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Anttila, C.

Publications and source records attributed to Anttila, C..

2 recordsLinked to original sources

Spatial analysis of Hofbauer cell transcriptome, distribution and morphology in placentas exposed to Plasmodium falciparum

Placental infection remains a significant health burden for mothers and their babies in low-income countries, especially in sub-Saharan Africa, where malaria transmission is intense. An increase in inflammatory biomarkers and poor vascularisation are characteristics of placentas infected with malaria. Hofbauer cells (HBCs) - placental villous macrophages of fetal origin - are one of the most abundant immune cells in the placenta. HBCs are thought to have roles in angiogenic processes and have been linked with the pathophysiology of several infections and inflammatory conditions during pregnancy, including malaria (caused by Plasmodium falciparum). However, there is limited in situ data on the transcriptional, proteomic or morphologic profile of these cells either during or following clearance of P. falciparum infection. We leveraged placental samples prospectively collected at delivery from 610 Malawian women enduring a high burden of malaria and other infections and nutritional deficiencies. We profiled placentas through spatial transcriptomic and proteomic platforms to discern in situ HBC features that could distinguish placentas with or without evidence of past malaria. In this cohort, past placental infection was common and was associated with lower birth weight babies (adjusted effect [95% confidence interval], -80.9 [-165.9, -3.7] g, P= 0.040). However, at term, HBC numbers, abundance, and transcriptional profiles from placentas with evidence of past infection were similar to those of placentas without malaria. HBCs may recover post-infection back to a basal state or may be replaced in the tissue over the course of pregnancy. Placentas with evidence of past malaria did show evidence of reduced fetal vessel development (mean area difference: -22.8% [-37.6, -7.9], P=0.003). Reduced vascular development following infection early in pregnancy may reflect disturbances to the normal vasculogenic and angiogenic processes, of which HBCs are an integral part.

immunology↗

Multimodal single cell analysis of the paediatric lower airway reveals novel immune cell phenotypes in early life health and disease

Inflammation is a key driver of cystic fibrosis (CF) lung disease, not addressed by current standard care. Improved understanding of the mechanisms leading to aberrant inflammation may assist the development of effective anti-inflammatory therapy. Single-cell RNA sequencing (scRNA-seq) allows profiling of cell composition and function at previously unprecedented resolution. Herein, we seek to use multimodal single-cell analysis to comprehensively define immune cell phenotypes, proportions and functional characteristics in preschool children with CF. We analyzed 42,658 cells from bronchoalveolar lavage of 11 preschool children with CF and a healthy control using scRNA-seq and parallel assessment of 154 cell surface proteins. Validation of cell types identified by scRNA-seq was achieved by assessment of samples by spectral flow cytometry. Analysis of transcriptome expression and cell surface protein expression, combined with functional pathway analysis, revealed 41 immune and epithelial cell populations in BAL. Spectral flow cytometry analysis of over 256,000 cells from a subset of the same patients revealed high correlation in major cell type proportions across the two technologies. Macrophages consisted of 13 functionally distinct sub populations, including previously undescribed populations enriched for markers of vesicle production and regulatory/repair functions. Other novel cell populations included CD4 T cells expressing inflammatory IFN/{beta} and NF{kappa}B signalling genes. Our work provides a comprehensive cellular analysis of the pediatric lower airway in preschool children with CF, reveals novel cell types and provides a reference for investigation of inflammation in early life CF.

systems biology↗