Allison Molen
Extracellular vesicles (EVs) are membrane-bound sacs released by cells that carry molecular cargo reflective of their cell of origin. EVs enriched using L1 cell adhesion molecule (L1CAM) as a marker of putative neuronal origin can cross the blood–brain barrier and provide a minimally invasive window into brain-related processes. Exosomal microRNA (miRNA) regulate gene expression and have been implicated in psychiatric disorders, including major depressive disorder (MDD). However, measuring and analyzing miRNA from L1CAM-positive EVs presents substantial analytical challenges due to low abundance and sparse detection across samples. Plasma samples from participants recruited through the Mid-Atlantic Twin Registry (MATR) were used to isolate EVs, followed by immunoprecipitation of L1CAM-positive EVs. Total RNA was analyzed using the Affymetrix GeneChip miRNA 4.0 microarray. Raw cell intensity files (N=400) were processed by establishing a reproducible pipeline including background correction, normalization, detection threshold filtering, ComBat correction, and principal component analysis. miRNA present in at least 50% of participants were retained for downstream analyses. Linear mixed models were applied to explore associations between miRNA expression and age as well as lifetime MDD status. Preprocessing reduced 292,681 array features to 2,578 human mature miRNA, with detection-threshold filtering identifying 50 miRNA consistently detectable across participants. Exploratory analyses identified two significantly differentially expressed miRNA associated with age. This study establishes a reproducible analytical framework for miRNA microarray data from L1CAM-positive EVs and highlights key challenges related to low abundance and sparsity. These findings provide a foundation for future studies investigating exosomal miRNA as peripheral biomarkers in neuropsychiatric research.