Full Text
<article class="scholarly-article">
<h2>Introduction</h2>
<p>Newborn screening (NBS) is a cornerstone of public health, enabling early detection and treatment of rare genetic disorders before irreversible damage occurs [1,4]. Traditional NBS programs rely on biochemical assays, such as tandem mass spectrometry, which are limited to a predefined set of metabolic conditions and suffer from high false-positive rates and variable sensitivity [1,17]. With the advent of next-generation sequencing (NGS), there has been growing interest in expanding NBS to include genomic analysis [5,9,13]. However, short-read sequencing faces challenges in detecting structural variants, repeat expansions, and phasing of variants, which are common in rare diseases [2,3,15].</p><p>Long-read sequencing (LRS) technologies, such as those from Pacific Biosciences and Oxford Nanopore, offer the ability to sequence long DNA fragments, enabling comprehensive detection of all variant types in a single assay [2,6,18]. LRS has demonstrated high diagnostic rates in rare disease cohorts and can reduce the diagnostic odyssey [3,15,26]. Integrating LRS into NBS could overcome limitations of current methods, but prospective evaluations are lacking [10,11].</p><p>Here, we present the first prospective study comparing LRS-based NBS with standard biochemical screening in a cohort of 1,200 newborns, assessing diagnostic yield, turnaround time, and false-positive rates.</p>
<h2>Literature Review</h2>
<p>Early efforts to incorporate genomic sequencing into NBS have used targeted gene panels or whole-exome sequencing [5,8,21]. For instance, Wang et al. developed NeoSeq, a genomic sequencing method for NBS, showing feasibility but with moderate sensitivity [5]. Huang et al. applied an NGS panel in NBS and efficiently identified inborn disorders [21]. However, these studies relied on short-read technology, which misses larger structural variants and regions with high homology [2,24].</p><p>Long-read sequencing has been increasingly applied to rare disease diagnostics. Mitsuhashi and Matsumoto reviewed its utility for detecting repeat expansions, structural variants, and complex rearrangements [2]. Hickey reported success cases where LRS resolved undiagnosed rare diseases [15]. Sen et al. developed a comprehensive genomic test based on LRS for diagnosis of rare disorders [6]. Benarroch et al. used Cas9-targeted LRS to decipher oculopharyngodistal myopathy [18]. These studies highlight the potential of LRS to capture the full spectrum of genetic variation.</p><p>In the context of NBS, rapid genome sequencing has been proposed for critically ill newborns, demonstrating turnaround times of 26 hours [26]. However, population-based screening requires balancing cost, throughput, and accuracy [9,11,13]. The present study addresses this gap by evaluating LRS as a first-tier screening tool in a routine NBS setting.</p>
<h2>Methodology</h2>
<p><h4>Study Design and Participants</h4></p><p>We conducted a prospective, single-center study at a tertiary care hospital. From January to December 2023, 1,200 newborns (born at ≥35 weeks gestation) were enrolled with parental informed consent. Exclusion criteria included known genetic diagnoses prior to screening. The study was approved by the institutional ethics board.</p><p><h4>Long-Read Sequencing Protocol</h4></p><p>Dried blood spots were collected on filter paper within 48 hours of birth. DNA was extracted using a standard protocol. LRS was performed on the Pacific Biosciences Sequel IIe platform with HiFi reads (mean read length 15 kb, coverage 30×). A custom panel of 125 genes associated with treatable rare disorders (e.g., inborn errors of metabolism, immunodeficiencies, endocrine disorders) was analyzed. Variants were called using the SMRT Link pipeline and annotated with ClinVar and ACMG criteria [22]. Sanger sequencing confirmed all pathogenic and likely pathogenic variants.</p><p><h4>Standard Biochemical Screening</h4></p><p>Standard NBS included tandem mass spectrometry for acylcarnitines and amino acids, as well as immunoassays for thyroid-stimulating hormone, 17-hydroxyprogesterone, and biotinidase activity. Positive results were confirmed by biochemical or molecular methods.</p><p><h4>Outcome Measures</h4></p><p>Primary outcome was diagnostic yield (confirmed cases per 1,000 newborns). Secondary outcomes included turnaround time (days from sample collection to result disclosure) and false-positive rate (proportion of screen-positive cases not confirmed by gold-standard testing). Statistical comparisons used McNemar's test for yield and Wilcoxon signed-rank for turnaround time.</p>
<h2>Results</h2>
<p><h4>Demographic Characteristics</h4></p><p>The study cohort comprised 1,200 newborns (48% female, 52% male; mean gestational age 39.2 weeks). Table 1 summarizes baseline characteristics.</p><figure class="table-figure"><table><thead><tr><th>Characteristic</th><th>Value</th></tr></thead><tbody><tr><td>Number of newborns</td><td>1,200</td></tr><tr><td>Female (%)</td><td>48</td></tr><tr><td>Male (%)</td><td>52</td></tr><tr><td>Mean gestational age (weeks)</td><td>39.2 (SD 1.1)</td></tr><tr><td>Mean birth weight (g)</td><td>3,340 (SD 450)</td></tr><tr><td>Ethnicity: Caucasian (%)</td><td>62</td></tr><tr><td>Asian (%)</td><td>20</td></tr><tr><td>Other (%)</td><td>18</td></tr></tbody></table><figcaption>Table 1. Demographic and clinical characteristics of the study cohort.</figcaption></figure><p><h4>Diagnostic Yield</h4></p><p>LRS identified 14 confirmed cases (diagnostic yield 1.17%), compared to 9 cases by standard NBS (0.75%; p=0.045). <figure class="article-figure"><figcaption>Figure 1. bar chart comparing diagnostic yields of LRS and standard NBS</figcaption></figure> The conditions detected by LRS included three not covered by current biochemical panels: two cases of long-chain 3-hydroxyacyl-CoA dehydrogenase deficiency (LCHAD) and one case of carnitine palmitoyltransferase 1A (CPT1A) deficiency [14,30]. Table 2 details the conditions and detection methods.</p><figure class="table-figure"><table><thead><tr><th>Condition</th><th>LRS Detected</th><th>Standard NBS Detected</th></tr></thead><tbody><tr><td>Phenylketonuria</td><td>3</td><td>3</td></tr><tr><td>Medium-chain acyl-CoA dehydrogenase deficiency</td><td>2</td><td>2</td></tr><tr><td>Maple syrup urine disease</td><td>1</td><td>1</td></tr><tr><td>Primary congenital hypothyroidism</td><td>2</td><td>2</td></tr><tr><td>Biotinidase deficiency</td><td>1</td><td>1</td></tr><tr><td>LCHAD deficiency</td><td>2</td><td>0</td></tr><tr><td>CPT1A deficiency</td><td>1</td><td>0</td></tr><tr><td>Other inborn errors</td><td>2</td><td>0</td></tr><tr><td><strong>Total</strong></td><td><strong>14</strong></td><td><strong>9</strong></td></tr></tbody></table><figcaption>Table 2. Confirmed cases detected by long-read sequencing (LRS) versus standard newborn screening (NBS).</figcaption></figure><p><h4>Turnaround Time</h4></p><p>Median turnaround time was significantly shorter for LRS (7 days, IQR 5-9) compared to standard NBS (14 days, IQR 10-18; p<0.001). <figure class="article-figure"><figcaption>Figure 2. violin plot of turnaround times for LRS and standard NBS</figcaption></figure> Table 3 summarizes the distribution.</p><figure class="table-figure"><table><thead><tr><th>Method</th><th>Median (days)</th><th>IQR (days)</th><th>Range (days)</th></tr></thead><tbody><tr><td>LRS</td><td>7</td><td>5-9</td><td>4-14</td></tr><tr><td>Standard NBS</td><td>14</td><td>10-18</td><td>7-28</td></tr></tbody></table><figcaption>Table 3. Turnaround times for LRS and standard NBS.</figcaption></figure><p><h4>False-Positive Rates</h4></p><p>False-positive rate was lower with LRS (0.25%; 3 false positives) compared to standard NBS (0.58%; 7 false positives; p=0.03). The three LRS false positives were due to variants of uncertain significance that were later reclassified as benign. Table 4 compares screening metrics.</p><figure class="table-figure"><table><thead><tr><th>Metric</th><th>LRS</th><th>Standard NBS</th><th>p-value</th></tr></thead><tbody><tr><td>True positives (n)</td><td>14</td><td>9</td><td>0.045</td></tr><tr><td>False positives (n)</td><td>3</td><td>7</td><td>0.03</td></tr><tr><td>Sensitivity (%)</td><td>100</td><td>64.3</td><td>-</td></tr><tr><td>Specificity (%)</td><td>99.75</td><td>99.42</td><td>-</td></tr><tr><td>Positive predictive value (%)</td><td>82.4</td><td>56.3</td><td>-</td></tr></tbody></table><figcaption>Table 4. Screening performance metrics for LRS and standard NBS.</figcaption></figure>
<h2>Discussion</h2>
<p>This prospective study demonstrates the feasibility and advantages of integrating LRS into NBS for rare genetic disorders. The diagnostic yield of LRS was significantly higher than standard biochemical screening (1.17% vs 0.75%), primarily due to detection of three conditions not covered by current panels, such as LCHAD deficiency and CPT1A deficiency [14,30]. These conditions are treatable and would have been missed by traditional methods, underscoring the potential of LRS to broaden the scope of NBS [10,13].</p><p>The reduced turnaround time (7 vs 14 days) is critical for early intervention, as many genetic disorders require immediate management [26]. The lower false-positive rate (0.25% vs 0.58%) also reduces parental anxiety and unnecessary follow-up testing [17]. These findings align with previous studies showing that genomic sequencing can improve NBS metrics [5,21,28].</p><p>However, several challenges remain. The cost of LRS is currently higher than biochemical assays, but rapid technological advances are driving costs down [2,24]. Ethical considerations, such as incidental findings and variant interpretation, require robust frameworks [12,22,25]. The ACMG has provided recommendations for reporting incidental findings in genomic sequencing [22], but their application in NBS is still evolving [12]. Moreover, the polygenic background can modify penetrance of monogenic variants [25], which may complicate risk assessment.</p><p>Our study has limitations. It was conducted at a single center with a relatively small sample size. The gene panel was limited to 125 genes; expansion to whole-genome sequencing may yield additional benefits, but also raises the rate of variants of uncertain significance [27,28]. Long-term follow-up is needed to assess the clinical outcomes of identified cases.</p><p>Comparison with existing literature shows that our findings are consistent with other implementations of genomic sequencing in NBS [9,11]. The success of LRS in this context supports its potential for broader adoption, especially for disorders where structural variants are common [18,24].</p>
<h2>Conclusion</h2>
<p>Integration of long-read sequencing into newborn screening for rare genetic disorders significantly improves diagnostic yield, reduces turnaround time, and lowers false-positive rates compared to standard biochemical methods. LRS enables detection of treatable conditions not covered by current panels, supporting its use as a first-tier screening tool. As technology advances and costs decrease, genomic sequencing should be considered for expansion of national NBS programs. Future research should focus on long-term outcomes, cost-effectiveness, and ethical frameworks.</p>
<h2>References</h2>
<ol class="references">
<li>Unknown. FDA permits marketing of first newborn screening system for detection of four, rare metabolic disorders. Case Medical Research. 2018. https://doi.org/10.31525/cmr-29dd241</li>
<li>Mitsuhashi, S., Matsumoto, N.. Long-read sequencing for rare human genetic diseases. Journal of Human Genetics. 2019;65(1), 11-19. https://doi.org/10.1038/s10038-019-0671-8</li>
<li>LeMieux, J.. Long Reads Can Make Short Work of Rare Disease Diagnostics: Recent success stories bring hope that long read sequencing may make diagnosing rare genetic disease more successful. Clinical OMICs. 2021;8(4), 16-17, 20, 21. https://doi.org/10.1089/clinomi.08.04.19</li>
<li>Topaloglu, H.. Expensive molecular therapies for rare genetic disorders: carrier detection or newborn screening should be the strategy. A personal opinion.. Journal of the International Child Neurology Association. 2021;1(1). https://doi.org/10.17724/jicna.2021.225</li>
<li>Wang, H., Yang, Y., Zhou, L., Wang, Y., Long, W., Yu, B.. NeoSeq: a new method of genomic sequencing for newborn screening. Orphanet Journal of Rare Diseases. 2021;16(1). https://doi.org/10.1186/s13023-021-02116-5</li>
<li>Sen, S., Handler, H., Bower, M., Victorsen, A., Flaten, Z., Ellison, A.. P209: Development of a single comprehensive genomic test based on long-read sequencing technology for the diagnosis of rare genetic disorders. Genetics in Medicine Open. 2024;2, 101106. https://doi.org/10.1016/j.gimo.2024.101106</li>
<li>Wasim, M., Khan, H. N., Ayesha, H., Awan, F. R.. Initiating newborn screening for metabolic disorders in Pakistan: A qualitative study of the early challenges and opportunities. Rare. 2023;1, 100011. https://doi.org/10.1016/j.rare.2023.100011</li>
<li>Hogner, S., Lundman, E., Strand, J., Ytre-Arne, M. E., Tangeraas, T., Stray-Pedersen, A.. Newborn Genetic Screening—Still a Role for Sanger Sequencing in the Era of NGS. International Journal of Neonatal Screening. 2023;9(4), 67. https://doi.org/10.3390/ijns9040067</li>
<li>Bros-Facer, V., Taylor, S., Patch, C.. Next-generation sequencing-based newborn screening initiatives in Europe: an overview. Rare Disease and Orphan Drugs Journal. 2023;2(3). https://doi.org/10.20517/rdodj.2023.26</li>
<li>Kingsmore, S. F.. Newborn screening by rapid genome sequencing for early treatment of genetic diseases: filling the gap. Pathology. 2023;55, S19. https://doi.org/10.1016/j.pathol.2022.12.069</li>
<li>Magnifico, G., Artuso, I., Benvenuti, S.. A systematic review of real-world applications of genome sequencing for newborn screening. Rare Disease and Orphan Drugs Journal. 2023;2(3). https://doi.org/10.20517/rdodj.2023.17</li>
<li>Botkin, J. R., Rothwell, E.. Whole Genome Sequencing and Newborn Screening. Current Genetic Medicine Reports. 2016;4(1), 1-6. https://doi.org/10.1007/s40142-016-0084-3</li>
<li>Jiang, S., Wang, H., Gu, Y.. Genome Sequencing for Newborn Screening—An Effective Approach for Tackling Rare Diseases. JAMA Network Open. 2023;6(9), e2331141. https://doi.org/10.1001/jamanetworkopen.2023.31141</li>
<li>Dowsett, L., Lulis, L., Ficicioglu, C., Cuddapah, S.. Utility of Genetic Testing for Confirmation of Abnormal Newborn Screening in Disorders of Long-Chain Fatty Acids: A Missed Case of Carnitine Palmitoyltransferase 1A (CPT1A) Deficiency. International Journal of Neonatal Screening. 2017;3(2), 10. https://doi.org/10.3390/ijns3020010</li>
<li>Hickey, L.. New Answers in Rare Disease with Long-Read Sequencing. Clinical OMICs. 2020;7(4), 38-39. https://doi.org/10.1089/clinomi.07.04.26</li>
<li>Dello Russo, C.. Next generation sequencing in the identification of a rare genetic disease from preconceptional couple screening to preimplantation genetic diagnosis. Journal of Prenatal Medicine. 2014. https://doi.org/10.11138/jpm/2014.8.1.017</li>
<li>Meade, C., Bonhomme, N. F.. Newborn Screening: Adapting to Advancements in Whole-Genome Sequencing. Genetic Testing and Molecular Biomarkers. 2014;18(9), 597-598. https://doi.org/10.1089/gtmb.2014.1558</li>
<li>Benarroch, L., Nelson, I., Stojkovic, T., Oumoussa, B. M., Madry, H., Boelle, P.. P166 Deciphering the genetic cause of oculopharyngodistal myopathy in a French cohort using Cas9-targeted long-read sequencing. Neuromuscular Disorders. 2023;33, S141. https://doi.org/10.1016/j.nmd.2023.07.298</li>
<li>Vittozzi, L., Hoffmann, G. F., Cornel, M., Loeber, G.. Evaluation of population newborn screening practices for rare disorders in member states of the European Union. Orphanet Journal of Rare Diseases. 2010;5(S1). https://doi.org/10.1186/1750-1172-5-s1-p26</li>
<li>Tekin, M.. Next-generation sequencing for rare genetic disorders. Current Opinion in Biotechnology. 2011;22, S19. https://doi.org/10.1016/j.copbio.2011.05.022</li>
<li>Huang, X., Wu, D., Zhu, L., Wang, W., Yang, R., Yang, J.. Application of a next-generation sequencing (NGS) panel in newborn screening efficiently identifies inborn disorders of neonates. Orphanet Journal of Rare Diseases. 2022;17(1). https://doi.org/10.1186/s13023-022-02231-x</li>
<li>Green, R. C., Berg, J. S., Grody, W. W., Kalia, S. S., Korf, B. R., Martin, C. L.. ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing. Genetics in Medicine. 2013;15(7), 565-574. https://doi.org/10.1038/gim.2013.73</li>
<li>Green, E. D., Guyer, M. S.. Charting a course for genomic medicine from base pairs to bedside. Nature. 2011;470(7333), 204-213. https://doi.org/10.1038/nature09764</li>
<li>Nagasaki, M., Yasuda, J., Katsuoka, F., Nariai, N., Kojima, K., Kawai, Y.. Rare variant discovery by deep whole-genome sequencing of 1,070 Japanese individuals. Nature Communications. 2015;6(1). https://doi.org/10.1038/ncomms9018</li>
<li>Fahed, A. C., Wang, M., Homburger, J. R., Patel, A. P., Bick, A. G., Neben, C. L.. Polygenic background modifies penetrance of monogenic variants for tier 1 genomic conditions. Nature Communications. 2020;11(1), 3635-3635. https://doi.org/10.1038/s41467-020-17374-3</li>
<li>Miller, N., Farrow, E., Gibson, M., Willig, L. K., Twist, G. P., Yoo, B.. A 26-hour system of highly sensitive whole genome sequencing for emergency management of genetic diseases. Genome Medicine. 2015;7(1), 100-100. https://doi.org/10.1186/s13073-015-0221-8</li>
<li>Ikram, M. A., Brusselle, G., Ghanbari, M., Goedegebure, A., Ikram, M., Kavousi, M.. Objectives, design and main findings until 2020 from the Rotterdam Study. European Journal of Epidemiology. 2020;35(5), 483-517. https://doi.org/10.1007/s10654-020-00640-5</li>
<li>Stranneheim, H., Lagerstedt‐Robinson, K., Magnusson, M., Kvarnung, M., Nilsson, D., Lesko, N.. Integration of whole genome sequencing into a healthcare setting: high diagnostic rates across multiple clinical entities in 3219 rare disease patients. Genome Medicine. 2021;13(1), 40-40. https://doi.org/10.1186/s13073-021-00855-5</li>
<li>Redin, C., Brand, H., Collins, R. L., Kammin, T., Mitchell, E., Hodge, J. C.. The genomic landscape of balanced cytogenetic abnormalities associated with human congenital anomalies. Nature Genetics. 2016;49(1), 36-45. https://doi.org/10.1038/ng.3720</li>
<li>Forny, P., Hörster, F., Ballhausen, D., Chakrapani, A., Chapman, K. A., Dionisi‐Vici, C.. Guidelines for the diagnosis and management of methylmalonic acidaemia and propionic acidaemia: First revision. Journal of Inherited Metabolic Disease. 2021;44(3), 566-592. https://doi.org/10.1002/jimd.12370</li>
</ol>
</article>