Association between prenatal immune phenotyping and cord blood leukocyte telomere length in the PRISM pregnancy cohort

Maternal circulating metabolic biomarkers and their prediction performance for gestational diabetes mellitus related macrosomia

INTRODUCTION

Gestational diabetes mellitus (GDM), a metabolism-related pregnancy complication, is significantly associated with an increased risk of macrosomia. We hypothesized that maternal circulating metabolic biomarkers differed between women with GDM and macrosomia (GDM-M) and women with GDM and normal neonatal weight (GDM-N), and had good prediction performance for GDM-M.

METHODS

Plasma samples from 44 GDM-M and 44 GDM-N were analyzed using Olink Proseek multiplex metabolism assay targeting 92 biomarkers. Combined different clinical characteristics and Olink markers, LASSO regression was used to optimize variable selection, and Logistic regression was applied to build a predictive model. Nomogram was developed based on the selected variables visually. Receiver operating characteristic (ROC) curve, calibration plot, and clinical impact curve were used to validate the model.

RESULTS

We found 4 metabolism-related biomarkers differing between groups [CLUL1 (Clusterin-like protein 1), VCAN (Versican core protein), FCRL1 (Fc receptor-like protein 1), RNASE3 (Eosinophil cationic protein), FDR <  0.05]. Based on the different clinical characteristics and Olink markers, a total of nine predictors, namely pre-pregnancy body mass index (BMI), weight gain at 24 gestational weeks (gw), parity, oral glucose tolerance test (OGTT) 2 h glucose at 24 gw, high-density lipoprotein (HDL) and low-density lipoprotein (LDL) at 24 gw, and plasma expression of CLUL1, VCAN and RNASE3 at 24 gw, were identified by LASSO regression. The model constructed using these 9 predictors displayed good prediction performance for GDM-M, with an area under the ROC of 0.970 (sensitivity = 0.955, specificity = 0.886), and was well calibrated (P _{Hosmer-Lemeshow test} = 0.897).

CONCLUSION

The Model included pre-pregnancy BMI, weight gain at 24 gw, parity, OGTT 2 h glucose at 24 gw, HDL and LDL at 24 gw, and plasma expression of CLUL1, VCAN and RNASE3 at 24 gw had good prediction performance for predicting macrosomia in women with GDM.

Integrating Environment and Aging Research: Opportunities for Synergy and Acceleration

Despite significant overlaps in mission, the fields of environmental health sciences and aging biology are just beginning to intersect. It is increasingly clear that genetics alone does not predict an individual’s neurological aging and sensitivity to disease. Accordingly, aging neuroscience is a growing area of mutual interest within environmental health sciences. The impetus for this review came from a workshop hosted by the National Academies of Sciences, Engineering, and Medicine in June of 2020, which focused on integrating the science of aging and environmental health research. It is critical to bridge disciplines with multidisciplinary collaborations across toxicology, comparative biology, epidemiology to understand the impacts of environmental toxicant exposures and age-related outcomes. This scoping review aims to highlight overlaps and gaps in existing knowledge and identify essential research initiatives. It begins with an overview of aging biology and biomarkers, followed by examples of synergy with environmental health sciences. New areas for synergistic research and policy development are also discussed. Technological advances including next-generation sequencing and other-omics tools now offer new opportunities, including exposomic research, to integrate aging biomarkers into environmental health assessments and bridge disciplinary gaps. This is necessary to advance a more complete mechanistic understanding of how life-time exposures to toxicants and other physical and social stressors alter biological aging. New cumulative risk frameworks in environmental health sciences acknowledge that exposures and other external stressors can accumulate across the life course and the advancement of new biomarkers of exposure and response grounded in aging biology can support increased understanding of population vulnerability. Identifying the role of environmental stressors, broadly defined, on aging biology and neuroscience can similarly advance opportunities for intervention and translational research. Several areas of growing research interest include expanding exposomics and use of multi-omics, the microbiome as a mediator of environmental stressors, toxicant mixtures and neurobiology, and the role of structural and historical marginalization and racism in shaping persistent disparities in population aging and outcomes. Integrated foundational and translational aging biology research in environmental health sciences is needed to improve policy, reduce disparities, and enhance the quality of life for older individuals.

Neighborhood-level disparities and subway utilization during the COVID-19 pandemic in New York City

The COVID-19 pandemic has yielded disproportionate impacts on communities of color in New York City (NYC). Researchers have noted that social disadvantage may result in limited capacity to socially distance, and consequent disparities. We investigate the association between neighborhood social disadvantage and the ability to socially distance, infections, and mortality in Spring 2020. We combine Census Bureau and NYC open data with SARS-CoV-2 testing data using supervised dimensionality-reduction with Bayesian Weighted Quantile Sums regression. The result is a ZIP code-level index with weighted social factors associated with infection risk. We find a positive association between neighborhood social disadvantage and infections, adjusting for the number of tests administered. Neighborhood disadvantage is also associated with a proxy of the capacity to socially isolate, NYC subway usage data. Finally, our index is associated with COVID-19-related mortality.

Nutri-epigenetics: the effect of maternal diet and early nutrition on the pathogenesis of autoimmune diseases

Autoimmune diseases comprise a wide group of diseases involving a self-response of the immune system against the host. The etiopathogenesis is very complex involving disease-specific factors but also environmental factors, among which the diet. Maternal diet during pregnancy as well as early nutrition recently attracted the interest of the scientists as contributing to the immune programming. In this paper, we reviewed the most recent literature on the effect of maternal diet and early nutrition in modulating the immune system in a selected subset of autoimmune diseases: type 1 diabetes, celiac disease, inflammatory bowel disease, juvenile idiopathic arthritis and rheumatoid arthritis. Particularly, we focused our narrative on the role of maternal and perinatal nutrition in the epigenetic mechanisms underlying the auto-immune response. Maternal diet during pregnancy as well as breastfeeding and early nutrition play a big role in many epigenetic mechanisms. Most of the nutrients consumed by the mother and the infant are known exerting epigenetic functions, such as folate, methionine, zinc, vitamins B12 and D, fibers, casein and gliadin, and they were linked to gene expression changes in the immune pathways. Despite the common role of maternal diet, breastfeeding and early nutrition in almost all the autoimmune diseases, each disease seems to have specific diet-driver epigenetic mechanisms that require further investigations. The research in this field is opening new routes to establishing a precision nutrition approach to the auto-immune diseases.