Potential Postmortem Microbial Biomarkers of Infant Death Investigation

Accuracy in determining factors contributing to infant death is essential to identifying or ruling out a cause and manner of death. Yet, even when the conditions resulting in infant death are known, the circumstances of death may be inaccurately or inconsistently reported. There is a critical need for identification and validation of reliable biomarker(s) capable of routinely and accurately determining the circumstances of death, especially in infants. The postmortem microbiome may aid in making such determinations. Our team has previously demonstrated (with NIJ funding) the adult postmortem microbiome can estimate the postmortem interval with a two-day accuracy. However, we lack any data and the fundamental understanding of the role and impact of the postmortem microbiome during infant death investigation. The goal of this project is to build on previous work by our team on the postmortem microbiome. This project is designed to characterize the variation in postmortem microbiomes and statistical modeling of infant death to advance our foundational understanding of microbial contributions to distinguish among natural, accidental, and non-accidental infant deaths using data from routine autopsies. Postmortem microbiome samples and metadata (e.g., sex, ethnicity, age) will be collected during routine autopsy at a large metropolitan medical examiner’s office from 50 infant (< 1 year) cases. This project will determine the genetic composition of infant postmortem microbiomes using whole genome sequencing. Data from this pioneering cross-sectional survey will be used in machine learning algorithm models to predict cause and manner of infant death from microbial communities collected at autopsy. Model performance will be evaluated based on their predictive power (accuracy) and reliability (error rate). To accomplish this project, we will leverage our expertise in forensic pathology, postmortem microbiomes, ecology, microbiology, and big data/machine learning analytics. Our unique multidisciplinary team has collaborated for over six years on postmortem microbiomes and their direct impact in forensics, especially during autopsy. Expected products from this work are a first-of-its-kind whole genome microbiome database associated with infant deaths, and a database of statistical models and their performance metrics to predict the circumstance of infant death based on microbial contributions, in addition to the interim and final reports. Further, mentoring of a student will contribute to educating and training a future workforce using these rapidly advancing technologies in forensics. Major insights resulting from the proposed project to broaden forensic microbiome applicability will be communicated to forensic practitioners at national meetings and through publications.
Note: This project contains a research and/or development component, as defined in applicable law, and complies with Part 200 Uniform Requirements - 2 CFR 200.210(a)(14). CA/NCF