Association of Vitamin D Level and Maternal Gut Microbiome during Pregnancy: Findings from a Randomized Controlled Trial of Antenatal Vitamin D Supplementation.

Shifts in the maternal gut microbiome and vitamin D deficiency during pregnancy have been associated, separately, with health problems for both the mother and the child. Yet, they have rarely been studied simultaneously. Here, we analyzed the gut microbiome (from stool samples obtained in late pregnancy) and vitamin D level (from blood samples obtained both in early and late pregnancy) data of pregnant women in the Vitamin D Antenatal Asthma Reduction Trial (VDAART), a randomized controlled trial of vitamin D supplementation during pregnancy, to investigate the association of vitamin D status on the pregnant women's microbiome. To find associations, we ran linear regressions on alpha diversity measures, PERMANOVA tests on beta diversity distances, and used the ANCOM-BC and Maaslin2 algorithms to find differentially abundant taxa. Analyses were deemed significant using a cut-off p-value of 0.05. We found that gut microbiome composition is associated with the vitamin D level in early pregnancy (baseline), the maternal gut microbiome does not show a shift in response to vitamin D supplementation during pregnancy, and that the genus Desulfovibrio is enriched in women without a substantial increase in vitamin D level between the first and the third trimesters of pregnancy. We conclude that increasing the vitamin D level during pregnancy could be protective against the growth of sulfate-reducing bacteria such as Desulfovibrio, which has been associated with chronic intestinal inflammatory disorders. More in-depth investigations are needed to confirm this hypothesis.

Association of vitamin D level and maternal gut microbiome during pregnancy: Findings from a randomized controlled trial of antenatal vitamin D supplementation.

Shifts in the maternal gut microbiome and vitamin D deficiency during pregnancy have been associated, separately, with health problems for both the mother and the child. Yet, they have rarely been studied simultaneously. Here, we analyzed gut microbiome (from stool samples obtained in late pregnancy) and vitamin D level (from blood samples obtained both in early and late pregnancy) data of pregnant women in the Vitamin D Antenatal Asthma Reduction Trial (VDAART), a randomized controlled trial of vitamin D supplementation during pregnancy, to investigate the association of vitamin D status on the pregnant women’s microbiome. To find associations we ran linear regressions on alpha diversity measures, PERMANOVA tests on beta diversity distances, and used the ANCOM-BS and Maaslin2 algorithms to find differentially abundant taxa. Analyses were deemed significant using a cut-off p-value of 0.05. We found that gut microbiome composition is associated with the vitamin D level in early pregnancy (baseline), the maternal gut microbiome does not show a shift in response to vitamin D supplementation during pregnancy, and that the genus Desulfovibrio is enriched in women without a substantial increase in vitamin D level between the first and the third trimesters of pregnancy. We conclude that increasing the vitamin D level during pregnancy could be protective against the growth of sulfate-reducing bacteria such as Desulfovibrio , which has been associated with chronic intestinal inflammatory disorders. More in-depth investigations are needed to confirm this hypothesis.

Benchmarking omics-based prediction of asthma development in children.

BACKGROUND: Asthma is a heterogeneous disease with high morbidity. Advancement in high-throughput multi-omics approaches has enabled the collection of molecular assessments at different layers, providing a complementary perspective of complex diseases. Numerous computational methods have been developed for the omics-based patient classification or disease outcome prediction. Yet, a systematic benchmarking of those methods using various combinations of omics data for the prediction of asthma development is still lacking. OBJECTIVE: We aimed to investigate the computational methods in disease status prediction using multi-omics data. METHOD: We systematically benchmarked 18 computational methods using all the 63 combinations of six omics data (GWAS, miRNA, mRNA, microbiome, metabolome, DNA methylation) collected in The Vitamin D Antenatal Asthma Reduction Trial (VDAART) cohort. We evaluated each method using standard performance metrics for each of the 63 omics combinations. RESULTS: Our results indicate that overall Logistic Regression, Multi-Layer Perceptron, and MOGONET display superior performance, and the combination of transcriptional, genomic and microbiome data achieves the best prediction. Moreover, we find that including the clinical data can further improve the prediction performance for some but not all the omics combinations. CONCLUSIONS: Specific omics combinations can reach the optimal prediction of asthma development in children. And certain computational methods showed superior performance than other methods.

Systems Pharmacology and Rational Polypharmacy: Nitric Oxide-Cyclic GMP Signaling Pathway as an Illustrative Example and Derivation of the General Case.

Impaired nitric oxide (NO˙)-cyclic guanosine 3', 5'-monophosphate (cGMP) signaling has been observed in many cardiovascular disorders, including heart failure and pulmonary arterial hypertension. There are several enzymatic determinants of cGMP levels in this pathway, including soluble guanylyl cyclase (sGC) itself, the NO˙-activated form of sGC, and phosphodiesterase(s) (PDE). Therapies for some of these disorders with PDE inhibitors have been successful at increasing cGMP levels in both cardiac and vascular tissues. However, at the systems level, it is not clear whether perturbation of PDE alone, under oxidative stress, is the best approach for increasing cGMP levels as compared with perturbation of other potential pathway targets, either alone or in combination. Here, we develop a model-based approach to perturbing this pathway, focusing on single reactions, pairs of reactions, or trios of reactions as targets, then monitoring the theoretical effects of these interventions on cGMP levels. Single perturbations of all reaction steps within this pathway demonstrated that three reaction steps, including the oxidation of sGC, NO˙ dissociation from sGC, and cGMP degradation by PDE, exerted a dominant influence on cGMP accumulation relative to other reaction steps. Furthermore, among all possible single, paired, and triple perturbations of this pathway, the combined perturbations of these three reaction steps had the greatest impact on cGMP accumulation. These computational findings were confirmed in cell-based experiments. We conclude that a combined perturbation of the oxidatively-impaired NO˙-cGMP signaling pathway is a better approach to the restoration of cGMP levels as compared with corresponding individual perturbations. This approach may also yield improved therapeutic responses in other complex pharmacologically amenable pathways.