semantic relations for interpreting dna microarray data and for novel hypotheses generation

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Semantic Relations for Interpreting DNA Microarray Data

and for Novel Hypotheses Generation

Dimitar Hristovski,1 PhD, Andrej Kastrin,2 Borut Peterlin,2 MD PhD, Thomas C Rindflesch,3 PhD

1Institute of Biomedical Informatics, Medical Faculty, University of Ljubljana, Slovenia

2Institute of Medical Genetics, University Medical Centre, Ljubljana, Slovenia3National Library of Medicine, National Institutes of Health, Bethesda, MD,

U.S.A.

e-mail: [email protected]

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Introduction

Microarray experiments:

• great potential to support progress in biomedical research,

• results NOT EASY to interpret,

• information about functions and relations of relevant genes needs to be extracted from the vast biomedical literature

Related Work

• Text mining and microarray analysis

• Literature-based Discovery

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Proposed Solution

• Computerized text analysis system• Extract semantic relations from literature

– SemRep

• Integrate with microarray experiments• Develop tools for:

– Interpretation– Novel hypotheses generation

Overall Design

Medline GEO

SemRepSem.rels Extraction

R Bioconductorscripts

Integrated Database=semantic relations +

microarrays

Interpretation & Discovery Tools

semantic relationsmicroarra

ys

SemRep

• Extracts semantic relations from biomedical text (implemented in Prolog)

• Based on UMLS Metathesaurus and Semantic Network– <MetaConc> SEMNET RELATION <MetaConc>

• Database of relations extracted from MEDLINE– 6.7M citations (01/01/1999 through 03/31/2009)– 43M sentences– 21M relation instances– 7M relation types

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Semantic Relations Extracted

• Wide range of relations in:– Clinical medicine– Molecular genetics– Pharmacogenomics

• Genetic Etiology: associated_with, predisposes, causes• Substance Relations: interacts_with, inhibits, stimulates • Pharmacological Effects: affects, disrupts, augments • Clinical Actions: administered_to, manifestation_of, treats, • Organism Characteristics: location_of, part_of, process_of • Co-existence: co-exists_with

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Examples

• “… the loss of Mbd1 could lead to autism-like behavioral phenotypes …”

• Relation: MDB1 causes Autistic Disorder • “… Mbd1 can directly regulate the

expression of Htr2c, one of the serotonin receptors, …”

• Relation: MBD1 interacts_with HTR2C

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Interpretation of Microarrays

Find known facts from the literature:

• Desease related:– Associated genes– Current treatments– …

• Microarray Genes:– Relations between genes (INHIBITS, STIMULATES, …)– Relations between the genes and anything else

Relations with “Parkinson” as Argument?

What Treats Parkinson?

What (causes, associated_with) Parkinson?

Sentences from which Relations are Extracted

Genes from the Microarray Related to Anything?

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Novel Hypotheses Generation

• Based on discovery patterns

• Discovery patterns:– search templates that have a higher likelihood of

returning a new discovery

• Specific discovery patterns for specific discovery tasks

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Discovery Patterns

• Inhibit the upregulated:– Search for substances, genes, ... which, according to the

literature, inhibit the top N (e.g. 300) genes that are upregulated on a given microarray

– Such substances, genes, … might be used to regulate the upregulated genes

• Stimulate the downregulated:– Search for substances, genes, ... which, according to the

literature, stimulate the top N (e.g. 300) genes that are downregulated on a given microarray

– Such substances, genes, … might be used to regulate the downregulated genes

Discovery Patterns – Graphical View

Disease X

Maybe_Treats2?

Upregulated

Downregulated

Genes Y1

Genes Y2

Drug Z1

(or substance)

Drug Z2

(or substance)

Inhibits

Stimulates

Maybe_Treats1?

Microarray Literature

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Results – Inhibit the Upregulated

Paclitaxel INHIBITS HSPB1|HSPB1 protein

Paclitaxel completely inhibited the expression of HSP27 (PMID: 15304155)

Quercetin INHIBITS HSPB1|HSPB1 gene

Quercetin …, inhibited the expression of both HSP70 and HSP27 (PMID: 12926076)

•Parkinson microarray GSE8397

•HSP27 (HSPB1) gene is upregulated on the microarray

•We identified paclitaxel and quercetin as substances that inhibit the expression of this gene

Inhibit the Upregulated

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Results – Stimulate the

Downregulated• NR4A2 downregulated on the microarray• We found out that:

– Pramipexol stimulates expression of NR4A2 – NR4A2 is associated with Parkinson disease

pramipexol STIMULATES NR4A2

… the increase of Nurr1 gene expression induced by PRX, ... (PMID: 15740846)

… the induction of Nurr1 gene expression by PRX ... (PMID: 15740846)

NR4A2 ASSOCIATED_WITH

Parkinson Disease

… lower levels of NURR1 gene expression were associated with significantly increased risk for PD (PMID: 18684475)

Explaining a Relation - Closed Discovery

Closed Discovery – Aligned Relations

Evaluation• Estimate – based on [Masseroli, BMC Bioinformatics

2006]:• Extract known facts – baseline precision on 2,042

extracted relations:– Gene – Disease (causes, assoc_with, …) P=74.2%– Gene – Gene (inhibits, stimulates, …) P=41.95%

• Propose Argument-Predicate distance for filtering (Gene-Gene):– At distance no more than 1: P=70.75%; R=43.6%– At distance no more than 2: P=55.88%; R=66.28%

• We use Argument-Predicate distance for ranking of semantic relations and we show relations more likely to be correct first.

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Conclusion

• A new bioinformatics tool for interpretation and novel hypotheses generation

• Based on integration of semantic relations extracted from literature with microarrays

• Available at:

• http://sembt.mf.uni-lj.si

Syntactic Processing

Mbd1 can directly regulate the expression of Htr2c• MedPost tagger and shallow parser[ NP[head([… inputmatch(mdb1),tag(noun)])], ...

[verb([inputmatch(regulate),lexmatch(regulate),tag(verb)])],...

NP[… head([… inputmatch(htr2c),tag(noun)])] ]

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Semantic Processing

• Identify concepts: MetaMap and ABGene

[ NP[head([… semtype(gngm),entrez(MBD1,4152)])], ...


NP[… head([… semtype(gngm),entrez(HTR2C,3358)])] ]

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Semantic Processing


[ NP[head([… semtype(gngm),entrez(MBD1,4152)], ...


NP[… head([… semtype(gngm),entrez(HTR2C,3358])] ]

• Match semantic type patterns to ontology:

<gngm> INTERACTS_WITH <gngm>

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Semantic Processing







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Semantic Processing







• Apply indicator rule: Verb(regulate) INTERACTS_WITH

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Semantic Processing








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Semantic Processing








• Substitute concepts for semantic types:

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Semantic Processing









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Semantic Processing









MBD1 INTERACTS_WITH HTR2C

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semantic relations for interpreting dna microarray data and for novel hypotheses generation

Documents

relations of relevant

upregulated genes

causessubstance relations

discovery patternsinhibit

biomedical text

specific discovery tasks

md phd

biomedical research