Roel Vermeulen, Professor, Utrecht University, at Europe That Protects - Safeguarding Our Planet, Safeguarding Our Health EU side event, 3-4 Dec 2019, THL, Helsinki

1. THE CHEMICAL
CONSTELLATION AND
HEALTH
EXPOSOME: STUDYING LIFE-LONG
EXPOSURES
Roel Vermeulen, PhD
Professor Environmental Epidemiology & Exposome Science

2. OUTLINE
Our chemical world is complex and vast
Impacts on health are significant
Way forwards; Exposome

3. Our chemical world is complex and vast
Landrigan et al., Lancet, 2017

4. Our chemical world is complex and vast
‘A high proportion of the
140,000 chemicals and
pesticides in commerce
have never been adequately
tested for safety’
let alone their combination
Volume
Wilson and Schwarzman, 2009

5. But it is not only chemicals
What we do, eat, breath and experience in life has a great impact on health
0 20 40 60 80 100
Colon cancer
Stroke
Coronary heart disease
Type 2 diabetes
Percent driven by ENVIRONMENTAL factors
Walter Willet, 2002

6. 100%
0%
0-6 year 10-14 year 30-34 year 60-64 year 80+ year
50%
KnownKnown Known Known Known
UnknownUnknown Unknown Unknown Unknown
Non-GeneticBurdenofdisease
GBD Project, 2014
What we do and don’t know
Lifecourse

7. Human EXPOSOME project: A paradigm shift to a new
systematic understanding of the cause of diseases
1990 20012005/10

8. Internal Exposome
External:
Environmental factors
Climate
Environment
Lifestyle
Nutrition
Social contacts
Stress
…
Internal:
Biological measures
Metabolites of chemicals
Endogenous metabolites
Microbiome
Epigenetics
…
The Exposome: Defined as all exposures from conception
onwards, including those from lifestyle, diet and the environment

9. Lange P, et al. Lung-Function Trajectories
Leading to Chronic Obstructive Pulmonary
Disease. N Engl J Med 2015 Jul 9;373(2):111-
122.
Lung-function trajectories from birth to death

10. To understand the complexity of the human exposome,
we must adopt analytical strategies and study designs
that incorporate untargeted measures of exposure
1
To measure the exposome, we need expand beyond traditional
environmental health and analytical chemistry approaches

11. Implementation of the exposome

12. Google Air View
Nitrogen Dioxide
Nitric Oxide
Black Carbon
UFP
PM 2.5
Reference Equipment
Latitude & Longitude
Vehicle Speed and Heading
Wind Direction
Wind Speed
External Temperature
External Pressure
Location+ Meteorology
Sample rate = 1 Hz
Air View CarsAmsterdam
330 Hours = 1.2 million 1-Hz measurements
Median Days per Road Segment = 30
Apte et al., 2017
Copenhagen

13. LONG-TERM EXPOSURE TO ULTRAFINE
PARTICLES AND INCIDENCE OF CARDIOVASCULAR
DISEASE
Kerckhof et al, 2017; Downward et al., 2018
All incident cardiovascular disease
4,304 events
Single pollutant models
PM2.5 0.98 (0.75:1.28)
Ultrafine Particulates (UFP) 1.18 (1.03:1.34)
NO2 1.04 (0.98:1.10)
LUR based on mobile monitoring

14. High-Resolution-Mass-Spectrometry
Walker DI, Go YM et al. (2016)
Exposures
Exposure
Monitoring, trace
analysis, geography
Internal dose Bioeffect
High resolution metabolomics
Internal dose Bioeffect
High-Resolution Metabolomics
DiseasePlasma metabolome
Lifetime
Exposures
Exposures
Exposure
Monitoring, trace
analysis, geography
Internal dose Bioeffect
High resolution metabolomics
Internal dose Bioeffect
High-Resolution Metabolomics
DiseasePlasma metabolome
Internal dose Biological response
High-resolution exposomics High-resolution metabolomics
Exposures
Exposure
Monitoring, trace
analysis, geography
Internal dose Bioeffect
High resolution metabolomics
Internal dose Bioeffect
High-Resolution Metabolomics
DiseasePlasma metabolome
0 2 4 6 8 10
0
25
50
75
100
Retention time (min)
Relativeabundance
L-Met(S)SO; Chiral column
L-Met(R)SO; Chiral column
L-Met(RS)SO; AE column
AE: F T M S + p ESI Full m s m /z= 166.0507-166. 05 57 N L: 1.57E 5
C hir al: FTM S + p E SI Full m s m /z= 166.0507-166. 05 57 N L: 1.87E 5
50 70 90 110 130 150 170
0
25
50
75
100
m/z
Relativeabundance
RT= 6.67
149.02
75.01
74.03
56.03
Scan #958 RT: 6.67 NL: 7.52E3
ITMS + c ESI Full ms2 166.05@cid35.00
Time
Intensity
−10−505101520
RetentionTime De viationvs. RetentionTime
Retention Tim e
RetentionTimeDeviation
0 100 200 300 400 500 600
Retention Tim e
PeakDensity
−50 0 50 100 150
0e+002e+044e+046e+048e+041e+05
ExtractedIonChr omatogram: 183.08 − 183.08 m/z
Retention Tim e (seconds)
Intensity
0 50 100 150
0e+002e+054e+056e+058e+05
ExtractedIonChr omatogram: 198.1 − 198.1 m/z
Retention Tim e (seconds)
Intensity
−50 0 50 100 150
020000400006000080000100000120000
ExtractedIonChr omatogram: 209.07 − 209.07 m/z
Retention Tim e (seconds)
Intensity
− 50 0 50 100 150
0e+001e+052e+053e+05
ExtractedIonChr omatogram: 166.09 −166.09 m/z
Retention Tim e (seconds)
Intensity
−50 0 50 100 150
0e+001e+052e+053e+054e+055e+05
ExtractedIonChr omatogram: 162.11 − 162.11 m/z
Retention Tim e (seconds)
Intensity
−50 0 50 100 150
050000100000150000200000250000
ExtractedIonChr omatogram: 205.1 − 205.1 m/z
Retention Tim e (seconds)
Intensity
300 350 400 450
050000100000150000
ExtractedIonChr omatogram: 400.34 − 400.34 m/z
Retention Tim e (seconds)
Intensity
250 300 350 400
020000400006000080000
ExtractedIonChr omatogram: 380.25 − 380.26 m/z
Retention Tim e (seconds)
Intensity
350 400 450 500
0e+001e+052e+053e+05
ExtractedIonChr omatogram: 510.35 − 510.36 m/z
Retention Tim e (seconds)
Intensity
×
Metabolic phenotype
Exposures
Exposure
Monitoring, trace
analysis, geography
Internal dose Bioeffect
High resolution metabolomics
Internal dose Bioeffect
High-Resolution Metabolomics
DiseasePlasma metabolome
Disease
Phenotype
Exposures

15. High-Resolution-Mass-Spectrometry
Covering the chemical space
Vermeulen et al., 2020

16. Exposure
2-3 shift length
measures of TCE
exposure using 3M
vapor monitoring
badge in Guangdong,
China Lan et al.
(2010)
High-resolution metabolomics
• 95 unexposed workers
• 80 workers using TCE in manufacturing
process
• Post-shift plasma collected
• MWAS using linear regression; FDR
20%
Exposure Endpoints
Internal dose Bioeffect
High-Resolution Metabolomics
• Personal monitoring
• Ambient measures
• Time, activity adjusted
exposures
• Biomonitoring
• Biomarkers
• Response markers
• Health outcome
Validation
Internal dose Bioeffect
High-Resolution Metabolomics
• Lit. in vitro studies
• Biomarkers
• Response markers
• Health outcome
Validation
Internal dose Bioeffect
High-Resolution Metabolomics
• Lit. in vitro studies
• Biomarkers
• Response markers
• Health outcome
Exposure Endpoints
Internal dose Bioeffect
High-Resolution Metabolomics
• Personal monitoring
• Ambient measures
• Time, activity adjusted
exposures
• Biomonitoring
• Biomarkers
• Response markers
• Health outcome
Additional
biomarkers
Immune, kidney injury and
exposure biomarkers
Kim et al. (2009), Lan et al.
(2010), Vermeulen (2012),
Zhang et al. (2014)
×
Walker DI, Uppal K, Zhang L, Vermeulen R, Smith M, Hu W, et al. (2016) High-resolution metabolomics of occupational exposure
to trichloroethylene. International Journal of Epidemiology. 45(5):1517-27.
High-resolution metabolomics of occupational exposure to
trichloroethylene

17. Adult onset Asthma CVD
Lineolate pathway
Jeong et al, 2018
Features associated with air pollution overlapped with the features
associated with AOA or CVD

18. Exposome Linking
exposures across
the lifespan to
disease and public
health;
The Power of Big Data
ExperimentalIn-silico
1
Niedzwiecki MM, Walker DI, Vermeulen R, Chadeau-Hyam M, Jones DP, Miller GW. The Exposome : Molecules to
Populations, Annual Reviews of Pharm and Tox., 2019

19. EU Human
Exposome Project
2020 - 2024
• 9 Projects
• 24 Countries
• 126 Research Groups
• 106 M Euro
Athlete
Ephor
Equal-Life
Eximious
ExpanseHeap
Hedimed
Longitools
Remedia

20. Our chemical world is complex and vast
Impacts on health are significant
Way forwards; Exposome

21. RESPONSIBILITY
Our chemical constellation
Increasingly complex
- Volume
- Variety
- Velocity
BPA -> bisphenol S (BPS),
bisphenol F (BPF) and
bisphenol HPF (BHPF).
Environmental
Postmarketing
Research
Mobile communication
2G -> 3G. -> 4G -> 5G
Perfluoronated compounds
PFOA -> GENX

22. While thousands of compounds are classified as
“generally recognized as safe”, they were never
subjected to the scientifically rigorous testing systems
currently in place.
A data-driven exposome approach ignores historical
decision-making and can help evaluate the effects of
classes of chemicals on specific biological
pathways known to be perturbed and help design new
compounds with minimal impact on human health and
the environment.
Vermeulen et al., 2020

23. Known environmental chemical
hazards by targeted biomonitoring
Why use untargeted methods for exposome research?
Unknown,
undocumented
chemical
exposures
Biological
response
Exposure memory