ArticleMolecular neurobiology2021
A Genome-Wide Study of Single-Nucleotide Polymorphisms in MicroRNAs and Further In Silico Analysis Reveals Their Putative Role in Susceptibility to Late-Onset Alzheimer's Disease.
Article in Molecular neurobiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- Association of rs2910164 in miR-146a with type 2 diabetes mellitus: A case-control and meta-analysis study.Frontiers in endocrinology · 2022Pooled it
- The promise of microRNA-based therapies in Alzheimer's disease: challenges and perspectives.Molecular neurodegeneration · 2021Review
- Diagnostic and therapeutic potential of exosomal miRNAs in Alzheimer's disease.Neural regeneration research · 2021Article
- Interplay of RNA-Binding Proteins and microRNAs in Neurodegenerative Diseases.International journal of molecular sciences · 2021Review
- Identification of miRNA-Target Gene Pairs in the Parietal and Frontal Lobes of the Brain in Patients with Alzheimer's Disease Using Bioinformatic Analyses.Neurochemical research · 2021Article
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
Late-onset Alzheimer's disease (LOAD) is a neurodegenerative disorder of growing relevance in an aging society for which predictive biomarkers are needed. Many genes involved in LOAD are tightly controlled by microRNAs (miRNAs), which can be modulated by single-nucleotide polymorphisms (SNPs). Our aim was to determine the association between SNPs in miRNAs and LOAD. We selected all SNPs in pre-miRNAs with a minor allele frequency (MAF) > 1% and genotyped them in a cohort of 229 individuals diagnosed with LOAD and 237 unrelated healthy controls. In silico analyses were performed to predict the effect of SNPs on miRNA stability and detect downstream pathways. Four SNPs were associated with LOAD risk with a p value < 0.01 (rs74704964 in hsa-miR-518d, rs71363366 in hsa-miR-1283-2, rs11983381 in hsa-miR-4653, and rs10934682 in hsa-miR-544b). In silico analyses support a possible functional effect of those SNPs in miRNA levels and in the regulation of pathways of relevance for the development of LOAD. Although the results are promising, additional studies are needed to validate the association between SNPs in miRNAs and the risk of developing LOAD. Graphical abstract.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.