# Comprehensive Deep Phenotyping and Multi-omics to Develop Clinical and Molecular Biomarkers for MeCP2-related Diseases

> **NIH NIH K23** · BAYLOR COLLEGE OF MEDICINE · 2024 · $210,314

## Abstract

Abstract
 The X-linked gene MECP2 (methyl CpG-binding protein 2) is associated with two major
neurodevelopmental disorders: Rett Syndrome (RTT), caused by loss-of-function mutations in MeCP2, and
MECP2 duplication syndrome (MDS), caused by too much MeCP2. RTT is one of the most common genetic
causes of intellectual disability in females, while (MDS) is one of the most common genomic rearrangements in
males. Because the MeCP2 protein regulates the expression of thousands of genes across multiple brain
regions, the phenotype of each disease extends well beyond intellectual disability to affect mood, motor control,
and autonomic functions1. The brain is exquisitely sensitive to the quantity of MeCP2: a drop of just 16% in
MeCP2 levels is enough to produce Rett-like symptoms. This single fact is a salient challenge to the most
promising therapies being developed for these diseases: slightly over-shooting treatment for RTT by increasing
MeCP2 levels too much will cause MDS; suppressing MeCP2 levels too much in MDS will cause RTT. To avoid
simply exchanging one set of debilitating symptoms for another, we need reliable ways to measure treatment
responses and to assess whether we are administering the correct dose.
 Preclinical studies in humanized mice have convincingly demonstrated that antisense oligonucleotides
(ASO) can reduce MeCP2 levels and reverse the MDS phenotype; more recent work identified kinases and
phosphatases that regulate MeCP2 stability, again with good results in mice. These options are both extremely
promising, but how do we measure MeCP2 levels in patients? MeCP2 is a nuclear, chromatin-bound protein
that is expressed at very high levels in the brain, where it is not accessible to direct measurement. We have
therefore been searching for other molecules that correlate with MeCP2 levels but are measurable in blood
samples or other relatively noninvasive means. I propose that, for such complex diseases as RTT and MDS, a
composite biomarker panel will be superior to any single-modality measure to judge treatment response. Our
preliminary studies have already identified two important molecular biomarkers that track with MeCP2 levels
in mice; we have several additional candidates as well. This study therefore aims to develop a panel of clinical
and molecular biomarkers that will guide therapeutic efforts to prevent over- or under-treatment in these
diseases. Texas Children's Hospital has the largest patient populations in the country for both RTT and MDS,
so we are well-positioned to accomplish 1) Develop outcome measures for MDS; 2) Correlate phenotypes with
the genomic structure at Xq28 locus; and 3) Validate in humans molecular biomarkers that track with changes
in MeCP2 levels in mice. Completing these three aims will lay the groundwork for clinical trials of ASOs in
MDS and pave the path forward for studies involving other allelic disorders involving too much or too little of
the same gene product.

## Key facts

- **NIH application ID:** 10877193
- **Project number:** 5K23NS125126-03
- **Recipient organization:** BAYLOR COLLEGE OF MEDICINE
- **Principal Investigator:** Davut Pehlivan
- **Activity code:** K23 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $210,314
- **Award type:** 5
- **Project period:** 2022-08-15 → 2027-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10877193

## Citation

> US National Institutes of Health, RePORTER application 10877193, Comprehensive Deep Phenotyping and Multi-omics to Develop Clinical and Molecular Biomarkers for MeCP2-related Diseases (5K23NS125126-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10877193. Licensed CC0.

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