Jane E. Gallagher Ph.D. - EPA ArchivesJane E. Gallagher Ph.D. Human Studies Division ORD NHEERL EPA...
Transcript of Jane E. Gallagher Ph.D. - EPA ArchivesJane E. Gallagher Ph.D. Human Studies Division ORD NHEERL EPA...
Jane E. Gallagher Ph.D.Jane E. Gallagher Ph.D.Human Studies DivisionHuman Studies DivisionORD NHEERL EPAORD NHEERL EPASeptember 24September 24--25 2007 25 2007 Public Health Applications of Human Public Health Applications of Human BiomonitoringBiomonitoring
Mechanistic Indicators of Childhood Asthma (MICA) -Integrating Environmental, Clinical and Susceptibility Markers to Improve the Impact of Human Air Pollution Studies.
Advances in biomarker development haveimproved our ability to detect early changes at the molecular and cellular level.
C lin ic a lD is e a s e
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Battery of endpoints Battery of endpoints capturing Net effectcapturing Net effect––over over several mechanisms of several mechanisms of
action/ classesaction/ classesComet assayComet assayP53 P53 FISHFISH11--OH OH pyrenepyreneCholinesterase Cholinesterase inhibition inhibition CrossCross--linking metals linking metals formaldehyde formaldehyde
HPRTHPRTDNA adducts DNA adducts methodsmethodsMutagen sensitivity Mutagen sensitivity Oxidative damage Oxidative damage MutagenicityMutagenicity
Integrated measure of dose across classes of chemicals
Environment Health Scientists
Clinicians
EvolvingTechnologies
C l i n i c a lD i s e a s e
E x p o s u r e
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•Identify Genetic variants that increase susceptibility
Environmental Studies Benefit from Knowledge Gained from Clinical Disease Studies (and visa versa)
•What factors affect a persons risk for a number of health conditions.
•Determine whether the effect of genetic variants that increase risk is different in the presence of
environmental exposures
•Early indicators/detection of disease
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Biological Fluids/cells
MICA
Change in research paradigm
Work across disciplines Give up data for the greater
good communicate
NHEERL
Westat
Henry Ford HealthSystem
South West Research Institut
RTI
Johns HopkinsMichigan State University nMercy College UNC at Chapel Hill
Rutgers University Harvard U.
NERL RTP
NERLCincinnati.
ECD ETDHSD
Genomics Core
National Center for Computational Toxicology
Region 5
Contracts
S. Edwards
MICA-Change Research Paradigm
Labcorp
EAWestat
MICA MICA A childhood asthma study and Parallel A childhood asthma study and Parallel rodent studyrodent study
A NHEERL and NCCT Computational A NHEERL and NCCT Computational Toxicology study Toxicology study
Combines and Integrates biomarkers of Combines and Integrates biomarkers of exposure effects and susceptibility in the exposure effects and susceptibility in the context of clinical measurements and context of clinical measurements and disease (asthma) outcome. disease (asthma) outcome.
National Center for Computational Toxicology
GoalsImprove linkages in the source to outcome paradigm
•Provide predictive models for Hazard ID
•Improve Quantitative Risk assessment Dose, species, chemical class
7 New Starts ---MICA
SOURCE HEALTH OUTCOME
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INTERNALDOSE
INTEGRATEDDOSE
EARLYRESPONSES
RNA--- Blood Gene expression DNA ----11 genes 55 SNP
Asthma
urine bloodFingernails
Vacuum dust and
Passive monitoring
BMI Blood PressureO2 SaturationCell differentialsBlood ChemistryCytokinesCreatininecotinineMedications
Lung functionNO ex
QuestionnaireDietTime activity
Odor test
MICA
MICAMICA
Increase our understanding of asthma by assessing the complex gene/environmental relationships through the combined use of innovative methods to manage and analyze multifactorial data
Objective
11 polymorphic genes
55 SNP
MICA RODENT Phase 1 Childhood asthma Phase 2
MICA Nested Within Detroit MICA Nested Within Detroit ChildrenChildren’’s Health Study s Health Study
Questionnaire
Lung FunctionLung Function
BiomarkersBiomarkers
MICAMICA AIR
Detroit Exposure Aerosol Research Study “DEARS”
National Exposure and Research Laboratory
MICAMICA200 children ( asthma and no asthma) 9200 children ( asthma and no asthma) 9--1212
years of age years of age 100 families participated in self monitoring100 families participated in self monitoring(indoor outdoor) as part of MICA air (indoor outdoor) as part of MICA air Vacuum Dust and medication list brought to Vacuum Dust and medication list brought to clinicclinicEducational and Educational and ““station walk throughstation walk through””presentation to provide context to the studypresentation to provide context to the studyConsent assent and Questionnaire Consent assent and Questionnaire Lung function, NO ex and odor testingLung function, NO ex and odor testingBlood, urine, fingernails collected Blood, urine, fingernails collected
> 90 percent of subjects provided samples at > 90 percent of subjects provided samples at each station.each station.
MICA Childhood Study MICA Childhood Study Multiple Risk FactorsMultiple Risk Factors
Asthma
3
Obesity
CardiovascularRisk
1
2
Asthma studies by race
MICA 85% African American
Study Design
Biomarkers of Integrated Dose:Metals (Lead, Mercury),
Metabolites of Polycyclic Aromatic Hydrocarbons, Cotinine, and Creatinine
Biomarkers of Early Effect:Autoantibodies, Mutagenicity
Gene Expression Inflammatory Markers
Clinically-relevant Outcomes:
Allergies, Asthma, Respiratory Symptoms,
Lung FunctionNOex VOC
Asthmatic and nonasthmatic Children n=200
Rodents: Blood and Lung Tissue
Gene ExpressionProfiles
InflammatoryMarkers
Susceptibility Factors: Genetic Variation-RNA, DNA
AmbientLevels
Internal Dose
EffectiveDose
Early Biological
Effect
ClinicalDisease
Pre-ClinicalEffects
Particulate matter (PM)
(concentrated to 200-600µg/m3)
Ambient Levelsof PM and air
toxics
Detroit-areaUrban Air
Rodent Study Detroit AIRConcentrated
Air Particles Exposures
MSU Mobile Air Research Laboratory (AirCARE 1)
J Harkema
Air Particle Concentratorand Inhalation Exposure System for Laboratory Rodents
Animals are exposed to concentrated fine and ultrafine particles in specially designed shoebox cages
MICA (I) MICA (I) Evaluate Utility of Rodent models for Evaluate Utility of Rodent models for analyzing gene expression data in analyzing gene expression data in
childhood asthma study childhood asthma study
Brown Norway Rats
Air/Saline Air/Ova CAPS/Saline
CAPS/Ova
MSU
Study Design
Biomarkers of Integrated Dose:Metals (Lead, Mercury),
Metabolites of Polycyclic Aromatic Hydrocarbons, Cotinine, and Creatinine
Biomarkers of Early Effect:Autoantibodies, Mutagenicity
Gene Expression Inflammatory Markers
Clinically-relevant Outcomes:
Allergies, Asthma, Respiratory Symptoms,
Lung FunctionNOex VOC
Asthmatic and nonasthmatic Children n=200
Rodents: Blood and Lung Tissue
Gene ExpressionProfiles
InflammatoryMarkers
Susceptibility Factors: Genetic Variation-RNA, DNA
AmbientLevels
Internal Dose
EffectiveDose
Early Biological
Effect
ClinicalDisease
Pre-ClinicalEffects
Particulate matter (PM)
(concentrated to 200-600µg/m3)
Ambient Levelsof PM and air
toxics
Detroit-areaUrban Air
MICA
INTERNAL DOSE
INTEGRATED DOSE
Health EffectAsthma
AIR/DUST
Lung functionNOexAntioxidantsAllergen skin testingPlasma ROSCytokines Blood panel Cell surface markers
ROSCholinesteraseMutagenicity1 OH Pyrene Antibodies to nervous system Cotinineproteins Coagulation factors
Metals Heavy MetalsPAH metabolitesETS Pb HgNapthols Phenanthrols
Gene expression - RNA Genotyping –DNA ( 11 genes 55 SNP )
Indoor outdoorPAH VOC No2O3 AllergensMolds
Passive monitoring: N02, PAHs VOC, (indoor and outdoors)Vacuumdust
Metals, PAHs,aero-allergens mold, endotoxin)
Biomarkers--- Clinical and EnvironmentalUrine Cotinine Creatinine
Urine Metals: Mercury, Cadmiun, Arsenic, Chromium, Manganese, Nickel
Urine 1- hydroxpyrene (1-OH pyrene) Napthols, Phenanthrols, Hydrocarbon Metabolites phthalates
Urine Mutagenicity Assays
SerumAutoantibodies for nervous system proteins, Blood Chemistry, Total IgE and specific antibodies to common aero-allergens (multiscreen inhalant and food antibody series)- *dust mite, Cockroach , Mouse, Rat Urine Protein,
Plasma Reactive Oxygen Species, cytokines (IL4, 6 IL13), tumor necrosis factor- alpha, c-reactive protein, fibrinogen
WholeBlood
hematology panel, lead and mercury, Gene expression (RNA), glycosolated hemoglobin
Nails Mercury, Cadmium, Arsenic, Chromium, Manganese, Nickel
Serum IgE-inducing proteins associated with fungal exposures
11 polymorphic genes
55 SNP
X D a ta0 1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6
Y D
ata
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5 0
1 0 0
1 5 0
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X Data0 1 2 3 4 5 6 7 8 9 10 11
Y D
ata
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% A1C vs diastolic p <.05
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X D a t a0 1 2 3 4 5 6 7 8 9 1 0 1 1
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Plot 1
s y s t o l ic D ia s to l ic b y g e n d e r ( f v s m ) a n d a g e
X D a t a
0 2 4 6 8 1 0 1 2 1 4 1 6 1 8 2 0 2 2
Y D
ata
0
2 0
4 0
6 0
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1 0 0
1 2 0
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X D a ta0 1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6
Y D
ata
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1 0 0
1 5 0
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relationship between % neut vs % eosin
R2 = 0.1321
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20
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eos % vs neut y
Linear (eos % vs neut y )
X Data
0 1 2 3
Y D
ata
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14asthma med types taken on daily basis
Singular, 16%
albuterol , 42%
Flovent , 3%
advair, 29%
pulmicort , 10%
050
010
0015
0020
00To
tal S
erum
IgE
Low Moderate High Asthma severity
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4060
8010
0ph
adia
top
Low Moderate High Asthma severity
010
2030
fx5e
food
scre
en
Low Moderate High Asthma severity
020
4060
80de
rmpt
erdu
stm
ite
Low Moderate High Asthma severity
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4060
8010
0de
rmfa
rindu
stm
ite
Low Moderate High Asthma severity
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4050
catd
ande
repi
thel
Low Moderate High Asthma severity
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2030
40do
gdan
der
Low Moderate High Asthma severity
02
46
8ge
rman
cock
roac
h
Low Moderate High Asthma severity
0.5
11.
52
mou
seur
inep
rot
Low Moderate High Asthma severity
05
1015
2025
ratu
rinep
rot
Low Moderate High Asthma severity
010
2030
aspe
rgill
fum
igat
us
Low Moderate High Asthma severity
05
1015
20cla
dosp
orhe
rbar
um
Low Moderate High Asthma severity
020
4060
80al
tern
aria
alte
rnat
a
Low Moderate High Asthma severity
05
1015
20pe
nici
llnot
atum
Low Moderate High Asthma severity
Male (Blue); Female (Green)
BMI vs systolic
80
90
100
110
120
130
140
150
160
10 20 30 40 50
% A1C vs diastolic p <.05
4.0
4.5
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X Data
0 1 2 3
Y D
ata
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NOW WHAT ???
CINCINNATI CHILDRENS HOSPITALStable
AsthmaticsUnStable
AsthmaticsNNORMAL
NASALEPITHELIAL
CELLS
HEAT MAP MICA
Biomarkers Exposure/Clinical indicators
Sub
ject
sDavid ReifNationalCenter for ComputationalToxicology
Elaine Hubal
Biomarker NeedsBiomarker NeedsExposure biomarkers in the context of clinical Exposure biomarkers in the context of clinical health indicators health indicators Mechanistic information test biological Mechanistic information test biological plausibility in rodents plausibility in rodents Validation of surrogate cells with target tissue Validation of surrogate cells with target tissue responsesresponses
Archiving of biological and environmental samples and measurements as new
technologies advance
C lin ic a lD is e a s e
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• High-data content technologies, elucidating the genetic and environmental basis for
toxicity and disease
Summary
Gene expression arrays
genes, pathways, and networks
computational
bioinformatic
statisticalanalysis.
Integration of Diverse Set of exposure, effects and susceptibility
AcknowledgementsAcknowledgements
National Center for Computational Toxicology
Stephen EdwardsElaine Hubal
David Reif
National Health Exposureand Effects Laboratory
PHASE II MICA
Westat
Henry Ford Health System Clinic Henry Ford Health System-lab
AcknowledgementsAcknowledgements
MICA-HSD Ed HudgensGina Andrews Brooke HeidenfelderJeff InmonMary JohnsonDanelle LobdellPauline MendolaJim PrahScott RhoneyElizabeth SamsDCHS Lucas NeasAnn WilliamsNCCTElaine HubalDavid ReifAdministrativeWalter BreyerEdward StrubbleMike Ray QADebra WalshKay Williams
NERLShaibal MukergeeHaluk OzkaynakRon Williams Dan ValleroNERL CincinnatiStephen Vesper
Mercy CollegeH. El FawalJohns HopkinsRobert HamiltonJohn WisemanCarol SchultzHarvard UniversityRutgers UniversityTina FainUNC Stephen RappaportSuryamya W.SWRI David CaamanRTIFrank Weber Peter GrosheWestatKurt PatriziHenry Ford Health SystemClinical and Lab
Contracts Robin Harris Jennifer HillLenora Hilliard Student ContractorsChris GarlingtonChrissy LinSharon MyersPeter Stone
Genomics core Susan Hester Chris CortonNHEERL Office of the Director Stephen Edwards ECD David DeMariniRegion 5George BollwegJackie Nwai
IRB Richard HermanMonica Nees
ETD Gary HatchMarsha Ward et alKay CrissmanMcGee
Nurses HSDMary Ann .BassettDeb LevinTracy. MontillaWestatAndrea Ware
Michigan State U.J. HarkemaLori Bramble
AcknowledgementsAcknowledgements