Multiple sclerosis is a demyelinating autoimmune disease that is difficult to manage clinically, because it is characterized by unpredictable periods of remission and relapse. If the disease could be adequately monitored, it is possible drugs could intervene to prevent damage, reducing rates of relapse and overall progression. Ideally, it would be possible to repeatedly biopsy the CNS for monitoring, but this is too challenging/morbid to have utility. Herein, we propose an approach that harnesses tissue engineering principles to develop an immunological niche (IN) in vivo to enable harvest of physiologically relevant immune populations. The central hypothesis of this work is that INs can be created to reflect aspects of the innate and/or adaptive immune system that correlate with the CNS. Furthermore, we hypothesize that INs will provide a location into which a non-invasive optical sensor of multiple sclerosis can be implanted.
Aim 1 will test the hypothesis that the FBR to implanted materials can be harnessed to create an IN reflective of innate immunity in the CNS and will dynamically monitor the formation of this niche. Scaffolds will be excised at appropriate time points during disease induction and analyzed with high-throughput gene expression arrays, scRNAseq, and machine learning to develop multivariate signatures capable of determining whether a mouse is diseased or healthy.
Aim 2 (K99) will harness specific antigen-binding peptides to build noninvasive sensors for biomarkers of disease progression. Fluorophore-labeled peptides that specifically bind biomarkers of disease will be incorporated into PEG hydrogels which will be engineered such that the binding of the desired antigen will enable detection via FRET. These sensors will be incorporated into the pores of the IN to enable non-invasive monitoring of MS.
Aim 3 (R00) will develop INs reflective of adaptive immune populations in the CNS, by incorporating antigens within the scaffolds. This section will create a non-invasive sensor and multivariate signature reflective of adaptive immune changes within the surrogates and harness both innate and adaptive INs to investigate mechanistic questions about innate-adaptive crosstalk in the development of MS. Taken together these studies will create engineered immunological niches and non-invasive sensors that enable the creation of enhanced diagnostics, prognostics, treatment monitors, and longitudinal immunology studies without euthanasia. This work is at the intersection of immunology and biomaterials and will require biomaterials synthesis, scRNAseq, computational analysis, tissue engineering, immunology, and biosensor design and validation. The applicant has significant experience in biomaterials, tissue engineering, and the host response, but requires further training in immunology, computational analysis, and biosensor design/validation. Both this award and the advisory committee will provide the applicant tools and expertise to begin his career as an independent investigator. Furthermore, this work will develop new diagnostics, new techniques useful to the field as a whole, and contribute to an understanding of unanswered questions in innate-adaptive crosstalk in autoimmunity.

Public Health Relevance

Multiple sclerosis is an autoimmune disease characterized by immune infiltrate into the CNS and subsequent damage to myelin, that is difficult to diagnose and monitor because the site for disease cannot be readily biopsied for analysis. The goal of this proposal is to create engineered immunological niches and corresponding non- invasive sensors that will correlate with the innate or adaptive immune responses during disease onset and progression by implanting engineered scaffolds in the subcutaneous space. The implications of this work are broad including diagnostics, prognostics, treatment monitoring tools, and research tools to enable longitudinal isolation of disease-inducing cells or non-invasive protein measurements from a single host without euthanasia.

National Institute of Health (NIH)
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Career Transition Award (K99)
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Special Emphasis Panel (ZEB1)
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Russell, Luisa Marie
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University of Michigan Ann Arbor
Biomedical Engineering
Biomed Engr/Col Engr/Engr Sta
Ann Arbor
United States
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