Nitrosylation of ß2-Tubulin Promotes Microtubule Disassembly and Differentiated Cardiomyocyte Beating in Ischemic Mice.

BACKGROUND: Beating cardiomyocyte regeneration therapies have revealed as alternative therapeutics for heart transplantation. Nonetheless, the importance of nitric oxide (NO) in cardiomyocyte regeneration has been widely suggested, little has been reported concerning endogenous NO during cardiomyocyte differentiation. METHODS: Here, we used P19CL6 cells and a Myocardiac infarction (MI) model to confirm NO-induced protein modification and its role in cardiac beating. Two tyrosine (Tyr) residues of ß2-tubulin (Y106 and Y340) underwent nitrosylation (Tyr-NO) by endogenously generated NO during cardiomyocyte differentiation from pre-cardiomyocyte-like P19CL6 cells. RESULTS: Tyr-NO-ß2-tubulin mediated the interaction with Stathmin, which promotes microtubule disassembly, and was prominently observed in spontaneously beating cell clusters and mouse embryonic heart (E11.5d). In myocardial infarction mice, Tyr-NO-ß2-tubulin in transplanted cells was closely related with cardiac troponin-T expression with their functional recovery, reduced infarct size and thickened left ventricular wall. CONCLUSION: This is the first discovery of a new target molecule of NO, ß2-tubulin, that can promote normal cardiac beating and cardiomyocyte regeneration. Taken together, we suggest therapeutic potential of Tyr-NO-ß2-tubulin, for ischemic cardiomyocyte, which can reduce unexpected side effect of stem cell transplantation, arrhythmogenesis.

RDscan: A New Method for Improving Germline and Somatic Variant Calling Based on Read Depth Distribution.

Several tools have been developed for calling variants from next-generation sequencing (NGS) data. Although they are generally accurate and reliable, most of them have room for improvement, especially regarding calling variants in datasets with low read depth. In addition, the somatic variants predicted by several somatic variant callers tend to have very low concordance rates. In this study, we developed a new method (RDscan) for improving germline and somatic variant calling in NGS data. RDscan removes misaligned reads, repositions reads, and calculates RDscore based on the read depth distribution. With RDscore, RDscan improves the precision of variant callers by removing false-positive variant calls. When we tested our new tool using the latest variant calling algorithms and data from the 1000 Genomes Project and Illumina's public datasets, accuracy was improved for most of the algorithms. After screening variants with RDscan, calling accuracies increased for germline variants in 11 of 12 cases and for somatic variants in 21 of 24 cases. RDscan is simple to use and can effectively remove false-positive variants while maintaining a low computation load. Therefore, RDscan, along with existing variant callers, should contribute to improvements in genome analysis.

Deep learning model enables the discovery of a novel immunotherapeutic agent regulating the kynurenine pathway.

Kynurenine (Kyn) is a key inducer of an immunosuppressive tumor microenvironment (TME). Although indoleamine 2,3-dioxygenase (IDO)-selective inhibitors have been developed to suppress the Kyn pathway, the results were not satisfactory due to the presence of various opposing mechanisms. Here, we employed an orally administered novel Kyn pathway regulator to overcome the limitation of anti-tumor immune response. We identified a novel core structure that inhibited both IDO and TDO. An orally available lead compound, STB-C017 (designated hereafter as STB), effectively inhibited the enzymatic and cellular activity of IDO and TDO in vitro. Moreover, it potently suppressed Kyn levels in both the plasma and tumor in vivo. STB monotherapy increased the infiltration of CD8+ T cells into TME. In addition, STB reprogrammed the TME with widespread changes in immune-mediated gene signatures. Notably, STB-based combination immunotherapy elicited the most potent anti-tumor efficacy through concurrent treatment with immune checkpoint inhibitors, leading to complete tumor regression and long-term overall survival. Our study demonstrated that a novel Kyn pathway regulator derived using deep learning technology can activate T cell immunity and potentiate immune checkpoint blockade by overcoming an immunosuppressive TME.

A Mutation in ZNF143 as a Novel Candidate Gene for Endothelial Corneal Dystrophy.

Corneal dystrophies (CDs) are a diverse group of inherited disorders with a heterogeneous genetic background. Here, we report the identification of a novel ZNF143 heterozygous missense mutation in three individuals of the same family with clinical and pathological features that are consistent with endothelial CD. Ophthalmologic examination revealed diffuse corneal clouding and edema with decreased endothelial cell density. Pathological findings showed increased corneal thickness due to edema of basal epithelial cells and stroma, and abnormal metaplastic endothelium with stratified epithelium-like changes. Patients' metaplastic corneal endothelial cells expressed predominantly cytokerain 7, cytokeratin 19, and E-cadherin. Although Sanger sequencing did not detect any mutation associated with endothelial CDs, whole exome sequencing identified the ZNF143 c.937G>C p.(Asp313His) mutation as a candidate gene for our patients' endothelial CD. In-vitro functional studies demonstrated that mutant ZNF143 promoted the mesenchymal-to-epithelial transition; it upregulated the expression of genes associated with epithelialization in human corneal endothelial cells. Additionally, proinflammatory cytokine responsive genes were significantly enriched after mutant ZNF143 transfection, which may contribute to the severe phenotype of the three patients. These findings link a mutation in ZNF143 with endothelial CD for the first time.

Integrated genome sizing (IGS) approach for the parallelization of whole genome analysis.

BACKGROUND: The use of whole genome sequence has increased recently with rapid progression of next-generation sequencing (NGS) technologies. However, storing raw sequence reads to perform large-scale genome analysis pose hardware challenges. Despite advancement in genome analytic platforms, efficient approaches remain relevant especially as applied to the human genome. In this study, an Integrated Genome Sizing (IGS) approach is adopted to speed up multiple whole genome analysis in high-performance computing (HPC) environment. The approach splits a genome (GRCh37) into 630 chunks (fragments) wherein multiple chunks can simultaneously be parallelized for sequence analyses across cohorts. RESULTS: IGS was integrated on Maha-Fs (HPC) system, to provide the parallelization required to analyze 2504 whole genomes. Using a single reference pilot genome, NA12878, we compared the NGS process time between Maha-Fs (NFS SATA hard disk drive) and SGI-UV300 (solid state drive memory). It was observed that SGI-UV300 was faster, having 32.5 mins of process time, while that of the Maha-Fs was 55.2 mins. CONCLUSIONS: The implementation of IGS can leverage the ability of HPC systems to analyze multiple genomes simultaneously. We believe this approach will accelerate research advancement in personalized genomic medicine. Our method is comparable to the fastest methods for sequence alignment.

Cancer Drug Response Profile scan (CDRscan): A Deep Learning Model That Predicts Drug Effectiveness from Cancer Genomic Signature.

In the era of precision medicine, cancer therapy can be tailored to an individual patient based on the genomic profile of a tumour. Despite the ever-increasing abundance of cancer genomic data, linking mutation profiles to drug efficacy remains a challenge. Herein, we report Cancer Drug Response profile scan (CDRscan) a novel deep learning model that predicts anticancer drug responsiveness based on a large-scale drug screening assay data encompassing genomic profiles of 787 human cancer cell lines and structural profiles of 244 drugs. CDRscan employs a two-step convolution architecture, where the genomic mutational fingerprints of cell lines and the molecular fingerprints of drugs are processed individually, then merged by 'virtual docking', an in silico modelling of drug treatment. Analysis of the goodness-of-fit between observed and predicted drug response revealed a high prediction accuracy of CDRscan (R2 > 0.84; AUROC > 0.98). We applied CDRscan to 1,487 approved drugs and identified 14 oncology and 23 non-oncology drugs having new potential cancer indications. This, to our knowledge, is the first-time application of a deep learning model in predicting the feasibility of drug repurposing. By further clinical validation, CDRscan is expected to allow selection of the most effective anticancer drugs for the genomic profile of the individual patient.

Development of the variant calling algorithm, ADIScan, and its use to estimate discordant sequences between monozygotic twins.

Calling variants from next-generation sequencing (NGS) data or discovering discordant sequences between two NGS data sets is challenging. We developed a computer algorithm, ADIScan1, to call variants by comparing the fractions of allelic reads in a tester to the universal reference genome. We then created ADIScan2 by modifying the algorithm to directly compare two sets of NGS data and predict discordant sequences between two testers. ADIScan1 detected >99.7% of variants called by GATK with an additional 724 393 SNVs. ADIScan2 identified ∼500 candidates of discordant sequences in each of two pairs of the monozygotic twins. About 200 of these candidates were included in the ∼2800 predicted by VarScan2. We verified 66 true discordant sequences among the candidates that ADIScan2 and VarScan2 exclusively predicted. ADIScan2 detected many discordant sequences overlooked by VarScan2 and Mutect, which specialize in detecting low frequency mutations in genetically heterogeneous cancerous tissues. Numbers of verified sequences alone were >5 times more than expected based on recently estimated mutation rates from whole genome sequences. Estimated post-zygotic mutation rates were 1.68 × 10-7 in this study. ADIScan1 and 2 would complement existing tools in screening causative mutations of diverse genetic diseases and comparing two sets of genome sequences, respectively.

Prevalence of Rare Genetic Variations and Their Implications in NGS-data Interpretation.

Next-generation sequencing (NGS) technology has improved enough to discover mutations associated with genetic diseases. Our study evaluated the feasibility of targeted NGS as a primary screening tool to detect causal variants and subsequently predict genetic diseases. We performed parallel computations on 3.7-megabase-targeted regions to detect disease-causing mutations in 103 participants consisting of 81 patients and 22 controls. Data analysis of the participants took about 6 hours using local databases and 200 nodes of a supercomputer. All variants in the selected genes led on average to 3.6 putative diseases for each patient while variants restricted to disease-causing genes identified the correct disease. Notably, only 12% of predicted causal variants were recorded as causal mutations in public databases: 88% had no or insufficient records. In this study, most genetic diseases were caused by rare mutations and public records were inadequate. Most rare variants, however, were not associated with genetic diseases. These data implied that novel, rare variants should not be ignored but interpreted in conjunction with additional clinical data. This step is needed so appropriate advice can be given to primary doctors and parents, thus fulfilling the purpose of this method as a primary screen for rare genetic diseases.

HLAscan: genotyping of the HLA region using next-generation sequencing data.

BACKGROUND: Several recent studies showed that next-generation sequencing (NGS)-based human leukocyte antigen (HLA) typing is a feasible and promising technique for variant calling of highly polymorphic regions. To date, however, no method with sufficient read depth has completely solved the allele phasing issue. In this study, we developed a new method (HLAscan) for HLA genotyping using NGS data. RESULTS: HLAscan performs alignment of reads to HLA sequences from the international ImMunoGeneTics project/human leukocyte antigen (IMGT/HLA) database. The distribution of aligned reads was used to calculate a score function to determine correctly phased alleles by progressively removing false-positive alleles. Comparative HLA typing tests using public datasets from the 1000 Genomes Project and the International HapMap Project demonstrated that HLAscan could perform HLA typing more accurately than previously reported NGS-based methods such as HLAreporter and PHLAT. In addition, the results of HLA-A, -B, and -DRB1 typing by HLAscan using data generated by NextGen were identical to those obtained using a Sanger sequencing-based method. We also applied HLAscan to a family dataset with various coverage depths generated on the Illumina HiSeq X-TEN platform. HLAscan identified allele types of HLA-A, -B, -C, -DQB1, and -DRB1 with 100% accuracy for sequences at ≥ 90× depth, and the overall accuracy was 96.9%. CONCLUSIONS: HLAscan, an alignment-based program that takes read distribution into account to determine true allele types, outperformed previously developed HLA typing tools. Therefore, HLAscan can be reliably applied for determination of HLA type across the whole-genome, exome, and target sequences.

Identification of somatic mutations using whole-exome sequencing in Korean patients with acute myeloid leukemia.

BACKGROUND: Acute myeloid leukemia (AML) is a biologically and clinically heterogeneous cancer of the bone marrow that is characterized by the rapid growth of abnormal myeloid cells. METHODS: We performed a mutational analysis to identify AML somatic mutations using the whole-exome sequencing data of 36 tumor-normal sample pairs from Korean patients with de novo AML. We explored the functional impact of the genes identified in the mutational analyses through an integrated Gene Ontology (GO) and pathway analysis. RESULTS: A total of 11 genes, including NEFH (p = 6.27 × 10-13 and q = 1.18 × 10-8) and TMPRSS13 (p = 1.40 × 10-10 and q = 1.32 × 10-6), also demonstrated q values less than 0.1 in 36 Korean AML patients. Five out of the 11 novel genes have previously been reported to be associated with other cancers. Two gene mutations, CEBPA (p = 5.22 × 10-5) and ATXN3 (p = 9.75 × 10-4), showed statistical significance exclusively in the M2 and M3 subtypes of the French-American-British classifications, respectively. A total of 501 genes harbored 478 missense, 22 nonsense, 93 frameshift indels, and/or three stop codon deletions and these gene mutations significantly enriched GO terms for signal transduction (GO:0007165, p = 1.77 × 10-3), plasma membrane (GO:0005886, p = 3.07 × 10-4), and scaffold protein binding (GO:0097110, p = 8.65 × 10-4). The mitogen-activated protein kinase (hsa04010, 7.67 × 10-4) was the most enriched Kyoto Encyclopedia of Genes and Genomes pathway. CONCLUSIONS: Morphological AML subtypes may in part reflect subtype specific patterns of genomic alterations. Following validation, future studies to evaluate the usefulness of these genes in genetic testing for the early diagnosis and prognostic prediction of AML patients would be worthwhile.

Genetic characterization of porcine epidemic diarrhea virus in Korea from 1998 to 2013.

The number of porcine epidemic diarrhea (PED) cases has increased over the past 20 years in Korea, with a major outbreak in 2013. A total of 27 Korean strains from 1998 to 2013 were analyzed (excluding the noncoding regions) and divided into two groups for comparison of the spike (S), ORF3, envelope (E), membrane (M), and nucleocapsid (N) genes with those of reference strains, vaccine strains, and previously identified strains based on phylogenetic analysis. Analysis of the selection patterns of PEDV isolated in Korea indicated positive selection of nine nonsynonymous sites in the S and N proteins and negative selection at 97 sites for all of the proteins. Interestingly, eight nonsynonymous mutations in S showed no significant pattern change over the 15-year period, and one of eight mutation sites was found only in IC05TK, GN05DJ, and KNU0802 in the epidemic years 2005 and 2008. These eight mutations were also present during the epidemic years in China. Furthermore, of the signs of positive selection in the S protein, the conservative substitutions were more frequent than radical substitutions in PEDVs, suggesting that the evolution of Korean strains has been slow. Serological cross-reactivity was detected between three field PEDVs and two vaccine strains, with different serum neutralization titers. In conclusion, although Korean PEDVs have been evolving slowly, their diverse antigenicity and genetics imply that multilateral efforts to prevent future PED outbreaks are required.

Novel COL9A3 mutation in a family diagnosed with multiple epiphyseal dysplasia: a case report.

BACKGROUND: Multiple epiphyseal dysplasia is a common skeletal dysplasia characterized by mild short stature, early-onset osteoarthritis mainly involving the hip and knee joints, and abnormally small and/or irregular epiphyses. Multiple epiphyseal dysplasia is clinically and genetically heterogeneous and six genes are associated with the phenotype of multiple epiphyseal dysplasia. CASE PRESENTATION: A 12-year-old Korean boy presented with intermittent knee pain. His height was 144.6 cm (20th percentile) and family history was notable for early-onset osteoarthritis in his father. The proband's x-rays revealed epiphyseal changes characteristic of multiple epiphyseal dysplasia associated with a collagen IX defect, with manifestations primarily restricted to the knees. Mutational analysis identified a novel c.104G>A substitution in exon 2 of COL9A3, resulting in p.Gly35Asp in the proband and his father. In silico analyses predicted the p.Gly35Asp amino acid change to be detelerious, and molecular dynamics simulation demonstrated a major structural change in the heterotrimeric collagen IX. CONCLUSION: So far, three COL9A3 mutations, have been reported. These three mutations are located at the splice donor or acceptor site of COL9A3 and cause skipping of exon 3, resulting in the deletion of 12 aminoacids in the COL3 domain of COL9A3. In contrast, the novel missense mutation identified in this two-generation family with multiple epiphyseal dysplasia is a missense mutation affecting the Gly residue of the Pro-Pro-Gly repeat sequence in the COL3 domain of collage IX, with accompanying major structural change of the collagen peptide.

Differential expression of MicroRNAs in patients with glioblastoma after concomitant chemoradiotherapy.

Glioblastoma multiforme (GBM) is the most aggressive primary brain tumor, and notorious for resistance to chemoradiotherapy. MicroRNAs (miRNAs) are significantly involved in the initiation and progression of numerous cancers; however, the role of miRNAs in recurrence of tumors remains unknown. Here we tried to identify novel miRNAs that are differentially expressed in recurrent GBM. Tissue samples were obtained from patients with primary and recurrent GBM treated with chemoradiotherapy, and the expression changes of miRNAs were measured by microarray. A total of 318 miRNAs were expressed in the GBM patients. The expression of 43 miRNAs were significantly altered at least 2-fold in primary and recurrent GBMs. Bioinformatic analysis revealed that the differentially expressed miRNAs and their putative target genes were mainly involved in cell death, cellular development, and cellular growth and proliferation, which are the key regulators for stem cells. Pathway analysis supported that the miRNAs may regulate signaling associated with induction and maintenance of cancer and stem cell, such as p53, ErbB1, Notch, Wnt, and TGF-ß signaling pathways. These data suggest that, in recurrent GBM, growth factor and anti-apoptotic signalings for cancer cell growth and proliferation are regulated by miRNAs. Our findings will aid future research in understanding the pathophysiology of recurrent GBM and identifying diagnostic markers and/or therapeutic targets for recurrence of GBM.

Proteomic and bioinformatic analysis of membrane proteome in type 2 diabetic mouse liver.

Type 2 diabetes mellitus (T2DM) is the most prevalent and serious metabolic disease affecting people worldwide. T2DM results from insulin resistance of the liver, muscle, and adipose tissue. In this study, we used proteomic and bioinformatic methodologies to identify novel hepatic membrane proteins that are related to the development of hepatic insulin resistance, steatosis, and T2DM. Using FT-ICR MS, we identified 95 significantly differentially expressed proteins in the membrane fraction of normal and T2DM db/db mouse liver. These proteins are primarily involved in energy metabolism pathways, molecular transport, and cellular signaling, and many of them have not previously been reported in diabetic studies. Bioinformatic analysis revealed that 16 proteins may be related to the regulation of insulin signaling in the liver. In addition, six proteins are associated with energy stress-induced, nine proteins with inflammatory stress-induced, and 14 proteins with endoplasmic reticulum stress-induced hepatic insulin resistance. Moreover, we identified 19 proteins that may regulate hepatic insulin resistance in a c-Jun amino-terminal kinase-dependent manner. In addition, three proteins, 14-3-3 protein beta (YWHAB), Slc2a4 (GLUT4), and Dlg4 (PSD-95), are discovered by comprehensive bioinformatic analysis, which have correlations with several proteins identified by proteomics approach. The newly identified proteins in T2DM should provide additional insight into the development and pathophysiology of hepatic steatosis and insulin resistance, and they may serve as useful diagnostic markers and/or therapeutic targets for these diseases.

Gene flow between the Korean peninsula and its neighboring countries.

SNP markers provide the primary data for population structure analysis. In this study, we employed whole-genome autosomal SNPs as a marker set (54,836 SNP markers) and tested their possible effects on genetic ancestry using 320 subjects covering 24 regional groups including Northern (=16) and Southern (=3) Asians, Amerindians (=1), and four HapMap populations (YRI, CEU, JPT, and CHB). Additionally, we evaluated the effectiveness and robustness of 50K autosomal SNPs with various clustering methods, along with their dependencies on recombination hotspots (RH), linkage disequilibrium (LD), missing calls and regional specific markers. The RH- and LD-free multi-dimensional scaling (MDS) method showed a broad picture of human migration from Africa to North-East Asia on our genome map, supporting results from previous haploid DNA studies. Of the Asian groups, the East Asian group showed greater differentiation than the Northern and Southern Asian groups with respect to Fst statistics. By extension, the analysis of monomorphic markers implied that nine out of ten historical regions in South Korea, and Tokyo in Japan, showed signs of genetic drift caused by the later settlement of East Asia (South Korea, Japan and China), while Gyeongju in South East Korea showed signs of the earliest settlement in East Asia. In the genome map, the gene flow to the Korean Peninsula from its neighboring countries indicated that some genetic signals from Northern populations such as the Siberians and Mongolians still remain in the South East and West regions, while few signals remain from the early Southern lineages.

Mapping human genetic diversity in Asia.

Asia harbors substantial cultural and linguistic diversity, but the geographic structure of genetic variation across the continent remains enigmatic. Here we report a large-scale survey of autosomal variation from a broad geographic sample of Asian human populations. Our results show that genetic ancestry is strongly correlated with linguistic affiliations as well as geography. Most populations show relatedness within ethnic/linguistic groups, despite prevalent gene flow among populations. More than 90% of East Asian (EA) haplotypes could be found in either Southeast Asian (SEA) or Central-South Asian (CSA) populations and show clinal structure with haplotype diversity decreasing from south to north. Furthermore, 50% of EA haplotypes were found in SEA only and 5% were found in CSA only, indicating that SEA was a major geographic source of EA populations.

Planning the human variome project: the Spain report.

The remarkable progress in characterizing the human genome sequence, exemplified by the Human Genome Project and the HapMap Consortium, has led to the perception that knowledge and the tools (e.g., microarrays) are sufficient for many if not most biomedical research efforts. A large amount of data from diverse studies proves this perception inaccurate at best, and at worst, an impediment for further efforts to characterize the variation in the human genome. Because variation in genotype and environment are the fundamental basis to understand phenotypic variability and heritability at the population level, identifying the range of human genetic variation is crucial to the development of personalized nutrition and medicine. The Human Variome Project (HVP; http://www.humanvariomeproject.org/) was proposed initially to systematically collect mutations that cause human disease and create a cyber infrastructure to link locus specific databases (LSDB). We report here the discussions and recommendations from the 2008 HVP planning meeting held in San Feliu de Guixols, Spain, in May 2008.

Single nucleotide polymorphisms in bone turnover-related genes in Koreans: ethnic differences in linkage disequilibrium and haplotype.

BACKGROUND: Osteoporosis is defined as the loss of bone mineral density that leads to bone fragility with aging. Population-based case-control studies have identified polymorphisms in many candidate genes that have been associated with bone mass maintenance or osteoporotic fracture. To investigate single nucleotide polymorphisms (SNPs) that are associated with osteoporosis, we examined the genetic variation among Koreans by analyzing 81 genes according to their function in bone formation and resorption during bone remodeling. METHODS: We resequenced all the exons, splice junctions and promoter regions of candidate osteoporosis genes using 24 unrelated Korean individuals. Using the common SNPs from our study and the HapMap database, a statistical analysis of deviation in heterozygosity depicted. RESULTS: We identified 942 variants, including 888 SNPs, 43 insertion/deletion polymorphisms, and 11 microsatellite markers. Of the SNPs, 557 (63%) had been previously identified and 331 (37%) were newly discovered in the Korean population. When compared SNPs in the Korean population with those in HapMap database, 1% (or less) of SNPs in the Japanese and Chinese subpopulations and 20% of those in Caucasian and African subpopulations were significantly differentiated from the Hardy-Weinberg expectations. In addition, an analysis of the genetic diversity showed that there were no significant differences among Korean, Han Chinese and Japanese populations, but African and Caucasian populations were significantly differentiated in selected genes. Nevertheless, in the detailed analysis of genetic properties, the LD and Haplotype block patterns among the five sub-populations were substantially different from one another. CONCLUSION: Through the resequencing of 81 osteoporosis candidate genes, 118 unknown SNPs with a minor allele frequency (MAF) > 0.05 were discovered in the Korean population. In addition, using the common SNPs between our study and HapMap, an analysis of genetic diversity and deviation in heterozygosity was performed and the polymorphisms of the above genes among the five populations were substantially differentiated from one another. Further studies of osteoporosis could utilize the polymorphisms identified in our data since they may have important implications for the selection of highly informative SNPs for future association studies.

Gene-gene interaction between IL-13 and IL-13Ralpha1 is associated with total IgE in Korean children with atopic asthma.

Interleukin (IL)-13, which is essential for IgE synthesis, mediates its effects by binding with a receptor composed of IL-4Ralpha and IL-13Ralpha1. We investigated the effects of IL-13 and IL-13Ralpha1 polymorphisms in Korean children with asthma, and whether these have been associated with IgE production. We enrolled 358 atopic asthmatic, 111 non-atopic asthmatic, and 146 non-atopic healthy children. IL-13 and IL-13Ralpha1 genotypes were identified using the PCR-RFLP method. There was an association between the asthma susceptibility and homozygosity for risk allele of IL-13 G+2044A. In children with atopic asthma, risk alleles in IL-13 (A-1512C and C-1112T) and IL-13Ralpha1 (A+1398G) showed increased total IgE (P=0.012, 0.015 and 0.017, respectively). Three-loci haplotype analysis for IL-13 showed that the haplotype composed of -1512C, -1112T and +2044A was associated with higher total IgE than other tested haplotypes in children with atopic asthma (P=0.003). The gene-gene interaction between risk alleles of each IL-13 promoter polymorphism and IL-13Ralpha1 polymorphism was associated with higher total IgE in children with atopic asthma (P=0.002, 0.010). These findings indicate that the IL-13 G+2044A is associated with asthma development and the IL-13 and IL-13Ralpha1 polymorphisms may interact to enhance IgE production.