Sickle cell disease associated lipid changes and their relevance towards the disease pathogenesis And Lipid Biomarkers and Embryo Quality in In Vitro Fertilization; Pregnancy Success Differentially Expressed by Body Weight

Abstract Sickle cell disease (SCD) is a group of genetic disorder that occurs due to genetic mutation of a beta-globin gene that lead to production of pathogenic hemoglobin S (HB S). Genotypes of SCD include Hb SS (sickle cell anemia) which is the most common and severe form of SCD affects about 20 to 25 million people worldwide, HbSC, Hb Sβ+- thalassemia, and Hb Sβ0-thalassemia. SCD is characterized by multiorgan complications that, in turn, affect lipids composition. During hypoxia a sequence of changes will take place such as HbS polymerization, erythrocyte rigidity and stickiness, and oxidative stress. The combination of these changes will affect lipids components such as polyunsaturated fatty acids (PUFA), which are substrates for a significant number of bioactive lipids such as the eicosanoids and some of the endocannabinoids. For example, vaso-occlusion crisis, the most common cause of SDC hospitalization, is found to be accompanied by changes in PUFA components of RBCs cell membrane encompassing Omega-3 and Omega-6. This comprehensive review outlines lipid changes that accompany SCD and also identify the gaps in our knowledge. This review will also allow us to devise better treatment options to manage the different pathophysiology and complications of SCD. Abstract: Introduction: A common risk factor for infertility is obesity. The global rise of obesity accompanied with infertility has led to widespread adoption of assisted reproductive technologies such as in vitro fertilization (IVF) to achieve pregnancy. However, pregnancy outcomes such as embryo quality vary after IVF, possibly due to disruptions in metabolism. Previous metabolomic studies investigating embryo quality were limited to characterizing broadly lipid classes, or a few molecular lipid species. Here, we sought to determine specific circulating lipids and metabolites with matrix-specific effects that could serve as putative biomarkers of embryo quality, correlated with BMI, and predicted clinical pregnancy subsequent IVF. Methods: Electronic health record (EHR) data, as well as lipids and metabolites obtained from follicular fluid (FF) and platelet poor plasma (PPP), were collected from women (n = 26) undergoing IVF. Lipids and metabolites were acquired via untargeted mass spectrometry. For embryo quality and BMI, we performed multiple linear regression analysis to find correlates. For 6 weeks pregnancy, we applied a linear discriminant analysis to select lipids and metabolites that allowed for group determination. Results: Several lipids and metabolites were selected from both matrices (FF and PPP) that either outperformed models containing only EHR or added value to EHR models. In predicting embryo quality, glycerophospholipids obtained from PPP produced the best fit model. The predicted values include (LPC) 22:6 , phosphatidylcholine (PC) 16:1/22:6, and phosphatidylethanolamine-plasmalogen (PE-P) 16:0/22:6 were negatively correlated with 2PN while Phosphatidylethanolamine (PE) 18:0/20:3, lysophosphatidylethanolamine (LPE) 18:1, PC 14:0/16:1, and PE-P 16:0/20:5 were positively correlated with 2PN (R adjusted = 0.730, RMSE = 0.329). For rLDA of 6-weeks of pregnancy, the best model was the metabolite model obtained from Platelet Poor Plasma (misclassification = 3.85%, Entropy R-squared = 0.809). The BMI multicomponent domain model obtained from FF, LPC 18:1, PC 16:1/22:6, and malic acid were negatively associated with BMI while Fasting insulin and PC 16:0/22:4 were positively correlated with BMI values (R-square adjusted = 0.819, RMSE = 0.127). However, the combined data model for FF has the best prediction of BMI values. In this model, PE-P 16:0/22:6, aspartic acid, and fasting insulin as positively correlated variables with BMI values, whereas indole-3-propionic acid was negatively correlated with BMI (R-squared adjusted = 0.856, RMSE = 0.113)

Development of an R script for simple lipidomic and metabolomic data analysis

Background: Metabolomic and lipidomic studies generate vast quantities of data that are often analysed in a closed software environment with little to no access to the underlying algorithms. As a result, data processed via different software pipelines yield different results thus leading to a widespread problem of low reproducibility within these fields. To address this problem, we are developing LipidAnalyst; an R based lipidomics software pipeline. As a part of this project, we are creating a simple statistical analysis and graphing module in R to generate accurate, reproducible, high-resolution figures. Methods: R scripts were developed under version 3.5.3 with the capability to undertake statistical analyses (e.g. ANOVA) and post-hoc tests (e.g. Tukey). Additional code plotted resultant information as high resolution violin and box plots that depicted statistical significance. Thereafter, lipidomic and metabolomic data were analysed by this code and compared against commercial software and Metaboanalyst, a primary software used in metabolomic and lipidomic research. Results: Code generated in house demonstrated the same results as those generated using commercial software (e.g. JMP 14.0 Pro) but were different from results obtained by using the MetaboAnalyst pipeline. Conclusions: This study demonstrated the prevalent danger of using closed-source software pipelines for the analysis of lipidomic and metabolomic data without validating the analysis outcomes via open-source software. Open source software such as LipidAnalyst, that has also been independently validated using multiple data sets, can then be published with the results to enable transparency of data analysis and improve the replicability of results across different labs.https://scholarscompass.vcu.edu/gradposters/1092/thumbnail.jp

A Pre-transplant Blood-based Lipid Signature for Prediction of Antibody-mediated Rejection in Kidney Transplant Patients

Purpose. The aim of this study is to demonstrate the potential of the pre-transplant lipidome to predict post-transplant antibody-mediated rejection (AMR) in kidney transplant patients. Methods. Patients were selected from a prospective observational cohort of a single-center adult kidney transplant center in the United States. The study included 16 kidney transplant patients who develop AMR within 2 years post-transplant and 29 stable control (SC) kidney transplant patients who did not develop AMR at any time within the post-transplant follow up. Selection of group differences on the day of transplant was determined by t-test analysis. Stepwise forward method was used to create Linear Discrimination Analysis with regularized correction (RLDA). Changes over time were estimated using sparse partial least square method which is validated by permutation testing. T-test was performed to compare two time points for the same group and groups at matched time points. JMP Pro 13 and MetaboAnalyst were used in the analysis of the Data. Results. A comparison of lipids classes on the day of transplant revealed PLs relative concentration differences between SC and AMR. Concentration of phosphatidylcholine (PC) was significantly diminished in AMR, while there was a trend for increased concentration of lysophosphatidylcholine (LPC). AMR group also showed significantly lower concentration of phosphatidylethanolamine (PE), lysophosphatidylethanolamine (LPE), plasmanylethanolamine (PE-O), and plasmenylethanolamine (PE-P). Our data demonstrated that there are significant differences in the lipidome between SC and AMR on the day of transplant. The analysis identified 7 distinct lipids that discriminated between AMR and SC (AUC) =0.95 (95%CI=0.84- 0.98), R2=0.63 (95%CI=0.4-0.8). A sPLSDA analysis of the data revealed a statistically significant alteration in the lipid profile at 6 months post-transplant compared to the day of transplant. The analysis revealed a panel of 13 lipids that were found to differentiate the two groups at 6 month post-transplant . Further data analysis confirms the presence of a sustained lipid metabolic difference between SC and AMR over time that distinguish between the patients with favorable and non-favorable transplant outcomes. Conclusion. This study demonstrates the potential of the pre-transplant lipidome towards determining AMR in kidney transplant patients, raising the possibility of using this information in risk stratification of patients about to undergo transplant.https://scholarscompass.vcu.edu/gradposters/1086/thumbnail.jp

Molecular Predictors of Anakinra Treatment Success in Heart Failure Patients with Reduced Ejection Fraction

Background. Kineret (Anakinra) is an interleukin-1 antagonist that is under investigation for its novel clinical application treating patients that have heart failure with reduced (\u3c50%) ejection fraction (HFrEF). A prior study from our group indicated that Anakinra may restore heart function by addressing dysregulations in HFrEF metabolic pathways. Herein, we attempt to elicit Anakinra’s effects on both metabolome and lipidome. Methods. Lipids and metabolites that had previously been quantified by mass spectrometry (MS) from patients (n=49) who had ≥2 mg/L of high-sensitivity C-reactive protein (hs-CRP) were mTIC normalized and transformed. We conducted a stepwise Linear Discriminant Analysis (r- LDA) to test Anakinra (2 and 12 weeks) vs placebo for separation from combined baseline. Metabolic pathway analysis was performed with Fisher’s exact test algorithm for detection of over-represented and enriched analytes. Univariate analysis (one tailed t-test p\u3c0.05) compared placebo and Anakinra after 12-weeks for effect(s). Metaboanalyst 4.0, JMP Pro 14.0, and a proprietary package in R (version 3.4.4) were the software for all analyses and data wrangling. Results. Analytes such as acylcarnitines C10:0 and C16:0 and hsCRP showed significant improvements after 12 weeks of Anakinra, leading to improved mitochondrial function, reduced inflammation, and overall better health outcomes. Statistically significant (p\u3c0.05) pathways including the citrate cycle, cysteine and methionine metabolism, galactose metabolism among others were associated with treatment. Conclusions. We were able to determine significant alterations to metabolomic and lipidomic concentrations after 12 weeks of Anakinra therapy. Our biochemical analyses verifies that Anakinra did improve heart function within our HFrEF pilot cohort.https://scholarscompass.vcu.edu/gradposters/1081/thumbnail.jp

Acute Fish Oil supplementation and Aspirin treatment modulates lipid profile in Platelet Rich Plasma: a randomized pilot trial

Aims: Platelet rich plasma (PRP) has been used in tissue repair to treat numerous inflammatory pathophysiologies. Recent studies have elucidated that the bioactive lipid fraction of PRP significantly contributes towards the resolution of inflammation. There has been great interest in how therapeutics could modulate the PRP lipidome to formulate a more pro-resolving matrix. Many of the pathways used to produce either pro-resolving or pro-inflammatory lipids are shared between ω-3 and ω-6 polyunsaturated fatty acids (PUFA). Here, we explored the separate and interacting effects acute exogenous ω-3 PUFA supplementation and aspirin had on the lipidome of PRP within 6 hours. Methods:PRP from 45 patients was obtained at baseline and after 6-hours from either control or those receiving one 1400 mg fish oil tablet, Bayer low-dose aspirin (81mg), or combinational therapy. Lipids were acquired by liquid chromatography mass spectrometry. Spearman rank correlation analysis visually assessed what effects treatments had on the relative abundance of PUFA derivatives. The control group was referenced for lipid selection across groups; lipids were selected on the basis that they significantly (p Results: Fish oil ω-3 PUFA supplementation and aspirin had separate and interacting effects on oxylipin and neutral lipid correlations. Strongly correlated (rho \u3e 0.65) ω-6 PUFA metabolites were reversed or reduced in magnitude following either treatment. A total of 24 lipid species were significantly modulated in the fish oil treatment group, with notable (p4), and lipoxin A4 (LXA4). Conclusion: We can confirm that fish oil supplementation and aspirin do exert modulatory effects on the lipid fraction of PRP within a short period of time (6-hours). The PUFAs composing fish oil impacted a wide range of the lipidome – possibly though a mechanism of ω-3/ω-6 enzymatic competition. Our results support that ω-3 PUFA supplementation may improve the efficacy of PRP for short-term use