Inhibitory Neurons in Nucleus Tractus Solitarius Are Involved in Decrease of Heart Rate Variability and Development of Depression-Like Behaviors in Temporal Lobe Epilepsy.

BACKGROUND: Diminished heart rate variability (HRV) has been observed in epilepsy, especially in epilepsy with depressive disorders. However, the underlying mechanism remains elusive. METHODS: We studied HRV, spontaneous recurrent seizures, and depression-like behaviors in different phases of pilocarpine-induced temporal lobe epilepsy (TLE) in mice. Single-cell RNA sequencing analysis was used to identify various nerve cell subsets in TLE mice with and without depression. Differentially expressed gene (DEG) analysis was performed in epilepsy, depression, and HRV central control-related brain areas. RESULTS: We found decreased HRV parameters in TLE mice, and alterations were positively correlated with the severity of depression-like behaviors. The severity of depression-like behaviors was correlated with the frequency of spontaneous recurrent seizure. Characteristic expression of mitochondria-related genes was significantly elevated in mice with depression in glial cells, and the enrichment analysis of those DEGs showed an enriched GABAergic synapse pathway in the HRV central control-related brain area. Furthermore, inhibitory neurons in the nucleus tractus solitarius, which is an HRV central control-related brain area, were specifically expressed in TLE mice combined with depression compared with those in mice without depression. A significantly enriched long-term depression pathway in DEGs from inhibitory neurons was found. CONCLUSIONS: Our study reported correlations between HRV and epilepsy-depression comorbidity in different phases of TLE. More importantly, we found that HRV central control-related inhibitory neurons are involved in the development of depression in TLE, providing new insights into epilepsy comorbid with depression.

eEF1A1 regulates the expression and alternative splicing of genes associated with Parkinson's disease in U251 cells.

BACKGROUND: Eukaryotic elongation factor 1A1 (eEF1A1) is an RNA-binding protein that is associated with PARK2 activity in cells, suggesting a possible role in Parkinson's disease (PD). OBJECTIVE: To clear whether eEF1A1 plays a role in PD through transcriptional or posttranscriptional regulation. METHODS: The GSE68719 dataset was downloaded from the GEO database, and the RNA-seq data of all brain tissue autopsies were obtained from 29 PD patients and 44 neurologically normal control subjects. To inhibit eEF1A1 from being expressed in U251 cells, siRNA was transfected into those cells, and RNA-seq high-throughput sequencing was used to determine the differentially expressed genes (DEGs) and differentially alternative splicing events (ASEs) resulting from eEF1A1 knockdown. RESULTS: eEF1A1 was significantly overexpressed in PD brain tissue in the BA9 area. GO and KEGG enrichment analyses revealed that eEF1A1 knockdown significantly upregulated the expression of the genes CXCL10, NGF, PTX3, IL6, ST6GALNAC3, NUPR1, TNFRSF21, and CXCL2 and upregulated the alternative splicing of the genes ACOT7, DDX10, SHMT2, MYEF2, and NDUFAF5. These genes were enriched in pathways related to PD pathogenesis, such as apoptosis, inflammatory response, and mitochondrial dysfunction. CONCLUSION: The results suggesting that eEF1A1 involved in the development of PD by regulating the differential expression and alternative splicing of genes, providing a theoretical basis for subsequent research.

Interictal Heart Rate Variability as a Biomarker for Comorbid Depressive Disorders among People with Epilepsy.

Depressive disorders are common among people with epilepsy (PwE). We here aimed to report an unbiased automatic classification of epilepsy comorbid depressive disorder cases via training a linear support vector machine (SVM) model using the interictal heart rate variability (HRV) data. One hundred and eighty-six subjects participated in this study. Among all participants, we recorded demographic information, epilepsy states and neuropsychiatric features. For each subject, we performed simultaneous electrocardiography and electroencephalography recordings both in wakefulness and non-rapid eye movement (NREM) sleep stage. Using these data, we systematically explored the full parameter space in order to determine the most effective combinations of data to classify the depression status in PwE. PwE with depressive disorders exhibited significant alterations in HRV parameters, including decreased time domain and nonlinear domain values both in wakefulness and NREM sleep stage compared with without depressive disorders and non-epilepsy controls. Interestingly, PwE without depressive disorder showed the same level of HRV values as the non-epilepsy control subjects. The SVM classification model of PwE depression status achieved a higher classification accuracy with the combination of HRV parameters in wakefulness and NREM sleep stage. Furthermore, the receiver operating characteristic (ROC) curve of the SVM classification model showed a satisfying area under the ROC curve (AUC: 0.758). Intriguingly, we found that the HRV measurements during NREM sleep are particularly important for correct classification, suggesting a mechanistic link between the dysregulation of heart rate during sleep and the development of depressive disorders in PwE. Our classification model may provide an objective measurement to assess the depressive status in PwE.