The Neuronal Transcription Factor Creb3l1 Potential Upregulates Ntrk2 in the Hypertensive Microenvironment to Promote Vascular Smooth Muscle Cell-Neuron Interaction and Prevent Neurons from Ferroptosis: A Bioinformatic Research of scRNA-seq Data

Zhao, Xiaoyu; Yang, Jie; Yang, Chuanhua

doi:10.1155/2022/8339759

Cited by 8 publications

(5 citation statements)

References 43 publications

(40 reference statements)

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“…CREB3L1 has been mostly found to be involved in tumour progression in the nervous system and as well to promote vascular smooth muscle cell-neuron interaction. 46,47 In other studies, CREB3L1 has also been found to play an important role in maintaining the function of vascular integrity and regulation of the blood pressure. 48 However, variations in the expression of CREB3L1 in DVT patients remain to be investigated.…”

Section: Discussionmentioning

confidence: 94%

Using genotyping and whole-exome sequencing data to improve genetic risk prediction in deep venous thrombosis

Faro

Johansson

Höglund

et al. 2022

Preprint

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BackgroundDeep Vein Thrombosis (DVT) is a common disease that can lead to serious complications such as pulmonary embolism and in-hospital mortality. More than 60% of DVT risk is influenced by genetic factors, such as Factor V Leiden (FVL) and prothrombin G20210A mutations (PTM). Characterising the genetic contribution and stratifying participants based on their genetic makeup can favourably impact risk prediction. Therefore, we aimed to develop and evaluate a genetic-based prediction model for DVT based on polygenic risk score (PRS) in the UK Biobank cohort.MethodsWe performed a genome-wide association study (GWAS) and constructed a PRS in the 60% (N=284,591) of the UK Biobank cohort. The remaining 40% (N=147,164) was employed to evaluate the PRS and to perform gene-based tests on exome-sequencing data to identify effects by rare variants.ResultsIn the GWAS, we discovered and replicated a novel variant (rs11604583) near TRIM51 gene and in the exome-sequencing data, and we identified a novel rare variant (rs187725533) located near CREB3L1, associated with 2.2-fold higher risk of DVT. In our PRS model, the top decile is associated with 3.4-fold increased risk of DVT, an effect that is 2.3-fold, when excluding FVL carriers. In the top PRS decile, cumulative risk of DVT at age of 80 years is 10% for FVL carriers, contraposed to 5% for FVL non-carriers.ConclusionWe showed that common and rare variants influence DVT risk and that the PRS improves risk prediction on top of FVL. This suggests that individuals classified with high PRS scores could benefit from early genetic screening.

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Section: Discussionmentioning

confidence: 94%

Using genotyping and whole-exome sequencing data to improve genetic risk prediction in deep venous thrombosis

Faro

Johansson

Höglund

et al. 2022

Preprint

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“…Secondly, RcisTarget was used to identify TFs and the genes that they directly regulate. Finally, each formed regulon was scored in each cell using AUCell [ 39 ]. Key TFs for tumor cells of each BC subtype were identified with p < 0.01.…”

Section: Methodsmentioning

confidence: 99%

Delving into the Heterogeneity of Different Breast Cancer Subtypes and the Prognostic Models Utilizing scRNA-Seq and Bulk RNA-Seq

Qin

et al. 2022

IJMS

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Background: Breast cancer (BC) is the most common malignancy in women with high heterogeneity. The heterogeneity of cancer cells from different BC subtypes has not been thoroughly characterized and there is still no valid biomarker for predicting the prognosis of BC patients in clinical practice. Methods: Cancer cells were identified by calculating single cell copy number variation using the inferCNV algorithm. SCENIC was utilized to infer gene regulatory networks. CellPhoneDB software was used to analyze the intercellular communications in different cell types. Survival analysis, univariate Cox, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox analysis were used to construct subtype specific prognostic models. Results: Triple-negative breast cancer (TNBC) has a higher proportion of cancer cells than subtypes of HER2+ BC and luminal BC, and the specifically upregulated genes of the TNBC subtype are associated with antioxidant and chemical stress resistance. Key transcription factors (TFs) of tumor cells for three subtypes varied, and most of the TF-target genes are specifically upregulated in corresponding BC subtypes. The intercellular communications mediated by different receptor–ligand pairs lead to an inflammatory response with different degrees in the three BC subtypes. We establish a prognostic model containing 10 genes (risk genes: ATP6AP1, RNF139, BASP1, ESR1 and TSKU; protective genes: RPL31, PAK1, STARD10, TFPI2 and SIAH2) for luminal BC, seven genes (risk genes: ACTR6 and C2orf76; protective genes: DIO2, DCXR, NDUFA8, SULT1A2 and AQP3) for HER2+ BC, and seven genes (risk genes: HPGD, CDC42 and PGK1; protective genes: SMYD3, LMO4, FABP7 and PRKRA) for TNBC. Three prognostic models can distinguish high-risk patients from low-risk patients and accurately predict patient prognosis. Conclusions: Comparative analysis of the three BC subtypes based on cancer cell heterogeneity in this study will be of great clinical significance for the diagnosis, prognosis and targeted therapy for BC patients.

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“…CellPhoneDB was used to analyze cell-cell communication. Single-cell gene expression matrices were calculated as input files to predict ligand-receptor interaction pairs among cells [ 27 , 28 ]. We further screened neuropeptide-associated cluster marker genes from these predicted ligand-receptor pairs, which were then included in the subsequent analysis.…”

Section: Methodsmentioning

confidence: 99%

Single-Cell Analysis Reveals the Role of the Neuropeptide Receptor FPR2 in Monocytes in Kawasaki Disease: A Bioinformatic Study

et al. 2022

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Exploring the role of neuropeptides in the communication between monocyte subtypes facilitates an investigation of the pathogenesis of Kawasaki disease (KD). We investigated the patterns of interaction between neuropeptide-associated ligands and receptors in monocyte subpopulations in KD patients. Single-cell analysis was employed for the identification of cell subpopulations in KD patients, and monocytes were classified into 3 subpopulations: classical monocytes (CMs), intermediate monocytes (IMs), and nonclassical monocytes (NCMs). Cell-cell communication and differential analyses were used to identify ligand-receptor interactions in monocytes. Five neuropeptide-related genes (SORL1, TNF, SORT1, FPR2, and ANXA1) were involved in cell-cell interactions, wherein FPR2, a neuropeptide receptor, was significantly highly expressed in KD. Weighted gene coexpression network analysis revealed a significant correlation between the yellow module and FPR2 ( p < 0.001 , CC = 0.43 ). Using the genes in the yellow module, we constructed a PPI network to assess the possible functions of the FPR2-associated gene network. Gene set enrichment analysis showed that increased FPR2 levels may be involved in immune system regulation. FPR2 in CMs mediates the control of inflammation in KD. The findings of this study may provide a novel target for the clinical treatment of KD.

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The Neuronal Transcription Factor Creb3l1 Potential Upregulates Ntrk2 in the Hypertensive Microenvironment to Promote Vascular Smooth Muscle Cell-Neuron Interaction and Prevent Neurons from Ferroptosis: A Bioinformatic Research of scRNA-seq Data

Cited by 8 publications

References 43 publications

Using genotyping and whole-exome sequencing data to improve genetic risk prediction in deep venous thrombosis

Using genotyping and whole-exome sequencing data to improve genetic risk prediction in deep venous thrombosis

Delving into the Heterogeneity of Different Breast Cancer Subtypes and the Prognostic Models Utilizing scRNA-Seq and Bulk RNA-Seq

Single-Cell Analysis Reveals the Role of the Neuropeptide Receptor FPR2 in Monocytes in Kawasaki Disease: A Bioinformatic Study

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