# A phenomics-first resource for interpretation of variants

> **NIH NIH RM1** · UNIV OF NORTH CAROLINA CHAPEL HILL · 2024 · $1,903,676

## Abstract

A Phenomics-First Resource (PFR) for interpretation of variants
Genomics is key to precision medicine; however, despite the ease of sequencing, clinical interpretation is still
thwarted because relevant data (disease, phenotype, and variant) is complex, heterogeneous, and
disaggregated across sources. Moreover, this evidence is sometimes incomplete, conflicting, and erroneous.
Consequently, clinicians face long lists of candidate diseases, genes, and countless variants of unknown
significance. This situation will not improve without capturing and harmonizing the underlying phenotypic
information; computability of this information is the bedrock for the emerging field of ​phenomics​. From basic
science to clinical care, communities need structured ways to represent and exchange phenotypes and
disease definitions. Addressing these fundamental phenomics needs makes it possible to computationally
assess and reveal links between diseases and variants. We have previously shown how the addition of
phenotypic information using the Human Phenotype Ontology (HPO) can improve the diagnostic yield for
hard-to-diagnose patients, and HPO is therefore now a global standard for “deep phenotyping”. We have
demonstrated the applicability of deep phenotyping in the evaluation of rare diseases which have overlapping
mechanistic underpinnings with common/complex diseases as well as evolutionarily conserved mechanisms in
model organisms. Having coordinated the community and prototyped the underlying computational platforms,
we will now align both phenotype ontologies and clinical terminologies, enabling better comparison and
inference of phenotypes for improved diagnostic efficacy. We propose to develop a Phenomics-First
Resource (PFR). ​Specifically we will:
 1. Create a community-driven framework of interoperable phenotype definitions across species​ (uPheno)
 2. Harmonize human disease definitions with the ​MONDO​ disease alignment resource
 3. Create a community-wide exchange standard for clinical and model-organism phenotypes
(​Phenopackets​)
 4. Develop an integrated phenomics platform ​to provide the research ​(e.g. BioLink) and clinical (​FHIR​)
 communities with programmatic access to phenomics ontologies, data, and algorithms
The dynamic suite of interlinked technologies will together leverage community-developed knowledge in order
to make variant interpretation more reliable, better provenanced, and more clinically actionable.

## Key facts

- **NIH application ID:** 11138176
- **Project number:** 7RM1HG010860-05
- **Recipient organization:** UNIV OF NORTH CAROLINA CHAPEL HILL
- **Principal Investigator:** MELISSA A HAENDEL
- **Activity code:** RM1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1,903,676
- **Award type:** 7
- **Project period:** 2024-06-01 → 2026-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11138176

## Citation

> US National Institutes of Health, RePORTER application 11138176, A phenomics-first resource for interpretation of variants (7RM1HG010860-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/11138176. Licensed CC0.

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