High Performance Computing in Life Sciences, Technical University of Applied Sciences Wildau, Wildau, Germany.
BIOMES NGS GmbH, Schwartzkopffstraße 1, 15745, Wildau, Germany.
Int Microbiol. 2023 Aug;26(3):601-610. doi: 10.1007/s10123-023-00324-6. Epub 2023 Feb 13.
Diabetes mellitus type 2 is a common disease that poses a challenge to the healthcare system. The disease is very often diagnosed late. A better understanding of the relationship between the gut microbiome and type 2 diabetes can support early detection and form an approach for therapies. Microbiome analysis offers a potential opportunity to find markers for this disease. Next-generation sequencing methods can be used to identify the bacteria present in the stool sample and to generate a microbiome profile through an analysis pipeline. Statistical analysis, e.g., using Student's t-test, allows the identification of significant differences. The investigations are not only focused on single bacteria, but on the determination of a comprehensive profile. Also, the consideration of the functional microbiome is included in the analyses. The dataset is not from a clinical survey, but very extensive.
By examining 946 microbiome profiles of diabetes mellitus type 2 sufferers (272) and healthy control persons (674), a large number of significant genera (25) are revealed. It is possible to identify a large profile for type 2 diabetes disease. Furthermore, it is shown that the diversity of bacteria per taxonomic level in the group of persons with diabetes mellitus type 2 is significantly reduced compared to a healthy control group. In addition, six pathways are determined to be significant for type 2 diabetes describing the fermentation to butyrate. These parameters tend to have high potential for disease detection.
With this investigation of the gut microbiome of persons with diabetes type 2 disease, we present significant bacteria and pathways characteristic of this disease.
2 型糖尿病是一种常见疾病,对医疗体系构成挑战。这种疾病通常诊断较晚。更好地了解肠道微生物组与 2 型糖尿病之间的关系,可以支持早期检测,并形成治疗方法。微生物组分析为寻找这种疾病的标志物提供了潜在机会。下一代测序方法可用于识别粪便样本中存在的细菌,并通过分析管道生成微生物组图谱。统计分析,例如使用学生 t 检验,可以识别出显著差异。这些研究不仅关注单一细菌,还关注综合特征的确定。此外,在分析中还考虑了功能微生物组。该数据集不是来自临床调查,而是非常广泛的。
通过检查 272 名 2 型糖尿病患者和 674 名健康对照者的 946 个微生物组图谱,发现了大量显著的属(25 个)。有可能识别出 2 型糖尿病疾病的大型图谱。此外,与健康对照组相比,糖尿病组中每个分类水平的细菌多样性显著降低。此外,确定了六个与 2 型糖尿病相关的途径,描述了丁酸的发酵。这些参数在疾病检测方面具有很高的潜力。
通过对 2 型糖尿病患者肠道微生物组的研究,我们提出了该疾病特征性的显著细菌和途径。