Identification and Validation of Novel Biomarkers Related to the Calcium Metabolism Pathway in Hypertension Patients Based on Comprehensive Bioinformatics Methods
Background: Hypertension is a universal
risk factor for cardiovascular diseases and is thus the leading cause of death
worldwide. The identification of novel
prognostic and pathogenesis biomarkers plays a key role in disease management. Methods: The GSE145854 and
GSE164494 datasets were downloaded
from the Gene Expression Omnibus (GEO) database and used for screening and validating hypertension signature
genes, respectively. Gene Ontology (GO) enrichment analysis was
performed on the differentially expressed genes (DEGs) related to calcium ion
metabolism in patients with hypertension. The core genes related to immune
infiltration were analyzed and screened, and the activity of the signature
genes and related pathways was quantified using gene set enrichment analysis
(GSEA). The infiltration of immune cells in the blood samples was analyzed, and
the DEGs that were abnormally expressed in the clinical blood samples of
patients with hypertension were verified via RT-qPCR. Results: A total of 176 DEGs were screened. GO showed
that DEGs was involved in the regulation of calcium ion metabolism in biological processes (BP), actin mediated
cell contraction, negative regulation of cell movement, and calcium ion
transmembrane transport, and in the
regulation of protease activity in molecular functions (MF). KEGG analysis revealed that the DEGs were involved mainly in
the cGMP-PKG signaling pathway, ubiquitin-protein transferase, tight junction-associated proteins, and the
regulation of myocardial cells. MF analysis revealed theimmune infiltration function of the cells. RT-qPCR revealed that the expression of
References
[1]
Smereczańska, M., Domian, N., Młynarczyk, M., et al. (2023) Evaluation of the Expression and Localization of the Multifunctional Protein CacyBP/SIP and Elements of the MAPK Signaling Pathway in the Adrenal Glands of Rats with Primary and Secondary Hypertension. International Journal of Molecular Sciences, 25, Article No. 84. https://doi.org/10.3390/ijms25010084
[2]
Gharipour, M., Nezafati, P., Sadeghian, L., et al. (2022) Precision Medicine and Metabolic Syndrome. ARYA Atherosclerosis, 18, 1-10.
[3]
Buford, T. (2016) Hypertension and Aging. Aging Research Reviews, 26, 96-111. https://doi.org/10.1016/j.arr.2016.01.007
[4]
Zhou, D., Xi, B., Zhao, M., et al. (2018) Uncontrolled Hypertension Increases Risk of All-Cause and Cardiovascular Disease Mortality in US Adults: The NHANES III Linked Mortality Study. Scientific Reports, 8, Article No. 9418. https://doi.org/10.1038/s41598-018-27377-2
[5]
Deussen, A. and Kopaliani, I. (2023) Targeting Inflammation in Hypertension. Current Opinion in Nephrology and Hypertension, 32, 111-117. https://doi.org/10.1097/MNH.0000000000000862
[6]
Zhu, Y., Yang, X. and Zu, Y. (2022) Integrated Analysis of WGCNA and Machine Learning Identified Diagnostic Biomarkers in Dilated Cardiomyopathy with Heart Failure. Frontiers in Cell and Developmental Biology, 10, Article ID: 1089915. https://doi.org/10.3389/fcell.2022.1089915
[7]
Orlov, Y., Anashkina, A., Klimontov, V., et al. (2021) Medical Genetics, Genomics and Bioinformatics Aid in Understanding Molecular Mechanisms of Human Diseases. International Journal of Molecular Sciences, 22, Article No. 9962. https://doi.org/10.3390/ijms22189962
[8]
Picard, M., Scott-Boyer, M., Bodein, A., et al. (2021) Integration Strategies of Multiomics Data for Machine Learning Analysis. Computational and Structural Biotechnology Journal, 19, 3735-3746. https://doi.org/10.1016/j.csbj.2021.06.030
[9]
Zheng, T., Zheng, Z., Zhou, H., et al. (2023) The Multifaceted Roles of COL4A4 in Lung Adenocarcinoma: An Integrated Bioinformatics and Experimental Study. Computers in Biology and Medicine, 170, Article ID: 107896. https://doi.org/10.1016/j.compbiomed.2023.107896
[10]
Zhou, X., Chen, Y., Zhang, Z., et al. (2024) Identification of Differentially Expressed Genes, Signaling Pathways and Immune Infiltration in Postmenopausal Osteoporosis by Integrated Bioinformatics Analysis. Heliyon, 10, E23794. https://doi.org/10.1016/j.heliyon.2023.e23794
[11]
Klinik Für Innere Medizin III A E N, Universitätsklinikum Jena, Jena, Germany (2019) Recent Advances in Hypertension Research. Acta Physiologica (Oxford, England), 226, E13295.
[12]
Wei, Y., George, N., Chang, C., et al. (2017) Assessing Sex Differences in the Risk of Cardiovascular Disease and Mortality per Increment in Systolic Blood Pressure: A Systematic Review and Meta-Analysis of Follow-Up Studies in the United States. PLOS ONE, 12, E0170218. https://doi.org/10.1371/journal.pone.0170218
[13]
Eid, A., El-Yazbi, A., Zouein, F., et al. (2018) Inositol 1,4,5-Trisphosphate Receptors in Hypertension. Frontiers in Physiology, 9, Article No. 1018. https://doi.org/10.3389/fphys.2018.01018
[14]
Ma, J., Li, Y., Yang, X., et al. (2023) Signaling Pathways in Vascular Function and Hypertension: Molecular Mechanisms and Therapeutic Interventions. Signal Transduction and Targeted Therapy, 8, Article No. 168. https://doi.org/10.1038/s41392-023-01430-7
[15]
Pan, X., Shao, Y., Wu, F., et al. (2018) FGF21 Prevents Angiotensin II-Induced Hypertension and Vascular Dysfunction by Activation of ACE2/Angiotensin-(1-7) Axis in Mice. Cell Metabolism, 27, 1323-1337.E5. https://doi.org/10.1016/j.cmet.2018.04.002
[16]
Wilson, C., Zhang, X., Buckley, C., et al. (2019) Increased Vascular Contractility in Hypertension Results from Impaired Endothelial Calcium Signaling. Hypertension (Dallas, Tex: 1979), 74, 1200-1214. https://doi.org/10.1161/HYPERTENSIONAHA.119.13791
[17]
Zhang, Z., Zhao, L., Zhou, X., et al. (2022) Role of Inflammation, Immunity, and Oxidative Stress in Hypertension: New Insights and Potential Therapeutic Targets. Frontiers in Immunology, 13, Article ID: 1098725. https://doi.org/10.3389/fimmu.2022.1098725
[18]
Pioli, M. and De Faria, A. (2019) Pro-Inflammatory Cytokines and Resistant Hypertension: Potential for Novel Treatments? Current Hypertension Reports, 21, Article No. 95. https://doi.org/10.1007/s11906-019-1003-2
[19]
Teixeira, D., Peruchetti, D., Souza, M., et al. (2020) A High Salt Diet Induces Tubular Damage Associated with a Pro-Inflammatory and Pro-Fibrotic Response in a Hypertension-Independent Manner. Biochimica et Biophysica Acta Molecular Basis of Disease, 1866, Article ID: 165907. https://doi.org/10.1016/j.bbadis.2020.165907
[20]
Giorgi, C., Danese, A., Missiroli, S., et al. (2018) Calcium Dynamics as a Machine for Decoding Signals. Trends in Cell Biology, 28, 258-273. https://doi.org/10.1016/j.tcb.2018.01.002
[21]
Marchi, S., Giorgi, C., Galluzzi, L., et al. (2020) Ca Fluxes and Cancer. Molecular Cell, 78, 1055-1069. https://doi.org/10.1016/j.molcel.2020.04.017
[22]
Lei, M., Wu, L., Terrar, D., et al. (2018) Modernized Classification of Cardiac Antiarrhythmic Drugs. Circulation, 138, 1879-1896. https://doi.org/10.1161/CIRCULATIONAHA.118.035455
[23]
Tiscione, S., Casas, M., Horvath, J., et al. (2021) IP3R-Driven Increases in Mitochondrial Ca2+ Promote Neuronal Death in NPC Disease. Proceedings of the National Academy of Sciences of the United States of America, 118, e2110629118. https://doi.org/10.1073/pnas.2110629118
[24]
Cui, C., Merritt, R., Fu, L., et al. (2017) Targeting Calcium Signaling in Cancer Therapy. Acta Pharmaceutica Sinica B, 7, 3-17. https://doi.org/10.1016/j.apsb.2016.11.001
[25]
Stearman, R., Bui, Q., Speyer, G., et al. (2019) Systems Analysis of the Human Pulmonary Arterial Hypertension Lung Transcriptome. American Journal of Respiratory Cell and Molecular Biology, 60, 637-649. https://doi.org/10.1165/rcmb.2018-0368OC
[26]
Saygin, D., Tabib, T., Bittar, H., et al. (2020) Transcriptional Profiling of Lung Cell Populations in Idiopathic Pulmonary Arterial Hypertension. Pulmonary Circulation, 10, 1-15. https://doi.org/10.1177/2045894020908782
[27]
Rahman, M., Rana, H., Peng, S., et al. (2021) Bioinformatics and Machine Learning Methodologies to Identify the Effects of Central Nervous System Disorders on Glioblastoma Progression. Briefings in Bioinformatics, 22, bbaa365. https://doi.org/10.1093/bib/bbaa365
[28]
Rahman, M., Peng, S., Hu, X., et al. (2020) A Network-Based Bioinformatics Approach to Identify Molecular Biomarkers for Type 2 Diabetes That Are Linked to the Progression of Neurological Diseases. International Journal of Environmental Research and Public Health, 17, Article No. 1035. https://doi.org/10.3390/ijerph17031035
[29]
Lu, X., Wang, L., Lin, X., et al. (2015) Genome-Wide Association Study in Chinese Identifies Novel Loci for Blood Pressure and Hypertension. Human Molecular Genetics, 24, 865-874. https://doi.org/10.1093/hmg/ddu478
[30]
Stanton, A., Heydarpour, M., Williams, J., et al. (2023) CACNA1D Gene Polymorphisms Associate with Increased Blood Pressure and Salt Sensitivity of Blood Pressure in White Individuals. Hypertension (Dallas, Tex: 1979), 80, 2665-2673. https://doi.org/10.1161/HYPERTENSIONAHA.123.21229
[31]
Pande, J., Mallhi, K., Sawh, A., et al. (2006) Aortic Smooth Muscle and Endothelial Plasma Membrane Ca2+ Pump Isoforms Are Inhibited Differently by the Extracellular Inhibitor Caloxin 1b1. American Journal of Physiology Cell Physiology, 290, C1341-C1349. https://doi.org/10.1152/ajpcell.00573.2005
