Microsystems & Nanoengineering (Mar 2021)

Acoustofluidic separation enables early diagnosis of traumatic brain injury based on circulating exosomes

  • Zeyu Wang,
  • Haichen Wang,
  • Ryan Becker,
  • Joseph Rufo,
  • Shujie Yang,
  • Brian E. Mace,
  • Mengxi Wu,
  • Jun Zou,
  • Daniel T. Laskowitz,
  • Tony Jun Huang

DOI
https://doi.org/10.1038/s41378-021-00244-3
Journal volume & issue
Vol. 7, no. 1
pp. 1 – 11

Abstract

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Abstract Traumatic brain injury (TBI) is a global cause of morbidity and mortality. Initial management and risk stratification of patients with TBI is made difficult by the relative insensitivity of screening radiographic studies as well as by the absence of a widely available, noninvasive diagnostic biomarker. In particular, a blood-based biomarker assay could provide a quick and minimally invasive process to stratify risk and guide early management strategies in patients with mild TBI (mTBI). Analysis of circulating exosomes allows the potential for rapid and specific identification of tissue injury. By applying acoustofluidic exosome separation—which uses a combination of microfluidics and acoustics to separate bioparticles based on differences in size and acoustic properties—we successfully isolated exosomes from plasma samples obtained from mice after TBI. Acoustofluidic isolation eliminated interference from other blood components, making it possible to detect exosomal biomarkers for TBI via flow cytometry. Flow cytometry analysis indicated that exosomal biomarkers for TBI increase in the first 24 h following head trauma, indicating the potential of using circulating exosomes for the rapid diagnosis of TBI. Elevated levels of TBI biomarkers were only detected in the samples separated via acoustofluidics; no changes were observed in the analysis of the raw plasma sample. This finding demonstrated the necessity of sample purification prior to exosomal biomarker analysis. Since acoustofluidic exosome separation can easily be integrated with downstream analysis methods, it shows great potential for improving early diagnosis and treatment decisions associated with TBI.