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Mujahid, Wajeeha, Safdar, Sahar, Aftab, Ayesha, Tabassum, Sania, Bakhtiar, Syeda Marriam. (1405). Integrative Metagenomic Analysis Reveals Human Gut Microbiome-Derived Candidate Non-invasive Biomarkers for Type II Diabetes Mellitus. سامانه مدیریت نشریات علمی, (), -. doi: 10.30476/ijms.2026.108150.4295
Wajeeha Mujahid; Sahar Safdar; Ayesha Aftab; Sania Tabassum; Syeda Marriam Bakhtiar. "Integrative Metagenomic Analysis Reveals Human Gut Microbiome-Derived Candidate Non-invasive Biomarkers for Type II Diabetes Mellitus". سامانه مدیریت نشریات علمی, , , 1405, -. doi: 10.30476/ijms.2026.108150.4295
Mujahid, Wajeeha, Safdar, Sahar, Aftab, Ayesha, Tabassum, Sania, Bakhtiar, Syeda Marriam. (1405). 'Integrative Metagenomic Analysis Reveals Human Gut Microbiome-Derived Candidate Non-invasive Biomarkers for Type II Diabetes Mellitus', سامانه مدیریت نشریات علمی, (), pp. -. doi: 10.30476/ijms.2026.108150.4295
Mujahid, Wajeeha, Safdar, Sahar, Aftab, Ayesha, Tabassum, Sania, Bakhtiar, Syeda Marriam. Integrative Metagenomic Analysis Reveals Human Gut Microbiome-Derived Candidate Non-invasive Biomarkers for Type II Diabetes Mellitus. سامانه مدیریت نشریات علمی, 1405; (): -. doi: 10.30476/ijms.2026.108150.4295

Integrative Metagenomic Analysis Reveals Human Gut Microbiome-Derived Candidate Non-invasive Biomarkers for Type II Diabetes Mellitus

Iranian Journal of Medical Sciences
مقالات آماده انتشار، اصلاح شده برای چاپ، انتشار آنلاین از تاریخ 02 شهریور 1405    اصل مقاله (2.55 M)
نوع مقاله: Original Article(s)
شناسه دیجیتال (DOI): 10.30476/ijms.2026.108150.4295
نویسندگان
Wajeeha Mujahid؛ Sahar Safdar* ؛ Ayesha Aftab؛ Sania Tabassum؛ Syeda Marriam Bakhtiar
Department of Bioinformatics and Biosciences, Capital University of Science and Technology, Islamabad, Pakistan
چکیده
Background: Type II Diabetes Mellitus (T2DM) is increasingly associated with alterations in the gut microbiome, which influences host metabolism, inflammation, and insulin sensitivity. Metagenomic profiling has emerged as a promising non-invasive strategy for identifying disease-associated microbial signatures. However, distinguishing disease-specific biomarkers from general dysbiosis remains a major challenge. This study aimed to develop an integrative subtractive metagenomic framework to identify candidate disease-specific gut microbial biomarkers. 
Methods: This in silico case-control study used publicly available metagenomics datasets from healthy controls and individuals with T2DM. Assembly-based and read-based taxonomic profiling approaches were integrated. Differential abundance analysis using the Wilcoxon rank-sum test identified key microbial taxa significantly associated with T2DM.  
Results: Potential microbial biomarkers were identified as Bacteroides dorei, Bacteroides gracilis, Bacteroides stercoris, Bacteroides ovatus, Bacteroides thetaiotaomicron, Bacteroides uniformis, Bacteroides vulgatus, Bacteroides xylanisolvens, Eggerthella lenta, Escherichia coli, Faecalibacterium prausnitzii, Parabacteroides distasonis, Ruminococcus torques, and Subdoligranulum. These taxa are involved in gut metabolic homeostasis and may serve as candidate non-invasive biomarkers for T2DM. 
Conclusion: The results of this study advance understanding of microbiome-disease crosstalk and form the basis for further in vitro and in vivo validation and microbiome-targeted therapeutic approaches. Overall, this integrative metagenomic study supports alteration of microbial ecology in T2DM, validating the use of gut microbiome profiling as a diagnostic and therapeutic tool in metabolic disease research.

تازه های تحقیق

Wajeeha Mujahid (Google Scholar)
Sahar Safdar (Google Scholar)

کلیدواژه‌ها
Metagenomics؛ Type II diabetes mellitus؛ Non-invasive biomarkers؛ Microbiome؛ Therapeutics
مراجع
  1. Reed J, Bain S, Kanamarlapudi V. A Review of Current Trends with Type 2 Diabetes Epidemiology, Aetiology, Pathogenesis, Treatments and Future Perspectives. Diabetes Metab Syndr Obes. 2021;14:3567-602. doi: 10.2147/DMSO.S319895. PubMed PMID: 34413662; PubMed Central PMCID: PMC8369920.
  2. Sadagopan A, Mahmoud A, Begg M, Tarhuni M, Fotso M, Gonzalez NA, et al. Understanding the Role of the Gut Microbiome in Diabetes and Therapeutics Targeting Leaky Gut: A Systematic Review. Cureus. 2023;15:e41559. doi: 10.7759/cureus.41559. PubMed PMID: 37554593; PubMed Central PMCID: PMC10405753.
  3. Berbudi A, Rahmadika N, Tjahjadi AI, Ruslami R. Type 2 Diabetes and its Impact on the Immune System. Curr Diabetes Rev. 2020;16:442-9. doi: 10.2174/1573399815666191024085838. PubMed PMID: 31657690; PubMed Central PMCID: PMC7475801.
  4. Alam S, Hasan MK, Neaz S, Hussain N, Hossain MF, Rahman T. Diabetes mellitus: insights from epidemiology, biochemistry, risk factors, diagnosis, complications and comprehensive management. Diabetology. 2021;2:36-50. doi: 0.3390/diabetology2020004.
  5. Anitha T, Vallazhath A, Maniyal V, Menon D. Advances in therapeutic strategies for atherosclerosis: from pharmacologics to stents and stent coatings. J Mater Chem B. 2026;14:2407-37. doi: 10.1039/d5tb02293b. PubMed PMID: 41668608.
  6. Wu H, Esteve E, Tremaroli V, Khan MT, Caesar R, Manneras-Holm L, et al. Metformin alters the gut microbiome of individuals with treatment-naive type 2 diabetes, contributing to the therapeutic effects of the drug. Nat Med. 2017;23:850-8. doi: 10.1038/nm.4345. PubMed PMID: 28530702.
  7. Zhang L, Chu J, Hao W, Zhang J, Li H, Yang C, et al. Gut Microbiota and Type 2 Diabetes Mellitus: Association, Mechanism, and Translational Applications. Mediators Inflamm. 2021;2021:5110276. doi: 10.1155/2021/5110276. PubMed PMID: 34447287; PubMed Central PMCID: PMC8384524.
  8. Bodke H, Jogdand S. Role of Probiotics in Human Health. Cureus. 2022;14:e31313. doi: 10.7759/cureus.31313. PubMed PMID: 36514580; PubMed Central PMCID: PMC9733784.
  9. Bakir-Gungor B, Bulut O, Jabeer A, Nalbantoglu OU, Yousef M. Discovering Potential Taxonomic Biomarkers of Type 2 Diabetes From Human Gut Microbiota via Different Feature Selection Methods. Front Microbiol. 2021;12:628426. doi: 10.3389/fmicb.2021.628426. PubMed PMID: 34512559; PubMed Central PMCID: PMC8424122.
  10. Brockley LJ, Souza VGP, Forder A, Pewarchuk ME, Erkan M, Telkar N, et al. Sequence-Based Platforms for Discovering Biomarkers in Liquid Biopsy of Non-Small-Cell Lung Cancer. Cancers (Basel). 2023;15. doi: 10.3390/cancers15082275. PubMed PMID: 37190212; PubMed Central PMCID: PMC10136462.
  11. Wirbel J, Pyl PT, Kartal E, Zych K, Kashani A, Milanese A, et al. Meta-analysis of fecal metagenomes reveals global microbial signatures that are specific for colorectal cancer. Nat Med. 2019;25:679-89. doi: 10.1038/s41591-019-0406-6. PubMed PMID: 30936547; PubMed Central PMCID: PMC7984229.
  12. Yadav A, Vishwakarma S, Krishna N, Katara P. Integrative omics: current status and future directions. In: Recent Trends in Computational Omics: Concepts and Methodology. New York: Nova Science Publishers; 2020. p. 1-46.
  13. Chen S, Zhou Y, Chen Y, Gu J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics. 2018;34:i884-i90. doi: 10.1093/bioinformatics/bty560. PubMed PMID: 30423086; PubMed Central PMCID: PMC6129281.
  14. Liu S, Rodriguez JS, Munteanu V, Ronkowski C, Sharma NK, Alser M, et al. Analysis of metagenomic data. Nat Rev Methods Primers. 2025;5. doi: 10.1038/s43586-024-00376-6. PubMed PMID: 40688383; PubMed Central PMCID: PMC12276902.
  15. Hauptfeld E, Pappas N, van Iwaarden S, Snoek BL, Aldas-Vargas A, Dutilh BE, et al. Integrating taxonomic signals from MAGs and contigs improves read annotation and taxonomic profiling of metagenomes. Nat Commun. 2024;15:3373. doi: 10.1038/s41467-024-47155-1. PubMed PMID: 38643272; PubMed Central PMCID: PMC11032395.
  16. Nurk S, Meleshko D, Korobeynikov A, Pevzner PA. metaSPAdes: a new versatile metagenomic assembler. Genome Res. 2017;27:824-34. doi: 10.1101/gr.213959.116. PubMed PMID: 28298430; PubMed Central PMCID: PMC5411777.
  17. Qayyum H, Talib MS, Ali A, Kayani MUR. Evaluating the potential of assembler-binner combinations in recovering low-abundance and strain-resolved genomes from human metagenomes. Heliyon. 2025;11:e41938. doi: 10.1016/j.heliyon.2025.e41938. PubMed PMID: 39897886; PubMed Central PMCID: PMC11786835.
  18. Menzel P, Ng KL, Krogh A. Fast and sensitive taxonomic classification for metagenomics with Kaiju. Nat Commun. 2016;7:11257. doi: 10.1038/ncomms11257. PubMed PMID: 27071849; PubMed Central PMCID: PMC4833860.
  19. Chaumeil PA, Mussig AJ, Hugenholtz P, Parks DH. GTDB-Tk v2: memory friendly classification with the genome taxonomy database. Bioinformatics. 2022;38:5315-6. doi: 10.1093/bioinformatics/btac672. PubMed PMID: 36218463; PubMed Central PMCID: PMC9710552.
  20. Kunakh O, Volkova A, Tutova G, Zhukov O. Diversity of diversity indices: Which diversity measure is better? Biosyst Divers. 2023;31:131-46. doi: 10.15421/012314.
  21. Calle ML. Statistical Analysis of Metagenomics Data. Genomics Inform. 2019;17:e6. doi: 10.5808/GI.2019.17.1.e6. PubMed PMID: 30929407; PubMed Central PMCID: PMC6459172.
  22. Zhou Z, Sun B, Yu D, Zhu C. Gut Microbiota: An Important Player in Type 2 Diabetes Mellitus. Front Cell Infect Microbiol. 2022;12:834485. doi: 10.3389/fcimb.2022.834485. PubMed PMID: 35242721; PubMed Central PMCID: PMC8886906.
  23. Que Y, Cao M, He J, Zhang Q, Chen Q, Yan C, et al. Gut Bacterial Characteristics of Patients With Type 2 Diabetes Mellitus and the Application Potential. Front Immunol. 2021;12:722206. doi: 10.3389/fimmu.2021.722206. PubMed PMID: 34484230; PubMed Central PMCID: PMC8415158.
  24. Blanco-Miguez A, Beghini F, Cumbo F, McIver LJ, Thompson KN, Zolfo M, et al. Extending and improving metagenomic taxonomic profiling with uncharacterized species using MetaPhlAn 4. Nat Biotechnol. 2023;41:1633-44. doi: 10.1038/s41587-023-01688-w. PubMed PMID: 36823356; PubMed Central PMCID: PMC10635831
  25. Zafar H, Saier MH, Jr. Gut Bacteroides species in health and disease. Gut Microbes. 2021;13:1-20. doi: 10.1080/19490976.2020.1848158. PubMed PMID: 33535896; PubMed Central PMCID: PMC7872030.
  26. Padilla-Martinez F, Wojciechowska G, Szczerbinski L, Kretowski A. Circulating Nucleic Acid-Based Biomarkers of Type 2 Diabetes. Int J Mol Sci. 2021;23. doi: 10.3390/ijms23010295. PubMed PMID: 35008723; PubMed Central PMCID: PMC8745431.
  27. Hills RD, Jr., Pontefract BA, Mishcon HR, Black CA, Sutton SC, Theberge CR. Gut Microbiome: Profound Implications for Diet and Disease. Nutrients. 2019;11. doi: 10.3390/nu11071613. PubMed PMID: 31315227; PubMed Central PMCID: PMC6682904.
  28. Cunningham AL, Stephens JW, Harris DA. Gut microbiota influence in type 2 diabetes mellitus (T2DM). Gut Pathog. 2021;13:50. doi: 10.1186/s13099-021-00446-0. PubMed PMID: 34362432; PubMed Central PMCID: PMC8343927.
  29. Kim HB, Cho YJ, Choi SS. Metformin increases gut multidrug resistance genes in type 2 diabetes, potentially linked to Escherichia coli. Sci Rep. 2024;14:21480. doi: 10.1038/s41598-024-72467-z. PubMed PMID: 39277620; PubMed Central PMCID: PMC11401871.
  30. Rios-Covian D, Salazar N, Gueimonde M, de Los Reyes-Gavilan CG. Shaping the Metabolism of Intestinal Bacteroides Population through Diet to Improve Human Health. Front Microbiol. 2017;8:376. doi: 10.3389/fmicb.2017.00376. PubMed PMID: 28326076; PubMed Central PMCID: PMC5339271.
  31. Parsaei M, Sarafraz N, Moaddab SY, Ebrahimzadeh Leylabadlo H. The importance of Faecalibacterium prausnitzii in human health and diseases. New Microbes New Infect. 2021;43:100928. doi: 10.1016/j.nmni.2021.100928. PubMed PMID: 34430035; PubMed Central PMCID: PMC8365382.
  32. Sharma S, Tripathi P. Gut microbiome and type 2 diabetes: where we are and where to go? J Nutr Biochem. 2019;63:101-8. doi: 10.1016/j.jnutbio.2018.10.003. PubMed PMID: 30366260.
  33. Woldeamlak B, Yirdaw K, Biadgo B. Role of Gut Microbiota in Type 2 Diabetes Mellitus and Its Complications: Novel Insights and Potential Intervention Strategies. Korean J Gastroenterol. 2019;74:314-20. doi: 10.4166/kjg.2019.74.6.314. PubMed PMID: 31870137; PubMed Central PMCID: PMC12285806.
  34. Sasidharan Pillai S, Gagnon CA, Foster C, Ashraf AP. Exploring the Gut Microbiota: Key Insights Into Its Role in Obesity, Metabolic Syndrome, and Type 2 Diabetes. J Clin Endocrinol Metab. 2024;109:2709-19. doi: 10.1210/clinem/dgae499. PubMed PMID: 39040013; PubMed Central PMCID: PMC11479700.
  35. Zhang L, Luo J, Li X, Guo S, Shi D. 16S rRNA Sequencing and Metagenomics Study of Gut Microbiota: Implications of BDB on Type 2 Diabetes Mellitus. Mar Drugs. 2020;18. doi: 10.3390/md18090469. PubMed PMID: 32957565; PubMed Central PMCID: PMC7551199.
  36. Wu Z, Gong C, Wang B. The relationship between dietary index for gut microbiota and diabetes. Sci Rep. 2025;15:6234. doi: 10.1038/s41598-025-90854-y. PubMed PMID: 39979448; PubMed Central PMCID: PMC11842723.
  37. Brial F, Chilloux J, Nielsen T, Vieira-Silva S, Falony G, Andrikopoulos P, et al. Human and preclinical studies of the host-gut microbiome co-metabolite hippurate as a marker and mediator of metabolic health. Gut. 2021;70:2105-14. doi: 10.1136/gutjnl-2020-323314. PubMed PMID: 33975870; PubMed Central PMCID: PMC8515120.
  38. Canfora EE, Meex RCR, Venema K, Blaak EE. Gut microbial metabolites in obesity, NAFLD and T2DM. Nat Rev Endocrinol. 2019;15:261-73. doi: 10.1038/s41574-019-0156-z. PubMed PMID: 30670819.
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