Integrating Newborn Genetic Screening with Traditional Screening to Improve Newborn Screening

Integrating Newborn Genetic Screening with Traditional Screening to Improve Newborn Screening | 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 Research Article Integrating Newborn Genetic Screening with Traditional Screening to Improve Newborn Screening Shuai Men, Zhiwei Wang, Xinxin Tang, Shuang Liu, Shuaimei Liu, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3995451/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Traditional newborn screening (NBS) for inborn errors of metabolism (IEM) and deafness has limitations due to the detection of fewer genetic disorders and variants, higher false-positive rates, and longer detection periods. This study aimed to explore the clinical validity of newborn genetic screening (NBGS) in newborns with IEM and deafness. Methods: We retrospectively enrolled 223 cases screened for IEM by tandem mass spectrometry (MS/MS)-next-generation sequencing (NGS), including 55 positive, 68 suspected positive, and 100 negative cases. Additionally, 196 cases screened for deafness were enrolled, including 96 variant-positive and 100 negative cases. Dry blood spot samples from the newborns were used for NBGS. Results: For IEM, NBGS detected 34 positives in 55 positive cases with a sensitivity of 61.8% (34/55), whereas variants were not detected in 21 cases. Four additional positive cases were found, including one at risk of glucose-6-phosphate dehydrogenase deficiency and three at risk of deafness. The diagnostic time observed between the two methods exhibited a significant difference: 13 days for NBGS and 35 days for MS/MS-NGS. For deafness, the consistency in the positive results between the two methods was 96.9% (93/96). Unexpectedly, three mitochondrial gene ( MT-RNR1 ) heterogeneous variants (m.1555A>G and m.7445A>G) were not detected by NBGS. We also detected nine variants out of 100 negative cases, including seven GJB2 (c.109G>A), one GJB3 (c.547G>A), and one MYO15A (c.10250_10252delCCT), with a 9% (9/100) detection rate by NBGS. Conclusion: As a novel screening method for newborns, NBGS can detect more gene variants, reduce the false-positive rate, and shorten the diagnostic cycle. Our research provides a foundation for the clinical application of NBGS. Newborn screening Tandem mass spectrometry Newborn genetic screening Inborn error of metabolism Deafness Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Medical screening tests are designed to detect diseases early in the pre-symptomatic phase to reduce the morbidity and mortality. Newborn screening (NBS) is a successful public health program that can detect inborn errors of metabolism (IEM) as early as possible, thus effectively reducing the incidence and mortality of IEM through early detection and intervention [ 1 , 2 ]. The early detection and timely treatment of newborns with IEM through NBS have emerged as a global imperative. Over the past few decades, biochemical techniques for the detection of specific metabolites in dry blood spots (DBS) have played an important role in the screening of neonatal genetic disorders. Initially, NBS was used only to detect phenylketonuria (PKU). With the evolution of technology, NBS has improved and an increasing number of IEM are being screened [ 3 – 5 ]. Currently, NBS based on tandem mass spectrometry (MS/MS) can detect biochemical markers of over 40 different diseases [ 6 – 9 ], which allows NBS programs to add more diseases at low cost and better efficiency. However, the clinical presentation of IEM is complex and varied, and its diagnosis often requires auxiliary tests such as the detection of gene variants. In addition, MS/MS has a high false-positive rate and positive predictive value [ 10 – 12 ]. In recent years, many scientific research institutions have applied genetic testing for neonatal genetic disease screening [ 13 – 15 ]. At the genetic level, dozens to thousands of diseases can be detected in a single test, favoring the development of a screening method for neonatal genetic disorders. With advances in genetic testing technology, the application of next-generation sequencing (NGS) in NBS is becoming more and more important [ 16 – 18 ]. ​Because of the wide range of applications of NGS, NBS is no longer limited to screening for IEM and can include additional neonatal genetic disorders and even certain genetic disorders without specific metabolites, such as deafness and spinal muscular atrophy [ 13 ]. Similar to MS/MS, NGS offers the possibility of screening more diseases at a lower cost per disease [ 19 ]. NGS, as a genetic screening method, is performed mainly through gene panels and genome sequencing (whole exome sequencing [WES] and whole genome sequencing [WGS]), which may significantly expand the screening of newborns for genetic disorders. Since its introduction, NGS has been rapidly and extensively used in research and clinical applications, particularly NBS, where it has shown potential value [ 20 – 22 ]. The most representative research is the BabySeq exome sequencing program and newborn exome sequencing for universal screening (NC NEXUS) exome sequencing program in the United States for newborn disease detection [ 23 – 25 ]. The aforementioned studies have demonstrated the promising potential of genome sequencing in NBS, as it enables the detection of diseases and variants that are beyond the reach of conventional NBS methods. However, the use of WES as a first- or second-line diagnostic test is still controversial [ 26 – 28 ], and it is still difficult to incorporate this technology into routine screening. In addition, no effective treatments have been identified for many diseases. The gap between diagnostic capacity and effective treatment means that many identified diseases may not satisfy the criteria for inclusion in NBS. A targeted gene panel is used in the genetic screening of newborns [ 29 , 14 ], which can be designed “as required” to incorporate disease-related genes of interest. Targeted gene panels are now being incorporated into routine genetic screening in a growing number of countries and regions around the world, and diverse genes can be included in the targeted gene panels [ 17 , 18 , 21 , 30 ], but these panels play a role in diagnosis after MS/MS screening. How to use a panel as a genetic screening program for newborns in clinical practice still needs to be explored. This study aimed to explore the clinical application value and feasibility of genetic screening by comparing traditional screening with genetic screening based on retrospective data from 223 cases with IEM and 196 with deafness from 2019 to 2022. We hope our findings can contribute to the development of an improved screening strategy for neonatal IEM and deafness. Materials and methods Population and sample collection This study was conducted at the Lianyungang Maternal and Child Health Hospital. Newborns born between January 2018 and December 2022 were screened, including the IEM group and the deafness group. In this study, 223 dried blood spot samples (from 130 males and 93 females) were collected from the IEM group, including 55 positive cases (clinically confirmed cases), 68 suspected positive cases (both the initial and recall screening values were abnormal, but the cases were not confirmed), and 100 negative cases (initial screening values were normal). Additionally, 196 dried blood spot samples (from 98 males and 98 females) were collected from the deafness group, including 96 variant-positive and 100 negative cases. The 100 negative cases were diagnosed with MS/MS and deafness, both of which were negative. The workflow of this study is illustrated in Fig. 1 . This study was approved by the Ethics Committee of Lianyungang Maternal and Child Health Hospital and written informed consent was obtained from all parents or guardians of the newborns before the screening. MS/MS-NGS for IEM Dried blood spots were collected from all newborns 72 h after birth on filter papers (903, Hangzhou Matridx Biotechnology Co., Ltd.). MS/MS-NGS: MS/MS was used to detect the biochemical indicators, and newborns were further investigated to diagnose the diseases by NGS (panel), as described in our previous study [ 30 ]. Newborn diseases detected by MS/MS-NGS included 56 common IEM with 86 genes (Supplementary Table S1 ). Genomic DNA was extracted from DBS or peripheral blood obtained from the patients and their parents using the Qiagen Blood DNA Mini Kit (Qiagen, Hilden, Germany). Target region sequences were enriched by multiple-probe hybridization using the SureSelect Human Exon Sequence Capture kit (Agilent, USA) and purified using Agencourt AMPure XP Beads (Beckman Coulter, USA). The purified product was treated according to the operation instructions of TruePrep DNA Library Prep Kit V2 for Illumina (Vazyme Biotech), and a special index was added using the TruePrep Index Kit V2 for Illumina (Vazyme Biotech). The library was analyzed using a Qubit 2100 Bioanalyzer (Agilent High Sensitivity DNA Kit, Agilent, USA), and a quantitative kit (Illumina DNA Standard Primer Premix Kit, Kapa, USA) was used for accurate library quantification. Massive parallel sequencing was performed using a HiSeq 2500 platform (Illumina, USA) with a mean sequencing depth of 100× coverage. Flow-through hybridization for deafness Thirteen variants of four common deafness genes were detected by flow-through hybridization, including GJB2 (c.35 delG, c.155 delTCTG, c.176 del16, c.235 delC, c.299 delAT), SLC26A4 (c.IVS7-2A > G, c.2168 A > G, c.1229C > T), MT-RNR1 (m.1555 > G, m.1494C > T, m.7445 A > G, m.12201 T > C), and GJB3 (c.538C > T). Genomic DNA was extracted from DBS or peripheral blood samples for polymerase chain reaction (PCR) amplification. The PCR products were thermally denatured into single-stranded DNA, which was then hybridized to low-density gene chip probes. Finally, the results were interpreted using chemical coloration. NBGS for newborns The NBGS panel included 112 common genetic diseases with 246 genes (Supplementary Table S2 ). The extracted genomic DNA was broken into 100–500 bp fragments by enzyme digestion. Then, these 150–200 bp fragments were separated using magnetic beads and subjected to end repair. "A" tail was added at 3' ends of the DNA to complete the DNA library construction. The DNA library was subjected to fragment size and concentration measurement using an Agilent 2100 Bioanalyzer (Agilent Technologies) and BMG. After "A" tailing and ligation, a customized NAD probe was used to capture the target region sequences, followed by pooling and quantification of the hybridization library. The pooled library was then subjected to single-chain cyclization and rolling-circle replication. After the cyclized library was constructed, DNA nanoball was sequenced (PE100 + 10) using the high-throughput gene sequencer MGISEQ-2000 with a mean sequencing depth of 100× coverage. An in-house verified variant calling pipeline was used to analyze single nucleotide variants, small insertions and deletions, and copy number variants (CNV) including CNVs involving 2 or more continuous exons in DMD [ 31 ], exon 7 deletion of SMN1 [ 32 ] and common CNVs involving HBA1/HBA2/HBB [ 33 ]. Bioinformatics analysis Raw high-throughput sequencing data were converted from Bcl to Fastq format by Illumina bcl2fastq, and then the sequencing reads were aligned with the NCBI human genome reference sequence (hg19/GRCh37) after low-quality filtering. The frequency of variants in the normal population was obtained from databases, including gnomAD (version 2.1.1, https://gnomad.broadinstitute.org ), 1000 Genome Project database (version 2015, http://www.1000genomes.org/ ), and dbSNP (version 2.0.1, https://www.ncbi.nlm.nih.gov/projects/SNP/ ). The databases such as ClinVar (version 2021, https://www.ncbi.nlm.nih.gov/clinvar/ ), OMIM (version 2023, http://www.omim.org ), and Human Gene Mutation Database (version 2023.1, http://www.hgmd.cf.ac.uk/ac/index.php/ ) were used to determine variant pathogenicity where appropriate. The biological function of the variants was predicted using bioinformatics software, including SIFT (version 2022, https://sift.bii.a-star.edu.sg ), PolyPhen-2 (version 2, http://genetics.bwh.harvard.edu/pph2 ), PROVEAN (version 1.1, http://provean.jcvi.org/index.php ), and Mutation Taster (version 2021, https://www.mutationtaster.org/ ), to further assess the possible pathogenicity. Interpretation of the pathogenicity of the novel variants was performed according to the standards and guidelines of the American College of Medical Genetics and Genomics [ 34 ]. Sanger sequencing Positive variants were verified by Sanger sequencing. Genomic DNA was extracted from DBS or peripheral blood samples and variants were amplified using specific primers. PCR was performed using the AmpliTaq Gold 360 Master Mix (ABI, USA). The PCR products were purified using ExoSAP-IT (ABI, USA), and sequenced and analyzed using a 3500Dx Genetic Analyzer (Thermo Fisher, Waltham, USA). Results Comparison of MS/MS-NGS and NBGS for IEM A total of 223 DBS were collected from newborns whose MS/MS-NGS results were positive (55), suspected positive (68), and negative (100). The 55 positive cases included 31 cases of amino acid metabolism (AAM), 14 organic acid metabolism (OAM), and 10 fatty acid metabolism (FAM) disorders. A total of 223 DBS were subjected to NBGS. The detection results showed that NBGS could accurately detect the known variants in MS/MS-NGS positive cases, and the consistency in the positive results between both methods was 61.8% (34/55) (Fig. 2A). Of the 34 positive cases detected by NBGS, 18 were AAM, eight were OAM, and eight were FAM. The detection rates for AAM, OAM, and FAM were 58.1% (18/31), 57.1% (8/14), and 80% (8/10), respectively (Fig. 2B). Of the 21 cases with inconsistent results using both methods, eight positive results were not detected by NBGS, including four cases of PKU, two cases of 3-methylcrotonyl-coenzyme A carboxylase deficiency, and one case of isolated hypermethioninemia and isovaleric acidemia. In the remaining 13 cases, NBGS detected a variant (Fig. 2A). For the 21 inconsistent results, we found that the variants were either of unknown significance or in introns, both of which were excluded from NBGS (Supplementary Table S3). Regarding the reporting time of the two methods, due to the traditional MS/MS-NGS screening being divided into two steps, the final results can only be obtained within 9–139 days (median of 35 days). In contrast, NBGS typically provides results within 13 days. Therefore, NBGS can accurately detect the variants in a shorter time (Supplementary Fig. 1). The study enrolled 68 cases with suspected positive results. Their initial MS/MS screening values were abnormal, and after recall and retesting, the results were still abnormal; however, they were not confirmed positive through clinical differential diagnosis or genetic testing in the end. Twenty-six cases with suspected positive were found to have a variant by NBGS. For the 100 negative cases enrolled, their initial MS/MS screening values were abnormal; after recall and retesting, the results were normal. Among these, 23 cases were identified by NBGS to have a variant. In addition, 39 pathogenic or likely pathogenic variants were detected in 21 suspected positive and negative cases. We identified that 29.2% (49/168) of individuals carry a specific variant in the suspected positive and negative cases, and the most commonly detected genes were DUOX2, MCCC1 , PAH, MATIA , and ATP7B (Fig. 2C). Other genes detected by NBGS in newborns with IEM Both MS/MS-NGS and NBGS involve screening for known disease-causing gene variants. However, NBGS can screen more variants than traditional MS/MS-NGS. The count of carried additional variants was 62 (27.8%, 62/223). There were 16, 10, and 36 variant carriers among the positive, suspected positive, and negative cases, respectively (Fig. 3A). Other genes most commonly detected by NBGS were GJB2 , SCL12A3 , SCL12A3 , and HBA1/HBA2 (Fig. 3B). Among the other genes, we found four positive cases. One case of incomplete dominant variation (c.406C>T) in the G6PD gene (X-linked incomplete dominant inheritance) was associated with classic glucose-6-phosphate dehydrogenase deficiency in the negative cases. The initial MS/MS results of this patient showed normal biochemical indicators. Among the remaining three cases, one patient was homozygous for a variant (c.109G>A) of the GJB2 gene associated with deafness. One patient was heterozygous for a dominant variant (c.547G>A) of the GJB3 gene associated with deafness. One patient was heterozygous for a homoplasmic variant (m.1095T>C) of the MT-RNR1 gene associated with deafness. All three patients successfully underwent neonatal hearing screening. Until now, none of the three patients have shown any symptoms of deafness. We will continue to follow-up all three cases regularly in the future. Comparison of flow-through hybridization and NBGS for deafness A total of 196 cases were tested by flow-through hybridization, including 96 variant-positive (85 chromosome variants and 11 mitochondrial variants) and 100 negative cases. NBGS was performed in these 196 cases. We found that NBGS could accurately detect the known variants, and the consistency in the variant-positive results between the two methods was 96.9% (93/96) (Fig. 4). Unexpectedly, three mitochondrial gene ( MT-RNR1 ) heterogeneity variants (m.1555A>G and m.7445A>G) were not detected by NBGS, with a detection rate of 72.7% (8/11), whereas the detection rate of the gene variants on the chromosome was 100% (85/85). However, Sanger sequencing (Supplementary Fig. 2) and flow-through hybridization results indicated heterogeneity variants in both cases of m.1555A>G and one case of m.7445A>G, which indicates that NBGS detection of the mitochondrial gene ( MT-RNR1 ) heterogeneity variants is limited and needs to be validated in conjunction with other methods (such as Sanger sequencing). Among the 96 variant-positive cases, we additionally detected six cases with a variant, including five cases with GJB2 (c.109G>A) and one with SLC26A4 (c.1252G>A); among the 100 variant-negative cases, we detected eight cases with a variant, including six cases with GJB2 (c.109G>A), one with GJB3 (c.547G>A), and one with MYO15A (c.10250_10252delCCT). However, these variants are not included in flow-through hybridization for deafness screening, which can lead to missed cases of deafness. Discussion ​ An estimated 3–6% of newborns, about 8 million infants worldwide are born each year with a genetic or partial genetic defect [ 35 ]. Genetic diseases, especially congenital diseases at birth, are caused by one or more genetic abnormalities, such as IEM, hearing loss, and primary immune deficiency [ 36 ]. Most of them are associated with high mortality and disability rates. As is well known, MS/MS has expanded the NBS program, which can complete detection by continuously expanding metabolite screening. However, as the number of analytes increases, the scope, quantity, and complexity of diagnosis become more difficult to manage. The NGS technology plays an important role in the diagnosis process following MS/MS screening, which can detect genes of interest to provide diagnosis. The combination of MS/MS and NGS (MS/MS-NGS) is an enhancement program for NBS. Currently, an increasing number of countries are using MS/MS-NGS as the main method for NBS and have achieved positive outcomes [ 30 , 37 , 38 ]. The primary objective of NBS is to identify only treatable diseases and those that have a significant impact on the cost of quality of life through early detection. These traditional methods for detecting newborn genetic diseases have many drawbacks such as being time-consuming and risk of missed screening [ 39 – 41 ]. As an alternative, newborn genetic disease screening allows children to be diagnosed and treated within a short period after birth, which can avoid death or reduce the degree of disability caused by genetic diseases [ 12 , 13 , 42 ]. Currently, there are many genetic testing techniques available. As with MSMS, NGS is expected to screen for more diseases at a lower total cost per disease. The screening of NGS is carried out through a gene panel, WES, or WGS. For neonatal disease screening, NGS can screen for a few to hundreds of diseases. The gene panel can be designed as needed to enrich the sequencing library's target gene regions for sequencing. WES primarily detects protein-coding regions and adjacent intronic regulatory sequences, while WGS detects the entire DNA sequence. The scalability of genetic testing techniques provides unprecedented opportunities to address the major global health issue of diagnosing and managing rare diseases. However, there are still some doubts about whether neonatal WGS/WES should be routinely applied in clinical practice. Therefore, the selection of optimal genetic testing techniques and types of diseases included requires further exploration [ 19 , 42 , 43 ]. With the emergence of more and more conditions, genetic testing has gradually become the first step in screening genetic metabolic diseases, but currently genetic testing has not replaced biochemical testing, only the role has changed [ 44 ]. In this study, we used a new targeted gene panel method as NBGS, which included 112 genetic diseases with 246 pathogenic genes. Preliminary clinical data from this study suggest certain advantages of NBGS over MS/MS-NGS, such as the ability to detect most of the diseases included in the traditional MS/MS-NGS screening, greatly reduced false-positive rates, detection of other genes and variants, and a shorter detection cycle. Compared with the flow-through hybridization, NBGS can detect more variant sites in patients with deafness and reduce the false-positive rate of mitochondrial gene variants. For IEM, the consistency in positive results between NBGS and MS/MS-NGS was 61.8% (34/55), and 21 inconsistent results were obtained with only one variant or no variants. After comparison, we found that these undetected variants were either of unknown significance or variants of introns, both of which were excluded from NBGS. These data show that genetic screening of newborns has certain limitations. MS/MS-NGS is generally considered a diagnostic technique, while NBGS is used for newborn screening. In this study, the detection efficiency of NBGS was evaluated using traditional MS/MS-NGS as the standard, which may have resulted in bias. Additionally, traditional testing methods have a high false positive rate, requiring newborns and their families to be recalled for retesting, resulting in a longer testing cycle [ 12 ], which may increase the family’s anxiety and complaints. Practical clinical studies have demonstrated that many families’ refusal of further diagnostic testing contributes to increased uncertainty surrounding treatment [ 45 , 46 ]. Genetic screening of newborns remains unaffected by factors such as gestational age, delivery method, or baby weight, ensuring prompt and accurate test results within 13 working days while alleviating the psychological burden associated with repeated tests. The simplified and efficient process of newborn genetic screening enhances accuracy and facilitates acceptance among neonatal families and medical professionals [ 12 , 42 , 47 ]. Our results show that NBGS can detect most positive genetic diseases in newborns. However, further exploration is needed to fully replace MS/MS-NGS with NBGS. Currently, a combined application approach can be used to maximize its role in NBS. For deafness, the consistency between variant-positive results of NBGS and MS/MS-NGS was 96.9% (93/96); three cases of the mitochondrial gene ( MT-RNR1 ) heterogeneity variants (m.1555A > G and m.7445A > G) were not detected, while the remaining eight homogeneous variants were all detected, indicating that there are limitations in the detection of the mitochondrial heterogeneity variant by NBGS, which may lead to some missed screening and increase the false negative rate. The Sanger sequencing and flow-through hybridization results of the three mitochondrial heterogeneity variants indicated the highest heterogeneity rate of about 50%, but they have not yet been detected by NBGS. Therefore, heterogeneity mutations in mitochondrial genes, especially low proportion heterogeneity, need to be validated in conjunction with other methods to prevent the occurrence of false negatives. The mitochondrial MT-RNR1 gene has been proven to be directly associated with drug-induced hearing loss [ 48 ]. Mitochondrial variants can cause deafness, whereas maternal variants are genetically inherited. When a homogeneous or heterogeneous variant is detected, the patient is sensitive to aminoglycosides [ 49 ]. These data indicate that NBGS is less sensitive for detecting variations in mitochondrial deafness genes compared to those in euchromosome deafness genes. In addition, our results showed that each of the 14 newborns had an additional variant as detected by NBGS. Thus, our findings provide a better understanding of the limitations of flow-through hybridization detection. Even when the flow-through hybridization test is negative, it should be kept in mind that deafness still has a genetic cause, as variants associated with the risk factors for deafness may be located in undetected regions [ 41 ]. The advantage of applying NBGS to this specific population is that it can detect gene variants not included in flow-through hybridization (7.14% in this study, 14/196), which is beneficial for clinical applications and cost saving. If newborn hearing screening is prioritized, services for timely intervention must be established. Otherwise, the early identification of hearing loss provides no advantage. With the increasing number of in-depth studies on deafness genes, new genes and variant types may be included in genetic deafness screening, which may greatly improve the accuracy of genetic screening and provide a more reliable and detailed basis for genetic counseling and research [ 41 , 50 , 51 ]. The disease selection of the panel used in this study was based on the current domestic and foreign disease spectrum of neonatal screening, international reports of neonatal screening disease spectrum and genetic diseases with high prevalence reported in the literature, and combined with more than 40 years of neonatal screening experience in China. After multiple repeated designs of the panel, 112 diseases and 246 genes were ultimately identified in the panel and were used as the NBGS. The 246 genes that may be candidate genes for future genetic screening in newborns. If this genetic testing can be applied clinically, it will undoubtedly serve as a diagnostic method for neonatal genetic diseases, which can shorten the time for disease intervention and treatment, thereby improving the health outcomes of patients. However, the premise is that the pathogenicity of all genetic variations of the included disease has been identified. Additionally, based on current NBGS cost, we estimate the cost of conducting NBGS testing to be over $ 100. In China, if NBGS is used for routine clinical testing on a large scale, the government may provide subsidies to offset some patient costs, which contributes to the implementation of genetic screening. Based on the above, we believe that genetic screening will soon be applied as a first-line detection method in clinical practice and achieve satisfactory results. Conclusions Based on the analysis of 223 cases of IEM and 196 cases of deafness, we found that compared to the traditional screening methods of MS/MS-NGS for IEM and flow-through hybridization for deafness, NBGS can detect a more comprehensive set of variants and reduce the false-positive rate. Furthermore, a shortened reporting cycle allows for the early detection of diseases, with detection rates comparable to those of the other two methods. ​However, many genetic screening strategies for rare diseases are still in the exploratory stage, and the disease types, genes, and loci to be included in neonatal genetic screening may require further evaluation. Overall, NBGS can be considered a new method for screening newborns for IEM, deafness, and other genetic disorders in clinical practice. Abbreviations NBS Newborn screening IEM Inborn errors of metabolism NBGS Newborn genetic screening MS/MS Tandem mass spectrometry NGS Next-generation sequencing DBS Dry blood spots PKU Phenylketonuria WES Whole exome sequencing WGS Whole genome sequencing PCR Polymerase chain reaction CNV Copy number variants AAM Amino acid metabolism OAM Organic acid metabolism FAM Fatty acid metabolism Declarations Acknowledgments Not applicable. Authors’ contributions L. W. and Y. W. designed and conceived the study. S. M. and Z. W. drafted the manuscript and performed statistical analysis. S. L. and X. T. collected study data. S.M. L. and Y. Z. revised the manuscript. S. M. and Z. W. have contributed equally to this work and share the first authorship. Funding This work was supported by the Program of Maternal and Child Health Research Project of Jiangsu Province (No. F202120) and the Program of Maternal and Child Health Research Project of Lianyungang City (No. F202105). Availability of data and materials The data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request. Ethics approval and consent to participate This study was approved by the Ethics Committee of Lianyungang Maternal and Child Health Hospital and written informed consent was obtained from all parents or guardians of the newborns before the screening. 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BMC Pediatr. 2018;18(1):225. Milko LV, Rini C, Lewis MA, Butterfield RM, Lin FC, Paquin RS, et al. Evaluating parents' decisions about next-generation sequencing for their child in the NC NEXUS (North Carolina Newborn Exome Sequencing for Universal Screening) study: a randomized controlled trial protocol. Trials. 2018;19(1):344. Wojcik MH, Zhang T, Ceyhan-Birsoy O, Genetti CA, Lebo MS, Yu TW, et al. Discordant results between conventional newborn screening and genomic sequencing in the BabySeq Project. Genet Med. 2021;23(7):1372-1375. Adhikari AN, Gallagher RC, Wang Y, Currier RJ, Amatuni G, Bassaganyas L, et al. The role of exome sequencing in newborn screening for inborn errors of metabolism. Nat Med. 2020 Sep;26(9):1392-1397. Rezapour A, Souresrafil A, Barzegar M, Sheikhy-Chaman M, Tatarpour P. Economic evaluation of next-generation sequencing techniques in diagnosis of genetic disorders: A systematic review. Clin Genet. 2023;103(5):513-528. 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NGS-based spinal muscular atrophy carrier screening of 10,585 diverse couples in China: a pan-ethnic study. Eur J Hum Genet. 2021;29(1):194-204. Shang X, Peng Z, Ye Y, Asan, Zhang X, Chen Y, et al. Rapid Targeted Next-Generation Sequencing Platform for Molecular Screening and Clinical Genotyping in Subjects with Hemoglobinopathies. EBioMedicine. 2017;23:150-159. Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, 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. 2015;17(5):405-24. Groisman B, Bermejo-Sánchez E, Romitti PA, Botto LD, Feldkamp ML, Walani SR, et al. Join World Birth Defects Day. Pediatr Res. 2019;86(1):3-4. Peng Q, Liu G, Zhu P, Wu C, He X, Li W, et al. A targeted gene capture next-generation sequencing panel for genetic screening of newborns. J Pak Med Assoc. 2020;70(10):1789-1794. Lampret BR, Remec ŽI, Torkar AD, Tanšek MŽ, Šmon A, Koračin V, et al. Expanded Newborn Screening Program in Slovenia using Tandem Mass Spectrometry and Confirmatory Next Generation Sequencing Genetic Testing. Zdr Varst. 2020;59(4):256-263. Martín-Rivada Á, Palomino Pérez L, Ruiz-Sala P, Navarrete R, Cambra Conejero A, Quijada Fraile P, et al. Diagnosis of inborn errors of metabolism within the expanded newborn screening in the Madrid region. JIMD Rep. 2022;63(2):146-161. Therrell BL, Padilla CD, Loeber JG, Kneisser I, Saadallah A, Borrajo GJ, Adams J. Current status of newborn screening worldwide: 2015. Semin Perinatol. 2015;39(3):171-87. Ombrone D, Giocaliere E, Forni G, Malvagia S, la Marca G. Expanded newborn screening by mass spectrometry: New tests, future perspectives. Mass Spectrom Rev. 2016;35(1):71-84. Zhu QW, Li MT, Zhuang X, Chen K, Xu WQ, Jiang YH, et al. Assessment of Hearing Screening Combined With Limited and Expanded Genetic Screening for Newborns in Nantong, China. JAMA Netw Open. 2021;4(9):e2125544. Wang H, Yang Y, Zhou L, Wang Y, Long W, Yu B. NeoSeq: a new method of genomic sequencing for newborn screening. Orphanet J Rare Dis. 2021;16(1):481. Woerner AC, Gallagher RC, Vockley J, Adhikari AN. The Use of Whole Genome and Exome Sequencing for Newborn Screening: Challenges and Opportunities for Population Health. Front Pediatr. 2021;9:663752. Mordaunt D, Cox D, Fuller M. Metabolomics to Improve the Diagnostic Efficiency of Inborn Errors of Metabolism. Int J Mol Sci. 2020;21(4):1195. Hewlett J, Waisbren SE. A review of the psychosocial effects of false-positive results on parents and current communication practices in newborn screening. J Inherit Metab Dis. 2006;29(5):677-82. Schmidt JL, Castellanos-Brown K, Childress S, Bonhomme N, Oktay JS, Terry SF, et al. The impact of false-positive newborn screening results on families: a qualitative study. Genet Med. 2012;14(1):76-80. Ye L, Yin Y, Chen M, Gong N, Peng Y, Liu H, et al. Combined genetic screening and traditional newborn screening to improve the screening efficiency of congenital hypothyroidism. Front Pediatr. 2023;11:1185802. Xing G, Chen Z, Cao X. Mitochondrial rRNA and tRNA and hearing function. Cell Res. 2007;17(3):227-39. Ding Y, Leng J, Fan F, Xia B, Xu P. The role of mitochondrial DNA mutations in hearing loss. Biochem Genet. 2013;51(7-8):588-602. Mori K, Moteki H, Miyagawa M, Nishio SY, Usami S. Social Health Insurance-Based Simultaneous Screening for 154 Mutations in 19 Deafness Genes Efficiently Identified Causative Mutations in Japanese Hearing Loss Patients. PLoS One. 2016;11(9):e0162230. Zhu Y, Hu L, Yang L, Wang L, Lu Y, Dong X, et al. Association Between Expanded Genomic Sequencing Combined With Hearing Screening and Detection of Hearing Loss Among Newborns in a Neonatal Intensive Care Unit. JAMA Netw Open. 2022;5(7):e22 Additional Declarations No competing interests reported. Supplementary Files SupplementaryFigure1.tif Supplementary Figure 1. Comparison of diagnostic time between NBGS and MS-MS-NGS. SupplementaryFigure2.tif Supplementary Figure 2. Sanger sequencing of three mitochondrial gene ( MT-RNR1 ) heterogeneity variations. (A): c.7445A>G; (B) and (C): c.1555A>G. Supplementarytable.docx Cite Share Download PDF Status: Posted 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-3995451","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":276221851,"identity":"9bb82825-68ef-4d32-a9f3-8a79d9dddab8","order_by":0,"name":"Shuai Men","email":"","orcid":"","institution":"Lianyungang Maternal and Child Health Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shuai","middleName":"","lastName":"Men","suffix":""},{"id":276221852,"identity":"c14f60fa-1c72-4ee4-8498-4124340c673a","order_by":1,"name":"Zhiwei Wang","email":"","orcid":"","institution":"Lianyungang Maternal and Child Health Hospital","correspondingAuthor":false,"prefix":"","firstName":"Zhiwei","middleName":"","lastName":"Wang","suffix":""},{"id":276221853,"identity":"eebfa27a-e23a-4429-a83b-4f7cc24a2289","order_by":2,"name":"Xinxin Tang","email":"","orcid":"","institution":"Lianyungang Maternal and Child Health Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xinxin","middleName":"","lastName":"Tang","suffix":""},{"id":276221854,"identity":"b0e7b6dd-a28c-4416-b21c-36b6f98143e8","order_by":3,"name":"Shuang Liu","email":"","orcid":"","institution":"Lianyungang Maternal and Child Health Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shuang","middleName":"","lastName":"Liu","suffix":""},{"id":276221855,"identity":"3930f029-4d80-44c8-8144-e99590cf83c5","order_by":4,"name":"Shuaimei Liu","email":"","orcid":"","institution":"Jiangsu Health Development Research Center, National Health and Family Planning Commission Contraceptives Adverse Reaction Surveillance Center","correspondingAuthor":false,"prefix":"","firstName":"Shuaimei","middleName":"","lastName":"Liu","suffix":""},{"id":276221856,"identity":"163c9031-f6b0-480d-97f4-0db49a91e0ff","order_by":5,"name":"Yali Zhao","email":"","orcid":"","institution":"Lianyungang Maternal and Child Health Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yali","middleName":"","lastName":"Zhao","suffix":""},{"id":276221857,"identity":"434f189c-086e-4a1e-89f7-39aaaf07a688","order_by":6,"name":"Yulin Wu","email":"","orcid":"","institution":"Jiangsu Health Development Research Center, National Health and Family Planning Commission Contraceptives Adverse Reaction Surveillance Center","correspondingAuthor":false,"prefix":"","firstName":"Yulin","middleName":"","lastName":"Wu","suffix":""},{"id":276221858,"identity":"ca6f2d00-9000-4d6e-bfea-585f7ca909ef","order_by":7,"name":"Leilei Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAklEQVRIie3Pv0vEMBTA8VcCdYl0fQXxPxAqgXBC5f4Ql5RCXVpnh3LkOKiT3Ow/Io6FwLlUunbsbQ431NFFfHE92joK5puh5MeHRwFcrr9aD3gGjNaHtltvXc8SBcgt8Z40IBH9GwKcPoyd/hCASRK9vpl3db/gwQkz4volXl08GJpSxjejpLnLFqpBHm78NC2aDGWTENllhR4hss5llFTII8OFKSqDsibiaTNO2gORL+RLS64safczpMtFn2iawrhIPUu6mSnL7iBB7ZCj8dPLxyoLnzuaoib+JdzmYhjK1XmwNQY/qziQ7e2+H8p4lFA+Hp+p8ec2Nkzfu1wu17/vG58yXej8/HvQAAAAAElFTkSuQmCC","orcid":"","institution":"Lianyungang Maternal and Child Health Hospital","correspondingAuthor":true,"prefix":"","firstName":"Leilei","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-02-28 03:00:59","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3995451/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3995451/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52303328,"identity":"f40c1f80-ba33-4f20-9c83-65ab3e5b9877","added_by":"auto","created_at":"2024-03-08 19:01:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":52198,"visible":true,"origin":"","legend":"\u003cp\u003eWorkflow for the study design. The dashed blue line is the IEM cases, the dashed orange line is the deaf cases, and the overlapping cases are those that intersect.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3995451/v1/e353f3065dc0fd8f1b5b0ff7.png"},{"id":52303329,"identity":"48428e1b-b693-40ee-9f55-4dedf536498b","added_by":"auto","created_at":"2024-03-08 19:01:33","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":116028,"visible":true,"origin":"","legend":"\u003cp\u003eScreening by NBGS for IEM. (A): Comparison of NBGS and MS/MS-NGS in newborns. (B): Detection of different IEM with NBGS. (C): Counts of genes detected for a variant in the negative (n = 100) and suspected positive (n = 68) cases.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3995451/v1/394dcfbc23be4616be359293.png"},{"id":52304726,"identity":"f368459d-c82f-46dc-bfe0-579f7b6964b0","added_by":"auto","created_at":"2024-03-08 19:09:33","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":62174,"visible":true,"origin":"","legend":"\u003cp\u003eOther genes were found in IEM cases. (A): Other genes detected by NBGS. (B): Counts of genes detected for a variant in the negative (n = 100), suspected positive (n = 70) cases, and true positive (n = 53) cases.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3995451/v1/4732a436fa9965eef4b63d61.png"},{"id":52303333,"identity":"69d83111-1999-4132-861f-fc55a6b11e90","added_by":"auto","created_at":"2024-03-08 19:01:33","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":33648,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of NBGS and flow-through hybridization for deafness cases.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-3995451/v1/ad378a59e4ae790fae1aa1d0.png"},{"id":59574578,"identity":"bb425498-ecfd-4b8c-a16b-a32d12aef3c5","added_by":"auto","created_at":"2024-07-03 11:02:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":697502,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3995451/v1/be4f67cb-ccda-4032-ad4b-979658d6398f.pdf"},{"id":52303332,"identity":"1c259174-294f-42f3-859a-10c6e5c5e5f0","added_by":"auto","created_at":"2024-03-08 19:01:33","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3417384,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Figure 1.\u003cstrong\u003e \u003c/strong\u003eComparison of diagnostic time between NBGS and MS-MS-NGS.\u003c/p\u003e","description":"","filename":"SupplementaryFigure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-3995451/v1/71bc0531d3f44f1207ae558f.tif"},{"id":52303334,"identity":"c7d6bdce-4b71-4d9f-be3d-f4a911c66a2e","added_by":"auto","created_at":"2024-03-08 19:01:33","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":626432,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Figure 2.\u003cstrong\u003e \u003c/strong\u003eSanger sequencing of three mitochondrial gene (\u003cem\u003eMT-RNR1\u003c/em\u003e) heterogeneity variations.\u003cstrong\u003e (A)\u003c/strong\u003e: c.7445A\u0026gt;G; \u003cstrong\u003e(B)\u003c/strong\u003e and \u003cstrong\u003e(C)\u003c/strong\u003e: c.1555A\u0026gt;G.\u003c/p\u003e","description":"","filename":"SupplementaryFigure2.tif","url":"https://assets-eu.researchsquare.com/files/rs-3995451/v1/9932cb7ec84cb7023d7c6bf7.tif"},{"id":52303331,"identity":"e176d8f8-032c-4b16-99f2-7f76a2d7c3aa","added_by":"auto","created_at":"2024-03-08 19:01:33","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":31324,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarytable.docx","url":"https://assets-eu.researchsquare.com/files/rs-3995451/v1/a41959d595144af316e84984.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Integrating Newborn Genetic Screening with Traditional Screening to Improve Newborn Screening","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMedical screening tests are designed to detect diseases early in the pre-symptomatic phase to reduce the morbidity and mortality. Newborn screening (NBS) is a successful public health program that can detect inborn errors of metabolism (IEM) as early as possible, thus effectively reducing the incidence and mortality of IEM through early detection and intervention [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The early detection and timely treatment of newborns with IEM through NBS have emerged as a global imperative. Over the past few decades, biochemical techniques for the detection of specific metabolites in dry blood spots (DBS) have played an important role in the screening of neonatal genetic disorders. Initially, NBS was used only to detect phenylketonuria (PKU). With the evolution of technology, NBS has improved and an increasing number of IEM are being screened [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Currently, NBS based on tandem mass spectrometry (MS/MS) can detect biochemical markers of over 40 different diseases [\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], which allows NBS programs to add more diseases at low cost and better efficiency. However, the clinical presentation of IEM is complex and varied, and its diagnosis often requires auxiliary tests such as the detection of gene variants. In addition, MS/MS has a high false-positive rate and positive predictive value [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In recent years, many scientific research institutions have applied genetic testing for neonatal genetic disease screening [\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. At the genetic level, dozens to thousands of diseases can be detected in a single test, favoring the development of a screening method for neonatal genetic disorders.\u003c/p\u003e \u003cp\u003eWith advances in genetic testing technology, the application of next-generation sequencing (NGS) in NBS is becoming more and more important [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. ​Because of the wide range of applications of NGS, NBS is no longer limited to screening for IEM and can include additional neonatal genetic disorders and even certain genetic disorders without specific metabolites, such as deafness and spinal muscular atrophy [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Similar to MS/MS, NGS offers the possibility of screening more diseases at a lower cost per disease [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. NGS, as a genetic screening method, is performed mainly through gene panels and genome sequencing (whole exome sequencing [WES] and whole genome sequencing [WGS]), which may significantly expand the screening of newborns for genetic disorders. Since its introduction, NGS has been rapidly and extensively used in research and clinical applications, particularly NBS, where it has shown potential value [\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The most representative research is the BabySeq exome sequencing program and newborn exome sequencing for universal screening (NC NEXUS) exome sequencing program in the United States for newborn disease detection [\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The aforementioned studies have demonstrated the promising potential of genome sequencing in NBS, as it enables the detection of diseases and variants that are beyond the reach of conventional NBS methods. However, the use of WES as a first- or second-line diagnostic test is still controversial [\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], and it is still difficult to incorporate this technology into routine screening. In addition, no effective treatments have been identified for many diseases. The gap between diagnostic capacity and effective treatment means that many identified diseases may not satisfy the criteria for inclusion in NBS.\u003c/p\u003e \u003cp\u003eA targeted gene panel is used in the genetic screening of newborns [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], which can be designed \u0026ldquo;as required\u0026rdquo; to incorporate disease-related genes of interest. Targeted gene panels are now being incorporated into routine genetic screening in a growing number of countries and regions around the world, and diverse genes can be included in the targeted gene panels [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], but these panels play a role in diagnosis after MS/MS screening. How to use a panel as a genetic screening program for newborns in clinical practice still needs to be explored. This study aimed to explore the clinical application value and feasibility of genetic screening by comparing traditional screening with genetic screening based on retrospective data from 223 cases with IEM and 196 with deafness from 2019 to 2022. We hope our findings can contribute to the development of an improved screening strategy for neonatal IEM and deafness.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePopulation and sample collection\u003c/h2\u003e \u003cp\u003eThis study was conducted at the Lianyungang Maternal and Child Health Hospital. Newborns born between January 2018 and December 2022 were screened, including the IEM group and the deafness group. In this study, 223 dried blood spot samples (from 130 males and 93 females) were collected from the IEM group, including 55 positive cases (clinically confirmed cases), 68 suspected positive cases (both the initial and recall screening values were abnormal, but the cases were not confirmed), and 100 negative cases (initial screening values were normal). Additionally, 196 dried blood spot samples (from 98 males and 98 females) were collected from the deafness group, including 96 variant-positive and 100 negative cases. The 100 negative cases were diagnosed with MS/MS and deafness, both of which were negative. The workflow of this study is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. This study was approved by the Ethics Committee of Lianyungang Maternal and Child Health Hospital and written informed consent was obtained from all parents or guardians of the newborns before the screening.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eMS/MS-NGS for IEM\u003c/h2\u003e \u003cp\u003eDried blood spots were collected from all newborns 72 h after birth on filter papers (903, Hangzhou Matridx Biotechnology Co., Ltd.). MS/MS-NGS: MS/MS was used to detect the biochemical indicators, and newborns were further investigated to diagnose the diseases by NGS (panel), as described in our previous study [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Newborn diseases detected by MS/MS-NGS included 56 common IEM with 86 genes (Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Genomic DNA was extracted from DBS or peripheral blood obtained from the patients and their parents using the Qiagen Blood DNA Mini Kit (Qiagen, Hilden, Germany). Target region sequences were enriched by multiple-probe hybridization using the SureSelect Human Exon Sequence Capture kit (Agilent, USA) and purified using Agencourt AMPure XP Beads (Beckman Coulter, USA). The purified product was treated according to the operation instructions of TruePrep DNA Library Prep Kit V2 for Illumina (Vazyme Biotech), and a special index was added using the TruePrep Index Kit V2 for Illumina (Vazyme Biotech). The library was analyzed using a Qubit 2100 Bioanalyzer (Agilent High Sensitivity DNA Kit, Agilent, USA), and a quantitative kit (Illumina DNA Standard Primer Premix Kit, Kapa, USA) was used for accurate library quantification. Massive parallel sequencing was performed using a HiSeq 2500 platform (Illumina, USA) with a mean sequencing depth of 100\u0026times; coverage.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eFlow-through hybridization for deafness\u003c/h2\u003e \u003cp\u003eThirteen variants of four common deafness genes were detected by flow-through hybridization, including \u003cem\u003eGJB2\u003c/em\u003e (c.35 delG, c.155 delTCTG, c.176 del16, c.235 delC, c.299 delAT), \u003cem\u003eSLC26A4\u003c/em\u003e (c.IVS7-2A\u0026thinsp;\u0026gt;\u0026thinsp;G, c.2168 A\u0026thinsp;\u0026gt;\u0026thinsp;G, c.1229C\u0026thinsp;\u0026gt;\u0026thinsp;T), \u003cem\u003eMT-RNR1\u003c/em\u003e (m.1555\u0026thinsp;\u0026gt;\u0026thinsp;G, m.1494C\u0026thinsp;\u0026gt;\u0026thinsp;T, m.7445 A\u0026thinsp;\u0026gt;\u0026thinsp;G, m.12201 T\u0026thinsp;\u0026gt;\u0026thinsp;C), and \u003cem\u003eGJB3\u003c/em\u003e (c.538C\u0026thinsp;\u0026gt;\u0026thinsp;T). Genomic DNA was extracted from DBS or peripheral blood samples for polymerase chain reaction (PCR) amplification. The PCR products were thermally denatured into single-stranded DNA, which was then hybridized to low-density gene chip probes. Finally, the results were interpreted using chemical coloration.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eNBGS for newborns\u003c/h2\u003e \u003cp\u003eThe NBGS panel included 112 common genetic diseases with 246 genes (Supplementary Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). The extracted genomic DNA was broken into 100\u0026ndash;500 bp fragments by enzyme digestion. Then, these 150\u0026ndash;200 bp fragments were separated using magnetic beads and subjected to end repair. \"A\" tail was added at 3' ends of the DNA to complete the DNA library construction. The DNA library was subjected to fragment size and concentration measurement using an Agilent 2100 Bioanalyzer (Agilent Technologies) and BMG. After \"A\" tailing and ligation, a customized NAD probe was used to capture the target region sequences, followed by pooling and quantification of the hybridization library. The pooled library was then subjected to single-chain cyclization and rolling-circle replication. After the cyclized library was constructed, DNA nanoball was sequenced (PE100\u0026thinsp;+\u0026thinsp;10) using the high-throughput gene sequencer MGISEQ-2000 with a mean sequencing depth of 100\u0026times; coverage. An in-house verified variant calling pipeline was used to analyze single nucleotide variants, small insertions and deletions, and copy number variants (CNV) including CNVs involving 2 or more continuous exons in DMD [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], exon 7 deletion of SMN1 [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] and common CNVs involving HBA1/HBA2/HBB [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eBioinformatics analysis\u003c/h2\u003e \u003cp\u003eRaw high-throughput sequencing data were converted from Bcl to Fastq format by Illumina bcl2fastq, and then the sequencing reads were aligned with the NCBI human genome reference sequence (hg19/GRCh37) after low-quality filtering. The frequency of variants in the normal population was obtained from databases, including gnomAD (version 2.1.1, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gnomad.broadinstitute.org\u003c/span\u003e\u003cspan address=\"https://gnomad.broadinstitute.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), 1000 Genome Project database (version 2015, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.1000genomes.org/\u003c/span\u003e\u003cspan address=\"http://www.1000genomes.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and dbSNP (version 2.0.1, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/projects/SNP/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/projects/SNP/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The databases such as ClinVar (version 2021, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/clinvar/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/clinvar/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), OMIM (version 2023, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.omim.org\u003c/span\u003e\u003cspan address=\"http://www.omim.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and Human Gene Mutation Database (version 2023.1, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.hgmd.cf.ac.uk/ac/index.php/\u003c/span\u003e\u003cspan address=\"http://www.hgmd.cf.ac.uk/ac/index.php/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) were used to determine variant pathogenicity where appropriate. The biological function of the variants was predicted using bioinformatics software, including SIFT (version 2022, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://sift.bii.a-star.edu.sg\u003c/span\u003e\u003cspan address=\"https://sift.bii.a-star.edu.sg\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), PolyPhen-2 (version 2, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://genetics.bwh.harvard.edu/pph2\u003c/span\u003e\u003cspan address=\"http://genetics.bwh.harvard.edu/pph2\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), PROVEAN (version 1.1, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://provean.jcvi.org/index.php\u003c/span\u003e\u003cspan address=\"http://provean.jcvi.org/index.php\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and Mutation Taster (version 2021, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.mutationtaster.org/\u003c/span\u003e\u003cspan address=\"https://www.mutationtaster.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), to further assess the possible pathogenicity. Interpretation of the pathogenicity of the novel variants was performed according to the standards and guidelines of the American College of Medical Genetics and Genomics [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSanger sequencing\u003c/h2\u003e \u003cp\u003ePositive variants were verified by Sanger sequencing. Genomic DNA was extracted from DBS or peripheral blood samples and variants were amplified using specific primers. PCR was performed using the AmpliTaq Gold 360 Master Mix (ABI, USA). The PCR products were purified using ExoSAP-IT (ABI, USA), and sequenced and analyzed using a 3500Dx Genetic Analyzer (Thermo Fisher, Waltham, USA).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eComparison of MS/MS-NGS and NBGS for IEM\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 223 DBS were collected from newborns whose MS/MS-NGS results were positive (55), suspected positive (68), and negative (100). The 55 positive cases included 31 cases of amino acid metabolism (AAM), 14 organic acid metabolism (OAM), and 10 fatty acid metabolism (FAM) disorders. A total of 223 DBS were subjected to NBGS. The detection results showed that NBGS could accurately detect the known variants in MS/MS-NGS positive cases, and the consistency in the positive results between both methods was 61.8% (34/55) (Fig. 2A). Of the 34 positive cases detected by NBGS, 18 were AAM, eight were OAM, and eight were FAM. The detection rates for AAM, OAM, and FAM were 58.1% (18/31), 57.1% (8/14), and 80% (8/10), respectively (Fig. 2B). Of the 21 cases with inconsistent results using both methods, eight positive results were not detected by NBGS, including four cases of PKU, two cases of 3-methylcrotonyl-coenzyme A carboxylase deficiency, and one case of isolated hypermethioninemia and isovaleric acidemia. In the remaining 13 cases, NBGS detected a variant (Fig. 2A). For the 21 inconsistent results, we found that the variants were either of unknown significance or in introns, both of which were excluded from NBGS (Supplementary Table S3). Regarding the reporting time of the two methods, due to the traditional MS/MS-NGS screening being divided into two steps, the final results can only be obtained within 9\u0026ndash;139 days (median of 35 days). In contrast, NBGS typically provides results within 13 days. Therefore, NBGS can accurately detect the variants in a shorter time (Supplementary Fig. 1).\u003c/p\u003e\n\u003cp\u003eThe study enrolled 68 cases with suspected positive results. Their initial MS/MS screening values were abnormal, and after recall and retesting, the results were still abnormal; however, they were not confirmed positive through clinical differential diagnosis or genetic testing in the end. Twenty-six cases with suspected positive were found to have a variant by NBGS. For the 100 negative cases enrolled, their initial MS/MS screening values were abnormal; after recall and retesting, the results were normal. Among these, 23 cases were identified by NBGS to have a variant. In addition, 39 pathogenic or likely pathogenic variants were detected in 21 suspected positive and negative cases. We identified that 29.2% (49/168) of individuals carry a specific variant in the suspected positive and negative cases, and the most commonly detected genes were \u003cem\u003eDUOX2, MCCC1\u003c/em\u003e\u003cem\u003e, PAH, MATIA\u003c/em\u003e, and \u003cem\u003eATP7B\u003c/em\u003e (Fig. 2C).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOther genes detected by NBGS in newborns with IEM\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBoth MS/MS-NGS and NBGS involve screening for known disease-causing gene variants. However, NBGS can screen more variants than traditional MS/MS-NGS. The count of carried additional variants was 62 (27.8%, 62/223). There were 16, 10, and 36 variant carriers among the positive, suspected positive, and negative cases, respectively (Fig. 3A). Other genes most commonly detected by NBGS were \u003cem\u003eGJB2\u003c/em\u003e, \u003cem\u003eSCL12A3\u003c/em\u003e, \u003cem\u003eSCL12A3\u003c/em\u003e, and \u003cem\u003eHBA1/HBA2\u0026nbsp;\u003c/em\u003e(Fig. 3B). Among the other genes, we found four positive cases. One case of incomplete dominant variation (c.406C\u0026gt;T) in the \u003cem\u003eG6PD\u003c/em\u003e gene (X-linked incomplete dominant inheritance) was associated with classic glucose-6-phosphate dehydrogenase deficiency in the negative cases. The initial MS/MS results of this patient showed normal biochemical indicators. Among the remaining three cases, one patient was homozygous for a variant (c.109G\u0026gt;A) of the \u003cem\u003eGJB2\u003c/em\u003e gene associated with deafness. One patient was heterozygous for a dominant variant (c.547G\u0026gt;A) of the \u003cem\u003eGJB3\u003c/em\u003e gene associated with deafness. One patient was heterozygous for a homoplasmic variant (m.1095T\u0026gt;C) of the \u003cem\u003eMT-RNR1\u0026nbsp;\u003c/em\u003egene associated with deafness. All three patients successfully underwent neonatal hearing screening. Until now, none of the three patients have shown any symptoms of deafness. We will continue to follow-up all three cases regularly in the future.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eflow-through hybridization\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;and NBGS for deafness\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 196 cases were tested by flow-through hybridization, including 96 variant-positive (85 chromosome variants and 11 mitochondrial variants) and 100 negative cases. NBGS was performed\u0026nbsp;in these 196 cases. We found that\u0026nbsp;NBGS could accurately detect the known variants, and the\u0026nbsp;consistency in the variant-positive results between the two methods was 96.9% (93/96) (Fig. 4). Unexpectedly, three mitochondrial gene (\u003cem\u003eMT-RNR1\u003c/em\u003e)\u0026nbsp;heterogeneity variants (m.1555A\u0026gt;G and m.7445A\u0026gt;G) were not detected by NBGS, with a detection rate of 72.7% (8/11), whereas the detection rate of\u0026nbsp;the gene variants on the chromosome was 100% (85/85).\u0026nbsp;However, Sanger sequencing\u0026nbsp;(Supplementary Fig. 2)\u0026nbsp;and\u0026nbsp;flow-through hybridization\u0026nbsp;results indicated heterogeneity variants in both cases of\u0026nbsp;m.1555A\u0026gt;G\u0026nbsp;and one case of\u0026nbsp;m.7445A\u0026gt;G, which indicates that NBGS detection of the mitochondrial gene (\u003cem\u003eMT-RNR1\u003c/em\u003e) heterogeneity variants is limited and needs to be validated in conjunction with other methods (such as Sanger sequencing). Among the 96 variant-positive cases, we additionally detected six cases with a variant, including five cases with \u003cem\u003eGJB2\u0026nbsp;\u003c/em\u003e(c.109G\u0026gt;A) and one with \u003cem\u003eSLC26A4\u003c/em\u003e (c.1252G\u0026gt;A); among the 100 variant-negative cases, we detected eight cases with a variant, including six cases with\u003cem\u003e\u0026nbsp;GJB2\u0026nbsp;\u003c/em\u003e(c.109G\u0026gt;A), one with\u003cem\u003e\u0026nbsp;GJB3\u0026nbsp;\u003c/em\u003e(c.547G\u0026gt;A),\u003cem\u003e\u0026nbsp;\u003c/em\u003eand one with \u003cem\u003eMYO15A\u003c/em\u003e (c.10250_10252delCCT). However, these variants are not included in flow-through hybridization for deafness screening, which can lead to missed cases of deafness.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e​ An estimated 3\u0026ndash;6% of newborns, about 8\u0026nbsp;million infants worldwide are born each year with a genetic or partial genetic defect [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Genetic diseases, especially congenital diseases at birth, are caused by one or more genetic abnormalities, such as IEM, hearing loss, and primary immune deficiency [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Most of them are associated with high mortality and disability rates. As is well known, MS/MS has expanded the NBS program, which can complete detection by continuously expanding metabolite screening. However, as the number of analytes increases, the scope, quantity, and complexity of diagnosis become more difficult to manage. The NGS technology plays an important role in the diagnosis process following MS/MS screening, which can detect genes of interest to provide diagnosis. The combination of MS/MS and NGS (MS/MS-NGS) is an enhancement program for NBS. Currently, an increasing number of countries are using MS/MS-NGS as the main method for NBS and have achieved positive outcomes [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. The primary objective of NBS is to identify only treatable diseases and those that have a significant impact on the cost of quality of life through early detection. These traditional methods for detecting newborn genetic diseases have many drawbacks such as being time-consuming and risk of missed screening [\u003cspan additionalcitationids=\"CR40\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. As an alternative, newborn genetic disease screening allows children to be diagnosed and treated within a short period after birth, which can avoid death or reduce the degree of disability caused by genetic diseases [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Currently, there are many genetic testing techniques available. As with MSMS, NGS is expected to screen for more diseases at a lower total cost per disease. The screening of NGS is carried out through a gene panel, WES, or WGS. For neonatal disease screening, NGS can screen for a few to hundreds of diseases. The gene panel can be designed as needed to enrich the sequencing library's target gene regions for sequencing. WES primarily detects protein-coding regions and adjacent intronic regulatory sequences, while WGS detects the entire DNA sequence. The scalability of genetic testing techniques provides unprecedented opportunities to address the major global health issue of diagnosing and managing rare diseases. However, there are still some doubts about whether neonatal WGS/WES should be routinely applied in clinical practice. Therefore, the selection of optimal genetic testing techniques and types of diseases included requires further exploration [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. With the emergence of more and more conditions, genetic testing has gradually become the first step in screening genetic metabolic diseases, but currently genetic testing has not replaced biochemical testing, only the role has changed [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, we used a new targeted gene panel method as NBGS, which included 112 genetic diseases with 246 pathogenic genes. Preliminary clinical data from this study suggest certain advantages of NBGS over MS/MS-NGS, such as the ability to detect most of the diseases included in the traditional MS/MS-NGS screening, greatly reduced false-positive rates, detection of other genes and variants, and a shorter detection cycle. Compared with the flow-through hybridization, NBGS can detect more variant sites in patients with deafness and reduce the false-positive rate of mitochondrial gene variants.\u003c/p\u003e \u003cp\u003e For IEM, the consistency in positive results between NBGS and MS/MS-NGS was 61.8% (34/55), and 21 inconsistent results were obtained with only one variant or no variants. After comparison, we found that these undetected variants were either of unknown significance or variants of introns, both of which were excluded from NBGS. These data show that genetic screening of newborns has certain limitations. MS/MS-NGS is generally considered a diagnostic technique, while NBGS is used for newborn screening. In this study, the detection efficiency of NBGS was evaluated using traditional MS/MS-NGS as the standard, which may have resulted in bias. Additionally, traditional testing methods have a high false positive rate, requiring newborns and their families to be recalled for retesting, resulting in a longer testing cycle [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], which may increase the family\u0026rsquo;s anxiety and complaints. Practical clinical studies have demonstrated that many families\u0026rsquo; refusal of further diagnostic testing contributes to increased uncertainty surrounding treatment [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Genetic screening of newborns remains unaffected by factors such as gestational age, delivery method, or baby weight, ensuring prompt and accurate test results within 13 working days while alleviating the psychological burden associated with repeated tests. The simplified and efficient process of newborn genetic screening enhances accuracy and facilitates acceptance among neonatal families and medical professionals [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Our results show that NBGS can detect most positive genetic diseases in newborns. However, further exploration is needed to fully replace MS/MS-NGS with NBGS. Currently, a combined application approach can be used to maximize its role in NBS.\u003c/p\u003e \u003cp\u003eFor deafness, the consistency between variant-positive results of NBGS and MS/MS-NGS was 96.9% (93/96); three cases of the mitochondrial gene (\u003cem\u003eMT-RNR1\u003c/em\u003e) heterogeneity variants (m.1555A\u0026thinsp;\u0026gt;\u0026thinsp;G and m.7445A\u0026thinsp;\u0026gt;\u0026thinsp;G) were not detected, while the remaining eight homogeneous variants were all detected, indicating that there are limitations in the detection of the mitochondrial heterogeneity variant by NBGS, which may lead to some missed screening and increase the false negative rate. The Sanger sequencing and flow-through hybridization results of the three mitochondrial heterogeneity variants indicated the highest heterogeneity rate of about 50%, but they have not yet been detected by NBGS. Therefore, heterogeneity mutations in mitochondrial genes, especially low proportion heterogeneity, need to be validated in conjunction with other methods to prevent the occurrence of false negatives. The mitochondrial \u003cem\u003eMT-RNR1\u003c/em\u003e gene has been proven to be directly associated with drug-induced hearing loss [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Mitochondrial variants can cause deafness, whereas maternal variants are genetically inherited. When a homogeneous or heterogeneous variant is detected, the patient is sensitive to aminoglycosides [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. These data indicate that NBGS is less sensitive for detecting variations in mitochondrial deafness genes compared to those in euchromosome deafness genes. In addition, our results showed that each of the 14 newborns had an additional variant as detected by NBGS. Thus, our findings provide a better understanding of the limitations of flow-through hybridization detection. Even when the flow-through hybridization test is negative, it should be kept in mind that deafness still has a genetic cause, as variants associated with the risk factors for deafness may be located in undetected regions [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The advantage of applying NBGS to this specific population is that it can detect gene variants not included in flow-through hybridization (7.14% in this study, 14/196), which is beneficial for clinical applications and cost saving. If newborn hearing screening is prioritized, services for timely intervention must be established. Otherwise, the early identification of hearing loss provides no advantage. With the increasing number of in-depth studies on deafness genes, new genes and variant types may be included in genetic deafness screening, which may greatly improve the accuracy of genetic screening and provide a more reliable and detailed basis for genetic counseling and research [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe disease selection of the panel used in this study was based on the current domestic and foreign disease spectrum of neonatal screening, international reports of neonatal screening disease spectrum and genetic diseases with high prevalence reported in the literature, and combined with more than 40 years of neonatal screening experience in China. After multiple repeated designs of the panel, 112 diseases and 246 genes were ultimately identified in the panel and were used as the NBGS. The 246 genes that may be candidate genes for future genetic screening in newborns. If this genetic testing can be applied clinically, it will undoubtedly serve as a diagnostic method for neonatal genetic diseases, which can shorten the time for disease intervention and treatment, thereby improving the health outcomes of patients. However, the premise is that the pathogenicity of all genetic variations of the included disease has been identified. Additionally, based on current NBGS cost, we estimate the cost of conducting NBGS testing to be over \u003cspan\u003e$\u003c/span\u003e100. In China, if NBGS is used for routine clinical testing on a large scale, the government may provide subsidies to offset some patient costs, which contributes to the implementation of genetic screening. Based on the above, we believe that genetic screening will soon be applied as a first-line detection method in clinical practice and achieve satisfactory results.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eBased on the analysis of 223 cases of IEM and 196 cases of deafness, we found that compared to the traditional screening methods of MS/MS-NGS for IEM and flow-through hybridization for deafness, NBGS can detect a more comprehensive set of variants and reduce the false-positive rate. Furthermore, a shortened reporting cycle allows for the early detection of diseases, with detection rates comparable to those of the other two methods. ​However, many genetic screening strategies for rare diseases are still in the exploratory stage, and the disease types, genes, and loci to be included in neonatal genetic screening may require further evaluation. Overall, NBGS can be considered a new method for screening newborns for IEM, deafness, and other genetic disorders in clinical practice.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eNBS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Newborn screening\u003c/p\u003e\n\u003cp\u003eIEM\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Inborn errors of metabolism\u003c/p\u003e\n\u003cp\u003eNBGS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Newborn genetic screening\u003c/p\u003e\n\u003cp\u003eMS/MS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Tandem mass spectrometry\u003c/p\u003e\n\u003cp\u003eNGS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Next-generation sequencing\u003c/p\u003e\n\u003cp\u003eDBS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Dry blood spots\u003c/p\u003e\n\u003cp\u003ePKU\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Phenylketonuria\u003c/p\u003e\n\u003cp\u003eWES\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Whole exome sequencing\u003c/p\u003e\n\u003cp\u003eWGS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Whole genome sequencing\u003c/p\u003e\n\u003cp\u003ePCR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Polymerase chain reaction\u003c/p\u003e\n\u003cp\u003eCNV\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Copy number variants\u003c/p\u003e\n\u003cp\u003eAAM\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Amino acid\u0026nbsp;metabolism\u003c/p\u003e\n\u003cp\u003eOAM\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Organic acid metabolism\u003c/p\u003e\n\u003cp\u003eFAM \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Fatty acid metabolism\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eL. W. and Y. W. designed and conceived the study. S. M. and Z. W. drafted the manuscript and performed statistical analysis. S. L. and X. T. collected study data. S.M. L. and Y. Z. revised the manuscript. S. M. and Z. W. have contributed equally to this work and share the first authorship.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work\u0026nbsp;was supported by the Program of Maternal and Child Health Research Project of Jiangsu Province (No. F202120) and the Program of Maternal and Child Health Research Project of Lianyungang City (No. F202105).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of Lianyungang Maternal and Child Health Hospital and written informed consent was obtained from all parents or guardians of the newborns before the screening.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eMoreno MA. 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JAMA Netw Open. 2022;5(7):e22\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Newborn screening, Tandem mass spectrometry, Newborn genetic screening, Inborn error of metabolism, Deafness","lastPublishedDoi":"10.21203/rs.3.rs-3995451/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3995451/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Traditional newborn screening (NBS) for inborn errors of metabolism (IEM) and deafness has limitations due to the detection of fewer genetic disorders and variants, higher false-positive rates, and longer detection periods. This study aimed to explore the clinical validity of newborn genetic screening (NBGS) in newborns with IEM and deafness.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e We retrospectively enrolled 223 cases screened for IEM by tandem mass spectrometry (MS/MS)-next-generation sequencing (NGS), including 55 positive, 68 suspected positive, and 100 negative cases. Additionally, 196 cases screened for deafness were enrolled, including 96 variant-positive and 100 negative cases. Dry blood spot samples from the newborns were used for NBGS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e For IEM, NBGS detected 34 positives in 55 positive cases with a sensitivity of 61.8% (34/55), whereas variants were not detected in 21 cases. Four additional positive cases were found, including one at risk of glucose-6-phosphate dehydrogenase deficiency and three at risk of deafness. The diagnostic time observed between the two methods exhibited a significant difference: 13 days for NBGS and 35 days for MS/MS-NGS. For deafness, the consistency in the positive results between the two methods was 96.9% (93/96). Unexpectedly, three mitochondrial gene (\u003cem\u003eMT-RNR1\u003c/em\u003e) heterogeneous variants (m.1555A\u0026gt;G and m.7445A\u0026gt;G) were not detected by NBGS. We also detected nine variants out of 100 negative cases, including seven \u003cem\u003eGJB2 \u003c/em\u003e(c.109G\u0026gt;A), one \u003cem\u003eGJB3 \u003c/em\u003e(c.547G\u0026gt;A),\u003cem\u003e \u003c/em\u003eand one \u003cem\u003eMYO15A\u003c/em\u003e (c.10250_10252delCCT), with a 9% (9/100) detection rate by NBGS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e As a novel screening method for newborns, NBGS can detect more gene variants, reduce the false-positive rate, and shorten the diagnostic cycle. Our research provides a foundation for the clinical application of NBGS.\u003c/p\u003e","manuscriptTitle":"Integrating Newborn Genetic Screening with Traditional Screening to Improve Newborn Screening","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-08 19:01:28","doi":"10.21203/rs.3.rs-3995451/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b53fa739-3079-4eb4-bf4b-2adc12ea5a46","owner":[],"postedDate":"March 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-07-03T10:54:31+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-08 19:01:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3995451","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3995451","identity":"rs-3995451","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}