Defining the Minimal Long-Term Follow-Up Data Elements for Newborn Screening.

Newborn screening (NBS) is hailed as a public health success, but little is known about the long-term outcomes following a positive newborn screen. There has been difficulty gathering long-term follow-up (LTFU) data consistently, reliably, and with minimal effort. Six programs developed and tested a core set of minimal LTFU data elements. After an iterative data collection process and the development of a data collection tool, the group agreed on the minimal LTFU data elements. The denominator captured all infants with an NBS diagnosis, accounting for children who moved or died prior to the follow-up year. They also agreed on three LTFU outcomes: if the child was still alive, had contact with a specialist, and received appropriate care specific to their diagnosis within the year. The six programs representing NBS public health programs, clinical providers, and research programs provided data across multiple NBS disorders. In 2022, 83.8% (563/672) of the children identified by the LTFU programs were alive and living in the jurisdiction; of those, 92.0% (518/563) saw a specialist, and 87.7% (494/563) received appropriate care. The core LTFU data elements can be applied as a foundation to address the impact of early diagnosis by NBS within and across jurisdictions.

Long-Term Follow-Up Cares and Check Initiative: A Program to Advance Long-Term Follow-Up in Newborns Identified with a Disease through Newborn Screening.

In the United States and around the world, newborns are screened on a population basis for conditions benefiting from pre-symptomatic diagnosis and treatment. The number of screened conditions continues to expand as novel technologies for screening, diagnosing, treating, and managing disease are discovered. While screening all newborns facilitates early diagnosis and treatment, most screened conditions are treatable but not curable. Patients identified by newborn screening often require lifelong medical management and community support to achieve the best possible outcome. To advance the long-term follow-up of infants identified through newborn screening (NBS), the Long-Term Follow-up Cares and Check Initiative (LTFU-Cares and Check) designed, implemented, and evaluated a system of longitudinal data collection and annual reporting engaging parents, clinical providers, and state NBS programs. The LTFU-Cares and Check focused on newborns identified with spinal muscular atrophy (SMA) through NBS and the longitudinal health information prioritized by parents and families. Pediatric neurologists who care for newborns with SMA entered annual data, and data tracking and visualization tools were delivered to state NBS programs with a participating clinical center. In this publication, we report on the development, use of, and preliminary results from the LTFU-Cares and Check Initiative, which was designed as a comprehensive model of LTFU. We also propose next steps for achieving the goal of a national system of LTFU for individuals with identified conditions by meaningfully engaging public health agencies, clinicians, parents, families, and communities.

Landscape Analysis of Neurodevelopmental Comorbidities in Newborn Screening Conditions: Challenges and Opportunities.

Newborn screening (NBS) is a large-scale public health program in the US that screens 3.8 million newborns for up to 81 genetic conditions each year. Many of these conditions have comorbidities, including neurodevelopmental disorders (NDDs). These comorbidities can have a significant impact on health outcomes across the lifespan. Most screened conditions are inborn errors of metabolism. PKU, the first condition identified by NBS, is an inherited metabolic disorder that can cause developmental delays and intellectual/developmental disabilities if not treated. The Newborn Screening Translational Research Network (NBSTRN) is a program that has been funded by the National Institute of Child Health and Human Development since 2008. NBSTRN is charged with developing, maintaining, and enhancing tools, resources, and expertise supporting NBS research. One of the tasks led by NBSTRN is to provide direction for developing question/answer sets used in the Longitudinal Pediatric Data Resource (LPDR) to create consensus-based and standardized common data elements (CDEs) for NBS conditions. There is growing interest in the NBS community in assessing neurodevelopmental trajectories through long-term follow-up studies. This could be streamlined by employing uniform CDEs. To address this unmet need, we conducted a landscape analysis to (1) explore the co-occurrence of NDD-related comorbidities and NBS conditions using text mining in MedGen, (2) compile a list of NDD-related CDEs from existing repositories as well as LPDR data dictionaries, and (3) identify challenges and knowledge gaps hindering the early identification of risks for NDDs in NBS conditions. Our findings can inform future efforts toward advancing the research infrastructure for this established public health program. The renewed awareness of the risk of NDDs after a positive NBS and diagnosis could lead to improved treatment guidelines for mental health conditions.

NBSTRN Tools to Advance Newborn Screening Research and Support Newborn Screening Stakeholders.

Rapid advances in the screening, diagnosis, and treatment of genetic disorders have increased the number of conditions that can be detected through universal newborn screening (NBS). However, the addition of conditions to the Recommended Uniform Screening Panel (RUSP) and the implementation of nationwide screening has been a slow process taking several years to accomplish for individual conditions. Here, we describe web-based tools and resources developed and implemented by the newborn screening translational research network (NBSTRN) to advance newborn screening research and support NBS stakeholders worldwide. The NBSTRN's tools include the Longitudinal Pediatric Data Resource (LPDR), the NBS Condition Resource (NBS-CR), the NBS Virtual Repository (NBS-VR), and the Ethical, Legal, and Social Issues (ELSI) Advantage. Research programs, including the Inborn Errors of Metabolism Information System (IBEM-IS), BabySeq, EarlyCheck, and Family Narratives Use Cases, have utilized NBSTRN's tools and, in turn, contributed research data to further expand and refine these resources. Additionally, we discuss ongoing tool development to facilitate the expansion of genetic disease screening in increasingly diverse populations. In conclusion, NBSTRN's tools and resources provide a trusted platform to enable NBS stakeholders to advance NBS research and improve clinical care for patients and their families.

Newborn sequencing is only part of the solution for better child health.

Newborn screening (NBS) aims to detect newborns with severe congenital diseases before the onset of clinical manifestations. Advancements in genomic technologies have led to proposals for the development of genomic-based NBS (G-NBS) in concert with traditional NBS. Proponents of G-NBS highlight how G-NBS could expand the number of diseases screened at birth to thousands and spur the development of new drugs and treatments for rare diseases. Balancing the excitement, some experts have pointed to the ethical dilemmas linked to G-NBS. The dialog, however, has yet to engage with sufficient urgency on how the new G-NBS might chart a course for improving the health of all children. Our analysis of more than 130 million births in the United States between 1959 and 1995 shows that traditional NBS led to improvements in infant mortality and health equity only when it was implemented in association with measures to improve healthcare access for children. We suggest that the new G-NBS will lead to better child health only when the same degree of attention devoted to genomic technologies will be directed to the promotion of public health measures that facilitate access to high-quality healthcare for all children.

Factors influencing creatine kinase-MM concentrations in newborns and implications for newborn screening for Duchenne muscular dystrophy.

INTRODUCTION: Newborn screening for Duchenne muscular dystrophy can be performed via a first-tier creatine kinase-MM measurement followed by reflex testing to second-tier molecular analysis of the DMD gene. In order to establish appropriate cut-offs for the creatine kinase-MM screen, factors that influence creatine kinase-MM in newborns were investigated. MATERIALS AND METHODS: Creatine kinase-MM data from a consented pilot study in New York State were collected over a two-year period and combined with de-identified validation data and analyzed. Univariate analysis and multiple linear regression analysis were performed. RESULTS: The analysis indicated that age of newborn at specimen collection, gestational age and birth weight were significant influencers of CK-MM levels in newborns. In addition, to a lesser extent, sex, race/ethnicity and seasonal temperature also affect CK-MM levels in newborns. CONCLUSIONS: To reduce false positive and false negative cases, newborn screening programs should be cognizant of factors that influence CK-MM when determining cut-offs for the assay. Variability based on age at specimen collection and birth weight are primarily observed within the first week of life. Therefore, particularly during this time period, multi-tiered cut-offs based on age of collection and lower cut-offs for premature and low birth weight babies are recommended. Other cut-off determinants may include sex, race/ethnicity and seasonal temperature.

Newborn screening for Duchenne muscular dystrophy: A two-year pilot study.

OBJECTIVE: Duchenne muscular dystrophy (DMD) is an X-linked disorder resulting in progressive muscle weakness and atrophy, cardiomyopathy, and in late stages, cardiorespiratory impairment, and death. As treatments for DMD have expanded, a DMD newborn screening (NBS) pilot study was conducted in New York State to evaluate the feasibility and benefit of NBS for DMD and to provide an early pre-symptomatic diagnosis. METHODS: At participating hospitals, newborns were recruited to the pilot study, and consent was obtained to screen the newborn for DMD. The first-tier screen measured creatine kinase-MM (CK-MM) in dried blood spot specimens submitted for routine NBS. Newborns with elevated CK-MM were referred for genetic counseling and genetic testing. The latter included deletion/duplication analysis and next-generation sequencing (NGS) of the DMD gene followed by NGS for a panel of neuromuscular conditions if no pathogenic variants were detected in the DMD gene. RESULTS: In the two-year pilot study, 36,781 newborns were screened with CK-MM. Forty-two newborns (25 male and 17 female) were screen positive and referred for genetic testing. Deletions or duplications in the DMD gene were detected in four male infants consistent with DMD or Becker muscular dystrophy. One female DMD carrier was identified. INTERPRETATION: This study demonstrated that the state NBS program infrastructure and screening technologies we used are feasible to perform NBS for DMD. With an increasing number of treatment options, the clinical utility of early identification for affected newborns and their families lends support for NBS for this severe disease.

Moving away from one disease at a time: Screening, trial design, and regulatory implications of novel platform technologies.

Most rare diseases are caused by single-gene mutations, and as such, lend themselves to a host of new gene-targeted therapies and technologies including antisense oligonucleotides, phosphomorpholinos, small interfering RNAs, and a variety of gene delivery and gene editing systems. Early successes are encouraging, however, given the substantial number of distinct rare diseases, the ability to scale these successes will be unsustainable without new development efficiencies. Herein, we discuss the need for genomic newborn screening to match pace with the growing development of targeted therapeutics and ability to rapidly develop individualized therapies for rare variants. We offer approaches to move beyond conventional "one disease at a time" preclinical and clinical drug development and discuss planned regulatory innovations that are necessary to speed therapy delivery to individuals in need. These proposals leverage the shared properties of platform classes of therapeutics and innovative trial designs including master and platform protocols to better serve patients and accelerate drug development. Ultimately, there are risks to these novel approaches; however, we believe that close partnership and transparency between health authorities, patients, researchers, and drug developers present the path forward to overcome these challenges and deliver on the promise of gene-targeted therapies for rare diseases.

Data sharing to advance gene-targeted therapies in rare diseases.

Recent advancements in gene-targeted therapies have highlighted the critical role data sharing plays in successful translational drug development for people with rare diseases. To scale these efforts, we need to systematize these sharing principles, creating opportunities for more rapid, efficient, and scalable drug discovery/testing including long-term and transparent assessment of clinical safety and efficacy. A number of challenges will need to be addressed, including the logistical difficulties of studying rare diseases affecting individuals who may be scattered across the globe, scientific, technical, regulatory, and ethical complexities of data collection, and harmonization and integration across multiple platforms and contexts. The NCATS/NIH Gene-Targeted Therapies: Early Diagnosis and Equitable Delivery meeting series held during June 2021 included data sharing models that address these issues and framed discussions of areas that require improvement. This article describes these discussions and provides a series of considerations for future data sharing.

Molecular Basis and Evolutionary Origin of 1-Nitronaphthalene Catabolism in Sphingobium sp. Strain JS3065.

Nitrated polycyclic aromatic hydrocarbons (nitro-PAHs) enter the environment from natural sources and anthropogenic activities. To date, microorganisms able to mineralize nitro-PAHs have not been reported. Here, Sphingobium sp. strain JS3065 was isolated by selective enrichment for its ability to grow on 1-nitronaphthalene as the sole carbon, nitrogen, and energy source. Analysis of the complete genome of strain JS3065 indicated that the gene cluster encoding 1-nitronaphthalene catabolism (nin) is located on a plasmid. Based on the genetic and biochemical evidence, the nin genes share an origin with the nag-like genes encoding naphthalene degradation in Ralstonia sp. strain U2. The initial step in degradation of 1-nitronaphthalene is catalyzed by a three-component dioxygenase, NinAaAbAcAd, resulting in formation of 1,2-dihydroxynaphthalene which is also an early intermediate in the naphthalene degradation pathway. Introduction of the ninAaAbAcAd genes into strain U2 enabled its growth on 1-nitronaphthalene. Phylogenic analysis of NinAc suggested that an ancestral 1-nitronaphthalene dioxygenase was an early step in the evolution of nitroarene dioxygenases. Based on bioinformatic analysis and enzyme assays, the subsequent assimilation of 1,2-dihydroxynaphthalene seems to follow the well-established pathway for naphthalene degradation by Ralstonia sp. strain U2. This is the first report of catabolic pathway for 1-nitronaphthalene and is another example of how expanding the substrate range of Rieske type dioxygenase enables bacteria to grow on recalcitrant nitroaromatic compounds. IMPORTANCE Nitrated polycyclic aromatic hydrocarbons (nitro-PAHs) have been widely detected in the environment and they are more toxic than their corresponding parent PAHs. Although biodegradation of many PAHs has been extensively described at genetic and biochemical levels, little is known about the microbial degradation of nitro-PAHs. This work reports the isolation of a Sphingobium strain growing on 1-nitronaphthalene and the genetic basis for the catabolic pathway. The pathway evolved from an ancestral naphthalene catabolic pathway by a remarkably small modification in the specificity of the initial dioxygenase. Data presented here not only shed light on the biochemical processes involved in the microbial degradation of globally important nitrated polycyclic aromatic hydrocarbons, but also provide an evolutionary paradigm for how bacteria evolve a novel catabolic pathway with minimal alteration of preexisting pathways for natural organic compounds.

Special issue: Newborn screening research.

This Special Issue provides a wide-ranging update from the front lines of newborn screening (NBS) research and is the result of conversations and collaborations facilitated by the Newborn Screening Translational Research Network (NBSTRN) across the NBS community and their extended networks. For 14 years NBSTRN has accelerated research efforts to advance NBS by creating a research infrastructure available to the NBS community to discover novel technologies to screen, diagnose, and treat newborns.Authors in this Special issues share their innovative and impactful efforts to advance NBS to include additional conditions, populations, genomics, and information sharing.

Newborn Screening for Duchenne Muscular Dystrophy: First Year Results of a Population-Based Pilot.

Advancements in therapies for Duchenne muscular dystrophy (DMD) have made diagnosis within the newborn period a high priority. We undertook a consortia approach to advance DMD newborn screening in the United States. This manuscript describes the formation of the Duchenne Newborn Screening Consortium, the development of the pilot protocols, data collection tools including parent surveys, and findings from the first year of a two-year pilot. The DMD pilot design is population-based recruitment of infants born in New York State. Data tools were developed to document the analytical and clinical validity of DMD NBS, capture parental attitudes, and collect longitudinal health information for diagnosed newborns. Data visualizations were updated monthly to inform the consortium on enrollment. After 12 months, 15,754 newborns were screened for DMD by the New York State Newborn Screening (NYS NBS) Program. One hundred and forty screened infants had borderline screening results, and sixteen infants were referred for molecular testing. Three male infants were diagnosed with dystrophinopathy. Data from the first year of a two-year NBS pilot for DMD demonstrate the feasibility of NBS for DMD. The consortia approach was found to be a useful model, and the Newborn Screening Translational Research Network's data tools played a key role in describing the NBS pilot findings and engaging stakeholders.

Newborn screening for Duchenne muscular dystrophy-early detection and diagnostic algorithm for female carriers of Duchenne muscular dystrophy.

Duchenne muscular dystrophy (DMD) is the most common pediatric-onset form of muscular dystrophy, occurring in 1 in 5,000 live male births. DMD is a multi-system disease resulting in muscle weakness with progressive deterioration of skeletal, heart, and smooth muscle, and learning disabilities. Pathogenic/likely pathogenic (P/LP) variants in the DMD gene, which encodes dystrophin protein, cause dystrophinopathy. All males with a P/LP variant in the X-linked DMD gene are expected to be affected. Two to 20% of female heterozygotes with a P/LP variant develop symptoms of dystrophinopathy ranging from mild muscle weakness to significant disability similar to Becker muscular dystrophy. Recently, with improvements in therapies and testing methodology, there is stronger evidence supporting newborn screening (NBS) for DMD for males and females because females may also develop symptoms. A consented pilot study to screen newborns for DMD was initiated in New York State (NYS) and conducted from 2019 to 2021. The identification of female carriers and the realization of the subsequent uncertainty of providers concerning follow-up during the pilot led to the development of algorithms for screening and diagnosis of carrier females, including both NBS and cascade molecular testing of family members.

Population-based screening of newborns: Findings from the newborn screening expansion study (part two).

Rapid advances in genomic technologies to screen, diagnose, and treat newborns will significantly increase the number of conditions in newborn screening (NBS). We previously identified four factors that delay and/or complicate NBS expansion: 1) variability in screening panels persists; 2) the short duration of pilots limits information about interventions and health outcomes; 3) recent recommended uniform screening panel (RUSP) additions are expanding the definition of NBS; and 4) the RUSP nomination and evidence review process has capacity constraints. In this paper, we developed a use case for each factor and suggested how model(s) could be used to evaluate changes and improvements. The literature on models was reviewed from a range of disciplines including system sciences, management, artificial intelligence, and machine learning. The results from our analysis highlighted that there is at least one model which could be applied to each of the four factors that has delayed and/or complicate NBS expansion. In conclusion, our paper supports the use of modeling to address the four challenges in the expansion of NBS.

Population-Based Screening of Newborns: Findings From the NBS Expansion Study (Part One).

Each year, through population-based newborn screening (NBS), 1 in 294 newborns is identified with a condition leading to early treatment and, in some cases, life-saving interventions. Rapid advancements in genomic technologies to screen, diagnose, and treat newborns promise to significantly expand the number of diseases and individuals impacted by NBS. However, expansion of NBS occurs slowly in the United States (US) and almost always occurs condition by condition and state by state with the goal of screening for all conditions on a federally recommended uniform panel. The Newborn Screening Translational Research Network (NBSTRN) conducted the NBS Expansion Study to describe current practices, identify expansion challenges, outline areas for improvement in NBS, and suggest how models could be used to evaluate changes and improvements. The NBS Expansion Study included a workshop of experts, a survey of clinicians, an analysis of data from online repositories of state NBS programs, reports and publications of completed pilots, federal committee reports, and proceedings, and the development of models to address the study findings. This manuscript (Part One) reports on the design, execution, and results of the NBS Expansion Study. The Study found that the capacity to expand NBS is variable across the US and that nationwide adoption of a new condition averages 9.5 years. Four factors that delay and/or complicate NBS expansion were identified. A companion paper (Part Two) presents a use case for each of the four factors and highlights how modeling could address these challenges to NBS expansion.

Using Long-Term Follow-Up Data to Classify Genetic Variants in Newborn Screened Conditions.

With the rapid increase in publicly available sequencing data, healthcare professionals are tasked with understanding how genetic variation informs diagnosis and affects patient health outcomes. Understanding the impact of a genetic variant in disease could be used to predict susceptibility/protection and to help build a personalized medicine profile. In the United States, over 3.8 million newborns are screened for several rare genetic diseases each year, and the follow-up testing of screen-positive newborns often involves sequencing and the identification of variants. This presents the opportunity to use longitudinal health information from these newborns to inform the impact of variants identified in the course of diagnosis. To test this, we performed secondary analysis of a 10-year natural history study of individuals diagnosed with metabolic disorders included in newborn screening (NBS). We found 564 genetic variants with accompanying phenotypic data and identified that 161 of the 564 variants (29%) were not included in ClinVar. We were able to classify 139 of the 161 variants (86%) as pathogenic or likely pathogenic. This work demonstrates that secondary analysis of longitudinal data collected as part of NBS finds unreported genetic variants and the accompanying clinical information can inform the relationship between genotype and phenotype.

The Longitudinal Pediatric Data Resource: Facilitating Longitudinal Collection of Health Information to Inform Clinical Care and Guide Newborn Screening Efforts.

The goal of newborn screening is to improve health outcomes by identifying and treating affected newborns. This manuscript provides an overview of a data tool to facilitate the longitudinal collection of health information on newborns diagnosed with a condition through NBS. The Newborn Screening Translational Research Network (NBSTRN) developed the Longitudinal Pediatric Data Resource (LPDR) to capture, store, analyze, visualize, and share genomic and phenotypic data over the lifespan of NBS identified newborns to facilitate understanding of genetic disease and to assess the impact of early identification and treatment. NBSTRN developed a consensus-based process using clinical care experts to create, maintain, and evolve question and answer sets organized into common data elements (CDEs). The LPDR contains 24,172 core and disease specific CDEs for 118 rare genetic diseases, and the CDEs are being made available through the NIH CDE Repository. The number of CDEs for each condition average of 2200 with a range from 69 to 7944. The LPDR is used by state NBS programs, clinical researchers, and community-based organizations. Case level, de-identified data sets are available for secondary research and data mining. The development of the LPDR for longitudinal data gathering, sharing, and analysis supports research and facilitates the translation of discoveries into clinical practice.

Accelerating the Pace of Newborn Screening Research to Advance Disease Understanding and Improve Health Outcomes:: Key Efforts of the Newborn Screening Translational Research Network (NBSTRN).

Each year in the United States, neonatal screening leads to approximately 1 in 220 newborns being identified with a condition that requires treatment, and in some cases, life-saving interventions. Research that discovers new technologies to screen, diagnose, and treat diseases helps to expand the number of conditions that are candidates for nationwide screening. The National Institute of Child Health and Human Development (NICHD) Hunter Kelly Newborn Screening Research Program funds research to advance newborn screening (NBS). A key effort is the Newborn Screening Translational Research Network (NBSTRN). For fourteen years, the American College of Medical Genetics and Genomics (ACMG) has developed and coordinated the activities of the NBSTRN. This article provides an overview of the NBSTRN.

The Human Phenotype Ontology in 2021.

The Human Phenotype Ontology (HPO, https://hpo.jax.org) was launched in 2008 to provide a comprehensive logical standard to describe and computationally analyze phenotypic abnormalities found in human disease. The HPO is now a worldwide standard for phenotype exchange. The HPO has grown steadily since its inception due to considerable contributions from clinical experts and researchers from a diverse range of disciplines. Here, we present recent major extensions of the HPO for neurology, nephrology, immunology, pulmonology, newborn screening, and other areas. For example, the seizure subontology now reflects the International League Against Epilepsy (ILAE) guidelines and these enhancements have already shown clinical validity. We present new efforts to harmonize computational definitions of phenotypic abnormalities across the HPO and multiple phenotype ontologies used for animal models of disease. These efforts will benefit software such as Exomiser by improving the accuracy and scope of cross-species phenotype matching. The computational modeling strategy used by the HPO to define disease entities and phenotypic features and distinguish between them is explained in detail.We also report on recent efforts to translate the HPO into indigenous languages. Finally, we summarize recent advances in the use of HPO in electronic health record systems.

FDA oversight of NSIGHT genomic research: the need for an integrated systems approach to regulation.

The National Institutes of Health (NIH) funded the Newborn Sequencing In Genomic medicine and public HealTh (NSIGHT) Consortium to investigate the implications, challenges, and opportunities associated with the possible use of genomic sequence information in the newborn period. Following announcement of the NSIGHT awardees in 2013, the Food and Drug Administration (FDA) contacted investigators and requested that pre-submissions to investigational device exemptions (IDE) be submitted for the use of genomic sequencing under Title 21 of the Code of Federal Regulations (21 CFR) part 812. IDE regulation permits clinical investigation of medical devices that have not been approved by the FDA. To our knowledge, this marked the first time the FDA determined that NIH-funded clinical genomic research projects are subject to IDE regulation. Here, we review the history of and rationale behind FDA oversight of clinical research and the NSIGHT Consortium's experiences in navigating the IDE process. Overall, NSIGHT investigators found that FDA's application of existing IDE regulations and medical device definitions aligned imprecisely with the aims of publicly funded exploratory clinical research protocols. IDE risk assessments by the FDA were similar to, but distinct from, protocol risk assessments conducted by local Institutional Review Boards (IRBs), and had the potential to reflect novel oversight of emerging genomic technologies. However, the pre-IDE and IDE process delayed the start of NSIGHT research studies by an average of 10 months, and significantly limited the scope of investigation in two of the four NIH approved projects. Based on the experience of the NSIGHT Consortium, we conclude that policies and practices governing the development and use of novel genomic technologies in clinical research urgently need clarification in order to mitigate potentially conflicting or redundant oversight by IRBs, NIH, FDA, and state authorities.