# Multiplex gene sequencing and metabolomics analysis from newborn dried blood spots to improve screening and diagnosis of metabolic disorders.

> **NIH NIH R01** · YALE UNIVERSITY · 2020 · $542,483

## Abstract

Abstract: Newborn screening (NBS) using tandem mass spectrometry (MS/MS) has transformed our ability to
identify and provide early, lifesaving treatment to infants with inborn errors of metabolism. While MS/MS
screening identifies most affected babies, it is accompanied by frequent false-positive results that require
collecting blood and urine samples for additional confirmatory testing. While DNA sequencing has become an
important part of confirmatory testing, newborn dried blood spots (DBS) yield only small and highly variable DNA
amounts. There is an urgent need for a more efficient second-tier NBS approach for confirming all screen-positive
cases directly from the DBS cards collected at birth. This is especially critical for infants at risk for metabolic
disease in their first weeks of life. The overall objective of this proposal is to combine novel DNA sequencing and
mass spectrometry technology to diagnose inborn metabolic disorders from DBS, and to demonstrate the clinical
feasibility of this approach for second-tier screening. To achieve this objective, the following specific aims will be
pursued: (1) Develop multiplex gene sequencing (RUSPseq) and 10X linked-read sequencing for rapid genetic
diagnosis without the need for additional parental testing; (2) Develop mass spectrometry (Q-TOF/LC-MS) and
Random Forest (RF) machine learning to identify novel metabolic markers, which will be integrated in a novel
second-tier screening panel to separate true and false-positive cases; and (3) Demonstrate clinical and
translational feasibility of this approach to more rapidly identify both true and false-positive cases. We will work
with the public NBS program and NBSTRN’s Pilot Research and Implementation workgroup to translate this
combined approach into second-tier NBS. These outcomes will have significant impact by reducing diagnostic
delays and uncertainties, and by reducing iterative testing rounds and the cost associated with them, thereby
reducing the burden on the healthcare system as well as patients and their families.

## Key facts

- **NIH application ID:** 10033377
- **Project number:** 1R01HD102537-01
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Curt Scharfe
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $542,483
- **Award type:** 1
- **Project period:** 2020-09-01 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10033377

## Citation

> US National Institutes of Health, RePORTER application 10033377, Multiplex gene sequencing and metabolomics analysis from newborn dried blood spots to improve screening and diagnosis of metabolic disorders. (1R01HD102537-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10033377. Licensed CC0.

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