1
|
Duyzend MH, Cacheiro P, Jacobsen JO, Giordano J, Brand H, Wapner RJ, Talkowski ME, Robinson PN, Smedley D. Improving prenatal diagnosis through standards and aggregation. Prenat Diagn 2024; 44:454-464. [PMID: 38242839 PMCID: PMC11006584 DOI: 10.1002/pd.6522] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 12/17/2023] [Accepted: 12/22/2023] [Indexed: 01/21/2024]
Abstract
Advances in sequencing and imaging technologies enable enhanced assessment in the prenatal space, with a goal to diagnose and predict the natural history of disease, to direct targeted therapies, and to implement clinical management, including transfer of care, election of supportive care, and selection of surgical interventions. The current lack of standardization and aggregation stymies variant interpretation and gene discovery, which hinders the provision of prenatal precision medicine, leaving clinicians and patients without an accurate diagnosis. With large amounts of data generated, it is imperative to establish standards for data collection, processing, and aggregation. Aggregated and homogeneously processed genetic and phenotypic data permits dissection of the genomic architecture of prenatal presentations of disease and provides a dataset on which data analysis algorithms can be tuned to the prenatal space. Here we discuss the importance of generating aggregate data sets and how the prenatal space is driving the development of interoperable standards and phenotype-driven tools.
Collapse
Affiliation(s)
- Michael H. Duyzend
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Genetics and Genomics, Department of Pediatrics, Boston Children’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Pilar Cacheiro
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK
| | - Julius O.B. Jacobsen
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK
| | - Jessica Giordano
- Department of Obstetrics & Gynecology, Columbia University Medical Center, New York, NY, USA
| | - Harrison Brand
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Ronald J. Wapner
- Department of Obstetrics & Gynecology, Columbia University Medical Center, New York, NY, USA
| | - Michael E. Talkowski
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
- Program in Biological and Biomedical Sciences, Division of Medical Sciences, Harvard Medical School, Boston, MA, USA
- Program in Bioinformatics and Integrative Genomics, Division of Medical Sciences, Harvard Medical School, Boston, MA, USA
| | - Peter N. Robinson
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA
- Institute for Systems Genomics, University of Connecticut, Farmington, CT 06032, USA
| | - Damian Smedley
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK
| |
Collapse
|