Hypothesis-Agnostic Network-Based Analysis of Real-World Data Suggests Ondansetron is Associated with Lower COVID-19 Any Cause Mortality.

BACKGROUND: The COVID-19 pandemic generated a massive amount of clinical data, which potentially hold yet undiscovered answers related to COVID-19 morbidity, mortality, long-term effects, and therapeutic solutions. OBJECTIVES: The objectives of this study were (1) to identify novel predictors of COVID-19 any cause mortality by employing artificial intelligence analytics on real-world data through a hypothesis-agnostic approach and (2) to determine if these effects are maintained after adjusting for potential confounders and to what degree they are moderated by other variables. METHODS: A Bayesian statistics-based artificial intelligence data analytics tool (bAIcis®) within the Interrogative Biology® platform was used for Bayesian network learning and hypothesis generation to analyze 16,277 PCR+ patients from a database of 279,281 inpatients and outpatients tested for SARS-CoV-2 infection by antigen, antibody, or PCR methods during the first pandemic year in Central Florida. This approach generated Bayesian networks that enabled unbiased identification of significant predictors of any cause mortality for specific COVID-19 patient populations. These findings were further analyzed by logistic regression, regression by least absolute shrinkage and selection operator, and bootstrapping. RESULTS: We found that in the COVID-19 PCR+ patient cohort, early use of the antiemetic agent ondansetron was associated with decreased any cause mortality 30 days post-PCR+ testing in mechanically ventilated patients. CONCLUSIONS: The results demonstrate how a real-world COVID-19-focused data analysis using artificial intelligence can generate unexpected yet valid insights that could possibly support clinical decision making and minimize the future loss of lives and resources.

Haptoglobin enhances cardiac transplant rejection.

RATIONALE: Early graft inflammation enhances both acute and chronic rejection of heart transplants, but it is unclear how this inflammation is initiated. OBJECTIVE: To identify specific inflammatory modulators and determine their underlying molecular mechanisms after cardiac transplantation. METHODS AND RESULTS: We used a murine heterotopic cardiac transplant model to identify inflammatory modulators of early graft inflammation. Unbiased mass spectrometric analysis of cardiac tissue before and ≤72 hours after transplantation revealed that 22 proteins including haptoglobin, a known antioxidant, are significantly upregulated in our grafts. Through the use of haptoglobin-deficient mice, we show that 80% of haptoglobin-deficient recipients treated with perioperative administration of the costimulatory blocking agent CTLA4 immunoglobulin exhibited >100-day survival of full major histocompatibility complex mismatched allografts, whereas all similarly treated wild-type recipients rejected their transplants by 21 days after transplantation. We found that haptoglobin modifies the intra-allograft inflammatory milieu by enhancing levels of the inflammatory cytokine interleukin-6 and the chemokine MIP-2 (macrophage inflammatory protein 2) but impair levels of the immunosuppressive cytokine interleukin-10. Haptoglobin also enhances dendritic cell graft recruitment and augments antidonor T-cell responses. Moreover, we confirmed that the protein is present in human cardiac allograft specimens undergoing acute graft rejection. CONCLUSIONS: Our findings provide new insights into the mechanisms of inflammation after cardiac transplantation and suggest that, in contrast to its prior reported antioxidant function in vascular inflammation, haptoglobin is an enhancer of inflammation after cardiac transplantation. Haptoglobin may also be a key component in other sterile inflammatory conditions.

YPED: an integrated bioinformatics suite and database for mass spectrometry-based proteomics research.

We report a significantly-enhanced bioinformatics suite and database for proteomics research called Yale Protein Expression Database (YPED) that is used by investigators at more than 300 institutions worldwide. YPED meets the data management, archival, and analysis needs of a high-throughput mass spectrometry-based proteomics research ranging from a single laboratory, group of laboratories within and beyond an institution, to the entire proteomics community. The current version is a significant improvement over the first version in that it contains new modules for liquid chromatography-tandem mass spectrometry (LC-MS/MS) database search results, label and label-free quantitative proteomic analysis, and several scoring outputs for phosphopeptide site localization. In addition, we have added both peptide and protein comparative analysis tools to enable pairwise analysis of distinct peptides/proteins in each sample and of overlapping peptides/proteins between all samples in multiple datasets. We have also implemented a targeted proteomics module for automated multiple reaction monitoring (MRM)/selective reaction monitoring (SRM) assay development. We have linked YPED's database search results and both label-based and label-free fold-change analysis to the Skyline Panorama repository for online spectra visualization. In addition, we have built enhanced functionality to curate peptide identifications into an MS/MS peptide spectral library for all of our protein database search identification results.

Review of software tools for design and analysis of large scale MRM proteomic datasets.

Selective or Multiple Reaction monitoring (SRM/MRM) is a liquid-chromatography (LC)/tandem-mass spectrometry (MS/MS) method that enables the quantitation of specific proteins in a sample by analyzing precursor ions and the fragment ions of their selected tryptic peptides. Instrumentation software has advanced to the point that thousands of transitions (pairs of primary and secondary m/z values) can be measured in a triple quadrupole instrument coupled to an LC, by a well-designed scheduling and selection of m/z windows. The design of a good MRM assay relies on the availability of peptide spectra from previous discovery-phase LC-MS/MS studies. The tedious aspect of manually developing and processing MRM assays involving thousands of transitions has spurred to development of software tools to automate this process. Software packages have been developed for project management, assay development, assay validation, data export, peak integration, quality assessment, and biostatistical analysis. No single tool provides a complete end-to-end solution, thus this article reviews the current state and discusses future directions of these software tools in order to enable researchers to combine these tools for a comprehensive targeted proteomics workflow.

Proteomics and the analysis of proteomic data: 2013 overview of current protein-profiling technologies.

Mass spectrometry has become a major tool in the study of proteomes. The analysis of proteolytic peptides and their fragment ions by this technique enables the identification and quantitation of the precursor proteins in a mixture. However, deducing chemical structures and then protein sequences from mass-to-charge ratios is a challenging computational task. Software tools incorporating powerful algorithms and statistical methods improved our ability to process the large quantities of proteomics data. Repositories of spectral data make both data analysis and experimental design more efficient. New approaches in quantitative and statistical proteomics make possible a greater coverage of the proteome, the identification of more post-translational modifications, and a greater sensitivity in the quantitation of targeted proteins.

Identification of CSPα clients reveals a role in dynamin 1 regulation.

Cysteine string protein α (CSPα), a presynaptic cochaperone for Hsc70, is required for synapse maintenance. Deletion of CSPα leads to neuronal dysfunction, synapse loss, and neurodegeneration. We utilized unbiased, systematic proteomics to identify putative CSPα protein clients. We found 22 such proteins whose levels are selectively decreased in CSPα knockout synapses. Of these putative CSPα protein clients, two directly bind to the CSPα chaperone complex and are bona fide clients. They are the t-SNARE SNAP-25 and the GTPase dynamin 1, which are necessary for synaptic vesicle fusion and fission, respectively. Using hippocampal cultures, we show that CSPα regulates the stability of client proteins and synaptic vesicle number. Our analysis of CSPα-dynamin 1 interactions reveals unexpectedly that CSPα regulates the polymerization of dynamin 1. CSPα, therefore, participates in synaptic vesicle endocytosis and may facilitate exo- and endocytic coupling. These findings advance the understanding of how synapses are functionally and structurally maintained.

Haptoglobin activates innate immunity to enhance acute transplant rejection in mice.

Immune tolerance to transplanted organs is impaired when the innate immune system is activated in response to the tissue necrosis that occurs during harvesting and implantation procedures. A key molecule in this immune pathway is the intracellular TLR signal adaptor known as myeloid differentiation primary response gene 88 (MyD88). After transplantation, MyD88 induces DC maturation as well as the production of inflammatory mediators, such as IL-6 and TNF-α. However, upstream activators of MyD88 function in response to transplantation have not been identified. Here, we show that haptoglobin, an acute phase protein, is an initiator of this MyD88-dependent inflammatory process in a mouse model of skin transplantation. Necrotic lysates from transplanted skin elicited higher inflammatory responses in DCs than did nontransplanted lysates, suggesting DC-mediated responses are triggered by factors released during transplantation. Analysis of transplanted lysates identified haptoglobin as one of the proteins upregulated during transplantation. Expression of donor haptoglobin enhanced the onset of acute skin transplant rejection, whereas haptoglobin-deficient skin grafts showed delayed acute rejection and antidonor T cell priming in a MyD88-dependent graft rejection model. Thus, our results show that haptoglobin release following skin necrosis contributes to accelerated transplant rejection, with potential implications for the development of localized immunosuppressive therapies.

Receiver operating characteristic (ROC) analysis of day 5 morphology grading and metabolomic Viability Score on predicting implantation outcome.

PURPOSE: Assessment of embryo viability is a key component of in vitro fertilization (IVF) and currently relies largely on embryo morphology and cleavage rate. In this study, we used receiver operating characteristic (ROC) analysis to compare the Viability Score (generated by metabolomic profiling of spent embryo culture media using near infrared (NIR) spectroscopy) to morphologic grading for predicting pregnancy in women undergoing single embryo transfer (SET) on day 5. METHODS: A total of 198 spent embryo culture media samples were collected in four IVF centers located in the USA, Europe and Australia. First, 137 samples (training set) were analyzed by NIR to develop an algorithm that generates a Viability Score predictive of pregnancy for each sample. Next, 61 samples (validation set) were analyzed by observers blinded to embryo morphology and IVF outcome, using the Day 5 algorithm generated with the training set. Pregnancy was defined as fetal cardiac activity (FCA) at 12 weeks of gestation. RESULTS: The Area Under the Curve (AUC) was greater for the metabolomic Viability Score compared to Morphology [Training set: 0.75 versus 0.55, p = 0.0011; Validation set: 0.68 versus 0.50, P = 0.021], and for a Composite score (obtained using a model combining Viability Score with morphologic grading), compared to morphology alone [0.74 versus 0.50, p = 0.004]. CONCLUSIONS: Our findings suggest that Viability Score alone or in combination with morphologic grading has the potential to be a better classifier for pregnancy outcome than morphology alone in women undergoing SET on day 5.

Dynamic and complex transcription factor binding during an inducible response in yeast.

Complex biological processes are often regulated, at least in part, by the binding of transcription factors to their targets. Recently, considerable effort has been made to analyze the binding of relevant factors to the suite of targets they regulate, thereby generating a regulatory circuit map. However, for most studies the dynamics of binding have not been analyzed, and thus the temporal order of events and mechanisms by which this occurs are poorly understood. We globally analyzed in detail the temporal order of binding of several key factors involved in the salt response of yeast to their target genes. Analysis of Yap4 and Sko1 binding to their target genes revealed multiple temporal classes of binding patterns: (1) constant binding, (2) rapid induction, (3) slow induction, and (4) transient induction. These results demonstrate that individual transcription factors can have multiple binding patterns and help define the different types of temporal binding patterns used in eukaryotic gene regulation. To investigate these binding patterns further, we also analyzed the binding of seven other key transcription factors implicated in osmotic regulation, including Hot1, Msn1, Msn2, Msn4, Skn7, and Yap6, and found significant coassociation among the different factors at their gene targets. Moreover, the binding of several key factors was correlated with distinct classes of Yap4- and Sko1-binding patterns and with distinct types of genes. Gene expression studies revealed association of Yap4, Sko1, and other transcription factor-binding patterns with different gene expression patterns. The integration and analysis of binding and expression information reveals a complex dynamic and hierarchical circuit in which specific combinations of transcription factors target distinct sets of genes at discrete times to coordinate a rapid and important biological response.

What is a gene, post-ENCODE? History and updated definition.

While sequencing of the human genome surprised us with how many protein-coding genes there are, it did not fundamentally change our perspective on what a gene is. In contrast, the complex patterns of dispersed regulation and pervasive transcription uncovered by the ENCODE project, together with non-genic conservation and the abundance of noncoding RNA genes, have challenged the notion of the gene. To illustrate this, we review the evolution of operational definitions of a gene over the past century--from the abstract elements of heredity of Mendel and Morgan to the present-day ORFs enumerated in the sequence databanks. We then summarize the current ENCODE findings and provide a computational metaphor for the complexity. Finally, we propose a tentative update to the definition of a gene: A gene is a union of genomic sequences encoding a coherent set of potentially overlapping functional products. Our definition side-steps the complexities of regulation and transcription by removing the former altogether from the definition and arguing that final, functional gene products (rather than intermediate transcripts) should be used to group together entities associated with a single gene. It also manifests how integral the concept of biological function is in defining genes.

Probabilistic enrichment of phosphopeptides by their mass defect.

The mass defect, that is, the difference between the nominal and actual monoisotopic masses, of a phosphorus in a phosphate group is greater than for most other atoms present in proteins. When the mass defects of tryptic peptides derived from the human proteome are plotted against their masses, phosphopeptides tend to fall off the regression line. By calculating the masses of all potential tryptic peptides from the human proteome, we show that regions of higher phosphorylation probability exist on such a plot. We developed a transformation function to estimate the mass defect of a peptide from its monoisotopic mass and empirically defined a simple formula for a user-selectable discriminant line that categorizes a peptide mass according to its probability of being phosphorylated. Our method performs similarly well on phosphopeptides derived from a database of experimentally validated phosphoproteins. The method is relatively insensitive to mass measurement error of up to 20 ppm. The approach can be used with a tandem mass spectrometer in real time to rapidly select and rank order the possible phosphopeptides from a mixture of unmodified peptides for subsequent phosphorylation site mapping and peptide sequence analysis.

PLTP deficiency improves the anti-inflammatory properties of HDL and reduces the ability of LDL to induce monocyte chemotactic activity.

We reported that phospholipid transfer protein (PLTP) deficiency decreased atherosclerosis in mouse models. Because the decreased atherosclerosis was accompanied by a significant decrease in plasma HDL levels, we examined the properties of PLTP knockout (PLTP0) HDL and tested its ability to prevent LDL-induced monocyte chemotactic activity in human artery wall cell cocultures. We isolated HDL and LDL from LDL receptor knockout/PLTP knockout (LDLr0/PLTP0) mice and from apolipoprotein B transgenic (apoBTg)/PLTP0 mice as well as their controls. PLTP0 HDL was relatively rich in protein and depleted in phosphatidylcholine. Turnover studies revealed a 3.5- to 4.0-fold increase in the turnover of protein and cholesteryl ester in HDL from PLTP0 mice compared with control mice. The ability of HDL from LDLr0/PLTP0 and apoBTg/PLTP0 mice to prevent the induction of monocyte chemotactic activity in human artery wall cell cocultures exposed to human LDL was dramatically better than that in controls. Moreover, LDL from PLTP0 mice was markedly resistant to oxidation and induced significantly less monocyte chemotactic activity compared with that in controls. In vitro, PLTP0 HDL removed significantly more oxidized phospholipids from LDL than did control HDL. We conclude that PLTP deficiency improves the anti-inflammatory properties of HDL in mice and reduces the ability of LDL to induce monocyte chemotactic activity.