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Comparison of the ABC and ACMG systems for variant classification.

Gunnar HougeEirik BratlandIngvild AukrustKristian TvetenGabrielė ŽukauskaitėIvona SansovicAlejandro J Brea-FernándezKarin MayerTeija PaakkolaCaoimhe McKennaWilliam WrightMilica Keckarevic MarkovicDorte Launholt LildballeMichal KonecnyThomas SmolPia AlhopuroEstelle Arnaud GouttenoireKatharina ObeidAlbena TodorovaMilena JankovicJoanna M LubienieckaMaja StojiljkovicMarie-Pierre BuisineBjørn Ivar HaukanesMarie LoransHanno RoomereFrançois Mickaël PetitMaria K HaanpääClaire BeneteauBelén PérezDijana Plaseska-KaranfilskaMatthias RathNico FuhrmannBibiana I FerreiraCoralea StephanouWenche SjursenAleš MaverCécile RouzierAdela Chiriță-EmandiJoão GonçalvesWei Cheng David KuekMartin BrolyLonneke Haer-WigmanMeow-Keong ThongSok-Kun TaeMichaela HyblovaJohan T den DunnenAndreas Laner
Published in: European journal of human genetics : EJHG (2024)
The ABC and ACMG variant classification systems were compared by asking mainly European clinical laboratories to classify variants in 10 challenging cases using both systems, and to state if the variant in question would be reported as a relevant result or not as a measure of clinical utility. In contrast to the ABC system, the ACMG system was not made to guide variant reporting but to determine the likelihood of pathogenicity. Nevertheless, this comparison is justified since the ACMG class determines variant reporting in many laboratories. Forty-three laboratories participated in the survey. In seven cases, the classification system used did not influence the reporting likelihood when variants labeled as "maybe report" after ACMG-based classification were included. In three cases of population frequent but disease-associated variants, there was a difference in favor of reporting after ABC classification. A possible reason is that ABC step C (standard variant comments) allows a variant to be reported in one clinical setting but not another, e.g., based on Bayesian-based likelihood calculation of clinical relevance. Finally, the selection of ACMG criteria was compared between 36 laboratories. When excluding criteria used by less than four laboratories (<10%), the average concordance rate was 46%. Taken together, ABC-based classification is more clear-cut than ACMG-based classification since molecular and clinical information is handled separately, and variant reporting can be adapted to the clinical question and phenotype. Furthermore, variants do not get a clinically inappropriate label, like pathogenic when not pathogenic in a clinical context, or variant of unknown significance when the significance is known.
Keyphrases
  • machine learning
  • deep learning
  • copy number
  • adverse drug
  • healthcare
  • emergency department
  • computed tomography
  • social media
  • biofilm formation
  • genome wide