Jessica Malenfant

Increased Natural Killer Cell Activity in Viremic HIV-1 Infection

NK cells are a subset of granular lymphocytes that are critical in the innate immune response to infection. These cells are capable of killing infected cells and secreting integral cytokines and chemokines. The role that this subset of cytolytic cells plays in HIV infection is not well understood. In this study, we dissected the function of NK cells in viremic and aviremic HIV-1-infected subjects, as well as HIV-1-negative control individuals. Despite reduced NK cell numbers in subjects with ongoing viral replication, these cells were significantly more active in secreting both IFN-γ and TNF-α than NK cells from aviremic subjects or HIV-1-negative controls. In addition, NK cells in subjects with detectable viral loads expressed significantly higher levels of CD107a, a marker of lysosomal granule exocytosis. The expression of CD107a correlated with NK cell-mediated cytokine secretion and cytolytic activity as well as with the level of viral replication, suggesting that CD107a represents a good marker for the functional activity of NK cells. Finally, killer Ig-related receptor+ NK cells were stable or elevated in viremic subjects, while the numbers of CD3−/CD56+/CD94+ and CD3−/CD56+/CD161+ NK cells were reduced. Taken together, these data demonstrate that viremic HIV-1 infection is associated with a reduction in NK cell numbers and a perturbation of NK cell subsets, but increased overall NK cell activity.

Software-Enabled Distributed Network Governance: The PopMedNet Experience.

Introduction: The expanded availability of electronic health information has led to increased interest in distributed health data research networks. Distributed Research Network Model: The distributed research network model leaves data with and under the control of the data holder. Data holders, network coordinating centers, and researchers have distinct needs and challenges within this model. Software Enabled Governance: PopMedNet: The concerns of network stakeholders are addressed in the design and governance models of the PopMedNet software platform. PopMedNet features include distributed querying, customizable workflows, and auditing and search capabilities. Its flexible role-based access control system enables the enforcement of varying governance policies. Selected Case Studies: Four case studies describe how PopMedNet is used to enforce network governance models. Issues and Challenges: Trust is an essential component of a distributed research network and must be built before data partners may be willing to participate further. The complexity of the PopMedNet system must be managed as networks grow and new data, analytic methods, and querying approaches are developed. Conclusions: The PopMedNet software platform supports a variety of network structures, governance models, and research activities through customizable features designed to meet the needs of network stakeholders.

A Query Workflow Design to Perform Automatable Distributed Regression Analysis in Large Distributed Data Networks

Introduction: Patient privacy and data security concerns often limit the feasibility of pooling patient-level data from multiple sources for analysis. Distributed data networks (DDNs) that employ privacy-protecting analytical methods, such as distributed regression analysis (DRA), can mitigate these concerns. However, DRA is not routinely implemented in large DDNs. Objective: We describe the design and implementation of a process framework and query workflow that allow automatable DRA in real-world DDNs that use PopMedNet™, an open-source distributed networking software platform. Methods: We surveyed and catalogued existing hardware and software configurations at all data partners in the Sentinel System, a PopMedNet-driven DDN. Key guiding principles for the design included minimal disruptions to the current PopMedNet query workflow and minimal modifications to data partners’ hardware configurations and software requirements. Results: We developed and implemented a three-step process framework and PopMedNet query workflow that enables automatable DRA: 1) assembling a de-identified patient-level dataset at each data partner, 2) distributing a DRA package to data partners for local iterative analysis, and 3) iteratively transferring intermediate files between data partners and analysis center. The DRA query workflow is agnostic to statistical software, accommodates different regression models, and allows different levels of user-specified automation. Discussion: The process framework can be generalized to and the query workflow can be adopted by other PopMedNet-based DDNs. Conclusion: DRA has great potential to change the paradigm of data analysis in DDNs. Successful implementation of DRA in Sentinel will facilitate adoption of the analytic approach in other DDNs.