• Korean Journal of Biological Psychiatry
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• v.30 no.1
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• pp.24-30
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• 2023

Objectives Alzheimer's disease (AD) is the most common form of dementia in older adults, damaging the brain and resulting in impaired memory, thinking, and behavior. The identification of differentially expressed genes and related pathways among affected brain regions can provide more information on the mechanisms of AD. The aim of our study was to identify differentially expressed genes associated with AD and combined biomarkers among them to improve AD risk prediction accuracy. Methods Machine learning methods were used to compare the performance of the identified combined biomarkers. In this study, three publicly available gene expression datasets from the hippocampal brain region were used. Results We detected 31 significant common genes from two different microarray datasets using the limma package. Some of them belonged to 11 biological pathways. Combined biomarkers were identified in two microarray datasets and were evaluated in a different dataset. The performance of the predictive models using the combined biomarkers was superior to those of models using a single gene. When two genes were combined, the most predictive gene set in the evaluation dataset was ATR and PRKCB when linear discriminant analysis was applied. Conclusions Combined biomarkers showed good performance in predicting the risk of AD. The constructed predictive nomogram using combined biomarkers could easily be used by clinicians to identify high-risk individuals so that more efficient trials could be designed to reduce the incidence of AD.

• Genomics & Informatics
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• v.21 no.3
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• pp.31.1-31.8
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• 2023

Multiple myeloma (MM) is a hematological malignancy. It is widely believed that genetic factors play a significant role in the development of MM, as investigated in numerous studies. However, the application of genomic information for clinical purposes, including diagnostic and prognostic biomarkers, remains largely confined to research. In this study, we utilized genetic information from the Genomic-Driven Clinical Implementation for Multiple Myeloma database, which is dedicated to clinical trial studies on MM. This genetic information was sourced from the genome-wide association studies catalog database. We prioritized genes with the potential to cause MM based on established annotations, as well as biological risk genes for MM, as potential drug target candidates. The DrugBank database was employed to identify drug candidates targeting these genes. Our research led to the discovery of 14 MM biological risk genes and the identification of 10 drugs that target three of these genes. Notably, only one of these 10 drugs, panobinostat, has been approved for use in MM. The two most promising genes, calcium signal-modulating cyclophilin ligand (CAMLG) and histone deacetylase 2 (HDAC2), were targeted by four drugs (cyclosporine, belinostat, vorinostat, and romidepsin), all of which have clinical evidence supporting their use in the treatment of MM. Interestingly, five of the 10 drugs have been approved for other indications than MM, but they may also be effective in treating MM. Therefore, this study aimed to clarify the genomic variants involved in the pathogenesis of MM and highlight the potential benefits of these genomic variants in drug discovery.

• Korean Journal of Biological Psychiatry
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• v.17 no.2
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• pp.65-69
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• 2010

Gene-environment interactions are important in pathogenesis of suicide or suicidal behavior. Twin and adoption studies and family studies show that genetic factors play a critical role in suicide or suicidal behavior. Given the strong association between serotonergic neurotransmission and suicide, recent molecular genetic studies have focused on polymorphisms of serotonin genes, especially on serotonin transporter and tryptophan hydroxylase genes. Some studies have revealed a significant interaction between s allele of the serotonin transporter gene and the risk of suicide attempt associated with childhood trauma. In addition, the polymorphism of brain-derived neurotrophic factor gene also may influence the effect of childhood trauma in relation to the risk of attempting suicide. Future studies should explore genetic and environmental factors in suicide or suicidal behavior and examine for gene and environment interaction.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.13
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• pp.5233-5237
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• 2014

Epigenetic modifications of tumour suppressor genes are involved in all kinds of human cancer. Aberrant promoter methylation is also considered to play an essential role in development of lung cancer, but the pathogenesis remains unclear.We collected the data of 112 subjects, including 56 diagnosed patients with lung cancer and 56 controls without cancer. Methylation of the FHIT, RASSF1A and RAR-${\beta}$ genes in DNA from all samples and the corresponding gene methylation status were assessed using the methylation-specific polymerase chain reaction (PCR, MSP). The results showed that the total frequency of separate gene methylation was significantly higher in lung cancer compared with controls (33.9-85.7 vs 0 %) (p<0.01).Similar outcomes were obtained from the aberrant methylation of combinations of any two or three genes (p<0.01). There was a tendency that the frequency of combinations of any two or three genes was higher in stage I+II than that in stage III+IV with lung cancer. However, no significant difference was found across various clinical stages and clinic pathological gradings of lung cancer (p>0.05).These observations suggest that there is a significant association of promoter methylation of individual genes with lung cancer risk, and that aberrant methylation of combination of any two or three genes may be associated with clinical stage in lung cancer patients and involved in the initiation of lung cancer tumorigenesis. Methylation of FHIT, RASSF1A and $RAR{\beta}$ genes may be related to progression of lung oncogenesis.

• Genomics & Informatics
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• v.19 no.1
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• pp.3.1-3.12
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• 2021

Functional interpretation of noncoding genetic variants associated with complex human diseases and traits remains a challenge. In an effort to enhance our understanding of common germline variants associated with lung cancer, we categorize regulatory elements based on eight major cell types of human lung tissue. Our results show that 21.68% of lung cancer-associated risk variants are linked to noncoding regulatory elements, nearly half of which are cell type-specific. Integrative analysis of high-resolution long-range chromatin interactome maps and single-cell RNA-sequencing data of lung tumors uncovers number of putative target genes of these variants and functionally relevant cell types, which display a potential biological link to cancer susceptibility. The present study greatly expands the scope of functional annotation of lung cancer-associated genetic risk factors and dictates probable cell types involved in lung carcinogenesis.

• Korean Journal of Biological Psychiatry
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• v.7 no.2
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• pp.123-130
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• 2000

The development of inexpensive high throughput methods to identify individual DNA sequences is important to the future growth of medical genetics. This has become increasingly apparent as psychiatric geneticists focus more attention on the molecular basis of complex multifactorial diseases at which most of psychiatric disease is estimated. Furthermore, candidate gene approaches used in identifying disease associated genes necessitate screening large sequence blocks for changes tracking with the disease state. Even after such genes are isolated, large scale mutational analysis will often be needed for risk assessment studies to define the likely medical consequences of carrying a mutated gene. This review provide basic knowledge of up-to-date technology, cDNA microarray which enables above mentioned various research themes.

• Genomics & Informatics
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• v.10 no.3
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• pp.184-193
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• 2012

Gastric cancer is ranked as the most common cancer in Koreans. A recent molecular biological study about the folate pathway gene revealed the correlation with a couple of cancer types. In the folate pathway, several genes are involved, including methylenetetrahydrofolate reductase (MTHFR), methyltetrahydrofolate-homocysteine methyltransferase reductase (MTRR), and methyltetrahydrofolate-homocysteine methyltransferase (MTR). The MTHFR gene has been reported several times for the correlation with gastric cancer risk. However, the association of the MTRR or MTR gene has not been reported to date. In this study, we investigated the association between the single nucleotide polymorphisms (SNPs) of the MTHFR, MTRR, and MTR genes and the risk of gastric cancer in Koreans. To identify the genetic association with gastric cancer, we selected 17 SNPs sites in folate pathway-associated genes of MTHFR, MTR, and MTRR and tested in 1,261 gastric cancer patients and 375 healthy controls. By genotype analysis, estimating odds ratios and 95% confidence intervals (CI), rs1801394 in the MTRR gene showed increased risk for gastric cacner, with statistical significance both in the codominant model (odds ratio [OR], 1.39; 95% CI, 1.04 to 1.85) and dominant model (OR, 1.34; 95% CI, 1.02 to 1.75). Especially, in the obese group (body mass index ${\geq}25kg/m^2$), the codominant (OR, 9.08; 95% CI, 1.01 to 94.59) and recessive model (OR, 3.72; 95% CI, 0.92 to 16.59) showed dramatically increased risk (p < 0.05). In conclusion, rs1801394 in the MTRR gene is associated with gastric cancer risk, and its functional significance need to be validated.

• Genomics & Informatics
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• v.8 no.3
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• pp.150-158
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• 2010

Genome-wise association studies (GWASs) have become popular approaches to identify genetic variants associated with human biological traits. In this study, we applied Structural Equation Models (SEMs) in order to model complex relationships between genetic networks and traits as risk factors. SEMs allow us to achieve a better understanding of biological mechanisms through identifying greater numbers of genes and pathways that are associated with a set of traits and the relationship among them. For efficient SEM analysis for GWASs, we developed a procedure, comprised of four stages. In the first stage, we conducted single-SNP analysis using regression models, where age, sex, and recruited area were included as adjusting covariates. In the second stage, Fisher's combination test was conducted for each gene to detect significant genes using p-values obtained from the single-SNP analysis. In the third stage, Fisher's exact test was adopted to determine which biological pathways were enriched with significant SNPs. Finally, based on a pathway that was associated with the four traits in common, a SEM was fit to model a causal relationship among the genetic factors and traits. We applied our SEM model to GWAS data with four central obesity related traits: suprailiac and subscapular measures for upper body fat, BMI, and hypertension. Study subjects were collected from two Korean cohort regions. After quality control, 327,872 SNPs for 8842 individuals were included in the analysis. After comparing two SEMs, we concluded that suprailiac and subscapular measures may indirectly affect hypertension susceptibility by influencing BMI. In conclusion, our analysis demonstrates that SEMs provide a better understanding of biological mechanisms by identifying greater numbers of genes and pathways.

• Advances in pediatric surgery
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• v.14 no.1
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• pp.75-82
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• 2008

Neuroblastoma arises from the primitive neural crest cells, and is a common malignancy in childhood. The clinical features are characterized by biological heterogeneity. Neuronal degeneration and differentiation occur in some patients. However treatment in the high risk group accounting for approximately half, has not been satisfactory despite a multimodal approach. Therefore, effective treatment is determined by the risk group of prognostic factors, such as age at diagnosis, stage of disease, pathological finding and N-myc amplification. Neuroblastoma can be diagnosed prenatally, which suggests its origin during the normal embryogenesis. Recent knowledge of molecular biology, such as Trk genes, and the concept of cancer stem cells have given us some improved understanding on this disease. Currently, targeted therapies based on the molecular biology of neuroblastoma are under investigation and increasing survival rate and decreasing late complications could be appreciated.

• Journal of Korean Biological Nursing Science
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• v.18 no.4
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• pp.305-317
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• 2016

Purpose: Recent studies demonstrated disruption of the circadian clock gene is associated with the development of obesity and metabolic syndrome. Obesity is often caused by the high calorie intake, In addition, the chronic stress tends to contribute to the increased risk for obesity. To evaluate the molecular mechanisms, we examined the expression of circadian clock genes in high fat diet-induced mice models with the chronic stress. Methods: C57BL/6J mice were fed with a 45% or 60% high fat diet for 8 weeks. Daily immobilization stress was applied to mice fed with a 45% high fat for 16 weeks. We compared body weight, food consumption, hormone levels and metabolic variables in blood. mRNA expression levels of metabolic and circadian clock genes in both fat and liver were determined by quantitative RT-PCR. Results: The higher fat content induced more severe hyperglycemia, hyperlipidemia and hyperinsulinemia, and these results correlated with their relevant gene expressions in fat and liver tissues. Chronic stress had only minimal effects on metabolic variables, but it altered the expression patterns of metabolic and circadian clock genes. Conclusion: These results suggest that the fat metabolism regulates the function of the circadian clock genes in peripheral tissues, and stress hormones may contribute to its regulation.