TY - JOUR
T1 - The exposome - A new approach for risk assessment
AU - Sillé, Fenna C.M.
AU - Karakitsios, Spyros
AU - Kleensang, Andre
AU - Koehler, Kirsten
AU - Maertens, Alexandra
AU - Miller, Gary W.
AU - Prasse, Carsten
AU - Quiros-Alcala, Lesliam
AU - Ramachandran, Gurumurthy
AU - Rappaport, Stephen M.
AU - Rule, Ana M.
AU - Sarigiannis, Denis
AU - Smirnova, Lena
AU - Hartung, Thomas
N1 - Funding Information:
Stephen Rappaport was supported by grant P42ES004705 (NIEHS). The mentioned work on computational toxicology was mainly executed by Thomas Luechtefeld during his PhD and within ToxTrack. Thomas Luechtefeld was supported by an NIEHS training grant (T32 ES007141). This work was supported by the EU-ToxRisk project (An Integrated European ?Flagship? Program Driving Mechanism-Based Toxicity Testing and Risk Assessment for the 21st Century) funded by the European Commission under the Horizon 2020 program (Grant Agreement No. 681002). This work has also received funding from the European Union's Seventh Programme for research, technological development and demonstration under grant agreement No 603946 (Health and Environment-wide Associations via Large population Surveys-HEALS). The fruitful discussions with further members of the Johns Hopkins Exposome Collaborative, namely Drs Hugh Ellis, Keeve Nachman, Scot Miller and Meredith McCormack, is gratefully appreciated. The most valuable input of many colleagues inside and outside our team is gratefully appreciated.
Funding Information:
Stephen Rappaport was supported by grant P42ES004705 (NIEHS). The mentioned work on computational toxicology was mainly executed by Thomas Luechtefeld during his PhD and within ToxTrack. Thomas Luechtefeld was supported by an NIEHS training grant (T32 ES007141). This work was supported by the EU-ToxRisk project (An Integrated European “Flag-ship” Program Driving Mechanism-Based Toxicity Testing and Risk Assessment for the 21st Century) funded by the European Commission under the Horizon 2020 program (Grant Agreement No. 681002). This work has also received funding from the European Union’s Seventh Programme for research, technological development and demonstration under grant agreement No 603946 (Health and Environment-wide Associations via Large population Surveys-HEALS). The fruitful discussions with further members of the Johns Hopkins Exposome Collaborative, namely Drs Hugh Ellis, Keeve Nachman, Scot Miller and Meredith McCormack, is gratefully appreciated. The most valuable input of many colleagues inside and outside our team is gratefully appreciated.
Publisher Copyright:
© The Authors, 2019.
PY - 2020/1
Y1 - 2020/1
N2 - Complementing the human genome with an exposome reflects the increasingly obvious impact of environmental exposure, which far exceeds the role of genetics, on human health. Considering the complexity of exposures and, in addition, the reactions of the body to exposures - i.e., the exposome - reverses classical exposure science where the precise measurement of single or few exposures is associated with specific health or environmental effects. The complete description of an individual's exposome is impossible; even less so is that of a population. We can, however, cast a wider net by foregoing some rigor in assessment and compensating with the statistical power of rich datasets. The advent of omics technologies enables a relatively cheap, high-content description of the biological effects of substances, especially in tissues and biofluids. They can be combined with many other rich data-streams, creating big data of exposure and effect. Computational methods increasingly allow data integration, discerning the signal from the noise and formulating hypotheses of exposure-effect relationships. These can be followed up in a targeted way. With a better exposure element in the risk equation, exposomics - new kid on the block of risk assessment - promises to identify novel exposure (interactions) and health/environment effect associations. This may also create opportunities to prioritize the more relevant chemicals for risk assessment, thereby lowering the burden on hazard assessment in an exposure-driven approach. Technological developments and synergies between approaches, quality assurance (ultimately as Good Exposome Practices), and the integration of mechanistic thinking will advance this approach.
AB - Complementing the human genome with an exposome reflects the increasingly obvious impact of environmental exposure, which far exceeds the role of genetics, on human health. Considering the complexity of exposures and, in addition, the reactions of the body to exposures - i.e., the exposome - reverses classical exposure science where the precise measurement of single or few exposures is associated with specific health or environmental effects. The complete description of an individual's exposome is impossible; even less so is that of a population. We can, however, cast a wider net by foregoing some rigor in assessment and compensating with the statistical power of rich datasets. The advent of omics technologies enables a relatively cheap, high-content description of the biological effects of substances, especially in tissues and biofluids. They can be combined with many other rich data-streams, creating big data of exposure and effect. Computational methods increasingly allow data integration, discerning the signal from the noise and formulating hypotheses of exposure-effect relationships. These can be followed up in a targeted way. With a better exposure element in the risk equation, exposomics - new kid on the block of risk assessment - promises to identify novel exposure (interactions) and health/environment effect associations. This may also create opportunities to prioritize the more relevant chemicals for risk assessment, thereby lowering the burden on hazard assessment in an exposure-driven approach. Technological developments and synergies between approaches, quality assurance (ultimately as Good Exposome Practices), and the integration of mechanistic thinking will advance this approach.
UR - http://www.scopus.com/inward/record.url?scp=85078625377&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85078625377&partnerID=8YFLogxK
U2 - 10.14573/altex.2001051
DO - 10.14573/altex.2001051
M3 - Article
C2 - 31960937
AN - SCOPUS:85078625377
VL - 37
SP - 3
EP - 23
JO - ALTEX : Alternativen zu Tierexperimenten
JF - ALTEX : Alternativen zu Tierexperimenten
SN - 1868-596X
IS - 1
ER -