732 posters,  2 sessions,  11 topics,  3542 authors,  923 institutions

ePostersLive® by SciGen® Technologies S.A. All rights reserved.

669
Informatics, Genomics, and Translational Research: Implications for the Evidence-based Treatment of Genetic Disorders Identified Through Newborn Screening

Primary tabs

Rate

No votes yet

Statistics

356 reads

Informatics, Genomics, and Translational Research: Implications for the Evidence-Based Treatment of Genetic Disorders Identified Through Newborn Screening

Advances in information technology and genomics have created the opportunity to aggregate and analyze a wealth of data to develop and strengthen understanding of genetic disorders, and establish an evidence base to inform standard of care and improve health outcomes.  Screening for genetic disorders in the newborn period leads to the early diagnosis of genetic conditions, and research programs are being developed that capitalize on the NBS system by enrolling patients in longitudinal studies and clinical trials.  In addition these research teams are working with state based newborn screening programs to pilot the use of whole exome and/or whole genome sequencing (WES or WGS) as an adjunct to standard newborn screening, and to diagnose and screen other cohorts of newborns from the neonatal intensive care unit to the well baby nursery.  State-based NBS programs have also begun screening for disorders that have a large amount of genetic heterogeneity, including onset of symptoms in childhood or beyond.  This offers a unique opportunity to translate knowledge from the research studies to routine clinical care while improving the understanding of genetic disorders in newborns, developing novel technologies, and studying the effectiveness of new treatments.  To support these research efforts, the NICHD created the Newborn Screening Translational Research Network (NBSTRN). The NBSTRN is developing an infrastructure for researchers to obtain resources and focused expertise in NBS. As part of this effort, the NBSTRN and Cincinnati Children’s are developing infrastructure and a suite of tools to securely house long-term follow-up data on children diagnosed with NBS conditions. This tool suite, the Longitudinal Pediatric Data Resource (LPDR), provides a secure environment for researchers to aggregate data on rare conditions and incorporates a set of common data elements (CDEs) established by a national panel of clinical experts. Elements are developed and managed through a custom Data Almanac application that provides the ability to search available CDEs and create custom data dictionaries. A REDCap™ based system that includes over 60 conditions and over 10,000 CDEs is available to NBS researchers. A data discovery and query application, NBSmart, enables visualization and interaction with long-term outcomes as well as genomic information across different studies. Over 100 researchers across 15 studies and 26 funding opportunities are utilizing the LPDR. To date, data from 5500 participants with over 1 million data points have been collected. The LPDR will also house clinical and whole-exome and genome sequencing data from the Newborn Sequencing in Genomic Medicine and Public Health (NSIGHT) project. The use of the LPDR by researchers will create unique cohorts of individuals with genetic disease and accelerate understanding of these conditions. 

Informatics: Our informatics tool enables collection, aggregation, analysis and dissemination of data from individuals with a genetic disorder identified through NBS to perform natural history studies, NBS pilots and clinical trials.

Genomics: Our genomics analysis platform enables the aggregation of data derived from multi-institutional efforts to create shared cohorts and is designed to simplify, expedite and enhance the use of WES/WGS in NBS. 

Translational Research: Researchers partner with clinicians and state based NBS programs to advance the understanding of these genetic conditions and to establish the analytical and clinical validation of novel technologies and treatments.

 

Enter Poster ID (e.gGoNextPreviousCurrent