Preterm Birth Network: Knowledge Base and Field Synopsis

1. Developing and Updating Cumulative Evidence on Genetic Associations: Experiences to date Preterm Birth Network: Knowledge Base and Field Synopsis Siobhan Dolan, MD, MPH Albert Einstein College of Medicine, Bronx, NY Network of Networks Meeting, November 2006, Venice, Italy

2. Activation of Maternal/Fetal HPA Axis Inflammation Pathological Uterine Distention Decidual Hemorrhage Abruption • Infection: - Chorion-Decidual - Systemic • Multifetal Preg • Polyhydramnios • Uterine abnormalities • Maternal-Fetal Stress • Premature Onset of Physiologic Initiators Prothrombin G20210A Factor V Leiden Protein C, S, Z Type 1 Plasminogen MTHFR Interleukins IL-1, IL-5, IL-8 TNF-a Fas L Gap jct IL-8 PGE2 Oxytocin recep CRH E1-E3 Mechanical stretch Chorion Decidua + CRH CYP1A1 GSTT1 Susceptibility to Environmental toxins + MMPs proteases uterotonins pPROM Uterine Contractions Cervical Change PTB Adapted from: Lockwood CJ, Paediatr Perinat Epidemiol 2001;15:78 and Wang X, et al. Paediatr Perinat Epidemiol 2001; 15: 63

3. Preterm Birth Network Update • Efforts to secure funding for a large collaborative study have been unsuccessful to date. • A modest number of researchers continue to be funded individually through MOD, NIH, etc. • Active researchers (internationally) remain interested in collaborating • PREBIC – the Preterm Birth International Collaborative and its subcommittee PREGENIA – the Preterm Birth and Genetics International Alliance remain active with joint projects and an annual meeting (last one held 4/06 in Geneva and next is scheduled for 9/07 in Italy).

4. Preterm Birth Network Joint Projects • Published paper on Genetic epidemiologic studies of preterm birth: Guidelines for research in the American Journal of Obstetrics and Gynecology

5. Guidelines for Research

6. Preterm Birth Network Joint Projects • The paper outlined: • Phenotypic criteria • Study Design: Including minimum and optimal data set for genetic epidemiology studies into preterm birth • Considerations in the selection of a control population • Candidate gene selection • The paper represents a first step in standardization across the field.

7. Invited Scientific Session at the ASHG meeting in New Orleans in October, 2006 SESSION 48 – Preterm Birth as a Common Complex Disorder: The Implications of Applied Genomic Research • 4:00 PMIntroduction. C. A. Moore, Centers for Disease Control and Prevention, Atlanta , GA. • 4:05 PMHeritability in prematurity: New insights into the genetics of preterm birth. K. Ward, Kapi'olani Hospital, Honolulu , HI . • 4:30 PMGenetics to genomics: A framework for approaching preterm birth as a common complex disorder. S. Dolan, March of Dimes, and Albert Einstein College of Medicine, White Plains , NY . • 4:55 PMMeta-analysis and knowledge integration: Implications for research on complex disease. J. P. Ioannidis, University of Ioannina School of Medicine , Ioannina , Greece . • 5:20 PMImplications of applied genomic research for public health: What will it take to bring down the rate of preterm birth? M. Khoury, Centers for Disease Control and Prevention, Atlanta , GA. • 5:40 PMQ&A

8. Invited Scientific Session at the ASHG meeting in New Orleans in October, 2006 • Generated interest amongst geneticists • Stimulated ASHG to consider reaching out to SMFM (Society for Maternal Fetal Medicine) as a “key partner”

9. Perinatal Genomics Knowledge Base • Major focus of effort in the past year • Grant application to develop a perinatal genomics knowledge base was submitted in response to a Translational Bioinformatics RFP to the National Library of Medicine at NIH on October 1, 2005. • Reviews in early 2006: • positive on importance, collaborators, and approach • negative on bioinformatics capacity • Resubmission in conjunction with the Bioinformatics Shared Resource at Albert Einstein College of Medicine in NYC just took place on November 1, 2006.

10. Context for Perinatal Genomics Knowledge Base

11. Published Data Unpublished Data Preterm Birth Network Data Albert Einstein Preterm Birth Knowledge Base EMBASE CDC Pub Lit NCBI (PubMed, Gene) Study platform metadata including aggregate clinical and covariate data Minimal data elements for study “Grey Literature”: unpublished results from web or personal communication Search by investigator, gene, author, interactive factor, study type… Browse and compare clinical and epidemiologic data from various study platforms Browse and conduct meta-analysis based on published literature data. - Browse investigator profiles. - Investigator login and ability to update study and profile. Translational engine • data processing • secondary data analysis • etc.

12. Perinatal Genomics Knowledge Base • Review asked us to be explicit about • What information we’re collecting • From where? • What are we doing with it?

13. Knowledge base is organized in three major components • The knowledge base will have three major components : • Investigators • Studies/data collection platforms • Literature (published and “grey”)

14. What are we collecting? • For the registry of investigators, the following key data will be collected from each contributor: • Last name, First name, Middle initial • Institution • Address • PI / Lab • Web site • Email • Phone number (s) • Statement of research interests • Key words describing research interests

15. What are we collecting? • For the registry of studies or data collection platforms, the following key data will be collected about each study or data collection platform that is contributed. • Last name, First name, Middle initial of PI • Name of study • Grant (if applicable) • Web site for study • Abstract of study • Type of study (cohort, case control, family based, etc) • # cases/controls or # in cohort or # parent-child trios • Definitions of cases and controls • Eligibility criteria – including inclusion and exclusion criteria • Methods for assessing phenotype and genotype • Quality checks (if any) on phenotype and genotype • Missing data • Location of study • Dates of enrollment • Types of participants • Age of participants • Race of participants • Geographic area of study

16. What are we collecting? • For the compendium of published and grey literature, the following data will be extracted for the knowledge base from each item to be entered: • Last name, First name, Middle initial of first author • Last name, First name, Middle initial of all subsequent authors • Type of information (abstract, conference proceeding, unpublished data, published journal article) • Peer-reviewed or not • Citation information with link to PUBMED abstract or other electronic access if available • For each study, the following data about gene disease association will be extracted and entered into the knowledge base: • Gene studied – with links to Entrez gene at http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=gene • Protein studied – with links to Entrez protein at http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=protein&cmd=search • Polymorphism studied – with links to dbSNP at http://www.ncbi.nlm.nih.gov/SNP/ • Chromosomal location studied • Keywords • Outcome studied (preterm birth, very preterm birth) • Modifiers (environmental agents) • Ethnic group (Caucasian, continent, etc) • Population studied (country) • Type of study and #cases / # controls, # triads, # in cohort • Phenotype description: Spontaneous, Ruptured membranes, chorioamnionitis, exact gestational age in weeks • Population genotyped – maternal, fetal, paternal • Association detected? Positive or negative? • Effect size (RR or OR with 95% CI / p value)

17. What are we collecting? • The data will be extracted in a standardized manner and will be stored using controlled vocabularies. This includes HUGO (Human Genome Organization nomenclature), ICD-10 (International Classification of Disease-10th revision), UMLS (Unified Medical Language System Metathesaurus) for genes and outcomes. • The clinical data outlined in the Guidelines paper by Pennell et al. will be used as the starting point for the clinical and phenotypic vocabulary, and will be refined by the project team with input from the Advisory Committee.

18. Sources of Evidence The published literature PUBMED – http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed EMBASE – http://www.embase.com/ ISI Science Citation Index - http://scientific.thomson.com/products/sci/ BIOSIS - http://www.biosis.org/ PLoS (Public Library of Science) - http://www.plos.org/index.php The HuGE Published Literature database (http://www.cdc.gov/genomics/hugenet) The “grey” literature Conference proceedings Books Abstracts Technical reports Journals not available in electronic searches Conference proceedings and abstract books of highest yield will be those from the American Society of Human Genetics, Society for Maternal Fetal Medicine, Society for Gynecologic Investigation, American College of Medical Genetics, and the American College of Obstetricians and Gynecologists.

19. PubMed Search Strategy

20. EMBASE Search Strategy

21. EMBASE Search Strategy

22. EMBASE Search Strategy

23. EMBASE Search Strategy

24. HuGE Navigator .

25. What are we doing with the data? • Building and curating an online knowledge base that is publicly accessible.

26. What are we doing with the data? • The relational database will have three major components that contain the data for: • the investigators (PKB_Contributor) • studies/data collection platforms (PKB_Project) • literature (PKB_Literature) • Each will be linked by key fields including the investigator’s name and the linkages will be curated by the project team so that literature regarding various study collection platforms is appropriately linked and contributors are linked to the various study collection platforms, etc.

27. Preliminary Database Schema

28. What are we doing with the data? • A fourth major component will be the gene annotation from the NCBI database which already resides on a server at the BISR. • For each gene where a finding regarding prematurity has been entered into the knowledge base, the gene will be noted along with the chromosomal location, outcome (preterm, very preterm, etc), type of association, strength of the association, study details, etc. • The knowledge base will use NCBI nomenclature for genes, proteins, and SNPs and will have alias mapping for users who might use non standard terminology such as that commonly used in obstetrics or by the clinical community.

29. Preliminary Database Schema

30. Alzheimer Research Forum as an example

31. Gene Overview

32. Opinions on Meta-Analysis ????

33. Our Progress to Date on Field Synopsis, by hand …Note: Each row represents one published report.

34. Table 1. Effect

35. Table 2. Study Details / Possible Biases

36. Table 3. Genotyping Concerns

37. Table 4. Interaction

38. Table 5. Biological evidence and comments

39. Preterm Birth Network Goals • Attain funding to build the knowledge base • Publish the high level field synopsis and perhaps a series of reviews • Continue to look for large scale funding of a collaborative prospective project • PREBIC annual meeting in September 2007

40. Thank you for your attention! Special thanks to: Muin Khoury John Ioannidis Cynthia Moore Bruce Lin Marta Gwinn Wei Yu