Year: 2025
Type: article
Abstract: Viral and chemical analyses were performed on 80 dead cats and 51 dead dogs from the Campania Region (Southern Italy), with the aim of evaluating in vivo the potential correlation between coronavirus (CoV) infections and levels of environmental pollutants such as dioxins and PCSs (PCDD/F, DL-PCB and NDL-PCB). The overall viral prevalence was 16.3% in cats and 23.5% in dogs. Both feline coronavirus (FCoV) and canine coronavirus (CCoV) were identified, with variable detection rates in all the other organs investigated, supporting studies that provide evidence of systemic viral spread. The highest prevalence of coronaviruses (CoVs) was observed in Naples (19.2% for FCoV; 30.7% for CCoV) and Caserta (11.1% for FCoV; 50.0% for CCoV), areas that include municipalities with the highest Municipality Index of Environmental Pressure (MIEP) scores. Chemical analyses showed that DL-PCBs were present at more elevated concentrations in CoV-infected dogs and cats than in non-infected animals, whereas ∑NDL-PCB and ∑PCDD/F were detected in greater amounts in non-infected subjects. Among PCDDs, the congener 2,3,7,8-TCDD displayed different distribution patterns between infected and non-infected animals. In cats, 70.0% of FCoV-positive individuals had 2,3,7,8-TCDD levels above the limit of quantification (LOQ), compared with 38.0% of FCoV-negative cats. In dogs, 78.0% of CCoV-infected animals exceeded the LOQ, compared with 20.0% of non-infected ones; this difference was statistically significant. The results of the study suggest that elevated levels of 2,3,7,8-TCDD may be associated with CCoV infection and replication in dogs, suggesting a possible relationship between environmental pollution and susceptibility to coronavirus infections.
Source: Viruses
DOI: 10.3390/v17091271
Language: English
Subfield: Health, Toxicology and Mutagenesis
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,137
Funder: Ministero della Salute
Award: G2384231202
OpenAlex ID: W4414353394
