Identifikasi Gen Pengatur Sentral pada Stroke Iskemik Menggunakan Pendekatan Berbasis Jaringan

Identification of Central Regulatory Genes in Ischemic Stroke Using a Network-Based Approach

Authors

DOI:

https://doi.org/10.30872/

Keywords:

Stroke iskemik, bioinformatika, gen pengatur sentral

Abstract

Stroke iskemik merupakan salah satu penyebab utama kematian dan disabilitas jangka panjang di dunia, dengan mekanisme patogenesis yang kompleks melibatkan proses inflamasi, respons imun, dan stres seluler. Penelitian ini bertujuan untuk mengidentifikasi gen pengatur sentral yang berperan dalam stroke iskemik menggunakan pendekatan bioinformatika berbasis jaringan. Data ekspresi gen diperoleh dari basis data publik dan dianalisis untuk mengidentifikasi differentially expressed genes (DEGs) dengan kriteria adjusted p-value < 0,05 dan |log2 fold change| ≥ 1. Analisis pengayaan fungsional dilakukan menggunakan Gene Ontology (GO) dan Kyoto Encyclopedia of Genes and Genomes (KEGG). Selanjutnya, jaringan protein–protein interaction (PPI) dikonstruksi dan dianalisis untuk mengidentifikasi gen hub berdasarkan topologi jaringan. Hasil analisis menunjukkan sebanyak 312 DEGs, yang didominasi oleh gen yang terlibat dalam jalur inflamasi dan imun, seperti cytokine signaling dan NF-κB signaling. Analisis jaringan mengidentifikasi gen pengatur sentral, termasuk TNF, STAT3, IL6, CXCL8, dan TYROBP, yang memiliki tingkat konektivitas tinggi. Temuan ini memberikan wawasan mengenai mekanisme molekuler stroke iskemik serta potensi biomarker dan target terapi, meskipun diperlukan validasi eksperimental lebih lanjut.

References

[1] D. Majumder, “Ischemic Stroke: Pathophysiology and Evolving Treatment Approaches,” Neurosci. Insights, vol. 19, pp. 1–8, Oct. 2024, doi: 10.1177/26331055241292600.

[2] M. A. Salaudeen, N. Bello, R. N. Danraka, and M. L. Ammani, “Understanding the Pathophysiology of Ischemic Stroke: The Basis of Current Therapies and Opportunity for New Ones,” Biomolecules, vol. 14, no. 3, pp. 1–23, Mar. 2024, doi: 10.3390/biom14030305.

[3] I. Pranandi and Z. Arieselia, “Integrative Transcriptomic Profiling of Human Neural Tissues Reveals Core Molecular Signatures of Neurodegeneration,” Journal of Natural Science Research and Review, vol. 2, no. 2, pp. 62–66, Feb. 2026, doi: 10.65150/EP-jnsrr/V2E2/2026-02.

[4] S. Rehman et al., “Molecular Mechanisms of Ischemic Stroke: A Review Integrating Clinical Imaging and Therapeutic Perspectives,” Biomedicines, vol. 12, no. 4, pp. 1–26, Apr. 2024, doi: 10.3390/biomedicines12040812.

[5] C. D. Maida, R. L. Norrito, S. Rizzica, M. Mazzola, E. R. Scarantino, and A. Tuttolomondo, “Molecular Pathogenesis of Ischemic and Hemorrhagic Strokes: Background and Therapeutic Approaches,” Int. J. Mol. Sci., vol. 25, no. 12, pp. 1–35, Jun. 2024, doi: 10.3390/ijms25126297.

[6] W. William, N. Sudiyono, and I. Pranandi, “Artificial Intelligence in Circadian Physiology: Predicting Biochemical and Hormonal Rhythms in Health and Disease,” Journal of Biomedical Advancement Scientific Research, vol. 1, no. 3, pp. 1–14, Nov. 2025, doi: 10.63721/25JBASR0126.

[7] S. Clarina, F. M. Siswanto, I. Pranandi, M. D. N. Handayani, R. Dewi, and R. Regina, “Identification Of Mir-103a/PLEKHA1 Pair As Candidate Biomarkers And Therapeutic Targets For Skin Aging By Bioinformatics Analysis,” Frontiers in Health Informatics, vol. 14, no. 2, pp. 2245–2254, May 2025, [Online]. Available: https://healthinformaticsjournal.com/index.php/IJMI/article/view/2495

[8] H. Wang et al., “Identification of central regulators related to residual feed intake in Huainan chickens based on weighted gene co-expression network analysis,” Poult. Sci., vol. 105, no. 5, pp. 1–8, Feb. 2026, doi: 10.1016/j.psj.2026.106687.

[9] “Gene Expression Omnibus.” Accessed: Mar. 10, 2026. [Online]. Available: https://www.ncbi.nlm.nih.gov/geo/

[10] H. Yin et al., “Unlocking biological insights from differentially expressed genes: Concepts, methods, and future perspectives,” J. Adv. Res., vol. 76, pp. 135–157, Oct. 2025, doi: 10.1016/j.jare.2024.12.004.

[11] “The Gene Ontology Resource.” Accessed: Mar. 10, 2026. [Online]. Available: https://geneontology.org/

[12] “KEGG: Kyoto Encyclopedia of Genes and Genomes.” Accessed: Mar. 10, 2026. [Online]. Available: https://www.genome.jp/kegg/

[13] “STRING Database.” Accessed: Mar. 10, 2026. [Online]. Available: https://string-db.org/

[14] “Cytoscape.” Accessed: Mar. 10, 2026. [Online]. Available: https://cytoscape.org/

[15] I. Pranandi, “Bioinformatics Exploration of Biochemical Traits Associated with Culturally Distinct Populations: Between Genetics and Identity,” Journal of Biomedical Advancement Scientific Research, vol. 1, no. 3, pp. 1–19, Nov. 2025, doi: 10.63721/25JBASR0127.

[16] Y. M. Yan et al., “Hub genes, diagnostic model, and predicted drugs in systemic sclerosis by integrated bioinformatics analysis,” Front. Genet., vol. 14, pp. 1–13, Jul. 2023, doi: 10.3389/fgene.2023.1202561.

[17] M. H. Kao et al., “Activating Transcription Factor 3 Diminishes Ischemic Cerebral Infarct and Behavioral Deficit by Downregulating Carboxyl-Terminal Modulator Protein,” Int. J. Mol. Sci., vol. 24, no. 3, pp. 1–9, Jan. 2023, doi: 10.3390/ijms24032306.

[18] X. Yang, S. Yan, P. Wang, and G. Wang, “Identification of Hub Genes in the Pathogenesis of Ischemic Stroke Based on Bioinformatics Analysis,” J. Korean Neurosurg. Soc., vol. 65, no. 5, pp. 697–709, May 2022, doi: 10.3340/jkns.2021.0200.

Downloads

Published

2026-05-28

Deprecated: json_decode(): Passing null to parameter #1 ($json) of type string is deprecated in /home/jskff/public_html/plugins/generic/citations/CitationsPlugin.php on line 68

How to Cite

[1]
N. Sudiyono, W. William, and Ian Pranandi, “Identifikasi Gen Pengatur Sentral pada Stroke Iskemik Menggunakan Pendekatan Berbasis Jaringan: Identification of Central Regulatory Genes in Ischemic Stroke Using a Network-Based Approach”, J. Sains. Kes, vol. 7, no. 2, pp. 309–317, May 2026, doi: 10.30872/.

Similar Articles

21-30 of 51

You may also start an advanced similarity search for this article.