Overall Research Program
My overall research program seeks to understand how genetic and social factors are associated with adverse health within vulnerable populations in the United States. Additionally, I am interested in understanding if/how the social environment is embodied to produce adverse health outcomes using epigenomics. I conduct my research using a mixed-methods approach, employing theory and methods from genomics, sociocultural anthropology, biocultural anthropology, medical anthropology, public health, and epidemiology to better contextualize health outcomes. My research and results are intended to be both shared within the scientific community to broaden our understanding on these topics and used as leverage to advocate for basic human rights within public policy and grassroots organizing spaces.
Dissertation Project (Ongoing)
Title: Noventa Millas: Genomics, migration history, and health disparities within Cuban Immigrants and Cuban-Americans in South Florida
My dissertation seeks to dispel the myth that Latinx people are a homogenous group through understanding how immigration histories and sociopolitics influence patterns of genomic diversity and health outcomes. For my dissertation project, I am working with my community of individuals of Cuban descent to understand these topics as it relates to their experiences (or their ancestors’ experiences) of immigrating from Cuba to the United States from the 1950s to the 2000s.
Master's Project (Concluded)
Title: Factors influencing taxonomic unevenness in scientific research: a mixed-methods case study of non-human primate genomic sequence data generation
Abbreviated abstract from published paper, available here.
Scholars have noted major disparities in the extent of scientific research conducted among taxonomic groups. Such trends may cascade if future scientists gravitate towards study species with more data and resources already available. As new technologies emerge, do research studies employing these technologies continue these disparities? Here, using non-human primates as a case study, we identified disparities in massively parallel genomic sequencing data and conducted interviews with scientists who produced these data to learn their motivations when selecting study species. We tested whether variables including publication history and conservation status were significantly correlated with publicly available sequence data in the NCBI Sequence Read Archive (SRA). Of the 179.6 terabases (Tb) of sequence data in SRA for 519 non-human primate species, 135 Tb (approx. 75%) were from only five species: rhesus macaques, olive baboons, green monkeys, chimpanzees and crab-eating macaques. The strongest predictors of the amount of genomic data were the total number of non-medical publications and number of medical publications. In a generalized linear model, the number of non-medical publications and closer phylogenetic distance to humans were the most predictive of the amount of genomic sequence data. We interviewed 33 authors of genomic data-producing publications and analyzed their responses using grounded theory. Consistent with our quantitative results, authors mentioned their choice of species was motivated by sample accessibility, prior published work and relevance to human medicine. Our mixed-methods approach helped identify and contextualize some of the driving factors behind species-uneven patterns of scientific research, which can now be considered by funding agencies, scientific societies and research teams aiming to align their broader goals with future data generation efforts.
I presented a poster on this project during the Graduate School Exhibition at Penn State, Anthropology Day at Penn State, and at the American Association of Physical Anthropologists Annual Conference 2018. Please refer to the published article for full results.