Pharmaceuticals in the environment: histopathological effects of non-steroidal antiinflammatory drugs (NSAIDs) in fish

Pharmaceutical residues have been detected in the environment for several decades. Concerns that diclofenac, a commonly used non-steroidal anti-inflammatory drug (NSAID), could cause histopathological and other effects in aquatic organisms have triggered different regulatory initiatives. However, the scientific basis for understanding risks to fish is inconclusive with large discrepancies between studies. The aim of this thesis was to further evaluate the effects of NSAIDs, focusing on histopathological effects in the kidney and liver using the three-spined stickleback (Gasterosteus aculeatus) as a model organism. This was complemented by a review of reported histopathological effects in fish after exposure to NSAIDs or treated municipal wastewater.Two laboratory exposure studies showed that renal hematopoietic hyperplasia occurred after exposure to diclofenac already at the lowest tested concentration of 4.6 µg/L, but only at 299 µg/L or higher for naproxen. Mortality, decreased condition factor and jaw lesions were also observed, but only at high concentrations. In the review, few studies fulfilled the inclusion criteria, and the evidence for overlapping histopathological effects was weak. A third experimental study exposed sticklebacks to treated municipal wastewater using a matched experimental design to facilitate comparisons with previous NSAID studies. No overlapping histopathological or apical effects were detected, but the results highlighted the importance of including sex as a factor in the analysis.In conclusion, NSAIDs cause histopathological effects in fish, but only at concentrations rarely reported in the aquatic environment. Diclofenac is also more potent than naproxen. There is currently no clear evidence that NSAIDs cause histopathological effects in wild fish, although the possibility of more sensitive species or effects in other organs cannot be excluded. This thesis also highlights the importance of robust methodology and transparent data interpretation.