Serum proteomic analysis during nicotine self-administration, withdrawal, extinction and relapse in rats.

Nicotine dependence is known to induce long-term neural adaptations in brain. The purpose of this study was to verify whether specific protein patterns related to nicotine dependence states could also be detected in a peripheral tissue. With this aim, a proteomic analysis was carried out in rat serum to compare simultaneously a large number of proteins. Rats were trained to learn nicotine self-administration (n 6; 0.03 mg/kg/infusion) and serum was taken repeatedly from the same animals at six time-points in distinct phases related to nicotine dependence. At time-point N (Naive), blood was collected before starting nicotine administration; time-point P (Priming) was the first self-administration session; at time-point S (Self administration) animals had been self-administering nicotine for 10 days; at time-point W (Withdrawal) access to nicotine was removed; time-point E (Extinction) was the fourth extinction session; at time-point R (Relapse) nicotine was available again (0.015mg/kg i.v.). Serum proteins were analysed by 2D electrophoresis, focussing them at the isoelectric point on non-linear immobilised 3 10 pH gradient strips followed by molecular mass discrimination on polyacrylamide gradient gels. Each sample was loaded on two gels, thus obtaining 72 maps with 206±52 spots (ave±stdev). Image analysis was performed by PDQuest software (Bio-Rad) on SyproRuby stained maps to match proteins amongst gels. The spot volume (optical densities*area) values were submitted to statistical analyses. The animal effect was removed by introducing an additive offset to increase the sensitivity of the statistical analysis. In order to reduce the dataset complexity, a filtering strategy was applied with an ANOVA F-test (10% cutoff) to select out only the most strongly responding points. A multivariate approach was then performed to further reduce the corresponding signals to a few simple summaries. Principal component analysis showed that separations could be revealed, therefore additional analyses were undertaken on selected pair wise comparisons. In comparisons: N versus S; S versus W; E versus R; S versus R; and S versus E a clear separation between the two compared groups could be observed, thus signifying that each dependence state correlates with a protein expression pattern in serum. To single out which selections of proteins best explained the contrasts, partial least squares discriminant analysis was adopted, allowing the computation of Variance Importance Coefficients to rank proteins by the contribution to the overall separation. The spots with highest ranking were identified by comparison with a published rat serum standard map (http://linux.farma.unimi.it/RSPSG/2D/index.html). Selected proteins were further analysed with a repeated-measure ANOVA test. Among them, C reactive protein and hemopexin displayed a statistically significant reduction after nicotine administration, which was maintained throughout the administration paradigm. Two hemopexin isoforms and another unidentified protein showed a minimum value in the self-administration state. Thiostatin displayed a specific increase in the extinction phase. This study showed that specific protein patterns related to the nicotine dependence states exist in peripheral tissues and can be detected with proteomic tools followed by statistical analyses. Further development of this approach may provide robust diagnostic methods to assess dependence states of drug-taking individuals