Association analysis of sphingomyelinase 2 polymorphisms for the extrinsic type of atopic dermatitis in Koreans.
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Asian People↗
Biomedical subjects
Taesung Park
Publications and source records attributed to Taesung Park.
Odds ratio based multifactor-dimensionality reduction method for detecting gene-gene interactions.
MOTIVATION: The identification and characterization of genes that increase the susceptibility to common complex multifactorial diseases is a challenging task in genetic association studies. The multifactor dimensionality reduction (MDR) method has been proposed and implemented by Ritchie et al. (2001) to identify the combinations of multilocus genotypes and discrete environmental factors that are associated with a particular disease. However, the original MDR method classifies the combination of multilocus genotypes into high-risk and low-risk groups in an ad hoc manner based on a simple comparison of the ratios of the number of cases and controls. Hence, the MDR approach is prone to false positive and negative errors when the ratio of the number of cases and controls in a combination of genotypes is similar to that in the entire data, or when both the number of cases and controls is small. Hence, we propose the odds ratio based multifactor dimensionality reduction (OR MDR) method that uses the odds ratio as a new quantitative measure of disease risk. RESULTS: While the original MDR method provides a simple binary measure of risk, the OR MDR method provides not only the odds ratio as a quantitative measure of risk but also the ordering of the multilocus combinations from the highest risk to lowest risk groups. Furthermore, the OR MDR method provides a confidence interval for the odds ratio for each multilocus combination, which is extremely informative in judging its importance as a risk factor. The proposed OR MDR method is illustrated using the dataset obtained from the CDC Chronic Fatigue Syndrome Research Group. AVAILABILITY: The program written in R is available.
Fatigue Syndrome, Chronic↗
arrayQCplot: software for checking the quality of microarray data.
UNLABELLED: arrayQCplot is a software for the exploratory analysis of microarray data. This software focuses on quality control and generates newly developed plots for quality and reproducibility checks. It is developed using R and provides a user-friendly graphical interface for graphics and statistical analysis. Therefore, novice users will find arrayQCplot as an easy-to-use software for checking the quality of their data by a simple mouse click. AVAILABILITY: arrayQCplot software is available from Bioconductor at http://www.bioconductor.org. A more detailed manual is available at http://bibs.snu.ac.kr/software/arrayQCplot CONTACT: tspark@stats.snu.ac.kr.
Algorithms↗
Growth hormone-releasing hormone (GHRH) polymorphisms associated with carcass traits of meat in Korean cattle.
BACKGROUND: Cold carcass weight (CW) and longissimus muscle area (EMA) are the major quantitative traits in beef cattle. In this study, we found several polymorphisms of growth hormone-releasing hormone (GHRH) gene and examined the association of polymorphisms with carcass traits (CW and EMA) in Korean native cattle (Hanwoo). RESULTS: By direct DNA sequencing in 24 unrelated Korean cattle, we identified 12 single nucleotide polymorphisms within the 9 kb full gene region, including the 1.5 kb promoter region. Among them, six polymorphic sites were selected for genotyping in our beef cattle (n = 428) and five marker haplotypes (frequency > 0.1) were identified. Statistical analysis revealed that -4241A>T showed significant associations with CW and EMA. CONCLUSION: Our findings suggest that polymorphisms in GHRH might be one of the important genetic factors that influence carcass yield in beef cattle. Sequence variation/haplotype information identified in this study would provide valuable information for the production of a commercial line of beef cattle.
Animals↗
Extension of the Haseman-Elston regression model to longitudinal data.
We propose an extension to longitudinal data of the Haseman and Elston regression method for linkage analysis. The proposed model is a mixed model having several random effects. As response variable, we investigate the sibship sample mean corrected cross-product (smHE) and the BLUP-mean corrected cross product (pmHE), comparing them with the original squared difference (oHE), the overall mean corrected cross-product (rHE), and the weighted average of the squared difference and the squared mean-corrected sum (wHE). The proposed model allows for the correlation structure of longitudinal data. Also, the model can test for gene x time interaction to discover genetic variation over time. The model was applied in an analysis of the Genetic Analysis Workshop 13 (GAW13) simulated dataset for a quantitative trait simulating systolic blood pressure. Independence models did not preserve the test sizes, while the mixed models with both family and sibpair random effects tended to preserve size well.
Algorithms↗
Combining multiple microarrays in the presence of controlling variables.
MOTIVATION: Microarray technology enables the monitoring of expression levels for thousands of genes simultaneously. When the magnitude of the experiment increases, it becomes common to use the same type of microarrays from different laboratories or hospitals. Thus, it is important to analyze microarray data together to derive a combined conclusion after accounting for the differences. One of the main objectives of the microarray experiment is to identify differentially expressed genes among the different experimental groups. The analysis of variance (ANOVA) model has been commonly used to detect differentially expressed genes after accounting for the sources of variation commonly observed in the microarray experiment. RESULTS: We extended the usual ANOVA model to account for an additional variability resulting from many confounding variables such as the effect of different hospitals. The proposed model is a two-stage ANOVA model. The first stage is the adjustment for the effects of no interests. The second stage is the detection of differentially expressed genes among the experimental groups using the residuals obtained from the first stage. Based on these residuals, we propose a permutation test to detect the differentially expressed genes. The proposed model is illustrated using the data from 133 microarrays collected at three different hospitals. The proposed approach is more flexible to use, and it is easier to accommodate the individual covariates in this model than using the meta-analysis approach. AVAILABILITY: A set of programs written in R will be electronically sent upon request.
Algorithms↗
Hormone levels before and after tubal sterilization.
OBJECTIVE: The aim of this study was to determine whether women experience significant luteal phase hormonal changes following interval tubal sterilization. DESIGN: This is a partly randomized, prospective clinical study. SETTING: This study involved healthy volunteers in an academic research environment. PATIENTS: This study involved 118 fertile women seeking tubal sterilization and 57 fertile controls with at least three normal cyclic menstrual periods before entry into the study. INTERVENTIONS: The patients were randomized to bipolar cautery or Hulka clip as sterilization methods. Barrier contraception or abstinence was used by controls. MAIN OUTCOME MEASURES: The main outcome measures are serum estradiol and progesterone levels and urinary estradiol and pregnanediol levels obtained during the luteal phase before, 1 year and 2 years after sterilization. RESULTS: The women randomized to the bipolar cautery group had higher midluteal progesterone levels measured between Days 5 and 11 postovulation (15.5 ng/mL before sterilization, 14.5 ng/mL at 1 year and 14.5 ng/mL at 2 years) than did the other two groups. The clip group had progesterone levels of 14.1, 12.0 and 12.5 ng/mL at baseline, 1 year and 2 years, respectively, and the control group had levels of 12.0, 11.9 and 11.3 ng/mL for the same periods. Serum estradiol and progesterone and urinary pregnanediol and estradiol were not significantly changed over the 2-year period, nor were there significant differences between the two groups. CONCLUSIONS: There were no significant hormonal changes in sterilized women over a period of 2 years when compared with their baseline levels or when compared with unsterilized age-matched controls.
Adult↗
Field evaluation of a rapid immunochromatographic dipstick test for the diagnosis of cholera in a high-risk population.
BACKGROUND: Early detection of cholera outbreaks is crucial for the implementation of the most appropriate control strategies. METHODS: The performance of an immunochromatographic dipstick test (Institute Pasteur, Paris, France) specific for Vibrio cholerae O1 was evaluated in a prospective study in Beira, Mozambique, during the 2004 cholera season (January-May). Fecal specimens were collected from 391 patients with acute watery nonbloody diarrhea and tested by dipstick and conventional culture. RESULTS: The overall sensitivity and specificity of the rapid test compared to culture were 95% (95% confidence interval [CI]: 91%-99%) and 89% (95% CI: 86%-93%), respectively. After stratification by type of sample (rectal swab/bulk stool) and severity of diarrhea, the sensitivity ranged between 85% and 98% and specificity between 77% and 97%. CONCLUSION: This one-step dipstick test performed well in the diagnosis of V. cholerae O1 in a setting with seasonal outbreaks where rapid tests are most urgently needed.
Adolescent↗
Whole-genome association studies of alcoholism with loci linked to schizophrenia susceptibility.
BACKGROUND: Alcoholism is a complex disease. There have been many reports on significant comorbidity between alcoholism and schizophrenia. For the genetic study of complex diseases, association analysis has been recommended because of its higher power than that of the linkage analysis for detecting genes with modest effects on disease. RESULTS: To identify alcoholism susceptibility loci, we performed genome-wide single-nucleotide polymorphisms (SNP) association tests, which yielded 489 significant SNPs at the 1% significance level. The association tests showed that tsc0593964 (P-value 0.000013) on chromosome 7 was most significantly associated with alcoholism. From 489 SNPs, 74 genes were identified. Among these genes, GABRA1 is a member of the same gene family with GABRA2 that was recently reported as alcoholism susceptibility gene. CONCLUSION: By comparing 74 genes to the published results of various linkage studies of schizophrenia, we identified 13 alcoholism associated genes that were located in the regions reported to be linked to schizophrenia. These 13 identified genes can be important candidate genes to study the genetic mechanism of co-occurrence of both diseases.
Alcoholism↗
Diagnostic plots for detecting outlying slides in a cDNA microarray experiment.
Different sources of systematic and random error variations are often observed in cDNA microarray experiments. A simple scatter plot is commonly used to examine outlying slides that have unusual expression patterns or larger variability than other slides. These outlying slides tend to have large impacts on the subsequent analyses, such as identification of differentially expressed genes and clustering analysis. However, it is difficult to select outlying slides rigorously and consistently based on subjective human pattern recognition on their scatter plots. A graphical method and a rigorous diagnostic measure are proposed to detect outlying slides. The proposed graphical method is easy to implement and shown to be quite effective in detecting outlying slides in real microarray data sets. This diagnostic measure is also informative to compare variability among slides. Two cDNA microarray data sets are carefully examined to illustrate the proposed approach. A 3840-gene microarray experiment for neuronal differentiation of cortical stem cells and a 2076-gene microarray experiment for anticancer compound time-course expression of the NCI-60 cancer cell lines.
Algorithms↗
A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer.
BACKGROUND: The likelihood of distant recurrence in patients with breast cancer who have no involved lymph nodes and estrogen-receptor-positive tumors is poorly defined by clinical and histopathological measures. METHODS: We tested whether the results of a reverse-transcriptase-polymerase-chain-reaction (RT-PCR) assay of 21 prospectively selected genes in paraffin-embedded tumor tissue would correlate with the likelihood of distant recurrence in patients with node-negative, tamoxifen-treated breast cancer who were enrolled in the National Surgical Adjuvant Breast and Bowel Project clinical trial B-14. The levels of expression of 16 cancer-related genes and 5 reference genes were used in a prospectively defined algorithm to calculate a recurrence score and to determine a risk group (low, intermediate, or high) for each patient. RESULTS: Adequate RT-PCR profiles were obtained in 668 of 675 tumor blocks. The proportions of patients categorized as having a low, intermediate, or high risk by the RT-PCR assay were 51, 22, and 27 percent, respectively. The Kaplan-Meier estimates of the rates of distant recurrence at 10 years in the low-risk, intermediate-risk, and high-risk groups were 6.8 percent (95 percent confidence interval, 4.0 to 9.6), 14.3 percent (95 percent confidence interval, 8.3 to 20.3), and 30.5 percent (95 percent confidence interval, 23.6 to 37.4). The rate in the low-risk group was significantly lower than that in the high-risk group (P<0.001). In a multivariate Cox model, the recurrence score provided significant predictive power that was independent of age and tumor size (P<0.001). The recurrence score was also predictive of overall survival (P<0.001) and could be used as a continuous function to predict distant recurrence in individual patients. CONCLUSIONS: The recurrence score has been validated as quantifying the likelihood of distant recurrence in tamoxifen-treated patients with node-negative, estrogen-receptor-positive breast cancer.
Algorithms↗
The epidemiology of acute pyelonephritis in South Korea, 1997-1999.
Acute pyelonephritis causes significant morbidity, tends to recur, and can be fatal; however, little is known regarding its epidemiology. In this paper, the authors describe the epidemiology of acute pyelonephritis in South Korea by using nationwide heath insurance claims data from 1997 to 1999. The National Health Insurance System of South Korea covers almost the entire population (99%). The overall average annual incidence rate of pyelonephritis in 1997-1999 was 35.7 per 10,000 population (male, 12.6; female, 59.0). Approximately one of every seven patients was hospitalized (incidence per 10,000: inpatients, 5.5; outpatients, 30.1). Incidence varied with age and was higher in the summer season. Following an initial episode, the risk of a second episode within 12 months was 9.2% for females and 5.7% for males; by contrast, the risk of a fifth episode within a year following a fourth episode was 50.0% for females and 53.0% for males. Female sex (hazard ratio = 1.89, 95% confidence interval: 1.60, 2.23), advancing age, outpatient treatments (hazard ratio = 1.35, 95% confidence interval: 1.14, 1.60), and medical aid (hazard ratio = 1.23, 95% confidence interval: 1.08, 1.40) increased the risk of any recurrence. Pyelonephritis has a clear seasonal pattern and high rate of recurrence. The incidence of hospitalization for pyelonephritis in South Korea is similar to that in the United States and Canada.
Adolescent↗
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↗
Statistical analysis of MMR vaccine adverse events on aseptic meningitis using the case cross-over design.
Vaccination is quite effective in reducing the incidence of disease. However, it may cause some adverse events. For example, one of the adverse events of measles-mumps-rubella(MMR) vaccination is the occurrence of aseptic meningitis. Since the vaccination rate is usually quite high, it is not plausible to use popular study designs such as cohort or case-control studies. We considered a case cross-over design to investigate the association between MMR vaccination and aseptic meningitis in Korean children. We used the Cochran-Mantel-Haenszel(CMH) approach, and obtained a Mantel-Haenszel odds ratio estimator as a measure of association. However, the validity of case cross-over design or the CMH approach in vaccine adverse studies has not been fully investigated. In this paper, through Monte Carlo simulation studies, we show the appropriateness of the case cross-over design and the CMH approach. We also discuss alternative approaches such as Poisson regression using offset and a simple uniformity test. In conclusion, the case cross-over design seems useful to investigate the association between vaccination and occurrence of acute adverse events.
Child, Preschool↗
Linkage analysis of longitudinal data.
BACKGROUND: We propose a statistical model for linkage analysis of the longitudinal data. The proposed model is a mixed model based on the new Haseman and Elston model and allows several random effects. Specifically, the proposed model includes a random effect for correlation among sib pairs having one sibling in common, and one for the correlation among siblings from the same parents. RESULTS: The proposed model was applied to the analysis of the Genetic Analysis Workshop 13 simulated data set for a quantitative trait of the systolic blood pressure. A simple independence model and two kinds of random effects models yielded good power for detecting linkage for these data sets, while the random effects models performed slightly better than the independence model. Both random effects models showed similar performance. CONCLUSIONS: The proposed models seem not only quite useful in detecting linkage with the longitudinal data for the trait but also quite flexible. They can handle a wide class of correlation structures. Models with a more general class of covariance structure are desirable.
Adult Children↗
Evaluation of normalization methods for microarray data.
BACKGROUND: Microarray technology allows the monitoring of expression levels for thousands of genes simultaneously. This novel technique helps us to understand gene regulation as well as gene by gene interactions more systematically. In the microarray experiment, however, many undesirable systematic variations are observed. Even in replicated experiment, some variations are commonly observed. Normalization is the process of removing some sources of variation which affect the measured gene expression levels. Although a number of normalization methods have been proposed, it has been difficult to decide which methods perform best. Normalization plays an important role in the earlier stage of microarray data analysis. The subsequent analysis results are highly dependent on normalization. RESULTS: In this paper, we use the variability among the replicated slides to compare performance of normalization methods. We also compare normalization methods with regard to bias and mean square error using simulated data. CONCLUSIONS: Our results show that intensity-dependent normalization often performs better than global normalization methods, and that linear and nonlinear normalization methods perform similarly. These conclusions are based on analysis of 36 cDNA microarrays of 3,840 genes obtained in an experiment to search for changes in gene expression profiles during neuronal differentiation of cortical stem cells. Simulation studies confirm our findings.
Analysis of Variance↗
Statistical tests for identifying differentially expressed genes in time-course microarray experiments.
MOTIVATION: Microarray technology allows the monitoring of expression levels for thousands of genes simultaneously. In time-course experiments in which gene expression is monitored over time, we are interested in testing gene expression profiles for different experimental groups. However, no sophisticated analytic methods have yet been proposed to handle time-course experiment data. RESULTS: We propose a statistical test procedure based on the ANOVA model to identify genes that have different gene expression profiles among experimental groups in time-course experiments. Especially, we propose a permutation test which does not require the normality assumption. For this test, we use residuals from the ANOVA model only with time-effects. Using this test, we detect genes that have different gene expression profiles among experimental groups. The proposed model is illustrated using cDNA microarrays of 3840 genes obtained in an experiment to search for changes in gene expression profiles during neuronal differentiation of cortical stem cells.
Algorithms↗
Risk analysis of aseptic meningitis after measles-mumps-rubella vaccination in Korean children by using a case-crossover design.
Epidemiologic study of a vaccine's adverse events is not easy; so many countries have no reliable data. Vaccines containing the Urabe or Hoshino strain have been withdrawn from use in several countries. However, the data are not strong enough to form the basis of a recommendation not to use specific strains. The authors used a case-crossover design to estimate the relative risk of aseptic meningitis in children after receiving the measles-mumps-rubella vaccine in Korea. Study subjects were hospitalized children aged 8-36 months who had aseptic meningitis in 1998. Cases were confirmed by hospital chart reviews using previously defined criteria. Through a telephone survey, the authors obtained vaccination date and place information from parents' vaccination records. Study results showed that no significant risk was associated with the Jeryl Lynn or Rubini strain of the vaccine (relative risk = 0.6, 95% confidence interval (CI): 0.18, 1.97). For the Urabe or Hoshino strain, the relative risk was 5.5 (95% CI: 2.6, 11.8); the risk increased in the third week after vaccination (relative risk = 15.6, 95% CI: 5.9, 41.2) and was elevated until the sixth week. The case-crossover design was useful in confirming the risk of acute adverse events after receiving vaccines.
Child, Preschool↗