Systems analysis of human brain gene expression: mechanisms for HIV-associated neurocognitive impairment and common pathways with Alzheimer’s disease
1 Department of Neurology, National Neurological AIDS Bank, David Geffen School of Medicine at the University of California, Los Angeles, CA, USA
2 Department of Human Genetics, David Geffen School of Medicine at the University of California, Los Angeles, CA, USA
3 Department of Medicine (Division of Infectious Disease & International Medicine) and Department of Psychiatry & Behavioral Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
4 Departments of Pathology and Neuroscience & Cell Biology, University of Texas Medical Branch, Galveston, USA
5 Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at the University of California, Los Angeles, CA, USA
6 VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA
7 Department of Pathology, Keck School of Medicine at the University of Southern California, Los Angeles, CA, USA
8 Departments of Neurology, Neuroscience, and Pathology, Manhattan HIV Brain Bank, The Mount Sinai School of Medicine, New York, USA
9 Department of Psychiatry, California NeuroAIDS Tissue Network, University of California, San Diego, USA
10 Department of Biostatistics, University of California, Los Angeles, CA, USA
BMC Medical Genomics 2013, 6:4 doi:10.1186/1755-8794-6-4Published: 13 February 2013
Human Immunodeficiency Virus-1 (HIV) infection frequently results in neurocognitive impairment. While the cause remains unclear, recent gene expression studies have identified genes whose transcription is dysregulated in individuals with HIV-association neurocognitive disorder (HAND). However, the methods for interpretation of such data have lagged behind the technical advances allowing the decoding genetic material. Here, we employ systems biology methods novel to the field of NeuroAIDS to further interrogate extant transcriptome data derived from brains of HIV + patients in order to further elucidate the neuropathogenesis of HAND. Additionally, we compare these data to those derived from brains of individuals with Alzheimer’s disease (AD) in order to identify common pathways of neuropathogenesis.
In Study 1, using data from three brain regions in 6 HIV-seronegative and 15 HIV + cases, we first employed weighted gene co-expression network analysis (WGCNA) to further explore transcriptome networks specific to HAND with HIV-encephalitis (HIVE) and HAND without HIVE. We then used a symptomatic approach, employing standard expression analysis and WGCNA to identify networks associated with neurocognitive impairment (NCI), regardless of HIVE or HAND diagnosis. Finally, we examined the association between the CNS penetration effectiveness (CPE) of antiretroviral regimens and brain transcriptome. In Study 2, we identified common gene networks associated with NCI in both HIV and AD by correlating gene expression with pre-mortem neurocognitive functioning.
Study 1: WGCNA largely corroborated findings from standard differential gene expression analyses, but also identified possible meta-networks composed of multiple gene ontology categories and oligodendrocyte dysfunction. Differential expression analysis identified hub genes highly correlated with NCI, including genes implicated in gliosis, inflammation, and dopaminergic tone. Enrichment analysis identified gene ontology categories that varied across the three brain regions, the most notable being downregulation of genes involved in mitochondrial functioning. Finally, WGCNA identified dysregulated networks associated with NCI, including oligodendrocyte and mitochondrial functioning. Study 2: Common gene networks dysregulated in relation to NCI in AD and HIV included mitochondrial genes, whereas upregulation of various cancer-related genes was found.
While under-powered, this study identified possible biologically-relevant networks correlated with NCI in HIV, and common networks shared with AD, opening new avenues for inquiry in the investigation of HAND neuropathogenesis. These results suggest that further interrogation of existing transcriptome data using systems biology methods can yield important information.