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There are four gasdermin (GSDM) proteins, including GSDMA, GSDMB, GSDMC, and GSDMD, in the human genome (1). Genome-wide association studies have reported genetic variants at 17q12.2.1 loci, including GSDMA , GSDMB , and ORDML3 genes, to be associated with kinds of autoimmune diseases, including asthma, type 1 diabetes, inflammatory bowel disease (IBD), and rheumatoid arthritis (1). However, the potential genetic mechanisms are unknown (1). In a recent study in PNAS, Chao et al. (1) identified that the GSDMB gene SNPs (rs2305479 G > A and rs2305480 C > T), which are associated with an increased susceptibility to asthma and IBD, could alter the structure of GSDMB, a sulfatide and phosphoinositide binding protein. In their discussion, Chao et al. (1) describe that GSDMB may … [↵][1]1To whom correspondence may be addressed. Email: liuguiyou1981{at}163.com or qhjiang{at}hit.edu.cn. [1]: #xref-corresp-1-1

A recent study analyzed 2053 multiple sclerosis (MS) cases and 799 healthy controls to investigate whether five genetic variants (rs11039149, rs12221497, rs2279238, rs7120118 and rs7114704) in NR1H3 are associated with MS risk. However this study reported negative results. It is very important that the appropriate samples and approach should be used in replication studies, which may provide the correct interpretation of the results. Here, we evaluated the above findings using large-scale MS genome-wide association studies with a total of 27,148 samples including 9772 MS cases and 17,376 controls, and multiple expression quantitative trait loci datasets. The results suggest that rs7120118 and rs2279238 variants are significantly associated with MS risk, and could significantly regulate NR1H3 expression in kinds of human tissues and cells. In summary, these findings provide important supplementary information about the association between NR1H3 variants and MS risk.

Background The development of single-cell RNA sequencing has enabled profound discoveries in biology, ranging from the dissection of the composition of complex tissues to the identification of novel cell types and dynamics in some specialized cellular environments. However, the large-scale generation of single-cell RNA-seq (scRNA-seq) data collected at multiple time points remains a challenge to effective measurement gene expression patterns in transcriptome analysis. Results We present an algorithm based on the Dynamic Time Warping score (DTWscore) combined with time-series data, that enables the detection of gene expression changes across scRNA-seq samples and recovery of potential cell types from complex mixtures of multiple cell types. Conclusions The DTWscore successfully classify cells of different types with the most highly variable genes from time-series scRNA-seq data. The study was confined to methods that are implemented and available within the R framework. Sample datasets and R packages are available at https://github.com/xiaoxiaoxier/DTWscore. Electronic supplementary material The online version of this article (doi:10.1186/s12859-017-1647-3) contains supplementary material, which is available to authorized users.

A recent study sequenced the full coding region of SORL1 in 1,255 early-onset Alzheimer's disease (EOAD) cases and 1,938 control individuals, and investigated the contribution of genetic variability in SORL1 to EOAD risk in a European cohort. This study identified six common variants and five low frequency variants in the SORL1 coding sequence. However, none of these 11 variants was significantly associated with EOAD risk after adjusting for multiple testing. We consider whether these 11 SORL1 variants identified in European EOAD contribute to late-onset Alzheimer's disease (LOAD) risk in individuals of European ancestry. Here, we investigated these 11 SORL1 variants identified in European EOAD and LOAD risk in individuals of European ancestry using a large-scale LOAD GWAS. Our results indicate that three genetic variants rs2070045, rs2276412, and rs17125548 as well as their tagged genetic variants contribute to LOAD risk in European population. We further investigate whether these variants could affect SORL1 expression using multiple expression quantitative trait loci (eQTLs) datasets. Our findings suggest that three genetic variants rs2070045, rs1699102, and rs3824968 could significantly regulate SORL1 expression in human brain tissues. We believe that our findings further provide important supplementary information about the involvement of the SORL1 variants in LOAD risk.

Figure S4. DTWscore identifies heterogeneous genes and non-heterogeneous genes from the synthetic data (condition 6). (PDF 122 kb)

Figure S6. Model-based clustering of HSMM dataset by any three highly variable genes. (PDF 68 kb)

Figure S3. DTWscore identifies heterogeneous genes and non-heterogeneous genes from the synthetic data (condition 5). (PDF 122 kb)

Figure S5. Model-based clustering of HSMM dataset by any two highly variable genes. (PDF 40 kb)

Figure S1. DTWscore identifies heterogeneous genes and non-heterogeneous genes from the synthetic data (condition 3). (PDF 122 kb)

Figure S2. DTWscore identifies heterogeneous genes and non-heterogeneous genes from the synthetic data (condition 4). (PDF 122 kb)

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

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.

Early studies had suggested that vitamin D intake was inversely associated with neurodegenerative diseases, such as Alzheimer’s disease and multiple sclerosis. However, the associations of vitamin D intake and outdoor activities with Parkinson’s disease (PD) are still unclear, so this study is to evaluate these relationships from a case-control study in elderly Chinese. The study population involved 209 cases with new onsets of PD and 210 controls without neurodegenerative diseases. The data on dietary vitamin D and outdoor activities were collected using a food-frequency questionnaire and self-report questionnaire. Multivariable logistic regressions were used to examine the associations between dietary outdoor activities, vitamin D intake and PD. Adjustment was made for sex, age, smoking, alcohol use, education, and body mass index (BMI). Adjusted odds ratios (ORs) for PD in quartiles for outdoor physical activity were 1 (reference), 0.739 (0.413, 1.321), 0.501 (0.282, 0.891), and 0.437 (0.241, 0.795), respectively (P=0.002 for trend). Adjusted ORs for PD in quartiles for total vitamin D intake were 1 (reference), 0.647 (0.357, 1.170), 0.571 (0.318, 1.022), and 0.538 (0.301, 0.960), respectively (P=0.011 for trend). Our study suggested that outdoor activity and total vitamin D intake were inversely associated with PD, and outdoor activity seems to be more significantly associated with decreased risk for PD.

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.

Aims The study was to examine whether glycosylation could improve the thermostability of recombinant Thermomyces lanuginosus lipase (Tll) expressed in Pichia pastoris. Methods and Results The Tll gene was synthesized and transformed into Pichia pastoris GS115.The recombinant Tll protein was expressed and purified, and its glycosylation site was identified by LCMS/MS as Asn-33. Two nonglycosylated mutants were constructed and the variant proteins were also expressed and purified. Effects of temperature on activities of the wild-type Tll and variants were analysed. The glycosylated Tll exhibited better thermostability than nonglycosylated variants. Conclusions Our experiments have demonstrated the improvement of Tll thermostability by Asn-33 glycosylation. Significance and Impact of the Study This work has deepened our understanding in the mechanism of Tll thermostability and will guide us to directional improvement of lipases and even other industrial enzymes.

Alzheimer's 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.

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.

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.

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.

Motivation With the development of biotechnology, DNA methylation data showed exponential growth. Epigenome-wide association study (EWAS) provide a systematic approach to uncovering epigenetic variants underlying common diseases/phenotypes. But the EWAS software has lagged behind compared with genome-wide association study (GWAS). To meet the requirements of users, we developed a convenient and useful software, EWAS2.0. Results EWAS2.0 can analyze EWAS data and identify the association between epigenetic variations and disease/phenotype. On the basis of EWAS1.0, we have added more distinctive features. EWAS2.0 software was developed based on our ‘population epigenetic framework’ and can perform: (i) epigenome-wide single marker association study; (ii) epigenome-wide methylation haplotype (meplotype) association study and (iii) epigenome-wide association meta-analysis. Users can use EWAS2.0 to execute chi-square test, t-test, linear regression analysis, logistic regression analysis, identify the association between epi-alleles, identify the methylation disequilibrium (MD) blocks, calculate the MD coefficient, the frequency of meplotype and Pearson's correlation coefficients and carry out meta-analysis and so on. Finally, we expect EWAS2.0 to become a popular software and be widely used in epigenome-wide associated studies in the future. Availability and implementation The EWAS software is freely available at http://www.ewas.org.cn or http://www.bioapp.org/ewas.

Large-scale genomewide association studies have reported that the CLU rs11136000 polymorphism is significantly associated with Alzheimer's 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.

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.

Tumor necrosis factor-β (TNF-β) plays important roles in mediating cancer development. Many studies have argued possible associations of TNF-β +252 AG polymorphism with different cancers. However, association between this most frequently studied polymorphism and susceptibility to cancer still remains controversial and ambiguous. The aim of this study is to determine the relationship of TNF-β +252 AG polymorphism with cancer through meta-analysis.Electronic searches of several databases were conducted for all publications on the associations between this variant and cancer through October 2011. Odds ratios (ORs) with 95 % confidence intervals (95 % CIs) were used to access the strength of this association in random-effect model.Thirty-three studies with 14,435 cancer patients and 10,583 healthy controls were included. In this meta-analysis, we detected statistically significant connections between this polymorphism and cancer risks [GG + GA vs. AA: OR = 1.24, 95 % CI = 1.02-1.51; GG vs. AA: OR = 1.43, 95 % CI = 1.05-1.95; G vs. A: OR = 1.28, 95 % CI = 1.28 (1.09-1.50)] in the overall ethnic population. Meanwhile, we detected significant associations in Asian population (GG + GA vs. AA), other population (GG vs. GA + AA), and Caucasian population (GG vs. AA, G vs. A) with the OR values being 1.21 (1.04-1.40), 1.64 (1.35-1.99), 1.65 (1.02, 2.65), and 1.39 (1.09-1.75), respectively.TNF-β +252 AG polymorphism is positively associated with susceptibility to cancer. However, this study also suggests that more studies should be conducted to further confirm the associations between this variant and specific types of cancers.

In PNAS, Yau et al. (1) identify a conserved 33-kb haplotype Ltab-Ncr3 across five genes, lymphotoxin-α ( Lta ), Tnf , lymphotoxin-β ( Ltb ), leukocyte-specific transcript 1 ( Lst1 ), and natural cytotoxicity-triggering receptor 3 ( Ncr3 ) in the MHC-III region in wild rats. The higher Ltb and Ncr3 expression, the lower Lst1 expression, and the expression of a shorter splice variant of Lst1 were associated with reduced arthritis severity in rats (1). Yau et al. (1) further analyzed the expression levels of LTB , LST1 , and NCR3 using whole-blood samples from 32 patients with rheumatoid arthritis (RA) and 92 healthy controls (1). They identify significantly increased expression of these three genes in RA cases (1). The mild RA cases also showed lower expression of LST1 and higher expression of … [↵][1]1To whom correspondence may be addressed. Email: hjw{at}tmu.edu.cn or qhjiang{at}hit.edu.cn. [1]: #xref-corresp-1-1

Large-scale genome-wide association study (GWAS) datasets provide strong support for investigations of the mechanisms underlying multiple sclerosis (MS) by using pathway analysis methods. In our recent study, we conducted a three-stage pathway analysis of GWAS and expression datasets. After identifying 15 shared MS pathways in separate MS GWAS datasets, we found that dysregulated MS genes were significantly enriched in 10 of the 15 MS risk pathways. Evidence showed that 17%-30% of genes are differentially expressed among individual ethnic populations. We then verified the potential disruption of genes in the 10 MS risk pathways cited above in Chinese MS patients. Here, we investigated potential up- and down-regulation of 42 MS genes in these 10 MS risk pathways using 132 Chinese MS patients and 76 healthy control subjects. We then identified 31 differentially expressed genes in Chinese MS patients compared to healthy control subjects. Moreover, the expression patterns of 28 of these genes were consistent with those obtained from Caucasian (European and American) MS patients, although 14 genes differed from the latter group's. Our results provide clinically useful clues about the link between these risk genes and MS susceptibility in the Chinese population.

In this study, we strove to substantiate the ability of linc-MAF-4 to act as a regulator of pathogenesis during multiple sclerosis (MS). We recruited 34 patients who were diagnosed with MS according to the revised McDonald criteria. Six patients with MS and 5 healthy volunteers contributed peripheral blood mononuclear cells for microarray analysis. Subsequent knockdown and overexpression of linc-MAF-4 in naive CD4+ T cells from the additional 28 patients with MS was performed to track changes in CD4+ T-cell subsets and their function, as well as to confirm results from the prior microarray analysis. Expression of linc-MAF-4 increased significantly in peripheral blood mononuclear cells of patients with MS compared with those of control participants. In addition, linc-MAF-4 regulated encephalitogenic T helper (Th)1-cell differentiation in patients with MS. Transfection of synthetic linc-MAF-4 into naive CD4+ T cells facilitated Th1-cell differentiation and inhibited Th2-cell differentiation by directly inhibiting MAF, which is a Th2-cell transcription factor. Linc-MAF-4 also promoted activation of CD4+ T cells from patients with MS. Expression level of linc-MAF-4 correlated with the annual relapse rate in patients with MS. Our results suggest that linc-MAF-4 is involved in the pathogenesis of MS, specifically via regulation of encephalitogenic T cells.-Zhang, F., Liu, G., Wei, C., Gao, C., Hao, J. Linc-MAF-4 regulates Th1/Th2 differentiation and is associated with the pathogenesis of multiple sclerosis by targeting MAF.

To analyze the relation between SNPs in DNA repair pathway-related genes and sensitivity of tumor radio-chemotherapy, 26 SNPs in 20 DNA repair genes were genotyped on 176 patients of NSCLC undertaking radio-chemotherapy treatment. In squamous cell carcinoma (SCC), as the rs2228000, rs2228001 (XPC), rs2273953 (TP73), rs2279744 (MDM2), rs2299939 (PTEN) and rs8178085, rs12334811 (DNA-PKcs) affected the sensitivity to chemotherapy, so did the rs8178085, rs12334811 to radiotherapy. Moreover rs344781, rs2273953 and rs12334811 were related with the survival time of SCC. In general, the “good” genotype GG (rs12334811) showed greater efficacy of radio-chemotherapy and MSF (24 months) on SCC. In adenocarcinoma, as the rs2699887 (PIK3), rs12334811 (DNA-PKcs) influenced the sensitivity to chemotherapy, so did the rs2299939, rs2735343 (PTEN) to radiotherapy. And rs402710, rs80270, rs2279744 and rs2909430 impacted the survival time of the adenocarcinoma patients. Both GG (rs2279744) and AG (rs2909430) showed a shorter survival time (MFS = 6). Additionally, some SNPs such as rs2228000, rs2228001 and rs344781 were found to regulate the expression of DNA repair pathway genes through eQTLs dataset analysis. These results indicate that SNPs in DNA repair pathway genes might regulate the expression and affect the DNA damage repair, and thereby impact the efficacy of radio-chemotherapy and the survival time of NSCLC.

Background: Much effort has been expended on identifying the genetic determinants of multiple sclerosis (MS). Existing large-scale genome-wide association study (GWAS) datasets provide strong support for using pathway and network-based analysis methods to investigate the mechanisms underlying MS. However, no shared genetic pathways have been identified to date. Objective: We hypothesize that shared genetic pathways may indeed exist in different MS-GWAS datasets. Methods: Here, we report results from a three-stage analysis of GWAS and expression datasets. In stage 1, we conducted multiple pathway analyses of two MS-GWAS datasets. In stage 2, we performed a candidate pathway analysis of the large-scale MS-GWAS dataset. In stage 3, we performed a pathway analysis using the dysregulated MS gene list from seven human MS case–control expression datasets. Results: In stage 1, we identified 15 shared pathways. In stage 2, we successfully replicated 14 of these 15 significant pathways. In stage 3, we found that dysregulated MS genes were significantly enriched in 10 of 15 MS risk pathways identified in stages 1 and 2. Conclusion: We report shared genetic pathways in different MS-GWAS datasets and highlight some new MS risk pathways. Our findings provide new insights on the genetic determinants of MS.

Gametogenesis is a complex process, which includes mitosis and meiosis and results in the production of ovum and sperm. The development of gametogenesis is dynamic and needs many different genes to work synergistically, but it is lack of global perspective research about this process. In this study, we detected the dynamic process of gametogenesis from the perspective of systems biology based on protein-protein interaction networks (PPINs) and functional analysis. Results showed that gametogenesis genes have strong synergistic effects in PPINs within and between different phases during the development. Addition to the synergistic effects on molecular networks, gametogenesis genes showed functional consistency within and between different phases, which provides the further evidence about the dynamic process during the development of gametogenesis. At last, we detected and provided the core molecular modules of different phases about gametogenesis. The gametogenesis genes and related modules can be obtained from our Web site Gametogenesis Molecule Online (GMO, http://gametsonline.nwsuaflmz.com/index.php), which is freely accessible. GMO may be helpful for the reference and application of these genes and modules in the future identification of key genes about gametogenesis. Summary, this work provided a computational perspective and frame to the analysis of the gametogenesis dynamics and modularity in both human and mouse.

Alzheimer’s disease (AD) is complex and one of the most common neurodegenerative diseases in the elderly (1). Three large-scale genome-wide association studies (GWAS) identified CD33 rs3865444 polymorphism to be significantly associated with AD susceptibility in European ancestry with genome-wide significance ( P < 5.00E-08). In our previous meta-analysis, we further confirmed the association between rs3865444 and AD susceptibility in Chinese and North American populations (1). In a recent study, Schwarz et al. analyze 13 SNPs, and identify that the … [↵][1]1To whom correspondence should be addressed. Email: qhjiang{at}hit.edu.cn. [1]: #xref-corresp-1-1

Embryonic stem cells (ESCs) play an important role in developmental biology which is still lacking clear molecular mechanisms. The "core" transcription factors (TFs) including OCT4, SOX2 and NANOG are essential for maintaining the stemness of ESCs. But the downstream targets of these "core" TFs are still ambiguous. Based on support vector machine (SVM) technology, this study develops a label method algorithm (LMA) for genome-wide target identification of "core" TFs in humans, which eliminates the need for negative training samples. This method integrates histone modifications and TF binding motifs as identification features. Compared with a previous mapping-convergence (M-C) algorithm, the LMA can provide more stable and reliable predictions. 4796, 3166 and 4384 target genes of OCT4, SOX2 and NANOG, respectively, were identified with the LMA model. Then verifications of the predicted targets were carried out based on their functional consistency and their connection degree in networks from a computational system biology perspective. The results showed that the targets of "core" TFs present higher gene functional similarity and closer connection distance than background levels.

ZSTK474 alleviates neurological deficits in the model of ischemic reperfusion. (DOCX 56 kb)

Alzheimer's 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 Fisher's 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.

Transforming naringin using the mycelium of Trichoderma harzianum CGMCC 1523 produces two metabolites, 3′,4′,5,7-tetrahydroxy flavanone-7-rhamnoglucoside (3′-OHN) and 3′,4′,5′,5,7-pentahydroxy flavanone-7-rhamnoglucoside (3′,5′-DOHN), both of which were characterized by ESI–MS, 1H NMR and 13C NMR analyses. The time course of the biotransformation by T. harzianum showed that 3′-OHN and 3′,5′-DOHN appeared simultaneously at 6 h, and the conversion yield (32.6%) of 3′,5′-DOHN was higher (10.6%) than that of 3′-OHN at 56 h. The optimal biotransformation temperature was 30 °C, the optimal pH was 5.0, and the optimal concentration of naringin was 400 mg/l. The bigger volume of biotransformation mixture and lower shaking speed did not favor hydroxylation reactions. The radical scavenging activity of naringin at 2000 μM was 11.1%, whereas activity of 3′-OHN at 100 μM could reach 38.4%, which is 68.6 times more than naringin. Antioxidative activity of 3′,5′-DOHN was increased 13.5% at 100 μM compared to 3′-OHN.

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.

Cardiovascular disease (CVD) is a class of diseases that involve the heart or blood vessels. It is reported that body mass index (BMI) is risk factor for CVD. Genome-wide association studies (GWAS) have recently provided rapid insights into genetics of CVD and its risk factors. However, the specific mechanisms how BMI influences CVD risk are largely unknown. We think that BMI may influences CVD risk by shared genetic pathways. In order to confirm this view, we conducted a pathway analysis of BMI GWAS, which examined approximately 329,091 single nucleotide polymorphisms from 4763 samples. We identified 31 significant KEGG pathways. There is literature evidence supporting the involvement of GnRH signaling, vascular smooth muscle contraction, dilated cardiomyopathy, Gap junction, Wnt signaling, Calcium signaling and Chemokine signaling in CVD. Collectively, our study supports the potential role of the CVD risk pathways in BMI. BMI may influence CVD risk by the shared genetic pathways. We believe that our results may advance our understanding of BMI mechanisms in CVD.

Parkinson’s disease (PD) is the second most common neurodegenerative disease in the elderly. Santiago and Potashkin (1) recently performed a network-based metaanalysis of four independent microarray datasets and identified hepatocyte nuclear factor 4 alpha (HNF4A) and polypyrimidine tract binding protein 1 (PTBP1) to be the longitudinally dynamic biomarkers for PD. They found that HNF4A is a central regulatory hub gene up-regulated in blood of PD patients and PTBP1 is the most down-regulated gene (1).

Colorectal cancer (CRC) is the third most common form of cancer and the second leading cause of cancer-related death in the Western countries. In order to detect common CRC genetic variants, genome-wide association studies (GWAS) have been performed and reported some novel CRC susceptibility variants. RHPN2 is located on 9q13.11, which encodes a member of the rhophilin family of Ras-homologous (Rho)-GTPase binding proteins. RHPN2 gene rs10411210 polymorphism was identified to be significantly associated with CRC in European ancestry. GWAS and candidate studies investigate whether rs10411210 polymorphism is associated with CRC risk in European, Asian and American populations. However, most studies reported no association. Evidence shows that RHPN2 rs10411210 variant may be a prognostic biomarker for patients with surgically resected CRC. Here we reevaluated this association using large-scale samples from 15 studies (131580 samples including 53564 CRC cases and 78016 controls) using meta-analysis method by searching the PubMed and Google Scholar databases. We did not identify significant heterogeneity among these 15 studies (P=0.4201 and I(2)=2.8%). Our results showed significant association between rs10411210 and CRC (P=9.17E-14, odds ratio (OR)=1.10, 95% confidence interval (CI) 1.07-1.13). In subgroup analysis, we found significant association between rs10411210 and CRC in European population with P=5.70E-09, OR=1.14, 95% CI 1.10-1.20 and Asian population with P=3.36E-07, OR=1.11, 95% CI 1.07-1.16, but not American population with P=0.0576, OR=1.05, 95% CI 1.00-1.09. Collectively, our analysis further highlights significant association between rs10411210 polymorphism and colorectal cancer.

Recent genome-wide association studies (GWAS) reported CR1 rs3818361 polymorphism to be an Alzheimer’s disease (AD) susceptibility variant in European ancestry. Three independent studies investigated this association in Chinese population. However, these studies reported weak or no significant association. Here, we reinvestigated the association using all the samples from three independent studies in Chinese population (N = 4047, 1244 AD cases and 2803 controls). We also selected three independent studies in European ancestry population (N = 11787, 3939 AD cases and 7848 controls) to evaluate the effect of rs3818361 polymorphism on AD risk in different ethnic backgrounds. In Chinese population, we did not identified significant heterogeneity using additive, recessive, and dominant genetic models. Meta-analysis showed significant association between rs3818361 and AD with P = 6.00E-03 and P = 5.00E-03. We further identified no heterogeneity of rs3818361 polymorphism between Chinese and European populations. We found that rs3818361 polymorphism contributed to AD with similar genetic risk in Chinese and European populations. In summary, this is the first study to show significant association between rs3818361 polymorphism and AD in Chinese population by a meta-analysis method. Our findings indicate that the effect of CR1 rs3818361 polymorphism on AD risk in Chinese cohorts is consistent with the increased risk observed in European AD cohorts.

Colorectal cancer (CRC) is a common complex disease caused by the combination of genetic variants and environmental factors. Genome-wide association studies (GWAS) have been performed and reported some novel CRC susceptibility variants. The rs16892766 (8q23.3) polymorphism was first identified to be significantly associated with CRC in European ancestry. The following studies investigated this association in Chinese, Japanese, Romanian, Swedish, African American, European American and Croatian populations. These studies reported consistent and inconsistent results. Here, we reevaluated this association using the relatively large-scale samples from 13 studies (N = 59737, 26237 cases and 33500 controls) using a meta-analysis by searching the PubMed, Google Scholar and CRCgene databases. We observed no significant heterogeneity among the included studies. Our results showed significant association between rs16892766 polymorphism and CRC (P = 1.33E-35, OR = 1.23, 95% CI 1.20-1.27). Collectively, our analysis further supports previous findings that the rs16892766 polymorphism is significantly associated with CRC susceptibility. We believe that our findings will be very useful for future genetic studies on CRC.

Long non-coding RNAs (lncRNAs) have emerged as critical regulators of genes at epigenetic, transcriptional and post-transcriptional levels, yet what genes are regulated by a specific lncRNA remains to be characterized. To assess the effects of the lncRNA on gene expression, an increasing number of researchers profiled the genome-wide or individual gene expression level change after knocking down or overexpressing the lncRNA. Herein, we describe a curated database named LncRNA2Target, which stores lncRNA-to-target genes and is publicly accessible at http://www.lncrna2target.org. A gene was considered as a target of a lncRNA if it is differentially expressed after the lncRNA knockdown or overexpression. LncRNA2Target provides a web interface through which its users can search for the targets of a particular lncRNA or for the lncRNAs that target a particular gene. Both search types are performed either by browsing a provided catalog of lncRNA names or by inserting lncRNA/target gene IDs/names in a search box.

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.

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.