Combined logical and data-driven models for linking signalling pathways to cellular response

Background Signalling pathways are the cornerstone on understanding cell function and predicting cell behavior. Recently, logical models of canonical pathways have been optimised with high-throughput phosphoproteomic data to construct cell-type specific pathways. However, less is known on how signalling pathways can be linked to a cellular response such as cell growth, death, cytokine secretion, or transcriptional activity. Results In this work, we measure the signalling activity (phosphorylation levels) and phenotypic behavior (cytokine secretion) of normal and cancer hepatocytes treated with a combination of cytokines and inhibitors. Using the two datasets, we construct "extended" pathways that integrate intracellular activity with cellular responses using a hybrid logical/data-driven computational approach. Boolean logic is used whenever a priori knowledge is accessible (i.e., construction of canonical pathways), whereas a data-driven approach is used for linking cellular behavior to signalling activity via non-canonical edges. The extended pathway is subsequently optimised to fit signalling and behavioural data using an Integer Linear Programming formulation. As a result, we are able to construct maps of primary and transformed hepatocytes downstream of 7 receptors that are capable of explaining the secretion of 22 cytokines. Conclusions We developed a method for constructing extended pathways that start at the receptor level and via a complex intracellular signalling pathway identify those mechanisms that drive cellular behaviour. Our results constitute a proof-of-principle for construction of "extended pathways" that are capable of linking pathway activity to diverse responses such as growth, death, differentiation, gene expression, or cytokine secretion.Marie Curie International Reintegration Grants (MIRG-14-CT-2007-046531)Vertex Pharmaceuticals IncorporatedBundesministerium für Wissenschaft und Forschung (HepatoSys)Massachusetts Institute of Technology (Rockwell International Career Development Professorship)Bundesministerium für Wissenschaft und Forschung (HepatoSys 0313081D

Inhibin secretion in women with the polycystic ovary syndrome before and after treatment with progesterone

<p>Abstract</p> <p>Objectives</p> <p>It has been suggested that inhibin secretion is altered in women with the polycystic ovary syndrome (PCOS). However, the contribution of a preceding luteal phase has not been taken into account. The aim of the present study was to investigate whether progesterone in the context of a simulated luteal phase affects basal and FSH-induced inhibin secretion in women with PCOS and elevated LH.</p> <p>Methods</p> <p>Ten women with PCOS and 8 normally cycling women participated in an experimental procedure (Exp) involving the administration of a single injection of recombinant FSH (450 IU sc). In the women with PCOS, the procedure was performed before (Exp 1) and after a 20-day treatment with progesterone (Exp 2), while in the normal women on day 2 of the cycle (Exp 3). Inhibin A and B levels were measured in blood samples taken before and 24 hours after the FSH injection.</p> <p>Results</p> <p>Basal LH levels were significantly higher and inhibin A levels were significantly lower in the PCOS group compared to the control group, while inhibin B levels were comparable in the two groups. In the PCOS group, after treatment with progesterone inhibin A and LH but not inhibin B levels decreased significantly (p < 0.05). After the FSH injection, inhibin A and B levels increased significantly in the women with PCOS (Exp 1 and Exp 2) but not in the control women (Exp 3).</p> <p>Conclusions</p> <p>In women with PCOS, as compared to control women, the dissimilar pattern of inhibin A and inhibin B secretion in response to FSH appears to be independent of a preceding simulated luteal phase. It is possible that compared to normal ovaries, the PCOS ovaries are less sensitive to endogenous LH regarding inhibin A secretion and more sensitive to exogenous FSH stimulation in terms of inhibin A and inhibin B secretion.</p

Translational systems pharmacology‐based predictive assessment of drug‐induced cardiomyopathy

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142916/1/psp412272.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142916/2/psp412272_am.pd

Translational Systems Pharmacology-Based Predictive Assessment of Drug-Induced Cardiomyopathy

Drug-induced cardiomyopathy contributes to drug attrition. We compared two pipelines of predictive modeling: (1) applying elastic net (EN) to differentially expressed genes (DEGs) of drugs; (2) applying integer linear programming (ILP) to construct each drug’s signaling pathway starting from its targets to downstream proteins, to transcription factors, and to its DEGs in human cardiomyocytes, and then subjecting the genes/proteins in the drugs’ signaling networks to EN regression. We classified 31 drugs with availability of DEGs into 13 toxic and 18 nontoxic drugs based on a clinical cardiomyopathy incidence cutoff of 0.1%. The ILP-augmented modeling increased prediction accuracy from 79% to 88% (sensitivity: 88%; specificity: 89%) under leave-one-out cross validation. The ILP-constructed signaling networks of drugs were better predictors than DEGs. Per literature, the microRNAs that reportedly regulate expression of our six top predictors are of diagnostic value for natural heart failure or doxorubicin-induced cardiomyopathy. This translational predictive modeling might uncover potential biomarkers

Prognostic value of follicular fluid 25-OH vitamin D and glucose levels in the IVF outcome

Objectives: The aim of the present study was to measure serum and follicular fluid 25-OH vitamin D and glucose levels in women who underwent IVF-ET treatment and to further investigate whether the circulating 25-OH vitamin D and glucose levels correlate with IVF success. Methods: This prospective observational study included 101 consecutive women who underwent 101 IVF-ICSI ovarian stimulation cycles and were allocated to one of the three groups according to their follicular fluid 25-OH vitamin D concentrations. Group A (n = 31) with less than 20 ng/ml, group B (n = 49) with vitamin levels between 20.1 and 30 ng/ml and group C (n = 21) with more than 30 ng/ml vitamin concentration. Results: Follicular fluid vitamin levels significantly correlated with the quality of embryos in total (r = -0.27, p = 0.027), while the quality of embryos of group C were of lower quality as compared to those of groups A and B (p = 0.009). Follicular fluid glucose levels were lower in women of group C as compared to the respective levels of groups A and B (p = 0.003). Clinical pregnancy rate demonstrated in 14.5% in women of group C and 32.3% and 32.7% in groups A and B, respectively (p = 0.047). Conclusion: The data suggests that excess serum and follicular fluid vitamin levels in combination with decreased follicular fluid glucose levels have a detrimental impact on the IVF outcome

Obstetric outcomes after treatment of periodontal disease during pregnancy: systematic review and meta-analysis

Objective To examine whether treatment of periodontal disease with scaling and root planing during pregnancy is associated with a reduction in the preterm birth rate

A crowd-sourcing approach for the construction of species-specific cell signaling networks

Motivation: Animal models are important tools in drug discovery and for understanding human biology in general. However, many drugs that initially show promising results in rodents fail in later stages of clinical trials. Understanding the commonalities and differences between human and rat cell signaling networks can lead to better experimental designs, improved allocation of resources and ultimately better drugs. Results: The sbv IMPROVER Species-Specific Network Inference challenge was designed to use the power of the crowds to build two species-specific cell signaling networks given phosphoproteomics, transcriptomics and cytokine data generated from NHBE and NRBE cells exposed to various stimuli. A common literature-inspired reference network with 220 nodes and 501 edges was also provided as prior knowledge from which challenge participants could add or remove edges but not nodes. Such a large network inference challenge not based on synthetic simulations but on real data presented unique difficulties in scoring and interpreting the results. Because any prior knowledge about the networks was already provided to the participants for reference, novel ways for scoring and aggregating the results were developed. Two human and rat consensus networks were obtained by combining all the inferred networks. Further analysis showed that major signaling pathways were conserved between the two species with only isolated components diverging, as in the case of ribosomal S6 kinase RPS6KA1. Overall, the consensus between inferred edges was relatively high with the exception of the downstream targets of transcription factors, which seemed more difficult to predict. Contact: [email protected] or [email protected]. Supplementary information: Supplementary data are available at Bioinformatics onlin

Polymorphisms of the endothelial nitric oxide synthase (NOS3) gene in preeclampsia: a candidate-gene association study

<p>Abstract</p> <p>Background</p> <p>The endothelial nitric oxide synthase gene (<it>NOS3</it>) has been proposed as a candidate gene for preeclampsia. However, studies so far have produced conflicting results. This study examines the specific role of variants and haplotypes of the <it>NOS3 </it>gene in a population of Caucasian origin.</p> <p>Methods</p> <p>We examined the association of three common variants of the <it>NOS3 </it>gene (4b/a, T-786C and G894T) and their haplotypes in a case-control sample of 102 patients with preeclampsia and 176 women with a history of uncomplicated pregnancies. Genotyping for the <it>NOS3 </it>variants was performed and odds ratios and 95% confidence intervals were obtained to evaluate the association between <it>NOS3 </it>polymorphisms and preeclampsia.</p> <p>Results</p> <p>The single locus analysis for the three variants using various genetic models and a model-free approach revealed no significant association in relation to clinical status. The analysis of haplotypes also showed lack of significant association.</p> <p>Conclusions</p> <p>Given the limitations of the candidate-gene approach in investigating complex traits, the evidence of our study does not support the major contributory role of these common <it>NOS3 </it>variants in preeclampsia. Future larger studies may help in elucidating the genetics of preeclampsia further.</p

A crowd-sourcing approach for the construction of species-specific cell signaling networks

Motivation: Animal models are important tools in drug discovery and for understanding human biology in general. However, many drugs that initially show promising results in rodents fail in later stages of clinical trials. Understanding the commonalities and differences between human and rat cell signaling networks can lead to better experimental designs, improved allocation of resources and ultimately better drugs. Results: The sbv IMPROVER Species-Specific Network Inference challenge was designed to use the power of the crowds to build two species-specific cell signaling networks given phosphoproteomics, transcriptomics and cytokine data generated from NHBE and NRBE cells exposed to various stimuli. A common literature-inspired reference network with 220 nodes and 501 edges was also provided as prior knowledge from which challenge participants could add or remove edges but not nodes. Such a large network inference challenge not based on synthetic simulations but on real data presented unique difficulties in scoring and interpreting the results. Because any prior knowledge about the networks was already provided to the participants for reference, novel ways for scoring and aggregating the results were developed. Two human and rat consensus networks were obtained by combining all the inferred networks. Further analysis showed that major signaling pathways were conserved between the two species with only isolated components diverging, as in the case of ribosomal S6 kinase RPS6KA1. Overall, the consensus between inferred edges was relatively high with the exception of the downstream targets of transcription factors, which seemed more difficult to predict. Contact: [email protected] or [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online