Revisiting Genetic Influence on Mercury Exposure and Intoxication in Humans: A Scoping Review.
Maria Elena Crespo-LópezJean Ludger BarthelemyAmanda Lopes-AraújoLetícia Santos-SacramentoCaio Gustavo Leal-NazaréIsabela Soares-SilvaBarbarella Matos MacchiJosé Luiz M do NascimentoGabriela de Paula ArrifanoMarcus Augusto-OliveiraPublished in: Toxics (2023)
Human intoxication to mercury is a worldwide health problem. In addition to the type and length of exposure, the genetic background plays an important role in mercury poisoning. However, reviews on the genetic influence in mercury toxicity are scarce and not systematic. Therefore, this review aimed to systematically overview the most recent evidence on the genetic influence (using single nucleotide polymorphisms, SNPs) on human mercury poisoning. Three different databases (PubMed/Medline, Web of Science and Scopus) were searched, and 380 studies were found that were published from 2015 to 2022. After applying inclusion/exclusion criteria, 29 studies were selected and data on characteristics (year, country, profile of participants) and results (mercury biomarkers and quantitation, SNPs, main findings) were extracted and analyzed. The largest number of studies was performed in Brazil, mainly involving traditional populations of the Tapajós River basin. Most studies evaluated the influence of the SNPs related to genes of the glutathione system (GST, GPx, etc.), the ATP-binding cassette transporters and the metallothionein proteins. The recent findings regarding other SNPs, such as those of apolipoprotein E and brain-derived neurotrophic factor genes, are also highlighted. The importance of the exposure level is discussed considering the possible biphasic behavior of the genetic modulation phenomena that could explain some SNP associations. Overall, recommendations are provided for future studies based on the analysis obtained in this scoping review.
Keyphrases
- genome wide
- dna methylation
- copy number
- case control
- endothelial cells
- public health
- healthcare
- big data
- mental health
- randomized controlled trial
- gene expression
- machine learning
- ms ms
- climate change
- high resolution
- induced pluripotent stem cells
- transcription factor
- health information
- dna binding
- tandem mass spectrometry
- high performance liquid chromatography