Non-invasive optical detection of HBV based on serum surface-enhanced Raman spectroscopy

An optical method of surface-enhanced Raman spectroscopy (SERS) was developed for non-invasive detection of hepatitis B surface virus (HBV). Hepatitis B virus surface antigen (HBsAg) is an established serological marker that is routinely used for the diagnosis of acute or chronic hepatitis B virus(HBV) infection. Utilizing SERS to analyze blood serum for detecting HBV has not been reported in previous literature. SERS measurements were performed on two groups of serum samples: one group for 50 HBV patients and the other group for 50 healthy volunteers. Blood serum samples are collected from healthy control subjects and patients diagnosed with HBV. Furthermore, principal components analysis (PCA) combined with linear discriminant analysis (LDA) were employed to differentiate HBV patients from healthy volunteer and achieved sensitivity of 80.0% and specificity of 74.0%. This exploratory work demonstrates that SERS serum analysis combined with PCA-LDA has tremendous potential for the non-invasive detection of HBV.

[1]  Rong Chen,et al.  Blood plasma surface-enhanced Raman spectroscopy for non-invasive optical detection of cervical cancer. , 2013, The Analyst.

[2]  G. Alexander,et al.  Liver transplantation in European patients with the hepatitis B surface antigen. , 1993, The New England journal of medicine.

[3]  Ding‐Shinn Chen,et al.  Dual chronic hepatitis B virus and hepatitis C virus infection , 2009, Hepatology international.

[4]  M. Nguyen,et al.  Hepatitis B surface antigen escape mutations: Indications for initiation of antiviral therapy revisited. , 2016, World journal of clinical cases.

[5]  L. Martí-Bonmatí,et al.  Metabolite identification in human liver needle biopsies by high‐resolution magic angle spinning 1H NMR spectroscopy , 2006, NMR in biomedicine.

[6]  Zufang Huang,et al.  Surface-enhanced Raman spectroscopy of saliva proteins for the noninvasive differentiation of benign and malignant breast tumors , 2015, International journal of nanomedicine.

[7]  M. Kumar,et al.  Virologic and histologic features of chronic hepatitis B virus-infected asymptomatic patients with persistently normal ALT. , 2008, Gastroenterology.

[8]  N. Xia,et al.  Evaluation of a novel chemiluminescent microplate enzyme immunoassay for hepatitis B surface antigen detection. , 2016, Journal of virological methods.

[9]  G. Xiao,et al.  Regulation of Hepatitis B Virus Replication by the Phosphatidylinositol 3-Kinase-Akt Signal Transduction Pathway , 2007, Journal of Virology.

[10]  B. Weber Recent developments in the diagnosis and monitoring of HBV infection and role of the genetic variability of the S gene , 2005, Expert review of molecular diagnostics.

[11]  Juqiang Lin,et al.  Serum albumin and globulin analysis for hepatocellular carcinoma detection avoiding false-negative results from alpha-fetoprotein test negative subjects , 2013 .

[12]  A. Talari,et al.  Raman Spectroscopy of Biological Tissues , 2007 .

[13]  Bernhard Lendl,et al.  A New Method for Fast Preparation of Highly Surface-Enhanced Raman Scattering (SERS) Active Silver Colloids at Room Temperature by Reduction of Silver Nitrate with Hydroxylamine Hydrochloride , 2003 .

[14]  Juqiang Lin,et al.  Diagnostic potential for gold nanoparticle-based surface-enhanced Raman spectroscopy to provide colorectal cancer screening using blood serum sample , 2012, Photonics and Optoelectronics Meetings.

[15]  Rong Chen,et al.  Label-free surface-enhanced Raman spectroscopy for detection of colorectal cancer and precursor lesions using blood plasma. , 2015, Biomedical optics express.

[16]  Zufang Huang,et al.  Label‐free optical detection of type II diabetes based on surface‐enhanced Raman spectroscopy and multivariate analysis , 2014 .

[17]  A. Mahadevan-Jansen,et al.  Near‐Infrared Raman Spectroscopy for In Vitro Detection of Cervical Precancers , 1998 .

[18]  Rong Chen,et al.  Study on gastric cancer blood plasma based on surface-enhanced Raman spectroscopy combined with multivariate analysis , 2011, Science China Life Sciences.