Postdoctoral Fellowship: SPRF: Anthropological Investigation of Demographic Variability in the Ancient Oral Microbiome

该奖项是美国国家科学基金会社会、行为和经济科学博士后研究奖学金（SPRF）项目的一部分。SPRF计划的目标是为学术界、工业界或私营部门和政府的科学事业准备有前途的早期职业博士级科学家。SPRF奖励包括在知名科学家的赞助下进行为期两年的培训，并鼓励博士后进行独立研究。美国国家科学基金会寻求促进科学界各阶层的科学家，包括那些未被充分代表的群体的科学家，参与其研究项目和活动；博士后阶段被认为是实现这一目标的一个重要的专业发展阶段。每个博士后必须解决各自学科领域的重要科学问题。在宾夕法尼亚州立大学Laura Weyrich博士的赞助下，该博士后奖学金奖支持一位早期职业研究人员调查人口统计学变量（年龄、性别）对古代口腔微生物组变异的影响，以阐明这些差异与过去健康结果的关系。虽然口腔微生物群与生活人群的疾病之间存在很强的联系，但口腔微生物群的个体差异与健康差异之间的关系仍不清楚。因此，本项目旨在通过调查哪些人口统计学因素导致口腔微生物群的个体差异，深入了解人类口腔微生物群、健康和疾病之间的关系。对人类-病原体相互作用的人类学研究可以进一步了解某些疾病的病因，以及过去的社会和环境条件如何有助于形成在世人群中观察到的健康不平等。因此，通过提供与健康结果有关的过去生物、社会和环境因素的时间信息，这个项目的成果可以帮助制定针对健康风险和暴露的公共卫生干预措施，并有助于改善受到健康差异不成比例影响的群体的生活质量。本项目从人类学、微生物学、人口学和生态学的角度出发，利用古人口学和生物分子分析对来自中世纪和后中世纪墓地的现有牙石样本进行研究，研究古代口腔微生物组的年龄和性别特异性变异，以实现两个主要研究目标。首先，重新审视人口因素（年龄和性别）对人类口腔微生物群多样性和组成的影响。其次，调查微生物群多样性和组成的变化如何影响基于性别的健康结果，如死亡率风险的变化，随着时间的推移。为了实现这些目标，使用贝叶斯方法进行过渡分析，以产生死亡年龄的年龄点估计，并使用基因组和蛋白质组学程序以及传统的形态学骨骼特征来估计性别。使用α -和β -多样性指标评估口腔微生物群的多样性和组成，并采用基于危害的统计方法评估这些指标对生存的影响。最终，该项目整合了古人类统计学和生物分子数据，可以阐明疾病骨骼表现的病因及其与生存的关系；病原体在塑造过去人类种群中所起的作用；以及人类与微生物相互作用的机制以及不同时期人类健康的不同模式的产生。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This award was provided as part of the NSF Social, Behavioral and Economic Sciences Postdoctoral Research Fellowships (SPRF) programs. The goal of the SPRF program is to prepare promising, early career doctoral-level scientists for scientific careers in academia, industry or private sector, and government. SPRF awards involve two years of training under the sponsorship of established scientists and encourage Postdoctoral Fellows to perform independent research. NSF seeks to promote the participation of scientists from all segments of the scientific community, including those from underrepresented groups, in its research programs and activities; the postdoctoral period is considered to be an important level of professional development in attaining this goal. Each Postdoctoral Fellow must address important scientific questions that advance their respective disciplinary fields. Under the sponsorship of Dr. Laura Weyrich at the Pennsylvania State University, this postdoctoral fellowship award supports an early career researcher investigating the effect of demographic variables (age, sex) on variation within the ancient oral microbiome to elucidate how these differences relate to health outcomes in the past. While there is a strong connection between the oral microbiome and disease in living populations, the relationship between individual variation in oral microbiota and health disparities remains unclear. Hence, this project aims to gain insight into the relationship between the human oral microbiome, health, and disease by investigating what demographic factors produce individual variation in oral microbiota. Anthropological studies on human-pathogen interactions can further our understanding of the etiology of certain diseases and how social and environmental conditions in the past helped to shape health inequities observed in living populations. Therefore, by contributing temporal information on past biological, social, and environmental factors related to health outcomes, the results of this project can help in the development of public health interventions that target health risks and exposures and can help to improve the quality of the life for groups who are disproportionately impacted by health disparities.Drawing on perspectives from anthropology, microbiology, demography, and ecology, this project studies age- and sex-specific variability in the ancient oral microbiome using paleodemographic and biomolecular analyses conducted on existing dental calculus samples from medieval and post-medieval cemeteries to achieve two primary research objectives. First, reexamine the effects of demographic factors (age and sex) on the diversity and composition of the human oral microbiome. Second, investigate how variation in microbiota diversity and composition effects sex-based health outcomes, as manifested in variation in risks of mortality, across time. To achieve these objectives a Bayesian approach to transition analysis is used to generate age point estimates for age-at-death, and genomic and proteomic procedures as well as traditional morphological skeletal traits are used to estimate sex. Oral microbiota diversity and composition are assessed using metrics of alpha- and beta-diversity, and hazards-based statistical approaches are employed to assess the effect of these metrics on survivorship. Ultimately, this project’s integration of paleodemographic and biomolecular data can shed light on the etiology of skeletal manifestations of disease and their relationship to survival; the role pathogens played in shaping past human populations; and the mechanisms involved in human-microbial interactions and the production of differential patterns of human health across time.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.