Evidence map›Paper›PMID 41510674›Full record

ArticleGenetics in medicine : official journal of the American College of Medical Genetics2026

Evaluating pregnancy and neonatal outcomes in mothers with genetic disease using electronic health care records.

Rory J Tinker, Lucas D Richter, Yutaka Furuta, Cathy Shyr, Sherwin M Shirazi, Jennifer Sucre, Luke A Gatta, John A Phillips, Josh F Peterson, Lisa Bastarache

Abstract read
In one paragraph

Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

10 authors.

Rory J TinkerDepartment of Medical Genetics and Genomics, Icahn School of Medicine at Mount Sinai, New York, NY; Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN. Electronic address: rory.tinker@mssm.edu.
Lucas D RichterDivision of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN.
Yutaka FurutaDivision of Medical Genetics and Genomic Medicine, Vanderbilt University Medical Center, Nashville, TN.
Cathy ShyrDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN.
Sherwin M ShiraziDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN.
Jennifer SucreMildred Stahlman Division of Neonatology, Monroe Carell Jr. Children's Hospital at Vanderbilt, Nashville, TN; Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, TN.
Luke A GattaMildred Stahlman Division of Neonatology, Monroe Carell Jr. Children's Hospital at Vanderbilt, Nashville, TN.
John A PhillipsDivision of Medical Genetics and Genomic Medicine, Vanderbilt University Medical Center, Nashville, TN.
Josh F PetersonDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN.
Lisa BastaracheDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN.

Funding

T32 training grant in medical genetics.T32GM082773 · NIGMS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Laszlo Tamas Kozicz, Eva Morava-Kozicz · 2008 to 2026
$4.9M
Translating the Clinical Knowledge of Mendelian Diseases to Real-world EHR Data to Improve Identification of Undiagnosed PatientsR01HG012657 · NHGRI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Lisa Bastarache, Douglas Ruderfer · 2022 to 2026
$4.3M
VGM: Vanderbilt Genomic Medicine Training ProgramT32HG008341 · NHGRI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Nancy J Cox, Joseph F. Peterson · 2016 to 2026
$2.8M
NHGRI NIH HHS R01 HG012657NHGRI NIH HHS T32 HG008341NIGMS NIH HHS T32 GM082773
6 · The paper itself

Abstract

purposeThe effect of Mendelian disorders on pregnancy and neonatal outcomes is poorly understood because of their rarity and the challenge of compiling complete prenatal and postnatal records.

methodsUsing electronic health records from a single academic center, we developed a retrospective cohort of maternal-infant dyads. Cases were mothers with molecularly confirmed Mendelian disorders paired with live-born infants; controls had no documented genetic disease. Outcomes were evaluated overall, by organ system, and by individual disorder.

resultsThe cohort included 58,912 dyads, 241 with genetic diagnoses and 58,671 controls. Although overall outcomes were generally favorable, mothers with genetic disorders had higher rates of cesarean delivery and neonatal intensive care unit admission, earlier gestational age, and lower Apgar scores. Neonatal risks were greatest among neurological and cardiovascular disorders. Known associations were replicated, including increased neonatal intensive care unit admission in 22q11.2 deletion syndrome, cesarean delivery in Turner syndrome, and gestational diabetes in cystic fibrosis. We also provided descriptive electronic-health-record-based case reports and case series for 35 disorders previously lacking published pregnancy outcome data.

conclusionThis study identifies elevated perinatal risks in specific Mendelian disease groups and demonstrates how electronic-health-record-linked data can support prenatal counseling, risk stratification, and individualized care for individuals with genetic disorders.

Indexed as

Genetic Diseases, InbornAdultCesarean SectionElectronic Health RecordsFemaleGestational AgeHumansInfant, NewbornMothersPregnancyPregnancy OutcomeRetrospective StudiesElectronic health recordsGenetic diseasesInfantPregnancy outcomePrenatal diagnosis

Identifiers

PMID41510674
PMCPMC13104601

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Registered trials

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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.