Gene Expression In Human Brain Research Articles

Neuronal Trans-Differentiation in Prostate Cancer Cells.

Neuroendocrine (NE) differentiation in prostate cancer (PCa) is an aggressive phenotype associated with therapy resistance. The complete phenotype of these cells is poorly understood. Clinical classification is based predominantly on the expression of standard NE markers. We analyzed the phenotype of NE carcinoma of the prostate utilizing in vitro methods, in silico, and immunohistochemical analyses of human disease. LNCaP cells, subjected to a variety of stressors (0.1% [v/v] fetal bovine serum, cyclic AMP) induced a reproducible phenotype consistent with neuronal trans-differentiation. Cells developed long cytoplasmic processes resembling neurons. As expected, serum deprived cells had decreased expression in androgen receptor and prostate specific antigen. A significant increase in neuronal markers also was observed. Gene array analysis demonstrated that LNCaP cells subjected to low serum or cAMP showed statistically significant manifestation of a human brain gene expression signature. In an in silico experiment using human data, we identified that only hormone resistant metastatic prostate cancer showed enrichment of the "brain profile." Gene ontology analysis demonstrated categories involved in neuronal differentiation. Three neuronal markers were validated in a large human tissue cohort. This study proposes that the later stages of PCa evolution involves neuronal trans-differentiation, which would enable PCa cells to acquire independence from the neural axis, critical in primary tumors. Prostate 76:1312-1325, 2016. © 2016 Wiley Periodicals, Inc.

Gene expression in the aging human brain: an overview.

The review aims to provide a summary of recent developments in the study of gene expression in the aging human brain. Profiling differentially expressed genes or 'transcripts' in the human brain over the course of normal aging has provided valuable insights into the biological pathways that appear activated or suppressed in late life. Genes mediating neuroinflammation and immune system activation in particular, show significant age-related upregulation creating a state of vulnerability to neurodegenerative and neuropsychiatric disease in the aging brain. Cellular ionic dyshomeostasis and age-related decline in a host of molecular influences on synaptic efficacy may underlie neurocognitive decline in later life. Critically, these investigations have also shed light on the mobilization of protective genetic responses within the aging human brain that help determine health and disease trajectories in older age. There is growing interest in the study of pre and posttranscriptional regulators of gene expression, and the role of noncoding RNAs in particular, as mediators of the phenotypic diversity that characterizes human brain aging. Gene expression studies in healthy brain aging offer an opportunity to unravel the intricately regulated cellular underpinnings of neurocognitive aging as well as disease risk and resiliency in late life. In doing so, new avenues for early intervention in age-related neurodegenerative disease could be investigated with potentially significant implications for the development of disease-modifying therapies.

Gene expression in human brain implicates sexually dimorphic pathways in autism spectrum disorders.

Autism spectrum disorder (ASD) is more prevalent in males, and the mechanisms behind this sex-differential risk are not fully understood. Two competing, but not mutually exclusive, hypotheses are that ASD risk genes are sex-differentially regulated, or alternatively, that they interact with characteristic sexually dimorphic pathways. Here we characterized sexually dimorphic gene expression in multiple data sets from neurotypical adult and prenatal human neocortical tissue, and evaluated ASD risk genes for evidence of sex-biased expression. We find no evidence for systematic sex-differential expression of ASD risk genes. Instead, we observe that genes expressed at higher levels in males are significantly enriched for genes upregulated in post-mortem autistic brain, including astrocyte and microglia markers. This suggests that it is not sex-differential regulation of ASD risk genes, but rather naturally occurring sexually dimorphic processes, potentially including neuron–glial interactions, that modulate the impact of risk variants and contribute to the sex-skewed prevalence of ASD.

Human Obesity Associated with an Intronic SNP in the Brain-Derived Neurotrophic Factor Locus.

Brain-derived neurotrophic factor (BDNF) plays a key role in energy balance. In population studies, SNPs of the BDNF locus have been linked to obesity, but the mechanism by which these variants cause weight gain is unknown. Here, we examined human hypothalamic BDNF expression in association with 44 BDNF SNPs. We observed that the minor C allele of rs12291063 is associated with lower human ventromedial hypothalamic BDNF expression (p < 0.001) and greater adiposity in both adult and pediatric cohorts (p values < 0.05). We further demonstrated that the major T allele for rs12291063 possesses a binding capacity for the transcriptional regulator, heterogeneous nuclear ribonucleoprotein D0B, knockdown of which disrupts transactivation by the T allele. Binding and transactivation functions are both disrupted by substituting C for T. These findings provide a rationale for BDNF augmentation as a targeted treatment for obesity in individuals who have the rs12291063 CC genotype.

Cosplicing network analysis of mammalian brain RNA-Seq data utilizing WGCNA and Mantel correlations.

Across species and tissues and especially in the mammalian brain, production of gene isoforms is widespread. While gene expression coordination has been previously described as a scale-free coexpression network, the properties of transcriptome-wide isoform production coordination have been less studied. Here we evaluate the system-level properties of cosplicing in mouse, macaque, and human brain gene expression data using a novel network inference procedure. Genes are represented as vectors/lists of exon counts and distance measures sensitive to exon inclusion rates quantifies differences across samples. For all gene pairs, distance matrices are correlated across samples, resulting in cosplicing or cotranscriptional network matrices. We show that networks including cosplicing information are scale-free and distinct from coexpression. In the networks capturing cosplicing we find a set of novel hubs with unique characteristics distinguishing them from coexpression hubs: heavy representation in neurobiological functional pathways, strong overlap with markers of neurons and neuroglia, long coding lengths, and high number of both exons and annotated transcripts. Further, the cosplicing hubs are enriched in genes associated with autism spectrum disorders. Cosplicing hub homologs across eukaryotes show dramatically increasing intronic lengths but stable coding region lengths. Shared transcription factor binding sites increase coexpression but not cosplicing; the reverse is true for splicing-factor binding sites. Genes with protein-protein interactions have strong coexpression and cosplicing. Additional factors affecting the networks include shared microRNA binding sites, spatial colocalization within the striatum, and sharing a chromosomal folding domain. Cosplicing network patterns remain relatively stable across species.

Disruption of DNA-methylation-dependent long gene repression in Rett syndrome

Disruption of the MECP2 gene leads to Rett syndrome (RTT), a severe neurological disorder with features of autism1. MECP2 encodes a methyl-DNA-binding protein2 that has been proposed to function as a transcriptional repressor, but despite numerous studies examining neuronal gene expression in Mecp2 mutants, no clear model has emerged for how MeCP2 regulates transcription3–9. Here we identify a genome-wide length-dependent increase in gene expression in MeCP2 mutant mouse models and human RTT brains. We present evidence that MeCP2 represses gene expression by binding to methylated CA sites within long genes, and that in neurons lacking MeCP2, decreasing the expression of long genes attenuates RTT-associated cellular deficits. In addition, we find that long genes as a population are enriched for neuronal functions and selectively expressed in the brain. These findings suggest that mutations in MeCP2 may cause neurological dysfunction by specifically disrupting long gene expression in the brain.

Expression of suppressor of cytokine signaling genes in human elderly and Alzheimer’s disease brains and human microglia

Multiple cellular systems exist to prevent uncontrolled inflammation in brain tissues; the suppressor of cytokine signaling (SOCS) proteins have key roles in these processes. SOCS proteins are involved in restricting cellular signaling pathways by enhancing the degradation of activated receptors and removing the stimuli for continued activation. There are eight separate SOCS genes that code for proteins with similar structures and properties. All SOCS proteins can reduce signaling of activated transcription factors Janus kinase (JAK) and signal transducer and activator of transcription (STAT), but they also regulate many other signaling pathways. SOCS-1 and SOCS-3 have particular roles in regulating inflammatory processes. Chronic inflammation is a key feature of the pathology present in Alzheimer’s disease (AD)-affected brains resulting from responses to amyloid plaques or neurofibrillary tangles, the pathological hallmarks of AD. The goal of this study was to examine SOCS gene expression in human non-demented (ND) and AD brains and in human brain-derived microglia to determine if AD-related pathology resulted in a deficit of these critical molecules. We demonstrated that SOCS-1, SOCS-2, SOCS-3 and cytokine-inducible SH2 containing protein (CIS) mRNA expression was increased in amyloid beta peptide (Aβ)- and inflammatory-stimulated microglia, while SOCS-6 mRNA expression was decreased by both types of treatments. Using human brain samples from the temporal cortex from ND and AD cases, SOCS-1 through SOCS-7 and CIS mRNA and SOCS-1 through SOCS-7 protein could be detected constitutively in ND and AD human brain samples. Although, the expression of key SOCS genes did not change to a large extent as a result of AD pathology, there were significantly increased levels of SOCS-2, SOCS-3 and CIS mRNA and increased protein levels of SOCS-4 and SOCS-7 in AD brains. In summary, there was no evidence of a deficit of these key inflammatory regulating proteins in aged or AD brains.

A quantitative transcriptome reference map of the normal human brain.

We performed an innovative systematic meta-analysis of 60 gene expression profiles of whole normal human brain, to provide a quantitative transcriptome reference map of it, i.e. a reference typical value of expression for each of the 39,250 known, mapped and 26,026 uncharacterized (unmapped) transcripts. To this aim, we used the software named Transcriptome Mapper (TRAM), which is able to generate transcriptome maps based on gene expression data from multiple sources. We also analyzed differential expression by comparing the brain transcriptome with those derived from human foetal brain gene expression, from a pool of human tissues (except the brain) and from the two normal human brain regions cerebellum and cerebral cortex, which are two of the main regions severely affected when cognitive impairment occurs, as happens in the case of trisomy 21. Data were downloaded from microarray databases, processed and analyzed using TRAM software and validated in vitro by assaying gene expression through several magnitude orders by 'real-time' reverse transcription polymerase chain reaction (RT-PCR). The excellent agreement between in silico and experimental data suggested that our transcriptome maps may be a useful quantitative reference benchmark for gene expression studies related to the human brain. Furthermore, our analysis yielded biological insights about those genes which have an intrinsic over-/under-expression in the brain, in addition offering a basis for the regional analysis of gene expression. This could be useful for the study of chromosomal alterations associated to cognitive impairment, such as trisomy 21, the most common genetic cause of intellectual disability.

Schizophrenia

Identifying genes for psychiatric disorders using traditional genetic approaches has thus far proven quite difficult. Reasons for this include the complexity of these disorders and the poor definition of the clinical phenotype. However, recent studies have demonstrated the power of an approach called convergent functional genomics (CFG). CFG is a methodology that integrates different types of data to increase the ability to identify genes involved in various psychiatric and nonpsychiatric disorders. The work exemplified in this article integrated human brain and blood gene expression data, relevant animal model brain and blood gene expression data, and human genetic data to identify candidate genes and blood biomarkers for schizophrenia.

Human speech- and reading-related genes display partially overlapping expression patterns in the marmoset brain

Language is a characteristic feature of human communication. Several familial language impairments have been identified, and candidate genes for language impairments already isolated. Studies comparing expression patterns of these genes in human brain are necessary to further understanding of these genes. However, it is difficult to examine gene expression in human brain. In this study, we used a non-human primate (common marmoset; Callithrix jacchus) as a biological model of the human brain to investigate expression patterns of human speech- and reading-related genes. Expression patterns of speech disorder- (FoxP2, FoxP1, CNTNAP2, and CMIP) and dyslexia- (ROBO1, DCDC2, and KIAA0319) related genes were analyzed. We found the genes displayed overlapping expression patterns in the ocular, auditory, and motor systems. Our results enhance understanding of the molecular mechanisms underlying language impairments.

Genetic variation affecting temporal patterns of gene expression and disease in human brain (776.1)

It is widely recognized that noncoding regions of the human genome, including those controlling the cis‐regulation of gene expression, harbor most disease‐associated genetic variants and most regions under selective constraint. Although the expression of many genes is a dynamic process that changes during an organism’s lifetime, most studies mapping genetic variants affecting gene expression have either ignored the variation in ages among individuals, or treated it as a confounding variable. Here we introduce a method for mapping genetic variants that affect the developmental timing of gene expression, which we call temporal expression quantitative trait loci (teQTL). Applying this approach to human prefrontal cortex, we found several thousand genes associated with teQTLs. These teQTLs are distinct from variants affecting expression levels throughout life, and are often associated with distal transcriptional enhancers or age‐related changes in DNA methylation. Moreover they coincide with dozens of SNPs previously implicated in neurological traits such as Alzheimer’s disease, Parkinson’s disease, and educational attainment. These results suggest that teQTLs are a widespread source of variation in human neurological phenotypes.Grant Funding Source: Supported by the Pew Foundation

Differential changes in gene expression in human brain during late first trimester and early second trimester of pregnancy

This study aimed to describe brain development during the first (B1) and second trimester (B3) in human fetuses. Ten brains from 10 to 18 weeks of gestational age (GA) were collected, and the RNA was used for transcriptome analysis (Affymetrix 1.0 ST microarray chip). Differences in brain development within 10 to 18 GA were investigated by dividing the sample into 10 to 12 (B1), 13 to 15(B2) and 16 to 18(B3) weeks. A fold change of 2 or above, with a false discovery rate of 5%, was used as cut-off to determine differential gene expression for individual genes. Quantitative real-time PCR was used to confirm differences. Tests for enrichment procedures (using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes) were then used to identify functional groups of mRNA. At 10 to 12 weeks, brains showed neuronal migration to be upregulated. From 10 to 18 weeks, brains showed genes coding for neuronal migration, differentiation and connectivity upregulated. ALDH1A1 and NPY genes, marker of spinal cord and striatum, were upregulated in B1 and B3 brains, respectively. Also, SLITRK6-HAS2 and CRYAB-PCDH18 genes for ear and eye sensory input were upregulated in B1. For the first time, brain global gene expression was described in human samples. Period B1 was dominated by genes coding for neuronal migration, differentiation, programmed cell death and sensory organs. B3 was dominated by neuronal proliferation, branching and myelination. Creating such a database will allow comparison with abnormals in future studies.

Widespread sex differences in gene expression and splicing in the adult human brain

There is strong evidence to show that men and women differ in terms of neurodevelopment, neurochemistry and susceptibility to neurodegenerative and neuropsychiatric disease. The molecular basis of these differences remains unclear. Progress in this field has been hampered by the lack of genome-wide information on sex differences in gene expression and in particular splicing in the human brain. Here we address this issue by using post-mortem adult human brain and spinal cord samples originating from 137 neuropathologically confirmed control individuals to study whole-genome gene expression and splicing in 12 CNS regions. We show that sex differences in gene expression and splicing are widespread in adult human brain, being detectable in all major brain regions and involving 2.5% of all expressed genes. We give examples of genes where sex-biased expression is both disease-relevant and likely to have functional consequences, and provide evidence suggesting that sex biases in expression may reflect sex-biased gene regulatory structures.

Induction of the Unfolded Protein Response Drives Enhanced Metabolism and Chemoresistance in Glioma Cells

The unfolded protein response (UPR) is an endoplasmic reticulum (ER)-based cytoprotective mechanism acting to prevent pathologies accompanying protein aggregation. It is frequently active in tumors, but relatively unstudied in gliomas. We hypothesized that UPR stress effects on glioma cells might protect tumors from additional exogenous stress (ie, chemotherapeutics), postulating that protection was concurrent with altered tumor cell metabolism. Using human brain tumor cell lines, xenograft tumors, human samples and gene expression databases, we determined molecular features of glioma cell UPR induction/activation, and here report a detailed analysis of UPR transcriptional/translational/metabolic responses. Immunohistochemistry, Western and Northern blots identified elevated levels of UPR transcription factors and downstream ER chaperone targets in gliomas. Microarray profiling revealed distinct regulation of stress responses between xenograft tumors and parent cell lines, with gene ontology and network analyses linking gene expression to cell survival and metabolic processes. Human glioma samples were examined for levels of the ER chaperone GRP94 by immunohistochemistry and for other UPR components by Western blotting. Gene and protein expression data from patient gliomas correlated poor patient prognoses with increased expression of ER chaperones, UPR target genes, and metabolic enzymes (glycolysis and lipogenesis). NMR-based metabolomic studies revealed increased metabolic outputs in glucose uptake with elevated glycolytic activity as well as increased phospholipid turnover. Elevated levels of amino acids, antioxidants, and cholesterol were also evident upon UPR stress; in particular, recurrent tumors had overall higher lipid outputs and elevated specific UPR arms. Clonogenicity studies following temozolomide treatment of stressed or unstressed cells demonstrated UPR-induced chemoresistance. Our data characterize the UPR in glioma cells and human tumors, and link the UPR to chemoresistance possibly via enhanced metabolism. Given the role of the UPR in the balance between cell survival and apoptosis, targeting the UPR and/or controlling metabolic activity may prove beneficial for malignant glioma therapeutics.

An Informatics Approach to Integrating Genetic and Neurological Data in Speech and Language Neuroscience

A number of heritable disorders impair the normal development of speech and language processes and occur in large numbers within the general population. While candidate genes and loci have been identified, the gap between genotype and phenotype is vast, limiting current understanding of the biology of normal and disordered processes. This gap exists not only in our scientific knowledge, but also in our research communities, where genetics researchers and speech, language, and cognitive scientists tend to operate independently. Here we describe a web-based, domain-specific, curated database that represents information about genotype-phenotype relations specific to speech and language disorders, as well as neuroimaging results demonstrating focal brain differences in relevant patients versus controls. Bringing these two distinct data types into a common database ( http://neurospeech.org/sldb ) is a first step toward bringing molecular level information into cognitive and computational theories of speech and language function. One bridge between these data types is provided by densely sampled profiles of gene expression in the brain, such as those provided by the Allen Brain Atlases. Here we present results from exploratory analyses of human brain gene expression profiles for genes implicated in speech and language disorders, which are annotated in our database. We then discuss how such datasets can be useful in the development of computational models that bridge levels of analysis, necessary to provide a mechanistic understanding of heritable language disorders. We further describe our general approach to information integration, discuss important caveats and considerations, and offer a specific but speculative example based on genes implicated in stuttering and basal ganglia function in speech motor control.

Gene × smoking interactions on human brain gene expression: finding common mechanisms in adolescents and adults

Numerous studies have examined gene × environment interactions (G × E) in cognitive and behavioral domains. However, these studies have been limited in that they have not been able to directly assess differential patterns of gene expression in the human brain. Here, we assessed G × E interactions using two publically available datasets to assess if DNA variation is associated with post-mortem brain gene expression changes based on smoking behavior, a biobehavioral construct that is part of a complex system of genetic and environmental influences. We conducted an expression quantitative trait locus (eQTL) study on two independent human brain gene expression datasets assessing G × E for selected psychiatric genes and smoking status. We employed linear regression to model the significance of the Gene × Smoking interaction term, followed by meta-analysis across datasets. Overall, we observed that the effect of DNA variation on gene expression is moderated by smoking status. Expression of 16 genes was significantly associated with single nucleotide polymorphisms that demonstrated G × E effects. The strongest finding (p = 1.9 × 10⁻¹¹) was neurexin 3-alpha (NRXN3), a synaptic cell-cell adhesion molecule involved in maintenance of neural connections (such as the maintenance of smoking behavior). Other significant G × E associations include four glutamate genes. This is one of the first studies to demonstrate G × E effects within the human brain. In particular, this study implicated NRXN3 in the maintenance of smoking. The effect of smoking on NRXN3 expression and downstream behavior is different based upon SNP genotype, indicating that DNA profiles based on SNPs could be useful in understanding the effects of smoking behaviors. These results suggest that better measurement of psychiatric conditions, and the environment in post-mortem brain studies may yield an important avenue for understanding the biological mechanisms of G × E interactions in psychiatry.

Insights into TREM2 biology by network analysis of human brain gene expression data

Rare variants in TREM2 cause susceptibility to late-onset Alzheimer's disease. Here we use microarray-based expression data generated from 101 neuropathologically normal individuals and covering 10 brain regions, including the hippocampus, to understand TREM2 biology in human brain. Using network analysis, we detect a highly preserved TREM2-containing module in human brain, show that it relates to microglia, and demonstrate that TREM2 is a hub gene in 5 brain regions, including the hippocampus, suggesting that it can drive module function. Using enrichment analysis we show significant overrepresentation of genes implicated in the adaptive and innate immune system. Inspection of genes with the highest connectivity to TREM2 suggests that it plays a key role in mediating changes in the microglial cytoskeleton necessary not only for phagocytosis, but also migration. Most importantly, we show that the TREM2-containing module is significantly enriched for genes genetically implicated in Alzheimer's disease, multiple sclerosis, and motor neuron disease, implying that these diseases share common pathways centered on microglia and that among the genes identified are possible new disease-relevant genes.

A Factor Analysis of Global GABAergic Gene Expression in Human Brain Identifies Specificity in Response to Chronic Alcohol and Cocaine Exposure

Although expression patterns of GABAergic genes in rodent brain have largely been elucidated, no comprehensive studies have been performed in human brain. The purpose of this study was to identify global patterns of GABAergic gene expression in healthy adults, including trans and cis effects in the GABAA gene clusters, before determining the effects of chronic alcohol and cocaine exposure on gene expression in the hippocampus. RNA-Seq data from ‘BrainSpan’ was obtained across 16 brain regions from postmortem samples from nine adults. A factor analysis was performed on global expression of 21 GABAergic pathway genes. Factor specificity for response to chronic alcohol/cocaine exposure was subsequently determined from the analysis of RNA-Seq data from postmortem hippocampus of eight alcoholics, eight cocaine addicts and eight controls. Six gene expression factors were identified. Most genes loaded (≥0.5) onto one factor; six genes loaded onto two. The largest factor (0.30 variance) included the chromosome 5 gene cluster that encodes the most common GABAA receptor, α1β2γ2, and genes encoding the α3β3γ2 receptor. Genes within this factor were largely unresponsive to chronic alcohol/cocaine exposure. In contrast, the chromosome 4 gene cluster factor (0.14 variance) encoding the α2β1γ1 receptor was influenced by chronic alcohol/cocaine exposure. Two other factors (0.17 and 0.06 variance) showed expression changes in alcoholics/cocaine addicts; these factors included genes involved in GABA synthesis and synaptic transport. Finally there were two factors that included genes with exceptionally low (0.10 variance) and high (0.09 variance) expression in the cerebellum; the former factor was unaffected by alcohol/cocaine exposure. This study has shown that there appears to be specificity of GABAergic gene groups, defined by covariation in expression, for response to chronic alcohol/cocaine exposure. These findings might have implications for combating stress-related craving and relapse.

Regional differences in gene expression and promoter usage in aged human brains

To characterize the promoterome of caudate and putamen regions (striatum), frontal and temporal cortices, and hippocampi from aged human brains, we used high-throughput cap analysis of gene expression to profile the transcription start sites and to quantify the differences in gene expression across the 5 brain regions. We also analyzed the extent to which methylation influenced the observed expression profiles. We sequenced more than 71 million cap analysis of gene expression tags corresponding to 70,202 promoter regions and 16,888 genes. More than 7000 transcripts were differentially expressed, mainly because of differential alternative promoter usage. Unexpectedly, 7% of differentially expressed genes were neurodevelopmental transcription factors. Functional pathway analysis on the differentially expressed genes revealed an overrepresentation of several signaling pathways (e.g., fibroblast growth factor and wnt signaling) in hippocampus and striatum. We also found that although 73% of methylation signals mapped within genes, the influence of methylation on the expression profile was small. Our study underscores alternative promoter usage as an important mechanism for determining the regional differences in gene expression at old age.

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

BackgroundHuman 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.MethodsIn 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.ResultsStudy 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.ConclusionsWhile 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.