Mingzhi Liao

PICALM Gene rs3851179 Polymorphism Contributes to Alzheimer’s Disease in an Asian Population

PICALM gene rs3851179 polymorphism was reported to an Alzheimer’s 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.

Predicting human microRNA precursors based on an optimized feature subset generated by GA-SVM.

MicroRNAs (miRNAs) are non-coding RNAs that play important roles in post-transcriptional regulation. Identification of miRNAs is crucial to understanding their biological mechanism. Recently, machine-learning approaches have been employed to predict miRNA precursors (pre-miRNAs). However, features used are divergent and consequently induce different performance. Thus, feature selection is critical for pre-miRNA prediction. We generated an optimized feature subset including 13 features using a hybrid of genetic algorithm and support vector machine (GA-SVM). Based on SVM, the classification performance of the optimized feature subset is much higher than that of the two feature sets used in microPred and miPred by five-fold cross-validation. Finally, we constructed the classifier miR-SF to predict the most recently identified human pre-miRNAs in miRBase (version 16). Compared with microPred and miPred, miR-SF achieved much higher classification performance. Accuracies were 93.97%, 86.21% and 64.66% for miR-SF, microPred and miPred, respectively. Thus, miR-SF is effective for identifying pre-miRNAs.

Identification of links between small molecules and miRNAs in human cancers based on transcriptional responses

The use of small molecules to target miRNAs is a new type of therapy for human diseases, particularly cancers. We proposed a novel high-throughput approach to identify the biological links between small molecules and miRNAs in 23 different cancers and constructed the Small Molecule-MiRNA Network (SMirN) for each cancer to systematically analyze the properties of their associations. In each SMirN, we partitioned small molecules (miRNAs) into modules, in which small molecules (miRNAs) were connected with one miRNA (small molecule). Almost all of the miRNA modules comprised miRNAs that had similar target genes and functions or were members of the same miRNA family. Most of the small molecule modules involved compounds with similar chemical structures, modes of action, or drug interactions. These modules can be used to identify drug candidates and new indications for existing drugs. Therefore, our approach is valuable to drug discovery and cancer therapy.

BIN1 gene rs744373 polymorphism contributes to Alzheimer's disease in East Asian population

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.

Alzheimer's Disease Variants with the Genome-Wide Significance are Significantly Enriched in Immune Pathways and Active in Immune Cells.

The existing large-scale genome-wide association studies (GWAS) datasets provide strong support for investigating the mechanisms of Alzheimer’s disease (AD) by applying multiple methods of pathway analysis. Previous studies using selected single nucleotide polymorphisms (SNPs) with several thresholds of nominal significance for pathway analysis determined that the threshold chosen for SNPs can reflect the disease model. Presumably, then, pathway analysis with a stringent threshold to define “associated” SNPs would test the hypothesis that highly associated SNPs are enriched in one or more particular pathways. Here, we selected 599 AD variants (P < 5.00E−08) to investigate the pathways in which these variants are enriched and the cell types in which these variants are active. Our results showed that AD variants are significantly enriched in pathways of the immune system. Further analysis indicated that AD variants are significantly enriched for enhancers in a number of cell types, in particular the B-lymphocyte, which is the most substantially enriched cell type. This cell type maintains its dominance among the strongest enhancers. AD SNPs also display significant enrichment for DNase in 12 cell types, among which the top 6 significant signals are from immune cell types, including 4 B cells (top 4 significant signals) and CD14+ and CD34+ cells. In summary, our results show that these AD variants with P < 5.00E−08 are significantly enriched in pathways of the immune system and active in immune cells. To a certain degree, the genetic predisposition for development of AD is rooted in the immune system, rather than in neuronal cells.

Cell adhesion molecule pathway genes are regulated by cis-regulatory SNPs and show significantly altered expression in Alzheimer's disease brains.

We previously identified the cell adhesion molecule (CAM) pathway as a consistent signal in 2 Alzheimers disease (AD) genome-wide association studies (GWAS). However, the genetic mechanisms of the CAM pathway in AD are unclear. Here, we conducted pathway analysis using (1) Kyoto Encyclopedia of Genes and Genomes and Gene Ontology pathways; (2) 4 brain expression GWAS datasets; and (3) 2 whole-genome AD case-control expression datasets. Using the 4 brain expression GWAS datasets, we identified that genes regulated by cis-regulatory single-nucleotide polymorphisms (SNPs) were significantly enriched in the CAM pathway (p = 2.05E-06, p = 6.10E-07, p = 2.05E-06, and p = 1.47E-07 for each dataset). Interestingly, CAM is a significantly enriched pathway using down-regulated genes (raw p = 0.0235 and adjusted p = 0.0305) and all differentially expressed genes (raw p = 0.0105 and adjusted p = 0.0156) in dataset 5, and all differentially expressed genes (raw p = 0.0041 and adjusted p = 0.0062) in dataset 6. Collectively, our results show that CAM pathway genes are regulated by cis-regulatory SNPs and show significantly altered expression in AD. We believe that our results advance the understanding of AD mechanisms and will be useful for future genetic studies of AD.

Dissection of human MiRNA regulatory influence to subpathway

The global insight into the relationships between miRNAs and their regulatory influences remains poorly understood. And most of complex diseases may be attributed to certain local areas of pathway (subpathway) instead of the entire pathway. Here, we reviewed the studies on miRNA regulations to pathways and constructed a bipartite miRNAs and subpathways network for systematic analyzing the miRNA regulatory influences to subpathways. We found that a small fraction of miRNAs were global regulators, environmental information processing pathways were preferentially regulated by miRNAs, and miRNAs had synergistic effect on regulating group of subpathways with similar function. Integrating the disease states of miRNAs, we also found that disease miRNAs regulated more subpathways than nondisease miRNAs, and for all miRNAs, the number of regulated subpathways was not in proportion to the number of the related diseases. Therefore, the study not only provided a global view on the relationships among disease, miRNA and subpathway, but also uncovered the function aspects of miRNA regulations and potential pathogenesis of complex diseases. A web server to query, visualize and download for all the data can be freely accessed at http://bioinfo.hrbmu.edu.cn/miR2Subpath.

Lack of association between PICALM rs3851179 polymorphism and Alzheimer's disease in Chinese population and APOEε4-negative subgroup

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 APOEε4-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 APOEε4-negative subgroup. Our results indicate that rs3851179 may not be an AD susceptibility locus in the Chinese population and the APOEε4-negative subgroup.

Integrating Genome-Wide Association Study and Brain Expression Data Highlights Cell Adhesion Molecules and Purine Metabolism in Alzheimer's Disease.

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.

PLNlncRbase: A resource for experimentally identified lncRNAs in plants

Accumulating published reports have confirmed the critical biological role (e.g., cell differentiation, gene regulation, stress response) for plant long non-coding RNAs (lncRNAs). However, a literature-derived database with the aim of lncRNA curation, data deposit and further distribution remains still absent for this particular lncRNA clade. PLNlncRbase has been designed as an easy-to-use resource to provide detailed information for experimentally identified plant lncRNAs. In the current version, PLNlncRbase has manually collected data from nearly 200 published literature, covering a total of 1187 plant lncRNAs in 43 plant species. The user can retrieve plant lncRNA entries from a well-organized interface through a keyword search by using the name of plant species or a lncRNA identifier. Each entry upon a query will be returned with detailed information for a specific plant lncRNA, including the species name, a lncRNA identifier, a brief description of the potential biological role, the lncRNA sequence, the lncRNA classification, an expression pattern of the lncRNA, the tissue/developmental stage/condition for lncRNA expression, the detection method for lncRNA expression, a reference literature, and the potential target gene(s) of the lncRNA extracted from the original reference. This database will be regularly updated to greatly facilitate future investigations of plant lncRNAs pertaining to their biological significance. The PLNlncRbase database is now freely available at http://bioinformatics.ahau.edu.cn/PLNlncRbase.