Identification and Validation of Functional Biomarkers for Keratoconus
Identification and Validation of Functional Biomarkers for Keratoconus
There is currently no medication for containing KC, nor any adequate biomarkers to predict
 the disease. Furthermore, there is considerable confusion in the field regarding the
 pathophysiology of the disease and involvement of inflammation. To that end, this study is
 designed to address some of these questions by determining the proteomic profiles of KC
 patients with different clinical grades. This relatively large cohort study is expected to
 yield significant information regarding the molecules that are deregulated during progression
 of KC and may provide a framework to assign diagnostic biomarkers and therapeutic
 intervention points.
The screening of keratoconus involves keratoconus related clinical signs like retinoscopy
 scissors reflex, Munson sign, stromal thinning, Vogt's striae, and Fleischer's ring, but
 corneal topography is the most useful method in the diagnosis of keratoconus, especially in
 the absence of clinical signs.

 Several devices are currently available for detecting early keratoconus by measuring anterior
 and posterior corneal topography and elevation(Mihaltz et al. 2009; Ishii et al. 2012).
 Corneal topographic and tomographic techniques which generate color-coded maps and
 topographic indices, are the most sensitive devices for confirming the diagnosis of
 keratoconus(Rabinowitz 1998; Rao et al. 2002) were used for diagnosis in this study. In
 addition, videokeratography has been shown to identify Forme fruste keratoconus (FFKC) in the
 absence of clinical signs of keratoconus. Videokeratographic indices such as the Klyce/Maeda
 criteria, the Rabinowitz criteria, and others have been developed to quantitatively analyze
 videokeratography and screen for keratoconus(Rao et al. 2002). These indices have been shown
 to identify keratoconus with a high degree of sensitivity and specificity. The Orbscan II is
 a three-dimensional slit-scan topography system for analysis of the corneal surfaces and
 anterior chamber and has been used on all patients in the study. It uses calibrated video and
 a scanning slit beam to measure x, y, and z locations of several thousand points. These
 points are used to construct topographic maps(Rao et al. 2002). The Pentacam (Oculus Inc) is
 a corneal tomographer technology which generates data on topograophy and elevation of
 anterior and posterior using a rotating Scheimpflug camera which has also been used on all
 subjects enrolled in this study. Various diagnostic parameters are available for keratoconus
 diagnosis depending on what mode of topography is being used. Maeda and Klyce designed a
 system to detect keratoconus. The system, which is based on linear discriminant analysis and
 a binary decision tree, identifies the map as representing keratoconus or nonkeratoconus and,
 based on a value from the discriminant analysis (the KPI), assigns the map an index expressed
 as a percentage that suggests the severity of keratoconus. At this time, however, Keratoconus
 Severity Index (KSI) and the Amsler-Krumeich classification are the most popular methods for
 grading keratoconus severity(Mihaltz et al. 2009; Ishii et al. 2012). KSI is based on indices
 estimated by a curvature map using Placido disk-based corneal topography, and Amsler-Krumeich
 classification defines the stage of keratoconus using biomicroscopy, mean central keratometry
 reading, spherical and cylindrical refraction change, and corneal thickness(Mihaltz et al.
 2009; Ishii et al. 2012). This is the index that has been used for the final gradation of
 keratoconus stages of all subjects in this study.
Inclusion Criteria:

 -  Evidence of corneal thinning by any type of keratometry

 Exclusion Criteria:

 -  Corneal inflammation without evidence of ectasia

 -  Retinal disorder subjects excluded