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Quantifying prediction of pathogenicity for within-codon concordance (PM5) using 7541 functional classifications of BRCA1 and MSH2 missense variants

Quantifying prediction of pathogenicity for within-codon concordance (PM5) using 7541 functional classifications of BRCA1 and MSH2 missense variants
Quantifying prediction of pathogenicity for within-codon concordance (PM5) using 7541 functional classifications of BRCA1 and MSH2 missense variants

Purpose: conditions and thresholds applied for evidence weighting of within-codon concordance (PM5) for pathogenicity vary widely between laboratories and expert groups. Because of the sparseness of available clinical classifications, there is little evidence for variation in practice.

Mehods: we used as a truthset 7541 dichotomous functional classifications of BRCA1 and MSH2, spanning 311 codons of BRCA1 and 918 codons of MSH2, generated from large-scale functional assays that have been shown to correlate excellently with clinical classifications. We assessed PM5 at 5 stringencies with incorporation of 8 in silico tools. For each analysis, we quantified a positive likelihood ratio (pLR, true positive rate/false positive rate), the predictive value of PM5-lookup in ClinVar compared with the functional truthset.

Results: pLR was 16.3 (10.6-24.9) for variants for which there was exactly 1 additional colocated deleterious variant on ClinVar, and the variant under examination was equally or more damaging when analyzed using BLOSUM62. pLR was 71.5 (37.8-135.3) for variants for which there were 2 or more colocated deleterious ClinVar variants, and the variant under examination was equally or more damaging than at least 1 colocated variant when analyzed using BLOSUM62.

Conclusion: these analyses support the graded use of PM5, with potential to use it at higher evidence weighting where more stringent criteria are met.

ACMG, Classification, Codon, PM5, Variant
1098-3600
552-563
Loong, Lucy
a8745718-75a4-49a5-beac-ff8de8c2e854
Cubuk, Cankut
9a916072-4100-4c45-ab8e-8a67cf6e2170
Choi, Subin
beaa809f-6f77-487b-954f-9e2f336ba557
Allen, Sophie
82cd9eb2-886d-4323-94d1-2cfd3f94792d
Torr, Beth
930d8ffc-e67f-401b-a44d-b15dd8c9010a
Garrett, Alice
d8fcdea3-8231-4d5e-8ada-4f932ca1a0c3
et al.,
ae4903c5-41d6-4d6f-a17f-317750752b09
Loveday, Chey
bed064d6-13e9-4429-b847-5ecaaf3f5e19
Durkie, Miranda
7caca497-e12f-4f13-99e0-f40e767f0163
Callaway, Alison
07ee9b43-9249-4a56-9582-4dc41d613101
Burghel, George J
0288eca6-9ca5-4806-bfeb-2f963643d326
Drummond, James
aceffa7d-29af-47e2-82da-9f7c2e6d5e6a
Robinson, Rachel
b81f9f32-b468-451d-959b-355aa680f7fb
Berry, Ian R
b720cb74-2247-4906-8c4e-9bde4742b772
Wallace, Andrew
94c565bc-4c46-47ef-b67b-fea558f4a97f
Eccles, Diana M
5b59bc73-11c9-4cf0-a9d5-7a8e523eee23
Tischkowitz, Marc
3c5f5429-fb53-4c80-8a42-6cec37ab67bc
Ellard, Sian
6c9b0ede-8980-4602-b063-444b165baa09
Ware, James S
6e99bb22-caf5-489e-aa0a-27c1423a671e
Hanson, Helen
fe4a8065-8b0d-4b30-a658-cd433570c2ec
Turnbull, Clare
63408861-754b-4f55-a010-29d1bea914e2
CanVIG-UK
Loong, Lucy
a8745718-75a4-49a5-beac-ff8de8c2e854
Cubuk, Cankut
9a916072-4100-4c45-ab8e-8a67cf6e2170
Choi, Subin
beaa809f-6f77-487b-954f-9e2f336ba557
Allen, Sophie
82cd9eb2-886d-4323-94d1-2cfd3f94792d
Torr, Beth
930d8ffc-e67f-401b-a44d-b15dd8c9010a
Garrett, Alice
d8fcdea3-8231-4d5e-8ada-4f932ca1a0c3
et al.,
ae4903c5-41d6-4d6f-a17f-317750752b09
Loveday, Chey
bed064d6-13e9-4429-b847-5ecaaf3f5e19
Durkie, Miranda
7caca497-e12f-4f13-99e0-f40e767f0163
Callaway, Alison
07ee9b43-9249-4a56-9582-4dc41d613101
Burghel, George J
0288eca6-9ca5-4806-bfeb-2f963643d326
Drummond, James
aceffa7d-29af-47e2-82da-9f7c2e6d5e6a
Robinson, Rachel
b81f9f32-b468-451d-959b-355aa680f7fb
Berry, Ian R
b720cb74-2247-4906-8c4e-9bde4742b772
Wallace, Andrew
94c565bc-4c46-47ef-b67b-fea558f4a97f
Eccles, Diana M
5b59bc73-11c9-4cf0-a9d5-7a8e523eee23
Tischkowitz, Marc
3c5f5429-fb53-4c80-8a42-6cec37ab67bc
Ellard, Sian
6c9b0ede-8980-4602-b063-444b165baa09
Ware, James S
6e99bb22-caf5-489e-aa0a-27c1423a671e
Hanson, Helen
fe4a8065-8b0d-4b30-a658-cd433570c2ec
Turnbull, Clare
63408861-754b-4f55-a010-29d1bea914e2

Loong, Lucy, Cubuk, Cankut, Choi, Subin, Allen, Sophie, Torr, Beth, Garrett, Alice and et al., , CanVIG-UK (2022) Quantifying prediction of pathogenicity for within-codon concordance (PM5) using 7541 functional classifications of BRCA1 and MSH2 missense variants. Genetics in Medicine, 24 (3), 552-563. (doi:10.1016/j.gim.2021.11.011).

Record type: Article

Abstract

Purpose: conditions and thresholds applied for evidence weighting of within-codon concordance (PM5) for pathogenicity vary widely between laboratories and expert groups. Because of the sparseness of available clinical classifications, there is little evidence for variation in practice.

Mehods: we used as a truthset 7541 dichotomous functional classifications of BRCA1 and MSH2, spanning 311 codons of BRCA1 and 918 codons of MSH2, generated from large-scale functional assays that have been shown to correlate excellently with clinical classifications. We assessed PM5 at 5 stringencies with incorporation of 8 in silico tools. For each analysis, we quantified a positive likelihood ratio (pLR, true positive rate/false positive rate), the predictive value of PM5-lookup in ClinVar compared with the functional truthset.

Results: pLR was 16.3 (10.6-24.9) for variants for which there was exactly 1 additional colocated deleterious variant on ClinVar, and the variant under examination was equally or more damaging when analyzed using BLOSUM62. pLR was 71.5 (37.8-135.3) for variants for which there were 2 or more colocated deleterious ClinVar variants, and the variant under examination was equally or more damaging than at least 1 colocated variant when analyzed using BLOSUM62.

Conclusion: these analyses support the graded use of PM5, with potential to use it at higher evidence weighting where more stringent criteria are met.

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Accepted/In Press date: 12 November 2021
e-pub ahead of print date: 30 November 2021
Published date: 3 March 2022
Additional Information: Funding Information: L.L., C.L., A.G., S.C., B.T., and H.H. are supported by Cancer Research UK Catalyst Award CanGene-CanVar (C61296/A27223). J.S.W. is funded by Wellcome Trust (107469/Z/15/Z), Medical Research Council (UK), British Heart Foundation (RE/18/4/34215), and the NIHR Imperial Biomedical Research Centre .
Keywords: ACMG, Classification, Codon, PM5, Variant

Identifiers

Local EPrints ID: 455802
URI: http://eprints.soton.ac.uk/id/eprint/455802
ISSN: 1098-3600
PURE UUID: 60be764c-ea42-4767-abbd-c99836f30a68
ORCID for Diana M Eccles: ORCID iD orcid.org/0000-0002-9935-3169

Catalogue record

Date deposited: 05 Apr 2022 16:41
Last modified: 28 Apr 2022 01:35

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Contributors

Author: Lucy Loong
Author: Cankut Cubuk
Author: Subin Choi
Author: Sophie Allen
Author: Beth Torr
Author: Alice Garrett
Author: et al.
Author: Chey Loveday
Author: Miranda Durkie
Author: Alison Callaway
Author: George J Burghel
Author: James Drummond
Author: Rachel Robinson
Author: Ian R Berry
Author: Andrew Wallace
Author: Diana M Eccles ORCID iD
Author: Marc Tischkowitz
Author: Sian Ellard
Author: James S Ware
Author: Helen Hanson
Author: Clare Turnbull
Corporate Author: CanVIG-UK

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