Functional association analysis performed by ToppCluster based on pathway networks showing enriched terms from Gene Ontology and pathways.
The genes were selected based on their involvement in signal transduction pathway (socs2 and hnf4a) or because they are important components of the lipid metabolic process (hmgr, acox1, fasn, cpt1a, fbp, cs, ppara, and dgat).
Although we selected our candidate genes based on their involvement in known metabolic pathways thought to be important for the pathogenesis of nephropathy, thus hoping to enhance the probability of finding significant interactions, the rest of the modeling was performed without any intervention, with interactions selected on the basis of statistical and not physiologic criteria.
Based on their involvement in several signalling pathways (Forde & Dale, 2007), they are considered potential therapeutic targets for several diseases (Chico et al, 2009).
These genes were chosen based on their involvement in protein misfolding pathways (PFDN2, UCHL1 and PSMA7), the regulation of angiogenesis (VEGFA and SERPINE1), iron metabolism and neurotoxicity (CP) and antioxidant mechanisms (BBOX1).
Seventeen candidate genes were selected based on their involvement in the polyphenolic biosynthetic pathway (Additional File 3; Figure S2).
Most of these were identified based on involvement in neurobiological pathways relevant to substance abuse and were in part vetted by addiction neurobiologists (see Acknowledgments).
We chose to confirm the expression of seven of those genes by RT PCR, selecting these genes based on their involvement in well-described metabolic pathways.
As shown in Fig. 1a, we selected to target phenoloxidase gene based on its involvement in several essential steps in the melanin synthesis pathway [ 52, 60].
This is not surprising based on the involvement of ABA in response to plant stress, and its central role in other pathways, including dormancy in leaf [ 55- 57], bud [ 55, 58- 65] and seed (reviewed in [ 66- 68]).
