Arevir 2008 1 ES / Bonn Apr 2008 Arevir University of Cologne - PowerPoint PPT Presentation

University of Cologne Institute of Virology Arevir 2008 1 ES / Bonn Apr 2008

Arevir University of Cologne Institute of Virology Analysis of resistance mutations of HI-Virus Bioinformatics analysis of relations between mutations of the HIV genome and phenotypical drug resistance for the optimization of anti-retroviral therapies Eugen Schülter Institut für Virologie der Universität zu Köln - Cologne center of advanced european studies and research - Bonn 2 ES / Bonn Apr 2008

Background University of Cologne Institute of Virology The Arevir project 1) is founded by Daniel Hoffmann, Rolf Kaiser and 1999 Joachim Selbig. Aim: develop computer based methods to enhance the interpretation of genotipic resistance tests. 2000 Niko Beerenwinkel created the basis for Arevir in his dissertation: Computational Analysis of HIV Drug Resistance Data 2001 Barbara Schmidt, Hauke Walter and Klaus Korn provided ~ 650 genotype � phenotype pairs 2001 First version of geno2pheno available online, predicting drug resistance from genotype 2006 Collaboration with EuResist (www.euresist.org) 2008 New Arevir DB and user interface version 1) The project was funded by the German Research Foundation (Grants HO 1582/1-1 to -3 and KA 1569/1-1 to -3) 3 ES / Bonn Apr 2008

Background University of Cologne Institute of Virology Why develop computer based methods? VL Therapy should be switched Resistance Test t We have to deal with: But: Selection of the optimal therapy remains a hard task! VL, CD4, side effects, preferences, resistance … Genotype: 41L, 67N, 68G, 70R, 86DE, 88S, 90I, 102Q, 103S, 118IV, 135T, 162H, 190A, 203DE, 210W, 211K, 214F, 215Y, 219E, 228H, 248D, 277K, 283I, 326V, 329IV, 334L We need a database to find out more about mutations and resistance, correlate therapies with clinical outcome etc. 4 ES / Bonn Apr 2008

Arevir DB basics University of Cologne Institute of Virology The Arevir DB is a relational database (MySQL version 5.0x) consisting of 54 tables and 14 views organized in 5 groups: � Patient related data (demographic data and diagnoses) � Therapy data � Isolate related data (serology, clinical chemistry) � Genotipic data (mutations) � Administrative data (access rights etc.) 5 ES / Bonn Apr 2008

Arevir Protection/Security University of Cologne Institute of Virology Connection to Arevir is only possible: � With SSH (secure shell) � Using public/private key authorization � From a computer whose IP-Address is in a subnet known to Arevir Restricted access to the data � Only people involved in patient care (e.g. responsible for diagnostic findings) have access to all data � Bioinformatics receive a copy of anonymized data Use of pseudonyms � When a new patient record is added a pseudonym using the SHA-1 algorithm is generated to facilitate data exchange without name disclosure 6 ES / Bonn Apr 2008

Security concept University of Cologne Institute of Virology Internet Rosie Internet SSH tunnel SSH User PC tunnel HTTP Mail Firewall FTP Telnet … SSH-Daemon Arevir security overview Arevir-DB Arevir- Server 7 ES / Bonn Apr 2008

Selbigs Data Funnel University of Cologne Institute of Virology For a meaningful correlation a large amount of data is needed! Sequences s Sequence Therapies Therapies s s t t n n e e i i t t a a 4 P 4 P V V D D L L C C 2001 2005 Data from ~ 500 Data from ~ 4500 patients � ~ 350 patients � ~ 150 records suitable records suitable for evaluation for evaluation Steady small result despite of an increasing amount of data 8 ES / Bonn Apr 2008

Arevir before 2008 University of Cologne Institute of Virology Arevir in June 2005 Arevir in February 2007 Patients ~ 4.500 Patients 2.444 Diagnoses ~ 2.900 Diagnoses 4.412 Therapies ~ 12.000 Therapies 6.154 CD4 values ~ 52.000 CD4 values 53.031 VL values ~ 41.000 VL values 25.972 Sequences ~ 3.000 Sequences 2.180 9 ES / Bonn Apr 2008

Data cleansing University of Cologne Institute of Virology Small errors can have quite big effects: VL 20.06.200 2 4,0 1,6 t Therapy A Therapy B 12W (15.06.2002) TCE 15.03.2002 10 ES / Bonn Apr 2008

Rosie University of Cologne Institute of Virology 11 ES / Bonn Apr 2008

Arevir 2008 University of Cologne Institute of Virology Arevir in May 2008 Arevir in June 2005 Arevir in February 2007 Patients ~ 4.500 Patients 2.444 Patients ~ 5.600 Diagnoses ~ 2.900 Diagnoses 4.412 Diagnoses ~ 9.200 Therapies ~ 12.000 Therapies 6.154 Therapies ~ 9.800 CD4 values ~ 52.000 CD4 values 53.031 Isolate - VL values ~ 41.000 VL values 25.972 values ~ 230.000 Sequences ~ 3.000 Sequences 2.180 Sequences ~ 5.100 12 ES / Bonn Apr 2008

Conclusions University of Cologne Institute of Virology Databases can help to improve the health condition of HIV infected. � By supporting therapy optimization algorithms � By enhancing our understanding of HIV But to extract useful information from a database, a large amount of data with high quality is needed! 13 ES / Bonn Apr 2008

Thank you! University of Cologne Institute of Virology Alexander Thielen Andre Altmann Bernd Kupfer Bettina Jaster Christian von Behren Claudia Müller Clemens Kühn Daniel Hoffmann Daniel Gillor Dörte Hammerschmidt Elena Knops Eu Resist Gerd Fätkenheuer 14 ES / Bonn Apr 2008 H k W l

University of Cologne Institute of Virology 15 ES / Bonn Apr 2008

Data cleansing I University of Cologne Institute of Virology Cleansing of patient names and assignment of an unique patient ID was done with new fuzzy indices (name aliases allowed) André Ramirez 23.03.1969 Andre Ramires 23.03.1969 Hans-Peter Schmidt 05.11.1982 Hans Schmidt 05.11.1982 Georgios Koehler 15.04.1958 Georgious Koeler 15.04.1958 Anna Meier 29.12.1978 Anna da Silveira 29.12.1978 John Miller 16.03.1970 John Miller 10.03.1970 Mgabe Osamba 12.04.1974 Ossamba Mgabe 11.04.1974 Examples are fictive! 16 ES / Bonn Apr 2008

Data cleansing II University of Cologne Institute of Virology Several checks applied to uncover suspicious data: � Genotypes without sampling date � Duplicate genotypes � Overlapping therapies � Date checks (e.g. infection < first positive test < first treatment etc.) � Therapies with 'forbidden' drug combinations � More than one isolate value (of a kind) in a period of 14 days � Same isolate value for different dates � Lab values out of specified range (e.g. HIVRNA > 10.000.000 copies/ml) � . . . Data cleansing is hard work, time consuming, tedious but absolutely necessary! 17 ES / Bonn Apr 2008

Arevir DB 'Scheme' University of Cologne Institute of Virology diagnoses identity 7431 2342 2342 Max Muster patients 'R75' 17.03.1963 2342 'FA3E359D1..' 1963 'M' 'IVDA' therapycom- therapies isolates ponents 4288 12630 2342 4288 2342 2002-06-23 '3TC' 2002-06-02 2003-11-05 150 mg isolate_values sequences 12630 2966 'HIVRNA' 12630 mutations 'bDNA' 'CCTCAGATC...' 165000 2966 3247583203 K65R, L74V... 18 ES / Bonn Apr 2008

Backup I University of Cologne Institute of Virology Silent Mutations Subtype B 10,0 9,0 8,0 PRO (treated) RT (treated) 7,0 PRO (naive) RT (naive) 6,0 5,0 4,0 1999 2000 2001 2002 2003 2004 2005 2006 19 ES / Bonn Apr 2008