A Bayesian approach to investigating presumed retinal micro(nano)plastics

The human retina, a highly vascularized, metabolically active, and immunologically privileged neural tissue, stands in contrast to the ubiquity of micro(nano)plastics (MNPs), which have been reported in every other organ system. Despite this, the presence of MNPs in the retina remains undocumented, a critical gap given their potential to contribute to local inflammation, microvascular occlusion, or act as cofactors in diseases such as diabetic retinopathy, age-related macular degeneration, or uveitis. Furthermore, the diverse physicochemical properties of MNPs – including their varying sizes, shapes, colors, and optical characteristics – raise the intriguing possibility that their presence within the retina could mimic commonly observed ophthalmic features. I hypothesize that certain features—previously attributed to other causes—such as tiny discrete foci in fundus photography and hyperreflective retinal foci in optical coherence tomography, may actually contain MNPs. This hypothesis carries significant biological implications not only for ophthalmology but also for environmental toxicology and public health. To formally evaluate its plausibility, I constructed a Bayesian model incorporating initial skepticism and considering varying likelihoods of observed evidence under both null and alternative assumptions. The model demonstrates that even with an extremely low prior probability, the reproducibility and discernible patterns of certain imaging findings can justify a significantly increased posterior belief, thus warranting further scientific inquiry. This work offers a probabilistic framework to re-evaluate retinal anomalies and encourages empirical investigation in environmental ophthalmology, without definitively proving MNP presence. The development of retinal imaging techniques for the specific detection of MNPs could provide a valuable tool for environmental toxicology, preventive medicine, and public health by offering a non-invasive biomarker for systemic MNPs exposure.