Biology subjects

Fafouti, M. E.

Publications and source records attributed to Fafouti, M. E..

3 recordsLinked to original sources

bioRxiv2026

Selective depletion of upper-layer somatostatin interneuron subtypes in schizophrenia

Schizophrenia (SCZ) is associated with cortical GABAergic dysfunction, but whether inhibitory interneurons are lost or persist in an altered molecular state remains unresolved. Here, we harmonized seven prefrontal post-mortem single-nucleus RNA-seq datasets onto a fine-grained taxonomy of cortical cell types and meta-analyzed their gene expression and abundance changes in SCZ (298 controls, 171 SCZ). First, we find a subclass-wide reduction of SST mRNA within somatostatin (Sst) neurons. Second, we find reduced abundance (depletion) of a subset of upper-layer Sst interneurons and increased abundance of L6b excitatory neurons, with both changes confirmed in spatial transcriptomics (12 controls, 12 SCZ). Notably, SCZ genetic risk is enriched in the most depleted Sst cells. Depleted Sst subtypes highly express HCN1, partially correspond to primate-specialized CALB1-expressing double-bouquet cells, and are among the cells lost earliest in Alzheimer's disease. These upper-layer Sst interneurons constitute an intrinsically vulnerable population and a promising target for neuroprotective and compensatory therapies.

bioinformatics↗

bioRxiv2026

Spatial dynamics of cellular and molecular plasticity in the maternal and postpartum mouse brain

Pregnancy is a critical window for neuroplasticity and maternal mental health, yet our understanding of the molecular and cellular changes underlying this adaptation remains incomplete. Here we profile the female mouse brain in nulliparous, late-pregnant and postpartum states with three single-cell spatial technologies (Slide-tags, MERFISH and Xenium). Together these assays resolve 1.5 million cells in one coronal plane spanning the cortex, striatum, lateral septum and preoptic area. Pregnancy is associated with changes in gene expression in most cell types, beyond the circuits previously established to govern maternal behavior. These changes resolve into three programs that are reproducible across platforms: synaptic pathways increase in neurons as growth and plasticity pathways decrease; immune and angiogenic pathways increase in glia and vascular cells; and cholesterol synthesis decreases as uptake increases across both neurons and glia. Finally, mapping human depression genetics onto these data, we find risk genes concentrated almost entirely in neurons, and this concentration changes with reproductive state in the preoptic area, basal forebrain and ventral striatum. These results place the neurons carrying depression risk among the circuits remodeled during pregnancy, providing a possible cellular substrate for peripartum vulnerability.

genomics↗

bioRxiv2025

Long-read proteogenomic atlas of human neuronal differentiation reveals isoform diversity informing neurodevelopmental risk mechanisms

RNA splicing shapes neuronal identity and disease risk, yet current maps lack the developmental resolution and depth to resolve this complexity. Here, we integrate deep long-read RNA sequencing and proteomics in iPSC-derived cortical neurons to generate a high-resolution proteogenomic atlas of human neuron development. We identify 182,371 mRNA isoforms (over half previously unknown) and provide direct peptide evidence for the translation of hundreds of novel protein-coding sequences. Population genetics demonstrates that variants affecting novel exons and splice sites are under negative selection, underscoring the potential significance of these isoforms. During neuronal maturation, we observe that ASD risk genes undergo dynamic isoform switching, including microexon inclusion and intron retention, that remodel key protein domains and regulatory regions. Furthermore, we uncover widespread, long-range coordination between splicing and polyadenylation. Finally, our atlas enables variant reinterpretation in ASD, highlighting the value of an isoform-centric view for interpreting pathogenic variation in neurodevelopment.

bioinformatics↗