A genome-wide association study and biological pathway analysis of epilepsy prognosis in a prospective cohort of newly treated epilepsy.

We present the analysis of a prospective multicentre study to investigate genetic effects on the prognosis of newly treated epilepsy. Patients with a new clinical diagnosis of epilepsy requiring medication were recruited and followed up prospectively. The clinical outcome was defined as freedom from seizures for a minimum of 12 months in accordance with the consensus statement from the International League Against Epilepsy (ILAE). Genetic effects on remission of seizures after starting treatment were analysed with and without adjustment for significant clinical prognostic factors, and the results from each cohort were combined using a fixed-effects meta-analysis. After quality control (QC), we analysed 889 newly treated epilepsy patients using 472 450 genotyped and 6.9 × 10(6) imputed single-nucleotide polymorphisms. Suggestive evidence for association (defined as Pmeta < 5.0 × 10(-7)) with remission of seizures after starting treatment was observed at three loci: 6p12.2 (rs492146, Pmeta = 2.1 × 10(-7), OR[G] = 0.57), 9p23 (rs72700966, Pmeta = 3.1 × 10(-7), OR[C] = 2.70) and 15q13.2 (rs143536437, Pmeta = 3.2 × 10(-7), OR[C] = 1.92). Genes of biological interest at these loci include PTPRD and ARHGAP11B (encoding functions implicated in neuronal development) and GSTA4 (a phase II biotransformation enzyme). Pathway analysis using two independent methods implicated a number of pathways in the prognosis of epilepsy, including KEGG categories 'calcium signaling pathway' and 'phosphatidylinositol signaling pathway'. Through a series of power curves, we conclude that it is unlikely any single common variant explains >4.4% of the variation in the outcome of newly treated epilepsy.

Diagnostic Test Accuracy of a 2-Transcript Host RNA Signature for Discriminating Bacterial vs Viral Infection in Febrile Children.

IMPORTANCE: Because clinical features do not reliably distinguish bacterial from viral infection, many children worldwide receive unnecessary antibiotic treatment, while bacterial infection is missed in others. OBJECTIVE: To identify a blood RNA expression signature that distinguishes bacterial from viral infection in febrile children. DESIGN, SETTING, AND PARTICIPANTS: Febrile children presenting to participating hospitals in the United Kingdom, Spain, the Netherlands, and the United States between 2009-2013 were prospectively recruited, comprising a discovery group and validation group. Each group was classified after microbiological investigation as having definite bacterial infection, definite viral infection, or indeterminate infection. RNA expression signatures distinguishing definite bacterial from viral infection were identified in the discovery group and diagnostic performance assessed in the validation group. Additional validation was undertaken in separate studies of children with meningococcal disease (n = 24) and inflammatory diseases (n = 48) and on published gene expression datasets. EXPOSURES: A 2-transcript RNA expression signature distinguishing bacterial infection from viral infection was evaluated against clinical and microbiological diagnosis. MAIN OUTCOMES AND MEASURES: Definite bacterial and viral infection was confirmed by culture or molecular detection of the pathogens. Performance of the RNA signature was evaluated in the definite bacterial and viral group and in the indeterminate infection group. RESULTS: The discovery group of 240 children (median age, 19 months; 62% male) included 52 with definite bacterial infection, of whom 36 (69%) required intensive care, and 92 with definite viral infection, of whom 32 (35%) required intensive care. Ninety-six children had indeterminate infection. Analysis of RNA expression data identified a 38-transcript signature distinguishing bacterial from viral infection. A smaller (2-transcript) signature (FAM89A and IFI44L) was identified by removing highly correlated transcripts. When this 2-transcript signature was implemented as a disease risk score in the validation group (130 children, with 23 definite bacterial, 28 definite viral, and 79 indeterminate infections; median age, 17 months; 57% male), all 23 patients with microbiologically confirmed definite bacterial infection were classified as bacterial (sensitivity, 100% [95% CI, 100%-100%]) and 27 of 28 patients with definite viral infection were classified as viral (specificity, 96.4% [95% CI, 89.3%-100%]). When applied to additional validation datasets from patients with meningococcal and inflammatory diseases, bacterial infection was identified with a sensitivity of 91.7% (95% CI, 79.2%-100%) and 90.0% (95% CI, 70.0%-100%), respectively, and with specificity of 96.0% (95% CI, 88.0%-100%) and 95.8% (95% CI, 89.6%-100%). Of the children in the indeterminate groups, 46.3% (63/136) were classified as having bacterial infection, although 94.9% (129/136) received antibiotic treatment. CONCLUSIONS AND RELEVANCE: This study provides preliminary data regarding test accuracy of a 2-transcript host RNA signature discriminating bacterial from viral infection in febrile children. Further studies are needed in diverse groups of patients to assess accuracy and clinical utility of this test in different clinical settings.

Novel association approach for variable number tandem repeats (VNTRs) identifies DOCK5 as a susceptibility gene for severe obesity.

Variable number tandem repeats (VNTRs) constitute a relatively under-examined class of genomic variants in the context of complex disease because of their sequence complexity and the challenges in assaying them. Recent large-scale genome-wide copy number variant mapping and association efforts have highlighted the need for improved methodology for association studies using these complex polymorphisms. Here we describe the in-depth investigation of a complex region on chromosome 8p21.2 encompassing the dedicator of cytokinesis 5 (DOCK5) gene. The region includes two VNTRs of complex sequence composition which flank a common 3975 bp deletion, all three of which were genotyped by polymerase chain reaction and fragment analysis in a total of 2744 subjects. We have developed a novel VNTR association method named VNTRtest, suitable for association analysis of multi-allelic loci with binary and quantitative outcomes, and have used this approach to show significant association of the DOCK5 VNTRs with childhood and adult severe obesity (P(empirical)= 8.9 × 10(-8) and P= 3.1 × 10(-3), respectively) which we estimate explains ~0.8% of the phenotypic variance. We also identified an independent association between the 3975 base pair (bp) deletion and obesity, explaining a further 0.46% of the variance (P(combined)= 1.6 × 10(-3)). Evidence for association between DOCK5 transcript levels and the 3975 bp deletion (P= 0.027) and both VNTRs (P(empirical)= 0.015) was also identified in adipose tissue from a Swedish family sample, providing support for a functional effect of the DOCK5 deletion and VNTRs. These findings highlight the potential role of DOCK5 in human obesity and illustrate a novel approach for analysis of the contribution of VNTRs to disease susceptibility through association studies.

Pathway-driven gene stability selection of two rheumatoid arthritis GWAS identifies and validates new susceptibility genes in receptor mediated signalling pathways.

Rheumatoid arthritis (RA) is the commonest chronic, systemic, inflammatory disorder affecting ∼1% of the world population. It has a strong genetic component and a growing number of associated genes have been discovered in genome-wide association studies (GWAS), which nevertheless only account for 23% of the total genetic risk. We aimed to identify additional susceptibility loci through the analysis of GWAS in the context of biological function. We bridge the gap between pathway and gene-oriented analyses of GWAS, by introducing a pathway-driven gene stability-selection methodology that identifies potential causal genes in the top-associated disease pathways that may be driving the pathway association signals. We analysed the WTCCC and the NARAC studies of ∼5000 and ∼2000 subjects, respectively. We examined 700 pathways comprising ∼8000 genes. Ranking pathways by significance revealed that the NARAC top-ranked ∼6% laid within the top 10% of WTCCC. Gene selection on those pathways identified 58 genes in WTCCC and 61 in NARAC; 21 of those were common (P(overlap)< 10(-21)), of which 16 were novel discoveries. Among the identified genes, we validated 10 known RA associations in WTCCC and 13 in NARAC, not discovered using single-SNP approaches on the same data. Gene ontology functional enrichment analysis on the identified genes showed significant over-representation of signalling activity (P< 10(-29)) in both studies. Our findings suggest a novel model of RA genetic predisposition, which involves cell-membrane receptors and genes in second messenger signalling systems, in addition to genes that regulate immune responses, which have been the focus of interest previously.

Demographic and motor features associated with the occurrence of neuropsychiatric and sleep complications of Parkinson's disease.

OBJECTIVE: To determine whether four key neuropsychiatric and sleep related features associated with Parkinson's disease (PD) are associated with the motor handicap and demographic data. BACKGROUND: The growing number of recognised non-motor features of PD makes routine screening of all these symptoms impractical. Here, we investigated the hypothesis that standard demographic data and the routine assessment of motor signs is associated with the presence of dementia, psychosis, clinically probable rapid eye movement (REM) sleep behavior disorder (cpRBD) and restless legs syndrome (RLS). METHODS: 775 patients with PD underwent standardised assessment of motor features and the presence of dementia, psychosis, cpRBD and RLS. A stepwise feature elimination procedure with fitted logistic regression models was applied to identify which/if any combination of demographic and motor factors is associated with each of the four studied non-motor features. A within-study out-of-sample estimate of the power of the predicted values of the models was calculated using standard evaluation procedures. RESULTS: Age and Hoehn&Yahr (H&Y) stage were strongly associated with the presence of dementia (p value<0.001 for both factors in the final selected model) while a combination of age, disease duration, H&Y stage, dopamine agonists and catechol-O-methyltransferase (COMT) inhibitors was associated with the presence of psychosis. Disease duration and H&Y stage were the significant indicators of cpRBD, and the lack of significant motor asymmetry was the only significant feature associated with RLS-type symptoms but the evidence of association was weak. CONCLUSIONS: Demographic and motor features routinely collected in patients with PD can estimate the occurrence of neuropsychiatric and sleep-related features of PD.

Using machine learning to examine drivers of inappropriate outpatient antibiotic prescribing in acute respiratory illnesses.

Using a machine-learning model, we examined drivers of antibiotic prescribing for antibiotic-inappropriate acute respiratory illnesses in a large US claims data set. Antibiotics were prescribed in 11% of the 42 million visits in our sample. The model identified outpatient setting type, patient age mix, and state as top drivers of prescribing.

famCNV: copy number variant association for quantitative traits in families.

UNLABELLED: A program package to enable genome-wide association of copy number variants (CNVs) with quantitative phenotypes in families of arbitrary size and complexity. Intensity signals that act as proxies for the number of copies are modeled in a variance component framework and association with traits is assessed through formal likelihood testing. AVAILABILITY AND IMPLEMENTATION: The Java package is made available at www.imperial.ac.uk/medicine/people/m.falchi/. CONTACT: m.falchi@imperial.ac.uk.

A machine learning model on Real World Data for predicting progression to Acute Respiratory Distress Syndrome (ARDS) among COVID-19 patients.

INTRODUCTION: Identifying COVID-19 patients that are most likely to progress to a severe infection is crucial for optimizing care management and increasing the likelihood of survival. This study presents a machine learning model that predicts severe cases of COVID-19, defined as the presence of Acute Respiratory Distress Syndrome (ARDS) and highlights the different risk factors that play a significant role in disease progression. METHODS: A cohort composed of 289,351 patients diagnosed with COVID-19 in April 2020 was created using US administrative claims data from Oct 2015 to Jul 2020. For each patient, information about 817 diagnoses, were collected from the medical history ahead of COVID-19 infection. The primary outcome of the study was the presence of ARDS in the 4 months following COVID-19 infection. The study cohort was randomly split into training set used for model development, test set for model evaluation and validation set for real-world performance estimation. RESULTS: We analyzed three machine learning classifiers to predict the presence of ARDS. Among the algorithms considered, a Gradient Boosting Decision Tree had the highest performance with an AUC of 0.695 (95% CI, 0.679-0.709) and an AUPRC of 0.0730 (95% CI, 0.0676 - 0.0823), showing a 40% performance increase in performance against a baseline classifier. A panel of five clinicians was also used to compare the predictive ability of the model to that of clinical experts. The comparison indicated that our model is on par or outperforms predictions made by the clinicians, both in terms of precision and recall. CONCLUSION: This study presents a machine learning model that uses patient claims history to predict ARDS. The risk factors used by the model to perform its predictions have been extensively linked to the severity of the COVID-19 in the specialized literature. The most contributing diagnosis can be easily retrieved in the patient clinical history and can be used for an early screening of infected patients. Overall, the proposed model could be a promising tool to deploy in a healthcare setting to facilitate and optimize the care of COVID-19 patients.

Myocardial depressant effects of interleukin 6 in meningococcal sepsis are regulated by p38 mitogen-activated protein kinase.

OBJECTIVES: Myocardial failure, leading to inotrope-unresponsive shock, is the predominant cause of death in meningococcal and other forms of septic shock. Proinflammatory cytokines released in septic shock are known to have myocardial depressant effects. We previously showed that interleukin 6 is a major myocardial depressant factor in children with meningococcal septicemia. In the current study, we aimed to investigate the mechanisms by which interleukin 6 induces myocardial failure in meningococcal sepsis and to identify potential novel therapeutic targets. DESIGN: Laboratory-based study. SETTING: University hospital and laboratories. PATIENTS: Children with a clinical diagnosis of meningococcal septic shock. METHODS: We studied interleukin 6-induced signaling events, both in vitro using isolated rat ventricular cardiac myocytes as a model of myocardial contractility and in whole blood from children with meningococcal sepsis. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We demonstrated involvement of Janus kinase 2, phosphatidylinositol 3-kinase, Akt, and p38 mitogen-activated protein kinase in interleukin 6-induced negative inotropy in isolated cardiac myocytes. Inhibition of p38 mitogen-activated protein kinase not only reversed interleukin 6-induced myocardial depression in both rat and human myocytes, but restored inotrope responsiveness. Cardiomyocytes transduced with dominant-negative p38 mitogen-activated protein kinase showed no interleukin 6-induced myocardial depression. To investigate p38 mitogen-activated protein kinase in vivo, we profiled global RNA expression patterns in peripheral blood of children with meningococcal septicemia. Transcripts for genes mapping to the p38 mitogen-activated protein kinase pathway showed significantly altered levels of abundance with a high proportion of genes of this pathway affected. CONCLUSIONS: Our findings demonstrate an integral role of the p38 mitogen-activated protein kinase pathway in interleukin 6-mediated cardiac contractile dysfunction and inotrope insensitivity. Dysregulation of the p38 mitogen-activated protein kinase pathway in meningococcal septicemia suggests that this pathway may be an important target for novel therapies to reverse myocardial dysfunction in patients with meningococcal septic shock who are not responsive to inotropic support.

HLA-C variants associated with amino acid substitutions in the peptide binding groove influence susceptibility to Kawasaki disease.

Kawasaki disease (KD) is a pediatric vasculitis caused by an unknown trigger in genetically susceptible children. The incidence varies widely across genetically diverse populations. Several associations with HLA Class I alleles have been reported in single cohort studies. Using a genetic approach, from the nine single nucleotide variants (SNVs) associated with KD susceptibility in children of European descent, we identified SNVs near the HLA-C (rs6906846) and HLA-B genes (rs2254556) whose association was replicated in a Japanese descent cohort (rs6906846 p = 0.01, rs2254556 p = 0.005). The risk allele (A at rs6906846) was also associated with HLA-C*07:02 and HLA-C*04:01 in both US multi-ethnic and Japanese cohorts and HLA-C*12:02 only in the Japanese cohort. The risk A-allele was associated with eight non-conservative amino acid substitutions (amino acid positions); Asp or Ser (9), Arg (14), Ala (49), Ala (73), Ala (90), Arg (97), Phe or Ser (99), and Phe or Ser (116) in the HLA-C peptide binding groove that binds peptides for presentation to cytotoxic T cells (CTL). This raises the possibility of increased affinity to a "KD peptide" that contributes to the vasculitis of KD in genetically susceptible children.

Diagnosis of Kawasaki Disease Using a Minimal Whole-Blood Gene Expression Signature.

Importance: To date, there is no diagnostic test for Kawasaki disease (KD). Diagnosis is based on clinical features shared with other febrile conditions, frequently resulting in delayed or missed treatment and an increased risk of coronary artery aneurysms. Objective: To identify a whole-blood gene expression signature that distinguishes children with KD in the first week of illness from other febrile conditions. Design, Setting, and Participants: The case-control study comprised a discovery group that included a training and test set and a validation group of children with KD or comparator febrile illness. The setting was pediatric centers in the United Kingdom, Spain, the Netherlands, and the United States. The training and test discovery group comprised 404 children with infectious and inflammatory conditions (78 KD, 84 other inflammatory diseases, and 242 bacterial or viral infections) and 55 healthy controls. The independent validation group comprised 102 patients with KD, including 72 in the first 7 days of illness, and 130 febrile controls. The study dates were March 1, 2009, to November 14, 2013, and data analysis took place from January 1, 2015, to December 31, 2017. Main Outcomes and Measures: Whole-blood gene expression was evaluated using microarrays, and minimal transcript sets distinguishing KD were identified using a novel variable selection method (parallel regularized regression model search). The ability of transcript signatures (implemented as disease risk scores) to discriminate KD cases from controls was assessed by area under the curve (AUC), sensitivity, and specificity at the optimal cut point according to the Youden index. Results: Among 404 patients in the discovery set, there were 78 with KD (median age, 27 months; 55.1% male) and 326 febrile controls (median age, 37 months; 56.4% male). Among 202 patients in the validation set, there were 72 with KD (median age, 34 months; 62.5% male) and 130 febrile controls (median age, 17 months; 56.9% male). A 13-transcript signature identified in the discovery training set distinguished KD from other infectious and inflammatory conditions in the discovery test set, with AUC of 96.2% (95% CI, 92.5%-99.9%), sensitivity of 81.7% (95% CI, 60.0%-94.8%), and specificity of 92.1% (95% CI, 84.0%-97.0%). In the validation set, the signature distinguished KD from febrile controls, with AUC of 94.6% (95% CI, 91.3%-98.0%), sensitivity of 85.9% (95% CI, 76.8%-92.6%), and specificity of 89.1% (95% CI, 83.0%-93.7%). The signature was applied to clinically defined categories of definite, highly probable, and possible KD, resulting in AUCs of 98.1% (95% CI, 94.5%-100%), 96.3% (95% CI, 93.3%-99.4%), and 70.0% (95% CI, 53.4%-86.6%), respectively, mirroring certainty of clinical diagnosis. Conclusions and Relevance: In this study, a 13-transcript blood gene expression signature distinguished KD from other febrile conditions. Diagnostic accuracy increased with certainty of clinical diagnosis. A test incorporating the 13-transcript disease risk score may enable earlier diagnosis and treatment of KD and reduce inappropriate treatment in those with other diagnoses.

Childhood tuberculosis is associated with decreased abundance of T cell gene transcripts and impaired T cell function.

The WHO estimates around a million children contract tuberculosis (TB) annually with over 80 000 deaths from dissemination of infection outside of the lungs. The insidious onset and association with skin test anergy suggests failure of the immune system to both recognise and respond to infection. To understand the immune mechanisms, we studied genome-wide whole blood RNA expression in children with TB meningitis (TBM). Findings were validated in a second cohort of children with TBM and pulmonary TB (PTB), and functional T-cell responses studied in a third cohort of children with TBM, other extrapulmonary TB (EPTB) and PTB. The predominant RNA transcriptional response in children with TBM was decreased abundance of multiple genes, with 140/204 (68%) of all differentially regulated genes showing reduced abundance compared to healthy controls. Findings were validated in a second cohort with concordance of the direction of differential expression in both TBM (r2 = 0.78 p = 2x10-16) and PTB patients (r2 = 0.71 p = 2x10-16) when compared to a second group of healthy controls. Although the direction of expression of these significant genes was similar in the PTB patients, the magnitude of differential transcript abundance was less in PTB than in TBM. The majority of genes were involved in activation of leucocytes (p = 2.67E-11) and T-cell receptor signalling (p = 6.56E-07). Less abundant gene expression in immune cells was associated with a functional defect in T-cell proliferation that recovered after full TB treatment (p<0.0003). Multiple genes involved in T-cell activation show decreased abundance in children with acute TB, who also have impaired functional T-cell responses. Our data suggest that childhood TB is associated with an acquired immune defect, potentially resulting in failure to contain the pathogen. Elucidation of the mechanism causing the immune paresis may identify new treatment and prevention strategies.

Genetic Variation in the SLC8A1 Calcium Signaling Pathway Is Associated With Susceptibility to Kawasaki Disease and Coronary Artery Abnormalities.

BACKGROUND: Kawasaki disease (KD) is an acute pediatric vasculitis in which host genetics influence both susceptibility to KD and the formation of coronary artery aneurysms. Variants discovered by genome-wide association studies and linkage studies only partially explain the influence of genetics on KD susceptibility. METHODS AND RESULTS: To search for additional functional genetic variation, we performed pathway and gene stability analysis on a genome-wide association study data set. Pathway analysis using European genome-wide association study data identified 100 significantly associated pathways (P<5×10-4). Gene stability selection identified 116 single nucleotide polymorphisms in 26 genes that were responsible for driving the pathway associations, and gene ontology analysis demonstrated enrichment for calcium transport (P=1.05×10-4). Three single nucleotide polymorphisms in solute carrier family 8, member 1 (SLC8A1), a sodium/calcium exchanger encoding NCX1, were validated in an independent Japanese genome-wide association study data set (meta-analysis P=0.0001). Patients homozygous for the A (risk) allele of rs13017968 had higher rates of coronary artery abnormalities (P=0.029). NCX1, the protein encoded by SLC8A1, was expressed in spindle-shaped and inflammatory cells in the aneurysm wall. Increased intracellular calcium mobilization was observed in B cell lines from healthy controls carrying the risk allele. CONCLUSIONS: Pathway-based association analysis followed by gene stability selection proved to be a valuable tool for identifying risk alleles in a rare disease with complex genetics. The role of SLC8A1 polymorphisms in altering calcium flux in cells that mediate coronary artery damage in KD suggests that this pathway may be a therapeutic target and supports the study of calcineurin inhibitors in acute KD.

Transforming growth factor-beta signaling pathway in patients with Kawasaki disease.

BACKGROUND: Transforming growth factor (TGF)-ß is a multifunctional peptide that is important in T-cell activation and cardiovascular remodeling, both of which are important features of Kawasaki disease (KD). We postulated that variation in TGF-ß signaling might be important in KD susceptibility and disease outcome. METHODS AND RESULTS: We investigated genetic variation in 15 genes belonging to the TGF-ß pathway in a total of 771 KD subjects of mainly European descent from the United States, the United Kingdom, Australia, and the Netherlands. We analyzed transcript abundance patterns using microarray and reverse transcriptase-polymerase chain reaction for these same genes, and measured TGF-ß2 protein levels in plasma. Genetic variants in TGFB2, TGFBR2, and SMAD3 and their haplotypes were consistently and reproducibly associated with KD susceptibility, coronary artery aneurysm formation, aortic root dilatation, and intravenous immunoglobulin treatment response in different cohorts. A SMAD3 haplotype associated with KD susceptibility replicated in 2 independent cohorts and an intronic single nucleotide polymorphism in a separate haplotype block was also strongly associated (A/G, rs4776338) (P=0.000022; odds ratio, 1.50; 95% confidence interval, 1.25 to 1.81). Pathway analysis using all 15 genes further confirmed the importance of the TGF-ß pathway in KD pathogenesis. Whole-blood transcript abundance for these genes and TGF-ß2 plasma protein levels changed dynamically over the course of the illness. CONCLUSIONS: These studies suggest that genetic variation in the TGF-ß pathway influences KD susceptibility, disease outcome, and response to therapy, and that aortic root and coronary artery Z scores can be used for phenotype/genotype analyses. Analysis of transcript abundance and protein levels further support the importance of this pathway in KD pathogenesis.

A heterotypic bystander effect for tumor cell killing after adeno-associated virus/phage-mediated, vascular-targeted suicide gene transfer.

Suicide gene transfer is the most commonly used cytotoxic approach in cancer gene therapy; however, a successful suicide gene therapy depends on the generation of efficient targeted systemic gene delivery vectors. We recently reported that selective systemic delivery of suicide genes such as herpes simplex virus thymidine kinase (HSVtk) to tumor endothelial cells through a novel targeted adeno-associated virus/phage vector leads to suppression of tumor growth. This marked effect has been postulated to result primarily from the death of cancer cells by hypoxia following the targeted disruption of tumor blood vessels. Here, we investigated whether an additional mechanism of action is involved. We show that there is a heterotypic "bystander" effect between endothelial cells expressing the HSVtk suicide gene and tumor cells. Treatment of cocultures of HSVtk-transduced endothelial cells and non-HSVtk-transduced tumor cells with ganciclovir results in the death of both endothelial and tumor cells. Blocking of this effect by 18alpha-glycyrrhetinic acid indicates that gap junctions between endothelial and tumor cells are largely responsible for this phenomenon. Moreover, the observed bystander killing is mediated by connexins 43 and 26, which are expressed in endothelial and tumor cell types. Finally, this heterotypic bystander effect is accompanied by a suppression of tumor growth in vivo that is independent of primary gene transfer into host-derived tumor vascular endothelium. These findings add an alternative nonmutually exclusive and potentially synergistic cytotoxic mechanism to cancer gene therapy based on targeted adeno-associated virus/phage and further support the promising role of nonmalignant tumor stromal cells as therapeutic targets.

Pathway analysis of GWAS provides new insights into genetic susceptibility to 3 inflammatory diseases.

Although the introduction of genome-wide association studies (GWAS) have greatly increased the number of genes associated with common diseases, only a small proportion of the predicted genetic contribution has so far been elucidated. Studying the cumulative variation of polymorphisms in multiple genes acting in functional pathways may provide a complementary approach to the more common single SNP association approach in understanding genetic determinants of common disease. We developed a novel pathway-based method to assess the combined contribution of multiple genetic variants acting within canonical biological pathways and applied it to data from 14,000 UK individuals with 7 common diseases. We tested inflammatory pathways for association with Crohn's disease (CD), rheumatoid arthritis (RA) and type 1 diabetes (T1D) with 4 non-inflammatory diseases as controls. Using a variable selection algorithm, we identified variants responsible for the pathway association and evaluated their use for disease prediction using a 10 fold cross-validation framework in order to calculate out-of-sample area under the Receiver Operating Curve (AUC). The generalisability of these predictive models was tested on an independent birth cohort from Northern Finland. Multiple canonical inflammatory pathways showed highly significant associations (p 10(-3)-10(-20)) with CD, T1D and RA. Variable selection identified on average a set of 205 SNPs (149 genes) for T1D, 350 SNPs (189 genes) for RA and 493 SNPs (277 genes) for CD. The pattern of polymorphisms at these SNPS were found to be highly predictive of T1D (91% AUC) and RA (85% AUC), and weakly predictive of CD (60% AUC). The predictive ability of the T1D model (without any parameter refitting) had good predictive ability (79% AUC) in the Finnish cohort. Our analysis suggests that genetic contribution to common inflammatory diseases operates through multiple genes interacting in functional pathways.