Post on 13-Feb-2017
transcript
S.M. Rappaport University of California,
Berkeley
What is the exposome?
S. M. Rappaport
About 2/3 of people die of chronic diseases …
Worldwide deaths , 2010 (50M) (Data from Lozano et al., Lancet,
2012) Cardiovascular
44%
Cancer22%
Respiratory 11%
Digestive8.2%
Neurological6.0%
Urogenital, blood &
endocrine4.0%
Diabetes3.6%
Other1.8%
mostly from heart disease and cancer
Chronic diseases63%
Infectious, maternal and childhood diseases
24%
Injuries, etc.12%
Genes or environment? The population attributable fraction (PAF) represents the proportion of disease cases that would be prevented if the causal factor were eliminated.
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E-risks of cancer
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SM Rappaport Data from Ezzati et al., “Comparative Quantification of Mortality and Burden of Disease Attributable to Selected Risk Factors,” Global Burden of Disease and Risk Factors, Chapter 4, WHO, 2006.
Finding unknown causes of cancer • Elaborating genetic factors employs high-tech
omics (GWAS and genome sequencing)o But has explained relatively little cancer risk
• Elaborating exposures relies on low-techquestionnaires, etc.o But has explained more than a third of cancer risk
• To find unknown causes of cancer, we mustlevel the playing field
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2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Num
ber o
f cita
tions
Year
Scientific citations to ‘exposome’ (Google Scholar)
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Wild CEBP Commentary
2nd NAS workshop
Rappaport & Smith Science Perspective
Exposomics & HELIX (EU Programs)
HERCULES (NIEHS Center)
1st NAS workshop
CHEAR (NIEHS RFA)
Phenome Center (ICL)
G Rc Pc Disease
traits
E Mc
Secondary traits Rr Pr
Mr
Disease pathways
G = genome E = exposome R = transcriptome P = proteome M = metabolome (all small molecules and metals) S. Rappaport, Biomarkers, 2012, 17(6), 48: 3-9
Causal pathway (c) Reactive pathway (r)
G Rc Pc Disease
traits
E Mc
Secondary traits Rr Pr
Mr
Chemical communication
Receptors Enzymes DNA
RNA Transcription factors
Hormones Neurotransmitters
Lipids
Signaling molecules and metabolites
Cytokines
G Rc Pc Disease
traits Secondary
traits Rr Pr
Mr
Chemical communication
E Pollutants
Drugs Food nutrients
& toxins
Antigens Foreign DNA and RNA
Microbial metabolites
Mc
G Rc Pc Disease
traits Rr Pr Secondary
traits
E
Mr
Mc
Epigenetic modifications Post-translational modifications Genetic modifications (mutations)
Altering communication
S. Rappaport, Biomarkers, 2012, 17(6), 48: 3-9
Capturing all exposures
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S.M. Rappaport and M.T. Smith, Science, 2010: 330:460-461
EXPOSURES ARE CHEMICALS … and the blood exposome includes all chemicals in the body .
The microbiota: Comprise 90% of the cells and 95% of protein-coding genes in the human body
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1.E-07 1.E-06 1.E-05 1.E-04 1.E-03 1.E-02 1.E-01 1.E+00 1.E+01 1.E+02 1.E+03 1.E+04 1.E+05
Cum
ulat
ive
perc
ent
Blood concentration (µM)
DrugsFoodsPollutantsEndogenous
Venlafaxine
Aspirin
Simvastatin
Digoxin
Estradiol
Testosterone
Cortisol
Homocysteine
Cholesterol
Malondialdehyde Benzene
Lead
DDE Arsenic
PCB 170
Perfluorononanoic acid
Hexachlorocyclohexane
BDE 100
Cotinine
OCDD
Trichloromethane
Acetaldehyde
Folic acid, Vitamin D3
Sulforaphane
Trimethylamine-N-oxide
γ-Tocopherol
Ethanol
Solanidine
β-Carotene
Caffeine
Aflatoxin B1
Genistein
Rappaport et al., Environ Health Perspect, 2014
Normal blood concentrations
(1,561 chemicals)
1,000-fold
A glimpse of the blood exposome
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Chemical space of the blood exposome All chemicals n = 1,561 (weighted by blood conc.)
Extraordinary diversity (>100 chemical classes from many sources)
Rappaport et al. Environ Health Perspect, 2014
Aliphaticamino acids
Flavonoids Fatty acids
Steroids
Sugars
PCBs
Dioxins
Chemicals with disease-risk citations n = 336 (weighted by # citations)
Epidemiologists look for chemicals that cause diseases, regardless of their sources (endogenous, food, pollution, drugs).
Small circulating molecules (‘metabolome’) provide one important avenue for characterizing biologically relevant exposures
Exposome-wide association studies (EWAS)
By applying EWAS with biospecimens from healthy and diseased subjects, we can discover useful biomarkers 16
SM Rappaport
http://www.flickr.com/photos/paulieparker/246707763/
Then we can target these biomarkers in large populations
S. Rappaport, Biomarkers, 2012, 17(6), 48: 3-9
Reactive biomarkers obscure causal pathways (reverse causality). Validation of exposure biomarkers requires biospecimens obtained prior to disease (prospective cohorts).
Biospecimens for EWAS? Reactive biomarkers
(disease) Causal biomarkers
(exposure)
G Rc Pc Disease
traits Rr Pr
E
Mr
Mc
Blood exposome
Pollutant biomarkers
Endogenous biomarkers
Biomarkers of disease
Drug biomarkers
Food biomarkers
Biomarkers of exposure
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Untargeted EWAS
Based on: S. Rappaport, Biomarkers, 2012, 17(6), 48: 3-9
Causal biomarkers
Reactive biomarkers
Future of the exposome and disease etiology
• Transformative research happens once in a generation • Between 1988 and 2010 genomic research dominated
investigations of disease etiology despite disappointing results
• Exposomic research via EWAS will find causes of disease and could dominate the next generation of etiologic research o This will require integrated omics technologies - that measure
chemicals comprehensively and efficiently in appropriate biospecimens - combined with advanced bioinformatics,
o and government-academia-industry partnerships
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Best wishes from Berkeley
Support from NIEHS through grants U54ES016115 and P42ES04705, IARC (senior visiting scientist award), the EU Exposomics project and Agilent Technologies (instrument loan)
Thanks to : Paulo Vineis (ICL) Dinesh Barupal (IARC) Augustin Scalbert (IARC) David Wishart (U. Calgary) Anthony Macherone (Agilent)
Martyn Smith Hasmik Grigoryan Will Edmands Kelsi Perttula Katie Hall Samantha Lu Lauren Petrick Yukiko Yano