There is a wide variety of immune factors that have been implicated in the chronic neuroinflammatory state leading to HAND.50 These largely involved cytokines, chemokines, and their cell surface receptors. Both cytokines and chemokines can affect HAND neuropathogenesis through numerous routes. HIV requires chemokine coreceptors to enter cells.51,52 As such, chemokines compete with HIV at these coreceptors and subsequently modify HIV replication53 and disease progression.54,55 Chemokines also affect macrophage activation and chemotaxis of monocytes and other cells across the blood–brain barrier (BBB),56,57 thus leading to increased inflammation and viral seeding of the CNS. Furthermore, chemokines can affect neuronal signaling with subsequent disturbance of glial and neuronal functions.58,59
Leveraging the increasing knowledge of how chemokines, cytokines, and other immune factors influence HAND pathogenesis, many groups have used candidate gene association studies to characterize how specific genetic susceptibility loci within immune-related genes modify risk for HAND.29,34,31,60 Here, we briefly discuss some of these genetic susceptibility loci. Additional detailed information regarding their biological roles of these gene products can be found in Ref. 61.
In recent years, there have been numerous reports of polymorphisms within catecholamine, and more specifically dopamine (DA)-related genes, resulting in measurable differences in neurophysiological and neurocognitive functioning in non-HIV cohorts. Among the most commonly examined are the catechol-O-methyl-transferase (COMT) val158met allele,95–103 the dopamine transporter-1 (DAT-1) 3′-UTR variable tandem repeat,104–109 and the brain-derived neurotrophic factor (BDNF) val66met allele.110–117 Although the effect of these variants on neurocognitive phenotypes has been small, it is conceivable that among vulnerable individuals in whom DA functioning is already compromised, such as those with HIV,107,118–121 the effects will be additive or synergistic. Thus far, cross-sectional studies have not indicated that these alleles increase one's risk of HIV-related neurocognitive deficits.4 For example, Levine et al,42 examining cross-sectional data from the National NeuroAIDS Tissue Consortium, did not detect any interactive effect of disease severity (as measured by CD4+ T-cell count) and COMT, DAT1, or BDNF genotypes described above on a number of neurocognitive domains in an exclusively HIV+ sample. Bousman et al132 reported interactive effects of COMT val158met genotype and executive functioning on sexual risk taking in both HIV+ and HIV– individuals. Although no differences in executive functioning were noted between groups, they did find that among Met allele carriers, those with greater executive functioning deficits reported greater number of sexual partners and other risky sexual practices.
The additive or synergistic effects of DA-related alleles and stimulants such as methamphetamine and cocaine in HIV+ cohorts have also been examined. Gupta et al39 investigated the impact of an SNP (rs6280) within the dopamine receptor-3 (DRD3) gene on neurocognitive functioning in 4 groups, stratified for HIV status and methamphetamine use. The biological connection between DRD3 and HAND is especially interesting, because macrophages are increasingly infected by HIV in the presence of both methamphetamine and increased extracellular DA individually, and that this process is mediated by DA receptors expressed in macrophages, including as DRD3. As the authors hypothesized, only the HIV+ methamphetamine users were found to have genotype-related neurocognitive alterations.
Analyzing longitudinal neurocognitive data from the Multicenter AIDS Cohort, our group has recently examined the longitudinal interaction between HIV status, stimulant use, and COMT genotype in a very large cohort (N = 952) that included both HIV+ and HIV-seronegative individuals. COMT genotype was found to impact the longitudinal neurocognitive functioning of only HIV-seronegative individuals.122 Furthermore, DA-related genetic variants in BDNF (rs6265), dopamine-β-hydroxylase (rs1611115), DR2/ANKK1 (rs1800497), and DR3 (rs6280) did not impact the longitudinal neurocognitive functioning of HIV+ individuals, despite the well-documented involvement of DA functioning in HAND.
Genome-wide association studies (GWAS) have become increasingly affordable and a practical means to study disease pathogenesis. Several such studies have identified additional risk variants associated with HIV disease progression, viral set point, rapid progressors, and other disease-related phenotypes, as previously reviewed.123,124 GWAS have also recently proven valuable for the study of already relatively well-characterized neurological diseases. As an example, a recent GWAS of late-onset Alzheimer disease resulted in the identification of several new genetic susceptibility loci.125–128 Regarding HAND, for which the neuropathogenesis is less understood, GWAS may hold even greater promise. This is because it is unlikely that one or a few genetic susceptibility loci confer a large proportion of the risk for HAND. Instead, variability in HAND risk may depend on a range of common variants, which are more amenable to detection through GWAS platforms (yet require very large sample sizes). As such, the genetic variants detected by GWAS may help to achieve an improved mechanistic understanding of the disease and ultimately lead to targets for pharmaceutical treatment and prevention.129 Only 1 GWAS focusing on HAND has been published to date.49 The study included 1287 white adults enrolled in the Multicenter AIDS Cohort Study. Leveraging the MACS longitudinal protocol that includes serial neurocognitive testing and neuromedical examinations, as well as prevalence of HAD, this study examined a variety of neurocognitive phenotypes for association with more than 2.5 million SNPs. No genetic susceptibility loci were associated with the phenotypes, which included decline in processing speed or executive functioning over time, prevalence of HAD, and prevalence of neurocognitive impairment based on a comprehensive neuropsychological battery. Two SNPs, within the SLC8A1 and NALCN genes, had P values just below the strict GWAS threshold in association with change in processing speed over time. SLC8A1 [solute carrier family 8 (sodium/calcium exchanger) member 1] is involved in ion channel/ion transporter activity in plasma and mitochondrial membranes. Both SLC8A1 and NALCN (sodium leak channel, nonselective) are involved in sodium transport across cellular and intracellular membranes. Loss of mitochondrial membrane potential and other effects of ion transport dysfunction have been implicated in HAD.130–132 Because of the relatively small sample size, future collaborative efforts that incorporate this data set may still yield important findings.
On a more sobering note, recent findings from our group suggest limited utility of genetic studies for elucidating the neuropathogenesis of HAND. Preliminary findings from a study of MACS-based study that examined the longitudinal neurocognitive data from 952 HIV+ and HIV-seronegative individuals did reveal that MIP-1α (CCL3) and MCP-1 (CCL2) genotype did affect neurocognitive functioning over time as a function of serostatus; however, the impact is very minor. As such, although these findings may further underscore the importance of these immune factors in HAND neuropathogenesis, the limited effects of individual gene variants on HAND may not particularly be useful for informing treatment strategies or further clarifying the pathogenic pathways that lead to HAND. As such, greater focus might be placed on dynamic cellular processes, described next.
Recent gene expression studies have taken advantage of genome-wide microarrays, allowing surveillance of virtually the entire transcriptome. Coupled with bioinformatics and statistical methods coming from the field of systems biology, putative biological networks associated with disease state can be identified.134,135 Gene expression studies have been widely used to investigate and discover cellular mechanism involved in the pathogenesis of HIV (as reviewed in Ref. 136). In the context of HAND, there have been a fast growing number of global transcriptome studies to date. Some investigators have focused on specific brain cells in vitro,134,137–139 using methods such as laser capture microdissection. However, with the availability of affordable microarrays, most transcriptome studies to date have used brains of HIV-infected (HIV+) humans, and have focused on gene expression changes underlying HIVE. Such studies, generally limited to examination of homogenized frontal gray matter tissue, have found altered regulation of genes involved in neuroimmune functioning, and also implicated neurodegenerative pathways based on dysregulation of genes involved in synapto-dendritic functioning and integrity,140 Toll-like receptors,141 and interferon response.142 As recently reviewed,143 findings from human microarray studies have been partially replicated in simian immunodeficiency virus models, especially regarding interferon-related and neuroinflammatory-related genes.144,145 Mouse astrocytes exposed to HIV have also shown some transcription overlap with those of simian and human studies.139 Similarities among animal and human brain transcriptome studies were recently reviewed.143
More recently, in analyzing gene microarray data derived from multiple brain regions of HIV+ individuals with HAND alone or HAND with HIVE, Gelman et al146 found 2 apparently distinct transcriptome profiles implicating 2 distinct etiological pathways to HAND. HIVE with concomitant HAND was associated with high viral load (mRNA) in the brain, upregulation of inflammatory pathways across all brain regions, and downregulation of neuronal transcripts in frontal neocortex, whereas HAND without HIVE was characterized by low brain viral burden without evidence of increased inflammatory response and without downregulation of transcripts in frontal neocortical neurons. Indeed, only transcripts characteristically expressed by vascular- and perivascular-type cells were consistently dysregulated in HAND without HIVE. These data were recently re-examined by Levine et al147 using weighted gene coexpression network analysis (WGCNA).148 Although standard gene expression studies such as that by Gelman et al146 use a group comparison approach, WGCNA enables a more systematic and global interpretation of gene expression data by examining correlations across all microarray probes, identifying biologically meaningful “modules” that are comprised of functionally related genes and/or correspond to cell types.149 WGCNA typically results in fewer than 20 modules (as opposed to thousands of genes), which can then be examined for their association to clinical or biological variables of interest. In a study by Levine et al,147 a number of biologically meaningful gene expression modules were identified and then correlated with a global neuropsychological functioning index and CNS penetration effectiveness (CPE) (Fig. 1). Although the WGCNA largely validated the findings from Gelman et al, it also identified meta-networks composed of multiple gene ontology categories, as well as oligodendrocyte and mitochondrial functioning.
Another area in which global transcriptome studies have been used in the context of HAND is to understand the effects of cART. Borjabad et al152 were the first to examine the relationship between cART use and global brain gene expression. Notably, cART-treated cases were found to have transcriptome signatures that more closely resembled those of HIV-seronegative cases. Furthermore, individuals who were taking cART at the time of death had 83%–93% fewer dysregulated genes compared with untreated individuals. Despite this, in both treated and untreated HIV+ brains, there were approximately 100 dysregulated genes related to immune functioning, interferon response, cell cycle, and myelin pathways. Interestingly, gene expression in the HIV+ brains did not correlate with brain viral burden, suggesting that even high CPE,153 which has been shown to reduce CSF viral load,154 may not reduce transcriptomic dysregulation. Indeed, the absence of an association between CPE and brain transcriptome by our group when using both standard differential expression analysis and WGCNA147 would help to explain the equivocal results of studies examining the relationship between CPE and HIV-related neurocognitive dysfunction to date.155–159
Although the examination of brain tissue transcriptome informs our understanding of the mechanistic underpinnings of HAND, the peripheral blood system has been the focus in the search for biomarkers and upstream mechanisms. Only recently has global transcription analysis been used in this context. Like brain tissue, the first hurdle is to separate the desired blood cells before extracting mRNA for microarray analysis. Thus far, monocytes have been the cells of choice for blood transcriptome studies of HAND, and for clear reasons. CD16+ monocytes are among the first cells to become infected with HIV, and a subset of these cells also seems to be associated with the pathogenesis of HAND.160,161 As the virus gains momentum and the immune system weakens, infected monocytes cross the BBB as “Trojan Horse” cells with increasing frequency, driven by both increased chemokine release in the CNS and the peripheral immune response.162–164 This increased traffic of monocytes into the CNS, which also included uninfected monocytes, further increases the expression of chemokines, leading to recruitment of even more monocytes in a feed-forward manner.165–167 Once inside the brain, monocytes differentiate into perivascular macrophages,167 where their role in the neuropathogenesis of HAND has been well described and includes the release of proinflammatory cytokines, chemokines, interferons, and viral proteins that are harmful to nearby neurons and other cells.164,168–172 Thus, monocytes are activated to migrate to the CNS by 2 mechanisms; peripheral immune activation and a chemokine gradient released from cells within the CNS, respectively, termed the “push” and “pull” of inflammatory cell recruitment.164 This interaction between the CNS and circulating blood monocytes is a key mechanism underlying HAND, and as such, delineating cellular alterations that occur within monocytes during this process holds promise for identifying biomarker and pharmaceutical targets.
More recently, the same group focused their analysis on neurophysiological measures rather than HAND.175 Specifically, they examined whether peripheral immune activation was associated with brain metabolite concentrations, as measured by MRS. Thirty-five HIV+ on cART and 8 HIV-seronegative adults were examined. Approximately half of the HIV+ sample was considered to have mild neurocognitive impairment based on standardized testing (the diagnosis of HAND was not determined). Absolute concentrations of brain metabolites in the frontal white matter, anterior cingulate cortex, and basal ganglia were determined and then examined in relation to monocyte gene transcription and a global neurocognitive measure. Among the HIV+ participants, they found an interferon-alpha–induced activation transcriptome phenotype that was strongly correlated with N-acetylaspartate in the frontal white matter. Notably, interferon-gamma inducible protein-10 (IP-10) was strongly correlated with plasma protein levels, and plasma IP-10 was inversely correlated with N-acetylaspartate in the anterior cingulated cortex. This study is particularly remarkable because it is the first to connect transcription changes with putative HIV-related neurophysiological changes. As discussed below, we believe that this tactic holds the greatest promise for elucidating the neuropathogenesis of HAND.
Finally, our laboratory has recently used the Illumina HT-12 v1 Expression BeadChip to analyze monocyte-derived transcriptome data from 86 HIV+ individuals enrolled in the Multicenter AIDS Cohort Trial.176 In contrast to the studies described above, which used standard fold-change comparisons between the HIV+ and control group, we used WGCNA with an all HIV+ sample, as described above.148,177 Unlike Sun et al,35 our standard differential expression analysis identified a number of individual gene transcripts that were significantly correlated with global neurocognitive functioning, after correcting for multiple comparisons. Of the 16 genes identified, many are involved in neuroprotection or neurodegenerative processes, including the interleukin-6 receptor, casein kinase 1-alpha-1, hypoxia upregulated-1, low-density lipoprotein receptor–related protein-12, kelch-like ECH-associated protein-1 (KEAP-1).178–193 Correlations between these gene transcripts and global neurocognitive functioning were in the expected direction considering their biological roles. The KEAP-1 findings are especially interesting, because they support a recently described role for nuclear factor E2-related factor 2 (nrf-2) in HAND.194 Briefly, KEAP-1 sequesters nrf-2 in the cytoplasm.195 Inhibiting the action of KEAP-1 allows more nrf-2 to enter the nucleus, where it promotes the expression of numerous anti-inflammatory and anti-oxidant proteins.196 The exploration in recent years by neuroAIDS researchers of factors that modify the activity of nrf-2 (eg, glycogen synthase kinase 3-β inhibitors197 and curcumin198) further points to the relevance of the KEAP-1/nrf-2 mechanism in HAND neuropathogenesis. As such, this pathway deserves further attention as a potential pharmacological target during early signs of HAND, or even as a prophylactic. In addition, the WGCNA identified 2 modules associated with global neurocognitive functioning. Gene ontology analysis of the significant modules indicates that mitotic cell cycle was positively correlated with global neurocognitive functioning, whereas translational elongation was negatively correlated. It is noted that our data differ from that of previous monocyte studies in that we did not specifically isolate CD14+ monocytes.
Genome-wide transcriptome studies have implicated numerous genes and biological pathways in the neuropathogenesis of HAND. Human studies have been partially replicated in simian and murine models. One limitation of previous studies is the use of homogenized brain tissue, which contains mRNA from numerous cell types,140,144,199,200 thus making it difficult to determine cell-specific molecular processes. In addition, most studies describe gene expression from 1 brain region (eg, frontal lobe), and those regional disease-related transcription changes may not reflect the disease-related transcription changes occurring in brain regions also commonly implicated in HAND (eg, basal ganglia). Also, most in vivo studies using brain tissue have sought to understand alterations in gene expression in brain tissue of humans or animals that expired in an advanced state of disease (ie, HIV-encephalitis or HIV-associated dementia). As such, it is uncertain whether the findings of these studies will generalize to HAND in the current era. In tandem with studies of brain tissue have been investigations of monocyte transcriptome, which may provide clues about earlier stages of pathogenesis. The interpretation of transcriptome data using systems biological methods open the way to novel therapeutic targets. For a more comprehensive discussion of both animal and human brain transcriptome studies, the reader is referred to a review by Winkler et al143
MicroRNAs (miRNAs) are small RNA molecules that modify transcription and translation though interactions with mRNA. Within the CNS, miRNAs regulate a variety of processes. As such, their role in neurological disease has received increasing attention. Still, only a handful of studies examining the role of miRNA in HAND have been published. The first study examined the impact of Tat on expression of selected miRNAs in primary cortical neurons in vitro.201 Tat was found to upregulate mir-128a, which in turn inhibited expression of SNAP25, a presynaptic protein. A second study involved examination of brain tissue; caudate and hippocampus from rhesus macaques with (4) and without (4) simian immunodeficiency virus-encephalitis (SIVE), and caudate from humans HIV-negative controls (6) and those with both HAND and HIVE (5, although only 3 were used for the microarray analysis).202 Although 3 miRNAs were found to be elevated in SIVE and HIVE (miR-142-5p, miR-142-3p, and miR-21), the study focused on miR-21. This miRNA, largely known for its link to oncogenesis, was significantly upregulated in the brains of both HIVE and SIVE, and was specifically found in neurons. Further analysis revealed that it was also induced stimulation of N-methyl-D-aspartic acid receptors, which lead to subsequent electrophysiological abnormalities. Using a variety of experiments, the authors showed that miR-21 targets the mRNA of myocyte enhancer factor 2C (MEF2C), a transcription factor crucial for neuronal function and a target of miR-21, ultimately reducing expression of this mRNA. Immunohistochemistry examination supported this by showing diminished expression of MEF2C in neurons of HIVE and SIVE brains. Noorbakhsh et al130 conducted miRNA profiling in the frontal lobe white matter of 4 HIV-negative and 4 HIVE cases matched by age and sex. Differential expression of multiple miRNAs was found. The authors used a 2-fold cutoff as a decision point for further analysis, a common cutoff in gene expression studies. The authors also used bioinformatics in their analysis. This included predicting the mRNA targets for each of the differentially expression miRNAs. Gene ontology term analysis was then performed for predicted mRNA targets to determine their functional classes, which revealed that most of the upregulated miRNAs targeting genes involved in immune response and inflammation, followed by nucleotide metabolism and cell cycle. Perhaps paradoxically, considering findings from many transcriptome studies, inflammation-related genes also ranked first among the targets of downregulated miRNAs. Cell death–related genes also ranked highly among targets of downregulated miRNAs. Furthermore, miRNAs targeting caspase-6 were downregulated, thereby allowing greater expression of this gene, which was confirmed by immunohistochemistry analysis in the astrocytes of HIVE brain sections.
Chromatin structure, and therefore gene expression, can be modified by the acetylation and deacetylation of histone proteins, a process that is mediated by histone deacetylases (HDACs).205 HDAC inhibitors have been shown to improve cognitive ability and may be candidates for treating a variety of neurological diseases.206,207 We are aware of only one study examining histone modification in the context of HAND neuropathogenesis. Saiyed et al208 examined the influence of Tat on the expression of HDAC2 in neuronal cells in vitro, and the subsequent effect of HDAC2 modification on regulating genes involved in synaptic plasticity and neuronal function. HDAC2 expression was negatively correlated with expression of CREB and CaMKIIa genes, which are involved in neuronal regulation.
In the genetic association studies described above, a variety of alleles have been associated with HAND; however, few findings have been reliably replicated. One possible reason for the lack of replicability of findings is the use of different neurobehavioral phenotypes across studies. Many used the diagnosis of HIV-associated dementia (HAD) as the phenotype,14,18,25,29,31 which is a largely unreliable behavioral phenotype.8 Others have used composite measures of global neurocognitive functioning, usually derived from a comprehensive battery of neuropsychological tests.20,23,34 The major drawback of these phenotypes, particularly HAD, is that they are complex, and influenced by a number of environmental, psychometric, and endogenous factors. The numerous nongenetic contributors to variance in these measures (eg, measurement error) makes them less suitable targets for genetic analysis, especially when effect sizes for genetic associations are generally small. Furthermore, global measures of neurocognitive functioning run the risk of missing domain-specific associations with genes of interest. Therefore, domain-specific composite scores (eg, memory or processing speed) may be more suitable cognitive phenotypes for use in genetic analysis. Domain-specific composite scores also have greater test–retest reliability when compared with individual measures, making them more attractive for creating progression phenotypes. In addition, the use of neurocognitive measures, many of which have demonstrated heritability, offers more precision and a more easily replicable phenotype across studies as compared with diagnostic categories.
Unlike the genomic studies, most transcriptome studies have used encephalitis (either SIVE or HIVE) as their disease phenotype. In the pre-cART era, HIVE was considered the neuropathological basis of HAND, which usually manifested in the more severe forms of HAD and minor cognitive/motor disorder. However, in the current era, this relationship is not valid. As described by Everall et al,10 among 589 brains from the NNTC cohort, HIV-related pathology was observed in only 17.5% (11% with classic HIVE, 5% with microglial nodular encephalitis or aseptic leptomeningitis, and 1.5% with HIV-leukoencephalopathy), despite the fact that 88% of the sample had been diagnosed with HAND at some point premortem. Instead, for most of the HAND cases in the current era of widespread cART use, which are mild-to-moderate in severity, the neuropathogenesis of HAND is likely due to neuronal dysfunction caused by a mild and chronic neuroinflammatory state.10,164,169,210 This change may have been best demonstrated recently by Gelman et al, who compared transcription changes of those who had premortem HAND without evidence of postmortem HIVE with that of individuals with premortem HAND who also showed postmortem HIVE. The 2 groups had very distinctive transcriptome profiles despite a similar behavioral phenotype. This study underscores the need to use currently relevant disease phenotypes.
Because of these difficulties in using neuropsychological tests, or diagnoses based primarily on such tests, as phenotypic measures of HAND, some have explored alternative outcome measures. Among these are various neuroimaging indices. While beyond the scope of this review, a variety of MRI and MRS markers have been associated with HIV disease progression, neurocognitive impairment, and response to putative treatments.211–216 Still, and perhaps owing to the more widespread neuroimflammatory process underlying HAND, neuroimaging has not yet yielded a reliable biomarker that could be used as a phenotype in genetic and molecular biological studies, although this is likely to change. Another possible target is neuropathological changes quantified through immunohistochemistry. As such, new neuropathological markers have been sought to explain the behavioral manifestations characteristic of HAND. Among these is dendritic simplification,217 or a combination of synaptic and dendritic markers. For example, Moore et al9 found that a combined neuropathological phenotype consisting synaptodendritic neurodegeneration, as measured by synaptophysin and microtubule-associated protein 2 (MAP2), is associated with HAND across both subcortical and cortical brain regions. Others have reported markers of β-amyloid deposition in the frontal cortex in HIV+ individuals.218–221 Whether or not this protein aggregation is etiologically related to MAP2 and synaptophysin remains unclear. In addition to these markers of neurodegeneration and abnormal protein aggregation, markers of neuroinflammation have also been shown to be associated with neurocognitive impairment or HIV-related brain dysfunction.12,85,222 Indeed, macrophage proliferation, microglial activation, astrocytes activation, and increased chemokine levels have all been found within the CSF and brain of HIV+ individuals.50,65,66,164,169,210,223–225 Although these may all represent candidates for neuropathogenic processes underlying HAND, new methods are necessary to determine which ones are relevant. Toward that end, an innovative approach for simultaneously determining which neuropathological markers are HAND-relevant and which genetic susceptibility loci influence HAND is to examine the association between genotype, neuropathological change, and behavioral outcomes. In this scenario, neuropathological changes (or neurophysiological in the case of neuroimaging) are considered intermediate phenotypes. Put more simply, if HAND is considered at its most basic level to be the end result of a sequence of physiological events that commences with HIV-induced cellular changes that are modified by genetic factors, then determining the extent to which known genetic susceptibility loci for HAND perturb candidate neuropathological and neurophysiological intermediate phenotypes may reveal which ones are most relevant. In this context, neuropathological intermediate phenotypes are less prone to exogenous factors and have a stronger association with genetic susceptibility loci than the neurobehavioral phenotypes (eg, cognitive and functional deficits). As an example, the genetic susceptibility loci found to be associated with HAND, and discussed above, modify host immune response and also modify risk for HAND. It logically follows that these genetic variants must also modify the pathophysiological pathways linking immune response and HAND. This line of investigation is important for the elucidation of HAND neuropathogenesis, yet remains almost completely unexplored. This is not surprising, as this approach has only recently been successfully used in genetic association studies of Alzheimer disease.226,227 For example, the association between ApoE genotype and Alzheimer disease–related cognitive impairment was shown to be mediated by a sequential cascade of amyloid plaque formation and subsequent development of neurofibrillary tangle pathology.226–229 Relevant to HAND, to the best of our knowledge, only 3 studies have examined the relationship between genetic susceptibility loci and neuropathological outcomes. Sato-Matsumura et al,12 with a sample of 44 AIDS patients with autopsy-verified HIVE or HIV-leukoencephalopathy and 30 AIDS patients without these neuropathologies, did not find an association between TNF-alpha genotype at rs1800629 and either of the neuropathological conditions. Diaz-Arrastia et al22 assessed for HIVE or vacuolar myelopathy in the brains of 270 HIV+ individuals who died with AIDS between 1989 and 1996. Neurocognitive functioning and HAND were not considered. They determined the presence of microglial nodules, multinucleated giant cells, myelin pallor, and vacuolar myelopathy in the brains and/or spinal cords. None of the alleles examined were associated with the presence of these markers. More recently, Soontornniyomkij et al43 found that ApoE ε4 and older age were independently associated with the increased likelihood of cerebral amyloid β-plaque deposition in HIV+ adults. Although the amyloid β-plaques in HIV brains were immunohistologically different from those in brains of individuals who died with symptomatic Alzheimer disease, this study is the first to provide a link between genotype and neuropathological findings in HIV. However, neither study considered clinical manifestation of HAND in their design. A preliminary analysis of neuropathological, neuropsychological, and genetic data from a combined data set from Levine et al31 and Moore et al,9 indicates that the MCP-1 marker (rs1024611) is associated with synaptodendritic simplification, and also that synaptodendritic simplification is associated with neurocognitive functioning, suggesting that a neuropathogenic link between genotype, neuropathology, and clinical HAND may be possible.17 This line of inquiry is currently being pursued with funding from the National Institute of Mental Health (R01MH096648-Levine & Moore).
Networks constructed from high-throughput data often reflect aspects of the underlying biology. For example, it has been observed that coexpressed genes tend to be also functionally related, and that clusters of coexpressed genes are often strongly enriched in specific functional categories or cell type markers.149 Transcriptional studies of various diseases have often found clusters of genes, termed modules, which correlate with disease status. For example, our WGCNA approach is a widely used systems biological approach for finding disease-related coexpression modules and intramodular hub genes.19,148,177 WGCNA can be interpreted as a stepwise data reduction technique, which (1) starts from the level of tens of thousands of variables (eg, gene expression probes), (2) identifies biologically interesting modules (eg, based on their association with disease status), (3) represents the modules by their centroids (eg, eigenvectors or intramodular hubs), (4) uses intramodular connectivity (also known as module membership measure or kME) to annotate genes with respect to module membership, and (5) combines gene significance and module membership measures for identifying significant hub nodes. The module centric analysis alleviates the multiple testing problem inherent in high dimensional data. Instead of relating thousands of variables to disease status, it only correlates a few dozen modules to disease status. Highly connected intramodular hub genes can be interpreted as module centroids that best represent the module.24 Often highly connected hub nodes in a network have been found to be important for the network's functioning.230
When selecting biomarkers (eg, gene expression profile) for a clinical trait (eg, disease status or survival time), the traditional (marginal) method is to base the selection on the statistical association of the individual candidate biomarkers with the disease (eg, finding differentially expressed genes using a Student t test or fold-change criterion). Network approaches have emerged as an increasingly used alternative to these traditional analysis methods (as the previous sections illustrate in the context of HAND), but their use for selecting biologically or clinically important genes has not been explored extensively, in particular in the context of aggregating evidence from multiple data sets (meta-analysis). Many biostatisticians wonder when to use (intramodular) network connectivity instead of a more traditional statistical significance measure (eg, a marginal meta-analysis method). To address this question, we recently compared hub gene selection (based on module membership to consensus modules) with marginal meta-analysis that considered each gene in isolation. Our comprehensive empirical studies revealed that the data analysis strategy (networks versus marginal approach) should be informed by the research goal.233 When it comes to gaining biological insights regarding molecular processes, then a coexpression-based meta-analysis method (consensus module analysis) typically perform much better than traditional marginal approaches. But, when it comes to validation success of statistical associations with the clinical outcome, then traditional marginal meta-analysis methods perform as good as (if not better) than coexpression-based approaches. Thus, when it comes to identifying highly significant and reproducible biomarkers, standard marginal approaches will work well. Although standard approaches are good at detecting the low-hanging fruits, they often fail to identify weak and subtle effects. Consensus network-based methods that focus on intramodular hubs can successfully tease out weak signals. Because of the heterogeneous and multifaceted nature of HAND pathogenesis, and the difficulties encountered thus far in validating robust biomarkers, such network-based methods may be most fruitful.
Genetic, transcriptomic, and epigenetic studies have yielded a wealth of information about the neuropathogenesis of HAND. Intersecting results across these 3 methodologies indicate, for example, mitochondrial dysfunction, which has also been implicated in peripheral neuropathy, another common NeuroAIDS condition, perhaps opening a novel avenue of research for HAND therapeutics.234–236 HAND is a behavioral syndrome for which the criteria will continue to evolve. As such, the utility of HAND as a phenotype for genetic and molecular biology studies will continue to yield inconsistent results. Emerging intermediate phenotype candidates, for which more robust associations with genetic and molecular markers might be found, include neuropathological (eg, immunohistochemical markers) and neuroimaging markers. This, in combination with systems biological methods for data reduction and interpretation, represents an exciting and fruitful direction for investigating HAND neuropathogenesis. As more researchers adopt this approach, significant progress in delineating the biological pathways underlying HIV-related neurocognitive impairment is likely to be seen, and as a result, will further improve diagnostic nosology for HAND.
The authors thank their research participants and colleagues from the Multicenter AIDS Cohort Study and National NeuroAIDS Tissue Consortium. The authors specially thank Natasha Nemanim for her editorial assistance.
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