A review of single-cell transcriptomics and epigenomics studies in maternal and child health

Reference

• Ehiri J. Maternal and Child Health. NY, USA: Springer; 2014.
   Google Scholar
• Nelissen ECM, van Montfoort APA, Dumoulin JCM, et al. Epigenetics and the placenta. Hum Reprod Update. 2010;17(3):397–417. doi:10.1093/humupd/dmq052
   PubMed Web of Science ®Google Scholar
• Breton CV, Landon R, Kahn LG, et al. Exploring the evidence for epigenetic regulation of environmental influences on child health across generations. Commun Biol. 2021;4(1):769. doi:10.1038/s42003-021-02316-6
   PubMed Web of Science ®Google Scholar
• Li Y, Ma L, Wu D, et al. Advances in bulk and single-cell multi-omics approaches for systems biology and precision medicine. Brief Bioinform. 2021;22(5):p.bbab024. doi:10.1093/bib/bbab024
   Web of Science ®Google Scholar
• Kashima Y, Sakamoto Y, Kaneko K, et al. Single-cell sequencing techniques from individual to multiomics analyses. Exp Mol Med. 2020;52(9):1419–1427. doi:10.1038/s12276-020-00499-2
   PubMed Web of Science ®Google Scholar
• Soma-Pillay P, Nelson-Piercy C, Tolppanen H, et al. Physiological changes in pregnancy. Cardiovasc J Afr. 2016;27(2):89–94. doi:10.5830/CVJA-2016-021
   PubMed Web of Science ®Google Scholar
• Pavličev M, Wagner GP, Chavan AR, et al. Single-cell transcriptomics of the human placenta: inferring the cell communication network of the maternal–fetal interface. Genome Res. 2017;27(3):349–361. doi:10.1101/gr.207597.116
   PubMed Web of Science ®Google Scholar
• Liu Y, Fan X, Wang R, et al. Single-cell RNA-seq reveals the diversity of trophoblast subtypes and patterns of differentiation in the human placenta. Cell Res. 2018;28(8):819–832. doi:10.1038/s41422-018-0066-y
   PubMed Web of Science ®Google Scholar
• Vento-Tormo R, Efremova M, Botting RA, et al. Single-cell reconstruction of the early maternal–fetal interface in humans. Nature. 2018;563(7731):347–353. doi:10.1038/s41586-018-0698-6
   PubMed Web of Science ®Google Scholar
• Suryawanshi H, Morozov P, Straus A, et al. A single-cell survey of the human first-trimester placenta and decidua. Sci Adv. 2018;4(10):eaau4788. doi:10.1126/sciadv.aau4788
   PubMed Web of Science ®Google Scholar
• Sun T, Gonzalez TL, Deng N, et al. Sexually dimorphic crosstalk at the maternal–fetal Interface. J Clin Endocrinol Metab. 2020;105(12):e4831–e4847. doi:10.1210/clinem/dgaa503
   PubMed Web of Science ®Google Scholar
• Li H, Peng H, Hong W, et al. Human placental endothelial cell and trophoblast heterogeneity and differentiation revealed by single-cell RNA sequencing. Cells. 2022;12(1):87. doi:10.3390/cells12010087
   PubMed Web of Science ®Google Scholar
• Arutyunyan A, Roberts K, Troulé K, et al. Spatial multiomics map of trophoblast development in early pregnancy. Nature. 2023;616(7955):143–151. doi:10.1038/s41586-023-05869-0
   PubMed Web of Science ®Google Scholar
• Wang M, Liu Y, Sun R, et al. Single-nucleus multi-omic profiling of human placental syncytiotrophoblasts identifies cellular trajectories during pregnancy. Nat Genet. 2024;56:294–305. doi:10.1038/s41588-023-01647-w
   PubMedGoogle Scholar
• Marsh B, Zhou Y, Kapidzic M, et al. Regionally distinct trophoblast regulate barrier function and invasion in the human placenta. Elife. 2022;11:e78829. doi:10.7554/eLife.78829
   PubMed Web of Science ®Google Scholar
• Toothaker JM, Olaloye O, McCourt BT, et al. Immune landscape of human placental villi using single-cell analysis. Development. 2022;149(8):p.dev200013. doi:10.1242/dev.200013
   Web of Science ®Google Scholar
• Huang J, Li Q, Peng Q, et al. Single-cell RNA sequencing reveals heterogeneity and differential expression of decidual tissues during the peripartum period. Cell Prolif. 2021;54(2):e12967. doi:10.1111/cpr.12967
   PubMed Web of Science ®Google Scholar
• Wang Q, Li J, Wang S, et al. Single-cell transcriptional profiling reveals cellular and molecular divergence in human maternal–fetal interface. Sci Rep. 2022;12(1):10892. doi:10.1038/s41598-022-14516-z
   PubMed Web of Science ®Google Scholar
• Chen G, Ning B, Shi T. Single-cell RNA-seq technologies and related computational data analysis. Front Genet. 2019;10:317. doi:10.3389/fgene.2019.00317
   PubMed Web of Science ®Google Scholar
• Zhang Y, Wang D, Peng M, et al. Single-cell RNA sequencing in cancer research. J Exp Clin Cancer Res. 2021;40(1):81. doi:10.1186/s13046-021-01874-1
   PubMed Web of Science ®Google Scholar
• Paik DT, Cho S, Tian L, et al. Single-cell RNA sequencing in cardiovascular development, disease and medicine. Nat Rev Cardiol. 2020;17(8):457–473. doi:10.1038/s41569-020-0359-y
   PubMed Web of Science ®Google Scholar
• Andrews TS, Kiselev VY, McCarthy D, et al. Tutorial: guidelines for the computational analysis of single-cell RNA sequencing data. Nature Protocols. 2021;16(1):1–9. doi:10.1038/s41596-020-00409-w
   PubMed Web of Science ®Google Scholar
• Zheng GXY, Terry JM, Belgrader P, et al. Massively parallel digital transcriptional profiling of single cells. Nat Commun. 2017;8(1):14049. doi:10.1038/ncomms14049
   PubMed Web of Science ®Google Scholar
• Chu SK, Zhao S, Shyr Y, et al. Comprehensive evaluation of noise reduction methods for single-cell RNA sequencing data. Brief Bioinform. 2022;23(2):p.bbab565. doi:10.1093/bib/bbab565
   Web of Science ®Google Scholar
• Tran HTN, Ang KS, Chevrier M, et al. A benchmark of batch-effect correction methods for single-cell RNA sequencing data. Genome Biol. 2020;21:1–32. doi:10.1186/s13059-019-1850-9
   Web of Science ®Google Scholar
• Scialdone A, Natarajan KN, Saraiva LR, et al. Computational assignment of cell-cycle stage from single-cell transcriptome data. Methods. 2015;85:54–61. doi:10.1016/j.ymeth.2015.06.021
   PubMed Web of Science ®Google Scholar
• Linderman GC, Rachh M, Hoskins JG, et al. Fast interpolation-based t-SNE for improved visualization of single-cell RNA-seq data. Nat Methods. 2019;16(3):243–245. doi:10.1038/s41592-018-0308-4
   PubMed Web of Science ®Google Scholar
• Becht E, McInnes L, Healy J, et al. Dimensionality reduction for visualizing single-cell data using UMAP. Nat Biotechnol. 2019;37(1):38–44. doi:10.1038/nbt.4314
   Web of Science ®Google Scholar
• Qi R, Ma A, Ma Q, et al. Clustering and classification methods for single-cell RNA-sequencing data. Brief Bioinform. 2019;21(4):1196–1208. doi:10.1093/bib/bbz062
   Web of Science ®Google Scholar
• Sun X, Lin X, Li Z, et al. A comprehensive comparison of supervised and unsupervised methods for cell type identification in single-cell RNA-seq. Brief Bioinform. 2022;23(2):bbab567. doi:10.1093/bib/bbab567
   PubMed Web of Science ®Google Scholar
• Trapnell C, Cacchiarelli D, Grimsby J, et al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat Biotechnol. 2014;32(4):381–386. doi:10.1038/nbt.2859
   PubMed Web of Science ®Google Scholar
• Griffiths JA, Scialdone A, Marioni JC. Using single-cell genomics to understand developmental processes and cell fate decisions. Mol Syst Biol. 2018;14(4):e8046. doi:10.15252/msb.20178046
   PubMed Web of Science ®Google Scholar
• La Manno G, Soldatov R, Zeisel A, et al. RNA velocity of single cells. Nature. 2018;560(7719):494–498. doi:10.1038/s41586-018-0414-6
   PubMed Web of Science ®Google Scholar
• Zappia L, Theis FJ. Over 1000 tools reveal trends in the single-cell RNA-seq analysis landscape. Gen Biol. 2021;22(1):301. doi:10.1186/s13059-021-02519-4
   PubMed Web of Science ®Google Scholar
• Shi P, Nie Y, Yang J, et al. Fundamental and practical approaches for single-cell ATAC-seq analysis. aBIOTECH. 2022;3(3):212–223. doi:10.1007/s42994-022-00082-5
   PubMedGoogle Scholar
• Yan F, Powell DR, Curtis DJ, et al. From reads to insight: a hitchhiker's guide to ATAC-seq data analysis. Gen Biol. 2020;21(1):22. doi:10.1186/s13059-020-1929-3
   PubMed Web of Science ®Google Scholar
• Baek S, Lee I. Single-cell ATAC sequencing analysis: from data preprocessing to hypothesis generation. Comput Struct Biotechnol J. 2020;18:1429–1439. doi:10.1016/j.csbj.2020.06.012
   PubMed Web of Science ®Google Scholar
• Fiers MWEJ, Minnoye L, Aibar S, et al. Mapping gene regulatory networks from single-cell omics data. Brief Funct Genom. 2018;17(4):246–254. doi:10.1093/bfgp/elx046
   PubMed Web of Science ®Google Scholar
• De Rop FV, Hulselmans G, Flerin C, et al. Systematic benchmarking of single-cell ATAC-sequencing protocols. Nat Biotechnol. 2023;1–11.
   PubMed Web of Science ®Google Scholar
• Cusanovich DA, Hill AJ, Aghamirzaie D, et al. A single-cell atlas of in vivo mammalian chromatin accessibility. Cell. 2018;174(5):1309–1324.e18. doi:10.1016/j.cell.2018.06.052
   PubMed Web of Science ®Google Scholar
• Korsunsky I, Millard N, Fan J, et al. Fast, sensitive and accurate integration of single-cell data with Harmony. Nat Methods. 2019;16(12):1289–1296. doi:10.1038/s41592-019-0619-0
   PubMed Web of Science ®Google Scholar
• Satpathy AT, Granja JM, Yost KE, et al. Massively parallel single-cell chromatin landscapes of human immune cell development and intratumoral T cell exhaustion. Nat Biotechnol. 2019;37(8):925–936. doi:10.1038/s41587-019-0206-z
   PubMed Web of Science ®Google Scholar
• Stuart T, Butler A, Hoffman P, et al. Comprehensive integration of single-cell data. Cell. 2019;177(7):1888–1902.e21. doi:10.1016/j.cell.2019.05.031
   PubMed Web of Science ®Google Scholar
• Zhang Y, Liu T, Meyer CA, et al. Model-based analysis of ChIP-Seq (MACS). Gen Biol. 2008;9(9):R137. doi:10.1186/gb-2008-9-9-r137
   PubMed Web of Science ®Google Scholar
• Fang R, Preissl S, Li Y, et al. Comprehensive analysis of single cell ATAC-seq data with SnapATAC. Nat Commun. 2021;12(1):1337. doi:10.1038/s41467-021-21583-9
   PubMed Web of Science ®Google Scholar
• Klemm SL, Shipony Z, Greenleaf WJ. Chromatin accessibility and the regulatory epigenome. Nat Rev Genet. 2019;20(4):207–220. doi:10.1038/s41576-018-0089-8
   PubMed Web of Science ®Google Scholar
• Wang L, Zhang Q, Qin Q, et al. Current progress and potential opportunities to infer single-cell developmental trajectory and cell fate. Curr Opin Syst Biol. 2021;26:1–11. doi:10.1016/j.coisb.2021.03.006
   PubMedGoogle Scholar
• Lee MYY, Kaestner KH, Li M. Benchmarking algorithms for joint integration of unpaired and paired single-cell RNA-seq and ATAC-seq data. Gen Biol. 2023;24(1):244. doi:10.1186/s13059-023-03073-x
   PubMedGoogle Scholar
• Ji Z, Zhou W, Hou W, et al. Single-cell ATAC-seq signal extraction and enhancement with SCATE. Gen Biol. 2020;21(1):161. doi:10.1186/s13059-020-02075-3
   PubMed Web of Science ®Google Scholar
• Tracey LJ, An Y, Justice MJ. CyTOF: an emerging technology for single-cell proteomics in the mouse. Curr Protoc. 2021;1(4):e118. doi:10.1002/cpz1.118
   PubMedGoogle Scholar
• Spitzer MH, Nolan GP. Mass cytometry: single cells, many features. Cell. 2016;165(4):780–791. doi:10.1016/j.cell.2016.04.019
   PubMed Web of Science ®Google Scholar
• Bennett HM, Stephenson W, Rose CM, et al. Single-cell proteomics enabled by next-generation sequencing or mass spectrometry. Nat Methods. 2023;20(3):363–374. doi:10.1038/s41592-023-01791-5
   PubMed Web of Science ®Google Scholar
• Stoeckius M, Hafemeister C, Stephenson W, et al. Simultaneous epitope and transcriptome measurement in single cells. Nat Methods. 2017;14(9):865–868. doi:10.1038/nmeth.4380
   PubMed Web of Science ®Google Scholar
• Williams CG, Lee HJ, Asatsuma T, et al. An introduction to spatial transcriptomics for biomedical research. Gen Med. 2022;14(1):68. doi:10.1186/s13073-022-01075-1
   Google Scholar
• Liu B, Li Y, Zhang L. Analysis and visualization of spatial transcriptomic data [review]. Front Genet. 2022;12:p.785290. doi:10.3389/fgene.2021.785290
   Web of Science ®Google Scholar
• Mossman HW. Comparative morphogenesis of the fetal membranes and accessory uterine structures. Contrib Embryol Carneg Instn. 1937;26:129–246.
   Google Scholar
• Burton GJ, Jauniaux E. What is the placenta? Am J Obstet Gynecol. 2015;213(Suppl. 4):S6.e1–S6.e4. doi:10.1016/j.ajog.2015.07.050
   PubMed Web of Science ®Google Scholar
• Gude NM, Roberts CT, Kalionis B, et al. Growth and function of the normal human placenta. Thromb Res. 2004;114(5):397–407. doi:10.1016/j.thromres.2004.06.038
   PubMedGoogle Scholar
• Wang Y, Zhao S. Integrated systems physiology: from molecules to function to disease. Vascular Biology of the Placenta. San Rafael (CA): Morgan & Claypool Life Sciences Copyright © 2010 by Morgan & Claypool Life Sciences.; 2010.
   Google Scholar
• Huppertz B. The anatomy of the normal placenta. J Clin Pathol. 2008;61(12):1296–302. doi:10.1136/jcp.2008.055277
   PubMed Web of Science ®Google Scholar
• Nelson AC, Mould AW, Bikoff EK, et al. Single-cell RNA-seq reveals cell type-specific transcriptional signatures at the maternal–foetal interface during pregnancy. Nat Commun. 2016;7(1):11414. doi:10.1038/ncomms11414
   PubMedGoogle Scholar
• Zhou X, Xu Y, Ren S, et al. Single-cell RNA-seq revealed diverse cell types in the mouse placenta at mid-gestation. Exp Cell Res. 2021;405(2):112715. doi:10.1016/j.yexcr.2021.112715
   PubMed Web of Science ®Google Scholar
• Davenport KM, Ortega MS, Liu H, et al. Single-nuclei RNA sequencing (snRNA-seq) uncovers trophoblast cell types and lineages in the mature bovine placenta. Proc Natl Acad Sci U S A. 2023;120(12):e2221526120. doi:10.1073/pnas.2221526120
   PubMed Web of Science ®Google Scholar
• Jiang X, Zhai J, Xiao Z, et al. Identifying a dynamic transcriptomic landscape of the cynomolgus macaque placenta during pregnancy at single-cell resolution. Dev Cell. 2023;58(9):806–821.e7. doi:10.1016/j.devcel.2023.03.012
   PubMed Web of Science ®Google Scholar
• Goldenberg RL, Culhane JF, Johnson DC. Maternal infection and adverse fetal and neonatal outcomes. Clin Perinatol. 2005;32(3):523–559. doi:10.1016/j.clp.2005.04.006
   PubMed Web of Science ®Google Scholar
• Kalish BT, Kim E, Finander B, et al. Maternal immune activation in mice disrupts proteostasis in the fetal brain. Nat Neurosci. 2021;24(2):204–213. doi:10.1038/s41593-020-00762-9
   PubMed Web of Science ®Google Scholar
• Lim AI, McFadden T, Link VM, et al. Prenatal maternal infection promotes tissue-specific immunity and inflammation in offspring. Science. 2021;373(6558):eabf3002. doi:10.1126/science.abf3002
   PubMed Web of Science ®Google Scholar
• Lu-Culligan A, Chavan AR, Vijayakumar P, et al. Maternal respiratory SARS-CoV-2 infection in pregnancy is associated with a robust inflammatory response at the maternal–fetal interface. Med. 2021;2(5):591–610.e10. doi:10.1016/j.medj.2021.04.016
   PubMedGoogle Scholar
• Li Q, Wang W, Pei C, et al. Expression of SARS-CoV-2 entry genes ACE2 and TMPRSS2 at single cell resolution in the peripartum decidua. Am J Transl Res. 2021;13(5):4389–4400.
   PubMed Web of Science ®Google Scholar
• Chen J, Du L, Wang F, et al. Cellular and molecular atlas of the placenta from a COVID-19 pregnant woman infected at midgestation highlights the defective impacts on foetal health. Cell Prolif. 2022;55(4):e13204. doi:10.1111/cpr.13204
   PubMed Web of Science ®Google Scholar
• Garcia-Flores V, Romero R, Xu Y, et al. maternal–fetal immune responses in pregnant women infected with SARS-CoV-2. Nat Commun. 2022;13(1):320. doi:10.1038/s41467-021-27745-z
   PubMed Web of Science ®Google Scholar
• Gao L, Mathur V, Tam SKM, et al. Single-cell analysis reveals transcriptomic and epigenomic impacts on the maternal–fetal interface following SARS-CoV-2 infection. Nat Cell Biol. 2023;25(7):1047–1060. doi:10.1038/s41556-023-01169-x
   PubMed Web of Science ®Google Scholar
• Matute JD, Finander B, Pepin D, et al. Single-cell immunophenotyping of the fetal immune response to maternal SARS-CoV-2 infection in late gestation. Pediatr Res. 2022;91(5):1090–1098. doi:10.1038/s41390-021-01793-z
   PubMed Web of Science ®Google Scholar
• Sureshchandra S, Zulu MZ, Doratt BM, et al. Single-cell RNA sequencing reveals immunological rewiring at the maternal–fetal interface following asymptomatic/mild SARS-CoV-2 infection. Cell Rep. 2022;39(11):110938. doi:10.1016/j.celrep.2022.110938
   PubMed Web of Science ®Google Scholar
• Leddy MA, Power ML, Schulkin J. The impact of maternal obesity on maternal and fetal health. Rev Obstet Gynecol. 2008;1(4):170–178.
   PubMedGoogle Scholar
• Enninga EAL, Jang JS, Hur B, et al. Maternal obesity is associated with phenotypic alterations in fetal immune cells by single-cell mass cytometry. Am J Reprod Immunol. 2021;85(3):e13358. doi:10.1111/aji.13358
   PubMed Web of Science ®Google Scholar
• Sureshchandra S, Mendoza N, Jankeel A, et al. Phenotypic and epigenetic adaptations of cord blood CD4+ T cells to maternal obesity [original research]. Front Immunol. 2021;12:p.617592. doi:10.3389/fimmu.2021.617592
   Web of Science ®Google Scholar
• Pan M-H, Zhu C-C, Ju J-Q, et al. Single-cell transcriptome analysis reveals that maternal obesity affects DNA repair, histone methylation, and autophagy level in mouse embryos. J Cell Physiol. 2021;236(7):4944–4953. doi:10.1002/jcp.30201
   PubMed Web of Science ®Google Scholar
• Zhao L, Law NC, Gomez NA, et al. Obesity impairs embryonic myogenesis by enhancing BMP signaling within the dermomyotome. Adv Sci (Weinh). 2021;8(22):e2102157. doi:10.1002/advs.202102157
   PubMedGoogle Scholar
• Sureshchandra S, Chan CN, Robino JJ, et al. Maternal Western-style diet remodels the transcriptional landscape of fetal hematopoietic stem and progenitor cells in rhesus macaques. Stem Cell Rep. 2022;17(12):2595–2609. doi:10.1016/j.stemcr.2022.10.003
   PubMed Web of Science ®Google Scholar
• Fan P, Wang Y, Lu K, et al. Modeling maternal cholesterol exposure reveals a reduction of neural progenitor proliferation using human cerebral organoids. Life Med. 2022;2(2):p.lnac034. doi:10.1093/lifemedi/lnac034
   Google Scholar
• McIntyre HD, Catalano P, Zhang C, et al. Gestational diabetes mellitus. Nat Rev Dis Prim. 2019;5(1):47. doi:10.1038/s41572-019-0098-8
   PubMed Web of Science ®Google Scholar
• Yang Y, Guo F, Peng Y, et al. Transcriptomic profiling of human placenta in gestational diabetes mellitus at the single-cell level [original research]. Front Endocrinol. 2021;12:p.679582. doi:10.3389/fendo.2021.679582
   Web of Science ®Google Scholar
• Jiao B, Wang Y, Li S, et al. Dissecting human placental cells heterogeneity in pre-eclampsia and gestational diabetes using single-cell sequencing. Mol Immunol. 2023;161:104–118. doi:10.1016/j.molimm.2023.07.005
   PubMed Web of Science ®Google Scholar
• Manivannan S, Mansfield C, Zhang X, et al. Single-cell transcriptomic profiling unveils dysregulation of cardiac progenitor cells and cardiomyocytes in a mouse model of maternal hyperglycemia. Comm Biol. 2022;5(1):820. doi:10.1038/s42003-022-03779-x
   PubMed Web of Science ®Google Scholar
• Rana S, Lemoine E, Granger JP, et al. Pre-eclampsia. Circul Res. 2019;124(7):1094–1112. doi:10.1161/CIRCRESAHA.118.313276
   PubMed Web of Science ®Google Scholar
• Zhen Lim TX, Pickering TA, Lee RH, et al. Hypertensive disorders of pregnancy and occurrence of ADHD, ASD, and epilepsy in the child: a meta-analysis. Pregnan Hypertens. 2023;33:22–29. doi:10.1016/j.preghy.2023.06.002
   PubMed Web of Science ®Google Scholar
• Tsang JCH, Vong JSL, Ji L, et al. Integrative single-cell and cell-free plasma RNA transcriptomics elucidates placental cellular dynamics. Proc Natl Acad Sci U S A. 2017;114(37):E7786–E7795. doi:10.1073/pnas.1710470114
   PubMed Web of Science ®Google Scholar
• Zhou W, Wang H, Yang Y, et al. Trophoblast cell subtypes and dysfunction in the placenta of individuals with pre-eclampsia revealed by single-cell RNA sequencing. Mol Cells. 2022;45(5):317–328. doi:10.14348/molcells.2021.0211
   PubMed Web of Science ®Google Scholar
• Zhang T, Bian Q, Chen Y, et al. Dissecting human trophoblast cell transcriptional heterogeneity in pre-eclampsia using single-cell RNA sequencing. Mol Genet Genom Med. 2021;9(8):e1730. doi:10.1002/mgg3.1730
   PubMed Web of Science ®Google Scholar
• Luo F, Liu F, Guo Y, et al. Single-cell profiling reveals immune disturbances landscape and HLA-F-mediated immune tolerance at the maternal–fetal interface in pre-eclampsia. Front Immunol. 2023;14:1234577. doi:10.3389/fimmu.2023.1234577
   PubMed Web of Science ®Google Scholar
• Admati I, Skarbianskis N, Hochgerner H, et al. Two distinct molecular faces of pre-eclampsia revealed by single-cell transcriptomics. Med. 2023;4(10):687–709.e7. doi:10.1016/j.medj.2023.07.005
   PubMedGoogle Scholar
• Yang J, Gong L, Liu Q, et al. Single-cell RNA-seq reveals developmental deficiencies in both the placentation and the decidualization in women with late-onset pre-eclampsia. Front Immunol. 2023;14:1142273. doi:10.3389/fimmu.2023.1142273
   PubMed Web of Science ®Google Scholar
• Hu J, Guo Q, Liu C, et al. Immune cell profiling of preeclamptic pregnant and postpartum women by single-cell RNA sequencing. Int Rev Immunol. 2022;43(1):1–12. doi:10.1080/08830185.2022.2144291
   PubMed Web of Science ®Google Scholar
• Gómez-Roig MD, Pascal R, Cahuana MJ, et al. Environmental exposure during pregnancy: influence on prenatal development and early life: a comprehensive review. Fet Diagn Ther. 2021;48(4):245–257. doi:10.1159/000514884
   PubMed Web of Science ®Google Scholar
• Hsu KS, Goodale BC, Ely KH, et al. Single-cell RNA-seq analysis reveals that prenatal arsenic exposure results in long-term, adverse effects on immune gene expression in response to influenza A infection. Toxicol Sci. 2020;176(2):312–328. doi:10.1093/toxsci/kfaa080
   PubMed Web of Science ®Google Scholar
• Salem NA, Mahnke AH, Konganti K, et al. Cell-type and fetal-sex-specific targets of prenatal alcohol exposure in developing mouse cerebral cortex. iScience. 2021;24(5):102439. doi:10.1016/j.isci.2021.102439
   PubMed Web of Science ®Google Scholar
• Hunter R, Baird B, Garcia M, et al. Gestational ozone inhalation elicits maternal cardiac dysfunction and transcriptional changes to placental pericytes and endothelial cells. Toxicol Sci. 2023;196(2):238–249. doi:10.1093/toxsci/kfad092
   PubMed Web of Science ®Google Scholar
• Goldenberg RL, Culhane JF, Iams JD, et al. Epidemiology and causes of preterm birth. Lancet. 2008;371(9606):75–84. doi:10.1016/S0140-6736(08)60074-4
   PubMed Web of Science ®Google Scholar
• Liu X, Aneas I, Sakabe N, et al. Single cell profiling at the maternal–fetal interface reveals a deficiency of PD-L1+ non-immune cells in human spontaneous preterm labor. Sci Rep. 2023;13(1):7903. doi:10.1038/s41598-023-35051-5
   PubMed Web of Science ®Google Scholar
• Pique-Regi R, Romero R, Tarca AL, et al. Single cell transcriptional signatures of the human placenta in term and preterm parturition. Elife. 2019;8:p.e52004. doi:10.7554/eLife.52004
   Web of Science ®Google Scholar
• Garcia-Flores V, Romero R, Peyvandipour A, et al. A single-cell atlas of murine reproductive tissues during preterm labor. Cell Rep. 2023;42(1):111846. doi:10.1016/j.celrep.2022.111846
   PubMed Web of Science ®Google Scholar