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Related Concept Videos

MicroRNAs01:22

MicroRNAs

MicroRNA (miRNA) are short, regulatory RNA transcribed from introns—non-coding regions of a gene—or intergenic regions—stretches of DNA present between genes. Several processing steps are required to form biologically active, mature miRNA. The initial transcript, called primary miRNA (pri-mRNA), base-pairs with itself forming a stem-loop structure. Within the nucleus, an endonuclease enzyme, called Drosha, shortens the stem-loop structure into hairpin-shaped pre-miRNA. After the pre-miRNA ends...
RNA Interference01:23

RNA Interference

RNA interference (RNAi) is a process in which a small non-coding RNA molecule blocks the post-transcriptional expression of a gene by binding to its messenger RNA (mRNA) and preventing the protein from being translated.
This process occurs naturally in cells, often through the activity of genomically-encoded microRNAs. Researchers can take advantage of this mechanism by introducing synthetic RNAs to deactivate specific genes for research or therapeutic purposes. For example, RNAi could be used...
MicroRNAs01:22

MicroRNAs

MicroRNA (miRNA) are short, regulatory RNA transcribed from introns—non-coding regions of a gene—or intergenic regions—stretches of DNA present between genes. Several processing steps are required to form biologically active, mature miRNA. The initial transcript, called primary miRNA (pri-mRNA), base-pairs with itself forming a stem-loop structure. Within the nucleus, an endonuclease enzyme, called Drosha, shortens the stem-loop structure into hairpin-shaped pre-miRNA. After the pre-miRNA ends...
siRNA - Small Interfering RNAs02:30

siRNA - Small Interfering RNAs

Small interfering RNAs, or siRNAs, are short regulatory RNA molecules that can silence genes post-transcriptionally, as well as the transcriptional level in some cases. siRNAs are important for protecting cells against viral infections and silencing transposable genetic elements.
In the cytoplasm, siRNA is processed from a double-stranded RNA, which comes from either endogenous DNA transcription or exogenous sources like a virus. This double-stranded RNA is then cleaved by the ATP-dependent...
MicroRNAs01:22

MicroRNAs

MicroRNA (miRNA) are short, regulatory RNA transcribed from introns (non-coding regions of a gene) or intergenic regions (stretches of DNA present between genes). Several processing steps are required to form biologically active, mature miRNA. The initial transcript, called primary miRNA (pri-mRNA), base-pairs with itself, forming a stem-loop structure. Within the nucleus, an endonuclease enzyme, called Drosha, shortens the stem-loop structure into hairpin-shaped pre-miRNA. After the pre-miRNA...
Nucleic Acid Structure01:25

Nucleic Acid Structure

The pentose sugar in DNA is deoxyribose, while in RNA the pentose sugar is ribose. The difference between the sugars is the presence of the hydroxyl group on the ribose's second carbon and a hydrogen on the deoxyribose's second carbon. The phosphate residue attaches to the hydroxyl group of the 5′ carbon of one sugar and the hydroxyl group of the 3′ carbon of the sugar of the next nucleotide, which forms  a 5′ to 3′ phosphodiester linkage.
DNA Structure
DNA has a double-helix structure. The...

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Circulating miRNAs and Machine Learning for Lateralizing Primary Aldosteronism.

Bálint Vékony1,2, Gábor Nyirő1,2,3, Zoltan Herold2

  • 1Department of Endocrinology (B.V., G.N., N.S., B.K.S., P.I.), Faculty of Medicine, Semmelweis University, Budapest, Hungary.

Hypertension (Dallas, Tex. : 1979)
|October 17, 2024
PubMed
Summary
This summary is machine-generated.

Circulating microRNAs (miRNAs) and machine learning can accurately distinguish unilateral from bilateral primary aldosteronism. This minimally invasive approach aids in early diagnosis and treatment of hypertension, bypassing invasive adrenal venous sampling.

Keywords:
deep learninghyperaldosteronismhypertensionmicroRNAs

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Area of Science:

  • Endocrinology
  • Genomics
  • Computational Biology

Background:

  • Primary aldosteronism is a significant cause of secondary hypertension, necessitating accurate differentiation between unilateral and bilateral forms for appropriate treatment.
  • Adrenal venous sampling, the current gold standard, presents challenges due to invasiveness and interpretation difficulties.
  • Exploring minimally invasive biomarkers like circulating microRNAs (miRNAs) is crucial for improving diagnostic strategies.

Purpose of the Study:

  • To investigate the efficacy of circulating miRNAs combined with machine learning in differentiating unilateral and bilateral primary aldosteronism.
  • To assess the feasibility of using peripheral blood samples for miRNA analysis, reducing the need for invasive procedures.
  • To develop a predictive model for accurate subtyping of primary aldosteronism.

Main Methods:

  • Plasma miRNA profiling was performed on primary aldosteronism patients using Illumina MiSeq.
  • Bioinformatics and machine learning identified candidate miRNAs for validation via quantitative PCR.
  • A deep learning model was employed for classification using both adrenal venous sampling and peripheral samples.

Main Results:

  • A 6-miRNA model achieved an area under the curve (AUC) of 87.1% for distinguishing unilateral primary aldosteronism.
  • Deep learning models demonstrated high accuracy, achieving 100% on a subset and 86.7% AUC on the full cohort of 108 patients.
  • Peripheral samples proved suitable for miRNA analysis, confirming the potential for a less invasive diagnostic approach.

Conclusions:

  • Machine learning analysis of circulating miRNAs provides a promising, minimally invasive alternative for primary aldosteronism lateralization.
  • This approach can expedite treatment initiation for bilateral adrenal hyperplasia by enabling early identification without further localization.
  • Utilizing circulating miRNAs offers significant benefits for both patients and healthcare providers in managing secondary hypertension.