Glaucoma

Glaucoma is a progressive optic neuropathy characterized by structural damage to the optic nerve leading to blindness through loss of retinal ganglion cells. Risk factors in glaucoma include elevated intraocular pressure (IOP), age, race, family history, myopia, and diabetes. The growing body of evidence indicates there is a heightened risk of developing glaucoma among individuals with Alzheimer's disease [165-168]. The pathogenesis of the optic nerve neuropathy in glaucoma is a matter of debate. It is widely accepted that elevated IOP and a variety of factors may all contribute to primary insult of the optic nerve [169-171]. Cellular mechanisms involving vascular insufficiency [172, 173], vasospasm [174, 175], glutamate exitotoxicity [176], neurotoxic cytokine release [177, 178], abnormal metabolism, and autoimmune reaction have all been suggested [170]. There are numerous major factors contributing to the cumulative optic nerve insult and malnutrition in glaucoma (Fig. 4.4). Ultimately, glaucoma affects an estimated 70 million people worldwide, mostly 40 or older. This represents a fast growing market for pharmaceutical intervention because of the progressively aging population of the Western world. At present there are neither drugs on the market that address the disease mechanism or reliable molecular diagnostics for addressing susceptibility or severity. As is the case with many complex diseases, global gene expression profiling using microarrays is becoming an important powerful tool in glaucoma research.

Over the last 2 years, several groups studied differential gene expression in glaucomous human optic nerve head (ONH) astrocytes [179], monkey [180], and rat [181] disease models as well as response to corticoid hormones in different eye tissues [182,183] and the response in normal ONH astrocytes to high pressure (a key risk factor associated with glaucoma [184]). In the pioneering work of Hernandes et al. [179] the expression of genes in cultured human astrocytes from glaucomous and normal ONH astrocytes were compared using standard Affymetrix U95Av2 arrays consisting of over 12,000 genes. Approximately 1700 genes were differentially regulated in diseased astrocytes relative to normal ONHs. In 150 of these genes a 5-fold or higher

Intraocular

Intraocular

Abnormal Autoregulation

Figure 4.4 Some possible causes of initial insult to the optic nerve head in different glaucoma patients [171]. While increased intraocular pressure (IOP) is the most significant risk factor for glaucoma, RGCs cell death caused by optic nerve deformation may provide an explanation for a mechanical cause of glaucoma. While elevated IOP definitely plays a role in structural displacement of the ONH causing cytosceletal alteration, and loss of microtubules in RGC axons impedes retrograde axonal transport [258-260], it is conceivable that it also provides indirect insults via reduced blood flow and reactivation of microglia [178]. The role of vascular factors also is thought to be of significance to optic nerve and RGCs injury [172-175].

Abnormal Autoregulation

Figure 4.4 Some possible causes of initial insult to the optic nerve head in different glaucoma patients [171]. While increased intraocular pressure (IOP) is the most significant risk factor for glaucoma, RGCs cell death caused by optic nerve deformation may provide an explanation for a mechanical cause of glaucoma. While elevated IOP definitely plays a role in structural displacement of the ONH causing cytosceletal alteration, and loss of microtubules in RGC axons impedes retrograde axonal transport [258-260], it is conceivable that it also provides indirect insults via reduced blood flow and reactivation of microglia [178]. The role of vascular factors also is thought to be of significance to optic nerve and RGCs injury [172-175].

difference was noted, and these could be classified according to generic biological functions, including signal transduction, transcription, cell adhesion, proliferation, and metabolism. In the follow-up study [184], the same group interrogated the response of normal cultured astrocytes under increased hydrostatic pressure (HP) using the same molecular techniques and type of array. The expression of 596 genes was altered; 38 genes were upregulated and 24 downregulated over time with a threshold of 1.5 or higher. The 38 genes were also analyzed by hierarchical clustering analysis. The genes were of multiple cellular functions that were indicative of the systemic effect of high pressure on astrocytes. In two studies on animal models, glaucoma was induced in the retina of rat [181] and monkey [180] while differential expression was evaluated using total mRNA from whole retina as probes. The advantage of these models is that the genetic background is the same since one eye remains normal, and disease is induced in the other of the same animal. Sixty-two and 39 genes were differentially expressed in mild and severe glaucoma in monkey, respectively. In rat 81 genes were differentially expressed, although most were not the same genes. Finally, using dexamethasone the induction of gene expression was studied in cultured human trabecular meshwork (HTM) cells [183] and several other eye tissues [182]. Dexamethasone specifically induces expression of myocilin (TIGR/MYOC) gene in HTM cells and is linked to several types of glaucoma. When comparing these two studies, the results were neither consistent nor conclusive: 30 genes were upregulated over 2-fold in HTM-DEX cells in the Ishibashi study [183] while 249 genes were upregulated 4-fold or greater in the work of Lo et al. [182].

Microarray expression analysis in glaucoma has not as yet been used for subcategorizing different types of glaucoma, identifying prognostic gene lists for predicting disease outcome and response to treatment, or comparing human and animal studies. The approach of using enriched cell-type-specific primary cultures has been undertaken by Hernandez and co-authors [179], and this approach is likely the most promising since it uncovers the contribution of specific retina cell types in the development of neuropathy and allows the reconstruction of cell-specific alterations in molecular pathways implicated in the disease. We have compared the genes expressed in disease tissue (the endpoint of microarray analysis) from four recent studies in glaucoma and showed a lack of consistency between these different sample sets. Less than 5 percent of the genes were the same (on average) between any pair of experiments (Table 4.1). This lack of consistency in genes identified was somewhat surprising since the disease pathologies appear similar among monkey, rat, and human and because these species share about 99 percent of the same genes. Even more surprising is the inconsistency between expression in normal human astrocytes under high pressure (believed to be the key risk factor in glaucoma) and glaucomatous astrocytes. Since high pressure is believed to be a key risk factor for glaucoma or, at least, lead to the induction of glaucoma, a higher percentage of common genes were expected. These conclusions are based upon signature molecular profiles found when comparing between individuals for other diseases such as in breast cancer [130]. Although there are several potential reasons for such inconsistencies, the major problem is the application of analytical methods to tissues from different genetic backgrounds with different (and uncontrolled) environmental conditions.

We have performed a comprehensive computational gene network analysis of microarray expression in human glaucoma using these previously published data sets [179]. The raw expression data on about 1700 genes differentially regulated in glaucoma astrocytes from 4 glaucoma patients and 4 age-matched normal individuals was loaded in MetaCore. After data normalization and processing, multiple networks were then built using different algorithms and expression threshold ratios. One of many networks is presented on Figure 4.5. The threshold ratio of 2.5 and higher was set up for this network before we applied the stringent algorithm called immediate interactions. This algorithm allows the connection of only proteins (presented as coding genes), which are: (1) experimentally shown to physically interact pairwise and (2) being over- or underexpressed above the threshold ratio. The pathways are highlighted in Figure 4.5 as solid lines.

TABLE 4.1 Overlap Between Sets of Glaucoma-Relevant Differentially Expressed Genes from Recent Studies

Hydrostatic (1.5-fold) [261]

Monkey Retina, Mild Glaucoma (1.5-fold) [180]

Monkey Retina, Severe Glaucoma (1.5-fold) [180]

Hydrostatic (1.5-fold) [261]

Monkey retina, mild glaucoma (1.5-fold) [180]

Monkey retina, severe glaucoma (1.5-fold) [180]

CDC42, FOS, VEGFC, Clusterin, HF1, Clq, C5, BMP4

Was this article helpful?

0 0

Post a comment