Data-driven consideration of genetic disorders for global genomic newborn screening programs

doi:10.1016/j.gim.2025.101443

. 2025 Jul;27(7):101443.

doi: 10.1016/j.gim.2025.101443. Epub 2025 May 9.

Data-driven consideration of genetic disorders for global genomic newborn screening programs

Thomas Minten¹, Sarah Bick², Sophia Adelson³, Nils Gehlenborg⁴, Laura M Amendola⁵, François Boemer⁶, Alison J Coffey⁷, Nicolas Encina⁸, Alessandra Ferlini⁹, Janbernd Kirschner¹⁰, Bianca E Russell¹¹, Laurent Servais¹², Kristen L Sund¹³, Ryan J Taft⁷, Petros Tsipouras¹⁴, Hana Zouk¹⁵; ICoNS Gene List Contributors; David Bick¹⁶; International Consortium on Newborn Sequencing (ICoNS); Robert C Green¹⁷, Nina B Gold¹⁸

Collaborators, Affiliations

Collaborators

Affiliations

¹ KU Leuven, Leuven, Belgium.
² Boston Children's Hospital, Boston, MA; Massachusetts General Hospital, Boston, MA; Harvard Medical School, Boston, MA.
³ Brigham and Women's Hospital, Boston, MA; Stanford School of Medicine, Stanford, CA.
⁴ Department of Biomedical Informatics, Harvard Medical School, Boston, MA.
⁵ National Institutes of Health, National Institute of Allergy and Infectious Disease, Rockville, MD.
⁶ CHU Liege, University of Liege, Liege, Belgium.
⁷ Illumina Inc, San Diego, CA.
⁸ ICoNS, Boston, MA; Ariadne Labs, Boston, MA; Harvard T.H. Chan School of Public Health, Boston, MA.
⁹ Unit of Medical Genetics, Department of Medical Sciences, University of Ferrara, Ferrara, Italy.
¹⁰ Department of Neuropediatrics and Muscle Disorders, University Medical Center Freiburg, Freiburg, Germany.
¹¹ Division of Clinical Genetics, Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA.
¹² University of Oxford, Oxford, UK; University of Liege, Liege, Belgium.
¹³ Nurture Genomics, Boston, MA.
¹⁴ FirstSteps-BNSI, Athens, Greece.
¹⁵ Laboratory for Molecular Medicine, Department of Pathology, Massachusetts General Hospital, Boston, MA; Department of Pathology, Harvard Medical School, Boston, MA; Broad Institute, Cambridge, MA.
¹⁶ Genomics England, London, UK.
¹⁷ Brigham and Women's Hospital, Boston, MA; Ariadne Labs, Boston, MA; Broad Institute, Cambridge, MA; Mass General Brigham, Boston, MA.
¹⁸ Department of Pediatrics, Massachusetts General Hospital, Boston, MA; Department of Pediatrics, Harvard Medical School, Boston, MA. Electronic address: ngold@mgh.harvard.edu.

PMID: 40357684
PMCID: PMC12229768 (available on 2026-05-09)
DOI: 10.1016/j.gim.2025.101443

Data-driven consideration of genetic disorders for global genomic newborn screening programs

Thomas Minten et al. Genet Med. 2025 Jul.

. 2025 Jul;27(7):101443.

doi: 10.1016/j.gim.2025.101443. Epub 2025 May 9.

Authors

Collaborators

Affiliations

¹ KU Leuven, Leuven, Belgium.
² Boston Children's Hospital, Boston, MA; Massachusetts General Hospital, Boston, MA; Harvard Medical School, Boston, MA.
³ Brigham and Women's Hospital, Boston, MA; Stanford School of Medicine, Stanford, CA.
⁴ Department of Biomedical Informatics, Harvard Medical School, Boston, MA.
⁵ National Institutes of Health, National Institute of Allergy and Infectious Disease, Rockville, MD.
⁶ CHU Liege, University of Liege, Liege, Belgium.
⁷ Illumina Inc, San Diego, CA.
⁸ ICoNS, Boston, MA; Ariadne Labs, Boston, MA; Harvard T.H. Chan School of Public Health, Boston, MA.
⁹ Unit of Medical Genetics, Department of Medical Sciences, University of Ferrara, Ferrara, Italy.
¹⁰ Department of Neuropediatrics and Muscle Disorders, University Medical Center Freiburg, Freiburg, Germany.
¹¹ Division of Clinical Genetics, Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA.
¹² University of Oxford, Oxford, UK; University of Liege, Liege, Belgium.
¹³ Nurture Genomics, Boston, MA.
¹⁴ FirstSteps-BNSI, Athens, Greece.
¹⁵ Laboratory for Molecular Medicine, Department of Pathology, Massachusetts General Hospital, Boston, MA; Department of Pathology, Harvard Medical School, Boston, MA; Broad Institute, Cambridge, MA.
¹⁶ Genomics England, London, UK.
¹⁷ Brigham and Women's Hospital, Boston, MA; Ariadne Labs, Boston, MA; Broad Institute, Cambridge, MA; Mass General Brigham, Boston, MA.
¹⁸ Department of Pediatrics, Massachusetts General Hospital, Boston, MA; Department of Pediatrics, Harvard Medical School, Boston, MA. Electronic address: ngold@mgh.harvard.edu.

PMID: 40357684
PMCID: PMC12229768 (available on 2026-05-09)
DOI: 10.1016/j.gim.2025.101443

Abstract

Purpose: Over 30 international studies are exploring newborn sequencing (NBSeq) to expand the range of genetic disorders included in newborn screening. Substantial variability in gene selection across programs exists, highlighting the need for a systematic approach to prioritize genes.

Methods: We assembled a data set comprising 25 characteristics about each of the 4390 genes included in 27 NBSeq programs. We used regression analysis to identify several predictors of inclusion and developed a machine learning model to rank genes for public health consideration.

Results: Among 27 NBSeq programs, the number of genes analyzed ranged from 134 to 4299, with only 74 (1.7%) genes included by over 80% of programs. The most significant associations with gene inclusion across programs were presence on the US Recommended Uniform Screening Panel (inclusion increase of 74.7%, CI: 71.0%-78.4%), robust evidence on the natural history (29.5%, CI: 24.6%-34.4%), and treatment efficacy (17.0%, CI: 12.3%-21.7%) of the associated genetic disease. A boosted trees machine learning model using 13 predictors achieved high accuracy in predicting gene inclusion across programs (area under the curve = 0.915, R² = 84%).

Conclusion: The machine learning model developed here provides a ranked list of genes that can adapt to emerging evidence and regional needs, enabling more consistent and informed gene selection in NBSeq initiatives.

Keywords: Gene selection; Gene-disorder associations; Genomic sequencing; Machine learning; Newborn screening.

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Conflict of interest statement

Conflict of Interest Laura M. Amendola, Alison J. Coffey, and Ryan J. Taft are employees and shareholders at Illumina Inc. Nils Gehlenborg is cofounder and equity owner of Datavisyn. Nina B. Gold provides occasional consulting services to RCG Consulting and receives honoraria from Ambry Genetics. Robert C. Green has received compensation for advising the following companies: Allelica, Atria, Fabric, Genomic Life and Juniper Genomics; and is cofounder of Genome Medical and Nurture Genomics. Bianca E. Russell and Kristen L. Sund are consultants at Nurture Genomics. Laurent Servais received personal compensation from Zentech and Illumina Inc. Petros Tsipouras is a cofounder of PlumCare RWE, LLC. All other authors declare no conflicts of interest.

Update of

Data-driven consideration of genetic disorders for global genomic newborn screening programs.
Minten T, Bick S, Adelson S, Gehlenborg N, Amendola LM, Boemer F, Coffey AJ, Encina N, Ferlini A, Kirschner J, Russell BE, Servais L, Sund KL, Taft RJ, Tsipouras P, Zouk H; ICoNS Gene List Contributors; Bick D; International Consortium on Newborn Sequencing (ICoNS); Green RC, Gold NB. Minten T, et al. medRxiv [Preprint]. 2025 Mar 25:2024.03.24.24304797. doi: 10.1101/2024.03.24.24304797. medRxiv. 2025. Update in: Genet Med. 2025 Jul;27(7):101443. doi: 10.1016/j.gim.2025.101443. PMID: 38585998 Free PMC article. Updated. Preprint.

Cited by

TREAT: systematic and inclusive selection process of genes for genomic newborn screening as part of the Screen4Care project.
Saier C, Sansen S, Berghout J, Freyler K, Einhorn M, Einhorn Y, Matalonga L, Beltran S, Novelli A, Selvatici R, Fortunato F, Montanari S, Martinez-Fresno M, Gumus G, Agolini E, Garnier N, Ferlini A, Bertini E, Kirschner J. Saier C, et al. Orphanet J Rare Dis. 2025 May 15;20(1):231. doi: 10.1186/s13023-025-03692-6. Orphanet J Rare Dis. 2025. PMID: 40375093 Free PMC article.

References

1. Waisbren SE, Bäck DK, Liu C, et al. Parents are interested in newborn genomic testing during the early postpartum period. Genet Med. 2015;17(6):501–504. - PMC - PubMed
1. Ceyhan-Birsoy O, Machini K, Lebo MS, et al. A curated gene list for reporting results of newborn genomic sequencing. Genet Med. 2017;19(7):809–818. - PMC - PubMed
1. Genetti CA, Schwartz TS, Robinson JO, et al. Parental interest in genomic sequencing of newborns: enrollment experience from the BabySeq Project. Genet Med. 2019;21(3):622–630. - PMC - PubMed
1. Holm IA, Agrawal PB, Ceyhan-Birsoy O, et al. The BabySeq project: implementing genomic sequencing in newborns. BMC Pediatr. 2018;18(1):225. - PMC - PubMed
1. Ceyhan-Birsoy O, Murry JB, Machini K, et al. Interpretation of Genomic Sequencing Results in Healthy and Ill Newborns: Results from the BabySeq Project. Am J Hum Genet. 2019;104(1):76–93. - PMC - PubMed

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[1] Waisbren SE, Bäck DK, Liu C, et al. Parents are interested in newborn genomic testing during the early postpartum period. Genet Med. 2015;17(6):501–504. - PMC - PubMed

[2] Waisbren SE, Bäck DK, Liu C, et al. Parents are interested in newborn genomic testing during the early postpartum period. Genet Med. 2015;17(6):501–504. - PMC - PubMed

[3] Ceyhan-Birsoy O, Machini K, Lebo MS, et al. A curated gene list for reporting results of newborn genomic sequencing. Genet Med. 2017;19(7):809–818. - PMC - PubMed

[4] Ceyhan-Birsoy O, Machini K, Lebo MS, et al. A curated gene list for reporting results of newborn genomic sequencing. Genet Med. 2017;19(7):809–818. - PMC - PubMed

[5] Genetti CA, Schwartz TS, Robinson JO, et al. Parental interest in genomic sequencing of newborns: enrollment experience from the BabySeq Project. Genet Med. 2019;21(3):622–630. - PMC - PubMed

[6] Genetti CA, Schwartz TS, Robinson JO, et al. Parental interest in genomic sequencing of newborns: enrollment experience from the BabySeq Project. Genet Med. 2019;21(3):622–630. - PMC - PubMed

[7] Holm IA, Agrawal PB, Ceyhan-Birsoy O, et al. The BabySeq project: implementing genomic sequencing in newborns. BMC Pediatr. 2018;18(1):225. - PMC - PubMed

[8] Holm IA, Agrawal PB, Ceyhan-Birsoy O, et al. The BabySeq project: implementing genomic sequencing in newborns. BMC Pediatr. 2018;18(1):225. - PMC - PubMed

[9] Ceyhan-Birsoy O, Murry JB, Machini K, et al. Interpretation of Genomic Sequencing Results in Healthy and Ill Newborns: Results from the BabySeq Project. Am J Hum Genet. 2019;104(1):76–93. - PMC - PubMed

[10] Ceyhan-Birsoy O, Murry JB, Machini K, et al. Interpretation of Genomic Sequencing Results in Healthy and Ill Newborns: Results from the BabySeq Project. Am J Hum Genet. 2019;104(1):76–93. - PMC - PubMed

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Data-driven consideration of genetic disorders for global genomic newborn screening programs

Collaborators

Affiliations

Data-driven consideration of genetic disorders for global genomic newborn screening programs

Authors

Collaborators

Affiliations

Abstract

Conflict of interest statement

Update of

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References

MeSH terms

Grants and funding

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Medical

Abstract

Conflict of interest statement

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