Dataset Information

Proteomics and Transcriptomics of the Hippocampus and Cortex in SUDEP and High-Risk SUDEP Patients.

ABSTRACT:

Objective

To identify the molecular signaling pathways underlying sudden unexpected death in epilepsy (SUDEP) and high-risk SUDEP compared to control patients with epilepsy.

Methods

For proteomics analyses, we evaluated the hippocampus and frontal cortex from microdissected postmortem brain tissue of 12 patients with SUDEP and 14 with non-SUDEP epilepsy. For transcriptomics analyses, we evaluated hippocampus and temporal cortex surgical brain tissue from patients with mesial temporal lobe epilepsy: 6 low-risk and 8 high-risk SUDEP as determined by a short (<50 seconds) or prolonged (≥50 seconds) postictal generalized EEG suppression (PGES) that may indicate severely depressed brain activity impairing respiration, arousal, and protective reflexes.

Results

In autopsy hippocampus and cortex, we observed no proteomic differences between patients with SUDEP and those with non-SUDEP epilepsy, contrasting with our previously reported robust differences between epilepsy and controls without epilepsy. Transcriptomics in hippocampus and cortex from patients with surgical epilepsy segregated by PGES identified 55 differentially expressed genes (37 protein-coding, 15 long noncoding RNAs, 3 pending) in hippocampus.

Conclusion

The SUDEP proteome and high-risk SUDEP transcriptome were similar to those in other patients with epilepsy in hippocampus and cortex, consistent with diverse epilepsy syndromes and comorbid conditions associated with SUDEP. Studies with larger cohorts and different epilepsy syndromes, as well as additional anatomic regions, may identify molecular mechanisms of SUDEP.

SUBMITTER: Leitner DF

PROVIDER: S-EPMC8205452 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Proteomics and Transcriptomics of the Hippocampus and Cortex in SUDEP and High-Risk SUDEP Patients.

Leitner Dominique F DF Mills James D JD Pires Geoffrey G Faustin Arline A Drummond Eleanor E Kanshin Evgeny E Nayak Shruti S Askenazi Manor M Verducci Chloe C Chen Bei Jun BJ Janitz Michael M Anink Jasper J JJ Baayen Johannes C JC Idema Sander S van Vliet Erwin A EA Devore Sasha S Friedman Daniel D Diehl Beate B Scott Catherine C Thijs Roland R Wisniewski Thomas T Ueberheide Beatrix B Thom Maria M Aronica Eleonora E Devinsky Orrin O

Neurology 20210428 21

<h4>Objective</h4>To identify the molecular signaling pathways underlying sudden unexpected death in epilepsy (SUDEP) and high-risk SUDEP compared to control patients with epilepsy.<h4>Methods</h4>For proteomics analyses, we evaluated the hippocampus and frontal cortex from microdissected postmortem brain tissue of 12 patients with SUDEP and 14 with non-SUDEP epilepsy. For transcriptomics analyses, we evaluated hippocampus and temporal cortex surgical brain tissue from patients with mesial tempo ...[more]

PMID: 33910938

Similar Datasets

Project description:Several lines of evidence link deficient serotonin function and SUDEP. Chronic treatment with serotonin reuptake inhibitors (SRIs) reduces ictal central apnoea, a risk factor for SUDEP. Reduced medullary serotonergic neurones, modulators of respiration in response to hypercapnia, were reported in a SUDEP post-mortem series. The amygdala and hippocampus have high serotonergic innervation and are functionally implicated in seizure-related respiratory dysregulation. We explored serotonergic networks in mesial temporal lobe structures in a surgical and post-mortem epilepsy series in relation to SUDEP risk. We stratified 75 temporal lobe epilepsy patients with hippocampal sclerosis (TLE/HS) into high (N = 16), medium (N = 11) and low risk (N = 48) groups for SUDEP based on generalised seizure frequency. We also included the amygdala in 35 post-mortem cases, including SUDEP (N = 17), epilepsy controls (N = 10) and non-epilepsy controls (N = 8). The immunohistochemistry labelling index (LI) and axonal length (AL) of serotonin transporter (SERT)-positive axons were quantified in 13 regions of interest with image analysis. SERT LI was highest in amygdala and subiculum regions. In the surgical series, higher SERT LI was observed in high risk than low risk cases in the dentate gyrus, CA1 and subiculum (p < 0.05). In the post-mortem cases higher SERT LI and AL was observed in the basal and accessory basal nuclei of the amygdala and peri-amygdala cortex in SUDEP compared to epilepsy controls (p < 0.05). Patients on SRI showed higher SERT in the dentate gyrus (p < 0.005) and CA4 (p < 0.05) but there was no difference in patients with or without a psychiatric history. Higher SERT in hippocampal subfields in TLE/HS cases with SUDEP risk factors and higher amygdala SERT in post-mortem SUDEP cases than epilepsy controls supports a role for altered serotonergic networks involving limbic regions in SUDEP. This may be of functional relevance through reduced 5-HT availability.

Project description:Rationale: Seizure clusters may be related to Sudden Unexpected Death in Epilepsy (SUDEP). Two or more generalized convulsive seizures (GCS) were captured during video electroencephalography in 7/11 (64%) patients with monitored SUDEP in the MORTEMUS study. It follows that seizure clusters may be associated with epilepsy severity and possibly with SUDEP risk. We aimed to determine if electroclinical seizure features worsen from seizure to seizure within a cluster and possible associations between GCS clusters, markers of seizure severity, and SUDEP risk. Methods: Patients were consecutive, prospectively consented participants with drug-resistant epilepsy from a multi-center study. Seizure clusters were defined as two or more GCS in a 24-h period during the recording of prolonged video-electroencephalography in the Epilepsy monitoring unit (EMU). We measured heart rate variability (HRV), pulse oximetry, plethysmography, postictal generalized electroencephalographic suppression (PGES), and electroencephalography (EEG) recovery duration. A linear mixed effects model was used to study the difference between the first and subsequent seizures, with a level of significance set at p < 0.05. Results: We identified 112 GCS clusters in 105 patients with 285 seizures. GCS lasted on average 48.7 ± 19 s (mean 49, range 2-137). PGES emerged in 184 (64.6%) seizures and postconvulsive central apnea (PCCA) was present in 38 (13.3%) seizures. Changes in seizure features from seizure to seizure such as seizure and convulsive phase durations appeared random. In grouped analysis, some seizure features underwent significant deterioration, whereas others improved. Clonic phase and postconvulsive central apnea (PCCA) were significantly shorter in the fourth seizure compared to the first. By contrast, duration of decerebrate posturing and ictal central apnea were longer. Four SUDEP cases in the cluster cohort were reported on follow-up. Conclusion: Seizure clusters show variable changes from seizure to seizure. Although clusters may reflect epilepsy severity, they alone may be unrelated to SUDEP risk. We suggest a stochastic nature to SUDEP occurrence, where seizure clusters may be more likely to contribute to SUDEP if an underlying progressive tendency toward SUDEP has matured toward a critical SUDEP threshold.

Project description:Rationale: Epicardial adipose tissue (EAT) has been independently associated with non-calcified, high-risk coronary plaques in low-to intermediate risk subjects. Recently, a bidirectional communication was shown between EAT and diseased coronary arteries. In high-risk patients it is unknown whether quantitative measures of EAT can capture, and which molecular players are involved in this mutual interplay. Objective: In a high-risk population, we aimed to determine how the volume of EAT is linked to coronary artery disease (CAD) and to identify potential EAT-deregulated pathways in CAD patients specifically related to coronary artery calcification (CAC). Methods and Results: In a prospective cohort of 574 degenerative severe aortic stenosis patients referred to cardiac surgery, we quantified fat depots by computed tomography (CT) and performed a comparative quantitative proteomics of thoracic fat, including EAT, mediastinal (MAT) and subcutaneous (SAT) adipose tissues. We did not find an independent association of EAT volume with the severity, distribution and complexity of coronary stenosis in invasive coronary angiography. Although, EAT volume was correlated with high CAC, its cardiovascular risk factors-adjusted association was not significant. Taking as reference non-CAD matched-patients and compared to MAT and SAT, EAT proteomic signature of CAD was characterized by up-regulation of pro-calcifying annexins (Annexin A2, ANXA2), fatty acid binding transporters (FABP4) and inflammatory signaling proteins, and by down-regulation of fetuin-A and redox state regulatory enzymes. In EAT, ANXA2 regulation was positively correlated with CAC. EAT gene expression studies confirmed overexpression of ANXA2 and FABP4 in CAD, but no expression of FETUA was detected. Compared with non-CAD, fetuin-A circulating levels were higher in CAD, whereas no fetuin-A pericardial fluid differences were found. Conclusions: In this high-risk cohort, EAT presented an imbalance of pro-calcifying, pro-inflammatory and lipid transporters mediators. These local EAT-mediated regulatory mechanisms were not reflected by the CT volume of EAT alone.

Dataset Information

Proteomics and Transcriptomics of the Hippocampus and Cortex in SUDEP and High-Risk SUDEP Patients.

Objective

Methods

Results

Conclusion

Publications

Proteomics and Transcriptomics of the Hippocampus and Cortex in SUDEP and High-Risk SUDEP Patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets