1
|
Buie RW, Rañola JM, Chen AT, Shirts BH. An Algorithm for Optimal Testing in Co‐segregation Analysis. Hum Mutat 2022; 43:547-556. [PMID: 35225377 PMCID: PMC9018554 DOI: 10.1002/humu.24363] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 01/29/2022] [Accepted: 02/23/2022] [Indexed: 11/07/2022]
Abstract
Clinical genetic sequencing tests often identify variants of uncertain significance. One source of data that can help classify the pathogenicity of variants is familial cosegregation analysis. Identifying and genotyping relatives for cosegregation analysis can be time consuming and costly. We propose an algorithm that describes a single measure of expected variant information gain from genotyping a single additional relative in a family. Then we explore the performance of this algorithm by comparing actual recruitment strategies used in 35 families who had pursued cosegregation analysis with synthetic pedigrees of possible testing outcomes if the families had pursued an optimized testing strategy instead. For each actual and synthetic pedigree, we calculated the likelihood ratio of pathogenicity as each successive test was added to the pedigree. We analyzed the differences in cosegregation likelihood ratio over time resulting from actual versus optimized testing approaches. Employing the testing strategy indicated by the algorithm would have led to maximal information more rapidly in 30 of the 35 pedigrees (86%). Many clinical and research laboratories are involved in targeted cosegregation analysis. The algorithm we present can facilitate a data driven approach to optimal relative recruitment and genotyping for cosegregation analysis and more efficient variant classification.
Collapse
Affiliation(s)
- Ronald W. Buie
- Department of Bioinformatics and Medical Education, School of Medicine University of Washington Seattle WA USA
| | | | - Annie T. Chen
- Department of Bioinformatics and Medical Education, School of Medicine University of Washington Seattle WA USA
| | - Brian H. Shirts
- Department of Laboratory Medicine and Pathology, School of Medicine University of Washington Seattle WA USA
| |
Collapse
|
2
|
Fanale D, Pivetti A, Cancelliere D, Spera A, Bono M, Fiorino A, Pedone E, Barraco N, Brando C, Perez A, Guarneri MF, Russo TDB, Vieni S, Guarneri G, Russo A, Bazan V. BRCA1/2 variants of unknown significance in hereditary breast and ovarian cancer (HBOC) syndrome: looking for the hidden meaning. Crit Rev Oncol Hematol 2022; 172:103626. [PMID: 35150867 DOI: 10.1016/j.critrevonc.2022.103626] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 01/28/2022] [Accepted: 02/07/2022] [Indexed: 01/04/2023] Open
Abstract
Hereditary breast and ovarian cancer syndrome is caused by germline mutations in BRCA1/2 genes. These genes are very large and their mutations are heterogeneous and scattered throughout the coding sequence. In addition to the above-mentioned mutations, variants of uncertain/unknown significance (VUSs) have been identified in BRCA genes, which make more difficult the clinical management of the patient and risk assessment. In the last decades, several laboratories have developed different databases that contain more than 2000 variants for the two genes and integrated strategies which include multifactorial prediction models based on direct and indirect genetic evidence, to classify the VUS and attribute them a clinical significance associated with a deleterious, high-low or neutral risk. This review provides a comprehensive overview of literature studies concerning the VUSs, in order to assess their impact on the population and provide new insight for the appropriate patient management in clinical practice.
Collapse
Affiliation(s)
- Daniele Fanale
- Section of Medical Oncology, Department of Surgical, Oncological and Oral Sciences, University of Palermo, 90127 Palermo, Italy
| | - Alessia Pivetti
- Section of Medical Oncology, Department of Surgical, Oncological and Oral Sciences, University of Palermo, 90127 Palermo, Italy
| | - Daniela Cancelliere
- Section of Medical Oncology, Department of Surgical, Oncological and Oral Sciences, University of Palermo, 90127 Palermo, Italy
| | - Antonio Spera
- Department of Radiotherapy, San Giovanni di Dio Hospital, ASP of Agrigento, Agrigento, Italy
| | - Marco Bono
- Section of Medical Oncology, Department of Surgical, Oncological and Oral Sciences, University of Palermo, 90127 Palermo, Italy
| | - Alessia Fiorino
- Section of Medical Oncology, Department of Surgical, Oncological and Oral Sciences, University of Palermo, 90127 Palermo, Italy
| | - Erika Pedone
- Section of Medical Oncology, Department of Surgical, Oncological and Oral Sciences, University of Palermo, 90127 Palermo, Italy
| | - Nadia Barraco
- Section of Medical Oncology, Department of Surgical, Oncological and Oral Sciences, University of Palermo, 90127 Palermo, Italy
| | - Chiara Brando
- Section of Medical Oncology, Department of Surgical, Oncological and Oral Sciences, University of Palermo, 90127 Palermo, Italy
| | - Alessandro Perez
- Section of Medical Oncology, Department of Surgical, Oncological and Oral Sciences, University of Palermo, 90127 Palermo, Italy
| | | | - Tancredi Didier Bazan Russo
- Section of Medical Oncology, Department of Surgical, Oncological and Oral Sciences, University of Palermo, 90127 Palermo, Italy
| | - Salvatore Vieni
- Division of General and Oncological Surgery, Department of Surgical, Oncological and Oral Sciences, University of Palermo, Italy
| | - Girolamo Guarneri
- Gynecology Section, Mother - Child Department, University of Palermo, 90127 Palermo, Italy
| | - Antonio Russo
- Section of Medical Oncology, Department of Surgical, Oncological and Oral Sciences, University of Palermo, 90127 Palermo, Italy.
| | - Viviana Bazan
- Department of Biomedicine, Neuroscience and Advanced Diagnostics, University of Palermo, 90127 Palermo, Italy
| |
Collapse
|
3
|
Caputo SM, Golmard L, Léone M, Damiola F, Guillaud-Bataille M, Revillion F, Rouleau E, Derive N, Buisson A, Basset N, Schwartz M, Vilquin P, Garrec C, Privat M, Gay-Bellile M, Abadie C, Abidallah K, Airaud F, Allary AS, Barouk-Simonet E, Belotti M, Benigni C, Benusiglio PR, Berthemin C, Berthet P, Bertrand O, Bézieau S, Bidart M, Bignon YJ, Birot AM, Blanluet M, Bloucard A, Bombled J, Bonadona V, Bonnet F, Bonnet-Dupeyron MN, Boulaire M, Boulouard F, Bouras A, Bourdon V, Brahimi A, Brayotel F, Bressac de Paillerets B, Bronnec N, Bubien V, Buecher B, Cabaret O, Carriere J, Chiesa J, Chieze-Valéro S, Cohen C, Cohen-Haguenauer O, Colas C, Collonge-Rame MA, Conoy AL, Coulet F, Coupier I, Crivelli L, Cusin V, De Pauw A, Dehainault C, Delhomelle H, Delnatte C, Demontety S, Denizeau P, Devulder P, Dreyfus H, d’Enghein CD, Dupré A, Durlach A, Dussart S, Fajac A, Fekairi S, Fert-Ferrer S, Fiévet A, Fouillet R, Mouret-Fourme E, Gauthier-Villars M, Gesta P, Giraud S, Gladieff L, Goldbarg V, Goussot V, Guibert V, Guillerm E, Guy C, Hardouin A, Heude C, Houdayer C, Ingster O, Jacquot-Sawka C, Jones N, Krieger S, Lacoste S, Lallaoui H, Larbre H, Laugé A, Le Guyadec G, Le Mentec M, Lecerf C, Le Gall J, Legendre B, Legrand C, Legros A, Lejeune S, Lidereau R, Lignon N, Limacher JM, Doriane Livon, Lizard S, Longy M, Lortholary A, Macquere P, Mailliez A, Malsa S, Margot H, Mari V, Maugard C, Meira C, Menjard J, Molière D, Moncoutier V, Moretta-Serra J, Muller E, Nevière Z, Nguyen Minh Tuan TV, Noguchi T, Noguès C, Oca F, Popovici C, Prieur F, Raad S, Rey JM, Ricou A, Salle L, Saule C, Sevenet N, Simaga F, Sobol H, Suybeng V, Tennevet I, Tenreiro H, Tinat J, Toulas C, Turbiez I, Uhrhammer N, Vande Perre P, Vaur D, Venat L, Viellard N, Villy MC, Warcoin M, Yvard A, Zattara H, Caron O, Lasset C, Remenieras A, Boutry-Kryza N, Castéra L, Stoppa-Lyonnet D. Classification of 101 BRCA1 and BRCA2 variants of uncertain significance by cosegregation study: A powerful approach. Am J Hum Genet 2021; 108:1907-1923. [PMID: 34597585 DOI: 10.1016/j.ajhg.2021.09.003] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 09/01/2021] [Indexed: 12/18/2022] Open
Abstract
Up to 80% of BRCA1 and BRCA2 genetic variants remain of uncertain clinical significance (VUSs). Only variants classified as pathogenic or likely pathogenic can guide breast and ovarian cancer prevention measures and treatment by PARP inhibitors. We report the first results of the ongoing French national COVAR (cosegregation variant) study, the aim of which is to classify BRCA1/2 VUSs. The classification method was a multifactorial model combining different associations between VUSs and cancer, including cosegregation data. At this time, among the 653 variants selected, 101 (15%) distinct variants shared by 1,624 families were classified as pathogenic/likely pathogenic or benign/likely benign by the COVAR study. Sixty-six of the 101 (65%) variants classified by COVAR would have remained VUSs without cosegregation data. Of note, among the 34 variants classified as pathogenic by COVAR, 16 remained VUSs or likely pathogenic when following the ACMG/AMP variant classification guidelines. Although the initiation and organization of cosegregation analyses require a considerable effort, the growing number of available genetic tests results in an increasing number of families sharing a particular variant, and thereby increases the power of such analyses. Here we demonstrate that variant cosegregation analyses are a powerful tool for the classification of variants in the BRCA1/2 breast-ovarian cancer predisposition genes.
Collapse
|
4
|
Fadason T, Farrow S, Gokuladhas S, Golovina E, Nyaga D, O'Sullivan JM, Schierding W. Assigning function to SNPs: Considerations when interpreting genetic variation. Semin Cell Dev Biol 2021; 121:135-142. [PMID: 34446357 DOI: 10.1016/j.semcdb.2021.08.008] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 08/12/2021] [Indexed: 12/26/2022]
Abstract
Assigning function to single nucleotide polymorphisms (SNPs) to understand the mechanisms that link genetic and phenotypic variation and disease is an area of intensive research that is necessary to contribute to the continuing development of precision medicine. However, despite the apparent simplicity that is captured in the name SNP - 'single nucleotide' changes are not easy to functionally characterize. This complexity arises from multiple features of the genome including the fact that function is development and environment specific. As such, we are often fooled by our terminology and underlying assumptions that there is a single function for a SNP. Here we discuss some of what is known about SNPs, their functions and how we can go about characterizing them.
Collapse
Affiliation(s)
- Tayaza Fadason
- Liggins Institute, The University of Auckland, Auckland, New Zealand; The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand
| | - Sophie Farrow
- Liggins Institute, The University of Auckland, Auckland, New Zealand; The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand
| | | | - Evgeniia Golovina
- Liggins Institute, The University of Auckland, Auckland, New Zealand
| | - Denis Nyaga
- Liggins Institute, The University of Auckland, Auckland, New Zealand
| | - Justin M O'Sullivan
- Liggins Institute, The University of Auckland, Auckland, New Zealand; The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand; Garvan Institute of Medical Research, Sydney, New South Wales, Australia; MRC Lifecourse Epidemiology Unit, University of Southampton, United Kingdom.
| | - William Schierding
- Liggins Institute, The University of Auckland, Auckland, New Zealand; The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand
| |
Collapse
|
5
|
Ollodart AR, Yeh CLC, Miller AW, Shirts BH, Gordon AS, Dunham MJ. Multiplexing mutation rate assessment: determining pathogenicity of Msh2 variants in Saccharomyces cerevisiae. Genetics 2021; 218:iyab058. [PMID: 33848333 PMCID: PMC8225350 DOI: 10.1093/genetics/iyab058] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 04/02/2021] [Indexed: 01/01/2023] Open
Abstract
Despite the fundamental importance of mutation rate as a driving force in evolution and disease risk, common methods to assay mutation rate are time-consuming and tedious. Established methods such as fluctuation tests and mutation accumulation experiments are low-throughput and often require significant optimization to ensure accuracy. We established a new method to determine the mutation rate of many strains simultaneously by tracking mutation events in a chemostat continuous culture device and applying deep sequencing to link mutations to alleles of a DNA-repair gene. We applied this method to assay the mutation rate of hundreds of Saccharomyces cerevisiae strains carrying mutations in the gene encoding Msh2, a DNA repair enzyme in the mismatch repair pathway. Loss-of-function mutations in MSH2 are associated with hereditary nonpolyposis colorectal cancer, an inherited disorder that increases risk for many different cancers. However, the vast majority of MSH2 variants found in human populations have insufficient evidence to be classified as either pathogenic or benign. We first benchmarked our method against Luria-Delbrück fluctuation tests using a collection of published MSH2 missense variants. Our pooled screen successfully identified previously characterized nonfunctional alleles as high mutators. We then created an additional 185 human missense variants in the yeast ortholog, including both characterized and uncharacterized alleles curated from ClinVar and other clinical testing data. In a set of alleles of known pathogenicity, our assay recapitulated ClinVar's classification; we then estimated pathogenicity for 157 variants classified as uncertain or conflicting reports of significance. This method is capable of studying the mutation rate of many microbial species and can be applied to problems ranging from the generation of high-fidelity polymerases to measuring the frequency of antibiotic resistance emergence.
Collapse
Affiliation(s)
- Anja R Ollodart
- Molecular Cellular Biology Program, University of Washington, Seattle, WA 98195, USA
- Genome Sciences Department, University of Washington, Seattle, WA 98195, USA
| | - Chiann-Ling C Yeh
- Genome Sciences Department, University of Washington, Seattle, WA 98195, USA
| | - Aaron W Miller
- Genome Sciences Department, University of Washington, Seattle, WA 98195, USA
| | - Brian H Shirts
- Department of Laboratory Medicine, University of Washington, Seattle, WA 98195, USA
| | - Adam S Gordon
- Department of Pharmacology, Northwestern University, Chicago, IL 60208, USA
| | - Maitreya J Dunham
- Genome Sciences Department, University of Washington, Seattle, WA 98195, USA
| |
Collapse
|
6
|
Clinical characteristics and disease progression of retinitis pigmentosa associated with PDE6B mutations in Korean patients. Sci Rep 2020; 10:19540. [PMID: 33177553 PMCID: PMC7658990 DOI: 10.1038/s41598-020-75902-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2020] [Accepted: 10/06/2020] [Indexed: 11/08/2022] Open
Abstract
Due to the genotype-phenotype heterogeneity in retinitis pigmentosa (RP), molecular diagnoses and prediction of disease progression is difficult. This study aimed to report ocular and genetic data from Korean patients with PDE6B-associated RP (PDE6B-RP), and establish genotype-phenotype correlations to predict the clinical course. We retrospectively reviewed targeted next-generation sequencing or whole exome sequencing data for 305 patients with RP, and identified PDE6B-RP in 15 patients (median age, 40.0 years). Amongst these patients, ten previously reported PDE6B variants (c.1280G > A, c.1488del, c.1547T > C, c.1604T > A, c.1669C > T, c.1712C > T, c.2395C > T, c.2492C > T, c.592G > A, and c.815G > A) and one novel variant (c.712del) were identified. Thirteen patients (86.7%) experienced night blindness as the first symptom at a median age of 10.0 years. Median age at diagnosis was 21.0 years and median visual acuity (VA) was 0.20 LogMAR at the time of genetic analysis. Nonlinear mixed models were developed and analysis revealed that VA exponentially decreased over time, while optical coherence tomography parameters linearly decreased, and this was related with visual field constriction. A high proportion of patients with the c.1669C > T variant (7/9, 77.8%) had cystoid macular edema; despite this, patients with this variant did not show a higher rate of functional or structural progression. This study will help clinicians predict functional and structural progression in patients with PDE6B-RP.
Collapse
|
7
|
Agata S, Tognazzo S, Alducci E, Matricardi L, Moserle L, Barana D, Montagna M. Segregation analysis of the BRCA2 c.9227G>T variant in multiple families suggests a pathogenic role in breast and ovarian cancer predisposition. Sci Rep 2020; 10:13987. [PMID: 32814805 PMCID: PMC7438490 DOI: 10.1038/s41598-020-70729-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Accepted: 07/20/2020] [Indexed: 11/09/2022] Open
Abstract
Classification of variants in the BRCA1 and BRCA2 genes has a major impact on the clinical management of subjects at high risk for breast and ovarian cancer. The identification of a pathogenic variant allows for early detection/prevention strategies in healthy carriers as well as targeted treatments in patients affected by BRCA-associated tumors. The BRCA2 c.9227G>T p.(Gly3076Val) variant recurs in families from Northeast Italy and is rarely reported in international databases. This variant substitutes the evolutionary invariant glycine 3076 with a valine in the DNA binding domain of the BRCA2 protein, thus suggesting a high probability of pathogenicity. We analysed clinical and genealogic data of carriers from 15 breast/ovarian cancer families in whom no other pathogenic variants were detected. The variant was shown to co-segregate with breast and ovarian cancer in the most informative families. Combined segregation data led to a likelihood ratio of 81,527:1 of pathogenicity vs. neutrality. We conclude that c.9227G>T is a BRCA2 pathogenic variant that recurs in Northeast Italy. It can now be safely used for the predictive testing of healthy family members to guide preventive surgery and/or early tumor detection strategies, as well as for PARP inhibitors treatments in patients with BRCA2-associated tumors.
Collapse
Affiliation(s)
- Simona Agata
- Immunology and Molecular Oncology Unit, Veneto Institute of Oncology IOV-IRCCS, Padua, Italy
| | - Silvia Tognazzo
- Immunology and Molecular Oncology Unit, Veneto Institute of Oncology IOV-IRCCS, Padua, Italy
| | - Elisa Alducci
- Immunology and Molecular Oncology Unit, Veneto Institute of Oncology IOV-IRCCS, Padua, Italy
| | - Laura Matricardi
- Immunology and Molecular Oncology Unit, Veneto Institute of Oncology IOV-IRCCS, Padua, Italy
| | - Lidia Moserle
- Immunology and Molecular Oncology Unit, Veneto Institute of Oncology IOV-IRCCS, Padua, Italy
| | - Daniela Barana
- Oncology Unit, Local Health and Social Care Unit ULSS8 Berica, Montecchio Maggiore, Italy
| | - Marco Montagna
- Immunology and Molecular Oncology Unit, Veneto Institute of Oncology IOV-IRCCS, Padua, Italy.
| |
Collapse
|
8
|
Considerations in assessing germline variant pathogenicity using cosegregation analysis. Genet Med 2020; 22:2052-2059. [PMID: 32773770 DOI: 10.1038/s41436-020-0920-4] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Revised: 07/17/2020] [Accepted: 07/20/2020] [Indexed: 12/31/2022] Open
Abstract
PURPOSE The American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) have developed guidelines for classifying germline variants as pathogenic or benign to interpret genetic testing results. Cosegregation analysis is an important component of the guidelines. There are two main approaches for cosegregation analysis: meiosis counting and Bayes factor-based quantitative methods. Of these, the ACMG/AMP guidelines employ only meiosis counting. The accuracy of either approach has not been sufficiently addressed in previous works. METHODS We analyzed hypothetical, simulated, and real-life data to evaluate the accuracy of each approach for cancer-associated genes. RESULTS We demonstrate that meiosis counting can provide incorrect classifications when the underlying genetic basis of the disease departs from simple Mendelian situations. Some Bayes factor approaches are currently implemented with inappropriate penetrance. We propose an improved penetrance model and describe several critical considerations, including the accuracy of cosegregation for moderate-risk genes and the impact of pleiotropy, population, and birth year. We highlight a webserver, COOL (Co-segregation Online, http://BJFengLab.org/ ), that implements an accurate Bayes factor cosegregation analysis. CONCLUSION An appropriate penetrance model improves the accuracy of Bayes factor cosegregation analysis for high-penetrant variants, and is a better choice than meiosis counting whenever feasible.
Collapse
|
9
|
Exploring the effect of ascertainment bias on genetic studies that use clinical pedigrees. Eur J Hum Genet 2019; 27:1800-1807. [PMID: 31296927 DOI: 10.1038/s41431-019-0467-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Revised: 06/09/2019] [Accepted: 06/25/2019] [Indexed: 12/21/2022] Open
Abstract
Recent studies have reported novel cancer risk associations with incidentally tested genes on cancer risk panels using clinically ascertained cohorts. Clinically ascertained pedigrees may have unknown ascertainment biases for both patients and relatives. We used a method to assess gene and variant risk and ascertainment bias based on comparing the number of observed disease instances in a pedigree given the sex and ages of individuals with those expected given established population incidence. We assessed the performance characteristics of the method by simulating families with varying genetic risk and proportion of individuals genotyped. We implemented this method using SEER cancer incidence data to assess clinical ascertainment bias in a set of 42 pedigrees with clinical testing ordered for either breast/ovarian cancer or colorectal/endometrial cancer at the University of Washington and negative sequencing results. In addition to expected biases consistent with the stated testing purpose, there were trends suggesting increased colorectal and endometrial cancer in pedigrees tested for breast cancer risk and trends suggesting increased breast cancer in families tested for colon cancer risk. There was no observed selection bias for prostate cancer in this set of families. This analysis illustrates that clinically ascertained data sets may have subtle biases. In the future, researchers seeking to explore risk associations with clinical data sets could assess potential ascertainment bias by comparing incidence of disease in families that test negative under given ordering criteria to expected population disease frequencies. Failure to assess for ascertainment bias increases the risk of false genetic associations.
Collapse
|
10
|
Swaminathan A, Shirts BH, Chen AT. Incorporating user feedback in the design of a genetics analysis tool: A two-part approach. J Biomed Inform 2019; 95:103204. [PMID: 31075532 DOI: 10.1016/j.jbi.2019.103204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2018] [Revised: 04/21/2019] [Accepted: 05/05/2019] [Indexed: 11/28/2022]
Abstract
While general usability assessment models for websites have been developed for a wide variety of contexts, research literature on incorporating user feedback in the design of online scientific tools is lacking. In this article, we present an approach that we developed and illustrate how it was used to elicit user feedback of the AnalyzeMyVariant tool, which enables geneticists to use family pedigree data to calculate pathogenicity likelihood ratios for variants of unknown significance. We reviewed existing usability literature and developed a survey instrument emphasizing concepts of importance to online, data-driven, scientific tools. The items on the survey instrument were grouped in four categories: usability, quality, privacy and security, and satisfaction. We performed a two-part evaluation using the survey and a semi-structured interview protocol. The survey instrument was used to collect data about the use experience of AnalyzeMyVariant from 57 genetic experts and trainees who were recruited via email invitations. We also conducted semi-structured interviews with six genetics experts to explore work contexts in which users might use the tool and further delve into issues faced in tool use. Interviews were inductively coded and major themes identified using the constant comparative method. We found that the needs of genetics professionals vary for research- and clinically-focused work. These differences can inform the design of tools to serve their needs. The major contribution of this work is the description of a two-part method to elicit user feedback to inform the design of online, data-driven, scientific tools, which focuses on constructs of particular relevance to these tools such as usability, quality, privacy, security, and satisfaction. The survey instrument that we developed, coupled with contextual interviews, may serve as an example that can be used by others conducting usability studies of similar tools. In addition, our results emphasize the importance of considering contextual factors such as background knowledge, situational factors, and the intended application of results, in the usability evaluation of scientific software. It is our hope that this two-part approach might be adapted to assess the usability of other online scientific tools and facilitate the design of tools to meet the needs of their target audiences.
Collapse
Affiliation(s)
- Aarti Swaminathan
- Biomedical Informatics and Medical Education, UW Medicine South Lake Union, 850 Republican Street, Box 358047, Seattle, WA 98109, USA
| | - Brian H Shirts
- University of Washington, Department of Laboratory Medicine, Box 357110, 1959 NE Pacific Street, NW120, Seattle, WA 98195-7110, USA.
| | - Annie T Chen
- Biomedical Informatics and Medical Education, UW Medicine South Lake Union, 850 Republican Street, Box 358047, Seattle, WA 98109, USA.
| |
Collapse
|
11
|
Ranola JMO, Pearlman R, Hampel H, Shirts BH. Modified capture-recapture estimates of the number of families with Lynch syndrome in Central Ohio. Fam Cancer 2019; 18:67-73. [PMID: 30019097 DOI: 10.1007/s10689-018-0096-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Past methods for estimating the population frequency of familial cancer syndromes have used cases and controls ignoring the familial nature of genetic disease. In this study we modified the capture-recapture method from ecology to estimate the number of families in central Ohio with Lynch syndrome (LS). We screened 1566 colorectal cancer cases and 545 endometrial cancer cases in central Ohio from 1999 to 2005 and identified 58 with LS. We screened an additional 3346 colorectal and 342 endometrial cancer cases from 2013 to 2016 and identified 149 with LS. We found 12 LS mutations shared between families observed in the first and second studies. We identified three individuals between studies who were closely related and eight who were more distantly related. We used identified family relationships and genetic test results to estimate family size and structure. Applying a modified capture-recapture method we estimate 1693 3-generation families in the area who have 288 unique LS causing mutations. Comprehensive colorectal and endometrial cancer screening will take about 20 years to identify 50% of families with LS. This is the first time that the capture-recapture method has been applied to estimate the burden of families with a specific heritable disease. Family structure reveals the potential extent of prevention and the time necessary to identify a proportion of families with LS.
Collapse
Affiliation(s)
- John Michael O Ranola
- Department of Laboratory Medicine, University of Washington, 1959 NE Pacific Street, NW120, Box 357110, Seattle, WA, 98195-7110, USA
| | - Rachel Pearlman
- Department of Internal Medicine and the Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
| | - Heather Hampel
- Department of Internal Medicine and the Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
| | - Brian H Shirts
- Department of Laboratory Medicine, University of Washington, 1959 NE Pacific Street, NW120, Box 357110, Seattle, WA, 98195-7110, USA.
| |
Collapse
|
12
|
Tsai GJ, Garrett LT, Makhnoon S, Bowen DJ, Burke W, Shirts BH. Patient goals, motivations, and attitudes in a patient-driven variant reclassification study. J Genet Couns 2018; 28:558-569. [PMID: 31163102 DOI: 10.1002/jgc4.1052] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2018] [Revised: 10/12/2018] [Accepted: 07/27/2018] [Indexed: 01/12/2023]
Abstract
Family studies to reclassify clinically ascertained variants of uncertain significance (VUS) can impact risk assessment, medical management, and psychological outcomes for patients and their families. There are limited avenues for patients and their families to actively participate in VUS reclassification, and access to family studies at most commercial laboratories is restricted by multiple factors. To explore patient attitudes about participation in family studies for VUS reclassification, we conducted semistructured pre- and post-participation telephone interviews with 38 participants in a family-based VUS reclassification study that utilized a patient-driven approach for family ascertainment and recruitment. Participants had VUS from multigene panel testing performed at multiple clinical laboratories for cancer or other disease risk. Inductive thematic analysis of transcribed interviews highlighted four major themes: (a) Participants' study goals were driven by the desire to resolve uncertainty related to the VUS, (b) Participants had mixed reactions to the VUS reclassification outcomes of the study, (c) Personal, public, and familial knowledge increased through study participation and (d) Participants used study participation to actively cope with the uncertainty of a VUS. As personalized genomic medicine becomes more prevalent, clinicians, clinical laboratories, and researchers could consider creating more opportunities for active partnership with patients and families, who are motivated to contribute data to familial VUS studies.
Collapse
Affiliation(s)
- Ginger J Tsai
- Department of Laboratory Medicine, University of Washington, Seattle, Washington
| | | | - Sukh Makhnoon
- Institute of Public Health Genomics, University of Washington, Seattle, Washington
| | - Deborah J Bowen
- Department of Bioethics and Humanities, University of Washington, Seattle, Washington
| | - Wylie Burke
- Department of Bioethics and Humanities, University of Washington, Seattle, Washington
| | - Brian H Shirts
- Department of Laboratory Medicine, University of Washington, Seattle, Washington
| |
Collapse
|
13
|
Outcomes of 92 patient-driven family studies for reclassification of variants of uncertain significance. Genet Med 2018; 21:1435-1442. [PMID: 30374176 DOI: 10.1038/s41436-018-0335-7] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2018] [Accepted: 09/28/2018] [Indexed: 01/30/2023] Open
Abstract
PURPOSE Family studies are an important but underreported source of information for reclassification of variants of uncertain significance (VUS). We evaluated outcomes of a patient-driven framework that offered familial VUS reclassification analysis to any adult with any clinically ascertained VUS from any laboratory in the United States. METHODS With guidance from FindMyVariant.org, participants recruited their own relatives for study participation. We genotyped relatives, calculated quantitative cosegregation likelihood ratios, and evaluated variant classifications using Tavtigian's unified framework for Bayesian analysis with American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) criteria. We report participation and VUS reclassification rates from the 50 families enrolled for at least one year and reclassification results for 112 variants from the larger 92-family cohort. RESULTS For the 50-family cohort, 6.7 relatives per family were invited to participate and 67% of relatives returned samples for genotyping. Sixty-one percent of VUS were reclassified, 84% of which were classified as benign or likely benign. Genotyping relatives identified a de novo variant, phase variants, and relatives with phenotypes highly specific for or incompatible with specific classifications. CONCLUSIONS Motivated families can contribute to successful VUS reclassification at substantially higher rates than those previously published. Clinical laboratories could consider offering family studies to all patients with VUS.
Collapse
|
14
|
Zuntini R, Ferrari S, Bonora E, Buscherini F, Bertonazzi B, Grippa M, Godino L, Miccoli S, Turchetti D. Dealing With BRCA1/2 Unclassified Variants in a Cancer Genetics Clinic: Does Cosegregation Analysis Help? Front Genet 2018; 9:378. [PMID: 30254663 PMCID: PMC6141711 DOI: 10.3389/fgene.2018.00378] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2018] [Accepted: 08/24/2018] [Indexed: 12/11/2022] Open
Abstract
Background: Detection of variants of uncertain significance (VUSs) in BRCA1 and BRCA2 genes poses relevant challenges for counseling and managing patients. VUS carriers should be managed similarly to probands with no BRCA1/2 variants detected, and predictive genetic testing in relatives is discouraged. However, miscomprehension of VUSs is common and can lead to inaccurate risk perception and biased decisions about prophylactic surgery. Therefore, efforts are needed to improve VUS evaluation and communication at an individual level. Aims: We aimed at investigating whether cosegregation analysis, integrated with a careful review of available functional data and in silico predictions, may improve VUSs interpretation and counseling in individual families. Methods: Patients with Breast Cancer (BC) and/or Ovarian Cancer (OC) fulfilling established criteria were offered genetic counseling and BRCA1/2 testing; VUSs identified in index cases were checked in other relatives affected by BC/OC whenever possible. As an alternative, if BC/OC clustered only in one branch of the family, the parental origin of the VUS was investigated. Public prediction tools and databases were used to collect additional information on the variants analyzed. Results: Out of 1045 patients undergoing BRCA1/2 testing in the period October 2011–April 2018, 66 (6.3%) carried class 3 VUSs. Cosegregation analysis was performed for 13 VUSs in 11 kindreds. Seven VUSs (53.8%) did not cosegregate with breast/ovarian cancer in the family, which provided evidence against their role in cancer clustering in those families. Among the 6 cosegregating VUSs, for two (BRCA1 c.5152+2T>G and BRCA2 c.7975A>G) additional evidence exists from databases and in silico tools supporting their pathogenicity, which reinforces the hypothesis they may have had a predisposing effect in respective families. For the remaining four VUSs (31%), cosegregation analysis failed to provide relevant information. Conclusion: Our findings suggest that cosegregation analysis in a clinical context may be helpful to improve test result interpretation in the specific family and, therefore, should be offered whenever possible. Besides, obtaining and sharing cosegregation data helps gathering evidence that may eventually contribute to VUS classification.
Collapse
Affiliation(s)
- Roberta Zuntini
- UO Genetica Medica, Azienda Ospedaliero-Universitaria di Bologna Policlinico S.Orsola-Malpighi and Centro di Ricerca sui Tumori Ereditari, Dipartimento di Scienze Mediche e Chirurgiche, Universitá di Bologna, Bologna, Italy
| | - Simona Ferrari
- UO Genetica Medica, Azienda Ospedaliero-Universitaria di Bologna Policlinico S.Orsola-Malpighi and Centro di Ricerca sui Tumori Ereditari, Dipartimento di Scienze Mediche e Chirurgiche, Universitá di Bologna, Bologna, Italy
| | - Elena Bonora
- UO Genetica Medica, Azienda Ospedaliero-Universitaria di Bologna Policlinico S.Orsola-Malpighi and Centro di Ricerca sui Tumori Ereditari, Dipartimento di Scienze Mediche e Chirurgiche, Universitá di Bologna, Bologna, Italy
| | - Francesco Buscherini
- UO Genetica Medica, Azienda Ospedaliero-Universitaria di Bologna Policlinico S.Orsola-Malpighi and Centro di Ricerca sui Tumori Ereditari, Dipartimento di Scienze Mediche e Chirurgiche, Universitá di Bologna, Bologna, Italy
| | - Benedetta Bertonazzi
- UO Genetica Medica, Azienda Ospedaliero-Universitaria di Bologna Policlinico S.Orsola-Malpighi and Centro di Ricerca sui Tumori Ereditari, Dipartimento di Scienze Mediche e Chirurgiche, Universitá di Bologna, Bologna, Italy
| | - Mina Grippa
- UO Genetica Medica, Azienda Ospedaliero-Universitaria di Bologna Policlinico S.Orsola-Malpighi and Centro di Ricerca sui Tumori Ereditari, Dipartimento di Scienze Mediche e Chirurgiche, Universitá di Bologna, Bologna, Italy
| | - Lea Godino
- UO Genetica Medica, Azienda Ospedaliero-Universitaria di Bologna Policlinico S.Orsola-Malpighi and Centro di Ricerca sui Tumori Ereditari, Dipartimento di Scienze Mediche e Chirurgiche, Universitá di Bologna, Bologna, Italy
| | - Sara Miccoli
- UO Genetica Medica, Azienda Ospedaliero-Universitaria di Bologna Policlinico S.Orsola-Malpighi and Centro di Ricerca sui Tumori Ereditari, Dipartimento di Scienze Mediche e Chirurgiche, Universitá di Bologna, Bologna, Italy
| | - Daniela Turchetti
- UO Genetica Medica, Azienda Ospedaliero-Universitaria di Bologna Policlinico S.Orsola-Malpighi and Centro di Ricerca sui Tumori Ereditari, Dipartimento di Scienze Mediche e Chirurgiche, Universitá di Bologna, Bologna, Italy
| |
Collapse
|