dermatitis 2) | |||||
| 077 | Premenopausal osteoporosis with compression fractures; pulmonary issues; severe progressive scoliosis; AVM; unilateral HL | F | UCP3 (NM_003356) | c.427C>T; (p.Arg143*) | Het | - | - | LP | Severe obesity with type II diabetes (AR/AD, Multifactorial) |
| 079 | Adult onset progressive ataxia; tachycardia; difficulty maintaining balance; shortness of breath, chest pain; sweating; blurred and double vision | F | PEX14 (NM_004565) | c. 298+1G>C | Het | - | - | P | Peroxisome biogenesis disorder 13A, Zellweger syndrome (AR) |
| 081 | Neurogenic bladder; fibromyalgia; Crohn’s; IBS; Celiac | F | MUTYH (NM_001128425) | c.536A>G, (p.Tyr179Cys) | Het | - | - | P | Adenomas, multiple colorectal (AR), somatic gastric cancer (SMu) |
| c.1187G>A, (p.Gly396Asp) | Het | P | |||||||
| ALDOB (NM_000035) | c.178C>T (p.Arg60*) | Het | LP | Fructose intolerance (AR) | |||||
| GJB2 (NM_004004) | c.35delG, (p.Gly12Valfs*2) | Het | P | Bart-Pumphrey syndrome (AD), Autosomal dominant deafness 3A (AD); Autosomal recessive deafness 1A (AR), Hystrix-like ichthyosis with deafness (AD), Keratitis-ichthyosis-deafness syndrome (AD), Keratoderma, palmoplantar, with deafness (AD), Vohwinkel syndrome (AD | |||||
| SLC26A4 (NM_000441) | c.626G>T, (p.Gly209Val) | Het | P | Autosomal recessive deafness 4, with enlarged vestibular aqueduct (AR); Pendred syndrome (AR) | |||||
| 084 | Early onset strokes | M | ERCC3 (NM_000122) | c.325C>T (p.Arg109*) | Het | 1 | 1 | LP | Trichothiodystrophy 2, photosensitive (AR); xeroderma pigmentosum, group B (AR) |
| SLC2A2 (NM_000340) | c.901C>T (p.Arg301*) | Het | 1 | 1 | LP | Fanconi-Bickel syndrome (AR); diabetes mellitus, noninsulin-dependent (AD) | |||
a, affected; AVM, arteriovenous malformation; EBD, Epidermolysis bullosa dystrophica; HL, hearing loss; IBS, irritable bowel syndrome; LDL, Low-density lipoprotein; LDS, Loeys—Dietz syndrome; p, positive; RP, reduced penetrance; T, tested.
Cancer cases
At the initiation of this study (2013), multigene cancer panels were not yet standard of care or readily available to Ontario patients. For families with a history suggestive of a hereditary cancer syndrome, research ES was offered if first-tier testing was negative or inconclusive. Research ES was available for cancer patients until March 2017 when panels became clinically available in Ontario.
ES for 18 families with a cancer history revealed a causative pathogenic variant in four families, a yield of 22% (table 2). Two families with a history of GI cancers were identified to have an MSH6 variant (c.3739_3742delACTC)[19] and a POLE variant (c.1372T>A) respectively, and two breast cancer families had an ATM variant (c.1065+1G>T) and MSH6 variant (c.3959_3962del) respectively.
Table 2:
Summary of cases with pathogenic or likely pathogenic variants consistent with phenotype
| ID | Test indication | Sex | Age* | Gene; transcript | Variant (cDNA, protein) | Zygosity | Relatives | ACMG class | OMIM phenotypes | |
|---|---|---|---|---|---|---|---|---|---|---|
| #T | #P | |||||||||
| 004 | Small bowel cancer, ampullary cancer | F | 69 | MSH6 (NM_000179) | c.3739_3742delACTC, (p.His1248Thrfs*4) | Het | 1 (a) | 1 (a) | P | Hereditary nonpolyposis colorectal cancer, type 5 (AD); familial endometrial cancer; mismatch repair cancer syndrome (AR) |
| 007 | Colorectal cancer, mixed polyposis | F | 48 | POLE (NM_006231) | c.1372T>A, (p.Tyr458Asn) | Het | 1 (a) | 1 (a) | LP | Susceptibility to colorectal cancer type 12 (AD); IMAGE-I syndrome (AR); FILS syndrome (AR) |
| 014 | Breast cancer | F | 41 | ATM (NM_000051) | c.1065+1G>T | Het | - | - | LP | Ataxia-telangiectasia (AR); lymphoma, B-cell non-Hodgkin, somatic; lymphoma, mantle cell, somatic; T-cell prolymphocytic leukemia, somatic; susceptibility to breast cancer (AD, Smu) |
| 021 | Breast cancer (MSS and IHC intact) | F | 36 | MSH6 (NM_000179) | c.3959_3962del, (p. Ala1320Glufs*6) | Het | - | - | P | Hereditary nonpolyposis colorectal cancer, type 5 (AD); familial endometrial cancer; mismatch repair cancer syndrome (AR) |
| 031 | Developmental delay, seizures, microcephaly | F | 28 | KCNQ2 (NM_172107) | c.1687G>A, (p.Asp563Asn) | Het | 1 | 0 | P | Early infantile epileptic encephalopathy type 7 (AD); myokymia (AD); benign neonatal seizures type 1 (AD) |
| 039 | Periodontal EDS | F | 69 | C1S (NM_001734) | c.949_951delGTG, (p.Val317del) | Het | 1 (a) | 1(a) | P | Ehlers-Danlos syndrome periodontal type 2 (AD); C1s deficiency |
| 057 | Clinical diagnosis of Charcot Marie Tooth disease type 2 | F | 55 | COL6A2 (NM_001849.3) | c.2417 G>A, (p.Cys806Tyr) | Het | - | - | VUS | Congenital myosclerosis(AR); Ullrich congenital muscular dystrophy (AR/AD); Bethlem myopathy 1 (AR/AD) |
| c.1273_1280 dupCGCAGGGG (p. Asp428Alafs*120) | Het | LP | ||||||||
| 084 | Early-onset strokes | M | 29 | SCN5A (NM_198056) | c.3823G>A, (p.Asp1275Asn) | Het | 1 (a) | 1(a) | P | Familial atrial fibrillation type 10 (AD); Brugada syndrome 1 (AD); dilated cardiomyopathy 1E (AD); nonprogressive heart block, type 1A (AD); Long QT syndrome-3 (AD); sick sinus syndrome 1(AR); familial ventricular fibrillation type 1; susceptibility to sudden infant death syndrome (AR) |
Age at initial referral.
a, affected; p, positive; T, tested
Non-cancer cases
Results are described below and presented in table 2 and online supplementary files and tables.
Family 31
The proband in family 31 was a 30-year-old female with early infantile-onset seizure disorder, global developmental delay and multiple other abnormalities (see online supplementary table 2 and online supplementary file 3 for more details). Previous workup had been extensive but uninformative, and included a 170-gene neurodevelopmental disorders panel.
ES identified a previously described heterozygous pathogenic variant in KCNQ2, c.1687G>A (p. Asp563Asn) in the proband. The variant was not identified in the proband’s mother (her father was unavailable for testing).
Pathogenic variants in KCNQ2 are associated with a spectrum of phenotypes ranging from benign familial neonatal epilepsy (BFNE) to early infantile or neonatal epileptic encephalopathy (EIEE or NEE)[20]. Features include encephalopathy which may result in moderate to severe global developmental impairment in addition to swallowing difficulties, strabismus, nystagmus, recurrent respiratory infections, microcephaly, and dysmorphic features[20,21]. Although the KCNQ2 variant did not explain all of the proband’s features, it explained most and is likely contributory to her history. Of note, the neurodevelopmental disorders panel conducted in 2015 did not include KCNQ2.
Family 39
Family 39 comprised of two sisters in their 60s with a personal and family history suggestive of periodontal Ehlers-Danlos syndrome (pEDS, formerly EDS type VIII). Clinical features included skin fragility with atrophic scars and easy bruising, loss of all teeth in the third or fourth decade, and gastrointestinal symptoms (irritable bowel syndrome, colitis). The family history was consistent with autosomal dominant inheritance. Both sisters underwent an EDS panel that included 18 genes associated with various types of EDS, which was uninformative.
ES identified a heterozygous pathogenic variant in C1S, c.949_951delGTG (p. Val317del) in both sisters, confirming the diagnosis of pEDS. Of note, a variant that results in the same protein change was previously reported in the literature and segregated in four affected relatives with pEDS with clinical features consistent with these patients[22].The C1S gene had been not associated with pEDS when the sisters had undergone panel testing in 2016, and therefore C1S was not on the EDS panel.
Family 57
The proband in family 57, age 55, had a clinical diagnosis of Charcot-Marie Tooth disease-axonal neuropathy type. She reported a history of muscle issues beginning in childhood, severe hypotonia, and congenital dislocation of the hip. Over the course of her workup, she revealed that she had undergone an electromyography (EMG) in childhood, which revealed chronic neurogenic process along with a strong predominant myopathic process. These findings suggested a congenital myopathy. The proband also had a history of aortic dilatation and other features including inguinal hernias and subluxation that were suggestive of a connective tissue disorder. On testing of a panel of connective tissue genes, she was found to carry a variant of unknown clinical significance in COL3A1 (c.2702A>G). Skin biopsy was arranged for biochemical collagen analysis and the results were negative, thus ruling out a diagnosis of vascular-type EDS. Extensive genetic testing including an aortic root dilation panel and spinal muscular atrophy panel were all uninformative.
ES initially revealed a variant of uncertain significance, c.2417 G>A (p.Cys806Tyr) in the COL6A2 gene. Follow-up clinical testing identified a likely pathogenic variant, c.1273_1280 dupCGCAGGGG (p. Asp428Alafs*120) in COL6A2, which was filtered out due to a low-quality score but found upon re-inspection of exome data with the Variantyx software.
Pathogenic variants in COL6A2 are associated with collagen type VI-related disorders, which represent a clinical spectrum of disorders that range from Bethlem myopathy at the mild end and Ullrich congenital muscular dystrophy at the severe end, both of which can display dominant or recessive inheritance. The proband’s history appeared consistent with a mild form of Ullrich congenital muscular dystrophy, which is characterized by congenital weakness, hypotonia, proximal joint contractures and hyperlaxity of distal joints. However, she did not report a history of joint contractures.
Family 84
Family 84 had a striking history of early-onset strokes. The proband, age 29 presented with a stroke at age 27. The proband’s brother had 2 strokes, at ages 28 and 33. Their father and paternal uncle both had a history of multiple strokes before age 50. The family was of Ashkenazi Jewish ancestry.
Multiple investigations had been conducted in the family, including NOTCH3 and TREX1 sequencing and a 10-gene hemiplegia/stroke panel – all of which was uninformative.
The affected proband and paternal uncle underwent GS, which identified a shared heterozygous pathogenic variant in SCN5A, c.3823G>A, (p.Asp1275Asn). Follow-up testing of the proband’s affected brother and father confirmed the presence of this variant in them. Pathogenic SCN5A variants are associated with varying phenotypes, ranging from dilated cardiomyopathy to Brugada syndrome. SCN5A variants are also associated with atrial fibrillation, which increases the risk of strokes. This specific variant has been described previously in a 14-year-old male with atrial arrhythmia and a stroke[23]. Although none of the four relatives described above have been documented to have atrial arrhythmia, most have first degree atrioventricular block with or without left atrial enlargement. Based on our current knowledge, this variant likely explains the family history of early-onset strokes.
Secondary findings cases (non-primary findings)
Family 31
The proband in family 31 (described above) was identified to have a likely pathogenic variant in LDLR, c.1085A>C (p. Asp362Ala), that was not detected in her mother. Pathogenic variants in LDLR are associated with familial hypercholesterolemia, and is included in the medically actionable genes recommended for return in clinical ES by ACMG[18]. This SF suggests that the proband is at significantly increased risk to develop severely elevated LDL cholesterol levels and subsequent cardiovascular sequelae. The early identification could allow for proper management and improved clinical outcomes for the proband, as well as cascade testing for her siblings and other relatives.
Family 37
The proband was identified as having three SF; a pathogenic variant in each GJB2, HADHA, and HFE. Therefore, she is a carrier of non-syndromic hearing loss and deafness (DFNB1), Long-chain 3-hydroxyacyl-CoA dehydrogenase deficiency and hereditary hemochromatosis. These results may have implications for family planning for the proband and relatives.
Family 81
ES identified multiple SF in the proband, including two trans pathogenic variants in the MUTYH gene, associated with MUTYH-adenomatous polyposis.
Of note, her presenting features included a history of GI issues, namely IBS, Celiac and Crohn’s disease with recurrent episodes of fevers, vomiting, diarrhea, abdominal cramping and hand swelling. Given that colonic polyps may cause some of these symptoms, her GI history may be explained by the MUTYH variants. Further investigations, such as a colonoscopy, could provide additional information. She was also identified to be a carrier of the common 35delG variant in GJB2, Pendred syndrome (SLC26A4) and fructose intolerance (ALDOB).
Diagnostic Odyssey and Costs
The number of prior genetic investigations for the eight diagnosed cases ranged from 2 to 11 tests, at an average cost of $9178.14 per case (total cost of $73 425.12 CAD) (online supplementary table 6). This cost is higher than costs reported for paediatric populations and likely reflective of adult patients undergoing genetic investigations[5]. For the cohort of diagnosed cases, we estimate that the cost of ES would have been roughly $2937.50 CAD per patient for exome or $4500 CAD for genome (estimated using costs from the literature and commercial laboratories).
Although we did not conduct a full economic analysis, our results suggest that the use of a single test, ES or GS in adults could identify a diagnosis. This could reduce the number of tests per patient and the time to diagnosis, representing a potentially a cost-effective approach.
DISCUSSION
Using ES or GS in a population of adults with suspected hereditary conditions, we observed a diagnostic yield of 17%, with a similar yield detected in cancer cases compared to non-cancer cases [22% vs. 14%]. The overall diagnostic yield is comparable to the yield of ES previously detected in an adult population[12] and as anticipated, lower than the yield reported in paediatrics[24,25].
Posey et al. conducted a retrospective study of 486 adults with heterogeneous presentations who had undergone ES[12]. A molecular diagnosis was identified in 85 patients, giving a yield of 17%, comparable to our results. It is important to note that there are some methodological and population distinctions between our study and Posey et al. Unlike our sample, ES was performed on the proband only for the entire cohort in Posey et al. Additionally, more than half of their participants (52%) were between the ages of 18 and 30 years. Whereas in our study, less than a third of our participants (13/47 or 28%) were between the ages of 18 and 35 and more than half (25 or 53%) were over 45. Another key distinction is in the distribution of clinical presentations of the referrals. While cancer referrals were rare (47/486) in Posey el al., 18/47 or 38% of our participants were referred for a cancer history. With regards to the non-cancer referrals, our population was mainly composed of patients with connective tissue/cardiovascular or neurological abnormalities, whereas abnormalities of the nervous system, musculature, and skeletal system were the most frequent phenotype classes in Posey et al. In our sample, diagnostic yield was highest for cerebrovascular abnormalities, cancer, and neurological phenotypes (1/2 or 50%, 4/18 or 22%, and 2/9 or 22%, respectively). In Posey et al., the highest yield was reported in patients with neurodevelopmental abnormalities (28%, 53/191) whereas the yield for cancer was less than 5%.
With regards to hereditary cancers, gene panels now offered routinely in Ontario may render ES less useful in this population. For example, MSH6, POLE and ATM are typically included in comprehensive cancer panels, and therefore the pathogenic variants detected in our study would likely be identified by standard of care testing if the families were to undergo investigations today. However, these families either previously tested negative for standard of care testing or were not eligible for testing at the time of evaluation. ES was able to fill a diagnostic gap. For example, family 21 with the MSH6 variant would not have met criteria for Lynch syndrome testing at the time based on family history alone[19].
Currently, genetic testing for most adult patients with a suspicion of a hereditary condition consists of phenotype-driven gene panels. Panels have been established to be cost-effective approaches in various clinical settings, including hereditary cancers and epilepsy, among others[26–28]. However, many patients undergoing investigations remain undiagnosed. All the cases with positive results in our study would not have been identified by standard genetic testing available in Toronto at the time of analysis.
The decline in ES/GS costs in combination with the improvements in quality, accuracy and uniformity in coverage make a strong case for the transition from panels to ES and eventually GS. However, the large-scale adoption for routine clinical testing would have to consider diagnostic yield, turnaround time and the technical limitations of each test. In general, ES is cheaper, requires less analysis and comes with a shorter turnaround time than GS. However, ES is limited in its ability to detect large insertions and deletions, deep intronic mutations and trinucleotide repeat expansions. For these reasons, GS is expected to have higher diagnostic yield; [29] however, initial data suggests that increase may be modest[29]. Whether GS will indeed have a higher yield and be cost-effective remains to be established. These questions deserve further consideration.
Approximately half of the probands had VUS identified. Over time, improvements in our understanding of human disease genes and pathogenicity may lead to reclassification of these variants. There is growing literature suggesting that reanalysis may enhance the diagnostic yield of ES, lead to management changes for patients and that it may be cost-effective. However, the process requires significant resource investment on the part of the laboratory professionals and clinicians, who may have to recontact patients in some cases[30]. Reanalysis and recontact of patients will need to be balanced with other clinical demands and priorities. Furthermore, improvements in conveying phenotype information from the clinic to the diagnostic laboratory, in addition to the application of data sharing modalities, may further increase the yield.
Overall, we anticipate these results will have direct medical consequences for patients and their relatives. In addition to providing a molecular diagnosis and triggering medical management changes, results can inform reproductive risk for relatives. Thus, this study provides evidence for the clinical utility of ES and GS for adults and therefore offers support for the use of ES or GS in this population.
SF from ES provide an opportunity to inform disease prevention for patients and their relatives, preventing significant morbidity. All of the SF identified in our study could have implications for the probands and relatives (e.g. family planning). More than one fifth of our participants (10/47) had a SF, with 6.4% having a medically actionable result, as defined by ACMG[18]. The frequency of actionable findings is consistent with the literature, where the frequency of actionable variants is in the range of 1-4%. Notably, SF were not actively sought for most of the families in our study- in which case, the frequency may have differed. Across the literature, the frequency of SF depends largely on the context, population and list of genes used, with frequencies in the lower end of the range identified when only the ACMG list is used[31–34].
A major limitation in this study was sample size and clinical heterogeneity. This limited our ability to determine the diagnostic yield by phenotype. A larger cohort, especially of non-cancer patients is needed to further evaluate yield across different disease areas and to better understand the clinical utility of ES or GS for adults and guide recommendations for eligibility.
ES and GS were also offered late in the diagnostic odyssey; most patients had undergone multiple investigations at the time of referral, including extensive genetic and biochemical testing. Therefore, the yield of GS and ES may indeed be higher and potentially more cost-effective if offered earlier in the diagnostic trajectory for adult patients. In addition, bias of ascertainment is likely to have factored in to the overall yield because patients were recruited at the discretion of the referring physician; if the patient had prior clinical ES testing requests rejected from the MOHLTC and if exhaustive testing was uninformative.
CONCLUSION
To our knowledge, this is one of the first studies investigating ES and GS in a cohort of adult patients with heterogeneous indications in Canada. From our early experience, ES or GS for adults was able to provide a molecular diagnosis for a proportion of patients, albeit less than is observed in paediatric populations. However, in many cases, the results ended a long and expensive diagnostic odyssey. In summary, ES or GS in this cohort of adults with suspected hereditary conditions led to an increased diagnostic yield over standard-of-care genetic testing and may support widespread adoption of this technology. Future studies should also focus on quantifying costs and assess the cost-effectiveness of ES and GS in adult populations.
Supplementary Material
Acknowledgments:
We would like to thank the staff at the Centre for Applied Genomics for supporting this study.
Funding:
JLE was funded by the McLaughlin Centre (grant #MC-2012-13, #MC-2014-11-1, and MC-2017-12) and CIHR- Champions of Genetics: Building the Next Generation Grant (FRN: 135730). CL was a visiting scientist at Pathology and Laboratory Medicine, Mount Sinai Hospital and Women’s College Hospital thanks to Salvador Madariaga (PRX18/00267) and M-BAE (BA18/00018) grants (Spanish Government).
Analysis was provided by the Broad Institute of MIT and Harvard Center for Mendelian Genomics (Broad CMG) and was funded by the National Human Genome Research Institute, the National Eye Institute, and the National Heart, Lung and Blood Institute grant UM1 HG008900 to Daniel MacArthur and Heidi Rehm.
Footnotes
Competing Interests: None.
‘Ethics Approval: This work was approved by the Mount Sinai Hospital Research Ethics Board (#12-0222-E)
References
- 1.Giampietro PF, Greenlee RT, McPherson E, Benetti LL, Berg RL, Wagner SF. Acute health events in adult patients with genetic disorders: the Marshfield Epidemiologic Study Area. Genet Med 2006;8:474–90.doi:10.109701.gim.0000232479.90268.40 [DOI] [PubMed] [Google Scholar]
- 2.Gilchrist DM. Medical genetics: 3. An approach to the adult with a genetic disorder. CMAJ 2002; 167. [PMC free article] [PubMed] [Google Scholar]
- 3.Snoek R, Nguyen TQ, van der Zwaag B, van Zuilen AD, Kruis HME, van Gils-Verrij LA, Goldschmeding R, Knoers NVAM, Rookmaaker MB, van Eerde AM. Importance of Genetic Diagnostics in Adult-Onset Focal Segmental Glomerulosclerosis. Nephron 2019;142:351–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Lepori N, Zand L, Sethi S, Fernandez-Juarez G, Fervenza FC. Clinical and pathological phenotype of genetic causes of focal segmental glomerulosclerosis in adults. Clin Kidney J 2018;11:179–90. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Stavropoulos DJ, Merico D, Jobling R, Bowdin S, Monfared N, Thiruvahindrapuram B, Nalpathamkalam T, Pellecchia G, Yuen RKC, Szego MJ, Hayeems RZ, Shaul RZ, Brudno M, Girdea M, Frey B, Alipanahi B, Ahmed S, Babul-Hirji R, Porras RB, Carter MT, Chad L, Chaudhry A, Chitayat D, Doust SJ, Cytrynbaum C, Dupuis L, Ejaz R, Fishman L, Guerin A, Hashemi B, Helal M, Hewson S, Inbar-Feigenberg M, Kannu P, Karp N, Kim R, Kronick J, Liston E, MacDonald H, Mercimek-Mahmutoglu S, Mendoza-Londono R, Nasr E, Nimmo G, Parkinson N, Quercia N, Raiman J, Roifman M, Schulze A, Shugar A, Shuman C, Sinajon P, Siriwardena K, Weksberg R, Yoon G, Carew C, Erickson R, Leach RA, Klein R, Ray PN, Meyn MS, Scherer SW, Cohn RD, Marshall CR. Whole genome sequencing expands diagnostic utility and improves clinical management in pediatric medicine. NPJ Genomic Medicine 2016; 1:15012.doi: 10.1038/gim.2016.221 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Stark Z, Schofield D, Alam K, Wilson W, Mupfeki N, Macciocca I, Shrestha R, White SM, Gaff C. Prospective comparison of the cost-effectiveness of clinical whole-exome sequencing with that of usual care overwhelmingly supports early use and reimbursement. Genet Med 2017;19:867–74.doi: 10.1038/gim.2016.221 [DOI] [PubMed] [Google Scholar]
- 7.Vissers LELM, van Nimwegen KJM, Schieving JH, Kamsteeg EJ, Kleefstra T, Yntema HG, Pfundt R, van der Wilt GJ, Krabbenborg L, Brunner HG, van der Burg S, Grutters J, Veltman JA, Willemsen MAAP. A clinical utility study of exome sequencing versus conventional genetic testing in pediatric neurology. Genet Med 2017;19:1055–63.doi: 10.1038/gim.2017.1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Veeramah KR, Johnstone L, Karafet TM, Wolf D, Sprissler R, Salogiannis J, Barth-Maron A, Greenberg ME, Stuhlmann T, Weinert S, Jentsch TJ, Pazzi M, Restifo LL, Talwar D, Erickson RP, Hammer MF. Exome sequencing reveals new causal mutations in children with epileptic encephalopathies. Epilepsia 2013;54:1270–81.doi: 10.1111/epi.12201 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Thevenon J, Duffourd Y, Masurel-Paulet A, Lefebvre M, Feillet F, El Chehadeh-Djebbar S, St-Onge J, Steinmetz A, Huet F, Chouchane M, Darmency-Stamboul V, Callier P, Thauvin-Robinet C, Faivre L, Rivière JB. Diagnostic odyssey in severe neurodevelopmental disorders: toward clinical whole-exome sequencing as a first-line diagnostic test. Clin Genet 2016;89:700–7.doi: 10.1111/cge.12732 [DOI] [PubMed] [Google Scholar]
- 10.Tan TY, Dillon OJ, Stark Z, Schofield D, Alam K, Shrestha R, Chong B, Phelan D, Brett GR, Creed E, Jarmolowicz A, Yap P, Walsh M, Downie L, Amor DJ, Savarirayan R, McGillivray G, Yeung A, Peters H, Robertson SJ, Robinson AJ, Macciocca I, Sadedin S, Bell K, Oshlack A, Georgeson P, Thorne N, Gaff C, White SM. Diagnostic impact and cost-effectiveness of whole-exome sequencing for ambulant children with suspected monogenic conditions. JAMA Pediatr 2017;171:855–62.doi: 10.1001/jamapediatrics.2017.1755 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Seidelmann SB, Smith E, Subrahmanyan L, Dykas D, Abou Ziki MD, Azari B, Hannah-Shmouni F, Jiang Y, Akar JG, Marieb M, Jacoby D, Bale AE, Lifton RP, Mani A. Application of whole exome sequencing in the clinical diagnosis and management of inherited cardiovascular diseases in adults. Circ Cardiovasc Genet 2017;10:1–9. doi: 10.1161/CIRCGENETICS.116.001573 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Posey JE, Rosenfeld JA, James RA, Bainbridge M, Niu Z, Wang X, Dhar S, Wiszniewski W, Akdemir ZH, Gambin T, Xia F, Person RE, Walkiewicz M, Shaw CA, Sutton VR, Beaudet AL, Muzny D, Eng CM, Yang Y, Gibbs RA, Lupski JR, Boerwinkle E, Plon SE. Molecular diagnostic experience of whole-exome sequencing in adult patients. Genet Med 2016;18:678–85. doi: 10.1038/gim.2015.142 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Farwell KD, Shahmirzadi L, El-Khechen D, Powis Z, Chao EC, Tippin Davis B, Baxter RM, Zeng W, Mroske C, Parra MC, Gandomi SK, Lu I, Li X, Lu H, Lu HM, Salvador D, Ruble D, Lao M, Fischbach S, Wen J, Lee S, Elliott A, Dunlop CL, Tang S. Enhanced utility of family-centered diagnostic exome sequencing with inheritance model-based analysis: results from 500 unselected families with undiagnosed genetic conditions. Genet Med 2015;17:578–86.doi: 10.1038/gim.2014.154 [DOI] [PubMed] [Google Scholar]
- 14.Boycott K, Hartley T, Adam S, Bernier F, Chong K, Fernandez BA, Friedman JM, Geraghty MT, Hume S, Knoppers BM, Laberge AM, Majewski J, Mendoza-Londono R, Meyn MS, Michaud JL, Nelson TN, Richer J, Sadikovic B, Skidmore DL, Stockley T, Taylor S, van Karnebeek C, Zawati MH, Lauzon J, Armour CM, Canadian College of Medical Geneticists. The clinical application of genome-wide sequencing for monogenic diseases in Canada: Position Statement of the Canadian College of Medical Geneticists. J Med Genet 2015;52:431–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Nguyen MT, Charlebois K. The clinical utility of whole-exome sequencing in the context of rare diseases - the changing tides of medical practice. Clin Genet 2015;88:313–9. doi: 10.1038/gim.2014.154 [DOI] [PubMed] [Google Scholar]
- 16.Demos M, Guella I, DeGuzman C, McKenzie MB, Buerki SE, Evans DM, Toyota EB, Boelman C, Huh LL, Datta A, Michoulas A, Selby K, Bjornson BH, Horvath G, Lopez-Rangel E, van Karnebeek CDM, Salvarinova R, Slade E, Eydoux P, Adam S, Van Allen MI, Nelson TN, Bolbocean C, Connolly MB, Farrer MJ. Diagnostic yield and treatment impact of targeted exome sequencing in early-onset epilepsy. Front Neurol 2019;10:434. doi: 10.3389/fneur.2019.00434 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, Grody WW, Hegde M, Lyon E, Spector E, Voelkerding K, Rehm HL, on behalf of the ACMG Laboratory Quality Assurance Committee. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med 2015;17:405–24.doi: 10.1038/gim.2015.30 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Kalia SS, Adelman K, Bale SJ, Chung WK, Eng C, Evans JP, Herman GE, Hufnagel SB, Klein TE, Korf BR, McKelvey KD, Ormond KE, Richards CS, Vlangos CN, Watson M, Martin CL, Miller DT. Recommendations for reporting of secondary findings in clinical exome and genome sequencing, 2016 update (ACMG SF v2.0): a policy statement of the American College of Medical Genetics and Genomics. Genet Med 2017;19:249–55.doi: 10.1038/gim.2016.190 [DOI] [PubMed] [Google Scholar]
- 19.Connor AA, Katzov-Eckert H, Whelan T, Aronson M, Lau L, Marshall C, Charames GS, Pollett A, Gallinger S, Lerner-Ellis J. Identification of a novel MSH6 germline variant in a family with multiple gastro-intestinal malignancies by next generation sequencing. Fam Cancer 2015;14:69–75.doi: 10.1007/s10689-014-9765-9 [DOI] [PubMed] [Google Scholar]
- 20.Miceli F, Soldovieri MV, Joshi N, Weckhuysen S, Cooper E, Taglialatela M. KCNQ2-Related Disorders.In: Pagon RA, Adam MP, Ardinger HH, Wallace SE, Amemiya A, Bean LJH, Bird T, Fong CT, Mefford HC, Smith RJH, Stephens K, eds. GeneReviews® [Internet]. Seattle (WA). University of Washington, Seattle, 1993-2020. Available from: https://www.ncbi.nlm.nih.gov/books/NBK32534/ (accessed Feb 2020). [Google Scholar]
- 21.Weckhuysen S, Ivanovic V, Hendrickx R, Van Coster R, Hjalgrim H, Møller RS, Grønborg S, Schoonjans AS, Ceulemans B, Heavin SB, Eltze C, Horvath R, Casara G, Pisano T, Giordano L, Rostasy K, Haberlandt E, Albrecht B, Bevot A, Benkel I, Syrbe S, Sheidley B, Guerrini R, Poduri A, Lemke JR, Mandelstam S, Scheffer I, Angriman M, Striano P, Marini C, Suls A, De Jonghe P, Group KS. Extending the KCNQ2 encephalopathy spectrum: clinical and neuroimaging findings in 17 patients. Neurology 2013;81:1697–703.doi: 10.1212/01.wnl.0000435296.72400.a1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Kapferer-Seebacher I, Pepin M, Werner R, Aitman TJ, Nordgren A, Stoiber H, Thielens N, Gaboriaud C, Amberger A, Schossig A, Gruber R, Giunta C, Bamshad M, Björck E, Chen C, Chitayat D, Dorschner M, Schmitt-Egenolf M, Hale CJ, Hanna D, Hennies HC, Heiss-Kisielewsky I, Lindstrand A, Lundberg P, Mitchell AL, Nickerson DA, Reinstein E, Rohrbach M, Romani N, Schmuth M, Silver R, Taylan F, Vandersteen A, Vandrovcova J, Weerakkody R, Yang M, Pope FM, Byers PH, Zschocke J, Molecular Basis of Periodontal EDS Consortium. Periodontal Ehlers-Danlos Syndrome is caused by mutations in C1R and C1S, which encode subcomponents C1r and C1s of Complement. Am J Hum Genet 2016;99:1005–14.doi: 10.1016/j.ajhg.2016.08.019. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Moreau A, Janin A, Millat G, Chevalier P. Cardiac voltage-gated sodium channel mutations associated with left atrial dysfunction and stroke in children. Europace 2018;20:1692–8. doi: 10.1093/europace/euy041 [DOI] [PubMed] [Google Scholar]
- 24.Kuperberg M, Lev D, Blumkin L, Zerem A, Ginsberg M, Linder I, Carmi N, Kivity S, Lerman-Sagie T, Leshinsky-Silver E. Utility of whole exome sequencing for genetic diagnosis of previously undiagnosed pediatric neurology patients. J Child Neurol 2016;31:1534–9. doi: 10.1177/0883073816664836 [DOI] [PubMed] [Google Scholar]
- 25.Stark Z, Tan TY, Chong B, Brett GR, Yap P, Walsh M, Yeung A, Peters H, Mordaunt D, Cowie S, Amor DJ, Savarirayan R, McGillivray G, Downie L, Ekert PG, Theda C, James PA, Yaplito-Lee J, Ryan MM, Leventer RJ, Creed E, Macciocca I, Bell KM, Oshlack A, Sadedin S, Georgeson P, Anderson C, Thorne N, Melbourne Genomics Health Alliance, Gaff C, White SM. A prospective evaluation of whole-exome sequencing as a first-tier molecular test in infants with suspected monogenic disorders. Genet Med 2016;18:1090–6.doi: 10.1038/gim.2016.1. [DOI] [PubMed] [Google Scholar]
- 26.Sánchez Fernández I, Loddenkemper T, Gaínza-Lein M, Sheidley BR, Poduri A. Diagnostic yield of genetic tests in epilepsy: A meta-analysis and cost-effectiveness study. Neurology 2019;31:1534–39.doi: 10.1212/WNL.0000000000006850 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Reid ES, Papandreou A, Drury S, Boustred C, Yue WW, Wedatilake Y, Beesley C, Jacques TS, Anderson G, Abulhoul L, Broomfield A, Cleary M, Grunewald S, Varadkar SM, Lench N, Rahman S, Gissen P, Clayton PT, Mills PB. Advantages and pitfalls of an extended gene panel for investigating complex neurometabolic phenotypes. Brain 2016;139:2844–54. doi: 10.1093/brain/aww221 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Asphaug L, Melberg HO. The cost-effectiveness of multigene panel testing for hereditary breast and ovarian cancer in Norway. MDM Policy Pract 2019;4:2381468318821103.doi: 10.1177/2381468318821103. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Schwarze K, Buchanan J, Taylor JC, Wordsworth S. Are whole-exome and whole-genome sequencing approaches cost-effective? A systematic review of the literature. Genet Med 2018; 20:1122–1130.doi: 10.1038/gim.2017.247 [DOI] [PubMed] [Google Scholar]
- 30.Duzkale H, Shen J, McLaughlin H, Alfares A, Kelly MA, Pugh TJ, Funke BH, Rehm HL, Lebo MS. A systematic approach to assessing the clinical significance of genetic variants. Clin Genet 2013;84:453–63. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Hart MR, Biesecker BB, Blout CL, Christensen KD, Amendola LM, Bergstrom KL, Biswas S, Bowling KM, Brothers KB, Conlin LK, Cooper GM, Dulik MC, East KM, Everett JN, Finnila CR, Ghazani AA, Gilmore MJ, Goddard KAB, Jarvik GP, Johnston JJ, Kauffman TL, Kelley WV, Krier JB, Lewis KL, McGuire AL, McMullen C, Ou J, Plon SE, Rehm HL, Richards CS, Romasko EJ, Miren Sagardia A, Spinner NB, Thompson ML, Turbitt E, Vassy JL, Wilfond BS, Veenstra DL, Berg JS, Green RC, Biesecker LG, Hindorff LA. Secondary findings from clinical genomic sequencing: prevalence, patient perspectives, family history assessment, and health-care costs from a multisite study. Genet Med 2019;21:1100–10.doi: 10.1038/s41436-018-0308-x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Gambin T, Jhangiani SN, Below JE, Campbell IM, Wiszniewski W, Muzny DM, Staples J, Morrison AC, Bainbridge MN, Penney S, McGuire AL, Gibbs RA, Lupski JR, Boerwinkle E. Secondary findings and carrier test frequencies in a large multiethnic sample. Genome Med 2015;7:54.doi: 10.1186/s13073-015-0171-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Dorschner MO, Amendola LM, Turner EH, Robertson PD, Shirts BH, Gallego CJ, Bennett RL, Jones KL, Tokita MJ, Bennett JT, Kim JH, Rosenthal EA, Kim DS, Tabor HK, Bamshad MJ, Motulsky AG, Scott CR, Pritchard CC, Walsh T, Burke W, Raskind WH, Byers P, Hisama FM, Nickerson DA, Jarvik GP, National Heart Lung and Blood Institute Grand Opportunity Exome Sequencing Project. Actionable, pathogenic incidental findings in 1,000 participants’ exomes. Am J Hum Genet 2013;93:631–40.doi: 10.1016/j.ajhg.2013.08.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Amendola LM, Dorschner MO, Robertson PD, Salama JS, Hart R, Shirts BH, Murray ML, Tokita MJ, Gallego CJ, Kim DS, Bennett JT, Crosslin DR, Ranchalis J, Jones KL, Rosenthal EA, Jarvik ER, Itsara A, Turner EH, Herman DS, Schleit J, Burt A, Jamal SM, Abrudan JL, Johnson AD, Conlin LK, Dulik MC, Santani A, Metterville DR, Kelly M, Foreman AK, Lee K, Taylor KD, Guo X, Crooks K, Kiedrowski LA, Raffel LJ, Gordon O, Machini K, Desnick RJ, Biesecker LG, Lubitz SA, Mulchandani S, Cooper GM, Joffe S, Richards CS, Yang Y, Rotter JI, Rich SS, O’Donnell CJ, Berg JS, Spinner NB, Evans JP, Fullerton SM, Leppig KA, Bennett RL, Bird T, Sybert VP, Grady WM, Tabor HK, Kim JH, Bamshad MJ, Wilfond B, Motulsky AG, Scott CR, Pritchard CC, Walsh TD, Burke W, Raskind WH, Byers P, Hisama FM, Rehm H, Nickerson DA, Jarvik GP. Actionable exomic incidental findings in 6503 participants: challenges of variant classification. Genome Res 2015;25:305–15.doi: 10.1101/gr.183483.114 [DOI] [PMC free article] [PubMed] [Google Scholar]
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