Placental gene expression-based cell type deconvolution: Cell proportions drive preeclampsia gene expression differences
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PROVIDER: PRJNA756030 | ENA |
REPOSITORIES: ENA
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Project description:The placenta mediates adverse pregnancy outcomes, including preeclampsia, characterized by gestational hypertension and proteinuria. Placental cell type heterogeneity in preeclampsia is not well-understood and limits mechanistic interpretation of bulk gene expression measures. We generated single-cell RNA-sequencing samples for integration with existing data to create the largest deconvolution reference of 19 fetal and 8 maternal cell types from placental villous tissue at term. We deconvoluted eight published microarray case-control studies of preeclampsia. Our findings indicate substantial placental cellular heterogeneity in preeclampsia that predict previously observed bulk gene expression differences. Our deconvolution reference lays the groundwork for cellular heterogeneity-aware investigation into placental dysfunction and adverse birth outcomes.
2022-08-22 | GSE182381 | GEO
Project description:The series is composed of thirty hybridizations for analysis of differentially expressed genes in normal placenta tissues from patients with normal labor and placenta tissues from patients with severe preeclampsia. Patients tissues samples were obtained from (Vasilis. Total RNA extraction was performed by using the MagNa Pure Compact RNA Isolation Kit (Roche Applied Science). Keywords: Gene expression study, Disease state Twenty-six out of 50 normal placentas were randomly selected to match with 17 preeclamptic placentas, accounting for parity. Microarrays were performed applying a direct comparison design.
2010-05-26 | E-GEOD-10588 | biostudies-arrayexpress
Project description:The series is composed of thirty hybridizations for analysis of differentially expressed genes in normal placenta tissues from patients with normal labor and placenta tissues from patients with severe preeclampsia. Patients tissues samples were obtained from (Vasilis. Total RNA extraction was performed by using the MagNa Pure Compact RNA Isolation Kit (Roche Applied Science). Keywords: Gene expression study, Disease state
2008-06-20 | GSE10588 | GEO
Project description:Analysis of genome-wide gene expression in placentas from women with preterm severe preeclampsia, with or without HELLP syndrome, compared to gestational age-matched controls. The hypothesis tested in the present study was that placental transcriptomic changes in preeclampsia are considerably different from controls. The results provide important information on placental transcriptomic changes in preeclampsia.
2018-12-30 | GSE66273 | GEO
Project description:Preeclampsia is a severe placenta-related pregnancy disorder that is generally divided into two subtypes named early-onset preeclampsia (onset <34 weeks of gestation), and lateonset preeclampsia (onset ≥34 weeks of gestation), with distinct pathophysiological origins. Both forms of preeclampsia have been associated with maternal systemic inflammation. However, alterations in the placental immune system have been less well characterized. Here, we studied immunological alterations in early- and late-onset preeclampsia placentas using a targeted expression profile approach. RNA was extracted from snap-frozen placenta samples (healthy n=13, early-onset preeclampsia n=13, and late-onset preeclampsia n=6). The expression of 730 immune-related genes from the Pan Cancer Immune Profiling Panel was measured, and the data were analyzed Q10 in the advanced analysis module of nSolver software (NanoString Technology). The results showed that early-onset preeclampsia placentas displayed reduced expression of complement, and toll-like receptor (TLR) associated genes, specifically TLR1 and TLR4. Mast cells and M2 macrophages were also decreased in early-onset preeclampsia compared to healthy pl acentas. The findings were confirmed by an immunohistochemistry approach using 20 healthy, 19 early-onset preeclampsia, and 10 late-onset preeclampsia placentas. We conclude that the placental innate immune system is altered in early-onset preeclampsia compared to uncomplicated pregnancies. The absence of these alterations in late-onset preeclampsia placentas indicates dissimilar immunological profiles. The study revealed distinct pathophysiological processes in earlyonset and late-onset preeclampsia placentas and imply that a tailored treatment to each subtype is desirable.
2021-12-13 | GSE190639 | GEO
Project description:The project aimed to investigate the possibility to use proteomics data to deconvolute cell line proportions in mixed samples. Samples containing either HEK 293, Caco-2, or A549 cells and mixtures of the three cell lines was analysed using the total protein approach. This was then used for proteomics informed deconvolution. The results show that proteome deconvolution provides an effective tool for investigating cellular composition in mixed samples. This was later applied also to in silico mixtures of primary human liver cells and liver tissue. However, those data are presented elsewhere.
2023-10-24 | PXD027282 | Pride
Project description:Difference in RNA content of different cell types introduces bias to gene expression deconvolution methods. If ERCC spike-ins are introduced into samples, predicted proportions of deconvolution methods can be corrected
2019-04-03 | GSE129240 | GEO
Project description:The pathogenesis of preeclampsia superimposed on chronic hypertension is poorly understood relative to preeclampsia occurring in pregnant people without chronic hypertension. Placental transcriptomes in pregnancies complicated by de novo preeclampsia and superimposed preeclampsia have not been previously compared.
2022-05-30 | GSE204835 | GEO
Project description:ObjectiveCandidate genes that are associated with preeclampsia have not been described fully. We conducted microarray and confirmatory quantitative real time polymerase chain reaction studies to investigate global placental gene expression in preeclampsia.Study designRNA was extracted from placental samples that were collected from 18 preeclampsia cases and 18 normotensive control subjects. Oligonucleotide probes that represented 22,000 genes were used to measure gene expression in each sample. Differential gene expression was evaluated with the Student t test, fold change assessment, and significance analysis of microarrays. Functions and functional relationships of differentially expressed genes were evaluated.ResultsGenes (n = 58) that participated in immune system, inflammation, oxidative stress, signaling, growth, and development pathways were expressed differentially in preeclampsia. These genes included previously described candidate genes (such as leptin), potential candidate genes with related functions (such as CYP11A) and novel genes (such as CDKN1C).ConclusionExpression of genes (both candidate and novel) with diverse functions is associated with preeclampsia risk, which reflects the complex pathogenesis.
| S-EPMC2702488 | biostudies-literature
Project description:Numerous multi-omic investigations of cancer tissue have documented varying and poor pairwise transcript:protein quantitative correlations and most deconvolution tools aiming to predict cell type proportions (cell admixture) have been developed and credentialed using transcript-level data alone. To estimate cell admixture using protein abundance data, we analyzed proteome (and transcriptome data) generated from contrived admixtures of tumor, stroma, and immune cell models or those selectively harvested from the tissue microenvironment by laser microdissection from high grade serous ovarian cancer (HGSOC) tumors. Co-quantified transcripts and proteins performed similarly to estimate stroma and immune cell admixture in two commonly used deconvolution algorithms ESTIMATE and ConsensusTME (r ≥ 0.63). Here we have developed and optimized protein-based signatures to estimate cell admixture proportions and benchmarked these using bulk tumor proteomics data from over 150 HGSOC patients. The optimized protein signatures supporting cell type proportion estimates from bulk tissue proteomic data are available at https://lmdomics.org/ProteoMixture/.
2024-01-12 | PXD044157 | Pride