Molecular epidemiology of pregnancy using omics data: advances, success stories, and challenges

Authors

Ali Rahnavard, Computational Biology Institute, Milken Institute School of Public Health, The George Washington University, Washington, DC, 20052, USA. rahnavard@gwu.edu.
Ranojoy Chatterjee, Computational Biology Institute, Milken Institute School of Public Health, The George Washington University, Washington, DC, 20052, USA.
Hui Wen, Computational Biology Institute, Milken Institute School of Public Health, The George Washington University, Washington, DC, 20052, USA.
Clark Gaylord, Computational Biology Institute, Milken Institute School of Public Health, The George Washington University, Washington, DC, 20052, USA.
Sabina Mugusi, Department of Clinical Pharmacology, Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania.
Kevin C. Klatt, Nutritional Sciences & Toxicology, University of California, Berkeley, CA, 94720, USA.
Emily R. Smith, Department of Global Health, The Milken Institute School of Public Health, The George Washington University, Washington, DC, 20052, USA. emilysmith@gwu.edu.

Document Type

Journal Article

Publication Date

1-26-2024

Journal

Journal of translational medicine

Volume

22

Issue

1

DOI

10.1186/s12967-024-04876-7

Keywords

Computational biology; Epidemiology; Omics; Pregnancy

Abstract

Multi-omics approaches have been successfully applied to investigate pregnancy and health outcomes at a molecular and genetic level in several studies. As omics technologies advance, research areas are open to study further. Here we discuss overall trends and examples of successfully using omics technologies and techniques (e.g., genomics, proteomics, metabolomics, and metagenomics) to investigate the molecular epidemiology of pregnancy. In addition, we outline omics applications and study characteristics of pregnancy for understanding fundamental biology, causal health, and physiological relationships, risk and prediction modeling, diagnostics, and correlations.

APA Citation

Rahnavard, Ali; Chatterjee, Ranojoy; Wen, Hui; Gaylord, Clark; Mugusi, Sabina; Klatt, Kevin C.; and Smith, Emily R., "Molecular epidemiology of pregnancy using omics data: advances, success stories, and challenges" (2024). GW Authored Works. Paper 4117.
https://hsrc.himmelfarb.gwu.edu/gwhpubs/4117

Department

Global Health