An emerging role for comprehensive proteome analysis in human pregnancy research

Renu Shankar, Neil Gude, Fiona Cullinane, Shaun Brennecke, Anthony W. Purcell, Eric K. Moses

Research output: Contribution to journalReview ArticleResearchpeer-review

38 Citations (Scopus)


Elucidation of underlying cellular and molecular mechanisms is pivotal to the comprehension of biological systems. The successful progression of processes such as pregnancy and parturition depends on the complex interactions between numerous biological molecules especially within the uterine microenvironment. The tissue- and stage-specific expression of these biomolecules is intricately linked to and modulated by several endogenous and exogenous factors. Malfunctions may manifest as pregnancy disorders such as preterm labour, pre-eclampsia and fetal growth restriction that are major contributors to maternal and perinatal morbidity and mortality. Despite the immense amount of information available, our understanding of several aspects of these physiological processes remains incomplete. This translates into significant difficulties in the timely diagnosis and effective treatment of pregnancy-related complications. However, the emergence of powerful mass spectrometry-based proteomic techniques capable of identifying and characterizing multiple proteins simultaneously has added a new dimension to the field of biomedical research. Application of these high throughput methodologies with more conventional techniques in pregnancy-related research has begun to provide a novel perspective on the biochemical blueprint of pregnancy and its related disorders. Further, by enabling the identification of proteins specific to a disease process, proteomics is likely to contribute, not only to the comprehension of the underlying pathophysiologies, but also to the clinical diagnosis of multifactorial pregnancy disorders. Although the application of this technology to pregnancy research is in its infancy, characterization of the cellular proteome, unearthing of functional networks and the identification of disease biomarkers can be expected to significantly improve maternal healthcare in the future.

Original languageEnglish
Pages (from-to)685-696
Number of pages12
Issue number6
Publication statusPublished - 1 Jun 2005
Externally publishedYes

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