Correlation between immune-related genes and depression-like features in an animal model and in humans.

A growing body of evidence suggests that immune-related genes play pivotal roles in the pathophysiology of depression. In the present study, we investigated a plausible connection between gene expression, DNA methylation, and brain structural changes in the pathophysiology of depression using a combined approach of murine and human studies. We ranked the immobility behaviors of 30 outbred Crl:CD1 (ICR) mice in the forced swim test (FST) and harvested their prefrontal cortices for RNA sequencing. Of the 24,532 analyzed genes, 141 showed significant correlations with FST immobility time, as determined through linear regression analysis with p ≤ 0.01. The identified genes were mostly involved in immune responses, especially interferon signaling pathways. Moreover, induction of virus-like neuroinflammation in the brains of two separate mouse cohorts (n = 30 each) using intracerebroventricular polyinosinic:polycytidylic acid injection resulted in increased immobility during FST and similar expression of top immobility-correlated genes. In human blood samples, candidate gene (top 5%) expression profiling using DNA methylation analysis found the interferon-related USP18 (cg25484698, p = 7.04 × 10-11, Δß = 1.57 × 10-2; cg02518889, p = 2.92 × 10-3, Δß =  - 8.20 × 10-3) and IFI44 (cg07107453, p = 3.76 × 10-3, Δß =  - 4.94 × 10-3) genes to be differentially methylated between patients with major depressive disorder (n = 350) and healthy controls (n = 161). Furthermore, cortical thickness analyses using T1-weighted images revealed that the DNA methylation scores for USP18 were negatively correlated with the thicknesses of several cortical regions, including the prefrontal cortex. Our results reveal the important role of the interferon pathway in depression and suggest USP18 as a potential candidate target. The results of the correlation analysis between transcriptomic data and animal behavior carried out in this study provide insights that could enhance our understanding of depression in humans.

Evolution of the multi-tRNA synthetase complex and its role in cancer.

Aminoacyl-tRNA synthetases (ARSs) are enzymes that ligate their cognate amino acids to tRNAs for protein synthesis. However, recent studies have shown that their functions are expanded beyond protein synthesis through the interactions with diverse cellular factors. In this review, we discuss how ARSs have evolved to expand and control their functions by forming protein assemblies. We particularly focus on a macromolecular ARS complex in eukaryotes, named multi-tRNA synthetase complex (MSC), which is proposed to provide a channel through which tRNAs reach bound ARSs to receive their cognate amino acid and transit further to the translation machinery. Approximately half of the ARSs assemble into the MSC through cis-acting noncatalytic domains attached to their catalytic domains and trans-acting factors. Evolution of the MSC included its functional expansion, during which the MSC interaction network was augmented by additional cellular pathways present in higher eukaryotes. We also discuss MSC components that could be functionally involved in the pathophysiology of tumorigenesis. For example, the activities of some trans-acting factors have tumor-suppressing effects or maintain DNA integrity and are functionally compromised in cancer. On the basis of Gene Ontology analyses, we propose that the regulatory activities of the MSC-associated ARSs mainly converge on five biological processes, including mammalian target of rapamycin (mTOR) and DNA repair pathways. Future studies are needed to investigate how the MSC-associated and free-ARSs interact with each other and other factors in the control of multiple cellular pathways, and how aberrant or disrupted interactions in the MSC can cause disease.

Exploratory biomarker analysis for treatment response in KRAS wild type metastatic colorectal cancer patients who received cetuximab plus irinotecan.

BACKGROUND: More than half of the patients selected based on KRAS mutation status fail to respond to the treatment with cetuximab in metastatic colorectal cancer (mCRC). We designed a study to identify additional biomarkers that could act as indicators for cetuximab treatment in mCRC. METHODS: We investigated 58 tumor samples from wild type KRAS CRC patients treated with cetuximab plus irinotecan (CI). We conducted the genotyping for mutations in either BRAF or PIK3CA and profiled comprehensively the expression of 522 kinase genes. RESULTS: BRAF mutation was detected in 5.1 % (3/58) of patients. All 50 patients showed wild type PIK3CA. Gene expression patterns that categorized patients with or without the disease control to CI were compared by supervised classification analysis. PSKH1, TLK2 and PHKG2 were overexpressed significantly in patients with the disease control to IC. The higher expression value of PSKH1 (r = 0.462, p < 0.001) and TLK2 (r = 0.361, p = 0.005) had the significant correlation to prolonged PFS. CONCLUSION: The result of this work demonstrated that expression nature of kinase genes such as PSKH1, TLK2 and PHKG2 may be informative to predict the efficacy of CI in wild type KRAS CRC. Mutations in either BRAF or PIK3CA were rare subsets in wild type KRAS CRC.

The association of shift work and TyG index among male workers in a chemical plant of Korea: a cross-sectional study.

Background: Disturbance of circadian rhythms caused by shift work has adverse effects on insulin resistance. Many previous studies have confirmed that shift work and insulin resistance are related using homeostasis model assessment-insulin resistance, one of the insulin resistance indicators. However, the triglycerides and glucose index (TyG index) has recently been studied as an insulin resistance indicator. The aim of this study is to investigate the association of shift work and TyG index, one of the indirect indicators of insulin resistance, using results of health checkups in one workplace. Methods: Based on medical examination data collected in February 2019, a total of 3,794 subjects from one chemical plant in Korea were selected for this study. Cut-off value of TyG index for predicting development of diabetes mellitus (DM) was 4.69. A multiple logistic regression analysis was performed after adjusting for age, employment period, obesity, abdominal obesity, smoking, drinking, physical activity, hypertension, stroke, heart disease. Results: As a result of logistic regression analysis, compared to day workers, odds ratio (OR) with a TyG index above cut-off value for predicting development of DM in shift workers was 1.220 after adjusting for age, employment period, obesity, abdominal obesity, smoking, drinking, physical activity, hypertension, stroke, heart disease (Model 1, OR: 1.276; 95% confidence interval [CI]: 1.099-1.482; Model 2, OR: 1.232; 95% CI: 1.055-1.438; Model 3, OR: 1.220, 95% CI: 1.030-1.444). Conclusions: There was a significant association between shift work and TyG index among male workers in a chemical plant. More research studies on the association between shift work and TyG index are needed in the future.

Selecting SNPs for pharmacogenomic association study.

SNP genotyping device is an essential tool in the upcoming era ofpersonal genome and personalised medicine. Human genome has more than 10 million SNPs whereas conventional SNP genotyping device can only hold 1 million SNPs. Thus, intelligent SNP contents selection is required to maximise the value of SNP genotyping device. Here, we developed a new selection algorithm and applied this method to design genotyping contents for cancerand pharmacogenomic association study. This approach significantly increased the product value when compared with contents of competitive SNP genotyping product.