Efficacy of Universal Genome Sequencing in Infant Extracorporeal Membrane Oxygenation

Efficacy of Universal Genome Sequencing in Infant Extracorporeal Membrane Oxygenation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Efficacy of Universal Genome Sequencing in Infant Extracorporeal Membrane Oxygenation Nicholas Carr, Makenzie Fulmer, Jennifer Rumpel, Abhishek Makkar, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8535209/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Objective To evaluate the feasibility and diagnostic yield of universal genome sequencing (GS) in infants receiving extracorporeal membrane oxygenation (ECMO). Study Design: Prospective multicenter study across eight Children’s Hospital Neonatal Consortium sites (October 2021–August 2023). Infants initiated on ECMO were enrolled for GS regardless of suspected genetic disease. Demographics, ECMO indications, and results from standard-care testing and study-based GS were analyzed. Results Twenty-five infants were enrolled. Primary ECMO indications included congenital diaphragmatic hernia (28%), meconium aspiration syndrome (24%), and primary respiratory failure (20%). GS identified pathogenic or likely pathogenic variants in 6/25 infants (24%), including three cytogenetic-confirmed diagnoses and three molecular diagnoses identified only by GS. Variants of uncertain significance were identified in 44% of infants, while 32% had negative results. Conclusion Universal GS during ECMO is feasible and yields a relatively high rate of clinically relevant diagnoses, supporting further assessment of the integration of genomic testing into ECMO care pathways. Health sciences/Health care/Diagnosis/Genetic testing Health sciences/Pathogenesis/Clinical genetics/Genetic testing genome sequencing ECMO neonate NICU genetic diagnosis precision medicine Introduction The application of genome sequencing (GS) in neonatal and pediatric intensive care settings has transformed the diagnostic landscape for critically ill infants. Several studies have shown that rapid GS outperforms conventional genetic testing in terms of diagnostic yield and turnaround time, leading to changes in management and possibly improved clinical outcomes. 1 , 2 , 3 , 4 These benefits are particularly relevant in neonatal and pediatric intensive care units (NICUs and PICUs) where timely etiologic diagnoses are essential for acute management decisions, prognostication, and family counseling. Infants requiring extracorporeal membrane oxygenation (ECMO) are among the sickest patients cared for in NICUs and PICUs, and they experience high morbidity and mortality. According to the Extracorporeal Life Support Organization (ELSO) registry, common neonatal indications for ECMO include congenital diaphragmatic hernia, meconium aspiration syndrome, and persistent pulmonary hypertension. 5 Since 2000, however, the proportion of ECMO cases categorized as “Other” has increased, often representing complex conditions with a potential genetic basis. 6 Early genetic diagnosis in this population may enable targeted therapies, reduce invasive procedures, streamline clinical decision-making, and provide clearer prognostic information to support family counseling. Given the demonstrated benefits of GS in NICU and PICU settings, there is growing interest in its application to infants receiving ECMO. A 2022 national survey of Level IV NICU centers in the United States found that 63% of respondents would consider implementing universal GS for ECMO patients if readily available. 7 Multiple case reports have identified unrecognized monogenic disorders in critically ill infants who had previously underwent ECMO. 8 , 9 , 10 , 11 , 12 , 13 Amin et al. retrospectively demonstrated a high diagnostic rate and clinical utility of GS for NICU patients requiring ECMO. 14 Our published data show that incorporating disease severity as a sequencing selection criterion leads to high diagnostic yields (close to 70%). 15 Taken together, these lines of evidence suggest the potential utility of GS in infant ECMO and indicate that testing all infants undergoing ECMO with GS, regardless of a suspicion for genetic disease, could uncover an underlying genetic disease in a relatively high percentage of infants. 16 , 17 In addition, genetic testing could uncover hematological defects relevant for ECMO care. Building on the strong interest noticed among ECMO providers, this multicenter study aimed to prospectively evaluate the feasibility and diagnostic efficacy of universal GS testing for infants requiring ECMO. Materials/Subjects and Methods: Study Design and Oversight This was a multicenter, prospective observational study designed to evaluate the feasibility and diagnostic yield of GS as a first-tier genetic test in infants requiring extracorporeal life support (ECLS) which encompases ECMO. The study was coordinated through the University of Utah, which served as the single institutional review board (IRB) of record and core data coordinating center. Participating sites were members of the Children’s Hospitals Neonatal Consortium (CHNC). All sites obtained local IRB reliance through the IRB Exchange (IREx) platform. Written informed consent was obtained from at least one biological parent before shipment of samples to the sequencing laboratory. Study Population Infants aged 0 to < 1 year undergoing clinically indicated ECMO for any diagnosis were eligible for enrollment. Inclusion criteria required (1) a successful blood draw at the time of ECMO cannulation and prior to initiation of the circuit, and (2) consent from at least one biological parent willing to provide a blood sample for study purposes. Exclusion criteria included inability to obtain parental consent within 7 days of the proband’s blood draw, failure to obtain a study blood sample at the time of cannulation, or cancellation of the ECMO procedure prior to initiation. Infants of all gestational ages, sexes, and ethnicities were eligible for inclusion. Consent Procedures Given the emergent nature of ECMO initiation, study blood samples could be drawn at the time of cannulation under a waiver of consent and held under refrigeration for up to six days. Parents were subsequently approached for study participation once the infant was stabilized. Consent discussions were conducted in person or remotely (via telephone or e-consent). Samples were destroyed if consent was not obtained within the seven-day window. Parental blood samples were collected once consent was obtained and shipped within 30 days of the infant’s sample collection. Sample Collection and Processing At the time of ECMO cannulation, approximately 1.0–1.25 mL of peripheral or central venous blood was collected into EDTA tubes by the clinical team. Samples were refrigerated within 24 hours of collection and shipped overnight to ARUP Laboratories (Salt Lake City, UT) to ensure receipt within seven days. Each consenting parent provided a 4 mL EDTA blood sample, processed under identical conditions. DNA was extracted from whole blood at ARUP, labeled only with the study identifier, and stored at − 80°C until analysis. Genome sequencing and analysis Genomic DNA was extracted from peripheral blood using the Chemagic Magnetic Separation Module I kit (PerkinElmer, MA, USA). GS libraries were prepared using the Illumina DNA Prep kit and underwent 2 × 150 bp paired-end sequencing using NovaSeq 6000 (Illumina, CA, USA). GS was performed on twenty-five cases (14 trios, 11 duos). We obtained raw FASTQ files and performed research analysis in parallel at ARUP Laboratories using Emedgene software with its built-in DRAGEN pipeline (Illumina Inc.) and at the Utah Center for Genetic Discovery (UCGD). At UCGD, reads were aligned to the GRCh38 human genome reference with BWA, and single-nucleotide variant (SNV) and short insertion/deletion (indel) calling was performed using either the Sentieon implementation of GATK algorithms or DeepVariant. SNV/indels were filtered using Slivar 18 for nonsynonymous, splicing, and 5’ UTR start-gain variants with < 2% population allele frequency and for co-segregation with the DBAS phenotype among sequenced individuals. Intronic variants with a SpliceAI score ≥ 0.1 were included. Structural variants (SVs) were called using Smoove 19 , RUFUS 20 , and Manta. 21 Smoove calls were annotated with population SV allele frequencies using SVAFotate 22 and filtered for rare (< 1%) co-segregating variants using Slivar. Results Twenty-five infants undergoing ECMO were enrolled from ICUs at eight CHNC member children’s hospitals between October 1, 2021, and August 16, 2023. The only inclusion criterion was initiation of ECMO, regardless of degree of suspicion for genetic disease, along with parental consent for blood sampling for GS analysis from both the infant and at least one parent. Approximately 19% of approached families declined participation. Most enrolled patients were neonates (n = 23, 92%) (Table 1 ). The majority were admitted to the NICU (n = 22, 88%), two (8%) to the cardiac intensive care unit (CICU) and one (4%) to the PICU. Thirteen infants (52%) were female, 11 (44%) were male, and one (4%) had gender not reported. Most infants were White (n = 18, 72%), followed by Black (n = 2, 8%), Asian (n = 1, 4%), Native American (n = 1, 4%), and Other (n = 1, 4%), with race not reported for two patients (8%). Ethnicity was reported as non-Hispanic/Latino in 17 (68%), Hispanic/Latino in five (20%), and unknown in three (12%). Six infants (24%) died during hospitalization (Table 1 ). Table 1 Summary of Patient Demographics n = 25 n % Patient age at admission Neonatal, 0-28d 23 92% Infant, 29d-365d 2 8% Sex n % Female 13 52% Male 11 44% Unknown 1 4% Race n % White 18 72% Black 2 8% Asian 1 4% Native American 1 4% Other or Unknown 3 12% Ethnicity n % Non-Hispanic/Latino 17 68% Hispanic/Latino 5 20% Unknown 3 12% Location at sampling Neonatal ICU (NICU) 22 88% Cardiac ICU (CICU) 2 8% Pediatric ICU (PICU) 1 4% Mortality n % Died during hospitalization 6 24% The primary ECMO indications included congenital diaphragmatic hernia (n = 7, 28%), meconium aspiration syndrome (n = 6, 24%), primary respiratory failure (n = 5, 20%), congenital heart disease (n = 2, 8%), hypoxic ischemic encephalopathy with respiratory failure (n = 2, 8%), metabolic disorders (n = 1, 4%), idiopathic persistent pulmonary hypertension of the newborn (n = 1, 4%), and other diagnoses (n = 1, 4%) (Table 2 ). Venoarterial (VA) support was most common (n = 17, 68%), followed by venovenous (VV) support (n = 6, 24%), central VA cannulation (n = 1, 4%), and VV with VA conversion (n = 1, 4%) (Table 2 ). GS was performed on all 25 infants at the time of ECMO initiation, at a mean age of 12.7 days (range, 0–140 days) and with a mean interval from admission to sample collection of 2.25 days (range, 0–32 days). Where possible, samples were obtained from both parents, with 14 trios and 11 duos (Supplementary Table 1). Usual-care genetic testing varied by site, and formal genetics consultation occurred in six patients (24%) (Table 2 ). The most common tests ordered under clinical guidance during hospitalization were newborn screening (n = 10, 40%), cytogenomic microarray (n = 9, 36%), and G-banded chromosome analysis (n = 5, 20%), although additional prenatal testing (n = 2, 8%), exome sequencing (ES) (n = 3, 12%), GS (n = 1, 4%), metabolic evaluation (n = 1, 4%), and other tests (n = 2, 8%) were also performed (Table 2 ). Table 2 Summary of ECLS Support and Genetic Testing n = 25 Patient ECLS indication, primary n % Congenital diaphragmatic hernia 7 28% Congenital heart disease 2 8% Hypoxic ischemic encephalopathy w/ respiratory failure 2 8% Meconium aspiration syndrome 6 24% Metabolic 1 4% PPHN, idiopathic 1 4% Primary respiratory failure 5 20% Other 1 4% ECLS support n % Veno-arterial (VA) 17 68% Veno-arterial, central 1 4% Veno-venous (VV) 6 24% VV with VA conversion 1 4% Formal genetics consultation n % Yes 6 24% Timing of study genome sequencing Mean (days) Range (days) Day of life at testing 12.7 0-140 Interval from date of admission to sample collection 2.25 0–32 Genetic testing ordered under clinical guidance n % Prenatal testing (NIPT/amniocentesis) 2 8% Newborn screening only 10 40% Microarray 9 36% Karyotype 5 20% Whole exome sequencing (WES) 3 12% Whole genome sequencing (WGS) 1 4% Metabolic eval 1 4% Other 2 8% Abbreviations: NIPT (maternal non-invasive pregnancy testing, cell-free DNA) The GS diagnostic yield was 24% (6/25) (Table 3 ). Three patients had concordant findings with usual-care cytogenetics: two cases of trisomy 21 and one case of 8p23.1 microdeletion syndrome (3.8 Mb including GATA4 ), presenting with multisystem involvement including respiratory failure, pulmonary hypertension, hypotension, cardiac anomalies, adrenal insufficiency, and other systemic features (Supplementary Table 1, 2). The remaining three cases were novel molecular diagnoses identified exclusively by GS: a maternally inherited autosomal dominant EPHB4 variant (capillary malformation–arteriovenous malformation 2, MIM: 618196), compound heterozygous ZNFX1 variants (immunodeficiency 91 and hyperinflammation, MIM: 619644), and an X-linked G6PD variant (anemia, congenital, nonspherocytic hemolytic, MIM: 300908), all presenting with severe, multisystem involvement including respiratory failure, pulmonary hypertension, hypotension, adrenal insufficiency, ischemic events, sepsis, and acute renal failure (Supplementary Table 1). Among the three patients with novel molecular diagnoses identified by GS, two of them also had secondary or incidental findings, including an additional pathogenic variant with clinical significance unrelated to ECMO and a pathogenic ACMG secondary finding (Supplementary Table 1). Table 3 Summary of Genomic Sequencing Results n = 25 n % Pathogenic / likely pathogenic 6 24% Variants of uncertain significance 11 44% No candidate variant identified 8 32% Eleven patients (44%) had variants of uncertain significance (VUS) potentially related to their phenotypes (Table 3 ). In some cases, pathogenic variants were identified without a second allele or with uncertain relevance to the clinical presentation due to the research structure of this study (Supplementary Table 1, 2). Eight patients (32%) had negative results (Table 3 ). Discussion Over the last decade, the utilization of GS in critically ill infants has steadily increased. Infants undergoing ECMO are among those with the most severe illness and the highest morbidity and mortality. To explore the application of GS in infant ECMO, we conducted a pilot multicenter study evaluating the diagnostic efficacy of universal GS at the time of ECMO cannulation. Among the 25 infants enrolled in this study, the diagnostic yield was 24%, with an additional 44% displaying VUS in clinically relevant genes or other findings of potential clinical relevance. Among infants with a diagnostic result, two also had secondary findings of potential clinical significance. Although the non-rapid, research-based design of this study limited our ability to assess real-time clinical utility, these findings suggest that universal GS has meaningful potential value in infant requiring ECMO. We propose that further studies are needed to systematically assess the clinical utility of universal GS in infant ECMO as well as related, potential healthcare cost benefits. ECMO is a life-saving intervention for infants with severe, potentially reversible cardiorespiratory failure. Despite advances in technology and patient selection, mortality remains high, particularly for infants with underlying genetic or structural anomalies. 5 , 23 , 24 Data from the ELSO registry demonstrate that congenital diaphragmatic hernia, meconium aspiration syndrome, and persistent pulmonary hypertension of the newborn remain among the most common neonatal indications for ECMO. However, an increasing proportion of cases fall into the 'Other' category—often reflecting rare or complex conditions with a possible genetic etiology. 5 , 6 , 24 Our findings align with these data and confirm the severity of disease in infants undergoing ECMO given the 24% mortality rate among participants in this study. In this context, early genomic diagnosis serves both to guide escalation of care and to identify disorders associated with extremely poor prognosis or outcomes not compatible with survival. In infants undergoing ECMO, GS has the potential not only to uncover the underlying cause of the disease but also to identify variants that may contribute to dysregulation of the coagulation and clotting cascades, modulation of which is critical in ECMO management to avoid bleeding or thrombotic complications. The identification of monogenic disorders may influence not only immediate management but also long-term care trajectories. For example, detection of pathogenic variants associated with poor prognosis may guide decisions regarding the discontinuation of ECMO. At the same time, identification of treatable metabolic or immunologic conditions could prompt targeted interventions. 8 , 14 , 17 , 25 Moreover, genetic diagnoses can inform decisions regarding candidacy for advanced therapies such as transplantation. 16 , 25 As pharmacogenomic knowledge in infants increases, future studies involving GS in ECMO could also evaluate tailoring drug selection and/or dosing based on pharmacogenomics profiling. The present study builds upon emerging evidence that integrating genomic testing into critical care workflows is feasible and can yield clinically actionable information within the narrow therapeutic windows characteristic of ECMO care. 8 , 9 Our findings demonstrate a 24% diagnostic yield, comparable to other NICU-based GS studies, with an additional subset of patients harboring VUSs that may gain relevance as genomic knowledge evolves. 2 , 14 , 26 In most studies conducted so far in NICUs/PICUs, high diagnostic yields involved an approach that included a pre-test clinical evaluation for the possible presence of genetic disease. The novel approach in this study relates to the high diagnostic yield achieved by selecting infants based solely on their need for ECMO, regardless of a suspicion for genetic disease. To our knowledge, this is one of the first studies to use GS in patients managed with ECMO in whom no pre-test clinical evaluation for genetic disease was performed. Beyond ECMO, our findings suggest that disease severity is important in assessing which infants may benefit from GS testing. As reflected in Table 2 , only a small proportion of infants in this cohort underwent clinically ordered exome (12%) or genome sequencing (4%) during hospitalization, despite high illness severity and diagnostic uncertainty. This highlights an opportunity to expand integration of WES/WGS in contemporary neonatal and pediatric critical care, particularly for ECMO patients who may derive substantial benefit from timely etiologic diagnosis. Testing all infants in a specific NICU/PICU/CICU cohort is particularly attractive for the inherent simplicity of this diagnostic protocol. Other examples could include infants and children scheduled for open heart surgery, transplantation, or other high acuity procedures. A key barrier to routine clinical use of WGS remains variability in reimbursement and payer approval processes. Access to testing frequently differs across private insurers and state Medicaid programs, resulting in inconsistent availability for clinically similar patients and potential delays in time-sensitive situations such as ECMO. These structural factors should be considered alongside future evaluations of clinical utility and cost-effectiveness. Emerging statewide precision-medicine initiatives have demonstrated reductions in unnecessary diagnostic testing, hospital length of stay, and overall healthcare costs associated with earlier deployment of rapid sequencing in critically ill infants. These experiences provide important context for future economic evaluations of universal sequencing strategies in ECMO populations. A limitation of the study was its research design, which did not allow an analysis of the effects of testing on clinical management and outcomes. Several authors have emphasized the importance of conducting a systematic assessment of clinical utility when studying the use of GS in the NICU/PICU environment. 27 Therefore, before translating the results of this pilot study into clinical practice, it will be important to perform studies to systematically assess the clinical utility and cost-effectiveness of universal GS in infant ECMO. The anticipated challenges of these studies are primarily the need for streamlined consent processes and robust multidisciplinary support for interpretation and counseling, and most notably the need for ultra-rapid turnaround times for GS results to affect clinical management. Cost-effectiveness analyses and prospective multicenter studies will also be important to define the role of universal GS in infant ECMO. 10 , 28 Despite its limitations, this study demonstrates that universal GS in infants receiving ECMO is feasible and yields a relatively high rate of clinically relevant diagnoses. Integration of universal rapid GS into ECMO care pathways has the potential to inform precise management, identify both treatable and lethal conditions earlier in the course of care, and support ethically aligned redirection of care when appropriate. Further prospective studies are needed to define the optimal role of GS in ECMO and to address barriers to equitable clinical implementation. Table 1 . Summary of Patient Demographics Table 2 . Summary of ECLS Support and Genetic Testing Table 3 . Summary of Genomic Sequencing Results Supplementary Table 1. Summary of individual genomic sequencing results and secondary findings Supplementary Table 2. Individual patient clinical characteristics including clinical history, family history, and medication exposures Declarations Funding Statement: Institutional Support from the University of Utah Division of Neonatology, Center for Genomic Medicine, and ARUP Laboratories along with a grant from the Ben B. and Iris M. Margolis Foundation. This work utilized computational resources and support from the Center for High Performance Computing at the University of Utah, partially funded by NIH Shared Instrumentation Grants S10OD034321 and S10OD021644. Ethical Approval and Informed Consent: The study was coordinated through the University of Utah, which served as the single institutional review board (IRB) of record and core data coordinating center. Participating sites were members of the Children’s Hospitals Neonatal Consortium (CHNC). All sites obtained local IRB reliance through the IRB Exchange (IREx) platform. Written informed consent was obtained from at least one biological parent before shipment of samples to the sequencing laboratory. This study was conducted in accordance with the ethical standards of the institutional review boards at all participating sites and with the principles outlined in the Declaration of Helsinki. Data Availability Statement: Deidentified sequencing data is available from the corresponding author upon reasonable request. Acknowledgments: We thank the participating infants and families, as well as the clinical teams and research staff at all eight Children’s Hospital Neonatal Consortium (CHNC) sites for their commitment to this study. We also acknowledge the contributions of our genomic laboratory partners and the CHNC infrastructure team for their support in data coordination and study implementation. Sequence alignment, variant calling, and variant interpretation analyses were performed in part by the Utah Center for Genetic Discovery Core facility, part of the Health Sciences Center Cores at the University of Utah. Contributors’ statements: Drs. Carr and Brunelli participated in study design, data analysis, and manuscript writing. Drs. Fulmer, Mao, and Boyden participated in data analysis, writing, and review. All other authors participated in manuscript writing and review. All authors agree with the final draft of this manuscript. Declaration of Conflicting Interest: The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. References Saunders CJ, Miller NA, Soden SE, Dinwiddie DL, Noll A, Alnadi NA, et al. Rapid whole-genome sequencing for genetic disease diagnosis in neonatal intensive care units. Sci Transl Med 2012, 4(154): 154ra135. Petrikin JE, Willig LK, Smith LD, Kingsmore SF. Rapid whole genome sequencing and precision neonatology. Seminars in perinatology 2015, 39(8): 623–631. Meng L, Pammi M, Saronwala A, Magoulas P, Ghazi AR, Vetrini F, et al. Use of Exome Sequencing for Infants in Intensive Care Units: Ascertainment of Severe Single-Gene Disorders and Effect on Medical Management. JAMA Pediatr 2017, 171(12): e173438. Clark MM, Stark Z, Farnaes L, Tan TY, White SM, Dimmock D, et al. 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Supplementary Files SupplementaryTable1.docx Supplementary Table 1 SupplementaryTable2.docx Supplementary Table 2 Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: revise 30 Jan, 2026 Review # 1 received at journal 28 Jan, 2026 Review # 2 received at journal 26 Jan, 2026 Reviewer # 2 agreed at journal 15 Jan, 2026 Reviewer # 1 agreed at journal 13 Jan, 2026 Reviewers invited by journal 13 Jan, 2026 Submission checks completed at journal 12 Jan, 2026 First submitted to journal 11 Jan, 2026 Unknown event 09 Jan, 2026 Editor assigned by journal 06 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8535209","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":574233600,"identity":"82e614aa-6cd0-4239-b97b-fded42945239","order_by":0,"name":"Nicholas Carr","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABD0lEQVRIiWNgGAWjYDACZgY2BoYCGK/iAIRmbAASB/BpMYDxzhyAaMCrhQFZC2MbEVrM2ZmfPfhgYGfPwH742efKeXfs+Rt4zB/83MEgx3cjAasWy2Y2c8MZBsmJDTxpxjPPbnuWOOMAj2Fj7xkGY0kcWgwO87BJ8xgwJzBIMBgzNm47nGDAwGPYwNvGkLgBv5Z6ewYJ9s+MjXMO24O0NP5tY6gnoOUwY4MED9CWhsOMG4BamoG2JBjg1MJmJjnD4HhiG09OMWPDscOJMw6zFc6WbZMwnHnmAXYt5w8/k/hQUW3Pz358M2NDzWF7/vbmDR/fttnI8x3HbgscsMFZzGBSAr/yUTAKRsEoGAV4AQBSn1kF8v7QWAAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-2488-2568","institution":"University of Utah","correspondingAuthor":true,"prefix":"","firstName":"Nicholas","middleName":"","lastName":"Carr","suffix":""},{"id":574233601,"identity":"24367b63-8903-408f-927d-1f2dbbd519e0","order_by":1,"name":"Makenzie Fulmer","email":"","orcid":"","institution":"ARUP Laboratories","correspondingAuthor":false,"prefix":"","firstName":"Makenzie","middleName":"","lastName":"Fulmer","suffix":""},{"id":574233602,"identity":"82fca345-cb0a-4f84-bf78-3e1ba5242114","order_by":2,"name":"Jennifer Rumpel","email":"","orcid":"https://orcid.org/0000-0002-5883-218X","institution":"Arkansas Children's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jennifer","middleName":"","lastName":"Rumpel","suffix":""},{"id":574233603,"identity":"381e9c93-049b-4933-9eb9-c9d5a78f8b66","order_by":3,"name":"Abhishek Makkar","email":"","orcid":"https://orcid.org/0000-0003-4654-0566","institution":"University of Texas Southwestern Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Abhishek","middleName":"","lastName":"Makkar","suffix":""},{"id":574233604,"identity":"28b359ff-cb51-4fad-8516-4f51994924ff","order_by":4,"name":"Burhan Mahmood","email":"","orcid":"https://orcid.org/0000-0002-6585-992X","institution":"UPMC Children's Hospital of Pittsburgh","correspondingAuthor":false,"prefix":"","firstName":"Burhan","middleName":"","lastName":"Mahmood","suffix":""},{"id":574233605,"identity":"965899eb-5939-41b8-a8e5-adc3a3e91968","order_by":5,"name":"Sarah Keene","email":"","orcid":"","institution":"Emory University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"","lastName":"Keene","suffix":""},{"id":574233606,"identity":"a0242200-f357-402f-82f9-00e2fa2d97fb","order_by":6,"name":"Natalie Rintoul","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Natalie","middleName":"","lastName":"Rintoul","suffix":""},{"id":574233607,"identity":"7322d98b-b1ce-42b7-b6c9-5cb295b83f3a","order_by":7,"name":"K. Wild","email":"","orcid":"https://orcid.org/0000-0002-0016-078X","institution":"Children's Hospital of Philadelphia","correspondingAuthor":false,"prefix":"","firstName":"K.","middleName":"","lastName":"Wild","suffix":""},{"id":574233608,"identity":"5bc90a92-a167-4859-a027-3cea836e007b","order_by":8,"name":"Amir Ashrafi","email":"","orcid":"","institution":"Children's Hospital Orange County","correspondingAuthor":false,"prefix":"","firstName":"Amir","middleName":"","lastName":"Ashrafi","suffix":""},{"id":574233609,"identity":"6c662d08-9b44-49be-92c8-5a0bd724a72a","order_by":9,"name":"Semsa Gogcu","email":"","orcid":"https://orcid.org/0000-0002-0429-9404","institution":"Wake Forest","correspondingAuthor":false,"prefix":"","firstName":"Semsa","middleName":"","lastName":"Gogcu","suffix":""},{"id":574233610,"identity":"ef5e13a0-dfd0-4737-95b2-2d98f8a9d112","order_by":10,"name":"Carrie Rau","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Carrie","middleName":"","lastName":"Rau","suffix":""},{"id":574233611,"identity":"283993c1-0d4f-4426-9743-de729615fffa","order_by":11,"name":"David Pattison","email":"","orcid":"","institution":"ARUP Laboratories","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"","lastName":"Pattison","suffix":""},{"id":574233612,"identity":"87ac4985-59e9-41c1-b594-e997d25fcf23","order_by":12,"name":"Hunter Best","email":"","orcid":"","institution":"ARUP Laboratories","correspondingAuthor":false,"prefix":"","firstName":"Hunter","middleName":"","lastName":"Best","suffix":""},{"id":574233613,"identity":"2c3922d0-6637-450b-a4fb-b6b808a04d1c","order_by":13,"name":"Steven Boyden","email":"","orcid":"","institution":"Utah Center for Genetic Discovery","correspondingAuthor":false,"prefix":"","firstName":"Steven","middleName":"","lastName":"Boyden","suffix":""},{"id":574233614,"identity":"4010244b-1f95-4d27-8047-5feab79463dd","order_by":14,"name":"Rong Mao","email":"","orcid":"","institution":"ARUP Laboratories","correspondingAuthor":false,"prefix":"","firstName":"Rong","middleName":"","lastName":"Mao","suffix":""},{"id":574233615,"identity":"cab2e09f-3095-4248-9023-23ef578840dd","order_by":15,"name":"Luca Brunelli","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Luca","middleName":"","lastName":"Brunelli","suffix":""}],"badges":[],"createdAt":"2026-01-06 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Table 1","description":"","filename":"SupplementaryTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8535209/v1/6994ce4f572a9f497f4910c8.docx"},{"id":100623740,"identity":"b8fb1a89-77c7-4b6e-bcc5-6475003dd73a","added_by":"auto","created_at":"2026-01-19 18:51:24","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":33047,"visible":true,"origin":"","legend":"Supplementary Table 2","description":"","filename":"SupplementaryTable2.docx","url":"https://assets-eu.researchsquare.com/files/rs-8535209/v1/6397c1aa8751eecfe11f5e46.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.","formattedTitle":"Efficacy of Universal Genome Sequencing in Infant Extracorporeal Membrane Oxygenation","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe application of genome sequencing (GS) in neonatal and pediatric intensive care settings has transformed the diagnostic landscape for critically ill infants. Several studies have shown that rapid GS outperforms conventional genetic testing in terms of diagnostic yield and turnaround time, leading to changes in management and possibly improved clinical outcomes.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e These benefits are particularly relevant in neonatal and pediatric intensive care units (NICUs and PICUs) where timely etiologic diagnoses are essential for acute management decisions, prognostication, and family counseling.\u003c/p\u003e \u003cp\u003eInfants requiring extracorporeal membrane oxygenation (ECMO) are among the sickest patients cared for in NICUs and PICUs, and they experience high morbidity and mortality. According to the Extracorporeal Life Support Organization (ELSO) registry, common neonatal indications for ECMO include congenital diaphragmatic hernia, meconium aspiration syndrome, and persistent pulmonary hypertension.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Since 2000, however, the proportion of ECMO cases categorized as \u0026ldquo;Other\u0026rdquo; has increased, often representing complex conditions with a potential genetic basis.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e Early genetic diagnosis in this population may enable targeted therapies, reduce invasive procedures, streamline clinical decision-making, and provide clearer prognostic information to support family counseling.\u003c/p\u003e \u003cp\u003eGiven the demonstrated benefits of GS in NICU and PICU settings, there is growing interest in its application to infants receiving ECMO. A 2022 national survey of Level IV NICU centers in the United States found that 63% of respondents would consider implementing universal GS for ECMO patients if readily available.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Multiple case reports have identified unrecognized monogenic disorders in critically ill infants who had previously underwent ECMO.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e Amin et al. retrospectively demonstrated a high diagnostic rate and clinical utility of GS for NICU patients requiring ECMO.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e Our published data show that incorporating disease severity as a sequencing selection criterion leads to high diagnostic yields (close to 70%).\u003csup\u003e15\u003c/sup\u003e Taken together, these lines of evidence suggest the potential utility of GS in infant ECMO and indicate that testing all infants undergoing ECMO with GS, regardless of a suspicion for genetic disease, could uncover an underlying genetic disease in a relatively high percentage of infants.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e In addition, genetic testing could uncover hematological defects relevant for ECMO care. Building on the strong interest noticed among ECMO providers, this multicenter study aimed to prospectively evaluate the feasibility and diagnostic efficacy of universal GS testing for infants requiring ECMO.\u003c/p\u003e"},{"header":"Materials/Subjects and Methods:","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Oversight\u003c/h2\u003e \u003cp\u003eThis was a multicenter, prospective observational study designed to evaluate the feasibility and diagnostic yield of GS as a first-tier genetic test in infants requiring extracorporeal life support (ECLS) which encompases ECMO. The study was coordinated through the University of Utah, which served as the single institutional review board (IRB) of record and core data coordinating center. Participating sites were members of the Children\u0026rsquo;s Hospitals Neonatal Consortium (CHNC). All sites obtained local IRB reliance through the IRB Exchange (IREx) platform. Written informed consent was obtained from at least one biological parent before shipment of samples to the sequencing laboratory.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Population\u003c/h3\u003e\n\u003cp\u003eInfants aged 0 to \u0026lt;\u0026thinsp;1 year undergoing clinically indicated ECMO for any diagnosis were eligible for enrollment. Inclusion criteria required (1) a successful blood draw at the time of ECMO cannulation and prior to initiation of the circuit, and (2) consent from at least one biological parent willing to provide a blood sample for study purposes. Exclusion criteria included inability to obtain parental consent within 7 days of the proband\u0026rsquo;s blood draw, failure to obtain a study blood sample at the time of cannulation, or cancellation of the ECMO procedure prior to initiation. Infants of all gestational ages, sexes, and ethnicities were eligible for inclusion.\u003c/p\u003e\n\u003ch3\u003eConsent Procedures\u003c/h3\u003e\n\u003cp\u003eGiven the emergent nature of ECMO initiation, study blood samples could be drawn at the time of cannulation under a waiver of consent and held under refrigeration for up to six days. Parents were subsequently approached for study participation once the infant was stabilized. Consent discussions were conducted in person or remotely (via telephone or e-consent). Samples were destroyed if consent was not obtained within the seven-day window. Parental blood samples were collected once consent was obtained and shipped within 30 days of the infant\u0026rsquo;s sample collection.\u003c/p\u003e\n\u003ch3\u003eSample Collection and Processing\u003c/h3\u003e\n\u003cp\u003eAt the time of ECMO cannulation, approximately 1.0\u0026ndash;1.25 mL of peripheral or central venous blood was collected into EDTA tubes by the clinical team. Samples were refrigerated within 24 hours of collection and shipped overnight to ARUP Laboratories (Salt Lake City, UT) to ensure receipt within seven days. Each consenting parent provided a 4 mL EDTA blood sample, processed under identical conditions. DNA was extracted from whole blood at ARUP, labeled only with the study identifier, and stored at \u0026minus;\u0026thinsp;80\u0026deg;C until analysis.\u003c/p\u003e\n\u003ch3\u003eGenome sequencing and analysis\u003c/h3\u003e\n\u003cp\u003eGenomic DNA was extracted from peripheral blood using the Chemagic Magnetic Separation Module I kit (PerkinElmer, MA, USA). GS libraries were prepared using the Illumina DNA Prep kit and underwent 2 \u0026times; 150 bp paired-end sequencing using NovaSeq 6000 (Illumina, CA, USA). GS was performed on twenty-five cases (14 trios, 11 duos). We obtained raw FASTQ files and performed research analysis in parallel at ARUP Laboratories using Emedgene software with its built-in DRAGEN pipeline (Illumina Inc.) and at the Utah Center for Genetic Discovery (UCGD). At UCGD, reads were aligned to the GRCh38 human genome reference with BWA, and single-nucleotide variant (SNV) and short insertion/deletion (indel) calling was performed using either the Sentieon implementation of GATK algorithms or DeepVariant. SNV/indels were filtered using Slivar\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e for nonsynonymous, splicing, and 5\u0026rsquo; UTR start-gain variants with \u0026lt;\u0026thinsp;2% population allele frequency and for co-segregation with the DBAS phenotype among sequenced individuals. Intronic variants with a SpliceAI score\u0026thinsp;\u0026ge;\u0026thinsp;0.1 were included. Structural variants (SVs) were called using Smoove\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e, RUFUS\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, and Manta.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e Smoove calls were annotated with population SV allele frequencies using SVAFotate\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e and filtered for rare (\u0026lt;\u0026thinsp;1%) co-segregating variants using Slivar.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eTwenty-five infants undergoing ECMO were enrolled from ICUs at eight CHNC member children\u0026rsquo;s hospitals between October 1, 2021, and August 16, 2023. The only inclusion criterion was initiation of ECMO, regardless of degree of suspicion for genetic disease, along with parental consent for blood sampling for GS analysis from both the infant and at least one parent. Approximately 19% of approached families declined participation. Most enrolled patients were neonates (n\u0026thinsp;=\u0026thinsp;23, 92%) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The majority were admitted to the NICU (n\u0026thinsp;=\u0026thinsp;22, 88%), two (8%) to the cardiac intensive care unit (CICU) and one (4%) to the PICU. Thirteen infants (52%) were female, 11 (44%) were male, and one (4%) had gender not reported. Most infants were White (n\u0026thinsp;=\u0026thinsp;18, 72%), followed by Black (n\u0026thinsp;=\u0026thinsp;2, 8%), Asian (n\u0026thinsp;=\u0026thinsp;1, 4%), Native American (n\u0026thinsp;=\u0026thinsp;1, 4%), and Other (n\u0026thinsp;=\u0026thinsp;1, 4%), with race not reported for two patients (8%). Ethnicity was reported as non-Hispanic/Latino in 17 (68%), Hispanic/Latino in five (20%), and unknown in three (12%). Six infants (24%) died during hospitalization (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of Patient Demographics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;25\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePatient age at admission\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeonatal, 0-28d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfant, 29d-365d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNative American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther or Unknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEthnicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic/Latino\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic/Latino\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLocation at sampling\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeonatal ICU (NICU)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiac ICU (CICU)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePediatric ICU (PICU)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMortality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDied during hospitalization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe primary ECMO indications included congenital diaphragmatic hernia (n\u0026thinsp;=\u0026thinsp;7, 28%), meconium aspiration syndrome (n\u0026thinsp;=\u0026thinsp;6, 24%), primary respiratory failure (n\u0026thinsp;=\u0026thinsp;5, 20%), congenital heart disease (n\u0026thinsp;=\u0026thinsp;2, 8%), hypoxic ischemic encephalopathy with respiratory failure (n\u0026thinsp;=\u0026thinsp;2, 8%), metabolic disorders (n\u0026thinsp;=\u0026thinsp;1, 4%), idiopathic persistent pulmonary hypertension of the newborn (n\u0026thinsp;=\u0026thinsp;1, 4%), and other diagnoses (n\u0026thinsp;=\u0026thinsp;1, 4%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Venoarterial (VA) support was most common (n\u0026thinsp;=\u0026thinsp;17, 68%), followed by venovenous (VV) support (n\u0026thinsp;=\u0026thinsp;6, 24%), central VA cannulation (n\u0026thinsp;=\u0026thinsp;1, 4%), and VV with VA conversion (n\u0026thinsp;=\u0026thinsp;1, 4%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). GS was performed on all 25 infants at the time of ECMO initiation, at a mean age of 12.7 days (range, 0\u0026ndash;140 days) and with a mean interval from admission to sample collection of 2.25 days (range, 0\u0026ndash;32 days). Where possible, samples were obtained from both parents, with 14 trios and 11 duos (Supplementary Table\u0026nbsp;1). Usual-care genetic testing varied by site, and formal genetics consultation occurred in six patients (24%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The most common tests ordered under clinical guidance during hospitalization were newborn screening (n\u0026thinsp;=\u0026thinsp;10, 40%), cytogenomic microarray (n\u0026thinsp;=\u0026thinsp;9, 36%), and G-banded chromosome analysis (n\u0026thinsp;=\u0026thinsp;5, 20%), although additional prenatal testing (n\u0026thinsp;=\u0026thinsp;2, 8%), exome sequencing (ES) (n\u0026thinsp;=\u0026thinsp;3, 12%), GS (n\u0026thinsp;=\u0026thinsp;1, 4%), metabolic evaluation (n\u0026thinsp;=\u0026thinsp;1, 4%), and other tests (n\u0026thinsp;=\u0026thinsp;2, 8%) were also performed (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of ECLS Support and Genetic Testing\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;25\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePatient ECLS indication, primary\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCongenital diaphragmatic hernia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCongenital heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypoxic ischemic encephalopathy w/ respiratory failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeconium aspiration syndrome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetabolic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePPHN, idiopathic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary respiratory failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eECLS support\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVeno-arterial (VA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVeno-arterial, central\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVeno-venous (VV)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVV with VA conversion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFormal genetics consultation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTiming of study genome sequencing\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRange (days)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDay of life at testing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0-140\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterval from date of admission to sample collection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u0026ndash;32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGenetic testing ordered under clinical guidance\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrenatal testing (NIPT/amniocentesis)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNewborn screening only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicroarray\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKaryotype\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhole exome sequencing (WES)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhole genome sequencing (WGS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetabolic eval\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eAbbreviations: NIPT (maternal non-invasive pregnancy testing, cell-free DNA)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe GS diagnostic yield was 24% (6/25) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Three patients had concordant findings with usual-care cytogenetics: two cases of trisomy 21 and one case of 8p23.1 microdeletion syndrome (3.8 Mb including \u003cem\u003eGATA4\u003c/em\u003e), presenting with multisystem involvement including respiratory failure, pulmonary hypertension, hypotension, cardiac anomalies, adrenal insufficiency, and other systemic features (Supplementary Table\u0026nbsp;1, 2). The remaining three cases were novel molecular diagnoses identified exclusively by GS: a maternally inherited autosomal dominant \u003cem\u003eEPHB4\u003c/em\u003e variant (capillary malformation\u0026ndash;arteriovenous malformation 2, MIM: 618196), compound heterozygous \u003cem\u003eZNFX1\u003c/em\u003e variants (immunodeficiency 91 and hyperinflammation, MIM: 619644), and an X-linked \u003cem\u003eG6PD\u003c/em\u003e variant (anemia, congenital, nonspherocytic hemolytic, MIM: 300908), all presenting with severe, multisystem involvement including respiratory failure, pulmonary hypertension, hypotension, adrenal insufficiency, ischemic events, sepsis, and acute renal failure (Supplementary Table\u0026nbsp;1). Among the three patients with novel molecular diagnoses identified by GS, two of them also had secondary or incidental findings, including an additional pathogenic variant with clinical significance unrelated to ECMO and a pathogenic ACMG secondary finding (Supplementary Table\u0026nbsp;1).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of Genomic Sequencing Results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;25\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathogenic / likely pathogenic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariants of uncertain significance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo candidate variant identified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eEleven patients (44%) had variants of uncertain significance (VUS) potentially related to their phenotypes (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In some cases, pathogenic variants were identified without a second allele or with uncertain relevance to the clinical presentation due to the research structure of this study (Supplementary Table\u0026nbsp;1, 2). Eight patients (32%) had negative results (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOver the last decade, the utilization of GS in critically ill infants has steadily increased. Infants undergoing ECMO are among those with the most severe illness and the highest morbidity and mortality. To explore the application of GS in infant ECMO, we conducted a pilot multicenter study evaluating the diagnostic efficacy of universal GS at the time of ECMO cannulation. Among the 25 infants enrolled in this study, the diagnostic yield was 24%, with an additional 44% displaying VUS in clinically relevant genes or other findings of potential clinical relevance. Among infants with a diagnostic result, two also had secondary findings of potential clinical significance. Although the non-rapid, research-based design of this study limited our ability to assess real-time clinical utility, these findings suggest that universal GS has meaningful potential value in infant requiring ECMO. We propose that further studies are needed to systematically assess the clinical utility of universal GS in infant ECMO as well as related, potential healthcare cost benefits.\u003c/p\u003e \u003cp\u003eECMO is a life-saving intervention for infants with severe, potentially reversible cardiorespiratory failure. Despite advances in technology and patient selection, mortality remains high, particularly for infants with underlying genetic or structural anomalies.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e Data from the ELSO registry demonstrate that congenital diaphragmatic hernia, meconium aspiration syndrome, and persistent pulmonary hypertension of the newborn remain among the most common neonatal indications for ECMO. However, an increasing proportion of cases fall into the 'Other' category\u0026mdash;often reflecting rare or complex conditions with a possible genetic etiology.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e Our findings align with these data and confirm the severity of disease in infants undergoing ECMO given the 24% mortality rate among participants in this study. In this context, early genomic diagnosis serves both to guide escalation of care and to identify disorders associated with extremely poor prognosis or outcomes not compatible with survival. In infants undergoing ECMO, GS has the potential not only to uncover the underlying cause of the disease but also to identify variants that may contribute to dysregulation of the coagulation and clotting cascades, modulation of which is critical in ECMO management to avoid bleeding or thrombotic complications.\u003c/p\u003e \u003cp\u003eThe identification of monogenic disorders may influence not only immediate management but also long-term care trajectories. For example, detection of pathogenic variants associated with poor prognosis may guide decisions regarding the discontinuation of ECMO. At the same time, identification of treatable metabolic or immunologic conditions could prompt targeted interventions.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e Moreover, genetic diagnoses can inform decisions regarding candidacy for advanced therapies such as transplantation.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e As pharmacogenomic knowledge in infants increases, future studies involving GS in ECMO could also evaluate tailoring drug selection and/or dosing based on pharmacogenomics profiling.\u003c/p\u003e \u003cp\u003eThe present study builds upon emerging evidence that integrating genomic testing into critical care workflows is feasible and can yield clinically actionable information within the narrow therapeutic windows characteristic of ECMO care.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Our findings demonstrate a 24% diagnostic yield, comparable to other NICU-based GS studies, with an additional subset of patients harboring VUSs that may gain relevance as genomic knowledge evolves.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e In most studies conducted so far in NICUs/PICUs, high diagnostic yields involved an approach that included a pre-test clinical evaluation for the possible presence of genetic disease. The novel approach in this study relates to the high diagnostic yield achieved by selecting infants based solely on their need for ECMO, regardless of a suspicion for genetic disease. To our knowledge, this is one of the first studies to use GS in patients managed with ECMO in whom no pre-test clinical evaluation for genetic disease was performed. Beyond ECMO, our findings suggest that disease severity is important in assessing which infants may benefit from GS testing. As reflected in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, only a small proportion of infants in this cohort underwent clinically ordered exome (12%) or genome sequencing (4%) during hospitalization, despite high illness severity and diagnostic uncertainty. This highlights an opportunity to expand integration of WES/WGS in contemporary neonatal and pediatric critical care, particularly for ECMO patients who may derive substantial benefit from timely etiologic diagnosis. Testing all infants in a specific NICU/PICU/CICU cohort is particularly attractive for the inherent simplicity of this diagnostic protocol. Other examples could include infants and children scheduled for open heart surgery, transplantation, or other high acuity procedures.\u003c/p\u003e \u003cp\u003eA key barrier to routine clinical use of WGS remains variability in reimbursement and payer approval processes. Access to testing frequently differs across private insurers and state Medicaid programs, resulting in inconsistent availability for clinically similar patients and potential delays in time-sensitive situations such as ECMO. These structural factors should be considered alongside future evaluations of clinical utility and cost-effectiveness.\u003c/p\u003e \u003cp\u003eEmerging statewide precision-medicine initiatives have demonstrated reductions in unnecessary diagnostic testing, hospital length of stay, and overall healthcare costs associated with earlier deployment of rapid sequencing in critically ill infants. These experiences provide important context for future economic evaluations of universal sequencing strategies in ECMO populations.\u003c/p\u003e \u003cp\u003eA limitation of the study was its research design, which did not allow an analysis of the effects of testing on clinical management and outcomes. Several authors have emphasized the importance of conducting a systematic assessment of clinical utility when studying the use of GS in the NICU/PICU environment.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e Therefore, before translating the results of this pilot study into clinical practice, it will be important to perform studies to systematically assess the clinical utility and cost-effectiveness of universal GS in infant ECMO. The anticipated challenges of these studies are primarily the need for streamlined consent processes and robust multidisciplinary support for interpretation and counseling, and most notably the need for ultra-rapid turnaround times for GS results to affect clinical management. Cost-effectiveness analyses and prospective multicenter studies will also be important to define the role of universal GS in infant ECMO.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eDespite its limitations, this study demonstrates that universal GS in infants receiving ECMO is feasible and yields a relatively high rate of clinically relevant diagnoses. Integration of universal rapid GS into ECMO care pathways has the potential to inform precise management, identify both treatable and lethal conditions earlier in the course of care, and support ethically aligned redirection of care when appropriate. Further prospective studies are needed to define the optimal role of GS in ECMO and to address barriers to equitable clinical implementation.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Summary of Patient Demographics\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Summary of ECLS Support and Genetic Testing\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Summary of Genomic Sequencing Results\u003c/p\u003e \u003cp\u003e \u003cb\u003eSupplementary Table\u0026nbsp;1.\u003c/b\u003e Summary of individual genomic sequencing results and secondary findings\u003c/p\u003e \u003cp\u003e \u003cb\u003eSupplementary Table\u0026nbsp;2.\u003c/b\u003e Individual patient clinical characteristics including clinical history, family history, and medication exposures\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding Statement:\u003c/h2\u003e \u003cp\u003eInstitutional Support from the University of Utah Division of Neonatology, Center for Genomic Medicine, and ARUP Laboratories along with a grant from the Ben B. and Iris M. Margolis Foundation. This work utilized computational resources and support from the Center for High Performance Computing at the University of Utah, partially funded by NIH Shared Instrumentation Grants S10OD034321 and S10OD021644.\u003c/p\u003e \u003cp\u003e Ethical Approval and Informed Consent: The study was coordinated through the University of Utah, which served as the single institutional review board (IRB) of record and core data coordinating center. Participating sites were members of the Children\u0026rsquo;s Hospitals Neonatal Consortium (CHNC). All sites obtained local IRB reliance through the IRB Exchange (IREx) platform. Written informed consent was obtained from at least one biological parent before shipment of samples to the sequencing laboratory. This study was conducted in accordance with the ethical standards of the institutional review boards at all participating sites and with the principles outlined in the Declaration of Helsinki.\u003c/p\u003e \u003cp\u003eData Availability Statement: Deidentified sequencing data is available from the corresponding author upon reasonable request.\u003c/p\u003e\u003ch2\u003eAcknowledgments:\u003c/h2\u003e \u003cp\u003e We thank the participating infants and families, as well as the clinical teams and research staff at all eight Children\u0026rsquo;s Hospital Neonatal Consortium (CHNC) sites for their commitment to this study. We also acknowledge the contributions of our genomic laboratory partners and the CHNC infrastructure team for their support in data coordination and study implementation. Sequence alignment, variant calling, and variant interpretation analyses were performed in part by the Utah Center for Genetic Discovery Core facility, part of the Health Sciences Center Cores at the University of Utah.\u003c/p\u003e \u003cp\u003eContributors\u0026rsquo; statements: Drs. Carr and Brunelli participated in study design, data analysis, and manuscript writing. Drs. Fulmer, Mao, and Boyden participated in data analysis, writing, and review. All other authors participated in manuscript writing and review. All authors agree with the final draft of this manuscript.\u003c/p\u003e \u003cp\u003eDeclaration of Conflicting Interest: The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSaunders CJ, Miller NA, Soden SE, Dinwiddie DL, Noll A, Alnadi NA, \u003cem\u003eet al.\u003c/em\u003e Rapid whole-genome sequencing for genetic disease diagnosis in neonatal intensive care units. \u003cem\u003eSci Transl Med\u003c/em\u003e 2012, 4(154): 154ra135.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePetrikin JE, Willig LK, Smith LD, Kingsmore SF. 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A follow-up study of clinical outcomes and cost-effectiveness. \u003cem\u003eGenet Med\u003c/em\u003e 2019, 21(1): 173\u0026ndash;180.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKingsmore SF. Is Rapid Exome Sequencing Standard of Care in the Neonatal and Pediatric Intensive Care Units? \u003cem\u003eJ Pediatr\u003c/em\u003e 2020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLantos JD, Brunelli L, Hayeems RZ. Understanding the Clinical Utility of Genome Sequencing in Critically Ill Newborns. \u003cem\u003eThe Journal of pediatrics\u003c/em\u003e 2023, 258: 113438.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchwarze K, Buchanan J, Taylor JC, Wordsworth S. Are whole-exome and whole-genome sequencing approaches cost-effective? A systematic review of the literature. \u003cem\u003eGenet Med\u003c/em\u003e 2018, 20(10): 1122\u0026ndash;1130.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-perinatology","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"jp","sideBox":"Learn more about [Journal of Perinatology](http://www.nature.com/jp/)","snPcode":"41372","submissionUrl":"https://mts-jper.nature.com/cgi-bin/main.plex","title":"Journal of Perinatology","twitterHandle":"@jperinatology","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"genome sequencing, ECMO, neonate, NICU, genetic diagnosis, precision medicine","lastPublishedDoi":"10.21203/rs.3.rs-8535209/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8535209/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo evaluate the feasibility and diagnostic yield of universal genome sequencing (GS) in infants receiving extracorporeal membrane oxygenation (ECMO).\u003c/p\u003e\u003ch2\u003eStudy Design:\u003c/h2\u003e \u003cp\u003eProspective multicenter study across eight Children\u0026rsquo;s Hospital Neonatal Consortium sites (October 2021\u0026ndash;August 2023). Infants initiated on ECMO were enrolled for GS regardless of suspected genetic disease. Demographics, ECMO indications, and results from standard-care testing and study-based GS were analyzed.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eTwenty-five infants were enrolled. Primary ECMO indications included congenital diaphragmatic hernia (28%), meconium aspiration syndrome (24%), and primary respiratory failure (20%). GS identified pathogenic or likely pathogenic variants in 6/25 infants (24%), including three cytogenetic-confirmed diagnoses and three molecular diagnoses identified only by GS. Variants of uncertain significance were identified in 44% of infants, while 32% had negative results.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eUniversal GS during ECMO is feasible and yields a relatively high rate of clinically relevant diagnoses, supporting further assessment of the integration of genomic testing into ECMO care pathways.\u003c/p\u003e","manuscriptTitle":"Efficacy of Universal Genome Sequencing in Infant Extracorporeal Membrane Oxygenation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-19 18:40:42","doi":"10.21203/rs.3.rs-8535209/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2026-01-30T11:39:23+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2026-01-28T06:38:17+00:00","index":1,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2026-01-26T22:01:08+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-01-15T21:31:13+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-01-14T02:52:08+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2026-01-14T02:38:51+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-12T16:12:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Perinatology","date":"2026-01-11T22:50:53+00:00","index":"","fulltext":""},{"type":"checksFailed","content":"","date":"2026-01-09T16:23:57+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-06T22:23:44+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-perinatology","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"jp","sideBox":"Learn more about [Journal of Perinatology](http://www.nature.com/jp/)","snPcode":"41372","submissionUrl":"https://mts-jper.nature.com/cgi-bin/main.plex","title":"Journal of Perinatology","twitterHandle":"@jperinatology","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"25524bfb-2854-4a87-acdb-9850463ec0eb","owner":[],"postedDate":"January 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":61102000,"name":"Health sciences/Health care/Diagnosis/Genetic testing"},{"id":61102001,"name":"Health sciences/Pathogenesis/Clinical genetics/Genetic testing"}],"tags":[],"updatedAt":"2026-04-13T23:55:25+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-19 18:40:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8535209","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8535209","identity":"rs-8535209","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}