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Published on: October 26, 2017
Identification of miRNA biomarkers for essential hypertension in small samples based on MPGAM
Zongjin Li1, Dongmei Liu1, YongChao Jin1
1Hebei Provincial Key Laboratory for Data Science and Application, College of Science, North China University of Science and Technology, Tangshan, 063210, China.
Abstract:
Essential hypertension (EH) is one of the most widespread chronic diseases globally, with a multifactorial etiology. MicroRNAs (miRNAs) are key regulators in the development and progression of EH and hold great promise as biomarkers. However, reliably identifying EH-related miRNA biomarkers in small-sample datasets remains challenging. To address these limitations, we propose a novel computational framework, the Modular Probability-driven Global Analytical Method (MPGAM), tailored for biomarker discovery in small-sample settings. MPGAM integrates three key innovations: (1) the Dual-Index Nearest Neighbor Similarity Measure (DINNSM), which captures local similarity structures more accurately than conventional correlation-based methods; (2) a multi-dimensional module evaluation strategy that incorporates gene significance, module membership, and known hypertension-associated miRNAs; and (3) a Probability-based Global Sorting Method (PGSM), which ranks miRNAs across modules based on probabilistic enrichment. Using the GSE75670 dataset from the GEO database, MPGAM identified ten candidate miRNA biomarkers. In this study, identification refers to the data-driven selection of miRNAs that exhibit potential associations with EH. These may include both previously reported EH-related miRNAs and novel candidates that have not been documented in existing literature. Among these, eight have been previously reported to be associated with blood pressure, including four (hsa-miR-107, hsa-miR-210, hsa-miR-665, and hsa-miR-449a) cited in more than five independent studies. Target gene interaction analysis further suggests that these miRNAs may exert coordinated regulatory effects on EH-related pathways. Compared to existing methods, MPGAM demonstrated greater effectiveness in miRNA biomarker identification and offers an interpretable approach.
Insights
A new computational method, MPGAM, effectively identifies microRNA biomarkers for essential hypertension in small datasets. This approach aids in discovering novel diagnostic and therapeutic targets for this widespread chronic disease.
Area of Science:
- Biochemistry and Molecular Biology
- Genetics and Genomics
- Computational Biology
Background:
- Essential hypertension (EH) is a prevalent global chronic disease with complex causes.
- MicroRNAs (miRNAs) are crucial in EH development and progression, showing potential as biomarkers.
- Identifying reliable miRNA biomarkers in small datasets for EH is a significant challenge.
Purpose of the Study:
- To introduce a novel computational framework, MPGAM, for effective miRNA biomarker discovery in small-sample settings for EH.
- To address limitations of existing methods in identifying EH-related miRNA biomarkers.
- To identify and validate candidate miRNA biomarkers associated with essential hypertension.
Main Methods:
- Developed the Modular Probability-driven Global Analytical Method (MPGAM) incorporating Dual-Index Nearest Neighbor Similarity Measure (DINNSM), multi-dimensional module evaluation, and Probability-based Global Sorting Method (PGSM).
- Applied MPGAM to the GSE75670 dataset from the GEO database for miRNA biomarker identification.
- Conducted target gene interaction analysis to explore regulatory pathways of identified miRNAs.
Main Results:
- MPGAM identified ten candidate miRNA biomarkers for EH from the GSE75670 dataset.
- Eight of the identified miRNAs have prior associations with blood pressure, with four (hsa-miR-107, hsa-miR-210, hsa-miR-665, hsa-miR-449a) appearing in over five studies.
- Target gene analysis indicated coordinated regulatory effects of these miRNAs on EH-related pathways.
Conclusions:
- MPGAM offers a novel, effective, and interpretable computational approach for miRNA biomarker discovery in small-sample settings.
- The identified candidate miRNAs, including novel ones, warrant further investigation as potential biomarkers for essential hypertension.
- The study highlights the potential of MPGAM in advancing biomarker discovery for complex diseases like EH.
