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中文摘要
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人体微生物组因解剖部位、生理状态和时间而异,因为它对内部和外部环境产生反应。 刺激。虽然积累的数据显示与2型糖尿病的关联,但缺乏关于糖尿病的数据。 从正常糖尿病发展到糖尿病前期和糖尿病。本文提出的纵向研究将允许 评估微生物组与糖尿病前期发展和进展为2型糖尿病的关系 同时分离时间性的混淆效应。这项研究将评估600名墨西哥裔美国人, 在基线和3、6、12、24和36个月后,来自德克萨斯州斯塔尔县的个体。最重要的是,这些 个体将由300名正常糖尿病患者和300名前驱糖尿病患者组成。粪便和鼻腔微生物组 将被评估。评估600名墨西哥裔美国人在斯塔尔县,得克萨斯州在6个点的时间超过3年, 来自两个微生物组站点的数据将产生7,200个样本和相关数据,以实现以下目标:目标1。 确定时间和季节性对鼻和肠道微生物组多样性、相对丰度和 600名墨西哥裔美国人粪便和鼻腔样本16 S核糖体RNA测序结果的变化 没有糖尿病的人-一半有前驱糖尿病,一半有正常的糖尿病。目标2.检验假设, 糖尿病前期的发展和进展为2型糖尿病将与糖尿病相关,并受其影响。 肠道和鼻腔微生物组的多样性和丰富性以及这些微生物组的相互作用。目标3.从 糖尿病前期和2型糖尿病患者的粪便和鼻腔样本, 从一个时间点到下一个时间点的相对丰度和多样性的变化,决定了物种的驱动力。 通过对680个标本进行全基因组测序,我们还建议两个 探索性/机会主义目的。第一,因为目标3中的物种水平测定将提供DNA数据, 病毒组和两个,因为所有的个体先前已经基因分型和整个外显子组测序。的 这些机会主义目的的样本规模不大,但数据的独特性值得评价。目标4: 对这些病毒的DNA病毒组的分布、丰度和多样性进行初步评估, 目标3中物种水平的样本测序。目标5。确定罕见和常见的影响 随着时间的推移,人类遗传变异对鼻腔和肠道微生物组的组成和动力学的影响。的 拟议的纵向分析对于更好地了解微生物组对环境的影响至关重要。 糖尿病前期的发展,进展为2型糖尿病,以及它们之间的相互关系。他们将确定 与变化最相关的属,并将确定那些驱动相对丰度变化的物种 和/或多样性。也许最重要的是,微生物组提供了一个容易修改的目标。然而,在这方面, 在此之前,必须了解随时间的正常变化及其与发展的关系 糖尿病前期和2型糖尿病。
英文摘要
The human microbiome varies by anatomic site, physiologic state, and time as it responds to internal and external stimuli. While accumulating data show associations with type 2 diabetes, there is a paucity of data on the progression from normal glycemia to prediabetes and diabetes. The longitudinal study proposed here will allow evaluating relationships of the microbiome with prediabetes development and progression to type 2 diabetes while separating the confounding effects of temporality. This study will evaluate 600 Mexican American individuals from Starr County, Texas at baseline and 3, 6, 12, 24, and 36 months later. Most importantly, these individuals will be composed of 300 with normal glycemia and 300 with prediabetes. Stool and nasal microbiomes will be evaluated. Evaluating 600 Mexican Americans in Starr County, Texas at 6 points in time over 3 years and from two microbiome sites will generate 7,200 samples and associated data to achieve the following: Aim 1. Determine the influence of time and seasonality on nasal and gut microbiome diversity, relative abundance, and change through 16S ribosomal RNA sequencing of stool and nasal samples from 600 Mexican American individuals without diabetes - half with prediabetes and half with normal glycemia. Aim 2. Test hypotheses that the development of prediabetes and progression to type 2 diabetes will be correlated with and impacted by the diversity and abundance of the gut and nasal microbiomes and that these microbiomes interact. Aim 3. From stool and nasal samples of incident cases of prediabetes and type 2 diabetes and from those with the greatest changes in relative abundance and diversity from one time point to the next, determine the species driving the changes through whole genome sequencing metagenomics on 680 specimens. We also propose two exploratory/opportunistic aims. One, because species level determinations in Aim 3 will provide data on the DNA virome and two, because all individuals have been previously genotyped and whole exome sequenced. The sample sizes for these opportunistic aims are modest, but the uniqueness of the data merit evaluation. Aim 4: Conduct a preliminary evaluation of the distribution, abundance, and diversity of the DNA virome from those samples being sequenced to the species level in Aim 3. Aim 5. Determine the effects of rare and common human genetic variation on the composition and dynamics of the nasal and gut microbiomes over time. The proposed longitudinal analyses are paramount to better understanding the impact of the microbiome on the development of prediabetes, progression to type 2 diabetes, and their reciprocal relationships. They will identify genera most associated with change and will identify those species that drive changes in relative abundance and/or diversity. Perhaps most significant is that the microbiome offers a readily modifiable target. However, before that, there must be an understanding of normal variation over time and its relationship to the development of prediabetes and type 2 diabetes.
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Microbiome and Worsening Glycemia Among Mexican Americans in Starr County, Texas
Genome-wide association to Staphylococcus carriage
Genome-wide association to Staphylococcus carriage
Genome-wide association to Staphylococcus carriage
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