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Wijaya JC, Khanabdali R, Georgiou HM, Kalionis B. Ageing in human parturition: impetus of the gestation clock in the decidua†. Biol Reprod 2020; 103:695-710. [PMID: 32591788 DOI: 10.1093/biolre/ioaa113] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 05/22/2020] [Accepted: 06/23/2020] [Indexed: 12/18/2022] Open
Abstract
Despite sharing many common features, the relationship between ageing and parturition remains poorly understood. The decidua is a specialized lining of endometrial tissue, which develops in preparation for pregnancy. The structure and location of the decidua support its role as the physical scaffold for the growing embryo and placenta, and thus, it is vital to sustain pregnancy. Approaching term, the physical support properties of the decidua are naturally weakened to permit parturition. In this review, we hypothesize that the natural weakening of decidual tissue at parturition is promoted by the ageing process. Studies of the ageing-related functional and molecular changes in the decidua at parturition are reviewed and classified using hallmarks of ageing as the framework. The potential roles of decidual mesenchymal stem/stromal cell (DMSC) ageing in labor are also discussed because, although stem cell exhaustion is also a hallmark of ageing, its role in labor is not completely understood. In addition, the potential roles of extracellular vesicles secreted by DMSCs in labor, and their parturition-related miRNAs, are reviewed to gain further insight into this research area. In summary, the literature supports the notion that the decidua ages as the pregnancy progresses, and this may facilitate parturition, suggesting that ageing is the probable impetus of the gestational clocks in the decidua. This conceptual framework was developed to provide a better understanding of the natural ageing process of the decidua during parturition as well as to encourage future studies of the importance of healthy ageing for optimal pregnancy outcomes.
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Affiliation(s)
- Joan C Wijaya
- Pregnancy Research Centre, Department of Maternal-Fetal Medicine, Royal Women's Hospital, Parkville, Victoria, Australia.,University of Melbourne Department of Obstetrics and Gynaecology, Royal Women's Hospital, Parkville, Victoria, Australia
| | - Ramin Khanabdali
- Pregnancy Research Centre, Department of Maternal-Fetal Medicine, Royal Women's Hospital, Parkville, Victoria, Australia.,University of Melbourne Department of Obstetrics and Gynaecology, Royal Women's Hospital, Parkville, Victoria, Australia.,Department of Process Development, Exopharm Limited, Melbourne, Victoria, Australia
| | - Harry M Georgiou
- Pregnancy Research Centre, Department of Maternal-Fetal Medicine, Royal Women's Hospital, Parkville, Victoria, Australia.,University of Melbourne Department of Obstetrics and Gynaecology, Royal Women's Hospital, Parkville, Victoria, Australia
| | - Bill Kalionis
- Pregnancy Research Centre, Department of Maternal-Fetal Medicine, Royal Women's Hospital, Parkville, Victoria, Australia.,University of Melbourne Department of Obstetrics and Gynaecology, Royal Women's Hospital, Parkville, Victoria, Australia
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Ghaemi MS, DiGiulio DB, Contrepois K, Callahan B, Ngo TTM, Lee-McMullen B, Lehallier B, Robaczewska A, Mcilwain D, Rosenberg-Hasson Y, Wong RJ, Quaintance C, Culos A, Stanley N, Tanada A, Tsai A, Gaudilliere D, Ganio E, Han X, Ando K, McNeil L, Tingle M, Wise P, Maric I, Sirota M, Wyss-Coray T, Winn VD, Druzin ML, Gibbs R, Darmstadt GL, Lewis DB, Partovi Nia V, Agard B, Tibshirani R, Nolan G, Snyder MP, Relman DA, Quake SR, Shaw GM, Stevenson DK, Angst MS, Gaudilliere B, Aghaeepour N. Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy. Bioinformatics 2019; 35:95-103. [PMID: 30561547 PMCID: PMC6298056 DOI: 10.1093/bioinformatics/bty537] [Citation(s) in RCA: 102] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Revised: 06/22/2018] [Accepted: 07/02/2018] [Indexed: 12/12/2022] Open
Abstract
Motivation Multiple biological clocks govern a healthy pregnancy. These biological mechanisms produce immunologic, metabolomic, proteomic, genomic and microbiomic adaptations during the course of pregnancy. Modeling the chronology of these adaptations during full-term pregnancy provides the frameworks for future studies examining deviations implicated in pregnancy-related pathologies including preterm birth and preeclampsia. Results We performed a multiomics analysis of 51 samples from 17 pregnant women, delivering at term. The datasets included measurements from the immunome, transcriptome, microbiome, proteome and metabolome of samples obtained simultaneously from the same patients. Multivariate predictive modeling using the Elastic Net (EN) algorithm was used to measure the ability of each dataset to predict gestational age. Using stacked generalization, these datasets were combined into a single model. This model not only significantly increased predictive power by combining all datasets, but also revealed novel interactions between different biological modalities. Future work includes expansion of the cohort to preterm-enriched populations and in vivo analysis of immune-modulating interventions based on the mechanisms identified. Availability and implementation Datasets and scripts for reproduction of results are available through: https://nalab.stanford.edu/multiomics-pregnancy/. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Mohammad Sajjad Ghaemi
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Département de Mathématiques et de Génie Industriel, École Polytechnique de Montréal, QC, Canada
- Groupe d’Études et de Recherche en Analyse des Décision (GERAD), Montréal, QC, Canada
- Centre Interuniversitaire de Recherche sur les Réseaux d’Entreprise, la Logistique et le Transport (CIRRELT), Montréal, QC, Canada
| | - Daniel B DiGiulio
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - Kévin Contrepois
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Benjamin Callahan
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Population Health and Pathobiology, College of Veterinary Medicine, North Carolina State University, Raleigh, NC, USA
| | - Thuy T M Ngo
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Cancer Early Detection Advanced Research Center, Knight Cancer Institute and Department of Molecular and Medical Genetics, Oregon Health Sciences University, Portland, OR, USA
| | | | - Benoit Lehallier
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Anna Robaczewska
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - David Mcilwain
- Department of Microbiology and Immunology, Stanford University, Stanford, CA, USA
| | - Yael Rosenberg-Hasson
- Institute for Immunity, Transplantation and Infection, Human Immune Monitoring Center Stanford, CA, USA
| | - Ronald J Wong
- Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Cecele Quaintance
- Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Anthony Culos
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Natalie Stanley
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Athena Tanada
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Amy Tsai
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Dyani Gaudilliere
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Edward Ganio
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Xiaoyuan Han
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Kazuo Ando
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Leslie McNeil
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Martha Tingle
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Paul Wise
- Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Ivana Maric
- Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Marina Sirota
- Institute for Computational Health Sciences, University of California San Francisco, San Francisco, CA, USA
- Department of Pediatrics, University of California San Francisco, San Francisco, CA, USA
| | - Tony Wyss-Coray
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Virginia D Winn
- Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, CA, USA
| | - Maurice L Druzin
- Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, CA, USA
| | - Ronald Gibbs
- Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, CA, USA
| | - Gary L Darmstadt
- Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - David B Lewis
- Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Vahid Partovi Nia
- Département de Mathématiques et de Génie Industriel, École Polytechnique de Montréal, QC, Canada
- Groupe d’Études et de Recherche en Analyse des Décision (GERAD), Montréal, QC, Canada
| | - Bruno Agard
- Département de Mathématiques et de Génie Industriel, École Polytechnique de Montréal, QC, Canada
- Centre Interuniversitaire de Recherche sur les Réseaux d’Entreprise, la Logistique et le Transport (CIRRELT), Montréal, QC, Canada
| | - Robert Tibshirani
- Departments of Biomedical Data Sciences and Statistics, Stanford University, Stanford, CA, USA
- Department of Statistics, Stanford University School of Medicine, Stanford, CA, USA
| | - Garry Nolan
- Department of Microbiology and Immunology, Stanford University, Stanford, CA, USA
| | - Michael P Snyder
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - David A Relman
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Microbiology and Immunology, Stanford University, Stanford, CA, USA
| | - Stephen R Quake
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Gary M Shaw
- Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - David K Stevenson
- Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Martin S Angst
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Brice Gaudilliere
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Nima Aghaeepour
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
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