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Jan JongbloedLaboratory Specialist Clinical GeneticsGenome DiagnosticsDepartment of GeneticsUMCG Groningen
CardioGene panelexperience
Cohorts:
Department of Genetics
AcknowledgmentsCardioGenetics:Rowida AlmomaniLudolf BovenAnne HerkertYvonne HoedemaekersIrene van LangenElisabetta LazzariniAnna PósafalviWouter te RijdtRichard SinkePeter van TintelenPaul van der Zwaag
Dutch Cardiology Depts:Maarten vd Berg (UMCG)Folkert Asselbergs (UMCU)Sebastiaan Piers (LUMC)Arthur Wilde (AMC)
Project 671239 Doelmatigheidsfonds UMCG
Genome diagnostics:Annemieke van der HoutJos DijkhuisenLennart JohanssonHenny LemminkMartine Meems-VeldhuisInge MulderRenée NiessenArjen ScheperMartijn VielYvonne Vos Dutch Clin Genet Depts:
Jasper vd Smagt (UMCU)Daniella Barge (LUMC)Karin van Spaendonck-Zwarts (AMC)
CGD:Terry VrijenhoekEdwin CuppenJoris VeltmanJohan den DunnenRaoul Hennekam
GCC (bionformatics):Lennart JohanssonJoeri van der VeldenPieter NierinckxMorris Schwertz
Genetics research:Eddy de BoerCleo van DiemenKrista van DijkRolf SijmonsBirgit Sikkema-RaddatzPieter vd VliesCisca Wijmenga
Dutch Diagnotics Sections:Dennis Dooijes (UMCURonald Lekanne (AMC)Marjon Slegtenhorst (EMC)Arthur vd Wijngaard (MUMC)
cardiomyopathies
Department of Genetics
DCM; dilatedcardiomyopathy
normalheart
HCM; hypertroficcardiomyopathy
ACM; aritmogeniccardiomyopathy
Wilde & Behr (2013) Nat Rev Cardiol 10:571-83
Rapid increase
Department of Genetics
van der Zwaag, thesis, 2012
Num
ber
of g
enes
repo
rted
Department of Genetics
Jongbloed (2011) Expert Opin Med Diagn 5:9-24van der Zwaag, thesis, 2012
Challenge for routine diagnostics:Extensive genetic heterogeneity
60+ genes involved
In multiple clinical phenotypes
no full penetrance
~20% diagnosis
Department of Genetics
Dutch cardio(myopathy) centers
Gene panel based appraochCardiomyopathies:
Groningen
5 Centers:
Dennis Dooijes (UMCU)Ronald Lekanne dit Deprez (AMC)Marjon Slegtenhorst (EMC)Arthur van de Wiingaard (MUMC)Jan Jongbloed (UMCG)
Utrecht
Amsterdam (AMC)
Rotterdam
Maastricht
Department of Genetics
Exome sequencing
MYBPC3
PKP2
Exome sequencing 2011/2012:Agilent Sure Selectwhole exome kit vs 4:
Av cov: 30-60xGreen: >20xOrange: 10-20xRed: <10x
Rowida Almomani
MYBPC3
PKP2
Exome sequencing 2013:Agilent Sure Selectwhole exome kit vs 5:
Av cov: 50-80xGreen: >20xOrange: 10-20xRed: <10x
Rowida Almomani
Exome sequencing:-High number of variants clinical interpretation-Insufficient coverage missing mutations
Targeted sequencing:capturing of exons of certain genes
Novel strategies: NGS
Department of Genetics
Candidate GeneScreening
Next GenerationSequencing
Which application?
Aim: apply one comprehensive test.Design and implement various targeted next generation sequencing (NGS) gene-panels
Targeted NGS
Department of Genetics
Sequencing:Illumina MiSeq machine151 bp sequencingPaired end
Enrichment:Agilent SureSelect
Data analysis:NextGene software
Data filtering/interpretation:Cartagenia software+ Alamut software
In addition Sanger sequenced amplicons: 15 for identification15 of badly covered regions
12 pat/MiSeq run!
Targeted NGS
Department of Genetics
Sequencing:AMC: Illumina MiSeqEMC: Illumina MiSeqMUMC: Illumina HiSeq 2000UMCU: Solid 5500
Enrichment:AMC: Nimblegen SeqCap easy choiceEMC: Agilent SureSelect custom kitMUMC: Agilent SureSelect WESUMCU: Agilent SureSelect custom kit
Data analysis:AMC: BWA + Genome Analysis TKEMC: BWA + SeqPilotMUMC: MaasVar databaseUMCU: ?
Data filtering/interpretation:AMC: Cartagenia + AlamutEMC: SeqPilot + AlamutMUMC: MaasVar databaseUMCU: Cartagenia + Alamut
Sanger sequencing badly covered amplicons + confirmation
Department of Genetics
Ludolf Boven, Krista Bos,Lennart Johannson, Eddy de Boer
Cardio-panel v1; 48 genes
MiSeq capacity:1 channel 5 miljoen reads
Readlength 150 bp 5.000.000 x 150 bps = 750.000.000 bp
Paired-end 750.000.000 x2 = 1.500.000.000 bp
Accuracy 75% 75% x 1.500.000.000 = 1.125.000.000 bp
Size Cardio Custom 320.000bp 1.125.000.000 bp /320.000 bp = 3515 bp
12 patients multiplex 3515 /12 = 292
Average coverage 292x
Validationcriteria:
Coverage minimal 30 for each nucleotidecompared to Sanger: Specificity 100%
Sensitivity 98%
Department of Genetics
Ludolf Boven, Krista Bos,Lennart Johannson, Eddy de Boer
Cardio-panel v1; 48 genes
ABCC9, ACTC1, ACTN2, ANKRD1, BAG3, CALR3, CRYAB, CSRP3/MLP, DES, DMD, DSC2, DSG2, DSP, EMD, GLA, JPH2, JUP, LAMA4, LAMP2, LMNA, MYBPC3, MYH6, MYH7, MYL2, MYL3, MYPN, MYOZ1, MYOZ2, PKP2, PLN, PRKAG2, PSEN1, PSEN2, RBM20, RYR2, SCN5A, SGCD, TAZ, TBX20, TCAP, TMEM43, TNNC1, TNNI3, TNNT2, TPM1, TTN, VCL, ZASP/LDB3
Department of Genetics
Processing in NextGene (1)
Convert FastQ file to FastA
Alignment of reads
Check of read quality with criteria: (removal of unsuitable reads)
median of the read ↑Q20
if a >3bp stretch cannot be called: removal
at least 25 useable bp for mapping
if ≥ 3bp (adjacent) quality ↓Q16: removal or trimming
removal of duplicate reads
Department of Genetics
Processing in NextGene (2)
Calculating coverage per bp (report on badly covered regions)
Output: mutation report for identity check
Calling of variants in ≥ 20% of reads(Allele frequency >0.20)
Output: vcf-file with variants
Upload into
Department of Genetics
Birgit Sikkema-Raddatz, Ludolf BovenLennart Johannson, Eddy de Boer
Cardio-panel v1; 48 genes1. Technical validation:- Coverage (quality of sequence data)- Specificity (confirmation Sanger) (100%)- Sensitivity (false positive rate NGS) (98%)- Reproducibility
24 patients, with Sanger sequencing data (~6 genes) 5 patients, duplicate analysis
2. Clinical validation: novel patients multiple runs
Department of Genetics
Cardio-panel v1; 48 genes
- 48 genes, 1134 targets - Coverage >30: 99% (<30: 4,398 bps out of 323,651 bps)
Department of Genetics
Cardio-panel v1; 48 genes
Reproducibility
Department of Genetics
5 patients analysed twice (in different runs):
- 231 variants (198–268) were detected per sample
- on average, 10 unique variants (8–14) were reported
- in total, 1,007 variants were detected; 51 of these were differently reported; nonconcordance rate: 0.00315%
Due to:* 12/51: badly covered regions* 24/51: alignment problems; different annotation
same variant* 15/51: false positives; allele freq ~0.2; only in F or R
Conclusions
Department of Genetics
Resequencing of gene panels on the MiSeq can be used in routine diagnostics
99% of all bases of the target genes is of high quality
No false positives
No false negatives
12-16 patients can be multiplexed
Average coverage: >200x (currently ~400x)
~15 exons require Sanger sequencing in parallelSikkema-Raddatz (2013) Hum Mutat
Department of Genetics
Onco-panel v1; 73 genesBRCA1, BRCA2, PTEN, NF1, CDK4, MUTYH, APC, MSH2, MSH6, MLH1, PMS2, CDH1, STK11, SDHB, RET, SDHD, WT1, SDHC, MEN1, SDHA, FLCN, VHL, NF2, PTCH, FH, BMPR1A, SMAD4, CHEK2, RAD51C, RAD51D, BRIP1, XRCC2, BARD1, HOXB13, KLLN, MITF, ENG, AXIN2, BMP4, TMEM127, CDC73, AIP, CDKN2B, CDKN2C, CDKN1A, CDKN1B, SDHAF2, MAX, PHOX2B, TERT, RUNX1, CEBPA, GATA2, PTCH2, MET, SUFU, TP53, CDKN2A, BAP1, PALB2, DICER1, SMARCB1, SMARCA4, BUB1B, PALLD, EGFR, PDGFRA, KIT, PRKAR1A, ATM, CEP57
Department of Genetics
Onco panel v1; 73 genesApplication on36 patients
9000 variants
40 variants- 35 substitutions- 5 indels
Filter onnovel variants
n = 40
Sanger Sequencingup to 6 genes
No false-positivesTotal: 105 variants
64 variants- 19 substitutions- 45 indels
Validation on24 patients
Targeted NGS for 73 genes
Sanger Sequencing
64/64 confirmed
Total no. of variants
No false-positives ornegatives
73 genes,996 targetsCoverage >30:99%
Department of Genetics
Onco panel v1; 73 genes
Class 2 (n = 32/70 ) e.g. RAD51C, MAX, ALK, …Preventive options available for the frequently associated tumor types
No official guidelines yet
Class 1 (n= 25/70 ) e.g. BRCA1, MLH1, RET,…
Preventive options available for the frequently associated
tumor types
Following national / international guidelines
Class 3 (n = 13/70) e.g. TP53, KIT, BAP1, ….
No preventive options available for frequently associated tumor
types (e.g. pancreatic cancer, sarcoma)
3 virtual sub-panels based on preventive options
Department of Genetics
Onco panel v1; 73 genes
Class 2 (n = 32/70 ) e.g. RAD51C, MAX, ALK, …Preventive options available for the frequently associated tumor types
No official guidelines yet
3 virtual sub-panels based on preventive options
Class 1 (n= 25/70 ) e.g. BRCA1, MLH1, RET,…
Preventive options available for the frequently associated
tumor types
Following national / international guidelines
Class 3 (n = 13/70) e.g. TP53, KIT, BAP1, ….
No preventive options available for frequently associated tumor
types (e.g. pancreatic cancer, sarcoma)
Most patients choose 1 + 2
Department of Genetics
Status of targeted gene panels
Panel No. of genes
Coverage > 20 for each
No. of patients
Cardio 55 99,3 >1000Onco 73 99,3 ~200Movement 88 99,4 ~100Skin 63 99,4 32Epilepsy 147 99,6 ~40Neuro Agilent IDLiver Agilent ID
Department of Genetics
Jos Dijkhuis, Martine Meems-Veldhuis, Inge Mulder, Paskal Norel, Arjen Scheper, Martijn Viel
Cardio-panel v2; 55 genesABCC9, ACTC1, ACTN2, ANKRD1, BAG3, CALR3,
CAV3, CRYAB, CSRP3/MLP, DES, DMD, DSC2, DSG2, DSP, DTNA, EMD, EYA4,
GATAD1, GLA, JPH2, JUP, LAMA4, LAMP2, LMNA,
MYBPC3, MYH6, MYH7, MYL2, MYL3, MYPN, MYOZ1, MYOZ2, NEXN, PKP2, PLN, PRKAG2,
PSEN1, PSEN2, RBM20, RYR2, SCN5A, SGCD, TAZ, TBX20,
TCAP, TMEM43, TNNC1, TNNI3, TNNT2, TPM1, TTN, TXNRD2, VCL, ZASP/LDB3
Since September 2012 in Routine Diagnostics:
>1000 patients received~1000 sequenced
-> ~1000 reports sent-> ~2-4 MiSeq run (12 patients) per week-> Of these 2 cardiomyopathy runs
Department of Genetics
Dutch cardio panels
AMC:23 genes (454): 350 patients41 genes (Solid): 140 patients41/46 (MiSeq): 270 patientsTTN: 60 (454), 20 (S), 50 (Mi)Aritmie: 130 (S), 50 (Mi)
Groningen
Utrecht
Amsterdam (AMC)
Rotterdam
Maastricht
EMC:45 genes (cardiochip): 500 patients
UMCU:CM, 64 genes: 300 patientsConduction panel, 33 genes: 60 patientsCongenital, 34 genes: 50 patientsTTN: 100 patientsConnective tissue, 18 genes: 60 patients
MUMC:34 genes (cardiochip): 260 patients34 genes (454): 100 patients45 (HiSeq): 220 patients
Department of Genetics
Analysis: workflow
FASTQ-file FASTA-file
VCF-file
Challenge: Data interpretationPer patient ± 250 variants
Benign -- Pathogenic
Department of Genetics
Filtering:- BED file (exons +/- 20 bp)- Quality (>20x)- 1000 genomes (≥0.02 MAF; ≥200 observation)- GoNL (≥0.02 MAF; ≥200 observation)- ESP (≥0.05 MAF; ≥200 observation)- SNP database (≥0.02 MAF; ≥200 observation)- “managed variant lists”
Cardio-panel v2; filteringPer patient 5 – 15 variants
Annemieke van der Hout, Henny Lemmink, Renée Niessen, Yvonne Vos
Department of Genetics
Cardio-panel v2; filtering
Annemieke van der Hout, Henny Lemmink, Renée Niessen, Yvonne Vos
Coverage >20
MVL* poly MVL
artefactGONL 2%
1000 genomes2% >200 observations
ESP5%>200 observations
dbSNP2% >200 observations
MVL Likely Benign
*MVL = managed variant list
Department of Genetics
Filtering:- BED file (exons +/- 20 bp)- Quality (>20x)- 1000 genomes (≥0.005 MAF; ≥200 observation)- GoNL (≥0.005 MAF; ≥200 observation)- ESP (≥0.005 MAF; ≥200 observation)- SNP database (≥0.005 MAF; ≥200 observation)- “managed variant lists”
Cardio-panel v2; filteringPer patient 0 – 5 variants
Annemieke van der Hout, Henny Lemmink, Renée Niessen, Yvonne Vos
Department of Genetics
Annemieke van der Hout, Henny Lemmink,Renée Niessen, Yvonne Vos
Cardio‐panel v2; interpretationFields Gene Variant Previous Classification HGMD How often found Relevante isoforms Grantham Score Allele frequency Population frequency
(1000 G, GoNL)
Conclusion Category:
Alamut: PhyloP score Mutation Taster Polyphen SIFT Align GVGD Conservation Splicing Google Scholar
BenignLikely BenignVOUSLikely PathogenicPathogenic
Pathogenic:-truncating mutations in “usual suspects” -missense mutations with sufficient proof
Likely Pathogenic:-truncating mutations in genes less studied-missense mutations fullfilling:
*conserved (at least up to chicken)*most or all prediction programs: pathogenic*not or <0.0005 MAF in control populations
Exception: not fullfilling the above,but additional data available
Department of Genetics
Diagnostic ReportReport includes
Only (likely) pathogenic mutations(with disclaimer that not all variants are reported)
Conclusion regarding: genotype – phenotype correlation
All tested genes
Total coverage (% of total region of interest covered with >20x)
Average read depth
Request for affected family members for segregation analysis
Normal reports: made by senior technicians, authorized by staff
Department of Genetics
Anna Pósafalvi
Cardio-panel v2; diagnostic yield
• Yield LP +P = 45%• Note: ~15% >1 P/LP• ~40% P/LP in “usual suspects” • Truncating TTN mutations: 36 (9%) of cases
-> 28 (13%) DCM patients-> 5 (5%) HCM patients-> 1 ARVC, 1 NCCM, 1 CM patient
43 pathogenic; 11%
134 likely pathogenic; 34%
213 VOUS/likely benign; 55%
390 patients
Diagnostic yield:
Department of Genetics
Anna Pósafalvi
Cardio-panel v2; diagnostic yield
• Yield LP +P = 45%• Note: ~15% >1 P/LP• ~40% P/LP in “usual suspects” • Truncating TTN mutations: 36 (9%) of cases
-> 28 (13%) DCM patients-> 5 (5%) HCM patients-> 1 ARVC, 1 NCCM, 1 CM patient
43 pathogenic; 11%
134 likely pathogenic; 34%
213 VOUS/likely benign; 55%
390 patients
Diagnostic yield:
Department of Genetics
Conclusion implementation
Improvements:* Reducing Turn-Around-Times1. Further robotization of sample processing
2. Optimizing the “pipe line” (Filtering parameters)
3. Automation of interpretation process
* Detection of exon deletions/duplications to avoid additional
MLPA analyses.
* Improving data interpretation
1. Targeted NGS can replace Sanger Sequencing
2. Improved diagnostic yield (~50% for cardiomyopathies)
Department of Genetics
Improvements/challenges
Improvements:* Reducing Turn-Around-Times1. Further robotization of sample processing
2. Optimizing the “pipe line” (Filtering parameters)
3. Automation of interpretation process
* Detection of exon deletions/duplications to avoid additional
MLPA analyses.
* Improving data interpretation
1. Targeted NGS can replace Sanger Sequencing
2. Improved diagnostic yield (~50% for cardiomyopathies)
Department of Genetics
Annemieke van der Hout, Henny Lemmink,Renée Niessen, Yvonne Vos
Cardio‐panel v2; interpretationFields Gene Variant Previous Classification HGMD How often found Relevante isoforms Grantham Score Allele frequency Population frequency
(1000 G, GoNL)
Conclusion Category:
Alamut: PhyloP score Mutation Taster Polyphen SIFT Align GVGD Conservation Splicing Google Scholar
BenignLikely BenignVOUSLikely PathogenicPathogenic
Department of Genetics
Jos Dijkhuis, Inge Mulder, Jerbic
Cardio‐panel v2; interpretation
Dit zit er nog ondercartagenia alamut
Department of Genetics
Improvements/challenges
Improvements:* Reducing Turn-Around-Times1. Further robotization of sample processing
2. Optimizing the “pipe line” (Filtering parameters)
3. Automation of interpretation process
* Detection of exon deletions/duplications to avoid additional
MLPA analyses.
* Improving data interpretation
1. Targeted NGS can replace Sanger Sequencing
2. Improved diagnostic yield (~50% for cardiomyopathies)
Department of Genetics
Exon deletion/duplications
Average coverage per target
Targets from X chromosome
One serie of 12 samples
Another serie of 12 samples
Instead of MLPANumber of reads: deletion, duplication compared to normal
Normalisation to avoid false positives
Lennart Johansson, Birgit Raddatz
Department of Genetics
Exon deletion/duplications
1. Best match: determine the control group
0
100
200
300
400
500
0 200 400 600 800 1000 1
Reeks2
Reeks3
Reeks4
Reeks5
Reeks6
Reeks7
Reeks8
Reeks9
Reeks10
Reeks11
Reeks12
20 per. Z
20 per. Z
20 per. Z
20 per. Z
20 per. Z
20 per. Z
20 per. Z
20 per. Z
20 per. Z
20 per. Z
20 per. Z
Controles with the most similar pattern compared to the sample
2. Normalisation per sample and per gen
Compare sample with control group:
Deletion: Ratio 0.65, Z-score <-3 Duplication: Ratio 1.25, Z-score >3
Lennart Johansson, Birgit Raddatz
Department of Genetics
Exon deletion/duplications
Quality control (calculation of variation)
Threshold to exclude
Bad samples
Bad genes (targets)
0
100
200
300
400
500
0 200 400 600 800 1000 1
Reeks2
Reeks3
Reeks4
Reeks5
Reeks6
Reeks7
Reeks8
Reeks9
Reeks10
Reeks11
Reeks12
20 per. Z
20 per. Z
20 per. Z
20 per. Z
20 per. Z
20 per. Z
20 per. Z
20 per. Z
20 per. Z
20 per. Z
20 per. Z
Department of Genetics
Exon deletion/duplications
Validation of 120 samples, including 10 known deletions/ duplications
On average 907 of the 930 targets of the onco panel pass the thresholds.No false negative results.
Lennart Johansson, Birgit Raddatz
Department of Genetics
Exon deletion/duplications
Results
2 positive controls in bad samples1 positive control bad target
1 positive control bad target
CardioOnco
Lennart Johansson, Birgit Raddatz
Department of Genetics
Improvements/challenges
Improvements:* Reducing Turn-Around-Times1. Further robotization of sample processing
2. Optimizing the “pipe line” (Filtering parameters)
3. Automation of interpretation process
* Detection of exon deletions/duplications to avoid additional
MLPA analyses.
* Improving data interpretation
1. Targeted NGS can replace Sanger Sequencing
2. Improved diagnostic yield (~50% for cardiomyopathies)
Department of Genetics
Interpretation
29 support pathogenicity (affected carrier)
13 partly support pathogenicity
6 support no pathogenicity (affected not carrier)
81 families
Outcome cosegregation analysis:
33 not decisive (presymptomatic; 1st degree rel)
Data sharing
Department of Genetics
Database/sharing (groep 3, Richard Sinke, UMCG)
•Project 1: VKGL, open source (Morris Swertz)Sharing of all data (vcf files); focus on technical aspects first
•Project 2: Cartagenia (Renée Niessen)Sharing data cardiomyopathy panels
•Project 3: pre-NGS data:Via managed variant lists Cartagenia?
Renée Niessen, Dennis Dooijes, Marjon Slegtenhorst,Ronald Lekanne dit Deprez, Arthur van de Wijgaard
Department of Genetics
Data sharing; cardiomyopathies
Gene panel based appraochCardiomyopathies:
Groningen
5 Centers:
Dennis Dooijes (UMCU)Ronald Lekanne dit Deprez (AMC)Marjon Slegtenhorst (EMC)Arthur van de Wiingaard (MUMC)Jan Jongbloed *UMCG)
Utrecht
Amsterdam (AMC)
Rotterdam
Maastricht
Department of Genetics
Guidelines NGS
Apply to diagnostic guidelines and recommendations
Department of Genetics
Minimal gene set:
As of may2013:
Core disease gene listCardiomyopathieën:
46 genes
Department of Genetics
Data sharing; cardiomyopathies
Goals
• Proof of concept• Identify potential issues• Guide development of complete NGS
consortium solution
Renée Niessen, Dennis Dooijes, Marjon Slegtenhorst,Ronald Lekanne dit Deprez, Arthur van de Wijgaard
Department of Genetics
Filtering:- BED file (exons +/- 20 bp)- Quality (>20x)- 1000 genomes (≥0.02 MAF; ≥200 observation)- GoNL (≥0.02 MAF; ≥200 observation)- ESP (≥0.05 MAF; ≥200 observation)- SNP database (≥0.02 MAF; ≥200 observation)- “managed variant lists”
Cardio-panel v2; filteringPer patient 5 – 15 variants
Annemieke van der Hout, Henny Lemmink, Renée Niessen, Yvonne Vos
Department of Genetics
Data sharing; cardiomyopathies
benignbenignpathogeniclikely benignbenign
(Limited) phenotype:Hypertrophic CMRestrictive CMDilated CMRight ventricular CM
One‐clickSubmission
Patie
nt1234
Curation, Validation
Phenotype, filter, assess, interpret, classify, report
LAB
• Frequency statistics• Curation information• hom/het; affected
ClinicalUse
NGS consortium solution
• Lessons learned: Lowlands consortium for CNV– >20k cases; already solved diagnostic cases!
• In parallel: similar NGS pilot in US– 5 labs (CHOP hospital lead); panels & exomes
Department of Genetics
Data sharing; cardiomyopathies
One-clickSubmission
Curation, Validation• Frequency statistics• Curation information• hom/het; affected
ClinicalUse
Department of Genetics
Data sharing; cardiomyopathies
• First Phase (Finished..)
–Groningen (UMCG) & Utrecht (UMCG)–Both using Bench Lab NGS platform
• Second Phase (Started…)
–Add Rotterdam (EMC), Amsterdam (AMC) & Maastricht (MUMC)
Pilot: Who?
Department of Genetics
Data sharing; cardiomyopathies
• Analyzed variants– Per analysis => Frequency information– Inconsistent or incomplete labeling possible
• Curated variants– In Bench: Managed Variant List (MVL)– Analysis independent
Two levels of Data
Department of Genetics
Data sharing; cardiomyopathies
• UMCG– # patients: 1000– # analyzed variants: 230k (6k unique)– # curated variants: 2000 (1800
unique)
• UMCU– # patients: 150– # analyzed variants: 40k 2.5k unique)– # curated variants: 530 (500
unique)
First Phase: Some Numbers
Department of Genetics
Data sharing; cardiomyopathies
• Only 4 pathogenic variants common between the two labs:
– p.C796R PKP2– p.R79* PKP2– p.Q791fs MYBPC3– p.P955fs MYBPC3
First Phase: Findings
Department of Genetics
Data sharing; cardiomyopathies
• Both g-, c- and p-notation important!
• Example:–Utrecht
• 11_47359280_-/C c.2373dupG p.Q791fs
–Groningen• 11_47359282_T/CT c.2372delAinsAG p.Q791fs• 11_47359282_-/C c.2371_2372insG p.Q791fs
First Phase: Findings
Department of Genetics
Data sharing; cardiomyopathies
• Sharing immediately provides new and valuable information.
• Identified important issues.–Notation–Labeling methodology
• e.g. What exactly means ‘likely pathogenic’ ?• e.g. When and how often do you label variants?
Intermediate Conclusions
Conclusions
Department of Genetics
Gene panel based NGS succesful in clinical diagnostics
Challenges (technical, interpretation, reporting) however
still remain, even in gene-panel based approaches
Deletion/duplication detection from targeted NGS data
possible
Data sharing important for further interpretation
Cohorts:
Department of Genetics
AcknowledgmentsCardioGenetics:Rowida AlmomaniLudolf BovenAnne HerkertYvonne HoedemaekersIrene van LangenElisabetta LazzariniAnna PósafalviWouter te RijdtRichard SinkePeter van TintelenPaul van der Zwaag
Dutch Cardiology Depts:Maarten vd Berg (UMCG)Folkert Asselbergs (UMCU)Sebastiaan Piers (LUMC)Arthur Wilde (AMC)
Project 671239 Doelmatigheidsfonds UMCG
Genome diagnostics:Annemieke van der HoutJos DijkhuisenLennart JohanssonHenny LemminkMartine Meems-VeldhuisInge MulderRenée NiessenArjen ScheperMartijn VielYvonne Vos Dutch Clin Genet Depts:
Jasper vd Smagt (UMCU)Daniella Barge (LUMC)Karin van Spaendonck-Zwarts (AMC)
CGD:Terry VrijenhoekEdwin CuppenJoris VeltmanJohan den DunnenRaoul Hennekam
GCC (bionformatics):Lennart JohanssonPieter NierinckxMorris Schwertz
Genetics research:Eddy de BoerCleo van DiemenKrista van DijkRolf SijmonsBirgit Sikkema-RaddatzPieter vd VliesCisca Wijmenga
Dutch Diagnotics Sections:Dennis Dooijes (UMCURonald Lekanne (AMC)Marjon Slegtenhorst (EMC)Arthur vd Wijngaard (MUMC)