4.2 Article

Genome-wide analysis of primary CD4+and CD8+T cell transcriptomes shows evidence for a network of enriched pathways associated with HIV disease

期刊

RETROVIROLOGY
卷 8, 期 -, 页码 -

出版社

BMC
DOI: 10.1186/1742-4690-8-18

关键词

-

类别

资金

  1. Millennium Foundation, Westmead
  2. AIDS Foundation Budget
  3. NHMRC [503807]

向作者/读者索取更多资源

Background: HIV preferentially infects CD4+ T cells, and the functional impairment and numerical decline of CD4+ and CD8+ T cells characterize HIV disease. The numerical decline of CD4+ and CD8+ T cells affects the optimal ratio between the two cell types necessary for immune regulation. Therefore, this work aimed to define the genomic basis of HIV interactions with the cellular transcriptome of both CD4+ and CD8+ T cells. Results: Genome-wide transcriptomes of primary CD4+ and CD8+ T cells from HIV+ patients were analyzed at different stages of HIV disease using Illumina microarray. For each cell subset, pairwise comparisons were performed and differentially expressed (DE) genes were identified (fold change > 2 and B-statistic > 0) followed by quantitative PCR validation. Gene ontology (GO) analysis of DE genes revealed enriched categories of complement activation, actin filament, proteasome core and proton-transporting ATPase complex. By gene set enrichment analysis (GSEA), a network of enriched pathways functionally connected by mitochondria was identified in both T cell subsets as a transcriptional signature of HIV disease progression. These pathways ranged from metabolism and energy production (TCA cycle and OXPHOS) to mitochondria meditated cell apoptosis and cell cycle dysregulation. The most unique and significant feature of our work was that the non-progressing status in HIV+ long-term non-progressors was associated with MAPK, WNT, and AKT pathways contributing to cell survival and anti-viral responses. Conclusions: These data offer new comparative insights into HIV disease progression from the aspect of HIV-host interactions at the transcriptomic level, which will facilitate the understanding of the genetic basis of transcriptomic interaction of HIV in vivo and how HIV subverts the human gene machinery at the individual cell type level.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.2
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Article Neurosciences

Sex-Dependent Shared and Nonshared Genetic Architecture Across Mood and Psychotic Disorders

Gabriella A. M. Blokland, Jakob Grove, Chia-Yen Chen, Chris Cotsapas, Stuart Tobet, Robert Handa, David St Clair, Todd Lencz, Bryan J. Mowry, Sathish Periyasamy, Murray J. Cairns, Paul A. Tooney, Jing Qin Wu, Brian Kelly, George Kirov, Patrick F. Sullivan, Aiden Corvin, Brien P. Riley, Tonu Esko, Lili Milani, Erik G. Jonsson, Aarno Palotie, Hannelore Ehrenreich, Martin Begemann, Agnes Steixner-Kumar, Pak C. Sham, Nakao Iwata, Daniel R. Weinberger, Pablo Gejman, Alan R. Sanders, Joseph D. Buxbaum, Dan Rujescu, Ina Giegling, Bettina Konte, Annette M. Hartmann, Elvira Bramon, Robin M. Murray, Michele T. Pato, Jimmy Lee, Ingrid Melle, Espen Molden, Roel A. Ophoff, Andrew McQuillin, Nicholas J. Bass, Rolf Adolfsson, Anil K. Malhotra, Nicholas G. Martin, Janice M. Fullerton, Philip B. Mitchell, Peter R. Schofield, Andreas J. Forstner, Franziska Degenhardt, Sabrina Schaupp, Ashley L. Comes, Manolis Kogevinas, Jose Guzman-Parra, Andreas Reif, Fabian Streit, Lea Sirignano, Sven Cichon, Maria Grigoroiu-Serbanescu, Joanna Hauser, Jolanta Lissowska, Fermin Mayoral, Bertram Muller-Myhsok, Thomas G. Schulze, Markus M. Nothen, Marcella Rietschel, John Kelsoe, Marion Leboyer, Stephane Jamain, Bruno Etain, Frank Bellivier, John B. Vincent, Martin Alda, Claire O'Donovan, Pablo Cervantes, Joanna M. Biernacka, Mark Frye, Susan L. McElroy, Laura J. Scott, Eli A. Stahl, Mikael Landen, Marian L. Hamshere, Olav B. Smeland, Srdjan Djurovic, Arne E. Vaaler, Ole A. Andreassen, Bernhard T. Baune, Tracy Air, Martin Preisig, Rudolf Uher, Douglas F. Levinson, Myrna M. Weissman, James B. Potash, Jianxin Shi, James A. Knowles, Roy H. Perlis, Susanne Lucae, Dorret Boomsma, Brenda W. J. H. Penninx, Jouke-Jan Hottenga, Eco J. C. de Geus, Gonneke Willemsen, Yuri Milaneschi, Henning Tiemeier, Hans J. Grabe, Alexander Teumer, Sandra Van der Auwera, Uwe Volker, Steven P. Hamilton, Patrik K. E. Magnusson, Alexander Viktorin, Divya Mehta, Niamh Mullins, Mark J. Adams, Gerome Breen, Andrew M. McIntosh, Cathryn M. Lewis, David M. Hougaard, Merete Nordentoft, Ole Mors, Preben B. Mortensen, Thomas Werge, Thomas D. Als, Anders D. Borglum, Tracey L. Petryshen, Jordan W. Smoller, Jill M. Goldstein

Summary: The study found significant sex-dependent genetic risk in schizophrenia, major depressive disorder, and bipolar disorder, with implications for genes related to neuronal development, immune functions, and vascular functions across and within these disorders. This suggests substantial genetic overlap between sexes in mood and psychotic disorders, with sex-specific effects enriched for genes involved in various physiological functions.

BIOLOGICAL PSYCHIATRY (2022)

Article Psychiatry

Interaction Testing and Polygenic Risk Scoring to Estimate the Association of Common Genetic Variants With Treatment Resistance in Schizophrenia

Antonio F. Pardinas, Sophie E. Smart, Isabella R. Willcocks, Peter A. Holmans, Charlotte A. Dennison, Amy J. Lynham, Sophie E. Legge, Bernhard T. Baune, Tim B. Bigdeli, Murray J. Cairns, Aiden Corvin, Ayman H. Fanous, Josef Frank, Brian Kelly, Andrew McQuillin, Ingrid Melle, Preben B. Mortensen, Bryan J. Mowry, Carlos N. Pato, Sathish Periyasamy, Marcella Rietschel, Dan Rujescu, Carmen Simonsen, David St Clair, Paul Tooney, Jing Qin Wu, Ole A. Andreassen, Kaarina Kowalec, Patrick F. Sullivan, Robin M. Murray, Michael J. Owen, James H. MacCabe, Michael C. O'Donovan, James T. R. Walters

Summary: This study examined the genetic architecture of treatment-resistant schizophrenia (TRS) by reassessing genetic data from schizophrenia studies and validating it in carefully ascertained clinical samples. The results showed that TRS is a polygenic trait with detectable heritability, and it is genetically correlated with traits related to intelligence and cognition. The study also found associations between TRS and a history of taking clozapine.

JAMA PSYCHIATRY (2022)

Article Transplantation

Nonutilization of Kidneys From Donors After Circulatory Determinant of Death

Yingxin Lin, Armando Teixeira-Pinto, Helen Opdam, Jeremy R. Chapman, Jonathan C. Craig, Natasha Rogers, Henry Pleass, Christopher Davies, Stephen McDonald, Jean Yang, Wai Lim, Germaine Wong

Summary: This study analyzed the data of DCDD donors in Australia and found that donor kidney function and duration of warm ischemia are the key factors for the nonutilization of DCDD kidneys. Strategies to reduce the duration of warm ischemia and improve post-transplant recipient kidney function may reduce rates of nonutilization.

TRANSPLANTATION DIRECT (2022)

Article Oncology

Whole genome duplication in oral squamous cell carcinoma in patients younger than 50 years: implications for prognosis and adverse clinicopathological factors

Laveniya Satgunaseelan, Dario Strbenac, Cali Willet, Tracy Chew, Rosemarie Sadsad, James Wykes, Tsu-Hui Hubert Low, Wendy A. Cooper, C. Soon Lee, Carsten E. Palme, Jean Y. H. Yang, Jonathan R. Clark, Ruta Gupta

Summary: The prevalence of whole genome duplication (WGD) is high in young patients with oral squamous cell carcinoma (OSCC), and it is associated with adverse pathological characteristics and clinical outcomes. TP53 mutations also occur before WGD.

GENES CHROMOSOMES & CANCER (2022)

Article Health Care Sciences & Services

Cross-Platform Omics Prediction procedure: a statistical machine learning framework for wider implementation of precision medicine

Kevin Y. X. Wang, Gulietta M. Pupo, Varsha Tembe, Ellis Patrick, Dario Strbenac, Sarah-Jane Schramm, John F. Thompson, Richard A. Scolyer, Samuel Muller, Garth Tarr, Graham J. Mann, Jean Y. H. Yang

Summary: In the era of precision medicine, molecular signatures from advanced omics technologies have the potential to guide clinical decisions. However, current approaches are often limited by location-specificity, which hampers the transferability of molecular signatures. To address this issue, the researchers developed a penalised regression model called Cross-Platform Omics Prediction (CPOP), which can predict patient outcomes in a platform-independent manner across time and experiments. CPOP improves upon traditional prediction frameworks by selecting ratio-based features with similar estimated effect sizes. The model demonstrated stable performance across datasets of similar biology, reducing the impact of technical noise generated by omics platforms. The researchers evaluated CPOP using melanoma transcriptomics data and showed its potential in a clinical screening framework for precision medicine. The model's generalization was further demonstrated with ovarian cancer and inflammatory bowel disease studies.

NPJ DIGITAL MEDICINE (2022)

Article Biochemical Research Methods

scFeatures: multi-view representations of single-cell and spatial data for disease outcome prediction

Yue Cao, Yingxin Lin, Ellis Patrick, Pengyi Yang, Jean Yee Hwa Yang

Summary: This study presents a method called scFeatures that creates interpretable cellular and molecular representations of single-cell and spatial data at the sample level. Summarizing a broad collection of features at the sample level is important for understanding disease mechanisms in different experimental studies and accurately classifying disease status of individuals.

BIOINFORMATICS (2022)

Article Hematology

Endoplasmic reticulum protein 5 attenuates platelet endoplasmic reticulum stress and secretion in a mouse model

Angelina J. Lay, Alexander Dupuy, Lejla Hagimola, Jessica Tieng, Mark Larance, Yunwei Zhang, Jean Yang, Yvonne Kong, Joyce Chiu, Emilia Gray, Zihao Qin, Diana Schmidt, Jessica Maclean, Benjamin Hofma, Marc Ellis, Maggie Kalev-Zylinska, Yair Argon, Shaun P. Jackson, Philip Hogg, Freda H. Passam

Summary: This study found that ERp5 plays a negative regulatory role in platelet ER stress response and highlights the importance of disulfide isomerases in platelet ER homeostasis. Furthermore, the study also revealed the close correlation between platelet ER stress and platelet secretion and thrombosis.

BLOOD ADVANCES (2023)

Article Biochemical Research Methods

scSTAR reveals hidden heterogeneity with a real-virtual cell pair structure across conditions in single-cell RNA sequencing data

Jie Hao, Jiawei Zou, Jiaqiang Zhang, Ke Chen, Duojiao Wu, Wei Cao, Guoguo Shang, Jean Y. H. Yang, KongFatt Wong-Lin, Hourong Sun, Zhen Zhang, Xiangdong Wang, Wantao Chen, Xin Zou

Summary: Cell-state transition analysis using single-cell RNA-sequencing can reveal additional information in time-resolved biological phenomena. However, current methods are limited to short-term evolution of cell states based on gene expression derivative. This study presents scSTAR, a method that overcomes this limitation by constructing a paired-cell projection between different biological conditions with arbitrary time spans, leading to more accurate predictions and new discoveries in aging and cancer research.

BRIEFINGS IN BIOINFORMATICS (2023)

Article Biochemical Research Methods

Benchmarking of analytical combinations for COVID-19 outcome prediction using single-cell RNA sequencing data

Yue Cao, Shila Ghazanfar, Pengyi Yang, Jean Yang

Summary: The advancement of scRNA-seq technology has led to its increasing use in large-scale patient cohort studies. This study evaluates the impact of analytical choices on patient outcome prediction using scRNA-seq COVID-19 datasets. The study examines the difference between single-view and multi-view feature spaces, surveys multiple learning platforms, and compares integration approaches. The results highlight the power of ensemble learning, consistency among different learning methods, and the importance of dataset normalization.

BRIEFINGS IN BIOINFORMATICS (2023)

Article Biology

Deep multimodal graph-based network for survival prediction from highly multiplexed images and patient variables

Xiaohang Fu, Ellis Patrick, Jean Y. H. Yang, David Dagan Feng, Jinman Kim

Summary: The spatial architecture and phenotypic heterogeneity of tumor cells are associated with cancer prognosis and outcomes. Imaging mass cytometry captures high-dimensional maps of disease-relevant biomarkers at single-cell resolution, which can inform patient-specific prognosis. However, existing methods for survival prediction do not utilize spatial phenotype information at the single-cell level, and there is a lack of end-to-end methods that integrate imaging data with clinical information for improved accuracy. We propose a deep multimodal graph-based network that considers spatial phenotype information and clinical variables to enhance survival prediction, and demonstrate its effectiveness in breast cancer datasets.

COMPUTERS IN BIOLOGY AND MEDICINE (2023)

Article Microbiology

NEMoE: a nutrition aware regularized mixture of experts model to identify heterogeneous diet-microbiome-host health interactions

Xiangnan Xu, Michal Lubomski, Andrew J. Holmes, Carolyn M. Sue, Ryan L. Davis, Samuel Muller, Jean Y. H. Yang

Summary: The NEMoE model is proposed to analyze the relationship between gut microbiota and health state, taking into account diet-specific variations. Through simulation studies and real-world data analysis, the effectiveness of this approach is demonstrated, showing its potential in designing personalized intervention strategies.

MICROBIOME (2023)

Article Biochemistry & Molecular Biology

Lipidomics Profiling and Risk of Coronary Artery Disease in the BioHEART-CT Discovery Cohort

Dantong Zhu, Stephen T. Vernon, Zac D'Agostino, Jingqin Wu, Corey Giles, Adam S. Chan, Katharine A. Kott, Michael P. Gray, Alireza Gholipour, Owen Tang, Habtamu B. Beyene, Ellis Patrick, Stuart M. Grieve, Peter J. Meikle, Gemma A. Figtree, Jean Y. H. Yang

Summary: The current CAD risk scores based on traditional risk factors often fail individuals. We aim to identify lipidomic biomarkers using non-invasive imaging technology and advanced lipidomic measurement to enable intervention before cardiovascular events.

BIOMOLECULES (2023)

Article Urology & Nephrology

Trajectories of systolic blood pressure decline in kidney transplant donors prior to circulatory death and delayed graft function

Yingxin Lin, Armando Teixeira-Pinto, Jonathan C. Craig, Helen Opdam, Jeremy C. Chapman, Henry Pleass, Angus Carter, Natasha M. Rogers, Christopher E. Davies, Stephen McDonald, Jean Yang, Wai H. Lim, Germaine Wong

Summary: The trajectory of blood pressure decline in kidneys donated after circulatory death can predict the risk of delayed graft function. The assessment of haemodynamic changes in donors during the agonal phase may be useful for determining donor suitability and post-transplant outcomes.

CLINICAL KIDNEY JOURNAL (2023)

Article Multidisciplinary Sciences

Atlas-scale single-cell multi-sample multi-condition data integration using scMerge2

Yingxin Lin, Yue Cao, Elijah Willie, Ellis Patrick, Jean Y. H. Yang

Summary: The emergence of multi-sample multi-condition single-cell multi-cohort studies allows researchers to investigate different cell states. The algorithm scMerge2 enables integration and analysis of large-scale single-cell datasets, revealing accurate signatures of disease progression and removing dataset variability in various single-cell profiling technologies.

NATURE COMMUNICATIONS (2023)

Review Mathematical & Computational Biology

Gene regulatory network reconstruction: harnessing the power of single-cell multi-omic data

Daniel Kim, Andy Tran, Hani Jieun Kim, Yingxin Lin, Jean Yee Hwa Yang, Pengyi Yang

Summary: Inferring gene regulatory networks is crucial in biology, and recent advances in sequencing technology have led to the development of state-of-the-art methods that utilize single-cell multi-omic data for more comprehensive and precise network reconstruction.

NPJ SYSTEMS BIOLOGY AND APPLICATIONS (2023)

暂无数据