Comparisons of microRNA set enrichment analysis tools on cancer de-regulated miRNAs from TCGA expression datasets

2020 ◽  
Vol 15 ◽  
Author(s):  
Jianwei Li ◽  
Leibo Liu ◽  
Qinghua Cui ◽  
Yuan Zhou
Keyword(s):  
Expression Profiles ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Analysis Tools ◽  
Disease Similarity ◽  
Comparison Results ◽  
Differentially Expressed Mirnas ◽  
Disease Associations ◽  
The Relationship

Background: De-regulation of microRNAs (miRNAs) is closely related with many complex diseases including cancers. In The Cancer Genome Atlas (TCGA), hundreds of differentially expressed miRNAs are stored for each type of cancer, which are hard to be intuitively interpreted. To date, several miRNA set enrichment tools have been tailored to predict the potential disease associations and functions of de-regulated miRNAs, including the miRNA Enrichment Analysis and Annotation tool (miEAA) and Tool for Annotations of human MiRNAs (TAM 1.0 & TAM 2.0). However, independent benchmarking of these tools is warranted to assess their effectiveness and robustness, and the relationship between enrichment analysis results and the prognosis significance of cancers. Method: Base on differentially expressed miRNAs from expression profiles in TCGA, we performed a series of tests and comprehensive comparison of the enrichment analysis results of miEAA, TAM 1.0 and TAM 2.0. The work focused on the performance of the three tools, disease similarity based on miRNA-disease associations from the enrichment analysis results, the relationship between the overrepresented miRNAs from enrichment analysis results and the prognosis significance of cancers. Results: The main results show that TAM 2.0 is more likely to identify the regulatory disease’s functions of de-regulated miRNA; it is feasible to calculate disease similarity based on enrichment analysis results of TAM 2.0; and there is weak positive correlation between the occurrence frequency of miRNAs in the TAM 2.0 enrichment analysis results and the prognosis significance of the cancer miRNAs. Conclusion: Our comparison results not only provide a reference for biomedical researchers to choose appropriate miRNA set enrichment analysis tools to achieve their own purpose, but also demonstrate that the degree of overrepresentation of miRNAs could be a supplementary indicator of the disease similarity and the prognostic effect of cancer miRNAs.

scholarly journals Identification of a prognostic long non-coding RNA signature in breast cancer

2020 ◽  
Author(s):  
Gaochen Lan ◽  
Xiaoling Yu ◽  
Yanna Zhao ◽  
Jinjian Lan ◽  
Wan Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cox Regression ◽  
Prognostic Biomarker ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Cox Regression Analysis

Abstract Background: Breast cancer is the most common malignant disease among women. At present, more and more attention has been paid to long non-coding RNAs (lncRNAs) in the field of breast cancer research. We aimed to investigate the expression profiles of lncRNAs and construct a prognostic lncRNA for predicting the overall survival (OS) of breast cancer.Methods: The expression profiles of lncRNAs and clinical data with breast cancer were obtained from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs were screened out by R package (limma). The survival probability was estimated by the Kaplan‑Meier Test. The Cox Regression Model was performed for univariate and multivariate analysis. The risk score (RS) was established on the basis of the lncRNAs’ expression level (exp) multiplied regression coefficient (β) from the multivariate cox regression analysis with the following formula: RS=exp a1 * β a1 + exp a2 * β a2 +……+ exp an * β an. Functional enrichment analysis was performed by Metascape.Results: A total of 3404 differentially expressed lncRNAs were identified. Among them, CYTOR, MIR4458HG and MAPT-AS1 were significantly associated with the survival of breast cancer. Finally, The RS could predict OS of breast cancer (RS=exp CYTOR * β CYTOR + exp MIR4458HG * β MIR4458HG + exp MAPT-AS1 * β MAPT-AS1). Moreover, it was confirmed that the three-lncRNA signature could be an independent prognostic biomarker for breast cancer (HR=3.040, P=0.000).Conclusions: This study established a three-lncRNA signature, which might be a novel prognostic biomarker for breast cancer.

scholarly journals Identification of key miRNAs in the progression of hepatocellular carcinoma using an integrated bioinformatics approach

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9000
Author(s):  
Qi Zheng ◽  
Xiaoyong Wei ◽  
Jun Rao ◽  
Cuncai Zhou
Keyword(s):  
Expression Profiles ◽  
Differentially Expressed ◽  
Data Set ◽  
Aberrant Expression ◽  
External Data ◽  
Genes Expression ◽  
Mirna Expression Profiles ◽  
Differentially Expressed Mirnas ◽  
Microarray Datasets ◽  
The Relationship

Backgroud It has been shown that aberrant expression of microRNAs (miRNAs) and transcriptional factors (TFs) is tightly associated with the development of HCC. Therefore, in order to further understand the pathogenesis of HCC, it is necessary to systematically study the relationship between the expression of miRNAs, TF and genes. In this study, we aim to identify the potential transcriptomic markers of HCC through analyzing common microarray datasets, and further establish the differential co-expression network of miRNAs–TF–mRNA to screen for key miRNAs as candidate diagnostic markers for HCC. Method We first downloaded the mRNA and miRNA expression profiles of liver cancer from the GEO database. After pretreatment, we used a linear model to screen for differentially expressed genes (DEGs) and miRNAs. Further, we used weighed gene co-expression network analysis (WGCNA) to construct the differential gene co-expression network for these DEGs. Next, we identified mRNA modules significantly related to tumorigenesis in this network, and evaluated the relationship between mRNAs and TFs by TFBtools. Finally, the key miRNA was screened out in the mRNA–TF–miRNA ternary network constructed based on the target TF of differentially expressed miRNAs, and was further verified with external data set. Results A total of 465 DEGs and 215 differentially expressed miRNAs were identified through differential genes expression analysis, and WGCNA was used to establish a co-expression network of DEGs. One module that closely related to tumorigenesis was obtained, including 33 genes. Next, a ternary network was constructed by selecting 256 pairs of mRNA–TF pairs and 100 pairs of miRNA–TF pairs. Network mining revealed that there were significant interactions between 18 mRNAs and 25 miRNAs. Finally, we used another independent data set to verify that miRNA hsa-mir-106b and hsa-mir-195 are good classifiers of HCC and might play key roles in the progression of HCC. Conclusion Our data indicated that two miRNAs—hsa-mir-106b and hsa-mir-195—are identified as good classifiers of HCC.

scholarly journals Integrative Analyses of Genes and miRNAs Associated With Age-Related Sarcopenia

2021 ◽  
Author(s):  
Sangyeob Lee ◽  
Jun-Il Yoo
Keyword(s):  
Target Genes ◽  
Expression Profiles ◽  
Vastus Lateralis ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Analysis Tool ◽  
Age Related ◽  
Differentially Expressed Mirnas ◽  
Low Expression

Abstract Background: Sarcopenia is an age-related disease with skeletal muscle loss, weakness, and functional impairment. The potential causes of sarcopenia including the programmed cell death of muscles, inflammation, reactive oxygen species, protein turnover, and mitochondrial dysfunction have been studied. The purpose of this study was to find differentially expressed miRNAs (DE-miRNAs) in the muscle samples of older people (GSE23527). In addition, we performed to identify new miRNA-mRNA regulatory network for treating sarcopeniaMethods: Gene expression profiles were obtained from microarray datasets (GSE8479 and GSE1428) of the vastus lateralis muscles of young and older male subjects. Dataset GSE23527 was derived from the platform of GPL10358 (LC_MRA-1001_miRHuman_11.0_080411) and contained microRNA arrays of 12 young muscle samples and 12 older muscle samples. The DEGs between the older and young GSE8479 and GSE1428 samples were identified using the online analysis tool imaGEO (https://imageo.genyo.es). Pathway and process enrichment analysis with the ontology sources in the KEGG pathway, GO biological processes, Reactome gene sets, WikiPathways, and CORUM were analyzed by Metascape. A PPI (protein-protein interaction) network of DEGs was constructed using the Search Tool for Retrieval of Interacting Genes (STRING) app in Cytoscape software (version 1.6.0). GEO2R (https://www.ncbi.nlm.nih.gov) was used to select differentially expressed miRNAs (DE-miRNAs) in the GSE 23527 dataset.Results: In the GSE8479 and GSE1428 datasets, a total of 81 DEGs were discovered, including four upregulated genes and 77 downregulated genes. The top 12 clusters and their representative enriched terms were identified using Metascape. A total of 79 nodes and 186 edges were predicted in the PPI network. One upregulated DE-miRNA (hsa-miR-450a-5p) and six downregulated DE-miRNAs (hsa-miR-127-3p, hsa-miR-24-2-5p, hsa-miR-378a-5p, hsa-miR-532-5p, hsa-miR-487b-5p, and has-miR-487b-3p) were selected in the miRBase database. The MiRWalk online database was utilized for exploring 8017 genes that were selected as genes regulated by DE-miRNAs and six of them overlapped with hub genes. COX7A1 and NDUFB5 showed significantly low expression in sarcopenia patients compared to the controls. COX7B and PDHA1 also displayed low expression in sarcopenia patients, but expression of COX7A1 and NDUFB5 was not significant. TIMM8A and CS showed similar expression rates in both samples.Conclusions: The present bioinformatics analysis showed that two target genes (COX7A1 and NDUFB5) were potentially downregulated in sarcopenia patients. These two genes could be the cause of sarcopenia with aging. In addition, present study showed that several miRNAs (hsa-miR-378a-5p, hsa-miR-532-5p, hsa-miR-127-3p, and hsa-miR-24-2-5p) were identified as regulating the target genes. These results suggest that controlling the identified miRNAs could be a prospective strategy for treating sarcopenia by regulating the mRNA-miRNA network.

scholarly journals Immunogenomic Landscape Analysis of Prognostic Immune-Related Genes in Hepatocellular Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Peng Qin ◽  
Mengyu Zhang ◽  
Xue Liu ◽  
Ziming Dong
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Immune Related Genes

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death. HBV infection is an important risk factor for the tumorigenesis of HCC, given that the inflammatory environment is closely related to morbidity and prognosis. Consequently, it is of urgent importance to explore the immunogenomic landscape to supplement the prognosis of HCC. The expression profiles of immune‐related genes (IRGs) were integrated with 377 HCC patients to generate differentially expressed IRGs based on the Cancer Genome Atlas (TCGA) dataset. These IRGs were evaluated and assessed in terms of their diagnostic and prognostic values. A total of 32 differentially expressed immune‐related genes resulted as significantly correlated with the overall survival of HCC patients. The Gene Ontology functional enrichment analysis revealed that these genes were actively involved in cytokine‐cytokine receptor interaction. A prognostic signature based on IRGs (HSPA4, PSME3, PSMD14, FABP6, ISG20L2, TRAF3, NDRG1, NRAS, CSPG5, and IL17D) stratified patients into high-risk versus low-risk groups in terms of overall survival and remained as an independent prognostic factor in multivariate analyses after adjusting for clinical and pathologic factors. Several IRGs (HSPA4, PSME3, PSMD14, FABP6, ISG20L2, TRAF3, NDRG1, NRAS, CSPG5, and IL17D) of clinical significance were screened in the present study, revealing that the proposed clinical-immune signature is a promising risk score for predicting the prognosis of HCC.

scholarly journals Identification of a prognostic long non-coding RNA signature in breast cancer

2020 ◽  
Author(s):  
Gaochen Lan ◽  
Xiaoling Yu ◽  
Yanna Zhao ◽  
Jinjian Lan ◽  
Wan Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cox Regression ◽  
Prognostic Biomarker ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Cox Regression Analysis

Abstract Background: Breast cancer is the most common malignant disease among women. At present, more and more attention has been paid to long non-coding RNAs (lncRNAs) in the field of breast cancer research. We aimed to investigate the expression profiles of lncRNAs and construct a prognostic lncRNA for predicting the overall survival (OS) of breast cancer. Methods: The expression profiles of lncRNAs and clinical data with breast cancer were obtained from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs were screened out by R package (limma). The survival probability was estimated by the Kaplan‑Meier Test. The Cox Regression Model was performed for univariate and multivariate analysis. The risk score (RS) was established on the basis of the lncRNAs’ expression level (exp) multiplied regression coefficient (β) from the multivariate cox regression analysis with the following formula: RS=exp a1 * β a1 + exp a2 * β a2 +……+ exp an * β an . Functional enrichment analysis was performed by Metascape. Results: A total of 3404 differentially expressed lncRNAs were identified. Among them, CYTOR , MIR4458HG and MAPT-AS1 were significantly associated with the survival of breast cancer. Finally, The RS could predict OS of breast cancer (RS=exp CYTOR * β CYTOR + exp MIR4458HG * β MIR4458HG + exp MAPT-AS1 * β MAPT-AS1 ). Moreover, it was confirmed that the three-lncRNA signature could be an independent prognostic biomarker for breast cancer (HR=3.040, P=0.000). Conclusions: This study established a three-lncRNA signature, which might be a novel prognostic biomarker for breast cancer.

Bioinformatics Analysis Reveals Functions of MicroRNAs in Rice Under the Drought Stress

2021 ◽  
Vol 15 (8) ◽  
pp. 927-936 ◽  
Author(s):  
Yan Peng ◽  
Yuewu Liu ◽  
Xinbo Chen
Keyword(s):  
Drought Stress ◽  
Target Genes ◽  
Hot Spot ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Protein Protein Interaction ◽  
Promising Tool ◽  
Differentially Expressed Mirnas ◽  
Aba Biosynthesis

Background: Drought is one of the most damaging and widespread abiotic stresses that can severely limit the rice production. MicroRNAs (miRNAs) act as a promising tool for improving the drought tolerance of rice and have become a hot spot in recent years. Objective: In order to further extend the understanding of miRNAs, the functions of miRNAs in rice under drought stress are analyzed by bioinformatics. Method: In this study, we integrated miRNAs and genes transcriptome data of rice under the drought stress. Some bioinformatics methods were used to reveal the functions of miRNAs in rice under drought stress. These methods included target genes identification, differentially expressed miRNAs screening, enrichment analysis of DEGs, network constructions for miRNA-target and target-target proteins interaction. Results: (1) A total of 229 miRNAs with differential expression in rice under the drought stress, corresponding to 73 rice miRNAs families, were identified. (2) 1035 differentially expressed genes (DEGs) were identified, which included 357 up-regulated genes, 542 down-regulated genes and 136 up/down-regulated genes. (3) The network of regulatory relationships between 73 rice miRNAs families and 1035 DEGs was constructed. (4) 25 UP_KEYWORDS terms of DEGs, 125 GO terms and 7 pathways were obtained. (5) The protein-protein interaction network of 1035 DEGs was constructed. Conclusion: (1) MiRNA-regulated targets in rice might mainly involve in a series of basic biological processes and pathways under drought conditions. (2) MiRNAs in rice might play critical roles in Lignin degradation and ABA biosynthesis. (3) MiRNAs in rice might play an important role in drought signal perceiving and transduction.

scholarly journals Transcriptome Analysis of Eggplant Root in Response to Root-Knot Nematode Infection

Pathogens ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 470
Author(s):  
Min Zhang ◽  
Hongyuan Zhang ◽  
Jie Tan ◽  
Shuping Huang ◽  
Xia Chen ◽  
...  
Keyword(s):  
Defense Mechanisms ◽  
Expression Profiles ◽  
Resistance Mechanism ◽  
Solanum Melongena ◽  
Enrichment Analysis ◽  
Nematode Resistance ◽  
Differentially Expressed ◽  
Root Knot Nematode ◽  
Solanum Torvum ◽  
Plant Nematode

Eggplant (Solanum melongena L.), which belongs to the Solanaceae family, is an important vegetable crop. However, its production is severely threatened by root-knot nematodes (RKNs) in many countries. Solanum torvum, a wild relative of eggplant, is employed worldwide as rootstock for eggplant cultivation due to its resistance to soil-borne diseases such as RKNs. In this study, to identify the RKN defense mechanisms, the transcriptomic profiles of eggplant and Solanum torvum were compared. A total of 5360 differentially expressed genes (DEGs) were identified for the response to RKN infection. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis showed that these DEGs are mainly involved in the processes of response to stimulus, protein phosphorylation, hormone signal transduction, and plant-pathogen interaction pathways. Many phytohormone-related genes and transcription factors (MYB, WRKY, and NAC) were differentially expressed at the four time points (ck, 7, 14, and 28 days post-infection). The abscisic acid signaling pathway might be involved in plant-nematode interactions. qRT-PCR validated the expression levels of some of the DEGs in eggplant. These findings demonstrate the nematode-induced expression profiles and provide some insights into the nematode resistance mechanism in eggplant.

Identification of differentially expressed microRNAs in outgrowth embryos compared with blastocysts and non-outgrowth embryos in mice

2019 ◽  
Vol 31 (4) ◽  
pp. 645 ◽  
Author(s):  
Jihyun Kim ◽  
Jaewang Lee ◽  
Jin Hyun Jun
Keyword(s):  
Bioinformatics Analysis ◽  
Preimplantation Embryo ◽  
Expression Profiles ◽  
In Silico Analysis ◽  
Differentially Expressed ◽  
Recurrent Implantation Failure ◽  
Preimplantation Embryo Development ◽  
Mirna Expression Profiles ◽  
Differentially Expressed Mirnas ◽  
Silico Analysis

Recurrent implantation failure (RIF) is one of the main causes for the repeated failure of IVF, and the major reason for RIF is thought to be a miscommunication between the embryo and uterus. However, the exact mechanism underlying embryo–uterus cross-talk is not fully understood. The aim of the present study was to identify differentially expressed microRNAs (miRNAs) among blastocysts, non-outgrowth and outgrowth embryos in mice using microarray analysis. A bioinformatics analysis was performed to predict the potential mechanisms of implantation. The miRNA expression profiles differed significantly between non-outgrowth and outgrowth embryos. In all, 3163 miRNAs were detected in blastocysts and outgrowth embryos. Of these, 10 miRNA candidates (let-7b, miR-23a, miR-27a, miR-92a, miR-183, miR-200c, miR-291a, miR-425, miR-429 and miR-652) were identified as significant differentially expressed miRNAs of outgrowth embryos by in silico analysis. The expression of the miRNA candidates was markedly changed during preimplantation embryo development. In particular, let-7b-5p, miR-200c-3p and miR-23a-3p were significantly upregulated in outgrowth embryos compared with non-outgrowth blastocysts. Overall, differentially expressed miRNAs in outgrowth embryos compared with blastocysts and non-outgrowth embryos could be involved in embryo attachment, and interaction between the embryo proper and maternal endometrium during the implantation process.

scholarly journals MicroRNA expression profiling involved in Borax-induced anti-tumor effect using gene-chip analysis

2020 ◽  
Author(s):  
Lun Wu ◽  
Ying Wei ◽  
Wen-Bo Zhou ◽  
Jiao Zhou ◽  
Li-Hua Yang ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Hepg2 Cells ◽  
Enrichment Analysis ◽  
Gene Chip ◽  
Differentially Expressed ◽  
Control Group ◽  
Pathway Enrichment Analysis ◽  
Ras Signaling ◽  
Therapeutic Benefits ◽  
Differentially Expressed Mirnas

Abstract Background Borax, a boron compound, which is becoming widely recognized for its biological effects, including antioxidant activity, cytotoxicity, and potential therapeutic benefits. However, the specific molecular mechanisms underlying borax-induced anti-tumor effect still remain to be to further elucidated. MicroRNAs (miRNAs) may play key roles in cellular processes including tumor progression, cell apoptosis and cytotoxicity. Thus, this study aimed to investigate, whether miRNAs were involved in the borax-mediated anti-tumor effect using miRNA profiling of a human liver cancer cell line (HepG2) using gene-chip analysis.Methods Total RNA was extracted and purified from HepG2 cells that were treated with 4 mM borax for either 2 or 24 h. The samples underwent microarray analysis using an Agilent Human miRNA Array. Differentially expressed miRNAs were analysed by volcano plot and heatmap, and were validated using real-time fluorescent quantitative PCR (qPCR).ResultsAmong this, 2- or 24-h exposure to borax significantly altered the expression level of miRNAs in HepG2 cells, 4 or 14 were upregulated and 3 were downregulated compared with the control group, respectively (≥2-fold; P<0.05). GO enrichment analysis and KEGG pathway enrichment analysis revealed that target genes of differentially expressed miRNAs in HepG2 cells predominantly participated in MAPK signaling pathway, TGF-beta signaling pathway, NF-kappa B signaling pathway, etc; in 2-h borax treatment group, while Ras signaling pathway, FoxO signaling pathway, Cellular senescence, etc; involved in 24-h treatment group.Conclusions Result indicates that borax-induced anti-tumor effect may be associated with alterations in miRNAs.

scholarly journals Bioinformatics-Based Study to Investigate Potential Differentially Expressed Genes and miRNAs in Hashimoto’s Thyroiditis

2021 ◽  
Author(s):  
Li Guoquan ◽  
Du Junwei ◽  
He Qi ◽  
Fu Xinghao ◽  
Ji Feihong ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Inflammatory Responses ◽  
Expression Profiles ◽  
Treatment Options ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Chronic Lymphocytic Thyroiditis ◽  
Hub Genes

Abstract BackgroundHashimoto's thyroiditis (HT), also known as chronic lymphocytic thyroiditis, is a common autoimmune disease, which mainly occurs in women. The early manifestation was hyperthyroidism, however, hypothyroidism may occur if HT was not controlled for a long time. Numerous studies have shown that multiple factors, including genetic, environmental, and autoimmune factors, were involved in the pathogenesis of the disease, but the exact mechanisms were not yet clear. The aim of this study was to identify differentially expressed genes (DEGs) by comprehensive analysis and to provide specific insights into HT. MethodsTwo gene expression profiles (GSE6339, GSE138198) about HT were downloaded from the Gene Expression Omnibus (GEO) database. The DEGs were assessed between the HT and normal groups using the GEO2R. The DEGs were then sent to the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The hub genes were discovered using Cytoscape and CytoHubba. Finally, NetworkAnalyst was utilized to create the hub genes' targeted microRNAs (miRNAs). ResultsA total of 62 DEGs were discovered, including 60 up-regulated and 2 down-regulated DEGs. The signaling pathways were mainly engaged in cytokine interaction and cytotoxicity, and the DEGs were mostly enriched in immunological and inflammatory responses. IL2RA, CXCL9, IL10RA, CCL3, CCL4, CCL2, STAT1, CD4, CSF1R, and ITGAX were chosen as hub genes based on the results of the protein-protein interaction (PPI) network and CytoHubba. Five miRNAs, including mir-24-3p, mir-223-3p, mir-155-5p, mir-34a-5p, mir-26b-5p, and mir-6499-3p, were suggested as likely important miRNAs in HT. ConclusionsThese hub genes, pathways and miRNAs contribute to a better understanding of the pathophysiology of HT and offer potential treatment options for HT.

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