Future Trends: Translational Informatics

James J. CiminoChief, Laboratory for Informatics Development

Mark O. Hatfield Clinical Research CenterNational Institutes of Health

Institute for e-Health Policy, January 12, 2011

Genetics 101

DNA DNA

Transcription

Replication

RNA AminoAcids Proteins

Structures

PathwaysTranslation

Folding

Phenome

Genome

The Genomic Timeline

BacterialGenome

1995

Human Genome

20031953

DNAStructure

Translational Research

The application of research findings in one domain

of study to another, (usually broader) domain.

Type 1 Type 2

ResearchersClinicians

“Type 0”

Bioinformatics

The Roles of Informatics

TranslationalInformatics

ClinicalKnowledge

BiologicKnowledge

ClinicalInformatics

Promise of Translational Informatics

• Diseases predicted by genes

• Effectiveness of prevention

• Diseases indicated by activation

• Appropriate testing

• Drug dose, toxicity and interactions

• Drug effectiveness

Case Study

• Patient with liver cancer and chest pain

• Physician suspects pulmonary embolism

• What is the best, least invasive test?

• Will warfarin work to prevent further emboli?

• What is the warfarin dose for this patient?

• Will warfarin interact with other medications?

How does the nose form?

• Definitely genetic• Not a big protein!• 5 types of tissue• Billions of cells• Coordination in time and space• How many genes?• How many variants?

Phylogeny Phylogeny

Ontogeny

Genomics of a Single Disease

DNA

...16...17...18...

-G-A-G--Pro-Glu-Glu-....5......6......7.....

Hemoglobin A Structure Function

1956

1953 2003

...16...17...18...

-G-T-G--Pro-Val-Glu-....5......6......7.....

Why is this so hard?

DNA DNA RNA AminoAcids Proteins

Pathways

Structures

Replication

Transcription

Translation

Folding

OtherGenes

EnvironmentFactors

Inhibition

Activation

Mutations

• 3 billion base pairs in the human genome• 100 trillion cells in the human body

Denaturation

Types of Translational Informatics

• Locating genetic sequences

• Identifying genetic mutations

• Tracking gene activation

• Modeling protein folding

• Simulating biologic pathways

• Drug discovery

• Personalized medicine

The NIH and Translational Informatics• GenBank

The NIH and Translational Informatics• GenBank

– Over 100 million sequences (100 billion bases)

• Genome-Wide Association Studies (GWAS)

The NIH and Translational Informatics• GenBank

– Over 100 million sequences (100 billion bases)

• Genome-Wide Association Studies (GWAS)– study disease-specific genetic differences

• Database of Phenome and Genome (dbGAP)

The NIH and Translational Informatics• GenBank

– Over 100 million sequences (100 billion bases)

• Genome-Wide Association Studies (GWAS)– study disease-specific genetic differences

• Database of Phenome and Genome (dbGAP)– archive of genotype-phenotype studies

• Entrez

The NIH and Translational Informatics• GenBank

– Over 100 million sequences (100 billion bases)

• Genome-Wide Association Studies (GWAS)– study disease-specific genetic differences

• Database of Phenome and Genome (dbGAP)– archive of genotype-phenotype studies

• Entrez– Cross-resource search tool for translational queries

• ClinSeq

The NIH and Translational Informatics• GenBank

– Over 100 million sequences (100 billion bases)

• Genome-Wide Association Studies (GWAS)– study disease-specific genetic differences

• Database of Phenome and Genome (dbGAP)– archive of genotype-phenotype studies

• Entrez– Cross-resource search tool for translational queries

• ClinSeq– Complete sequencing of 1000 individuals

• Biomedical Translational Research Information System (BTRIS)

The NIH and Translational Informatics• GenBank

– Over 100 million sequences (100 billion bases)

• Genome-Wide Association Studies (GWAS)– study disease-specific genetic differences

• Database of Phenome and Genome (dbGAP)– archive of genotype-phenotype studies

• Entrez– Cross-resource search tool for translational queries

• ClinSeq– Complete sequencing of 1000 individuals

• Biomedical Translational Research Information System (BTRIS)– reusing clinical research data (1.5 billion rows of data)

• Infobuttons

The NIH and Translational Informatics• GenBank

– Over 100 million sequences (100 billion bases)

• Genome-Wide Association Studies (GWAS)– study disease-specific genetic differences

• Database of Phenome and Genome (dbGAP)– archive of genotype-phenotype studies

• Entrez– Cross-resource search tool for translational queries

• ClinSeq– Complete sequencing of 1000 individuals

• Biomedical Translational Research Information System (BTRIS)– reusing clinical research data (1.5 billion rows of data)

• Infobuttons– delivering translational knowledge to the point of care

Now What?

• This biology stuff is complicated

• Translational research is about applying findings from one domain to another domain

• Translational informatics is the key to communicating data and knowledge between domains

• Translational informatics research is a new field

• We still need:– Informatics research support (NCTR? NCTI? NIBI?)– Training (extramural and intramural)– Support for collaborative efforts (CTSAs)– Centralization of resources for efficiency and equity