1
|
Spiekerkoetter U, Bick D, Scott R, Hopkins H, Krones T, Gross ES, Bonham JR. Genomic newborn screening: Are we entering a new era of screening? J Inherit Metab Dis 2023; 46:778-795. [PMID: 37403863 DOI: 10.1002/jimd.12650] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 06/01/2023] [Accepted: 06/13/2023] [Indexed: 07/06/2023]
Abstract
Population newborn screening (NBS) for phenylketonuria began in the United States in 1963. In the 1990s electrospray ionization mass spectrometry permitted an array of pathognomonic metabolites to be identified simultaneously, enabling up to 60 disorders to be recognized with a single test. In response, differing approaches to the assessment of the harms and benefits of screening have resulted in variable screening panels worldwide. Thirty years on and another screening revolution has emerged with the potential for first line genomic testing extending the range of screening conditions recognized after birth to many hundreds. At the annual SSIEM conference in 2022 in Freiburg, Germany, an interactive plenary discussion on genomic screening strategies and their challenges and opportunities was conducted. The Genomics England Research project proposes the use of Whole Genome Sequencing to offer extended NBS to 100 000 babies for defined conditions with a clear benefit for the child. The European Organization for Rare Diseases seeks to include "actionable" conditions considering also other types of benefits. Hopkins Van Mil, a private UK research institute, determined the views of citizens and revealed as a precondition that families are provided with adequate information, qualified support, and that autonomy and data are protected. From an ethical standpoint, the benefits ascribed to screening and early treatment need to be considered in relation to asymptomatic, phenotypically mild or late-onset presentations, where presymptomatic treatment may not be required. The different perspectives and arguments demonstrate the unique burden of responsibility on those proposing new and far-reaching developments in NBS programs and the need to carefully consider both harms and benefits.
Collapse
Affiliation(s)
- Ute Spiekerkoetter
- Department of Pediatrics, Adolescent Medicine and Neonatology, Faculty of Medicine, University Children's Hospital, Freiburg, Germany
| | | | | | | | - Tanja Krones
- URPP Human Reproduction Reloaded - H2R and Institute of Biomedical Ethics and History of Medicine, University Hospital/University of Zurich, Zurich, Switzerland
| | | | - James R Bonham
- International Society of Neonatal Screening, Maarssen, The Netherlands
| |
Collapse
|
2
|
Kannan B, Navamani HK, Jayaseelan VP, Arumugam P. A Rare Biotinidase Deficiency in the Pediatrics Population: Genotype-Phenotype Analysis. J Pediatr Genet 2023; 12:1-15. [PMID: 36684547 PMCID: PMC9848769 DOI: 10.1055/s-0042-1757887] [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: 01/24/2022] [Accepted: 09/06/2022] [Indexed: 11/07/2022]
Abstract
Biotinidase (BTD) deficiency is a rare autosomal recessive metabolic disorder caused by insufficient biotin metabolism, where it cannot recycle the vitamin biotin. When this deficiency is not treated with supplements, it can lead to severe neurological conditions. Approximately 1 in 60,000 newborns are affected by BTD deficiency. The BTD deficiency causes late-onset biotin-responsive multiple carboxylase deficiency, which leads to acidosis or lactic acidosis, hypoglycemia, and abnormal catabolism. BTD deficiency is of two types based on the amount of BTD Enzyme present in the serum. A wide range of pathogenic mutations in the BTD gene are reported worldwide. Mutations in the BTD gene lead to profound and partial BTD deficiency. Profound BTD deficiency results in a severe pathogenic condition. A high frequency of newborns are affected with the partial deficiency worldwide. They are mostly asymptomatic, but symptoms may appear during stressful conditions such as fasting or viral infections. Several pathogenic mutations are significantly associated with neurological, ophthalmological, and skin problems along with several other clinical features. This review discusses the BTD gene mutation in multiple populations detected with phenotypic features. The molecular-based biomarker screening is necessary for the disease during pregnancy, as it could be helpful for the early identification of BTD deficiency, providing a better treatment strategy. Moreover, implementing newborn screening for the BTD deficiency helps patients prevent several diseases.
Collapse
Affiliation(s)
- Balachander Kannan
- Molecular Biology Lab, Centre for Cellular and Molecular Research, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India
| | - Hepzibah Kirubamani Navamani
- Department of Obstetrics and Gynaecology, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Saveetha Medical College and Hospitals, Chennai, Tamil Nadu, India
| | - Vijayashree Priyadharsini Jayaseelan
- Molecular Biology Lab, Centre for Cellular and Molecular Research, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India
| | - Paramasivam Arumugam
- Molecular Biology Lab, Centre for Cellular and Molecular Research, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India
| |
Collapse
|
3
|
Wojcik MH, Zhang T, Ceyhan-Birsoy O, Genetti CA, Lebo MS, Yu TW, Parad RB, Holm IA, Rehm HL, Beggs AH, Green RC, Agrawal PB. Discordant results between conventional newborn screening and genomic sequencing in the BabySeq Project. Genet Med 2021; 23:1372-1375. [PMID: 33772220 PMCID: PMC8263473 DOI: 10.1038/s41436-021-01146-5] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2021] [Revised: 03/01/2021] [Accepted: 03/03/2021] [Indexed: 12/12/2022] Open
Abstract
PURPOSE Newborn screening (NBS) is performed to identify neonates at risk for actionable, severe, early-onset disorders, many of which are genetic. The BabySeq Project randomized neonates to receive conventional NBS or NBS plus exome sequencing (ES) capable of detecting sequence variants that may also diagnose monogenic disease or indicate genetic disease risk. We therefore evaluated how ES and conventional NBS results differ in this population. METHODS We compared results of NBS (including hearing screens) and ES for 159 infants in the BabySeq Project. Infants were considered "NBS positive" if any abnormal result was found indicating disease risk and "ES positive" if ES identified a monogenic disease risk or a genetic diagnosis. RESULTS Most infants (132/159, 84%) were NBS and ES negative. Only one infant was positive for the same disorder by both modalities. Nine infants were NBS positive/ES negative, though seven of these were subsequently determined to be false positives. Fifteen infants were ES positive/NBS negative, all of which represented risk of genetic conditions that are not included in NBS programs. No genetic explanation was identified for eight infants referred on the hearing screen. CONCLUSION These differences highlight the complementarity of information that may be gleaned from NBS and ES in the newborn period.
Collapse
Affiliation(s)
- Monica H Wojcik
- Division of Genetics and Genomics, The Manton Center for Orphan Disease Research, Boston Children's Hospital, and Department of Pediatrics, Harvard Medical School, Boston, MA, USA.
- Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA.
- Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Tian Zhang
- Division of Genetics and Genomics, The Manton Center for Orphan Disease Research, Boston Children's Hospital, and Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Ozge Ceyhan-Birsoy
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Casie A Genetti
- Division of Genetics and Genomics, The Manton Center for Orphan Disease Research, Boston Children's Hospital, and Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Matthew S Lebo
- Laboratory for Molecular Medicine, Partners HealthCare Personalized Medicine, Cambridge, MA, USA
- Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Timothy W Yu
- Division of Genetics and Genomics, The Manton Center for Orphan Disease Research, Boston Children's Hospital, and Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Richard B Parad
- Department of Pediatric Newborn Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Ingrid A Holm
- Division of Genetics and Genomics, The Manton Center for Orphan Disease Research, Boston Children's Hospital, and Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Heidi L Rehm
- Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Laboratory for Molecular Medicine, Partners HealthCare Personalized Medicine, Cambridge, MA, USA
- Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Alan H Beggs
- Division of Genetics and Genomics, The Manton Center for Orphan Disease Research, Boston Children's Hospital, and Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Robert C Green
- Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine (Genetics), Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Ariadne Labs, Boston, MA, USA
| | - Pankaj B Agrawal
- Division of Genetics and Genomics, The Manton Center for Orphan Disease Research, Boston Children's Hospital, and Department of Pediatrics, Harvard Medical School, Boston, MA, USA.
- Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA.
- Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| |
Collapse
|
4
|
Zhao M, Havrilla JM, Fang L, Chen Y, Peng J, Liu C, Wu C, Sarmady M, Botas P, Isla J, Lyon GJ, Weng C, Wang K. Phen2Gene: rapid phenotype-driven gene prioritization for rare diseases. NAR Genom Bioinform 2020; 2:lqaa032. [PMID: 32500119 PMCID: PMC7252576 DOI: 10.1093/nargab/lqaa032] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Revised: 04/10/2020] [Accepted: 04/28/2020] [Indexed: 02/07/2023] Open
Abstract
Human Phenotype Ontology (HPO) terms are increasingly used in diagnostic settings to aid in the characterization of patient phenotypes. The HPO annotation database is updated frequently and can provide detailed phenotype knowledge on various human diseases, and many HPO terms are now mapped to candidate causal genes with binary relationships. To further improve the genetic diagnosis of rare diseases, we incorporated these HPO annotations, gene-disease databases and gene-gene databases in a probabilistic model to build a novel HPO-driven gene prioritization tool, Phen2Gene. Phen2Gene accesses a database built upon this information called the HPO2Gene Knowledgebase (H2GKB), which provides weighted and ranked gene lists for every HPO term. Phen2Gene is then able to access the H2GKB for patient-specific lists of HPO terms or PhenoPacket descriptions supported by GA4GH (http://phenopackets.org/), calculate a prioritized gene list based on a probabilistic model and output gene-disease relationships with great accuracy. Phen2Gene outperforms existing gene prioritization tools in speed and acts as a real-time phenotype-driven gene prioritization tool to aid the clinical diagnosis of rare undiagnosed diseases. In addition to a command line tool released under the MIT license (https://github.com/WGLab/Phen2Gene), we also developed a web server and web service (https://phen2gene.wglab.org/) for running the tool via web interface or RESTful API queries. Finally, we have curated a large amount of benchmarking data for phenotype-to-gene tools involving 197 patients across 76 scientific articles and 85 patients' de-identified HPO term data from the Children's Hospital of Philadelphia.
Collapse
Affiliation(s)
- Mengge Zhao
- Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - James M Havrilla
- Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Li Fang
- Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Ying Chen
- Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Jacqueline Peng
- Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.,Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Cong Liu
- Department of Biomedical Informatics, Columbia University Medical Center, New York, NY 10032, USA
| | - Chao Wu
- Division of Genomic Diagnostics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Mahdi Sarmady
- Division of Genomic Diagnostics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.,Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Pablo Botas
- Foundation 29, Pozuelo de Alarcon, 28223 Madrid, Spain
| | - Julián Isla
- Foundation 29, Pozuelo de Alarcon, 28223 Madrid, Spain.,Dravet Syndrome European Federation, 29200 Brest, France
| | - Gholson J Lyon
- Institute for Basic Research in Developmental Disabilities (IBR), Staten Island, NY 10314, USA
| | - Chunhua Weng
- Department of Biomedical Informatics, Columbia University Medical Center, New York, NY 10032, USA
| | - Kai Wang
- Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.,Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| |
Collapse
|
5
|
Mackay ZP, Dukhovny D, Phillips KA, Beggs AH, Green RC, Parad RB, Christensen KD. Quantifying Downstream Healthcare Utilization in Studies of Genomic Testing. VALUE IN HEALTH : THE JOURNAL OF THE INTERNATIONAL SOCIETY FOR PHARMACOECONOMICS AND OUTCOMES RESEARCH 2020; 23:559-565. [PMID: 32389220 PMCID: PMC7293136 DOI: 10.1016/j.jval.2020.01.017] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2019] [Revised: 12/17/2019] [Accepted: 01/26/2020] [Indexed: 05/28/2023]
Abstract
OBJECTIVES The challenges of understanding how interventions influence follow-up medical care are magnified during genomic testing because few patients have received it to date and because the scope of information it provides is complex and often unexpected. We tested a novel strategy for quantifying downstream healthcare utilization after genomic testing to more comprehensively and efficiently identify related services. We also evaluated the effectiveness of different methods for collecting these data. METHODS We developed a risk-based approach for a trial of newborn genomic sequencing in which we defined primary conditions based on existing diagnoses and family histories of disease and defined secondary conditions based on unexpected findings. We then created patient-specific lists of services associated with managing primary and secondary conditions. Services were quantified based on medical record reviews, surveys, and telephone check-ins with parents. RESULTS By focusing on services that genomic testing would most likely influence in the short-term, we reduced the number of services in our analyses by more than 90% compared with analyses of all observed services. We also identified the same services that were ordered in response to unexpected findings as were identified during expert review and by confirming whether recommendations were completed. Data also showed that quantifying healthcare utilization with surveys and telephone check-ins alone would have missed the majority of attributable services. CONCLUSIONS Our risk-based strategy provides an improved approach for assessing the short-term impact of genomic testing and other interventions on healthcare utilization while conforming as much as possible to existing best-practice recommendations.
Collapse
Affiliation(s)
- Zoë P Mackay
- Boston University School of Medicine, Boston, MA, USA
| | - Dmitry Dukhovny
- Department of Pediatrics, Oregon Health & Science University, Portland, OR, USA
| | - Kathryn A Phillips
- Center for Translational and Policy Research on Personalized Medicine, Department of Clinical Pharmacy, University of California San Francisco, San Francisco, CA, USA; Philip R Lee Institute for Health Policy, University of California San Francisco, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer Center, University of California at San Francisco, San Francisco, CA, USA
| | - Alan H Beggs
- Harvard Medical School, Boston, MA, USA; Division of Genetics and Genomics, The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, MA, USA
| | - Robert C Green
- Harvard Medical School, Boston, MA, USA; Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA; Partners Healthcare Personalized Medicine, Boston, MA, USA
| | - Richard B Parad
- Harvard Medical School, Boston, MA, USA; Department of Pediatric Newborn Medicine, Brigham & Women's Hospital, Boston, MA, USA
| | - Kurt D Christensen
- Harvard Medical School, Boston, MA, USA; Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA; Precision Medicine Translational Research Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA, USA.
| |
Collapse
|
6
|
Interpretation of Genomic Sequencing Results in Healthy and Ill Newborns: Results from the BabySeq Project. Am J Hum Genet 2019; 104:76-93. [PMID: 30609409 DOI: 10.1016/j.ajhg.2018.11.016] [Citation(s) in RCA: 153] [Impact Index Per Article: 30.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Accepted: 11/23/2018] [Indexed: 12/27/2022] Open
Abstract
Genomic sequencing provides many opportunities in newborn clinical care, but the challenges of interpreting and reporting newborn genomic sequencing (nGS) results need to be addressed for its broader and effective application. The BabySeq Project is a pilot randomized clinical trial that explores the medical, behavioral, and economic impacts of nGS in well newborns and those admitted to a neonatal intensive care unit (NICU). Here we present childhood-onset and actionable adult-onset disease risk, carrier status, and pharmacogenomics findings from nGS of 159 newborns in the BabySeq Project. nGS revealed a risk of childhood-onset disease in 15/159 (9.4%) newborns; none of the disease risks were anticipated based on the infants' known clinical or family histories. nGS also revealed actionable adult-onset disease risk in 3/85 (3.5%) newborns whose parents consented to receive this information. Carrier status for recessive diseases and pharmacogenomics variants were reported in 88% and 5% of newborns, respectively. Additional indication-based analyses were performed in 29/32 (91%) NICU newborns and 6/127 (5%) healthy newborns who later had presentations that prompted a diagnostic analysis. No variants that sufficiently explained the reason for the indications were identified; however, suspicious but uncertain results were reported in five newborns. Testing parental samples contributed to the interpretation and reporting of results in 13/159 (8%) newborns. Our results suggest that nGS can effectively detect risk and carrier status for a wide range of disorders that are not detectable by current newborn screening assays or predicted based on the infant's known clinical or family history, and the interpretation of results can substantially benefit from parental testing.
Collapse
|