MicroRNAs as Biomarkers in First Episode Schizophrenia
Purpose
This study investigates whether tiny molecules called microRNAs (miRNAs), found in special brain-derived "packages" (neural-derived extracellular vesicles, or NDEs) that travel from the brain into the blood, can serve as helpful indicators (biomarkers) for schizophrenia. Currently, doctors diagnose schizophrenia and monitor treatment primarily through clinical interviews, which can be slow and imprecise. This study will work with 80 individuals recently diagnosed with first-episode schizophrenia who are beginning treatment with either aripiprazole or risperidone, along with 80 healthy volunteers. Blood samples will be collected from all participants. For individuals with schizophrenia, blood will be drawn at the beginning of treatment and again after 12 weeks. By comparing patterns of brain-derived miRNAs in the blood of patients versus healthy volunteers, and by observing changes in these miRNAs during treatment, the researchers hope to discover whether these molecules can help diagnose schizophrenia more quickly and predict how well a treatment will work. If successful, this study will provide initial evidence that these miRNAs could become valuable new tools leading to earlier, more accurate diagnoses and more personalized treatment selection.
Conditions
- Schizophrenia Disorder
- Schizophreniform Disorder
- Schizoaffective Disorder
- Psychosis Not Otherwise Specified (NOS)
Eligibility
- Eligible Ages
- Between 15 Years and 40 Years
- Eligible Sex
- All
- Accepts Healthy Volunteers
- Yes
Inclusion Criteria
- Acute first episode of psychosis with DSM-5 diagnosis of schizophrenia, schizoaffective disorder, schizophreniform disorder, or psychosis Not Otherwise Specified (NOS) 2. Current positive symptoms rated ≥4 (moderate) on one or more of these BPRS items: hallucinatory behavior, unusual thought content, grandiosity, conceptual disorganization 3. Early phase of illness as defined by having taken antipsychotic drugs for a cumulative lifetime period ≤2 weeks 4. Age 15 to 40 5. Receiving or about to start naturalistic treatment with either aripiprazole or risperidone 6. Full capacity to consent
Exclusion Criteria
- Participant voluntarily withdraws consent at any given time during the study - Loss of capacity to consent during the study - Treating psychiatrist determines that the participant requires an antipsychotic medication other than aripiprazole or risperidone due to adverse effects, poor tolerability, poor response, or any other reason - The investigator, sponsor, independent safety monitor, or DSMB determines discontinuation is necessary to protect the participant - Pregnancy is discovered during the study
Study Design
- Phase
- N/A
- Study Type
- Interventional
- Allocation
- Non-Randomized
- Intervention Model
- Parallel Assignment
- Intervention Model Description
- This study uses a parallel assignment model in which two groups of participants are followed simultaneously. Eighty first-episode schizophrenia (FES) participants are followed for 12 weeks while receiving naturalistic treatment with either aripiprazole or risperidone, as prescribed by their treating psychiatrist, with blood samples collected at baseline and week 12 for neural-derived extracellular vesicle (NDE) miRNA analysis. Eighty healthy volunteers (HV) provide a single baseline blood sample for NDE miRNA analysis to serve as a comparison group. The study is non-randomized, as the choice of antipsychotic medication is determined by the treating psychiatrist and patient preference rather than by the research team.
- Primary Purpose
- Diagnostic
- Masking
- None (Open Label)
- Masking Description
- Laboratory staff conducting NDE isolation and miRNA sequencing will be blinded to participant group identity (FES vs. HV) to decrease risk of bias during laboratory analyses.
Arm Groups
| Arm | Description | Assigned Intervention |
|---|---|---|
|
Experimental First-Episode Schizophrenia - Aripiprazole/Risperidone |
FES participants receiving naturalistic treatment with aripiprazole or risperidone as prescribed by their treating psychiatrist. Blood samples collected at baseline and week 12 for NDE miRNA analysis. |
|
|
Active Comparator Healthy volunteers |
Healthy volunteers providing a single baseline blood sample for NDE miRNA analysis comparison. |
|
Recruiting Locations
Glen Oaks, New York 11004
More Details
- Status
- Recruiting
- Sponsor
- Northwell Health
Detailed Description
Schizophrenia is a significant psychiatric illness characterized by psychosis, social withdrawal, and cognitive difficulties leading to impaired daily functioning. Diagnosis and treatment assessment remain heavily reliant on clinical interviews, which are subjective and lack objective biological indicators. Previous research has established evidence of miRNA dysregulation in schizophrenia through genome-wide association studies, post-mortem brain tissue analysis, and biological fluid studies. A more recent and promising approach involves measuring miRNAs specifically contained within neural-derived extracellular vesicles (NDEs) isolated from plasma. These NDEs carry brain-specific miRNA cargo and can be identified in peripheral blood, offering a less invasive approach compared to cerebrospinal fluid or brain tissue. This study addresses the identified knowledge gap by investigating plasma NDE miRNAs as novel diagnostic and treatment response biomarkers specifically in first-episode schizophrenia (FES). The focus on FES participants minimizes confounding effects associated with long-term medication use and extended illness duration. The study employs a 12-week mechanistic clinical trial design with clinical assessments, neurocognitive testing (MATRICS), and blood collection for NDE miRNA sequencing at baseline and 12 weeks. MiRNA sequencing will be performed using Illumina NovaSeq6000 following NDE isolation via L1/NCAM antibody immunoprecipitation. Statistical analysis includes differential expression analysis using DESeq, Binary Elastic Net Regression for feature selection, and machine learning models (random forests, gradient boosting, SVM) for predictive performance assessment.