# Gene Dosage Imbalance in Neurodevelopmental Disorders

> **NIH NIH R01** · GEISINGER CLINIC · 2022 · $810,433

## Abstract

PROJECT SUMMARY
Mental health conditions negatively impact the quality of life of millions of individuals every year. Genomics
research has challenged long-held etiological boundaries among psychiatric, developmental, and neurological
diagnoses, collectively known as developmental brain disorders (DBD). Clinically distinct DBD, including autism
and schizophrenia (SCZ), share etiologies across a continuum of rare through common genomic variants that
confer varying impacts on brain function. Employing a genomics-first approach linked to electronic health record
(EHR) data, we will study the full continuum of DBD-related genomic variants and their combined effects on
phenotypic expression. A novel feature is our inclusion of a largely unexplored class of DBD-related copy number
variants (CNVs) of intermediate effect size (e.g., 15q11.2 BP1-2 deletions) that fall between the two extremes of
rare and common variation. We will leverage existing data from DiscovEHR, Geisinger’s large-scale genomics
initiative of >260,000 participants with exome sequence, SNP genotype, and longitudinal EHR data. We will
investigate how the interplay across the full continuum of genomic variants contributes to clinical DBD and
medical comorbidities through the following aims: 1) Evaluate the prevalence of DBD genomic variants of
large and intermediate effect size in a healthcare system-based population. Exome sequence data from
DiscovEHR participants will be analyzed to assess the prevalence of DBD variants of large and intermediate
effect size in genomic regions and genes known to be strong contributors to DBD risk. A subset of variant-
positive individuals will be phenotyped in Aims 2 and 3. 2) Conduct retrospective e-phenotyping, using
existing structured and unstructured EHR data, to investigate clinical variability and penetrance of DBD
variants. Building on Geisinger’s innovative EHR-based data extraction and PheWAS methodologies, we will
develop tiered, replicable strategies for highly accurate capture of DBD and medical phenotypes. These
phenotypes will be validated through systematic chart review of 1200 individuals with DBD variants. 3) Perform
prospective direct phenotyping using in-person and online assessments to compare quantitative traits
in individuals with DBD variants of large and intermediate effect size. Given the known limitations of using
EHR data to capture fine-grained cognitive and behavioral phenotypes, we will augment Aim 2 with in-person
assessments for variants of large and intermediate effect size (n=1250 total) and additional online surveys for
intermediate CNVs and controls (n=1000 each). 4) Evaluate the impact of PGS on clinical risk or resilience
for DBD in the presence of a DBD variant of large or intermediate effect size. We will model the added
impact of PGS on risk or resilience for DBD in individuals with variants of large and intermediate effect sizes.
These investigations may ultimately lead to individual-level DBD risk predictions...

## Key facts

- **NIH application ID:** 10375879
- **Project number:** 2R01MH074090-16A1
- **Recipient organization:** GEISINGER CLINIC
- **Principal Investigator:** David H. Ledbetter
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $810,433
- **Award type:** 2
- **Project period:** 2005-03-15 → 2026-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10375879

## Citation

> US National Institutes of Health, RePORTER application 10375879, Gene Dosage Imbalance in Neurodevelopmental Disorders (2R01MH074090-16A1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10375879. Licensed CC0.

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