GAGE: generally applicable gene set enrichment for pathway analysis

Background  

Gene set analysis (GSA) is a widely used strategy for gene expression data analysis based on pathway knowledge. GSA focuses on sets of related genes and has established major advantages over individual gene analyses, including greater robustness, sensitivity and biological relevance. However, previous GSA methods have limited usage as they cannot handle datasets of different sample sizes or experimental designs.     

Genomewide linkage scan of 409 European-ancestry and African American families with schizophrenia: suggestive evidence of linkage at 8p23.3-p21.2 and 11p13.1-q14.1 in the combined sample

We report the clinical characteristics of a schizophrenia sample of 409 pedigrees--263 of European ancestry (EA) and 146 of African American ancestry (AA)--together with the results of a genome scan (with a simple tandem repeat polymorphism interval of 9 cM) and follow-up fine mapping. A family was required to have a proband with schizophrenia (SZ) and one or more siblings of the proband with SZ or schizoaffective disorder. Linkage analyses included 403 independent full-sibling affected sibling pairs (ASPs) (279 EA and 124 AA) and 100 all-possible half-sibling ASPs (15 EA and 85 AA). Nonparametric multipoint linkage analysis of all families detected two regions with suggestive evidence of linkage at 8p23.3-q12 and 11p11.2-q22.3 (empirical Z likelihood-ratio score [Z(lr)] threshold >/=2.65) and, in exploratory analyses, two other regions at 4p16.1-p15.32 in AA families and at 5p14.3-q11.2 in EA families. The most significant linkage peak was in chromosome 8p; its signal was mainly driven by the EA families. Z(lr) scores >2.0 in 8p were observed from 30.7 cM to 61.7 cM (Center for Inherited Disease Research map locations). The maximum evidence in the full sample was a multipoint Z(lr) of 3.25 (equivalent Kong-Cox LOD of 2.30) near D8S1771 (at 52 cM); there appeared to be two peaks, both telomeric to neuregulin 1 (NRG1). There is a paracentric inversion common in EA individuals within this region, the effect of which on the linkage evidence remains unknown in this and in other previously analyzed samples. Fine mapping of 8p did not significantly alter the significance or length of the peak. We also performed fine mapping of 4p16.3-p15.2, 5p15.2-q13.3, 10p15.3-p14, 10q25.3-q26.3, and 11p13-q23.3. The highest increase in Z(lr) scores was observed for 5p14.1-q12.1, where the maximum Z(lr) increased from 2.77 initially to 3.80 after fine mapping in the EA families.     

Assessment of gene set analysis methods based on microarray data

Gene set analysis (GSA) incorporates biological information into statistical knowledge to identify gene sets differently expressed between two or more phenotypes. It allows us to gain an insight into the functional working mechanism of cells beyond the detection of differently expressed gene sets. In order to evaluate the competence of GSA approaches, three self-contained GSA approaches with different statistical methods were chosen; Category, Globaltest and Hotelling's T² together with their assayed power to identify the differences expressed via simulation and real microarray data. The Category does not take care of the correlation structure, while the other two deal with correlations.     

Genome‐wide association study identifies loci associated with liability to alcohol and drug dependence that is associated with variability in reward‐related ventral striatum activity in African‐ and European‐Americans

Genetic influences on alcohol and drug dependence partially overlap, however, specific loci underlying this overlap remain unclear. We conducted a genome‐wide association study (GWAS) of a phenotype representing alcohol or illicit drug dependence (ANYDEP) among 7291 European‐Americans (EA; 2927 cases) and 3132 African‐Americans (AA: 1315 cases) participating in the family‐based Collaborative Study on the Genetics of Alcoholism. ANYDEP was heritable (h ² in EA = 0.60, AA = 0.37). The AA GWAS identified three regions with genome‐wide significant (GWS; P < 5E‐08) single nucleotide polymorphisms (SNPs) on chromosomes 3 (rs34066662, rs58801820) and 13 (rs75168521, rs78886294), and an insertion‐deletion on chromosome 5 (chr5:141988181). No polymorphisms reached GWS in the EA. One GWS region (chromosome 1: rs1890881) emerged from a trans‐ancestral meta‐analysis (EA + AA) of ANYDEP, and was attributable to alcohol dependence in both samples. Four genes (AA: CRKL, DZIP3, SBK3; EA: P2RX6) and four sets of genes were significantly enriched within biological pathways for hemostasis and signal transduction. GWS signals did not replicate in two independent samples but there was weak evidence for association between rs1890881 and alcohol intake in the UK Biobank. Among 118 AA and 481 EA individuals from the Duke Neurogenetics Study, rs75168521 and rs1890881 genotypes were associated with variability in reward‐related ventral striatum activation. This study identified novel loci for substance dependence and provides preliminary evidence that these variants are also associated with individual differences in neural reward reactivity. Gene discovery efforts in non‐European samples with distinct patterns of substance use may lead to the identification of novel ancestry‐specific genetic markers of risk.     

Random forests-based differential analysis of gene sets for gene expression data

In DNA microarray studies, gene-set analysis (GSA) has become the focus of gene expression data analysis. GSA utilizes the gene expression profiles of functionally related gene sets in Gene Ontology (GO) categories or priori-defined biological classes to assess the significance of gene sets associated with clinical outcomes or phenotypes. Many statistical approaches have been proposed to determine whether such functionally related gene sets express differentially (enrichment and/or deletion) in variations of phenotypes. However, little attention has been given to the discriminatory power of gene sets and classification of patients.     

Ethnic Differences in Self‐reported and Measured Obesit

As use of self‐reported data to classify obesity continues, ethnic differences in reporting errors remain unclear. The objective of this study is to elucidate misreporting disparities between African Americans (AAs) and European Americans (EAs). The Pennington Center Longitudinal Study (PCLS) is an ongoing investigation of environmental, behavioral, and biological factors associated with obesity, diabetes, and other common diseases. Self‐reported and measured height and weight were collected during initial screening for eligibility in various studies by telephone and clinic visits. All ethnicity‐sex groups (15,656 adults aged 18–65 years, 53% obese, 34% AA, 37% men) misreported heights and weights increasingly as measured values increased (P < 0.0001). More AA vs. EA women (P < 0.001) misreported height and weight, but more EA vs. AA men misreported their weight (P < 0.02). Obesity was underestimated more in AA vs. EA women (self‐reported ? measured prevalence = ?4.0% (AA) vs. ?2.6% (EA), P < 0.0001), but less in AA vs. EA men (?3.2% (AA) vs. ?4.2% (EA), P < 0.0001)). With measured obesity prevalence equalized at 53% in all groups, the self‐reported obesity prevalence in women was 50.4% (AA) vs. 49.6% (EA), and in men 49.8% (AA) vs. 47.3 (EA). Underestimation in women was ?2.6% (AA) vs. ?3.4% (EA); in men it was ?3.2% (AA) vs. ?5.7% (EA), P < 0.003. Self‐reported height and weight portend underestimation of obesity prevalence and the effect varies by ethnicity and gender. However, comparisons depend on the true prevalence within ethnicity‐gender groups. After controlling for obesity prevalence, disparity in underestimation was greater in EA than in AA men (P < 0.003) but not women.     

The Multivariate Nonparametric Methods for Identifying Gene Sets with Differential Expression

Background

Gene Set Analysis (GSA) identifies differential expression gene sets amid the different phenotypes. The results of published papers in this filed are inconsistent and there is no consensus on the best method. In this paper two new methods, in comparison to the previous ones, are introduced for GSA.

Methods

The MMGSA and MRGSA methods based on multivariate nonparametric techniques were presented. The implementation of five GSA methods (Hotelling's T², Globaltest, Abs_Cat, Med_Cat and Rs_Cat) and the novel methods to detect differential gene expression between phenotypes were compared using simulated and real microarray data sets.

Results

In a real dataset, the results showed that the powers of MMGSA and MRGSA were as well as Globaltest and Tsai. The MRGSA method has not a good performance in the simulation dataset.

Conclusions

The Globaltest method is the best method in the real or simulation datasets. The performance of MMGSA in simulation dataset is good in small-size gene sets. The GLS methods are not good in the simulated data, except the Med_Cat method in large-size gene sets.     

Morphological and molecular variation in the least madtom Noturus hildebrandi (Siluriformes: Ictaluridae), a Mississippi Embayment endemic: evidence for a cryptic lineage in the Hatchie River

Sheared principal component analysis of 40 morphometric characteristics measured for 146 individuals and relative frequencies of pigmentation patterns scored for 980 individuals of the least madtom Noturus hildebrandi, a diminutive catfish endemic to eastern lowland drainages of the Mississippi Embayment region of North America, suggested a clinal pattern of morphological variation extending across the range from north to south. DNA sequence data representing 90 individuals from the mitochondrial gene cytochrome b (cytb) analysed using Bayesian phylogenetic methods recovered four major haplotype clades, suggestive of a high degree of isolation by drainage. Individual gene trees of cytb and four additional nuclear loci as well as trees based on concatenated datasets of these genes consistently recovered a cryptic lineage of individuals from the Hatchie River drainage that is morphologically indistinguishable from surrounding populations. Gene‐tree analyses failed to recover a monophyletic N. hildebrandi with respect to Noturus baileyi. A coalescence‐based species tree analysis, however, did recover N. hildebrandi monophyly with high support, suggesting that relationships reflected in individual gene trees and concatenated datasets are in part artefacts of incomplete lineage sorting or an ancient introgressive event. Results are consistent with the hypothesis of an ancient connection between the Hatchie and Tennessee River systems. Current subspecific designations are of limited utility as they reflect morphological variation and are not entirely consistent with phylogeny. Discrepancies between the pattern of variation observed in the morphological and molecular data may be explained by recent local adaptation to individual stream conditions that masks deeper evolutionary divergences.     

Differential gene expression between African American and European American colorectal cancer patients

The incidence and mortality of colorectal cancer (CRC) is higher in African Americans (AAs) than other ethnic groups in the U. S., but reasons for the disparities are unknown. We performed gene expression profiling of sporadic CRCs from AAs vs. European Americans (EAs) to assess the contribution to CRC disparities. We evaluated the gene expression of 43 AA and 43 EA CRC tumors matched by stage and 40 matching normal colorectal tissues using the Agilent human whole genome 4x44K cDNA arrays. Gene and pathway analyses were performed using Significance Analysis of Microarrays (SAM), Ten-fold cross validation, and Ingenuity Pathway Analysis (IPA). SAM revealed that 95 genes were differentially expressed between AA and EA patients at a false discovery rate of ≤5%. Using IPA we determined that most prominent disease and pathway associations of differentially expressed genes were related to inflammation and immune response. Ten-fold cross validation demonstrated that following 10 genes can predict ethnicity with an accuracy of 94%: CRYBB2, PSPH, ADAL, VSIG10L, C17orf81, ANKRD36B, ZNF835, ARHGAP6, TRNT1 and WDR8. Expression of these 10 genes was validated by qRT-PCR in an independent test set of 28 patients (10 AA, 18 EA). Our results are the first to implicate differential gene expression in CRC racial disparities and indicate prominent difference in CRC inflammation between AA and EA patients. Differences in susceptibility to inflammation support the existence of distinct tumor microenvironments in these two patient populations.     

The identification of new biomarkers for bladder cancer: A study based on TCGA and GEO datasets

Bladder cancer (BC) is one of the most common neoplastic diseases worldwide. With the highest recurrence rate among all cancers, treatment of BC only improved a little in the last 30 years. Available biomarkers are not sensitive enough for the diagnosis of BC, whereas the standard diagnostic method, cystoscopy, is an invasive test and expensive. Hence, seeking new biomarkers of BC is urgent and challenging. With that order, we screened the overlapped differentially expressed genes (DEGs) of GSE13507 and TCGA BLCA datasets. Subsequent protein–protein interactions network analysis recognized the hub genes among these DEGs. Further functional analysis including Gene Ontology and KEGG pathway analysis and gene set enrichment analysis were processed to investigate the role of these genes and potential underlying mechanisms in BC. Kaplan–Meier analysis and Cox hazard ratio analysis were carried out to clarify the diagnostic and prognostic role of these genes. In conclusion, our present study demonstrated that ACTA2, CDC20, MYH11, TGFB3, TPM1, VIM, and DCN are all potential diagnostic biomarkers for BC. And may also be potential treatment targets for clinical implication in the future.     

Potassium channel gene associations with joint processing speed and white matter impairments in schizophrenia

Patients with schizophrenia show decreased processing speed on neuropsychological testing and decreased white matter integrity as measured by diffusion tensor imaging, two traits shown to be both heritable and genetically associated indicating that there may be genes that influence both traits as well as schizophrenia disease risk. The potassium channel gene family is a reasonable candidate to harbor such a gene given the prominent role potassium channels play in the central nervous system in signal transduction, particularly in myelinated axons. We genotyped members of the large potassium channel gene family focusing on putatively functional single nucleotide polymorphisms (SNPs) in a population of 363 controls, 194 patients with schizophrenia spectrum disorder (SSD) and 28 patients with affective disorders with psychotic features who completed imaging and neuropsychological testing. We then performed three association analyses using three phenotypes – processing speed, whole‐brain white matter fractional anisotropy (FA) and schizophrenia spectrum diagnosis. We extracted SNPs showing an association at a nominal P value of <0.05 with all three phenotypes in the expected direction: decreased processing speed, decreased FA and increased risk of SSD. A single SNP, rs8234, in the 3′ untranslated region of voltage‐gated potassium channel subfamily Q member 1 (KCNQ1) was identified. Rs8234 has been shown to affect KCNQ1 expression levels, and KCNQ1 levels have been shown to affect neuronal action potentials. This exploratory analysis provides preliminary data suggesting that KCNQ1 may contribute to the shared risk for diminished processing speed, diminished white mater integrity and increased risk of schizophrenia.     

Evolutionary Relationship of the Ligand-Gated Ion Channels and the Avermectin-Sensitive,Glutamate-Gated Chloride Channels

Two cDNAs, GluClα and GluClβ, encoding glutamate-gated chloride channel subunits that represent targets of the avermectin class of antiparasitic compounds, have recently been cloned from Caenorhabditis elegans (Cully et al., Nature, 371, 707–711, 1994). Expression studies in Xenopus oocytes showed that GluClα and GluClβ have pharmacological profiles distinct from the glutamate-gated cation channels as well as the γ-aminobutyric acid (GABA)- and glycine-gated chloride channels. Establishing the evolutionary relationship of related proteins can clarify properties and lead to predictions about their structure and function. We have cloned and determined the nucleotide sequence of the GluClα and GluClβ genes. In an attempt to understand the evolutionary relationship of these channels with the members of the ligand-gated ion channel superfamily, we have performed gene structure comparisons and phylogenetic analyses of their nucleotide and predicted amino acid sequences. Gene structure comparisons reveal the presence of several intron positions that are not found in the ligand-gated ion channel superfamily, outlining their distinct evolutionary position. Phylogenetic analyses indicate that GluClα and GluClβ form a monophyletic subbranch in the ligand-gated ion channel superfamily and are related to vertebrate glycine channels/receptors. Glutamate-gated chloride channels, with electrophysiological properties similar to GluClα and GluClβ, have been described in insects and crustaceans, suggesting that the glutamate-gated chloride channel family may be conserved in other invertebrate species. The gene structure and phylogenetic analyses in combination with the distinct pharmacological properties demonstrate that GluClα and GluClβ belong to a discrete ligand-gated ion channel family that may represent genes orthologous to the vertebrate glycine channels. Received: 30 September 1996 / Accepted: 15 November 1996     

Genome‐wide association studies of alcohol dependence,DSM‐IV criterion count and individual criteria

Genome‐wide association studies (GWAS) of alcohol dependence (AD) have reliably identified variation within alcohol metabolizing genes (eg, ADH1B) but have inconsistently located other signals, which may be partially attributable to symptom heterogeneity underlying the disorder. We conducted GWAS of DSM‐IV AD (primary analysis), DSM‐IV AD criterion count (secondary analysis), and individual dependence criteria (tertiary analysis) among 7418 (1121 families) European American (EA) individuals from the Collaborative Study on the Genetics of Alcoholism (COGA). Trans‐ancestral meta‐analyses combined these results with data from 3175 (585 families) African‐American (AA) individuals from COGA. In the EA GWAS, three loci were genome‐wide significant: rs1229984 in ADH1B for AD criterion count (P = 4.16E?11) and Desire to cut drinking (P = 1.21E?11); rs188227250 (chromosome 8, Drinking more than intended, P = 6.72E?09); rs1912461 (chromosome 15, Time spent drinking, P = 1.77E?08). In the trans‐ancestral meta‐analysis, rs1229984 was associated with multiple phenotypes and two additional loci were genome‐wide significant: rs61826952 (chromosome 1, DSM‐IV AD, P = 8.42E?11); rs7597960 (chromosome 2, Time spent drinking, P = 1.22E?08). Associations with rs1229984 and rs18822750 were replicated in independent datasets. Polygenic risk scores derived from the EA GWAS of AD predicted AD in two EA datasets (P < .01; 0.61%‐1.82% of variance). Identified novel variants (ie, rs1912461, rs61826952) were associated with differential central evoked theta power (loss ? gain; P = .0037) and reward‐related ventral striatum reactivity (P = .008), respectively. This study suggests that studying individual criteria may unveil new insights into the genetic etiology of AD liability.     

Regiospecificity of Human Cytochrome P450 1A1-Mediated Oxidations: The Role of Steric Effects

Abstract

Cytochrome P450 1A1 oxidizes a diverse range of substrates, including the procarcinogenic xenobiotic benzo[a]pyrene (B[a]P) and endogenous fatty acid precursors of prostaglandins, such as arachidonic acid (AA) and eicosapentaenoic acid (EA). We have investigated the extent to which enzyme-substrate interactions govern regio- and stereoselectivity of oxidation of these compounds by using docking and molecular dynamics (MD) simulations to examine the likelihood of substrate oxidation at various sites. Due to structural differences between the substrates analyzed, B[a]P and its diols (planar, rigid), and the fatty acids AA and EA (long, flexible), different docking strategies were required. B[a]P, B[a]P-7,8-diols, (+) 7S,85- and (-) 7R,8R-diols, were docked into the active site of a homology model of P450 1A1 using an automated routine. Affinity (Accelrys, San Diego, CA). AA and EA, on the other hand, required a series of restrained MD simulations to obtain a variety of productive binding modes. All complexes were evaluated by MD-based in silico site scoring to predict product profiles based on certain geometric criteria, such as angle and distance of a given substrate atom from the ferryl oxygen. For all substrates studied, the in vitro profiles were generally reflected by the in silico scores, which suggests that steric factors play a key role in determining regiospecificity in P450 1A1-mediated oxidations. We have also shown that molecular dynamics simulations may be very useful in determination of product profiles for structurally diverse substrates of P450 enzymes.     

DTNBP1 (Dystrobrevin binding protein 1) and schizophrenia: association evidence in the 3' end of the gene

OBJECTIVES: Dysbindin (DTNBP1) has been identified as a susceptibility gene for schizophrenia (SZ) through a positional approach. However, a variety of single nucleotide polymorphisms (SNPs) and haplotypes, in different parts of the gene, have been reported to be associated in different samples, and a precise molecular mechanism of disease remains to be defined. We have performed an association study with two well-characterized family samples not previously investigated at the DTNBP1 locus. METHODS: We examined 646 subjects in 136 families with SZ, largely of European ancestry (EA), genotyping 26 SNPs in DTNBP1. RESULTS: Three correlated markers (rs875462, rs760666, and rs7758659) at the 3' region of DTNBP1 showed evidence for association to SZ (p = 0.004), observed in both the EA (p = 0.031) and the African American (AA) subset (p = 0.045) with the same over-transmitted allele. The most significant haplotype in our study was rs7758659-rs3213207 (global p = 0.0015), with rs3213207 being the most frequently reported associated marker in previous studies. A non-conservative missense variant (Pro272Ser) in the 3' region of DTNBP1 that may impair DTNBP1 function was more common in SZ probands (8.2%) than in founders (5%) and in dbSNP (2.1%), but did not reach statistical significance. CONCLUSION: Our results provide evidence for an association of SZ with SNPs at the 3' end of DTNBP1 in the samples studied.     

EA15, MIR22, LINC00472 as diagnostic markers for diabetic kidney disease

This study aimed to investigate the molecular mechanisms of diabetic kidney disease (DKD) and to explore new potential therapeutic strategies and biomarkers for DKD. First we analyzed the differentially expressed changes between patients with DKD and the control group using the chip data in Gene Expression Omnibus (GEO) database. Then the gene chip was subjected to be annotated again, so as to screen long noncoding RNAs (lncRNAs) and study expression differences of these lncRNAs in DKD and controlled samples. At last, the function of the differential lncRNAs was analyzed. A total of 252 lncRNAs were identified, and 14 were differentially expressed. In addition, there were 1,629 differentially expressed messenger RNAs (mRNAs) genes, and proliferation and apoptosis adapter protein 15 (PEA15), MIR22, and long intergenic nonprotein coding RNA 472 ( LINC00472) were significantly differentially expressed in DKD samples. Through functional analysis of the encoding genes coexpressed by the three lncRNAs, we found these genes were mainly enriched in type 1 diabetes and autoimmune thyroid disease pathways, whereas in Gene Ontology (GO) function classification, they were also mainly enriched in the immune response, type I interferon signaling pathways, interferon-γ mediated signaling pathways, and so forth. To summary, we identified EA15, MIR22, and LINC00472 may serve as the potential diagnostic markers of DKD.     

Evaluation of habitat suitability index models by global sensitivity and uncertainty analyses: a case study for submerged aquatic vegetation

Habitat suitability index (HSI) models are commonly used to predict habitat quality and species distributions and are used to develop biological surveys, assess reserve and management priorities, and anticipate possible change under different management or climate change scenarios. Important management decisions may be based on model results, often without a clear understanding of the level of uncertainty associated with model outputs. We present an integrated methodology to assess the propagation of uncertainty from both inputs and structure of the HSI models on model outputs (uncertainty analysis: UA) and relative importance of uncertain model inputs and their interactions on the model output uncertainty (global sensitivity analysis: GSA). We illustrate the GSA/UA framework using simulated hydrology input data from a hydrodynamic model representing sea level changes and HSI models for two species of submerged aquatic vegetation (SAV) in southwest Everglades National Park: Vallisneria americana (tape grass) and Halodule wrightii (shoal grass). We found considerable spatial variation in uncertainty for both species, but distributions of HSI scores still allowed discrimination of sites with good versus poor conditions. Ranking of input parameter sensitivities also varied spatially for both species, with high habitat quality sites showing higher sensitivity to different parameters than low‐quality sites. HSI models may be especially useful when species distribution data are unavailable, providing means of exploiting widely available environmental datasets to model past, current, and future habitat conditions. The GSA/UA approach provides a general method for better understanding HSI model dynamics, the spatial and temporal variation in uncertainties, and the parameters that contribute most to model uncertainty. Including an uncertainty and sensitivity analysis in modeling efforts as part of the decision‐making framework will result in better‐informed, more robust decisions.     

Voltage-Gated Potassium Channel Genes Are Clustered in Paralogous Regions of the Mouse Genome

Cloning of the Drosophila Shaker gene established that a neurological phenotype including locomotor dysfunction can be caused by a mutation in a voltage-gated potassium (K) channel gene. Shaker sequences have been used to isolate a large family of related K channel genes from both flies and mammals. Toward elucidating the evolutionary relationship between loci and the potential causal connection that K channels may have to mammalian genetic disorders, we report here the genetic mapping of 12-16 different murine, voltage-gated K channel genes. We find that multiple genes, in some cases from distantly related K channel subfamilies, occur in clusters in the mouse genome. These mapping results suggest that the K channel gene subfamilies arose through ancient localized gene duplication events, followed by chromosomal duplications and rearrangements as well as further gene duplication. We also note that several neurologic disorders of both mouse and human are associated with the chromosomal regions containing K channel genes.