Transcriptional network predicts viral set point during acute HIV-1 infection

BACKGROUND HIV-1-infected individuals with higher viral set points progress to AIDS more rapidly than those with lower set points. Predicting viral set point early following infection can contribute to our understanding of early control of HIV-1 replication, to predicting long-term clinical outcomes, and to the choice of optimal therapeutic regimens. METHODS In a longitudinal study of 10 untreated HIV-1-infected patients, we used gene expression profiling of peripheral blood mononuclear cells to identify transcriptional networks for viral set point prediction. At each sampling time, a statistical analysis inferred the optimal transcriptional network that best predicted viral set point. We then assessed the accuracy of this transcriptional model by predicting viral set point in an independent cohort of 10 untreated HIV-1-infected patients from Malawi. RESULTS The gene network inferred at time of enrollment predicted viral set point 24 weeks later in the independent Malawian cohort with an accuracy of 87.5%. As expected, the predictive accuracy of the networks inferred at later time points was even greater, exceeding 90% after week 4. The composition of the inferred networks was largely conserved between time points. The 12 genes comprising this dynamic signature of viral set point implicated the involvement of two major canonical pathways: interferon signaling (p<0.0003) and membrane fraction (p<0.02). A silico knockout study showed that HLA-DRB1 and C4BPA may contribute to restricting HIV-1 replication. CONCLUSIONS Longitudinal gene expression profiling of peripheral blood mononuclear cells from patients with acute HIV-1 infection can be used to create transcriptional network models to early predict viral set point with a high degree of accuracy.

[1]  Paola Sebastiani,et al.  Genetic dissection and prognostic modeling of overt stroke in sickle cell anemia , 2005, Nature Genetics.

[2]  G. Stark,et al.  Unphosphorylated STAT1 prolongs the expression of interferon-induced immune regulatory genes , 2009, Proceedings of the National Academy of Sciences.

[3]  T. Matano,et al.  Induction of CD8+ Cells Able To Suppress CCR5-Tropic Simian Immunodeficiency Virus SIVmac239 Replication by Controlled Infection of CXCR4-Tropic Simian-Human Immunodeficiency Virus in Vaccinated Rhesus Macaques , 2007, Journal of Virology.

[4]  Jack T Stapleton,et al.  The Major Genetic Determinants of HIV-1 Control Affect HLA Class I Peptide Presentation , 2010, Science.

[5]  Jacques Fellay,et al.  A Whole-Genome Association Study of Major Determinants for Host Control of HIV-1 , 2007, Science.

[6]  J. Schmitz,et al.  Emergence of CTL coincides with clearance of virus during primary simian immunodeficiency virus infection in rhesus monkeys. , 1999, Journal of immunology.

[7]  É. Cohen,et al.  Hypophosphorylation of poly(A) polymerase and increased polyadenylation activity are associated with human immunodeficiency virus type 1 Vpr expression. , 2002, Virology.

[8]  F. Hecht,et al.  The Relation Between Symptoms, Viral Load, and Viral Load Set Point in Primary HIV Infection , 2007, Journal of acquired immune deficiency syndromes.

[9]  K. Harada,et al.  Direct Observation of Vortex Dynamics in Superconducting Films with Regular Arrays of Defects , 1996, Science.

[10]  Christopher J. Miller,et al.  HIV-1 Tat reprograms immature dendritic cells to express chemoattractants for activated T cells and macrophages , 2003, Nature Medicine.

[11]  M. Gerstein,et al.  A Bayesian Networks Approach for Predicting Protein-Protein Interactions from Genomic Data , 2003, Science.

[12]  John W. Mellors,et al.  Prognosis in HIV-1 Infection Predicted by the Quantity of Virus in Plasma , 1996, Science.

[13]  Marco Ramoni,et al.  Inferring Nonstationary Gene Networks from Longitudinal Gene Expression Microarrays , 2011, J. Signal Process. Syst..

[14]  Bette Korber,et al.  Dominant influence of HLA-B in mediating the potential co-evolution of HIV and HLA , 2004, Nature.

[15]  H. Clifford Lane,et al.  Administration of an Anti-CD8 Monoclonal Antibody Interferes with the Clearance of Chimeric Simian/Human Immunodeficiency Virus during Primary Infections of Rhesus Macaques , 1998, Journal of Virology.

[16]  D. Ho,et al.  Temporal association of cellular immune responses with the initial control of viremia in primary human immunodeficiency virus type 1 syndrome , 1994, Journal of virology.

[17]  Gil Alterovitz,et al.  Mapping transcription mechanisms from multimodal genomic data , 2010, BMC Bioinformatics.

[18]  Nir Friedman,et al.  Inferring Cellular Networks Using Probabilistic Graphical Models , 2004, Science.

[19]  Su Jin Lee,et al.  Extracellular HIV-1 Tat up-regulates expression of matrix metalloproteinase-9 via a MAPK-NF-κB dependent pathway in human astrocytes , 2009, Experimental & Molecular Medicine.

[20]  Brad T. Sherman,et al.  Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources , 2008, Nature Protocols.

[21]  Steffen L. Lauritzen,et al.  Graphical Models for Genetic Analyses , 2003 .

[22]  K. Kelnar,et al.  High-throughput RNAi screening in vitro: from cell lines to primary cells. , 2005, RNA.

[23]  J. Mascola,et al.  Monitoring HIV vaccine trial participants for primary infection: studies in the SIV/macaque model , 2009, AIDS.

[24]  J. Goedert,et al.  HLA and HIV-1: heterozygote advantage and B*35-Cw*04 disadvantage. , 1999, Science.

[25]  J. Reynolds,et al.  Methamphetamine and HIV-1 gp120 Effects on Lipopolysaccharide Stimulated Matrix Metalloproteinase-9 Production by Human Monocyte-Derived Macrophages , 2011, Immunological investigations.

[26]  J. Mesirov,et al.  Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. , 1999, Science.

[27]  Marco Ramoni,et al.  Transcriptional network classifiers , 2009, BMC Bioinformatics.

[28]  David J. Volsky,et al.  Microarray analysis of changes in cellular gene expression induced by productive infection of primary human astrocytes: implications for HAD , 2004, Journal of Neuroimmunology.

[29]  Michael P Busch,et al.  Dynamics of HIV viremia and antibody seroconversion in plasma donors: implications for diagnosis and staging of primary HIV infection , 2003, AIDS.

[30]  Jeffrey N. Martin,et al.  HIV Controllers with HLA-DRB1*13 and HLA-DQB1*06 Alleles Have Strong, Polyfunctional Mucosal CD4+ T-Cell Responses , 2010, Journal of Virology.

[31]  D. Montefiori,et al.  Control of viremia in simian immunodeficiency virus infection by CD8+ lymphocytes. , 1999, Science.

[32]  M. Carrington,et al.  Possession of HLA class II DRB1*1303 associates with reduced viral loads in chronic HIV-1 clade C and B infection. , 2011, The Journal of infectious diseases.