A likelihood ratio approach for utilizing case-control data in the clinical classification of rare sequence variants: Application to BRCA1 and BRCA2

Zanti M, O'Mahony DG, Parsons MT, Li H, Dennis J, Aittomäkkiki K, Andrulis IL, Anton-Culver H, Aronson KJ, Augustinsson A, Becher H, Bojesen SE, Bolla MK, Brenner H, Brown MA, Buys SS, Canzian F, Caputo SM, Castelao JE, Chang-Claude J, Czene K, Daly MB, De Nicolo A, Devilee P, Dörk T, Dunning AM, Dwek M, Eccles DM, Engel C, Gareth Evans D, Fasching P, Gago-Dominguez M, García-Closas M, García-Sáenz JA, Gentry-Maharaj A, Geurts-Giele WR, Giles GG, Glendon G, Goldberg MS, Gómez Garcia EB, Göendert M, Guénel P, Hahnen E, Haiman CA, Hall P, Hamann U, Harkness EF, Hogervorst FB, Hollestelle A, Hoppe R, Hopper JL, Houdayer C, Houlston RS, Howell A, Jakimovska M, Jakubowska A, Jernström H, John EM, Kaaks R, Kitahara CM, Koutros S, Kraft P, Kristensen VN, Lacey JV, Lambrechts D, Léoné M, Lindblom A, Lubiski J, Lush M, Mannermaa A, Manoochehri M, Manoukian S, Margolin S, Martinez ME, Menon U, Milne RL, Monteiro AN, Murphy RA, Neuhausen SL, Nevanlinna H, Newman WG, Offit K, Park SK, James P, Peterlongo P, Peto J, Plaseska-Karanfilska D, Punie K, Radice P, Rashid MU, Rennert G, Romero A, Rosenberg EH, Saloustros E, Sandler DP, Schmidt MK, Schmutzler RK, Shu XO, Simard J, Southey MC, Stone J, Stoppa-Lyonnet D, Tamimi RM, Tapper WJ, Taylor JA, Teo SH, Teras LR, Terry MB, Thomassen M, Troester MA, Vachon CM, Vega A, Vreeswijk MP, Wang Q, Wappenschmidt B, Weinberg CR, Wolk A, Zheng W, Feng B, Couch FJ, Spurdle AB, Easton DF, Goldgar DE, Michailidou K (2023)

Publication Type: Journal article

Publication year: 2023

Journal

Book Volume: 2023

Article Number: 9961341

DOI: 10.1155/2023/9961341

Abstract

A large number of variants identified through clinical genetic testing in disease susceptibility genes are of uncertain significance (VUS). Following the recommendations of the American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP), the frequency in case-control datasets (PS4 criterion) can inform their interpretation. We present a novel case-control likelihood ratio-based method that incorporates gene-specific age-related penetrance. We demonstrate the utility of this method in the analysis of simulated and real datasets. In the analysis of simulated data, the likelihood ratio method was more powerful compared to other methods. Likelihood ratios were calculated for a case-control dataset of BRCA1 and BRCA2 variants from the Breast Cancer Association Consortium (BCAC) and compared with logistic regression results. A larger number of variants reached evidence in favor of pathogenicity, and a substantial number of variants had evidence against pathogenicity findings that would not have been reached using other case-control analysis methods. Our novel method provides greater power to classify rare variants compared with classical case-control methods. As an initiative from the ENIGMA Analytical Working Group, we provide user-friendly scripts and preformatted Excel calculators for implementation of the method for rare variants in BRCA1, BRCA2, and other high-risk genes with known penetrance.

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Involved external institutions

QIMR Berghofer Medical Research Institute (früher: the Queensland Institute of Medical Research) Australia (AU) Lund University / Lunds universitet Sweden (SE) Universitätsklinikum Hamburg-Eppendorf (UKE) Germany (DE) University of Cambridge United Kingdom (GB) Gentofte Hospital Denmark (DK) Deutsches Krebsforschungszentrum (DKFZ) Germany (DE) University of Queensland Australia (AU) University of Utah United States (USA) (US) Instituto de Investigación Sanitaria Galicia Sur Spain (ES) Institut Curie France (FR) University of Southampton United Kingdom (GB) Karolinska Institute Sweden (SE) Fox Chase Cancer Center United States (USA) (US) University of Westminster United Kingdom (GB) Ospedale San Raffaele (früher: Centro San Raffaele del Monte Tabor Foundation) Italy (IT) Leiden University Medical Center Netherlands (NL) Medizinische Hochschule Hannover (MHH) / Hannover Medical School Germany (DE) Complejo Hospitalario Universitario de Santiago de Compostela Spain (ES) University of Manchester United Kingdom (GB) Universität Leipzig Germany (DE) National Cancer Institute (NCI) United States (USA) (US) Hospital Clínico San Carlos Spain (ES) Antoni van Leeuwenhoek Netherlands (NL) University College London (UCL) United Kingdom (GB) Erasmus University Medical Center (MC) Netherlands (NL) Cancer Council Victoria Australia (AU) Mount Sinai Hospital (MSH) Canada (CA) Maastricht University Netherlands (NL) Keck School of Medicine of USC United States (USA) (US) Research Center in Epidemiology and Population Health / Centre de recherche en Epidémiologie et Santé des Populations (CESP) France (FR) Universitätsklinikum Köln Germany (DE) Dr. Margarete Fischer-Bosch-Institut für Klinische Pharmakologie Germany (DE) Pomeranian Medical University / Pomorski Uniwersytet Medyczny w Szczecinie (PMU) Poland (PL) Melbourne School of Population and Global Health Australia (AU) University of Rouen / Université de Rouen France (FR) Huntsman Cancer Institute United States (USA) (US) Cyprus Institute of Neurology and Genetics Cyprus (CY) Helsinki University Central Hospital (HUCH) / Helsingin seudun yliopistollinen keskussairaala (HYKS) Finland (FI) University of California Irvine United States (USA) (US) Queen's University Canada (CA) Katholieke Universiteit Leuven (KUL) / Catholic University of Leuven Belgium (BE) Hospices Civils de Lyon (CHU) France (FR) Fondazione IRCCS: Istituto Nazionale dei Tumori Italy (IT) H. Lee Moffitt Cancer Center & Research Institute United States (USA) (US) University of British Columbia Canada (CA) City of Hope Medical Center United States (USA) (US) University of Eastern Finland Finland (FI) Södersjukhuset Sweden (SE) Moores Cancer Center United States (USA) (US) Memorial Sloan Kettering Cancer Center United States (USA) (US) Seoul National University (SNU) / 서울대학교 Korea, Republic of (KR) General University Hospital of Larissa Greece (GR) The University of Melbourne Australia (AU) IFOM - FIRC Institute of Molecular Oncology Italy (IT) London School of Hygiene and Tropical Medicine United Kingdom (GB) Research Center for Genetic Engineering and Biotechnology "Georgi D. Efremov" (RCGEB) Republic of North Macedonia (MK) Hospital Universitario Puerta de Hierro - Majadahonda Spain (ES) Clalit Health Services Israel (IL) National Institute of Environmental Health Sciences (NIEHS) United States (USA) (US) Netherlands Cancer Institute (NKI) Netherlands (NL) Centre hospitalier universitaire de Québec Canada (CA) Vanderbilt University Medical Center United States (USA) (US) The Institute of Cancer Research (ICR) United Kingdom (GB) Harvard T.H. Chan School of Public Health United States (USA) (US) Oslo University Hospital / Oslo Universitetssykehus Rikshospitalet Norway (NO) Stanford University United States (USA) (US) Odense Universitetshospital (OUH) Denmark (DK) Mayo Clinic United States (USA) (US) University of North Carolina at Chapel Hill United States (USA) (US) Ciber de Enfermedades Raras (CIBERER) Spain (ES) Cancer Research Initiatives Foundation (CARIF) / Cancer Research Malaysia (CRM) Malaysia (MY) American Cancer Society United States (USA) (US) Columbia University United States (USA) (US)

How to cite

APA:

Zanti, M., O'Mahony, D.G., Parsons, M.T., Li, H., Dennis, J., Aittomäkkiki, K.,... Michailidou, K. (2023). A likelihood ratio approach for utilizing case-control data in the clinical classification of rare sequence variants: Application to BRCA1 and BRCA2. Human Mutation, 2023. https://doi.org/10.1155/2023/9961341

MLA:

Zanti, Maria, et al. "A likelihood ratio approach for utilizing case-control data in the clinical classification of rare sequence variants: Application to BRCA1 and BRCA2." Human Mutation 2023 (2023).

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