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Search Results: 1 - 10 of 444 matches for " Naoyuki Kamatani "
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ParaHaplo 2.0: a program package for haplotype-estimation and haplotype-based whole-genome association study using parallel computing
Kazuharu Misawa, Naoyuki Kamatani
Source Code for Biology and Medicine , 2010, DOI: 10.1186/1751-0473-5-5
Abstract: We developed a program package for parallel computation of haplotype estimation. Our program package, ParaHaplo 2.0, is intended for use in workstation clusters using the Intel Message Passing Interface (MPI). We compared the performance of our algorithm to that of the regular permutation test on both Japanese in Tokyo, Japan and Han Chinese in Beijing, China of the HapMap dataset.Parallel version of ParaHaplo 2.0 can estimate haplotypes 100 times faster than a non-parallel version of the ParaHaplo.ParaHaplo 2.0 is an invaluable tool for conducting haplotype-based genome-wide association studies (GWAS). The need for fast haplotype estimation using parallel computing will become increasingly important as the data sizes of such projects continue to increase. The executable binaries and program sources of ParaHaplo are available at the following address: http://en.sourceforge.jp/projects/parallelgwas/releases/ webciteRecent advances in various high-throughput genotyping technologies have allowed us to test allele frequency differences between case and control populations on a genome-wide scale [1]. Genome-wide association studies (GWAS) are used to compare the frequency of alleles or genotypes of a particular variant between cases and controls for a particular disease across a given genome [2-4]. More than a million single-nucleotide polymorphisms (SNPs) are analyzed in SNP-based GWAS. One difficulty faced when conducting SNP-based GWAS is performing corrections for multiple comparisons. Under the assumption that all SNPs are independent, a Bonferroni correction for a P value is usually used to account for multiple tests. When SNP loci are in linkage disequilibrium, Bonferroni corrections are known to be too conservative [5]. As a result, SNP-based GWAS may exclude the truly significant SNPs from analysis [6].To cope with problems related to multiple comparisons in GWAS, haplotype-based algorithms were developed to correct for multiple comparisons at multiple SNP loci
ParaHaplo: A program package for haplotype-based whole-genome association study using parallel computing
Kazuharu Misawa, Naoyuki Kamatani
Source Code for Biology and Medicine , 2009, DOI: 10.1186/1751-0473-4-7
Abstract: We developed a set of computer programs for the parallel computation of accurate P-values in haplotype-based GWAS. Our program, ParaHaplo, is intended for workstation clusters using the Intel Message Passing Interface (MPI). We compared the performance of our algorithm to that of the regular permutation test on JPT and CHB of HapMap.ParaHaplo can detect smaller differences between 2 populations than SNP-based GWAS. We also found that parallel-computing techniques made ParaHaplo 100-fold faster than a non-parallel version of the program.ParaHaplo is a useful tool in conducting haplotype-based GWAS. Since the data sizes of such projects continue to increase, the use of fast computations with parallel computing--such as that used in ParaHaplo--will become increasingly important. The executable binaries and program sources of ParaHaplo are available at the following address: http://sourceforge.jp/projects/parallelgwas/?_sl=1 webciteRecent advances in high-throughput genotyping technologies have allowed us to test allele frequency differences between case and control populations on a genome-wide scale [1]. Genome-wide association studies (GWAS) are used to compare the frequency of alleles or genotypes of a particular variant between disease cases and controls, across a given genome. A common approach is to test for differences in the allele frequencies of every single-nucleotide polymorphism (SNP) between the case and the control populations, by using the chi-square test [2-4]. The chi-square test uses the Pearson score, which increases as the difference in allele frequency between 2 populations increase. The chi-square test evaluates the Pearson score by way of the chi-square distribution.One crucial problem in conducting SNP-based GWAS is performing corrections for multiple comparisons. A Bonferroni correction for a P-value is usually used to account for multiple testing under the assumption that all SNPs are independent. When SNP loci are in linkage disequilibrium, Bo
ParaHaplo 3.0: A program package for imputation and a haplotype-based whole-genome association study using hybrid parallel computing
Kazuharu Misawa, Naoyuki Kamatani
Source Code for Biology and Medicine , 2011, DOI: 10.1186/1751-0473-6-10
Abstract: We developed a program package for parallel computation of genotype imputation and haplotype reconstruction. Our program package, ParaHaplo 3.0, is intended for use in workstation clusters using the Intel Message Passing Interface. We compared the performance of ParaHaplo 3.0 on the Japanese in Tokyo, Japan and Han Chinese in Beijing, and Chinese in the HapMap dataset. A parallel version of ParaHaplo 3.0 can conduct genotype imputation 20 times faster than a non-parallel version of ParaHaplo.ParaHaplo 3.0 is an invaluable tool for conducting haplotype-based GWASs. The need for faster genotype imputation and haplotype reconstruction using parallel computing will become increasingly important as the data sizes of such projects continue to increase. ParaHaplo executable binaries and program sources are available at http://en.sourceforge.jp/projects/parallelgwas/releases/ webcite.Recent advances in various high-throughput genotyping technologies have allowed us to test allelic frequency differences between case and control populations on a genome-wide scale [1]. Genome-wide association studies (GWASs) are used to compare the frequency of alleles or genotypes of a particular variant between cases and controls for a particular disease across a given genome [2-4]. More than a million single nucleotide polymorphisms (SNPs) are analyzed in SNP-based GWASs and haplotype-based GWASs [5,6].By modeling the patterns of linkage disequilibrium in a reference panel, genotypes not directly measured in the study samples can be imputed [7]. SNP genotype imputation has been proposed as a powerful means to include genetic markers into large-scale disease association studies without the need to actually genotype them [8,9]To quickly conduct GWASs, we developed a software package for the parallel computation of genotype imputation and haplotype reconstruction called ParaHaplo 3.0. ParaHaplo 3.0 contains all of the functions of ParaHaplo 1.0 [5] and ParaHaplo 2.0 [6], plus it can conduct ge
The Textile Plot: A New Linkage Disequilibrium Display of Multiple-Single Nucleotide Polymorphism Genotype Data
Natsuhiko Kumasaka,Yusuke Nakamura,Naoyuki Kamatani
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0010207
Abstract: Linkage disequilibrium (LD) is a major concern in many genetic studies because of the markedly increased density of SNP (Single Nucleotide Polymorphism) genotype markers. This dramatic increase in the number of SNPs may cause problems in statistical analyses, such as by introducing multiple comparisons in hypothesis testing and colinearity in logistic regression models, because of the presence of complex LD structures. Inferences must be made about the underlying genetic variation through the LD structure before applying statistical models to the data. Therefore, we introduced the textile plot to provide a visualization of LD to improve the analysis of the genetic variation present in multiple-SNP genotype data. The plot can accentuate LD by displaying specific geometrical shapes, and allowing for the underlying haplotype structure to be inferred without any haplotype-phasing algorithms. Application of this technique to simulated and real data sets illustrated the potential usefulness of the textile plot as an aid to the interpretation of LD in multiple-SNP genotype data. The initial results of LD mapping and haplotype analyses of disease genes are encouraging, indicating that the textile plot may be useful in disease association studies.
The molecular mechanism of osteoclastogenesis in rheumatoid arthritis
Nobuyuki Udagawa, Shigeru Kotake, Naoyuki Kamatani, Naoyuki Takahashi, Tatsuo Suda
Arthritis Research & Therapy , 2002, DOI: 10.1186/ar431
Abstract: Bone-resorbing osteoclasts originate from hemopoietic cells probably of the colony-forming unit-megakaryocyte (CFU-M)-derived monocyte–macrophage family. Osteoclasts are large multinucleated giant cells that express tartrate-resistant acid phosphatase (TRAP) activity and calcitonin receptors, and they have the ability to form resorption pits on bone and dentine slices. The characteristics of osteoclasts thus differ from those of macrophage polykaryons.We have developed a mouse coculture system of hemopoietic cells and primary osteoblasts to investigate osteoclast formation in vitro[1-3]. In this coculture system, several systemic and local factors induced formation of TRAP-positive multinucleated cells, which satisfied most of the osteoclast criteria [4]. Subsequent experiments established that the target cells of osteotropic factors for inducing osteoclast formation in the coculture were osteoblasts/stromal cells but not osteoclast precursors. In the coculture system, cell-to-cell contact between osteoblastic cells and osteoclast progenitors was essential for inducing osteoclastogenesis.From these experimental findings, we proposed in 1992 that osteoblastic cells induce osteoclast differentiation factor as a membrane-associated factor in response to various osteotropic factors [4]. Six years later, we succeeded in the molecular cloning of osteoclast differentiation factor from a cDNA library of mouse stromal ST2 cells treated with bone-resorbing factors [5]. Osteoclast differentiation factor is a member of the tumor necrosis factor (TNF) ligand family, and was found to be identical to RANKL, TNF-related activation-induced cytokine and osteoprotegerin (OPG) ligand, which were independently identified by three other research groups [5-9]. The ad hoc Committee of the American Society of Bone and Mineral Research has recommended using RANKL as the standardized name [10].RANKL induced osteoclast differentiation from mouse hemopoietic cells and human peripheral blood mon
Replication of association of the D-repeat polymorphism in asporin with osteoarthristis
Shiro Ikegawa, Shingo Kawamura, Atsushi Takahashi, Takahiro Nakamura, Naoyuki Kamatani
Arthritis Research & Therapy , 2006, DOI: 10.1186/ar1992
Abstract: It is not surprising that an association of a gene with a disease is found in some populations but not in others. Such diversity has been established for many common complex diseases with several explanations [5]. In this particular case, one explanation is the difference in the inclusion criteria used to recruit study participants. Whereas we recruited symptomatic OA patients with supporting radiographic evidence, Rodriguez-Lopez and colleagues used joint replacement surgery as inclusion criteria (Table 1).Another explanation is ethnic diversity, which is apparent in the very different allelic frequencies between the Spanish and Japanese populations. We question the authors' generalization of the three European populations (Spanish, Greek and UK) as 'European Caucasian', given the diverse frequencies of asporin alleles in the three populations [1,3,4] (Table 2), as well as their history and geography. The Spanish population in particular is distinct from the others; for example, the frequency of the common allele, Asp13 (D13), in the Spanish control groups shows statistically significant differences (p = 0.00088 versus UK; p = 0.021 versus Greek). The allelic frequency in hip OA also is very different.However, it is notable that in studies of knee OA for all three European populations, the allelic frequency of D13 is decreased and that of D14 is increased in the case group – the same trend observed in our Japanese study (Table 2). In all four populations, the odds ratios exceed 1. Given that the deviation of the odds ratio is random, the probability for its occurrence by chance is (1/2)4 = 1/16, which is substantially low. If we combine data for all three European populations, the association becomes significant (p = 0.030; odds ratio 1.26, 95% confidence interval 1.02 to 1.56). We believe that this estimation is valid because the inclusion criteria are the same, provided that the ethnicity is consistent as the Spanish group itself proposed. If so, the association
Prediction model for knee osteoarthritis based on genetic and clinical information
Hiroshi Takahashi, Masahiro Nakajima, Kouichi Ozaki, Toshihiro Tanaka, Naoyuki Kamatani, Shiro Ikegawa
Arthritis Research & Therapy , 2010, DOI: 10.1186/ar3157
Abstract: We genotyped risk alleles of the three susceptibility genes, asporin (ASPN), growth differentiation factor 5 (GDF5), and double von Willebrand factor A domains (DVWA) for a total of 2,158 Japanese subjects (933 OA and 1,225 controls) and statistically analyzed their effects. After that, we constructed prediction models by using the logistic regression analysis.When the effects of each allele were assumed to be the same and multiplicative, each additional risk allele increased the odds ratio (OR) by a factor of 1.23 (95% confidence interval (CI), 1.12 to 1.34). Individuals with five or six risk alleles showed significantly higher susceptibility when compared with those with zero or one, with an OR of 2.67 (95% CI, 1.46 to 4.87; P = 0.0020). Statistical evaluation of the prediction power of models showed that a model using only genotyping data had poor predictability. We obtained a model with good predictability by incorporating clinical data, which was further improved by rigorous age adjustment.Our results showed that consideration of adjusted clinical information, as well as increases in the number of risk alleles to be integrated, is critical for OA prediction by using data from case-control studies. To the authors' knowledge, this is the first report of the OA-prediction model combining both genetic and clinical information.Osteoarthritis (OA) is the most common bone and joint disease and is characterized by progressive cartilage degeneration. OA is a polygenic disease caused by genetic and environmental factors [1]. Epidemiologic studies have suggested that genetic factors strongly affect the onset and development of OA [2]. Genetic association studies are now uncovering the genetic factors responsible for of OA, that is, its susceptibility genes. Candidate-gene approaches have identified several genes associated with OA, and genome-wide association studies have recently found several promising OA-susceptibility genes [1,3].Identification of OA-susceptibility ge
ITGAV polymorphism and disease susceptibility in a Japanese rheumatoid arthritis population
Noriko Iikuni, Shu Kobayashi, Katsunori Ikari, Taisuke Tomatsu, Masako Hara, Hisashi Yamanaka, Naoyuki Kamatani, Shigeki Momohara
Arthritis Research & Therapy , 2007, DOI: 10.1186/ar2303
Abstract: One feature of the pathophysiology of RA is the hyper-angiogenesis observed in the synovial tissue and, along with excess macrophages and T lymphocytes, αvβ3 ligands are also abundant in synovial fluid [2]. As a key player in angiogenesis [3], it has been suggested that ITGAV may be a RA susceptibility gene. The linkage study also supports this view because the 2q31 region containing ITGAV exhibited linkage in a dense genome scan [4].Although the European association study by Jacq and colleagues [1] indicated ITGAV to be a new minor RA susceptibility gene, a replication study conducted in a population of different ethnicity is helpful in exploring whether the association is caused by a common variance through various ethnic groups. We therefore undertook a large population-based study to investigate the association between ITGAV and RA in a Japanese population.DNA samples were obtained from 1,504 Japanese RA patients and 449 population control individuals [5]. Genotypes were determined using the TaqMan method, in accordance with the manufacturer's instructions (Applied Biosystems, Tokyo, Japan). Table 1 shows the genotype distributions and allelic frequencies of patients and control individuals. Unlike the European population, the rs3738919-C allele was more frequent in control individuals in our Japanese population, and no significant differences were observed in allele frequencies for Japanese RA patients and control individuals (0.908 and 0.922, respectively).There are several factors that must be accounted for when a study fails to corroborate a previously identified association. One of these is an ethnicity-specific effect. Ethnic differences can result in differences in allele frequencies, and the genetic background of the disease itself may vary between ethnic groups. Another issue that must be considered is that, usually, negative association studies of a target gene outside the HLA region lack sufficient power to detect the genetic effect because the diseas
IL-23 induces human osteoclastogenesis via IL-17 in vitro, and anti-IL-23 antibody attenuates collagen-induced arthritis in rats
Toru Yago, Yuki Nanke, Manabu Kawamoto, Takefumi Furuya, Tsuyoshi Kobashigawa, Naoyuki Kamatani, Shigeru Kotake
Arthritis Research & Therapy , 2007, DOI: 10.1186/ar2297
Abstract: Rheumatoid arthritis is a chronic inflammatory disease characterized by the destruction of articular cartilage and bone [1]. Our group and another have detected osteoclasts in synovial tissues [2] and eroded bone surfaces [3], suggesting that osteoclastic bone resorption is involved in the pathogenesis of rheumatoid arthritis (RA).Furthermore, levels of inflammatory cytokines such as TNF-α, IL-6, and IL-1 are elevated in synovial fluids of patients with RA [4,5], and the cytokines promote bone resorption by inducing the differentiation or activation of osteoclasts [2,6,7]. It is well known that attenuating the activity of inflammatory cytokines in patients with RA inhibits bone resorption and destruction.IL-23, which was recently identified as a heterodimeric, proinflammatory cytokine and new member of the IL-12 family [8], is secreted by antigen-presenting cells. IL-23 is composed of p19 and p40 subunits and shares a common p40 subunit with IL-12 [8]. IL-23 signals through the IL-23 receptor complex, which is composed of the IL-12 receptor β chain and the IL-23 receptor [9]. IL-23 was initially described as a cytokine able to induce the expression of IFN-γ in human CD45RO-positive (memory) T cells and to activate memory T cells to secrete inflammatory cytokines including IFN-γ and IL-17 [8,10]. Furthermore, it is reported that recombinant human (rh)IL-23 upregulates the production of IFN-γ, IL-17, and IL-10 in activated human na?ve T cells [11]. In models of T helper type 1 (Th1) differentiation of human T cells, it was initially proposed that IL-23 acts later than IL-12 and maintains Th1 commitment by its preferential action on memory T cells [12-14].In animal studies, it is reported that IL-23-deficient (IL-23 p19-/-) mice are resistant to experimental autoimmune encephalomyelitis (EAE), whereas IL-12 (p35)-deficient mice are still susceptible to inflammation [15]. Murphy and colleagues reported that mice with collagen-induced arthritis (CIA) and IL-23 deficiency
Genome Wide Association Study of Age at Menarche in the Japanese Population
Chizu Tanikawa, Yukinori Okada, Atsushi Takahashi, Katsutoshi Oda, Naoyuki Kamatani, Michiaki Kubo, Yusuke Nakamura, Koichi Matsuda
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0063821
Abstract: Age at menarche (AAM) is a complex trait involving both genetic and environmental factors. To identify the genetic factors associated with AAM, we conducted a large-scale meta-analysis of genome-wide association studies using more than 15,000 Japanese female samples. Here, we identified an association between SNP (single nucleotide polymorphism) rs364663 at the LIN28B locus and AAM, with a P-value of 5.49×10?7 and an effect size of 0.089 (year). We also evaluated 33 SNPs that were previously reported to be associated with AAM in women of European ancestry. Among them, two SNPs rs4452860 and rs7028916 in TMEM38B indicated significant association with AAM in the same directions as reported in previous studies (P = 0.0013 with an effect size of 0.051) even after Bonferroni correction for the 33 SNPs. In addition, six loci in or near CCDC85A, LOC100421670, CA10, ZNF483, ARNTL, and RXRG exhibited suggestive association with AAM (P<0.05). Our findings elucidated the impact of genetic variations on AAM in the Japanese population.
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