PURPOSE: Changes in the phase transition temperatures and conformation of human meibum lipid with age and meibomian gland dysfunction (MGD) have been quantified. Less than 1% of the infrared spectral range was used in the previous studies to demonstrate differences. In this study, the remaining 99% of the spectral frequencies were analyzed to gain insight into changes that occur in meibum with age. METHODS: Infrared spectra of meibum from 27 normal donors were acquired. Principal component analysis (PCA) was used to quantify the variance between the spectra. RESULTS: PCA was applied to a set of training spectra of human meibum to predict the age of meibum donors. The plot of predicted age versus actual age was linear, p < 0.001 with a slope of 1.00 and r = 0.909. This indicates that changes in constituents of the meibum spectra (eigenvectors) were due to age-related compositional differences. Eigenvector 1 accounted for 92% of the variance observed among all of the meibum spectra. The spectral features of the two major eigenvectors indicate that with increasing age, the meibum contains more wax, double bonds and terminal CH(3) groups, and is less ordered. The environment of the carbonyl band becomes less polar with increasing age. These results are similar to those obtained for human sebum. CONCLUSIONS: PCA is an excellent chemometric algorithm that may be used to characterize MGD and age-related changes in human meibum. The eigenvectors that define the variations in the spectra provide clues to the compositional changes that occur in meibum with age.
PURPOSE: Changes in the phase transition temperatures and conformation of human meibum lipid with age and meibomian gland dysfunction (MGD) have been quantified. Less than 1% of the infrared spectral range was used in the previous studies to demonstrate differences. In this study, the remaining 99% of the spectral frequencies were analyzed to gain insight into changes that occur in meibum with age. METHODS: Infrared spectra of meibum from 27 normal donors were acquired. Principal component analysis (PCA) was used to quantify the variance between the spectra. RESULTS: PCA was applied to a set of training spectra of human meibum to predict the age of meibum donors. The plot of predicted age versus actual age was linear, p < 0.001 with a slope of 1.00 and r = 0.909. This indicates that changes in constituents of the meibum spectra (eigenvectors) were due to age-related compositional differences. Eigenvector 1 accounted for 92% of the variance observed among all of the meibum spectra. The spectral features of the two major eigenvectors indicate that with increasing age, the meibum contains more wax, double bonds and terminal CH(3) groups, and is less ordered. The environment of the carbonyl band becomes less polar with increasing age. These results are similar to those obtained for human sebum. CONCLUSIONS: PCA is an excellent chemometric algorithm that may be used to characterize MGD and age-related changes in human meibum. The eigenvectors that define the variations in the spectra provide clues to the compositional changes that occur in meibum with age.
Authors: Rashmi K Shrestha; Douglas Borchman; Gary N Foulks; Marta C Yappert; Sarah E Milliner Journal: Invest Ophthalmol Vis Sci Date: 2011-09-21 Impact factor: 4.799
Authors: Douglas Borchman; Gary N Foulks; Marta C Yappert; James Bell; Emily Wells; Shantanu Neravetla; Victoria Greenstone Journal: Invest Ophthalmol Vis Sci Date: 2011-06-01 Impact factor: 4.799
Authors: Sin Man Lam; Louis Tong; Bastien Reux; Xinrui Duan; Andrea Petznick; Siew Sian Yong; Cynthia Boo Shiao Khee; Martin J Lear; Markus R Wenk; Guanghou Shui Journal: J Lipid Res Date: 2013-11-28 Impact factor: 5.922
Authors: Samad Faheem; Sung-Hye Kim; Jonathan Nguyen; Shantanu Neravetla; Matthew Ball; Gary N Foulks; Marta C Yappert; Douglas Borchman Journal: Exp Eye Res Date: 2012-04-28 Impact factor: 3.467