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Metabolic and functional alterations of neurons in the dorsolateral prefrontal cortex (dlPFC) are thought to contribute to impulsivity, which is a hallmark of addictive behaviors that underlie compulsive drug seeking and taking in humans. To determine if there is a transcriptional signature in dlPFC neurons of humans with cocaine use disorder, we performed total RNA-sequencing on neuronal nuclei isolated from post-mortem dlPFC of cocaine addicts and healthy controls. Our results point toward a transcriptional mechanism whereby cocaine alters specific gene networks in dlPFC neurons. In particular, we identified an AP-1 regulated transcriptional network in dlPFC neurons associated with cocaine use disorder that contains several differentially expressed hub genes. Several of these hub genes are GWAS hits for traits that might involve dysfunction of brain reward circuitry (Body-Mass Index, Obesity) or dlPFC (Bipolar disorder, Schizophrenia).
Further study is warranted to determine their potential pathophysiological role in cocaine addiction. Early studies identified the prefrontal cortex (PFC) as a brain region that undergoes significant changes after long-term cocaine use. For example, using brain imaging techniques it has been shown that long-term cocaine users have reduced volume of PFC, which is accompanied by functional hypoactivity in the region. As a highly evolved portion of frontal cortex, PFC is currently thought to mediate inhibitory control over behavior as a normal brain process.
Therefore, dysfunction of this brain region is thought to lead to impulsivity, which is a hallmark of addictive behaviors that underlie compulsive drug seeking and taking. Numerous studies have sought to translate this clinical work by showing that PFC dysfunction in rodents leads to a loss of inhibitory control and increased drug seeking behaviors in animal models.
While the homology between rodent and human PFC remains uncertain, some functional studies suggest that human dorsolateral PFC (dlPFC), or Broadman’s Area 46, may play a similar role to medial PFC in rodents. However, it is clear that rodent mPFC does not account for all of the diverse functions of human dlPFC, leading to the view that it first evolved in non-human primates.While there is a large literature concerning changes in the function, morphology, and metabolism of the human PFC after chronic cocaine use, little is known about the transcriptional alterations that underlie these changes in human dlPFC, which has been suggested as a target for treating addiction. An earlier study performed gene expression profiling using microarrays in brain samples of human cocaine abusers. One limitation of this study is that it used whole tissue extracts for expression profiling, leading to their identification of prominent changes in oligodendrocytic transcripts in their analysis. The presence of multiple cell types in brain tissue samples thus prevents detection of neural-specific pathophysiology. Another limitation is the reliance on microarray technology, which has many disadvantages when compared to next generation sequencing technologies.
There has also been little to no progress in the discovery of novel drugs for the treatment of cocaine use disorder. A gap thus remains in our understanding of how transcription in dlPFC neurons is altered after cocaine use in humans, and how those neuroplastic changes relate to abnormal functioning of the region.To address this, we performed total RNA-sequencing on fluorescent-activated cell sorting (FACS)-isolated dlPFC neuronal nuclei from humans who were chronic users of cocaine with severe patterns of use and from healthy controls. Cocaine intoxication deaths were selected based on forensic autopsy certification of the cause and manner of death. All cases selected for analysis met criteria for cocaine dependence with intoxication at autopsy (ICD-10 F14.22) and DSM-IV diagnostic criteria for cocaine abuse or dependence (replaced by cocaine use disorder in DSM-5). Cocaine users are at high risk for developing cocaine use disorder. The cocaine cases selected for this study were chronic users, many of whom were “crack” cocaine users based on informant interviews and scene investigations.After we validated the cell type-specificity of our approach, we identified 883 differentially expressed transcripts in dlPFC neurons of cocaine addicts, several of which have known roles in neuroplasticity underlying drug addiction. We then performed Weighted Gene Co-Expression Network Analysis (WGCNA) and identified a gene network in dlPFC neurons whose expression is altered in cocaine users compared to healthy controls.
Several of the differentially expressed hub genes in this module are GWAS hits in other diseases with potential neuropsychiatric components. Our results corroborate previous studies identifying increased AP-1 mediated transcription in the brain after cocaine administration and provide an important translational step forward by showing these same signaling pathways are altered in neurons of human addicts. Cell type-specific total RNA-sequencing from human post-mortem dlPFC neuronsWe performed total RNA-sequencing on dlPFC neuronal nuclei isolated from humans with chronic cocaine use disorder who died from cocaine intoxication and from healthy controls (Table ) (Supplementary Table ). The cocaine cases were sampled from a robust collection of brains taken at forensic autopsy. We utilized a method for obtaining total RNA from neurons in frozen human brain tissue that does not require ribosomal depletion based on previous methods for isolating neuronal nuclei from human post-mortem brains.
Importantly, the nuclear sorting method we used minimizes aberrant transcription induced during FACS when compared to sorting methods that rely on enzymatic dissociation of brain tissue. We did not observe any difference in the abundance of neuronal nuclei across cases and controls, suggesting that any brain volume loss observed in the dlPFC of human cocaine addicts is not due to loss of neurons (Table ). Likewise, there was no difference in the average RIN (RNA integrity number) values of isolated RNA between cases and controls; RIN values are low—compared to those seen for whole cell RNA extracts—due to the lack of rRNA content in isolated nuclei.
The high quality of the extracted nuclear RNA was nonetheless confirmed by the broad distribution of transcript sizes (Supplementary Figure ). After sequencing, we compared the relative abundance of transcript types across all samples and found that we captured a comparable amount of each type across all samples (Fig. ). We did not observe any differences in relative transcript type abundance across cocaine and control cases. These data show that we consistently captured all transcript types in RNA-sequencing from human post-mortem neurons in an unbiased manner.
As we did not perform a ribosomal depletion step, we also captured a wide variety of neuron-specific structural and regulatory RNAs that are otherwise lost with traditional poly-A-selection library preparation approaches for RNA-sequencing. Many of these transcripts are annotated but do not have known functions.
Importantly, the rRNA in our samples did not saturate the reads in any sample, and we reliably quantified protein-coding transcript expression across all samples. The total transcriptome is available as a resource in Supplementary Table. Cell type-specific total RNA-sequencing in human post-mortem dlPFC neuronal nuclei. ( a) Quantification of read counts for each transcript type that was detected using RNA-sequencing. Healthy controls are shown on the left while cocaine cases are on the right. We did not detect any statistically significant differences in abundance of transcript types across cases and controls.
( b) Neuron-specific transcripts are highly expressed, including microtuble associated protein 2 ( MAP2), synaptophysin ( SYP), enolase 2 ( ENO2), neuronal nuclear protein ( NEUN, also known as RBFOX3) and postsynaptic density 95 ( PSD95). The astrocyte specific protein, glial fibrillary acidic protein ( GFAP) was expressed at several orders of magnitude lower levels, while microglial and oligodendrocyte specific transcripts ( OLIG1/2, oligodendrocyte transcription factor 1/2; NCF1, neutrophil cytosolic factor 1; and GDF15, growth differentiation factor 15) were not detected. Y-axis is log counts Per million.
Standard error of the mean is shown. – Astrocyte-specific, Oilgo. – Oligodendrocyte-specific. Confirming the cell type-specificity of our sequencing data, we observed high expression (7logCPM) of several neuron-specific transcripts such as: microtubule associated protein 2 ( MAP2), synaptophysin ( SYP), enolase 2 ( ENO2), neuronal nuclear protein ( NEUN), and postsynaptic density 95 ( PSD95) (Fig. ).
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Glial fibrillary acidic protein ( GFAP), a marker for astrocytes, is barely present—at several orders of magnitude lower levels, while markers from oligodendrocytes and microglia were not detected,. These data validate our FACS sorting method for isolating neuronal nuclei from human post-mortem brain tissue and verify the purity of our total RNA-sequencing samples. Transcriptional alterations in human post-mortem dlPFC neurons of cocaine-addicted individualsAfter validating the cell type-specificity and purity of our RNA-sequencing, we performed a differential expression analysis and identified transcriptome-wide alterations in transcript expression induced by cocaine use disorder in dlPFC neurons. Our data identify several up-regulated transcripts that have been implicated previously as general mechanisms underlying drug-induced neuronal plasticity, including c-JUN, c-FOS, and JUNB (Fig. ). Our data support the literature identifying these transcription factors as mediators of transcriptional alterations seen in brain in addiction via the AP-1 binding site.
Differential expression of transcripts in human dlPFC between cocaine and control cases. We used Voom limma to identify 883 transcripts with a nominal p-value. Overall, our differential expression signature contains 10 different transcript types across 883 transcripts.
We quantified the proportion of transcript types in our differential expression signature and found that more than half of the alterations identified were in protein-coding transcripts, showing that our total nuclear RNA-sequencing strategy robustly captures transcriptional activity of protein-coding genes. Alterations in pseudogene transcripts were the second most abundant, followed by alterations in lincRNAs (long intervening non-coding RNAs) and antisense transcripts. We note that non-coding RNA transcripts as a whole were overrepresented in the differentially expressed transcripts (p 0.05), suggesting that non-coding RNAs were significantly and preferentially altered. The enrichment of non-coding RNAs in the differential expression signature compared to their abundance in the genome highlights the advantage of using total RNA-sequencing in human samples to identify transcriptional mechanisms of disease pathology, as non-coding transcripts have been shown to play a critical role in regulating post-transcriptional processing of their functional homologs and remain an elusive target in our understanding of human disease.
Calculating gene co-expression networks in dlPFC neurons of cocaine-addicted humansTo study dlPFC transcriptional networks associated with cocaine use disorder, we calculated weighted gene co-expression networks on the total transcriptome of dlPFC neurons from all samples. We identified 13 distinct gene co-expression modules (Fig. ). Each module is comprised of a group of coexpressed genes—exhibiting strongly correlated patterns of expression in our dataset—and given an arbitrary color for a name.
Resampling methods confirmed that these modules are robust and reproducible, and GO and KEGG (Kyoto Encyclopedia of Genes and Genomes) term enrichment suggests that these modules are functionally coherent and biologically meaningful (Fig. ). For example, we identified modules associated with mitochondrial metabolism (lightcyan), cell junctions (black), and mRNA splicing (darkturquoise), among others. Module membership and intramodular statistics are provided in Supplementary Table. Weighted Gene Co-expression Network Analysis (WGCNA) of total RNA-sequencing data from human dlPFC neurons from cocaine and control cases reveals 13 distinct co-expression modules. ( a) Each module is labeled by an arbitrary color represented at top and at left, and darker yellow and red represent greater topological overlap. ( b) Z 10 (green line) denotes strong evidence for their reproducibility. Evidence is considered moderate when 10 Z 2.
All modules identified in dlPFC have Z quality scores 10 (green line), suggesting there is strong evidence for their robustness and reproducibility. Transcripts in the brown module are significantly enriched for several distinct biological processes related to neuroplasticityTo identify modules associated with case/control status, we first investigated if any modules were overrepresented with differentially expressed genes. We found that only 3 modules showed significant enrichment after Bonferroni correction: lightcyan ( P = 2.4 × 10 −32, Odds Ratio = 34.620–60–61), grey60 ( P = 8.4 × 10 −17, Odds Ratio = 179.5–30), and brown ( P = 6 × 10 −34, Odds Ratio = 5.64.4–7.1). To investigate if these three modules were correlated with case/control status at the network level, we calculated each module’s eigengene, which approximates the average expression of genes in the module. We then correlated each module eigengene to case/control status. The brown module showed the strongest effect ( P = 0.016), suggesting that it is the strongest candidate for downstream analysis of cocaine-related changes.
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The brown module includes 550 transcripts and exhibits higher module eigengene expression in the cocaine cohort, thus associating perturbations of this network with cocaine use disorder (Fig. ). Furthermore, it was significantly enriched for several biological processes including small GTPase signaling, neurotransmitter secretion, and regulation of ATP-related and metabolic processes suggesting that this network may play an important role in neuroplasticity (Fig. ). These analyses provide important validation that the brown module likely contains genes that contribute importantly to the aberrant patterns of gene expression seen in cocaine users. Brown module expression is increased in human dlPFC neurons from cocaine addicts.
( a) Network diagram of brown module containing 550 transcripts, each shown as an individual node. Lines between nodes connect highly co-expressed transcripts within our dataset (threshold: k 3). Orange nodes show Hub genes, defined as the top 10% most connected transcripts.
Differentially-expressed transcripts are outlined in blue (p.