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

Ali Rahnavard; Ranojoy Chatterjee; Hui Wen; Clark Gaylord; Sabina Mugusi; Kevin C Klatt; Emily R Smith

doi:10.1186/s12967-024-04876-7

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

J Transl Med. 2024 Jan 26;22(1):106. doi: 10.1186/s12967-024-04876-7.

Authors

Ali Rahnavard^{1

2}, Ranojoy Chatterjee^{3

4}, Hui Wen^{3

4}, Clark Gaylord^{3

4}, Sabina Mugusi⁵, Kevin C Klatt⁶, Emily R Smith^{7

8}

Affiliations

¹ Computational Biology Institute, Milken Institute School of Public Health, The George Washington University, Washington, DC, 20052, USA. rahnavard@gwu.edu.
² Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, 20052, USA. rahnavard@gwu.edu.
³ Computational Biology Institute, Milken Institute School of Public Health, The George Washington University, Washington, DC, 20052, USA.
⁴ Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, 20052, USA.
⁵ Department of Clinical Pharmacology, Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania.
⁶ Nutritional Sciences & Toxicology, University of California, Berkeley, CA, 94720, USA.
⁷ Department of Global Health, The Milken Institute School of Public Health, The George Washington University, Washington, DC, 20052, USA. emilysmith@gwu.edu.
⁸ Department of Exercise and Nutrition Sciences, The Milken Institute School of Public Health, The George Washington University, Washington, DC, 20052, USA. emilysmith@gwu.edu.

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.

Keywords: Computational biology; Epidemiology; Omics; Pregnancy.

Publication types

Review

MeSH terms

Female
Genomics* / methods
Humans
Metabolomics / methods
Metagenomics
Molecular Epidemiology
Pregnancy
Proteomics* / methods

Grants and funding

INV-016930/GATES/Bill & Melinda Gates Foundation/United States