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

该奖项是作为NSF社会、行为和经济学博士后研究奖学金(SPRF)计划的一部分提供的。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职业生涯培养有前途的、早期职业博士水平的科学家。SPRF奖项包括在知名科学家的赞助下进行两年的培训，并鼓励博士后研究员进行独立研究。国家科学基金会致力于促进科学界所有阶层的科学家参与其研究方案和活动，包括那些来自代表性不足的群体的科学家；博士后阶段被认为是实现这一目标的专业发展的一个重要水平。每个博士后研究员都必须解决推动各自学科领域向前发展的重要科学问题。在宾夕法尼亚州立大学Laura Weyrich博士的赞助下，这项博士后奖学金支持一名早期职业研究人员调查人口统计变量(年龄、性别)对古代口腔微生物组内变异的影响，以阐明这些差异如何与过去的健康结果相关。虽然在活着的人群中，口腔微生物群与疾病之间有很强的联系，但口腔微生物区系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区系的个体差异来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促进我们对某些疾病的病因以及过去的社会和环境条件如何帮助形成在活着的人口中观察到的健康不平等的理解。因此，通过提供过去与健康结果相关的生物、社会和环境因素的时间信息，该项目的结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。该项目从人类学、微生物学、人口学和生态学的角度出发，利用对中世纪和后中世纪墓地现有的牙结石样本进行的古人口统计学和生物分子分析，研究古代口腔微生物组中年龄和性别的特定变异性，以实现两个主要研究目标。首先，重新检查人口统计因素(年龄和性别)对人类口腔微生物组多样性和组成的影响。第二，调查微生物区系多样性和组成的变化如何影响以性别为基础的健康结果，这体现在死亡风险随时间的变化。为了实现这些目标，使用贝叶斯过渡分析方法来生成死亡年龄的年龄点估计，并使用基因组和蛋白质组程序以及传统的形态骨骼特征来估计性别。口腔微生物区系的多样性和组成使用α-和β-多样性的衡量标准进行评估，并采用基于风险的统计方法来评估这些衡量标准对生存的影响。最终，该项目对古人口学和生物分子数据的整合可以揭示疾病骨骼表现的病因学及其与生存的关系；病原体在塑造过去的人类种群中所起的作用；以及涉及人类-微生物相互作用和人类健康随时间产生不同模式的机制。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.