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Ju-Han Kim

Publications and source records attributed to Ju-Han Kim.

6 recordsLinked to original sources
PubMed2005

Design issues in toxicogenomics using DNA microarray experiment.

The methods of toxicogenomics might be classified into omics study (e.g., genomics, proteomics, and metabolomics) and population study focusing on risk assessment and gene-environment interaction. In omics study, microarray is the most popular approach. Genes falling into several categories (e.g., xenobiotics metabolism, cell cycle control, DNA repair etc.) can be selected up to 20,000 according to a priori hypothesis. The appropriate type of samples and species should be selected in advance. Multiple doses and varied exposure durations are suggested to identify those genes clearly linked to toxic response. Microarray experiments can be affected by numerous nuisance variables including experimental designs, sample extraction, type of scanners, etc. The number of slides might be determined from the magnitude and variance of expression change, false-positive rate, and desired power. Instead, pooling samples is an alternative. Online databases on chemicals with known exposure-disease outcomes and genetic information can aid the interpretation of the normalized results. Gene function can be inferred from microarray data analyzed by bioinformatics methods such as cluster analysis. The population study often adopts hospital-based or nested case-control design. Biases in subject selection and exposure assessment should be minimized, and confounding bias should also be controlled for in stratified or multiple regression analysis. Optimal sample sizes are dependent on the statistical test for gene-to-environment or gene-to-gene interaction. The design issues addressed in this mini-review are crucial in conducting toxicogenomics study. In addition, integrative approach of exposure assessment, epidemiology, and clinical trial is required.

Computational Biology↗
PubMed2004

Two-stage normalization using background intensities in cDNA microarray data.

BACKGROUND: In the microarray experiment, many undesirable systematic variations are commonly observed. Normalization is the process of removing such variation that affects the measured gene expression levels. Normalization plays an important role in the earlier stage of microarray data analysis. The subsequent analysis results are highly dependent on normalization. One major source of variation is the background intensities. Recently, some methods have been employed for correcting the background intensities. However, all these methods focus on defining signal intensities appropriately from foreground and background intensities in the image analysis. Although a number of normalization methods have been proposed, no systematic methods have been proposed using the background intensities in the normalization process. RESULTS: In this paper, we propose a two-stage method adjusting for the effect of background intensities in the normalization process. The first stage fits a regression model to adjust for the effect of background intensities and the second stage applies the usual normalization method such as a nonlinear LOWESS method to the background-adjusted intensities. In order to carry out the two-stage normalization method, we consider nine different background measures and investigate their performances in normalization. The performance of two-stage normalization is compared to those of global median normalization as well as intensity dependent nonlinear LOWESS normalization. We use the variability among the replicated slides to compare performance of normalization methods. CONCLUSIONS: For the selected background measures, the proposed two-stage normalization method performs better than global or intensity dependent nonlinear LOWESS normalization method. Especially, when there is a strong relationship between the background intensity and the signal intensity, the proposed method performs much better. Regardless of background correction methods used in the image analysis, the proposed two-stage normalization method can be applicable as long as both signal intensity and background intensity are available.

Cell Line, Tumor↗
PubMed2004

Clinical characteristics of hypervagotonic sinus node dysfunction.

BACKGROUND: Sinus node dysfunction (SND) is caused not only by intrinsic sinus node disease, but also by the extrinsic factors. Among the extrinsic factors, autonomic imbalance is most common. Symptomatic SND usually requires permanent pacemaker therapy. However, the clinical characteristics and patient response to medical therapy for hypervagotonic SND have not been properly clarified. MATERIALS AND METHODS: Thirty two patients (14 men, 18 women, 51 +/- 14 years) with hypervagotonic SND were included in this study, but those patients who had taken calcium antagonists, beta-blockers or other antiarrhythmic drugs were excluded. Hypervagotonic SND was diagnosed if the abnormal electrophysiologic properties of the sinus node were normalized after the administration of atropine (0.04 mg/kg). RESULTS: The presenting arrhythmias were 16 cases of sinus bradycardia (50.0%), 12 of sinus pause (37.5%), 3 of sinoatrial block (9.4%) and 1 of tachy-bradycardia (3.1%). Nine (28.1%) patients had hypertension, 7 (21.9%) smoked, 2 (6.3%) had diabetes mellitus, and 1 (3.1%) had hypercholesterolemia. Among the patients, 3 had no remarkable symptoms, 13 had dizziness, 7 had syncope, 3 had weakness and 6 had shortness of breath. Twenty five (78.1%) patients were treated with theophylline, 1 patient with tachy-bradycardia syndrome was treated with digoxin and propafenone, and 6 (18.8%) were treated with no medication. During the 43 +/- 28 month follow-up, 25 patients remained asymptomatic, but 6 who took no medication developed mild dizziness. One patient needed permanent pacemaker implantation owing to recurrent syncope despite of theophylline treatment. CONCLUSION: These results show that hypervagotonic SND has a benign course and most of the patients can be managed safely without implanting a pacemaker. (Ed note: I like the abstract. It is short and direct, as it should be.)

Dizziness↗
PubMed2002

Identification of radiation-specific responses from gene expression profile.

The responses to ionizing radiation (IR) in tumors are dependent on cellular context. We investigated radiation-related expression patterns in Jurkat T cells with nonsense mutation in p53 using cDNA microarray. Expression of 2400 genes in gamma-irradiated cells was distinct from other stimulations like anti-CD3, phetohemagglutinin (PHA) and concanavalin A (ConA) in unsupervised clustering analysis. Among them, 384 genes were selected for their IR-specific changes to make 'RadChip'. In spite of p53 status, every type of cells showed similar patterns in expression of these genes upon gamma-radiation. Moreover, radiation-induced responses were clearly separated from the responses to other genotoxic stress like UV radiation, cisplatin and doxorubicin. We focused on two IR-related genes, phospholipase Cgamma2 (PLCG2) and cytosolic epoxide hydrolase (EPHX2), which were increased at 12 h after gamma-radiation in RT-PCR. TPCK could suppress the induction of these two genes in either of Jurkat T cells and PBMCs, which might suggest the transcriptional regulation of PLCG2 and EPHX2 by NF-kappaB upon gamma-radiation. From these results, we could identify the IR-specific genes from expression profiling, which can be used as radiation biomarkers to screen radiation exposure as well as probing the mechanism of cellular responses to ionizing radiation.

Apoptosis↗
PubMed2002

Functional catechol-O-methyltransferase gene polymorphism and susceptibility to schizophrenia.

Genetic polymorphism of catechol-O-methyltransferase (COMT), involved in the degradation of catecholamine neurotransmitters, has been investigated as a candidate for modifier of susceptibility to development of schizophrenia. To address this issue further, we carried out a study in Korean schizophrenic patients and controls. The study population consisted of 103 Korean inpatients diagnosed as schizophrenic and their 103 age and sex matched controls. The patients were divided into two groups on the basis of history of aggressive behavior, family history of schizophrenia and related disorders, and age at onset of the disease. The COMT genotypes were determined by a PCR based method. No statistically significant overall associations between the COMT genotypes and risk of schizophrenia were observed. However, subjects with at least one low activity associated COMT-L allele showed a tendency of elevated risk for schizophrenia (OR=1.7, 95% CI=0.9-3.1) compared with those homozygous for the high activity associated COMT-H alleles. Moreover, when cases were stratified by family history of schizophrenia, a significant combined effect was seen: the cases with concurrent family history of schizophrenia and the COMT-L allele containing genotypes had an almost 4-fold (OR=3.9, 95% CI=1.1-14.3) higher risk of schizophrenia compared to controls with the COMT-HH genotypes. Future studies with larger sample sizes are, however, needed to confirm this novel finding.

Adult↗