Genomic newborn screening: feasibility, acceptability and clinical outcomes

Genomic newborn screening: feasibility, acceptability and clinical outcomes | 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 Genomic newborn screening: feasibility, acceptability and clinical outcomes Zornitza Stark, Sebastian Lunke, Lilian Downie, Jade Caruana, and 32 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6616246/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 Oct, 2025 Read the published version in Nature Medicine → Version 1 posted You are reading this latest preprint version Abstract Incorporating genomic sequencing into newborn screening (NBS) will dramatically increase the number of detectable conditions but evidence is needed to guide policy. The BabyScreen + study screened 1,000 newborns for variants in 605 genes associated with early-onset, severe, treatable conditions using whole genome sequencing performed on dried blood spot cards. Sixteen infants (1.6%) were identified as having high chance results. Of these, only one was detected by standard NBS. Average time to genomic NBS result was 13 days. Clinical impact ranged from instituting preventative measures or surveillance to active management, including transplantation. Twenty relatives received a diagnosis following cascade testing. Median parental decisional regret was low (median 0, IQR 0–10); >99% of participants thought gNBS should be available to all parents. Our study demonstrates the feasibility of clinically accredited gNBS, using a scalable model that is highly acceptable to parents. Future research is needed to address issues of scalability and equity. Health sciences/Health care/Paediatrics Health sciences/Health care/Public health/Population screening Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Newborn screening (NBS) for rare conditions is one of the most effective public health interventions 1 , delivered with high uptake, quick turnaround times and at low cost. However, the increased ability to diagnose and treat rare diseases ushered in by the era of genomic and precision medicine 2,3 has challenged the ability of NBS programs to keep pace, with the time to include a new condition averaging nine years in the USA 4 . Incorporating genomic sequencing into NBS programs offers the opportunity to substantially increase the number of conditions screened and to include conditions that do not have available biochemical markers, such as those predisposing to childhood cancers 5 . Further, genomic sequencing provides flexibility to add or remove conditions at low incremental cost and has the potential to provide health benefit over an individual’s lifetime through reuse of data for diagnostic, screening and research purposes 6 . Genomic NBS (gNBS) raises considerable issues when implementation at population level is considered. There is little consensus on how it should be offered in terms of timing or method of consent; what testing modality or samples to use; which conditions to screen; or how to manage downstream healthcare system impacts. Despite extensive debate over the past 10 years 7 , there is little evidence from prospective cohorts to guide policy and implementation 8–11 . Multiple studies are currently underway in diverse healthcare systems which will test out the feasibility of different implementation models and provide early data on patient, family and healthcare system outcomes 5 . The BabyScreen + study aims to address some of these questions through multidisciplinary evaluation of a prospective cohort of 1,000 newborns in a public healthcare system, with gNBS offered for 605 genes associated with early-onset, treatable childhood conditions alongside standard NBS (stdNBS) 12,13 . The study assessed a broad range of outcomes including feasibility of performing clinically accredited genome sequencing using dried blood spot (DBS) cards; screening outcomes compared with stdNBS; parental psychosocial outcomes and acceptability. Results Demographics and recruitment Study enrolment was initiated 12 by 1288 prospective parents, with 301 (23%) not completing enrolment, declining screening or withdrawing from the study. gNBS was completed for 1000 newborns over 16 months, of whom 523 (52%) were male and 477 (48%) female, including 13 sets of twins (Figure 1). Ancestry, geographical location and socio-economic indices of relative advantage and disadvantage of participants were similar to that of the age- and sex-matched Australian population, with a relative over-representation of higher educated individuals (Figure 2). Recruitment by a healthcare professional (active recruitment) resulted in the highest number of study participants completing enrolment (667/998, 67%, Figure 3), with social media advertising the most successful passive recruitment method (190/998, 19%). Active recruitment had the lowest proportion of incomplete enrolments (Table S2). Feasibility of genome sequencing from dried blood spots DBS cards from 1003 newborns were processed for gNBS. Reprocessing was required for 82 (8.2%) samples due to sample-related (3.2%) or process-related (5.0%) failures (Table S3). DNA re-extraction was performed for 79 (7.9%), using new punches from the existing DBS card (50), collection of new DBS cards (7), or collection of fresh blood samples (22 samples, Table S4). Three participants declined sample recollection. Sequencing data generation failed target coverage requirements for 191 (19%) samples, requiring additional sequencing. Process improvements, including optimisation of sample quantitation methods and sequencer loading concentrations, reduced failure rates from an initial average of 28% to less than 5% (Figure S1). All re-extracted and re-processed samples were successfully reported on the second attempt. Excluding samples that required re-extraction would have led to two missed high chance results ( UNC13D, GNAS, Table 1). Average TAT for stdNBS followed by gNBS was 24 days from sample collection (Target: 28 days, Min: 11, Max: 68, CI95: 23.5-24.5). Average TAT for gNBS was 13 days (Min: 6, Max: 56, CI95: 12.7-13.3), with 73% reported within the target of 14 days. The proportion of reports issued within target TAT increased from 65% to 81% following reduction in sequencing failure rates. Genomic data analysis and interpretation Analysis protocols (Figure 4) were validated using a cohort of 108 clinical cases of critically ill infants undergoing genomic testing, with 61 known low chance and 47 known high chance results 2 . Validation data showed >97% sensitivity with 46 of the known high chance cases correctly flagged. The high chance case missed by the analysis had a multi-nucleotide variant ( ACAD9 , NM_014049.4, c.1376_1381delinsCCT, p.(Lys459_Ser461delinsThrCys). This that was incorrectly annotated by the analysis software as two non-high impact variants, a known limitation. No cases were incorrectly classified as low chance by the automated system, however 32 of 61 (51%, Table S5) of known low chance cases required manual review of non-reportable variants. Of the 1000 study samples, 451 (45%) were automatically reported as low chance. In the remaining 549 (55%) cases, 1045 variants were manually reviewed, with 36 variants undergoing full assessment and 18 ultimately reported. Of the non-reportable variants, 1009 were discarded due to insufficient evidence for pathogenicity, including all copy number variants (CNVs) (Table S6). The 18 variants that underwent full assessment but were not reported were excluded for a range of reasons, including mismatched mechanism of disease or mode of inheritance, or association with adult-onset or mild disease (Tables S6 and S7). Modelling filter conditions showed an automatic low chance report rate of 82% was achievable (Table S8) but increased the likelihood of false negative results. Only reporting variants previously described as pathogenic in ClinVar would have resulted in the loss of one high chance result ( GNAS , Table 1). High chance results were issued for 16 newborns (1.6%, Table 1). No discordances with stdNBS were identified. One newborn was identified as having hypothyroidism through stdNBS. gNBS provided the precise etiology ( GNAS variant) enabling cascade testing and surveillance for multisystem involvement. All high chance results were confirmed by orthogonal testing on new samples, with no discordances. All variants in recessive genes were confirmed in trans. Clinical impact of high chance results Clinical impact ranged from instituting preventative measures or surveillance to active management. Nine results in three genes (G6PD, MT-RNR1, RYR1) prompted preventative measures (Table 1). These were managed by the gNBS team without involvement of specialist services. Five results ( FBN1, GNAS, ENG, GJB2, DICER1) led to initiation of surveillance measures which included echocardiogram, blood tests, MRI scan, audiology assessment and follow-up with specialist physicians. Two results ( PKHB, UNC13D) resulted in immediate treatment (Table 1). The infant with glycogen storage disorder due to PKHB variant had unrelated congenital heart disease and had been scheduled for cardiac surgery. Identification of an underlying metabolic disorder enabled appropriate multi-disciplinary management of peri-operative fasting to avoid episodes of hypoglycemia. The infant diagnosed with UNC13D -related HLH was clinically well at the time of gNBS result disclosure, but immunological testing revealed early signs of immune dysregulation. The diagnosis enabled early commencement of therapy with immune modulators and proactive planning for bone marrow transplantation, which was performed at 4 months of age. Testing in first-degree relatives resulted in 20 additional diagnoses (12 parents, eight siblings). None of the affected relatives were previously suspected of having a genetic condition, although clinical findings and family histories consistent with the diagnoses were present in four parents ( FBN1, GNAS, ENG, DICER1 ). Two participants required re-analysis of gNBS data for diagnostic purposes within the study period. One was a newborn with a low chance result who had a diagnosis of moderate bilateral sensorineural hearing loss from newborn hearing screening. Diagnostic re-analysis did not identify a genetic cause for hearing loss. The second newborn with a high chance result for G6PD deficiency had diagnostic re-analysis following admission to neonatal intensive care with multiorgan failure. A re-analysis report was issued within 24 hours of the request, with no additional genetic diagnosis identified. Table 1. High chance results reported in BabyScreen+ and their clinical impact. Gene Condition Case number Variant(s) ACMG classification Inheritance Clinical impact Prevention G6PD G6PD deficient haemolytic anaemia, OMIM #300908 1 & 2 NM_000402.4:c.1039G>A (p.Glu347Lys) Class 5 Maternal Information provided on triggers of hemolytic crisis. Alerts placed in hospital medical records and primary care physician notified. Ten family members diagnosed 3 & 4 NM_001360016.2:c.1376G>T (p.Arg459Leu) Class 5 Maternal 5 NM_000402.4:c.1093G>A (p.Ala365Thr) Class 5 Maternal 6 NM_001360016.2:c.542A>T (p.Asp181Val) Class 5 Maternal MT-RNR1 Mitochondrial non-syndromic sensorineural hearing loss, MONDO #0010779 7 NC_012920.1:m.1494C>T (homoplasmic) Class 4 Maternal Information provided on avoidance of aminoglycoside exposure Alerts placed in hospital medical records and primary care physician notified. One family member diagnosed Audiology assessment at six months of age for proband and mother 8 NC_012920.1:m.1555A>G (48% heteroplasmy) Class 5 Maternal Information provided on avoidance of aminoglycoside exposure Alerts placed in hospital medical records and primary care physician notified. Audiology assessment recommended if concerns arise regarding hearing RYR1 Malignant hyperthermia susceptibility 1, OMIM #145600 9 NM_000540.3:c.1202G>T (p.Arg401Leu) Class 4 Paternal Information provided on avoidance of suxamethonium and volatile anesthetic agents Alerts placed in hospital medical records and primary care physician notified. Three family members diagnosed Surveillance FBN1 Marfan syndrome, OMIM #154700 10 NM_000138.5:c.5518C>T (p.Arg1840Cys) Class 4 Maternal Echocardiogram and regular cardiology review Two family members diagnosed, referred for surveillance GNAS a Pseudohypoparathyroidism 1a, OMIM #103580 11 NM_000516.7:c.476T>C (p.Val159Ala) b Class 5 Maternal Treatment with thyroxine, endocrinology assessment Two family members diagnosed, referred to endocrinology ENG Hereditary haemorrhagic telangiectasia (HHT) type 1, OMIM #187300 12 NM_001114753.3:c.1310G>A (p.Arg437Gln) Class 4 Paternal MRI for cerebral arteriovenous malformations. Referral to HHT clinic for ongoing surveillance. One family member diagnosed, referred to adult HHT clinic GJB2 Autosomal recessive deafness 1A, OMIM #220290 13 NM_004004.6:c.35del (p.Gly12Valfs*2) NM_004004.6:c.583A>G (p.Met195Val) Class 5 Biparental Referred for annual audiology assessments DICER1 DICER1-related tumor predisposition, MONDO #0100216 14 NM_177438.3:c.745C>T (p.Gln249*) Class 5 Paternal Referred to pediatric oncologist for regular surveillance One family member diagnosed, referred to adult familial cancer center Treatment PHKB Phosphorylase kinase deficiency of liver and muscle, OMIM #261750 15 NM_000293.3:c.1127-2A>G (homozygous) Class 5 Biparental Admission to hospital for unrelated cardiac surgery, protocol to avoid hypoglycemia during fasting followed Liver ultrasound UNC13D c Familial hemophagocytic lymphohistiocytosis (HLH) 3, OMIM #608898 16 NM_199242.2:c.817C>T (p.Arg273*) NM_199242.3:c.627del (p.Val210Trpfs*39) Class 5 Biparental Immunological tests abnormal at time of results Admitted to hospital for treatment with steroids and Emapalumab Bone marrow transplant a Sample reprocessed by taking new punches from the existing DBS card after initial laboratory processing batch failure b Previously described in the literature only (identified via Genomenon Mastermind) c Sample reprocessed by collecting a new blood sample after initial poor sample quality Psychosocial outcomes and attitudes towards scr eening Out of 1012 parents who consented to gNBS, 998 (99%) completed a survey (Figure 1). We conducted 48 interviews with 46 birth parents and three partners. This included 22 pre-test gNBS acceptors, two gNBS decliners, 17 low chance results recipients, and eight high chance results recipients. Most survey respondents (80%) indicated they consented ‘immediately’ using Genetics Adviser, with the decision perceived as either ‘easy’ or ‘very easy’ (Table S10). Only 8% found decision-making difficult. Interviewees valued Genetics Adviser, with education content generally used to reaffirm decisions, provide guidance on what to consider, understand the impact of their decision, or facilitate discussions with partners. Interviewees also described how they considered clinical, psychosocial, and practical factors in gNBS decisions. They weighed up benefits of screening, the types of conditions being screened, potential barriers, and their ability to navigate results. Decisions to have gNBS were most strongly influenced by a desire “To know what to expect for my baby’s future” (77% survey respondents) (Figure 5). The main influence for declining gNBS (10 surveys completed) was concern about the result having negative impact on parents (80%) (Table S11). At enrolment, the median trait anxiety score was 32.63 (IQR 28.42 – 38.94). Most survey respondents scored under the cut-off for probable clinical state anxiety at enrolment (80%), and at the T3 survey (85%, n=422). Post-result return, decision regret was very low (Median 0, IQR 0-10, n=500). Parents of infants who received a high chance result were asked to complete an adapted version of the Genomics Outcomes Scale (GOS). Five participants (31%) responded to the GOS scale, with a mean empowerment score of 25.6 (CI 23.07-28.13) out of 30. Interviewees who received a low chance gNBS result reported positive impacts such as reassurance. Interviewees who received a high chance result valued results due to their clinical utility. Prompt genetic counselling and access to high quality information facilitated adaptation. Most respondents (82%) would choose to have gNBS for a future baby, and 92% would recommend it to a family member (Table S12). All but one respondent thought that gNBS should be available to all parents, and 97% thought it should be publicly funded. Discussion The BabyScreen + study provided screening for disease-causing variants in 605 genes associated with severe, early-onset, treatable childhood conditions in a prospective cohort of 1,000 newborns. We found 1.6% of newborns had an increased chance of a screened condition, leading to a range of interventions from preventative measures and surveillance through to bone marrow transplant. Only one of these diagnoses was identified by stdNBS, highlighting the ability of gNBS to identify a much broader range of actionable rare disorders. Parental attitudes towards gNBS were positive with minimal decisional regret. We have demonstrated feasibility of delivering clinically accredited gNBS within a public healthcare system using a scalable model designed to be minimally disruptive to the healthcare system and to families. The model was informed by prior studies 5,14–16 , as well as public and professional consultation including focus groups 17,18 , key informant interviews 19 and discrete choice experiments with over 2,000 members of the Australian public 20 . Our model includes education and consent using online tools during pregnancy; use of existing DBS collection pathways; and laboratory processes that integrate with stdNBS and balance automation and manual review of genomic data to minimize false positive results. The use of clinically accredited genome sequencing and analysis facilitates reuse of the data for diagnostic purposes and for further age-appropriate screening 21 . While prior studies have mostly elected to offer gNBS in the newborn period using trained personnel, concerns have been raised about the scalability and appropriateness of these models, given the complexity of information required for gNBS consent and the potential impact on consent for stdNBS 5,22 . The stated preference, of both parents and healthcare providers, for information provision and consent during pregnancy 18,19,23 led us to implement a model where gNBS was introduced during pregnancy using multi-modal approaches. An extensively evaluated online digital platform 24,25 provided education and decision support, including case vignettes and value clarification exercises. The resultant cohort is diverse and largely reflective of the Australian population, with 80% of parents reporting being able to make an ‘easy’ decision to have gNBS. However, the temporal separation of consent from sample collection in this model raises new challenges such as the need to ensure ongoing consent and to develop laboratory protocols for accurate sample identification. The overall model requires further evaluation at scale to ensure it supports equitable access, particularly to families disadvantaged by socioeconomic or cultural and linguistic factors. Further consideration also needs to be given about how information provision and consent will integrate with other screening tests offered in pregnancy, notably reproductive carrier screening where there is considerable overlap in the conditions screened 13,26,27 , potentially creating confusion for healthcare providers and potential parents alike. This issue is highlighted by the high chance result for UNC13D -related HLH in our cohort where the parents had completed expanded reproductive carrier screening for 200 genes. This test included two more frequent genetic causes of familial HLH but excluded UNC13D . Similar to other studies, we found using DBS cards for gNBS was feasible, with 2.4% of samples requiring reprocessing to obtain results due to sample-related failures 28 . Taking additional punches from the original DBS card addressed most reprocessing requirements, negating the need for sample recollection. Opting not to reprocess would have resulted in two missed high chance results, including that of HLH ( UNC13D ). The average time to report of 13 days compares favorably with stdNBS and is faster than the time to report from other studies, which ranged from 32.5 11 to 64 days 8 . While we elected to perform gNBS after stdNBS to minimize disruption, we envisage the two occurring in parallel. Achieving clinically meaningful turnaround times for gNBS is important as many of the conditions are immediately actionable, as demonstrated in this cohort by the newborn diagnosed with glycogen storage disease who had forthcoming cardiac surgery for unrelated reasons. Knowledge of the underlying condition allowed appropriate planning of peri-operative care under the guidance of a metabolic physician to avoid fasting hypoglycaemia. A high degree of automation will be required to scale gNBS to public health programs but careful calibration is needed to minimize false positive and negative results 5 . We adopted an integrated approach, incorporating stdNBS results and multi-disciplinary review prior to reporting. Adherence to pre-defined variant lists can lead to false negatives 8 and would have likely led to at least one missed result in our cohort as well. Similarly, automation can miss complexities, such as common in cis variants in genes with recessive inheritance 11 , increasing false positives with significant impact on families and the workforce when considered at scale (Table S7). Our analysis approach mitigates these common pitfalls; our rate of high chance results (1.6%) is comparable with that of other studies 8,11 despite hundreds more genes being analyzed 13 (Table S13). While the rate of manual review required in our setup currently cannot be considered scalable, we have shown that a small number of simple changes can substantially increase automation without major compromises to accuracy (Table S8). Continual refinement of automation pipelines and the integration of data generated by pilot gNBS studies will optimize this balancing act moving forwards 29 . We identified a wide range of conditions, with G6PD deficiency the commonest finding. Just over half of the high chance results were managed without involvement of specialist services. The remainder required input from multiple specialists and prompt access to other investigations. In addition, 20 relatives received a molecular diagnosis through cascade testing. As gNBS scales, there will be a need to systematically develop dedicated downstream pathways that integrate results, investigations and referrals to a broad range of pediatric and adult services with adequate psychosocial support for families. Equitable access to these pathways, including for regional and remote communities, will be a key consideration for public health programs. Prospective parents and the general public express positive views towards gNBS, while health professionals are typically more cautious 5,30–35 . Many concerns have been raised about the potential psychosocial risks of sequencing newborns, including effects on parent-child bonding, perceived child vulnerability and self and partner blame 36 . In this cohort, parents held positive views following gNBS, generally found the decision easy to make and supported future public funding. We found no evidence of adverse psychosocial outcomes such as increased anxiety or decision regret, consistent with smaller previous cohorts. 14,37,38 Rather, participants reported feeling empowered. Even those with a high chance result reported adapting to the information through access to prompt high-quality information. The limitations of this study included the relatively small cohort size and recruitment over an 18-month period. This means that the laboratory and clinical systems were not tested at the scale that would be required to deliver a national screening program. For the population of Australia this would require 300,000 samples to be processed per annum and over 4,500 high chance results to be returned in a variety of settings, necessitating substantial investment in infrastructure, workforce development and national consistency. In addition, there was an over-representation of highly educated parents and targeted efforts would be required to ensure equity of access both to screening and to downstream care pathways. Other areas that remain underexplored include the potential for the data to be reused for clinical and screening purposes throughout an individual’s lifetime. While we were able to demonstrate the benefits of data reuse for diagnostic purposes in two infants within a relatively short period of time, large-scale implementation of a data reuse model would include further considerations of consent models, infrastructure requirements and integration with electronic medical records for example. In conclusion we have demonstrated feasibility and acceptability of gNBS in a public healthcare system, using a model that integrates with the existing stdNBS program and delivers clinically accredited results with rapid turnaround times. While we provide comprehensive multidisciplinary evaluation, much larger longitudinal studies are now required to demonstrate scalability to population level and assess other outcome measures such as equity, cost-effectiveness and long-term impacts on families and healthcare systems. Methods Study setting The previously published study protocol 12 is summarized here. BabyScreen+ was designed to evaluate the acceptability and feasibility of gNBS in a prospective cohort of 1000 newborns from the state of Victoria, Australia, using clinically accredited genome sequencing. The study was funded by the Australian Government’s Genomics Health Futures Mission (MRF2015937) without any restrictions or encumbrances. The funding agency was not involved in any aspects of the study including design, analysis and reporting. Ethics approval was obtained from the Royal Children’s Hospital Research Ethics Committee (HREC/91500/RCHM-2023). All laboratory procedures, data analysis, and reporting were performed by Victorian Clinical Genetics Services (VCGS), a wholly owned not-for-profit subsidiary of the Murdoch Children’s Research Institute, in Melbourne, Australia. VCGS is responsible for the delivery of stdNBS for the state of Victoria, and DBS cards were accessed with permission from participants and the Victorian State Government. Recruitment gNBS was offered, free of charge, during the third trimester of pregnancy in private and public healthcare settings. Recruiting healthcare professionals attended an education session and were provided with study cards, posters and videos. The study was also advertised via social media, SMS and a pregnancy app. Birth parents could enroll if aged 16 or over; planning to give birth in Victoria, Australia; and intending to participate in stdNBS. Enrolment was ideally in pregnancy but was available up until two weeks after birth. Study cards and advertising materials contained a QR code connecting potential participants to the online platform Genetics Adviser, which provided education and decision support 24,25 . Participants consented separately to research and to gNBS. Contact with a genetic counsellor was available at any stage. DNA extraction and sequencing Following completion of stdNBS, DNA was extracted from four 3mm DBS punches using the Mag-Bind DNA Blood and Tissue kit (Omega Biotek). PCR-free genome sequencing libraries were created using the PCR-free DNA prep kit (Illumina) and sequenced using a 2x150 bases paired end read configuration to an average depth of 30x on a NovaSeq X Plus instrument (Illumina). Sequencing library quantitation was initially performed using the Qubit dsDNA High Sensitivity kit (Thermo Fisher Scientific), and was transitioned to real-time PCR based library quantitation using the KAPA Library Quantification kit for Illumina Platforms (Roche) on a QuantStudio 7 Pro instrument (Thermo Fisher Scientific) as per standard protocol, following troubleshooting of sequencing data issues. Genomic data analysis and interpretation Data analysis and interpretation were performed using the Dragen and Emedgene (Illumina) analysis tools, with custom in-house filter configuration (Table S1) designed to identify variants for potential reporting in 605 genes associated with early-onset treatable childhood conditions. Details of the gene selection process are previously published 13 . Variants classified as likely pathogenic or pathogenic based on ACMG guidelines 39 and consistent with the relevant mode of inheritance were considered. Carrier status, adult-onset or mild forms of conditions, and variants of uncertain significance were not reported. Return of results and clinical management Results were designated either “low chance”, where no reportable variants were identified, or “high chance”. For low chance results, participants were informed via email and SMS of result availability on Genetics Adviser. Genetic counselling was available on request. For high chance results, parents were contacted by a genetic counsellor to discuss the result, and to arrange clinical geneticist appointment, followed by additional testing (including confirmation and segregation of reported variants), and referral to specialist services as needed. Participant surveys Participating birth parents provided pregnancy and demographic information (T1) and completed a research survey (T2) as part of enrolment, with a further optional survey three months post-result (T3). Pregnancy and demographic variables were compared with age and sex-matched Australian Government Census data, or the Australian Institute of Health and Welfare’s National Perinatal Data Collection. For participants who consented to gNBS, study specific multiple-choice survey items were used to measure the difficulty of decision making; reasons for choosing to have gNBS; acceptability; attitudes towards gNBS; and preferences for having gNBS for future children. Trait anxiety was measured at enrolment using the State-Trait Anxiety Inventory trait anxiety scale (STAI-T). State anxiety was measured using the short-form six-item STAI-6 at enrolment and three months post-result 40 . The Decision Regret Scale 41 was administered three months post-result. For participants who chose not to have gNBS, reasons for declining were identified at enrolment using a study-specific matrix survey comprising 11 options rated on a five-point Likert scale. Item logic was used in the data collection platform to administer the Genomics Outcome Scale (GOS) in the T3 survey to participants with an infant who received a high chance result. The Genomics Outcome Scale is a patient reported outcome measure (PROM) for clinical genetics services 42 . The GOS consists of 6-items with 5-point Likert scale responses options ranging from Strongly Disagree to Strongly Agree. Participant interviews A random sample of participants who accepted gNBS were invited to take part in interviews prior to receiving their results and/or approximately 3 months after receiving a low chance result. These participants were purposively sampled to ensure that participants were spread across age groups, study sites, and ancestry. We also invited all participants who declined gNBS or received a high chance result. Semi-structured interviews were conducted via Zoom or by phone and were audio-recorded for transcription. An external transcription company transcribed all audio recordings verbatim, the researcher conducting the interviews then removed identifying details from the transcripts and assigned pseudonyms to all interviewees. Written notes were used for two interviews due to technical issues associated with those recordings. Analysis Statistical analysis of participant survey and recruitment data were done using StataSE 18, and analysis of laboratory data were performed as outlined in the Supplementary Appendix. Turnaround times (TAT) for samples that required recollection were measured from receipt of the new sample. Qualitative data were analyzed using content analysis. Declarations Ethical approval This study is governed and administered by the Murdoch Children’s Research Institute (MCRI), Melbourne, Australia. All genetic testing is performed by VCGS, Melbourne, Australia, a wholly owned not-for-profit subsidiary of MCRI. VCGS is clinically accredited (NATA/RCPA) to ISO15189;2012 to carry out genetic and genomic testing. The project has received ethics approval from the Royal Children’s Hospital Melbourne Human Research Ethics Committee (main BabyScreen+ protocol: HREC/91500/RCHM-2023; key informant interviews: HREC/90929/RCHM-2022; and focus groups and DCE: HREC/91392/RCHM-2022). F unding The BabyScreen+ study was funded by the Australian Government’s Genomics Health Futures Mission (MRF2015937) without any restrictions or encumbrances. The funding agency was not involved in any aspects of the study including design, analysis and reporting. The research conducted at the Murdoch Children's Research Institute was supported by the Victorian Government 's Operational Infrastructure Support Program. J.Ch. is generously supported by The Royal Children's Hospital Foundation as The Chair in Genomic Medicine. Competing interests Yvonne Bombard and Marc Clausen are co-founders of the Genetics Adviser platform. The other authors have no conflicts of interest to declare. Data Availability All data supporting the findings of this study are available within the paper and its Supplementary Information. Clinically reported variants have been submitted to ClinVar under accession numbers SUB15105434, SUB15105434, SCV005399527.1, SCV003921943.3, SCV005086718.1, SUB15105434, SCV001244783.2, SCV005400334.1, SCV005398282.1, SUB15105434, SCV005400615.1, SCV005400606.1 (Table S9). Any additional data are available from the corresponding author upon reasonable request. Data are located in controlled access data storage at the Murdoch Children’s Research Institute. Code availability Not applicable. References Centers for Disease & Prevention. Ten great public health achievements--worldwide, 2001-2010. MMWR Morb Mortal Wkly Rep 60 , 814-818 (2011). Lunke, S. , et al. Integrated multi-omics for rapid rare disease diagnosis on a national scale. Nat Med 29 , 1681-1691 (2023). Tambuyzer, E. , et al. 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Two-step offer and return of multiple types of additional genomic findings to families after ultrarapid trio genomic testing in the acute care setting: a study protocol. BMJ Open 13 , e072999 (2023). Lynch, F. , et al. Australian public perspectives on genomic newborn screening: which conditions should be included? Hum Genomics 18 , 45 (2024). Lynch, F. , et al. Australian Public Perspectives on Genomic Newborn Screening: Risks, Benefits, and Preferences for Implementation. Int J Neonatal Screen 10 (2024). Tutty, E. , et al. Key informant perspectives on implementing genomic newborn screening: a qualitative study guided by the Action, Actor, Context, Target, Time framework. Eur J Hum Genet 32 , 1599-1605 (2024). Peters, R.B., S.; Lynch, F.; Vears, D.F.; Downie, L.; Archibald, A.D.; Lunke, S.; Stark, Z.; Goranitis, I. Societal preferences for the value and implementation of genomic newborn screening: insights from 2 discrete choice experiments in Australia. Am J Hum Genet (2025). 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Kirk, E.P.D., M.B.; Archibald, A.D.; Tutty, E.; Caruana, J.; Halliday, J.L.; Lewis, S.; McClaren, B.J.; Newson, A.J.; et al. Nationwide reproductive couple-based carrier screening. N Engl J Med in press (2024). Downie, L., Lunke, S. & Stark, Z. The Intersection Between Genetic Reproductive Carrier Screening and Genomic Newborn Screening: Implications for Clinical Practice. Prenat Diagn (2025). Ding, Y. , et al. Scalable, high quality, whole genome sequencing from archived, newborn, dried blood spots. NPJ Genom Med 8 , 5 (2023). Kingsmore, S.F. , et al. Prequalification of genome-based newborn screening for severe childhood genetic diseases through federated training based on purifying hyperselection. Am J Hum Genet 111 , 2618-2642 (2024). Bombard, Y. , et al. Public views on participating in newborn screening using genome sequencing. Eur J Hum Genet 22 , 1248-1254 (2014). 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Pereira, S. , et al. Psychosocial Effect of Newborn Genomic Sequencing on Families in the BabySeq Project: A Randomized Clinical Trial. JAMA Pediatr 175 , 1132-1141 (2021). Armstrong, B. , et al. Parental Attitudes Toward Standard Newborn Screening and Newborn Genomic Sequencing: Findings From the BabySeq Study. Front Genet 13 , 867371 (2022). Richards, S. , et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med 17 , 405-424 (2015). Marteau, T.M. & Bekker, H. The development of a six-item short-form of the state scale of the Spielberger State-Trait Anxiety Inventory (STAI). Br J Clin Psychol 31 , 301-306 (1992). Brehaut, J.C. , et al. Validation of a decision regret scale. Med Decis Making 23 , 281-292 (2003). Grant, P.E., Pampaka, M., Payne, K., Clarke, A. & McAllister, M. Developing a short-form of the Genetic Counselling Outcome Scale: The Genomics Outcome Scale. Eur J Med Genet 62 , 324-334 (2019). Additional Declarations Yes there is potential Competing Interest. Yvonne Bombard and Marc Clausen are co-founders of the Genetics Adviser platform. The other authors have no conflicts of interest to declare. Supplementary Files BabyScreenoutcomespaperSupplementaryappendixv1clean.docx Supplementary figures and tables Cite Share Download PDF Status: Published Journal Publication published 09 Oct, 2025 Read the published version in Nature Medicine → Version 1 posted 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-6616246","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":460431419,"identity":"e62d0f0b-0f25-472a-9b7e-872201013e06","order_by":0,"name":"Zornitza 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1","display":"","copyAsset":false,"role":"figure","size":156550,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eParticipation in BabyScreen+.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEligible participants initiated enrolment via the online platform Genetics Adviser, accessible via a QR code either on a study invitation card obtained from a healthcare professional (active recruitment), or on a range of other advertising material (passive recruitment). Engagement was tracked from first login to the platform using a unique study ID. Completion of the Genetics Adviser education and decision support module, T1 and T2 research surveys, and consent to both research participation and clinical gNBS was mandatory in order to complete enrolment. Completion of the T3 survey, distributed three months post-result, was optional. 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Charts C to F contain comparisons between the BabyScreen+ cohort and the age and sex-matched population of Victoria, Australia, based on Australian Census data. Geographic location (Remoteness Area) and Index of Relative Socio-economic Advantage and Disadvantage are based on the classifications used by the Australian Bureau of Statistics. These variables are from a level 2 statistical area (average population of 10,000 people). Participants were able to select more than one response when reporting their ancestry. Ancestry data is presented as a proportion of the total responses. The top five ancestries from the BabyScreen+ data are presented with the addition of Aboriginal and Torres Strait Islander ancestry. The BabyScreen+ demographic survey indicated that Oceanic ancestry refers to people from the Pacific Islands or Micronesia. The 2021 Australian Census did not provide such guidance, as such it is likely that many of the responses indicating Oceanic ancestry refer to respondents of European ancestry born in Australia.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6616246/v1/60c4ef145b8986c149f67d89.png"},{"id":83514132,"identity":"e65f98fe-a4fa-44b7-b642-ed5b6cab7fce","added_by":"auto","created_at":"2025-05-27 17:51:09","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":150395,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eQuarterly recruitment numbers by recruitment method.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEach participant family is represented as a single square, with a total of 987 enrolled families (including 13 sets of twins). Recruitment methods were broadly categorized as ‘active’, where a study invitation card was offered to a prospective participant by a healthcare professional (midwife, obstetrician, or primary care physician) in both the public and private healthcare sector. Passive methods were only utilized in the public healthcare setting and included study posters and videos in antenatal clinic waiting rooms, study invitation cards enclosed in hospital antenatal packs provided by mail, direct text messages to pregnant women, and advertisement on a designated pregnancy app used at one participating hospital. A paid social media advertising campaign on Facebook and Instagram was targeted to women between the ages of 18 and 45 located in the state of Victoria, Australia. The study team recruited eligible participants that contacted the study team directly and unsolicited. Commencement of deployment was asynchronous for different recruitment methods, with major deployment dates indicated.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6616246/v1/ccaabca464eaaf47775db15d.png"},{"id":83514130,"identity":"d2fed67d-89a4-46de-9fe7-bbb7fe770296","added_by":"auto","created_at":"2025-05-27 17:51:09","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":118269,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGenomic data analysis workflow for the BabyScreen+ study.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sup\u003e\u003cem\u003eKnown benign variants include variants classified as benign or likely benign by VCGS and/or Shariant, and/or variants that are (likely) benign with at least two stars in ClinVar. \u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003eVery common variants include variants with a frequency of more than 2% in VCGS internal data and/or gnomAD. \u003c/em\u003e\u003csup\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sup\u003e\u003cem\u003eKnown pathogenic variants include variants classified as (likely) pathogenic by VCGS, in Shariant, and/or in ClinVar. \u003c/em\u003e\u003csup\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sup\u003e\u003cem\u003eHigh impact variants include nonsense, frameshift, canonical splice site, start loss, stop loss, and large deletions and duplications. \u003c/em\u003e\u003csup\u003e\u003cem\u003e5\u003c/em\u003e\u003c/sup\u003e\u003cem\u003eVariants in the literature include missense, in-frame, and splice region variants in the Mastermind Cited Variant Reference (now known as the Indexed Variant File). \u003c/em\u003e\u003csup\u003e\u003cem\u003e6\u003c/em\u003e\u003c/sup\u003e\u003cem\u003eVariants too common for monoallelic disease (0.01% in gnomAD) or biallelic disease (0.1% in gnomAD). Mode of inheritance (MOI) is derived from the MOI of the gene in the BabyScreen+ panel in PanelApp Australia. \u003c/em\u003e\u003csup\u003e\u003cem\u003e7\u003c/em\u003e\u003c/sup\u003e\u003cem\u003eOnly heterozygous variants are allowed for monoallelic MOI. Biallelic MOI requires a homozygous or hemizygous zygosity, or else two (or more) variants in the same gene.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6616246/v1/cb81eda3abfe1b5c0d49005a.png"},{"id":83514714,"identity":"11ec14a9-cff0-4a7e-ac7c-216fa57608b9","added_by":"auto","created_at":"2025-05-27 17:59:09","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":162709,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFactors influencing participants’ decision to have genomic newborn screening.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eParticipants who consented to genomic newborn screening were asked to rate the extent to which their decision was influenced by each statement at enrolment\u003c/em\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6616246/v1/0d2a05b0758f7fd8f893cca5.png"},{"id":93201376,"identity":"32385d63-51ca-4810-aafc-91aeaf983996","added_by":"auto","created_at":"2025-10-10 07:05:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1982068,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6616246/v1/d7971068-3efc-4b20-a120-568459d27d6a.pdf"},{"id":83514138,"identity":"7561c54e-14ee-43d3-aca0-812f60ecc01c","added_by":"auto","created_at":"2025-05-27 17:51:09","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":146590,"visible":true,"origin":"","legend":"Supplementary figures and tables","description":"","filename":"BabyScreenoutcomespaperSupplementaryappendixv1clean.docx","url":"https://assets-eu.researchsquare.com/files/rs-6616246/v1/f2830d2ada815d965efcd17a.docx"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential Competing Interest.\nYvonne Bombard and Marc Clausen are co-founders of the Genetics Adviser platform. The other authors have no conflicts of interest to declare.","formattedTitle":"Genomic newborn screening: feasibility, acceptability and clinical outcomes","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNewborn screening (NBS) for rare conditions is one of the most effective public health interventions\u003csup\u003e1\u003c/sup\u003e, delivered with high uptake, quick turnaround times and at low cost. However, the increased ability to diagnose and treat rare diseases ushered in by the era of genomic and precision medicine\u003csup\u003e2,3\u003c/sup\u003e has challenged the ability of NBS programs to keep pace, with the time to include a new condition averaging nine years in the USA\u003csup\u003e4\u003c/sup\u003e. Incorporating genomic sequencing into NBS programs offers the opportunity to substantially increase the number of conditions screened and to include conditions that do not have available biochemical markers, such as those predisposing to childhood cancers\u003csup\u003e5\u003c/sup\u003e. Further, genomic sequencing provides flexibility to add or remove conditions at low incremental cost and has the potential to provide health benefit over an individual\u0026rsquo;s lifetime through reuse of data for diagnostic, screening and research purposes\u003csup\u003e6\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGenomic NBS (gNBS) raises considerable issues when implementation at population level is considered. There is little consensus on how it should be offered in terms of timing or method of consent; what testing modality or samples to use; which conditions to screen; or how to manage downstream healthcare system impacts. Despite extensive debate over the past 10 years\u003csup\u003e7\u003c/sup\u003e, there is little evidence from prospective cohorts to guide policy and implementation\u003csup\u003e8\u0026ndash;11\u003c/sup\u003e. Multiple studies are currently underway in diverse healthcare systems which will test out the feasibility of different implementation models and provide early data on patient, family and healthcare system outcomes\u003csup\u003e5\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe BabyScreen\u0026thinsp;+\u0026thinsp;study aims to address some of these questions through multidisciplinary evaluation of a prospective cohort of 1,000 newborns in a public healthcare system, with gNBS offered for 605 genes associated with early-onset, treatable childhood conditions alongside standard NBS (stdNBS)\u003csup\u003e12,13\u003c/sup\u003e. The study assessed a broad range of outcomes including feasibility of performing clinically accredited genome sequencing using dried blood spot (DBS) cards; screening outcomes compared with stdNBS; parental psychosocial outcomes and acceptability.\u003c/p\u003e"},{"header":"Results","content":"\u003ch3\u003e\u003cstrong\u003eDemographics and\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003erecruitment\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eStudy enrolment was initiated\u003csup\u003e12\u003c/sup\u003e by 1288 prospective parents, with 301 (23%) not completing enrolment, declining screening or withdrawing from the study. gNBS was completed for 1000 newborns over 16 months, of whom 523 (52%) were male and 477 (48%) female, including 13 sets of twins (Figure 1). Ancestry, geographical location and socio-economic indices of relative advantage and disadvantage of participants were similar to that of the age- and sex-matched Australian population, with a relative over-representation of higher educated individuals (Figure 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRecruitment by a healthcare professional (active recruitment) resulted in the highest number of study participants completing enrolment (667/998, 67%, Figure 3), with social media advertising the most successful passive recruitment method (190/998, 19%). Active recruitment had the lowest proportion of incomplete enrolments (Table S2).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFeasibility of genome sequencing from dried blood\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003espots\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDBS cards from 1003 newborns were processed for gNBS. Reprocessing was required for 82 (8.2%) samples due to sample-related (3.2%) or process-related (5.0%) failures (Table S3). DNA re-extraction was performed for 79 (7.9%), using new punches from the existing DBS card (50), collection of new DBS cards (7), or collection of fresh blood samples (22 samples, Table S4). Three participants declined sample recollection.\u003c/p\u003e\n\u003cp\u003eSequencing data generation failed target coverage requirements for 191 (19%) samples, requiring additional sequencing. Process improvements, including optimisation of sample quantitation methods and sequencer loading concentrations, reduced failure rates from an initial average of 28% to less than 5% (Figure S1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll re-extracted and re-processed samples were successfully reported on the second attempt. Excluding samples that required re-extraction would have led to two missed high chance results (\u003cem\u003eUNC13D, GNAS,\u0026nbsp;\u003c/em\u003eTable 1).\u003c/p\u003e\n\u003cp\u003eAverage TAT for stdNBS followed by gNBS was 24 days from sample collection (Target: 28 days, Min: 11, Max: 68, CI95: 23.5-24.5). Average TAT for gNBS was 13 days (Min: 6, Max: 56, CI95: 12.7-13.3), with 73% reported within the target of 14 days. The proportion of reports issued within target TAT increased from 65% to 81% following reduction in sequencing failure rates.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eGenomic data analysis and interpretation\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eAnalysis protocols (Figure 4) were validated using a cohort of 108 clinical cases of critically ill infants undergoing genomic testing, with 61 known low chance and 47 known high chance results\u003csup\u003e2\u003c/sup\u003e. Validation data showed \u0026gt;97% sensitivity with 46 of the known high chance cases correctly flagged. The high chance case missed by the analysis had a multi-nucleotide variant (\u003cem\u003eACAD9\u003c/em\u003e, NM_014049.4, c.1376_1381delinsCCT, p.(Lys459_Ser461delinsThrCys). This that was incorrectly annotated by the analysis software as two non-high impact variants, a known limitation. No cases were incorrectly classified as low chance by the automated system, however 32 of 61 (51%, Table S5) of known low chance cases required manual review of non-reportable variants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOf the 1000 study samples, 451 (45%) were automatically reported as low chance. In the remaining 549 (55%) cases, 1045 variants were manually reviewed, with 36 variants undergoing full assessment and 18 ultimately reported. Of the non-reportable variants, 1009 were discarded due to insufficient evidence for pathogenicity, including all copy number variants (CNVs) (Table S6). The 18 variants that underwent full assessment but were not reported were excluded for a range of reasons, including mismatched mechanism of disease or mode of inheritance, or association with adult-onset or mild disease (Tables S6 and S7).\u003c/p\u003e\n\u003cp\u003eModelling filter conditions showed an automatic low chance report rate of 82% was achievable (Table S8) but increased the likelihood of false negative results. Only reporting variants previously described as pathogenic in ClinVar would have resulted in the loss of one high chance result (\u003cem\u003eGNAS\u003c/em\u003e, Table 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHigh chance results were issued for 16 newborns (1.6%, Table 1). No discordances with stdNBS were identified. One newborn was identified as having hypothyroidism through stdNBS. gNBS provided the precise etiology (\u003cem\u003eGNAS\u003c/em\u003e variant) enabling cascade testing and surveillance for multisystem involvement. All high chance results were confirmed by orthogonal testing on new samples, with no discordances. All variants in recessive genes were confirmed in \u003cem\u003etrans.\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eClinical impact of high chance results\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eClinical impact ranged from instituting preventative measures or surveillance to active management. Nine results in three genes \u003cem\u003e(G6PD, MT-RNR1, RYR1)\u003c/em\u003e prompted preventative measures (Table 1). These were managed by the gNBS team without involvement of specialist services. Five results (\u003cem\u003eFBN1, GNAS, ENG, GJB2, DICER1)\u0026nbsp;\u003c/em\u003eled to initiation of surveillance measures which included echocardiogram, blood tests, MRI scan, audiology assessment and follow-up with specialist physicians. Two results (\u003cem\u003ePKHB, UNC13D)\u0026nbsp;\u003c/em\u003eresulted in immediate treatment (Table 1). The infant with glycogen storage disorder due to \u003cem\u003ePKHB\u003c/em\u003e variant had unrelated congenital heart disease and had been scheduled for cardiac surgery. Identification of an underlying metabolic disorder enabled appropriate multi-disciplinary management of peri-operative fasting to avoid episodes of hypoglycemia. The infant diagnosed with \u003cem\u003eUNC13D\u003c/em\u003e-related HLH was clinically well at the time of gNBS result disclosure, but immunological testing revealed early signs of immune dysregulation. The diagnosis enabled early commencement of therapy with immune modulators and proactive planning for bone marrow transplantation, which was performed at 4 months of age.\u003c/p\u003e\n\u003cp\u003eTesting in first-degree relatives resulted in 20 additional diagnoses (12 parents, eight siblings). None of the affected relatives were previously suspected of having a genetic condition, although clinical findings and family histories consistent with the diagnoses were present in four parents (\u003cem\u003eFBN1, GNAS, ENG, DICER1\u003c/em\u003e). Two participants required re-analysis of gNBS data for diagnostic purposes within the study period. One was a newborn with a low chance result who had a diagnosis of moderate bilateral sensorineural hearing loss from newborn hearing screening. Diagnostic re-analysis did not identify a genetic cause for hearing loss. The second newborn with a high chance result for \u003cem\u003eG6PD\u003c/em\u003e deficiency had diagnostic re-analysis following admission to neonatal intensive care with multiorgan failure. A re-analysis report was issued within 24 hours of the request, with no additional genetic diagnosis identified.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. High chance results reported in BabyScreen+ and their clinical impact.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"1037\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGene\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCondition\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCase number\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariant(s)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eACMG classification\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInheritance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 389px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical impact\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 1037px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevention\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cem\u003eG6PD\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 151px;\"\u003e\n \u003cp\u003eG6PD deficient haemolytic anaemia, OMIM #300908\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1 \u0026amp; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eNM_000402.4:c.1039G\u0026gt;A (p.Glu347Lys)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eClass 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eMaternal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 389px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eInformation provided on triggers of hemolytic crisis.\u003c/li\u003e\n \u003cli\u003eAlerts placed in hospital medical records and primary care physician notified.\u003c/li\u003e\n \u003cli\u003eTen family members diagnosed\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e3 \u0026amp; 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eNM_001360016.2:c.1376G\u0026gt;T (p.Arg459Leu)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eClass 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eMaternal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eNM_000402.4:c.1093G\u0026gt;A (p.Ala365Thr)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eClass 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eMaternal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eNM_001360016.2:c.542A\u0026gt;T (p.Asp181Val)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eClass 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eMaternal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cem\u003eMT-RNR1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 151px;\"\u003e\n \u003cp\u003eMitochondrial non-syndromic sensorineural hearing loss, MONDO #0010779\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eNC_012920.1:m.1494C\u0026gt;T (homoplasmic)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eClass 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eMaternal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 389px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eInformation provided on avoidance of aminoglycoside exposure\u003c/li\u003e\n \u003cli\u003eAlerts placed in hospital medical records and primary care physician notified.\u003c/li\u003e\n \u003cli\u003eOne family member diagnosed\u003c/li\u003e\n \u003cli\u003eAudiology assessment at six months of age for proband and mother\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eNC_012920.1:m.1555A\u0026gt;G (48% heteroplasmy)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eClass 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eMaternal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 389px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eInformation provided on avoidance of aminoglycoside exposure\u003c/li\u003e\n \u003cli\u003eAlerts placed in hospital medical records and primary care physician notified.\u003c/li\u003e\n \u003cli\u003eAudiology assessment recommended if concerns arise regarding hearing\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cem\u003eRYR1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eMalignant hyperthermia susceptibility 1, OMIM #145600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eNM_000540.3:c.1202G\u0026gt;T (p.Arg401Leu)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eClass 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003ePaternal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 389px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eInformation provided on avoidance of suxamethonium and volatile anesthetic agents\u003c/li\u003e\n \u003cli\u003eAlerts placed in hospital medical records and primary care physician notified.\u003c/li\u003e\n \u003cli\u003eThree family members diagnosed\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 1037px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurveillance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cem\u003eFBN1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eMarfan syndrome, OMIM #154700\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eNM_000138.5:c.5518C\u0026gt;T (p.Arg1840Cys)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eClass 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eMaternal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 389px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eEchocardiogram and regular cardiology review\u003c/li\u003e\n \u003cli\u003eTwo family members diagnosed, referred for surveillance\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cem\u003eGNAS\u003c/em\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003ePseudohypoparathyroidism 1a, OMIM #103580\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eNM_000516.7:c.476T\u0026gt;C (p.Val159Ala)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eClass 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eMaternal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 389px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eTreatment with thyroxine, endocrinology assessment\u003c/li\u003e\n \u003cli\u003eTwo family members diagnosed, referred to endocrinology\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cem\u003eENG\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eHereditary haemorrhagic telangiectasia (HHT) type 1, OMIM #187300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eNM_001114753.3:c.1310G\u0026gt;A (p.Arg437Gln)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eClass 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003ePaternal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 389px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eMRI for cerebral arteriovenous malformations. Referral to HHT clinic for ongoing surveillance.\u003c/li\u003e\n \u003cli\u003eOne family member diagnosed, referred to adult HHT clinic\u0026nbsp;\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cem\u003eGJB2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eAutosomal recessive deafness 1A, OMIM #220290\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eNM_004004.6:c.35del (p.Gly12Valfs*2)\u003c/p\u003e\n \u003cp\u003eNM_004004.6:c.583A\u0026gt;G (p.Met195Val)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eClass 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eBiparental\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 389px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eReferred for annual audiology assessments\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cem\u003eDICER1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eDICER1-related tumor predisposition, MONDO #0100216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eNM_177438.3:c.745C\u0026gt;T (p.Gln249*)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eClass 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003ePaternal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 389px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eReferred to pediatric oncologist for regular surveillance\u003c/li\u003e\n \u003cli\u003eOne family member diagnosed, referred to adult familial cancer center\u0026nbsp;\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 1037px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cem\u003ePHKB\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003ePhosphorylase kinase deficiency of liver and muscle, OMIM #261750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eNM_000293.3:c.1127-2A\u0026gt;G (homozygous)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eClass 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eBiparental\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 389px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eAdmission to hospital for unrelated cardiac surgery, protocol to avoid hypoglycemia during fasting followed\u003c/li\u003e\n \u003cli\u003eLiver ultrasound\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cem\u003eUNC13D\u003c/em\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eFamilial hemophagocytic lymphohistiocytosis (HLH) 3, OMIM #608898\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 227px;\"\u003e\n \u003cp\u003eNM_199242.2:c.817C\u0026gt;T (p.Arg273*)\u003c/p\u003e\n \u003cp\u003eNM_199242.3:c.627del (p.Val210Trpfs*39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eClass 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eBiparental\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 389px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eImmunological tests abnormal at time of results\u003c/li\u003e\n \u003cli\u003eAdmitted to hospital for treatment with steroids and Emapalumab\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eBone marrow transplant\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Sample reprocessed by taking new punches from the existing DBS card after initial laboratory processing batch failure\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003e Previously described in the literature only (identified via Genomenon Mastermind)\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ec\u003c/sup\u003e Sample reprocessed by collecting a new blood sample after initial poor sample quality\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003ePsychosocial outcomes and attitudes towards scr\u003c/strong\u003e\u003cstrong\u003eeening\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eOut of 1012 parents who consented to gNBS, 998 (99%) completed a survey (Figure 1). We conducted 48 interviews with 46 birth parents and three partners. This included 22 pre-test gNBS acceptors, two gNBS decliners, 17 low chance results recipients, and eight high chance results recipients.\u003c/p\u003e\n\u003cp\u003eMost survey respondents (80%) indicated they consented \u0026lsquo;immediately\u0026rsquo; using Genetics Adviser, with the decision perceived as either \u0026lsquo;easy\u0026rsquo; or \u0026lsquo;very easy\u0026rsquo; (Table S10). Only 8% found decision-making difficult. Interviewees valued Genetics Adviser, with education content generally used to reaffirm decisions, provide guidance on what to consider, understand the impact of their decision, or facilitate discussions with partners.\u003c/p\u003e\n\u003cp\u003eInterviewees also described how they considered clinical, psychosocial, and practical factors in gNBS decisions. They weighed up benefits of screening, the types of conditions being screened, potential barriers, and their ability to navigate results.\u003c/p\u003e\n\u003cp\u003eDecisions to have gNBS were most strongly influenced by a desire \u0026ldquo;To know what to expect for my baby\u0026rsquo;s future\u0026rdquo; (77% survey respondents) (Figure 5). The main influence for declining gNBS (10 surveys completed) was concern about the result having negative impact on parents (80%) (Table S11).\u003c/p\u003e\n\u003cp\u003eAt enrolment, the median trait anxiety score was 32.63 (IQR 28.42 \u0026ndash; 38.94). Most survey respondents scored under the cut-off for probable clinical state anxiety at enrolment (80%), and at the T3 survey (85%, n=422). Post-result return, decision regret was very low (Median 0, IQR 0-10, n=500). Parents of infants who received a high chance result were asked to complete an adapted version of the Genomics Outcomes Scale (GOS). Five participants (31%) responded to the GOS scale, with a mean empowerment score of 25.6 (CI 23.07-28.13) out of 30. Interviewees who received a low chance gNBS result reported positive impacts such as reassurance. Interviewees who received a high chance result valued results due to their clinical utility. Prompt genetic counselling and access to high quality information facilitated adaptation.\u003c/p\u003e\n\u003cp\u003eMost respondents (82%) would choose to have gNBS for a future baby, and 92% would recommend it to a family member (Table S12). All but one respondent thought that gNBS should be available to all parents, and 97% thought it should be publicly funded.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe BabyScreen\u0026thinsp;+\u0026thinsp;study provided screening for disease-causing variants in 605 genes associated with severe, early-onset, treatable childhood conditions in a prospective cohort of 1,000 newborns. We found 1.6% of newborns had an increased chance of a screened condition, leading to a range of interventions from preventative measures and surveillance through to bone marrow transplant. Only one of these diagnoses was identified by stdNBS, highlighting the ability of gNBS to identify a much broader range of actionable rare disorders. Parental attitudes towards gNBS were positive with minimal decisional regret.\u003c/p\u003e \u003cp\u003eWe have demonstrated feasibility of delivering clinically accredited gNBS within a public healthcare system using a scalable model designed to be minimally disruptive to the healthcare system and to families. The model was informed by prior studies\u003csup\u003e5,14\u0026ndash;16\u003c/sup\u003e, as well as public and professional consultation including focus groups\u003csup\u003e17,18\u003c/sup\u003e, key informant interviews\u003csup\u003e19\u003c/sup\u003e and discrete choice experiments with over 2,000 members of the Australian public\u003csup\u003e20\u003c/sup\u003e. Our model includes education and consent using online tools during pregnancy; use of existing DBS collection pathways; and laboratory processes that integrate with stdNBS and balance automation and manual review of genomic data to minimize false positive results. The use of clinically accredited genome sequencing and analysis facilitates reuse of the data for diagnostic purposes and for further age-appropriate screening\u003csup\u003e21\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWhile prior studies have mostly elected to offer gNBS in the newborn period using trained personnel, concerns have been raised about the scalability and appropriateness of these models, given the complexity of information required for gNBS consent and the potential impact on consent for stdNBS\u003csup\u003e5,22\u003c/sup\u003e. The stated preference, of both parents and healthcare providers, for information provision and consent during pregnancy\u003csup\u003e18,19,23\u003c/sup\u003e led us to implement a model where gNBS was introduced during pregnancy using multi-modal approaches. An extensively evaluated online digital platform\u003csup\u003e24,25\u003c/sup\u003e provided education and decision support, including case vignettes and value clarification exercises. The resultant cohort is diverse and largely reflective of the Australian population, with 80% of parents reporting being able to make an \u0026lsquo;easy\u0026rsquo; decision to have gNBS. However, the temporal separation of consent from sample collection in this model raises new challenges such as the need to ensure ongoing consent and to develop laboratory protocols for accurate sample identification. The overall model requires further evaluation at scale to ensure it supports equitable access, particularly to families disadvantaged by socioeconomic or cultural and linguistic factors. Further consideration also needs to be given about how information provision and consent will integrate with other screening tests offered in pregnancy, notably reproductive carrier screening where there is considerable overlap in the conditions screened\u003csup\u003e13,26,27\u003c/sup\u003e, potentially creating confusion for healthcare providers and potential parents alike. This issue is highlighted by the high chance result for \u003cem\u003eUNC13D\u003c/em\u003e-related HLH in our cohort where the parents had completed expanded reproductive carrier screening for 200 genes. This test included two more frequent genetic causes of familial HLH but excluded \u003cem\u003eUNC13D\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eSimilar to other studies, we found using DBS cards for gNBS was feasible, with 2.4% of samples requiring reprocessing to obtain results due to sample-related failures\u003csup\u003e28\u003c/sup\u003e. Taking additional punches from the original DBS card addressed most reprocessing requirements, negating the need for sample recollection. Opting not to reprocess would have resulted in two missed high chance results, including that of HLH (\u003cem\u003eUNC13D\u003c/em\u003e).\u003c/p\u003e \u003cp\u003eThe average time to report of 13 days compares favorably with stdNBS and is faster than the time to report from other studies, which ranged from 32.5\u003csup\u003e11\u003c/sup\u003e to 64 days\u003csup\u003e8\u003c/sup\u003e. While we elected to perform gNBS after stdNBS to minimize disruption, we envisage the two occurring in parallel. Achieving clinically meaningful turnaround times for gNBS is important as many of the conditions are immediately actionable, as demonstrated in this cohort by the newborn diagnosed with glycogen storage disease who had forthcoming cardiac surgery for unrelated reasons. Knowledge of the underlying condition allowed appropriate planning of peri-operative care under the guidance of a metabolic physician to avoid fasting hypoglycaemia.\u003c/p\u003e \u003cp\u003eA high degree of automation will be required to scale gNBS to public health programs but careful calibration is needed to minimize false positive and negative results\u003csup\u003e5\u003c/sup\u003e. We adopted an integrated approach, incorporating stdNBS results and multi-disciplinary review prior to reporting. Adherence to pre-defined variant lists can lead to false negatives\u003csup\u003e8\u003c/sup\u003e and would have likely led to at least one missed result in our cohort as well. Similarly, automation can miss complexities, such as common \u003cem\u003ein cis\u003c/em\u003e variants in genes with recessive inheritance\u003csup\u003e11\u003c/sup\u003e, increasing false positives with significant impact on families and the workforce when considered at scale (Table S7). Our analysis approach mitigates these common pitfalls; our rate of high chance results (1.6%) is comparable with that of other studies\u003csup\u003e8,11\u003c/sup\u003e despite hundreds more genes being analyzed\u003csup\u003e13\u003c/sup\u003e (Table S13). While the rate of manual review required in our setup currently cannot be considered scalable, we have shown that a small number of simple changes can substantially increase automation without major compromises to accuracy (Table S8). Continual refinement of automation pipelines and the integration of data generated by pilot gNBS studies will optimize this balancing act moving forwards\u003csup\u003e29\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWe identified a wide range of conditions, with G6PD deficiency the commonest finding. Just over half of the high chance results were managed without involvement of specialist services. The remainder required input from multiple specialists and prompt access to other investigations. In addition, 20 relatives received a molecular diagnosis through cascade testing. As gNBS scales, there will be a need to systematically develop dedicated downstream pathways that integrate results, investigations and referrals to a broad range of pediatric and adult services with adequate psychosocial support for families. Equitable access to these pathways, including for regional and remote communities, will be a key consideration for public health programs.\u003c/p\u003e \u003cp\u003eProspective parents and the general public express positive views towards gNBS, while health professionals are typically more cautious\u003csup\u003e5,30\u0026ndash;35\u003c/sup\u003e. Many concerns have been raised about the potential psychosocial risks of sequencing newborns, including effects on parent-child bonding, perceived child vulnerability and self and partner blame\u003csup\u003e36\u003c/sup\u003e. In this cohort, parents held positive views following gNBS, generally found the decision easy to make and supported future public funding. We found no evidence of adverse psychosocial outcomes such as increased anxiety or decision regret, consistent with smaller previous cohorts. \u003csup\u003e14,37,38\u003c/sup\u003e Rather, participants reported feeling empowered. Even those with a high chance result reported adapting to the information through access to prompt high-quality information.\u003c/p\u003e \u003cp\u003eThe limitations of this study included the relatively small cohort size and recruitment over an 18-month period. This means that the laboratory and clinical systems were not tested at the scale that would be required to deliver a national screening program. For the population of Australia this would require 300,000 samples to be processed per annum and over 4,500 high chance results to be returned in a variety of settings, necessitating substantial investment in infrastructure, workforce development and national consistency. In addition, there was an over-representation of highly educated parents and targeted efforts would be required to ensure equity of access both to screening and to downstream care pathways. Other areas that remain underexplored include the potential for the data to be reused for clinical and screening purposes throughout an individual\u0026rsquo;s lifetime. While we were able to demonstrate the benefits of data reuse for diagnostic purposes in two infants within a relatively short period of time, large-scale implementation of a data reuse model would include further considerations of consent models, infrastructure requirements and integration with electronic medical records for example.\u003c/p\u003e \u003cp\u003eIn conclusion we have demonstrated feasibility and acceptability of gNBS in a public healthcare system, using a model that integrates with the existing stdNBS program and delivers clinically accredited results with rapid turnaround times. While we provide comprehensive multidisciplinary evaluation, much larger longitudinal studies are now required to demonstrate scalability to population level and assess other outcome measures such as equity, cost-effectiveness and long-term impacts on families and healthcare systems.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy setting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe previously published study protocol\u003csup\u003e12\u003c/sup\u003e is summarized here. BabyScreen+ was designed to evaluate the acceptability and feasibility of gNBS in a prospective cohort of 1000 newborns from the state of Victoria, Australia, using clinically accredited genome sequencing. The study was funded by the Australian Government\u0026rsquo;s Genomics Health Futures Mission (MRF2015937) without any restrictions or encumbrances. The funding agency was not involved in any aspects of the study including design, analysis and reporting. Ethics approval was obtained from the Royal Children\u0026rsquo;s Hospital Research Ethics Committee (HREC/91500/RCHM-2023). All laboratory procedures, data analysis, and reporting were performed by Victorian Clinical Genetics Services (VCGS), a wholly owned not-for-profit subsidiary of the Murdoch Children\u0026rsquo;s Research Institute, in Melbourne, Australia. VCGS is responsible for the delivery of stdNBS for the state of Victoria, and DBS cards were accessed with permission from participants and the Victorian State Government. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRecruitment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003egNBS was offered, free of charge, during the third trimester of pregnancy in private and public healthcare settings. Recruiting healthcare professionals attended an education session and were provided with study cards, posters and videos. The study was also advertised via social media, SMS and a pregnancy app. Birth parents could enroll if aged 16 or over; planning to give birth in Victoria, Australia; and intending to participate in stdNBS. Enrolment was ideally in pregnancy but was available up until two weeks after birth. Study cards and advertising materials contained a QR code connecting potential participants to the online platform Genetics Adviser, which provided education and decision support\u003csup\u003e24,25\u003c/sup\u003e. Participants consented separately to research and to gNBS. Contact with a genetic counsellor was available at any stage. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDNA extraction and sequencing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFollowing completion of stdNBS, DNA was extracted from four 3mm DBS punches using the Mag-Bind DNA Blood and Tissue kit (Omega Biotek). PCR-free genome sequencing libraries were created using the PCR-free DNA prep kit (Illumina) and sequenced using a 2x150 bases paired end read configuration to an average depth of 30x on a NovaSeq X Plus instrument (Illumina). Sequencing library quantitation was initially performed using the Qubit dsDNA High Sensitivity kit (Thermo Fisher Scientific), and was transitioned to real-time PCR based library quantitation using the KAPA Library Quantification kit for Illumina Platforms (Roche) on a QuantStudio 7 Pro instrument (Thermo Fisher Scientific) as per standard protocol, following troubleshooting of sequencing data issues.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGenomic data analysis and interpretation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData analysis and interpretation were performed using the Dragen and Emedgene (Illumina) analysis tools, with custom in-house filter configuration (Table S1) designed to identify variants for potential reporting in 605 genes associated with early-onset treatable childhood conditions. Details of the gene selection process are previously published\u003csup\u003e13\u003c/sup\u003e. Variants classified as likely pathogenic or pathogenic based on ACMG guidelines\u003csup\u003e39\u003c/sup\u003e and consistent with the relevant mode of inheritance were considered. Carrier status, adult-onset or mild forms of conditions, and variants of uncertain significance were not reported.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReturn of results and clinical management\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResults were designated either \u0026ldquo;low chance\u0026rdquo;, where no reportable variants were identified, or \u0026ldquo;high chance\u0026rdquo;. For low chance results, participants were informed via email and SMS of result availability on Genetics Adviser. Genetic counselling was available on request. For high chance results, parents were contacted by a genetic counsellor to discuss the result, and to arrange clinical geneticist appointment, followed by additional testing (including confirmation and segregation of reported variants), and referral to specialist services as needed.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipant surveys\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipating birth parents provided pregnancy and demographic information (T1) and completed a research survey (T2) as part of enrolment, with a further optional survey three months post-result (T3). Pregnancy and demographic variables were compared with age and sex-matched Australian Government Census data, or the Australian Institute of Health and Welfare\u0026rsquo;s National Perinatal Data Collection. For participants who consented to gNBS, study specific multiple-choice survey items were used to measure the difficulty of decision making; reasons for choosing to have gNBS; acceptability; attitudes towards gNBS; and preferences for having gNBS for future children. Trait anxiety was measured at enrolment using the State-Trait Anxiety Inventory trait anxiety scale (STAI-T). State anxiety was measured using the short-form six-item STAI-6 at enrolment and three months post-result\u003csup\u003e40\u003c/sup\u003e. The Decision Regret Scale\u003csup\u003e41\u003c/sup\u003e was administered three months post-result. For participants who chose not to have gNBS, reasons for declining were identified at enrolment using a study-specific matrix survey comprising 11 options rated on a five-point Likert scale. \u0026nbsp;Item logic was used in the data collection platform to administer the Genomics Outcome Scale (GOS) in the T3 survey to participants with an infant who received a high chance result. The Genomics Outcome Scale is a patient reported outcome measure (PROM) for clinical genetics services\u003csup\u003e42\u003c/sup\u003e. The GOS consists of 6-items with 5-point Likert scale responses options ranging from Strongly Disagree to Strongly Agree. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipant interviews\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA random sample of participants who accepted gNBS were invited to take part in interviews prior to receiving their results and/or approximately 3 months after receiving a low chance result. These participants were purposively sampled to ensure that participants were spread across age groups, study sites, and ancestry. We also invited all participants who declined gNBS or received a high chance result.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSemi-structured interviews were conducted via Zoom or by phone and were audio-recorded for transcription. \u0026nbsp;An external transcription company transcribed all audio recordings verbatim, the researcher conducting the interviews then removed identifying details from the transcripts and assigned pseudonyms to all interviewees. Written notes were used for two interviews due to technical issues associated with those recordings. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analysis of participant survey and recruitment data were done using StataSE 18, and analysis of laboratory data were performed as outlined in the Supplementary Appendix. Turnaround times (TAT) for samples that required recollection were measured from receipt of the new sample. Qualitative data were analyzed using content analysis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study is governed and administered by the Murdoch Children\u0026rsquo;s Research Institute (MCRI), Melbourne, Australia. All genetic testing is performed by VCGS, Melbourne, Australia, a wholly owned not-for-profit subsidiary of MCRI. VCGS is clinically accredited (NATA/RCPA) to ISO15189;2012 to carry out genetic and genomic testing. The project has received ethics approval from the Royal Children\u0026rsquo;s Hospital Melbourne Human Research Ethics Committee (main BabyScreen+ protocol: HREC/91500/RCHM-2023; key informant interviews: HREC/90929/RCHM-2022; and focus groups and DCE: HREC/91392/RCHM-2022). \u0026nbsp;\u003c/p\u003e\n\u003cp id=\"_Toc197440027\"\u003e\u003cstrong\u003eF\u003c/strong\u003e\u003cstrong\u003eunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe BabyScreen+ study was funded by the Australian Government\u0026rsquo;s Genomics Health Futures Mission (MRF2015937) without any restrictions or encumbrances. The funding agency was not involved in any aspects of the study including design, analysis and reporting. The research conducted at the Murdoch Children\u0026apos;s Research Institute was supported by the Victorian Government \u0026apos;s Operational Infrastructure Support Program. J.Ch. is generously supported by The Royal Children\u0026apos;s Hospital Foundation as The Chair in Genomic Medicine.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYvonne Bombard and Marc Clausen are co-founders of the Genetics Adviser platform.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe other authors have no conflicts of interest to declare.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data supporting the findings of this study are available within the paper and its Supplementary Information. Clinically reported variants have been submitted to ClinVar under accession numbers SUB15105434, SUB15105434, SCV005399527.1, SCV003921943.3, SCV005086718.1, SUB15105434, SCV001244783.2, SCV005400334.1, SCV005398282.1, SUB15105434, SCV005400615.1, SCV005400606.1 (Table S9). Any additional data are available from the corresponding author upon reasonable request. Data are located in controlled access data storage at the Murdoch Children\u0026rsquo;s Research Institute.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCenters for Disease \u0026amp; Prevention. 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The development of a six-item short-form of the state scale of the Spielberger State-Trait Anxiety Inventory (STAI). \u003cem\u003eBr J Clin Psychol\u003c/em\u003e \u003cstrong\u003e31\u003c/strong\u003e, 301-306 (1992).\u003c/li\u003e\n\u003cli\u003eBrehaut, J.C.\u003cem\u003e, et al.\u003c/em\u003e Validation of a decision regret scale. \u003cem\u003eMed Decis Making\u003c/em\u003e \u003cstrong\u003e23\u003c/strong\u003e, 281-292 (2003).\u003c/li\u003e\n\u003cli\u003eGrant, P.E., Pampaka, M., Payne, K., Clarke, A. \u0026amp; McAllister, M. Developing a short-form of the Genetic Counselling Outcome Scale: The Genomics Outcome Scale. \u003cem\u003eEur J Med Genet\u003c/em\u003e \u003cstrong\u003e62\u003c/strong\u003e, 324-334 (2019).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6616246/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6616246/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIncorporating genomic sequencing into newborn screening (NBS) will dramatically increase the number of detectable conditions but evidence is needed to guide policy. The BabyScreen\u0026thinsp;+\u0026thinsp;study screened 1,000 newborns for variants in 605 genes associated with early-onset, severe, treatable conditions using whole genome sequencing performed on dried blood spot cards. Sixteen infants (1.6%) were identified as having high chance results. Of these, only one was detected by standard NBS. Average time to genomic NBS result was 13 days. Clinical impact ranged from instituting preventative measures or surveillance to active management, including transplantation. Twenty relatives received a diagnosis following cascade testing. Median parental decisional regret was low (median 0, IQR 0\u0026ndash;10); \u0026gt;99% of participants thought gNBS should be available to all parents. Our study demonstrates the feasibility of clinically accredited gNBS, using a scalable model that is highly acceptable to parents. Future research is needed to address issues of scalability and equity.\u003c/p\u003e","manuscriptTitle":"Genomic newborn screening: feasibility, acceptability and clinical outcomes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-27 17:51:04","doi":"10.21203/rs.3.rs-6616246/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-medicine","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"nm","sideBox":"Learn more about [Nature Medicine](http://www.nature.com/nm/)","snPcode":"","submissionUrl":"","title":"Nature Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Research","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"ec757606-e376-4bb0-97b3-8885c1992503","owner":[],"postedDate":"May 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":48908600,"name":"Health sciences/Health care/Paediatrics"},{"id":48908601,"name":"Health sciences/Health care/Public health/Population screening"}],"tags":[],"updatedAt":"2025-10-10T07:05:33+00:00","versionOfRecord":{"articleIdentity":"rs-6616246","link":"https://doi.org/10.1038/s41591-025-03986-z","journal":{"identity":"nature-medicine","isVorOnly":false,"title":"Nature Medicine"},"publishedOn":"2025-10-09 04:00:00","publishedOnDateReadable":"October 9th, 2025"},"versionCreatedAt":"2025-05-27 17:51:04","video":"","vorDoi":"10.1038/s41591-025-03986-z","vorDoiUrl":"https://doi.org/10.1038/s41591-025-03986-z","workflowStages":[]},"version":"v1","identity":"rs-6616246","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6616246","identity":"rs-6616246","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}