# Scalable tool and comprehensive maps to interpret structural variation across the neuropsychiatric spectrum

> **NIH NIH R01** · BROAD INSTITUTE, INC. · 2024 · $760,312

## Abstract

ABSTRACT
Structural variants (SVs), defined as rearrangements of ≥50 DNA nucleotides, are a major source of genetic
diversity among humans and an important component of the architecture of neuropsychiatric disorders (NPDs).
Despite their etiological significance, remarkably little is known about the consequences of SV formation across
the genome as there is a dearth of accurate measures to assess the genome-wide impact of gains or losses of
DNA (‘dosage sensitivity’). In contrast, robust models of mutation intolerance in genes have been derived from
single nucleotide variants (SNVs), which occur at ~200-fold higher frequency in the genome than SVs. These
metrics of negative selection against loss-of-function mutations within genes (e.g., LOEUF from the genome
aggregation database [gnomAD]) have been critical to gene and locus discovery across NPDs and Mendelian
disorders. By contrast, the absence of equivalent measures for SVs has hindered discovery. This renewal seeks
to build on the foundational tools, maps of genomic variation, and association studies across NPDs completed
during the initial funding period to now define the landscape of SVs across diverse global populations and
determine their relative contribution to the individual and cross-disorder NPD risk. To accomplish these goals,
we will leverage the coalescence of massive-scale biobank and NPD study initiatives led by members of our
research team with the development of new tools and resources that can scale to millions of individuals. We will
first aggregate and harmonize SV callsets generated using our GATK-SV and GATK-gCNV tools across >2.6
million samples with genome and exome sequencing data to create expansive SV maps across diverse
populations. We will then apply new statistical approaches to predict SV mutation rates and develop models of
genome-wide dosage sensitivity (Aim 1). These new SV variant classes and dosage sensitivity metrics will be
integrated into family-based and case-control association studies of NPDs across 387,675 cases from ongoing
cohort collections (Aim 2). Notably, these datasets will include significant initiatives led by members of our team
to investigate the dimensions of NPDs across diverse populations that are currently under-represented in NPD
studies. Finally, we will use innovative new approaches to investigate the influence of SVs that have been cryptic
to discovery from existing technologies but are now accessible to long-read sequencing and we will apply new
analysis methods to explore their potential influence on NPDs (Aim 3). Overall, each aim addresses a current
void in neuropsychiatric genomics and success in any one area would represent an important advance for the
field. We have assembled an outstanding team of experts across all domains of computational and statistical
genomics, as well as the phenotypic dimensions of neuropsychiatric conditions, and at its conclusion this
proposal will yield novel tools and resources at an unprecedented...

## Key facts

- **NIH application ID:** 10868517
- **Project number:** 5R01MH115957-06
- **Recipient organization:** BROAD INSTITUTE, INC.
- **Principal Investigator:** MICHAEL E TALKOWSKI
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $760,312
- **Award type:** 5
- **Project period:** 2018-08-10 → 2028-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10868517

## Citation

> US National Institutes of Health, RePORTER application 10868517, Scalable tool and comprehensive maps to interpret structural variation across the neuropsychiatric spectrum (5R01MH115957-06). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10868517. Licensed CC0.

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