CHRISTA CAGGIANO

Research Interests:

Population genomics, statistical genetics, biobank-scale data integration, rare disease mapping, health disparities, cell-free DNA biomarkers

Current Position:

Postdoctoral Fellow / Institute for Genomic Health

2023 - present /Icahn School of Medicine at Mount Sinai, New York, New York

Advisor: Eimear Kenny

Grants:

NIH NHGRI F32 / April 2026 - March 2027

A framework to characterize monogenic disease in founder populations using biobank-scale data

NIH NINDS F31 / April 2021 - March 2023

A Comprehensive Protocol for Tissue of Origin Prediction in Circulating Cell-Free DNA

Education:

University of California Los Angeles / 2017 - 2023 / Los Angeles, California

Ph.D., Bioinformatics

Thesis: Bioinformatic strategies for population precision health
Advisor: Noah Zaitlen

Brandeis University / 2013 - 2017 / Waltham, Massachusetts

B.S., Biological Physics with honors / B.A., Art History

Minor, Computer Science

Thesis: Bioinformatic approaches to chromatin structure and RNA editing in Drosophila melanogaster
Advisor: Michael Rosbash

Honors and Awards:

July 2025 / NIH

Extramural LRP for Health Disparities Research

October 2022 / ASHG

Epstein Pre-Doctoral Semi-Finalist

October 2019 / ProbGen

Trainee Travel Award

Fall 2019 / UCLA

Neurogenetics T32 Awardee

May 2017 / Brandeis University

Sandra Fisher Prize for Exceptional Achievement in the Creative Arts

Summer 2016 / Brandeis University

Provost Undergraduate Research Grant

Research Experience:

Postdoctoral Fellow / Institute for Genomic Health at Mount Sinai

2023 - present / New York, New York

Developing statistical and computational methods to identify monogenic disease loci in founder populations using biobank-scale genomic and electronic health record (EHR) data
Leading an NIH-funded (NHGRI F32) research program integrating identity-by-descent (IBD) mapping, population genetics models, and clinical phenotyping
Collaborating with clinicians and data scientists to translate genomic findings into clinically relevant insights for precision medicine
Mentoring students and trainees in statistical genetics, reproducible research practices, and large-scale data analysis
Contributing to grant writing, study design, and dissemination of research findings (manuscripts in preparation)

Graduate Research Assistant / UCLA

2017 - 2023 / Los Angeles, California

Developed statistical and machine learning methods to predict ALS status from cell-free DNA methylation data, demonstrating the potential of non-invasive biomarkers for neurodegenerative disease (paper, Github)
Led analysis of population structure and health disparities in the UCLA ATLAS biobank, identifying novel disease risks in underrepresented populations (e.g., Iranian, Armenian, Filipino ancestry) (paper, Github, website)

Bioinformatics Intern / Asuragen

Summer 2017 / Austin, Texas

Developed Bayesian statistical methods that have up to 99.9% specificity in identifying cancerous mutations in a non-invasive cancer screening technology

Research Assistant / Rosbash Laboratory, Brandeis University

2014-2017 / Waltham, Massachusetts

Built a bioinformatics pipeline in R to analyze high-throughput sequencing data to quantify the biology of sleep
Designed and carried out phenotypic genetic screens in Drosophila
Performed ATAC-seq and RNA-seq next-generation sequencing experiments

Student Scholar / Women’s Studies Research Center

2014-2017 / Waltham, Massachusetts

Created statistical workflow in SPSS and R to develop a major thesis about Pagan religious behavior
Contributed data insights to the book, Solitary Pagans

Research Assistant / Laboratory for Laser Energetics

2012-2014 / Rochester, New York

Fabricated liquid crystal radial and azimuthal polarization converters which were used in academic and industrial research settings to increase laser power and efficiency.

Publications:

Caggiano, C., Shemirani, R., Kenny, E. “Revisiting Founder Populations in an Age of Global Biobanks.”, Annual Review of Genomics and Human Genetics, May 2026, DOI: 10.1146/annurev-genom-020525-034901

Caggiano*, C., Morselli*, M., Qiang, X., Celona, B., Thompson, M., et al., “Tissue informative cell-free DNA methylation sites in amyotrophic lateral sclerosis.”, Genome Medicine, October 2025, DOI: 10.1186/s13073-025-01542-5

Liou, L., Caggiano, C., “Advancing methods for multi-ancestry genomics” Trends in Genetics, October 2025, DOI: 10.1016/j.tig.2025.10.003

Boltz T., Schwartz T., Bot M., Hou K., Caggiano C., et al., “Cell-type deconvolution of bulk-blood RNA-seq reveals biological insights into neuropsychiatric disorders.”, The American Journal of Human Genetics, January 2024, DOI: 10.1016/j.ajhg.2023.12.018

Caggiano, C., Boudaie A., Shemirani R., Mefford J., Petter E., Chiu A., Ercelen D., et al., “Disease risk and healthcare utilization among ancestrally diverse groups in the Los Angeles region.”, Nature Medicine, July 2023, DOI: 10.1038/s41591-023-02425-1

Johnson R., Ding Y., Venkateswaran V., Bhattacharya A., Chiu, A., Schwarz T., Freund M., Zhan L., Burch K.S., Caggiano C., et al., “Leveraging genomic diversity for discovery in an EHR-linked biobank: the UCLA ATLAS Community Health Initiative”, Genome Medicine, September 2022, DOI: 10.1186/s13073-022-01106-x

Caggiano C., Celona B., Garton F., Mefford J., Black B., Lomen-Hoerth C., Dahl A., Zaitlen N., “Estimating the rate of cell type degeneration from epigenetic sequencing of cell-free DNA”, Nature Communications, May 2021, DOI: 10.1038/s41467-021-22901-x

Van Paemel R., De Koker A., Caggiano C., Morlion A., Mestdagh P., De Wilde B., Vandesompele J., De Preter K.M, “Genome-Wide Study of the Effect of Blood Collection Tubes on the Cell-Free DNA Methylome” Epigenetics, October 2020, DOI: 10.1080/15592294.2020.1827714

Newberry R. W., Arhar T., Costello J., Hartoularos G. C., Maxwell A. M., Naing Z. Z. C., Pittman M., Reddy N. R., Schwarz D. M. C., Wassarman D. R., Wu T. S., Barrero D., Caggiano C., et al. “Robust Sequence Determinants of α-Synuclein Toxicity in Yeast Implicate Membrane Binding”, ACS Chemical Biology, July 2020, DOI: 10.1021/acschembio.0c00339

Invited Presentations:

UCLA Neurogenetics EHR Workshop

May 2024 / Los Angeles, California

American Statistical Society STATGEN 2024

May 2024 / Pittsburgh, Pennsylvania

Regeneron DRIFT Symposium

October 2022 / Los Angeles, California

Conference Presentations:

American Society of Human Genetics (ASHG)

October 2025 / Boston, Massachusetts

American Society of Human Genetics (ASHG)

October 2022 / Los Angeles, California

Research in Computational Molecular Biology (RECOMB)

June 2020 / Padova, Italy (online due to Covid-19)

American Society of Human Genetics (ASHG)

October 2019 / Houston, Texas

Probabilistic Modeling in Genomics (ProbGen)

October 2019 / Aussois, France

Northern California Computational Biology Symposium

October 2018 / San Francisco, California

Poster Presentations:

American Society of Human Genetics (ASHG)

October 2024 / Boulder, Colorado

European Society for Human Genetics (ESHG)

June 2022 / Vienna, Austria

Society for Molecular Biology and Evolution (SMBE)

July 2021 / online due to Covid-19

Women in Computational Biology

November 2019 / Washington, D.C.

Probabilistic Modeling In Genomics (ProbGen)

November 2018 / Cold Spring Harbor, New York

OMEGA Laser User’s Group

April 2013 / Rochester, New York

Teaching Experience:

2020-present / Horizons Labs

Bioinformatics mentor to high school students

2017 / Department of Computer Science, Brandeis University

Teaching Assistant in Introduction to Python

2016-2017 / Department of Physics, Brandeis University

Provost Teaching Assistant, Physics I/II