Biology subjects

Tripathy, S. J.

Publications and source records attributed to Tripathy, S. J..

10 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↗

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↗

bioRxiv2025

Hyperpolarization activated cation channel mediated intrinsic plasticity changes underlie the malleability of with-in cell-type electrophysiological heterogeneity

Within cell-type neuronal electrophysiological, morphological, and transcriptomic heterogeneity is the norm in the brain. Although generally considered a fixed property within cell-types, this heterogeneity is malleable and declines in regions of the human brain that generate seizures. Building off this foundational work we hypothesize that such plasticity of cell-type heterogeneity, specifically its decline, arises from the shared history of neuronal activity that drive intrinsic plasticity mechanisms in a concerted fashion. To explore this hypothesis we study neuronal activity in two model systems: human cortical slice cultures from patients with epilepsy as well as slices from the medial prefrontal cortex (mPFC) and subiculum of rodent kainic acid (KA) model of temporal lobe epilepsy. Biophysical properties and spiking dynamics were characterized using whole-cell patch clamp recordings of layer 2 and layer 3 (L2&3) pyramidal neurons in human slice culture as well as deep layer subicular neurons and layer 5 (L5) mPFC of KA mice. We found a significant decline in biophysical heterogeneity and a reduction in information coding in both the KA and slice culture models. In both these models we found a consistent increase in hyperpolarization-activated cation current (HCN) dependent electrophysiological properties, the blockade of which restored electrophysiological heterogeneity and information coding. Our findings demonstrate that within cell-type heterogeneity is malleable, and despite being a complex distributed network property, can be tuned by a single ionic current. These findings emphasize the plasticity of within cell-type heterogeneity, suggesting the potential for targeted interventions to restore neuronal heterogeneity changes that accompany epilepsy and potentially other neurological and neuropsychiatric diseases.

neuroscience↗

bioRxiv2023

BrainRBPedia: a resource for RNA-binding proteins relevant to neurodevelopmental disorders

RNA-binding proteins (RBPs) are crucial players in the post-transcriptional regulation of mRNA and play major roles in ensuring proper neuronal development and function. Deficits in RBP function have been implicated in a number of neurodevelopmental disorders including autism spectrum disorder (ASD) and intellectual disability (ID), yet we lack resources that integrate current knowledge of RBP function, tissue expression, and disease association in one place to aid in their experimental characterization. Here we introduce BrainRBPedia - a database of 1072 RBPs with both disease annotations for neurodevelopmental disorders and functional annotations relevant to these disorders, including loss-of-function intolerance and expression specificity to the brain, neurons, and neuronal development. Using these functional annotations, we develop a machine learning model to prioritize RBPs likely to be involved in ASD and ID. Our model indicates that RBPs with high loss-of-function intolerance and those upregulated during neuronal differentiation are disproportionately likely to contribute to ASD and ID etiology. In summary, BrainRBPedia comprises a unique resource for researchers interested in the experimental characterization of RBPs in relation to neurodevelopmental disorders and suggests functional signatures of RBPs likely to play a role in neurodevelopment.

bioinformatics↗

bioRxiv2022

Investigating microglia-neuron crosstalk by characterizing microglial contamination in human and mouse Patch-seq datasets

Microglia are dynamic immune cells with diverse functional roles, including the regulation of neuronal excitability. Here, we leveraged an inconvenient truth of neuronal Patch-seq datasets -- that they routinely display evidence of contamination by surrounding microglia -- to better understand aspects of microglia-neuronal crosstalk. We first quantified the presence of microglial transcripts in three Patch-seq datasets of human and mouse neocortical neurons and observed extensive off-target contamination by microglia in each. Variation in microglial contamination was explained foremost by donor identity, especially in human samples, and neuronal cell type identity. Differential expression testing and enrichment analyses suggest that microglial contamination in Patch-seq is reflective of activated microglia and that these transcriptional signatures are distinct from those captured via single-nucleus RNAseq. Finally, neurons with greater microglial contamination differed markedly in their electrophysiological characteristics, including lowered input resistances and more depolarized action potential thresholds. Our results suggest microglial contamination contributes to cell- and donor-related electrophysiological variability and sheds light on how microglia might impact neurons in vivo.

neuroscience↗

bioRxiv2022

Bulk and Single-nucleus Transcriptomics Highlight Intra-telencephalic and Somatostatin Neurons in Alzheimer's Disease

BackgroundCortical neuron loss is a pathological hallmark of late-onset Alzheimers disease (AD). However, it remains unclear which neuronal subtypes are most vulnerable to degeneration and contribute most to cognitive decline. MethodsWe analyzed postmortem bulk brain RNA-sequencing (RNAseq) data collected from three studies of aging and AD comprising six neocortical regions (704 individuals; 1037 samples). We estimated relative cell type proportions from each brain sample using neuronal subclass-specific marker genes derived from ultra-high depth single-nucleus RNAseq data (snRNAseq). We associated cell type proportions with AD across all samples using mixed-effects mega-analyses. Bulk tissue analyses were complemented by analyses of three AD snRNAseq datasets using the same cell type definitions and diagnostic criteria (51 individuals). Lastly, we identified cell subtype associations with specific neuropathologies, cognitive decline, and residual cognition. ResultsIn our mega-analyses, we identified the strongest associations of AD with fewer somatostatin (SST) inhibitory neurons ({beta}=-0.48, pbonf=8.98x10-9) and intra-telencephalic (IT) excitatory neurons ({beta}=-0.45, pbonf =4.32x10-7). snRNAseq-based cell type proportion analyses especially supported the association of SST neurons. Analyses of cell type proportions with specific AD-related phenotypes in ROS/MAP consistently implicated fewer SST neurons with greater brain-wide postmortem tau and beta amyloid ({beta}=-0.155, pFDR=3.1x10-4) deposition, as well as more severe cognitive decline prior to death ({beta}=0.309, pFDR=3.9x10-6). Greater IT neuron proportions were associated strongly with improved cognition ({beta}=0.173, pFDR=8.3x10-5) and residual cognition ({beta}=0.175, pFDR=1.2x10-5), but not canonical AD neuropathology. ConclusionsProportionally fewer SST and IT neurons were significantly associated with AD diagnosis across multiple studies and cortical regions. These findings support seminal work implicating somatostatin and pyramidal neurons in the pathogenesis of AD and improves our current understanding of neuronal vulnerability in AD.

neuroscience↗

bioRxiv2021

Age-dependent increased sag current in human pyramidal neurons dampens baseline cortical activity

Aging involves various neurobiological changes, although their effect on brain function in humans remains poorly understood. The growing availability of human neuronal and circuit data provides opportunities for uncovering age-dependent changes of brain networks and for constraining models to predict consequences on brain activity. Here we found increased sag voltage amplitude in human middle temporal gyrus layer 5 pyramidal neurons from older subjects, and captured this effect in biophysical models of younger and older pyramidal neurons. We used these models to simulate detailed layer 5 microcircuits and found lower baseline firing in older pyramidal neuron microcircuits, with minimal effect on response. We then validated the predicted reduced baseline firing using extracellular multi-electrode recordings from human brain slices of different ages. Our results thus report changes in human pyramidal neuron input integration properties and provide fundamental insights on the neuronal mechanisms of altered cortical excitability and resting state activity in human aging.

neuroscience↗

bioRxiv2021

LaminaRGeneVis: a tool to visualize gene expression across the laminar architecture of the human neocortex

Application of RNA sequencing has enabled the characterization of genome-wide gene expression in the human brain, including distinct layers of the neocortex. Neuroanatomically, the molecular patterns that underlie the laminar organization of the neocortex can help link structure to circuitry and function. To advance our understanding of cortical architecture, we created LaminaRGeneVis, a web application that displays across-layer cortical gene expression from multiple datasets. These datasets were collected using bulk, single-nucleus, and spatial RNA sequencing methodologies and these data were harmonized to facilitate comparisons between datasets. The online resource facilitates single- and multi-gene analyses by providing figures and statistics for user-friendly assessment of laminar gene expression patterns in the adult human neocortex. Availability and implementationLaminaRGeneVis is available at https://ethanhkim.shinyapps.io/laminargenevis. The source code and data is accessible at https://github.com/ethanhkim/laminargenevis.

neuroscience↗

bioRxiv2021

Reduced inhibition in depression impairs stimulus processing in human cortical microcircuits

Cortical processing depends on finely-tuned excitatory and inhibitory connections in neuronal microcircuits. Reduced inhibition by somatostatin-expressing interneurons is a key component of altered inhibition associated with treatment-resistant major depressive disorder (depression), which is implicated in cognitive deficits and rumination, but the link remains to be better established mechanistically in humans. Here, we tested the impact of reduced somatostatin interneuron mediated inhibition on cortical processing in human neuronal microcircuits using a data-driven computational approach. We integrated human cellular, circuit and gene-expression data to generate detailed models of human cortical microcircuits in health and depression. We simulated microcircuit baseline and response activity and found reduced signal-to-noise ratio and increased false/failed detection of stimuli due to a higher baseline activity in depression. Our results thus applied novel models of human cortical microcircuits to demonstrate mechanistically how reduced inhibition impairs cortical processing in depression, providing quantitative links between altered inhibition and cognitive deficits.

neuroscience↗

bioRxiv2017

Transcriptomic Correlates Of Neuron Electrophysiological Diversity

How neuronal diversity emerges from complex patterns of gene expression remains poorly understood. Here we present an approach to understand electrophysiological diversity through gene expression by integrating transcriptomics with intracellular electrophysiology. Using a brain-wide dataset of 34 neuron types, we identified 420 genes whose expression levels significantly correlated with variability in one or more of 11 electrophysiological parameters. The majority of these correlations were consistent in an independent sample of 12 visual cortex cell types. Many associations reported here have the potential to provide new insights into how neurons generate functional diversity, and correlations of ion channel genes like Gabrd and Scn1a (Nav1.1) with resting potential and spiking frequency are consistent with known causal mechanisms. These results suggest that despite the complexity linking gene expression to electrophysiology, there are likely some general principles that govern how individual genes establish phenotypic diversity across very different cell types.

neuroscience↗