Biomedical subjects

Jihoon Kim

Publications and source records attributed to Jihoon Kim.

8 recordsLinked to original sources

PubMed2026

Assessing the comorbidity between asthma and depression through polygenic risk scoring and time-to-event models.

BACKGROUND: Patients with asthma have an increased risk of developing depression, affecting their quality of life. To date, the processes contributing to this comorbidity remain unclear. METHODS: We integrated two large genome-wide association studies (88,486 patients with asthma and 447,859 controls; 412,024 patients with depression and 1,587,577 controls) with cross-sectional and longitudinal information available from the All of Us Research Program (N = 87,167) through polygenic risk scoring (PRS), Cox proportional-hazards models, one-sample Mendelian randomization (MR), and gene-set and drug-repurposing analyses. RESULTS: We observed that depression PRS was associated with increased asthma risk (hazard ratio, HR = 1.13, 95% CI = 1.09-1.17), also when accounting for comorbidity status (HR = 1.08, 95% CI = 1.04-1.12). Conversely, the effect of asthma PRS was null after accounting for comorbidity status. One-sample MR analysis showed an effect of depression genetic liability on asthma, ranging from beta = 0.36 ± 0.03 when considering a linear relationship to beta = 3.21 ± 0.31 when considering possible nonlinear relationships. Conversely, the effect of asthma genetic risk on depression was null after accounting for potential confounders. The gene-set analyses showed that asthma and depression polygenic risks share biological processes, molecular functions, and cellular components related to the immune system and the lung-brain axis. CONCLUSIONS: Genetic predisposition contributes to asthma-depression comorbidity through direct effects and shared pathogenic processes. These findings highlight the potential to develop targeted interventions to prevent and treat the co-occurrence of respiratory and neuropsychiatric disorders.

Comorbidity↗

PubMed2006

Selection of neural differentiation-specific genes by comparing profiles of random differentiation.

Differentiation of embryonic stem cells (ESCs) into neurons requires a high level of transcriptional regulation. To further understand the transcriptional regulation of neural differentiation of ESCs, we used oligonucleotide microarray to examine the gene expressions of the guided differentiation (GD) model for dopaminergic (DA) neurons from mouse ESCs. We also determined the gene expression profiles of the random differentiation (RD) model of mouse ESCs into embryoid bodies. From K-means clustering analysis using the expression patterns of the two models, most of the genes (1,282 of 1,884 genes [68.0%]) overlapped in their expression patterns. Six hundred twenty-two differentially expressed genes (DEGs) from the GD model by random variance F-test were classified by their critical molecular functions in neurogenesis and DNA replication (Gene Ontology analysis). However, 400 genes among GD-DEGs (64.3%) showed a high correlation with RD in Spearman's correlation analysis (Spearman's coefficient p(s) >or= .6). The genes showing marginal correlation (-.4 < p(s) < .6) were present in the early stages of differentiation of both GD and RD, which were non-specific to brain development. Finally, we distinguished 66 GD-specific genes based on p(s) <or= -.4, the molecular functions of which were related mainly to vesicle formation, neurogenesis, and transcription factors. From among these GD-specific genes, we confirmed the expression of Serpini1 and Rab33a in P19 differentiation models and adult brains. From these results, we identified the specific genes required for neural differentiation by comparing gene expressions of GD with RD; these would potentially be the highly specific candidate genes necessary for differentiation of DA neurons.

Animals↗

PubMed2005

ArrayXPath II: mapping and visualizing microarray gene-expression data with biomedical ontologies and integrated biological pathway resources using Scalable Vector Graphics.

SUMMARY: ArrayXPath (http://www.snubi.org/software/ArrayXPath/) is a web-based service for mapping and visualizing microarray gene-expression data with integrated biological pathway resources using Scalable Vector Graphics (SVG). Deciphering the crosstalk among pathways and integrating biomedical ontologies and knowledge bases may help biological interpretation of microarray data. ArrayXPath is empowered by integrating gene-pathway, disease-pathway, drug-pathway and pathway-pathway correlations with integrated Gene Ontology, Medical Subject Headings and OMIM Morbid Map-based annotations. We applied Fisher's exact test and relative risk to evaluate the statistical significance of the correlations. ArrayXPath produces Javascript-enabled SVGs for web-enabled interactive visualization of gene-expression profiles integrated with gene-pathway-disease interactions enriched by biomedical ontologies.

Cluster Analysis↗

PubMed2004

ArrayXPath: mapping and visualizing microarray gene-expression data with integrated biological pathway resources using Scalable Vector Graphics.

Biological pathways can provide key information on the organization of biological systems. ArrayXPath (http://www.snubi.org/software/ArrayXPath/) is a web-based service for mapping and visualizing microarray gene-expression data for integrated biological pathway resources using Scalable Vector Graphics (SVG). By integrating major bio-databases and searching pathway resources, ArrayXPath automatically maps different types of identifiers from microarray probes and pathway elements. When one inputs gene-expression clusters, ArrayXPath produces a list of the best matching pathways for each cluster. We applied Fisher's exact test and the false discovery rate (FDR) to evaluate the statistical significance of the association between a cluster and a pathway while correcting the multiple-comparison problem. ArrayXPath produces Javascript-enabled SVGs for web-enabled interactive visualization of pathways integrated with gene-expression profiles.

Cluster Analysis↗

PubMed2004

ChromoViz: multimodal visualization of gene expression data onto chromosomes using scalable vector graphics.

SUMMARY: ChromoViz is an R package for the visualization of microarray gene expression data, cross-species and cross-platform comparisons, as well as non-expression genomic data obtained from public databases onto chromosomes. Chromosomal visualization format is proposed for the clear decoupling of the data layer from the procedure layer and the combined visualization of genomic data from heterogeneous data sources. Visualization with Javascript-enabled scalable vector graphics enables interactive visualization and navigation of data objects on the Web. AVAILABILITY: http://www.snubi.org/software/ChromoViz/

Chromosome Mapping↗

PubMed2004

Gene expression profiling of anti-GBM glomerulonephritis model: the role of NF-kappaB in immune complex kidney disease.

BACKGROUND: Immune complexes may cause an irreversible onset of chronic renal disease. Most patients with chronic renal disease undergo a final common pathway, marked by glomerulosclerosis and interstitial fibrosis. We attempted to draw a molecular map of anti-glomerular basement membrane (GBM) glomerulonephritis in mice using oligonucleotide microarray technology. METHODS: Kidneys were harvested at days 1, 3, 7, 11, and 16 after inducing glomerulonephritis by using anti-GBM antibody. In parallel with examining the biochemical and histologic changes, gene expression profiles were acquired against five pooled control kidneys. Gene expression levels were cross-validated by either reverse transcription-polymerase chain reaction (RT-PCR), real-time PCR, or immunohistochemistry. RESULTS: Pathologic changes in anti-GBM glomerulonephritis were confirmed in both BALB/c and C57BL/6 strains. Among the 13,680 spotted 65mer oligonucleotides, 1112 genes showing significant temporal patterns by permutation analysis of variance (ANOVA) with multiple testing correction [false discovery ratio (FDR) < 0.05] were chosen for cluster analysis. From the expression profile, acute inflammatory reactions characterized by the elevation of various cytokines, including interleukin (IL)-1 and IL-6, were identified within 3 days of disease onset. After 7 days, tissue remodeling response was prominent with highly induced extracellular-matrix (ECM) genes. Although cytokines related to lymphocyte activation were not detected, monocyte or mesangial cell proliferation-related genes were increased. Tumor necrosis factor-alpha (TNF-alpha) and nuclear factor-kappaB (NF-kappaB) pathway were consistently activated along the entire disease progression, inducing various target genes like complement 3, IL-1b, IL-6, Traf1, and Saa1. CONCLUSION: We made a large-scale gene expression time table for mouse anti-GBM glomerulonephritis model, providing a comprehensive overview on the mechanism governing the initiation and the progression of inflammatory renal disease.

Animals↗

PubMed2003

Social network analysis of gene expression data.

To investigate the structure of genomic interaction network, social affiliation network analysis was performed for the yeast gene expression compendium dataset of hundreds of systematic perturbations. Network density and centrality indices of genes and groups of genes revealed the core-peripheral and the significant intermediary players that may be critical for the control of the biological system.

Computational Biology↗

PubMed2002

Dynamic impedance measurements during radio-frequency heating of cornea.

Hyperopia affects approximately 25% of the population. The aim of different heating modalities for the treatment of hyperopia is to steepen the central curvature of the cornea. Conductive keratoplasty (CK) involves the placement of radio-frequency (RF) lesions around a 7-mm-diameter ring concentric with the pupil of the eye. Dynamics of lesion formation during CK depend on corneal electrical impedance, which is expected to change during each 600-ms-long macropulse. The purpose of this study was to measure impedance dynamics during CK. RF lesions were made in in vitro porcine eyes at different power settings. Voltage and current measurements were acquired using a high-speed computer-based data acquisition system. Root-mean-square voltages (VRMS) and curre (IRMS) were calculated for each micropulse, and impedance was determined by calculating the quotient VRMS/IRMS. Initial corneal impedance in vitro was approximately 2000 ohms. During the macropulse, impedance decreased initially due to increased mobility of conductive ions. At higher power settings (e.g., > 70%, or maximum peak-to-peak voltage of 233 V), impedance increased after the initial decrease, indicative of local water vaporization and/or tissue coagulation. Preliminary impedance data obtained for in vivo porcine eyes were similar in magnitude to the in vitro values.

Animals↗