Hui Hu Ph.D.
Assistant Professor of Medicine
Associate Epidemiologist
Channing Division of Network Medicine
Brigham and Women's Hospital and Harvard Medical School
July 27, 2022
To draw attention to the critical need for more complete environmental exposure assessment
"encompasses all life-course environmental exposures from the prenatal period onwards, complementing the genome"
"in a broader sense of all lifestyle, infections, radiation, natural and man-made chemicals and occupational exposures"
Two domains:
Source: Hu et al. 2022
Examples of publicly available spatial and contextual exposome data sources
Source: Hu et al. 2022
Source: Hu et al. 2022
This approach is increasingly challenging in spatial and contextual exposome studies:
- Lack of expertise
- Infeasible to conduct sensitivity analyses
Potential solution: establish reference spatial and contextual exposome databases with gold-standard measures
- on different spatial and contextual exposome constructs
- across different geographic areas and time periods
Two approaches with different assumptions/hypotheses:
vs
Source: Hu et al. 2020
Total number of variables | p-value of var1 | p-value cut point | Statistically significant? |
---|---|---|---|
100 | 0.0001 | 0.0005 | Yes |
1,000 | 0.0001 | 0.00005 | No |
Source: Hu et al. 2020
Spatiotemporal Linkages
id | long | lat | startDate | endDate |
---|---|---|---|---|
id | exp1 | exp2 | ... |
---|---|---|---|
Source: Lovasi et al. 2011
Many statistical methods have been developed/applied in exposome-health studies
Predominantly developed to handle exposures measured at the individual-level
Source: Hu et al. 2022
Toxicant/Chemical Mixtures | The Spatial and Contextual Exposome | |
---|---|---|
Number of variables | 10-10 | 10 -10 |
Common sample size | 10 -10 | ≥10 |
Spatial structure | No | Yes |
Temporal structure | Minimal | Yes |
2
4
3
2
4
5
ExWAS and elastic-net
p=5,784
N=819,399
ExWAS
p=337
N=3,108
p=237
N=1,200
p<20
N<250
50,368 patients with COVID-19 between March 2020 and October 2021
Predictors:
Linked data from:
VSBR only: 0.63 (0.59, 0.67)
VSBR+PRAMS: 0.68 (0.65, 0.72)
VSBR+PRAMS+
Exposome: 0.74 (0.70, 0.77)
Gradient boosting decision trees: