Characterization of expressed human meibum using hyperspectral stimulated Raman scattering microscopy

Jerry R Paugh; Alba Alfonso-Garcia; Andrew Loc Nguyen; Jeffrey L Suhalim; Marjan Farid; Sumit Garg; Jeremiah Tao; Donald J Brown; Eric O Potma; James V Jester

doi:10.1016/j.jtos.2018.10.003

Characterization of expressed human meibum using hyperspectral stimulated Raman scattering microscopy

Ocul Surf. 2019 Jan;17(1):151-159. doi: 10.1016/j.jtos.2018.10.003. Epub 2018 Oct 11.

Authors

Affiliations

¹ Southern California College of Optometry at Marshall B. Ketchum University, Fullerton, CA, USA. Electronic address: jpaugh@ketchum.edu.
² Department of Chemistry, University of California, Irvine, Irvine, CA, USA; University of California at Davis, Department of Biomedical Engineering, Davis, CA, USA.
³ Department of Mathematics, California State University Fullerton, California, USA.
⁴ Department of Biomedical Engineering, University of California, Irvine, CA, USA.
⁵ Gavin Herbert Eye Institute, University of California, Irvine, CA, USA.
⁶ Department of Chemistry, University of California, Irvine, Irvine, CA, USA.
⁷ Department of Biomedical Engineering, University of California, Irvine, CA, USA; Gavin Herbert Eye Institute, University of California, Irvine, CA, USA.

Abstract

Purpose: This study examined whether hyperspectral stimulated Raman scattering (hsSRS) microscopy can detect differences in meibum lipid to protein composition of normal and evaporative dry eye subjects with meibomian gland dysfunction.

Methods: Subjects were evaluated for tear breakup time (TBUT), staining, meibum expression and gland dropout. Expressed meibum was analyzed using SRS vibrational signatures in the CH stretching region (2800-3050 cm^-1). Vertex component analysis and K-means clustering were used to group the spectral signatures into four fractions containing high lipid (G1) to high protein (G4).

Results: Thirty-three subjects could be statistically analyzed using pooled meibum (13 with stable tear films (TBUTs > 10 s) and 20 with unstable tear films (TBUTs ≤ 10 s). Significant differences in meibum from subjects with unstable vs. stable TBUTs were found for the G1 fraction (medians 0.164 and 0.020, respectively; p = 0.012) and the G2 fraction (medians 0.244 and 0.272, respectively; p = 0.045). No differences were observed for the G3 and G4 fractions. Single orifice samples were not significantly different vs. pooled samples from the fellow eye, and eyelid sector samples (nasal, central and temporal) G2:G3 fractional components were not significantly different (p = 0.449). Spearman analysis suggested a significant inverse correlation between G1 fraction and TBUT (R = -0.351; p = 0.045).

Conclusions: hsSRS microscopy allows compositional analysis of expressed meibum from humans which correlated to changes in TBUT. These findings support the hypothesis that hsSRS may be useful in classifying meibum quality and evaluating the effects of therapy.

Keywords: Dry eye; Human meibum; Machine learning; Raman spectroscopy.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Review

MeSH terms

Adolescent
Adult
Aged
Aged, 80 and over
Eyelid Diseases / diagnosis
Eyelid Diseases / metabolism*
Female
Humans
Lipid Metabolism
Machine Learning*
Male
Meibomian Glands / diagnostic imaging
Meibomian Glands / metabolism*
Middle Aged
Nonlinear Optical Microscopy / methods*
Reproducibility of Results
Tears / metabolism*
Young Adult

Abstract

Publication types

MeSH terms

Grants and funding