Proceedings of the Texas A&M Medical Student Grand Rounds

Targeting Serum Cytokines as Prognostic Biomarkers for COVID-19 Biosensors

June 28, 2022 Shourya Kumar

Shourya Kumar and Limei Tian, PhD

Introduction: Coronaviruses are enveloped RNA viruses in humans and animals that can cause acute and chronic diseases1. In patients with a weak immune system or other (unknown) pre-existing conditions, an uncontrolled inflammatory response linked to a cytokine storm has been associated with severe pulmonary inflammation being the leading cause of death2. In fact, studies show increased levels of cytokine storms correlate with more severe disease progression. Specifically, IL-6, IL-8, and IL-10 are shown to be predictors for quicker diagnosis of severe COVID-19 disease3-4. Various point-of-care biosensors targeting cytokines have shown therapeutic value in determining the severity of COVID-19 disease. Methods: One biosensor utilizes an aptameric dual graphene-TWEEN 80 field effect transistor (DGTFET) to enable on-site, wireless detection of cytokines (IFN-γ, TNF-α, and IL-6) from several body fluids5. Another biosensor made from a cellulose-nanoparticle combination, utilizes conjugated gold nanoparticles to anti IL-6 antibodies, fixed to modified filter paper/wax paper. A subsequent 10uL sample is added to the first portion of the strip, dried with high heat (hairdryer), and then washed with a wash-buffer. The resulting colorimetric signal is then imaged with a smartphone app6. Another biosensor integrates machine learning with a microfluidic, nanoplasmonic digital immunoassay to profile cytokine levels of COVID-19 patients. The one-step immunoassay works by utilizing anti-cytokine capture antibody and antigen nanocubes conjugated with paired detection antibodies as signal transducers. The resulting sandwich complex is then imaged with a dark field microscope and analyzed with an on-board machine learning system7. Results: The biosensor developed by Hao, et al. demonstrates the capabilities of their DGTFET device in detecting cytokines IFN-γ, TNF-α, and IL-6 in biofluids including serum, saliva, urine and sweat, with respective limits of detection (LODs) of 476 × 10−15, 611 × 10−15, and 608 × 10−15 M5. The biosensor developed by Adrover-Jaume, et al. achieved a LOD of 17 pg mL-1 in blood6. Finally, the biosensor developed by Gao, et al. allows for simultaneous detection of six cytokines with LODs of LODs of 0.91 pg mL–1 (IL-1β), 0.47 pg mL–1 (IL-2), 0.46 pg mL–1 (IL-6), 1.36 pg mL–1 (IL-10), 0.71 pg mL–1 (TNF-α), and 1.08 pg mL–1 (IFN-γ)7.  Conclusions: Together, these studies demonstrate the significant advances that have made in development of biomarkers targeting cytokines, allowing for earlier detection of potentially severe COVID-19 disease progression, ultimately improving patient outcomes.

  1.  Pedersen SF, Ho Y-C. SARS-CoV-2: a storm is raging. Journal of Clinical Investigation. Published online March 27, 2020. doi:10.1172/jci137647
  2. Bakhiet M, Taurin S. SARS-CoV-2: Targeted managements and vaccine development. Cytokine & Growth Factor Reviews. Published online December 2020. doi:10.1016/j.cytogfr.2020.11.001
  3. Han H, Ma Q, Li C, et al. Profiling serum cytokines in COVID-19 patients reveals IL-6 and IL-10 are disease severity predictors. Emerging Microbes & Infections. 2020;9(1):1123-1130. doi:10.1080/22221751.2020.1770129
  4. Tang, J., Ravichandran, S., Lee, Y., Grubbs, G., Coyle, E. M., Klenow, L., Genser, H., Golding, H., & Khurana, S. (2021). Antibody affinity maturation and plasma IgA associate with clinical outcome in hospitalized COVID-19 patients. Nature Communications (Vol. 12, Issue 1). Springer Science and Business Media LLC. https://doi.org/10.1038/s41467-021-21463-2
  5. Hao, Z., Luo, Y., Huang, C., Wang, Z., Song, G., Pan, Y., Zhao, X., & Liu, S. (2021). An Intelligent Graphene-Based Biosensing Device for Cytokine Storm Syndrome Biomarkers Detection in Human Biofluids. Small (Weinheim an der Bergstrasse, Germany), 17(29), e2101508. https://doi.org/10.1002/smll.202101508
  6. Adrover-Jaume, C., Alba-Patiño, A., Clemente, A., Santopolo, G., Vaquer, A., Russell, S. M., Barón, E., González del Campo, M. del M., Ferrer, J. M., Berman-Riu, M., García-Gasalla, M., Aranda, M., Borges, M., & de la Rica, R. (2021). Paper biosensors for detecting elevated IL-6 levels in blood and respiratory samples from COVID-19 patients. Sensors and Actuators B: Chemical (Vol. 330, p. 129333). Elsevier BV. https://doi.org/10.1016/j.snb.2020.129333
  7. Gao, Z., Song, Y., Hsiao, T. Y., He, J., Wang, C., Shen, J., MacLachlan, A., Dai, S., Singer, B. H., Kurabayashi, K., & Chen, P. (2021). Machine-Learning-Assisted Microfluidic Nanoplasmonic Digital Immunoassay for Cytokine Storm Profiling in COVID-19 Patients. ACS nano, acsnano.1c06623. Advance online publication. https://doi.org/10.1021/acsnano.1c06623
Engineering Medicine Immunology Inflammation Microbiology
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