Assessing the Impact of Nanoplastics in Biological Systems: Systematic Review of In Vitro Animal Studies

Nanoplastic (NP) pollution has emerged as a growing concern due to its potential impact on human health, although its adverse effects on different organ systems are not yet fully understood. This systematic scoping review, conducted in accordance with international guidelines, aimed to map the current evidence on the biological effects of NPs. In vitro animal studies assessing cellular damage caused by exposure to any type of NP were searched on PubMed, Web of Science, and Scopus. Data on primary outcomes related to genotoxicity and cytotoxicity (cell viability, oxidative stress, inflammation, DNA and cytoplasmic damage, apoptosis) were extracted from the included studies, and overall reporting quality was assessed. A total of 108 articles published between 2018 and 2024, mostly by China (54%), Spain (14%), and Italy (9%), were included. Polystyrene (PS) was the most frequently studied polymer (85%). NP sizes in solution ranged from 15 to 531 nm, with a higher prevalence in the 40-100 nm range (38%). The overall quality of studies was rated as moderate (60%), with many lacking essential details about cell culture conditions (e.g., pH of the medium, passage number, substances used). A higher frequency of negative effects from NP exposure was observed in respiratory cell lines, while immune, digestive, and hepatic cell lines showed greater resistance. Nervous, urinary, and connective tissue systems were impacted by NPs. Positively charged and smaller PS particles were consistently associated with higher toxicity across all systems. In summary, this review highlights the multifactorial nature of NP toxicity, influenced by size, surface charge, and polymer type. It also reveals a significant knowledge gap, stemming from the predominant use of immortalized monocultures exposed to commercially available PS NPs, the limited use of environmentally relevant particles, and the underutilization of advanced experimental models (e.g., organ-on-chip systems) that better mimic physiological conditions.