Evidence map›Paper›PMID 39355980›Full record

ArticleGenetics in medicine : official journal of the American College of Medical Genetics2025

Estimating the sensitivity of genomic newborn screening for treatable inherited metabolic disorders.

Sarah L Bick, Aparna Nathan, Hannah Park, Robert C Green, Monica H Wojcik, Nina B Gold

Abstract read
In one paragraph

Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Sarah L BickDivision of Genetics and Genomics, Boston Children's Hospital, Boston, MA; Division of Medical Genetics and Metabolism, Massachusetts General Hospital for Children, Boston, MA; Harvard Medical School, Boston, MA.
Aparna NathanDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA.
Hannah ParkDivision of Genetics and Genomics, Boston Children's Hospital, Boston, MA; Harvard Medical School, Boston, MA; Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital, Boston, MA.
Robert C GreenHarvard Medical School, Boston, MA; Mass General Brigham, Boston, MA; Broad Institute of MIT and Harvard, Cambridge, MA; Ariadne Labs, Boston, MA.
Monica H WojcikDivision of Genetics and Genomics, Boston Children's Hospital, Boston, MA; Harvard Medical School, Boston, MA; Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital, Boston, MA; Broad Institute of MIT and Harvard, Cambridge, MA.
Nina B GoldDivision of Medical Genetics and Metabolism, Massachusetts General Hospital for Children, Boston, MA; Harvard Medical School, Boston, MA. Electronic address: ngold@mgh.harvard.edu.

Funding

TRAINING GRANT IN GENETICST32GM007748 · NIGMS · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI Anne O'Donnell-Luria, Louise Wilkins-Haug · 1985 to 2026
$12.0M
Implementation of Whole Genome Sequencing as Screening in a Diverse Cohort of Healthy InfantsU01TR003201 · NCATS · BRIGHAM AND WOMEN'S HOSPITAL · PI GREEN, ROBERT C., HOLM, INGRID ADELE · 2021 to 2024
$5.1M
Genome-first approach to treatable genetic conditions in adultsK08HG012811 · NHGRI · MASSACHUSETTS GENERAL HOSPITAL · PI Nina Beth Gold · 2023 to 2026
$883k
The Burden of Genetic Disorders in Infant MortalityK23HD102589 · NICHD · BOSTON CHILDREN'S HOSPITAL · PI WOJCIK, MONICA HSIUNG · 2020 to 2024
$840k
NCATS NIH HHS U01 TR003201NHGRI NIH HHS K08 HG012811NICHD NIH HHS K23 HD102589NIGMS NIH HHS T32 GM007748
6 · The paper itself

Abstract

purposeOver 30 research groups and companies are exploring newborn screening using genomic sequencing (NBSeq), but the sensitivity of this approach is not well understood.

methodsWe identified individuals with treatable inherited metabolic disorders (IMDs) and ascertained the proportion whose DNA analysis revealed explanatory deleterious variants (EDVs). We examined variables associated with EDV detection and estimated the sensitivity of DNA-first NBSeq. We further predicted the annual rate of true-positive and false-negative NBSeq results in the United States for several conditions on the Recommended Uniform Screening Panel.

resultsWe identified 635 individuals with 80 unique IMDs. In univariate analyses, Black race (OR = 0.37, 95% CI: 0.16-0.89, P = .02) and public insurance (OR = 0.60, 95% CI: 0.39-0.91, P = .02) were less likely to be associated with finding EDVs. Had all individuals been screened with NBSeq, the sensitivity would have been 80.3%. We estimated that between 0 and 649.9 cases of Recommended Uniform Screening Panel IMDs would be missed annually by NBSeq in the United States.

conclusionThe overall sensitivity of NBSeq for treatable IMDs is estimated at 80.3%. That sensitivity will likely be lower for Black infants and those who are on public insurance.

Indexed as

Genetic TestingNeonatal ScreeningFemaleGenomicsHumansInfant, NewbornMaleMetabolic DiseasesMetabolism, Inborn ErrorsSensitivity and SpecificitySequence Analysis, DNAUnited StatesDetection sensitivityExplanatory deleterious variantsGenomic sequencingInherited metabolic diseasesNewborn screening

Identifiers

PMID39355980
PMCPMC11717630

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.