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We report the first genome-wide association study (GWAS) whose sample size (1,053 Swedish subjects) is sufficiently powered to detect genome-wide significance (p<1.5 x 10(-7)) for polymorphisms that modestly alter therapeutic warfarin dose. The anticoagulant drug warfarin is widely prescribed for reducing the risk of stroke, thrombosis, pulmonary embolism, and coronary malfunction. However, Caucasians vary widely (20-fold) in the dose needed for therapeutic anticoagulation, and hence prescribed doses may be too low (risking serious illness) or too high (risking severe bleeding). Prior work established that approximately 30% of the dose variance is explained by single nucleotide polymorphisms (SNPs) in the warfarin drug target VKORC1 and another approximately 12% by two non-synonymous SNPs (*2, *3) in the cytochrome P450 warfarin-metabolizing gene CYP2C9. We initially tested each of 325,997 GWAS SNPs for association with warfarin dose by univariate regression and found the strongest statistical signals (p<10(-78)) at SNPs clustering near VKORC1 and the second lowest p-values (p<10(-31)) emanating from CYP2C9. No other SNPs approached genome-wide significance. To enhance detection of weaker effects, we conducted multiple regression adjusting for known influences on warfarin dose (VKORC1, CYP2C9, age, gender) and identified a single SNP (rs2108622) with genome-wide significance (p = 8.3 x 10(-10)) that alters protein coding of the CYP4F2 gene. We confirmed this result in 588 additional Swedish patients (p<0.0029) and, during our investigation, a second group provided independent confirmation from a scan of warfarin-metabolizing genes. We also thoroughly investigated copy number variations, haplotypes, and imputed SNPs, but found no additional highly significant warfarin associations. We present power analysis of our GWAS that is generalizable to other studies, and conclude we had 80% power to detect genome-wide significance for common causative variants or markers explaining at least 1.5% of dose variance. These GWAS results provide further impetus for conducting large-scale trials assessing patient benefit from genotype-based forecasting of warfarin dose.

Identifying drug targets is a critical step in pharmacology. Drug phenotypic and chemical indexes are two important indicators in this field. However, in previous studies, the indexes were always isolated and the candidate proteins were often limited to a small subset of the human genome. Based on the correlations observed in pharmacological and genomic spaces, we develop a computational framework, drugCIPHER, to infer drug-target interactions in a genome-wide scale. Three linear regression models are proposed, which respectively relate drug therapeutic similarity, chemical similarity and their combination to the relevance of the targets on the basis of a protein-protein interaction network. Typically, the model integrating both drug therapeutic similarity and chemical similarity, drugCIPHER-MS, achieved an area under the Receiver Operating Characteristic (ROC) curve of 0.988 in the training set and 0.935 in the test set. Based on drugCIPHER-MS, a genome-wide map of drug biological fingerprints for 726 drugs is constructed, within which unexpected drug-drug relations emerged in 501 cases, implying possible novel applications or side effects. Our findings demonstrate that the integration of phenotypic and chemical indexes in pharmacological space and protein-protein interactions in genomic space can not only speed the genome-wide identification of drug targets but also find new applications for the existing drugs.

Background Studies in mice have shown that PPARα is an important regulator of hepatic lipid metabolism and the acute phase response. However, little information is available on the role of PPARα in human liver. Here we set out to compare the function of PPARα in mouse and human hepatocytes via analysis of target gene regulation. Methodology/Principal Findings Primary hepatocytes from 6 human and 6 mouse donors were treated with PPARα agonist Wy14643 and gene expression profiling was performed using Affymetrix GeneChips followed by a systems biology analysis. Baseline PPARα expression was similar in human and mouse hepatocytes. Depending on species and time of exposure, Wy14643 significantly induced the expression of 362–672 genes. Surprisingly minor overlap was observed between the Wy14643-regulated genes from mouse and human, although more substantial overlap was observed at the pathway level. Xenobiotics metabolism and apolipoprotein synthesis were specifically regulated by PPARα in human hepatocytes, whereas glycolysis-gluconeogenesis was regulated specifically in mouse hepatocytes. Most of the genes commonly regulated in mouse and human were involved in lipid metabolism and many represented known PPARα targets, including CPT1A, HMGCS2, FABP1, ACSL1, and ADFP. Several genes were identified that were specifically induced by PPARα in human (MBL2, ALAS1, CYP1A1, TSKU) or mouse (Fbp2, lgals4, Cd36, Ucp2, Pxmp4). Furthermore, several putative novel PPARα targets were identified that were commonly regulated in both species, including CREB3L3, KLF10, KLF11 and MAP3K8. Conclusions/Significance Our results suggest that PPARα activation has a major impact on gene regulation in human hepatocytes. Importantly, the role of PPARα as master regulator of hepatic lipid metabolism is generally well-conserved between mouse and human. Overall, however, PPARα regulates a mostly divergent set of genes in mouse and human hepatocytes.

KRAS mutations occur in 35-45% of metastatic colorectal cancers (mCRC) and preclude responsiveness to EGFR-targeted therapy with cetuximab or panitumumab. However, less than 20% patients displaying wild-type KRAS tumors achieve objective response. Alterations in other effectors downstream of the EGFR, such as BRAF, and deregulation of the PIK3CA/PTEN pathway have independently been found to give rise to resistance. We present a comprehensive analysis of KRAS, BRAF, PIK3CA mutations, and PTEN expression in mCRC patients treated with cetuximab or panitumumab, with the aim of clarifying the relative contribution of these molecular alterations to resistance. We retrospectively analyzed objective tumor response, progression-free (PFS) and overall survival (OS) together with the mutational status of KRAS, BRAF, PIK3CA and expression of PTEN in 132 tumors from cetuximab or panitumumab treated mCRC patients. Among the 106 non-responsive patients, 74 (70%) had tumors with at least one molecular alteration in the four markers. The probability of response was 51% (22/43) among patients with no alterations, 4% (2/47) among patients with 1 alteration, and 0% (0/24) for patients with > or =2 alterations (p<0.0001). Accordingly, PFS and OS were increasingly worse for patients with tumors harboring none, 1, or > or =2 molecular alteration(s) (p<0.001). When expression of PTEN and mutations of KRAS, BRAF and PIK3CA are concomitantly ascertained, up to 70% of mCRC patients unlikely to respond to anti-EGFR therapies can be identified. We propose to define as 'quadruple negative', the CRCs lacking alterations in KRAS, BRAF, PTEN and PIK3CA. Comprehensive molecular dissection of the EGFR signaling pathways should be considered to select mCRC patients for cetuximab- or panitumumab-based therapies.

Lymphoblastoid cell lines (LCLs), originally collected as renewable sources of DNA, are now being used as a model system to study genotype-phenotype relationships in human cells, including searches for QTLs influencing levels of individual mRNAs and responses to drugs and radiation. In the course of attempting to map genes for drug response using 269 LCLs from the International HapMap Project, we evaluated the extent to which biological noise and non-genetic confounders contribute to trait variability in LCLs. While drug responses could be technically well measured on a given day, we observed significant day-to-day variability and substantial correlation to non-genetic confounders, such as baseline growth rates and metabolic state in culture. After correcting for these confounders, we were unable to detect any QTLs with genome-wide significance for drug response. A much higher proportion of variance in mRNA levels may be attributed to non-genetic factors (intra-individual variance--i.e., biological noise, levels of the EBV virus used to transform the cells, ATP levels) than to detectable eQTLs. Finally, in an attempt to improve power, we focused analysis on those genes that had both detectable eQTLs and correlation to drug response; we were unable to detect evidence that eQTL SNPs are convincingly associated with drug response in the model. While LCLs are a promising model for pharmacogenetic experiments, biological noise and in vitro artifacts may reduce power and have the potential to create spurious association due to confounding.

Antimicrobial peptides (AMPs) protect the host intestinal mucosa against microorganisms. Abnormal expression of defensins was shown in inflammatory bowel disease (IBD), but it is not clear whether this is a primary defect. We investigated the impact of anti-inflammatory therapy with infliximab on the mucosal gene expression of AMPs in IBD. Mucosal gene expression of 81 AMPs was assessed in 61 IBD patients before and 4-6 weeks after their first infliximab infusion and in 12 control patients, using Affymetrix arrays. Quantitative real-time reverse-transcription PCR and immunohistochemistry were used to confirm microarray data. The dysregulation of many AMPs in colonic IBD in comparison with control colons was widely restored by infliximab therapy, and only DEFB1 expression remained significantly decreased after therapy in the colonic mucosa of IBD responders to infliximab. In ileal Crohn's disease (CD), expression of two neuropeptides with antimicrobial activity, PYY and CHGB, was significantly decreased before therapy compared to control ileums, and ileal PYY expression remained significantly decreased after therapy in CD responders. Expression of the downregulated AMPs before and after treatment (DEFB1 and PYY) correlated with villin 1 expression, a gut epithelial cell marker, indicating that the decrease is a consequence of epithelial damage. Our study shows that the dysregulation of AMPs in IBD mucosa is the consequence of inflammation, but may be responsible for perpetuation of inflammation due to ineffective clearance of microorganisms.

CDKN1C (encoding tumor suppressor p57(KIP2)) is a cyclin-dependent kinase (CDK) inhibitor whose family members are often transcriptionally downregulated in human cancer via promoter DNA methylation. In this study, we show that CDKN1C is repressed in breast cancer cells mainly through histone modifications. In particular, we show that CDKN1C is targeted by histone methyltransferase EZH2-mediated histone H3 lysine 27 trimethylation (H3K27me3), and can be strongly activated by inhibition of EZH2 in synergy with histone deacetylase inhibitor. Consistent with the overexpression of EZH2 in a variety of human cancers including breast cancer, CDKN1C in these cancers is downregulated, and breast tumors expressing low levels of CDKN1C are associated with a poor prognosis. We further show that assessing both EZH2 and CDKN1C expression levels as a measurement of EZH2 pathway activity provides a more predictive power of disease outcome than that achieved with EZH2 or CDKN1C alone. Taken together, our study reveals a novel epigenetic mechanism governing CDKN1C repression in breast cancer. Importantly, as a newly identified EZH2 target with prognostic value, it has implications in patient stratification for cancer therapeutic targeting EZH2-mediated gene repression.

Statins effectively lower total and plasma LDL-cholesterol, but the magnitude of decrease varies among individuals. To identify single nucleotide polymorphisms (SNPs) contributing to this variation, we performed a combined analysis of genome-wide association (GWA) results from three trials of statin efficacy. Bayesian and standard frequentist association analyses were performed on untreated and statin-mediated changes in LDL-cholesterol, total cholesterol, HDL-cholesterol, and triglyceride on a total of 3932 subjects using data from three studies: Cholesterol and Pharmacogenetics (40 mg/day simvastatin, 6 weeks), Pravastatin/Inflammation CRP Evaluation (40 mg/day pravastatin, 24 weeks), and Treating to New Targets (10 mg/day atorvastatin, 8 weeks). Genotype imputation was used to maximize genomic coverage and to combine information across studies. Phenotypes were normalized within each study to account for systematic differences among studies, and fixed-effects combined analysis of the combined sample were performed to detect consistent effects across studies. Two SNP associations were assessed as having posterior probability greater than 50%, indicating that they were more likely than not to be genuinely associated with statin-mediated lipid response. SNP rs8014194, located within the CLMN gene on chromosome 14, was strongly associated with statin-mediated change in total cholesterol with an 84% probability by Bayesian analysis, and a p-value exceeding conventional levels of genome-wide significance by frequentist analysis (P = 1.8 x 10(-8)). This SNP was less significantly associated with change in LDL-cholesterol (posterior probability = 0.16, P = 4.0 x 10(-6)). Bayesian analysis also assigned a 51% probability that rs4420638, located in APOC1 and near APOE, was associated with change in LDL-cholesterol. Using combined GWA analysis from three clinical trials involving nearly 4,000 individuals treated with simvastatin, pravastatin, or atorvastatin, we have identified SNPs that may be associated with variation in the magnitude of statin-mediated reduction in total and LDL-cholesterol, including one in the CLMN gene for which statistical evidence for association exceeds conventional levels of genome-wide significance. PRINCE and TNT are not registered. CAP is registered at Clinicaltrials.gov NCT00451828.

Valproic acid (VPA) has demonstrated potential as a therapeutic candidate for spinal muscular atrophy (SMA) in vitro and in vivo. Two cohorts of subjects were enrolled in the SMA CARNIVAL TRIAL, a non-ambulatory group of \"sitters\" (cohort 1) and an ambulatory group of \"walkers\" (cohort 2). Here, we present results for cohort 1: a multicenter phase II randomized double-blind intention-to-treat protocol in non-ambulatory SMA subjects 2-8 years of age. Sixty-one subjects were randomized 1:1 to placebo or treatment for the first six months; all received active treatment the subsequent six months. The primary outcome was change in the modified Hammersmith Functional Motor Scale (MHFMS) score following six months of treatment. Secondary outcomes included safety and adverse event data, and change in MHFMS score for twelve versus six months of active treatment, body composition, quantitative SMN mRNA levels, maximum ulnar CMAP amplitudes, myometry and PFT measures. At 6 months, there was no difference in change from the baseline MHFMS score between treatment and placebo groups (difference = 0.643, 95% CI = -1.22-2.51). Adverse events occurred in >80% of subjects and were more common in the treatment group. Excessive weight gain was the most frequent drug-related adverse event, and increased fat mass was negatively related to change in MHFMS values (p = 0.0409). Post-hoc analysis found that children ages two to three years that received 12 months treatment, when adjusted for baseline weight, had significantly improved MHFMS scores (p = 0.03) compared to those who received placebo the first six months. A linear regression analysis limited to the influence of age demonstrates young age as a significant factor in improved MHFMS scores (p = 0.007). This study demonstrated no benefit from six months treatment with VPA and L-carnitine in a young non-ambulatory cohort of subjects with SMA. Weight gain, age and treatment duration were significant confounding variables that should be considered in the design of future trials. Clinicaltrials.gov NCT00227266.

The increased sequencing of pathogen genomes and the subsequent availability of genome-scale functional datasets are expected to guide the experimental work necessary for target-based drug discovery. However, a major bottleneck in this has been the difficulty of capturing and integrating relevant information in an easily accessible format for identifying and prioritizing potential targets. The open-access resource TDRtargets.org facilitates drug target prioritization for major tropical disease pathogens such as the mycobacteria Mycobacterium leprae and Mycobacterium tuberculosis; the kinetoplastid protozoans Leishmania major, Trypanosoma brucei, and Trypanosoma cruzi; the apicomplexan protozoans Plasmodium falciparum, Plasmodium vivax, and Toxoplasma gondii; and the helminths Brugia malayi and Schistosoma mansoni. Here we present strategies to prioritize pathogen proteins based on whether their properties meet criteria considered desirable in a drug target. These criteria are based upon both sequence-derived information (e.g., molecular mass) and functional data on expression, essentiality, phenotypes, metabolic pathways, assayability, and druggability. This approach also highlights the fact that data for many relevant criteria are lacking in less-studied pathogens (e.g., helminths), and we demonstrate how this can be partially overcome by mapping data from homologous genes in well-studied organisms. We also show how individual users can easily upload external datasets and integrate them with existing data in TDRtargets.org to generate highly customized ranked lists of potential targets. Using the datasets and the tools available in TDRtargets.org, we have generated illustrative lists of potential drug targets in seven tropical disease pathogens. While these lists are broadly consistent with the research community's current interest in certain specific proteins, and suggest novel target candidates that may merit further study, the lists can easily be modified in a user-specific manner, either by adjusting the weights for chosen criteria or by changing the criteria that are included.