title: Predicting the risk for corneal graft rejection by aqueous humor analysis.
abstract: OBJECTIVE
  Cytokine patterns determined in the aqueous humor before penetrating keratoplasty (PK) may enable us to predict immune reactions (IR). We therefore analyzed 6 cytokines in the aqueous humor of patients before PK. By prospective clinical follow-up, we tested whether patients who developed an IR would present different preoperative cytokine patterns compared to patients without IR.
  
  
  METHODS
  We analyzed 18 samples of aqueous humor from 18 patients undergoing PK. The following cytokines were analyzed by cytometric bead array: interleukin 2 (IL-2), interleukin 4 (IL-4), interleukin 5 (IL-5), interleukin 10 (IL-10), tumor-necrosis-factor α (TNF-α), and interferon γ (INF-γ). Seven patients presented with signs of IR during follow up. We performed Cox proportional hazards analysis to determine significant predictors for IR. We iteratively eliminated all co-variates with p values over 0.1 from the survival model (backward selection).
  
  
  RESULTS
  Our final Cox model included the hazardous factors IL-4 (p=0.043) and INF-γ (p=0.059), protective factors IL-2 (p=0.081), IL-5 (p=0.028), and age at time of surgery (p=0.029). We performed a linear discriminant analysis based on these coefficients. The resulting function was: (-9.979*IL5) + (9.262*IL4) + (-3.928*IL2) + (1.709*IFN-γ) + (-0.183*age). A median of -4.97 separated patients with and without IR with no classification error.
  
  
  CONCLUSIONS
  We demonstrate that cytokine levels in the aqueous humor can be predictive for IR. Our method allowed an almost 100% separation between patients with and without IR. This finding has the potential to improve the aftercare of PK fundamentally. However, our results need to be confirmed in a larger prospective cohort.
authors.affiliation: University Eye Hospital, Freiburg, Germany. philip.maier@uniklinik-freiburg.de
authors.forename: Philip
authors.initials: P
authors.lastname: Maier
authors.forename: Ulrike
authors.initials: U
authors.lastname: Heizmann
authors.forename: Daniel
authors.initials: D
authors.lastname: Böhringer
authors.forename: Yvonne
authors.initials: Y
authors.lastname: Kern
authors.forename: Thomas
authors.initials: T
authors.lastname: Reinhard
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D001082:Aqueous Humor / Q000737:chemistry / Q000276:immunology*; D003315:Cornea / Q000473:pathology / Q000601:surgery; D003316:Corneal Diseases / Q000473:pathology / Q000601:surgery; D005260:Female; D006084:Graft Rejection / Q000175:diagnosis* / Q000276:immunology / Q000378:metabolism; D006801:Humans; D007111:Immunity, Cellular; D007371:Interferon-gamma / Q000009:adverse effects* / Q000032:analysis / Q000276:immunology; D007376:Interleukin-2 / Q000032:analysis / Q000276:immunology*; D015847:Interleukin-4 / Q000009:adverse effects* / Q000032:analysis / Q000276:immunology; D015848:Interleukin-5 / Q000032:analysis / Q000276:immunology*; D015948:Keratoplasty, Penetrating; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D012307:Risk Factors
chemical_list: D007376:Interleukin-2; D015848:Interleukin-5; D015847:Interleukin-4; D007371:Interferon-gamma