Automated variant re-evaluation is labor-balanced and gives clinically relevant results: Hereditary cardiac disease as a use case

Anne Grosen; Charlotte K Lautrup; Emil Bahsen; Henrik K Jensen; Dorte L Lildballe

doi:10.1016/j.ejmg.2024.104981

Automated variant re-evaluation is labor-balanced and gives clinically relevant results: Hereditary cardiac disease as a use case

Anne Grosen, Charlotte K Lautrup, Emil Bahsen, Henrik K Jensen, Dorte L Lildballe^*

^*Corresponding author af dette arbejde

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avis › Tidsskriftartikel › Forskning › peer review

Abstract

BACKGROUND: Genetic findings influence clinical care of patients suspected of hereditary cardiac diseases. As additional knowledge arises over time, the classification of genetic variants may change. The labor cost associated with systematic manual reevaluation for reported variants is substantial. We applied an automated variant classifier for reevaluation of previous reported variants to assess how such tools may assist in manual reevaluation.

METHODS: Historically (2010-2022), patients (N = 2987) suspected of inherited cardiomyopathies or ion-channel disorders were screened for genetic variants in at least one of up to 114 genes. We had reported 1455 unique variants, of which 742 were among the 14 most relevant genes. In the 14-gene-group, we compared our reported classification to that of an autoclassifier and manually reevaluated variant classification of all variants. Among the remaining genes (N = 100), only variants where the autoclassifier predicted change of clinical impact, such as variant of uncertain significance to likely pathogenic or oppositely, were manually reevaluated.

RESULTS: We identified 9% (66/742) of variants with clinical impact in the 14-gene-group. Of these, 91% could have been identified solely evaluating the 120 variants where the autoclassifier had predicted a change of clinical impact. In the 100 remaining genes, a change of clinical impact was identified in 3% (22/713) after manual reevaluation.

CONCLUSION: Using an autoclassifier reduces the workload to identify variants likely to have a change in variant class with clinical impact. Hence, we recommend using such tools to identify the variants most relevant to manually reevaluate to improve patient care.

Originalsprog	Engelsk
Artikelnummer	104981
Tidsskrift	European Journal of Medical Genetics
Vol/bind	72
ISSN	1769-7212
DOI	https://doi.org/10.1016/j.ejmg.2024.104981
Status	Udgivet - dec. 2024

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10.1016/j.ejmg.2024.104981Licens: CC BY-NC-ND

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title = "Automated variant re-evaluation is labor-balanced and gives clinically relevant results: Hereditary cardiac disease as a use case",

abstract = "BACKGROUND: Genetic findings influence clinical care of patients suspected of hereditary cardiac diseases. As additional knowledge arises over time, the classification of genetic variants may change. The labor cost associated with systematic manual reevaluation for reported variants is substantial. We applied an automated variant classifier for reevaluation of previous reported variants to assess how such tools may assist in manual reevaluation.METHODS: Historically (2010-2022), patients (N = 2987) suspected of inherited cardiomyopathies or ion-channel disorders were screened for genetic variants in at least one of up to 114 genes. We had reported 1455 unique variants, of which 742 were among the 14 most relevant genes. In the 14-gene-group, we compared our reported classification to that of an autoclassifier and manually reevaluated variant classification of all variants. Among the remaining genes (N = 100), only variants where the autoclassifier predicted change of clinical impact, such as variant of uncertain significance to likely pathogenic or oppositely, were manually reevaluated.RESULTS: We identified 9% (66/742) of variants with clinical impact in the 14-gene-group. Of these, 91% could have been identified solely evaluating the 120 variants where the autoclassifier had predicted a change of clinical impact. In the 100 remaining genes, a change of clinical impact was identified in 3% (22/713) after manual reevaluation.CONCLUSION: Using an autoclassifier reduces the workload to identify variants likely to have a change in variant class with clinical impact. Hence, we recommend using such tools to identify the variants most relevant to manually reevaluate to improve patient care.",

keywords = "Genetic variant classification, Inherited cardiomyopathy, Inherited ion-channel disease",

author = "Anne Grosen and Lautrup, {Charlotte K} and Emil Bahsen and Jensen, {Henrik K} and Lildballe, {Dorte L}",

year = "2024",

month = dec,

doi = "10.1016/j.ejmg.2024.104981",

language = "English",

volume = "72",

journal = "European Journal of Medical Genetics",

issn = "1769-7212",

publisher = "Elsevier Masson",

}

Automated variant re-evaluation is labor-balanced and gives clinically relevant results: Hereditary cardiac disease as a use case. / Grosen, Anne ; Lautrup, Charlotte K; Bahsen, Emil et al.
I: European Journal of Medical Genetics, Bind 72, 104981, 12.2024.

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avis › Tidsskriftartikel › Forskning › peer review

TY - JOUR

T1 - Automated variant re-evaluation is labor-balanced and gives clinically relevant results

T2 - Hereditary cardiac disease as a use case

AU - Grosen, Anne

AU - Lautrup, Charlotte K

AU - Bahsen, Emil

AU - Jensen, Henrik K

AU - Lildballe, Dorte L

PY - 2024/12

Y1 - 2024/12

N2 - BACKGROUND: Genetic findings influence clinical care of patients suspected of hereditary cardiac diseases. As additional knowledge arises over time, the classification of genetic variants may change. The labor cost associated with systematic manual reevaluation for reported variants is substantial. We applied an automated variant classifier for reevaluation of previous reported variants to assess how such tools may assist in manual reevaluation.METHODS: Historically (2010-2022), patients (N = 2987) suspected of inherited cardiomyopathies or ion-channel disorders were screened for genetic variants in at least one of up to 114 genes. We had reported 1455 unique variants, of which 742 were among the 14 most relevant genes. In the 14-gene-group, we compared our reported classification to that of an autoclassifier and manually reevaluated variant classification of all variants. Among the remaining genes (N = 100), only variants where the autoclassifier predicted change of clinical impact, such as variant of uncertain significance to likely pathogenic or oppositely, were manually reevaluated.RESULTS: We identified 9% (66/742) of variants with clinical impact in the 14-gene-group. Of these, 91% could have been identified solely evaluating the 120 variants where the autoclassifier had predicted a change of clinical impact. In the 100 remaining genes, a change of clinical impact was identified in 3% (22/713) after manual reevaluation.CONCLUSION: Using an autoclassifier reduces the workload to identify variants likely to have a change in variant class with clinical impact. Hence, we recommend using such tools to identify the variants most relevant to manually reevaluate to improve patient care.

AB - BACKGROUND: Genetic findings influence clinical care of patients suspected of hereditary cardiac diseases. As additional knowledge arises over time, the classification of genetic variants may change. The labor cost associated with systematic manual reevaluation for reported variants is substantial. We applied an automated variant classifier for reevaluation of previous reported variants to assess how such tools may assist in manual reevaluation.METHODS: Historically (2010-2022), patients (N = 2987) suspected of inherited cardiomyopathies or ion-channel disorders were screened for genetic variants in at least one of up to 114 genes. We had reported 1455 unique variants, of which 742 were among the 14 most relevant genes. In the 14-gene-group, we compared our reported classification to that of an autoclassifier and manually reevaluated variant classification of all variants. Among the remaining genes (N = 100), only variants where the autoclassifier predicted change of clinical impact, such as variant of uncertain significance to likely pathogenic or oppositely, were manually reevaluated.RESULTS: We identified 9% (66/742) of variants with clinical impact in the 14-gene-group. Of these, 91% could have been identified solely evaluating the 120 variants where the autoclassifier had predicted a change of clinical impact. In the 100 remaining genes, a change of clinical impact was identified in 3% (22/713) after manual reevaluation.CONCLUSION: Using an autoclassifier reduces the workload to identify variants likely to have a change in variant class with clinical impact. Hence, we recommend using such tools to identify the variants most relevant to manually reevaluate to improve patient care.

KW - Genetic variant classification

KW - Inherited cardiomyopathy

KW - Inherited ion-channel disease

UR - http://www.scopus.com/inward/record.url?scp=85207907246&partnerID=8YFLogxK

U2 - 10.1016/j.ejmg.2024.104981

DO - 10.1016/j.ejmg.2024.104981

M3 - Journal article

C2 - 39481677

SN - 1769-7212

VL - 72

JO - European Journal of Medical Genetics

JF - European Journal of Medical Genetics

M1 - 104981

ER -

Automated variant re-evaluation is labor-balanced and gives clinically relevant results: Hereditary cardiac disease as a use case

Abstract

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