Provision and availability of genomic medicine services in Level IV neonatal intensive care units

SeqFirst: Building equity access to a precise genetic diagnosis in critically ill newborns

Access to a precise genetic diagnosis (PrGD) in critically ill newborns is limited and inequitable because the complex inclusion criteria used to prioritize testing eligibility omit many patients at high risk for a genetic condition. SeqFirst-neo is a program to test whether a genotype-driven workflow using simple, broad exclusion criteria to assess eligibility for rapid genome sequencing (rGS) increases access to a PrGD in critically ill newborns. All 408 newborns admitted to a neonatal intensive care unit between January 2021 and February 2022 were assessed, and of 240 eligible infants, 126 were offered rGS (i.e., intervention group [IG]) and compared to 114 infants who received conventional care in parallel (i.e., conventional care group [CCG]). A PrGD was made in 62/126 (49.2%) IG neonates compared to 11/114 (9.7%) CCG infants. The odds of receiving a PrGD were ∼9 times greater in the IG vs. the CCG, and this difference was maintained at 12 months follow-up. Access to a PrGD in the IG vs. CCG differed significantly between infants identified as non-White (34/74, 45.9% vs. 6/29, 20.7%; p = 0.024) and Black (8/10, 80.0% vs. 0/4; p = 0.015). Neonatologists were significantly less successful at predicting a PrGD in non-White than non-Hispanic White infants. The use of a standard workflow in the IG with a PrGD revealed that a PrGD would have been missed in 26/62 (42%) infants. The use of simple, broad exclusion criteria that increase access to genetic testing significantly increases access to a PrGD, improves access equity, and results in fewer missed diagnoses.

Going Back in Time: Prenatal Presentations of Postnatal Genetic Diagnoses Made in a Neonatal Intensive Care Unit

OBJECTIVES

Prenatal genetic diagnosis can impact care across the perinatal continuum; however, prenatal suspicion for genetic disorders may be complicated by incomplete knowledge of fetal rare-disease phenotypes. Here, we describe the prenatal presentations of a cohort of infants with rare genetic conditions who were diagnosed postnatally in a neonatal intensive care unit (NICU), to characterize prenatal presenting features and evaluate why the diagnosis was not identified prenatally.

METHODS

Retrospective cohort study of infants born over a 7 year period (2017-2023) who were admitted to a Level IV NICU and received a postnatal genetic diagnosis prior to 1 year of age. We identified which of these infants had been imaged prenatally at our Maternal Fetal Care Center (MFCC) as an opportunity for prenatal genetic diagnosis. Clinical data were abstracted from the medical records.

RESULTS

51 cases met the inclusion criteria. Nine of the 51 infants were not strongly suspected to have a genetic syndrome prenatally when seen at the MFCC, as evidenced by lack of prenatal genetic consultation and lack of documented suspicion for a genetic etiology. These cases largely had absent or uncertain prenatal phenotypes. In most cases (42/51, 82.4%), prenatal diagnostic testing was not pursued even if offered. Overall, postnatal diagnoses, of which there was one dual diagnosis, were made by karyotype/FISH (11/52, 21.1%), microarray (8/52, 15.4%), gene panel/targeted testing (17/52, 32.7%), or exome sequencing (16/52, 30.8%).

CONCLUSIONS

Our data illustrate the challenges in fetal phenotyping and support a broad approach to prenatal testing to facilitate early genetic diagnosis, which may meaningfully impact postnatal care.

Multidimensional and Longitudinal Impact of a Genetic Diagnosis for Critically Ill Infants

BACKGROUND AND OBJECTIVES

Many genetic conditions present in the NICU, where a diagnostic evaluation is pursued. However, understanding of the impact of a genetic diagnosis on clinical outcomes and health-related quality of life for these infants remains incomplete. We therefore evaluated parent-reported outcomes complemented by clinical outcomes measures over one year for a cohort of infants in the NICU undergoing genetic evaluation.

METHODS

Prospective cohort study evaluating outcomes after genetics consultation in a level IV NICU via parent report and electronic medical record review. Eligible infants were genetically undiagnosed at enrollment. Parent surveys were administered at baseline and 3, 6, and 12 months following enrollment and assessed genetic testing utility as well as parent-reported infant health-related quality of life using the Infant Toddler Quality of Life Questionnaire.

RESULTS

A total of 110 infant-parent pairs were enrolled. Infants had a median age at enrollment of 15 days (interquartile range 8-37.75). At baseline, 74% (81/110) of parents endorsed high importance of finding a genetic diagnosis, but perceived importance significantly decreased over time. Over the study period, 38 infants received a molecular diagnosis per parent report, although this was discordant with electronic medical record review. Identification of a diagnosis did not significantly impact health-related quality of life across most domains, which was lower overall than population norms.

CONCLUSIONS

A genetic diagnosis is highly desired by parents in the NICU, though waning interest over time for undiagnosed families may reflect parental emotional adaptation and acceptance. Additional supports are needed to improve perceived quality of life.

"It's hard to wait": Provider perspectives on current genomic care in safety-net NICUs

PURPOSE

Critically ill infants from marginalized populations disproportionately receive care in neonatal intensive care units (NICUs) that lack access to state-of-the-art genomic care, leading to inequitable outcomes. We sought provider perspectives to inform our implementation study (VIGOR) providing rapid genomic sequencing within these settings.

METHODS

We conducted semistructured focus groups with neonatal and genetics providers at 6 NICUs at safety-net hospitals, informed by the Promoting Action on Research Implementation in Health Services framework, which incorporates evidence, context, and facilitation domains. We iteratively developed codes and themes until thematic saturation was reached.

RESULTS

Regarding evidence, providers felt that genetic testing benefits infants and families. Regarding context, the major barriers identified to genomic care were genetic testing cost, lack of genetics expertise for disclosure and follow-up, and navigating the complexity of selecting and ordering genetic tests. Providers had negative feelings about the current status quo and inequity in genomic care across NICUs. Regarding facilitation, providers felt that a virtual support model such as VIGOR would address major barriers and foster family-centered care and collaboration.

CONCLUSION

NICU providers at safety-net hospitals believe that access to state-of-the-art genomic care is critical for optimizing infant outcomes; yet, substantial barriers exist that the VIGOR study may address.

Analysis of the causes of neonatal death and genetic variations in congenital anomalies: a multi-center study

Background

Neonatal deaths often result from preventable conditions that can be addressed with appropriate interventions. This study aims to analyze the distribution of the causes of neonatal death and explore genetic variations that lead to congenital anomalies in Northwest China.

Methods

This multi-center observational study was conducted across six medical centers in Shaanxi province, Northwest China. Clinical data were retrospectively collected from neonates admitted between 2016 and 2020. Kaplan-Meier analysis was utilized to estimate survival rates, while high-throughput sequencing platforms were employed to detect mutations causing congenital anomalies.

Results

Among 73,967 neonates requiring hospital care, 424 neonatal deaths were recorded, leading to a neonatal mortality rate of 0.57%. The primary causes of death included neonatal respiratory distress syndrome (23.8%), birth asphyxia (19.8%), neonatal septicemia (19.3%), and congenital anomalies (13.6%). The leading causes of neonatal deaths due to congenital anomalies were congenital heart defects (38.6%), bronchopulmonary dysplasia (14.0%), and inherited metabolic disorders (10.5%). Genetic analysis identified 83 pathogenic or likely pathogenic variants in 23 genes among the neonates with congenital anomalies, including four novel mutations (c.4198+1G>T, c.1075delG, c.610-1G>A, c.7769C>T) in the ABCC8, CDKL5, PLA2G6, and NIPBL genes.

Conclusion

Congenital anomalies represent a significant and preventable cause of neonatal deaths in Northwest China. Early detection of congenital anomalies through genetic testing and comprehensive prenatal care are crucial for reducing neonatal mortality rates and improving pregnancy outcomes.

Multidimensional and Longitudinal Impact of a Genetic Diagnosis for Critically Ill Infants

Background and Objectives

Many genetic conditions present in the neonatal intensive care unit (NICU), where a diagnostic evaluation is pursued. However, understanding of the impact of a genetic diagnosis on clinical outcomes and health-related quality of life for these infants remains incomplete. We therefore evaluated parent-reported outcomes complemented by clinical outcomes measures over one year for a cohort of infants in the NICU undergoing genetic evaluation.

Methods

Prospective cohort study evaluating outcomes after genetics consultation in a level IV NICU via parent-report and electronic medical records (EMR) review. Eligible infants were genetically undiagnosed at enrollment. Parent surveys were administered at baseline and three, six-, and 12-months following enrollment and assessed genetic testing utility as well as parent-reported infant health-related quality of life using the Infant Toddler Quality of Life Questionnaire.

Results

110 infant-parent pairs were enrolled. Infants had a median age at enrollment of 15 days (interquartile range 8-37.75). At baseline, 74% (81/110) of parents endorsed high importance of finding a genetic diagnosis, but perceived importance significantly decreased over time. Over the study period, 38 infants received a molecular diagnosis per parent report, though this was discordant with EMR review. Identification of a diagnosis did not significantly impact health-related quality of life across most domains, which was lower overall than population norms.

Conclusions

A genetic diagnosis is highly desired by parents in the NICU, though waning interest over time for undiagnosed families may reflect parental emotional adaptation and acceptance. Additional supports are needed to improve perceived quality of life.

NeoGx: Machine-Recommended Rapid Genome Sequencing for Neonates

Background

Genetic disease is common in the Level IV Neonatal Intensive Care Unit (NICU), but neonatology providers are not always able to identify the need for genetic evaluation. We trained a machine learning (ML) algorithm to predict the need for genetic testing within the first 18 months of life using health record phenotypes.

Methods

For a decade of NICU patients, we extracted Human Phenotype Ontology (HPO) terms from clinical text with Natural Language Processing tools. Considering multiple feature sets, classifier architectures, and hyperparameters, we selected a classifier and made predictions on a validation cohort of 2,241 Level IV NICU admits born 2020-2021.

Results

Our classifier had ROC AUC of 0.87 and PR AUC of 0.73 when making predictions during the first week in the Level IV NICU. We simulated testing policies under which subjects begin testing at the time of first ML prediction, estimating diagnostic odyssey length both with and without the additional benefit of pursuing rGS at this time. Just by using ML to accelerate initial genetic testing (without changing the tests ordered), the median time to first genetic test dropped from 10 days to 1 day, and the number of diagnostic odysseys resolved within 14 days of NICU admission increased by a factor of 1.8. By additionally requiring rGS at the time of positive ML prediction, the number of diagnostic odysseys resolved within 14 days was 3.8 times higher than the baseline.

Conclusions

ML predictions of genetic testing need, together with the application of the right rapid testing modality, can help providers accelerate genetics evaluation and bring about earlier and better outcomes for patients.

Implementation of rapid genomic sequencing in safety-net neonatal intensive care units: protocol for the VIrtual GenOme CenteR (VIGOR) proof-of-concept study

INTRODUCTION

Rapid genomic sequencing (rGS) in critically ill infants with suspected genetic disorders has high diagnostic and clinical utility. However, rGS has primarily been available at large referral centres with the resources and expertise to offer state-of-the-art genomic care. Critically ill infants from racial and ethnic minority and/or low-income populations disproportionately receive care in safety-net and/or community settings lacking access to state-of-the-art genomic care, contributing to unacceptable health equity gaps. VIrtual GenOme CenteR is a 'proof-of-concept' implementation science study of an innovative delivery model for genomic care in safety-net neonatal intensive care units (NICUs).

METHODS AND ANALYSIS

We developed a virtual genome centre at a referral centre to remotely support safety-net NICU sites predominantly serving racial and ethnic minority and/or low-income populations and have limited to no access to rGS. Neonatal providers at each site receive basic education about genomic medicine from the study team and identify eligible infants. The study team enrols eligible infants (goal n of 250) and their parents and follows families for 12 months. Enrolled infants receive rGS, the study team creates clinical interpretive reports to guide neonatal providers on interpreting results, and neonatal providers return results to families. Data is collected via (1) medical record abstraction, (2) surveys, interviews and focus groups with neonatal providers and (3) surveys and interviews with families. We aim to examine comprehensive implementation outcomes based on the Proctor Implementation Framework using a mixed methods approach.

ETHICS AND DISSEMINATION

This study is approved by the institutional review board of Boston Children's Hospital (IRB-P00040496) and participating sites. Participating families are required to provide electronic written informed consent and neonatal provider consent is implied through the completion of surveys. The results will be disseminated via peer-reviewed publications and data will be made accessible per National Institutes of Health (NIH) policies.

TRIAL REGISTRATION NUMBER

NCT05205356/clinicaltrials.gov.

Genomic medicine in neonatal care: progress and challenges

During the neonatal period, many genetic disorders present and contribute to neonatal morbidity and mortality. Genomic medicine-the use of genomic information in clinical care- has the potential to significantly reduce morbidity and mortality in the neonatal period and improve outcomes for this population. Diagnostic genomic testing for symptomatic newborns, especially rapid testing, has been shown to be feasible and have diagnostic and clinical utility, particularly in the short-term. Ongoing studies are assessing the feasibility and utility, including personal utility, of implementation in diverse populations. Genomic screening for asymptomatic newborns has also been studied, and the acceptability and feasibility of such an approach remains an active area of investigation. Emerging precision therapies, with examples even at the "n-of-1" level, highlight the promise of precision diagnostics to lead to early intervention and improve outcomes. To sustainably implement genomic medicine in neonatal care in an ethical, effective, and equitable manner, we need to ensure access to genetics and genomics knowledge, access to genomic tests, which is currently limited by payors, feasible processes for ordering these tests, and access to follow up in the clinical and research realms. Future studies will provide further insight into enablers and barriers to optimize implementation strategies.