Environmental exposures and the etiology of cancer Paolo Vineis Imperial College London Washington, NAS conference on The Exposome
Overview What do we know about environment and cancer How do we know about cancer etiology: mismeasurement of the environment, mismeasurement of genes; migrants, heritability What we expect from new tools for the identification of biomarkers: e.g. metabonomics
The issue of attributable proportion : what is the environment?
1. Broad definition of environment Why cancer is mainly environmental Annual incidence of cancer (per million) in migrants from Japan to Hawaii, in the Japanese and in Hawaiian Caucasians Migrants Japanese Hawaii Caucasians Colon 371 78 368 Stomach 397 1,331 217
2. Narrow definition: single chemicals (Group I in IARC Monographs) (from Vineis and Xun. The emerging epidemic of environmental cancers in developing countries, Ann Oncol2009)
Exposure name Arsenic in drinkingwater (Vol. 84; 2004) Evaluation Human Animal S L Route(s) of exposure Inhalation or ingestion of contaminated ground and surface water Benzo[a]pyrene (Vol. 32, Suppl. 7, Vol. 92; in preparation) Household combustion of coal, indoor emissions from (Vol. 95; in prepar.) Radon-222 and its decay products (Vol. 43, Vol. 78; 2001) X- and Gamma (γ)- Radiation (Vol. 75; 2000) Aflatoxins (naturally occurring mixtures of) (Vol. 56, Vol. 82; 2002) Asbestos (Vol. 14; Suppl 7; 1987) ND S Inhalation (mainly of tobacco smoke) and ingestion S S Inhalation of decay products from soil, rocks (granite), and groundwater S S Irradiation from natural and man-made sources. S S Ingestion of contaminated foods S S Mainly inhalation of fibres; also ingestion of contaminated water Benzene (Vol. 29; Suppl 7; 1987) S S Inhalation of ambient air and ingestion of water contaminated from gasoline processes
Beryllium and beryllium compounds (Vol. 58; 1993) 1,3-Butadiene (Vol. 71, Vol. 97; in preparation) Cadmium and cadmium compounds (Vol. 58; 1993) Chromium[VI] (Vol. 49; 1990) Erionite (Vol. 42, Suppl. 7; 1987) Formaldehyde (Vol. 88; 2006) Involuntary smoking (exposure to secondhand or 'environmental' tobacco smoke) (Vol. 83; 2004) Iron and steel founding (Vol. 34, Suppl. 7; 1987) Nickel compounds (Vol. 49; 1990) Neutrons (Vol. 75; 2000) S S Inhalation L S Inhalation S S Inhalation of fumes and dusts and ingestion of contaminated foods S S Inhalation, ingestion and skin contact S S Inhalation S S Main general exposure through inhalation S L/S Inhalation of contaminated air S ND Inhalation of contaminated air at or near foundries S S Mainly Inhalation; also ingestion I S Mainly from natural outdoor irradiation
Rubber industry (Vol. 28, Suppl. 7; 1987) S N/D Inhalation of dusts., fumes, skin contact Silica, crystalline (Vol. 68; 1997) S S Inhaled in the form of quartz/cristobalite or ingestion Solar radiation (Vol. 55; 1992) S S Natural outdoor terrestrial irradiation 2,3,7,8- Tetrachlorodibenzopara-dioxin (PCDD) (Vol. 69; 1997) L S Ingestion of contaminated foods and Inhalation
3. Burden differs with different definitions Two papers with estimates of proportion of cancers attributable to environment worldwide 1. Pruss-Ustun A & Corvalan C. (WHO), 2006 19% 2. Boffetta et al. (IARC), 2007 19% is a gross overestimation by an order of magnitude in respect to generally accepted references e.g. Doll & Peto s estimate See comment in Saracci R, Vineis P: Disease proportions attributable to environment Environmental Health 2007, 6 : 38
Definitions of environment PAPER 1 Outdoor air pollution Indoor air pollution Lead Water sanitation, hygiene Climate change Occupational carcinogens Occupational particulate Occupational stress PAPER 2 Air, water and soil pollutants
Once the two definitions are matched. Paper 1 estimate become : 5.1% vs. 3.0% by Doll & Peto These are surprisingly close Where is the order of magnitude overestimate? However: -little knowledge on who and where is exposed -problem of misclassification and underestimation of risks
4. Nature vs. Nurture Long-lasting debate: nature vs nurture, i.e. how many diseases (and physiological traits) are attributable to genes and how many to the environment e.g. 1. The Bell Curve by Herrnstein and Murray (1994) claimed that afro-americans have lower IQs for genetic reasons 2. Is homosexuality a genetic disease? 3. Is depression genetically-based? 4. and cancer?
Odds Ratio 9 7 5 3 1 30 25 20 15 10 5 4 3 2 1 Reported Risk Allele Frequencies by Odds Ratios for Discrete Traits Sarasquete Osteonecros is Hakonars on Type 1 van DMHeel Celiac Disease WTCCC Type 1 DM Thorlieifsso n Exfoliation Glaucoma 0.0 0.2 0.4 0.6 0.8 1.0 Risk Allele Frequency (%)
Who cares about an OR=1.25? OR = odds ratios, calculated with a simple additive model. For example, for subjects with 10 risk alleles the relative risk would be 3.5. These subjects would represent 13% of the population, and over 54% of the population would carry 10 risk alleles or more. Vineis P et al, Expectations and challenges stemming from genome-wide association studies, Mutagenesis 2009 071012
Initial Lessons from GWA Studies Most genetic effects to date are very modest, but the cumulative effect can be great Relatively little work to date in environmental modifiers of genetic associations (gene x environment interactions) Little work on characterizing full spectrum of effects of putative causal variants or regions identified through GWA (courtesy T Manolio)
Methodological problems in environmental epidemiology
A self-fulfilling prophecy: are we underestimating the role of the environment in gene-environment interaction research? ( P Vineis Int J Epidemiol2004) According to estimates, the common genotyping method Taqman has 96% sensitivity and 98% specificity, thus allowing little error in classification. On the contrary, sensitivity in environmental exposure assessment is quite often lower than 70% and specificity even lower.
Genotype is stable, measured accurately (sens, spec=90-100%), frequency of alleles is high Environmental exposures are changing (life-course events), often measured inaccurately, frequency may be too low In addition, genetic polymorphisms are investigated with high-throughput technologies that allow researchers to investigate thousands of SNP at a time: with the usual p-values this originates a large number of false positives (see Bayesian strategy proposed by Colhoun et al, Lancet 2003 361: 865-872) False positives with genetic research vs false positives+negatives with environmental research?
THE IMPACT OF MEASUREMENT ERROR Correlation coefficients (r) for the measurement of estrone by different laboratories and resulting observed relative risks given true relative risks of 1.5, 2.0 and 2.5 (from Hankinson et al, 1994). True relative risks Laboratory r RRt=1.5 RRt=2.0 RRt=2.5 ------------------------------------------------------------------------------------- Observed relative risks Lab 1 0.12 1.1 1.1 1.1 Lab 2 0.82 1.4 1.8 2.1 Lab 3 0.57 1.3 1.5 1.7 Lab 4 0.90 1.4 1.9 2.3 Observed RR = exp (ln RRt * r)
Impact of the ICC on the Observed Odds Ratio (OR) Given True OR for Disease of 1.5, 2.0, 2.5, 3.0 and 3.5 (courtesy of R Vermeulen and N Rothman). 4.0 3.5 3.0 Observed OR 2.5 2.0 1.5 1.0 0.5 1.0 0.8 0.6 0.4 0.2 Intraclass Correlation Coefficient (ICC) 0.0
Imprecise exposure assessment Genotype is fixed, exposures are variable and there are windows of susceptibility Mercury analysis and speciation Representation of time interval of interest (vulnerable time window) Fetal/maternal circulation Peak or average concentration (courtesy of P Grandjean) Relative contribution 10 Maternal hair: 8-9 cm 8 6 4 2 Cord blood Lag time -5 0 5 10 15 20 25 30 35 40 Duration of pregnancy (weeks)
Some environmental exposures can be studied by epidemiology with confidence, i.e. measurement error is relatively low and has little impact on estimates (e.g. smoking). Advancement in exposure assessment due e.g. to GIS techniques for air pollution. In this case biomarkers can supplement traditional techniques for exposure assessment and increase biological plausibility (Demetriou et al, paper in preparation). When measurement error is too high we need biomarkers (e.g. number of sexual partners, OR for cervical cancer around 2; HPV strains, OR around 100-500).
Air-pollution and lung cancer mortality (Pope, JAMA 2002)
Sometimes assessing exposure without a biomarker is impossible ORs and 95% CI s for NHL for increasing quartiles of concentration of congener 118 relative to the lowest quartile (Engel et al, 2007) Janus CLUE I 2.4 (0.9-6.5) 8.1 (1.0-68.9) 4.9 (1.6-15.3) 6.6 (0.7-59.0), 5.3 (1.5-18.8) 13.0 (1.6-106.8) P(trend) 0.005 0.05
Discoveries that support the original model of molecular epidemiology Marker linked to exposure or disease Exposure Internal dose Urinary metabolites (NNK, NNN) Nitrosocompounds in tobacco Biologically effective dose DNA adducts PAHs, aromatic compounds Albumin adducts AFB 1 Hemoglobin adducts Acrylamide, Styrene, 1,3-Butadiene Preclinical effect Exposure and/or cancer Chromosome aberrations Lung, Leukemia, Benzene HPRT PAHs, 1,3-Butadiene Glycophorin A PAHs Gene expression Cisplatin Genetic susceptibility Phenotypic markers DNA repair capacity in head and neck cancer SNPs NAT2, GSTM Bladder CYP1A1 Lung Vineis and Perera, 2007
However... The measurement of most biomarkers requires large amounts of biological material E.g. PCB in serum 0.5 ml, 1 straw in EPIC Bulky DNA adducts 1-5 microg of DNA Need to explore the possibilities offered by new technologies and also neglected types of media, such as Red Blood Cells (abundant and not very used) Principle of calibration
1.2 1.0 0.8 RR Estimate 0.6 0.4 0.2 0.0 10 20 30 40 50 Calibrated Uncalibrated CI calibrated lower CI calibrated upper Fibre (g/day) Statistical model adjusted for energy, height, weight, physical activity, alcohol and tobacco (Bingham et al Lancet 2003)
No event Added event Event brought forward Vulnerablity Reserve Threshold for change in clinical state. Time Interaction between air pollution and clinical vulnerability (courtesy R Anderson)
Supervised analysis defined profiles robustly associated with known dietary factors
EPIC Metabonomics Pilot Sera from 40 EPIC subjects originating from three different countries (United Kingdom (n=16), France (8), Italy(16)) were analysedby UPLC-MS (IC) Of these 40 individuals, 10 were blinded duplicated samples (50 samples total)
EPIC Metabonomics Pilot Sera from 40 EPIC subjects originating from three different countries (United Kingdom (n=16), France (8), Italy(16)) were analysedby UPLC-MS (IC)
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