Infant Respiratory Syncytial Virus Bronchiolitis and Subsequent Risk of Pneumonia, Otitis Media, and Antibiotic Utilization.

Infant respiratory syncytial virus (RSV) bronchiolitis in the first 6 months of life was associated with increased odds of pneumonia, otitis media, and antibiotic prescription fills in the second 6 months of life. These data suggest a potential value of future RSV vaccination programs on subsequent respiratory health.

Dose, Timing, and Type of Infant Antibiotic Use and the Risk of Childhood Asthma.

BACKGROUND: Aspects of infant antibiotic exposure and its association with asthma development have been variably explored. We aimed to evaluate comprehensively and simultaneously the impact of dose, timing, and type of infant antibiotic use on the risk of childhood asthma. METHODS: Singleton, term-birth, non-low-birth-weight, and otherwise healthy children enrolled in the Tennessee Medicaid Program were included. Infant antibiotic use and childhood asthma diagnosis were ascertained from prescription fills and healthcare encounter claims. We examined the association using multivariable logistic regression models. RESULTS: Among 152 622 children, 79% had at least 1 antibiotic prescription fill during infancy. Infant antibiotic use was associated with increased odds of childhood asthma in a dose-dependent manner, with a 20% increase in odds (adjusted odds ratio [aOR], 1.20 [95% confidence interval {CI}, 1.19-1.20]) for each additional antibiotic prescription filled. This significant dose-dependent relationship persisted after additionally controlling for timing and type of the antibiotics. Infants who had broad-spectrum-only antibiotic fills had increased odds of developing asthma compared with infants who had narrow-spectrum-only fills (aOR, 1.10 [95% CI, 1.05-1.19]). There was no significant association between timing, formulation, anaerobic coverage, and class of antibiotics and childhood asthma. CONCLUSIONS: We found a consistent dose-dependent association between antibiotic prescription fills during infancy and subsequent development of childhood asthma. Our study adds important insights into specific aspects of infant antibiotic exposure. Clinical decision making regarding antibiotic stewardship and prevention of adverse effects should be critically assessed prior to use during infancy.

The current state of omics technologies in the clinical management of asthma and allergic diseases.

OBJECTIVE: To review the state of omics science specific to asthma and allergic diseases and discuss the current and potential applicability of omics in clinical disease prediction, treatment, and management. DATA SOURCES: Studies and reviews focused on the use of omics technologies in asthma and allergic disease research and clinical management were identified using PubMed. STUDY SELECTIONS: Publications were included based on relevance, with emphasis placed on the most recent findings. RESULTS: Omics-based research is increasingly being used to differentiate asthma and allergic disease subtypes, identify biomarkers and pathological mediators, predict patient responsiveness to specific therapies, and monitor disease control. Although most studies have focused on genomics and transcriptomics approaches, increasing attention is being placed on omics technologies that assess the effect of environmental exposures on disease initiation and progression. Studies using omics data to identify biological targets and pathways involved in asthma and allergic disease pathogenesis have primarily focused on a specific omics subtype, providing only a partial view of the disease process. CONCLUSION: Although omics technologies have advanced our understanding of the molecular mechanisms underlying asthma and allergic disease pathology, omics testing for these diseases are not standard of care at this point. Several important factors need to be addressed before these technologies can be used effectively in clinical practice. Use of clinical decision support systems and integration of these systems within electronic medical records will become increasingly important as omics technologies become more widely used in the clinical setting.

Association of newborn screening metabolites with risk of wheezing in childhood.

BACKGROUND: There are critical gaps in our understanding of the temporal relationships between metabolites and subsequent asthma development. This is the first study to examine metabolites from newborn screening in the etiology of early childhood wheezing. METHODS: One thousand nine hundred and fifty one infants enrolled between 2012 and 2014 from pediatric practices located in Middle Tennessee in the population-based birth cohort study, the Infant Susceptibility to Pulmonary Infections and Asthma Following RSV Exposure Study (INSPIRE), were linked with metabolite data from the Tennessee Newborn Screening Program. The association between the levels of 37 metabolites and the number of wheezing episodes in the past 12 months was assessed at 1, 2, and 3 years of life. RESULTS: Several metabolites were significantly associated with the number of wheezing episodes. Two acylcarnitines, C10:1 and C18:2, showed robust associations. Increasing levels of C10:1 were associated with increasing number of wheezing episodes at 2 years (OR 2.11, 95% CI 1.41-3.17) and 3 years (OR 2.56, 95% CI 1.59-4.11), while increasing levels of C18:2 were associated with increasing number of wheezing episodes at 1 year (OR 1.38, 95% CI 1.12-1.71) and 2 years (OR 1.47, 95% CI 1.17-1.84). CONCLUSIONS: Identification of specific metabolites and associated pathways involved in wheezing pathogenesis offer insights into potential targets to prevent childhood asthma morbidity.

Mediation of Adverse Pregnancy Outcomes in Autoimmune Conditions by Pregnancy Complications: A Mediation Analysis of Autoimmune Conditions and Adverse Pregnancy Outcomes.

OBJECTIVE: Autoimmune conditions are associated with an increased risk of adverse pregnancy complications and outcomes, suggesting that pregnancy complications may mediate the excess risk. We performed a causal mediation analysis to quantify the mediated effects of autoimmune conditions on adverse pregnancy outcomes. METHODS: We queried a California birth cohort created from linked birth certificates and hospital discharge summaries. From 2,963,888 births, we identified women with rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), psoriasis, and inflammatory bowel disease (IBD). Pregnancy complications included preeclampsia/hypertension, gestational diabetes mellitus, and infection in pregnancy. Adverse pregnancy outcomes were preterm birth, cesarean delivery, and small for gestational age. We performed a mediation analysis to estimate the total effects of each autoimmune condition and adverse pregnancy outcome and the indirect effects through pregnancy complications. RESULTS: All 4 autoimmune conditions were associated with preterm birth and cesarean delivery, and RA, SLE, and IBD were associated with offspring that were small for gestational age. The strongest mediator of RA, SLE, and psoriasis was preeclampsia/hypertension, accounting for 20-33% of the excess risk of preterm births and 10-19% of excess cesarean deliveries. Gestational diabetes mellitus and infections generally mediated <10% of excess adverse pregnancy outcomes. Of the 4 autoimmune conditions, selected pregnancy complications mediated the least number of adverse pregnancy outcomes among women with IBD. CONCLUSION: We found evidence that some excess risk of adverse pregnancy outcomes is mediated through pregnancy complications, particularly preeclampsia/hypertension. Quantifying excess risk and associated pathways provides insight into the underlying etiologies of adverse pregnancy outcomes and can inform intervention strategies.

Impact of autoimmune rheumatic diseases on birth outcomes: a population-based study.

Objectives: Autoimmune rheumatic diseases (ARDs) affect women of childbearing age and have been associated with adverse birth outcomes. The impact of diseases like ankylosing spondylitis and psoriatic arthritis (PsA) on birth outcomes remains less studied to date. Our objective was to evaluate the impact of ARDs on preterm birth (PTB), congenital anomalies, low birth weight (LBW) and small for gestational age (SGA), in a large cohort of women. Methods: We conducted a propensity score-matched analysis to predict ARD from a retrospective birth cohort of all live, singleton births in California occurring between 2007 and 2012. Data were derived from birth certificate records linked to hospital discharge International Classification of Diseases, ninth revision codes. Results: We matched 10 244 women with a recorded ARD diagnosis (rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), antiphospholipid syndrome, PsA); ankylosing spondylitis and juvenile idiopathic arthritis (JIA) to those without an ARD diagnosis. The adjusted OR (aOR) of PTB was increased for women with any ARD (aOR 1.93, 95% CI 1.78 to 2.10) and remained significant for those with RA, SLE, PsA and JIA. The odds of LBW and SGA were also significantly increased among women with an ARD diagnosis. ARDs were not associated with increased odds of congenital anomalies. Conclusion: Consistent with prior literature, we found that women with ARDs are more likely to have PTB or deliver an SGA infant. Some reassurance is provided that an increase in congenital anomalies was not found even in this large cohort.

The Association of Polymorphisms in Circadian Clock and Lipid Metabolism Genes With 2nd Trimester Lipid Levels and Preterm Birth.

Deregulation of the circadian system in humans and animals can lead to various adverse reproductive outcomes due to genetic mutations and environmental factors. In addition to the clock, lipid metabolism may also play an important role in influencing reproductive outcomes. Despite the importance of the circadian clock and lipid metabolism in regulating birth timing few studies have examined the relationship between circadian genetics with lipid levels during pregnancy and their relationship with preterm birth (PTB). In this study we aimed to determine if single nucleotide polymorphisms (SNPs) in genes from the circadian clock and lipid metabolism influence 2nd trimester maternal lipid levels and if this is associated with an increased risk for PTB. We genotyped 72 SNPs across 40 genes previously associated with various metabolic abnormalities on 930 women with 2nd trimester serum lipid measurements. SNPs were analyzed for their relationship to levels of total cholesterol, high density lipoprotein (HDL), low density lipoprotein (LDL) and triglycerides (TG) using linear regression. SNPs were also evaluated for their relationship to PTB using logistic regression. Five SNPs in four genes met statistical significance after Bonferroni correction (p < 1.8 × 10-4) with one or more lipid levels. Of these, four SNPs were in lipid related metabolism genes: rs7412 in APOE with total cholesterol, HDL and LDL, rs646776 and rs599839 in CELSR2-PSRC1-SORT1 gene cluster with total cholesterol, HDL and LDL and rs738409 in PNPLA3 with HDL and TG and one was in a circadian clock gene: rs228669 in PER3 with TG. Of these SNPs only PER3 rs228669 was marginally associated with PTB (p = 0.02). In addition, PER3 rs228669 acts as an effect modifier on the relationship between TG and PTB.

Development and validation of a clinical model for preconception and early pregnancy risk prediction of gestational diabetes mellitus in nulliparous women.

Implementation of dietary and lifestyle interventions prior to and early in pregnancy in high risk women has been shown to reduce the risk of gestational diabetes mellitus (GDM) development later in pregnancy. Although numerous risk factors for GDM have been identified, the ability to accurately identify women before or early in pregnancy who could benefit most from these interventions remains limited. As nulliparous women are an under-screened population with risk profiles that differ from their multiparous counterparts, development of a prediction model tailored to nulliparous women may facilitate timely preventive intervention and improve maternal and infant outcomes. We aimed to develop and validate a model for preconception and early pregnancy prediction of gestational diabetes mellitus based on clinical risk factors for nulliparous women. A risk prediction model was built within a large California birth cohort including singleton live birth records from 2007-2012. Model accuracy was assessed both internally and externally, within a cohort of women who delivered at University of Iowa Hospitals and Clinics between 2009-2017, using discrimination and calibration. Differences in predictive accuracy of the model were assessed within specific racial/ethnic groups. The prediction model included five risk factors: race/ethnicity, age at delivery, pre-pregnancy body mass index, family history of diabetes, and pre-existing hypertension. The area under the curve (AUC) for the California internal validation cohort was 0.732 (95% confidence interval (CI) 0.728, 0.735), and 0.710 (95% CI 0.672, 0.749) for the Iowa external validation cohort. The model performed particularly well in Hispanic (AUC 0.739) and Black women (AUC 0.719). Our findings suggest that estimation of a woman's risk for GDM through model-based incorporation of risk factors accurately identifies those at high risk (i.e., predicted risk >6%) who could benefit from preventive intervention encouraging prompt incorporation of this tool into preconception and prenatal care.

First trimester prenatal screening biomarkers and gestational diabetes mellitus: A systematic review and meta-analysis.

Biomarkers commonly assessed in prenatal screening have been associated with a number of adverse perinatal and birth outcomes. However, it is not clear whether first trimester measurements of prenatal screening biomarkers are associated with subsequent risk of gestational diabetes mellitus (GDM). We aimed to systematically review and statistically summarize studies assessing the relationship between first trimester prenatal screening biomarker levels and GDM development. We comprehensively searched PubMed/MEDLINE, EMBASE, CINAHL, and Scopus (from inception through January 2018) and manually searched the reference lists of all relevant articles. We included original, published, observational studies examining the association of first trimester pregnancy associated plasma protein-A (PAPP-A) and/or free ß-human chorionic gonadotropin (free ß-hCG) levels with GDM diagnosis. Mean differences were calculated comparing PAPP-A and free ß-hCG multiples of median (MoM) levels between women who developed GDM and those who did not and were subsequently pooled using two-sided random-effects models. Our meta-analysis of 13 studies on PAPP-A and nine studies on free ß-hCG indicated that first trimester MoM levels for both biomarkers were lower in women who later developed GDM compared to women who remained normoglycemic throughout pregnancy (MD -0.17; 95% CI -0.24, -0.10; MD -0.04; 95% CI -0.07-0.01). There was no evidence for between-study heterogeneity among studies on free ß-hCG (I2 = 0%). A high level of between-study heterogeneity was detected among the studies reporting on PAPP-A (I2 = 90%), but was reduced after stratifying by geographic location, biomarker assay method, and timing of GDM diagnosis. Our meta-analysis indicates that women who are diagnosed with GDM have lower first trimester levels of both PAPP-A and free ß-hCG than women who remain normoglycemic throughout pregnancy. Further assessment of the predictive capacity of these biomarkers within large, diverse populations is needed.

Pregnancy-Related Changes of Amino Acid and Acylcarnitine Concentrations: The Impact of Obesity.

Objective Our primary objective was to assess the difference in amino and fatty acid biomarkers throughout pregnancy in women with and without obesity. Interactions between biomarkers and obesity status for associations with maternal and fetal metabolic measures were secondarily analyzed. Methods Overall 39 women (15 cases, 24 controls) were enrolled in this study during their 15- to 20-weeks' visit at the University of Iowa Hospitals and Clinics. We analyzed 32 amino acid and acylcarnitine concentrations with tandem mass spectrometry for differences throughout pregnancy as well as among women with and without obesity (body mass index [BMI] ≥ 35, BMI < 25). Results There were substantial changes in amino acids and acylcarnitine metabolites between the second and third trimesters (nonfasting state) of pregnancy that were significant after correcting for multiple testing (p < 0.002). Examining differences by maternal obesity, C8:1 (second trimester) and C2, C4-OH, C18:1 (third trimester) were higher in women with obesity compared with women without obesity. Several metabolites were marginally (0.002 < p < 0.05) correlated with birth weight, maternal glucose, and maternal weight gain stratified by obesity status and trimester. Conclusions Understanding maternal metabolism throughout pregnancy and the influence of obesity is a critical step in identifying potential mechanisms that may contribute to adverse outcomes in pregnancies complicated by obesity.