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Multidimensional immune profiling in HIV-associated neuroinflammation

Multidimensional immune profiling in HIV-associated neuroinflammation

Neurocognitive impairment is driven in part by persistent neuro-inflammation. Drugs of abuse, such as marijuana and cocaine, cause alterations in cognitive functioning and have significant immunomodulatory effects. While the effects of HIV infection and drug abuse have been independently studied, the complex interactions between these biological factors are poorly characterized. This multi-disciplinary project, with complementary expertise in neuroscience, drug addiction, HIV immunology, and computational biology, aims to develop systems biology methods to investigate the effects of drugs of abuse on immune function, brain structure/function, and neurocognition in HIV-infected persons. The sample will include 160 adults with HIV infection who use cocaine only, marijuana only, cocaine and marijuana, or neither drug, comprising 4 distinct groups (~40/group). At study completion, we will have produced a comprehensive, multi-disciplinary dataset, and our systems biology approach will provide significant insights to generate novel hypotheses for future research on the complex biological intersection of HIV and substance use. The R25 intern will assist in the development of pipelines for immunological data processing, comparative analysis and visualization  as well as construct models that predict neurro-inflammation. This work will contribute to a multi-PI NIH research grant award to Dr. Christina Meade and Dr. David Murdoch.

Timeline and Desired Outcomes:

  • Weeks 1-2: Review and summarize the literature on HIV associated cognitive disorder relating to known immunological predictors; summarize the current state of statistical approaches incorporating multi-modal data (cytokine measurements, domain specific imaging defects)
  • Weeks 3-4: Construct pre-processing and data storage plans for immunological, behavioral, and imaging datasets
  • Weeks 5-7: Develop pipelines for immunological data processing – perform modeling of multiplexed cytokine analyses; develop automated techniques to identify potentially novel immune cell subsets using dimension reduction methods (PCA, randomized projections)
  • Weeks 8-10: Initiate development of predictive models utilizing multi-modal datasets (neurobehavioral, imaging, immunology). First, the intern will aim to identify neural injury variables (imaging, neurofilament & neopterin CSF levels) most predictive of NCI. Next, the intern will identify inflammation and drug abuse variables that predict the levels of the previously identified neural injury variables. Lastly, integrated hierarchical modeling will be performed with reduction in neuronal and inflammation variables.

Special Project Features:

The project is ongoing and recruits participants on a weekly basis. The intern will have the opportunity to participate in weekly lab meetings with the PI and lab technician. Immunological assays are also ongoing for interim analyses. Thus, the intern may have the opportunity to assist with the assays and generate real-time data for comprehension and analysis.

Expectations for Intern:

  • Interest or experience in immunology or neurosciences is an asset
  • Basic data preparation & management (appending multiple similar datasets; i.e. ELISA output)
  • Experience with machine learning or statistical learning
  • Experience with predictive modeling and integrated hierarchical modeling
  • Data processing and analysis developed in the context of this research will use the open source R, Python, and Julia languages
  • Exploratory visual analysis of high-dimensional immunological data will be performed using the packages such as SPADE and VISNE
  • Adaptive multi-task LASSO procedures, Bayesian hierarchical modes (Hamiltonian Monte Carlo software Stan)