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J Am Med Inform Assoc. 2017 Sep 28. doi: 10.1093/jamia/ocx105. [Epub ahead of print]

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

Boland MR1,2,3,4,5,6, Parhi P7, Li L8,9, Miotto R8,9, Carroll R10, Iqbal U6,11,12, Nguyen PA6,11,13, Schuemie M6,14, You SC6,15, Smith D16, Mooney S16, Ryan P5,6,14, Li YJ6,12,13, Park RW6,15, Denny J10,17, Dudley JT8,9, Hripcsak G5,6, Gentine P7, Tatonetti NP5,6.

Author information

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
Observational Health Data Sciences and Informatics, Columbia University, New York, NY, USA.
7
Department of Earth and Environmental Engineering, Columbia University, New York, NY, USA.
8
Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
9
Institute for Next Generation Healthcare, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
10
Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, 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

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.

KEYWORDS:

attention deficit hyperactivity disorder; electronic health records; environmental exposure; pregnancy; seasons

PMID:
29036387
DOI:
10.1093/jamia/ocx105

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