Hong Yu, M.D., Ph.D. - US grants

DESCRIPTION (provided by applicant): A stent-graft is a conduit composed of a polymer membrane supported by a metal stent that is placed in a vessel using catheter technology. We have genetically engineered vascular smooth muscle cells (SMC) and placed them on a stent graft that was specifically designed to shelter the SMC cells from implantation trauma. We found that these genetically engineered cells survived and proliferated and that gene expression was maintained at high levels over a long period, indicating the feasibility of this new gene therapy strategy to deliver the gene product directly into the bloodstream. The objective of this project is to explore whether a stent-graft suffused with genetically engineered SMC can be used to deliver functional Factor IX (F.IX) to treat hemophilia B. Hemophilia B is an X-linked bleeding diathesis resulting from a deficiency of blood coagulation factor IX. Hemophilia is an ideal model for gene therapy because precise regulation and tissue-specific transgene expression are not required. We will use a hemophilic dog model to study the feasibility of bioengineering a stent graft for gene therapy. We hypothesize that the intravascular delivery of F. IX using a stent-graft suffused with retrovirally transduced SMC will offer the opportunity for delivery of F.IX at a therapeutic level to correct the coagulation defect. We will first determine how long and how much of the transgene product canine F.IX can be produced from the bioengineered stent grafts after being implanted into the aorta of a hemophilia B dog using catheter technology. We will modulate the level of F.IX production by the length of the implanted stent graft. Then, we will determine whether the secreted F. X at these levels can ameliorate the coagulation defect in a hemophilic dog by measuring coagulation parameters. The host immune response to the transgene product canine F.IX will also be examined. The outcome of the project will have direct applications in the treatment of hemophilia as well as other blood and vascular disorders.

DESCRIPTION (provided by applicant): Most biomedical text mining systems target only text information and do not provide intelligent access to other important data such as Figures. More than any other documentation, figures usually represent the evidence of discovery in the biomedical literature. Full-text biomedical articles nearly always incorporate images that are the crucial content of biomedical knowledge discovery. Biomedical scientists need to access images to validate research facts and to formulate or to test novel research hypotheses. Evaluation has shown that textual statements reported in the literature are frequently noisy (i.e., contain false facts). Capturing images that are essentially experimental evidence to support the textual fact will benefit biomedical information systems, databases, and biomedical scientists. We are developing a biomedical literature figure search engine BioFigureSearch. We develop innovative algorithms and models in natural language processing, image processing, machine learning and user interfacing. The deliverables will be novel biomedical natural language figure processing (bNLfP) algorithms and iBioFigureSearch allowing biomedical scientists to access figure data effectively, and open-source tools that will enhance biomedical information retrieval, summarization, and question answering. The bNLfP algorithms we will be developing can be applied or integrated into other biomedical text-mining systems.

DESCRIPTION (provided by applicant): Adverse drug events (ADEs) result in substantial patient morbidity and lead to over 100,000 deaths yearly. The timely identification of previously unknown toxicities of cancer drugs is an important, unsolved problem. In the United States, 20% of the 548 drugs introduced into the market between 1975 and 1999 were either withdrawn or acquired a new black box warning during the 25-year period following initial approval by the Food and Drug Administration. Adverse drug events are an important cause of morbidity and mortality in patients, yet 95% of ADEs are unreported, leading to delays in the detection of previously unknown ADEs and underestimation of the risk to known ADEs. It is known that Electronic Medical Record (EMR), discharge summaries, and lab results contain ADE information and biomedical natural language processing (BioNLP) provides automated tools that facilitate chart review and thus improve patient surveillance and post-marketing pharmacovigilance. The objectives for this proposal are to develop intelligent BioNLP approaches to extract disease, medication, and structured ADE information from EMRs, and then evaluate extracted ADEs for detecting known ADE types as well as clinically unrecognized or novel ADEs whose pattern or effect have not been previously identified.

? DESCRIPTION (provided by applicant): Periodontitis is a bacteria-driven inflammatory bone loss disease affecting 47% of adults in the United States. Oral pathogens, such as Aggregatibacter actinomycetemcomitans (Aa), the pathogen associated with localized aggressive periodontitis, stimulate mammalian cells to generate and release sphingosine-1-phosphate (S1P). S1P binds to five G protein-coupled receptors, which initiates various cellular signaling pathways and affects many physiological and pathophysiological processes. However, it is unknown how S1P signaling modulates the inflammatory bone loss response induced by oral pathogens. The long-term goal is to understand the role of S1P signaling in regulating the immune response to oral pathogens and to develop a novel therapeutic strategy for periodontitis. Our preliminary study demonstrated that S1P signaling is critical in regulating the immune response to Aa. In a periodontal inflammatory bone loss animal model, deficiency in generation of S1P in mice (sphingosine kinase 1 KO mice) attenuated periodontal leukocyte infiltration and alleviated alveolar bone loss in response to Aa stimulation. Additionally, pharmacological inhibition or RNA silencing of S1P receptor 2 (S1PR2) in murine bone marrow-derived macrophages (BMM) significantly attenuated COX-2, IL-1ß, IL-6, and TNF mRNA expressions induced by Aa. Furthermore, pharmacological inhibition of S1PR2 in BM-derived preosteoclasts suppressed osteoclastogenesis induced by Aa-stimulated conditioned media. The overall objective of this application is to establish S1PR2-mediated signaling as a key modulator in regulating the immune response to the oral pathogen Aa. We hypothesize that the Aa-induced proinflammatory bone loss response is mediated through S1PR2 signaling. Blocking S1PR2 signaling will reduce proinflammatory cytokine production, attenuate osteoclastogenesis, and alleviate alveolar bone loss induced by Aa. We will test these two specific aims to determine if 1) S1PR2 deficiency in vitro will significantly decrease ERK, PLC, Rho, and NF-?B protein kinase activities, reduce proinflammatory cytokine production, and attenuate osteoclastogenesis in response to Aa exposure. Additionally, we will determine if blocking S1PR2 will decrease osteoclastogenic factors RANK, RANKL, and M-CSF. 2) S1PR2 deficiency in vivo will decrease periodontal leukocyte infiltration, alleviate proinflammatory cytokine production, and attenuate alveolar bone loss. Under the first aim, we will use BMM or preosteoclasts derived from S1pr2+/+ and S1pr2-/- mice to determine if S1PR2 deficiency in cells will reduce the immune response to Aa. Additionally, we will determine if blocking S1PR2 will decrease RANK, RANKL, and M-CSF induced by Aa in BMM or osteoblasts. Under the second aim, we will use an Aa-induced periodontal inflammatory bone loss animal model to determine if S1PR2 deficiency in mice will reduce the inflammatory bone loss response induced by Aa. This study will elucidate the role of S1PR2 signaling, a novel key mechanism, in the pathogenesis of periodontitis. This study will define a new therapeutic target and lay the foundation to develop a novel therapeutic strategy for periodontitis by targeting S1PR2.

Project Summary/Abstract Preventing the onset of acute myocardial infarction (AMI) and its recurrence, and reducing the morbidity and mortality associated with AMI, remain of significant public health and clinical concern. Monitoring contemporary trends in AMI incidence, treatment, and in-hospital and long-term outcomes is of considerable importance given periodic national updates of treatment guidelines, emphasis on reducing hospital readmissions, and revised definitions and classifications of AMI. Continuously supported by the NHLBI, we have conducted more than 35 years of population-based surveillance of AMI incidence and attack rates, hospital management practices, and the in-hospital and long-term prognosis associated with AMI among residents of central MA hospitalized at all central MA medical centers. We have a highly experienced team of cardiologists, epidemiologists, clinical informatics, and health services researchers who will build on multi- decade long trends (1975-2011) in our principal study endpoints examined previously in this study to the two new study years of patients hospitalized with AMI at all central MA medical centers in 2014 and 2017. To sustain our efforts into the era of electronic medical records (EMRs), and after implementation of the ICD-10 system in 2015, we will develop a new automated AMI surveillance system that efficiently utilizes EMRs by taking advantage of state-of-art natural language processing (NLP) methods that will be compatible with ICD-10 (Aim 1). We will use the new NLP method to streamline traditional chart review-based collection of socio-demographic, clinical, treatment, and hospital and post-discharge outcomes data in patients hospitalized with AMI at all 11 central MA medical centers in 2014 and 2017. The data extracted from NLP-streamlined chart reviews will be used to validate and refine the NLP system. Issues related to changes from ICD-9 to ICD- 10 will be carefully addressed. The new NLP-enriched EMR-based surveillance system will eventually be implemented in all participating central MA hospitals. Using the NLP-enriched and EMR-based surveillance data, we will monitor the contemporary clinical epidemiology of AMI, and out-of-hospital deaths due to coronary disease, and changing landscape, over a more than 40 year period (1975-2017) (Aim 2). The new EMR-based and NLP-enriched system will enhance the population-based surveillance of acute coronary disease. This new system will be cost-effective, more efficient and near-real time, have greater accuracy and precision, and can be readily updated to accommodate changes in information technologies and broadly applicable to other hospital systems. It will support our continued efforts to provide unique community- based observational data on several populations that are often excluded from clinical trials, and that are increasing in numbers, namely the elderly and patients with multiple morbidities. Furthermore, it will generate critical data to inform more national clinical guidelines on the enhanced prevention and management of AMI. If successful, the system can serve as a model and be implemented statewide in MA and elsewhere in the US.

Periodontitis is a bacteria-driven inflammatory bone loss disease affecting 47% of adults in the United States.1 We were the first to demonstrate that sphingosine-1-phosphate receptor 2 (S1PR2) plays a key role in regulating the inflammatory bone loss response.18 S1PR2, a G protein-coupled receptor, is expressed in most tissues and mammalian cells.14,15 Previous studies19,21 showed that S1PR2 controls the migration of monocytes and macrophages in response to S1P, affecting immune responses. Our previous study18 demonstrated that knockdown of S1PR2 by a specific S1PR2 shRNA significantly reduced IL-1?, IL-6, and TNF-? protein levels induced by an oral pathogen Aggregatibacter actinomycetemcomitans (Aa); suppressed osteoclastogenesis and bone resorption induced by RANKL compared with controls. Consistent with our previous study, our preliminary data have shown that inhibition of S1PR2 by its specific antagonist JTE013 significantly reduced IL- 1?, IL-6, and TNF-? protein levels induced by Aa, and suppressed osteoclastogenesis induced by RANKL compared with controls. Furthermore, treatment with S1PR2 shRNA or JTE013 suppressed chemotaxis of monocytes and macrophages induced by Aa-stimulated cell culture media. Since generation of proinflammatory cytokines, chemotaxis of inflammatory cells, and osteoclastogenesis lead to periodontal tissue damages, alveolar bone loss, and tooth loss, we hypothesize that pharmacological inhibition of S1PR2 will reduce inflammatory bone loss induced by oral pathogens and serve as a novel therapeutic strategy for periodontitis. There are several critical gaps on how S1PR2 regulates cellular signaling pathways that control oral pathogen-induced proinflammatory cytokine production, chemotaxis of monocytes and macrophages, and osteoclastogenesis. Therefore, the objective of the proposal is to elucidate the specific cellular signaling pathways regulated by S1PR2 in controlling these immune responses. Moreover, we will determine if inhibiting S1PR2 in vivo can attenuate inflammatory bone loss induced by oral pathogens. Our specific aims will determine if knockdown or inhibition of S1PR2 in vitro will 1) reduce PI3K, MAPKs, RhoA, and NF-kB induced by Aa, subsequently decreasing IL-1?, IL-6, and TNF-? production; 2) reduce the activation of PI3K induced by Aa-stimulated cell culture media, subsequently decreasing chemotaxis of monocytes and macrophages; 3) suppress podosome components (PI3K, Src, Pyk2, integrins, F-actin, integrins, paxillin, vinculin, and talin) on monocytes and macrophages induced by RANKL, subsequently suppressing osteoclastogenesis; and 4) whether pharmacological inhibition of S1PR2 in vivo can reduce inflammatory bone loss in an experimental periodontitis model induced by Aa. These studies define novel signaling pathways regulated by S1PR2 in modulating bacterial infection, chemotaxis of monocytes and macrophages, and osteoclastogenesis. Moreover, these studies will develop a novel therapeutic approach for periodontitis and other inflammatory bone loss diseases by targeting S1PR2.