Systems analysis of human brain gene expression: Mechanisms for HIV-associated neurocognitive impairment and common pathways with Alzheimer's disease

Andrew J. Levine, Jeremy A. Miller, Paul Shapshak, Benjamin Gelman, Elyse J. Singer, Charles H. Hinkin, Deborah Commins, Susan Morgello, Igor Grant, Steve Horvath

Research output: Contribution to journalArticle

33 Citations (Scopus)

Abstract

Background: 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. Methods. 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. Results: 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. Conclusions: 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.

Original languageEnglish (US)
Article number4
JournalBMC Medical Genomics
Volume6
Issue number1
DOIs
StatePublished - 2013

Fingerprint

Systems Analysis
HIV-1
Alzheimer Disease
Gene Expression
HIV
Brain
Transcriptome
Encephalitis
Gene Ontology
Systems Biology
Gene Regulatory Networks
Genes
Oligodendroglia
Virus Diseases
Gliosis
Mitochondrial Genes
Neoplasm Genes
Information Systems
Neurocognitive Disorders
Up-Regulation

Keywords

  • CNS penetration effectiveness
  • Coexpression module
  • HIV encephalitis
  • HIV-associated dementia
  • HIV-associated neurocognitive disorder
  • National neuroAIDS tissue consortium
  • Weighted gene coexpression network analysis
  • WGCNA

ASJC Scopus subject areas

  • Genetics(clinical)
  • Genetics

Cite this

Systems analysis of human brain gene expression : Mechanisms for HIV-associated neurocognitive impairment and common pathways with Alzheimer's disease. / Levine, Andrew J.; Miller, Jeremy A.; Shapshak, Paul; Gelman, Benjamin; Singer, Elyse J.; Hinkin, Charles H.; Commins, Deborah; Morgello, Susan; Grant, Igor; Horvath, Steve.

In: BMC Medical Genomics, Vol. 6, No. 1, 4, 2013.

Research output: Contribution to journalArticle

Levine, AJ, Miller, JA, Shapshak, P, Gelman, B, Singer, EJ, Hinkin, CH, Commins, D, Morgello, S, Grant, I & Horvath, S 2013, 'Systems analysis of human brain gene expression: Mechanisms for HIV-associated neurocognitive impairment and common pathways with Alzheimer's disease', BMC Medical Genomics, vol. 6, no. 1, 4. https://doi.org/10.1186/1755-8794-6-4
Levine, Andrew J. ; Miller, Jeremy A. ; Shapshak, Paul ; Gelman, Benjamin ; Singer, Elyse J. ; Hinkin, Charles H. ; Commins, Deborah ; Morgello, Susan ; Grant, Igor ; Horvath, Steve. / Systems analysis of human brain gene expression : Mechanisms for HIV-associated neurocognitive impairment and common pathways with Alzheimer's disease. In: BMC Medical Genomics. 2013 ; Vol. 6, No. 1.
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AU - Gelman, Benjamin

AU - Singer, Elyse J.

AU - Hinkin, Charles H.

AU - Commins, Deborah

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N2 - Background: 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. Methods. 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. Results: 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. Conclusions: 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.

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