The MeCP2E1/E2-BDNF-miR132 Homeostasis Regulatory Network Is Region-Dependent in the Human Brain and Is Impaired in Rett Syndrome Patients
Bibliographic record
Abstract
Rett Syndrome (RTT) is a rare and progressive neurodevelopmental disorder that is caused by de novo mutations in the X-linked Methyl CpG binding protein 2 (MECP2) gene and is subjected to X-chromosome inactivation. RTT is commonly associated with neurological regression, autistic features, motor control impairment, seizures, loss of speech and purposeful hand movements, mainly affecting females. Different animal and cellular model systems have tremendously contributed to our current knowledge about MeCP2 and RTT. However, the majority of these findings remain unexamined in the brain of RTT patients. Based on previous studies in rodent brains, the highly conserved neuronal microRNA “miR132” was suggested to be an inhibitor of MeCP2 expression. The neuronal miR132 itself is induced by Brain Derived Neurotrophic Factor (BDNF), a neurotransmitter modulator, which in turn is controlled by MeCP2. This makes the basis of the MECP2-BDNF-miR132 feedback regulatory loop in the brain. Here, we studied the components of this feedback regulatory network in humans, and its possible impairment in the brain of RTT patients. In this regards, we evaluated the transcript and protein levels of MECP2/MeCP2E1 and E2 isoforms, BDNF/BDNF, and miR132 (both 3p and 5p strands) by real time RT-PCR, Western blot, and ELISA in four different brain regions of the human RTT brains and their age-, post-mortem delay-, and sex-matched controls. The transcript level of the studied elements was significantly compromised in RTT patients, even though the change was not identical in different parts of the brain. Our data indicates that MeCP2E1/E2-BDNF protein levels did not follow their corresponding transcript trends. Correlational studies suggested that the MECP2E1/E2-BDNF-miR132 homeostasis regulation in the human brain might not be similarly controlled in different parts of the brain. Despite challenges in evaluating autopsy samples in rare diseases, our findings would help to shed some light on RTT pathobiology, and obscurities caused by limited studies on MeCP2 regulation in the human brain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".