| Literature DB >> 33957866 |
João Mendes1,2,3, Paulo Rodrigues-Santos4,5,6,7,8, Ana Luísa Areia4,5,9, Jani-Sofia Almeida4,5,6,7,8, Vera Alves4,5,6, Manuel Santos-Rosa4,5,6, Anabela Mota-Pinto4,5,10.
Abstract
BACKGROUND: Preterm birth (PTB) is one of the major causes of neonatal morbidity and mortality worldwide. It is commonly accepted that the act of giving birth is the final step in a proinflammatory signaling cascade, orchestrated by an intrauterine milieu coupled to hormonal cues. Consequently, the inflammatory process plays a pivotal role during the pathogenesis of human labor, both in term and preterm deliveries. The ability of innate lymphoid cells (ILCs) to act as pro-inflammatory mediators arose the interest to study their role in normal and pathological pregnancies. The aim of this work was to analyze the relative frequencies of ILCs subsets in pregnancy and the levels of IL-4, IL-17, IL-22, and IFN-γ as inflammatory mediators. Accordingly, we hypothesized that changes in the proportions of ILCs subpopulations could be related to preterm birth.Entities:
Keywords: Inflammation; Innate immune response; Innate lymphoid cells; Preterm birth; Preterm labor
Mesh:
Substances:
Year: 2021 PMID: 33957866 PMCID: PMC8101215 DOI: 10.1186/s12865-021-00423-x
Source DB: PubMed Journal: BMC Immunol ISSN: 1471-2172 Impact factor: 3.615
Descriptive statistics of study and control group. We found a significant statistical difference in birth weight, which is lower in the study group (* p < 0.001 t-test, 95% CI)
| Median Maternal Age | Median Gestational Age | Median Birth Weight | Median Placenta Weight | |
|---|---|---|---|---|
| 34 (33 < 95% CI < 37) | 40 (39 < 95% CI < 40) | 3635 (2962 < 95% CI < 3755) | 500.5 (448 < 95% CI < 603) | |
| 32 (22 < 95% CI < 35) | 36 (34 < 95% CI < 37) | 2505 (2130 < 95% CI < 3125) | 472 (413 < 95% CI < 731) |
Fig. 1Graphic displaying the relative percentage of the different ILC populations in Peripheral Blood samples in pregnant women in the 1st (n = 24), 2nd (n = 18) and 3rd (n = 18)
Fig. 2Graphic displaying the relative percentage of the different ILC populations in Peripheral Blood samples in the moment of labor in full term birth (FTB, n = 15) compared to preterm birth (PTB, n = 6)
Fig. 3Graphic displaying the relative percentage of the different ILC populations in Peripheral Blood samples before (BPgr) or after the administration of Progesterone (24 h Pgr) in women who delivered PTB
Fig. 4Decidual and cord blood ILCs in FTB and PTB. a Graphic displaying the relative percentage of the different ILC populations in full term birth (FTB, n = 15) compared to preterm birth (PTB, n = 6), in human decidua. b Graphic displaying the relative percentage of the different ILC populations in FTB (n = 15) compared to PTB (n = 5) in cord blood samples. Multiple t-student tests where used for statistical analysis with a 95% confidence interval, p-value * p < 0.05; ** p < 0.01 (two tailed)
Fig. 5Enzyme-Linked Immunosorbent Assay (ELISA) in cord blood and maternal peripheral blood in FTB and PTB. a Graphic displaying IL-17 plasmatic concentrations in cord blood FTB (n = 15) and PTB (n = 5), as well as, plasmatic concentrations of IL-17 in maternal Peripheral Blood (PB) (n = 6). b Graphic displaying IL-22 plasmatic concentrations in cord blood FTB (n = 15) and PTB (n = 6), as well as, plasmatic concentrations of IL-22 in maternal Peripheral Blood (PB) (n = 6). c Graphic displaying Ifn-γ plasmatic concentrations in cord blood FTB (n = 15) and PTB (n = 6), as well as, plasmatic concentrations of Ifn-γ in maternal Peripheral Blood (PB). d Graphic displaying IL-4 plasmatic concentrations in cord blood FTB (n = 15) and PTB (n = 6), as well as, plasmatic concentrations of IL-4 in maternal Peripheral Blood (PB). Student’s t-tests were used for statistical analysis with a 95% confidence interval. A statistical significant decrease in Ifn-γ plasma concentration was found, in peripheral blood samples in women with PTB
Fig. 6Gating strategy for identification of ILC3 subpopulations. a Identification of lymphocyte population. b Gating of CD45 + CD3-cells. c Selection Lin-CD127+ cells (d). isolating CD161+ cells. e Gating ILC3 cells as CRTH2- CD117+. f Discrimination between ILC3 NCR+ and ILC3 NCR- based on NKp44 expression (Data analyzed in FlowJo®)
Fig. 7Full minus one (FMO) for CRTH2 (a) and FMO for CD161 (b)