Genetic Pleiotropy between Nicotine Dependence and Respiratory Outcomes.

Smoking is a major cause of respiratory conditions. To date, the genetic pleiotropy between smoking behavior and lung function/chronic obstructive pulmonary disease (COPD) have not been systematically explored. We leverage large data sets of smoking behavior, lung function and COPD, and addressed two questions, (1) whether the genetic predisposition of nicotine dependence influence COPD risk and lung function; and (2) the genetic pleiotropy follow causal or independent model. We found the genetic predisposition of nicotine dependence was associated with COPD risk, even after adjusting for smoking behavior, indicating genetic pleiotropy and independent model. Two known nicotine dependent loci (15q25.1 and 19q13.2) were associated with smoking adjusted lung function, and 15q25.1 reached genome-wide significance. At various suggestive p-value thresholds, the smoking adjusted lung function traits share association signals with cigarettes per day and former smoking, substantially greater than random chance. Empirical data showed the genetic pleiotropy between nicotine dependence and COPD or lung function. The basis of pleiotropic effect is rather complex, attributable to a large number of genetic variants, and many variants functions through independent model, where the pleiotropic variants directly affect lung function, not mediated by influencing subjects' smoking behavior.

Airway Epithelial Expression Quantitative Trait Loci Reveal Genes Underlying Asthma and Other Airway Diseases.

Genome-wide association studies (GWASs) have identified loci that are robustly associated with asthma and related phenotypes; however, the molecular mechanisms underlying these associations need to be explored. The most relevant tissues to study the functional consequences of asthma are the airways. We used publically available data to derive expression quantitative trait loci (eQTLs) for human epithelial cells from small and large airways and applied the eQTLs in the interpretation of GWAS results of asthma and related phenotypes. For the small airways (n = 105), we discovered 660 eQTLs at a 10% false discovery rate (FDR), among which 315 eQTLs were not previously reported in a large-scale eQTL study of whole lung tissue. A large fraction of the identified eQTLs is supported by data from Encyclopedia of DNA Elements (ENCODE) showing that the eQTLs reside in regulatory elements (57.5 and 67.6% of cis- and trans-eQTLs, respectively). Published pulmonary GWAS hits were enriched as airway epithelial eQTLs (9.2-fold). Further, genes regulated by asthma GWAS loci in epithelium are significantly enriched in immune response pathways, such as IL-4 signaling (FDR, 5.2 × 10(-4)). The airway epithelial eQTLs described in this study are complementary to previously reported lung eQTLs and represent a powerful resource to link GWAS-associated variants to their regulatory function and thus elucidate the molecular mechanisms underlying asthma and airway-related conditions.

Decrease of mRNA Editing after Spinal Cord Injury is Caused by Down-regulation of ADAR2 that is Triggered by Inflammatory Response.

We recently showed that spinal cord injury (SCI) leads to a decrease in mRNA editing of serotonin receptor 2C (5-HT2CR) contributing to post-SCI spasticity. Here we study post-SCI mRNA editing and global gene expression using massively parallel sequencing. Evidence is presented that the decrease in 5-HT2CR editing is caused by down-regulation of adenosine deaminase ADAR2 and that editing of at least one other ADAR2 target, potassium channel Kv1.1, is decreased after SCI. Bayesian network analysis of genome-wide transcriptome data indicates that down-regulation of ADAR2 (1) is triggered by persistent inflammatory response to SCI that is associated with activation of microglia and (2) results in changes in neuronal gene expression that are likely to contribute both to post-SCI restoration of neuronal excitability and muscle spasms. These findings have broad implications for other diseases of the Central Nervous System and could open new avenues for developing efficacious antispastic treatments.

Shared genetic etiology underlying Alzheimer's disease and type 2 diabetes.

Epidemiological evidence supports the observation that subjects with type 2 diabetes (T2D) are at higher risk to develop Alzheimer's disease (AD). However, whether and how these two conditions are causally linked is unknown. Possible mechanisms include shared genetic risk factors, which were investigated in this study based on recent genome wide association study (GWAS) findings. In order to achieve our goal, we retrieved single nucleotide polymorphisms (SNPs) associated with T2D and AD from large-scale GWAS meta-analysis consortia and tested for overlap among the T2D- and AD-associated SNPs at various p-value thresholds. We then explored the function of the shared T2D/AD GWAS SNPs by leveraging expressional quantitative trait loci, pathways, gene ontology data, and co-expression networks. We found 927 SNPs associated with both AD and T2D with p-value ≤0.01, an overlap significantly larger than random chance (overlapping p-value of 6.93E-28). Among these, 395 of the shared GWAS SNPs have the same risk allele for AD and T2D, suggesting common pathogenic mechanisms underlying the development of both AD and T2D. Genes influenced by shared T2D/AD SNPs with the same risk allele were first identified using a SNP annotation variation (ANNOVAR) software, followed by using Association Protein-Protein Link Evaluator (DAPPLE) software to identify additional proteins that are known to physically interact with the ANNOVAR gene annotations. We found that gene annotations from ANNOVAR and DAPPLE significantly enriched specific KEGG pathways pertaining to immune responses, cell signaling and neuronal plasticity, cellular processes in which abnormalities are known to contribute to both T2D and AD pathogenesis. Thus, our observation suggests that among T2D subjects with common genetic predispositions (e.g., SNPs with consistent risk alleles for T2D and AD), dysregulation of these pathogenic pathways could contribute to the elevated risks for AD in subjects. Interestingly, we found that 532 of the shared T2D/AD GWAS SNPs had divergent risk alleles in the two diseases. For individual shared T2D/AD SNPs with divergent alleles, one of the allelic forms may contribute to one of the diseases (e.g., T2D), but not necessarily to the other (e.g., AD), or vice versa. Collectively, our GWAS studies tentatively support the epidemiological observation of disease concordance between T2D and AD. Moreover, the studies provide the much needed information for the design of future novel therapeutic approaches, for a subpopulation of T2D subjects with genetic disposition to AD, that could benefit T2D and reduce the risk for subsequent development of AD.

Meta-eQTL: a tool set for flexible eQTL meta-analysis.

BACKGROUND: Increasing number of eQTL (Expression Quantitative Trait Loci) datasets facilitate genetics and systems biology research. Meta-analysis tools are in need to jointly analyze datasets of same or similar issue types to improve statistical power especially in trans-eQTL mapping. Meta-analysis framework is also necessary for ChrX eQTL discovery. RESULTS: We developed a novel tool, meta-eqtl, for fast eQTL meta-analysis of arbitrary sample size and arbitrary number of datasets. Further, this tool accommodates versatile modeling, eg. non-parametric model and mixed effect models. In addition, meta-eqtl readily handles calculation of chrX eQTLs. CONCLUSIONS: We demonstrated and validated meta-eqtl as fast and comprehensive tool to meta-analyze multiple datasets and ChrX eQTL discovery. Meta-eqtl is a set of command line utilities written in R, with some computationally intensive parts written in C. The software runs on Linux platforms and is designed to intelligently adapt to high performance computing (HPC) cluster. We applied the novel tool to liver and adipose tissue data, and revealed eSNPs underlying diabetes GWAS loci.

Molecularly defined unfolded protein response subclasses have distinct correlations with fatty liver disease in zebrafish.

The unfolded protein response (UPR) is a complex network of sensors and target genes that ensure efficient folding of secretory proteins in the endoplasmic reticulum (ER). UPR activation is mediated by three main sensors, which regulate the expression of hundreds of targets. UPR activation can result in outcomes ranging from enhanced cellular function to cell dysfunction and cell death. How this pathway causes such different outcomes is unknown. Fatty liver disease (steatosis) is associated with markers of UPR activation and robust UPR induction can cause steatosis; however, in other cases, UPR activation can protect against this disease. By assessing the magnitude of activation of UPR sensors and target genes in the liver of zebrafish larvae exposed to three commonly used ER stressors (tunicamycin, thapsigargin and Brefeldin A), we have identified distinct combinations of UPR sensors and targets (i.e. subclasses) activated by each stressor. We found that only the UPR subclass characterized by maximal induction of UPR target genes, which we term a stressed-UPR, induced steatosis. Principal component analysis demonstrated a significant positive association between UPR target gene induction and steatosis. The same principal component analysis showed significant correlation with steatosis in samples from patients with fatty liver disease. We demonstrate that an adaptive UPR induced by a short exposure to thapsigargin prior to challenging with tunicamycin reduced both the induction of a stressed UPR and steatosis incidence. We conclude that a stressed UPR causes steatosis and an adaptive UPR prevents it, demonstrating that this pathway plays dichotomous roles in fatty liver disease.

A unique gene expression signature associated with serotonin 2C receptor RNA editing in the prefrontal cortex and altered in suicide.

Editing of the pre-mRNA for the serotonin receptor 2C (5-HT2CR) by site-specific adenosine deamination (A-to-I pre-mRNA editing) substantially increases the functional plasticity of this key neurotransmitter receptor and is thought to contribute to homeostatic mechanisms in neurons. 5-HT2CR mRNA editing generates up to 24 different receptor isoforms. The extent of editing correlates with 5-HT2CR functional activity: more highly edited isoforms exhibit the least function. Altered 5-HT2CR editing has been reported in postmortem brains of suicide victims. We report a comparative analysis of the connections among 5-HT2CR editing, genome-wide gene expression and DNA methylation in suicide victims, individuals with major depressive disorder and non-psychiatric controls. The results confirm previous findings of an overrepresentation of highly edited mRNA variants (which encode hypoactive 5-HT2CR receptors) in the brains of suicide victims. A large set of genes for which the expression level is associated with editing was detected. This signature set of editing-associated genes is significantly enriched for genes that are involved in synaptic transmission, genes that are preferentially expressed in neurons, and genes whose expression is correlated with the level of DNA methylation. Notably, we report that the link between 5-HT2CR editing and gene expression is disrupted in suicide victims. The results suggest that the postulated homeostatic function of 5-HT2CR editing is dysregulated in individuals who committed suicide.

Differences in DNA methylation between human neuronal and glial cells are concentrated in enhancers and non-CpG sites.

We applied Illumina Human Methylation450K array to perform a genomic-scale single-site resolution DNA methylation analysis in neuronal and nonneuronal (primarily glial) nuclei separated from the orbitofrontal cortex of postmortem human brain. The findings were validated using enhanced reduced representation bisulfite sequencing. We identified thousands of sites differentially methylated (DM) between neuronal and nonneuronal cells. The DM sites were depleted within CpG-island-containing promoters but enriched in predicted enhancers. Classification of the DM sites into those undermethylated in neurons (neuronal type) and those undermethylated in nonneuronal cells (glial type), combined with findings of others that methylation within control elements typically negatively correlates with gene expression, yielded large sets of predicted neuron-specific and non-neuron-specific genes. These sets of predicted genes were in excellent agreement with the available direct measurements of gene expression in human and mouse. We also found a distinct set of DNA methylation patterns that were unique for neuronal cells. In particular, neuronal-type differential methylation was overrepresented in CpG island shores, enriched within gene bodies but not in intergenic regions, and preferentially harbored binding motifs for a distinct set of transcription factors, including neuron-specific activity-dependent factors. Finally, non-CpG methylation was substantially more prevalent in neurons than in nonneuronal cells.

Gene expression patterns unveil a new level of molecular heterogeneity in colorectal cancer.

The recognition that colorectal cancer (CRC) is a heterogeneous disease in terms of clinical behaviour and response to therapy translates into an urgent need for robust molecular disease subclassifiers that can explain this heterogeneity beyond current parameters (MSI, KRAS, BRAF). Attempts to fill this gap are emerging. The Cancer Genome Atlas (TGCA) reported two main CRC groups, based on the incidence and spectrum of mutated genes, and another paper reported an EMT expression signature defined subgroup. We performed a prior free analysis of CRC heterogeneity on 1113 CRC gene expression profiles and confronted our findings to established molecular determinants and clinical, histopathological and survival data. Unsupervised clustering based on gene modules allowed us to distinguish at least five different gene expression CRC subtypes, which we call surface crypt-like, lower crypt-like, CIMP-H-like, mesenchymal and mixed. A gene set enrichment analysis combined with literature search of gene module members identified distinct biological motifs in different subtypes. The subtypes, which were not derived based on outcome, nonetheless showed differences in prognosis. Known gene copy number variations and mutations in key cancer-associated genes differed between subtypes, but the subtypes provided molecular information beyond that contained in these variables. Morphological features significantly differed between subtypes. The objective existence of the subtypes and their clinical and molecular characteristics were validated in an independent set of 720 CRC expression profiles. Our subtypes provide a novel perspective on the heterogeneity of CRC. The proposed subtypes should be further explored retrospectively on existing clinical trial datasets and, when sufficiently robust, be prospectively assessed for clinical relevance in terms of prognosis and treatment response predictive capacity. Original microarray data were uploaded to the ArrayExpress database (http://www.ebi.ac.uk/arrayexpress/) under Accession Nos E-MTAB-990 and E-MTAB-1026.

DUSP 4 expression identifies a subset of colorectal cancer tumors that differ in MAPK activation, regardless of the genotype.

As dual-specificity phosphatase (DUSP) expression has been correlated to sensitivity to MEK inhibitors, DUSP expression levels may indicate activation of the mitogen-activated protein kinase (MAPK) pathway in many tumor types. In this study, we investigate if DUSP levels can indicate different levels of MAPK activation within colorectal cancer (CRC) patients. In three different CRC patient microarray datasets, we analyzed the expression of DUSP1. DUSP4 and DUSP6 according to mutational status, their correlation with survival and their association with different clinical characteristics. DUSP4 was significantly differentially expressed between all mutational subgroups with the highest expression in BRAF mutated tumors. Moreover, high DUSP4 expression was associated with a worse overall survival and with clinical characteristics typical for BRAF mutant patients. The use of DUSP expression as a predictive biomarker towards MAPK targeted therapy in CRC patients needs further investigation.

microRNAs in colon cancer: a roadmap for discovery.

Cancer omics data are exponentially created and associated with clinical variables, and important findings can be extracted based on bioinformatics approaches which can then be experimentally validated. Many of these findings are related to a specific class of non-coding RNA molecules called microRNAs (miRNAs) (post-transcriptional regulators of mRNA expression). The related research field is quite heterogeneous and bioinformaticians, clinicians, statisticians and biologists, as well as data miners and engineers collaborate to cure stored data and on new impulses coming from the output of the latest Next Generation Sequencing technologies. Here we review the main research findings on miRNA of the first 10 years in colon cancer research with an emphasis on possible uses in clinical practice. This review intends to provide a road map in the jungle of publications of miRNA in colorectal cancer, focusing on data availability and new ways to generate biologically relevant information out of these huge amounts of data.

A comprehensive characterization of genome-wide copy number aberrations in colorectal cancer reveals novel oncogenes and patterns of alterations.

To develop a comprehensive overview of copy number aberrations (CNAs) in stage-II/III colorectal cancer (CRC), we characterized 302 tumors from the PETACC-3 clinical trial. Microsatellite-stable (MSS) samples (n = 269) had 66 minimal common CNA regions, with frequent gains on 20 q (72.5%), 7 (41.8%), 8 q (33.1%) and 13 q (51.0%) and losses on 18 (58.6%), 4 q (26%) and 21 q (21.6%). MSS tumors have significantly more CNAs than microsatellite-instable (MSI) tumors: within the MSI tumors a novel deletion of the tumor suppressor WWOX at 16 q23.1 was identified (p<0.01). Focal aberrations identified by the GISTIC method confirmed amplifications of oncogenes including EGFR, ERBB2, CCND1, MET, and MYC, and deletions of tumor suppressors including TP53, APC, and SMAD4, and gene expression was highly concordant with copy number aberration for these genes. Novel amplicons included putative oncogenes such as WNK1 and HNF4A, which also showed high concordance between copy number and expression. Survival analysis associated a specific patient segment featured by chromosome 20 q gains to an improved overall survival, which might be due to higher expression of genes such as EEF1B2 and PTK6. The CNA clustering also grouped tumors characterized by a poor prognosis BRAF-mutant-like signature derived from mRNA data from this cohort. We further revealed non-random correlation between CNAs among unlinked loci, including positive correlation between 20 q gain and 8 q gain, and 20 q gain and chromosome 18 loss, consistent with co-selection of these CNAs. These results reinforce the non-random nature of somatic CNAs in stage-II/III CRC and highlight loci and genes that may play an important role in driving the development and outcome of this disease.

Nonrandom distribution of cryptic repeating triplets of purines and pyrimidines (RNY)(n) in gp120 of HIV Type1.

We have analyzed purine (R) and pyrimidine (Y) codon patterns in variable and constant regions of HIV-1 gp120 in seven patients infected with different HIV-1 subtypes and naive to antiretroviral therapy. We have calculated the relative frequency of each in-frame codon RNY, YNR, RNR, and YNY (N=any nucleotide) in variable and constant regions of gp120, in the sequence within indels and at indels' flanking sites. Our data show that hypervariable regions V1, V2, V4, and V5 are characterized by the presence of long stretches of RNY codons constituting the majority of the sequence portion within insertions/deletions. In full-length gp120 and within inserted/deleted fragments the number of AVT (V=A, C, G) codons did not exceed 50% of the total RNY codons. RNY strings in variable regions spanned up to 21 codons and were always in frame. In contrast, RNY strings in constant regions were mostly out of frame and their length was limited to five codons. The frequency of the codon RNY was found to be significantly higher in variable regions (p<0.0001; t-test), within indels, and at indels' flanking sites (p<0.0001; χ(2) test). Analysis of the distribution of RNY strings equal to or longer than five codons in the full genome of HXB2 also shows that these sequences are mostly out of frame, unless they contain a potential N-glycosylation site or an asparagine. These data suggest that cryptic repeats of RNY may play a role in the genesis of multiple base insertions and deletions in hypervariable regions of gp120.