Document text
Principal Investigator: JOSEPH A KOVACS
Organization: CLINICAL CENTER
Fiscal Year: 2024
Funding agency: NIH Clinical Center
At present, there are no clear guidelines as to when antiretroviral (ARV) therapy for human immunodeficiency virus (HIV) should be stopped in the setting of elevated liver enzymes. In large part, this is due to a limited understanding of the natural history of ARV-related hepatotoxicity. We have undertaken a pilot study (Janaki Kuruppu is PI) to estimate the prevalence of hepatic fibrosis in a cohort of HIV-infected patients who have chronically elevated transaminases while on ARV therapy in the absence of Hepatitis B (HBV) or C (HCV) coinfection. Liver biopsy specimens are being evaluated for fibrosis by microscopic examination, the current gold standard for assessing the nature and severity of liver disease. Fibrosis, as well as other histopathology, is being measured using a validated scoring system. Significant liver abnormalities, primarily steatohepatitis, but also fibrosis, have been seen in the 40/62 patients as reported. We have continued to follow these patients long-term to better understand the natural history of these liver abnormalities, and potentially to repeat a liver biopsy in a subgroup of patients, to examine the histopathologic changes that have occurred over time. We have also examined the predictive value of Fibroscans, which were performed in parallel with other evaluations, for identifying fibrosis in patients with elevated transaminases but without HBV or HCV co-infection. This study will provide clinically relevant information on the significance of elevated transaminases in HIV- infected patients without co-infection with HCV or HBV, and facilitate management of such patients.
Biomarkers including D-dimer and IL-6 have been shown to predict mortality in HIV-infected patients, independent of CD4 and viral load. To better understand the mechanism leading to D- dimer elevation, we have undertaken a cross-sectional study to examine markers of coagulation, platelet function, endothelial activation and inflammation, and to identify correlates of elevated D-dimer levels. Our hope is that this analysis will provide insights into which of these pathways is leading to D-dimer elevation. To date we have enrolled approximately 230 HIV+ patients and HIV-volunteers. Preliminary analysis suggests that TNF-alpha, sVCAM, and von Willebrand Factor correlate with levels of D-Dimer. These data suggest that ongoing monocyte activation plays a role in D-dimer elevation.
We have enrolled an additional 60 patients to study the correlates of immunologic non-response in patients receiving cART, including 30 subjects and 30 controls. We have examined immunophenotypic characteristics of the patients, as well as looked for evidence of infection with a variety of viral pathogens, including unknown viruses. We are in the process of examining T-cell receptor repertoire diversity, as well as a detailed flow cytometry panel, biomarker panel, and RNA expression levels using microarrays. We have also examined whole exome sequencing of a subset of these patients to see if there are any genetic markers that can distinguish immunologic non-responders from responders to cART; preliminary analyses have not identified any SNPs associated with increased or decreased risk of being a non- responder. We have also started recruiting INR patients as well as controls to undergo BAL to allow studying immune cells in the lung by single cell RNA seq. The goal is to better understand the mechanisms leading to poor immunologic response in HIV-infected patients.
Compared to immunologic responders, Immunologic non-responders on cART (CD4<350 cells/mm3, with controlled viremia) have increased risk for HIV-related opportunistic complications as well as non-HIV related disorders, including liver, cardiac, metabolic, renal, and CNS disease. To date no interventions have been shown to improve clinically relevant immunologic responses in such patients. Given that PD-1 has been shown to have increased expression on CD4 and CD8 cells in HIV infected patients, and that in certain cancers an anti-PD-1 antibody, pembrolizumab, has shown remarkable biologic activity, we undertook, in collaboration with Merck, a phase 1/2 placebo controlled trial of a single dose of pembrolizumab in immunologic non-responders (CD4 cell number of 100-350 cells/mm3, viral load <40). The primary endpoint is safety, but we will also be examining changes in immunologic and virologic markers as well as changes in CD8-mediated killing of HIV-infected cells. The study has enrolled 7 patients to date; however, no patients have enrolled over the past 4 years, in part as a consequence of the COVID pandemic. Given the difficulties in enrolling patients, we are in the process of closing the study to new enrollment.
Weight gain has been associated with the use of INSTIs such as dolutegravir, as well as the nucleotide reverse transcriptase inhibitor tenofovir alafenamide, out of proportion to weight gain seen with other ARVs such as efavirenz, but the mechanism of action responsible for this is currently unknown. Weight gain can be associated with onset or exacerbation of other medical problems such as diabetes and heart disease, with potentially harmful clinical consequences. To better understand what leads to this weight gain, we have developed a protocol (Janaki Kuruppu is the study PI), in collaboration with investigators at NIDDK, to compare the metabolic effects of dolutegravir to tenofovir alafenamide. We plan to utilize metabolic rooms to measure the metabolic rates at baseline and following short-term administration of the drugs to healthy volunteers, and will also examine food intake and changes in biomarkers such as leptin that are related to weight gain. Insights into the mechanism can potentially identify interventions to minimize this weight gain and associated medical issues.
cART is frequently given in combination with drugs such as INH and rifapentine for prophylaxis to prevent activation of tuberculosis in patients with latent tuberculosis infection. Given the potential impact of rifapentine on enzymes important in drug metabolism, such as CYP3A, it’s important to understand drug-drug interactions of ARVs with INH/rifapentine. We have undertaken 2 studies to examine this, in collaboration with investigators in the Pharmacy department. In the first study, the interaction between either dolutegravir or darunavir/cobicistat and INH/rifapentine was studied. The dolutegravir arm was prematurely discontinued following the development of flu-like symptoms and elevated aminotransferase levels in 2 of 4 subjects after the third INH/rifapentine dose. Markedly elevated levels of interferon-gamma, CXCL10, C-reactive protein, and other cytokines were temporally associated with symptoms. Dolutegravir levels were decreased, while INH levels were increased, during co-administration. In the second arm, darunavir levels were found to be decreased by 71-96%, suggesting that the drugs should not be co-administered. A second, ongoing study is examining the drug-drug interactions of tenofovir alafenamide with INH/rifapentine. Enrollment is complete, drug levels and pharmacokinetic parameters have been determined, and we are in the process of analyzing the data.
Terms: <(TNF)-α><AIDS Virus><Acquired Immune Deficiency Syndrome Virus><Acquired Immunodeficiency Syndrome Virus><Aminotransferases><Anti-Retroviral Agents><B cell differentiation factor><B cell stimulating factor 2><B-Cell Differentiation Factor><B-Cell Differentiation Factor-2><B-Cell Stimulatory Factor-2><BCDF><BSF-2><BSF2><Biological><Biological Markers><Biopsy Sample><Biopsy Specimen><Blood monocyte><C-reactive protein><CD4 Cells><CD4 Positive T Lymphocytes><CD4 T cells><CD4 helper T cell><CD4 lymphocyte><CD4+ T-Lymphocyte><CD4-Positive Lymphocytes><CD8><CD8 Cell><CD8 T cells><CD8 lymphocyte><CD8+ T cell><CD8+ T-Lymphocyte><CD8-Positive Lymphocytes><CD8-Positive T-Lymphocytes><CD8B><CD8B1><CD8B1 gene><CNS Diseases><CNS disorder><COVID-19 pandemic affected><COVID-19 pandemic consequence><COVID-19 pandemic effects><COVID-19 pandemic impact><COVID-19 pandemic impacted><CP34><CRG-2><CXCL10><CXCL10 gene><CYP3><CYP3A><CYP3A4><CYP3A4 gene><Cachectin><Cancers><Cardiac Diseases><Cardiac Disorders><Cell Body><Cell Count><Cell Number><Cells><Central Nervous System Diseases><Central Nervous System Disorders><Characteristics><Chronic><Clinical><Clotting><Coagulation><Coagulation Process><Collaborations><Correlation Studies><Cross Sectional Analysis><Cross-Sectional Analyses><Cross-Sectional Studies><Cross-Sectional Survey><Cytochrome P450 3A4><Cytochrome P450, Subfamily IIIA, Polypeptide 4><Cytochrome P450PCN1><D-dimer><D-dimer fibrin><D-dimer fragments><Data><Development><Diabetes Mellitus><Diagnosis><Disease><Disease Frequency Surveys><Disorder><Dose><Drug Interactions><Drug Kinetics><Drugs><Eating><Endothelium><Enrollment><Enzyme Gene><Enzymes><Evaluation><FAMILY III P450><Fibrin fragment D><Fibrosis><Flow Cytofluorometries><Flow Cytofluorometry><Flow Cytometry><Flow Microfluorimetry><Flow Microfluorometry><Food Intake><Gene Transcription><Genetic Markers><Genetic Transcription><Glucocorticoid-Inducible P450><Goals><Guidelines><HCV><HCV co-infection><HCV coinfection><HCV infection><HIV><HIV Infections><HPGF><HTLV-III Infections><HTLV-III-LAV Infections><Heart Diseases><Hepatic Disorder><Hepatitis B><Hepatitis C><Hepatitis C co-infection><Hepatitis C virus><Hepatitis C virus infection><Hepatitis, Viral, Non-A, Non-B, Parenterally-Transmitted><Hepatitus C><Hepatocyte-Stimulating Factor><Hepatotoxic effect><Hepatotoxicity><Histopathology><Human Immunodeficiency Viruses><Human T-Lymphotropic Virus Type III Infections><Hybridoma Growth Factor><IFI10><IFN-Gamma><IFN-beta 2><IFN-g><IFN-γ><IFNB2><IFNG><IFNγ><IL-6><IL6 Protein><INP10><IP-10><Immune><Immune Interferon><Immune response><Immunes><Immunochemical Immunologic><Immunologic><Immunologic Subtyping><Immunological><Immunological response><Immunologically><Immunologics><Immunophenotyping><Infection><Inflammation><Interferon Gamma><Interferon Type II><Interleukin-6><Intervention><Intervention Strategies><Investigators><Keytruda><Kidney Diseases><LAV-HTLV-III><LYT3><Leptin><Liver><Liver Fibrosis><Liver Toxicity><Liver diseases><Liver lesion biopsy><Lung><Lung Respiratory System><Lymphadenopathy-Associated Virus><M tuberculosis infection><M. tb infection><M. tuberculosis infection><M.tb infection><M.tuberculosis infection><MGI-2><MOB-1><MTB infection><Macrophage-Derived TNF><Malignant Neoplasms><Malignant Tumor><Marrow monocyte><Measures><Mediating><Medical><Medication><Metabolic><Metabolic Diseases><Metabolic Disorder><Methods><Microscopic><Monocyte-Derived TNF><Morbidity><Morbidity - disease rate><Mycobacterium tuberculosis (MTB) infection><Mycobacterium tuberculosis infection><Myeloid Differentiation-Inducing Protein><NIDDK><National Institute of Diabetes and Digestive and Kidney Diseases><Natural History><Nature><Nephropathy><Nifedipine Oxidase><Nucleotides><Ob Gene Product><Ob Protein><Obese Gene Product><Obese Protein><Opportunistic Infections><P450C3><P450PCN1><PD 1><PD-1><PD-1 antibody><PD1><PD1 antibody><Pathogenesis><Pathway interactions><Patients><Pharmaceutical Preparations><Pharmacies><Pharmacokinetics><Pharmacy facility><Phase><Pilot Projects><Plasmacytoma Growth Factor><Predictive Value><Prevalence><Process><Prophylactic treatment><Prophylaxis><Proteins, specific or class, C-reactive><Protocol><Protocols documentation><QOL><Quality of life><RNA Expression><Renal Disease><Reporting><Research Personnel><Researchers><Reverse Transcriptase Inhibitors><Risk><Ristocetin Cofactor><Ristocetin-Willebrand Factor><SCYB10><Safety><Series><Severities><Statistical Correlation><Steatohepatitis><Steroid-Inducible P450- III><Symptoms><System><T-cell receptor repertoire><T4 Cells><T4 Lymphocytes><T8 Cells><T8 Lymphocytes><TB infection><TCR repertoire><TNF><TNF A><TNF Alpha><TNF gene><TNF-α><TNFA><TNFα><Tenofovir><Thesaurismosis><Time><Toxic effect on liver cells><Transaminases><Transcription><Tuberculosis><Tumor Necrosis Factor><Tumor Necrosis Factor-alpha><Viral Burden><Viral Hepatitis B><Viral Load><Viral Load result><Viread><Viremia><Virus><Virus-HIV><Weight Gain><Weight Increase><anti-PD-1 Ab><anti-PD-1 antibodies><anti-PD-1 monoclonal antibodies><anti-PD1 Ab><anti-PD1 antibodies><anti-PD1 monoclonal antibodies><anti-programmed cell death protein 1 antibodies><anti-programmed death-1 antibody><anti-retroviral><antiretroviral therapy><antiretroviral treatment><arm><bio-markers><biologic><biologic marker><biomarker><biomarker array><biomarker panel><body weight gain><body weight increase><clinical relevance><clinically relevant><co-infection><cohort><coinfection><coronavirus disease 2019 pandemic consequence><coronavirus disease 2019 pandemic impact><cytokine><design><designing><developmental><diabetes><disseminated TB><disseminated tuberculosis><drug metabolism><drug/agent><efavirenz><effects following the COVID-19 pandemic><enroll><exome sequencing><exome-seq><fibrin fragment D-dimer><fibrin fragment D1 dimer><fibrin fragment DD><fibrotic liver><flow cytophotometry><flu><gIP-10><gene biomarker><gene expression biomarker><gene marker><gene signature biomarker><genetic biomarker><healthy volunteer><heart disorder><hep C><hepatic body system><hepatic disease><hepatic fibrosis><hepatic organ system><hepatic toxicity><hepatitis C coinfection><hepatitis C virus co-infection><hepatitis C virus coinfection><hepatitis non A non B><hepatopathy><hepatoxicity><histopathologic examination><histopathological examination><host response><immune system response><immunophenotype><immunoresponse><impact of the SARS-CoV-2 pandemic><improved><infection by hepatitis c virus><infection due to Mycobacterium tuberculosis><insight><interferon beta 2><interventional strategy><kidney disorder><lFN-Gamma><liver biopsy><liver disorder><malignancy><marker panel><metabolic rate><metabolism disorder><monocyte><mortality><neoplasm/cancer><non A, non B hepatitis><non-A, non-B hepatitis><participant enrollment><pathogenic virus><pathway><patient enrollment><patient subclass><patient subcluster><patient subgroups><patient subpopulations><patient subsets><patient subtypes><pembrolizumab><pilot study><placebo control trial><placebo controlled trial><platelet function><premature><prematurity><prevent><preventing><primary end point><primary endpoint><programmed cell death 1><programmed cell death protein 1><programmed death 1><pulmonary><recruit><renal disorder><responders and non-responders><responders from non-responders><responders or non-responders><responders versus non-responders><responders vs non-responders><responders/nonresponders><rifapentine><scRNA-seq><serum hepatitis><single cell RNA-seq><single cell RNAseq><single cell expression profiling><single cell transcriptomic profiling><single-cell RNA sequencing><sle2><systemic lupus erythematosus susceptibility 2><tuberculosis infection><tuberculous spondyloarthropathy><viraemia><viral pathogen><viral sepsis><virus pathogen><virusemia><volunteer><von Willebrand Factor><von Willebrand Protein><wt gain>