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

Zanti M 1 , O'Mahony DG 1 , Parsons MT 2 , Li H 3 , Dennis J 4 , Aittomäkkiki K 5 Show all authors , Andrulis IL 6 , Anton-Culver H 7 , Aronson KJ 8 , Augustinsson A 9 , Becher H 10 , Bojesen SE 11 , Bolla MK 4 , Brenner H 12 , Brown MA 13 , Buys SS 14 , Canzian F 15 , Caputo SM 16 , Castelao JE 17 , Chang-Claude J 18 , GC-HBOC study Collaborators , Czene K 19 , Daly MB 20 , De Nicolo A 21 , Devilee P 22 , Dörk T 23 , Dunning AM 24 , Dwek M 25 , Eccles DM 26 , Engel C 27 , Evans DG 28 , Fasching PA 29 , Gago-Dominguez M 30 , García-Closas M 31 , García-Sáenz JA 32 , Gentry-Maharaj A 33 , Geurts-Giele WRR 34 , Giles GG 35 , Glendon G 6 , Goldberg MS 36 , Garcia EBG 37 , Güendert M 38 , Guénel P 39 , Hahnen E 40 , Haiman CA 41 , Hall P 19 , Hamann U 42 , Harkness EF 43 , Hogervorst FBL 44 , Hollestelle A 45 , Hoppe R 46 , Hopper JL 47 , Houdayer C 48 , Houlston RS 49 , Howell A 50 , ABCTB Investigators , Jakimovska M 51 , Jakubowska A 52 , Jernström H 9 , John EM 53 , Kaaks R 18 , Kitahara CM 54 , Koutros S 31 , Kraft P 55 , Kristensen VN 56 , Lacey JV 57 , Lambrechts D 58 , Léoné M 59 , Lindblom A 60 , Lubiński J 52 , Lush M 4 , Mannermaa A 61 , Manoochehri M 42 , Manoukian S 62 , Margolin S 63 , Martinez ME 64 , Menon U 33 , Milne RL 35 , Monteiro AN 65 , Murphy RA 66 , Neuhausen SL 67 , Nevanlinna H 68 , Newman WG 28 , Offit K 69 , Park SK 70 , James P 71 , Peterlongo P 72 , Peto J 73 , Plaseska-Karanfilska D 51 , Punie K 74 , Radice P 75 , Rashid MU 42 , Rennert G 76 , Romero A 77 , Rosenberg EH 78 , Saloustros E 79 , Sandler DP 80 , Schmidt MK 81 , Schmutzler RK 40 , Shu XO 82 , Simard J 83 , Southey MC 35 , Stone J 47 , Stoppa-Lyonnet D 16 , Tamimi RM 84 , Tapper WJ 26 , Taylor JA 80 , Teo SH 85 , Teras LR 86 , Terry MB 87 , Thomassen M 88 , Troester MA 89 , Vachon CM 90 , Vega A 91 , Vreeswijk MPG 92 , Wang Q 4 , Wappenschmidt B 40 , Weinberg CR 93 , Wolk A 94 , Zheng W 82 , Feng B 95 , Couch FJ 96 , Spurdle AB 2 , Easton DF 4 , Goldgar DE 95 , Michailidou K 1

Affiliations 

  • 1 Biostatistics Unit, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
  • 2 Population Health Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
  • 3 Cancer Control and Population Science, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA
  • 4 Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
  • 5 Department of Clinical Genetics, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
  • 6 Fred A. Litwin Center for Cancer Genetics, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, Ontario, Canada
  • 7 Department of Medicine, Genetic Epidemiology Research Institute, University of California Irvine, Irvine, CA, USA
  • 8 Department of Public Health Sciences, and Cancer Research Institute, Queen's University, Kingston, ON, Canada
  • 9 Oncology, Department of Clinical Sciences in Lund, Lund University, Lund, Sweden
  • 10 Institute for Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
  • 11 Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
  • 12 Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
  • 13 School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, Queensland, Australia
  • 14 Department of Internal Medicine and Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA
  • 15 Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany
  • 16 Service de Génétique, Institut Curie, Paris, France
  • 17 Oncology and Genetics Unit, Instituto de Investigación Sanitaria Galicia Sur (IISGS), Xerencia de Xestion Integrada de Vigo-SERGAS, Vigo, Spain
  • 18 Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
  • 19 Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
  • 20 Department of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, PA, USA
  • 21 Center for Omics Sciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
  • 22 Department of Pathology, Leiden University Medical Center, Leiden, the Netherlands
  • 23 Gynaecology Research Unit, Hannover Medical School, Hannover, Germany
  • 24 Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
  • 25 School of Life Sciences, University of Westminster, London, UK
  • 26 Faculty of Medicine, University of Southampton, Southampton, UK
  • 27 Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
  • 28 Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
  • 29 Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, University Hospital Erlangen, Erlangen, Germany
  • 30 Genomic Medicine Group, International Cancer Genetics and Epidemiology Group, Fundación Pública Galega de Medicina Xenómica, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago, SERGAS, Santiago de Compostela, Spain
  • 31 Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD, USA
  • 32 Medical Oncology Department, Hospital Clínico San Carlos, Instituto de Investigación Sanitaria San Carlos (IdISSC), Centro Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain
  • 33 MRC Clinical Trials Unit, Institute of Clinical Trials & Methodology, University College London, London, UK
  • 34 Department of Clinical Genetics, Erasmus University Medical Center, Rotterdam, the Netherlands
  • 35 Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
  • 36 Department of Medicine, McGill University, Montréal, QC, Canada
  • 37 Department of Clinical Genetics, Maastricht University Medical Center, Maastricht, the Netherlands
  • 38 Molecular Epidemiology Group, C080, German Cancer Research Center (DKFZ), Heidelberg, Germany
  • 39 Team 'Exposome and Heredity', CESP, Gustave Roussy, INSERM, University Paris-Saclay, UVSQ, Villejuif, France
  • 40 Center for Familial Breast and Ovarian Cancer, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
  • 41 Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
  • 42 Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
  • 43 Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
  • 44 Family Cancer Clinic, The Netherlands Cancer Institute - Antoni van Leeuwenhoek hospital, Amsterdam, the Netherlands
  • 45 Department of Medical Oncology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
  • 46 Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany
  • 47 Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
  • 48 Department of Genetics, F76000 and Normandy University, UNIROUEN, Inserm U1245, Normandy Centre for Genomic and Personalized Medicine, Rouen University Hospital, Rouen, France
  • 49 Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
  • 50 Division of Cancer Sciences, University of Manchester, Manchester, UK
  • 51 Research Centre for Genetic Engineering and Biotechnology 'Georgi D. Efremov', MASA, Skopje, Republic of North Macedonia
  • 52 Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
  • 53 Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA
  • 54 Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
  • 55 Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
  • 56 Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway
  • 57 Department of Computational and Quantitative Medicine, City of Hope, Duarte, CA, USA
  • 58 Laboratory for Translational Genetics, Department of Human Genetics, KU Leuven, Leuven, Belgium
  • 59 Genetic and Cancer Medical Laboratory HCL-CLB, Hospices Civils de Lyon, Bron, France
  • 60 Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
  • 61 Translational Cancer Research Area, University of Eastern Finland, Kuopio, Finland
  • 62 Unit of Medical Genetics, Department of Medical Oncology and Hematology, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milan, Italy
  • 63 Department of Oncology, Södersjukhuset, Stockholm, Sweden
  • 64 Moores Cancer Center, University of California San Diego, La Jolla, CA, USA
  • 65 Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA
  • 66 School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada
  • 67 Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, CA, USA
  • 68 Department of Obstetrics and Gynecology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
  • 69 Clinical Genetics Research Lab, Department of Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
  • 70 Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea
  • 71 Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Victoria, Australia
  • 72 Genome Diagnostics Program, IFOM - ETS the AIRC Institute of Molecular Oncology, Milan, Italy
  • 73 Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
  • 74 Department of General Medical Oncology and Multidisciplinary Breast Centre, Leuven Cancer Institute and University Hospitals Leuven, Leuven, Belgium
  • 75 Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori (INT), Milan, Italy
  • 76 Clalit National Cancer Control Center, Carmel Medical Center and Technion Faculty of Medicine, Haifa, Israel
  • 77 Medical Oncology Department, Hospital Universitario Puerta de Hierro, Madrid, Spain
  • 78 Department of Pathology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek hospital, Amsterdam, the Netherlands
  • 79 Department of Oncology, University Hospital of Larissa, Larissa, Greece
  • 80 Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
  • 81 Division of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, the Netherlands
  • 82 Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
  • 83 Genomics Center, Centre Hospitalier Universitaire de Québec - Université Laval Research Center, Québec City, QC, Canada
  • 84 Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
  • 85 Breast Cancer Research Programme, Cancer Research Malaysia, Subang Jaya, Selangor, Malaysia
  • 86 Department of Population Science, American Cancer Society, Atlanta, GA, USA
  • 87 Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
  • 88 Department of Clinical Genetics, Odense University Hospital, Odence C, Denmark
  • 89 Department of Epidemiology, Gillings School of Global Public Health and UNC Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
  • 90 Department of Quantitative Health Sciences, Division of Epidemiology, Mayo Clinic, Rochester, MN, USA
  • 91 Centro de Investigación en Red de Enfermedades Raras (CIBERER), Madrid, Spain
  • 92 Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
  • 93 Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
  • 94 Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
  • 95 Department of Dermatology, Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, UT, USA
  • 96 Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
Hum Mutat, 2023;2023.
PMID: 38725546 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 analyses 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 to classical case-control methods. As an initiative from the ENIGMA Analytical Working Group, we provide user-friendly scripts and pre-formatted excel calculators for implementation of the method for rare variants in BRCA1, BRCA2 and other high-risk genes with known penetrance.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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