Neurexin 3 is differentially methylated and downregulated following chronic ethanol use.

Neurexin 3 is differentially methylated and downregulated following chronic ethanol use. | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Neurexin 3 is differentially methylated and downregulated following chronic ethanol use. Clara C. Lowe, Frances Miller, Dongqin Zhu, Kip Zimmerman, Larry Wilhelm, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6278278/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background : Increasing evidence confirms the value of unbiased epigenomic and transcriptomic profiling in the identification of neuroadaptations in alcohol use disorder (AUD). Through this integrated omics analysis, we identified neurexin3 ( NRXN3 ) as a critical player in mediating alcohol’s effects on the cortex in primates and mice. Neurexins are presynaptic cell adhesion molecules critical in synaptic adaptations. Although neurexin3 has been linked to substance use disorders, the specific regulatory mechanisms that enable NRXN3 ’s transcript/isoform diversity and the downstream effects on synaptic dynamics contributing to AUD remain unknown. Methods : We conducted unbiased genome-wide DNA methylation (DNAm) and RNAseq analyses of the dorsolateral prefrontal cortex (dlPFC) of rhesus macaques that remained alcohol-naïve (controls) or self-administered ethanol for 12 months. qPCR and immunohistochemistry were used to measure the levels of Nrxn3 transcripts and isoforms in parvalbumin interneurons in the prelimbic cortex (PLC) of mice following chronic ethanol exposure. Results : Our unbiased omics analyses identified sex-specific differences in DNAm and gene expression. However, there was a shared enrichment in signaling pathways mediating synaptic neurotransmission and plasticity. Specifically, we found differential DNAm mapping to NRXN3 , and a specific downregulation of transcript NRXN3b . We further showed this downregulation was conserved in mice following chronic ethanol use, and occurred in parvalbumin interneurons of the PLC. Conclusions: Our research provides significant insights into the complex mechanisms by which ethanol affects the expression of NRXN3 within the PFC/PLC and how this might be modulating synaptic plasticity in a cell type and sex-specific manner. alcohol rhesus macaques DNA methylation neurexin alternative splicing parvalbumin Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Chronic ethanol use causes alterations in multiple neurotransmitter systems leading to an imbalance in excitatory/inhibitory transmission( 1 ). Epigenomic and transcriptomic studies( 2 – 4 ) have proven critical in our understanding of the molecular mechanisms underlying these neuroadaptations. For instance, epigenomic analysis of the nucleus accumbens of rhesus macaques following chronic ethanol use( 2 – 4 ) identified novel genes involved in synaptic plasticity. We further showed that manipulation of these targets reduced ethanol intake ( 5 ); results that highlight the value of this approach to identify potential new therapeutic targets for alcohol use disorder (AUD). In this study, we use a similar approach to characterize the alcohol-associated molecular mechanisms of the prefrontal cortex (PFC), a brain area that plays a central role in guiding executive function and decision making and has been consistently linked with heavy drinking, craving, relapse and difficulty moderating alcohol intake( 6 – 14 ). In fact, interventional studies have linked direct stimulation of PFC areas with reductions in alcohol craving and drinking metrics( 10 , 12 , 14 – 17 ), providing proof-of-concept for AUD treatments that modulate PFC function. We were particularly interested in identifying those molecules that are critical regulators of synaptic plasticity as their manipulation could potentially restore synaptic function and reduce ethanol intake. Neurexins (nrxns) are a family of presynaptic cell adhesion molecules crucial for neuronal communication and plasticity( 18 – 20 ). As key components of the synaptic cleft, neurexins interact with a variety of post-synaptic proteins to mediate synaptic formation, neurotransmission and plasticity( 21 – 23 ). Neurexins are encoded by three genes ( NRXN1 , NRXN2 , and NRXN3 ) and exhibit remarkable structural diversity through alternative splicing (AS) and the use of alternative promoters( 18 , 21 , 23 – 29 ). In fact, neurexins contain six highly conserved splicing sites (SS) and they are commonly spliced into either a longer alpha (a) or the shorter beta (b) and gamma (g, NRXN1 only) forms ( 21 , 24 , 28 , 30 – 35 ). The different isoforms exert different functions; thus, neurexins enable synaptic plasticity by meeting the specific needs of different synapses and adapting neural circuits to changing conditions. Genome wide association studies (GWAS) have linked single nucleotide polymorphisms (SNPs) mapping to NRXNs to various neurodegenerative( 36 – 39 ) and neuropsychiatric disorders( 29 , 40 , 41 ), including substance use disorders( 42 , 43 ). Unlike the other neurexins, SNPs mapping to NRXN3 have been linked to opioid, nicotine, and alcohol dependence( 44 , 45 ), making NRXN3 a genetic candidate for drug addiction( 19 , 38 , 43 – 52 ). Although the role of these SNPs in NRXN3 function remains unknown, studies using full knock outs (KOs) or conditional KOs have shown that NRXN3α couples Ca²⁺ channels to the neurotransmitter release machinery at excitatory synapses( 26 , 31 , 32 , 53 – 60 ). NRXN3α is also involved in the regulation of postsynaptic AMPA receptors in the hippocampus( 32 ), presynaptic release probability of the neurotransmitter readily releasable pool( 61 ), and GABA release through binding to dystroglycan at inhibitory synapses in the olfactory bulb( 26 ). NRXN3β regulates synaptic strength via the control of tonic endocannabinoid signaling in hippocampal excitatory synapses( 20 , 62 ), decreases neurotransmitter release probability in cortical cultures( 63 ), impairs presynaptic Ca 2+ influx triggered by action potentials in excitatory synapses( 20 , 62 ), facilitates clustering of postsynaptic AMPA receptors in the hippocampus( 53 ), and is required for GABA release in the olfactory bulb( 53 ). These findings underscore the complementary yet distinct roles of NRXN3α and NRXN3β, their distinct synaptic functions in different brain regions, and their significance in maintaining synaptic health. While it is known that these synaptic functions are altered with chronic alcohol use, the specific mechanisms related to the regulations of NRXN3 and the downstream effects on synaptic dynamics contributing to AUD remain unknown. Here, we completed genome-wide DNA methylation (GW-DNAm) and transcriptomic (RNAseq) analyses of the dorsolateral prefrontal cortex (dlPFC) of rhesus macaques that remained alcohol-naïve or were exposed to chronic alcohol for 12 months, and identified differentially methylated regions (DMRs) mapping to NRXN3 . Parallel expression analysis of NRXN3α and NRXN3β transcripts showed downregulation of NRXN3β transcripts and isoforms in the macaque dlPFC and the mouse prelimbic cortex (PLC) following chronic ethanol use. This work demonstrates a conserved alcohol-associated mechanism across species. We further explored the alcohol-associated adaptations of Nrxn3α/β in parvalbumin (pvalb) interneurons( 64 – 66 ), which are crucial in modulating the activity of pyramidal neurons( 67 – 70 ) in the PLC, and may contribute to regulating the alcohol-associated imbalance between excitatory and inhibitory neurotransmission characteristic of AUD. Materials and Methods Mice : All experimental procedures received approval from the Institutional Animal Care and Use Committee (IACUC) at Wake Forest University School of Medicine (WFUSOM). Adult (8–10 weeks old) female (F) and male (M) C57BL6 mice from Jackson Laboratory were individually housed on a 12:12 light/dark cycle. Mice (Fs: n = 26, Ms: n = 14) were exposed to an intermittent access two bottle choice (IA-2BC) ethanol paradigm. Mice had access to water only (controls (C), n = 19) or a 10% ethanol solution and water (drinkers (D), n = 21), alternating every other day for 22 hours three times a week. After ~ 21 sessions, mice were euthanized by transcardial perfusion. The PLC from one hemisphere of 16 Cs and 18 Ds was used to isolate DNA/RNA. The PLC from 6 C and 6 D Fs was used for immunoblotting. The brains from 13 Cs and 15 Ds were fixed for immunohistology. Rhesus macaques : Six cohorts (4, 5, 6a, 6b, 7a and 7b) of young adult Ms and Fs (n = 40, ~ 4–6 years old) rhesus macaques (C: 6 Fs and 9 Ms and heavy and very heavy drinkers (HVHD): 7 Fs and 8 Ms that consumed on average 2.9–5.2 g/kg/day ethanol intake) from the Monkey Alcohol and Tissue Research Resource (MATRR database)( 71 ), were included. All procedures were conducted in accordance with the Guide for the Care and Use of Laboratory Animals and the NIH PHS Policy on Humane Care and Use of Laboratory Animals for the care and use of laboratory animal resources and approved by the Oregon National Primate Research Center (ONPRC) Institutional Animal Care and Use Committee. Detailed drinking and physiological data are described in supplemental methods, available at MATRR.com and as previously described ( 72 ) ( 73 ). After necropsy, brain slabs were immediately flash frozen in liquid nitrogen and stored at -80 ̊C for future processing. Samples (~ 30mg) from the dlPFC area 46 (dlPFC-A46) were excised and processed using the Qiagen AllPrep DNA/RNA/miRNA Universal Kit as described( 2 , 3)to isolate DNA and RNA. Genome-wide DNA methylation profiling : One microgram of genomic DNA from macaque samples was used for SureSelect XT Human Methyl-Seq library preparation (Agilent Technologies, Santa Clara, CA, USA) as described( 2 , 3 ). DNA libraries were sequenced on an Illumina NovaSeq6000 at the University of Oregon Genomics & Cell Characterization Core Facility (GC3F). The differential DNAm analysis was carried out by applying a generalized linear mixed effects model (GLMM) implemented in R package PQLseq (version 1.2.1)( 74 , 75 ) separately for each CpG site. We modeled the average consumption of ethanol at 12 months as a predictor of DNAm rate and included age as covariate in the binomial model. Relatedness of the animals was accounted for as a random effect in the model. Each nominal p-value was corrected for multiple comparisons by the False Discovery Rate (FDR). In parallel, the nominal p-value was used as input for Comb-p( 76 ) analysis to identify differentially methylated regions (DMRs) as previously described( 3 ). RNAseq library and sequencing : For stranded RNA-seq, cDNA libraries were prepared with the TruSeq stranded mRNA library prep Kit (Illumina, San Diego, CA, USA). The resulting libraries were sequenced on a HiSeq 4000 (Genomics & Cell Characterization Core Facility, University of Oregon) using a paired-end run (2 × 150 bases). A minimum of 100 M reads was generated from each library. Differential Expression Analysis : Quality of the sequences were verified through FastQC (v. 0.1.1.2)( 77 ). Sequences were aligned to the macaque Mmul_10 (INSDCA Assembly GCA_003339765.3) genome through the STAR alignment package (v. 2.7.3a)( 78 ) allowing for a maximum of 3 mismatches and only unique alignments. Read counts at the gene level were also obtained with the STAR package and were based on the Ensembl.Mmul_10.100 genome annotation. Upper quartile normalization was performed using the edgeR (v. 3.28.0)( 79 ) bioconductor package (Bioconductor, Cambridge, UK). Genes with at least 0.2 CPM across samples were retained for further analysis. These thresholds translate into roughly 10 reads per minimum library size (10/minimum library size in millions)( 80 ). Differential expression (DE) between the C and HVHD groups was determined using edgeR’s Fisher’s exact test function, with the option of “tagwise” dispersion. The threshold for significance was unadjusted p = 0.05. Network analysis : Significant DMRs that had gene annotations were analyzed in STRING, MCODE and ClueGO to find biological pathways enriched with future ethanol drinking( 81 , 82 ). STRING was applied to find only “High confidence” protein-protein interactions with options for “textmining” and “neighborhood” disabled( 81 ). MCODE was applied to the remaining interactions to obtain a set of highly interconnected gene clusters( 82 ) and the biological functions of each clusters with MCODE scores greater than 4.0 were identified through the KEGG pathways( 83 ). Synthesis of complementary DNA (cDNA) by reverse transcription for quantitative PCR (qPCR) : cDNA was synthesized from total RNA (250ng) isolated from the dlPFC-A46 or PLC using the SuperScript IV Reverse Transcriptase (Invitrogen, Vilnius, Lithuania) following the manufacturer’s instructions. qPCR was performed using GoTaq® qPCR Master Mix (1x, A6001, Promega, Madison, WI, USA), forward and reverse primer (400nM each, see Table 1), and template DNA (7.5ng) or nuclease-free water. The following conditions were used: 95°C for 2 minutes (1 cycle); 95°C for 15 seconds; 59°C for 30 seconds (40 cycles). Post-amplification melting curves were analyzed to assess primer specificity. Data were normalized to the geometric mean of the expression levels of the housekeeping genes RPL32 and RPL13A . Relative quantification was performed using the ΔΔCt method. Immunohistology : The fixed (4% PFA) mouse brains (10 µm cryosections) were incubated with primary antibodies (1: 400 Nrxn3β (Invitrogen, Rockford, IL, USA), 1:30 Nrxn3α (R&D Systems, Minneapolis MN, USA), 1:800 pvalb (Invitrogen, Rockford, IL, USA), secondary Alexa fluorescence-conjugated secondary antibodies, and nuclear stain) as described in supplemental material. Fluorescence images were captured using a Leica DMi8 fluorescence microscope. For deeper resolution, confocal images were also acquired from the same slices and analyzed using a Nikon A1plus confocal microscope (Eclipse Ni-E, Nikon, Tokyo, Japan). Representative images were created using ImageJ software and Python script executed in Google Colab. Western blotting : 25µg of protein from mouse PLC were resolved in 4–12% Bis-Tris gels (Invitrogen, Carlsbad, CA, USA), and subsequently transferred to PVDF membranes overnight. Results were normalized using total protein using the iBright1500 (Invitrogen). After blocking, membranes were incubated with primary antibodies against Nrxn3α and Nrxn3β, and horseradish peroxidase-conjugated secondary antibodies. Protein bands were visualized using enhanced chemiluminescence (ECL Select Western Blotting Detection Reagent, Cytiva, Buckinghamshire, UK) using the iBright1500 (Invitrogen). Luciferase reporter assay : To determine the promoter and enhancer activity of the macaque DMRs we cloned the human homologous regions (DMR-M: GRCh38, chr14:79279949–79280380 and DMR-MF: GRCh38, chr14:77981589–77981676) in the luciferase reporter vector pGL3 (Promega, Madison, WI, USA) and transfected HEK293 cells (ATCC, Manassas, VA) using 100ng (10:1 ratio of 90ng of constructed firefly plasmid including the DMR to 10ng of normalization SV40 plasmid). Control vectors were used as recommended by the manufacturer. 48 hours later, cells were assayed for relative luminescence units (RLU) using the Dual-Glo® Luciferase Assay System (Promega, Madison, WI, USA) and the SpectraMax iD3 Microplate Reader (Molecular Devices). Data was normalized against the Renilla expression. All experiments were performed in triplicate. Statistical Analyses : To assess the effects on ethanol and water intake, ethanol preference ratio (EPR), and total fluid intake (TFI) in mice, repeated measures ANOVA with Bonferroni post hoc tests were employed. To check for differences in variance and normality, we applied a Levene’s test and Shapiro-Wilk test; respectively. Gene and protein expression differences across groups were compared using a two-sample t-test when variance was found to be consistent. When assumptions of homogeneity of data and variance were violated, non-parametric methods such as the Welch’s t-test or Mann-Whitney U test were employed. If sphericity was not met, as determined by Mauchly's test, adjustments were made using the Greenhouse-Geisser correction. All statistical results are presented as mean ± SEM, and significance was set at a p-value of less than 0.05 for differences between groups. For the luciferase assays, we used ANOVA followed by Bonferroni test, with a p-value < 0.05 considered statistically significant. Results Chronic heavy alcohol use is associated with sex-specific differential DNAm and gene expression in the macaque dlPFC-A46. Across all sites, the most noticeable differences in DNAm levels between groups (C and HVHD, in M and F) was in the intermediate ranges of DNAm (25–75%) (Fig. 1 A). In the MF combined analysis, we identified 180 DMRs (p Sidak < 0.05), with a slight bias towards hypomethylation (Fig. 1 B-C). These differentially methylated genes (DMGs) were enriched in Ca 2+ binding, cell adhesion, synapse assembly ( ATP2B2 , CDH22 , LTBP4 , RCN1 (Fig. 1 G), RYR1 , PCDHB2 , 3, 6, 7). The top-most significant DMRs mapped to IKZF1 , a novel regulator of microglia homeostasis( 84 ); LINGO3 , a member of the leucine-rich repeat and immunoglobin-domain containing protein family; and several protocadherins (Fig. 1 F and Table S2). When each sex was analyzed separately, there were 906 DMRs (p Sidak < 0.05) in Ms and 420 DMRs (p Sidak < 0.05) in Fs (Fig. 1 C). In Ms, the levels of differential DNAm were relatively small; in fact, among the 960 DMRs, only 126 had an average differential DNAm over 5% (Fig. 1 B). In Fs, larger DNAm differences between Cs and HVHDs were identified, with most of the DMRs displaying differential DNAm rates over 5% (n = 323; Fig. 1 B). The topmost significant DMGs in Ms included the transcription factor HLX , and the X-ray repair cross complementing protein, XCCR1 , which is involved in DNA repair in the brain ( 85 – 87 ) (Fig. 1 D, Table S2). In Fs, the protein tyrosine phosphatase receptor type Q ( PTPRQ ), IKFZ1 and the secretory carrier membrane protein 4 ( SCAMP4 ) were the most DMGs (Fig. 1 E, Table S2). When the interaction between sex and ethanol intake was included in the analysis (MF-Intrxn), we identified 253 DMRs showing different DNAm signatures in Ms and Fs (Table S2, Fig. 1 J-L). For instance, the DMR mapping to the N-acetylglucosamine kinase gene ( NAGK ) was hypermethylated in HVHDs in both Ms and Fs; however, the change was more dramatic for Ms (Fig. 1 J). The DMR mapping to an intergenic location in chromosome 15, showed very similar DNAm in Ms, but a significant reduction in DNAm in HVHD Fs (Fig. 1 K). And the DMR mapping to SFXN5 showed no change in Fs but a significant hypomethylation in HVHD Ms (Fig. 1 L). We then used the total of 1008 DMRs (p nominal < 0.05) in the “MF-Intrxn” comparison and identified 20 DMRs that were shared with the M comparison and 57 DMRs common with the F comparison, indicating that those are signals specific of Ms or Fs; respectively (Table S3; Fig. 1 H-I). As an example, a DMR mapping to the tyrosine phosphatase receptor type Q ( PTPRQ ) is hypomethylated exclusively in HVHD Fs (Fig. 1 I); while an intergenic DMR mapping to chromosome 20 is exclusive of Ms (Fig. 1 H). Taken all these results together, Ms and Fs show very different patterns of DNAm, with very little overlap and small number of DMRs identified in MF combined as compared to each sex separately, and with the interaction. RNAseq analysis of the dlPFC-A46 identified 1,170 and 3,366 differentially expressed genes (DEGs) in Ms and Fs; respectively (Sup. Table 4; Fig. 2 A-B). After correction for multiple comparisons, these numbers were reduced to 1,092 DEGs in Fs and only 9 DEGs remained in Ms. When Ms and Fs were analyzed together, we identified 979 DEGs with 48 remaining after FDR correction (Fig. 2 C-D). Among the most significantly DEGs in the combined MF analysis, the genes encoding the water homeostasis master regulator aquaporin 4 ( AQP4 )( 88 ) and the tripartite motif protein TRIM22 proposed to be a potent activator of NF-kB( 89 ), were upregulated compared to their age-matched Cs (Fig. 2 E-F). The 9 DEGs in Ms were also included in the MF comparison, indicating they were not unique to Ms. In Fs, we identified numerous DEGs mapping to neurotransmitter receptor subunits of GABAergic ( GABBR2 , GABRA1 , GABRA3 , GABRA4 , GABRB2 , Fig. 3 ), glutamatergic ( GRIA1 , GRIA2 , GRID1 , GRIN1 , GRIN2A , GRIN3A , GRM2 , GRM5 , GRM7 ), dopamine ( DRD1 , Fig. 3 ), cannabinoid ( CNR1 ) and cholinergic receptors ( CHRM1 , CHRM3 , CHRM4 , CHRNA2 , CHRNB2 , Fig. 3 ). All these genes were downregulated (Sup. Table 4) in HVHD Fs compared to Cs. These results suggest sex-specific differences in gene expression as we observed in our DNAm analysis. We note that the higher levels of alcohol consumption in Fs (4.5g/kg/day vs 3.3 g/kg/day, p t−test = 5.74x10 − 3 ; Supp. Figure 1 A) may have led to more pronounced and significant effects in Fs, but many of these changes may also reflect true biological differences between M and F that, in turn, relate to the original differences in drinking. Integration of omics highlights the potential role of DNAm as an epigenetic mechanism regulating gene expression associated with chronic ethanol use in rhesus macaques. Using the macaque omics data, we next combined the differentially methylated (p (Sidak) < 0.05) and expressed (M: p unadj < 0.05 and F: FDR < 0.05) datasets and identified 36 and 17 (56 at p unadj < 0.05) genes that were DMGs and DEGs in Ms and Fs, respectively (Sup. Table 5). In Fs, these genes included the pre-synaptic neuronal voltage-gated Ca 2+ 2.2/N-type ( CACNA1B ), which is crucial for SNARE-mediated neurotransmission, and was hypomethylated and downregulated in HVHDs; the gene encoding claudin-10 ( CLDN10 ), which is important for the formation of tight junctions in the endothelial cells in the brain blood barrier (BBB), that was hypomethylated and upregulated in HVHDs; the CLMP gene encoding a cell junction protein involved in regulation of AMPA and Kainate receptors function, that was hypermethylated and downregulated in HVHDs; and the gene encoding an actin cytoskeleton interacting protein, PDLIM2 , that was hypermethylated and upregulated in HVHDs (Fig. 3 A). In Ms, the DMGs and DEGs included genes encoding the aldo-keto reductase family 1 B10 protein ( AKR1B10 ), for the GABA A receptor ( GABRD ) and for the growth arrest-specific 2-like 1 protein ( GAS2L1 ), which were hypermethylated and downregulated in HVHDs; and for catenin alpha-1 ( CTNNA1 ), involved in adherens junction and signal transduction, which was hypermethylated and upregulated in HVHDs (Fig. 3 B). All of the DMRs mapping to these genes were located within the gene body, and they mapped to an internal exon ( CAMK2B ), intron ( AKR1B10 and CTNNA1 ) or to alternative 1st exons ( GAS2L1, CLDN10 , CLMP and PDLIM2 ) or to promoters ( GABRD ). Differentially methylated and expressed genes in the macaque dlPFC-A46 are enriched in synaptic transmission. Using the combined set of differentially methylated (p Sidak < 0.05; annotated to genes) and expressed genes (F: FDR < 0.05; M: p unadj < 0.05) per each sex (F: 1,427; M: 1,613), we performed network and pathway analyses to identify the biological functions distinguishing HVHD from Cs after 12m of ethanol intake. In Fs and Ms, there was a common enrichment in gene expression regulation, lipid metabolism, cytoskeleton organization, vesicle transport, synapse organization and synaptic transmission (Fig. 4 A-B). There were 187 common genes that were DMGs and/or DEGs in both sexes (Sup. Table 6). Among these, 63 showed the same direction of change in DNAm and/or expression in both sexes. These included the gene encoding the Ca 2+ -responsive transcriptional regulator CAMTA1 , that was hypermethylated in HVHDs; the leucine-rich repeat and immunoglobulin-like domain-containing nogo receptor- interacting protein 3 ( LINGO3 ), involved in myelination, that was hypomethylated in HVHDs; as well as the gene encoding the kinesin family member 5B ( KIF5B ) with a role in synaptic plasticity, that was upregulated in both sexes. There were 89 genes that showed the opposite change in direction in DNAm or gene expression in Ms and Fs (Sup. Table 6). For example, the gene encoding the transcription factor LHX3 was hypermethylated in Fs but hypomethylated in Ms. Similarly, the RNA binding protein encoded by CELF4 , which regulates translation of mRNAs associated with synaptic function, was hypomethylated in Fs but hypermethylated in Ms. In addition, Fs showed an upregulation in genes involved in cellular respiration (i.e. COX8A ), and transcriptional and translational regulation as compared to Ms (i.e. RPL8 ). Fs also showed a unique enrichment in myelination regulation and ephrin signaling (Fig. 4 B); while in Ms there was an enrichment in immune response, cilium movement, intracellular signaling cascades and blood brain barrier transport (Fig. 4 A). These results highlight the sex-specific differences between Ms and Fs in adapting to the chronic and heavy amounts of alcohol consumed over time. Beyond the sex-specific differences, we noted a shared enrichment in synaptic transmission pathways in Ms and Fs. Interestingly, the genes within this same pathway are mostly different between both sexes. In Fs, genes in this pathway included several cadherins (i.e. CDH7 ), Na/Ca 2+ exchange channels (i.e. SLC24A2 ), ATPases (i.e. ATP2A2 , Fig. 5 B), regulators of microtubule polymerization (i.e. ARHGEF7 ), numerous genes involved in protein-protein interactions at synapses (i.e. NRXN3 ), regulators of phosphorylation of synaptic proteins (i.e. GIT1 ), regulators of cytosolic Ca 2+ levels (i.e. SRI ), members of dendrites (i.e. PALM ), presynaptic active zone (i.e. PCLO ), excitatory synapses (i.e. CAMK2B ) and regulators of vesicle-mediated neurotransmitter transport and release (i.e. VAMP3, SYT1 ), among others. It is important to note that HPCA (neuron-specific calcium-binding protein), several ATPases, DVL1 (scaffolding protein), ERC2 and BSN (regulators of neurotransmitter release), PCLO , CAMK2B (Fig. 5 B), SYT1 and NRXN3 connect most of these signaling pathways, potentially serving as hubs. In Ms, genes within this pathway such are GRID1 , NRXN3 , GABRD , SLC32A1 (downregulated in HVHD; Fig. 5 D) or DLGAP1 are directly involved in regulating synaptic protein interactions, GABAergic synapses, or social behavior (Fig. 5 C). Through the translation initiation factor EIF4EBP2 and the RNA binding protein encoded by FMR1 (upregulated in HVHD), these synaptic relevant pathways are linking to the regulation of transcription and translation, and to numerous neural relevant pathways, such as action potential or voltage-gated channels (i.e. CACNA1H and PDE4B were upregulated in HVHD). It is important to note that both EIF4EBP2 and FMR1 are enriched in the brain, and they act as regulators of synaptic activity and plasticity. These results indicate that the specific molecules underlying the alcohol-associated adaptations in synaptic transmission might be, mostly, sex-specific. However, we note that NRXN3 was enriched in both, Ms and Fs, indicating a potential common target that could modulate synaptic signaling in both sexes albeit through different mechanisms. NRXN3 is differentially methylated and expressed in HVHD macaques . In Ms and Fs, NRXNs were identified as being DMGs and DEGs (Fig. 5 , 6 ). Specifically, there was a DMR (DMR-M) mapping to an alternative exon 1 of NRXN3 b (ENSMMUT00000096019; transcript 207) that was significantly hypomethylated following chronic alcohol use (Fig. 6 A, C) in HVHD Ms. We note that we did not observe a difference in NRXN3b between nonheavy drinking Ms and Cs, indicating that this effect is specific to heavy amounts of ethanol intake. In Fs, this same DMR showed higher levels of DNAm in HVHDs, but this difference was not significant (Fig. 6 C). We note that the differential DNAm levels for this DMR were small, and this could be due to the cell-type specific DNAm signals in a heterogeneous tissue such as the dlPFC-A46. Also linked to NRXN3 , there was a hypermethylated DMR (DMR-MF) in HVHD Ms and Fs that was located upstream (~ 200kb) of the TSS of NRXN3a (Fig. 6 A-B). This DMR was also identified as nominally significant in Fs only (pZ = 4.31x10 − 5 ; pSidak = 7.64x10 − 1 ). RNAseq analysis found no differential expression of total NRXN3 between Cs and HVHDs in Ms; however, total NRXN3 was downregulated in HVHD Fs compared to Cs (Fig. 6 D). It should be noted that RNAseq did not enable the analysis of distinct transcripts; thus, we conducted quantitative real-time PCR (qPCR) on the same samples and identified a significant downregulation of NRXN3 b and no changes in NRXN3a in HVHDs Ms and Fs (Fig. 6 E-H). Although the expression of NRXN3a in Fs showed a trend towards downregulation in HVHDs, we believe this is driven by higher expression in only two of the control Fs (Fig. 6 E). These results highlight the importance of investigating gene expression at the transcript level. The macaque DMRs mapping to NRXN3 have regulatory function. The DMR-M only reached significant differential DNAm levels in Ms, and we argue that the lack of significance in Fs might be due to the smaller sample size and the larger variance in DNAm in Fs. While the DMR-MF did not survive correction for multiple comparisons, we tested its potential regulatory function. Our studies indicate that the DMR mapping to the 1st exon of NRXN3b (DMR-M; Fig. 1 A) functions as a weak promoter and strong enhancer (Fig. 7 B-C). On the other hand, the DMR mapping upstream of NRXN3a (DMR-MF; Fig. 1 A) might function as a silencer, given the significant reduction in RLU when tested for promoter or enhancer function (Fig. 7 B-C). Nrxn3b is downregulated in female mice following chronic ethanol use, while Nrxn3b is downregulated in parvalbumin neurons in the PLC of both male and female mice. As we observed in macaques, F mice consumed higher levels of ethanol than Ms (16.28±22.17 g/kg vs 11.21±8.18 g/kg; p (t,two−tailed) = 5.16x10 − 3 ; Sup. Figure 1B). We also note that 9 of the 14 Fs consumed more than 15g/kg/day, while none of the Ms reached this higher level of intake. Following IA-2BC, the levels of Nrxn3a mRNA expression in the PLC of Fs was not different between Ds and Cs (Fig. 6 I), while Nrxn3b was downregulated (Fig. 6 J). Furthermore, immunoblotting results showed a significant reduction in the levels of Nrxn3b protein isoform in the same tissues (Fig. 6 L) and no changes in the expression of Nrxn3 a (Fig. 6 K). In Ms, transcript levels were not significantly different between groups for either Nrxn3 α or Nrxn3β (Fig. 6 M, N). Following up on these results, we investigated if the sex-specific changes in the levels of Nrxn3a and Nrxn3b in the PLC observed with alcohol intake were altered in a specific cell type. We selected pvalb interneurons in the PLC, which are known to express high levels of Nrxn3 (based on single nuclei RNAseq data, human protein atlas;( 64 – 66 )), and are important modulators of excitability in excitatory neurons. To cover the whole PLC area, we used brain slices within Bregma coordinates ranging from 1.6 to 2.9. The percent area of the overlap between Nrxn3β and pvalb interneurons as well as the individual percent areas of Nrxn3β and pvalb interneurons were initially associated with the bregma coordinates to examine whether there was any significant association within PLC anterior-posterior location and Nrxn3β and/or pvalb interneurons that needed to be accounted for prior to taking the mean percent overlap in each mouse. Beta regression was computed with percent area as the outcome and bregma coordinate as the predictor adjusting for mouse as a fixed effect. No significant effect was identified for the percent area of pvalb interneurons (p = 3.90x10 − 1 ), Nrxn3β (p = 2.93x10 − 1 ) or the overlap between both (p = 8.70x10 − 1 ). The means of the overlap between Nrxn3β and pvalb interneuons were then computed for each mouse and beta regression was computed on the mean overlap as the outcome and group (D vs C) as the predictor, accounting for sex as a covariate. We identified a significant effect of drinking and sex on the percent overlap of Nrxn3β with pvalb interneurons (drinking status: effect size = -1.62, p = 1.82x10 − 6 ; sex: effect size = -1.22, p = 2.41x10 − 4 , Fig. 8 A, C). The number of pvalb interneurons did not differ significantly in Fs, but there was a significant larger number of pvalb interneurons in Ms compared to Fs (sex: effect size = 0.34, p = 4.57x10 − 2 , Fig. 8 A, B). There was a significant interaction between sex and drinking status, with Ms having much lower levels of Nrxn3b in pvalb interneurons as compared to Fs, especially the Cs. In Fs, the reduction of Nrxn3b in pvalb interneurons agrees with the mRNA and protein levels observed from the PLC (Fig. 6 I-L), and suggests that, the effects of alcohol on this particular cell type might be driving the downregulations we observed in the bulk analyses. Contrarily to Fs, we observed a reduction in the number of pvalb interneurons in Ms following drinking (p = 4.57x10 − 02 , Fig. 8 B). Interestingly, the levels of Nrxn3b in pvalb interneurons were also significantly reduced in male Ds compared to Cs (Fig. 8 C). These results indicate that while Nrxn3b responds similarly in pvalb interneurons following chronic ethanol intake, there might be sex-specific differences in the number of pvalb interneurons as well as in the distribution of Nrxn3 transcripts across cell types in the PLC. Discussion In this study, we characterized the DNAm and gene expression profiles in the dlPFC-A46 of rhesus macaques following chronic heavy alcohol use. The integration of these two datasets enabled identification of the molecular mechanisms underlying synaptic adaptations linked to chronic heavy ethanol use in this cortical region in both Ms and Fs. While most of the signaling pathways were shared in both sexes, there was sex dimorphism in the specific genes associated with synaptic neuroadaptations following chronic ethanol use. We acknowledge that there were sex-specific differences in drinking levels that might lead to more pronounced and significant effects in females, but that does not minimize the events where we do identify significant interactions between sex and drinking. Whether due to a sex-effect or a drinking level effect (linked to sex), our results indicate that therapeutic approaches need take into consideration sex (and potentially drinking levels within the heavy and very heavy drinking classification) in the development of effective treatments for Ms and Fs. In Fs, we identified many DEGs; however, in Ms only 9 DEGs survived FDR correction. This discrepancy could be due to the small differences in DNAm found in Ms (most DMRs showed < 5% differential DNAm) as compared to Fs, which could be confounded by the fewer number of F samples included in these omics analyses. Additionally, and because our analyses were conducted in bulk samples from the dlPFC-A46, cell type specific DNAm signatures might contribute to these small DNAm differences that might be washed out by the heterogeneous nature of the dlPFC-A46 and not be captured as changes in gene expression using bulk analyses. Beyond the differences in DEGs between Ms and Fs, our results emphasize the value of integrating multiple omics datasets to identify the molecular mechanism underlying alcohol-associated adaptations. We identified DMGs and DEGs involved in synaptic plasticity, vesicle transport, cell adhesion and neurotransmission in Ms and Fs. Notably, the differential DNAm patterns, gene expression and associated genes within these signaling pathways underlying such chronic alcohol use adaptations suggest sex-specific mechanisms. For instance, and within the synaptic transmission network, most of the genes were unique to Ms or Fs, except for NRXN3 , a critical synaptic hub protein that was differentially methylated and expressed in both sexes. The neurexin family of proteins are cell adhesion molecules that are integral to synaptic formation and plasticity( 34 , 90 ), and are implicated in a range of neuropsychiatric and neurodegenerative conditions( 40 , 91 , 92 ), including substance use disorders( 46 ). Neurexins are master regulators of synaptic organization known to regulate excitatory and inhibitory synapses( 21 , 28 , 31 ) in a cell type and brain region specific manner. Extensive studies on the role of specific SS of Nrxn3α and Nrxn3b in the hippocampus and, to a lesser degree, in the PFC have been conducted( 93 ), proving the functional differences of the various transcripts encoded by Nrxn3 . However, nothing is known about the regulatory mechanisms driving AS and promoter use of this gene. This is particularly important since synaptic plasticity is at the core of neuroadaptations to changing environmental conditions, such as chronic ethanol use. Our study suggests that chronic heavy alcohol might lead to changes in DNAm on NRXN3 , contributing to the regulation of alternative promoter use of NRXN3 , resulting in a reduction in NRXN3 b . Specifically, two DMRs mapping to NRXN3 and with regulatory function, DMR-M as a weak promoter and strong enhancer and DMR-MF as a silencer, might regulate the expression of the shorter NRXN3β transcript, although this might take place in a sex-specific manner. Given the reported potential differences in DNAm patterns in Ms and Fs, we do not discard the possibility that different regulatory mechanisms might lead to the observed shared NRXN3b downregulation in Ms and Fs. Further studies are needed to determine the target(s) of these regulatory regions and their role in modulating the expression of the different NRXN3 transcripts in Ms and Fs. In agreement with sex-specific regulatory differences, our transcriptomic RNAseq analysis showed no differences in the overall levels of NRXN3 in Ms but a significant downregulation in Fs. It is also possible that these differences are due to cell type-specific differences in the NRXN3 transcripts’ landscape in Ms and Fs. Evidence in the literature supports sex dimorphism in Nrxn3’s function( 64 ). A prior study observed sex-dependent changes in Nrxn3 expression and AS in mouse hippocampus following chronic stress, suggesting that Nrxn3 may engage in sex-specific functions in the hippocampus( 93 ). A recent study found sex-specific differences in intrinsic connectivity and synaptic function of Nrxn3 in pvalb interneurons in the ventral subiculum( 64 ). This study revealed that pvalb interneurons synapse onto regular spiking pyramidal neurons in Ms, but to burst spiking pyramidal neurons in Fs. Furthermore, conditional Nrxn3 -KO in pvalb interneurons impaired synapse density, postsynaptic strength and inhibitory postsynaptic current amplitude at pvalb- regular spiking synapses in Ms but enhanced presynaptic release and IPSC amplitude in Fs. These results support a role for Nrxn3 in mediating inhibitory synaptic transmission in a sex- and cell-type specific manner. Specifically, in Fs the degree of pvalb-mediated inhibition is governed by differences in postsynaptic strength, while in Ms is driven by synapse numbers. These authors further hypothesized that the role of Nrxn3 from the same presynaptic cell is dramatically influenced by the composition of postsynaptic proteins( 20 ). This is particularly relevant, as it is known that Nrxn3 transcripts with different SS bind to different postsynaptic binding partners( 26 , 33 , 63 ). Although this study did not distinguish between Nrxn3α and Nrxn3b, it clearly demonstrates a sexually dimorphic role of Nrxn3 and suggests that the Nrxn3 transcripts’ landscape could be sexually dimorphic, leading to functional differences in Ms and Fs. Our study also shows that the effect of alcohol on Nrxn3 expression was conserved across species, although only in Fs. Specifically, Nrxn3b transcript was downregulated in the dlPFC-A46 and PLC of F macaques and mice, with no change in Nrxn3a. Furthermore, Nrxn3b isoform was downregulated in the PLC of F mice following chronic alcohol use. No dlPFC-A46 tissue was available for protein analyses in macaques. These results suggest that, in F mice, Nrxn3 transcripts (and isoforms) in the PLC respond similarly to chronic alcohol use as in HVHD drinking F macaques. Interestingly, and contrarily to what we observed in macaque HVHD drinking Ms, Nrxn3 transcripts were not downregulated in the PLC of M mice. These results might indicate a species-specific difference in transcriptional regulation, warranting further studies. Given the critical role Nrxn3 plays in pvalb interneurons in the ventral subiculum( 64 ), we next sought to gain cell type resolution and investigated if Nrxn3 protein levels were altered in this specific cell type following chronic ethanol use. Our studies revealed that, in agreement with the mRNA data, Nrxn3b was dramatically downregulated in pvalb interneurons in the PLC of F mice, with no changes in Nrxn3α. Unexpectedly, we also observed a downregulation of Nrxn3b in pvalb interneurons in Ms, even though there were no differences at the mRNA level of the PLC. As noted, it is possible that this discrepancy is due to sex- and cell-type specific differences in the Nrxn3 landscape, with Ms displaying more variability in transcripts’ types by cell types. It is known that other cell types express Nrxn3b ( 38 ) and it is also possible that, as the different cell types adapt to the presence of heavy chronic ethanol, the expression levels of Nrxn3b change accordingly in a cell-type specific manner. Additional studies profiling the alcohol adaptations of Nrxn3 at single cell level are needed to address this question. In the meantime, our results show that pvalb interneurons display the same response to chronic alcohol use in Ms and Fs, a downregulation of Nrxn3b. Others have shown that Nrxn3 is highly expressed in pvalb interneurons( 64 ) and it contributes to pvalb interneurons’ function in modulating excitability of pyramidal neurons(67, 68., 94–98). Chronic ethanol has been linked to reduced number, impaired maturation and reduced excitability of pvalb interneurons( 99 ), leading to a decrease in their inhibitory control over pyramidal neurons( 95 , 100 ) in the PFC( 101 ), which heightened excitatory signaling and could contribute to compulsive drinking( 102 ). However, whether Nrxn3 levels are impacted by chronic alcohol use in this specific cell type remained to be explored. Our study showed consistent number of pvalb interneurons in the PLC in F mice, with downregulation of Nrxn3b expression in pvalb interneurons, with no difference in Nrxn3a levels. These results suggest a direct modulation of this specific isoform rather than an overall reduction in pvalb interneuron numbers or an overall reduction in Nrxn3 levels. In Ms, the effects seem to be a combination of reduced number of pvalb interneurons and reduced Nrxn3b expression. The functional consequences of this reduction remain to be explored. In summary, our research provides significant insights into the complex mechanisms by which ethanol affects the expression of NRXN3 within the PFC. Our results suggest that alcohol might be exerting its effects on synaptic plasticity, at least partially, by modulating DNAm in regulatory regions that alter NRXN3 expression, underscoring the intricate adaptations of NRXN3 regulation and function in response to alcohol in Ms and Fs. We hypothesize that alcohol could be contributing to the increased excitatory state seen in AUD, at least, through alterations in the splicing landscape of NRXN3 . The observed Nrxn3β downregulation in cortical pvalb interneurons would diminish inhibitory control on pyramidal neurons, leading to an imbalance favoring excitatory signaling and reinforcing substance dependence and compulsive behaviors( 103 , 104 ). These changes destabilize the delicate balance necessary for proper neural function, highlighting the importance of Nrxn3b in maintaining synaptic integrity and function. Declarations Data Sharing : The data that support the findings of this study are available on GEO under the following accession number: TBD Author contributions : BMF and RCJ designed the macaque methylomics experiments. RCJ designed and supervised all the molecular biology experiments as well as the studies conducted in rodents. KAG and SWG designed, implemented and oversaw the alcohol self-administration protocol and provided the rhesus macaque samples. RK provided the macaque tissues. TC and RCJ isolated the macaque DNA/RNA samples and prepared the omics libraries. DNA methylation and transcriptomic bioinformatic analyses were performed by KDZ, PD and LJW. FM conducted all the mouse alcohol intake experiments. RC advised on WB conditions. FM, DZ, CCL and RCJ collected all the samples from mice. CCL performed all the rodent molecular and cellular experiments on neurexin 3 and analyzed all the corresponding data. KDZ advised and conducted the appropriate statistical analyses in all the experiments. CM, CCL and KRG conducted and analyzed the confocal imaging. CCL and RCJ wrote the manuscript. KAG, BMF, KFRG, RC, RK, KDZ, CCL and RCJ provided edits to the final version manuscript. Conflict of Interest statement : The authors declare no conflict of interest. References Avchalumov Y, Mandyam CD (2020) Synaptic Plasticity and its Modulation by Alcohol. Brain Plast 6(1):103–111 Cervera-Juanes R, Wilhelm LJ, Park B, Grant KA, Ferguson B (2016) Genome-wide analysis of the nucleus accumbens identifies DNA methylation signals differentiating low/binge from heavy alcohol drinking. Alcohol Cervera-Juanes R, Wilhelm LJ, Park B, Grant KA, Ferguson B (2017) Alcohol-dose-dependent DNA methylation and expression in the nucleus accumbens identifies coordinated regulation of synaptic genes. 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Nature 426(6965):442–446 Lu X, Shu HJ, Lambert PM, Benz A, Zorumski CF, Mennerick S (2025) delta-Containing GABA(A) receptors on parvalbumin interneurons modulate neuronal excitability and network dynamics in the mouse medial prefrontal cortex. J Neurophysiol 133(4):1003–1013 Ferranti AS, Johnson KA, Winder DG, Conn PJ, Joffe ME (2022) Prefrontal cortex parvalbumin interneurons exhibit decreased excitability and potentiated synaptic strength after ethanol reward learning. Alcohol 101:17–26 Saito M, Smiley JF, Hui M, Masiello K, Betz J, Ilina M et al (2019) Neonatal Ethanol Disturbs the Normal Maturation of Parvalbumin Interneurons Surrounded by Subsets of Perineuronal Nets in the Cerebral Cortex: Partial Reversal by Lithium. Cereb Cortex 29(4):1383–1397 Thompson SM, Fabian CB, Ferranti AS, Joffe ME (2023) Acute alcohol and chronic drinking bidirectionally regulate the excitability of prefrontal cortex vasoactive intestinal peptide interneurons. Neuropharmacology 238:109638 Ding ZM, Ingraham CM, Rodd ZA, McBride WJ (2016) Alcohol drinking increases the dopamine-stimulating effects of ethanol and reduces D2 auto-receptor and group II metabotropic glutamate receptor function within the posterior ventral tegmental area of alcohol preferring (P) rats. Neuropharmacology 109:41–48 Marin O (2012) Interneuron dysfunction in psychiatric disorders. Nat Rev Neurosci 13(2):107–120 Fogaca MV, Duman RS (2019) Cortical GABAergic Dysfunction in Stress and Depression: New Insights for Therapeutic Interventions. Front Cell Neurosci 13:87 Additional Declarations The authors declare no competing interests. Supplementary Files SupFigure1DrinkingLevels.png Supplemental Figure 1. Average ethanol drinking levels (g/kg/day) of the male and female macaques (A) and mice (B) following chronic ethanol intake. Sup.Table1.xlsx Sup.Table2.xlsx Sup.Table3.xlsx Sup.Table4.xlsx Sup.Table5.xlsx Sup.Table6.xlsx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6278278","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":432146579,"identity":"170ff2ba-b82f-4d44-be1f-a5adc36a990e","order_by":0,"name":"Clara C. 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Those hypomethylated and significant (p\u003csub\u003eSidak\u003c/sub\u003e \u0026lt; 0.05) are represented in blue, and those hypermethylated and significant are shown in red. \u003cstrong\u003eG-L\u003c/strong\u003e) Violin plots of the DNAm rates in Cs and HVHD of DMRs identified in the M only (\u003cstrong\u003eH\u003c/strong\u003e), F only (\u003cstrong\u003eI\u003c/strong\u003e), MF comparison that showed the same direction of change (\u003cstrong\u003eG\u003c/strong\u003e), or those behaving differently in Ms and Fs (\u003cstrong\u003eK-L\u003c/strong\u003e).\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-6278278/v1/dee6b8b53b0d3304cd233e52.png"},{"id":79150585,"identity":"57ca0d10-4d67-462a-b353-6f6724f0a764","added_by":"auto","created_at":"2025-03-25 04:24:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":366498,"visible":true,"origin":"","legend":"\u003cp\u003eSex-specific and common differentially expressed genes (DEGs) were identified following chronic ethanol use in the dlPFC of rhesus macaques. \u003cstrong\u003eA-C\u003c/strong\u003e) Volcano plots of the DEGs identified in M (\u003cstrong\u003eA\u003c/strong\u003e), F (\u003cstrong\u003eB\u003c/strong\u003e) and MF (\u003cstrong\u003eC\u003c/strong\u003e); respectively. Those upregulated are shown in blue (p\u0026lt;0.05) or dark blue (FDR\u0026lt;0.05), and those downregulated are shown in red (p\u0026lt;0.05) or dark red (FDR\u0026lt;0.05). \u003cstrong\u003eD\u003c/strong\u003e) Venn diagram of the unique and common DEGs across comparisons.\u003cstrong\u003e E-F\u003c/strong\u003e) Violin plots showing the normalized counts of DEGs that are common in Ms and Fs.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-6278278/v1/f997cf57a0034938a50d20c9.png"},{"id":79151376,"identity":"9ad15d02-a57f-4c5e-a49b-35db6a4343f0","added_by":"auto","created_at":"2025-03-25 04:40:16","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":674798,"visible":true,"origin":"","legend":"\u003cp\u003eViolin plots of the DNAm rates and normalized counts of genes that were differentially methylated and expressed in female (\u003cstrong\u003eA\u003c/strong\u003e) and male (\u003cstrong\u003eB\u003c/strong\u003e) macaques. C: controls and HVHD: heavy and very heavy drinkers.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-6278278/v1/b0e96b07ae840682c39c27c0.png"},{"id":79151379,"identity":"e8867cc6-59db-4479-aa00-18b20e832f1b","added_by":"auto","created_at":"2025-03-25 04:40:16","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2763071,"visible":true,"origin":"","legend":"\u003cp\u003eNetworks and enriched pathways of the differentially methylated and expressed genes in male (\u003cstrong\u003eA\u003c/strong\u003e) and female (\u003cstrong\u003eB\u003c/strong\u003e) macaques. Pathways related to gene expression regulation are shown in green, those involved in lipid metabolism in yellow, those enriched in intracellular signaling in blue, those in cell adhesion in pink and those enriched in neural relevant functions in red.\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-6278278/v1/8ec753632a5717ade7c9b679.png"},{"id":79150591,"identity":"a1c7aee8-218a-4513-964d-f78acab50f45","added_by":"auto","created_at":"2025-03-25 04:24:16","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1615741,"visible":true,"origin":"","legend":"\u003cp\u003eSynaptic transmission networks and enriched pathways of the differentially methylated and expressed genes in female (\u003cstrong\u003eA\u003c/strong\u003e) and male (\u003cstrong\u003eC\u003c/strong\u003e) macaques. Similar color denotes similar enriched pathways within the network. Genes involved in multiple pathways are shown by the different colors of the pie chart. \u003cstrong\u003eB-D\u003c/strong\u003e) Violin plots of the DNAm rates and normalized counts of genes that were differentially methylated and expressed in females (\u003cstrong\u003eB\u003c/strong\u003e) and males (\u003cstrong\u003eD\u003c/strong\u003e).\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-6278278/v1/41ef5990115a654d545f2696.png"},{"id":79150602,"identity":"072bcf30-388b-44e8-a611-1ca340588eee","added_by":"auto","created_at":"2025-03-25 04:24:16","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":628018,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eNRXN3\u003c/em\u003e is differentially methylated and expressed in rhesus macaques and mice following chronic ethanol intake. \u003cstrong\u003eA\u003c/strong\u003e) Gene structure of \u003cem\u003eNRXN3\u003c/em\u003e in rhesus macaques. Gray exons are those shared across transcripts, green are those exons unique to different transcripts, and those in orange are alternative first exons. \u003cstrong\u003eB) \u003c/strong\u003eDifferential DNAm rates of the differentially methylated region (DMR) mapping upstream of the transcription start site of \u003cem\u003eNRXN3a\u003c/em\u003e in males and females. Brown is male and blue is females. \u003cstrong\u003eC)\u003c/strong\u003e Differential DNAm rates of the differentially methylated region (DMR) mapping to \u003cem\u003eNRXN3b \u003c/em\u003ein males and females. \u003cstrong\u003eD) \u003c/strong\u003eNormalized counts of \u003cem\u003eNRXN3\u003c/em\u003e in males and females. \u003cstrong\u003eE-J\u003c/strong\u003e). Normalized expression of \u003cem\u003eNRXN3a\u003c/em\u003e and \u003cem\u003eNRXN3b\u003c/em\u003e in rhesus macaque and mouse female (\u003cstrong\u003eE-F\u003c/strong\u003e, \u003cstrong\u003eI-J\u003c/strong\u003e) and male (\u003cstrong\u003eG-H\u003c/strong\u003e, \u003cstrong\u003eM-N\u003c/strong\u003e) following chronic ethanol use measured by qPCR. \u003cstrong\u003eK-L\u003c/strong\u003e) Levels of Nrxn3a and Nrxn3b isoform expression in females.\u003c/p\u003e","description":"","filename":"Fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-6278278/v1/4406f6c2afc8251270c993d0.png"},{"id":79150597,"identity":"b6181bda-9fa7-41fa-afe5-99fe0b4c3636","added_by":"auto","created_at":"2025-03-25 04:24:16","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":211610,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eN-O\u003c/strong\u003e) Relative luminescence units (RLU) of the DMRs mapping to \u003cem\u003eNRXN3\u003c/em\u003e(\u003cstrong\u003eA\u003c/strong\u003e) showing promoter (\u003cstrong\u003eB\u003c/strong\u003e) and enhancer/silencer (\u003cstrong\u003eC\u003c/strong\u003e) function.\u003c/p\u003e","description":"","filename":"Fig7.png","url":"https://assets-eu.researchsquare.com/files/rs-6278278/v1/7b61f2d856ef2bf5a58800e0.png"},{"id":79150945,"identity":"58119c1b-ee96-4267-bda5-affae19ae0bc","added_by":"auto","created_at":"2025-03-25 04:32:17","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":1232611,"visible":true,"origin":"","legend":"\u003cp\u003eNrxn3b is specifically downregulated in parvalbumin (PV) interneurons of the prelimbic cortex (PLC) of male (Ms) and female (Fs) mice following chronic ethanol intake. \u003cstrong\u003eA) \u003c/strong\u003eImmunohistochemistry and confocal imaging of PV (blue) and Nrxn3b in the PLC following chronic ethanol use in Ms and Fs. \u003cstrong\u003eB\u003c/strong\u003e) Number of (PV) interneurons in the PLC in Ms and Fs between controls (Cs) and drinkers (Ds). \u003cstrong\u003eC\u003c/strong\u003e) Violin plots show a downregulation of Nrxn3b in PV interneurons with chronic ethanol intake. * \u0026lt;0.05, *** \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"Fig8.png","url":"https://assets-eu.researchsquare.com/files/rs-6278278/v1/71b6a50e2ef68f3e154c7617.png"},{"id":79152058,"identity":"6e597976-9a76-44dc-aeb0-081d4176549a","added_by":"auto","created_at":"2025-03-25 04:56:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":8866716,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6278278/v1/5b6eeaa2-d7f2-4bc4-930c-0f3ae525d203.pdf"},{"id":79150936,"identity":"d3227509-ffaa-4dda-976a-c02fcebdac03","added_by":"auto","created_at":"2025-03-25 04:32:16","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":153705,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplemental Figure 1\u003c/strong\u003e. Average ethanol drinking levels (g/kg/day) of the male and female macaques (\u003cstrong\u003eA\u003c/strong\u003e) and mice (\u003cstrong\u003eB\u003c/strong\u003e) following chronic ethanol intake.\u003c/p\u003e","description":"","filename":"SupFigure1DrinkingLevels.png","url":"https://assets-eu.researchsquare.com/files/rs-6278278/v1/d1dedc4dac6e84f6d09364d3.png"},{"id":79150588,"identity":"0b4110aa-74e3-42fe-bf4c-fae37613192d","added_by":"auto","created_at":"2025-03-25 04:24:16","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":12383,"visible":true,"origin":"","legend":"","description":"","filename":"Sup.Table1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6278278/v1/910c7ce83c7ab1f13deb426b.xlsx"},{"id":79150586,"identity":"184a8500-61e0-4e96-becd-abaf88221320","added_by":"auto","created_at":"2025-03-25 04:24:16","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":210137,"visible":true,"origin":"","legend":"","description":"","filename":"Sup.Table2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6278278/v1/0fe1efc2828cfe3db2136d2c.xlsx"},{"id":79150587,"identity":"c79d6674-13c5-408b-86c4-6de824419b30","added_by":"auto","created_at":"2025-03-25 04:24:16","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":39902,"visible":true,"origin":"","legend":"","description":"","filename":"Sup.Table3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6278278/v1/af4365e34f57aef701a85049.xlsx"},{"id":79150943,"identity":"f0e78d8f-b694-45d8-86bc-4bd3a8f23e46","added_by":"auto","created_at":"2025-03-25 04:32:16","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":443790,"visible":true,"origin":"","legend":"","description":"","filename":"Sup.Table4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6278278/v1/321ba4584e65bba52e725869.xlsx"},{"id":79150940,"identity":"7a75434e-f76b-41e0-9ad5-20faa3ae3d7a","added_by":"auto","created_at":"2025-03-25 04:32:16","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":27979,"visible":true,"origin":"","legend":"","description":"","filename":"Sup.Table5.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6278278/v1/43033a9fea77c5b4f7942463.xlsx"},{"id":79150598,"identity":"fb41fcc6-58f5-4f40-9c58-8470c64fac45","added_by":"auto","created_at":"2025-03-25 04:24:16","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":43035,"visible":true,"origin":"","legend":"","description":"","filename":"Sup.Table6.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6278278/v1/58a2583f3668f081d7afae09.xlsx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eNeurexin 3 is differentially methylated and downregulated following chronic ethanol use.\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChronic ethanol use causes alterations in multiple neurotransmitter systems leading to an imbalance in excitatory/inhibitory transmission(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Epigenomic and transcriptomic studies(\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) have proven critical in our understanding of the molecular mechanisms underlying these neuroadaptations. For instance, epigenomic analysis of the nucleus accumbens of rhesus macaques following chronic ethanol use(\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) identified novel genes involved in synaptic plasticity. We further showed that manipulation of these targets reduced ethanol intake (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e); results that highlight the value of this approach to identify potential new therapeutic targets for alcohol use disorder (AUD). In this study, we use a similar approach to characterize the alcohol-associated molecular mechanisms of the prefrontal cortex (PFC), a brain area that plays a central role in guiding executive function and decision making and has been consistently linked with heavy drinking, craving, relapse and difficulty moderating alcohol intake(\u003cspan additionalcitationids=\"CR7 CR8 CR9 CR10 CR11 CR12 CR13\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). In fact, interventional studies have linked direct stimulation of PFC areas with reductions in alcohol craving and drinking metrics(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR15 CR16\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), providing proof-of-concept for AUD treatments that modulate PFC function. We were particularly interested in identifying those molecules that are critical regulators of synaptic plasticity as their manipulation could potentially restore synaptic function and reduce ethanol intake.\u003c/p\u003e \u003cp\u003eNeurexins (nrxns) are a family of presynaptic cell adhesion molecules crucial for neuronal communication and plasticity(\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). As key components of the synaptic cleft, neurexins interact with a variety of post-synaptic proteins to mediate synaptic formation, neurotransmission and plasticity(\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Neurexins are encoded by three genes (\u003cem\u003eNRXN1\u003c/em\u003e, \u003cem\u003eNRXN2\u003c/em\u003e, and \u003cem\u003eNRXN3\u003c/em\u003e) and exhibit remarkable structural diversity through alternative splicing (AS) and the use of alternative promoters(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan additionalcitationids=\"CR24 CR25 CR26 CR27 CR28\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). In fact, neurexins contain six highly conserved splicing sites (SS) and they are commonly spliced into either a longer alpha (a) or the shorter beta (b) and gamma (g, \u003cem\u003eNRXN1\u003c/em\u003e only) forms (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan additionalcitationids=\"CR31 CR32 CR33 CR34\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). The different isoforms exert different functions; thus, neurexins enable synaptic plasticity by meeting the specific needs of different synapses and adapting neural circuits to changing conditions.\u003c/p\u003e \u003cp\u003eGenome wide association studies (GWAS) have linked single nucleotide polymorphisms (SNPs) mapping to \u003cem\u003eNRXNs\u003c/em\u003e to various neurodegenerative(\u003cspan additionalcitationids=\"CR37 CR38\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e) and neuropsychiatric disorders(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e), including substance use disorders(\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). Unlike the other neurexins, SNPs mapping to \u003cem\u003eNRXN3\u003c/em\u003e have been linked to opioid, nicotine, and alcohol dependence(\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e), making \u003cem\u003eNRXN3\u003c/em\u003e a genetic candidate for drug addiction(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan additionalcitationids=\"CR44 CR45 CR46 CR47 CR48 CR49 CR50 CR51\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e). Although the role of these SNPs in \u003cem\u003eNRXN3\u003c/em\u003e function remains unknown, studies using full knock outs (KOs) or conditional KOs have shown that \u003cem\u003eNRXN3α\u003c/em\u003e couples Ca\u0026sup2;⁺ channels to the neurotransmitter release machinery at excitatory synapses(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan additionalcitationids=\"CR54 CR55 CR56 CR57 CR58 CR59\" citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e). \u003cem\u003eNRXN3α\u003c/em\u003e is also involved in the regulation of postsynaptic AMPA receptors in the hippocampus(\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), presynaptic release probability of the neurotransmitter readily releasable pool(\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e), and GABA release through binding to dystroglycan at inhibitory synapses in the olfactory bulb(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). \u003cem\u003eNRXN3β\u003c/em\u003e regulates synaptic strength via the control of tonic endocannabinoid signaling in hippocampal excitatory synapses(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e), decreases neurotransmitter release probability in cortical cultures(\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e), impairs presynaptic Ca\u003csup\u003e2+\u003c/sup\u003e influx triggered by action potentials in excitatory synapses(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e), facilitates clustering of postsynaptic AMPA receptors in the hippocampus(\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e), and is required for GABA release in the olfactory bulb(\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). These findings underscore the complementary yet distinct roles of NRXN3α and NRXN3β, their distinct synaptic functions in different brain regions, and their significance in maintaining synaptic health. While it is known that these synaptic functions are altered with chronic alcohol use, the specific mechanisms related to the regulations of \u003cem\u003eNRXN3\u003c/em\u003e and the downstream effects on synaptic dynamics contributing to AUD remain unknown.\u003c/p\u003e \u003cp\u003eHere, we completed genome-wide DNA methylation (GW-DNAm) and transcriptomic (RNAseq) analyses of the dorsolateral prefrontal cortex (dlPFC) of rhesus macaques that remained alcohol-na\u0026iuml;ve or were exposed to chronic alcohol for 12 months, and identified differentially methylated regions (DMRs) mapping to \u003cem\u003eNRXN3\u003c/em\u003e. Parallel expression analysis of \u003cem\u003eNRXN3α\u003c/em\u003e and \u003cem\u003eNRXN3β\u003c/em\u003e transcripts showed downregulation of NRXN3β transcripts and isoforms in the macaque dlPFC and the mouse prelimbic cortex (PLC) following chronic ethanol use. This work demonstrates a conserved alcohol-associated mechanism across species. We further explored the alcohol-associated adaptations of Nrxn3α/β in parvalbumin (pvalb) interneurons(\u003cspan additionalcitationids=\"CR65\" citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e), which are crucial in modulating the activity of pyramidal neurons(\u003cspan additionalcitationids=\"CR68 CR69\" citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e) in the PLC, and may contribute to regulating the alcohol-associated imbalance between excitatory and inhibitory neurotransmission characteristic of AUD.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eMice\u003c/span\u003e: All experimental procedures received approval from the Institutional Animal Care and Use Committee (IACUC) at Wake Forest University School of Medicine (WFUSOM). Adult (8\u0026ndash;10 weeks old) female (F) and male (M) C57BL6 mice from Jackson Laboratory were individually housed on a 12:12 light/dark cycle. Mice (Fs: n\u0026thinsp;=\u0026thinsp;26, Ms: n\u0026thinsp;=\u0026thinsp;14) were exposed to an intermittent access two bottle choice (IA-2BC) ethanol paradigm. Mice had access to water only (controls (C), n\u0026thinsp;=\u0026thinsp;19) or a 10% ethanol solution and water (drinkers (D), n\u0026thinsp;=\u0026thinsp;21), alternating every other day for 22 hours three times a week. After ~\u0026thinsp;21 sessions, mice were euthanized by transcardial perfusion. The PLC from one hemisphere of 16 Cs and 18 Ds was used to isolate DNA/RNA. The PLC from 6 C and 6 D Fs was used for immunoblotting. The brains from 13 Cs and 15 Ds were fixed for immunohistology.\u003c/p\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eRhesus macaques\u003c/span\u003e: Six cohorts (4, 5, 6a, 6b, 7a and 7b) of young adult Ms and Fs (n\u0026thinsp;=\u0026thinsp;40, ~\u0026thinsp;4\u0026ndash;6 years old) rhesus macaques (C: 6 Fs and 9 Ms and heavy and very heavy drinkers (HVHD): 7 Fs and 8 Ms that consumed on average 2.9\u0026ndash;5.2 g/kg/day ethanol intake) from the Monkey Alcohol and Tissue Research Resource (MATRR database)(\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e), were included. All procedures were conducted in accordance with the Guide for the Care and Use of Laboratory Animals and the NIH PHS Policy on Humane Care and Use of Laboratory Animals for the care and use of laboratory animal resources and approved by the Oregon National Primate Research Center (ONPRC) Institutional Animal Care and Use Committee. Detailed drinking and physiological data are described in supplemental methods, available at MATRR.com and as previously described (\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e) (\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAfter necropsy, brain slabs were immediately flash frozen in liquid nitrogen and stored at -80 ̊C for future processing. Samples (~\u0026thinsp;30mg) from the dlPFC area 46 (dlPFC-A46) were excised and processed using the Qiagen AllPrep DNA/RNA/miRNA Universal Kit as described(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, 3)to isolate DNA and RNA.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eGenome-wide DNA methylation profiling\u003c/span\u003e: One microgram of genomic DNA from macaque samples was used for SureSelect XT Human Methyl-Seq library preparation (Agilent Technologies, Santa Clara, CA, USA) as described(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). DNA libraries were sequenced on an Illumina NovaSeq6000 at the University of Oregon Genomics \u0026amp; Cell Characterization Core Facility (GC3F).\u003c/p\u003e \u003cp\u003eThe differential DNAm analysis was carried out by applying a generalized linear mixed effects model (GLMM) implemented in R package PQLseq (version 1.2.1)(\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e) separately for each CpG site. We modeled the average consumption of ethanol at 12 months as a predictor of DNAm rate and included age as covariate in the binomial model. Relatedness of the animals was accounted for as a random effect in the model. Each nominal p-value was corrected for multiple comparisons by the False Discovery Rate (FDR). In parallel, the nominal p-value was used as input for Comb-p(\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e) analysis to identify differentially methylated regions (DMRs) as previously described(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eRNAseq library and sequencing\u003c/span\u003e: For stranded RNA-seq, cDNA libraries were prepared with the TruSeq stranded mRNA library prep Kit (Illumina, San Diego, CA, USA). The resulting libraries were sequenced on a HiSeq 4000 (Genomics \u0026amp; Cell Characterization Core Facility, University of Oregon) using a paired-end run (2 \u0026times; 150 bases). A minimum of 100 M reads was generated from each library.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eDifferential Expression Analysis\u003c/span\u003e: Quality of the sequences were verified through FastQC (v. 0.1.1.2)(\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e). Sequences were aligned to the macaque Mmul_10 (INSDCA Assembly GCA_003339765.3) genome through the STAR alignment package (v. 2.7.3a)(\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e) allowing for a maximum of 3 mismatches and only unique alignments. Read counts at the gene level were also obtained with the STAR package and were based on the Ensembl.Mmul_10.100 genome annotation. Upper quartile normalization was performed using the edgeR (v. 3.28.0)(\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e) bioconductor package (Bioconductor, Cambridge, UK). Genes with at least 0.2 CPM across samples were retained for further analysis. These thresholds translate into roughly 10 reads per minimum library size (10/minimum library size in millions)(\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e). Differential expression (DE) between the C and HVHD groups was determined using edgeR\u0026rsquo;s Fisher\u0026rsquo;s exact test function, with the option of \u0026ldquo;tagwise\u0026rdquo; dispersion. The threshold for significance was unadjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eNetwork analysis\u003c/span\u003e: Significant DMRs that had gene annotations were analyzed in STRING, MCODE and ClueGO to find biological pathways enriched with future ethanol drinking(\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e). STRING was applied to find only \u0026ldquo;High confidence\u0026rdquo; protein-protein interactions with options for \u0026ldquo;textmining\u0026rdquo; and \u0026ldquo;neighborhood\u0026rdquo; disabled(\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e). MCODE was applied to the remaining interactions to obtain a set of highly interconnected gene clusters(\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e) and the biological functions of each clusters with MCODE scores greater than 4.0 were identified through the KEGG pathways(\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eSynthesis of complementary DNA (cDNA) by reverse transcription for quantitative PCR (qPCR)\u003c/span\u003e: cDNA was synthesized from total RNA (250ng) isolated from the dlPFC-A46 or PLC using the SuperScript IV Reverse Transcriptase (Invitrogen, Vilnius, Lithuania) following the manufacturer\u0026rsquo;s instructions. qPCR was performed using GoTaq\u0026reg; qPCR Master Mix (1x, A6001, Promega, Madison, WI, USA), forward and reverse primer (400nM each, see Table\u0026nbsp;1), and template DNA (7.5ng) or nuclease-free water. The following conditions were used: 95\u0026deg;C for 2 minutes (1 cycle); 95\u0026deg;C for 15 seconds; 59\u0026deg;C for 30 seconds (40 cycles). Post-amplification melting curves were analyzed to assess primer specificity. Data were normalized to the geometric mean of the expression levels of the housekeeping genes \u003cem\u003eRPL32\u003c/em\u003e and \u003cem\u003eRPL13A\u003c/em\u003e. Relative quantification was performed using the ΔΔCt method.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eImmunohistology\u003c/span\u003e: The fixed (4% PFA) mouse brains (10 \u0026micro;m cryosections) were incubated with primary antibodies (1: 400 Nrxn3β (Invitrogen, Rockford, IL, USA), 1:30 Nrxn3α (R\u0026amp;D Systems, Minneapolis MN, USA), 1:800 pvalb (Invitrogen, Rockford, IL, USA), secondary Alexa fluorescence-conjugated secondary antibodies, and nuclear stain) as described in supplemental material. Fluorescence images were captured using a Leica DMi8 fluorescence microscope. For deeper resolution, confocal images were also acquired from the same slices and analyzed using a Nikon A1plus confocal microscope (Eclipse Ni-E, Nikon, Tokyo, Japan). Representative images were created using ImageJ software and Python script executed in Google Colab.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eWestern blotting\u003c/span\u003e: 25\u0026micro;g of protein from mouse PLC were resolved in 4\u0026ndash;12% Bis-Tris gels (Invitrogen, Carlsbad, CA, USA), and subsequently transferred to PVDF membranes overnight. Results were normalized using total protein using the iBright1500 (Invitrogen). After blocking, membranes were incubated with primary antibodies against Nrxn3α and Nrxn3β, and horseradish peroxidase-conjugated secondary antibodies. Protein bands were visualized using enhanced chemiluminescence (ECL Select Western Blotting Detection Reagent, Cytiva, Buckinghamshire, UK) using the iBright1500 (Invitrogen).\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eLuciferase reporter assay\u003c/span\u003e: To determine the promoter and enhancer activity of the macaque DMRs we cloned the human homologous regions (DMR-M: GRCh38, chr14:79279949\u0026ndash;79280380 and DMR-MF: GRCh38, chr14:77981589\u0026ndash;77981676) in the luciferase reporter vector pGL3 (Promega, Madison, WI, USA) and transfected HEK293 cells (ATCC, Manassas, VA) using 100ng (10:1 ratio of 90ng of constructed firefly plasmid including the DMR to 10ng of normalization SV40 plasmid). Control vectors were used as recommended by the manufacturer. 48 hours later, cells were assayed for relative luminescence units (RLU) using the Dual-Glo\u0026reg; Luciferase Assay System (Promega, Madison, WI, USA) and the SpectraMax iD3 Microplate Reader (Molecular Devices). Data was normalized against the Renilla expression. All experiments were performed in triplicate.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eStatistical Analyses\u003c/span\u003e: To assess the effects on ethanol and water intake, ethanol preference ratio (EPR), and total fluid intake (TFI) in mice, repeated measures ANOVA with Bonferroni post hoc tests were employed. To check for differences in variance and normality, we applied a Levene\u0026rsquo;s test and Shapiro-Wilk test; respectively. Gene and protein expression differences across groups were compared using a two-sample t-test when variance was found to be consistent. When assumptions of homogeneity of data and variance were violated, non-parametric methods such as the Welch\u0026rsquo;s t-test or Mann-Whitney U test were employed. If sphericity was not met, as determined by Mauchly's test, adjustments were made using the Greenhouse-Geisser correction.\u003c/p\u003e \u003cp\u003eAll statistical results are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM, and significance was set at a p-value of less than 0.05 for differences between groups. For the luciferase assays, we used ANOVA followed by Bonferroni test, with a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eChronic heavy alcohol use is associated with sex-specific differential DNAm and gene expression in the macaque dlPFC-A46.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAcross all sites, the most noticeable differences in DNAm levels between groups (C and HVHD, in M and F) was in the intermediate ranges of DNAm (25\u0026ndash;75%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn the MF combined analysis, we identified 180 DMRs (p\u003csub\u003eSidak\u003c/sub\u003e \u0026lt; 0.05), with a slight bias towards hypomethylation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB-C). These differentially methylated genes (DMGs) were enriched in Ca\u003csup\u003e2+\u003c/sup\u003e binding, cell adhesion, synapse assembly (\u003cem\u003eATP2B2\u003c/em\u003e, \u003cem\u003eCDH22\u003c/em\u003e, \u003cem\u003eLTBP4\u003c/em\u003e, \u003cem\u003eRCN1\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG), \u003cem\u003eRYR1\u003c/em\u003e, \u003cem\u003ePCDHB2\u003c/em\u003e, 3, 6, 7). The top-most significant DMRs mapped to \u003cem\u003eIKZF1\u003c/em\u003e, a novel regulator of microglia homeostasis(\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e); \u003cem\u003eLINGO3\u003c/em\u003e, a member of the leucine-rich repeat and immunoglobin-domain containing protein family; and several protocadherins (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF and Table S2). When each sex was analyzed separately, there were 906 DMRs (p\u003csub\u003eSidak\u003c/sub\u003e \u0026lt; 0.05) in Ms and 420 DMRs (p\u003csub\u003eSidak\u003c/sub\u003e \u0026lt; 0.05) in Fs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). In Ms, the levels of differential DNAm were relatively small; in fact, among the 960 DMRs, only 126 had an average differential DNAm over 5% (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). In Fs, larger DNAm differences between Cs and HVHDs were identified, with most of the DMRs displaying differential DNAm rates over 5% (n\u0026thinsp;=\u0026thinsp;323; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). The topmost significant DMGs in Ms included the transcription factor \u003cem\u003eHLX\u003c/em\u003e, and the X-ray repair cross complementing protein, \u003cem\u003eXCCR1\u003c/em\u003e, which is involved in DNA repair in the brain (\u003cspan additionalcitationids=\"CR86\" citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD, Table S2). In Fs, the protein tyrosine phosphatase receptor type Q (\u003cem\u003ePTPRQ\u003c/em\u003e), \u003cem\u003eIKFZ1\u003c/em\u003e and the secretory carrier membrane protein 4 (\u003cem\u003eSCAMP4\u003c/em\u003e) were the most DMGs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE, Table S2). When the interaction between sex and ethanol intake was included in the analysis (MF-Intrxn), we identified 253 DMRs showing different DNAm signatures in Ms and Fs (Table S2, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eJ-L). For instance, the DMR mapping to the N-acetylglucosamine kinase gene (\u003cem\u003eNAGK\u003c/em\u003e) was hypermethylated in HVHDs in both Ms and Fs; however, the change was more dramatic for Ms (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eJ). The DMR mapping to an intergenic location in chromosome 15, showed very similar DNAm in Ms, but a significant reduction in DNAm in HVHD Fs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eK). And the DMR mapping to \u003cem\u003eSFXN5\u003c/em\u003e showed no change in Fs but a significant hypomethylation in HVHD Ms (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eL). We then used the total of 1008 DMRs (p\u003csub\u003enominal\u003c/sub\u003e \u0026lt; 0.05) in the \u0026ldquo;MF-Intrxn\u0026rdquo; comparison and identified 20 DMRs that were shared with the M comparison and 57 DMRs common with the F comparison, indicating that those are signals specific of Ms or Fs; respectively (Table S3; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eH-I). As an example, a DMR mapping to the tyrosine phosphatase receptor type Q (\u003cem\u003ePTPRQ\u003c/em\u003e) is hypomethylated exclusively in HVHD Fs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eI); while an intergenic DMR mapping to chromosome 20 is exclusive of Ms (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eH). Taken all these results together, Ms and Fs show very different patterns of DNAm, with very little overlap and small number of DMRs identified in MF combined as compared to each sex separately, and with the interaction.\u003c/p\u003e \u003cp\u003eRNAseq analysis of the dlPFC-A46 identified 1,170 and 3,366 differentially expressed genes (DEGs) in Ms and Fs; respectively (Sup. Table\u0026nbsp;4; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-B). After correction for multiple comparisons, these numbers were reduced to 1,092 DEGs in Fs and only 9 DEGs remained in Ms. When Ms and Fs were analyzed together, we identified 979 DEGs with 48 remaining after FDR correction (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC-D). Among the most significantly DEGs in the combined MF analysis, the genes encoding the water homeostasis master regulator aquaporin 4 (\u003cem\u003eAQP4\u003c/em\u003e)(\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e) and the tripartite motif protein \u003cem\u003eTRIM22\u003c/em\u003e proposed to be a potent activator of NF-kB(\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e), were upregulated compared to their age-matched Cs (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE-F). The 9 DEGs in Ms were also included in the MF comparison, indicating they were not unique to Ms. In Fs, we identified numerous DEGs mapping to neurotransmitter receptor subunits of GABAergic (\u003cem\u003eGABBR2\u003c/em\u003e, \u003cem\u003eGABRA1\u003c/em\u003e, \u003cem\u003eGABRA3\u003c/em\u003e, \u003cem\u003eGABRA4\u003c/em\u003e, \u003cem\u003eGABRB2\u003c/em\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), glutamatergic (\u003cem\u003eGRIA1\u003c/em\u003e, \u003cem\u003eGRIA2\u003c/em\u003e, \u003cem\u003eGRID1\u003c/em\u003e, \u003cem\u003eGRIN1\u003c/em\u003e, \u003cem\u003eGRIN2A\u003c/em\u003e, \u003cem\u003eGRIN3A\u003c/em\u003e, \u003cem\u003eGRM2\u003c/em\u003e, \u003cem\u003eGRM5\u003c/em\u003e, \u003cem\u003eGRM7\u003c/em\u003e), dopamine (\u003cem\u003eDRD1\u003c/em\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), cannabinoid (\u003cem\u003eCNR1\u003c/em\u003e) and cholinergic receptors (\u003cem\u003eCHRM1\u003c/em\u003e, \u003cem\u003eCHRM3\u003c/em\u003e, \u003cem\u003eCHRM4\u003c/em\u003e, \u003cem\u003eCHRNA2\u003c/em\u003e, \u003cem\u003eCHRNB2\u003c/em\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). All these genes were downregulated (Sup. Table\u0026nbsp;4) in HVHD Fs compared to Cs. These results suggest sex-specific differences in gene expression as we observed in our DNAm analysis. We note that the higher levels of alcohol consumption in Fs (4.5g/kg/day vs 3.3 g/kg/day, p\u003csub\u003et\u0026minus;test\u003c/sub\u003e = 5.74x10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e; Supp. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA) may have led to more pronounced and significant effects in Fs, but many of these changes may also reflect true biological differences between M and F that, in turn, relate to the original differences in drinking.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eIntegration of omics highlights the potential role of DNAm as an epigenetic mechanism regulating gene expression associated with chronic ethanol use in rhesus macaques.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eUsing the macaque omics data, we next combined the differentially methylated (p\u003csub\u003e(Sidak)\u003c/sub\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and expressed (M: p\u003csub\u003eunadj\u003c/sub\u003e \u0026lt; 0.05 and F: FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05) datasets and identified 36 and 17 (56 at p\u003csub\u003eunadj\u003c/sub\u003e \u0026lt; 0.05) genes that were DMGs and DEGs in Ms and Fs, respectively (Sup. Table\u0026nbsp;5). In Fs, these genes included the pre-synaptic neuronal voltage-gated Ca\u003csup\u003e2+\u003c/sup\u003e 2.2/N-type (\u003cem\u003eCACNA1B\u003c/em\u003e), which is crucial for SNARE-mediated neurotransmission, and was hypomethylated and downregulated in HVHDs; the gene encoding claudin-10 (\u003cem\u003eCLDN10\u003c/em\u003e), which is important for the formation of tight junctions in the endothelial cells in the brain blood barrier (BBB), that was hypomethylated and upregulated in HVHDs; the \u003cem\u003eCLMP\u003c/em\u003e gene encoding a cell junction protein involved in regulation of AMPA and Kainate receptors function, that was hypermethylated and downregulated in HVHDs; and the gene encoding an actin cytoskeleton interacting protein, \u003cem\u003ePDLIM2\u003c/em\u003e, that was hypermethylated and upregulated in HVHDs (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003eIn Ms, the DMGs and DEGs included genes encoding the aldo-keto reductase family 1 B10 protein (\u003cem\u003eAKR1B10\u003c/em\u003e), for the GABA A receptor (\u003cem\u003eGABRD\u003c/em\u003e) and for the growth arrest-specific 2-like 1 protein (\u003cem\u003eGAS2L1\u003c/em\u003e), which were hypermethylated and downregulated in HVHDs; and for catenin alpha-1 (\u003cem\u003eCTNNA1\u003c/em\u003e), involved in adherens junction and signal transduction, which was hypermethylated and upregulated in HVHDs (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). All of the DMRs mapping to these genes were located within the gene body, and they mapped to an internal exon (\u003cem\u003eCAMK2B\u003c/em\u003e), intron (\u003cem\u003eAKR1B10\u003c/em\u003e and \u003cem\u003eCTNNA1\u003c/em\u003e) or to alternative 1st exons (\u003cem\u003eGAS2L1, CLDN10\u003c/em\u003e, \u003cem\u003eCLMP\u003c/em\u003e and \u003cem\u003ePDLIM2\u003c/em\u003e) or to promoters (\u003cem\u003eGABRD\u003c/em\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eDifferentially methylated and expressed genes in the macaque dlPFC-A46 are enriched in synaptic transmission.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eUsing the combined set of differentially methylated (p\u003csub\u003eSidak\u003c/sub\u003e \u0026lt; 0.05; annotated to genes) and expressed genes (F: FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05; M: p\u003csub\u003eunadj\u003c/sub\u003e \u0026lt; 0.05) per each sex (F: 1,427; M: 1,613), we performed network and pathway analyses to identify the biological functions distinguishing HVHD from Cs after 12m of ethanol intake. In Fs and Ms, there was a common enrichment in gene expression regulation, lipid metabolism, cytoskeleton organization, vesicle transport, synapse organization and synaptic transmission (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-B). There were 187 common genes that were DMGs and/or DEGs in both sexes (Sup. Table\u0026nbsp;6). Among these, 63 showed the same direction of change in DNAm and/or expression in both sexes. These included the gene encoding the Ca\u003csup\u003e2+\u003c/sup\u003e-responsive transcriptional regulator \u003cem\u003eCAMTA1\u003c/em\u003e, that was hypermethylated in HVHDs; the leucine-rich repeat and immunoglobulin-like domain-containing nogo receptor- interacting protein 3 (\u003cem\u003eLINGO3\u003c/em\u003e), involved in myelination, that was hypomethylated in HVHDs; as well as the gene encoding the kinesin family member 5B (\u003cem\u003eKIF5B\u003c/em\u003e) with a role in synaptic plasticity, that was upregulated in both sexes. There were 89 genes that showed the opposite change in direction in DNAm or gene expression in Ms and Fs (Sup. Table\u0026nbsp;6). For example, the gene encoding the transcription factor \u003cem\u003eLHX3\u003c/em\u003e was hypermethylated in Fs but hypomethylated in Ms. Similarly, the RNA binding protein encoded by \u003cem\u003eCELF4\u003c/em\u003e, which regulates translation of mRNAs associated with synaptic function, was hypomethylated in Fs but hypermethylated in Ms. In addition, Fs showed an upregulation in genes involved in cellular respiration (i.e. \u003cem\u003eCOX8A\u003c/em\u003e), and transcriptional and translational regulation as compared to Ms (i.e. \u003cem\u003eRPL8\u003c/em\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFs also showed a unique enrichment in myelination regulation and ephrin signaling (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB); while in Ms there was an enrichment in immune response, cilium movement, intracellular signaling cascades and blood brain barrier transport (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). These results highlight the sex-specific differences between Ms and Fs in adapting to the chronic and heavy amounts of alcohol consumed over time.\u003c/p\u003e \u003cp\u003eBeyond the sex-specific differences, we noted a shared enrichment in synaptic transmission pathways in Ms and Fs. Interestingly, the genes within this same pathway are mostly different between both sexes. In Fs, genes in this pathway included several cadherins (i.e. \u003cem\u003eCDH7\u003c/em\u003e), Na/Ca\u003csup\u003e2+\u003c/sup\u003e exchange channels (i.e. \u003cem\u003eSLC24A2\u003c/em\u003e), ATPases (i.e. \u003cem\u003eATP2A2\u003c/em\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB), regulators of microtubule polymerization (i.e. \u003cem\u003eARHGEF7\u003c/em\u003e), numerous genes involved in protein-protein interactions at synapses (i.e. \u003cem\u003eNRXN3\u003c/em\u003e), regulators of phosphorylation of synaptic proteins (i.e. \u003cem\u003eGIT1\u003c/em\u003e), regulators of cytosolic Ca\u003csup\u003e2+\u003c/sup\u003e levels (i.e. \u003cem\u003eSRI\u003c/em\u003e), members of dendrites (i.e. \u003cem\u003ePALM\u003c/em\u003e), presynaptic active zone (i.e. \u003cem\u003ePCLO\u003c/em\u003e), excitatory synapses (i.e. \u003cem\u003eCAMK2B\u003c/em\u003e) and regulators of vesicle-mediated neurotransmitter transport and release (i.e. \u003cem\u003eVAMP3, SYT1\u003c/em\u003e), among others. It is important to note that \u003cem\u003eHPCA\u003c/em\u003e (neuron-specific calcium-binding protein), several ATPases, \u003cem\u003eDVL1\u003c/em\u003e (scaffolding protein), \u003cem\u003eERC2\u003c/em\u003e and \u003cem\u003eBSN\u003c/em\u003e (regulators of neurotransmitter release), \u003cem\u003ePCLO\u003c/em\u003e, \u003cem\u003eCAMK2B\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB), \u003cem\u003eSYT1\u003c/em\u003e and \u003cem\u003eNRXN3\u003c/em\u003e connect most of these signaling pathways, potentially serving as hubs.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn Ms, genes within this pathway such are \u003cem\u003eGRID1\u003c/em\u003e, \u003cem\u003eNRXN3\u003c/em\u003e, \u003cem\u003eGABRD\u003c/em\u003e, \u003cem\u003eSLC32A1\u003c/em\u003e (downregulated in HVHD; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD) or \u003cem\u003eDLGAP1\u003c/em\u003e are directly involved in regulating synaptic protein interactions, GABAergic synapses, or social behavior (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). Through the translation initiation factor \u003cem\u003eEIF4EBP2\u003c/em\u003e and the RNA binding protein encoded by \u003cem\u003eFMR1\u003c/em\u003e (upregulated in HVHD), these synaptic relevant pathways are linking to the regulation of transcription and translation, and to numerous neural relevant pathways, such as action potential or voltage-gated channels (i.e. \u003cem\u003eCACNA1H\u003c/em\u003e and \u003cem\u003ePDE4B\u003c/em\u003e were upregulated in HVHD). It is important to note that both \u003cem\u003eEIF4EBP2\u003c/em\u003e and \u003cem\u003eFMR1\u003c/em\u003e are enriched in the brain, and they act as regulators of synaptic activity and plasticity. These results indicate that the specific molecules underlying the alcohol-associated adaptations in synaptic transmission might be, mostly, sex-specific. However, we note that \u003cem\u003eNRXN3\u003c/em\u003e was enriched in both, Ms and Fs, indicating a potential common target that could modulate synaptic signaling in both sexes albeit through different mechanisms.\u003c/p\u003e \u003cp\u003e \u003cb\u003eNRXN3\u003c/b\u003e \u003cb\u003eis differentially methylated and expressed in HVHD macaques\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eIn Ms and Fs, \u003cem\u003eNRXNs\u003c/em\u003e were identified as being DMGs and DEGs (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Specifically, there was a DMR (DMR-M) mapping to an alternative exon 1 of NRXN3\u003cem\u003eb\u003c/em\u003e (ENSMMUT00000096019; transcript 207) that was significantly hypomethylated following chronic alcohol use (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA, C) in HVHD Ms. We note that we did not observe a difference in \u003cem\u003eNRXN3b\u003c/em\u003e between nonheavy drinking Ms and Cs, indicating that this effect is specific to heavy amounts of ethanol intake. In Fs, this same DMR showed higher levels of DNAm in HVHDs, but this difference was not significant (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). We note that the differential DNAm levels for this DMR were small, and this could be due to the cell-type specific DNAm signals in a heterogeneous tissue such as the dlPFC-A46. Also linked to \u003cem\u003eNRXN3\u003c/em\u003e, there was a hypermethylated DMR (DMR-MF) in HVHD Ms and Fs that was located upstream (~\u0026thinsp;200kb) of the TSS of \u003cem\u003eNRXN3a\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA-B). This DMR was also identified as nominally significant in Fs only (pZ\u0026thinsp;=\u0026thinsp;4.31x10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e; pSidak\u0026thinsp;=\u0026thinsp;7.64x10\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eRNAseq analysis found no differential expression of total \u003cem\u003eNRXN3\u003c/em\u003e between Cs and HVHDs in Ms; however, total \u003cem\u003eNRXN3\u003c/em\u003e was downregulated in HVHD Fs compared to Cs (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD). It should be noted that RNAseq did not enable the analysis of distinct transcripts; thus, we conducted quantitative real-time PCR (qPCR) on the same samples and identified a significant downregulation of NRXN3\u003cem\u003eb\u003c/em\u003e and no changes in \u003cem\u003eNRXN3a\u003c/em\u003e in HVHDs Ms and Fs (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE-H). Although the expression of \u003cem\u003eNRXN3a\u003c/em\u003e in Fs showed a trend towards downregulation in HVHDs, we believe this is driven by higher expression in only two of the control Fs (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE). These results highlight the importance of investigating gene expression at the transcript level.\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe macaque DMRs mapping to\u003c/b\u003e \u003cb\u003eNRXN3\u003c/b\u003e \u003cb\u003ehave regulatory function.\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe DMR-M only reached significant differential DNAm levels in Ms, and we argue that the lack of significance in Fs might be due to the smaller sample size and the larger variance in DNAm in Fs. While the DMR-MF did not survive correction for multiple comparisons, we tested its potential regulatory function. Our studies indicate that the DMR mapping to the 1st exon of \u003cem\u003eNRXN3b\u003c/em\u003e (DMR-M; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA) functions as a weak promoter and strong enhancer (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB-C). On the other hand, the DMR mapping upstream of \u003cem\u003eNRXN3a\u003c/em\u003e (DMR-MF; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA) might function as a silencer, given the significant reduction in RLU when tested for promoter or enhancer function (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB-C).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eNrxn3b\u003c/b\u003e \u003cb\u003eis downregulated in female mice following chronic ethanol use, while Nrxn3b is downregulated in parvalbumin neurons in the PLC of both male and female mice.\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAs we observed in macaques, F mice consumed higher levels of ethanol than Ms (16.28\u0026plusmn;22.17 g/kg vs 11.21\u0026plusmn;8.18 g/kg; p\u003csub\u003e(t,two\u0026minus;tailed)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;5.16x10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e; Sup. Figure\u0026nbsp;1B). We also note that 9 of the 14 Fs consumed more than 15g/kg/day, while none of the Ms reached this higher level of intake.\u003c/p\u003e \u003cp\u003eFollowing IA-2BC, the levels of \u003cem\u003eNrxn3a\u003c/em\u003e mRNA expression in the PLC of Fs was not different between Ds and Cs (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eI), while \u003cem\u003eNrxn3b\u003c/em\u003e was downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eJ). Furthermore, immunoblotting results showed a significant reduction in the levels of Nrxn3b protein isoform in the same tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eL) and no changes in the expression of Nrxn3\u003cem\u003ea\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eK). In Ms, transcript levels were not significantly different between groups for either Nrxn3\u003cem\u003eα\u003c/em\u003e or \u003cem\u003eNrxn3β\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eM, N).\u003c/p\u003e \u003cp\u003eFollowing up on these results, we investigated if the sex-specific changes in the levels of \u003cem\u003eNrxn3a\u003c/em\u003e and \u003cem\u003eNrxn3b\u003c/em\u003e in the PLC observed with alcohol intake were altered in a specific cell type. We selected pvalb interneurons in the PLC, which are known to express high levels of \u003cem\u003eNrxn3\u003c/em\u003e (based on single nuclei RNAseq data, human protein atlas;(\u003cspan additionalcitationids=\"CR65\" citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e)), and are important modulators of excitability in excitatory neurons.\u003c/p\u003e \u003cp\u003eTo cover the whole PLC area, we used brain slices within Bregma coordinates ranging from 1.6 to 2.9. The percent area of the overlap between Nrxn3β and pvalb interneurons as well as the individual percent areas of Nrxn3β and pvalb interneurons were initially associated with the bregma coordinates to examine whether there was any significant association within PLC anterior-posterior location and Nrxn3β and/or pvalb interneurons that needed to be accounted for prior to taking the mean percent overlap in each mouse. Beta regression was computed with percent area as the outcome and bregma coordinate as the predictor adjusting for mouse as a fixed effect. No significant effect was identified for the percent area of pvalb interneurons (p\u0026thinsp;=\u0026thinsp;3.90x10\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), Nrxn3β (p\u0026thinsp;=\u0026thinsp;2.93x10\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) or the overlap between both (p\u0026thinsp;=\u0026thinsp;8.70x10\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eThe means of the overlap between Nrxn3β and pvalb interneuons were then computed for each mouse and beta regression was computed on the mean overlap as the outcome and group (D vs C) as the predictor, accounting for sex as a covariate. We identified a significant effect of drinking and sex on the percent overlap of Nrxn3β with pvalb interneurons (drinking status: effect size = -1.62, p\u0026thinsp;=\u0026thinsp;1.82x10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e; sex: effect size = -1.22, p\u0026thinsp;=\u0026thinsp;2.41x10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA, C). The number of pvalb interneurons did not differ significantly in Fs, but there was a significant larger number of pvalb interneurons in Ms compared to Fs (sex: effect size\u0026thinsp;=\u0026thinsp;0.34, p\u0026thinsp;=\u0026thinsp;4.57x10\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA, B). There was a significant interaction between sex and drinking status, with Ms having much lower levels of Nrxn3b in pvalb interneurons as compared to Fs, especially the Cs.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn Fs, the reduction of Nrxn3b in pvalb interneurons agrees with the mRNA and protein levels observed from the PLC (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eI-L), and suggests that, the effects of alcohol on this particular cell type might be driving the downregulations we observed in the bulk analyses. Contrarily to Fs, we observed a reduction in the number of pvalb interneurons in Ms following drinking (p\u0026thinsp;=\u0026thinsp;4.57x10\u003csup\u003e\u0026minus;\u0026thinsp;02\u003c/sup\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eB). Interestingly, the levels of Nrxn3b in pvalb interneurons were also significantly reduced in male Ds compared to Cs (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eC). These results indicate that while Nrxn3b responds similarly in pvalb interneurons following chronic ethanol intake, there might be sex-specific differences in the number of pvalb interneurons as well as in the distribution of \u003cem\u003eNrxn3\u003c/em\u003e transcripts across cell types in the PLC.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we characterized the DNAm and gene expression profiles in the dlPFC-A46 of rhesus macaques following chronic heavy alcohol use. The integration of these two datasets enabled identification of the molecular mechanisms underlying synaptic adaptations linked to chronic heavy ethanol use in this cortical region in both Ms and Fs. While most of the signaling pathways were shared in both sexes, there was sex dimorphism in the specific genes associated with synaptic neuroadaptations following chronic ethanol use. We acknowledge that there were sex-specific differences in drinking levels that might lead to more pronounced and significant effects in females, but that does not minimize the events where we do identify significant interactions between sex and drinking. Whether due to a sex-effect or a drinking level effect (linked to sex), our results indicate that therapeutic approaches need take into consideration sex (and potentially drinking levels within the heavy and very heavy drinking classification) in the development of effective treatments for Ms and Fs.\u003c/p\u003e \u003cp\u003eIn Fs, we identified many DEGs; however, in Ms only 9 DEGs survived FDR correction. This discrepancy could be due to the small differences in DNAm found in Ms (most DMRs showed\u0026thinsp;\u0026lt;\u0026thinsp;5% differential DNAm) as compared to Fs, which could be confounded by the fewer number of F samples included in these omics analyses. Additionally, and because our analyses were conducted in bulk samples from the dlPFC-A46, cell type specific DNAm signatures might contribute to these small DNAm differences that might be washed out by the heterogeneous nature of the dlPFC-A46 and not be captured as changes in gene expression using bulk analyses. Beyond the differences in DEGs between Ms and Fs, our results emphasize the value of integrating multiple omics datasets to identify the molecular mechanism underlying alcohol-associated adaptations. We identified DMGs and DEGs involved in synaptic plasticity, vesicle transport, cell adhesion and neurotransmission in Ms and Fs. Notably, the differential DNAm patterns, gene expression and associated genes within these signaling pathways underlying such chronic alcohol use adaptations suggest sex-specific mechanisms. For instance, and within the synaptic transmission network, most of the genes were unique to Ms or Fs, except for \u003cem\u003eNRXN3\u003c/em\u003e, a critical synaptic hub protein that was differentially methylated and expressed in both sexes.\u003c/p\u003e \u003cp\u003eThe neurexin family of proteins are cell adhesion molecules that are integral to synaptic formation and plasticity(\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e), and are implicated in a range of neuropsychiatric and neurodegenerative conditions(\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e, \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e), including substance use disorders(\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). Neurexins are master regulators of synaptic organization known to regulate excitatory and inhibitory synapses(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e) in a cell type and brain region specific manner. Extensive studies on the role of specific SS of \u003cem\u003eNrxn3α\u003c/em\u003e and \u003cem\u003eNrxn3b\u003c/em\u003e in the hippocampus and, to a lesser degree, in the PFC have been conducted(\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e), proving the functional differences of the various transcripts encoded by \u003cem\u003eNrxn3\u003c/em\u003e. However, nothing is known about the regulatory mechanisms driving AS and promoter use of this gene. This is particularly important since synaptic plasticity is at the core of neuroadaptations to changing environmental conditions, such as chronic ethanol use. Our study suggests that chronic heavy alcohol might lead to changes in DNAm on \u003cem\u003eNRXN3\u003c/em\u003e, contributing to the regulation of alternative promoter use of \u003cem\u003eNRXN3\u003c/em\u003e, resulting in a reduction in NRXN3\u003cem\u003eb\u003c/em\u003e. Specifically, two DMRs mapping to \u003cem\u003eNRXN3\u003c/em\u003e and with regulatory function, DMR-M as a weak promoter and strong enhancer and DMR-MF as a silencer, might regulate the expression of the shorter \u003cem\u003eNRXN3β\u003c/em\u003e transcript, although this might take place in a sex-specific manner. Given the reported potential differences in DNAm patterns in Ms and Fs, we do not discard the possibility that different regulatory mechanisms might lead to the observed shared \u003cem\u003eNRXN3b\u003c/em\u003e downregulation in Ms and Fs. Further studies are needed to determine the target(s) of these regulatory regions and their role in modulating the expression of the different \u003cem\u003eNRXN3\u003c/em\u003e transcripts in Ms and Fs.\u003c/p\u003e \u003cp\u003eIn agreement with sex-specific regulatory differences, our transcriptomic RNAseq analysis showed no differences in the overall levels of \u003cem\u003eNRXN3\u003c/em\u003e in Ms but a significant downregulation in Fs. It is also possible that these differences are due to cell type-specific differences in the \u003cem\u003eNRXN3\u003c/em\u003e transcripts\u0026rsquo; landscape in Ms and Fs. Evidence in the literature supports sex dimorphism in Nrxn3\u0026rsquo;s function(\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e). A prior study observed sex-dependent changes in \u003cem\u003eNrxn3\u003c/em\u003e expression and AS in mouse hippocampus following chronic stress, suggesting that Nrxn3 may engage in sex-specific functions in the hippocampus(\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e). A recent study found sex-specific differences in intrinsic connectivity and synaptic function of Nrxn3 in pvalb interneurons in the ventral subiculum(\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e). This study revealed that pvalb interneurons synapse onto regular spiking pyramidal neurons in Ms, but to burst spiking pyramidal neurons in Fs. Furthermore, conditional \u003cem\u003eNrxn3\u003c/em\u003e-KO in pvalb interneurons impaired synapse density, postsynaptic strength and inhibitory postsynaptic current amplitude at pvalb- regular spiking synapses in Ms but enhanced presynaptic release and IPSC amplitude in Fs. These results support a role for Nrxn3 in mediating inhibitory synaptic transmission in a sex- and cell-type specific manner. Specifically, in Fs the degree of pvalb-mediated inhibition is governed by differences in postsynaptic strength, while in Ms is driven by synapse numbers. These authors further hypothesized that the role of Nrxn3 from the same presynaptic cell is dramatically influenced by the composition of postsynaptic proteins(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). This is particularly relevant, as it is known that \u003cem\u003eNrxn3\u003c/em\u003e transcripts with different SS bind to different postsynaptic binding partners(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e). Although this study did not distinguish between Nrxn3α and Nrxn3b, it clearly demonstrates a sexually dimorphic role of Nrxn3 and suggests that the \u003cem\u003eNrxn3\u003c/em\u003e transcripts\u0026rsquo; landscape could be sexually dimorphic, leading to functional differences in Ms and Fs.\u003c/p\u003e \u003cp\u003eOur study also shows that the effect of alcohol on \u003cem\u003eNrxn3\u003c/em\u003e expression was conserved across species, although only in Fs. Specifically, \u003cem\u003eNrxn3b\u003c/em\u003e transcript was downregulated in the dlPFC-A46 and PLC of F macaques and mice, with no change in Nrxn3a. Furthermore, Nrxn3b isoform was downregulated in the PLC of F mice following chronic alcohol use. No dlPFC-A46 tissue was available for protein analyses in macaques. These results suggest that, in F mice, \u003cem\u003eNrxn3\u003c/em\u003e transcripts (and isoforms) in the PLC respond similarly to chronic alcohol use as in HVHD drinking F macaques. Interestingly, and contrarily to what we observed in macaque HVHD drinking Ms, \u003cem\u003eNrxn3\u003c/em\u003e transcripts were not downregulated in the PLC of M mice. These results might indicate a species-specific difference in transcriptional regulation, warranting further studies.\u003c/p\u003e \u003cp\u003eGiven the critical role Nrxn3 plays in pvalb interneurons in the ventral subiculum(\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e), we next sought to gain cell type resolution and investigated if Nrxn3 protein levels were altered in this specific cell type following chronic ethanol use. Our studies revealed that, in agreement with the mRNA data, Nrxn3b was dramatically downregulated in pvalb interneurons in the PLC of F mice, with no changes in Nrxn3α. Unexpectedly, we also observed a downregulation of Nrxn3b in pvalb interneurons in Ms, even though there were no differences at the mRNA level of the PLC. As noted, it is possible that this discrepancy is due to sex- and cell-type specific differences in the \u003cem\u003eNrxn3\u003c/em\u003e landscape, with Ms displaying more variability in transcripts\u0026rsquo; types by cell types. It is known that other cell types express \u003cem\u003eNrxn3b\u003c/em\u003e (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e) and it is also possible that, as the different cell types adapt to the presence of heavy chronic ethanol, the expression levels of \u003cem\u003eNrxn3b\u003c/em\u003e change accordingly in a cell-type specific manner. Additional studies profiling the alcohol adaptations of Nrxn3 at single cell level are needed to address this question. In the meantime, our results show that pvalb interneurons display the same response to chronic alcohol use in Ms and Fs, a downregulation of Nrxn3b. Others have shown that Nrxn3 is highly expressed in pvalb interneurons(\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e) and it contributes to pvalb interneurons\u0026rsquo; function in modulating excitability of pyramidal neurons(67, 68., 94\u0026ndash;98). Chronic ethanol has been linked to reduced number, impaired maturation and reduced excitability of pvalb interneurons(\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e), leading to a decrease in their inhibitory control over pyramidal neurons(\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e, \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e) in the PFC(\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e), which heightened excitatory signaling and could contribute to compulsive drinking(\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e). However, whether Nrxn3 levels are impacted by chronic alcohol use in this specific cell type remained to be explored. Our study showed consistent number of pvalb interneurons in the PLC in F mice, with downregulation of Nrxn3b expression in pvalb interneurons, with no difference in Nrxn3a levels. These results suggest a direct modulation of this specific isoform rather than an overall reduction in pvalb interneuron numbers or an overall reduction in Nrxn3 levels. In Ms, the effects seem to be a combination of reduced number of pvalb interneurons and reduced Nrxn3b expression. The functional consequences of this reduction remain to be explored.\u003c/p\u003e \u003cp\u003eIn summary, our research provides significant insights into the complex mechanisms by which ethanol affects the expression of \u003cem\u003eNRXN3\u003c/em\u003e within the PFC. Our results suggest that alcohol might be exerting its effects on synaptic plasticity, at least partially, by modulating DNAm in regulatory regions that alter \u003cem\u003eNRXN3\u003c/em\u003e expression, underscoring the intricate adaptations of \u003cem\u003eNRXN3\u003c/em\u003e regulation and function in response to alcohol in Ms and Fs. We hypothesize that alcohol could be contributing to the increased excitatory state seen in AUD, at least, through alterations in the splicing landscape of \u003cem\u003eNRXN3\u003c/em\u003e. The observed Nrxn3β downregulation in cortical pvalb interneurons would diminish inhibitory control on pyramidal neurons, leading to an imbalance favoring excitatory signaling and reinforcing substance dependence and compulsive behaviors(\u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e, \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e). These changes destabilize the delicate balance necessary for proper neural function, highlighting the importance of Nrxn3b in maintaining synaptic integrity and function.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Sharing\u003c/strong\u003e: The data that support the findings of this study are available on GEO under the following accession number: TBD\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003eBMF and RCJ designed the macaque methylomics experiments. RCJ designed and supervised all the molecular biology experiments as well as the studies conducted in rodents. KAG and SWG designed, implemented and oversaw the alcohol self-administration protocol and provided the rhesus macaque samples. RK provided the macaque tissues. TC and RCJ isolated the macaque DNA/RNA samples and prepared the omics libraries. DNA methylation and transcriptomic bioinformatic analyses were performed by KDZ, PD and LJW. FM conducted all the mouse alcohol intake experiments. RC advised on WB conditions. FM, DZ, CCL and RCJ collected all the samples from mice. CCL performed all the rodent molecular and cellular experiments on neurexin 3 and analyzed all the corresponding data. KDZ advised and conducted the appropriate statistical analyses in all the experiments. CM, CCL and KRG conducted and analyzed the confocal imaging. CCL and RCJ wrote the manuscript. KAG, BMF, KFRG, RC, RK, KDZ, CCL and RCJ provided edits to the final version manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest statement\u003c/strong\u003e: The authors declare no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAvchalumov Y, Mandyam CD (2020) Synaptic Plasticity and its Modulation by Alcohol. 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Front Cell Neurosci 13:87\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[{"identity":"085ef338-3a37-4b7c-a064-e76cc3c1ade6","identifier":"10.13039/100000027","name":"National Institute on Alcohol Abuse and Alcoholism","awardNumber":"T32AA007565","order_by":0},{"identity":"473154cc-d810-4064-8d2d-43b6d816bd1e","identifier":"10.13039/100000027","name":"National Institute on Alcohol Abuse and Alcoholism","awardNumber":"AA026092 ","order_by":1},{"identity":"0a6b543c-68e3-4694-bf7e-f75fbe378684","identifier":"10.13039/100000027","name":"National Institute on Alcohol Abuse and Alcoholism","awardNumber":"AA027552 ","order_by":2},{"identity":"bb121e07-bdac-4af0-8a2f-e8ff499ea21d","identifier":"10.13039/100000027","name":"National Institute on Alcohol Abuse and Alcoholism","awardNumber":"AA026278 ","order_by":3},{"identity":"ec370597-b34f-4e05-a945-db2f52fdbb11","identifier":"10.13039/100000027","name":"National Institute on Alcohol Abuse and Alcoholism","awardNumber":"AA010760 ","order_by":4},{"identity":"c6f36543-6ca9-4141-b429-1165efa7427a","identifier":"10.13039/100000027","name":"National Institute on Alcohol Abuse and Alcoholism","awardNumber":"AA019431 ","order_by":5},{"identity":"c6d6fe6a-b7ca-4870-97f2-73fb5b73c352","identifier":"10.13039/100000027","name":"National Institute on Alcohol Abuse and Alcoholism","awardNumber":"AA013510 ","order_by":6},{"identity":"203369e5-77ba-4fa3-a9b8-0de34168d999","identifier":"10.13039/100000002","name":"National Institutes of Health","awardNumber":"AA029691 ","order_by":7},{"identity":"8d93e471-4141-4168-a77c-b3b87c55459c","identifier":"10.13039/100000027","name":"National Institute on Alcohol Abuse and Alcoholism","awardNumber":"AA026117 ","order_by":8},{"identity":"8e50688e-def8-466d-95ae-44c5f45640a3","identifier":"10.13039/100000002","name":"National Institutes of Health","awardNumber":"AA030676 ","order_by":9},{"identity":"99a206ba-0121-4c83-a8cb-c907b7c3206c","identifier":"10.13039/100000002","name":"National Institutes of Health","awardNumber":"T32NS115704","order_by":10}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"alcohol, rhesus macaques, DNA methylation, neurexin, alternative splicing, parvalbumin","lastPublishedDoi":"10.21203/rs.3.rs-6278278/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6278278/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cu\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/u\u003e: Increasing evidence confirms the value of unbiased epigenomic and transcriptomic profiling in the identification of neuroadaptations in alcohol use disorder (AUD). Through this integrated omics analysis, we identified neurexin3 (\u003cem\u003eNRXN3\u003c/em\u003e) as a critical player in mediating alcohol’s effects on the cortex in primates and mice. Neurexins are presynaptic cell adhesion molecules critical in synaptic adaptations. Although neurexin3 has been linked to substance use disorders, the specific regulatory mechanisms that enable \u003cem\u003eNRXN3\u003c/em\u003e’s transcript/isoform diversity and the downstream effects on synaptic dynamics contributing to AUD remain unknown.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/u\u003e: We conducted unbiased genome-wide DNA methylation (DNAm) and RNAseq analyses of the dorsolateral prefrontal cortex (dlPFC) of rhesus macaques that remained alcohol-naïve (controls) or self-administered ethanol for 12 months. qPCR and immunohistochemistry were used to measure the levels of Nrxn3 transcripts and isoforms in parvalbumin interneurons in the prelimbic cortex (PLC) of mice following chronic ethanol exposure.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/u\u003e: Our unbiased omics analyses identified sex-specific differences in DNAm and gene expression. However, there was a shared enrichment in signaling pathways mediating synaptic neurotransmission and plasticity. Specifically, we found differential DNAm mapping to \u003cem\u003eNRXN3\u003c/em\u003e, and a specific downregulation of transcript \u003cem\u003eNRXN3b\u003c/em\u003e. We further showed this downregulation was conserved in mice following chronic ethanol use, and occurred in parvalbumin interneurons of the PLC. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cu\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003e\u003c/u\u003e\u0026nbsp;Our research provides significant insights into the complex mechanisms by which ethanol affects the expression of \u003cem\u003eNRXN3\u003c/em\u003ewithin the PFC/PLC and how this might be modulating synaptic plasticity in a cell type and sex-specific manner.\u003c/p\u003e","manuscriptTitle":"Neurexin 3 is differentially methylated and downregulated following chronic ethanol use.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-25 04:24:11","doi":"10.21203/rs.3.rs-6278278/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ce672bd9-76c5-4c41-a6d2-4d8b48846c86","owner":[],"postedDate":"March 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-07T17:35:21+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-25 04:24:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6278278","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6278278","identity":"rs-6278278","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}