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Translational Case Histories. Harvard Medical School Center for Biomedical Informatics i2b2 National Center for Biomedical Computing Isaac S. Kohane, MD, PhD John Glaser, PhD Susanne Churchill, PhD. First signal: 1 year after Celecoxib 8 months after Rofecoxib.

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translational case histories

Translational Case Histories

Harvard Medical School

Center for Biomedical Informatics

i2b2 National Center for Biomedical Computing

Isaac S. Kohane, MD, PhD

John Glaser, PhD

Susanne Churchill, PhD

slide3

First signal:

  • 1 year after Celecoxib
  • 8 months after Rofecoxib
slide4
For every million prescriptions, 0.5% increase in MI (95%CI 0.1 to 0.9)
  • 50.3% of the deviance explained
effect on patient age
Effect on patient age
  • Negative association between mean age at MI and prescription volume
  • Spearman correlation -0.67, P<0.05
i2b2 test relnet project
I2B2: Test RelNet Project
  • Correlate available GEO expression data for GPL96 platform containing expressions for more than 22K human genes
  • Number of gene pairs for this gene chip: ~ 250 Million
  • Multi-threaded application to run on the high-performance Cluster environment from HP
  • Bottleneck: the back-end Database
  • Current, fine-tuned version of the application takes about 2-3 months to complete one data set calculation
recurrent themes
Recurrent Themes
  • Access to large numbers of phenotyped specimens
  • Inadequacy of informatics at the cutting edge
    • Inadequacy of software solutions alone
  • A persistent multidisciplinary requirement
overall remission rate with citalopram 32 9
Overall Remission Rate with Citalopram = 32.9%

QIDS: Quick Inventory of Depressive Symptoms, self report

N = 943/2876

No depression

Mildsymptoms

Moderatesymptoms

Severesymptoms

Very severe symptoms

Percent (%)

Last QIDS-SR Score

Trivedi MH, et al. Am J Psychiatry 2006;163:28-40.

slide12
Aims:
  • Identify a cohort of patients with TRD, and a matched cohort with SSRI-responsive MDD.
    • Data-mining tools
    • Natural language processing
  • Conduct the first genomewide association study of TRD.
slide14
Scan computerized medical records (DataMart)
    • ICD9 RA x 3 plus one of:
      • CCP or RF
      • Erosions on x-ray
      • DMARD treatment
  • Crimson “discarded” blood samples (cases and controls)
  • CCP on all samples (and bank serum)
  • DNA on all samples for genetic studies

adds >95% specificity

www.i2b2.org/disease/arthritis.html

slide16

Association in population samples

Affecteds

Controls

SNP frequency in cases compared to controls

Positive controls: MHC, PTPN22, STAT4, TRAF1-C5, TNFAIP3

slide17

…...acgt…ggaatac…...

…...acgt…ggaatac…..

Allele ‘A’

NspI

NspI

NspI

NspI

…...acgt…ggattac…..

......acgt…ggattac……

Allele ‘B’

NspI

NspI

NspI

NspI

_ B

_ _

‘B’ methylated

both unmethylated

‘B’ expressed

‘A’ expressed

both expressed

MSRE digested

Allele ‘A’

Allele ‘B’

A B

A _

control

(no digestion)

‘A’ methylated

gene network enrichment analysis
Gene Network Enrichment Analysis

Microarray data

Protein protein interaction network

Molecular Function

Biological Process

diabetes genome anatomy project mouse models of insulin resistance insulin deficiency and obesity
Diabetes Genome Anatomy Project:Mouse Models of Insulin Resistance, Insulin Deficiency and Obesity
  • Knockouts
    • Insulin receptor
    • Insulin receptor substrates
    • Leptin
    • PGC1A
  • Environmental
    • High fat diets
    • Drug treatments (Streptozotocin)

Tissues

67 Conditions Total

three functional sets are consistently over represented in disease models
Three Functional Sets Are Consistently Over-represented In Disease Models
  • Insulin signaling, interleukins, and nuclear receptors.
  • Insulin signaling is consistent with the given disease models. Was not identified using standard techniques.
  • Interleukins and nuclear receptors consistent with the inflammation and disordered metabolism associated with type 2 diabetes.

Insulin signaling

NuclearReceptors

Nuclear receptors: 31 of 67.

Interleukins: 38 of 67.

Insulin signaling: 45 of 67.

Interleukins

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