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©2020 MFMER | slide-1 ©2020 MFMER | slide-1
Rationale Application of Next Generation Sequencing (NGS) Technology in Coagulation Disorders Rajiv K. Pruthi, M.B.B.S. Consultant I Associate Professor of Medicine Director, Mayo Comprehensive Hemophilia Center Co-Director, Special Coagulation and Molecular Hematopathology Laboratories, Chair, Coagulation Diseases Oriented Group (Hematology) Mayo Clinic, Rochester, MN
A Case-based Workshop: Clinical and Laboratory Aspects of Hemophilia and Thrombosis Dec 4th, 2020 pruthi.rajiv@mayo.edu
©2020 Mayo Foundation for Medical Education and Research | slide-1
©2020 MFMER | slide-2 ©2020 MFMER | slide-2
Relevant Financial Relationship(s)
• None.
Off Label Usage:
• Not applicable
DISCLOSURES
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©2020 MFMER | slide-3 ©2020 MFMER | slide-3
LEARNING OBJECTIVE
Primer on PCR & Next Generation Sequencing
Overview of hereditary bleeding disorders and
thrombophilia
Rational application of NGS to hereditary
bleeding disorders
Rational application of NGS to hereditary
thrombophilia
©2020 MFMER | slide-4 ©2020 MFMER | slide-4
Definitions
Phenotypic diagnosis:
Relies on protein based testing: plasma, platelet aggregation etc
May not be widely available
Platelet aggregation tests cannot be mailed in to reference laboratories
Role of genotypic diagnosis:
Prognosis in established diagnosis
Establishing the diagnosis based on genotype information (when protein based assays are not available/reliable)
Can be mailed into reference laboratories
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Schematic Diagram of PCR
Template DNA
dCTP
dATP
dGTP
dTTP
Primer
Primer
Taq DNA
Polymerase
DNA strand separation
DNA at 95oC
Taq DNA polymerase mediated primer extension when reheated
Primers anneal when cooled Repeated cycles lead to exponential increase in number of DNA copies
+
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PCR of FVIII gene in multi-exon deleted patient Normal
Control Patient
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Sequencing output: forward and reverse strands
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Adapted from: Jill M. Johnsen et al. Blood 2013;122:3268-3275
©2013 by American Society of Hematology
Next Generation Sequencing (NGS)
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Mayo Clinic
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NGS Workflow
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Mayo Clinic
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Pre-analytic
Library Prep
Sequencing
Template Prep
• Demultiplexing
• Base calling
• Alignment
• Variant calling
• Specialized applications
• Variant Annotation
• Variant significance*
10
20
30
“Wet Bench” Process “Dry Bench” Informatics
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NGS sequence output: depth of read varies >500
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Major advantages
•Sequence multiple samples on one run
•Sequence multiple regions on one run
•Whole exome: only coding regions
•Whole genome: coding and non coding regions
•Time consuming analytics
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Approach to presentation: Hereditary bleeding disorders Inherited thrombophilia
• Patients evaluated for bleeding symptoms
• Based on phenotype assays
• Diagnosis established
• No diagnosis established
• Is there a role for NGS testing
• Impact on management
• Venous thromboembolism (VTE)
• Asymptomatic individual
• Symptomatic individual
• Phenotype assays
• Diagnosis established
• No diagnosis established
• Is there a role for NGS testing
• Impact on management
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Type and incidence of inherited bleeding disorders
VWD 40%
Hemophilia A 25%
FXI deficieny 10%
Platelet disorder 8%
Hemophilia B 6%
FVII deficiency 4%
Fibrinogen defect 2% Rare/Combined
3% Unspecified 2%
Frequency
Sivapalaratnam, S et al BJH 2017; 179:363
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Phenotype diagnosis established: What is the role of genotyping? •Plasmatic bleeding disorders
•Hemophilia A and B
•Von Willebrand disease
•Platelet bleeding disorders
•Syndromic vs Non-Syndromic
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Severe hemophilia A genotypes (MLOF initiative)
34.7
38.3
17.4
7.2
5.9
1.2
1.1 0.6
0.2
0.2
Frequency
Int 22 Inv Type 1
Single nucleotide
Frameshift
Int 22 Inv Type 2
Larger SV
Int 1 inv
Small indel
None
Int 22 Inv complex
Int 1 Inv Complex
Johnsen, JM et al Blood Advances 2017; 1:824
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©2011 MFMER |
3146613-16
Large deletions
Multiple exon
Nonsense
Nonsense light chain
Nonsense non-light chain
Intron 22 inversion
Intron 1 inversion
Small in/dels
In poly A runs Outside poly A runs
Missense
Missense light chain Missense non-light chain
Splice site
Conserved Non-conserved
Unknown
Single exon
3.57 (2.26-5.66)
Pooled OR
9.24 (5.39-15.84)
1.09 (0.54-2.2)
1.37 (1.05-1.79)
1.80 (1.22-2.64)
1.04 (0.73-1.49)
0.92 (0.57-1.50)
0.51 (0.41-0.65)
0.27(0.17-0.43)
0.30 (0.20-0.44)
0.37 (0.21-0.65)
0.23 (0.14-0.36)
Reference
0.65 (0.50-0.86)
0.95 (0.59-1.54)
0.76 (0.33-1.78)
0.31 (0.05-1.92)
0.37 (0.23-0.59)
Genotype to phenotype correlation: Inhibitor risk hemophilia A
Gouw S et al Blood 2012; 119:2922
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Hemophilia B Leyden: Phenotypic evolution
0 10 20 30 40 50 60 70
150
100
50
0
Normal
Leyden
Brandenburg
AR
FIX
:C %
no
rma
l
Age Funnell, APW et al Trends in Genetics 2014; 30: 18-23
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Genotyping Platelet Disorders: Prognostic
• Hermansky-Pudlack (HPS 1 and 4)
• Type 1: monitor for pulmonary fibrosis
• MYH9-related disorders
• Nephritis
• RUNX1 variant
• Increased risk for acute myeloid leukemia
• Targeted platelet panels vs while exome or genome sequencing
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Take home message: For patients with established phenotypic diagnosis of bleeding disorders •Genotyping has prognostic value
•Technology used in genotyping depends on cost/efficiency/affordability etc
•PCR/Sequencing: for targeted mutation analysis
•NGS technologies: costs will decline
•Exonic vs intronic mutations
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Illustrative case(s): Bleeding disorders
•Mild lifelong bleeding symptoms no diagnosis forthcoming with phenotypic testing
• 41 yr old female:
• Menorrhagia at menarche, excessive spontaneous bruising, prolonged bleeding with minor cuts, frequent epistaxis, excess bleeding with procedures: LEEP, hysterectomy, gum surgery
• ISTH Bleeding assessment tool: Score 13 (normal <6)
• Extensive laboratory testing normal: PT/APTT, thrombin time, VWF assays, platelet aggregation, platelet electron microscopy, PAI-1, alpha 2 antiplasmin, ROTEM, TEG. etc
• Phenotype diagnosis NOT established
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Outcomes of NGS testing in coagulation disorders
• Thrombogenomics HTS group
• 2396 index patients (bleeding with or without phenotypic diagnosis, thrombocytopenia, platelet function defect, thrombosis)
• Referred for NGS assay after diagnosis of
• Bleeding disorder (phenotypic diagnosis established)or
• Undiagnosed bleeding disorder (phenotypic diagnosis NOT established) or
• Thrombophilia
Downes K et al Blood 2019; 134:2082
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Diagnostic Yield: Patients with Bleeding disorders
0 20 40 60 80 100
Platelet count (n=335)
Platelet function (n=430)
Coagulation (n=728)
Unexplained bleeding (n=619)
All patients (n=2396)
Proportion of patients (%)
Pathogenic
Likely Pathogenic
Variant of uncertain
significance
No variant
Downes K et al Blood 2019; 134:2082
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Whole exome sequencing in bleeding disorders
Thrombocytopenia (n=17) Plt function defect (n=19) Undiagnosed (n=51)
4/17 (23%)
Diagnostic Yield
1/19 (5%)
P2RY12 MYH9 x 2
SLFN14
GP9
7/51 (13%)
F7 & F13A1
F2, F8, VWF
GP1BA
MPL
F2
F5
F11
Mild low VWF
Heterozygous
Saes JL et al Haemophilia 2019; 25: 127
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Back to the patient (41 year old female with undiagnosed bleeding): Beighton Score 7/9
Possible hypermobile EHD
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Take home message
•For patients with undiagnosed bleeding disorders: yield of finding a pathogenic variant with NGS is low
•Criteria for pathogenicity is evolving as functional data are generated
•Vascular disorders (e.g. Ehlers Danlos) will not be detected by coagulation assays
•Clinical evaluation is important (Beighton Score)
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Illustrative case(s): Thrombophilia Testing
• Who, how and when?
• Asymptomatic patient: genotyping for VTE prophylaxis strategy
• No indication for thrombophilia testing for VTE prophylaxis risk stratification
• Symptomatic patient with VTE
• Provoked
• ASH Choosing Wisely 2018: do not order thrombophilia testing
• Unprovoked Venous Thromboembolism:
• Young individual/Strong family history of VTE
• Recurrent VTE
• Cost effective approach: plasma based assays
• Is there a role for Next generation sequencing?
• Approach: exome vs genome
Blood 2013; 122: 3879 & 2014;124:3524
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Problems associated with phenotypic (plasma/protein) based assays
50
40
30
20
10
0 AT
activity
PC
activity
PS
Tot-Ag
PS
Fr Ag
PS
activity
CV
(%)
Overall error rate 2 to 8%:
false-normal (deficient plasma) OR false-abnormal (normal plasma)
Favaloro et al Sem Thromb Hemost 2005; 31:49
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Identification of risk factors for VTE: NGS technology
•Current studies based on candidate gene approach
•Evolving to GWAS studies
•Approach will depend on individual goals:
•Genotype vs Discovery of novel alleles
Cunha MLR et al Thromb Hemost 2015; 114: 920-932
Morange, PE JTH 2011; 9:Supp1: 258-264
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Genetic risk factors for VTE:What is currently known ?
Locus SNP Allele Frequency OR/RR Phenotype
ABO O,A2 vs A1B 0.3 1.5 FVIII/VWF
F2 rs1799963 G/A 0.02 2.5 FII
F5 rs6025 G/A 0.05 3.0 APC-R
FGG rs2066865 C/T 0.25 1.47 Fibrinogen
PROC
Multiple private
10
PC def
PROS1 PS def
SERPINC1 AT def
Morange, PE JTH 2011; 9:Supp1: 258-264
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Outcomes of NGS testing in thrombophilia
•Thrombogenomics HTS group
•2396 index patients (bleeding with or without phenotypic diagnosis, thrombocytopenia, platelet function defect, thrombosis)
•Referred for NGS assay after finding of a thrombophilia, bleeding disorder or undiagnosed.
•Thrombotic patients: abnormality of protein C anticoagulant pathway (PC & PS)
•Diagnostic yield: 48.9%
Downes K et al Blood 2019; 134:2082
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Diagnostic Yield
0 20 40 60 80 100
Thrombotic (n=284)
Platelet count (n=335)
Platelet function (n=430)
Coagulation (n=728)
Unexplained bleeding (n=619)
All patients (n=2396)
Proportion of patients (%)
Pathogenic
Likely Pathogenic
Variant of uncertain
significance
No variant
Downes K et al Blood 2019; 134:2082
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Application of GWAS to determining risk loci
Locus SNP Allele Frequency OR Phenotype
C4BPB/C4BP
A
rs3813948 T/C 0.08 1.18 C4BP
F11 rs2036914
rs2289252
C/T
C/T
0.52
0.41
1.35 FXI
GP6 rs1613662 A/G 0.82 1.15 Plt act.
KNG1 rs710446 T/C 0.45 1.2 aPTT
HIVEP1 rs169713 T/C 0.21 1.2 Unknown
SERPINC1 rs2227589 C/T 0.1 1.29 AT
STXBP5 rs1039084 A/G 0.46 1.11
VWF TC2N rs184841 C/T 0.44 1.27
VWF rs1063856 A/G 0.37 1.15
Morange, PE JTH 2011; 9:Supp1: 258-264
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Findings from GWAS
• Findings:
• Rare genetic variants influence risk for VTE
• Individually have a low OR/RR for VTE
• Novel risk alleles are still being discovered (inflammation related genes)
• Potential explanations:
• VTE is a multifactorial disease
• Study methodology
• Population studied
• Statistical power
• large numbers approximately 140,000 cases required to identify 10 alleles with an OR of 1.12
Lotta L, et al.BMC Med Genomics 2012; 5: 7.
Lotta L, et al. J Thromb Haemost 2013; 11: 1228–1239.
Reviewed in:Cunha MLR et al Thromb Hemost 2015; 114: 920-932
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Conclusions • Next Generation Sequencing is a technology (to be judiciously applied)
• Genotyping patients with established phenotypic diagnoses is relevant (prognostic)
• Currently targeted testing most likely optimal approach
• Single gene vs Limited Panel approach
• Advantages of NGS: develop ‘dynamic’ panels: additional of discovery of new genes
• Option to have whole genome/exome
• (masking of non significant genes)
• Unmasking/analysis of genes as they become relevant
• Indiscriminate genotyping of patients with no phenotypic diagnosis has a low yield
• Efforts to continue research and clinical testing aids in understanding biology of disease
• Important to report unreported variants to databases to advance knowledge
• Current needs and future potential options:
• Current strategy: counsel individual patients based on population studies
• Future strategy: counsel individual patients based on individualized risks
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pruthi.rajiv@mayo.edu
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