# Functionally specialized components of disease heritability in ENCODE data

> **NIH NIH U01** · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · 2021 · $495,749

## Abstract

PROJECT SUMMARY/ABSTRACT
Genetic discoveries from genome-wide association studies have led to important insights on human disease
mechanisms. In particular, disease-associated variants are enriched in regions of the genome that are active in
gene regulation. However, most of these analyses have focused on individual variants with the strongest
evidence of association and on broadly defined functional annotations, which provide limited scope for
understanding disease mechanisms. In this proposal we analyze a broader set of genome-wide variants, in
conjunction with functionally specialized annotations with potential mechanistic interpretations, such as
context-specific regulatory elements or binding sites for specific transcription factors. We utilize methods that
ascribe heritability to specific segments of the genome, leveraging polygenic signals distributed across the
entire genome instead of a limited number of known genetic associations. These methods can pinpoint
disease heritability to smaller and more specific subsets of the genome defined by precise context-specific
functional annotations. In addition to highlighting specific mechanisms of disease, localizing to precise
annotations will offer the ability to identify causal variants. We will take advantage of large databases of genetic
data, in addition to a vast array of functional genomics data from ENCODE and other consortia. Specifically,
we will (1) develop new statistical methods and apply them to define causal alleles, (2) identify the genes that
are acting downstream of those causal allele, and characterize the transcription factor mediated mechanisms
that are being disrupted by those causal alleles, and (3) define the cell-state specific regulatory mechanisms
that are altered by the causal alleles. The proposal represents a collaboration between Drs. Alkes Price and
Soumya Raychaudhuri, bringing together expertise in functional genomics, human disease genetics, and
polygenic modeling. The investigators have a strong track record of integrating and applying strategies to
exploit functional genomic data to define human genetic mechanisms.

## Key facts

- **NIH application ID:** 10236759
- **Project number:** 3U01HG009379-04S1
- **Recipient organization:** HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH
- **Principal Investigator:** ALKES L PRICE
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $495,749
- **Award type:** 3
- **Project period:** 2021-02-01 → 2022-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10236759

## Citation

> US National Institutes of Health, RePORTER application 10236759, Functionally specialized components of disease heritability in ENCODE data (3U01HG009379-04S1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10236759. Licensed CC0.

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