Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
6824 participants
OBSERVATIONAL
2022-09-01
2025-06-02
Brief Summary
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Baby Detect Project is an innovative NBS program using a panel of target sequencing that aims to identify 126 treatable severe early onset genetic diseases at birth caused by 361 genes. The list of diseases has been established in close collaboration with the Paediatricians of the University Hospital in Liege. The investigators use dedicated dried blood spots collected between the first day and 28 days of life of babies, after a consent sign by parents.
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Detailed Description
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However, timing is of great importance for medication administration. The benefit that can be measured in a patient who has already suffered from a long irreversible degenerative disorder is small and, sometimes, it hardly justifies the cost and the burden of the treatment. Early diagnosis is, thus, of primary importance both to obtain the best effect of the innovative medications and to accelerate their development.
The investigators are pioneered in the field of genetic newborn screening (NBS) in rare diseases by funding, designing, and leading an innovative genetic NBS program initiated in March 2018 in Southern Belgium for Spinal Muscular Atrophy (SMA) that allowed, so far, for 11 children to be detected and treated early and avoid the terrible fate of the disease. The program was disseminated in 17 countries and included public dissemination and health-economic analysis since the very beginning \[1\]. (www.facebook.com/sunmayariseonsma).
Drawing upon our experience with SMA screening, the investigators have designed a project to screen up to 40,000 newborns/year progressively in 3 years for virtually all the rare diseases that can benefit from treatment or a pre-symptomatic clinical trial.
The methodology of Baby Detect includes sequencing of target genes on dried blood spots collected from the NBS cards in a timely and cost-efficient manner, and its high dynamicity allows for any newly treatable rare disease to be included in its scheme in no longer than 6 months.
Baby Detect, as a multidisciplinary newborn screening program, involves expertise in areas from genetics and medicine to laboratory studies, computer science, Data Protection, Ethics, and health economy. It will constitute the proof of concept that is needed before moving to a whole region-scale population.
Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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Newborns with consent
Newborns with parent's consent
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
* consent of parent
Exclusion Criteria
* Non consent of parent
28 Days
ALL
Yes
Sponsors
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Centre Hospitalier Régional de la Citadelle
OTHER
University of Liege
OTHER
Sanofi
INDUSTRY
Orchard Therapeutics
INDUSTRY
Takeda
INDUSTRY
Zentech-Lacar Company
UNKNOWN
Leon Fredericq Foundation
UNKNOWN
Centre Hospitalier Universitaire de Liege
OTHER
Responsible Party
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Laurent Servais
Professor
Principal Investigators
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Laurent Servais
Role: PRINCIPAL_INVESTIGATOR
Centre Hospitalier Universitaire de Liege
Locations
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CRMN, Hôpital La Citadelle
Liège, Wallonia, Belgium
Countries
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References
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Boemer F, Hovhannesyan K, Piazzon F, Minner F, Mni M, Jacquemin V, Mashhadizadeh D, Benmhammed N, Bours V, Jacquinet A, Harvengt J, Bulk S, Dideberg V, Helou L, Palmeira L, Dangouloff T; BabyDetect Expert Panel; Servais L. Population-based, first-tier genomic newborn screening in the maternity ward. Nat Med. 2025 Apr;31(4):1339-1350. doi: 10.1038/s41591-024-03465-x. Epub 2025 Jan 28.
Dangouloff T, Hovhannesyan K, Mashhadizadeh D, Minner F, Mni M, Helou L, Piazzon F, Palmeira L, Boemer F, Servais L. Feasibility and Acceptability of a Newborn Screening Program Using Targeted Next-Generation Sequencing in One Maternity Hospital in Southern Belgium. Children (Basel). 2024 Jul 30;11(8):926. doi: 10.3390/children11080926.
Related Links
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Related Info
Other Identifiers
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Baby Detect
Identifier Type: -
Identifier Source: org_study_id
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