An end to genetic exceptionalism: reframing the ethics of genomic sequencing for rapid neonatal diagnosis.

Kaiulani S Shulman, Kristen Fishler Malone, Hadley Stevens Smith, Bimal P Chaudhari, Monica H Wojcik

Abstract readReview

In one paragraph

Review in Seminars in perinatology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Kaiulani S ShulmanHarvard Medical School, Boston, MA, USA.

Kristen Fishler MaloneMunroe-Meyer Institute for Genetics & Rehabilitation, University of Nebraska Medical Center, Omaha, NE, USA.

Hadley Stevens SmithHarvard Medical School, Boston, MA, USA; Precision Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.

Bimal P ChaudhariDivisions of Neonatology, Genetics and Genomic Medicine, Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA.

Monica H WojcikDivisions of Genetics and Genomics, Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA. Electronic address: monica.wojcik@childrens.harvard.edu.

Funding

The Burden of Genetic Disorders in Infant MortalityK23HD102589 · NICHD · BOSTON CHILDREN'S HOSPITAL · PI WOJCIK, MONICA HSIUNG · 2020 to 2024

$840k

NICHD NIH HHS K23 HD102589

6 · The paper itself

Abstract

Exome or genome sequencing (ES/GS) is increasingly used as the first-line test for postnatal diagnosis of rare genetic conditions, especially in intensive care units (ICUs). Early concerns regarding the use of broad genetic testing centered on the potential for psychosocial harm, particularly related to unexpected or uncertain findings. As the usage of ES/GS has grown and evolved, the ethical concerns initially raised have not borne out in empirical measurement of patient and family experience. We therefore review the use of diagnostic genomic sequencing in the neonatal intensive care unit with comparison to other standard diagnostic tests that have not elicited similar ethical questioning. We frame this landscape within the concept of genetic contextualism rather than exceptionalism and suggest that this approach may lead to a more productive future for applied genomic medicine, especially for sick neonates and infants in the NICU.

Indexed as

Exome SequencingGenetic Diseases, InbornGenetic TestingGenomicsNeonatal ScreeningHumansInfant, NewbornIntensive Care Units, NeonatalWhole Genome SequencingEthicsExome sequencingGenome sequencingInfantNeonate

Identifiers

PMID40518318

DOI10.1016/j.semperi.2025.152110

PMCPMC12719933

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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.