Indonesian Journal of Medical Chemistry and Bioinformatics


The lung parenchyma is largely impacted by the infectious condition known as pulmonary tuberculosis (pulmonary TB) when the immune system creates a wall around the germs in the lungs, a tiny, hard bulge known as a tubercle develops, earning the disease the name tuberculosis. Although the majority of TB germs target the lungs, they can also harm other bodily organs. The identification of TB biomarkers, which are crucial for diagnosis, treatment monitoring, risk analysis, and prognosis, has been the subject of extensive research. Differences in metabolites between normal cells and tuberculosis are considered to be able to support the diagnosis of tuberculosis. Metabolite data was taken from the Metabolomic workbench and further identification and prediction were carried out in silico. A total of 44 samples found 69 metabolites which were then carried out further analysis. Found as many as 5 metabolites that play an important role in tuberculosis. Of the 5 metabolites, 2 candidate biomarkers were found which are known to have potential as biomarkers. The candidate biomarkers for these metabolites are trans-3-methyluric acid and nicotinic acid. However, this simulation needs further testing to obtain more accurate biomarkers and support the diagnosis.

Bahasa Abstract

Tuberkulosis paru (TB paru) adalah penyakit menular yang menyerang parenkim paru. Nama Tuberkulosis berasal dari tuberkulum yang berarti tonjolan kecil dan keras yang terbentuk ketika sistem kekebalan membangun dinding di sekitar bakteri di paru-paru. Kuman TBC mayoritas menyerang paru-paru, namun kuman TBC juga dapat menyerang organ tubuh lainnya. Ada banyak penelitian dalam literatur tentang penemuan biomarker untuk TB, yang penting untuk diagnosis, pemantauan pengobatan, analisis risiko, dan prognosis. Perbedaan metabolit dari sel normal dan tuberkulosis dianggap dapat mendukung diagnosis tuberkulosis. Data metabolit diambil dari meja kerja Metabolomic dan identifikasi dan prediksi lebih lanjut dilakukan secara in silico. Sebanyak 44 sampel ditemukan 69 metabolit yang kemudian dilakukan analisis lebih lanjut. Ditemukan sebanyak 5 metabolit yang berperan penting dalam tuberkulosis. Dari 5 metabolit tersebut, ditemukan 2 kandidat biomarker yang diketahui berpotensi sebagai biomarker. Biomarker kandidat untuk metabolit ini adalah asam trans-3-metilurat dan asam nikotinat. Namun, simulasi ini membutuhkan pengujian lebih lanjut untuk mendapatkan biomarker yang lebih akurat dan mendukung diagnosis.


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