About

Connie J. Mulligan, Ph.D., uses molecular genetic data to investigate questions about human health and disease, taking an interdisciplinary perspective on evolution and health. Her research focuses on the impact of childhood adversity and the basis of racial health disparities. Since 2008, she has been investigating the genetic and cultural risk factors for hypertension in African Americans living in Tallahassee, FL, in collaboration with colleagues from the University of Florida and Anthropology. Her work explores the basis of racial disparities in hypertension, incorporating estimates of genetic ancestry, allele frequencies, measures of discrimination, and personal social networks, revealing significant interactions between genetic variants and sociocultural factors. Since 2010, she has studied the effects of violence and stress on mothers in the Democratic Republic of Congo and their newborns, focusing on epigenetic mechanisms such as DNA methylation that may mediate fetal programming. Her ongoing studies include gene expression analysis and longitudinal health assessments of children. In 2016, she began a collaboration with researchers from Yale and Jordan to investigate risk and resilience in Syrian refugees, examining genetic and epigenetic variants that influence responses to trauma and their potential transmission to future generations. Her work in this area was reported in Science in 2018, under the title 'Lessons in Resilience.'

Research topics

• Computer Science
• Sociology
• Biology
• Political Science
• Data science
• Psychology
• Gender studies
• Anthropology
• Psychiatry
• Genetics
• Engineering
• World Wide Web
• Medicine
• Environmental health
• Evolutionary biology
• Communication

Selected publications

• Data for: Gut Microbiome in Infancy Predicts Malaria Susceptibility

  Zenodo (CERN European Organization for Nuclear Research) · 2026-04-17

  datasetOpen access

  This dataset contains the processed microbiome data and metadata supporting the analyses reported in Dutton et al., "Gut Microbiome in Infancy Predicts Malaria Susceptibility," currently under review at Frontiers in Cellular and Infection Microbiology. Study: A prospective longitudinal cohort of 47 mother-infant dyads recruited at birth in malaria-endemic eastern Democratic Republic of Congo. Infant fecal samples were collected at six weeks, three months, six months, and twelve months of age, as well as at passive malaria sick and post-treatment visits. Full-length 16S rRNA sequencing was performed on PacBio circular consensus sequencing reads across two SMRT cells, and the reads were processed through the DADA2 framework (primer trimming with F27/R1492, length filtering 1000-1600 bp with maxEE=2, PacBio error model, bimera removal, taxonomic assignment against SILVA v138.1). Files: psCombinedCongo_V5.rds - A phyloseq S4 R object containing the OTU table (8,975 taxa x 245 samples), taxonomy table (kingdom through species), and sample metadata including infant ID, timepoint, malaria status variables (BeforeMalaria, DuringMalaria, PostMalaria), bednet use, antibiotic exposure, infant sex, and related covariates. This object is the merged product of two sequencing rounds. working_malaria_risk_score.csv - Per-infant composite malaria risk scores (range 0-6) derived from household questionnaire data covering bednet use, antimalarial drug use during pregnancy, maternal and household malaria cases, and environmental risk. Used as a covariate in the k-NN classifier sensitivity analyses. Reproducibility: These data files are the inputs to the R Markdown analysis pipeline archived separately at Zenodo (see Related identifiers). The full upstream DADA2 sequence processing pipeline that generated psCombinedCongo_V5.rds from raw PacBio FASTQ files is also included in the archived code repository. The analysis pipeline uses renv to pin exact package versions; running renv::restore() followed by knitting the analysis Rmd reproduces all main figures (1-7), supplemental figures (S1-S4), classifier analyses, validation analyses, and statistical results reported in the manuscript.Raw sequence data: Raw PacBio CCS reads are deposited with the NCBI Sequence Read Archive (to be released upon publication of the associated manuscript)

  PublisherDOI

• Analysis pipeline for 'Gut Microbiome in Infancy Predicts Malaria Susceptibility'

  Zenodo (CERN European Organization for Nuclear Research) · 2026-04-18

  otherOpen access

  R Markdown pipeline reproducing all figures, tables, and statistical results for the manuscript Dutton et al., 'Gut Microbiome in Infancy Predicts Malaria Susceptibility,' currently under review at Frontiers in Microbiology. Inputs are full-length 16S rRNA PacBio CCS reads (raw reads archived at NCBI SRA) processed through DADA2, packaged as a phyloseq object. The pipeline reproduces all main and supplemental figures, classifier analyses (k-NN with Boruta feature selection, 72-model grid search, repeated cross-validation, LOOCV, permutation testing, sensitivity covariate models), ANCOM-BC differential abundance (including bednet-adjusted sensitivity), DAR multi-method consensus, LEfSe, and SplinectomeR longitudinal analyses. Exact package versions are pinned via renv.lock. Restore the environment with renv::restore() and knit Congo_Malaria_Rev1.Rmd.

  PublisherDOI

• Data for: Gut Microbiome in Infancy Predicts Malaria Susceptibility

  Zenodo (CERN European Organization for Nuclear Research) · 2026-04-17

  datasetOpen access

  This dataset contains the processed microbiome data and metadata supporting the analyses reported in Dutton et al., "Gut Microbiome in Infancy Predicts Malaria Susceptibility," currently under review at Frontiers in Cellular and Infection Microbiology. Study: A prospective longitudinal cohort of 47 mother-infant dyads recruited at birth in malaria-endemic eastern Democratic Republic of Congo. Infant fecal samples were collected at six weeks, three months, six months, and twelve months of age, as well as at passive malaria sick and post-treatment visits. Full-length 16S rRNA sequencing was performed on PacBio circular consensus sequencing reads across two SMRT cells, and the reads were processed through the DADA2 framework (primer trimming with F27/R1492, length filtering 1000-1600 bp with maxEE=2, PacBio error model, bimera removal, taxonomic assignment against SILVA v138.1). Files: psCombinedCongo_V5.rds - A phyloseq S4 R object containing the OTU table (8,975 taxa x 245 samples), taxonomy table (kingdom through species), and sample metadata including infant ID, timepoint, malaria status variables (BeforeMalaria, DuringMalaria, PostMalaria), bednet use, antibiotic exposure, infant sex, and related covariates. This object is the merged product of two sequencing rounds. working_malaria_risk_score.csv - Per-infant composite malaria risk scores (range 0-6) derived from household questionnaire data covering bednet use, antimalarial drug use during pregnancy, maternal and household malaria cases, and environmental risk. Used as a covariate in the k-NN classifier sensitivity analyses. Reproducibility: These data files are the inputs to the R Markdown analysis pipeline archived separately at Zenodo (see Related identifiers). The full upstream DADA2 sequence processing pipeline that generated psCombinedCongo_V5.rds from raw PacBio FASTQ files is also included in the archived code repository. The analysis pipeline uses renv to pin exact package versions; running renv::restore() followed by knitting the analysis Rmd reproduces all main figures (1-7), supplemental figures (S1-S4), classifier analyses, validation analyses, and statistical results reported in the manuscript.Raw sequence data: Raw PacBio CCS reads are deposited with the NCBI Sequence Read Archive (to be released upon publication of the associated manuscript)

  PublisherDOI

• Analysis pipeline for 'Gut Microbiome in Infancy Predicts Malaria Susceptibility'

  Zenodo (CERN European Organization for Nuclear Research) · 2026-04-18

  otherOpen access

  R Markdown pipeline reproducing all figures, tables, and statistical results for the manuscript Dutton et al., 'Gut Microbiome in Infancy Predicts Malaria Susceptibility,' currently under review at Frontiers in Microbiology. Inputs are full-length 16S rRNA PacBio CCS reads (raw reads archived at NCBI SRA) processed through DADA2, packaged as a phyloseq object. The pipeline reproduces all main and supplemental figures, classifier analyses (k-NN with Boruta feature selection, 72-model grid search, repeated cross-validation, LOOCV, permutation testing, sensitivity covariate models), ANCOM-BC differential abundance (including bednet-adjusted sensitivity), DAR multi-method consensus, LEfSe, and SplinectomeR longitudinal analyses. Exact package versions are pinned via renv.lock. Restore the environment with renv::restore() and knit Congo_Malaria_Rev1.Rmd.

  PublisherDOI

• Analysis pipeline for 'Gut Microbiome in Infancy Predicts Malaria Susceptibility'

  Zenodo (CERN European Organization for Nuclear Research) · 2026-04-18

  otherOpen access

  R Markdown pipeline reproducing all figures, tables, and statistical results for the manuscript Dutton et al., 'Gut Microbiome in Infancy Predicts Malaria Susceptibility,' currently under review at Frontiers in Microbiology. Inputs are full-length 16S rRNA PacBio CCS reads (raw reads archived at NCBI SRA) processed through DADA2, packaged as a phyloseq object. The pipeline reproduces all main and supplemental figures, classifier analyses (k-NN with Boruta feature selection, 72-model grid search, repeated cross-validation, LOOCV, permutation testing, sensitivity covariate models), ANCOM-BC differential abundance (including bednet-adjusted sensitivity), DAR multi-method consensus, LEfSe, and SplinectomeR longitudinal analyses. Exact package versions are pinned via renv.lock. Restore the environment with renv::restore() and knit Congo_Malaria_Rev1.Rmd.

  PublisherDOI

• Analysis pipeline for 'Gut Microbiome in Infancy Predicts Malaria Susceptibility'

  Zenodo (CERN European Organization for Nuclear Research) · 2026-04-17

  otherOpen access

  Analysis pipeline accompanying Dutton et al., "Gut Microbiome in Infancy Predicts Malaria Susceptibility" (Frontiers in Cellular and Infection Microbiology, Rev1). Reproduces all figures, tables, and validation analyses. Data inputs (psCombinedCongo_V5.rds, working_malaria_risk_score.csv) are deposited separately at Zenodo; raw PacBio reads at NCBI SRA.

  PublisherDOI

• TRACE: applying AI language models to extract ancestry information from curated biomedical literature

  Frontiers in Digital Health · 2025-09-19 · 1 citations

  articleOpen access

  Introduction: Ancestry reporting is essential to ensure transparency and proper representation in biomedical studies. However, manually extracting this information from study texts is time-consuming and inefficient. In this paper, we present TRACE (Tool for Researching Ancestry and Cell Extraction), powered by GPT-4 and web-crawling, to automate ancestry identification by detecting cell lines or cultures in texts and tracing their ancestry. Methods: TRACE extracts cell lines and primary cultures from research articles and follows web sources to determine their ancestry. We compared TRACE's outputs to a manually generated database to confirm its performance in identifying and verifying ancestry information. Results: The results reveal an overrepresentation of European/White samples and significant underreporting. TRACE enables large-scale, systematic ancestry analysis-a valuable resource for researchers and agencies assessing biases in sample selection. Conclusions: As an open-source tool, TRACE it facilitates broader use to evaluate and improve ancestry representation in biomedical research.

  PublisherOA PDFDOI

• Epigenetic age acceleration and psychosocial stressors in early childhood

  Epigenomics · 2025-06-02 · 7 citations

  reviewOpen access1st authorCorresponding

  The impact of psychosocial stress on mental and physical health is well-documented. Adverse experiences that occur early in life are particularly impactful on later life health. Epigenetic modifications, such as DNA methylation, have been proposed as a possible mechanism to mediate the impact of childhood events on adult health outcomes. The development of epigenetic clocks to estimate epigenetic age has revealed many examples of epigenetic age acceleration (and deceleration) in association with exposure to psychosocial stressors. Furthermore, altered epigenetic aging has been associated with downstream health outcomes. Here studies are discussed that have reported associations of epigenetic aging with early-life exposure to psychosocial stressors, such as childhood abuse and neglect, and with later-life health outcomes, including increased mortality, morbidity, and disease risk. Protective factors that may mitigate the effect of psychosocial stress on epigenetic aging, and possibly enable reversal of epigenetic aging, are also discussed.

  PublisherOA PDFDOI

• Social dynamics influencing cholera risk in the City of Goma, Democratic Republic of Congo: a qualitative study

  BMC Public Health · 2025-05-15 · 1 citations

  articleOpen access

  BACKGROUND: Cholera remains a major and increasing global public health problem for all people without adequate access to safe water. Goma, in the eastern Democratic Republic of Congo (DRC), has been a major cholera hotspot in Africa since 1994 and is currently experiencing one of the largest outbreaks in the world. This article contributes to the existing scholarship on cholera risk by utilizing a variety of qualitative research methods. Goma offers several advantages to a study of cholera as a city on the shores of Kivu Lake, but where the majority of population does not have access to clean water and experiences recurrent cholera epidemic outbreaks. METHODS: Two local members of our research team are experts in public health and conducted all the interviews in Swahili and French. They also led transect walks and a participatory mapping workshop. Data were collected between 2021 and 2022 in six areas of Goma. Data were analysed using a qualitative software Open code 4.03 to generate codes for a thematic purpose. RESULTS: Our results show that the lack of water infrastructure was the main issue with cholera risk in Goma as it prompted use of unsafe drinking water from Lake Kivu, the small Lake vert and Mubambiro River. Additionally, there were specific social groups with an increased risk based on age and gender, health status, some occupational risks, and socio-economic status. Cholera risks were framed in relation to broader life-threatening events, such as natural disasters, that occurred in the city. Cholera risk was also ascribed to challenges with care seeking and treatment, and issues with implementation of prevention strategies. Finally, the lack of empowerment of local communities in cholera prevention measures was considered a secondary source of risk due to the emphasis on the public health outreach practices and short-term emergency responses. CONCLUSION: This work broadens our understanding of factors that contribute to cholera risk in Goma. These factors should be addressed by implementing diverse strategies that involve the affected communities rather than focusing on rapid public health outreach response interventions. In addition, the, development and the maintenance of a safe and reliable water infrastructures in the city is essential to reduce the chronic nature of cholera infection in the city of Goma.

  PublisherOA PDFDOI

• Phlorest phylogeny derived from Kitchen et al. 2009 'Bayesian phylogenetic analysis of Semitic languages identifies an Early Bronze Age origin of Semitic in the Near East'

  Zenodo (CERN European Organization for Nuclear Research) · 2025-11-12

  datasetOpen accessSenior author

  Cite the source of the dataset as: Kitchen A, Ehret C, Assefa S & Mulligan CJ. 2009. Bayesian phylogenetic analysis of Semitic languages identifies an Early Bronze Age origin of Semitic in the Near East. Proceedings of the Royal Society B: Biological Sciences, 270(1668), 2703-2710.

  PublisherDOI

Recent grants

• Epigenetic alterations and stress among new mothers and neonates in the Democratic Republic of Congo: A biocultural investigation of the intergenerational effects of war

  NSF · $353k · 2012–2016

• A biocultural investigation of epigenetics, gene expression and the intergenerational effects of stress in mothers and neonates

  NSF · $499k · 2017–2022

• Human Dispersals Out of Africa: Mitochondrial and Y chromosomal Genetic Analysis of Eritrean and Omani Populations

  NSF · $323k · 2005–2011

• Doctoral Dissertation Improvement: Testing for archaic hominid introgression in Eritrean and Yemeni modern human genomes

  NSF · $26k · 2013–2017

• Doctoral Dissertation Research: Effect of intrauterine environment on newborn telomere length

  NSF · $19k · 2015–2018

Frequent coauthors

• Clarence C. Gravlee

  University of Florida

  25 shared

• Christopher J. Clukay

  University of Florida

  20 shared

• David Goldman

  National Institutes of Health

  18 shared

• Rebecca Gray

  Saint Luke's Hospital

  17 shared

• Alex B. Wang

  McGill University

  17 shared

• Mary‐Anne Enoch

  National Institute on Alcohol Abuse and Alcoholism

  17 shared

• Matti Virkkunen

  University of Helsinki

  16 shared

• Darlene A. Kertes

  University of Florida

  16 shared

Education

• M.Phil., Ph.D., Molecular Biophysics and Biochemistry

  Yale University