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ADR TOXIC’OMICS
Andrew A. Monte, MD University of Colorado &
Rocky Mountain Poison & Drug Center
DISCLOSURES
Salary partially supported by EMF Research Training Fellowship 2012-2014.
Supported by NIH/NCATS Colorado CTSI grant number UL1 TR001082.
Grant support from the John A. Hartford Foundation.
Grant support from the Dept of EM at UCo.
Opinions discussed are solely my own and do not represent anyone else’s views.
OBJECTIVES
1. History of ADR ‘omics.
2. How we can use single ’omic associations.
3. Systems biology ADR ’omics.
WHY ADRS?
74% of all physician office visits involve drug therapy.
$234.1 billion in prescription costs in 2008.
Repesent approx 6% of hospital admissions.
Easier to characterize phenotypes.
Far more common than overdose.
WE NEED TO OWN THIS.
HISTORICAL TOXICOGENOMICS
510 BC: Pythagoras described the danger of eating fava beans.
510 BC: Pythagoras described the danger of eating fava beans.
1931: First report of inherited difference in response to a chemical (inability to taste phenylthiourea).
HISTORICAL TOXICOGENOMICS
510 BC: Pythagoras described the danger of eating fava beans.
1931: First report of inherited difference in response to a chemical (inability to taste phenylthiourea).
1955: Dern reported primaquine induced hemolysis varied by ethnicity in WWII soldiers.
HISTORICAL TOXICOGENOMICS
510 BC: Pythagoras described the danger of eating fava beans.
1931: First report of inherited difference in response to a chemical (inability to taste phenylthiourea).
1955: Dern reported primaquine induced hemolysis varied by ethnicity in WWII soldiers.
1957: Arno Motulsky proposed genetic basis as an explanation for individual differences in drug efficacies and adverse reactions.
1960: Peripheral neuropathy associated with metabolism polymorphism, “slow acetylators” for INH.
HISTORICAL TOXICOGENOMICS
NAT2 METABOLISM OF INH
72 yo M starting carbamazepine for trigeminal neuralgia.
CARBAMAZEPINE
SHLA-B*1502 associated with SJS/TEN in Asian populations (Taiwan).
HLA-A*3101 hypersensitivity in European populations.
NNT 39 in European, 56 in Japanese, 83 in patients of undetermined descent.
DOES SCREENING MAKE SENSE?
Prevalence of HLA*3101=2-5%
Cost ≈ $400
PPV=79.17%, NPV=63.93% in European populations.
21% of ⊕ tests will not have the ADR. 36% of the ADRs will still have a ⊖ test.
Stop the drug!
NOT ENOUGH APAP?
Can we predict DILI due to therapeutic APAP dosing?
Winnike, et al. used metabolomics at baseline and during 7 days of 4g dosing.
No association with pre-dosing metabolites.
After beginning therapy, metabolites predicted ALT rise prior to standard laboratory testing.
Heard, et al. manuscript in review
SO WHAT?
If they keep taking APAP, LFTs come down!
CYP2C9/VKOR1 and INR.
Statin induced rhabdomyolysis.
Aspirin induced asthma.
Single ‘omic screening isn’t cost effective for clinically
insignificant ADRs!
ABACAVIR
Stevens Johnson Syndrome/TENS
Mortality 10-30%
HLA-B*5701
IDSA recommends ALL patients beginning abacavir be screened.
HLA-B 5701 BINDING GROOVE
Binding groove with abacavir
Binding groove without abacavir
Abacavir
HLA-B 5701 BINDING GROOVE
Binding groove with abacavir
Binding groove without abacavir
Abacavir
Allo-Reactive T Cells
HOW GOOD IS SCREENING?
Hypersensitivity reactions in 5-8% in pre-marketing studies.
PPV=47.9%, NPV 99%.
Screen 100, SJS prevented in 4, no abacavir in 2 that would tolerate.
Bad ADRs with high NPVs, screening makes sense!
‘OMIC ELIMINATION OF SEVERE ADRS
Disulfiram induced liver failure?
Gadolinium induced nephrogenic systemic fibrosis?
Ergotamine induced retroperioneal fibrosis?
Lithium induced SIADH?
Others?
COMMON MISTAKES
Assuming ‘omic associations will be predictive.
Assuming small cohort ‘omic associations will translate to broader populations.
Oversimplification.
‘OMICS LIMITATIONS
DNA Sequence GenomicsHistone
ModificationExon
Intron
RNA Transcriptomics
Environmental Factors Epigenomics
CH3
Methylation
Protein Proteomics
Metabolites Metabolomics
Phenotype Drug response
{
Inhibitory RNA
‘OMICS LIMITATIONS
Genomics: variable penetrance
Epigenomics: environmental differences
Transcriptomics: post-translational modification
Proteomics: variable receptor microenvironments
Metabolomics: adaptation with polygenic response
Phenomics?
PHENOMICS
Unbiased study of large-scale phenotype data.
Identify new biologic pathways.
Can be performed with EMR data!
Demands a systems biology approach.
ToxIC?
‘OMICS LIMITATIONS
Genomics: variable penetrance
Epigenomics: environmental differences
Transcriptomics: post-translational modification
Proteomics: variable receptor microenvironments
Metabolomics: adaptation with polygenic response
Phenomics?
PHENOMICS DATABASES
Consortium for Neuropsychiatric Phenomics: 52 centers, funded by NIH. http://www.phenomics.ucla.edu
US Biobank: Dept of Health Wellcome Trust: 500,000 patients. http://www.ukbiobank.ac.uk
Personal Genome Project: Privately funded. http://www.personalgenomes.org
NSAID HEPATOTOXICITY
Among the most common drugs used worldwide.
Responsible for 10% of drug induced hepatotoxicity.
25% that develop jaundice die.
Severe ADR, commonly used.
‘Omics identified mechanisms: 1.) drug induced cell death, 2.) mitochondrial dysfunction leading to apoptosis 3.) immune reaction.
Can systems biology predict this?
NSAID HEPATOTOXICITY
NSAID HEPATOTOXICITY
CYP2C8*2, CYP2C8*3, CYP2C8*4, CYP2C8*5 have been associated with ibuprofen induced hepatotoxicity.
CYP2E1*2, rare variant associated with decreased enzyme function. No association with APAP hepatotoxicity.
UGT2B7*2 associated with diclofenac induced hepatotoxicity.
MnSOD2 associated with nimesulide hepatotoxicity.
TOO COMPLEX!!!
SEPSIS PHENOMICS
Phenomics, proteomics, metabolomics in 150 sepsis patients.
Model: Phenomics + Metabolomics predicted survival in sepsis, accuracy 83.6% for 28 day survival.
Identified pathways previously unrecognized to be physiologically important in survival.
Langley, RJ, et al. Sci Translational Med. 2013.
SEPSIS SYSTEMS BIOLOGY
6 carnitine esters decreased in survivors.
16 carnitine esters and 4 fatty acids elevated in survivors.
Suggests B-oxidation defect in non-survivors.
Sepsis survivors mobilized various energetic substances for oxidative metabolism.
SEPSIS PHENOMICS
Phenomics, proteomics, metabolomics in 150 sepsis patients.
Model: Phenomics + Metabolomics predicted survival in sepsis, accuracy 83.6% for 28 day survival.
Identified pathways previously unrecognized to be physiologically important in survival.
Langley, RJ, et al. Sci Translational Med. 2013.
SYSTEMS BIOLOGY
Genomic +Metabolomic+ Phenomic +
Lots of Patients=
Prediction/Elimination of ADRs
HETEROGENEITY INH ADRS
BRING IT FULL CIRCLE
INH ADRs are perfect for systems biology studies.
Many TB clinics with many patients.
Significant phenotypes gathered, vitals, demographics, physical exam, LFTs, etc.
Prospective study needed.
SUMMARY
Look for single ‘omics association with severe ADRs.
Phenomics may identify common pathways.
Other ‘omics are needed to link them.
Need high throughput integrative analytics.
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