이선재 교수

Abstract We performed integrative network analyses to identify targets that can be used for effectively treating liver diseases with minimal side effects. We first generated co‐expression networks (CNs) for 46 human tissues and liver cancer to explore the functional relationships between genes and examined the overlap between functional and physical interactions. Since increased de novo lipogenesis is a characteristic of nonalcoholic fatty liver disease (NAFLD) and hepatocellular carcinoma (HCC)

Biological networks provide new opportunities for understanding the cellular biology in both health and disease states. We generated tissue specific integrated networks (INs) for liver, muscle and adipose tissues by integrating metabolic, regulatory and protein-protein interaction networks. We also generated human co-expression networks (CNs) for 46 normal tissues and 17 cancers to explore the functional relationships between genes as well as their relationships with biological functions, and in

Hepatocellular carcinoma (HCC) has a high mortality rate and early detection of HCC is crucial for the application of effective treatment strategies. HCC is typically caused by either viral hepatitis infection or by fatty liver disease. To diagnose and treat HCC it is necessary to elucidate the underlying molecular mechanisms. As a major cause for development of HCC is fatty liver disease, we here investigated anomalies in regulation of lipid metabolism in the liver. We applied a tailored networ

Our integrative approaches highlighted mechanistic differences among tumors and allowed the identification of a survival signature and several potential therapeutic targets for the treatment of HCC.

BACKGROUND & AIMS: Cirrhosis complications are often triggered by bacterial infections with multidrug-resistant organisms. Alterations in the gut and oral microbiome in decompensated cirrhosis (DC) influence clinical outcomes. We interrogated: (i) gut and oral microbiome community structures, (ii) virulence factors (VFs) and antimicrobial resistance genes (ARGs) and (iii) oral-gut microbial overlap in patients with differing cirrhosis severity. METHODS: Fifteen healthy controls (HCs), as well as

Background Mitochondria are involved in cancer energy metabolism, although the mechanisms underlying the involvement of mitoribosomal dysfunction in hepatocellular carcinoma (HCC) remain poorly understood. Here, we investigated the effects of mitoribosomal impairment-mediated alterations on the immunometabolic characteristics of liver cancer. Methods We used a mouse model of HCC, liver tissues from patients with HCC, and datasets from The Cancer Genome Atlas (TCGA) to elucidate the relationship

Species composition of the healthy adult gut microbiota tends to be stable over time. Destabilization of the gut microbiome under the influence of different factors is the main driver of the microbial dysbiosis and subsequent impacts on host physiology. Here, we used metagenomics data from a Swedish longitudinal cohort, to determine the stability of the gut microbiome and uncovered two distinct microbial species groups; persistent colonizing species (PCS) and transient colonizing species (TCS).

Caffeine, which shares consubstantial structural similarity with purine adenosine, has been demonstrated as a nonselective adenosine receptor antagonist for eliciting most of the biological functions at physiologically relevant dosages. Accumulating evidence supports caffeine's beneficial effects against different disorders, such as total cardiovascular diseases and type 2 diabetes. Conversely, paradoxical effects are also linked to caffeine ingestion in humans including hypertension-hypotension

The human gut microbiota is of increasing interest, with metagenomics a key tool for analyzing bacterial diversity and functionality in health and disease. Despite increasing efforts to expand microbial gene catalogs and an increasing number of metagenome-assembled genomes, there have been few pan-metagenomic association studies and in-depth functional analyses across different geographies and diseases. Here, we explored 6014 human gut metagenome samples across 19 countries and 23 diseases by pe

Obesity has become a global public health and economic problem. Obesity is a major risk factor for a number of complications, such as type 2 diabetes, cardiovascular disease, fatty liver disease, and cancer. Serotonin (5-hydroxytryptamine [5-HT]) is a biogenic monoamine that plays various roles in metabolic homeostasis. It is well known that central 5-HT regulates appetite and mood. Several 5-HT receptor agonists and selective serotonin receptor uptake inhibitors (SSRIs) have shown beneficial ef

The complex and dynamic nature of human physiology, as exemplified by metabolism, has often been overlooked due to the lack of quantitative and systems approaches. Recently, systems biology approaches have pushed the boundaries of our current understanding of complex biochemical, physiological, and environmental interactions, enabling proactive medicine in the near future. From this perspective, we review how state-of-the-art computational modelling of human metabolism, i.e., genome-scale metabo

Alternative splicing (AS) is a procedure during gene expression that allows the production of multiple mRNAs from a single gene, leading to a larger number of proteins with various functions. The alternative splicing (AS) of Fas (Apo-1/CD95) pre-mRNA can generate membrane-bound or soluble isoforms with pro-apoptotic and anti-apoptotic functions. SRSF6, a member of the Serine/Arginine-rich protein family, plays essential roles in both constitutive and alternative splicing. Here, we identified SRS

The normalization of RNA sequencing data is a primary step for downstream analysis. The most popular method used for the normalization is the trimmed mean of M values (TMM) and DESeq. The TMM tries to trim away extreme log fold changes of the data to normalize the raw read counts based on the remaining non-deferentially expressed genes. However, the major problem with the TMM is that the values of trimming factor M are heuristic. This paper tries to estimate the adaptive value of M in TMM based