Microarrays promise much in elucidating the pathogenesis of complex diseases such as PD but the lack of concordance in published data sets to date certainly questions their relevance. Here we have shown that a standardised approach to analysing PD-related microarray data can account for a considerable proportion of the discordance. We used a common analytical approach which improved data convergence and uncovered new leads for PD pathogenesis. We also recognised a potential anatomical bias in the datasets derived from brain regions with high neuronal loss. Our approach therefore provided an improved comparative analysis between existing datasets and further considered ‘tissue-of-origin’ effects.
Pathway analysis may uncover concordance between datasets not found in gene lists
Complex phenotypes, by their very nature, are aetiologically heterogeneous. This implies that single gene signatures may not be shared by all affected individuals. However, the identification of particularly relevant genetic pathways, have a higher probability of being revealed as convergent across multiple individuals and multiple studies than individual genes per se. Moreover, the differences reflected in a pathway or network of genes may be robust enough to overcome the effects of experimental noise and inter-study variability prone to bias single gene expression values. Therefore, this approach results in an increase in sensitivity to detect interesting and novel patterns in gene expression between multiple samples of cases and controls.
Common data analysis highlights dopamine signaling pathway in SN
Context is very important in gene expression studies and as expected the analysis of SN tissue-derived data sets further improved our concordance and highlighted the ‘dopamine receptor signaling’ pathway. However rather than representing a primary pathogenic effect the extensive down regulation of genes such as DOPA decarboxylase (DDC), dopamine receptor 2 (DRD2), dopamine transporter (SLC6A3 or DAT) and tyrosine hydroxylase (TH) was probably entirely due to a disproportionate number of SN dopaminergic neurons between cases and controls. On a positive note, the microarray data was providing accurate molecular fingerprints of the comparative tissue being examined; a modern pixelated analogy to the histological section. However the relative neuronal loss in the SN also reduced our signal to noise ratio for pathogenic relevance.
Accordingly we pursued two alternative approaches to maximise potentially useful information on the underlying biological processes. First, the implementation of a correction factor for dopaminergic neuronal loss in the SN data sets and second, the analysis of non-SN or unaffected tissues for data convergence. The purpose of the correction factor was not to magically recreate the early disease landscape but to remove ‘red herrings’ that solely reflected the relative numbers of neurons between cases and controls. The retention of genes differentially regulated in the residual dopaminergic neuron data set should have improved the overall specificity of this approach.
Following our ‘neuronal loss’ correction, two alternative pathways gained prominence: ephrin receptor signaling and the axonal guidance pathway. The latter is consistent with the findings of recent studies 
including one that combined gene expression data with genotype data from two genome-wide association studies 
. There is actually considerable overlap between the axon guidance and ephrin signaling pathways with ephrins along with netrins, slits and semaphorins being the main families of guidance molecules in the developing nervous system 
. It remains to be clarified whether the differential expression of axon guidance genes in PD represent neurodevelopmental manifestations, compensatory attempts at rewiring, or dysregulated expression patterns induced by a devastated environment.
As discussed above microarray data is very powerful in illustrating cytoarchitectural differences between cases and controls such as dopaminergic neuron loss. Given the considerable literature supporting the involvement of glia in PD pathogenesis 
we might have expected glial markers to inversely differentiated in the SN data sets. The absence of significant fold changes in activated microglial markers in particular argues against a substantial glial component to neurodegeneration in the terminal PD brain.
Growth factor signaling pathways are prominent in non-SN tissues
The distinct gene expression pattern of brain areas that are not overtly affected by PD pathology may be less confounded than the SN with respect to the cell death associated with PD. It could be argued that the transcriptomes of unaffected tissues might be too divergent from those of predilection sites such as the SN, such that they provide very little informative data. Our analysis, which has highlighted consistent differences in growth-factor signaling in non-SN datasets, argues that areas affected late in the disease, such as the prefrontal cortex 
could at the time of post mortem exhibit similar mechanisms of degeneration as initially occurred in the SN. Our approach highlights the differential expression of IGF-1 and VEGF signaling pathways. Importantly the IGF1 signaling pathway was also over-represented in two ‘corrected’ SN datasets ().
This pathway has been largely unexamined for associations with PD although IGF1 signaling is reported to have neuroprotective effects on dopaminergic neurons 
and it has recently been suggested that excessive IGF1 signaling accelerates ageing through deleteriously effects on protective mechanisms against proteotoxicity such as Lewy body formation in PD 
. Furthermore we have recently showed that a polymorphism in the 3′ untranslated region of the IGF2 gene, a homologue of IGF1
was protective against PD 
Similarly VEGF is known to promote the growth and survival of dopaminergic neurons 
Interestingly both IGF1 and insulin enhance VEGF expression in vitro 
providing a plausible mechanism that might underlie the co-prominence of these signaling pathways in our re-analysis.
Challenges and Future Directions
Case-control expression analysis in a degenerative disease like PD poses difficult issues when attempting to uncover pathways contributing to disease initiation. It would be advantageous to target tissues that express the proteins that are fundamental to the disease process and are different in individuals who are at risk of the disease. At the same time we need to account for any influences of the pathological process on these profiles. Microarray data of predilection sites such as the SN illustrates cytoarchitectural differences between cases and controls but to understand some of the early pathogenic processes, we would ideally want to assay a brain region very similar to SN but that is only belatedly affected.
An additional consideration is the ability of the pathway approach, used in our analyses, to provide adequate specificity for PD over other neurodegenerative conditions. This issue remains to be clarified, and requires further investigation. It is important to recognise that there may be genetic expression patterns common to neurodegenerative diseases, generally. These may reflect common pathological changes (such as cell death, markers of oxidative stress or neuro-inflammation etc) or shared risk factors influencing neurodegeneration.
There are still inherent difficulties in obtaining reproducible gene expression data from post mortem brain, even if an optimal region of the brain could be assayed 
. Furthermore this information can only be used retrospectively for the potential benefit of future PD patients. Therefore there is considerable interest in developing strategies to obtain human RNA from more accessible sources such as blood or neuronal-like cell lines. The finding of down regulation of α-synuclein in microarray analysis of whole blood samples from PD patients versus controls is exciting because it implies that PD-specific changes can be found ante mortem
in readily accessible tissues 
. It is also of note that these tissues also revealed differential expression of the VEGF signaling pathway (observed in other non-SN tissue samples). However, there is a real risk that peripheral tissues, such as whole blood examined here, may express few proteins fundamental to the disease process and therefore be of limited ability to demonstrate case - control differences relevant to nervous system disorders 
. The lack of available gene expression data from multiple tissues in PD patients at various stages of the disease prevents such an analysis but highlights the need for ongoing research efforts in this area.
Interestingly one peripherally accessible neural tissue, the olfactory mucosa, has been used to demonstrate significant differences in functional assays and gene expression between schizophrenics, bipolar affective disorder and controls 
. Such cells from PD patients and controls may yet provide an opportunity to interrogate neuronal mechanisms without relying on post mortem tissue 
In this paper we have presented a summary of the available microarray data from PD case-control studies and have suggested some potential strategies for uncovering primary pathogenic mechanisms. For others who wish to use and explore these data we have constructed an online database which enables rapid evaluation on a single gene or pathway basis.