Analisis Differential Abundance Pada Mikrobioma Usus Menggunakan Metode Analysis Of Compositions Of Microbiomes With Bias Correction (ANCOM-BC)

Salsabila, Ashila Nasywa (2026) Analisis Differential Abundance Pada Mikrobioma Usus Menggunakan Metode Analysis Of Compositions Of Microbiomes With Bias Correction (ANCOM-BC). Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Mikrobioma usus berperan penting dalam metabolisme, system imun, dan Risiko berbagai penyakit kronis melalui interaksinya dengan pola makan dan lingkungan. Metabolit yang dihasilkan mikroorganisme ini memengaruhi kondisi usus, sehingga setiap orang memiliki respons yang berbeda-beda terhadap asupan nutrisi, Namun, tantangan utama dalam meneliti hal ini Adalah data mikrobioma yang bersifat komposisional karena dinyatakan dalam bentuk kelimpahan relative, sehingga perubahan proporsi satu takson dapat memengaruhi takson lain secara relative tanpa mencerminkan perubahan jumlah absolut. Permasalahan ini diperparah oleh adanyan bias sampling fraction yang berpotensi menghasilkan kesimpulan yang bias. Analysis of Compotitional of Microbiomes with Bias Correction (ANCOM-BC) dikembangkan untuk mengatasi keterbatasan tersebut dengan mengoreksi bias sampling fraction menggunakan pendekatan regresi linier pada skala log. Penelitian ini bertujuan untuk menganalisis differential abundance pada mikrobioma usus manusia menggunakan metode ANCOM-BC dengan mengintegrasikan variabel Indeks Massa Tubuh (IMT). Hasil analisis menunjukkan bahwa metode ANCOM-BC dapat mengidentifikasi takson signifikan setelah mengoreksi bias sampling fraction. Pada kelompok Overweight, ditemukan peningkatan kelimpahan yang signifikan pada 16 takson yang mengindikasikan adaptasi mikrobioma terhadap ketersediaan substrat energi. Sementara itu, pada kelompok Obese, terdapat 9 takson signifikan dengan terjadi pergeseran fungsional yang ditandai dengan penurunan signifikan pada takson produsen butirat yang mencerminkan pola efesiensi pemanenan energi berakaitan dengan patofisiologi obesitas. Temuan ini menegaskan bahwa penggunaan ANCOM-BC memberikan inferensi yang lebih reliabel dalam mendeteksi perubahan profil mikrobioma yang berhubungan dengan status kesehatan subjeknya.
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The gut microbiome plays a crucial role in metabolism, immune system regulation, and the risk of various chronic diseases through its interactions with dietary patterns and environmental factors. Metabolites produced by these microorganisms influence gut conditions, resulting in individual differences in responses to nutritional intake. However, a major challenge in microbiome research is the compositional nature of microbiome data, which are expressed as relative abundances. Changes in the proportion of one taxon can affect the relative proportions of other taxa without necessarily reflecting changes in their absolute abundances. This issue is further complicated by sampling fraction bias, which may lead to biased conclusions. Analysis of Compositions of Microbiomes with Bias Correction (ANCOM-BC) was developed to address these limitations by correcting sampling fraction bias using a log-linear regression framework. This study aims to analyze differential abundance in the human gut microbiome using the ANCOM-BC method while incorporating Body Mass Index (BMI) as a covariate. The results demonstrate that ANCOM-BC effectively identifies significant taxa after correcting for sampling fraction bias. In the overweight group, 16 taxa exhibited significantly increased abundance, suggesting microbiome adaptation to greater energy substrate availability. In contrast, the obese group showed 9 significant taxa, characterized by functional shifts marked by a significant reduction in butyrate-producing taxa. This finding reflects enhanced energy-harvesting efficiency associated with the pathophysiology of obesity. These findings highlight that ANCOM-BC provides more reliable inference for detecting alterations in microbiome profiles associated with individuals' health status.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	ANCOM-BC, Data Komposisional, Differential Abundance, Indeks Massa Tubuh, Mikrobioma Usus, ANCOM–BC, Body Mass Index, Compositional Data, Differential Abundance, Gut Microbiome
Subjects:	Q Science > QR Microbiology
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis
Depositing User:	Ashila Nasywa Salsabila
Date Deposited:	31 Jul 2026 02:31
Last Modified:	31 Jul 2026 02:35
URI:	http://repository.its.ac.id/id/eprint/138590

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