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SUPPLEMENTARY DATA Low-Dose Azathioprine with Allopurinol For

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SUPPLEMENTARY DATA Low-Dose Azathioprine With Allopurinol For Inflammatory Bowel Disease: DNA-Incorporated Deoxythioguanine and Transcriptome Analysis as Biological Indicators Sally A. Coulthard1*, Phil Berry2, Sarah McGarrity2, Simon McLaughlin3, Azhar Ansari4 and Christopher P. F. Redfern2 1Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne; 2Northern Institute of Cancer Research, Newcastle University, Newcastle upon Tyne; 3Department of Gastroenterology, Royal Bournemouth Hospital, Bournemouth, Dorset; Faculty of health and social sciences, Bournemouth University, Bournemouth, Dorset 4Gastroenterology Dept., East Surrey Hospital, Redhill, East Surrey Corresponding author *Dr Chris Redfern Northern Institute for Cancer Research, Newcastle University, Medical School, Framlington Place, Newcastle upon Tyne, NE2 4HH Telephone: +44 191 208 4416 Email: [email protected] LIST OF SUPPLEMENTARY DATA Supplementary Figure 1: Linear model of DNA-incorporated dTG with time. Supplementary Table 1- Samples by site Supplementary Table 2 Genes significantly repressed > 1.5 fold in response to LDAA treatment Supplementary Table 3 Genes significantly over-expressed > 1.5 fold in response to LDAA treatment Supplementary Table 4 Gene Ontologies with significant enrichment for genes repressed > 1.5 fold in response to LDAA treatment BH FDR < 0.001 Supplementary Table 5 Gene Ontologies with significant enrichment for genes over-expressed > 1.5 fold in response to LDAA treatment BH FDR < 0.001 Supplementary Table 6 Genes significantly repressed > 1.5 fold in response to AZA treatment Supplementary Table 7 Genes significantly over-expressed > 1.5 fold in response to AZA treatment Supplementary Table 8 Gene Ontologies with significant enrichment for genes repressed > 1.5 fold in response to AZA treatment BH FDR < 0.05 Supplementary Table 9 Gene ontologies with significant enrichment for genes over-expressed in response to AZA for a sub-sample of three of the five AZA-treated patients Supplementary Table 10 Genes significantly repressed or over-expressed_> 1.5 fold in both LDAA and AZA-treated patients. Supplementary Table 11 Gene ontology terms associated with genes common to LDAA and AZA treatments. Supplementary Figure 1 Linear model of dTG versus time category (approximately equal intervals of around 84 days or 12 weeks). A Box-Cox transformation (dTG values raised to power of 0.22) was applied to normalise dTG data. Red symbols are ESH data, with solid fill representing LDAA patients and open symbols are AZA-treated patients. Black (open) symbols are AZA-treated patients from other sites. Red lines are a linear model (additive for time and drug effects) fitted to the ESH data for LDAA- (solid lines) and AZA-treated patients (dashed line); in this model the drug effect was significant (ANOVA, F1,55 = 7.8, P = 0.007 ). The black line is the same model fitted to all data (ie ESH data plus data from other sites for AZA-treated patients) as the drug effect was marginal (ANOVA, F1,122 = 3.4, P = 0.066 ). For both models, the effect of time category was significant (ANOVA, P ≤ 0.011). Similar results were obtained using time on therapy for each patient as a continuous predictor. Number of patients in each time period by drug group. All sites ESH only Days AZA LDAA AZA LDAA < 84 14 2 2 2 84-167 13 9 5 9 168-252 3 2 1 2 > 252 67 35 19 35 total 97 48 27 48 Supplementary Table 1- Samples by site: patients on full-dose azathioprine alone (AZA) or receiving low-dose azathioprine with allopurinol (LDAA) and with measurements of DNA-incorporated thiopurines in nucleated blood cells (NBC) Number of patients Site code AZA LDAA* CHS 6 0 DCH 2 0 ESH 27 48 NF 9 0 NTH 31 0 RBCH 12 0 STH 5 0 STT 5 0 *LDAA samples from sites other than ESH were excluded from analyses as these were from patients transferred from AZA rather than thiopurine-naïve patients as at ESH. One patient in the LDAA group at ESH was treated with the xanthine oxidase inhibitor Febuxostat instead of allopurinol. Table S2: LDAA, genes repressed on treatment compared to pre-treatment sample. Gene Symbol Entrez ID logFC logCPM LR PValue AANAT 15 -1.191504596 1.324612827 28.54951625 9.13E-08 ABHD12B 145447 -0.986452883 4.531484448 18.78955774 1.46E-05 ACO1 48 -0.783656985 5.053360859 20.78661167 5.13E-06 ACSL1 2180 -0.584765836 10.23477937 3.942845788 0.047071085 ACVR1B 91 -0.47842508 4.571553125 4.379700651 0.036369384 ADAM19 8728 -0.404583862 7.469457161 5.018490248 0.025078026 ADAM9 8754 -0.662526487 4.794411938 10.25916162 0.001360075 ADAMTSL4 54507 -0.436392631 7.478503265 6.063773844 0.013798252 ADAR 103 -0.422429673 9.370059669 4.31356443 0.03780966 ADCY3 109 -0.606639585 3.039347632 5.120584247 0.023643655 ADCY4 196883 -0.430251513 3.460026976 4.577854984 0.032387734 ADGRG2 10149 -0.607721356 1.810953283 5.494836664 0.019072709 ADGRG3 222487 -0.623722929 7.616781091 7.383446588 0.00658269 ADORA2A-AS1 646023 -0.628243252 2.091308555 10.24197822 0.001372803 AGBL5 60509 -0.623074106 4.023774624 9.079298561 0.002585192 AIM2 9447 -0.920724303 4.755777695 13.56699 0.000230198 AIMP2 7965 -0.502652954 1.490324981 5.500503006 0.019011004 AIRN 100271873 -0.473067169 3.765751623 6.472855782 0.010953438 ALKBH4 54784 -0.701325757 3.128429544 12.78418703 0.000349562 ALOX12 239 -0.481116481 4.175854528 8.143950049 0.004320506 ALOX5AP 241 -0.431179132 6.818494065 4.352406918 0.036956681 ANKDD1A 348094 -0.568099138 3.528232188 9.893524729 0.001658614 ANKRD18A 253650 -0.857095233 2.193215273 4.554505547 0.032832243 ANKRD22 118932 -1.302621522 2.908321407 14.6336721 0.000130561 ANKRD33B 651746 -0.677244001 4.488250653 8.171228444 0.004256007 ANKRD55 79722 -0.558854337 2.287387423 5.154498274 0.023186233 ANKS1B 56899 -1.788773459 2.052243775 65.64147302 5.41E-16 ANXA3 306 -0.899354839 6.677726157 4.700177436 0.030159504 AP4B1-AS1 100287722 -0.723104081 2.234951007 8.204900218 0.004177741 AP5B1 91056 -0.512562208 7.553037305 5.613662657 0.017820976 APOBEC3A 200315 -0.40269303 5.358019084 5.489413669 0.019131958 APOBEC3B 9582 -0.820162744 4.55877326 16.18031254 5.76E-05 APOL6 80830 -0.456430485 7.795859284 6.288499894 0.012152386 APOM 55937 -0.449254091 1.934277656 3.921347361 0.047676655 APTR 100505854 -0.517840352 3.086688847 5.932742172 0.014862097 ARGFXP2 503640 -0.714192965 2.765115491 11.6138282 0.000654633 ARHGAP24 83478 -0.477043503 4.204166096 4.54104686 0.033091349 ARHGAP26-AS1 100874239 -0.662540571 3.406569233 10.81107451 0.001008947 ARHGEF26 26084 -0.674347617 1.86755273 6.727906848 0.009491592 ARRDC5 645432 -0.467424329 2.766723783 4.332910116 0.037382281 ASAP1-IT2 100507117 -0.666691674 2.653748914 7.771574877 0.005307476 ASB14 142686 -0.67499297 2.28964838 6.062183961 0.013810679 ASB9P1 728619 -0.596545537 1.799497598 6.724579666 0.009509314 ASGR2 433 -0.689107869 3.002909194 5.781688426 0.016193978 ASPH 444 -0.551813978 6.051991591 3.845395817 0.049882746 ATAT1 79969 -0.552295203 1.775410353 6.615212249 0.010111129 ATP11B 23200 -0.433723305 7.867978251 4.088934181 0.043164853 ATP1A1-AS1 84852 -0.582602724 2.477017817 7.816144317 0.005178155 ATP8B1 5205 -0.447677953 4.295545412 5.339927615 0.020842339 ATP8B4 79895 -0.847306735 5.958904608 4.746824027 0.029352421 B4GALT5 9334 -0.569267302 7.380725393 6.029819772 0.014066169 BAIAP2L1 55971 -0.987990399 2.892133757 23.42684762 1.30E-06 BATF2 116071 -1.494752715 2.544983925 26.18651703 3.10E-07 BCL6 604 -0.615072682 8.833857711 6.416237575 0.011308149 BEAN1 146227 -0.732015198 2.013132929 9.620553006 0.001924118 BEND7 222389 -0.600543732 2.345892933 4.607443301 0.031833461 BMP8A 353500 -0.499064505 1.999112403 5.955288265 0.014673203 BMX 660 -0.784964522 3.693910467 6.08654257 0.013621538 BORCS8 729991 -0.452609747 3.130157993 6.585247864 0.01028273 BRD7P3 23629 -0.598663576 2.707637311 7.871535867 0.005021898 BST1 683 -0.475427223 5.873362641 5.850535938 0.015572308 BYSL 705 -0.562295904 3.734967314 5.194837959 0.022654067 C10orf11 83938 -0.654729685 1.344634775 7.302788606 0.006884768 C11orf42 160298 -0.927543259 1.973936626 14.0103997 0.000181802 C11orf95 65998 -0.424674072 2.3710683 4.006855202 0.0453156 C19orf44 84167 -0.534213581 1.223540751 5.948341919 0.014731136 C1orf56 54964 -1.398041657 3.727599521 56.17083581 6.64E-14 C1QTNF7 114905 -0.575618543 2.644362376 8.763635894 0.003072958 C1RL 51279 -0.509435505 6.454531116 6.35357757 0.011714483 C1RL-AS1 283314 -0.555853253 5.193299513 8.633421739 0.003300511 C3AR1 719 -0.810180226 4.68445987 10.43001619 0.001239837 C4orf19 55286 -0.492535654 1.445163008 5.178870191 0.022863186 C5orf45 51149 -0.82724434 2.878315477 18.86241161 1.40E-05 C5orf56 441108 -0.862877091 4.873769155 22.19073138 2.47E-06 C5orf58 133874 -0.530099852 4.206036802 6.629077111 0.010032723 C5orf66 100996485 -0.948506242 3.53592578 20.60069841 5.66E-06 C7orf49 78996 -0.757919495 5.509912325 14.42424983 0.000145911 C9orf139 401563 -0.550191759 3.959176642 7.708631501 0.00549574 C9orf66 157983 -0.496741255 3.373525672 7.298628557 0.006900726 C9orf84 158401 -0.978079393 7.22180488 12.32599657 0.000446693 CA4 762 -0.760642162 3.633501924 6.987731825 0.008207029 CACNA1E 777 -1.24199829 4.661005458 14.1590688 0.000167985 CAMKK2 10645 -0.437277538 7.08271834 4.453334581 0.034833166 CAPN12 147968 -0.59793688 2.529527543 9.351864544 0.002227587 CAPN3 825 -0.501043269 4.502391772 4.611278117 0.031762352 CAPNS2 84290 -0.604481025 1.759750407 4.108790905 0.042660851 CARD14 79092 -0.767677995 3.079932618 10.31699472 0.001318108 CARD17 440068 -0.481123117 1.41264383 5.015238385 0.02512517 CARD6 84674 -0.541309494
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    Cellular and Molecular Signatures in the Disease Tissue of Early Rheumatoid Arthritis Stratify Clinical Response to csDMARD-Therapy and Predict Radiographic Progression Frances Humby1,* Myles Lewis1,* Nandhini Ramamoorthi2, Jason Hackney3, Michael Barnes1, Michele Bombardieri1, Francesca Setiadi2, Stephen Kelly1, Fabiola Bene1, Maria di Cicco1, Sudeh Riahi1, Vidalba Rocher-Ros1, Nora Ng1, Ilias Lazorou1, Rebecca E. Hands1, Desiree van der Heijde4, Robert Landewé5, Annette van der Helm-van Mil4, Alberto Cauli6, Iain B. McInnes7, Christopher D. Buckley8, Ernest Choy9, Peter Taylor10, Michael J. Townsend2 & Costantino Pitzalis1 1Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK. Departments of 2Biomarker Discovery OMNI, 3Bioinformatics and Computational Biology, Genentech Research and Early Development, South San Francisco, California 94080 USA 4Department of Rheumatology, Leiden University Medical Center, The Netherlands 5Department of Clinical Immunology & Rheumatology, Amsterdam Rheumatology & Immunology Center, Amsterdam, The Netherlands 6Rheumatology Unit, Department of Medical Sciences, Policlinico of the University of Cagliari, Cagliari, Italy 7Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow G12 8TA, UK 8Rheumatology Research Group, Institute of Inflammation and Ageing (IIA), University of Birmingham, Birmingham B15 2WB, UK 9Institute of
  • UNIVERSITY of CALIFORNIA RIVERSIDE Investigations Into The

    UNIVERSITY of CALIFORNIA RIVERSIDE Investigations Into The

    UNIVERSITY OF CALIFORNIA RIVERSIDE Investigations into the Role of TAF1-mediated Phosphorylation in Gene Regulation A Dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Cell, Molecular and Developmental Biology by Brian James Gadd December 2012 Dissertation Committee: Dr. Xuan Liu, Chairperson Dr. Frank Sauer Dr. Frances M. Sladek Copyright by Brian James Gadd 2012 The Dissertation of Brian James Gadd is approved Committee Chairperson University of California, Riverside Acknowledgments I am thankful to Dr. Liu for her patience and support over the last eight years. I am deeply indebted to my committee members, Dr. Frank Sauer and Dr. Frances Sladek for the insightful comments on my research and this dissertation. Thanks goes out to CMDB, especially Dr. Bachant, Dr. Springer and Kathy Redd for their support. Thanks to all the members of the Liu lab both past and present. A very special thanks to the members of the Sauer lab, including Silvia, Stephane, David, Matt, Stephen, Ninuo, Toby, Josh, Alice, Alex and Flora. You have made all the years here fly by and made them so enjoyable. From the Sladek lab I want to thank Eugene, John, Linh and Karthi. Special thanks go out to all the friends I’ve made over the years here. Chris, Amber, Stephane and David, thank you so much for feeding me, encouraging me and keeping me sane. Thanks to the brothers for all your encouragement and prayers. To any I haven’t mentioned by name, I promise I haven’t forgotten all you’ve done for me during my graduate years.
  • Supplementary Table S4. FGA Co-Expressed Gene List in LUAD

    Supplementary Table S4. FGA Co-Expressed Gene List in LUAD

    Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase
  • Greg's Awesome Thesis

    Greg's Awesome Thesis

    Analysis of alignment error and sitewise constraint in mammalian comparative genomics Gregory Jordan European Bioinformatics Institute University of Cambridge A dissertation submitted for the degree of Doctor of Philosophy November 30, 2011 To my parents, who kept us thinking and playing This dissertation is the result of my own work and includes nothing which is the out- come of work done in collaboration except where specifically indicated in the text and acknowledgements. This dissertation is not substantially the same as any I have submitted for a degree, diploma or other qualification at any other university, and no part has already been, or is currently being submitted for any degree, diploma or other qualification. This dissertation does not exceed the specified length limit of 60,000 words as defined by the Biology Degree Committee. November 30, 2011 Gregory Jordan ii Analysis of alignment error and sitewise constraint in mammalian comparative genomics Summary Gregory Jordan November 30, 2011 Darwin College Insight into the evolution of protein-coding genes can be gained from the use of phylogenetic codon models. Recently sequenced mammalian genomes and powerful analysis methods developed over the past decade provide the potential to globally measure the impact of natural selection on pro- tein sequences at a fine scale. The detection of positive selection in particular is of great interest, with relevance to the study of host-parasite conflicts, immune system evolution and adaptive dif- ferences between species. This thesis examines the performance of methods for detecting positive selection first with a series of simulation experiments, and then with two empirical studies in mammals and primates.