# Molecular Basis of Human Visual System Disorders

> **NIH NIH R01** · BAYLOR COLLEGE OF MEDICINE · 2024 · $562,985

## Abstract

Abstract
The primary objective of this proposal is to enhance the molecular diagnosis rate and deepen our understanding
of the molecular mechanisms underlying Retinitis Pigmentosa (RP). RP, the most prevalent form of retinal
degeneration, affects 1 in 3,000 people worldwide. The genetics and pathways responsible for the disease are
highly heterogeneous. Currently, approximately 25% of cases remain unexplained upon molecular mutation
screen, representing one of the most significant gaps in our current knowledge of the disease. To address this
challenge, we propose to systematically identify novel mutant alleles and genes that are overlooked by the
current screening process through a combination of whole-genome sequencing and functional validation
experiments. To achieve this goal, during our last funding period, we established a large collection of over 450
well-characterized RP patient families whose pathogenic mutations remain unassigned after screening for coding
mutations in known retinal disease genes. Patients from these families are likely affected by mutations missed
by current technologies, representing a well-characterized, valuable resource for identifying new mutations and
disease-associated genes. During last funding period, whole exome sequencing has been performed for all
unsolved probands, including 200 with whole-genome sequencing. Building on this work, our Specific Aims are:
Specific Aim 1. Characterize the novel RP associated disease gene DDX41
Specific Aim 2. Unravel the full spectrum of mutations in unsolved RP patients
Specific Aim 3. Identify and characterize novel RP disease genes
 Progress toward these goals is likely to identify multiple novel RP genes whose subsequent study will lead
to new insights into disease mechanisms as well as lay the foundation for developing new diagnoses and
treatment methods, including gene therapy. Importantly, the protocols and software tools developed from these
aims, particularly noncoding mutation identification, will be applicable to other human diseases as well.

## Key facts

- **NIH application ID:** 10883236
- **Project number:** 2R01EY022356-11
- **Recipient organization:** BAYLOR COLLEGE OF MEDICINE
- **Principal Investigator:** RUI CHEN
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $562,985
- **Award type:** 2
- **Project period:** 2012-06-01 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10883236

## Citation

> US National Institutes of Health, RePORTER application 10883236, Molecular Basis of Human Visual System Disorders (2R01EY022356-11). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10883236. Licensed CC0.

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