Birth month affects lifetime disease risk: a phenome-wide method

Nontraditional models as research tools: the road not taken

Historical reasons resulted in the almost exclusive use of a few species, most prominently Mus musculus, as the mainstream models in biomedical research. This selection was not based on Mus's distinctive relevance to human disease but rather to the pre-existing availability of resources and tools for the species that were used as models, which has enabled their adoption for research in health sciences. Unless the utilization and range of nontraditional research models expand considerably, progress in biomedical research will remain restricted within the trajectory that has been set by the existing models and their ability to provide clinically relevant information.

Being born in autumn or winter is associated with asthma and allergic rhinitis in Finland

BACKGROUND

Our population-based study has previously shown that being born in winter or spring was associated with adult-onset asthma. The aim was to study if season of birth (SOB) is associated with airway allergy and related diseases: NSAID exacerbated respiratory disease (N-ERD), asthma, allergic rhinitis (AR), nonallergic rhinitis (NAR), chronic rhinosinusitis with nasal polyps (CRSwNP) and CRS without nasal polyps (CRSsNP) in Finland.

METHODS

A randomly sampled retrospective registry-based follow-up data (n = 74,868) of patients visiting Hospital District of Helsinki and Uusimaa (HUS) in Finland was used. The birth date, sex, visit date and comorbidities were collected from electronic health record data during visits from 2005 to 2019.

RESULTS

The mean (SD, range) age of the sample was 34.53 (25.47, 0-102) years, with 48.7 % being men. We divided the whole population in four groups based on the season they were born (SOB-groups). When observing these four SOB-groups, the proportion of those having asthma was 43.1%, 42.1%, 41.1%, 42.7%, in winter, spring, summer, and autumn SOB-groups, respectively. The proportion of those having AR was 12.6%, 12.0%, 10.7%, 12.1%, respectively. When having summer as a reference, being born in any other time of year was significantly associated with AR and, being born in autumn or winter was associated with asthma. No significant association was observed in CRS or N-ERD or NAR groups in adjusted models.

CONCLUSIONS

The study suggests that early life immunological events may have a role a role in pathogenesis of asthma and AR. As no association was observed between SOB and CRSsNP, CRSwNP, N-ERD or NAR, further studies on this are warranted.

Timing patterns of initial respiratory syncytial virus infection and factors influencing disease severity in hospitalized infants with different health status

This study aimed to determine the timing patterns of the initial respiratory syncytial virus (RSV) infection and to identify the factors influencing disease severity in infants of varying health status. A retrospective study was conducted at the Affiliated Children's Hospital of Chongqing Medical University from 2012 to 2022. The timing of the first RSV infection was estimated in infants with differing health status using correlation analysis, considering their birth time. Logistic regression was utilized to identify factors influencing severe RSV infection in these infants. RSV detection primarily occurred in the winter and spring. Epidemic season and peak timing of RSV were not significantly affected by health status or the COVID-19 pandemic. A strong positive correlation was observed between the age at RSV infection and the interval from birth to the RSV peak season. Infants born during the RSV epidemic season exhibited a higher likelihood of infection within the first 2 months postbirth. In contrast, those born outside the RSV epidemic season were more susceptible to infection during the subsequent peak. Notably, infants with pre-existing health conditions contracted RSV at an earlier age compared to their healthy counterparts. Among healthy infants, severe RSV infection was associated with sex, age, and timing of infection. For infants with underlying conditions, severe RSV infection was primarily related to age and timing of infection. The initial timing of RSV infection in infants varied depending on their health status. Young age and infection timing during the RSV epidemic season were significant risk factors for severe RSV infection. These findings provide a theoretical basis for optimizing immunization strategies for infants with diverse health conditions.

An epidemiological study of season of birth, mental health, and neuroimaging in the UK Biobank

Environmental exposures during the perinatal period are known to have a long-term effect on adult physical and mental health. One such influential environmental exposure is the time of year of birth which affects the amount of daylight, nutrients, and viral load that an individual is exposed to within this key developmental period. Here, we investigate associations between season of birth (seasonality), four mental health traits (n = 137,588) and multi-modal neuroimaging measures (n = 33,212) within the UK Biobank. Summer births were associated with probable recurrent Major Depressive Disorder (β = 0.026, pcorr = 0.028) and greater mean cortical thickness in temporal and occipital lobes (β = 0.013 to 0.014, pcorr<0.05). Winter births were associated with greater white matter integrity globally, in the association fibers, thalamic radiations, and six individual tracts (β = -0.013 to -0.022, pcorr<0.05). Results of sensitivity analyses adjusting for birth weight were similar, with an additional association between winter birth and white matter microstructure in the forceps minor and between summer births, greater cingulate thickness and amygdala volume. Further analyses revealed associations between probable depressive phenotypes and a range of neuroimaging measures but a paucity of interactions with seasonality. Our results suggest that seasonality of birth may affect later-life brain structure and play a role in lifetime recurrent Major Depressive Disorder. Due to the small effect sizes observed, and the lack of associations with other mental health traits, further research is required to validate birth season effects in the context of different latitudes, and by co-examining genetic and epigenetic measures to reveal informative biological pathways.

Optimal timing of influenza vaccination in young children: population based cohort study

OBJECTIVE

To assess optimal timing of influenza vaccination in young children.

DESIGN

Population based cohort study.

SETTING

United States.

PARTICIPANTS

Commercially insured children aged 2-5 years who were vaccinated against influenza during 2011-18.

MAIN OUTCOME MEASURE

Rates of diagnosis of influenza among children who were vaccinated against influenza, by birth month.

RESULTS

Overall, 819 223 children aged 2-5 received influenza vaccination. Children vaccinated in November and December were least likely to have a diagnosis of influenza, a finding that may be confounded by unmeasured factors that influence the timing of vaccination and risk of influenza. Vaccination commonly occurred on days of preventive care visits and during birth months. Children born in October were disproportionately vaccinated in October and were, on average, vaccinated later than children born in August and earlier than those born in December. Children born in October had the lowest rate of influenza diagnosis (for example, 2.7% (6016/224 540) versus 3.0% (6462/212 622) for those born in August; adjusted odds ratio 0.88, 95% confidence interval 0.85 to 0.92).

CONCLUSIONS

In a quasi-experimental analysis of young children vaccinated against influenza, birth month was associated with the timing of vaccination through its influence on the timing of preventive care visits. Children born in October were most likely to be vaccinated in October and least likely to have a diagnosis of influenza, consistent with recommendations promoting October vaccination.

The estimated effect of season and vitamin D in the first trimester on pubertal timing in girls and boys: a cohort study and an instrumental variable analysis

BACKGROUND

Season of birth has been associated with age at menarche. Maternal vitamin D levels in pregnancy may explain this effect. We investigated whether the season of first trimester or maternal 25-hydroxyvitamin D3 [25(OH)D3] levels were associated with pubertal timing in children.

METHODS

We conducted a follow-up study of 15 819 children born in 2000-03 from the Puberty Cohort, nested in the Danish National Birth Cohort (DNBC). Mean differences in attaining numerous pubertal markers, including a combined estimate for the average age at attaining all pubertal markers, were estimated for low (November-April) relative to high (May-October) sunshine exposure season in the first trimester using multivariable interval-censored regression models. Moreover, we conducted a two-sample instrumental variable analysis using season as an instrument for maternal first-trimester 25(OH)D3 plasma levels obtained from a non-overlapping subset (n = 827) in the DNBC.

RESULTS

For the combined estimate, girls and boys of mothers who had their first trimester during November-April had earlier pubertal timing than girls and boys of mothers whose first trimester occurred during May-October: -1.0 months (95% CI: -1.7 to -0.3) and -0.7 months (95% CI: -1.4 to -0.1), respectively. In the instrumental variable analysis, girls and boys also had earlier pubertal timing: respectively, -1.3 months (95% CI: -2.1 to -0.4) and -1.0 months (95% CI: -1.8 to -0.2) per SD (22 nmol/L) decrease in 25(OH)D3.

CONCLUSIONS

Both first pregnancy trimester during November-April and lower 25(OH)D3 were associated with earlier pubertal timing in girls and boys.

The effects of an increase in the retirement age on health care costs: evidence from administrative data

In this paper, we use unique health record data that cover outpatient care and the associated costs to quantify the health care costs of a sizable increase in the retirement age in Germany. For the identification, we exploit a sizable cohort-specific pension reform which abolished an early retirement program for all women born after 1951. Our results show that health care costs significantly increase by about 2.9% in the age group directly affected by the increase in the retirement age (women aged 60-62). We further show that the cost increase is mainly driven by the following specialist groups: Ophthalmologists, general practitioners (GPs), neurology, orthopedics, and radiology. While the effects are significant and meaningful on the individual level, we show that the increase in health care costs is modest relative to the positive fiscal effects of the pension reform. Specifically, we estimate an aggregate increase in the health costs of about 7.7 million euro for women born in 1952 aged 60-62 which amounts to less than 2% of the overall positive fiscal effects of the pension reform.

Assessment of effects of moon phases on hospital outpatient visits: An observational national study

Objectives

A vast amount of literature has been conducted for investigating the association of different lunar phases with human health; and it has mixed reviews for association and non-association of diseases with lunar phases. This study investigates the existence of any impact of moon phases on humans by exploring the difference in the rate of outpatient visits and type of diseases that prevail in either non-moon or moon phases.

Methods

We retrieved dates of non-moon and moon phases for eight years (1st January 2001-31st December 2008) from the timeanddate.com website for Taiwan. The study cohort consisted of 1 million people from Taiwan's National Health Insurance Research Database (NHIRD) followed over eight years (1st January 2001-31st December 2008). We used the two-tailed, paired-t-test to compare the significance of difference among outpatient visits for 1229 moon phase days and 1074 non-moon phase days by using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes from NHIRD records.

Results

We found 58 diseases that showed statistical differences in number of outpatient visits in the non-moon and moon phases.

Conclusions

The results of our study identified diseases that have significant variations during different lunar phases (non-moon and moon phases) for outpatient visits in the hospital. In order to fully understand the reality of the pervasive myth of lunar effects on human health, behaviors and diseases, more in-depth research investigations are required for providing comprehensive evidence covering all the factors, such as biological, psychological and environmental aspects.

Seasonal variations in renal biopsy numbers and primary glomerular disease features based on the Japan renal biopsy registry

We analyzed the seasonal variations in the number of renal biopsies and clinical characteristics of primary glomerular disease in Japan using the Japan Renal Biopsy Registry (J-RBR). We retrospectively collected clinical and pathological data of patients with primary glomerular disease who were registered in the J-RBR between 2007 and 2018. Immunoglobulin A nephropathy (IgAN), minimal change nephrotic syndrome (MCNS), membranous nephropathy (MN), and postinfectious acute glomerulonephritis (PIAGN) constituted the four major glomerular disorders included in this study (total, 13,989; IgAN, 9121; MCNS, 2298; MN, 2447; and PIAGN, 123). The number of patients with IgAN or MCNS was higher during summer. However, no overt seasonal variations were observed in patients with MN or PIAGN. Subgroup analyses suggested that in the patients with IgAN, more renal biopsies of severe cases were performed during winter, probably owing to age and blood pressure. Furthermore, more renal biopsies of severe cases were performed during spring and winter in patients with MCNS even after adjusting for the abovementioned host factors. This study suggests that seasonal factors influence the decision to perform renal biopsy as well as the pathogenesis of primary glomerular disease. Thus, our findings may provide important insights regarding the pathophysiology of primary glomerular disease.

Education mediating the associations between early life factors and frailty: a cross-sectional study of the UK Biobank

OBJECTIVES

Exposures in utero and during infancy may impact the development of diseases later in life. They may be linked with development of frailty, although the mechanism is unclear. This study aims to determine the associations between early life risk factors and development of frailty among middle-aged and older adults as well as potential pathways via education, for any observed association.

DESIGN

A cross-sectional study.

SETTINGS

This study used data from UK Biobank, a large population-based cohort.

PARTICIPANTS

502 489 individuals aged 37-73 years were included in the analysis.

PRIMARY AND SECONDARY OUTCOME MEASURES

Early life factors in this study included being breast fed as a baby, maternal smoking, birth weight, the presence of perinatal diseases, birth month and birth place (in or outside the UK). We developed a frailty index comprising 49 deficits. We used generalised structural equation modelling to examine the associations between early life factors and development of frailty and whether any observed association was mediated via educational attainment.

RESULTS

A history of breast feeding and normal birth weight were associated with a lower frailty index while maternal smoking, the occurrence of perinatal diseases and birth month with a longer day length were associated with a higher frailty index. Educational level mediated the relationship between these early life factors and frailty index.

CONCLUSIONS

This study highlights that biological and social risk occurring at different stages of life are related to the variations in frailty index in later life and suggests opportunities for prevention across the life course.

Month-of-Birth Effect on Muscle Mass and Strength in Community-Dwelling Older Women: The French EPIDOS Cohort

Background. Vitamin D is involved in muscle health and function. This relationship may start from the earliest stages of life during pregnancy when fetal vitamin D relies on maternal vitamin D stores and sun exposure. Our objective was to determine whether there was an effect of the month of birth (MoB) on muscle mass and strength in older adults. Methods. Data from 7598 community-dwelling women aged ≥ 70 years from the French multicentric EPIDOS cohort were used in this analysis. The quadricipital strength was defined as the mean value of 3 consecutive tests of the maximal isometric voluntary contraction strength of the dominant lower limb. The muscle mass was defined as the total appendicular skeletal muscle mass measured using dual energy X-ray absorptiometry scanner. The MoB was used as a periodic function in regressions models adjusted for potential confounders including age, year of birth, latitude of recruitment center, season of testing, body mass index, number of comorbidities, IADL score, regular physical activity, sun exposure at midday, dietary protein intake, dietary vitamin D intake, use vitamin D supplements, history and current use of corticosteroids. Results. A total of 7133 older women had a measure of muscle strength (mean age, 80.5 ± 3.8 years; mean strength, 162.3 ± 52.1 N). Data on total ASM were available from 1321 women recruited in Toulouse, France (mean, 14.86 ± 2.04 kg). Both the sine and cosine functions of MoB were associated with the mean quadricipital strength (respectively β = -2.1, p = 0.045 and β = -0.5, p = 0.025). The sine function of MoB was associated with total ASM (β = -0.2, p = 0.013), but not the cosine function (β = 0.1, p = 0.092). Both the highest value of average quadricipital strength (mean, 163.4 ± 20.2 N) and the highest value of total ASM (15.24 ± 1.27 kg) were found among participants born in August. Conclusions. Summer-early fall months of birth were associated with higher muscle mass and strength in community-dwelling older women.

Date of birth and the incidence of acute ischemic stroke in Hungary

INTRODUCTION

The effect of the date of birth on the incidence of cardiovascular disease was confirmed in earlier studies. We aimed to determine whether the season of birth may be associated with a higher incidence of stroke in later life by analyzing thrombolysis numbers according over a ten-year period in Hungary.

PATIENTS AND METHODS

We analyzed daily thrombolysis numbers between 2007 and 2016 according to the patients' date of birth based on seasons. The correlation between cumulative thrombolysis numbers between 2007 and 2016 per month and birth numbers per month based on data of the 1949 census were also examined.

RESULTS

Our results indicate that being born in the spring and summer in the northern hemisphere may be associated with a higher frequency of ischemic stroke necessitating thrombolytic treatment. This equates to a higher risk when conception and early pregnancy occur in the summer and autumn months.

CONCLUSIONS

This, however, cannot be defined as a causal relationship if we consider the number of live births in 1949, as both measures change similarly during the year, as indicated by the strong positive correlation between thrombolysis frequency according to date of birth between 2007 and 2016 and the number of births in the 1949 census by month.

Social Media Impact of Myopia Research

Background: Myopia has become a public health issue worldwide. The fast increase in myopia prevalence in the last years has been accompanied by an increase in information through social and conventional media. This has led to the fight not only against a pandemic but also against the infodemic. The excess of information has made it increasingly difficult for health professionals to identify high-quality articles. Alternative Metrics are useful tools to identify publications that provoke attention to society. This research aims to study the impact that research on myopia has had on social media. Methods: Almetric Explorer was used to make a search using “myopia” as a keyword. The 100 outputs with the highest attention were analyzed and correlated with the number of cites on Web of Science using Spearman’s correlation coefficient. Results: The top 100 Altmetric Attention Score were published in 47 journals and had a mean value of Altmetric Attention Score of 437.61 ± 718.33. The outputs were mostly discussed on Twitter, with a mean of 296.36 ± 1585.58 tweets and retweets, and a mean of 185.18 ± 211.57 readers in Mendeley. There was a low correlation between Altmetric Attention Score and Web of Science Cites for the top-100 outputs. Conclusions: although myopia is a research topic with a high interest in society, most cited articles are not those with the most impact on social media. Myopia researchers should make more effort in promoting their goals, and social media is a useful tool to share them.

Impact of Environmental Pollution on Female Reproduction

The increased pollution in the world atmosphere is a global concern. Water, air, and soil are polluted by various sources, such as farm fertilizer, sewage industrial waste products, fumes, and plastics, which in turn impact human health. Plastics and other mixtures of waste affect live in the water. Moreover, the ecosystem is disrupted by the use of heavy metal-containing chemicals in agriculture, and those are eventually consumed by humans. The consequences are a significant negative impact on health including reproductive health, which impairs fertility in the human population. Reproductive functions are severely affected by different chemicals which may interfere with hormonal functions. Greater consequences are faced by the women as the number of germ cells present in the ovary is fixed during fetal life, and which are nonrenewable. From the production of ovum to fertilization, to implantation, and finally continuation of pregnancy, all are affected by the heavy metals and endocrine disruptors. Lifestyle modifications such as consumption of organic foods, plastic product avoidance, separation of residential areas from industrial/agricultural areas, proper waste disposal, and so on, may help to improve the situation.

Association between maternal per- and polyfluoroalkyl substance exposure and newborn telomere length: Effect modification by birth seasons

BACKGROUND

Telomere length (TL) is an important biomarker of biological aging and disease that may be affected by prenatal exposure to environmental pollutants. Birth seasons have been linked to reproductive and immune-related diseases. Prenatal exposure to per- and polyfluoroalkyl substance (PFAS) has been associated with adverse birth outcomes, but the effects of PFAS and birth seasons on newborn TL are poorly understood.

OBJECTIVES

To explore the individual and combined effects of maternal PFAS exposure on newborn TL, with exploration of the interaction between PFAS and birth seasons on newborn TL.

METHODS

Between June 2015 and May 2018, a total of 499 mother-newborn pairs were recruited for a birth cohort study in Guangxi, China. Maternal blood samples were collected during pregnancy. Nine PFASs were measured by ultraperformance liquid chromatography-mass spectrometry. Newborn TL was assessed using quantitative real-time polymerase chain reaction. Modeling newborn TL as the outcome, multivariable linear regressions were performed for individual PFAS exposures, and Bayesian Kernel Machine Regressions were performed for PFAS mixtures. Furthermore, interaction analyses were conducted to evaluate the effect modification by birth seasons in these relationships.

RESULTS

For both single and multipollutant models, PFASs exposure were inversely associated with newborn TL, although none of the relationships were significant. The mixture of PFASs showed a potential positive trend of combined effect on newborn TL but non-statistically significant. Each ln-transformed unit concentration increase in PFOA was related to a 20.41% (95% CI: -30.44%, -8.93%) shorter TL in spring-born infants but not in those born in other birth seasons. Mothers in the middle and highest tertiles of PFOA exposure had 11.69% and 10.71% shorter TLs in spring-born infants, respectively.

CONCLUSION

Maternal PFAS exposure showed little association with newborn TL. The results suggested potential effect modification by birth season on the association between PFOA exposure and newborn TL.

The effect of ultraviolet radiation on the incidence and severity of major mental illness using birth month, birth year, and sunspot data

Background and objectives

The evaluation of the severity of patients afflicted with major mental illness (MMI) has been problematic because of confounding variables and genetic variability. There have been multiple studies that suggest several human diseases, especially schizophrenia, are predisposed to be born in certain months or seasons. This observation implied an epigenetic effect of sunlight, likely ultraviolet radiation (UVR), which is damaging to DNA, especially in an embryo. This paper outlines a method to evaluate the severity of schizophrenia (SZ), bipolar disorder (BPD), and schizoaffective disorder (SZ-AFF) using the month/year of birth of those affected compared to the month/year of birth of the general population (GP).

Relevance

Our previous research found that more intense UVR (equal to or greater than 90 sunspot number (SSN)) had a negative effect on the average human lifespan. Also, human birth rates vary in frequency by month of birth reflecting variables like availability of food, sunlight, and other unknown epigenetic factors. We wanted to see if the patient month of birth varied from the average birth months of the general population and if UVR has an epigenetic effect promoting these diseases.

Methods

We obtained the month and year of birth of 1,233 patients admitted over a 15-year period to Maine's largest state psychiatric hospital and counted the months of birth for each diagnosis of SZ, BPD, and SZ-AFF, and compared these results to the general population's birth months of 4,265,555 persons from U. S. Census Year 2006. The number of patients in each month was normalized to August and compared with the normalized birth months of the general population (GP). Plots of the normalized months were considered rates of change (e.g., derivatives) and their respective integrals gave domains of each mental illness relative to the GP. Normalizing the GP to unity was then related to the factor 1.28, e.g., 28% more entropy, deduced from the Sun's fractal dimension imprinted on biological organisms.

Results

The percent of patients meeting our criterion for severity: SZ = 27%; BPD = 26%; SZ-AFF = 100%.

Conclusions

High UVR intensity or a rapid increase in UVR in early gestation are likely epigenetic triggers of major mental illness. BPD is more epigenetically affected than SZ or SZ-AFF disorders. We found that 52% of 1,233 patients comprised the core function of a tertiary-care psychiatric hospital. Also, mental illness exacerbated when the median SSN doubled. This work also validates the Kraeplinian dichotomy.

What is new in this research

This paper offers a new paradigm for evaluating the severity of MMI and supports significant epigenetic effects from UVR.

Impact of birth season on second-to-fourth digit ratio, prostate volume, and prostate cancer

Purpose

The second-to-fourth digit ratio (digit ratio), which is determined in utero, is associated with exposure to visible sunlight during early pregnancy and the season of birth. The digit ratio is also associated with benign prostatic hyperplasia (BPH) and prostate cancer. This suggests that BPH and prostate cancer may be related to the birth season. Therefore, this study aimed to determine whether prostate volume and prostate cancer were related to the birth season.

Materials and Methods

A total of 858 male patients with lower urinary tract symptoms were enrolled. The right digit ratio was measured, and the month of birth was surveyed. Serum prostate-specific antigen (PSA) levels were measured, and prostate volumes were measured by transrectal ultrasonography. Patients with suspected prostate cancer underwent prostate biopsy.

Results

The mean age, digit ratio, prostate volume, and serum PSA level of 858 patients were 61.6 years, 0.947, 36.2 mL, and 4.24 ng/mL, respectively. Age, serum PSA levels, prostate biopsy rates, and cancer detection rates did not differ significantly according to the birth season. However, compared with the summer birth group, the winter birth group had lower digit ratios (0.951±0.040 vs. 0.941±0.040; p=0.014), larger prostate volumes (33.4±14.9 mL vs. 38.2±20.7 mL; p=0.008), and more prostate cancer (5.3% vs. 11.3%; p=0.031). Multivariate analysis showed that birth season independently predicted prostate cancer.

Conclusions

The relationships of birth season with prostate volume and prostate cancer may be due to differences in the amount of light exposure during early pregnancy.

Harnessing electronic health records to study emerging environmental disasters: a proof of concept with perfluoroalkyl substances (PFAS)

Environmental disasters are anthropogenic catastrophic events that affect health. Famous disasters include the Seveso disaster and the Fukushima-Daiichi nuclear meltdown, which had disastrous health consequences. Traditional methods for studying environmental disasters are costly and time-intensive. We propose the use of electronic health records (EHR) and informatics methods to study the health effects of emergent environmental disasters in a cost-effective manner. An emergent environmental disaster is exposure to perfluoroalkyl substances (PFAS) in the Philadelphia area. Penn Medicine (PennMed) comprises multiple hospitals and facilities within the Philadelphia Metropolitan area, including over three thousand PFAS-exposed women living in one of the highest PFAS exposure areas nationwide. We developed a high-throughput method that utilizes only EHR data to evaluate the disease risk in this heavily exposed population. We replicated all five disease/conditions implicated by PFAS exposure, including hypercholesterolemia, thyroid disease, proteinuria, kidney disease and colitis, either directly or via closely related diagnoses. Using EHRs coupled with informatics enables the health impacts of environmental disasters to be more easily studied in large cohorts versus traditional methods that rely on interviews and expensive serum-based testing. By reducing cost and increasing the diversity of individuals included in studies, we can overcome many of the hurdles faced by previous studies, including a lack of racial and ethnic diversity. This proof-of-concept study confirms that EHRs can be used to study human health and disease impacts of environmental disasters and produces equivalent disease-exposure knowledge to prospective epidemiology studies while remaining cost-effective.

The effect of season of birth on brain epigenome-wide DNA methylation of older adults

Perinatal light exposure predisposes towards health and behaviour in adulthood. Season of birth is associated with psychiatric, allergic, cardiovascular and metabolic problems. It has been proposed that early-life environmental light disrupts the development of biological rhythms which, in turn, influence later-life health. However, the mechanisms linking perinatal seasonal light to later-life biological rhythm and health in humans are unknown. In this study, we investigated the association between season of birth and epigenome-wide DNA methylation of two postmortem human brain regions (16 hypothalamus, 14 temporal cortex). We did not find statistically significant differences at the whole epigenome level, either because we lacked statistical power or that no association exists. However, when we examined 24 CpG sites that had the highest significance or differential methylation, we identified regions which may be associated with circadian rhythm entrainment, cholinergic neurotransmission and neural development. Amongst methylation of the core clock genes, we identified that hypothalamus Neuronal PAS Domain Protein 2 (NPAS2) gene has hypermethylated regions in long photoperiod-born individuals. In addition, we found nominal associations between season of birth and genes linked to chronotype and narcolepsy. Season of birth-related brain DNA methylation profile was different than a previously reported blood methylation profile, suggesting a tissue-specific mechanism of perinatal light programming. Overall, we are the first to analyse the relationship between season of birth and human brain DNA methylation. Further studies with larger sample sizes are required to confirm an imprinting effect of perinatal light on the circadian clock.

Researching 100 t cows: An innovative approach to identify intrinsic cows factors associated with a high lifetime milk production

Longevity is an important trait both from an economic and social perspective. Modern dairy cows are criticized for their short productive lifespan: only a minority of animals survives to a fourth lactation, implying that most cows are culled before reaching their maximal potential. In contrast, the population of 100 t cows (HT), reaching the threshold of 100,000 kg lifetime milk yield, is growing rapidly. As these cows combine a long lifespan with high functionality, a better understanding of their intrinsic characteristics might help us to improve the overall lifespan and lifetime production in dairy cows. The aim of the present research was to compare HT with their less-producing herd mates in order to identify intrinsic cow factors associated with longevity and high lifetime production. Therefore, we matched 26,248 HT with 691,597 herd mates, born in the same year in the same herd. Data were provided by Coöperatie rundveeverbetering (CRV) and contained birth dates, calving dates, milk yield and dam information. In addition, scores for conformation traits based on classifications in the first lactation and breeding values (for milk yield, fertility, udder health and claw health) were provided. Multivariable conditional logistic regression models were built to identify factors associated with reaching a lifetime milk yield of 100,000 kg. Results revealed cows born in September and born out of heifers to have the highest odds to become a HT. When cows received a score ≥ 83 (population average 80) for udder and feet & legs conformation, they had higher odds of reaching the 100,000 kg threshold. While a greater body condition and larger rump angle increased the odds of becoming a HT, this was decreased in cows with a large body depth. Finally, breeding values for milk yield, fertility, udder health and claw health were positively associated with the likelihood of reaching a lifetime milk yield of 100,000 kg. In conclusion, to increase lifetime milk yield in dairy herds, farmers should select heifers with high scores for conformation traits like udder and feet & legs and high breeding values for milk yield, fertility and udder health. Furthermore, our data suggest that being born in September out of a heifer potentially contributes to reaching a high lifetime milk yield.

Birth month and infant gross motor development: Results from the Japan Environment and Children's Study (JECS)

The association between birth month and neurodevelopmental or psychiatric disorders has been investigated in a number of previous studies; however, the results have been inconsistent. This study investigated the association between birth month and child gross motor development at 6 and 12 months of age in a large cohort of infants (n = 72,203) participating in the Japan Environment and Children’s Study (JECS). Gross motor development was assessed using the Ages and Stages Questionnaire (ASQ-3). At 6 months and 12 months, 20.7% and 14.2%, respectively, had ASQ-3 indications of gross motor problems. Birth month was strongly associated with gross motor development at both time points, particularly at 6 months. Summer-born infants had the worst outcomes at both 6 months and 12 months of age. This outcome applied to the ASQ-3 score itself and to the adjusted Relative Risk (aRR), with the highest aRRs (relative to January-born) among August-born (aRR 2.51; 95%CI 2.27–2.78 at 6 months), and June-born (aRR 1.84; 95%CI 1.63–2.09 at 12 months). Boys had better scores than girls both at 6 and 12 months of age. We speculate that seasonal factors—such as maternal vitamin D deficiency and influenza infection—affecting the fetus in early pregnancy might account for the findings.

Development of an Informatics Algorithm to Link Seasonal Infectious Diseases to Birth-Dependent Diseases Across Species: A Case Study with Osteosarcoma

Many diseases have been linked with birth seasonality, and these fall into four main categories: mental, cardiovascular, respiratory and women's reproductive health conditions. Informatics methods are needed to uncover seasonally varying infectious diseases that may be responsible for the increased birth month-dependent disease risk observed. We have developed a method to link seasonal infectious disease data from the USA to birth month dependent disease data from humans and canines. We also include seasonal air pollution and climate data to determine the seasonal factors most likely involved in the response. We test our method with osteosarcoma, a rare bone cancer. We found the Lyme disease incidence was the most strongly correlated significant factor in explaining the birth month-osteosarcoma disease pattern (R=0.418, p=2.80X10-23), and this was true across all populations observed: canines, pediatric, and adult populations.

Early life factors and COVID-19 infection in England: A prospective analysis of UK Biobank participants

This study aims to examine whether maternal smoking, birth weight, birth month and breastfeeding are associated with COVID-19 infection and hospitalisation. Maternal smoking was positively associated with COVID-19 infection. Breastfeeding was negatively associated with COVID-19 infection. The odds of being hospitalised due to COVID-19 were higher among those who had lower birthweight and mothers who were smoking during pregnancy.

Identifying distinct trajectories of acute otitis media in children: A prospective cohort study

Objectives

To identify possibly distinct acute otitis media (AOM) trajectories in childhood and identify determinants associated with specific AOM trajectories. To explore which child will become prone to recurrent AOM episodes and which will not.

Design

Population‐based prospective cohort study among 7863 children from birth until 10 years and their mothers.

Methods

This study was embedded in the Generation R Study: a population‐based prospective cohort study. Data on AOM and determinants were collected by repeated parental questionnaires. Distinct AOM trajectories within the population were identified with latent‐class analyses. Next, using multivariate analysis we checked whether specific determinants were associated with specific trajectories.

Results

Three distinct trajectories were identified; that is, non–otitis prone, early AOM—that is children who suffered AOM episodes until 3 years of age but not beyond, and persistent AOM—that is children who remained otitis‐prone. Male gender (OR: 1.26, CI: 1.11‐1.43) and day‐care attendance (OR: 1.31, CI: 1.06‐1.60) were associated with increased odds of early AOM. Breastfeeding was beneficial for children in both the early‐AOM and persistent‐AOM trajectories (OR: 0.78 and 0.77, respectively). Birth in the summer or autumn as compared with birth in the spring decreased odds of AOM only in the persistent‐AOM trajectory. Half of all AOM‐prone children recovered after the age of 3 years.

Conclusion

Specific determinants are associated with different AOM trajectories. Future research is needed to better predict which child will remain otitis‐prone and which recovers after the age of 3 years to better tailor treatment towards the needs of the individual child.

Born in winter or spring more susceptible to all-cause and cardiovascular disease death in rural areas of China: results from a 11.9-year follow-up study

There has been no evidence on the effects of birth season and birth month on mortality in China. We aimed to explore the association between birth season, birth month and all-cause and cardiovascular disease (CVD) death. A population-based sample of 21,338 Chinese rural participants aged ≥35 years at baseline was included in our analysis. Age and multivariable adjusted Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) for the relationship between astronomical birth season (autumn as the reference), birth month (November as the reference), and all-cause and CVD mortality. During a median follow-up period of 11.9 years, 2,207 people died from all-cause and 1,214 people were attributed to CVD death. In multivariable adjusted analyses, for all-cause death, spring and winter had HRs (95% CIs) of 1.134 (1.005–1.280) and 1.162 (1.038–1.301), respectively; January, March, May, and August had HRs (95% CIs) of 1.249 (1.027–1.518), 1.234 (1.008–1.512), 1.276 (1.037–1.571), and 1.232 (1.003–1.513), respectively. For CVD death, spring and winter with HRs (95% CIs) of mortality were 1.232 (1.048–1.449) and 1.174 (1.007–1.369), respectively; March with HR (95% CI) of mortality were 1.343 (1.030–1.750) (all P < 0.05). Our study indicated that people born in the winter or spring were significantly associated with all-cause and cardiovascular disease mortality in rural areas of China.

Phenotype risk scores (PheRS) for pancreatic cancer using time-stamped electronic health record data: Discovery and validation in two large biobanks

BACKGROUND

Traditional methods for disease risk prediction and assessment, such as diagnostic tests using serum, urine, blood, saliva or imaging biomarkers, have been important for identifying high-risk individuals for many diseases, leading to early detection and improved survival. For pancreatic cancer, traditional methods for screening have been largely unsuccessful in identifying high-risk individuals in advance of disease progression leading to high mortality and poor survival. Electronic health records (EHR) linked to genetic profiles provide an opportunity to integrate multiple sources of patient information for risk prediction and stratification. We leverage a constellation of temporally associated diagnoses available in the EHR to construct a summary risk score, called a phenotype risk score (PheRS), for identifying individuals at high-risk for having pancreatic cancer. The proposed PheRS approach incorporates the time with respect to disease onset into the prediction framework. We combine and contrast the PheRS with more well-known measures of inherited susceptibility, namely, the polygenic risk scores (PRS) for prediction of pancreatic cancer.

METHODOLOGY

We first calculated pairwise, unadjusted associations between pancreatic cancer diagnosis and all possible other diagnoses across the medical phenome. We call these pairwise associations co-occurrences. After accounting for cross-phenotype correlations, the multivariable association estimates from a subset of relatively independent diagnoses were used to create a weighted sum PheRS. We constructed time-restricted risk scores using data from 38,359 participants in the Michigan Genomics Initiative (MGI) based on the diagnoses contained in the EHR at 0, 1, 2, and 5 years prior to the target pancreatic cancer diagnosis. The PheRS was assessed for predictability in the UK Biobank (UKB). We tested the relative contribution of PheRS when added to a model containing a summary measure of inherited genetic susceptibility (PRS) plus other covariates like age, sex, smoking status, drinking status, and body mass index (BMI).

RESULTS

Our exploration of co-occurrence patterns identified expected associations while also revealing unexpected relationships that may warrant closer attention. Solely using the pancreatic cancer PheRS at 5 years before the target diagnoses yielded an AUC of 0.60 (95% CI = [0.58, 0.62]) in UKB. A larger predictive model including PheRS, PRS, and the covariates at the 5-year threshold achieved an AUC of 0.74 (95% CI = [0.72, 0.76]) in UKB. We note that PheRS does contribute independently in the joint model. Finally, scores at the top percentiles of the PheRS distribution demonstrated promise in terms of risk stratification. Scores in the top 2% were 10.20 (95% CI = [9.34, 12.99]) times more likely to identify cases than those in the bottom 98% in UKB at the 5-year threshold prior to pancreatic cancer diagnosis.

CONCLUSIONS

We developed a framework for creating a time-restricted PheRS from EHR data for pancreatic cancer using the rich information content of a medical phenome. In addition to identifying hypothesis-generating associations for future research, this PheRS demonstrates a potentially important contribution in identifying high-risk individuals, even after adjusting for PRS for pancreatic cancer and other traditional epidemiologic covariates. The methods are generalizable to other phenotypic traits.

Extending an open-source tool to measure data quality: case report on Observational Health Data Science and Informatics (OHDSI)

Introduction

As the health system seeks to leverage large-scale data to inform population outcomes, the informatics community is developing tools for analysing these data. To support data quality assessment within such a tool, we extended the open-source software Observational Health Data Sciences and Informatics (OHDSI) to incorporate new functions useful for population health.

Methods

We developed and tested methods to measure the completeness, timeliness and entropy of information. The new data quality methods were applied to over 100 million clinical messages received from emergency department information systems for use in public health syndromic surveillance systems.

Discussion

While completeness and entropy methods were implemented by the OHDSI community, timeliness was not adopted as its context did not fit with the existing OHDSI domains. The case report examines the process and reasons for acceptance and rejection of ideas proposed to an open-source community like OHDSI.

Season-of-birth phenomenon in health and longevity: epidemiologic evidence and mechanistic considerations

In many human populations, especially those living in regions with pronounced climatic differences between seasons, the most sensitive (prenatal and neonatal) developmental stages occur in contrasting conditions depending on the season of conception. The difference in prenatal and postnatal environments may be a factor significantly affecting human development and risk for later life chronic diseases. Factors potentially contributing to this kind of developmental programming include nutrition, outdoor temperature, infectious exposures, duration of sunlight, vitamin D synthesis, etc. Month of birth is commonly used as a proxy for exposures which vary seasonally around the perinatal period. Season-of-birth patterns have been identified for many chronic health outcomes. In this review, the research evidence for the seasonality of birth in adult-life disorders is provided and potential mechanisms underlying the phenomenon of early life seasonal programming of chronic disease and longevity are discussed.

Violet-light suppression of thermogenesis by opsin 5 hypothalamic neurons

The opsin family of G-protein-coupled receptors are used as light detectors in animals. Opsin 5 (also known as neuropsin or OPN5) is a highly conserved opsin that is sensitive to visible violet light1,2. In mice, OPN5 is a known photoreceptor in the retina3 and skin4 but is also expressed in the hypothalamic preoptic area (POA)5. Here we describe a light-sensing pathway in which POA neurons that express Opn5 regulate thermogenesis in brown adipose tissue (BAT). We show that Opn5 is expressed in glutamatergic warm-sensing POA neurons that receive synaptic input from several thermoregulatory nuclei. We further show that Opn5 POA neurons project to BAT and decrease its activity under chemogenetic stimulation. Opn5-null mice show overactive BAT, increased body temperature, and exaggerated thermogenesis when cold-challenged. Moreover, violet photostimulation during cold exposure acutely suppresses BAT temperature in wild-type mice but not in Opn5-null mice. Direct measurements of intracellular cAMP ex vivo show that Opn5 POA neurons increase cAMP when stimulated with violet light. This analysis thus identifies a violet light-sensitive deep brain photoreceptor that normally suppresses BAT thermogenesis.

Environmental temperature as a mediator on the association between photoperiod at birth and chronotype

The association between chronotypes and season of birth (SOB) remains an inconclusive issue due, in some extension, to the lack of investigations of mediation mechanisms. We evaluated the association of photoperiod at birth (PAB) with chronotypes and sleep duration in Brazil (n = 810), and the mediating effect of meteorological factors, sex, age and rs4753426 polymorphism in the melatonin receptor MTNR1B. Longer PAB was associated with a delayed mid-sleep phase with a suppressive effect of maximum environmental temperature. No significant interactions were identified for the other variables. These findings suggest that photoperiod and environmental temperature modulate chronotype development at early stages.

Seasonally variant gene expression in full-term human placenta

Seasonal exposures influence human health and development. The placenta, as a mediator of the maternal and fetal systems and a regulator of development, is an ideal tissue to understand the biological pathways underlying relationships between season of birth and later life health outcomes. Here, we conducted a differential expression (DE) analysis of season of birth in full-term human placental tissue to evaluate whether the placenta may be influenced by seasonal cues. Of the analyzed transcripts, 583 displayed DE between summer and winter births (False Discovery Rate [FDR] q < .05); among these, BHLHE40, MIR210HG, and HILPDA had increased expression among winter births (Bonferroni P < .05). Enrichment analyses of the seasonally variant genes between summer and winter births indicated overrepresentation of transcription factors HIF1A, VDR, and CLOCK, among others, and of GO term pathways related to ribosomal activity and infection. Additionally, a cosinor analysis found rhythmic expression for approximately 11.9% of all 17 664 analyzed placental transcripts. These results suggest that the placenta responds to seasonal cues and add to the growing body of evidence that the placenta acts as a peripheral clock, which may provide a molecular explanation for the extensive associations between season of birth and health outcomes.

Season of Birth Impacts the Neonatal Nasopharyngeal Microbiota

Objective: Pathogenic airway bacteria colonizing the neonatal airway increase the risk of childhood asthma, but little is known about the determinants of the establishment and dynamics of the airway microbiota in early life. We studied associations between perinatal risk factors and bacterial richness of the commensal milieu in the neonatal respiratory tract. Methods: Three hundred and twenty-eight children from the Copenhagen Prospective Studies on Asthma in the Childhood2000 (COPSAC2000) at-risk birth cohort were included in this study. The bacterial richness in each of the nasopharynxes of the 1-month old, asymptomatic neonates was analyzed by use of a culture-independent technique (T-RFLP). Information on perinatal risk factors included predisposition to asthma, allergy and eczema; social status of family; maternal exposures during pregnancy; mode of delivery; and postnatal exposures. The risk factor analysis was done by conventional statistics and partial least square discriminant analysis (PLSDA). Results: The nasopharyngeal bacterial community at 1-month displayed an average of 35 (IQR: 14-55, range 1-161) phylogenetically different bacteria groups. Season of birth was associated with nasopharyngeal bacterial richness at 1-month of age with a higher bacterial richness (p = 0.003) and more abundant specific bacterial profiles representing Gram-negative alpha-proteobacteria and Gram-positive Bacilli in the nasopharynx of summer-born children. Conclusion: Early postnatal bacterial colonization of the upper airways is significantly affected by birth season, emphasizing a future focus on the seasonality aspect in modelling the impact of early dynamic changes in airway bacterial communities in relation to later disease development.

Interactions between season of birth, chronological age and genetic polymorphisms in determining later-life chronotype

Human chronotype, the temporal pattern of daily behaviors, is influenced by postnatal seasonal programming and ageing. The aim of this study was to investigate genetic variants that are associated with season of birth programming and longitudinal chronotype change. Longitudinal sleep timing and genotype data from 1449 participants were collected for up to 27 years. Gene-environment interaction analysis was performed for 445 candidate single nucleotide polymorphisms that have previously been associated with chronotype. Associations were tested using linear mixed model. We identified 67 suggestively significant genomic loci that have genotype-ageing interaction and 25 genomic loci that may have genotype-season of birth interaction in determining chronotype. We attempted to replicate the results using longitudinal data of the UK Biobank from approximately 30,000 participants. Biological functions of these genes suggest that epigenetic regulation of gene expression and neural development may have roles in these processes. The strongest associated gene for sleep trajectories was ALKBH5, which has functions of DNA repair and epigenetic regulation. A potential candidate gene for postnatal seasonal programming was SIRT1, which has previously been implicated in postnatal programming, ageing and longevity. Genetic diversity may explain the heterogeneity in ageing-related change of sleep timing and postnatal environmental programming of later-life chronotype.

The emerging landscape of health research based on biobanks linked to electronic health records: Existing resources, statistical challenges, and potential opportunities

Biobanks linked to electronic health records provide rich resources for health-related research. With improvements in administrative and informatics infrastructure, the availability and utility of data from biobanks have dramatically increased. In this paper, we first aim to characterize the current landscape of available biobanks and to describe specific biobanks, including their place of origin, size, and data types. The development and accessibility of large-scale biorepositories provide the opportunity to accelerate agnostic searches, expedite discoveries, and conduct hypothesis-generating studies of disease-treatment, disease-exposure, and disease-gene associations. Rather than designing and implementing a single study focused on a few targeted hypotheses, researchers can potentially use biobanks' existing resources to answer an expanded selection of exploratory questions as quickly as they can analyze them. However, there are many obvious and subtle challenges with the design and analysis of biobank-based studies. Our second aim is to discuss statistical issues related to biobank research such as study design, sampling strategy, phenotype identification, and missing data. We focus our discussion on biobanks that are linked to electronic health records. Some of the analytic issues are illustrated using data from the Michigan Genomics Initiative and UK Biobank, two biobanks with two different recruitment mechanisms. We summarize the current body of literature for addressing these challenges and discuss some standing open problems. This work complements and extends recent reviews about biobank-based research and serves as a resource catalog with analytical and practical guidance for statisticians, epidemiologists, and other medical researchers pursuing research using biobanks.

Female Reproductive Performance and Maternal Birth Month: A Comprehensive Meta-Analysis Exploring Multiple Seasonal Mechanisms

Globally, maternal birth season affects fertility later in life. The purpose of this systematic literature review is to comprehensively investigate the birth season and female fertility relationship. Using PubMed, we identified a set of 282 relevant fertility/birth season papers published between 1972 and 2018. We screened all 282 studies and removed 131 non-mammalian species studies on fertility and 122 studies that were on non-human mammals. Our meta-analysis focused on the remaining 29 human studies, including twelve human datasets from around the world (USA, Europe, Asia). The main outcome was change in female fertility as observed by maternal birth month and whether this change was correlated with either temperature or rainfall. We found that temperature was either strongly correlated or anti-correlated in studies, indicating that another factor closely tied to temperature may be the culprit exposure. We found that rainfall only increases fertility in higher altitude locations (New Zealand, Romania, and Northern Vietnam). This suggests the possibility of a combined or multi-factorial mechanism underlying the female fertility - birth season relationship. We discuss other environmental and sociological factors on the birth season - female fertility relationship. Future research should focus on the role of birth season and female fertility adjusting for additional factors that modulate female fertility as discussed in this comprehensive review.

Robust-ODAL: Learning from heterogeneous health systems without sharing patient-level data

Electronic Health Records (EHR) contain extensive patient data on various health outcomes and risk predictors, providing an efficient and wide-reaching source for health research. Integrated EHR data can provide a larger sample size of the population to improve estimation and prediction accuracy. To overcome the obstacle of sharing patient-level data, distributed algorithms were developed to conduct statistical analyses across multiple clinical sites through sharing only aggregated information. However, the heterogeneity of data across sites is often ignored by existing distributed algorithms, which leads to substantial bias when studying the association between the outcomes and exposures. In this study, we propose a privacy-preserving and communication-efficient distributed algorithm which accounts for the heterogeneity caused by a small number of the clinical sites. We evaluated our algorithm through a systematic simulation study motivated by real-world scenarios and applied our algorithm to multiple claims datasets from the Observational Health Data Sciences and Informatics (OHDSI) network. The results showed that the proposed method performed better than the existing distributed algorithm ODAL and a meta-analysis method.

Environmental determinants associated with acute otitis media in children: a longitudinal study

BACKGROUND

Acute otitis media (AOM) is a common pediatric disease and frequent reason for antibiotic treatment. We aimed to identify environmental and host factors associated with AOM and assess which determinants were associated with AOM at specific ages.

METHODS

This study among 7863 children was embedded in the Generation R Study: a population-based prospective cohort study from fetal life onwards. Data on outcome and possible determinants were collected using questionnaires until 6 years. We used generalized estimating equation models to examine associations with AOM with longitudinal odds at different ages, considering correlations between repeated measurements.

RESULTS

Male gender increased odds of AOM in children at 2, 3, and 4 years but not at other ages. Postnatal household smoking, presence of siblings, and pet birds increased odds of AOM. Breastfeeding decreased AOM odds, most notably in the first 2 months of life. No association was found for season of birth, maternal age, ethnicity, aberrant birth weight for gestational age, prenatal smoking, furry pets, and daycare attendance.

CONCLUSIONS

Risk of childhood AOM varies with age. Significant association with AOM was found for gender and breastfeeding at specific ages and for household smoking, presence of siblings, and pet birds at all the studied ages.

Development and validation of the PEPPER framework (Prenatal Exposure PubMed ParsER) with applications to food additives

Background

Globally, 36% of deaths among children can be attributed to environmental factors. However, no comprehensive list of environmental exposures exists. We seek to address this gap by developing a literature-mining algorithm to catalog prenatal environmental exposures.

Methods

We designed a framework called.

PEPPER

Prenatal Exposure PubMed ParsER to a) catalog prenatal exposures studied in the literature and b) identify study type. Using PubMed Central, PEPPER classifies article type (methodology, systematic review) and catalogs prenatal exposures. We coupled PEPPER with the FDA's food additive database to form a master set of exposures.

Results

We found that of 31 764 prenatal exposure studies only 53.0% were methodology studies. PEPPER consists of 219 prenatal exposures, including a common set of 43 exposures. PEPPER captured prenatal exposures from 56.4% of methodology studies (9492/16 832 studies). Two raters independently reviewed 50 randomly selected articles and annotated presence of exposures and study methodology type. Error rates for PEPPER's exposure assignment ranged from 0.56% to 1.30% depending on the rater. Evaluation of the study type assignment showed agreement ranging from 96% to 100% (kappa = 0.909, p < .001). Using a gold-standard set of relevant prenatal exposure studies, PEPPER achieved a recall of 94.4%.

Conclusions

Using curated exposures and food additives; PEPPER provides the first comprehensive list of 219 prenatal exposures studied in methodology papers. On average, 1.45 exposures were investigated per study. PEPPER successfully distinguished article type for all prenatal studies allowing literature gaps to be easily identified.

Birth month, birth season, and overall and cardiovascular disease mortality in US women: prospective cohort study

OBJECTIVES

To 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.

DESIGN

Prospective cohort study.

SETTING

Nurses' Health Study, established in 1976, an ongoing prospective cohort study in the United States.

PARTICIPANTS

Female registered nurses who reported information on date of birth at study enrolment (n=116 911, 1976-2014, followed for 38 years).

EXPOSURE

Birth month and astronomical birth season (based on solstices and equinoxes as boundaries of the season categories).

MAIN OUTCOME MEASURES

Age 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.

RESULTS

Among 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%.

CONCLUSION

Participants 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.

Applied Veterinary Informatics: Development of a Semantic and Domain-Specific Method to Construct a Canine Data Repository

Animals are used to study the pathogenesis of various human diseases, but typically as animal models with induced disease. However, companion animals develop disease spontaneously in a way that mirrors disease development in humans. The purpose of this study is to develop a semantic and domain-specific method to enable construction of a data repository from a veterinary hospital that would be useful for future studies. We developed a two-phase method that combines semantic and domain-specific approaches to construct a canine data repository of clinical data collected during routine care at the Matthew J Ryan Veterinary Hospital of the University of Pennsylvania (PennVet). Our framework consists of two phases: (1) a semantic data-cleaning phase and (2) a domain-specific data-cleaning phase. We validated our data repository using a gold standard of known breed predispositions for certain diseases (i.e., mitral valve disease, atrial fibrillation and osteosarcoma). Our two-phase method allowed us to maximize data retention (99.8% of data retained), while ensuring the quality of our result. Our final population contained 84,405 dogs treated between 2000 and 2017 from 194 distinct dog breeds. We observed the expected breed associations with mitral valve disease, atrial fibrillation, and osteosarcoma (P < 0.05) after adjusting for multiple comparisons. Precision ranged from 60.0 to 83.3 for the three diseases (avg. 74.2) and recall ranged from 31.6 to 83.3 (avg. 53.3). Our study describes a two-phase method to construct a clinical data repository using canine data obtained during routine clinical care at a veterinary hospital.

The Association Between Season of Birth and Atopic Dermatitis in the Northern Hemisphere: A Systematic Review and Meta-Analysis

BACKGROUND

Cold and dry climate negatively affects skin barrier functions. This could explain the higher incidence of atopic dermatitis (AD) in Northern countries distant from the equator, as well as the general worsening of AD in Northern European winter months. Although it has been suggested that fall and winter birth is associated with AD, this remains unknown.

OBJECTIVES

To examine whether the prevalence of AD is associated with season of birth.

METHODS

We conducted a systematic review and meta-analysis. Two reviewers independently searched 3 databases. Study quality was assessed using a Newcastle-Ottawa scale. Study heterogeneity was assessed with Cochrane Q and I² statistics. Odds ratios with 95% CIs were calculated. Publication bias was assessed using funnel plots.

RESULTS

The systematic review identified 23 relevant articles of which 9 articles were included in the meta-analysis. Among a total of 726,378 children aged 0 to 12 years, the overall pooled prevalence of AD was 12.9%. The pooled prevalence of AD was 15.4% (95% CI, 12.1%-19.1%), 14.9% (95% CI, 12.0%-18.1%), 12.7% (95% CI, 10.2%-15.4%), and 13.7% (95% CI, 10.8%-17.0%), among children born in the fall, winter, spring, and summer, respectively. AD was significantly associated with fall (odds ratio, 1.16; 95% CI, 1.06-1.28; P = .0018) and winter (odds ratio, 1.15; 95% CI, 1.04-1.27; P = .0076) birth compared with spring birth.

CONCLUSIONS

Although a positive and significant association was observed between being born in fall and winter and developing AD on the Northern hemisphere, there is a need for additional and better-designed studies to understand the effect of seasonal changes on the risk of AD.

Evaluating statistical approaches to leverage large clinical datasets for uncovering therapeutic and adverse medication effects

Motivation

Phenome-wide association studies (PheWAS) have been used to discover many genotype-phenotype relationships and have the potential to identify therapeutic and adverse drug outcomes using longitudinal data within electronic health records (EHRs). However, the statistical methods for PheWAS applied to longitudinal EHR medication data have not been established.

Results

In this study, we developed methods to address two challenges faced with reuse of EHR for this purpose: confounding by indication, and low exposure and event rates. We used Monte Carlo simulation to assess propensity score (PS) methods, focusing on two of the most commonly used methods, PS matching and PS adjustment, to address confounding by indication. We also compared two logistic regression approaches (the default of Wald versus Firth's penalized maximum likelihood, PML) to address complete separation due to sparse data with low exposure and event rates. PS adjustment resulted in greater power than PS matching, while controlling Type I error at 0.05. The PML method provided reasonable P-values, even in cases with complete separation, with well controlled Type I error rates. Using PS adjustment and the PML method, we identify novel latent drug effects in pediatric patients exposed to two common antibiotic drugs, ampicillin and gentamicin.

Availability and implementation

R packages PheWAS and EHR are available at https://github.com/PheWAS/PheWAS and at CRAN (https://www.r-project.org/), respectively. The R script for data processing and the main analysis is available at https://github.com/choileena/EHR.

Supplementary information

Supplementary data are available at Bioinformatics online.

Translational medicine in the Age of Big Data

The ability to collect, store and analyze massive amounts of molecular and clinical data is fundamentally transforming the scientific method and its application in translational medicine. Collecting observations has always been a prerequisite for discovery, and great leaps in scientific understanding are accompanied by an expansion of this ability. Particle physics, astronomy and climate science, for example, have all greatly benefited from the development of new technologies enabling the collection of larger and more diverse data. Unlike medicine, however, each of these fields also has a mature theoretical framework on which new data can be evaluated and incorporated-to say it another way, there are no 'first principals' from which a healthy human could be analytically derived. The worry, and it is a valid concern, is that, without a strong theoretical underpinning, the inundation of data will cause medical research to devolve into a haphazard enterprise without discipline or rigor. The Age of Big Data harbors tremendous opportunity for biomedical advances, but will also be treacherous and demanding on future scientists.

Disease associations depend on visit type: results from a visit-wide association study

Introduction

Widespread adoption of Electronic Health Records (EHR) increased the number of reported disease association studies, or Phenome-Wide Association Studies (PheWAS). Traditional PheWAS studies ignore visit type (i.e., department/service conducting the visit). In this study, we investigate the role of visit type on disease association results in the first Visit-Wide Association Study or ‘VisitWAS’.

Results

We studied this visit type effect on association results using EHR data from the University of Pennsylvania. Penn EHR data comes from 1,048 different departments and clinics. We analyzed differences between cancer and obstetrics/gynecologist (Ob/Gyn) visits. Some findings were expected (i.e., increase of neoplasm diagnoses among cancer visits), but others were surprising, including an increase in infectious disease conditions among those visiting the Ob/Gyn.

Conclusion

We conclude that assessing visit type is important for EHR studies because different medical centers have different visit type distributions. To increase reproducibility among EHR data mining algorithms, we recommend that researchers report visit type in studies.

Electronic supplementary material

The online version of this article (10.1186/s13040-019-0203-2) contains supplementary material, which is available to authorized users.

Attention deficit hyperactivity disorder late birthdate effect common in both high and low prescribing international jurisdictions: a systematic review

BACKGROUND

Multiple studies have found that the youngest children in a classroom are at elevated risk of being diagnosed with, or medicated for, ADHD. This systematic review was conducted to investigate whether this late birthdate effect is the norm and whether the strength of effect is related to the absolute risk of being diagnosed/medicated.

METHODS

A literature search of the PubMed and ERIC databases and snowball and grey literature searching were conducted.

RESULTS

A total of 19 studies in 13 countries covering over 15.4 million children investigating this relationship were identified. Three other studies exploring related topics were identified. The diversity of methodologies prevented a meta-analysis. Instead a systematic review of the 22 studies was conducted. A total of 17 of the 19 studies found that the youngest children in a school year were considerably more likely to be diagnosed and/or medicated than their older classmates. Two Danish studies found either a weak or no late birth date effect. There was no consistent relationship between per-capita diagnosis or medication rates and the strength of the relative age effect, with strong effects reported in most jurisdictions with comparatively low rates.

CONCLUSIONS

It is the norm internationally for the youngest children in a classroom to be at increased risk of being medicated for ADHD, even in jurisdictions with relatively low prescribing rates. A lack of a strong effect in Denmark may be accounted for by the common practice of academic 'redshirting', where children judged by parents as immature have a delayed school start. Redshirting may prevent and/or disguise late birthdate effects and further research is warranted. The evidence of strong late birthdate effects in jurisdictions with comparatively low diagnosis/medication rates challenges the notion that low rates indicate sound diagnostic practices.

ODAL: A one-shot distributed algorithm to perform logistic regressions on electronic health records data from multiple clinical sites

Electronic Health Records (EHR) contain extensive information on various health outcomes and risk factors, and therefore have been broadly used in healthcare research. Integrating EHR data from multiple clinical sites can accelerate knowledge discovery and risk prediction by providing a larger sample size in a more general population which potentially reduces clinical bias and improves estimation and prediction accuracy. To overcome the barrier of patient-level data sharing, distributed algorithms are developed to conduct statistical analyses across multiple sites through sharing only aggregated information. The current distributed algorithm often requires iterative information evaluation and transferring across sites, which can potentially lead to a high communication cost in practical settings. In this study, we propose a privacy-preserving and communication-efficient distributed algorithm for logistic regression without requiring iterative communications across sites. Our simulation study showed our algorithm reached comparative accuracy comparing to the oracle estimator where data are pooled together. We applied our algorithm to an EHR data from the University of Pennsylvania health system to evaluate the risks of fetal loss due to various medication exposures.