Literature DB >> 28252636

The Exome Clinic and the role of medical genetics expertise in the interpretation of exome sequencing results.

Dustin Baldridge1, Jennifer Heeley1,2, Marisa Vineyard1, Linda Manwaring1, Tomi L Toler1, Emily Fassi1, Elise Fiala1, Sarah Brown3, Charles W Goss4, Marcia Willing1, Dorothy K Grange1, Beth A Kozel1,5, Marwan Shinawi1.   

Abstract

PURPOSE: Evaluation of the clinician's role in the optimal interpretation of clinical exome sequencing (ES) results.
METHODS: Retrospective chart review of the first 155 patients who underwent clinical ES in our Exome Clinic and direct interaction with the ordering geneticist to evaluate the process of interpretation of results.
RESULTS: The most common primary indication was neurodevelopmental problems (~66%), followed by multiple congenital anomalies (~10%). Based on sequencing data, the overall diagnostic yield was 36%. After assessment by the medical geneticist, incorporation of detailed phenotypic and molecular data, and utilization of additional diagnostic modalities, the final diagnostic yield increased to 43%. Seven patients in our cohort were included in initial case series that described novel genetic syndromes, and 23% of patients were involved in subsequent research studies directly related to their results or involved in efforts to move beyond clinical ES for diagnosis. Clinical management was directly altered due to the ES findings in 12% of definitively diagnosed cases.
CONCLUSIONS: Our results emphasize the usefulness of ES, demonstrate the significant role of the medical geneticist in the diagnostic process of patients undergoing ES, and illustrate the benefits of postanalytical diagnostic work-up in solving the "diagnostic odyssey." Genet Med advance online publication 02 March 2017.

Entities:  

Mesh:

Year:  2017        PMID: 28252636      PMCID: PMC5581723          DOI: 10.1038/gim.2016.224

Source DB:  PubMed          Journal:  Genet Med        ISSN: 1098-3600            Impact factor:   8.822


INTRODUCTION

Clinical exome sequencing (ES) has revolutionized the diagnostic work-up in patients with genetic disease and has changed the diagnostic process in medical genetics practice[1]. The increasing utilization of ES has rapidly identified new genetic syndromes and contributed to solving many diagnostic odysseys[2]. Reports of the yield of exome sequencing through diagnostic laboratories have ranged from 25% to 30%[3-5]. Trio sequencing and focusing on specific disease subgroups can raise the diagnostic rate[5,6]. Many (23–30%) of these diagnosed patients were found to have mutations in genes that had been reported in association with the respective phenotype within the prior 2 to 3 years[3,5]. Exome sequencing has provided insights into the genetic and phenotypic heterogeneity (e.g., atypical and milder presentations) of Mendelian disorders, and highlighted the importance of de novo mutations and “blended phenotypes” (co-existing diagnoses that combine the clinical features of each) in rare genetic disorders[3-5]. The application of this unbiased whole genome technology has led to shifting of the diagnostic skills of the medical geneticist from focusing on detailed phenotypic characterization to identify the genetic etiology to “next-generation phenotyping”: the interpretation and validation of molecular test results in clinical practice by analyzing observed clinical features[7]. To date, there have only been a few attempts to study the role played by the medical geneticist in interpretation of results as part of the diagnostic process of ES, the concordance rate between the laboratory exome results and the geneticist’s interpretation, and the ability of ES to alter a patient’s or family’s medical management. Duke recently reported that the medical geneticists and the laboratories were 90% concordant in their interpretation of the exome results, and discordance occurred when the medical geneticist reconsidered additional clinical information and/or additional laboratory tests and genotyping of family members[8]. Another study showed that establishing a diagnosis through ES can lead to discontinuation of additional planned studies, screening patients for additional manifestations, altering management, identification of disease in other at risk family members, and reproductive planning[9]. The potential cost-effectiveness of ES has also been evaluated by calculating the cost of previous diagnostic workups, concluding that in some cases it may be most cost-effective to perform ES as a first test[10]. In this study, we present our experience with the “Exome Clinic” with special emphasis on the diagnostic course after ES has been completed by the laboratory. We evaluate the role of the medical geneticist in interpretation of results, auxiliary studies performed to determine pathogenicity of genetic variants, follow up clinical tests, and post-exome enrollment in research studies. We discuss the diagnostic yield of ES in our cohort as a function of different phenotypic features. The utility of exome reanalysis 1–2 years after the original report is also presented. Finally, we recorded details of the social and financial implications of our exome results, such as determinations of misattributed paternity and the patient’s out-of-pocket cost.

MATERIALS AND METHODS

Chart Review and Clinical Evaluation

The Washington University School of Medicine Institutional Review Board approved this study. Clinical data were obtained by retrospective chart review and interview with the ordering medical geneticists and genetic counselors (Supplementary Material 1).

ES Laboratory Results

Exomes for 155 probands were ordered between March 2012 and January 2015. Exomes were performed in 3 different laboratories: 127 were analyzed through GeneDx (Gaithersburg, Maryland), 20 through Ambry Genetics (Aliso Viejo, California) and 8 through Baylor Genetics (Houston, Texas). Laboratories reported genetic variants as pathogenic, likely pathogenic, or variants of uncertain significance (VUS) but did not report benign or likely benign variants. We refer to this classification as variant-level assertion. GeneDx also classified the variants in relation to the patient’s phenotype as either definitively or possibly related and reported potential candidate genes for new genetic syndromes, which had not previously been associated with a human phenotype. Ambry Genetics classified variants as either likely positive, which we interpreted as possible, or positive, which we considered as definitively associated with the phenotype. Baylor Genetics classified the variants under “disease genes related to clinical phenotype” as either “deleterious” or “VUS.” We considered “deleterious” and “VUS” as definitive and possible, respectively. All three laboratories also reported incidental variants. Definitions of these terms were adapted from Retterer et al. 2015[6]. We refer to these definitive, possible, candidate, and incidental classifications as case-level assertion, which is a synthesis of all the molecular data in a single subject specifying whether the test results provide a molecular diagnosis, according to the testing laboratory.

Clinical Assessment of ES Findings

Results of ES were discussed individually with the ordering medical geneticist and exome findings were confirmed or reclassified as needed as definitively, likely, possibly, or unlikely causative of the patient’s symptoms based on the molecular data (variant and case-level classifications) and the geneticist’s clinical assessment (Supplementary Material 1). We refer to this classification as clinical-level assertion. This clinical impression was then categorized as concordant or discordant with the laboratory’s case-level assertion to allow us to analyze how the geneticist’s interpretation influenced the final diagnosis (Supplementary Material 1). The statistical tools used for data analysis are presented in Supplementary Material 1.

RESULTS

Characteristics of the Cohort

Detailed descriptions of the clinical characteristics and molecular findings of the patients are documented in Supplementary Table 1. Demographic and phenotypic characteristics of our cohort are recorded in Table 1 and Supplementary Material 1. Sequencing cost for Medicaid patients was not covered by their insurance plans, and was either paid for by philanthropic support or absorbed by the hospital that sent the testing. Out-of-pocket costs to families with private insurance and for whom ES was sent as outpatients were available for 82 cases (Figure 1A). 54 of these cases had an out-of-pocket cost of $0, and the average cost was $386.31 with a maximum cost of $4,012.
Table 1

Demographic Details of Cohort.

Gender
 Male87 (56%)
 Female68 (44%)
Ethnicity
 Caucasian130 (84%)
 Mixed14 (9%)
 African-American8 (5%)
 Hispanic3 (2%)
Patient location
 Outpatient133 (86%)
 Inpatient22 (14%)
Insurance (133 cases)
 Private90 (68%)
 Medicaid43 (32%)
Dysmorphism (154 cases)
 Yes73 (47%)
 Mild17 (11%)
 No64 (42%)
OFC
 Normal93 (61%)
 < −1.88 SD42 (28%)
 > +1.88 SD17 (11%)
Height
 Normal99 (64%)
 < 5th centile50 (32%)
 > 95th centile6 (4%)
Weight
 Normal106 (68%)
 < 5th centile36 (23%)
 > 95th centile13 (8%)
Consanguinity6 (3.9%)
Average age at ES (range)6 years(3 days–33 years)
Average turnaround time in months (range)4.7 (1.3–7.9)
Figure 1

Cost and phenotypic characterization of the cohort

A) Scatter plot of the out-of-pocket cost in ascending order. B) Each case was assigned a phenotype-based, single primary indication for performing ES. The number and percentage of cases are shown in parenthesis. MCA: Multiple congenital anomalies. C) Each phenotypic feature of the probands was assigned to an organ system, and the total count of cases is displayed. D) The frequency and distribution of the neurodevelopmental phenotypes in the cohort. The darker portion of the bar in C and D indicates the proportion of cases that achieved a definitive diagnosis.

The average age at which symptoms in patients began was 11 months, with a median of 7 weeks, ranging from birth to 22 years. Of note, 63 patients (41%) had onset of symptoms at birth. Patients were first seen by a medical geneticist at an average age of 3 years, with a median of 14 months and a range from birth to 31 years old. The primary indications for ES, the most common affected organ systems, and the most common neurodevelopmental findings are presented in Figure 1B, 1C, and 1D, respectively. The average number of organ systems affected in our cohort was 2.6 (median 2 and range 1 to 7 out of 15 possible organ systems). The average number of services (other than genetics) involved in the care of the patients in our cohort was 3.3 (median 3 and range 0 to 10 out of 19 possible services).

Variant Classification and Interpretation

The diagnostic laboratory reported 237 genetic variants, with an average of 1.5 variants reported per patient and a range from 0 to 6. The distribution of genetic variants based on variant-level assertion was as follows: 79 pathogenic, 37 likely pathogenic, and 107 VUS as well as 14 incidental findings (Figure S2, Tables S1, S2) that were classified by the laboratory as known pathogenic (12) or expected pathogenic (2). Among the 155 cases, 56 cases (36%) have definitive diagnosis based on case-level assertion by the laboratory, 60 cases were reported as possible, 10 cases as candidate, and 29 cases as negative (Figures 2A, S1, Tables S3). Due to the presence of autosomal recessive (AR) conditions and blended phenotypes among the 56 definitive cases, the number of variants was 71. Definitive diagnoses in 4 genes were identified in more than one unrelated case: ARID1B (2), GABRB2 (3), NGLY1 (2), and PTPN11 (2). Eleven cases had mitochondrial genome sequencing completed as part of the ES order but none of these yielded abnormal results. Misattributed or non-paternity was found in two families as a result of ES testing.
Figure 2

Characterization of case-level and clinical-level assertions

A) The relative percentages of each case-level classification as reported by the testing laboratory. B) The diagnostic rates according to case-level and clinical-level assertions are shown as the proportion of cases, in gray. The change in classification of cases is indicated, with 16 cases promoted and 5 demoted.

Based on the assessment of the ordering medical geneticist, the final diagnosis was changed in 21 subjects (14%) (Figures 2B,S1, S2, Tables S1, S2, S3, 2, 3). The diagnosis in 16 subjects was promoted such that the clinical geneticist determined that the variant was more definitively related to the phenotype, and in 5 subjects it was demoted. Consequently, there was a net gain of 11 additional definitive diagnoses, for a total of 67 cases (43%) definitively diagnosed (Table 2). There were multiple reasons for changing the case-level classification (Table 3). First, the clinical geneticist has direct and detailed knowledge of the patient’s phenotype and the opportunity to order follow up studies including biochemical and radiological studies, segregation analysis in relatives, and/or single-gene re-sequencing or deletion/duplication studies to search for a mutation in the second allele. Furthermore, there were variants in candidate genes that were promoted because of subsequent publication of new syndromes, either in other similarly affected patients or contribution of these patients to syndrome discovery themselves[11-16]. Thirty-two (48%) out of the 67 definitive cases had mutations in genes described in 2011 or later. This includes 7 (10%) being described as new genetic syndromes[12-16] (WES038, WES052, WES057, WES062, WES079, WES105, WES121), 3 of which are in the process of being published. Five cases (7.5%) had definitive variants in two genes resulting in “blended phenotypes” (WES028[17], WES030, WES060, WES070, WES128). Reanalysis of the exome data was performed in 14 cases by the molecular laboratory, usually 12 to 18 months after the initial report was generated. In 7 cases the reanalysis resulted in no change, in 4 cases it resulted in a new definitive diagnosis (WES013, WES019, WES039, WES131[18]) due to subsequently published new syndromes or functional analysis of variants, and in one case a previously reported variant was demoted (WES002). The remaining two cases (WES099, WES112) involved efforts by the laboratory to identify candidate disease genes for which there have not yet been human phenotypes associated.
Table 2

Description of Definitively Diagnosed Cases.

CaseNumberGeneVariant(s)De NovoInheritedUnknownInheritanceSequencingCompanyClassification(s)MedicalGeneticist’sInterpretationTestingLaboratoryaDisease Modeof InheritancebPhenotypeMIMNumberFinal clinical diagnosis
WES152ADARc.577C>G, p.P193A; c.3020-3C>G, IVS11-3C>GX, XDefinitiveConcordantGAR615010Aicardi-Goutieres syndrome
WES111AHDC1c.2373_2374delTG, p.C791WfsX57XDefinitiveConcordantGAD615829Xia-Gibbs syndrome
WES056ANKRD11c.6159_6162delGGCT, p.A2054PfsX32XDefinitiveConcordantGAD148050KBG syndrome
WES066ARID1Bc.3644delC, p.1215QfsX9XDefinitiveConcordantGAD135900Coffin-Siris syndrome 1
WES030ARID1B / FGFR3c.2281G>A, p.G761S / c.445+(2_5)delTAGG, IVS4+(2_5)delTAGGX (FGFR3)X (ARID1B)Possible / PossiblePromoted / PromotedGAD / AD135900 / 149730Coffin-Siris syndrome 1/ LADD syndrome
WES126ATMc.3993+1G>A, IVS26+1G>A; c.5763-1050A>G, IVS39-1050A>GX, XPossiblePromotedGAR208900Ataxia telangectasia
WES028ATP2B3 / LAMA1c.1445G>A, p.R482H / c.6074C>T, p.T2025M; c.1741C>T, p.R2381CX / X, XPossible / PossiblePromoted / PromotedGXL / AR302500 / 615960ATP2B3-related disorder / LAMA1-related disorder
WES076CHD7c.8279delA, p.N2760IfsX39XDefinitiveConcordantGAD214800CHARGE syndrome
WES086COL1A1c.652G>T, p.G218CXDefinitiveConcordantGAD166200Osteogenesis imperfecta type 1
WES085COL4A1c.2291G>A, p.G764DXDefinitiveConcordantGAD607595COL4A1-related disorders
WES121COQ4c.245T>A, p.L82Q; c.473G>A, p.R158QX, XCandidatePromotedGAR616276COQ4-related disorder
WES038CTBP1c.991C>T, p.R331WXCandidatePromotedGADNone yetCTBP1-related disorder
WES050CYB5R3c.250C>T, p.R84XXcPossiblePromotedGAR250800Methemoglobinemia type II
WES109CYP11A1c.1078C>T, p.R360WXcDefinitiveConcordantGAR613743CYP11A1-related adrenal insufficiency with sex reversal
WES131DNMT3Ac.2645G>A, p.R882HXPossiblePromotedGAD615879Tatton-Brown-Rahman syndrome
WES128DYRK1A / STK11c.889_893dupAGGTT, p.F298LfsX40; c.665-9_665-5delCTCTT, IVS5-9_IVS5-5delCTCTTX, XDefinitiveConcordantGAD / AD614104 / 175200DYRK1A-related intellectual disability / Peutz-Jeghers syndrome
WES047EIF2B5c.318A>T, p.L106F; c.799C>T, p.Q267XXXDefinitiveConcordantGAR603896Vanishing white matter disease
WES117FGD1c.563_570delTGCCTGCC, p.L188RfsX26XDefinitiveConcordantGXL305400Aarskog syndrome
WES134FGFR1c.2152C>G, p.R718GXDefinitiveConcordantGAD615465Hartsfield syndrome
WES020FHL1c.799delC, p.H267Tfs*23XDefinitiveConcordantAXL300696Emery-Dreifuss muscular dystophy type 6
WES104FLGc.1501C>T, p.R501XXDefinitiveConcordantGAD146700Ichthyosis vulgaris
WES051FOXG1c.700T>C, p.S234PXDefinitiveConcordantGAD613454FOXG1-related disorder, Rett-like
WES049GABRA1c.643C>G, p.L215VXDefinitiveConcordantGAD615744GABRA1-related disorder
WES052GABRB2c.909G>T, p.K303NXCandidatePromotedGADNone yetGABRB2-related disorder
WES062GABRB2c.863T>G, p.I288SXDefinitiveConcordantGADNone yetGABRB2-related disorder
WES105GABRB2c.845T>C, p.V282AXDefinitiveConcordantGADNone yetGABRB2-related disorder
WES070GALNS / SUFUc.1485C>G, p.N495K; c.539T>C, p.V180A / c.794_808del15, p.N265_V269delX / XXPossible / PossiblePromoted / PromotedBAR / AD253000 / 109400Morquio syndrome / Gorlin syndrome
WES140GNAO1c.833_835delAGA, p.K278delXDefinitiveConcordantGAD615473GNAO1-related disorder (Early infantile epileptic encephalopathy 17)
WES019GRIN2Bc.1916C>T, p.A639VXPossiblePromotedAAD616139GRIN2B-related disorder (Early infantile epileptic encephalopathy 27)
WES039HNRNPKc.1008+1G>A, IVS12+1G>AXDefinitiveConcordantGAD616580Au-Kline syndrome
WES120KAT6Bc.2184T>G, p.Y728XXDefinitiveConcordantGAD603736KAT6B-related disorder
WES095KCNB1c.629C>T, p.T210MXDefinitiveConcordantGAD616056KCNB1-related disorder (Early infantile epileptic encephalopathy 26)
WES071KCNQ2c.740C>T, p.S247LXDefinitiveConcordantGAD613720KCNQ2-related disorder (Early infantile epileptic encephalopathy 7)
WES107KCNT1c.1193G>A, p.R398QXDefinitiveConcordantGAD614959KCNT1-related disorder (Early infantile epileptic encephalopathy 14)
WES114KMT2Ac.7419delT, p.P2474LfsX35XDefinitiveConcordantGAD605130Wiedemann-Steiner syndrome
WES029KMT2Dc.12039_12046delAGCCCTGG, p.A4014SfsX23XDefinitiveConcordantGAD147920Kabuki syndrome
WES153NBASc.688dupT, p.S230QfsX4; c.2524G>T, p.V842FX, XDefinitiveConcordantGAR616483Infantile liver failure syndrome 2
WES037NGLY1c.347C>G, p.S116X; c.881+5G>T, IVS5+5G>TX, XDefinitiveConcordantGAR615273NGLY1-related congenital disorder of deglycosylation
WES096NGLY1c.953T>C, p.L318P; c.1169G>C, p.R390PX, XDefinitiveConcordantGAR615273NGLY1-related congenital disorder of deglycosylation
WES007OCA2c.1327G>A, p.V443IXDefinitiveConcordantBAR203200Oculocutaneous Albinism, type II
WES155OPHN1c.155-2A>C, IVS2-2A>CXDefinitiveConcordantGXL300486OPHN1-related disorder
WES065PANK2c.1561G>A, p.G521R; c.1264T>C, p.C422RXXDefinitiveConcordantGAR234200PANK2-related disorder (Neurodegeneration with Brain Iron Accumulation)
WES129PGAP1c.1546_1549delGTCA, p.V516KfsX4; c.1077T>G, p.Y359XX, XPossiblePromotedGAR615802PGAP-related disorder
WES025PHF6c.915_916delTGinsAA, p.C305XXDefinitiveConcordantAXL301900Borjeson-Forssman-Lehmann syndrome
WES059PHGDHc.1538C>T, p.S513F; c.1078+1G>A, IVS9+1G>AX, XDefinitiveConcordantGAR601815Phosphoglycerate dehydrogenase deficiency
WES089PIK3CDc.3061G>A, p.E1021KXDefinitiveConcordantGAD615513Primary immunodeficiency 14
WES040PKHD1c.930delC, p.T311LfsX8; c.5134G>A, p.G1712RX, XDefinitiveConcordantGAR263200Autosomal recessive polycystic kidney disease
WES087PLA2G6c.1613G>A, p.R538H; c.319dupC, p.L107PfsX10X, XDefinitiveConcordantGAR256600Infantile neuronal axonal dystrophy type 1
WES148POLR3Bc.2570+5G>A, IVS22+5G>A; c.3317T>C, p.I1106TX, XPossiblePromotedGAR614381Hypomyelinating leukodystrophy type 8
WES077PTPN11c.922A>G, p.N308DXDefinitiveConcordantGAD163950Noonan syndrome
WES154PTPN11c.836A>G, p.Y279CXDefinitiveConcordantGAD151100Noonan syndrome with multiple lentigines
WES074SCN1Ac.677C>T, p.T226MXDefinitiveConcordantGAD604403SCN1A-related epilepsy disorder
WES013SCYL1c.1039C>T, p.Q347*XcPossiblePromotedAAR616719SCYL1-related disorder
WES113SLC16A2c.623_624delGCinsAA, p.G208EXDefinitiveConcordantGXL300523Allan-Herndon-Dudley syndrome
WES122SNX27c.510C>G, p.Y170X; c.1295G>A, p.C432YX, XCandidatePromotedGARNone yetSNX27-related disorder
WES009STXBP1c.875G>T, p.R292LXDefinitiveConcordantAAD612164STXBP1-related disorder (Early infantile epileptic encephalopathy 4)
WES147TBC1D24c.1008delT, p.H336QfsX12; c.680G>T, p.R227LX, XDefinitiveConcordantGAR220500DOORS syndrome (deafness, onychodystrophy, osteodystrophy, mental retardation and seizures)
WES082TBX1c.1392_1403del12, p.A473_A476delXDefinitiveConcordantGAD188400TBX-1-related DiGeorge syndrome
WES118TBX3c.1090G>T, p.E364XXDefinitiveConcordantGAD181450Ulnar-mammary syndrome
WES060TCF12 / EFTUD2c.1319delA, p.N440TfsX79 / c.270A>G, p.T90TX / XDefinitive / DefinitiveConcordant / ConcordantGAD / AD615314 / 610536Craniosnostosis type 3 / Mandibulofacial dysostosis Guion-Almeida type
WES079TELO2c.1100G>T, p.C367F; c.2296G>A, p.V766MX, XCandidatePromotedGAR616954TELO2-related disorder
WES132TNNT2c.833G>A, p.R278HXDefinitiveConcordantGAD115195TNNT2-related disorder
WES017TRMUc.718C>T, p.R240XXcDefinitiveConcordantGAR613070Combined Respiratory Chain Deficiency (Infantile Liver Failure)
WES130TUBA1Ac.1168C>T, p.R390CXDefinitiveConcordantGAD611603Lissencephaly type 3
WES084UBE3Ac.2563_2566dupCTTA, p.K856TfsX2XDefinitiveConcordantGAD105830UBE3A-related disorder
WES015UBE3Bc.2990G>C, p.R997PXcPossiblePromotedAAR244450Blepharophimosis-Ptosis-Intellectual disability syndrome (Kaufman oculocerebrofacial syndrome)
WES057WACc.1721G>A, p.W574XXDefinitiveConcordantGAD616708DeSanto-Shinawi syndrome

G: GeneDx, B: Baylor Genetics, C: Ambry Genetics.

AR: autosomal recessive; AD: autosomal dominant; XL: X-linked.

Homozygous variant.

Table 3

Reasons for Changing the Diagnosis.

Case NumberGene(s)Variant(s)Testing LaboratoryLaboratory Case-Level ClassificationClinical Geneticist Clinical-Level ClassificationReason
Cases That Were Demoted by the Clinical Geneticist
WES002HEXA / VPS13Bc.1073+1G>AIVS9+1G>A / c.11256_11290+10del, IVS58+10delCBDefinitiveUnlikelyHexosaminidase A activity was normal and clinical phenotype is not consistent with Tay Sachs / Lack of a second mutation in VSP13B and phenotype is not consistent with Cohen syndrome
WES003PANK2c.1561G>A, p.G521RBDefinitiveUnlikelyBrain MRI and clinical course are not consistent with PANK2-related phenotype
WES069UPB1 / GAMTc.917-1G>A, IVS8-1G>A / c.327G>A, p.K109KBDefinitiveUnlikelyNegative biochemical studies for creatine deficiency syndromes and pyrimidine metabolism defects
WES090DPYDc.1905+1G>A, IVS14+1G>A; c.1679T>G, p.I560SGDefinitivePossibleBiochemical studies were consistent but clinical phenotype did not fit with the phenotype of dihydropyrimidine dehydrogenase deficiency
WES091DMDDeletion of exons 45-51GDefinitivePossibleThe neurological and cardiac phenotypes, normal muscle histopathological findings, and normal CK are not consistent with the expected clinical findings of this in-frame DMD deletion
Cases That Were Promoted by the Clinical Geneticist
WES013SCYL1c.1039C>T, p.Q347*APossibleDefinitiveClinical phenotype of the patient matched a newly described syndrome 2 years after initial analysis
WES015UBE3Bc.2990G>C, p.R997PAPossibleDefinitiveFacial features and clinical phenotype of the patient matched published syndrome
WES019GRIN2Bc.1916C>T, p.A639VAPossibleDefinitiveClinical phenotype of the patient matched neurological findings reported in patients with GRIN2B mutations
WES028ATP2B3 / LAMA1c.1445G>A, p.R482H / c.6074C>T, p.T2025M; c.1741C>T, p.R2381CGPossibleDefinitiveIn vitro functional studies showed impaired PMCA3 pump function and data supported a synergistic effect with LAMA1 mutations[17]
WES030ARID1B / FGFR3c.2281G>A, p.G761S / c.445+(2_5)delTAGG, IVS4+(2_5)delTAGGGPossibleDefinitiveThe blended phenotype in the patient matched published syndromes related to these genes
WES038CTBP1c.991C>T, p.R331WGCandidateDefinitiveThe patient was one of 4 patients described with a new genetic syndrome[15]
WES050CYB5R3c.250C>T, p.R84XGPossibleDefinitiveFollow up measurement of NADH to cytochrome b5 activity and methemoglobin level in blood were consistent with CYB5R3 deficiency
WES052GABRB2c.909G>T, p.K303NGCandidateDefinitiveSubsequent publication of new syndrome in other patients[12]; the patient is part of an ongoing study on a series of patients to define the phenotype
WES070GALNS / SUFUc.1485C>G, p.N495K; c.539T>C, p.V180A / c.794_808del15, p.N265_V269delGPossibleDefinitiveClinical phenotype of the patient matched the two published syndromes
WES079TELO2c.1100G>T, p.C367F; c.2296G>A, p.V766MGCandidateDefinitiveThe patient was 1 of 6 patients described with a new genetic syndrome[16]
WES121COQ4c.245T>A, p.L82Q; c.473G>A, p.R158QGCandidateDefinitiveThe patient was 1 of 4 patients described with a new CoQ10 deficiency syndrome[13]
WES122SNX27c.510C>G, p.Y170X; c.1295G>A, p.C432YGCandidateDefinitiveBrain MRI and neurological phenotype were consistent with newly described syndrome[11]
WES126ATMc.3993+1G>A, IVS26+1G>A; c.5763-1050A>G, IVS39-1050A>GGPossibleDefinitiveRe-sequencing of ATM detected a second mutation; elevated AFP and neurological findings matched the diagnosis
WES129PGAP1c.1546_1549delGTCA, p.V516KfsX4; c.1077T>G, p.Y359XGPossibleDefinitiveClinical and neurological phenotype of the patient matched published syndrome
WES131DNMT3Ac.2645G>A, p.R882HGPossibleDefinitiveClinical phenotype of the patient was consistent with a newly described syndrome[18]
WES148POLR3Bc.2570+5G>A, IVS22+5G>A; c.3317T>C, p.I1106TGPossibleDefinitiveBrain MRI and clinical phenotype of the patient matched published syndrome

G: GeneDx, B: Baylor Genetics, A: Ambry Genetics.

We then assessed the relationship between the diagnostic yield, as determined by the medical geneticist, and various demographic and phenotypic characteristics (Table S4). Our results indicated a higher diagnostic yield for females (47%), patients with a craniofacial anomaly (64%), and patients with an abnormal head circumference, specifically microcephaly (50%), but none of these effects were statistically significant. Caucasians had a statistically significant higher rate of diagnosis compared to all other racial groups (46% vs. 24%, p=0.04), which persisted after adjusting for craniofacial anomaly in the multivariable logistic regression model, demonstrating the disproportionately low diagnosis rate for non-Caucasians. The following additional categories were tested for effect on diagnostic rate and were found to be not significant: inpatient versus outpatient status, all other phenotypic categories, death, abnormal height or weight, dysmorphism, and positive family history. The inheritance patterns in the 72 conditions (67 subjects; 5 with two conditions caused by variants in different genes) that were determined to be definitive are as follows: 42 (58%) autosomal dominant (AD), 24 (33%) AR, and 6 (8%) X-linked. Of the 89 variants that are associated with these 72 conditions, 34 (38%) were de novo, including one variant in each of two cases with AR conditions (Table 2). The average paternal age at delivery of the 42 patients with de novo mutations was 32 years with a median of 32 years and a range of 22 to 49 years. For the inherited variants, 25 were passed from the mother, 18 from the father, 4 from both (homozygous for recessive condition), and 8 had unknown inheritance due to at least one parent not being sequenced. We observed reduced penetrance of 5 variants that were associated with AD conditions and inherited from seemingly unaffected parents, although parental cardiac evaluations are pending in 2 of these cases. In 9 cases, ES was sent prior to the implementation of the 2013 ACMG guidelines for reporting incidental findings[19]. Of the remaining 146 cases, 5 (3%) families opted out and 141 (97%) families elected to receive the findings. 14 patients (10%) had one incidental finding each. Incidental findings were found in the following genes from the ACMG-recommended list of 56 genes: BRCA2 (2), FBN1, LDLR (2), MYBPC3 (4), MYH7, RET, SCN5A, TTN (2) (Table S5). Although the laboratories’ reports indicate that these incidental variants are known pathogenic in 12 cases, only 5 of these 12 are uniformly classified as pathogenic in ClinVar (http://www.ncbi.nlm.nih.gov/clinvar/) and the remainder have conflicting interpretations of pathogenicity, with some submitters even identifying two of these variants as likely benign (Table S5). Follow up assessment or evaluation was done based on established guidelines and protocols for these cases and their carrier relatives (Table S5).

The Effect of Exome Results on Auxiliary Tests, Management and Research Studies

We examined whether the exome results affected subsequent diagnostic work-up or changed patient management. Additional diagnostic studies were performed in 84 subjects (54%), including molecular studies (proband or family members) in 37 (24%), imaging studies in 29 (19%), and biochemical and/or chemistry tests in 22 (14%). The distribution of the 84 cases based on clinical-level assertion was the following: 48 were definitive, 4 were likely, 8 were possible, 20 were unlikely, 1 was incidental only, and 3 had completely negative results, but had follow up genetic testing performed due to concerns regarding poor coverage of the exome data at particular genes of interest (Supplementary Material 1, Table S6). In 12 out of the 84 cases, these follow up studies were due to the discovery of an ACMG-designated incidental finding. An echocardiogram was performed in 19 (12%) probands or family members, 7 of which were due to incidental findings. In addition, cancer surveillance protocols were initiated in 7 probands or related family members due to variants found by ES, 2 of which were incidental. Three families used the ES information for prenatal or pre-implantation genetic diagnosis. In 8 out of the 67 definitive cases (12%), clinical care was directly altered due to primary ES findings, as follows: 1) discontinuation of levothyroxine (WES113, SLC16A2); 2) cardiac ablation in an asymptomatic patient (WES118, TBX3) found to have Wolff-Parkinson-White syndrome on the EKG that was ordered based on ES results; 3) prophylactic thyroidectomy and Hirschprung’s diagnosis (WES018, RET); 4) neuropsychology evaluation because of known deficits associated with this condition, although not obviously present in this case, which showed ADHD and anxiety disorder and resulted in an atomoxetine prescription (WES057, WAC); 5) orthopedics referral of a patient (WES025, PHF6) with a condition known to cause musculoskeletal phenotypes which led to diagnosis and surgical repair of her scoliosis; 6) amantadine trial initiated for ataxia telangiectasia (WES126, ATM); 7) a trial of methylene blue and vitamin C in a patient (WES050, CYB5R3) with methemoglobinemia; and, lastly, 8) serine prescription for serine-responsive seizures (WES059, PHGDH). Thirty-six patients were enrolled in research studies related to their ES results. These include efforts to characterize the potential functional effect of a particular variant, as well as reanalysis of otherwise negative clinical exome data for research purposes.

DISCUSSION

Although there have been several studies reporting clinical ES results, most of these reports are from diagnostic laboratories and do not focus on the medical geneticists’ interpretation of the findings. The main purpose of this study was to evaluate the medical geneticist’s role in the optimal interpretation of the exome results, and how this might alter the final diagnostic yield. The overall definitive diagnosis rate of clinical ES in our cohort was 36% based on laboratory sequencing data but this increased to 43% after the integration of the molecular and phenotypic data by the medical geneticist as well as the incorporation of additional diagnostic modalities. Fifty-four percent of patients in our cohort underwent “post-analytical” auxiliary diagnostic studies, including biochemical analyses, imaging studies, complementary molecular tests (e.g., deletion and duplication analysis of a specific gene or Sanger sequencing of a gene with low exome coverage), and/or genotyping affected and unaffected family members for segregation analysis. Furthermore, each genetic variant was evaluated by a thorough literature review and searching databases such as ExAC and ClinVar. This extensive post-exome assessment by the clinician is time consuming and illustrates that ES results as reported by the molecular laboratory require clinical context. The laboratory identifies sequence changes and provides information about suspected pathogenicity, but the medical geneticist must compare the expected phenotype associated with the molecular finding to the patient’s phenotype to determine if they align, and whether the molecular finding may account for the patient’s clinical presentation. In 5 cases, we determined that the molecular finding was not consistent with the patient’s phenotype, and the genetic variant was considered to be either benign or not completely explanatory. In 16 other cases, the classification was promoted to a more definitive category and ultimately the final diagnosis was modified (Table 3). However, in other patients the final diagnosis is still uncertain and pathogenicity of the variants is difficult to establish due to lack of functional data, inability to perform segregation analysis, incomplete explanation of the phenotype by the variant, or candidate gene status. These limitations pose challenges to the clinician and demonstrate that receiving the exome results can be the beginning of a continuing exploration process rather than the end of the “diagnostic odyssey.” As evidenced by large-scale research studies that use ES as a tool for discovery such as the Deciphering Developmental Disorders[20], the rate of discovery of new genetic syndromes is rapidly increasing. Therefore, reanalysis of previously reported clinical ES data has the potential to increase the sensitivity of the test. In fact, 48% of definitive cases in our study had mutations in genes with associated syndromes described in 2011 or later. Subsequent reanalysis of the exome data, either at the request of the medical geneticist or at the prompting of internal reanalysis by the diagnostic laboratory, directly resulted in 7 additional definitive diagnoses than would have otherwise been obtained, illustrating the need to perform ongoing data mining for previously submitted cases with negative exome results. The increased diagnostic yield in our cohort relative to previously reported clinical series[3-6,8-10] can be in part attributed to the selection process we apply for subspecialty referrals for the Exome Clinic, including an ES-specific referral form (Supplementary Material 2) and review of the suitability of the case by a medical geneticist. It is also possible that there was a selection bias toward the most severely affected patients referred to a tertiary medical center, reflected by a relatively high number of organ systems, services involved, as well as highly skewed growth parameters and high rate of dysmorphism in the probands when the test was initially implemented in our institution. We cannot exclude the contribution of other factors such as a high trio rate (83%), different categories of indications, or differences in sample size. This study has a number of important limitations. For example, ES was ordered through 3 different laboratories that used different terminology to classify the variants in relation to patient’s phenotype, which limits cross-case comparison. In addition, the laboratories’ data analysis processes changed over time as algorithms have improved and ACMG guidelines have been implemented. However, there were no statistically significant differences among the three different diagnostic laboratories regarding the number of cases with incidental findings, the proportion of cases that received a definitive diagnosis at the case-level, and whether the case-level classification was revised by the clinician (Supplementary Material 1). Another factor limiting the generalizability of our findings is that these patients were all part of a highly selected population that was evaluated at a tertiary medical center. Our study shows that clinical ES is a powerful diagnostic tool especially for atypical and mild presentations of well-established genetic syndromes. For example, none of the patients who received diagnoses of CHARGE, Noonan, ataxia telangiectasia and LADD syndromes met clinical diagnostic criteria, but rather exhibited partial phenotypes. Furthermore, the discovery of five patients in our cohort having “blended phenotypes”, as similarly described in other cohorts[3,21,22], should change our traditional diagnostic approach. ES is a valuable gene discovery tool as illustrated in 7 patients who were included in initial case series that described novel genetic syndromes. Other unexpected exome results were related to potential germline mosaicism in one case (WES057) and uniparental disomy in another case (WES050). This information about non-Mendelian modes of inheritance was very important for providing accurate recurrence risks in future pregnancies. ES also uncovered non-paternity in two cases, which required a consultation with our institutional ethics committee and ultimately led to altered strategies for pretest counseling regarding this complicated issue. Incidental findings present in 9% of our cohort patients often resulted in additional interventions in both the probands and their carrier relatives. This number is higher than we would have expected by comparison to previous cohorts.[3-5,23] However, based on the conflicting assertions in ClinVar (Table S5), it is clear that the performing laboratories over called incidental findings and the actual rate is 3.8% (6/14). These data illustrate the challenges in variant classification and the need for simple and consistent criteria for classification based on variant-specific databases and knowledge bases[23]. We speculate that this lack of uniformity may be due to changes in how variants are classified over time, especially after the release of the 2015 ACMG guidelines[24]. The role of the medical geneticist in following up these incidental results is as important as it is for following up primary results because subsequent monitoring, such as cancer screening and cardiac monitoring, can have life-saving consequences for the patients and their relatives. However, the conflicting interpretations of the data as presented here and the workup performed for patients with uncertain incidental findings (Table S5) illustrate the challenges the medical geneticist faces and reveal one of the significant drawbacks of ES related to false positive incidental findings, which could lead to substantial harmful consequences including performing unnecessary and potentially harmful tests and procedures, increased healthcare costs due to performing unnecessary follow-up evaluations, and causing anxiety among a percentage of patients undergoing ES[23,25,26]. These are important points that should be carefully considered prior to ordering ES and during pretesting counseling. For many patients, ending a diagnostic odyssey limits additional expensive, time-consuming, and potentially invasive diagnostic procedures. It also allows precise determination of recurrence risk and prognosis. ES results were used by 3 families from our cohort for prenatal diagnosis testing. Although the discovery of a treatable condition can dramatically change the clinical outcome, the exome resulted in specific treatments in only a limited number of our patients. Nevertheless, clinical management was directly altered due to primary ES findings in 8 patients, which is 5.2% of all patients who underwent ES. It is also possible that careful clinical assessment for part of these cases would detect clinical findings that might ultimately change the management even without the molecular data. The correlation of diagnostic yield in our cohort with various demographic and phenotypic characteristics showed a higher yield for Caucasians, females, patients with craniofacial anomalies, and patients with abnormal head circumference, but none of these reached statistical significance except for ethnic background (Supplementary Material 1, Table S4). It is important to note that patients from minority populations are under-represented in our cohort, suggesting a need for increased access to ES for individuals from these backgrounds. While the average out-of-pocket cost for ES was $386 per family and although we do not have detailed socioeconomic data for our cohort, we speculate that economic factors may play a role in this discrepancy. Publicly funded insurance plans do not routinely provide coverage for ES and families with high out-of-pocket costs sometimes self-selected not to pursue this testing. Compounding this situation, non-Caucasians achieved a significantly lower diagnostic rate of only 24%. This finding may be due in part to an underrepresentation of minority populations in variant databases, causing challenges in interpreting the clinical significance of variants found in these populations. Taking into account the work involved in interpreting and following up both primary and incidental exome findings, the complex phenotype of patients referred for ES, as well as the constantly evolving nature of these results due to re-analysis and publication of new genetic syndromes, medical geneticists serve an essential role in this complex diagnostic process. This study shows that the partnership of the clinician with the molecular laboratory can increase the diagnostic yield by 7%. An accurate molecular diagnosis ends a diagnostic odyssey, allows for precise genetic counseling, and has the potential to change clinical management. It is also the launching point for the development of targeted pharmacologic therapies, which can hopefully translate these discoveries into efficacious novel treatments to achieve the promise of personalized genomic medicine.
  26 in total

1.  A novel variant in GABRB2 associated with intellectual disability and epilepsy.

Authors:  Siddharth Srivastava; Julie Cohen; Jonathan Pevsner; Swaroop Aradhya; Dianalee McKnight; Elizabeth Butler; Michael Johnston; Ali Fatemi
Journal:  Am J Med Genet A       Date:  2014-08-13       Impact factor: 2.802

Review 2.  Diagnostic clinical genome and exome sequencing.

Authors:  Leslie G Biesecker; Robert C Green
Journal:  N Engl J Med       Date:  2014-06-19       Impact factor: 91.245

3.  Genetic Misdiagnoses and the Potential for Health Disparities.

Authors:  Arjun K Manrai; Birgit H Funke; Heidi L Rehm; Morten S Olesen; Bradley A Maron; Peter Szolovits; David M Margulies; Joseph Loscalzo; Isaac S Kohane
Journal:  N Engl J Med       Date:  2016-08-18       Impact factor: 91.245

4.  A defect in the retromer accessory protein, SNX27, manifests by infantile myoclonic epilepsy and neurodegeneration.

Authors:  Nadirah Damseh; Chris M Danson; Motee Al-Ashhab; Bassam Abu-Libdeh; Matthew Gallon; Kanchan Sharma; Barak Yaacov; Elizabeth Coulthard; Maeve A Caldwell; Simon Edvardson; Peter J Cullen; Orly Elpeleg
Journal:  Neurogenetics       Date:  2015-04-17       Impact factor: 2.660

5.  The usefulness of whole-exome sequencing in routine clinical practice.

Authors:  Alejandro Iglesias; Kwame Anyane-Yeboa; Julia Wynn; Ashley Wilson; Megan Truitt Cho; Edwin Guzman; Rebecca Sisson; Claire Egan; Wendy K Chung
Journal:  Genet Med       Date:  2014-06-05       Impact factor: 8.822

6.  Actionable exomic incidental findings in 6503 participants: challenges of variant classification.

Authors:  Laura M Amendola; Michael O Dorschner; Peggy D Robertson; Joseph S Salama; Ragan Hart; Brian H Shirts; Mitzi L Murray; Mari J Tokita; Carlos J Gallego; Daniel Seung Kim; James T Bennett; David R Crosslin; Jane Ranchalis; Kelly L Jones; Elisabeth A Rosenthal; Ella R Jarvik; Andy Itsara; Emily H Turner; Daniel S Herman; Jennifer Schleit; Amber Burt; Seema M Jamal; Jenica L Abrudan; Andrew D Johnson; Laura K Conlin; Matthew C Dulik; Avni Santani; Danielle R Metterville; Melissa Kelly; Ann Katherine M Foreman; Kristy Lee; Kent D Taylor; Xiuqing Guo; Kristy Crooks; Lesli A Kiedrowski; Leslie J Raffel; Ora Gordon; Kalotina Machini; Robert J Desnick; Leslie G Biesecker; Steven A Lubitz; Surabhi Mulchandani; Greg M Cooper; Steven Joffe; C Sue Richards; Yaoping Yang; Jerome I Rotter; Stephen S Rich; Christopher J O'Donnell; Jonathan S Berg; Nancy B Spinner; James P Evans; Stephanie M Fullerton; Kathleen A Leppig; Robin L Bennett; Thomas Bird; Virginia P Sybert; William M Grady; Holly K Tabor; Jerry H Kim; Michael J Bamshad; Benjamin Wilfond; Arno G Motulsky; C Ronald Scott; Colin C Pritchard; Tom D Walsh; Wylie Burke; Wendy H Raskind; Peter Byers; Fuki M Hisama; Heidi Rehm; Debbie A Nickerson; Gail P Jarvik
Journal:  Genome Res       Date:  2015-01-30       Impact factor: 9.043

7.  Discovery of four recessive developmental disorders using probabilistic genotype and phenotype matching among 4,125 families.

Authors:  Nadia Akawi; Jeremy McRae; Morad Ansari; Meena Balasubramanian; Moira Blyth; Angela F Brady; Stephen Clayton; Trevor Cole; Charu Deshpande; Tomas W Fitzgerald; Nicola Foulds; Richard Francis; George Gabriel; Sebastian S Gerety; Judith Goodship; Emma Hobson; Wendy D Jones; Shelagh Joss; Daniel King; Nikolai Klena; Ajith Kumar; Melissa Lees; Chris Lelliott; Jenny Lord; Dominic McMullan; Mary O'Regan; Deborah Osio; Virginia Piombo; Elena Prigmore; Diana Rajan; Elisabeth Rosser; Alejandro Sifrim; Audrey Smith; Ganesh J Swaminathan; Peter Turnpenny; James Whitworth; Caroline F Wright; Helen V Firth; Jeffrey C Barrett; Cecilia W Lo; David R FitzPatrick; Matthew E Hurles
Journal:  Nat Genet       Date:  2015-10-05       Impact factor: 38.330

8.  Overcalling secondary findings.

Authors:  Leslie G Biesecker
Journal:  Genet Med       Date:  2016-03-17       Impact factor: 8.822

9.  Clinical application of whole-exome sequencing across clinical indications.

Authors:  Kyle Retterer; Jane Juusola; Megan T Cho; Patrik Vitazka; Francisca Millan; Federica Gibellini; Annette Vertino-Bell; Nizar Smaoui; Julie Neidich; Kristin G Monaghan; Dianalee McKnight; Renkui Bai; Sharon Suchy; Bethany Friedman; Jackie Tahiliani; Daniel Pineda-Alvarez; Gabriele Richard; Tracy Brandt; Eden Haverfield; Wendy K Chung; Sherri Bale
Journal:  Genet Med       Date:  2015-12-03       Impact factor: 8.822

10.  Clinical Impact and Cost-Effectiveness of Whole Exome Sequencing as a Diagnostic Tool: A Pediatric Center's Experience.

Authors:  C Alexander Valencia; Ammar Husami; Jennifer Holle; Judith A Johnson; Yaping Qian; Abhinav Mathur; Chao Wei; Subba Rao Indugula; Fanggeng Zou; Haiying Meng; Lijun Wang; Xia Li; Rachel Fisher; Tony Tan; Amber Hogart Begtrup; Kathleen Collins; Katie A Wusik; Derek Neilson; Thomas Burrow; Elizabeth Schorry; Robert Hopkin; Mehdi Keddache; John Barker Harley; Kenneth M Kaufman; Kejian Zhang
Journal:  Front Pediatr       Date:  2015-08-03       Impact factor: 3.418

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  33 in total

1.  A head-to-head evaluation of the diagnostic efficacy and costs of trio versus singleton exome sequencing analysis.

Authors:  Tiong Yang Tan; Sebastian Lunke; Belinda Chong; Dean Phelan; Miriam Fanjul-Fernandez; Justine E Marum; Vanessa Siva Kumar; Zornitza Stark; Alison Yeung; Natasha J Brown; Chloe Stutterd; Martin B Delatycki; Simon Sadedin; Melissa Martyn; Ilias Goranitis; Natalie Thorne; Clara L Gaff; Susan M White
Journal:  Eur J Hum Genet       Date:  2019-07-18       Impact factor: 4.246

2.  A clinically driven variant prioritization framework outperforms purely computational approaches for the diagnostic analysis of singleton WES data.

Authors:  Zornitza Stark; Harriet Dashnow; Sebastian Lunke; Tiong Y Tan; Alison Yeung; Simon Sadedin; Natalie Thorne; Ivan Macciocca; Clara Gaff; Alicia Oshlack; Susan M White; Paul A James
Journal:  Eur J Hum Genet       Date:  2017-08-23       Impact factor: 4.246

3.  The value of genomic variant ClinVar submissions from clinical providers: Beyond the addition of novel variants.

Authors:  Karen E Wain; Emily Palen; Juliann M Savatt; Devin Shuman; Brenda Finucane; Andrea Seeley; Thomas D Challman; Scott M Myers; Christa Lese Martin
Journal:  Hum Mutat       Date:  2018-11       Impact factor: 4.878

Review 4.  Genomic medicine for undiagnosed diseases.

Authors:  Anastasia L Wise; Teri A Manolio; George A Mensah; Josh F Peterson; Dan M Roden; Cecelia Tamburro; Marc S Williams; Eric D Green
Journal:  Lancet       Date:  2019-08-05       Impact factor: 79.321

5.  Altered inhibitory synapses in de novo GABRA5 and GABRA1 mutations associated with early onset epileptic encephalopathies.

Authors:  Ciria C Hernandez; Wenshu XiangWei; Ningning Hu; Dingding Shen; Wangzhen Shen; Andre H Lagrange; Yujia Zhang; Lifang Dai; Changhong Ding; Zhaohui Sun; Jiasheng Hu; Hongmin Zhu; Yuwu Jiang; Robert L Macdonald
Journal:  Brain       Date:  2019-07-01       Impact factor: 13.501

6.  High Rate of Recurrent De Novo Mutations in Developmental and Epileptic Encephalopathies.

Authors:  Fadi F Hamdan; Candace T Myers; Patrick Cossette; Philippe Lemay; Dan Spiegelman; Alexandre Dionne Laporte; Christina Nassif; Ousmane Diallo; Jean Monlong; Maxime Cadieux-Dion; Sylvia Dobrzeniecka; Caroline Meloche; Kyle Retterer; Megan T Cho; Jill A Rosenfeld; Weimin Bi; Christine Massicotte; Marguerite Miguet; Ledia Brunga; Brigid M Regan; Kelly Mo; Cory Tam; Amy Schneider; Georgie Hollingsworth; David R FitzPatrick; Alan Donaldson; Natalie Canham; Edward Blair; Bronwyn Kerr; Andrew E Fry; Rhys H Thomas; Joss Shelagh; Jane A Hurst; Helen Brittain; Moira Blyth; Robert Roger Lebel; Erica H Gerkes; Laura Davis-Keppen; Quinn Stein; Wendy K Chung; Sara J Dorison; Paul J Benke; Emily Fassi; Nicole Corsten-Janssen; Erik-Jan Kamsteeg; Frederic T Mau-Them; Ange-Line Bruel; Alain Verloes; Katrin Õunap; Monica H Wojcik; Dara V F Albert; Sunita Venkateswaran; Tyson Ware; Dean Jones; Yu-Chi Liu; Shekeeb S Mohammad; Peyman Bizargity; Carlos A Bacino; Vincenzo Leuzzi; Simone Martinelli; Bruno Dallapiccola; Marco Tartaglia; Lubov Blumkin; Klaas J Wierenga; Gabriela Purcarin; James J O'Byrne; Sylvia Stockler; Anna Lehman; Boris Keren; Marie-Christine Nougues; Cyril Mignot; Stéphane Auvin; Caroline Nava; Susan M Hiatt; Martina Bebin; Yunru Shao; Fernando Scaglia; Seema R Lalani; Richard E Frye; Imad T Jarjour; Stéphanie Jacques; Renee-Myriam Boucher; Emilie Riou; Myriam Srour; Lionel Carmant; Anne Lortie; Philippe Major; Paola Diadori; François Dubeau; Guy D'Anjou; Guillaume Bourque; Samuel F Berkovic; Lynette G Sadleir; Philippe M Campeau; Zoha Kibar; Ronald G Lafrenière; Simon L Girard; Saadet Mercimek-Mahmutoglu; Cyrus Boelman; Guy A Rouleau; Ingrid E Scheffer; Heather C Mefford; Danielle M Andrade; Elsa Rossignol; Berge A Minassian; Jacques L Michaud
Journal:  Am J Hum Genet       Date:  2017-11-02       Impact factor: 11.025

7.  Clinical whole-exome sequencing for the diagnosis of rare disorders with congenital anomalies and/or intellectual disability: substantial interest of prospective annual reanalysis.

Authors:  Sophie Nambot; Julien Thevenon; Paul Kuentz; Yannis Duffourd; Emilie Tisserant; Ange-Line Bruel; Anne-Laure Mosca-Boidron; Alice Masurel-Paulet; Daphné Lehalle; Nolwenn Jean-Marçais; Mathilde Lefebvre; Pierre Vabres; Salima El Chehadeh-Djebbar; Christophe Philippe; Frederic Tran Mau-Them; Judith St-Onge; Thibaud Jouan; Martin Chevarin; Charlotte Poé; Virginie Carmignac; Antonio Vitobello; Patrick Callier; Jean-Baptiste Rivière; Laurence Faivre; Christel Thauvin-Robinet
Journal:  Genet Med       Date:  2017-11-02       Impact factor: 8.822

8.  Exome and genome sequencing for pediatric patients with congenital anomalies or intellectual disability: an evidence-based clinical guideline of the American College of Medical Genetics and Genomics (ACMG).

Authors:  Kandamurugu Manickam; Monica R McClain; Laurie A Demmer; Sawona Biswas; Hutton M Kearney; Jennifer Malinowski; Lauren J Massingham; Danny Miller; Timothy W Yu; Fuki M Hisama
Journal:  Genet Med       Date:  2021-07-01       Impact factor: 8.822

9.  Randomized prospective evaluation of genome sequencing versus standard-of-care as a first molecular diagnostic test.

Authors:  Deanna G Brockman; Christina A Austin-Tse; Renée C Pelletier; Caroline Harley; Candace Patterson; Holly Head; Courtney Elizabeth Leonard; Kimberly O'Brien; Lisa M Mahanta; Matthew S Lebo; Christine Y Lu; Pradeep Natarajan; Amit V Khera; Krishna G Aragam; Sekar Kathiresan; Heidi L Rehm; Miriam S Udler
Journal:  Genet Med       Date:  2021-05-11       Impact factor: 8.822

10.  Genome-Wide Sequencing for Unexplained Developmental Disabilities or Multiple Congenital Anomalies: A Health Technology Assessment.

Authors: 
Journal:  Ont Health Technol Assess Ser       Date:  2020-03-06
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