KEOPS complex expression in the frontal cortex in major depression and schizophrenia

O-sialoglycoprotein Endopeptidase (OSGEP) Suppresses Hepatic Ischemia-Reperfusion Injury-Induced Ferroptosis Through Modulating the MEK/ERK Signaling Pathway

Hepatic ischemia-reperfusion injury (HIRI) was widely accepted as a critical complication of liver resection and transplantation. A growing body of evidence suggested that O-sialoglycoprotein endopeptidase (OSGEP) was involved in cell proliferation and mitochondrial metabolism. However, whether OSGEP could mediate the pathogenesis of HIRI has still remained unclarified. This study investigated whether OSGEP could be protective against HIRI and elucidated the potential mechanisms. The OSGEP expression level was detected in cases undergoing ischemia-related hepatectomy and a stable oxygen-glucose deprivation/reoxygenation (OGD/R) condition in hepG2 cells. Additionally, it was attempted to establish a mouse model of HIRI, thus, the function and mechanism of OSGEP could be analyzed. At one day after hepatectomy, the negative association of OSGEP expression level with the elevated serum levels of aspartate aminotransferase (AST) and alanine aminotransferase (ALT) was noted. Moreover, it was attempted to carry out gain- and loss-of-function analyses of OSGEP in hepG2 cells to reveal its influences on OGD/R-induced injury and relevant signaling pathways. The findings suggested that OSGEP overexpression significantly protected hepG2 cells against ferroptotic cell death, while OSGEP consumption had opposite effects. Consistent with in vitro studies, OSGEP deficiency exacerbated liver functions and ferroptotic cell death in a mouse model of HIRI. The results also revealed that OSGEP mediated the progression of HIRI by regulating the MEK/ERK signaling pathway. Rescue experiments indicated that ERK1/2 knockdown or overexpression reversed the effects of OSGEP overexpression or knockdown on hepG2 cells under OGD/R condition. Taken together, the findings demonstrated that OSGEP could contribute to alleviate HIRI by mediating the MEK-ERK signaling pathway, which may serve as a potential prognostic marker and a therapeutic target for HIRI.

Conservation and Diversification of tRNA t6A-Modifying Enzymes across the Three Domains of Life

The universal N⁶-threonylcarbamoyladenosine (t⁶A) modification occurs at position 37 of tRNAs that decipher codons starting with adenosine. Mechanistically, t⁶A stabilizes structural configurations of the anticodon stem loop, promotes anticodon–codon pairing and safeguards the translational fidelity. The biosynthesis of tRNA t⁶A is co-catalyzed by two universally conserved protein families of TsaC/Sua5 (COG0009) and TsaD/Kae1/Qri7 (COG0533). Enzymatically, TsaC/Sua5 protein utilizes the substrates of L-threonine, HCO₃⁻/CO₂ and ATP to synthesize an intermediate L-threonylcarbamoyladenylate, of which the threonylcarbamoyl-moiety is subsequently transferred onto the A37 of substrate tRNAs by the TsaD–TsaB –TsaE complex in bacteria or by the KEOPS complex in archaea and eukaryotic cytoplasm, whereas Qri7/OSGEPL1 protein functions on its own in mitochondria. Depletion of tRNA t⁶A interferes with protein homeostasis and gravely affects the life of unicellular organisms and the fitness of higher eukaryotes. Pathogenic mutations of YRDC, OSGEPL1 and KEOPS are implicated in a number of human mitochondrial and neurological diseases, including autosomal recessive Galloway–Mowat syndrome. The molecular mechanisms underscoring both the biosynthesis and cellular roles of tRNA t⁶A are presently not well elucidated. This review summarizes current mechanistic understandings of the catalysis, regulation and disease implications of tRNA t⁶A-biosynthetic machineries of three kingdoms of life, with a special focus on delineating the structure–function relationship from perspectives of conservation and diversity.

Altered expression of somatostatin signaling molecules and clock genes in the hippocampus of subjects with substance use disorder

Substance use disorders are a debilitating group of psychiatric disorders with a high degree of comorbidity with major depressive disorder. Sleep and circadian rhythm disturbances are commonly reported in people with substance use disorder and major depression and associated with increased risk of relapse. Hippocampal somatostatin signaling is involved in encoding and consolidation of contextual memories which contribute to relapse in substance use disorder. Somatostatin and clock genes also have been implicated in depression, suggesting that these molecules may represent key converging pathways involved in contextual memory processing in substance use and major depression. We used hippocampal tissue from a cohort of subjects with substance use disorder (n = 20), subjects with major depression (n = 20), subjects with comorbid substance use disorder and major depression (n = 24) and psychiatrically normal control subjects (n = 20) to test the hypothesis that expression of genes involved in somatostatin signaling and clock genes is altered in subjects with substance use disorder. We identified decreased expression of somatostatin in subjects with substance use disorder and in subjects with major depression. We also observed increased somatostatin receptor 2 expression in subjects with substance use disorder with alcohol in the blood at death and decreased expression in subjects with major depression. Expression of the clock genes Arntl, Nr1d1, Per2 and Cry2 was increased in subjects with substance use disorder. Arntl and Nr1d1 expression in comparison was decreased in subjects with major depression. We observed decreased expression of Gsk3β in subjects with substance use disorder. Subjects with comorbid substance use disorder and major depression displayed minimal changes across all outcome measures. Furthermore, we observed a significant increase in history of sleep disturbances in subjects with substance use disorder. Our findings represent the first evidence for altered somatostatin and clock gene expression in the hippocampus of subjects with substance use disorder and subjects with major depression. Altered expression of these molecules may impact memory consolidation and contribute to relapse risk.

Aging biological markers in a cohort of antipsychotic-naïve first-episode psychosis patients

Schizophrenia is a severe and multifactorial disorder with an unknown causative pathophysiology. Abnormalities in neurodevelopmental and aging processes have been reported. Relative telomere length (RTL) and DNA methylation age (DMA), well-known biomarkers for estimating biological age, are both commonly altered in patients with schizophrenia compared to healthy controls. However, few studies investigated these aging biomarkers in first-episode psychosis (FEP) and in antipsychotic-naïve patients. To cover the existing gap regarding DMA and RTL in FEP and antipsychotic treatment, we aimed to verify whether those aging markers could be associated with psychosis and treatment response. Thus, we evaluated these measures in the blood of FEP antipsychotic-naïve patients and healthy controls (HC), as well as the response to antipsychotics after 10 weeks of treatment with risperidone. RTL was measured in 392 subjects, being 80 FEP and 312 HC using qPCR, while DMA was analyzed in a subset of 60 HC, 60 FEP patients (antipsychotic-naïve) and 59 FEP-10W (after treatment) using the "Multi-tissue Predictor"and the Infinium HumanMethylation450 BeadChip Kit. We observed diminished DMA and longer RTL in FEP patients before treatment compared to healthy controls, indicating a decelerated aging process in those patients. We found no statistical difference between responder and non-responder patients at baseline for both markers. An increased DMA was observed in patients after 10 weeks of treatment, however, after adjusting for blood cell composition, no significant association remained. Our findings indicate a decelerated aging process in the early phases of the disease.

Integration of Imaging Genomics Data for the Study of Alzheimer's Disease Using Joint-Connectivity-Based Sparse Nonnegative Matrix Factorization

Imaging genetics reveals the connection between microscopic genetics and macroscopic imaging, enabling the identification of disease biomarkers. In this work, we make full use of prior knowledge that has significant reference value for investigating the correlation between the brain and genetics to explore more biologically substantial biomarkers. In this paper, we propose joint-connectivity-based sparse nonnegative matrix factorization (JCB-SNMF). The algorithm simultaneously projects structural magnetic resonance imaging (sMRI), single-nucleotide polymorphism sites (SNPs), and gene expression data onto a common feature space, where heterogeneous variables with large coefficients in the same projection direction form a common module. In addition, the connectivity information for each region of the brain and genetic data are added as prior knowledge to identify regions of interest (ROIs), SNPs, and gene-related risks related to Alzheimer's disease (AD) patients. GraphNet regularization increases the anti-noise performance of the algorithm and the biological interpretability of the results. The simulation results show that compared with other NMF-based algorithms (JNMF, JSNMNMF), JCB-SNMF has better anti-noise performance and can identify and predict biomarkers closely related to AD from significant modules. By constructing a protein-protein interaction (PPI) network, we identified SF3B1, RPS20, and RBM14 as potential biomarkers of AD. We also found some significant SNP-ROI and gene-ROI pairs. Among them, two SNPs rs4472239 and rs11918049 and three genes KLHL8, ZC3H11A, and OSGEPL1 may have effects on the gray matter volume of multiple brain regions. This model provides a new way to further integrate multimodal impact genetic data to identify complex disease association patterns.