Tear Biomarkers in Alzheimer's and Parkinson's Diseases, and Multiple Sclerosis: Implications for Diagnosis (Systematic Review).
Angelika Król-GrzymałaEdyta Sienkiewicz-SzłapkaEwa FiedorowiczDominika RozmusAnna CieślińskaAndrzej E GrzybowskiPublished in: International journal of molecular sciences (2022)
Biological material is one of the most important aspects that allow for the correct diagnosis of the disease, and tears are an interesting subject of research because of the simplicity of collection, as the well as the relation to the components similar to other body fluids. In this review, biomarkers for Alzheimer's disease (AD), Parkinson's disease (PD), and multiple sclerosis (MS) in tears are investigated and analyzed. Records were obtained from the PubMed and Google Scholar databases in a timeline of 2015-2022. The keywords were: tear film/tear biochemistry/tear biomarkers + diseases (AD, PD, or MS). The recent original studies were analyzed, discussed, and biomarkers present in tears that can be used for the diagnosis and management of AD, PD, and MS diseases were shown. α-synTotal and α-synOligo, lactoferrin, norepinephrine, adrenaline, epinephrine, dopamine, α-2-macroglobulin, proteins involved in immune response, lipid metabolism and oxidative stress, apolipoprotein superfamily, and others were shown to be biomarkers in PD. For AD as potential biomarkers, there are: lipocalin-1, lysozyme-C, and lacritin, amyloid proteins, t-Tau, p-Tau; for MS there are: oligoclonal bands, lipids containing choline, free carnitine, acylcarnitines, and some amino acids. Information systematized in this review provides interesting data and new insight to help improve clinical outcomes for patients with neurodegenerative disorders.
Keyphrases
- multiple sclerosis
- mass spectrometry
- systematic review
- ms ms
- immune response
- oxidative stress
- rotator cuff
- healthcare
- meta analyses
- cognitive decline
- gold nanoparticles
- big data
- deep learning
- dna damage
- high resolution
- dendritic cells
- ischemia reperfusion injury
- toll like receptor
- social media
- health information
- genome wide identification