Conjunctival inflammatory gene expression profiling in dry eye disease: Correlations with HLA-DRA and HLA-DRB1

Abstract

Purpose: In several multicenter clinical trials, HLA-DR was found to be a potential biomarker of dry eye disease (DED)'s severity and prognosis. Given the fact that HLA-DR receptor is a heterodimer consisting in an alpha and a beta chain, we intended to investigate the correlation of inflammatory targets with the corresponding transcripts, HLA-DRA and HLA-DRB1, to characterize specific targets closely related to HLA-DR expressed in conjunctival cells from patients suffering from DED of various etiologies. Methods: A prospective study was conducted in 88 patients with different forms of DED. Ocular symptom scores, ocular-staining grades, tear breakup time (TBUT) and Schirmer test were evaluated. Superficial conjunctival cells were collected by impression cytology and total RNAs were extracted for analyses using the new NanoString® nCounter technology based on an inflammatory human code set containing 249 inflammatory genes. Results: Two hundred transcripts were reliably detected in conjunctival specimens at various levels ranging from 1 to 222,546 RNA copies. Overall, from the 88 samples, 21 target genes showed a highly significant correlation (R > 0.8) with HLA-DRA and HLA-DRB1, HLA-DRA and B1 presenting the highest correlation (R = 0.9). These selected targets belonged to eight family groups, namely interferon and interferon-stimulated genes, tumor necrosis factor superfamily and related factors, Toll-like receptors and related factors, complement system factors, chemokines/cytokines, the RIPK enzyme family, and transduction signals such as the STAT and MAPK families. Conclusions: We have identified a profile of 21 transcripts correlated with HLA-DR expression, suggesting closely regulated signaling pathways and possible direct or indirect interactions between them. The NanoString® nCounter technology in conjunctival imprints could constitute a reliable tool in the future for wider screening of inflammatory biomarkers in DED, usable in very small samples. Broader combinations of biomarkers associated with HLA-DR could be analyzed to develop new diagnostic approaches, identify tighter pathophysiological gene signatures and personalize DED therapies more efficiently.