Search

Adverse drug reactions (ADRs) pose critical public health issues, affecting over 6% of hospitalized patients. While knowledge of potential drug-drug interactions (DDI) is necessary to prevent ADR, the rapid pace of drug discovery makes it challenging to maintain a strong insight into DDIs. In this study, we present a novel literature-mining framework for enhancing the predictions of DDIs and ADR types by integrating drug-gene interactions (DGIs). The ADR types were adapted from a DDI corpus, including i) adverse effect; ii) effect at molecular level; iii) effect related to pharmacokinetics; and iv) DDIs without known ADRs. By using random forest classifier our approach achieves an F-score of 0.87 across the ADRs classification using only the DDI features. We then enhanced the performance of the classifier by including DGIs (F-score = 0.90), and applied the classification model trained with the DDI corpus to identify the drugs that might interact with the drugs for cutaneous diseases. We successfully predict previously known ADRs for drugs prescribed to cutaneous diseases, and are also able to identify promising new ADRs.

Psoriasis is a complex disease of skin with a prevalence of about 2%. We conducted the largest meta-analysis of genome-wide association studies (GWAS) for psoriasis to date, including data from eight different Caucasian cohorts, with a combined effective sample size >39,000 individuals. We identified 16 additional psoriasis susceptibility loci achieving genome-wide significance, increasing the number of identified loci to 63 for European-origin individuals. Functional analysis highlighted the roles of interferon signalling and the NFκB cascade, and we showed that the psoriasis signals are enriched in regulatory elements from different T cells (CD8 + T-cells and CD4 + T-cells including T H 0, T H 1 and T H 17). The identified loci explain ∼28% of the genetic heritability and generate a discriminatory genetic risk score (AUC=0.76 in our sample) that is significantly correlated with age at onset (p=2 × 10 -89 ). This study provides a comprehensive layout for the genetic architecture of common variants for psoriasis.

In the 3 decades since the discovery of the polymerase chain reaction, a progression of remarkable technical advances has driven great strides in our understanding of molecular biology such that now we are able to study at once the entire and complete set of RNA transcripts that are produced by the genome. In this review, we describe the milestones that have led to this era of global transcriptional analysis, how these approaches have been extended towards skin disease, and their future directions., (Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.)

Transcription factor binding, chromatin modifications and large scale chromatin re-organization underlie progressive, irreversible cell lineage commitments and differentiation. We know little, however, about chromatin changes as cells enter transient, reversible states such as migration. Here we demonstrate that when human progenitor keratinocytes either differentiate or migrate they form complements of typical enhancers and super-enhancers that are unique for each state. Unique super-enhancers for each cellular state link to gene expression that confers functions associated with the respective cell state. These super-enhancers are also enriched for skin disease sequence variants. GRHL3, a transcription factor that promotes both differentiation and migration, binds preferentially to super-enhancers in differentiating keratinocytes, while during migration, it binds preferentially to promoters along with REST, repressing the expression of migration inhibitors. Key epidermal differentiation transcription factor genes, including GRHL3, are located within super-enhancers, and many of these transcription factors in turn bind to and regulate super-enhancers. Furthermore, GRHL3 represses the formation of a number of progenitor and non-keratinocyte super-enhancers in differentiating keratinocytes. Hence, chromatin relocates GRHL3 binding and enhancers to regulate both the irreversible commitment of progenitor keratinocytes to differentiation and their reversible transition to migration.

Autoimmune diseases affect 7.5% of the US population, and they are among the leading causes of death and disability. A notable feature of many autoimmune diseases is their greater prevalence in females than in males, but the underlying mechanisms of this have remained unclear. Through the use of high-resolution global transcriptome analyses, we demonstrated a female-biased molecular signature associated with susceptibility to autoimmune disease and linked this to extensive sex-dependent co-expression networks. This signature was independent of biological age and sex-hormone regulation and was regulated by the transcription factor VGLL3, which also had a strong female-biased expression. On a genome-wide level, VGLL3-regulated genes had a strong association with multiple autoimmune diseases, including lupus, scleroderma and Sjögren's syndrome, and had a prominent transcriptomic overlap with inflammatory processes in cutaneous lupus. These results identified a VGLL3-regulated network as a previously unknown inflammatory pathway that promotes female-biased autoimmunity. They demonstrate the importance of studying immunological processes in females and males separately and suggest new avenues for therapeutic development., Competing Interests: Competing Financial Interests. The authors declare no competing financial interests.

In the past decade, high-throughput techniques have facilitated the "-omics" research. Transcriptomic study, for instance, has advanced our understanding on the expression landscape of different human diseases and cellular mechanisms. The National Center for Biotechnology Center (NCBI) initialized Genetic Expression Omnibus (GEO) to promote the sharing of transcriptomic data to facilitate biomedical research. In this chapter, we will illustrate how to use GEO to search and analyze the public available transcriptomic data, and we will provide easy to follow protocol for researchers to data mine the powerful resources in GEO to retrieve relevant information that can be valuable for fibrosis research.

In the past decade, the volume of "omics" data generated by the different high-throughput technologies has expanded exponentially. The managing, storing, and analyzing of this big data have been a great challenge for the researchers, especially when moving towards the goal of generating testable data-driven hypotheses, which has been the promise of the high-throughput experimental techniques. Different bioinformatics approaches have been developed to streamline the downstream analyzes by providing independent information to interpret and provide biological inference. Text mining (also known as literature mining) is one of the commonly used approaches for automated generation of biological knowledge from the huge number of published articles. In this review paper, we discuss the recent advancement in approaches that integrate results from omics data and information generated from text mining approaches to uncover novel biomedical information., Competing Interests: The authors declare that there is no conflict of interests regarding the publication of this paper.

Background: Psoriasis is a chronic inflammatory skin disease characterized by epidermal hyperproliferation and altered keratinocyte differentiation and inflammation and is caused by the interplay of genetic and environmental factors. Previous studies have revealed that DNA methylation (DNAm) and genetic makers are closely associated with psoriasis, and strong evidences have shown that DNAm can be controlled by genetic factors, which attracted us to evaluate the relationship among DNAm, genetic makers, and disease status., Methods: We utilized the genome-wide methylation data of psoriatic skin (PP, N  = 114) and unaffected control skin (NN, N  = 62) tissue samples in our previous study, and we performed whole-genome genotyping with peripheral blood of the same samples to evaluate the underlying genetic effect on skin DNA methylation. Causal inference test (CIT) was used to assess whether DNAm regulate genetic variation and gain a better understanding of the epigenetic basis of psoriasis susceptibility., Results: We identified 129 SNP-CpG pairs achieving the significant association threshold, which constituted 28 unique methylation quantitative trait loci (MethQTL) and 34 unique CpGs. There are 18 SNPs were associated with psoriasis at a Bonferoni-corrected P  < 0.05, and these 18 SNPs formed 93 SNP-CpG pairs with 17 unique CpG sites. We found that 11 of 93 SNP-CpG pairs, composed of 5 unique SNPs and 3 CpG sites, presented a methylation-mediated relationship between SNPs and psoriasis. The 3 CpG sites were located on the body of C1orf106 , the TSS1500 promoter region of DMBX1 and the body of SIK3 ., Conclusions: This study revealed that DNAm of some genes can be controlled by genetic factors and also mediate risk variation for psoriasis in Chinese Han population and provided novel molecular insights into the pathogenesis of psoriasis.

Background: C-reactive protein (CRP) is associated with immune, cardiometabolic, and psychiatric traits and diseases. Yet it is inconclusive whether these associations are causal., Methods and Findings: We performed Mendelian randomization (MR) analyses using two genetic risk scores (GRSs) as instrumental variables (IVs). The first GRS consisted of four single nucleotide polymorphisms (SNPs) in the CRP gene (GRSCRP), and the second consisted of 18 SNPs that were significantly associated with CRP levels in the largest genome-wide association study (GWAS) to date (GRSGWAS). To optimize power, we used summary statistics from GWAS consortia and tested the association of these two GRSs with 32 complex somatic and psychiatric outcomes, with up to 123,865 participants per outcome from populations of European ancestry. We performed heterogeneity tests to disentangle the pleiotropic effect of IVs. A Bonferroni-corrected significance level of less than 0.0016 was considered statistically significant. An observed p-value equal to or less than 0.05 was considered nominally significant evidence for a potential causal association, yet to be confirmed. The strengths (F-statistics) of the IVs were 31.92-3,761.29 and 82.32-9,403.21 for GRSCRP and GRSGWAS, respectively. CRP GRSGWAS showed a statistically significant protective relationship of a 10% genetically elevated CRP level with the risk of schizophrenia (odds ratio [OR] 0.86 [95% CI 0.79-0.94]; p < 0.001). We validated this finding with individual-level genotype data from the schizophrenia GWAS (OR 0.96 [95% CI 0.94-0.98]; p < 1.72 × 10-6). Further, we found that a standardized CRP polygenic risk score (CRPPRS) at p-value thresholds of 1 × 10-4, 0.001, 0.01, 0.05, and 0.1 using individual-level data also showed a protective effect (OR < 1.00) against schizophrenia; the first CRPPRS (built of SNPs with p < 1 × 10-4) showed a statistically significant (p < 2.45 × 10-4) protective effect with an OR of 0.97 (95% CI 0.95-0.99). The CRP GRSGWAS showed that a 10% increase in genetically determined CRP level was significantly associated with coronary artery disease (OR 0.88 [95% CI 0.84-0.94]; p < 2.4 × 10-5) and was nominally associated with the risk of inflammatory bowel disease (OR 0.85 [95% CI 0.74-0.98]; p < 0.03), Crohn disease (OR 0.81 [95% CI 0.70-0.94]; p < 0.005), psoriatic arthritis (OR 1.36 [95% CI 1.00-1.84]; p < 0.049), knee osteoarthritis (OR 1.17 [95% CI 1.01-1.36]; p < 0.04), and bipolar disorder (OR 1.21 [95% CI 1.05-1.40]; p < 0.007) and with an increase of 0.72 (95% CI 0.11-1.34; p < 0.02) mm Hg in systolic blood pressure, 0.45 (95% CI 0.06-0.84; p < 0.02) mm Hg in diastolic blood pressure, 0.01 ml/min/1.73 m2 (95% CI 0.003-0.02; p < 0.005) in estimated glomerular filtration rate from serum creatinine, 0.01 g/dl (95% CI 0.0004-0.02; p < 0.04) in serum albumin level, and 0.03 g/dl (95% CI 0.008-0.05; p < 0.009) in serum protein level. However, after adjustment for heterogeneity, neither GRS showed a significant effect of CRP level (at p < 0.0016) on any of these outcomes, including coronary artery disease, nor on the other 20 complex outcomes studied. Our study has two potential limitations: the limited variance explained by our genetic instruments modeling CRP levels in blood and the unobserved bias introduced by the use of summary statistics in our MR analyses., Conclusions: Genetically elevated CRP levels showed a significant potentially protective causal relationship with risk of schizophrenia. We observed nominal evidence at an observed p < 0.05 using either GRSCRP or GRSGWAS-with persistence after correction for heterogeneity-for a causal relationship of elevated CRP levels with psoriatic osteoarthritis, rheumatoid arthritis, knee osteoarthritis, systolic blood pressure, diastolic blood pressure, serum albumin, and bipolar disorder. These associations remain yet to be confirmed. We cannot verify any causal effect of CRP level on any of the other common somatic and neuropsychiatric outcomes investigated in the present study. This implies that interventions that lower CRP level are unlikely to result in decreased risk for the majority of common complex outcomes.

Epidermal growth factor receptor (EGFR) is central to epithelial cell physiology, and deregulated EGFR signaling has an important role in a variety of human carcinomas. Here we show that silencing of the EGF-related factor amphiregulin (AREG) markedly inhibits the expansion of human keratinocytes through mitotic failure and accumulation of cells with ⩾ 4n DNA content. RNA-sequencing-based transcriptome analysis revealed that tetracycline-mediated AREG silencing significantly altered the expression of 2331 genes, 623 of which were not normalized by treatment with EGF. Interestingly, genes irreversibly upregulated by suppression of AREG overlapped with genes involved in keratinocyte differentiation. Moreover, a significant proportion of the irreversibly downregulated genes featured upstream binding sites recognized by forkhead box protein M1 (FoxM1), a key transcription factor in the control of mitosis that is widely dysregulated in cancer. The downregulation of FoxM1 and its target genes preceded mitotic arrest. Constitutive expression of FoxM1 in AREG knockdown cells normalized cell proliferation, reduced the number of cells with ⩾ 4n DNA content and rescued expression of FoxM1 target genes. These results demonstrate that AREG controls G2/M progression and cytokinesis in keratinocytes via activation of a FoxM1-dependent transcriptional program, suggesting new avenues for treatment of epithelial cancer.

Psoriasis vulgaris (PsV) is a common inflammatory and hyperproliferative skin disease. Up to 30% of people with PsV eventually develop psoriatic arthritis (PsA), an inflammatory musculoskeletal condition. To discern differences in genetic risk factors for PsA and cutaneous-only psoriasis (PsC), we carried out a genome-wide association study (GWAS) of 1,430 PsA case subjects and 1,417 unaffected control subjects. Meta-analysis of this study with three other GWASs and two targeted genotyping studies, encompassing a total of 9,293 PsV case subjects, 3,061 PsA case subjects, 3,110 PsC case subjects, and 13,670 unaffected control subjects of European descent, detected 10 regions associated with PsA and 11 with PsC at genome-wide (GW) significance. Several of these association signals (IFNLR1, IFIH1, NFKBIA for PsA; TNFRSF9, LCE3C/B, TRAF3IP2, IL23A, NFKBIA for PsC) have not previously achieved GW significance. After replication, we also identified a PsV-associated SNP near CDKAL1 (rs4712528, odds ratio [OR] = 1.16, p = 8.4 × 10(-11)). Among identified psoriasis risk variants, three were more strongly associated with PsC than PsA (rs12189871 near HLA-C, p = 5.0 × 10(-19); rs4908742 near TNFRSF9, p = 0.00020; rs10888503 near LCE3A, p = 0.0014), and two were more strongly associated with PsA than PsC (rs12044149 near IL23R, p = 0.00018; rs9321623 near TNFAIP3, p = 0.00022). The PsA-specific variants were independent of previously identified psoriasis variants near IL23R and TNFAIP3. We also found multiple independent susceptibility variants in the IL12B, NOS2, and IFIH1 regions. These results provide insights into the pathogenetic similarities and differences between PsC and PsA., (Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Human leukocyte antigen (HLA) genes confer substantial risk for autoimmune diseases on a log-additive scale. Here we speculated that differences in autoantigen-binding repertoires between a heterozygote's two expressed HLA variants might result in additional non-additive risk effects. We tested the non-additive disease contributions of classical HLA alleles in patients and matched controls for five common autoimmune diseases: rheumatoid arthritis (ncases = 5,337), type 1 diabetes (T1D; ncases = 5,567), psoriasis vulgaris (ncases = 3,089), idiopathic achalasia (ncases = 727) and celiac disease (ncases = 11,115). In four of the five diseases, we observed highly significant, non-additive dominance effects (rheumatoid arthritis, P = 2.5 × 10(-12); T1D, P = 2.4 × 10(-10); psoriasis, P = 5.9 × 10(-6); celiac disease, P = 1.2 × 10(-87)). In three of these diseases, the non-additive dominance effects were explained by interactions between specific classical HLA alleles (rheumatoid arthritis, P = 1.8 × 10(-3); T1D, P = 8.6 × 10(-27); celiac disease, P = 6.0 × 10(-100)). These interactions generally increased disease risk and explained moderate but significant fractions of phenotypic variance (rheumatoid arthritis, 1.4%; T1D, 4.0%; celiac disease, 4.1%) beyond a simple additive model.

DNA sequencing identifies common and rare genetic variants for association studies, but studies typically focus on variants in nuclear DNA and ignore the mitochondrial genome. In fact, analyzing variants in mitochondrial DNA (mtDNA) sequences presents special problems, which we resolve here with a general solution for the analysis of mtDNA in next-generation sequencing studies. The new program package comprises 1) an algorithm designed to identify mtDNA variants (i.e., homoplasmies and heteroplasmies), incorporating sequencing error rates at each base in a likelihood calculation and allowing allele fractions at a variant site to differ across individuals; and 2) an estimation of mtDNA copy number in a cell directly from whole-genome sequencing data. We also apply the methods to DNA sequence from lymphocytes of ~2,000 SardiNIA Project participants. As expected, mothers and offspring share all homoplasmies but a lesser proportion of heteroplasmies. Both homoplasmies and heteroplasmies show 5-fold higher transition/transversion ratios than variants in nuclear DNA. Also, heteroplasmy increases with age, though on average only ~1 heteroplasmy reaches the 4% level between ages 20 and 90. In addition, we find that mtDNA copy number averages ~110 copies/lymphocyte and is ~54% heritable, implying substantial genetic regulation of the level of mtDNA. Copy numbers also decrease modestly but significantly with age, and females on average have significantly more copies than males. The mtDNA copy numbers are significantly associated with waist circumference (p-value = 0.0031) and waist-hip ratio (p-value = 2.4×10-5), but not with body mass index, indicating an association with central fat distribution. To our knowledge, this is the largest population analysis to date of mtDNA dynamics, revealing the age-imposed increase in heteroplasmy, the relatively high heritability of copy number, and the association of copy number with metabolic traits.

Previous studies have identified 41 independent genome-wide significant psoriasis susceptibility loci. After our first psoriasis genome-wide association study, we designed a custom genotyping array to fine-map eight genome-wide significant susceptibility loci known at that time (IL23R, IL13, IL12B, TNIP1, MHC, TNFAIP3, IL23A and RNF114) enabling genotyping of 2269 single-nucleotide polymorphisms (SNPs) in the eight loci for 2699 psoriasis cases and 2107 unaffected controls of European ancestry. We imputed these data using the latest 1000 Genome reference haplotypes, which included both indels and SNPs, to increase the marker density of the eight loci to 49 239 genetic variants. Using stepwise conditional association analysis, we identified nine independent signals distributed across six of the eight loci. In the major histocompatibility complex (MHC) region, we detected three independent signals at rs114255771 (P = 2.94 × 10(-74)), rs6924962 (P = 3.21 × 10(-19)) and rs892666 (P = 1.11 × 10(-10)). Near IL12B we detected two independent signals at rs62377586 (P = 7.42 × 10(-16)) and rs918518 (P = 3.22 × 10(-11)). Only one signal was observed in each of the TNIP1 (rs17728338; P = 4.15 × 10(-13)), IL13 (rs1295685; P = 1.65 × 10(-7)), IL23A (rs61937678; P = 1.82 × 10(-7)) and TNFAIP3 (rs642627; P = 5.90 × 10(-7)) regions. We also imputed variants for eight HLA genes and found that SNP rs114255771 yielded a more significant association than any HLA allele or amino-acid residue. Further analysis revealed that the HLA-C*06-B*57 haplotype tagged by this SNP had a significantly higher odds ratio than other HLA-C*06-bearing haplotypes. The results demonstrate allelic heterogeneity at IL12B and identify a high-risk MHC class I haplotype, consistent with the existence of multiple psoriasis effectors in the MHC.

Psoriasis is a chronic autoimmune disease with complex genetic architecture. Previous genome-wide association studies (GWAS) and a recent meta-analysis using Immunochip data have uncovered 36 susceptibility loci. Here, we extend our previous meta-analysis of European ancestry by refined genotype calling and imputation and by the addition of 5,033 cases and 5,707 controls. The combined analysis, consisting of over 15,000 cases and 27,000 controls, identifies five new psoriasis susceptibility loci at genome-wide significance (P<5 × 10(-8)). The newly identified signals include two that reside in intergenic regions (1q31.1 and 5p13.1) and three residing near PLCL2 (3p24.3), NFKBIZ (3q12.3) and CAMK2G (10q22.2). We further demonstrate that NFKBIZ is a TRAF3IP2-dependent target of IL-17 signalling in human skin keratinocytes, thereby functionally linking two strong candidate genes. These results further integrate the genetics and immunology of psoriasis, suggesting new avenues for functional analysis and improved therapies.

Psoriasis has been linked to cardiometabolic diseases, but epidemiological findings are inconsistent. We investigated the association between psoriasis and cardiometabolic outcomes in a German cross-sectional study (n=4,185) and a prospective cohort of German Health Insurance beneficiaries (n=1,811,098). A potential genetic overlap was explored using genome-wide data from >22,000 coronary artery disease and >4,000 psoriasis cases, and with a dense genotyping study of cardiometabolic risk loci on 927 psoriasis cases and 3,717 controls. After controlling for major confounders, in the cross-sectional analysis psoriasis was significantly associated with type 2 diabetes (T2D, adjusted odds ratio (OR)=2.36; 95% confidence interval CI=1.26-4.41) and myocardial infarction (MI, OR=2.26; 95% CI=1.03-4.96). In the longitudinal study, psoriasis slightly increased the risk for incident T2D (adjusted relative risk (RR)=1.11; 95% CI=1.08-1.14) and MI (RR=1.14; 95% CI=1.06-1.22), with highest risk increments in systemically treated psoriasis, which accounted for 11 and 17 excess cases of T2D and MI per 10,000 person-years. Except for weak signals from within the major histocompatibility complex, there was no evidence of genetic risk loci shared between psoriasis and cardiometabolic traits. Our findings suggest that psoriasis, in particular severe psoriasis, increases the risk for T2D and MI, and that the genetic architecture of psoriasis and cardiometabolic traits is largely distinct.

Motivation: Pathway analysis to reveal biological mechanisms for results from genetic association studies have great potential to better understand complex traits with major human disease impact. However, current approaches have not been optimized to maximize statistical power to identify enriched functions/pathways, especially when the genetic data derives from studies using platforms (e.g. Immunochip and Metabochip) customized to have pre-selected markers from previously identified top-rank loci. We present here a novel approach, called Minimum distance-based Enrichment Analysis for Genetic Association (MEAGA), with the potential to address both of these important concerns., Results: MEAGA performs enrichment analysis using graphical algorithms to identify sub-graphs among genes and measure their closeness in interaction database. It also incorporates a statistic summarizing the numbers and total distances of the sub-graphs, depicting the overlap between observed genetic signals and defined function/pathway gene-sets. MEAGA uses sampling technique to approximate empirical and multiple testing-corrected P-values. We show in simulation studies that MEAGA is more powerful compared to count-based strategies in identifying disease-associated functions/pathways, and the increase in power is influenced by the shortest distances among associated genes in the interactome. We applied MEAGA to the results of a meta-analysis of psoriasis using Immunochip datasets, and showed that associated genes are significantly enriched in immune-related functions and closer with each other in the protein-protein interaction network., Availability and Implementation: http://genome.sph.umich.edu/wiki/MEAGA CONTACT: : tsoi.teen@gmail.com or goncalo@umich.edu, Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Background: Although analysis pipelines have been developed to use RNA-seq to identify long non-coding RNAs (lncRNAs), inference of their biological and pathological relevance remains a challenge. As a result, most transcriptome studies of autoimmune disease have only assessed protein-coding transcripts., Results: We used RNA-seq data from 99 lesional psoriatic, 27 uninvolved psoriatic, and 90 normal skin biopsies, and applied computational approaches to identify and characterize expressed lncRNAs. We detect 2,942 previously annotated and 1,080 novel lncRNAs which are expected to be skin specific. Notably, over 40% of the novel lncRNAs are differentially expressed and the proportions of differentially expressed transcripts among protein-coding mRNAs and previously-annotated lncRNAs are lower in psoriasis lesions versus uninvolved or normal skin. We find that many lncRNAs, in particular those that are differentially expressed, are co-expressed with genes involved in immune related functions, and that novel lncRNAs are enriched for localization in the epidermal differentiation complex. We also identify distinct tissue-specific expression patterns and epigenetic profiles for novel lncRNAs, some of which are shown to be regulated by cytokine treatment in cultured human keratinocytes., Conclusions: Together, our results implicate many lncRNAs in the immunopathogenesis of psoriasis, and our results provide a resource for lncRNA studies in other autoimmune diseases.

Atopic dermatitis and psoriasis are the two most common immune-mediated inflammatory disorders affecting the skin. Genome-wide studies demonstrate a high degree of genetic overlap, but these diseases have mutually exclusive clinical phenotypes and opposing immune mechanisms. Despite their prevalence, atopic dermatitis and psoriasis very rarely co-occur within one individual. By utilizing genome-wide association study and ImmunoChip data from >19,000 individuals and methodologies developed from meta-analysis, we have identified opposing risk alleles at shared loci as well as independent disease-specific loci within the epidermal differentiation complex (chromosome 1q21.3), the Th2 locus control region (chromosome 5q31.1), and the major histocompatibility complex (chromosome 6p21-22). We further identified previously unreported pleiotropic alleles with opposing effects on atopic dermatitis and psoriasis risk in PRKRA and ANXA6/TNIP1. In contrast, there was no evidence for shared loci with effects operating in the same direction on both diseases. Our results show that atopic dermatitis and psoriasis have distinct genetic mechanisms with opposing effects in shared pathways influencing epidermal differentiation and immune response. The statistical analysis methods developed in the conduct of this study have produced additional insight from previously published data sets. The approach is likely to be applicable to the investigation of the genetic basis of other complex traits with overlapping and distinct clinical features., (Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.)

To enhance our knowledge regarding biological pathway regulation, we took an integrated approach, using the biomedical literature, ontologies, network analyses and experimental investigation to infer novel genes that could modulate biological pathways. We first constructed a novel gene network via a pairwise comparison of all yeast genes' Ontology Fingerprints--a set of Gene Ontology terms overrepresented in the PubMed abstracts linked to a gene along with those terms' corresponding enrichment P-values. The network was further refined using a Bayesian hierarchical model to identify novel genes that could potentially influence the pathway activities. We applied this method to the sphingolipid pathway in yeast and found that many top-ranked genes indeed displayed altered sphingolipid pathway functions, initially measured by their sensitivity to myriocin, an inhibitor of de novo sphingolipid biosynthesis. Further experiments confirmed the modulation of the sphingolipid pathway by one of these genes, PFA4, encoding a palmitoyl transferase. Comparative analysis showed that few of these novel genes could be discovered by other existing methods. Our novel gene network provides a unique and comprehensive resource to study pathway modulations and systems biology in general., (© The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Psoriasis vulgaris (PsV) risk is strongly associated with variation within the major histocompatibility complex (MHC) region, but its genetic architecture has yet to be fully elucidated. Here, we conducted a large-scale fine-mapping study of PsV risk in the MHC region in 9,247 PsV-affected individuals and 13,589 controls of European descent by imputing class I and II human leukocyte antigen (HLA) genes from SNP genotype data. In addition, we imputed sequence variants for MICA, an MHC HLA-like gene that has been associated with PsV, to evaluate association at that locus as well. We observed that HLA-C(∗)06:02 demonstrated the lowest p value for overall PsV risk (p = 1.7 × 10(-364)). Stepwise analysis revealed multiple HLA-C(∗)06:02-independent risk variants in both class I and class II HLA genes for PsV susceptibility (HLA-C(∗)12:03, HLA-B amino acid positions 67 and 9, HLA-A amino acid position 95, and HLA-DQα1 amino acid position 53; p < 5.0 × 10(-8)), but no apparent risk conferred by MICA. We further evaluated risk of two major clinical subtypes of PsV, psoriatic arthritis (PsA; n = 3,038) and cutaneous psoriasis (PsC; n = 3,098). We found that risk heterogeneity between PsA and PsC might be driven by HLA-B amino acid position 45 (Pomnibus = 2.2 × 10(-11)), indicating that different genetic factors underlie the overall risk of PsV and the risk of specific PsV subphenotypes. Our study illustrates the value of high-resolution HLA and MICA imputation for fine mapping causal variants in the MHC., (Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.)

To increase our understanding of psoriasis, we used high-throughput complementary DNA sequencing (RNA-seq) to assay the transcriptomes of lesional psoriatic and normal skin. We sequenced polyadenylated RNA-derived complementary DNAs from 92 psoriatic and 82 normal punch biopsies, generating an average of ∼38 million single-end 80-bp reads per sample. Comparison of 42 samples examined by both RNA-seq and microarray revealed marked differences in sensitivity, with transcripts identified only by RNA-seq having much lower expression than those also identified by microarray. RNA-seq identified many more differentially expressed transcripts enriched in immune system processes. Weighted gene coexpression network analysis (WGCNA) revealed multiple modules of coordinately expressed epidermal differentiation genes, overlapping significantly with genes regulated by the long noncoding RNA TINCR, its target gene, staufen-1 (STAU1), the p63 target gene ZNF750, and its target KLF4. Other coordinately expressed modules were enriched for lymphoid and/or myeloid signature transcripts and genes induced by IL-17 in keratinocytes. Dermally expressed genes were significantly downregulated in psoriatic biopsies, most likely because of expansion of the epidermal compartment. These results show the power of WGCNA to elucidate gene regulatory circuits in psoriasis, and emphasize the influence of tissue architecture in both differential expression and coexpression analysis.

Atopic dermatitis is a common inflammatory skin disease with a strong heritable component. Pathogenetic models consider keratinocyte differentiation defects and immune alterations as scaffolds, and recent data indicate a role for autoreactivity in at least a subgroup of patients. FLG (encoding filaggrin) has been identified as a major locus causing skin barrier deficiency. To better define risk variants and identify additional susceptibility loci, we densely genotyped 2,425 German individuals with atopic dermatitis (cases) and 5,449 controls using the Immunochip array followed by replication in 7,196 cases and 15,480 controls from Germany, Ireland, Japan and China. We identified four new susceptibility loci for atopic dermatitis and replicated previous associations. This brings the number of atopic dermatitis risk loci reported in individuals of European ancestry to 11. We estimate that these susceptibility loci together account for 14.4% of the heritability for atopic dermatitis.

Biased G protein-coupled receptor agonists are orthosteric ligands that possess pathway-selective efficacy, activating or inhibiting only a subset of the signaling repertoire of their cognate receptors. In vitro, D-Trp(12),Tyr(34)-bPTH(7-34) [bPTH(7-34)], a biased agonist for the type 1 PTH receptor, antagonizes receptor-G protein coupling but activates arrestin-dependent signaling. In vivo, both bPTH(7-34) and the conventional agonist hPTH(1-34) stimulate anabolic bone formation. To understand how two PTH receptor ligands with markedly different in vitro efficacy could elicit similar in vivo responses, we analyzed transcriptional profiles from calvarial bone of mice treated for 8 wk with vehicle, bPTH(7-34) or hPTH(1-34). Treatment of wild-type mice with bPTH(7-34) primarily affected pathways that promote expansion of the osteoblast pool, notably cell cycle regulation, cell survival, and migration. These responses were absent in β-arrestin2-null mice, identifying them as downstream targets of β-arrestin2-mediated signaling. In contrast, hPTH(1-34) primarily affected pathways classically associated with enhanced bone formation, including collagen synthesis and matrix mineralization. hPTH(1-34) actions were less dependent on β-arrestin2, as might be expected of a ligand capable of G protein activation. In vitro, bPTH(7-34) slowed the rate of preosteoblast proliferation, enhanced osteoblast survival when exposed to an apoptotic stimulus, and stimulated cell migration in wild-type, but not β-arrestin2-null, calvarial osteoblasts. These results suggest that bPTH(7-34) and hPTH(1-34) affect bone mass in vivo through predominantly separate genomic mechanisms created by largely distinct receptor-signaling networks and demonstrate that functional selectivity can be exploited to change the quality of G protein-coupled receptor efficacy.

To gain further insight into the genetic architecture of psoriasis, we conducted a meta-analysis of 3 genome-wide association studies (GWAS) and 2 independent data sets genotyped on the Immunochip, including 10,588 cases and 22,806 controls. We identified 15 new susceptibility loci, increasing to 36 the number associated with psoriasis in European individuals. We also identified, using conditional analyses, five independent signals within previously known loci. The newly identified loci shared with other autoimmune diseases include candidate genes with roles in regulating T-cell function (such as RUNX3, TAGAP and STAT3). Notably, they included candidate genes whose products are involved in innate host defense, including interferon-mediated antiviral responses (DDX58), macrophage activation (ZC3H12C) and nuclear factor (NF)-κB signaling (CARD14 and CARM1). These results portend a better understanding of shared and distinctive genetic determinants of immune-mediated inflammatory disorders and emphasize the importance of the skin in innate and acquired host defense.

Objectives: To determine the characteristics of asymptomatic elevated blood pressure patients in an accident and emergency setting and assess the effect of a nurse-led intervention system., Design: Cross-sectional study., Setting: Accident and Emergency Department of a regional hospital in Hong Kong., Participants: Patients with blood pressures of 140/90 mm Hg or above recorded twice (at triage and discharge) with no previous history of hypertension. Exclusion criteria were: (1) admission to hospital; (2) known hypertension; (3) referral for hypertension; (4) blood pressure higher than 180/120 mm Hg on rechecking., Intervention: Patients were issued a referral by the discharge nurse to follow-up for blood pressure monitoring in primary care., Main Outcome Measures: Diagnosis of hypertension, follow-up rate, and risk factors of hypertension., Results: Of 245 patients with asymptomatic elevated blood pressure, we were able to contact 222 for follow-up, of whom 136 (61%) claimed to have been followed up for their blood pressure, and 48 (22%) were diagnosed to have hypertension. The nurse time for finding one case was 28 minutes. The projected impact could be large. If this simple nursing guideline is implemented territory-wide, more than 7000 new cases of asymptomatic hypertension might be picked up annually., Conclusion: The implementation of a simple nurse-led hypertension referral system is a cost-effective way to screen asymptomatic subjects with elevated blood pressures in the accident and emergency department.

Psoriatic arthritis (PsA) is a chronic inflammatory musculoskeletal disease affecting up to 30% of psoriasis vulgaris (PsV) cases and approximately 0.25 to 1% of the general population. To identify common susceptibility loci, we performed a meta-analysis of three imputed genome-wide association studies (GWAS) on psoriasis, stratified for PsA. A total of 1,160,703 single-nucleotide polymorphisms (SNPs) were analyzed in the discovery set consisting of 535 PsA cases and 3,432 controls from Germany, the United States, and Canada. We followed up two SNPs in 1,931 PsA cases and 6,785 controls comprising six independent replication panels from Germany, Estonia, the United States, and Canada. In the combined analysis, a genome-wide significant association was detected at 2p16 near the REL locus encoding c-Rel (rs13017599, P=1.18 × 10(-8), odds ratio (OR)=1.27, 95% confidence interval (CI)=1.18-1.35). The rs13017599 polymorphism is known to associate with rheumatoid arthritis (RA), and another SNP near REL (rs702873) was recently implicated in PsV susceptibility. However, conditional analysis indicated that rs13017599, rather than rs702873, accounts for the PsA association at REL. We hypothesize that c-Rel, as a member of the Rel/NF-κB family, is associated with PsA in the context of disease pathways that involve other identified PsA and PsV susceptibility genes including TNIP1, TNFAIP3, and NFκBIA.

Background: Despite large amounts of available genomic and proteomic data, predicting the structure and response of signaling networks is still a significant challenge. While statistical method such as Bayesian network has been explored to meet this challenge, employing existing biological knowledge for network prediction is difficult. The objective of this study is to develop a novel approach that integrates prior biological knowledge in the form of the Ontology Fingerprint to infer cell-type-specific signaling networks via data-driven Bayesian network learning; and to further use the trained model to predict cellular responses., Results: We applied our novel approach to address the Predictive Signaling Network Modeling challenge of the fourth (2009) Dialog for Reverse Engineering Assessment's and Methods (DREAM4) competition. The challenge results showed that our method accurately captured signal transduction of a network of protein kinases and phosphoproteins in that the predicted protein phosphorylation levels under all experimental conditions were highly correlated (R2 = 0.93) with the observed results. Based on the evaluation of the DREAM4 organizer, our team was ranked as one of the top five best performers in predicting network structure and protein phosphorylation activity under test conditions., Conclusions: Bayesian network can be used to simulate the propagation of signals in cellular systems. Incorporating the Ontology Fingerprint as prior biological knowledge allows us to efficiently infer concise signaling network structure and to accurately predict cellular responses.

Background: To utilize the large volume of gene expression information generated from different microarray experiments, several meta-analysis techniques have been developed. Despite these efforts, there remain significant challenges to effectively increasing the statistical power and decreasing the Type I error rate while pooling the heterogeneous datasets from public resources. The objective of this study is to develop a novel meta-analysis approach, Consistent Differential Expression Pattern (CDEP), to identify genes with common differential expression patterns across different datasets., Results: We combined False Discovery Rate (FDR) estimation and the non-parametric RankProd approach to estimate the Type I error rate in each microarray dataset of the meta-analysis. These Type I error rates from all datasets were then used to identify genes with common differential expression patterns. Our simulation study showed that CDEP achieved higher statistical power and maintained low Type I error rate when compared with two recently proposed meta-analysis approaches. We applied CDEP to analyze microarray data from different laboratories that compared transcription profiles between metastatic and primary cancer of different types. Many genes identified as differentially expressed consistently across different cancer types are in pathways related to metastatic behavior, such as ECM-receptor interaction, focal adhesion, and blood vessel development. We also identified novel genes such as AMIGO2, Gem, and CXCL11 that have not been shown to associate with, but may play roles in, metastasis., Conclusions: CDEP is a flexible approach that borrows information from each dataset in a meta-analysis in order to identify genes being differentially expressed consistently. We have shown that CDEP can gain higher statistical power than other existing approaches under a variety of settings considered in the simulation study, suggesting its robustness and insensitivity to data variation commonly associated with microarray experiments., Availability: CDEP is implemented in R and freely available at: http://genomebioinfo.musc.edu/CDEP/., Contact: zhengw@musc.edu.

Two species of philometrid nematode, Philometra overstreeti and Philometroides paralichthydis, infect the southern flounder, Paralichthys lethostigma. Individuals of P. overstreeti are located between the teeth and inside the bony part of the branchial arches of the fish. Individuals of P. paralichthydis are associated with the bones of the buccal cavity and among muscles that control the dorsal and anal fins. Sequencing of part of the cytochrome oxidase I gene revealed 4 distinct genetic clades, each corresponding exactly to the 4 respective locations of the parasites in the host, suggesting the need for taxonomic revision. We hypothesized that each clade represented a separate species and, because the worms are morphologically indistinguishable, compared population level parameters of the clades comprising each currently recognized species. For each currently recognized species, the presence of worms from 1 clade was negatively correlated with the presence of worms from the other. Results also indicated significant differences between the clades in prevalences relative to both biotic and abiotic factors. Results clearly indicated major differences in the ecology of the philometrids constituting each clade. Taken as a whole, molecular and ecological data support the contention that the 4 genetic clades are likely 4 distinct species.

Developing ontologies to account for the complexity of biological systems requires the time intensive collaboration of many participants with expertise in various fields. While each participant may contribute to construct a list of terms for ontology development, no objective methods have been developed to evaluate how relevant each of these terms is to the intended domain. We have developed a computational method based on a hypergeometric enrichment test to evaluate the relevance of such terms to the intended domain. The proposed method uses the PubMed literature database to evaluate whether each potential term for ontology development is overrepresented in the abstracts that discuss the particular domain. This evaluation provides an objective approach to assess terms and prioritize them for ontology development.

Motivation: Genome-wide association (GWA) studies may identify multiple variants that are associated with a disease or trait. To narrow down candidates for further validation, quantitatively assessing how identified genes relate to a phenotype of interest is important., Results: We describe an approach to characterize genes or biological concepts (phenotypes, pathways, diseases, etc.) by ontology fingerprint--the set of Gene Ontology (GO) terms that are overrepresented among the PubMed abstracts discussing the gene or biological concept together with the enrichment p-value of these terms generated from a hypergeometric enrichment test. We then quantify the relevance of genes to the trait from a GWA study by calculating similarity scores between their ontology fingerprints using enrichment p-values. We validate this approach by correctly identifying corresponding genes for biological pathways with a 90% average area under the ROC curve (AUC). We applied this approach to rank genes identified through a GWA study that are associated with the lipid concentrations in plasma as well as to prioritize genes within linkage disequilibrium (LD) block. We found that the genes with highest scores were: ABCA1, lipoprotein lipase (LPL) and cholesterol ester transfer protein, plasma for high-density lipoprotein; low-density lipoprotein receptor, APOE and APOB for low-density lipoprotein; and LPL, APOA1 and APOB for triglyceride. In addition, we identified genes relevant to lipid metabolism from the literature even in cases where such knowledge was not reflected in current annotation of these genes. These results demonstrate that ontology fingerprints can be used effectively to prioritize genes from GWA studies for experimental validation.

Philometra overstreeti Moravec et de Buron, 2006 and Philomnetroides paralichthydis Moravec et de Buron, 2006 are common parasites of the southern flounder, Paralichthys lethostigma Jordan et Gilbert. Because the life cycles of these parasites are unknown, our goal was to assess whether species of copepod commonly found in our estuaries could serve as intermediate hosts for these philometrids. Individuals of five species of copepods were collected and exposed to L1 larvae of each philometrid species. The cyclopoid Oithlona colcarva Bowman was the only species to become successfully infected. Successive moulting of philometrid larvae in the haemocoel of the copepods was studied using transmission electron microscopy. At 23 degrees C the moult from L1 to L2 was observed for both species as early as 24 h post exposure to L1 larvae. The moult from L2 to L3 was initiated within 2 days post exposure and completed by 6-7 days post exposure. Some parasite-induced tissue damage occurred in the copepod but no cellular response against larval philometrids was observed.

Transgenic overexpression of Fli-1 in normal mice leads to SLE-like disease and increased expression was reported in SLE-affected human and murine lymphocytes. Reducing Fli-1 expression in MRL/lpr mice decreased antibody production, proteinuria, renal pathology, and mortality. Compared to those with wild-type expression of Fli-1, we report here that proliferative responses of Fli-1-deficient naïve B cells to several mitogens were reduced in lupus-prone and control mice. Expression of mitogen receptors, including BCR, TLR4, and TLR9, was not significantly impacted in Fli-1-deficient naïve B cells. IL12a transcripts were upregulated and NFAT transcripts were downregulated in Fli-1-deficient MRL/lpr B cells. These results demonstrate that Fli-1 deficiency affects B cell proliferative responses to mitogens, independent of BCR and TLR expression. IL12a and NFAT, known to influence proliferation, were identified as potential mediators of this effect. This may be a mechanism by which overexpression of Fli-1 contributes to B cell hyperactivity and subsequent SLE pathogenesis.

A well-designed microarray database can provide valuable information on gene expression levels. However, designing an efficient microarray database with minimum space usage is not an easy task since designers need to integrate the microarray data with the information of genes, probe annotation, and the descriptions of each microarray experiment. Developing better methods to store microarray data can greatly improve the efficiency and usefulness of such data. A new schema is proposed to store microarray data by using array data type in an object-relational database management system--PostgreSQL. The implemented database can store all the microarray data from the same chip in an array data structure. The variable-length array data type in PostgreSQL can store microarray data from same chip. The implementation of our schema can help to increase the data retrieval and space efficiency.