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Gene expression biomarkers of immune recovery in HIV infected patients

Gene expression biomarkers of immune recovery in HIV infected patients
HIV感染者免疫恢复的基因表达生物标志物
批准号:
8591371
负责人:
DOUGLAS D RICHMAN
金额:
$35.05万
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-12-15 至 2014-11-30

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DESCRIPTION (provided by applicant): Poor immune recovery following highly active antiretroviral treatment (HAART) represents a significant health problem affecting a large proportion (30%) of HIV-infected patients. Despite suppressing HIV replication, patients that are unable to sufficiently increase their CD4+ T cell numbers are at significant risk of clinical progression (AIDS-defining event or death). Currently there is a critical need to define the host genes that contribute to CD4+ T cell recovery in order to identify targets for immune modulating therapies. In addition, it is essential to identify biomarkers that can be used to tailor different HAART-regimens to the individual HIV-infected patient in order to maximize CD4+ T cell recovery and increase the utility of existing therapies. In Aim 1 of this proposal differentially expressed genes between HIV-infected patients (exhibiting complete virological suppression) with a good (DCD4 3200 cells/mm3) versus a poor (DCD4 <200 cells/mm3) outcome after 48 weeks of HAART will be identified using microarrays. We hypothesize that genes contributing to immune recovery will induce CD4+ T cell proliferation and prevent apoptosis and this will be confirmed in vitro by siRNA knockdown and gene over expression analysis. In Aim 2 we will expand upon our preliminary studies that showed gene expression prior to HAART can predict with 100% accuracy which HIV- infected patients progress to good versus poor outcome after 48 weeks of drug treatment. Gene expression classifiers predictive of immune recovery will be constructed exclusively for HIV-infected patients treated with a protease inhibitor (PI)-based HAART regimen, and then for patients treated with a non-nucleoside reverse transcriptase inhibitor (NNRTI)-based regimen. Using an innovative approach we will then use the PI-based gene expression classifier to determine if any of the poor outcome patients that were treated with an NNRTI- based regimen were predicted as having a good outcome under a PI-based regimen, and vice versa. In this way we will identify the total number of patients that were placed on the wrong regimen with respect to CD4+ T cell recovery. In the future we will be able to tailor different HAART regimens to the individual patient to increase the extent of immune recovery. In Aim 3 the role of microRNAs (miRNAs) in immune recovery will be investigated. We hypothesize that miRNA degradation of mRNA targets represents one mechanism contributing to the differential gene expression between good and poor outcome groups (Aim 3A), and that a combination of miRNA expression with gene expression will result in more accurate classifiers (Aim 3B). When these studies are complete we will have identified the host genes (i.e. cytokines) that cause immune recovery in HIV-infected patients treated with HAART and may be formulated into immune modulating therapies in the future. We will also have developed gene expression biomarkers capable of guiding the treatment options for HIV-infected patients in order to maximize increases in CD4+ T cell numbers.
期刊论文(1)
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会议论文
Factors regulated by interferon gamma and hypoxia-inducible factor 1A contribute to responses that protect mice from Coccidioides immitis infection.
受干扰素 γ 和缺氧诱导因子 1A 调节的因子有助于保护小鼠免受粗球孢子菌感染。
DOI: 10.1186/1471-2180-12-218
发表时间: 2012
期刊: BMC microbiology
影响因子: 4.2
作者: [Woelk,ChristopherH, Zhang,JinX, Walls,Lorraine, Viriyakosol,Suganya, Singhania,Akul, Kirkland,TheoN, Fierer,Joshua]
通讯作者: Fierer,Joshua
Measuring the Latent Reservoir and Monitoring Eradication Strategies
Gene expression biomarkers of immune recovery in HIV infected patients
Targeting regulators of cellular gene transcription to impact HIV latency
Targeting regulators of cellular gene transcription to impact HIV latency
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