cardio gene panel experience - biosb research...
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Jan JongbloedLaboratory Specialist Clinical GeneticsGenome DiagnosticsDepartment of GeneticsUMCG Groningen
CardioGene panelexperience
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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)
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cardiomyopathies
Department of Genetics
DCM; dilatedcardiomyopathy
normalheart
HCM; hypertroficcardiomyopathy
ACM; aritmogeniccardiomyopathy
Wilde & Behr (2013) Nat Rev Cardiol 10:571-83
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Rapid increase
Department of Genetics
van der Zwaag, thesis, 2012
Num
ber
of g
enes
repo
rted
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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
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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
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Department of Genetics
Exome sequencing
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MYBPC3
PKP2
Exome sequencing 2011/2012:Agilent Sure Selectwhole exome kit vs 4:
Av cov: 30-60xGreen: >20xOrange: 10-20xRed: <10x
Rowida Almomani
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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
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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
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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!
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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
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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%
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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
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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
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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
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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
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Department of Genetics
Cardio-panel v1; 48 genes
- 48 genes, 1134 targets - Coverage >30: 99% (<30: 4,398 bps out of 323,651 bps)
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Department of Genetics
Cardio-panel v1; 48 genes
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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
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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
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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
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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%
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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
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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
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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
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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
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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
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Department of Genetics
Analysis: workflow
FASTQ-file FASTA-file
VCF-file
Challenge: Data interpretationPer patient ± 250 variants
Benign -- Pathogenic
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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
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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
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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
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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
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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
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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:
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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:
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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)
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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)
![Page 39: Cardio Gene panel experience - BioSB research schoolbiosb.nl/wp-content/uploads/2014/10/Day-2-Jongbloed... · 2014-10-29 · Department of Genetics Ludolf Boven, Krista Bos, Lennart](https://reader036.vdocuments.net/reader036/viewer/2022062604/5fadd32b5d5df574fc5e2582/html5/thumbnails/39.jpg)
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
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Department of Genetics
Jos Dijkhuis, Inge Mulder, Jerbic
Cardio‐panel v2; interpretation
Dit zit er nog ondercartagenia alamut
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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)
![Page 42: Cardio Gene panel experience - BioSB research schoolbiosb.nl/wp-content/uploads/2014/10/Day-2-Jongbloed... · 2014-10-29 · Department of Genetics Ludolf Boven, Krista Bos, Lennart](https://reader036.vdocuments.net/reader036/viewer/2022062604/5fadd32b5d5df574fc5e2582/html5/thumbnails/42.jpg)
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
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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
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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
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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
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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
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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)
![Page 48: Cardio Gene panel experience - BioSB research schoolbiosb.nl/wp-content/uploads/2014/10/Day-2-Jongbloed... · 2014-10-29 · Department of Genetics Ludolf Boven, Krista Bos, Lennart](https://reader036.vdocuments.net/reader036/viewer/2022062604/5fadd32b5d5df574fc5e2582/html5/thumbnails/48.jpg)
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)
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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
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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
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Department of Genetics
Guidelines NGS
Apply to diagnostic guidelines and recommendations
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Department of Genetics
Minimal gene set:
As of may2013:
Core disease gene listCardiomyopathieën:
46 genes
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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
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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
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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
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• 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
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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?
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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
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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
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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
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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
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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
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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
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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)
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