# Comprehensive and non-invasive prenatal screening of coding variation

> **NIH NIH F32** · MASSACHUSETTS GENERAL HOSPITAL · 2024 · $87,892

## Abstract

Abstract
Non-invasive prenatal screening (NIPS) involves assessment of circulating cell-free fetal DNA (cffDNA)
extracted from maternal plasma and the widespread clinical application of this technique to detect chromosomal
aneuploidies in pregnancy is now routine and the standard of care. While NIPS technology has advanced to
detect some targeted genomic abnormalities, current approaches are low-resolution and able to capture only a
small fraction of genetic conditions important to prenatal diagnosis. Our preliminary studies on 6 samples
suggest the feasibility of a high resolution non-invasive prenatal screen (hrNIPS), that can capture the vast
majority of pathogenic coding variation (SNV, indel, CNV). However, our results suggest that the ability to call
all types of variation can be improved through calibration of statistical models and development of new
techniques. Integration of phenotype data will allow interpretation and prioritization of identified pathogenic
variants.
Therefore, we will deploy hrNIPS on 100 samples with paired fetal exome sequencing data to develop and
calibrate methods over this large number of samples (Aim 1). We will call variation on these samples using the
improved methods and implement an infrastructure to capture systematic phenotypes in these samples using
the phenopackets schema (Aim 2). Further, we will use phenopackets and associated HPO terms to leverage
phenotype-aware algorithms to prioritize identified variants for further review. We will interpret all variation in a
clinical context using ACMG criteria and explore which types of variants might impact prenatal care (Aim 3).
Finally, we will investigate the potential added value of hrNIPS as a maternal carrier screen. In parallel with these
research aims, an exceptional team of seven mentors and advisors across disciplines, career stages, and
institutions will provide didactic training, hands-on research support, and regular opportunities for presentation.
Collectively, the ability to comprehensively assess coding variation in pregnancy with hrNIPS would allow early
and non-invasive pregnancy assessment for molecular diagnosis and has the potential to transform the standard
of care.

## Key facts

- **NIH application ID:** 10910871
- **Project number:** 5F32HD112084-02
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** Michael H Duyzend
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $87,892
- **Award type:** 5
- **Project period:** 2023-07-01 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10910871

## Citation

> US National Institutes of Health, RePORTER application 10910871, Comprehensive and non-invasive prenatal screening of coding variation (5F32HD112084-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10910871. Licensed CC0.

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