# Statistical methods to localize disease heritability and identify biological mechanisms

> **NIH NIH R37** · BROAD INSTITUTE, INC. · 2024 · $842,036

## Abstract

Genetic studies of both common and rare genetic variation have been extremely successful in identifying genes and variants associated to schizophrenia, autism and other psychiatric disorders. Nevertheless, for most psychiatric disorders, the vast majority of genetic effects are as yet undetected. Our specific aims are to 1) quantify the heritability explained by rare and functional classes of variation; 2) boost association power via leveraging related traits; and 3) infer biological mechanisms via local fine-mapping and genome- wide causal inference. We will guide our research using >800,000 samples from genome-wide association, exome sequencing and genome sequencing studies of psychiatric disease. The methods we propose to develop will be implemented in software packages that we will make widely available to the community.

## Key facts

- **NIH application ID:** 10897897
- **Project number:** 5R37MH107649-10
- **Recipient organization:** BROAD INSTITUTE, INC.
- **Principal Investigator:** Benjamin Michael Neale
- **Activity code:** R37 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $842,036
- **Award type:** 5
- **Project period:** 2015-07-01 → 2028-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10897897

## Citation

> US National Institutes of Health, RePORTER application 10897897, Statistical methods to localize disease heritability and identify biological mechanisms (5R37MH107649-10). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10897897. Licensed CC0.

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