Patient Genetic Determinants of Chronic Wound Microbiome Composition

项目摘要 慢性创伤是一种流行病，在美国有数百万人受到折磨， 国际吧老年人、肥胖者和糖尿病患者的慢性伤口发生率更高， 而这类人群的比例正在上升。慢性创伤与 生活质量大大降低，包括抑郁症和死亡率增加， 他人慢性伤口流行的扩大还反映在医疗费用的快速上涨上。非- 这些伤口的愈合性质受到微生物感染的严重影响， 通常发现它们作为微生物群落同时出现在伤口中。最近的一项研究提供了 有证据表明，一个人的基因塑造了居住在慢性伤口上的细菌物种， 与治愈率有关认识到理解这一点的生物医学重要性， 该项目的具体目标是：1）确定与慢性疾病相关的患者基因组位点， 伤口微生物组特征; 2）建立慢性伤口预测模型的可行性 感染;和，3）功能上验证相关基因座。研究设计包括比较患者的 通过微生物组-全基因组关联研究，将慢性伤口微生物组与其基因组相关联。的 设计包括超过1,000个样本的发现队列，围绕主要SNP的区域插补， 贝叶斯精细映射，以确定可信的集合，包括可能的因果变量。根据关联结果 研究中，特定的基因组区域将用于建立细菌物种的第一个预测模型 在慢性伤口中发生;预计这种模型最终将在预测中得到应用。 和治疗药物。模型开发将通过使用贝叶斯可信集来完成， 来自相关区域的SNP在结构方程建模框架中告知潜在变量。一个 将使用超过250个样本的独立验证队列来评估这些样本的预测能力。 模型此外，预计最有可能是因果关系的SNP的湿实验室功能验证实验将产生 关于慢性伤口所导致的宿主-微生物相互作用的新的机械见解。长期 这项工作的目标是利用个体遗传学来对抗慢性伤口，改善公众健康 结果。

PROJECT SUMMARY Chronic wounds are an epidemic afflicting several million people in the United States, and many million more worldwide. The elderly, the obese and those with diabetes have much higher incidence of chronic wounds, and the proportion of the population that fall into these categories is rising. Chronic wounds are associated with considerable reductions in quality of life, including increased rates of depression and mortality, among others. The expansion of the chronic wound epidemic is also reflected in rapidly rising medical costs. The non- healing nature of these wounds is heavily influenced by microbial infection, and multiple bacterial species are commonly found to simultaneously occur in wounds as microbial communities. A recent study provided evidence that one's genetics shape the bacterial species that inhabit their chronic wounds and these species were consequential to healing rates. Recognizing the biomedical importance of understanding this relationship, the specific aims of the project are to: 1) Identify patient genomic loci associated with chronic wound microbiome characteristics; 2) Establish the feasibility of predictive modeling for chronic wound infections; and, 3) Functionally validate associated loci. The study design consists of comparing patients' chronic wound microbiomes to their genomes through a microbiome-genome wide association study. The design includes a discovery cohort of greater than 1,000 samples, regional imputation around lead SNPs and Bayesian fine-mapping to identify credible sets including likely causal variants. Based on results of association studies, specific genomic regions will be used to build the first predictive models for bacterial species occurrence in chronic wounds; it is anticipated that such models will eventually find application in predictive and therapeutic medicine. Model development will be accomplished by using the Bayesian credible sets of SNPs from associated regions to inform latent variables in a structural equation modeling framework. An independent validation cohort of greater than 250 samples will be used to assess the predictive power of these models. Also, wet lab functional validation experiments of SNPs most likely to be causal are expected to yield new mechanistic insights about host-microbe interactions consequential to chronic wounds. The long-term goal of this work is to leverage individual genetics to combat chronic wounds and improve public health outcomes.