Uncovering exposures responsible for birth season – disease effects: a global study

Author:

Boland Mary Regina12345,Parhi Pradipta6,Li Li78,Miotto Riccardo78,Carroll Robert9,Iqbal Usman101112,Nguyen Phung-Anh (Alex)101113,Schuemie Martijn1014,You Seng Chan1015,Smith Donahue16,Mooney Sean16,Ryan Patrick51014,Li Yu-Chuan (Jack)101213,Park Rae Woong1015,Denny Josh917,Dudley Joel T78,Hripcsak George510,Gentine Pierre6,Tatonetti Nicholas P510

Affiliation:

1. Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA

2. Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA, USA

3. Center for Excellence in Environmental Toxicology, University of Pennsylvania, Philadelphia, PA, USA

4. Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA

5. Department of Biomedical Informatics, Columbia University, New York, NY, USA

6. Department of Earth and Environmental Engineering, Columbia University, New York, NY, USA

7. Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA

8. Institute for Next Generation Healthcare, Icahn School of Medicine at Mount Sinai, New York, NY, USA

9. Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA

10. Observational Health Data Sciences and Informatics, Columbia University, New York, NY, USA

11. Masters Program in Global Health and Development Department, College of Public Health, Taipei Medical University, Taiwan

12. College of Medical Science and Technology, Taipei Medical University, Taiwan

13. International Center for Health Information Technology, Taipei Medical University, Taiwan

14. Janssen Research and Development, Raritan, NJ, USA

15. Department of Biomedical Informatics, Ajou University School of Medicine, Republic of Korea

16. Department of Biomedical Informatics, University of Washington, Seattle, Washington, USA

17. Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA

Abstract

Abstract Objective Birth month and climate impact lifetime disease risk, while the underlying exposures remain largely elusive. We seek to uncover distal risk factors underlying these relationships by probing the relationship between global exposure variance and disease risk variance by birth season. Material and Methods This study utilizes electronic health record data from 6 sites representing 10.5 million individuals in 3 countries (United States, South Korea, and Taiwan). We obtained birth month–disease risk curves from each site in a case-control manner. Next, we correlated each birth month–disease risk curve with each exposure. A meta-analysis was then performed of correlations across sites. This allowed us to identify the most significant birth month–exposure relationships supported by all 6 sites while adjusting for multiplicity. We also successfully distinguish relative age effects (a cultural effect) from environmental exposures. Results Attention deficit hyperactivity disorder was the only identified relative age association. Our methods identified several culprit exposures that correspond well with the literature in the field. These include a link between first-trimester exposure to carbon monoxide and increased risk of depressive disorder (R = 0.725, confidence interval [95% CI], 0.529-0.847), first-trimester exposure to fine air particulates and increased risk of atrial fibrillation (R = 0.564, 95% CI, 0.363-0.715), and decreased exposure to sunlight during the third trimester and increased risk of type 2 diabetes mellitus (R = −0.816, 95% CI, −0.5767, −0.929). Conclusion A global study of birth month–disease relationships reveals distal risk factors involved in causal biological pathways that underlie them.

Funder

National Center for Advancing Translational Sciences

NIH

Korea Health Industry Development Institute

Ministry of Health and Welfare

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

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