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Find video protocols related to scientific articles indexed in Pubmed.
RADB: a database of rheumatoid arthritis-related polymorphisms.
Database (Oxford)
PUBLISHED: 09-15-2014
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Rheumatoid arthritis (RA) is an autoimmune disease that has a complex genetic basis. Therefore, it is important to explore the genetic background of RA. The extensive recent application of polymorphic genetic markers, especially single nucleotide polymorphisms, has presented us with a large quantity of genetic data. In this study, we developed the Database of Rheumatoid Arthritis-related Polymorphisms (RADB), to integrate all the RA-related genetic polymorphisms and provide a useful resource for researchers. We manually extracted the RA-related polymorphisms from 686 published reports, including RA susceptibility loci, polymorphisms associated with particular clinical features of RA, polymorphisms associated with drug response in RA and polymorphisms associated with a higher risk of cardiovascular disease in RA. Currently, RADB V1.0 contains 3235 polymorphisms that are associated with 636 genes and refer to 68 countries. The detailed information extracted from the literature includes basic information about the articles (e.g., PubMed ID, title and abstract), population information (e.g., country, geographic area and sample size) and polymorphism information (e.g., polymorphism name, gene, genotype, odds ratio and 95% confidence interval, P-value and risk allele). Meanwhile, useful annotations, such as hyperlinks to dbSNP, GenBank, UCSC, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway, are included. In addition, a tool for meta-analysis was developed to summarize the results of multiple studies. The database is freely available at http://www.bioapp.org/RADB. Database URL: http://www.bioapp.org/RADB.
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CD33 rs3865444 Polymorphism Contributes to Alzheimer's Disease Susceptibility in Chinese, European, and North American Populations.
Mol. Neurobiol.
PUBLISHED: 09-04-2014
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The CD33 rs3865444 polymorphism was first identified to be associated with Alzheimer's disease (AD) in European population. However, the following studies reported weak or no significant association in Chinese, Japanese, Korean, American, and Canadian populations. We think that these negative results may have been caused by either relatively small sample sizes compared with those used for the previous GWAS in European ancestry or the genetic heterogeneity of the rs3865444 polymorphism in different populations. Here, we reevaluated this association using the relatively large-scale samples from previous 27 studies (N?=?86,759; 31,106 cases and 55,653 controls) by searching the PubMed, AlzGene, and Google Scholar databases. We identified significant heterogeneity and observed no significant association between the rs3865444 polymorphism and AD in pooled populations (P?=?0.264, odds ratio (OR)?=?0.97, 95 % confidence interval (CI) 0.93-1.02). In subgroup analysis, we identified significant heterogeneity only in East Asian population and observed no significant association between the rs3865444 polymorphism and AD. We further identified significant heterogeneity and observed significant association between the rs3865444 polymorphism and AD in Chinese population. We identified no significant heterogeneity and significant association in North American and European populations. Collectively, our analysis shows that the CD33 rs3865444 polymorphism is associated with AD susceptibility in Chinese, European, and North American populations. We believe that our findings will be very useful for future genetic studies on AD.
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Pathway analysis of genome-wide association study and transcriptome data highlights new biological pathways in colorectal cancer.
Mol. Genet. Genomics
PUBLISHED: 08-30-2014
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Colorectal cancer (CRC) is a common malignancy that meets the definition of a complex disease. Genome-wide association study (GWAS) has identified several loci of weak predictive value in CRC, however, these do not fully explain the occurrence risk. Recently, gene set analysis has allowed enhanced interpretation of GWAS data in CRC, identifying a number of metabolic pathways as important for disease pathogenesis. Whether there are other important pathways involved in CRC, however, remains unclear. We present a systems analysis of KEGG pathways in CRC using (1) a human CRC GWAS dataset and (2) a human whole transcriptome CRC case-control expression dataset. Analysis of the GWAS dataset revealed significantly enriched KEGG pathways related to metabolism, immune system and diseases, cellular processes, environmental information processing, genetic information processing, and neurodegenerative diseases. Altered gene expression was confirmed in these pathways using the transcriptome dataset. Taken together, these findings not only confirm previous work in this area, but also highlight new biological pathways whose deregulation is critical for CRC. These results contribute to our understanding of disease-causing mechanisms and will prove useful for future genetic and functional studies in CRC.
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Synergistic transcriptional and post-transcriptional regulation of ESC characteristics by core pluripotency transcription factors in protein-protein interaction networks.
PLoS ONE
PUBLISHED: 08-29-2014
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The molecular mechanism that maintains the pluripotency of embryonic stem cells (ESCs) is not well understood but may be reflected in complex biological networks. However, there have been few studies on the effects of transcriptional and post-transcriptional regulation during the development of ESCs from the perspective of computational systems biology. In this study, we analyzed the topological properties of the "core" pluripotency transcription factors (TFs) OCT4, SOX2 and NANOG in protein-protein interaction networks (PPINs). Further, we identified synergistic interactions between these TFs and microRNAs (miRNAs) in PPINs during ESC development. Results show that there were significant differences in centrality characters between TF-targets and non-TF-targets in PPINs. We also found that there was consistent regulation of multiple "core" pluripotency TFs. Based on the analysis of shortest path length, we found that the module properties were not only within the targets regulated by common or multiple "core" pluripotency TFs but also between the groups of targets regulated by different TFs. Finally, we identified synergistic regulation of these TFs and miRNAs. In summary, the synergistic effects of "core" pluripotency TFs and miRNAs were analyzed using computational methods in both human and mouse PPINs.
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Identifying the Association Between Alzheimer's Disease and Parkinson's Disease Using Genome-Wide Association Studies and Protein-Protein Interaction Network.
Mol. Neurobiol.
PUBLISHED: 08-18-2014
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Alzheimer's disease (AD) and Parkinson's disease (PD) are the first and second most common neurodegenerative diseases in the elderly. Shared clinical and pathological features have been reported. Recent large-scale genome-wide association studies (GWAS) have been conducted and reported a number of AD and PD variants. Until now, the underlying genetic mechanisms for all these newly identified PD variants as well as the association between AD and PD are still unclear exactly. We think that PD variants may contribute to AD and PD by influence on brain gene expression. Here, we conducted a systems analysis using (1) AD and PD variants (P?
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Network-based analysis of genotype-phenotype correlations between different inheritance modes.
Bioinformatics
PUBLISHED: 07-30-2014
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Recent studies on human disease have revealed that aberrant interaction between proteins probably underlies a substantial number of human genetic diseases. This suggests a need to investigate disease inheritance mode using interaction, and based on which to refresh our conceptual understanding of a series of properties regarding inheritance mode of human disease.
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Integrating Genome-Wide Association Study and Brain Expression Data Highlights Cell Adhesion Molecules and Purine Metabolism in Alzheimer's Disease.
Mol. Neurobiol.
PUBLISHED: 06-29-2014
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Alzheimer's disease (AD) is the most common neurodegenerative disease in the elderly. Recently, genome-wide association studies (GWAS) have been used to investigate AD pathogenesis. However, a large proportion of AD heritability has yet to be explained. We previously identified the cell adhesion molecule (CAM) pathway as a consistent signal in two AD GWAS. However, it is unclear whether CAM is present in the Genetic and Environmental Risk for Alzheimer's Disease Consortium (GERAD) GWAS and brain expression GWAS. Meanwhile, we think integrating AD GWAS and AD brain expression datasets may provide complementary information to identify important pathways involved in AD. Here, we conducted a systems analysis using (1) KEGG pathways, (2) large-scale AD GWAS from GERAD (n?=?11,789), (3) two brain expression GWAS datasets (n?=?399) from the AD cerebellum and temporal cortex, and (4) previous results from pathway analysis of AD GWAS. Our results indicate that (1) CAM is a consistent signal in five AD GWAS; (2) CAM is the most significant signal in AD; (3) we confirmed previous AD risk pathways related to immune system and diseases, and cardiovascular disease, etc.; and (4) we highlighted the purine metabolism pathway in AD for the first time. We believe that our results may advance our understanding of AD mechanisms and will be very informative for future genetic studies in AD.
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Analyzing 54,936 Samples Supports the Association Between CD2AP rs9349407 Polymorphism and Alzheimer's Disease Susceptibility.
Mol. Neurobiol.
PUBLISHED: 06-19-2014
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The CD2-associated protein (CD2AP) rs9349407 polymorphism was first identified to be significantly associated with Alzheimer's disease (AD) in European ancestry by genome-wide association studies (GWAS). However, the following studies reported no association in Chinese, Japanese, African-American, Canadian, and European populations. We think that these negative results may have been caused by either relatively small sample sizes compared with those used for the previous GWAS in European ancestry or the genetic heterogeneity of the rs9349407 polymorphism in different populations. Here, we reevaluated this association using the relatively large-scale samples from 15 previous studies (N?=?54,936; 23,777 cases and 31,159 controls) by searching the PubMed, AlzGene, and Google Scholar databases. Using an additive genetic model, we did not identify a significant heterogeneity among the 15 studies. Using meta-analysis, we observed a significant association between the rs9349407 polymorphism and AD with P?=?8.78E-07, odds ratio (OR)?=?1.08, 95 % confidence interval (CI) 1.05-1.12. To our knowledge, this is the first meta-analysis to investigate the association between rs9349407 polymorphism and AD in East Asian, American, Canadian, and European populations. Our analysis further supports previous findings that the CD2AP rs9349407 polymorphism contributes to AD susceptibility. We believe that our findings will be very useful for future genetic studies on AD.
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System analysis of LWDH related genes based on text mining in biological networks.
Biomed Res Int
PUBLISHED: 05-15-2014
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Liuwei-dihuang (LWDH) is widely used in traditional Chinese medicine (TCM), but its molecular mechanism about gene interactions is unclear. LWDH genes were extracted from the existing literatures based on text mining technology. To simulate the complex molecular interactions that occur in the whole body, protein-protein interaction networks (PPINs) were constructed and the topological properties of LWDH genes were analyzed. LWDH genes have higher centrality properties and may play important roles in the complex biological network environment. It was also found that the distances within LWDH genes are smaller than expected, which means that the communication of LWDH genes during the biological process is rapid and effectual. At last, a comprehensive network of LWDH genes, including the related drugs and regulatory pathways at both the transcriptional and posttranscriptional levels, was constructed and analyzed. The biological network analysis strategy used in this study may be helpful for the understanding of molecular mechanism of TCM.
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An Updated Analysis with 85,939 Samples Confirms the Association Between CR1 rs6656401 Polymorphism and Alzheimer's Disease.
Mol. Neurobiol.
PUBLISHED: 04-18-2014
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The complement receptor 1 (CR1) rs6656401 polymorphism was first identified to be associated with Alzheimer's disease (AD) in European ancestry. However, the following studies reported weak or no significant association in Chinese, Japanese, Korean, African-American, Polish, and Canadian populations. We think that these negative results may have been caused by either relatively small sample sizes compared with those used for the previous genome-wide association studies (GWAS) in European ancestry or the genetic heterogeneity of the rs6656401 polymorphism in different populations. Here, we reevaluated this association using the relatively large-scale samples from previous 24 studies (N?=?85,939, 30,100 cases and 55,839 controls) by searching the PubMed, AlzGene, and Google Scholar databases. Using additive model, we did not identify significant heterogeneity among the 24 studies. We observed significant association between the rs6656401 polymorphism and AD in pooled populations (P?=?1.82E-26, odds ratio (OR)?=?1.18, 95 % confidence interval (CI) 1.15-1.22). In subgroup analysis, we identified significant results in East Asian population with P?=?5.00E-04, OR?=?1.31, 95 % CI 1.13-1.52. To our knowledge, this is the first meta-analysis to investigate the association between rs6656401 polymorphism and AD in East Asian, African-American, Canadian, and European populations. Our analysis further supports previous findings that the CR1 rs6656401 polymorphism contributes to AD susceptibility. We believe that our findings will be very useful for future genetic studies on AD.
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CLU rs2279590 polymorphism contributes to Alzheimer's disease susceptibility in Caucasian and Asian populations.
J Neural Transm
PUBLISHED: 03-14-2014
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It is reported that CLU rs2279590 polymorphism is significantly associated with Alzheimer's disease (AD) in European ancestry. Recent studies investigated rs2279590 polymorphism in Asian population (Chinese, Japanese and Korean). Four studies showed negative association and two studies showed weak association between rs2279590 and AD. We believe that the weak association or no association may be caused by the relatively small sample size in Asian population. Here, we reinvestigated the association in Asian population. Meanwhile, to investigate the genetic heterogeneity of the rs2279590 polymorphism in Asian and Caucasian populations, we searched the PubMed and AlzGene databases and selected 11 independent studies (6 studies in Asian population and 5 studies in Caucasian population) including 20,655 individuals (8,605 cases and 12,050 controls) for meta-analysis. Our results showed significant association between rs2279590 polymorphism and AD in Asian population with P = 2.00E-04 and P = 2.00E-04 using additive and recessive models, respectively. We observed no significant heterogeneity between Asian and Caucasian populations. We believe that our results may be helpful to understand the mechanisms of CLU in AD pathogenesis and will be useful for future genetic studies in AD.
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Analyzing Large-Scale Samples Confirms the Association Between the ABCA7 rs3764650 Polymorphism and Alzheimer's Disease Susceptibility.
Mol. Neurobiol.
PUBLISHED: 02-28-2014
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Large-scale genome-wide association studies (GWAS) have revealed that the ABCA7 rs3764650 polymorphism (or its proxies, namely rs115550680, rs3752246, and rs4147929) is associated with Alzheimer's disease (AD) susceptibility in individuals of Caucasian ancestry. The following studies have investigated this finding in Chinese (N?=?633 and N?=?1,224), Japanese (N?=?1,735), Korean (N?=?844), African American (N?=?5,896), and Canadian (N?=?1,104) populations. However, these studies reported a weak or negligible association. We hypothesized that these negative results may have been caused by either relatively small sample sizes compared with those used for the previous GWAS in individuals of Caucasian ancestry or the genetic heterogeneity of the rs3764650 polymorphism (or its proxies) in different populations. Here, we reevaluated the association between rs3764650 and AD using large-scale samples from 18 previous studies (N?=?79,381-30,590 cases and 48,791 controls) by searching PubMed, AlzGene, and Google Scholar databases. Using allele, dominant, recessive, and additive models, we did not identify significant heterogeneity among the 18 studies. We observed a significant association between rs3764650 and AD using the allele (P?=?1.76E?-?26, odds ratio (OR)?=?1.21, 95 % confidence interval (CI) 1.17-1.26), dominant (P?=?4.00E?-?04, OR?=?1.17, 95 % CI 1.07-1.28), recessive (P?=?3.00E?-?03, OR?=?1.43, 95 % CI 1.13-1.81), and additive models (P?=?3.00E?-?03, OR?=?1.49, 95 % CI 1.16-1.91). Collectively, our analysis further supports previous findings that the ABCA7 rs3764650 polymorphism is associated with AD susceptibility. We believe that our findings will be very useful for future genetic studies on AD.
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Pathway Analysis of Two Amyotrophic Lateral Sclerosis GWAS Highlights Shared Genetic Signals with Alzheimer's Disease and Parkinson's Disease.
Mol. Neurobiol.
PUBLISHED: 02-06-2014
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Amyotrophic lateral sclerosis (ALS) is the third most common neurodegenerative disease after Alzheimer's disease (AD) and Parkinson's disease (PD). In order to unravel more genetic etiology of ALS, genome-wide association studies (GWAS) have been conducted. However, the newly identified ALS susceptibility loci exert only very small risk effects and cannot fully explain the underlying ALS genetic risk. A large proportion of the heritability of ALS is still to be explained. Recently, pathway analysis of GWAS has been used to investigate the mechanisms of AD and PD. We think that AD or PD risk pathways may also be involved in ALS. In order to confirm this view, we conducted a pathway analysis of two independent ALS GWAS. We identified multiple classifications of the Kyoto Encyclopedia of Genes and Genomes pathways related to metabolism, immune system and diseases, environmental information processing, genetic information processing, cellular processes, and nervous system and neurodegenerative diseases to be the consistent signals in the two ALS GWAS. On the single pathway level, we identified 12 shared pathways. We compared the findings from ALS GWAS with those of previous pathway analyses of AD and PD GWAS. The results further supported the involvement of AD and PD risk pathways in ALS. We believe that our results may advance the understanding of ALS mechanisms and will be very useful for future genetic studies.
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Prioritization of candidate genes for periodontitis using multiple computational tools.
J. Periodontol.
PUBLISHED: 01-30-2014
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Both genetic and environmental factors contribute to the development of periodontitis. Genetic studies identified a variety of candidate genes for periodontitis. The aim of the present study is to identify the most promising candidate genes for periodontitis using an integrative gene ranking method.
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Association between polymorphisms in the promoter region of interleukin-10 and susceptibility to inflammatory bowel disease.
Mol. Biol. Rep.
PUBLISHED: 01-10-2014
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The aim of this study was to assess the association of polymorphisms in the promoter region of the IL-10 gene with the risk of inflammatory bowel disease (IBD), including Crohn's disease (CD) and ulcerative colitis (UC). Fifteen studies (3,693 cases and 4,574 controls) were included in a meta-analysis of association between IL-10 -1082G/A, -819C/T and -592C/A polymorphisms, and IBD, CD and UC using allele contrast and the recessive, dominant, and additive models. Hardy-Weinberg equilibrium was confirmed for each study. Heterogeneity and study quality were investigated using stratification analyses and sensitivity analyses. Polymorphism -1082G/A showed significant association with CD, with odds ratios (ORs) for the GG + GA genotype and GG versus AA genotype of 1.278 (1.004-1.627) and 1.238 (1.027-1.492) in all subjects. Significant associations were found in the Caucasian subgroup using the allele contrast, dominant, and additive models. C-allele carriers of the -819C/T polymorphism were at increased risk of IBD (OR 1.093, 95% CI 1.004-1.190). Association with the -819C/T polymorphism was also found in Caucasians with CD (C vs. T: OR 1.104, 95% CI 1.010-1.206; CC + CT vs. TT: OR 1.328, 95% CI 1.006-1.754; CC vs. TT: OR 1.339, 95% CI 1.008-1.778), and with UC (CC vs. CT + TT: OR 1.188, 95% CI 1.019-1.385). No significant association was found between the -592C/A polymorphism and IBD, CD or UC. In conclusion, the meta-analysis demonstrated clear association between the IL-10 polymorphisms -1082G/A and -819C/T and the risk of IBD.
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MCPerm: a Monte Carlo permutation method for accurately correcting the multiple testing in a meta-analysis of genetic association studies.
PLoS ONE
PUBLISHED: 01-01-2014
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Traditional permutation (TradPerm) tests are usually considered the gold standard for multiple testing corrections. However, they can be difficult to complete for the meta-analyses of genetic association studies based on multiple single nucleotide polymorphism loci as they depend on individual-level genotype and phenotype data to perform random shuffles, which are not easy to obtain. Most meta-analyses have therefore been performed using summary statistics from previously published studies. To carry out a permutation using only genotype counts without changing the size of the TradPerm P-value, we developed a Monte Carlo permutation (MCPerm) method. First, for each study included in the meta-analysis, we used a two-step hypergeometric distribution to generate a random number of genotypes in cases and controls. We then carried out a meta-analysis using these random genotype data. Finally, we obtained the corrected permutation P-value of the meta-analysis by repeating the entire process N times. We used five real datasets and five simulation datasets to evaluate the MCPerm method and our results showed the following: (1) MCPerm requires only the summary statistics of the genotype, without the need for individual-level data; (2) Genotype counts generated by our two-step hypergeometric distributions had the same distributions as genotype counts generated by shuffling; (3) MCPerm had almost exactly the same permutation P-values as TradPerm (r = 0.999; P<2.2e-16); (4) The calculation speed of MCPerm is much faster than that of TradPerm. In summary, MCPerm appears to be a viable alternative to TradPerm, and we have developed it as a freely available R package at CRAN: http://cran.r-project.org/web/packages/MCPerm/index.html.
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Cardiovascular disease contributes to Alzheimers disease: evidence from large-scale genome-wide association studies.
Neurobiol. Aging
PUBLISHED: 10-07-2013
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Alzheimers disease (AD) is the most common and complex neurodegenerative disease in the elderly individuals. Recently, genome-wide association studies (GWAS) have been used to investigate AD pathogenesis. These GWAS have yielded important new insights into the genetic mechanisms of AD. However, these newly identified AD susceptibility loci exert only very small risk effects and cannot fully explain the underlying AD genetic risk. We hypothesize that combining the findings from different AD GWAS may have greater power than genetic analysis alone. To identify new AD risk factors, we integrated findings from 3 previous large-scale AD GWAS (n = 14,138) using a gene-based meta-analysis and subsequently conducted a pathway analysis using the kyoto encyclopedia of genes and genomes and gene ontology databases. Interestingly, we not only confirmed previous findings, but also highlighted, for the first time, the involvement of cardiovascular disease-related pathways in AD. Our results provided the clues as to the link between these diseases using pathway analysis methods. We believe that these findings will be very useful for future genetic studies of AD.
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The CLU Gene rs11136000 Variant is Significantly Associated with Alzheimers Disease in Caucasian and Asian Populations.
Neuromolecular Med.
PUBLISHED: 03-06-2013
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Large-scale genomewide association studies have reported that the CLU rs11136000 polymorphism is significantly associated with Alzheimers disease (AD) in people of Caucasian ancestry. Recently, this association was investigated in Asian populations (Chinese, Japanese, and Korean). However, these studies reported either a weak association or no association between the rs11136000 polymorphism and AD. We believe that this discrepancy may be caused by the relatively small sample size of the previous studies and the genetic heterogeneity of the rs11136000 polymorphism in AD among different populations. For this study, we searched the PubMed and AlzGene databases. We selected 18 independent studies (6 studies of Asian populations and 12 of populations of Caucasian ancestry) that evaluated the association between the rs11136000 polymorphism and AD using a case-control experimental design. We evaluated the genetic heterogeneity of the rs11136000 polymorphism in Caucasian and Asian populations. We then investigated the rs11136000 polymorphism by a meta-analysis in Asian populations using allele, dominant, and recessive models. We identified a significant association between rs11136000 and AD with the allele model (P = 2.00 × 10(-4)) and the dominant model (P = 5.00 × 10(-3)). Meanwhile, a similar genetic risk of the rs11136000 polymorphism in AD was observed in Asian and Caucasian populations. Further meta-analysis in pooled Asian and Caucasian populations indicated a more significant association with the allele (P = 8.30 × 10(-24)), dominant (P = 4.46 × 10(-17)), and recessive (P = 3.92 × 10(-12)) models. Collectively, our findings from this meta-analysis indicate that the effect of the CLU rs11136000 polymorphism on AD risk in Asian cohorts (Chinese, Japanese, and Korean) is consistent with the protective effect observed in Caucasian AD cohorts.
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BIN1 gene rs744373 polymorphism contributes to Alzheimers disease in East Asian population.
Neurosci. Lett.
PUBLISHED: 01-29-2013
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Large-scale genome-wide association studies (GWAS) identified BIN1 gene rs744373 polymorphism to be significantly associated with Alzheimers disease (AD) in Caucasian ancestry. Recently, this polymorphism was also investigated in East Asian population. However, no study reported significant association. We consider that the failure to replicate significant association between rs744373 polymorphism and AD may be caused by the relatively small sample size. In this research, we evaluated this association using pooled samples from previous studies (n=4982, 1437 AD cases and 3545 controls). Two methods including pooled analysis and meta-analysis were used to investigate the association. Using the pooled analysis, we observed significant association between rs744373 polymorphism and AD by both genotype test (P=3.94E-03, 4.59E-03 and 1.04E-02) and allele test (P=1.12E-03, OR=1.16, 95% CI 1.06-1.28). Interestingly, the meta-analysis confirmed this association with P=8.00E-03 (OR=1.14, 95% CI 1.03-1.25) and P=2.00E-02 (OR=1.16, 95% CI 1.02-1.32). We also evaluated the effect of rs744373 polymorphism on AD risk in different ethnic backgrounds and found that rs744373 polymorphism contributed to AD with similar genetic risk in East Asian and Caucasian populations. To our knowledge, this is the first study to show significant association between rs744373 polymorphism and AD in East Asian population.
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PICALM gene rs3851179 polymorphism contributes to Alzheimers disease in an Asian population.
Neuromolecular Med.
PUBLISHED: 01-17-2013
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PICALM gene rs3851179 polymorphism was reported to an Alzheimers disease (AD) susceptibility locus in a Caucasian population. However, recent studies reported consistent and inconsistent results in an Asian population. Four studies indicated no association between rs3851179 and AD in a Chinese population and one study reported weak association in a Japanese population. We consider that the failure to replicate the significant association between rs3851179 and AD may be caused by at least two reasons. The first reason may be the genetic heterogeneity in AD among different populations, and the second may be the relatively small sample size compared with large-scale GWAS in Caucasian ancestry. In order to confirm this view, in this research, we first evaluated the genetic heterogeneity of rs3851179 polymorphism in Caucasian and Asian populations. We then investigated rs3851179 polymorphism in an Asian population by a pooled analysis method and a meta-analysis method. We did not observe significant genetic heterogeneity of rs3851179 in the Caucasian and Asian populations. Our results indicate that rs3851179 polymorphism is significantly associated with AD in the Asian population by both pooled analysis and meta-analysis methods. We believe that our findings will be very useful for future genetic studies in AD.
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Measles contributes to rheumatoid arthritis: evidence from pathway and network analyses of genome-wide association studies.
PLoS ONE
PUBLISHED: 01-01-2013
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Growing evidence from epidemiological studies indicates the association between rheumatoid arthritis (RA) and measles. However, the exact mechanism for this association is still unclear now. We consider that the strong association between both diseases may be caused by shared genetic pathways. We performed a pathway analysis of large-scale RA genome-wide association studies (GWAS) dataset with 5,539 cases and 20,169 controls of European descent. Meanwhile, we evaluated our findings using previously identified RA loci, protein-protein interaction network and previous results from pathway analysis of RA and other autoimmune diseases GWAS. We confirmed four pathways including Cytokine-cytokine receptor interaction, Jak-STAT signaling, T cell receptor signaling and Cell adhesion molecules. Meanwhile, we highlighted for the first time the involvement of Measles and Intestinal immune network for IgA production pathways in RA. Our results may explain the strong association between RA and measles, which may be caused by the shared genetic pathway. We believe that our results will be helpful for future genetic studies in RA pathogenesis and may significantly assist in the development of therapeutic strategies.
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HGPGD: the human gene population genetic difference database.
PLoS ONE
PUBLISHED: 01-01-2013
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Demographic events such as migration, and evolutionary events like mutation and recombination, have contributed to the genetic variations that are found in the human genome. During the evolution and differentiation of human populations, different functional genes and pathways (a group of genes that act together to perform specific biological tasks) would have displayed different degrees of genetic diversity or evolutionary conservatism. To query the genetic differences of functional genes or pathways in populations, we have developed the human gene population genetic difference (HGPGD) database. Currently, 11 common population genetic features, 18,158 single human genes, 220 KEGG (Kyoto Encyclopedia of Genes and Genomes) human pathways and 4,639 Gene Ontology (GO) categories (3,269 in biological process; 862 in molecular function; and 508 in cellular component) are available in the HGPGD database. The 11 population genetic features are related mainly to three aspects: allele frequency, linkage disequilibrium pattern, and transferability of tagSNPs. By entering a list of Gene IDs, KEGG pathway IDs or GO category IDs and selecting a population genetic feature, users can search the genetic differences between pairwise HapMap populations. We hope that, when the researchers carry out gene-based, KEGG pathway-based or GO category-based research, they can take full account of the genetic differences between populations. The HGPGD database (V1.0) is available at http://www.bioapp.org/hgpgd.
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Cell adhesion molecules contribute to Alzheimers disease: multiple pathway analyses of two genome-wide association studies.
J. Neurochem.
PUBLISHED: 11-17-2011
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Alzheimers disease (AD) is a kind of complex neurological disorder. The complex genetic architecture of AD makes genetic analysis difficult. Fortunately, a pathway-based method to study the existing genome-wide association studies datasets has been applied into AD. However, no shared Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway was reported. In this study, we performed multiple pathway analyses of French AD genome-wide association studies dataset (discovery dataset, n = 7360, 2032 cases and 5328 controls) and Pfizer dataset (validation dataset, n = 2220, 1034 cases and 1186 controls). First, we performed multiple pathway analyses by Hypergeometric test, improved gene set enrichment analysis (IGSEA) and Z-statistic test in KEGG. Using Hypergeometric test, we identified 54 and 25 significant pathways (p < 0.05) in discovery dataset and validation dataset, respectively. Using IGSEA method, we identified three significant pathways in both discovery and validation datasets, respectively. Using Z-statistic test, we identified 19 significant pathways in validation dataset. Among the significant pathways, cell adhesion molecules (CAM) pathway was identified to be the only consistent signal emerging across multiple analyses in KEGG. After permutation and multiple testing corrections, CAM pathway was significant with p = 2.40E-05 (Hypergeometric test) and p = 3.00E-03 (IGSEA) in discovery dataset. In validation dataset, CAM pathway was significant with p = 1.84E-06 (Hypergeometric test), p = 1.00E-02 (IGSEA) and p = 2.81E-03 (Z-statistic test). We replicated the association by multiple pathway analyses in Gene Ontology using Hypergeometric test (WebGestalt), modified Fishers exact test (DAVID) and Binomial test (PANTHER). Our findings provided further evidence on the association between CAM pathway and AD susceptibility, which would be helpful to study the genetic mechanisms of AD and may significantly assist in the development of therapeutic strategies.
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Identifying highly conserved and highly differentiated gene ontology categories in human populations.
PLoS ONE
PUBLISHED: 10-27-2011
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Detecting and interpreting certain system-level characteristics associated with human population genetic differences is a challenge for human geneticists. In this study, we conducted a population genetic study using the HapMap genotype data to identify certain special Gene Ontology (GO) categories associated with high/low genetic difference among 11 Hapmap populations. Initially, the genetic differences in each gene region among these populations were measured using allele frequency, linkage disequilibrium (LD) pattern, and transferability of tagSNPs. The associations between each GO term and these genetic differences were then identified. The results showed that cellular process, catalytic activity, binding, and some of their sub-terms were associated with high levels of genetic difference, and genes involved in these functional categories displayed, on average, high genetic diversity among different populations. By contrast, multicellular organismal processes, molecular transducer activity, and some of their sub-terms were associated with low levels of genetic difference. In particular, the neurological system process under the multicellular organismal process category had low levels of genetic difference; the neurological function also showed high evolutionary conservation between species in some previous studies. These results may provide a new insight into the understanding of human evolutionary history at the system-level.
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Assessing the patterns of linkage disequilibrium in genic regions of the human genome.
FEBS J.
PUBLISHED: 09-08-2011
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We used the genotyping data generated by the International HapMap Project to study the patterns of linkage disequilibrium (LD) in human genic regions. LD patterns for 11,998 genes from 11 HapMap populations were identified by analyzing the distribution of haplotype blocks. The genes were prioritized using LD levels. The results showed that there were significant differences in the degree of LD between genes. Genes with high or low LD (the upper and lower quartiles of the LD levels) fell into different Gene Ontology functional categories. The high LD genes clustered preferentially in the metabolic process, macromolecule localization and cell-cycle categories, whereas the low LD genes clustered in the developmental process, ion transport, and immune and regulation system categories. Furthermore, we subdivided the genic region into 3-UTR, 5-UTR and CDS (coding region), and compared the different LD patterns in these subregions. We found that the LD patterns in low LD genes had a more interspersed block structure compared with the high LD genes. This was especially true in the CDS and 5-UTR. The extent of LD was somewhat higher in 5-UTRs compared with 3-UTRs for both high and low LD genes. In addition, we assessed the overlap for the intragenic LD regions and found that the LD regions in high LD genes were more consistent among populations. Comprehensive information about the distribution of LD patterns in gene regions in populations may provide insights into the evolutionary history of humans and help in the selection of biomarkers for disease association studies.
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The expanded human disease network combining protein-protein interaction information.
Eur. J. Hum. Genet.
PUBLISHED: 03-09-2011
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The human disease network (HDN) has become a powerful tool for revealing disease-disease associations. Some studies have shown that genes that share similar or same disease phenotypes tend to encode proteins that interact with each other. Therefore, protein-protein interactions (PPIs) may help us to further understand the relationships between diseases with overlapping clinical phenotypes. In this study, we constructed the expanded HDN (eHDN) by combining disease gene information with PPI information, and analyzed its topological features and functional properties. We found that the network is hierarchical and, most diseases are connected to only a few diseases, whereas a small part of diseases are linked to many different diseases. Diseases in a specific disease class tend to cluster together, and genes associated with the same disease are functionally related. Comparing the eHDN with the original HDN (oHDN, constructed using disease gene information) revealed high consistency over all topological and functional properties. This, to some extent, indicates that our eHDN is reliable. In the eHDN, we found some new associations among diseases resulting from the shared genes interacting with disease genes. The new eHDN will provide a valuable reference for clinicians and medical researchers.
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Association between the IL7R T244I polymorphism and multiple sclerosis: a meta-analysis.
Mol. Biol. Rep.
PUBLISHED: 06-30-2010
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Previously published analyses of the association between the interleukin 7 receptor (IL7R) T244I polymorphism (rs6897932) and multiple sclerosis (MS) have yielded conflicting results. We performed a meta-analysis to assess whether the combined data showed this association, and to investigate its effect size. We analyzed 10 studies identified from PubMed (12,185 MS patients and 15,855 controls) and calculated the odds ratios (ORs) and 95% confidence intervals (CIs) for the C-allele, the C/C genotype (recessive effect) and the C/C + C/T (dominant effect) genotype. Heterogeneity within and between studies was observed: allele C: Q = 30.86, P = 0.002; genotype C/C: Q = 30.28, P = 0.003. Using a random-effects model, the C-allele and the C/C genotype were associated with MS (OR = 1.11, 95% CI = 1.04-1.19, P = 0.001 for the C-allele; OR = 1.15, 95% CI = 1.06-1.24, P = 0.0009 for the C/C genotype). The C/C + C/T genotype was also associated with MS using a fixed-effects model (OR = 1.15, 95% CI = 1.05-1.26, P = 0.003). There was no significant publication bias among the selected studies according to the funnel plot. We also performed the analysis on a European subgroup. This revealed an association between IL7R T244I and MS (P < 0.00001 for the C-allele and the C/C genotype; P = 0.0004 for the C/C + C/T genotype), no heterogeneity was observed (allele C: P = 0.07; genotype C/C: P = 0.10). In conclusion, the meta-analysis demonstrated that the IL7R T244I polymorphism was associated with susceptibility to MS.
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Predict potential drug targets from the ion channel proteins based on SVM.
J. Theor. Biol.
PUBLISHED: 08-06-2009
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The identification of molecular targets is a critical step in the drug discovery and development process. Ion channel proteins represent highly attractive drug targets implicated in a diverse range of disorders, in particular in the cardiovascular and central nervous systems. Due to the limits of experimental technique and low-throughput nature of patch-clamp electrophysiology, they remain a target class waiting to be exploited. In our study, we combined three types of protein features, primary sequence, secondary structure and subcellular localization to predict potential drug targets from ion channel proteins applying classical support vector machine (SVM) method. In addition, our prediction comprised two stages. In stage 1, we predicted ion channel target proteins based on whole-genome target protein characteristics. Firstly, we performed feature selection by Mann-Whitney U test, then made predictions to identify potential ion channel targets by SVM and designed a new evaluating indicator Q to prioritize results. In stage 2, we made a prediction based on known ion channel target protein characteristics. Genetic algorithm was used to select features and SVM was used to predict ion channel targets. Then, we integrated results of two stages, and found that five ion channel proteins appeared in both prediction results including CGMP-gated cation channel beta subunit and Gamma-aminobutyric acid receptor subunit alpha-5, etc., and four of which were relative to some nerve diseases. It suggests that these five proteins are potential targets for drug discovery and our prediction strategies are effective.
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Novel strategies to mine alcoholism-related haplotypes and genes by combining existing knowledge framework.
Sci. China, C, Life Sci.
PUBLISHED: 03-11-2009
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High-throughout single nucleotide polymorphism detection technology and the existing knowledge provide strong support for mining the disease-related haplotypes and genes. In this study, first, we apply four kinds of haplotype identification methods (Confidence Intervals, Four Gamete Tests, Solid Spine of LD and fusing method of haplotype block) into high-throughout SNP genotype data to identify blocks, then use cluster analysis to verify the effectiveness of the four methods, and select the alcoholism-related SNP haplotypes through risk analysis. Second, we establish a mapping from haplotypes to alcoholism-related genes. Third, we inquire NCBI SNP and gene databases to locate the blocks and identify the candidate genes. In the end, we make gene function annotation by KEGG, Biocarta, and GO database. We find 159 haplotype blocks, which relate to the alcoholism most possibly on chromosome 1 approximately 22, including 227 haplotypes, of which 102 SNP haplotypes may increase the risk of alcoholism. We get 121 alcoholism-related genes and verify their reliability by the functional annotation of biology. In a word, we not only can handle the SNP data easily, but also can locate the disease-related genes precisely by combining our novel strategies of mining alcoholism-related haplotypes and genes with existing knowledge framework.
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Meta-analysis of 125 rheumatoid arthritis-related single nucleotide polymorphisms studied in the past two decades.
PLoS ONE
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Candidate gene association studies and genome-wide association studies (GWAs) have identified a large number of single nucleotide polymorphisms (SNPs) loci affecting susceptibility to rheumatoid arthritis (RA). However, for the same locus, some studies have yielded inconsistent results. To assess all the available evidence for association, we performed a meta-analysis on previously published case-control studies investigating the association between SNPs and RA.
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Lack of association between PICALM rs3851179 polymorphism and Alzheimers disease in Chinese population and APOE?4-negative subgroup.
Neurobiol. Aging
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Recently, the association between PICALM rs3851179 polymorphism and Alzheimers disease (AD) was investigated in the Chinese population by 3 independent studies. However, both allele and genotype tests failed to reveal any association. The association was identified only in the APOE?4-negative subgroup. We think that the failure to replicate the association may be because of the relatively small sample size. In this research, we reinvestigated the association using all the samples from these 3 studies (n = 2486, and 1202 cases and 1284 control subjects). We failed to replicate this association between the rs3851179 polymorphism and AD in all samples and the APOE?4-negative subgroup. Our results indicate that rs3851179 may not be an AD susceptibility locus in the Chinese population and the APOE?4-negative subgroup.
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DBGSA: a novel method of distance-based gene set analysis.
J. Hum. Genet.
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When compared with single gene functional analysis, gene set analysis (GSA) can extract more information from gene expression profiles. Currently, several gene set methods have been proposed, but most of the methods cannot detect gene sets with a large number of minor-effect genes. Here, we propose a novel distance-based gene set analysis method. The distance between two groups of genes with different phenotypes based on gene expression should be larger if a certain gene set is significantly associated with the given phenotype. We calculated the distance between two groups with different phenotypes, estimated the significant P-values using two permutation methods and performed multiple hypothesis testing adjustments. This method was performed on one simulated data set and three real data sets. After a comparison and literature verification, we determined that the gene resampling-based permutation method is more suitable for GSA, and the centroid statistical and average linkage statistical distance methods are efficient, especially in detecting gene sets containing more minor-effect genes. We believe that this distance-based method will assist us in finding functional gene sets that are significantly related to a complex trait. Additionally, we have prepared a simple and publically available Perl and R package (http://bioinfo.hrbmu.edu.cn/dbgsa or http://cran.r-project.org/web/packages/DBGSA/).
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Enrichment Disequilibrium: a novel approach for measuring the degree of enrichment after gene enrichment test.
Biochem. Biophys. Res. Commun.
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Commonly used gene enrichment analysis methods, such as Hypergeometric distribution, play an important role in the functional analysis of interesting gene lists. But the statistical significance obtained by these methods only represents the probability of error that is involved in accepting enrichment, and is not suitable to evaluate the degree of enrichment. Although there have been some methods to measure the enrichment degrees, such as relative enrichment factor, new methods are still needed to meet the requirements for comparing the degree of enrichment.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

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We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

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In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.