# An Investigation of Tandem Repeat Variation in Schizophrenia

> **NIH NIH R21** · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · 2024 · $464,750

## Abstract

PROJECT SUMMARY
Tandem repeats are a prevalent class of genomic variant, prone to high frequency of mutation and known to
underlay some neurological disorders, including the trinucleotide repeat disorders, Huntington’s Disease and
spinocerebellar ataxias. To date, a systematic investigation of the role of TRs in schizophrenia has not yet been
conducted, partly owing to technical limitations in genotyping tandem repeats, as well as lack of access to large-
scale, sequenced schizophrenia cohorts.
The goal of the current project is to apply recently developed TR profiling tools to whole genome sequenced
(WGS), schizophrenia cohorts to identify variation in short tandem repeats (STRs) and variable number tandem
repeats (VNTRs), that may contribute to schizophrenia genetic risk.
The proposed systematic study of TR variation in schizophrenia has a high likelihood of uncovering novel genetic
risk factors. The study will leverage innovative algorithms for high-throughput TR genotyping applied to large
and well-powered schizophrenia cohorts. Therefore, this timely and well-powered approach could lead to novel
insights into the role of tandem repeat variation in schizophrenia and human disease, with important translational
implications.

## Key facts

- **NIH application ID:** 10951937
- **Project number:** 1R21MH137536-01
- **Recipient organization:** ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
- **Principal Investigator:** Rebecca Birnbaum
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $464,750
- **Award type:** 1
- **Project period:** 2024-05-15 → 2026-05-14

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10951937

## Citation

> US National Institutes of Health, RePORTER application 10951937, An Investigation of Tandem Repeat Variation in Schizophrenia (1R21MH137536-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10951937. Licensed CC0.

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