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Effects of pharmacologically targeting neuroimmune pathways on alcohol drinking in mice selectively bred to drink to intoxication.

BACKGROUND
Rodent models of high alcohol drinking offer opportunities to better understand factors for Alcohol Use Disorders (AUD) and test potential treatments. Selective breeding was carried out to create two unique High Drinking in the Dark (HDID-1, HDID-2) mouse lines that represent models of genetic risk for binge-like drinking. A number of studies have indicated that neuroimmune genes are important for regulation of alcohol drinking. We tested whether compounds shown to reduce drinking in other models also reduce alcohol intake in these unique genetic lines.


METHODS
We report tests of gabapentin, tesaglitazar, fenofibrate, caffeic acid phenethyl ester (CAPE), ibrutinib, and rolipram. Although these compounds have different mechanisms of action, they have all been shown to reduce inflammatory responses. We evaluated effects of these compounds on alcohol intake. In order to facilitate comparison with previously published findings for some compounds, we employed similar schedules that were previously used for that compound.


RESULTS
Gabapentin increased ethanol binge-like alcohol drinking in female HDID-1 and HS/NPT mice. Tesaglitazar and fenofibrate did not alter two bottle choice (2BC) drinking in male HDID-1 or HS/NPT mice. However, tesaglitazar had no effect on DID ethanol intake but reduced blood alcohol levels (BAL), and fenofibrate increased DID intake with no effects on BAL. CAPE had no effect on ethanol intake. Ibrutinib reduced intake in female HDID-1 in initial testing, but did not reduce intake in a second week of testing. Rolipram reduced DID intake and BALs in male and female HDID-1, HDID-2, and HS/NPT mice.


CONCLUSIONS
A number of compounds shown to reduce ethanol drinking in other models and genotypes are not effective in HDID mice, or their genetically heterogeneous founders, HS/NPT. The most promising compound was the PDE4 inhibitor, rolipram. These results highlight the importance of assessing generalizability when rigorously testing compounds for therapeutic development.