Alzheimer's Disease Associated Presenilin 1 and 2 Genes Dysregulation in Neonatal Lymphocytes Following Perinatal Asphyxia.
Agata TarkowskaWanda Furmaga-JabłońskaJacek BoguckiJanusz KockiRyszard PlutaPublished in: International journal of molecular sciences (2021)
Perinatal asphyxia is mainly a brain disease leading to the development of neurodegeneration, in which a number of peripheral lesions have been identified; however, little is known about the expression of key genes involved in amyloid production by peripheral cells, such as lymphocytes, during the development of hypoxic-ischemic encephalopathy. We analyzed the gene expression of the amyloid protein precursor, β-secretase, presenilin 1 and 2 and hypoxia-inducible factor 1-α by RT-PCR in the lymphocytes of post-asphyxia and control neonates. In all examined periods after asphyxia, decreased expression of the genes of the amyloid protein precursor, β-secretase and hypoxia-inducible factor 1-α was noted in lymphocytes. Conversely, expression of presenilin 1 and 2 genes decreased on days 1-7 and 8-14 but increased after survival for more than 15 days. We believe that the expression of presenilin genes in lymphocytes could be a potential biomarker to determine the severity of the post-asphyxia neurodegeneration or to identify the underlying factors for brain neurodegeneration and get information about the time they occurred. This appears to be the first worldwide data on the role of the presenilin 1 and 2 genes associated with Alzheimer's disease in the dysregulation of neonatal lymphocytes after perinatal asphyxia.
Keyphrases
- poor prognosis
- peripheral blood
- gene expression
- binding protein
- genome wide
- pregnant women
- long non coding rna
- bioinformatics analysis
- dna methylation
- induced apoptosis
- white matter
- resting state
- machine learning
- healthcare
- functional connectivity
- protein protein
- multiple sclerosis
- genome wide analysis
- deep learning
- artificial intelligence
- endoplasmic reticulum stress
- cell proliferation
- cell death
- big data
- transcription factor
- data analysis