A weighted, score-based variant classification system
based on the ACMG ISV guidelines
Keith Nykamp, PhD
Clinical Genomics Scientist
INVITAE
© 2015 Invitae Corporation. All Rights Reserved. | CONFIDENTIAL | 1
Our Mission
Bring genetic information into medical practice to improve the healthcare
of billions of people.
genomic sequence
Variant Classification
health management
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What is needed?
A scalable and efficient method for confident and consistent variant classification
Thousands
ClinVar Assertions
100
100%
90
90%
80
80%
submissions
70
70%
% single
novel
variant
submissions
percent
60
60%
50
50%
40
40%
30
30%
20
20%
10
10%
0
Mar
2013
Mar
2015
germilne
# germline
variants
# clinical testing
clinical_testing
0%
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Standardization efforts
ACMG/AMP ISV Guidelines
Draft
Aug
2013
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Standardization efforts
ACMG/AMP ISV Guidelines
Draft
Aug
2013
Published
Mar
2015
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Standardization efforts
ACMG/AMP ISV Guidelines
Draft
Published
Mar
2015
Aug
2013
v1
Our approach
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A score-based approach
PVS1
BA1
PS1 PS2
PS3 PS4
BS1 BS2
BS3 BS4
PM1
PM4
PM5
PM2
PM3
PM6
BP1
BP3
BP5
PP1
PP2
PP3
PP4
BP2
BP4
BP6
PP5
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A score-based approach
Very
Strong
PVS1
BA1
PVS1 BA1
PS1 PS2
PS3 PS4
BS1 BS2
BS3 BS4
PM1
PM4
PM5
PM2
PM3
PM6
BP1
BP3
BP5
PP1
PP2
PP3
PP4
Strong
PS1 PS2 BS1 BS2
PS3 PS4 BS3 BS4
Moderate
BP2
BP4
BP6
PM1 PM2 BP1 BP2
PM3 PM4 BP3 BP4
PM5 PM6 BP5 BP6
Supporting
PP1 PP2 PP3
PP4 PP5
PP5
© 2015 Invitae Corporation. All Rights Reserved. | CONFIDENTIAL | 8
A score-based approach
Very
Strong
PVS1 BA1
Strong
PS1 PS2 BS1 BS2
PS3 PS4 BS3 BS4
Moderate
PM1 PM2 BP1 BP2
PM3 PM4 BP3 BP4
PM5 PM6 BP5 BP6
Supporting
PP1 PP2 PP3
PP4 PP5
4.0POINTS
– 5.0
8
CRITERIA
2.5POINTS
– 3.5
CRITERIA
1.5POINTS
– 2.0
2
CRITERIA
0.5POINTS
– 1.0
CRITERIA
9
13
© 2015 Invitae Corporation. All Rights Reserved. | CONFIDENTIAL | 9
Implementation, expert review and evolution
Draft
Published
Aug
2013
v1
v2
Mar
2015
July
2014
May
2014
Oct
2013
v3
22
CRITERIA
v3.1
89
CRITERIA
11,000
VARIANTS
Our Signout Team
•
•
•
•
Add/remove criteria
Change scores, adjust LB threshold
create priority groups
add usage notes
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Hierarchical score-based rules for variant classification
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Hierarchical score-based rules for variant classification
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Sherloc Interpretations
ClinVar Consensus Interpretation = Likely Pathogenic
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Confidence and consistency
• Sherloc interpretations were often (92.2%) in the consensus majority
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Confidence and consistency
• Sherloc interpretations were often (92.2%) in the consensus majority
• Almost all differences were P-LP or VUS-LB-B differences
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Confidence and consistency
• Sherloc interpretations were often (92.2%) in the consensus majority
• Almost all differences were P-LP or VUS-LB-B differences
• The single exception was a Sherloc VUS compared to a Consensus LP
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Confidence and consistency
• Other laboratories were also often in the consensus, but less so (85.7%)
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Confidence and consistency
• Other laboratories were also often in the consensus, but less so (85.7%)
• The average lab had more clinically significant differences
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Confidence and consistency
Re-evaluated 42 variants with 1 or more discordant classifications
• 39 (92.5%) matched the previous interpretation exactly
• 2 matched within the same pathogenicity group:
- 1 P to LP change with inconsistent use of Clinical Findings
- 1 B to LB change with omission of Misc. Benign evidence
• 1 changed (VUS to LP) with addition of Misc. Pathogenic evidence
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Community Involvement
We think Sherloc is useful because it is adaptable, efficient
and transparent
The Sherloc point system and SOPs will be made available
• May be useful to the community, ClinGen working groups
• In the near term, contact us directly
• Medium term, we hope to publish
• We welcome input and guidance from the community
© 2015 Invitae Corporation. All Rights Reserved. | CONFIDENTIAL | 20
Acknowledgements
CLINICAL GENOMICS GROUP
• M A R T I N P O W E R S
• M I C H A E L A N D E R S O N
• Y U YA K O B AYA S H I
• S C O T T T O P P E R
S O F T WA R E E N G I N E E R I N G
• J O N S O R E N S O N
• V I N C E N T F U S A R O
GENETICS DEVELOPMENT
• E M I LY H A R E
• K AT R I N A M I T C H E L
D ATA A N A LY S I S
• S T E V E L I N C O L N
• S H A N YA N G
C O M M U N I C AT I O N S
• K AT H E R I N E S T U E L A N D
• J I M B U T L E R
