Transcriptomic organization of the human brain in post-traumatic stress disorder

Girgenti, Matthew J.; Wang, Jiawei; Ji, Dingjue; Cruz, Dianne A.; Stein, Murray B.; Gelernter, Joel; Young, Keith A.; Huber, Bertrand R.; Williamson, Douglas E.; Friedman, Matthew J.; Krystal, John H.; Zhao, Hongyu; Duman, Ronald S.

doi:10.1038/s41593-020-00748-7

Cited by 124 publications

(174 citation statements)

References 102 publications

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“…A key up-regulated gene identified in Girgenti et al, ELK1 , was significantly up-regulated in both cortical regions in the present study, and the somatostatin gene ( SST ) , identified as robustly down-regulated in several regions of the cortex in Girgenti et al, was in the top ten of all down-regulated transcripts in both dlPFC and dACC here. ADAMTS2 , the second highest upregulated DEG in the combined cortical sample, was the top up-regulated gene in the dACC and the third most up-regulated in the dlPFC in Girgenti et al, 2020 55 . Both studies further found enrichment of PTSD-associated DEGs related to interneurons and their molecular functions.…”

Section: Discussionmentioning

confidence: 93%

Decoding shared versus divergent transcriptomic signatures across cortico-amygdala circuitry in PTSD and depressive disorders

Jaffe

Barry

Tao

et al. 2021

Preprint

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Post-traumatic stress disorder (PTSD) is a debilitating neuropsychiatric disease with a projected lifetime risk of 8.7%. PTSD is highly comorbid with depressive disorders including major depressive disorder (MDD) and bipolar disorder (BD). It is hypothesized that the overlap in symptoms stems from partially shared underlying neurobiological mechanisms. To better understand shared and unique transcriptional patterns of PTSD and MDD we performed RNA-sequencing in the postmortem brain of two prefrontal cortex (PFC) regions and two amygdala (AMY) regions, from neurotypical donors (N=109) as well as donors with diagnoses of PTSD (N=107) or MDD (N=109) across 1285 RNA-seq samples. We identified a small number of differentially expressed genes (DEGs) specific to PTSD, mostly in the cortex compared to amygdala. PTSD-specific DEGs were preferentially enriched in cortistatin-expressing cells, a subpopulation of somatostatin interneurons. These PTSD DEGs also showed strong enrichment for gene sets associated with immune-related pathways and microglia, largely driven by decreased expression of these genes in PTSD donors. While we identified a greater number of DEGs for MDD, there were only a few that were specific to MDD as they showed high overlap with PTSD DEGs. Finally, we used weighted gene co-expression network analysis (WGCNA) as an orthogonal approach to confirm the observed cellular and molecular associations. These findings highlight the sub-population of cortistatin-expressing interneurons as having potential functional significance in PTSD and provide supporting evidence for dysregulated neuroinflammation and immune signaling in MDD and PTSD pathophysiology.

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Section: Discussionmentioning

confidence: 93%

Decoding shared versus divergent transcriptomic signatures across cortico-amygdala circuitry in PTSD and depressive disorders

Jaffe

Barry

Tao

et al. 2021

Preprint

Self Cite

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“…In addition to ADHD/epilepsy, a recent study highlighted the involvement of ELFN1 in post-traumatic stress disorder (PTSD) pathophysiology. Girgenti et al (2021) performed the first transcriptome-wide analysis of gene expression changes in the postmortem brain of a large cohort of PTSD subjects. RNA-seq analysis of four prefrontal cortex subregions from 52 PTSD subjects and 46 control subjects revealed the downregulation of ELFN1 and GABA-related genes such as GAD2 (glutamate decarboxylase 2), SST, PNOC (prepronociceptin), and SLC32A1 (VGAT) in the dorsolateral prefrontal cortex (dlPFC) of PTSD patients.…”

Section: Elfn1 Gene and Neuropsychiatric Disordersmentioning

confidence: 99%

“…RNA-seq analysis of four prefrontal cortex subregions from 52 PTSD subjects and 46 control subjects revealed the downregulation of ELFN1 and GABA-related genes such as GAD2 (glutamate decarboxylase 2), SST, PNOC (prepronociceptin), and SLC32A1 (VGAT) in the dorsolateral prefrontal cortex (dlPFC) of PTSD patients. In a transcriptome-wide association study, they identified ELFN1 as a gene conferring significant genetic liability for PTSD (Girgenti et al, 2021).…”

Section: Elfn1 Gene and Neuropsychiatric Disordersmentioning

confidence: 99%

“…The reduction of ELFN1 and SST expressions in the dlPFC of PTSD patients (Girgenti et al, 2021) suggests that alterations to the PFC SST-IN-containing neural circuit is included in the pathophysiology of PTSD. This idea is consistent with the results of recent neuroimaging studies on PTSD patients.…”

Section: Ptsdmentioning

confidence: 99%

“…It is hypothesized that disruption of the executive-control network would be included in the etiology of PTSD by top-down regulation of emotions (Abdallah et al, 2019;Kunimatsu et al, 2019). Given that the ELFN1 expression status is significantly associated with PTSD and ELFN1 expression is reduced in the dlPFC (Girgenti et al, 2021), ELFN1 may play a role together with other GABA-related key drivers (SST, PNOC, and GAD2) in the executive-control network.…”

Section: Ptsdmentioning

confidence: 99%

See 2 more Smart Citations

Trans-Synaptic Regulation of Metabotropic Glutamate Receptors by Elfn Proteins in Health and Disease

Matsunaga

Aruga

2021

Front. Neural Circuits

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Trans-regulation of G protein-coupled receptors (GPCRs) by leucine-rich repeat (LRR) transmembrane proteins has emerged as a novel type of synaptic molecular interaction in the last decade. Several studies on LRR–GPCR interactions have revealed their critical role in synapse formation and in establishing synaptic properties. Among them, LRR–GPCR interactions between extracellular LRR fibronectin domain-containing family proteins (Elfn1 and Elfn2) and metabotropic glutamate receptors (mGluRs) are particularly interesting as they can affect a broad range of synapses through the modulation of signaling by glutamate, the principal excitatory transmitter in the mammalian central nervous system (CNS). Elfn–mGluR interactions have been investigated in hippocampal, cortical, and retinal synapses. Postsynaptic Elfn1 in the hippocampus and cerebral cortex mediates the tonic regulation of excitatory input onto somatostatin-positive interneurons (INs) through recruitment of presynaptic mGluR7. In the retina, presynaptic Elfn1 binds to mGluR6 and is necessary for synapse formation between rod photoreceptor cells and rod-bipolar cells. The repertoire of binding partners for Elfn1 and Elfn2 includes all group III mGluRs (mGluR4, mGluR6, mGluR7, and mGluR8), and both Elfn1 and Elfn2 can alter mGluR-mediated signaling through trans-interaction. Importantly, both preclinical and clinical studies have provided support for the involvement of the Elfn1–mGluR7 interaction in attention-deficit hyperactivity disorder (ADHD), post-traumatic stress disorder (PTSD), and epilepsy. In fact, Elfn1–mGluR7-associated disorders may reflect the altered function of somatostatin-positive interneuron inhibitory neural circuits, the mesolimbic and nigrostriatal dopaminergic pathway, and habenular circuits, highlighting the need for further investigation into this interaction.

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TOXGB: Teamwork Optimization Based XGBoost model for early identification of post-traumatic stress disorder

Gupta

Goel²,

Singh

et al. 2022

Cogn Neurodyn

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Post-traumatic stress (PTSD) is considered a clinical issue that influences numerous people from diverse trades all over the world. Numerous research scholars recorded diverse complexities to estimate the severity of the PTSD symptoms in the patients. But diagnosing PTSD and obtaining accurate diagnosing techniques becomes a more complicated task. Therefore, this paper develops a speech based post-traumatic stress disorder monitoring method and the significant objective of the proposed method is to determine if the patients are affected by PTSD. The proposed approach utilizes three different steps: pre-processing or pre-emphasis, feature extraction as well as classification to evaluate the patients affected by PTSD or not. The input speech signal is initially provided to the pre-processing phase where the speech gets segmented into frames. The speech frame is then extracted and classified using XGBoost based Teamwork optimization (XGB-TWO) algorithm. In addition to this, we utilized two different types of datasets namely TIMIT and FEMH to evaluate and classify the PSTD from the speech signals. Furthermore, based on the evaluation of the proposed model to diagnose PTSD patients, various evaluation metrics namely accuracy, specificity, sensitivity, and recall are evaluated. Finally, the experimental investigation and comparative analysis are carried out and the evaluation results demonstrated that the accuracy rate achieved for the proposed technique is 98.25%.

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Transcriptomic organization of the human brain in post-traumatic stress disorder

Cited by 124 publications

References 102 publications

Decoding shared versus divergent transcriptomic signatures across cortico-amygdala circuitry in PTSD and depressive disorders

Decoding shared versus divergent transcriptomic signatures across cortico-amygdala circuitry in PTSD and depressive disorders

Trans-Synaptic Regulation of Metabotropic Glutamate Receptors by Elfn Proteins in Health and Disease

TOXGB: Teamwork Optimization Based XGBoost model for early identification of post-traumatic stress disorder

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