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

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.

SUBMITTER: Boland MR

PROVIDER: S-EPMC7282503 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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

Boland Mary Regina MR Parhi Pradipta P Li Li L Miotto Riccardo R Carroll Robert R Iqbal Usman U Nguyen Phung-Anh Alex PA Schuemie Martijn M You Seng Chan SC Smith Donahue D Mooney Sean S Ryan Patrick P Li Yu-Chuan Jack YJ Park Rae Woong RW Denny Josh J Dudley Joel T JT Hripcsak George G Gentine Pierre P Tatonetti Nicholas P NP

Journal of the American Medical Informatics Association : JAMIA 20180301 3

<h4>Objective</h4>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.<h4>Material and methods</h4>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 b ...[more]

PMID: 29036387

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Project description:ObjectivesTo evaluate the associations between birth month, birth season, and overall and cardiovascular disease mortality, and to examine the role of familial and socioeconomic factors in these associations.DesignProspective cohort study.SettingNurses' Health Study, established in 1976, an ongoing prospective cohort study in the United States.ParticipantsFemale registered nurses who reported information on date of birth at study enrolment (n=116?911, 1976-2014, followed for 38 years).ExposureBirth month and astronomical birth season (based on solstices and equinoxes as boundaries of the season categories).Main outcome measuresAge and various multivariable adjusted hazard ratios and 95% confidence intervals for the association between birth months (using November as the reference), astronomical birth season (using autumn as the reference), and overall and cardiovascular disease specific mortality were assessed using Cox proportional hazards models.ResultsAmong study participants, 43?248 overall deaths were documented during 4?136?364 person years of follow-up since enrolment, including 8360 cardiovascular disease related deaths. In fully adjusted multivariable analyses, no significant association was observed between birth month, birth season, and overall mortality. Compared with women born in November, increased cardiovascular disease mortality was observed among those born from March to July (hazard ratio for March, 1.09, 95% confidence interval 0.98 to 1.21; April, 1.12, 1.00 to 1.24; May, 1.08, 0.98 to 1.20; June, 1.07, 0.96 to 1.19; and July 1.08, 0.98 to 1.20). Those born in April had the highest cardiovascular disease mortality, and those born in December had the lowest (December, 0.95, 0.85 to 1.06). The relative difference between the lowest and highest risk month was 17.89%. Women born in spring (1.10, 1.04 to 1.17) and summer (1.09, 1.03 to 1.16) had a higher cardiovascular disease mortality than women born in the autumn. Adjustment for familial and socioeconomic factors did not change these results. The relative difference between the lowest and highest risk season was 10.00%.ConclusionParticipants born in the spring and summer (especially those born in March-July) had a slight but significant increase in cardiovascular disease specific mortality. However, no seasonal birth month effect was observed among women for overall mortality. Familial and socioeconomic factors did not appear to alter these associations. Further studies are required to confirm these findings and reveal mechanisms of these seasonal birth month effects in cardiovascular disease mortality.

Project description:Previous research suggests statistical associations between season of birth (SOB) with prevalence of neurobehavioral disorders such as schizophrenia and bipolar disorder, personality traits such as novelty and sensation seeking, and suicidal behavior. These effects are thought to be mediated by seasonal differences in perinatal photoperiod, which was recently shown to imprint circadian clock neurons and behavior in rodents. However, it is unknown whether SOB is associated with any measurable differences in the normal human adult brain, and whether individual SOB can be deduced based on phenotype. Here I show that SOB predicts morphological differences in brain structure, and that MRI scans carry spatially distributed information allowing significantly above chance prediction of an individual's SOB. Using an open source database of over 550 structural brain scans, Voxel-Based Morphometry (VBM) analysis showed a significant SOB effect in the left superior temporal gyrus (STG) in males (p=0.009, FWE whole-brain corrected), with greater gray matter volumes in fall and winter births. A cosinor analysis revealed a significant annual periodicity in the left STG gray matter volume (Zero Amplitude Test: p<5×10(-7)), with a peak towards the end of December and a nadir towards the end of June, suggesting that perinatal photoperiod accounts for this SOB effect. Whole-brain VBM maps were used as input features to multivariate machine-learning based analyses to classify SOB. Significantly greater than chance prediction was achieved in females (overall accuracy 35%, p<0.001), but not in males (overall accuracy 26%, p=0.45). Pairwise binary classification in females revealed that the highest discrimination was obtained for winter vs. summer classification (peak area under the ROC curve=0.71, p<0.0005). Discriminating regions included fusiform and middle temporal gyrus, inferior and superior parietal lobe, cerebellum, and dorsolateral and dorsomedial prefrontal cortex. Results indicate that SOB is detectable with MRI, imply that SOB exerts effects on the developing human brain that persist through adulthood, and suggest that neuroimaging may be a valuable intermediate phenotype in bridging the gap between SOB and personality and neurobehavioral disorders.

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

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

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