The Economic, Medical and Psychosocial Consequences of Whole Genome Sequencing for the Genetic Diagnosis of Patients With Intellectual Disability: The DEFIDIAG Study Protocol

Catherine Lejeune, Charley Robert-Viard, Nicolas Meunier-Beillard, Myriam Alice Borel, Léna Gourvès, Stéphanie Staraci, Anne-Laure Soilly, Francis Guillemin, Valerie Seror, Hamza Achit, Marion Bouctot, Marie-Laure Asensio, Anne-Sophie Briffaut, Christelle Delmas, Ange-Line Bruel, Alexia Benoit, Alban Simon, Bénédicte Gerard, Hamza Hadj Abdallah, Stanislas Lyonnet, Laurence Faivre, Christel Thauvin-Robinet, Sylvie Odent, Delphine Heron, Damien Sanlaville, Thierry Frebourg, Jean Muller, Yannis Duffourd, Anne Boland, Jean-François Deleuze, Hélène Espérou, Christine Binquet, Hélène Dollfus, Catherine Lejeune, Charley Robert-Viard, Nicolas Meunier-Beillard, Myriam Alice Borel, Léna Gourvès, Stéphanie Staraci, Anne-Laure Soilly, Francis Guillemin, Valerie Seror, Hamza Achit, Marion Bouctot, Marie-Laure Asensio, Anne-Sophie Briffaut, Christelle Delmas, Ange-Line Bruel, Alexia Benoit, Alban Simon, Bénédicte Gerard, Hamza Hadj Abdallah, Stanislas Lyonnet, Laurence Faivre, Christel Thauvin-Robinet, Sylvie Odent, Delphine Heron, Damien Sanlaville, Thierry Frebourg, Jean Muller, Yannis Duffourd, Anne Boland, Jean-François Deleuze, Hélène Espérou, Christine Binquet, Hélène Dollfus

Abstract

Introduction: Like other countries, France has invested in a national medical genomics program. Among the four pilot research studies, the DEFIDIAG project focuses on the use of whole genome sequencing (WGS) for patients with intellectual disability (ID), a neurodevelopmental condition affecting 1-3% of the general population but due to a plethora of genes. However, the access to genomic analyses has many potential individual and societal issues in addition to the technical challenges. In order to help decision-makers optimally introduce genomic testing in France, there is a need to identify the socio-economic obstacles and leverages associated with the implementation of WGS. Methods and Analysis: This humanities and social sciences analysis is part of the DEFIDIAG study. The main goal of DEFIDIAG is to compare the percentage of causal genetic diagnoses obtained by trio WGS (including the patient and both parents) (WGST) to the percentage obtained using the minimal reference strategy currently used in France (Fragile-X testing, chromosomal microarray analysis, and gene panel strategy including 44 ID genes) for patients with ID having their first clinical genetics consultation. Additionally, four complementary studies will be conducted. First, a cost-effectiveness analysis will be undertaken in a subsample of 196 patients consulting for the first time for a genetic evaluation; in a blinded fashion, WGST and solo (index case, only) genomic analysis (WGSS) will be compared to the reference strategy. In addition, quantitative studies will be conducted: the first will estimate the cost of the diagnostic odyssey that could potentially be avoidable with first-line WGST in all patients previously investigated in the DEFIDIAG study; the second will estimate changes in follow-up of the patients in the year after the return of the WGST analysis compared to the period before inclusion. Finally, through semi-directive interviews, we will explore the expectations of 60 parents regarding genomic analyses. Discussion: Humanities and social sciences studies can be used to demonstrate the efficiency of WGS and assess the value that families associate with sequencing. These studies are thus expected to clarify trade-offs and to help optimize the implementation of genomic sequencing in France. Ethics Statement: The protocol was approved by the Ethics Committee Sud Méditerranée I (June 2019)-identification number: 2018-A00680-55 and the French data privacy commission (CNIL, authorization 919361). Clinical Trial Registration: (ClinicalTrials.gov), identifier (NCT04154891).

Keywords: cost-effectiveness; genome sequencing; intellectual disability; micro-costing; qualitative study.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2022 Lejeune, Robert-Viard, Meunier-Beillard, Borel, Gourvès, Staraci, Soilly, Guillemin, Seror, Achit, Bouctot, Asensio, Briffaut, Delmas, Bruel, Benoit, Simon, Gerard, Hadj Abdallah, Lyonnet, Faivre, Thauvin-Robinet, Odent, Heron, Sanlaville, Frebourg, Muller, Duffourd, Boland, Deleuze, Espérou, Binquet and Dollfus.

Figures

FIGURE 1
FIGURE 1
Design of the efficiency study: This figure illustrates the design of the cost-effectiveness study. Three strategies will be compared: the solo Whole Genome Sequencing strategy (WGSS), the trio Whole Genome Sequencing strategy (WGST) and the reference strategy. Comparisons will be made simultaneously in terms of cost and effectiveness (positive diagnosis).
FIGURE 2
FIGURE 2
Design of the impact of genome sequencing on the diagnostic odyssey and follow-up: This figure illustrates the design of the before-after study aiming at assessing the impact of WGS on patients’ follow-up (12 months after the reporting of WGS results) compared to the period of 1 year preceding the inclusion.

References

    1. Adithyan G. S., Sivakami M., Jacob J. (2017). Positive and Negative Impacts on Caregivers of Children with Intellectual Disability in India. Dcid 28 (2), 74–94. 10.5463/dcid.v28i2.595
    1. Aviesan (2025). France Médecine Génomique. . (Accessed November 8, 2021).
    1. Binquet C., Lejeune C., Faivre L., Bouctot M., Asensio M. A., Simon A., et al. (2022). Genome Sequencing for Genetics Diagnosis of Patients with Intellectual Disability: The DEFIDIAG Study. Front. Genet 12, 1–13. 10.3389/fgene.2021.766964
    1. Briggs A. H., Gray A. M. (1999). Methods in Health Service Research: Handling Uncertainty in Economic Evaluations of Healthcare Interventions. BMJ 319 (7210), 635–638. 10.1136/bmj.319.7210.635
    1. Buntinx W., Cans C., Colleaux L., Courbois Y., Debbané M., Desportes, et al. (2016). Déficiences Intellectuelles. Expertise Collective. Institut national de la santé et de la recherche médicale INSERM.
    1. Chérot E., Keren B., Dubourg C., Carré W., Fradin M., Lavillaureix A., et al. (2018). Using Medical Exome Sequencing to Identify the Causes of Neurodevelopmental Disorders: Experience of 2 Clinical Units and 216 Patients. Clin. Genet. 93, 567–576. 10.1111/cge.13102
    1. Collins F. S., Morgan M., Patrinos A. (2003). The Human Genome Project: Lessons from Large-Scale Biology. Science 300 (5617), 286–290. 10.1126/science.1084564
    1. Foster M. W., Mulvihill J. J., Sharp R. R. (2009). Evaluating the Utility of Personal Genomic Information. Genet. Med. 11 (8), 570–574. 10.1097/GIM.0b013e3181a2743e
    1. Frick K. D. (2009). Microcosting Quantity Data Collection Methods. Med. Care 47 (1), S76–S81. 10.1097/MLR.0b013e31819bc064
    1. Gilissen C., Hehir-Kwa J. Y., Thung D. T., van de Vorst M., van Bon B. W. M., Willemsen M. H., et al. (2014). Genome Sequencing Identifies Major Causes of Severe Intellectual Disability. Nature 511, 344–347. 10.1038/nature13394
    1. Hennink M. M., Kaiser B. N., Marconi V. C. (2017). , 27, 591–608. 10.1177/1049732316665344 Code Saturation versus Meaning Saturation: How Many Interviews Are Enough? Qual. Health Res. 4
    1. Jegathisawaran J., Tsiplova K., Hayeems R., Ungar W. J. (2020). Determining Accurate Costs for Genomic Sequencing Technologies-A Necessary Prerequisite. J. Community Genet. 11 (2), 235–238. 10.1007/s12687-019-00442-7
    1. Kohler J. N., Turbitt E., Lewis K. L., Wilfond B. S., Jamal L., Peay H. L., et al. (2017). Defining Personal Utility in Genomics: A Delphi Study. Clin. Genet. 92 (3), 290–297. 10.1111/cge.12998
    1. Lionel A. C., Costain G., Monfared N., Walker S., Reuter M. S., Hosseini S. M., et al. (2018). Improved Diagnostic Yield Compared with Targeted Gene Sequencing Panels Suggests a Role for Whole-Genome Sequencing as a First-Tier Genetic Test. Genet. Med. 20 (4), 435–443. 10.1038/gim.2017.119
    1. Mollison L., O’Daniel J. M., Henderson G. E., Berg J. S., Skinner D. (2020). Parents' Perceptions of Personal Utility of Exome Sequencing Results. Genet. Med. 22 (4), 752–757. 10.1038/s41436-019-0730-8
    1. Monroe G. R., Frederix G. W., Savelberg S. M. C., de Vries T. I., Duran K. J., van der Smagt J. J., et al. (2016). Effectiveness of Whole-Exome Sequencing and Costs of the Traditional Diagnostic Trajectory in Children with Intellectual Disability. Genet. Med. 18 (9), 949–956. 10.1038/gim.2015.200
    1. Ontario Health (Quality) (2020). Genome-Wide Sequencing for Unexplained Developmental Disabilities or Multiple Congenital Anomalies: A Health Technology Assessment. Ont Health Technol. Assess. Ser. 20 (11), 1–178.
    1. Peplow M. (2016). The 100 000 Genomes Project. BMJ 353, i1757. 10.1136/bmj.i1757
    1. Redin C., Gérard B., Lauer J., Herenger Y., Muller J., Quartier A., et al. (2014). Efficient Strategy for the Molecular Diagnosis of Intellectual Disability Using Targeted High-Throughput Sequencing. J. Med. Genet. 51 (11), 724–736. 10.1136/jmedgenet-2014-102554
    1. Schwarze K., Buchanan J., Fermont J. M., Dreau H., Tilley M. W., Taylor J. M., et al. (2020). The Complete Costs of Genome Sequencing: a Microcosting Study in Cancer and Rare Diseases from a Single center in the United Kingdom. Genet. Med. 22 (1), 85–94. 10.1038/s41436-019-0618-7
    1. Stark Z., Schofield D., Alam K., Wilson W., Mupfeki N., Macciocca I., et al. (2017). Prospective Comparison of the Cost-Effectiveness of Clinical Whole-Exome Sequencing with that of Usual Care Overwhelmingly Supports Early Use and Reimbursement. Genet. Med. 19 (8), 867–874. 10.1038/gim.2016.221
    1. Thomas D. R., Thomas A. (2006). A General Inductive Approach for Analyzing Qualitative Evaluation Data. Am. J. Eval. 27 (2), 237–246. 10.1177/1098214005283748
    1. Tsiplova K., Zur R. M., Marshall C. R., Stavropoulos D. J., Pereira S. L., Merico D., et al. (2017). A Microcosting and Cost-Consequence Analysis of Clinical Genomic Testing Strategies in Autism Spectrum Disorder. Genet. Med. 19 (11), 1268–1275. 10.1038/gim.2017.47
    1. Van Nimwegen K. (2017). “Health Technology Assessment of Next-Generation Sequencing,” ([NijmegenThe Netherlands]: Radboud University; ). [thesis]. 10.13140/RG.2.2.19492.99201
    1. Vissers L. E. L. M., van Nimwegen K. J. M., Schieving J. H., Kamsteeg E.-J., Kleefstra T., Yntema H. G., et al. (2017). A Clinical Utility Study of Exome Sequencing versus Conventional Genetic Testing in Pediatric Neurology. Genet. Med. 19 (9), 1055–1063. 10.1038/gim.2017.1
    1. Vrijenhoek T., Middelburg E. M., Monroe G. R., van Gassen K. L. I., Geenen J. W., Hövels A. M., et al. (2018). Whole-exome Sequencing in Intellectual Disability; Cost before and after a Diagnosis. Eur. J. Hum. Genet. 26 (11), 1566–1571. 10.1038/s41431-018-0203-6
    1. York Health Economics Consortium (2016). Net Monetary Benefit . (Accessed November 8, 2021).
    1. Yuen T., Carter M. T., Szatmari P., Ungar W. J. (2018). Cost-effectiveness of Genome and Exome Sequencing in Children Diagnosed with Autism Spectrum Disorder. Appl. Health Econ. Health Pol. 16 (4), 481–493. 10.1007/s40258-018-0390-x
    1. Zhao W., Wang J., He X., Huang X., Jiao Y., Dai M., et al. (2004). BGI-RIS: an Integrated Information Resource and Comparative Analysis Workbench for rice Genomics. Nucleic Acids Res. 32, 377D–382D. 10.1093/nar/gkh085

Source: PubMed

Sponsors et collaborateurs

Les conditions médicales

Interventions en matière de drogue

3
S'abonner