Integrating Real-Time Multi-System Cytokine Signaling in Chronic Disease

Information

  • Research Project
  • 10275578
  • ApplicationId
    10275578
  • Core Project Number
    R35GM142833
  • Full Project Number
    1R35GM142833-01
  • Serial Number
    142833
  • FOA Number
    PAR-20-117
  • Sub Project Id
  • Project Start Date
    8/1/2021 - 3 years ago
  • Project End Date
    5/31/2026 - a year from now
  • Program Officer Name
    ZHAO, XIAOLI
  • Budget Start Date
    8/1/2021 - 3 years ago
  • Budget End Date
    5/31/2022 - 2 years ago
  • Fiscal Year
    2021
  • Support Year
    01
  • Suffix
  • Award Notice Date
    7/29/2021 - 3 years ago

Integrating Real-Time Multi-System Cytokine Signaling in Chronic Disease

Project Summary/Abstract Over the next five years, my laboratory aims to study time-resolved systemic inflammation across multiple chronic diseases. Though pro-inflammatory cytokine signaling is common amongst chronic diseases, it is unclear what cytokines are active at various timepoints throughout disease initiation and progression. It is also unclear what cytokines are functional in the inflection from acute to chronic-phase inflammatory signaling. Current methods of research evaluation are not amenable to rapid kinetics (enzymatic immunoassays) or quantitative multiplexing (molecular imaging techniques). We plan to use a fluorescent carbon nanosensor-based platform I have previously developed, modified to rapidly detect pro-inflammatory cytokines in a multiplexed manner. The multiplexed cytokine nanosensor will be encapsulated within an injectable hydrogel matrix for minimally-invasive implantation and rapid measurement. We will use this sensor platform to create a cytokine signal detection network for both circulating and in situ cytokine signals in rodent models of chronic diseases. The nanosensor network will initially be validated in healthy mice using exogenous cytokine injection. We will ensure the sensor detects multiple cytokines simultaneously, at disease-relevant concentrations, is functional for months, and exhibits no specificity issues. The encapsulating hydrogel matrix will be designed to allow passage of proteins but retention of the sensor based on size, and will undergo minimal biofouling. Following technology validation, we will use the nanosensor network to measure local and circulating cytokine levels in at least eight models of chronic disease, including: cardiovascular disease, cancer, neurodegenerative disease, and autoimmune disease. Future work will be extended to infectious disease, chronic renal disease, musculoskeletal disease, and others. In each disease model, we will couple traditional assessments of inflammation and immune response, as evaluated by weekly blood draws coupled with enzymatic immunoassays. Local inflammation will also be evaluated at the time of sacrifice via single-cell transcriptomic sequencing and immunohistochemical staining. Kinetic cytokine measurements will be obtained via the nanosensor network, deployed in at least 7 locations in each animal, 2 local and 2 systemic, via hydrogel injection. Each will be measured daily for kinetic cytokine quantification prior to and immediately after disease initiation, during chronic progression, and during end-stage disease. Sensor measurement will be performed via whole-animal imaging and simple 3-second light excitation non-invasively from outside the animal. These sensors will provide real-time, long-term quantification of cytokine concentrations throughout disease progression. We expect to understand kinetic cytokine changes in the inflection from acute to chronic inflammatory responses and the pro-inflammatory contribution of multiple organs during disease development. We will investigate pro-inflammatory cytokine signatures for each disease at specific times in its development, providing scientists studying each field difficult-to-obtain dynamic data and further insight into the pathogenesis of chronic disease.

IC Name
NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES
  • Activity
    R35
  • Administering IC
    GM
  • Application Type
    1
  • Direct Cost Amount
    250000
  • Indirect Cost Amount
    142500
  • Total Cost
    392500
  • Sub Project Total Cost
  • ARRA Funded
    False
  • CFDA Code
    859
  • Ed Inst. Type
    BIOMED ENGR/COL ENGR/ENGR STA
  • Funding ICs
    NIGMS:392500\
  • Funding Mechanism
    Non-SBIR/STTR RPGs
  • Study Section
    ZRG1
  • Study Section Name
    Special Emphasis Panel
  • Organization Name
    CITY COLLEGE OF NEW YORK
  • Organization Department
    ENGINEERING (ALL TYPES)
  • Organization DUNS
    603503991
  • Organization City
    NEW YORK
  • Organization State
    NY
  • Organization Country
    UNITED STATES
  • Organization Zip Code
    100367207
  • Organization District
    UNITED STATES