Inflammatory cytokines as predictors of therapeutic response to valproate in patients with comorbid alcohol use disorder and bipolar disorder

Inflammatory cytokines as predictors of therapeutic response to valproate in patients with comorbid alcohol use disorder and bipolar disorder | 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 Article Inflammatory cytokines as predictors of therapeutic response to valproate in patients with comorbid alcohol use disorder and bipolar disorder Ilya Blokhin, Dana Ascherman, Feng Miao, Lisa Harlow, Eleonore Beurel, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5903730/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 Objective: Alcohol use disorder (AUD) is a chronic condition commonly associated with bipolar disorder (BD). We previously reported that valproate (VPA) can decrease drinking in some patients with comorbid AUD/BD. Predictors of treatment response to VPA, however, are yet to be elucidated, and it is not possible to prospectively identify patients who may benefit from the course of VPA. Both pathogenesis of AUD/BD and mechanism of action of VPA are related to inflammation (AUD/BD confers a pro-inflammatory state, while VPA has anti-inflammatory properties) which is associated with an altered counts of plasma vesicles. Approach: Patients with co-occurring AUD/BD were recruited and treated with VPA for 3 months at an average dose of 1,000 mg a day. Clinical response was defined as a decrease in proportion of weekly heavy drinking days (defined as ³ 5 drinks per day for men and ³ 4 drinks per day for women). Levels of inflammatory cytokines in plasma were measured using MAGPIX Luminex. Counts of apoptotic bodies and microparticles were determined using flow cytometry with size beads. Results: We found that plasma levels of C-reactive protein (CRP) at baseline were significantly increased in patients who responded to VPA. We did not find the difference in counts of microparticles or apoptotic bodies between responders and non-responders. In line, we observed that treatment with VPA conferred an anti-inflammatory effect but did not alter counts of plasma vesicles. Conclusion: Patients with AUD/BD who have increased levels of CRP are more likely to benefit from the treatment with VPA. Health sciences/Biomarkers/Predictive markers Biological sciences/Molecular biology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Alcohol use disorder (AUD) is a chronic condition characterized by a problematic pattern of alcohol use leading to clinically significant impairment. Alcohol consumption accounts for 2.6 million deaths per year or 4.7% of all deaths worldwide, according to the report from the World Health Organization ( 1 ). In the United States, 14% of adults currently meet criteria of AUD, and 29% met AUD criteria once during their lifetime ( 2 – 4 ). Annual cost of AUD and alcohol-related disorders has reached ~ $ 250 billion ( 5 ), and prevalence of AUD continues to rise ( 6 ). Despite considerable progress has been made in achieving abstinence ( 7 ), ~ 70–80% of patients still relapse within a year following treatment ( 8 , 9 ). Bipolar disorder (BD) has the highest prevalence of co-occurring with AUD and other substance use disorders, compared to other mental illnesses ( 10 – 12 ). BD I and BD II are associated with AUD in 49% and 38.9% of cases, respectively ( 13 ). Patients with comorbid AUD/BD have an increased incidence of manic and depressive symptoms, higher impulsivity, and marked violence ( 14 ). Co-occurring AUD/BD is also associated with severe morbidity and increased suicide risk ( 15 ). Effective therapeutic interventions to target AUD in AUD/BD population are lacking. We have previously shown that some patients with co-occurring AUD/BD respond to valproate (VPA), a medication known as a GABAergic agonist that modulates dopaminergic system and also acts as an epigenetic modifier. Thus, we observed that patients with AUD/BD treated with VPA had significantly lower proportion of heavy drinking days and fewer drinks per heavy drinking day compared to placebo ( 16 ). Likewise, Brady et al. ( 17 ) reported that VPA prevented relapse to heavy drinking in patients with AUD. Predictors of therapeutic response to VPA in patients with AUD/BD remain unknown, and patients who would likely benefit from VPA cannot be prospectively identified. Recent evidence suggests that AUD and BD increase production of pro-inflammatory cytokines while VPA reduces levels of pro-inflammatory factors. For example, AUD is associated with an increased plasma levels of such inflammatory markers as tumor necrosis factor (TNF), CCL2, and CCL5 ( 18 , 19 ). There is also an association between BD and increased pro-inflammatory cytokines including C-reactive protein (CRP), IL-2, IL-6, and TNF ( 20 – 25 ). VPA, on the other hand, has been known to diminish inflammatory indices ( 26 ). Inflammation is closely intertwined with circulating plasma vesicles which appear to promote inflammation. Extracellular vesicles are generally divided into apoptotic bodies (1–5 µm, shed as a result of apoptosis) and microparticles (100–1000 nm, shed by the membrane blebbing). Pro-inflammatory state triggers an increased production of extracellular vesicles ( 27 , 28 ), and shed vesicles constitute a rich source of pro-inflammatory compounds, thus further amplifying inflammation ( 29 , 30 ). We hypothesized that patients who respond to VPA have higher baseline inflammatory indices and higher counts of plasma vesicles and that VPA has an anti-inflammatory effect and decreases counts of plasma vesicles in patients with AUD/BD. Materials and Methods Subjects Subjects with DSM-IV-defined diagnoses of AUD and BD (AUD/BD) were enrolled in the study. Protocol included two parts. In the first part, we addressed if treatment with VPA affects plasma levels on cytokines and counts of plasma vesicles; in the second part, we aimed to identify if cytokines of interest can serve as predictors of clinical response to VPA. 9 subjects were included in the first part, and 11 subjects were included in the second part (5 non-responders and 6 responders). Study protocol was approved by the Institutional Review Boards of the University of Pittsburgh and the University of Miami. Subjects were excluded if they had any other major psychiatric disorder, if they had any severe or unstable medical conditions, or if they were pregnant or lactating. Treatment with VPA Patients received a course of VPA for 3 months at the average dose of 1,000 mg a day. The use of alternative mood stabilizers (lithium, carbamazepine, or lamotrigine) was not allowed. Liver function tests (including alanine aminotransferase, aspartate aminotransferase, and γ-glutamyl transpeptidase) and VPA plasma levels were evaluated periodically. Blood was collected from the median cubital vein prior to the initiation of treatment with VPA and throughout the study. Plasma samples were stored at -80°C until use. Evaluation of clinical response Alcohol use was assessed using the Timeline Follow-Back for Recent Drinking. The use of other drugs was monitored through regular urine drug screens. The primary alcohol use outcome was the change in proportion of weekly heavy drinking days (defined as ≥ 5 drinks per day for men and ≥ 4 drinks per day for women). Measurement of plasma cytokines Plasma levels of cytokines, chemokines, and growth factors were measured on a MAGPIX Luminex using a commercially available multiplex assays such as ProcartaPlex Multiplex Immunoassay (Thermo Fisher Scientific), Milliplex Map Kit (Millipore), and Magnetic Luminex Assay (R&D Systems), in accordance with the manufacturers’ recommendations. Assays were checked for quality control to fit the standard curves. A standard curve was run for each lot, and samples were normalized to the averaged standard curve values using standard software from the Luminex. Isolation of apoptotic bodies Plasma was thawed on ice, and apoptotic bodies were isolated using centrifugation at 2,000 g on a 5415 D centrifuge (Eppendorf) for 20 minutes. Quantitative real-time PCR (qRT-PCR) RNA from apoptotic bodies was isolated by Qiagen RNeasy kit, in accordance to manufacturer’s instructions. DNase treatment was performed using RNase-Free DNase Set (Qiagen). RNA profile, quality, and concentrations were determined by Nanodrop 2000; samples with RNA Integrity Number (A260:A280 ratio) between 1.9–2.1 were included in the study. RNA was reversely transcribed using High Capacity cDNA Reverse Transcription Kit (Thermo Fisher Scientific), and qRT-PCR was performed on QuantStudio 6 Flex (Thermo Fisher Scientific) using probe-based assays from Integrated DNA Technologies. Flow cytometry Apoptotic bodes and microparticles were counted in Flow Cytometry Shared Resource of the Sylvester Comprehensive Cancer Center at the University of Miami Miller School of Medicine. Flow Cytometry Size Calibration Kit (F13838, Thermo Fisher Scientific) was used to determine the size of particles between 1–10 µm in diameter. 123count eBeads Counting Beads (01-1234, Thermo Fisher Scientific) were used to determine the absolute counts of apoptotic bodies; counting beads were 7 µm in diameter and emitted a signal in the violet (405 nm) and blue (488 nm) lasers. Samples and 123count eBeads Counting Beads were mixed in 1:1 ratio (100 µl of each) and added to 0.3 ml of PBS. Sample acquisition was performed on a BD FACS Aria Fusion machine equipped with a violet (405 nm), blue (488 nm), yellow-green (561 nm), and red (640 nm) lasers. Forward Scatter and Side Scatter parameters were set on a logarithmic scale, and the Forward Scatter threshold was set at the lowest limit of 200. The Forward Scatter and Side Scatter voltages were then adjusted to set the Flow Cytometry Size Calibration beads on scale with the 10 µm diameter microspheres set at the highest scale for both Forward Scatter and Side Scatter. A marker was then set between 1 µm to 5 µm to delineate the apoptotic bodies, and events below 1 µm and above background noise were classified as microparticles. The voltages on the FITC and PerCP parameters where then adjusted to bring the 123count eBeads Counting Beads on scale. Statistical Analysis Statistical analysis was performed using two-tailed Student’s t test. Data are expressed as mean ± SEM unless otherwise stated. Differences with P < 0.05 were considered to be statistically significant. Results Effect of VPA on plasma levels of inflammatory markers There is some evidence that VPA affects inflammatory pathways and decreases inflammation ( 31 ). Specifically, VPA alters such cytokines as IL-5, IL-1β, IL-6, IL-10, TNF, and CCL2 ( 32 , 33 ). We therefore set out to determine if treatment with VPA may alter plasma levels of inflammatory markers in patients with AUD/BD. We found that a course of VPA decreased levels of pro-inflammatory CRP and increased levels of the metalloproteinase MMP-10 (P 0.05, Table 1 ). Table 1 Relative change in plasma levels of cytokines after treatment with valproate. Statistical analysis was performed using two-tailed Student’s t test. Cytokine Fold Change p value CCL-3/MIP-1a 0.87 0.8 CXCL-12/SDF-1a 0.99 0.9 IL-27 1.00 0.9 CXCL-10/IP-10 1.12 0.7 IL-8 1.07 0.9 IL-10 1.95 0.1 CCL-11/Eotaxin 1.47 0.4 IL-17a 1.08 0.6 CCL-5/RANTES 0.43 0.4 CCL-4/MIP-1b 1.06 0.8 CCL-2/MCP-1 1.38 0.1 IL-9 1.00 0.9 CXCL-1/GRO-a 1.31 0.7 IL-23 0.75 0.7 IL-21 1.06 0.9 IL-22 1.03 0.9 IL-1a 1.58 0.2 IL-2 1.15 0.2 IL-4 2.25 0.3 IL-6 3.04 0.3 TNF 1.27 0.2 C5/C5a 1.02 0.9 C2 0.86 0.4 C3a 0.85 0.4 Inflammatory markers as predictors of therapeutic response to VPA in patients with AUD/BD Currently, there are no predictors of treatment response in isolated AUD, with combined AUD/BD remaining even more challenging to approach with reliable prognosticators. Results from several studies indicate that inflammatory cytokines are frequently increased in patients with AUD ( 34 ), BD ( 20 , 21 , 35 ), and in patients with combined psychiatric illnesses such as AUD/major depressive disorder ( 36 ). We therefore screened panels of pro- and anti-inflammatory markers in patients with AUD/BD to address if plasma concentrations of cytokines prior to the treatment with VPA may predict a therapeutic response. Among recruited patients with AUD/BD, approximately 50% demonstrated decreased use of alcohol in response to VPA. Responders were designated as those individuals who were either abstinent or with significant decrease in weekly heavy drinking days (heavy drinking days were defined as = > 5 sd/d for males or = > 4 sd/d for females). We observed that responders had higher initial levels of pro-inflammatory cytokine CRP (P 0.05, Table 2 ). Table 2 Cytokines not predictive of clinical response to valproate. Values expressed as a relative of the group of responders to the group of non-responders. Statistical analysis was performed using two-tailed Student’s t test. Cytokine Fold Change p value Eotaxin 0.87 0.8 IL-17 0.53 0.5 IP-10 1.04 0.9 MCP-1 1.29 0.3 MIP-1b 1.34 0.4 RANTES 1.01 0.9 SDF-1a ( 13 ) 2.03 0.1 C2 0.96 0.4 C3 1.02 0.8 C5/C5a 0.62 0.2 MMP-10 0.82 0.5 IL-1a 0.93 0.9 IL-2 0.62 0.6 IL-4 1.07 0.8 IL-6 1.29 0.6 TNF 0.65 0.6 Effect of VPA on apoptotic bodies and microparticles The effect of VPA on counts of plasma vesicles is unknown. Given that VPA confers a pro-inflammatory effect ( 31 ) and that plasma vesicles are capable of inducing and amplifying inflammation ( 29 , 37 , 38 ), we sought to ascertain whether VPA affects counts of apoptotic bodies or microparticles in AUD/BD cohort. First, we isolated apoptotic bodies using centrifugation and determined RNA distribution using Nanodrop 2000. In contrast to previous reports ( 39 ), RNA profile in apoptotic bodies was strikingly different from that in nucleated cells (Fig. 3). To ensure RNA integrity, we measured expression of several genes by quantitative real-time PCR. While we observed that all measured genes were robustly expressed indicating high quality of RNA (Fig. 4A), we unexpectedly found that expression of genes tended to be much less in patients with detectable plasma levels of VPA compared to those with undetectable VPA levels (collected from a small additional cohort of patients who were likely non-compliant with the treatment protocol, P = 0.1, Fig. 4B). We reasoned that two scenarios could be responsible for such a trend. First, VPA could lower the levels of apoptotic bodies in plasma which would be in line with previous report describing anti-apoptotic effect of VPA ( 26 ) and with the observed anti-inflammatory action of VPA (Fig. 1). Second, VPA could decrease levels of RNA cargo in apoptotic bodies. To differentiate between two scenarios, we counted apoptotic bodies and microparticles in plasma using flow cytometry with size beads and found that counts of plasma vesicles did not differ in patients prior to and after the treatment with VPA (P > 0.05, Fig. 5). Apoptotic bodies and microparticles as predictors of therapeutic response to VPA in patients with AUD/BD Next, we aimed to address if plasma levels of apoptotic bodies and/or microparticles can predict therapeutic response to VPA in patients with AUD/BD. No difference in counts of apoptotic bodies or microparticles was detected between responders and non-responders to VPA (Fig. 6) indicating that plasma vesicles are unlikely to serve as prognosticators of therapeutic response to VPA. Discussion The salient findings of the current study are: 1) Altered plasma levels of CRP but not altered counts of plasma vesicles predict response to VPA in patients with AUD/BD, 2) Treatment with VPA alters plasma levels of inflammatory cytokines but does not affect counts of plasma vesicles. Treatment of AUD in a personalized manner is yet to be achieved. AUD rarely presents as an isolated disease and is commonly associated with other psychiatric illnesses, most often – with BD ( 11 , 40 ). We previously reported that patients with AUD/BD treated with VPA had a lower proportion of heavy drinking days and fewer drinks per heavy drinking day ( 16 ). We could not determine, however, why certain patients respond to VPA while others remain refractory. Difficulty in finding predictors for AUD/BD may result from the complexity of the intertwined pathogenetic mechanisms, as these psychiatric conditions co-occur. As almost all psychiatric illnesses, AUD and BD are polygenic diseases which develop and progress as a result of numerous interactions between various genetic and environmental factors. Even in a non-comorbid AUD, there are currently no predictors of clinical response to such commonly used medications as naltrexone or acamprosate. Likewise, no algorithms have been developed to address which subpopulations of patients with BD would respond to a particular mood stabilizer or atypical antipsychotic. In the current study, we found that pro-inflammatory cytokines may serve as a marker of clinical response to VPA. Specifically, we determined that responders to VPA have increased baseline plasma levels of CRP. We also observed that VPA decreases CRP and increases the metalloproteinase MMP-10. Mechanisms by which VPA imparts an anti-inflammatory effect are not elucidated but are likely related to an ability of VPA to function as an inhibitor of histone deacetylases thereby orchestrating the expression of multiple genes. These epigenetic properties of VPA recently again came under scrutiny, as clinical benefits were discerned in repurposing VPA for the treatment of systemic inflammation in patients with COVID-2019 ( 41 , 42 ). We also addressed if patients with AUD/BD have altered counts of plasma vesicles. It has been known that various classes of extracellular vesicles including apoptotic bodies and microparticles are closely linked to the progression of a pro-inflammatory state. Treatment of endothelial cells with CRP causes the release of extracellular vesicles ( 43 ). Likewise, production of extracellular vesicles is triggered by the staphylococcal superantigen-like protein 5 ( 44 ). Reversely, extracellular vesicles induced expression of cyclooxygenase-2 and production of prostacyclins in endothelial cells ( 29 ). In our study, although responders to VPA had elevated levels of inflammatory indices, we did not observe the difference in counts of plasma vesicles between responders and non-responders suggesting that both apoptotic bodies and microparticles are unlikely to be reliable predictors of clinical response to VPA. That inflammation is a marker of clinical response to VPA may be related to the involvement of inflammation in both AUD and BD. Increased levels of CRP were reported in men who consume excessive amounts of alcohol ( 45 , 46 ). Furthermore, patients with AUD were demonstrated to have altered systemic concentrations of multiple cytokines (reviewed in ( 47 )). Several studies established the association between BD and increased pro-inflammatory cytokines including CRP, IL-2, IL-6, and TNF ( 20 – 25 ). One may speculate that elevated levels of pro-inflammatory markers in AUD/BD are not mere bystanders but rather a pathogenetic link, and VPA is effective in these patients due to its anti-inflammatory action. We suggest that identified set of pro- and anti-inflammatory cytokines may represent only a part of putative prognostic panel, and further search for other predictors of response to VPA in patients with AUD/BD is warranted. RNA sequencing studies of brain from patients with BD showed that only a handful of genes were differentially expressed ( 48 , 49 ). AUD, on the contrary, is accompanied by genome-wide changes in brain transcriptome ( 50 – 53 ); VPA also induces broad changes in gene expression ( 31 , 54 ). Potential predictors may be represented by perturbed expression of non-coding RNAs, altered DNA methylation profiles, and chromatin remodeling (latter may be particularly attractive given that VPA is a histone deacetylase inhibitor). Development of a comprehensive prognostic panel will allow to find patients with co-occurring AUD/BD who will likely benefit from VPA. Our study has few limitations. Sample size is relatively small, and more patients should be recruited for a replication cohort as well as for search of novel prognosticators. Furthermore, data from our cohort may not be highly generalizable. Recent study demonstrated that Han Chinese population has a much lower prevalence of low-grade inflammation in BD ( 35 ), so that other ethnic groups may have to be studied separately. Declarations Acknowledgements Authors thank Drs. James Potash, Eric Hollander, and Helen Lavretsky for valuable suggestions regarding the manuscript. Authors also thank Patricia Guevara from the Flow Cytometry Shared Resource of the Sylvester Comprehensive Cancer Center at the University of Miami Miller School of Medicine for skilled assistance with the provision of sophisticated fluorescence analysis and cell sorting services. Sources of funding This study was supported by R01 AA015385, in part by R01 DA019992 and R01 AA024933 (to IMS), and R01 AA029924 (to CW). Disclosures Authors declare no conflict of interest. References Anderson BO, Berdzuli N, Ilbawi A, Kestel D, Kluge HP, Krech R, et al. Health and cancer risks associated with low levels of alcohol consumption. Lancet Public Health. 2023;8(1):e6-e7. Grant BF, Goldstein RB, Saha TD, Chou SP, Jung J, Zhang H, et al. Epidemiology of DSM-5 Alcohol Use Disorder: Results From the National Epidemiologic Survey on Alcohol and Related Conditions III. JAMA Psychiatry. 2015;72(8):757–66. Carvalho AF, Heilig M, Perez A, Probst C, Rehm J. Alcohol use disorders. Lancet. 2019;394(10200):781–92. Kranzler HR. Overview of Alcohol Use Disorder. Am J Psychiatry. 2023;180(8):565–72. Sacks JJ, Gonzales KR, Bouchery EE, Tomedi LE, Brewer RD. 2010 National and State Costs of Excessive Alcohol Consumption. Am J Prev Med. 2015;49(5):e73-e9. 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Kapoor M, Wang JC, Farris SP, Liu Y, McClintick J, Gupta I, et al. Analysis of whole genome-transcriptomic organization in brain to identify genes associated with alcoholism. Transl Psychiatry. 2019;9(1):89. Hill EJ, Nagel DA, O'Neil JD, Torr E, Woehrling EK, Devitt A, et al. Effects of lithium and valproic acid on gene expression and phenotypic markers in an NT2 neurosphere model of neural development. PLoS One. 2013;8(3):e58822. Additional Declarations The authors have declared there is NO conflict of interest to disclose 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. 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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-5903730","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":431124786,"identity":"4d102169-84ba-4b3f-98c3-88249afd5483","order_by":0,"name":"Ilya 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version.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-5903730/v1/8aa818d11129cd35efed443e.png"},{"id":79575607,"identity":"38bc5c10-12f0-4a44-a250-afef49ba1bbc","added_by":"auto","created_at":"2025-03-31 11:15:44","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":153494,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-5903730/v1/c55a7ffd5b7cec18267c0c02.png"},{"id":90084531,"identity":"18c9a903-bfba-4a82-88ca-70d7970a567b","added_by":"auto","created_at":"2025-08-28 09:40:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1679288,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5903730/v1/020baf3b-8f0c-408c-8e55-7d4d6a272776.pdf"}],"financialInterests":"The authors have declared there is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose","formattedTitle":"Inflammatory cytokines as predictors of therapeutic response to valproate in patients with comorbid alcohol use disorder and bipolar disorder","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAlcohol use disorder (AUD) is a chronic condition characterized by a problematic pattern of alcohol use leading to clinically significant impairment. Alcohol consumption accounts for 2.6\u0026nbsp;million deaths per year or 4.7% of all deaths worldwide, according to the report from the World Health Organization (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). In the United States, 14% of adults currently meet criteria of AUD, and 29% met AUD criteria once during their lifetime (\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Annual cost of AUD and alcohol-related disorders has reached ~\u003cspan\u003e$\u003c/span\u003e250\u0026nbsp;billion (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), and prevalence of AUD continues to rise (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Despite considerable progress has been made in achieving abstinence (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), ~\u0026thinsp;70\u0026ndash;80% of patients still relapse within a year following treatment (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBipolar disorder (BD) has the highest prevalence of co-occurring with AUD and other substance use disorders, compared to other mental illnesses (\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). BD I and BD II are associated with AUD in 49% and 38.9% of cases, respectively (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Patients with comorbid AUD/BD have an increased incidence of manic and depressive symptoms, higher impulsivity, and marked violence (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Co-occurring AUD/BD is also associated with severe morbidity and increased suicide risk (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Effective therapeutic interventions to target AUD in AUD/BD population are lacking. We have previously shown that some patients with co-occurring AUD/BD respond to valproate (VPA), a medication known as a GABAergic agonist that modulates dopaminergic system and also acts as an epigenetic modifier. Thus, we observed that patients with AUD/BD treated with VPA had significantly lower proportion of heavy drinking days and fewer drinks per heavy drinking day compared to placebo (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Likewise, Brady et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) reported that VPA prevented relapse to heavy drinking in patients with AUD. Predictors of therapeutic response to VPA in patients with AUD/BD remain unknown, and patients who would likely benefit from VPA cannot be prospectively identified.\u003c/p\u003e \u003cp\u003eRecent evidence suggests that AUD and BD increase production of pro-inflammatory cytokines while VPA reduces levels of pro-inflammatory factors. For example, AUD is associated with an increased plasma levels of such inflammatory markers as tumor necrosis factor (TNF), CCL2, and CCL5 (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). There is also an association between BD and increased pro-inflammatory cytokines including C-reactive protein (CRP), IL-2, IL-6, and TNF (\u003cspan additionalcitationids=\"CR21 CR22 CR23 CR24\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). VPA, on the other hand, has been known to diminish inflammatory indices (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eInflammation is closely intertwined with circulating plasma vesicles which appear to promote inflammation. Extracellular vesicles are generally divided into apoptotic bodies (1\u0026ndash;5 \u0026micro;m, shed as a result of apoptosis) and microparticles (100\u0026ndash;1000 nm, shed by the membrane blebbing). Pro-inflammatory state triggers an increased production of extracellular vesicles (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), and shed vesicles constitute a rich source of pro-inflammatory compounds, thus further amplifying inflammation (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe hypothesized that patients who respond to VPA have higher baseline inflammatory indices and higher counts of plasma vesicles and that VPA has an anti-inflammatory effect and decreases counts of plasma vesicles in patients with AUD/BD.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSubjects\u003c/h2\u003e \u003cp\u003eSubjects with DSM-IV-defined diagnoses of AUD and BD (AUD/BD) were enrolled in the study. Protocol included two parts. In the first part, we addressed if treatment with VPA affects plasma levels on cytokines and counts of plasma vesicles; in the second part, we aimed to identify if cytokines of interest can serve as predictors of clinical response to VPA. 9 subjects were included in the first part, and 11 subjects were included in the second part (5 non-responders and 6 responders). Study protocol was approved by the Institutional Review Boards of the University of Pittsburgh and the University of Miami. Subjects were excluded if they had any other major psychiatric disorder, if they had any severe or unstable medical conditions, or if they were pregnant or lactating.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eTreatment with VPA\u003c/h3\u003e\n\u003cp\u003ePatients received a course of VPA for 3 months at the average dose of 1,000 mg a day. The use of alternative mood stabilizers (lithium, carbamazepine, or lamotrigine) was not allowed. Liver function tests (including alanine aminotransferase, aspartate aminotransferase, and γ-glutamyl transpeptidase) and VPA plasma levels were evaluated periodically. Blood was collected from the median cubital vein prior to the initiation of treatment with VPA and throughout the study. Plasma samples were stored at -80\u0026deg;C until use.\u003c/p\u003e\n\u003ch3\u003eEvaluation of clinical response\u003c/h3\u003e\n\u003cp\u003eAlcohol use was assessed using the Timeline Follow-Back for Recent Drinking. The use of other drugs was monitored through regular urine drug screens. The primary alcohol use outcome was the change in proportion of weekly heavy drinking days (defined as \u0026ge; 5 drinks per day for men and \u0026ge; 4 drinks per day for women).\u003c/p\u003e\n\u003ch3\u003eMeasurement of plasma cytokines\u003c/h3\u003e\n\u003cp\u003ePlasma levels of cytokines, chemokines, and growth factors were measured on a MAGPIX Luminex using a commercially available multiplex assays such as ProcartaPlex Multiplex Immunoassay (Thermo Fisher Scientific), Milliplex Map Kit (Millipore), and Magnetic Luminex Assay (R\u0026amp;D Systems), in accordance with the manufacturers\u0026rsquo; recommendations. Assays were checked for quality control to fit the standard curves. A standard curve was run for each lot, and samples were normalized to the averaged standard curve values using standard software from the Luminex.\u003c/p\u003e\n\u003ch3\u003eIsolation of apoptotic bodies\u003c/h3\u003e\n\u003cp\u003ePlasma was thawed on ice, and apoptotic bodies were isolated using centrifugation at 2,000 g on a 5415 D centrifuge (Eppendorf) for 20 minutes.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eQuantitative real-time PCR (qRT-PCR)\u003c/h2\u003e \u003cp\u003eRNA from apoptotic bodies was isolated by Qiagen RNeasy kit, in accordance to manufacturer\u0026rsquo;s instructions. DNase treatment was performed using RNase-Free DNase Set (Qiagen). RNA profile, quality, and concentrations were determined by Nanodrop 2000; samples with RNA Integrity Number (A260:A280 ratio) between 1.9\u0026ndash;2.1 were included in the study. RNA was reversely transcribed using High Capacity cDNA Reverse Transcription Kit (Thermo Fisher Scientific), and qRT-PCR was performed on QuantStudio 6 Flex (Thermo Fisher Scientific) using probe-based assays from Integrated DNA Technologies.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eFlow cytometry\u003c/h3\u003e\n\u003cp\u003eApoptotic bodes and microparticles were counted in Flow Cytometry Shared Resource of the Sylvester Comprehensive Cancer Center at the University of Miami Miller School of Medicine. Flow Cytometry Size Calibration Kit (F13838, Thermo Fisher Scientific) was used to determine the size of particles between 1\u0026ndash;10 \u0026micro;m in diameter. 123count eBeads Counting Beads (01-1234, Thermo Fisher Scientific) were used to determine the absolute counts of apoptotic bodies; counting beads were 7 \u0026micro;m in diameter and emitted a signal in the violet (405 nm) and blue (488 nm) lasers. Samples and 123count eBeads Counting Beads were mixed in 1:1 ratio (100 \u0026micro;l of each) and added to 0.3 ml of PBS. Sample acquisition was performed on a BD FACS Aria Fusion machine equipped with a violet (405 nm), blue (488 nm), yellow-green (561 nm), and red (640 nm) lasers. Forward Scatter and Side Scatter parameters were set on a logarithmic scale, and the Forward Scatter threshold was set at the lowest limit of 200. The Forward Scatter and Side Scatter voltages were then adjusted to set the Flow Cytometry Size Calibration beads on scale with the 10 \u0026micro;m diameter microspheres set at the highest scale for both Forward Scatter and Side Scatter. A marker was then set between 1 \u0026micro;m to 5 \u0026micro;m to delineate the apoptotic bodies, and events below 1 \u0026micro;m and above background noise were classified as microparticles. The voltages on the FITC and PerCP parameters where then adjusted to bring the 123count eBeads Counting Beads on scale.\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis was performed using two-tailed Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e test. Data are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM unless otherwise stated. Differences with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered to be statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eEffect of VPA on plasma levels of inflammatory markers\u003c/h2\u003e \u003cp\u003eThere is some evidence that VPA affects inflammatory pathways and decreases inflammation (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Specifically, VPA alters such cytokines as IL-5, IL-1β, IL-6, IL-10, TNF, and CCL2 (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). We therefore set out to determine if treatment with VPA may alter plasma levels of inflammatory markers in patients with AUD/BD. We found that a course of VPA decreased levels of pro-inflammatory CRP and increased levels of the metalloproteinase MMP-10 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;1). Most of pro- and anti-inflammatory cytokines, however, remained unaffected, although there was a trend to increased concentrations of IL-10 and CCL-2 (e.g. MCP-1) (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRelative change in plasma levels of cytokines after treatment with valproate. Statistical analysis was performed using two-tailed Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e test.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCytokine\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFold Change\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCL-3/MIP-1a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCXCL-12/SDF-1a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCXCL-10/IP-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCL-11/Eotaxin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-17a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCL-5/RANTES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCL-4/MIP-1b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCL-2/MCP-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCXCL-1/GRO-a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-1a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC5/C5a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC3a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eInflammatory markers as predictors of therapeutic response to VPA in patients with AUD/BD\u003c/h2\u003e \u003cp\u003eCurrently, there are no predictors of treatment response in isolated AUD, with combined AUD/BD remaining even more challenging to approach with reliable prognosticators. Results from several studies indicate that inflammatory cytokines are frequently increased in patients with AUD (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e), BD (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e), and in patients with combined psychiatric illnesses such as AUD/major depressive disorder (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). We therefore screened panels of pro- and anti-inflammatory markers in patients with AUD/BD to address if plasma concentrations of cytokines prior to the treatment with VPA may predict a therapeutic response. Among recruited patients with AUD/BD, approximately 50% demonstrated decreased use of alcohol in response to VPA. Responders were designated as those individuals who were either abstinent or with significant decrease in weekly heavy drinking days (heavy drinking days were defined as =\u0026thinsp;\u0026gt;\u0026thinsp;5 sd/d for males or =\u0026thinsp;\u0026gt;\u0026thinsp;4 sd/d for females). We observed that responders had higher initial levels of pro-inflammatory cytokine CRP (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;2) while other cytokines did not correlate with the clinical response to VPA (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCytokines not predictive of clinical response to valproate. Values expressed as a relative of the group of responders to the group of non-responders. Statistical analysis was performed using two-tailed Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e test.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCytokine\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFold Change\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEotaxin\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIL-17\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIP-10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMCP-1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMIP-1b\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRANTES\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSDF-1a\u003c/b\u003e (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eC2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eC3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eC5/C5a\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMMP-10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIL-1a\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIL-2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIL-4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIL-6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTNF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eEffect of VPA on apoptotic bodies and microparticles\u003c/h2\u003e \u003cp\u003eThe effect of VPA on counts of plasma vesicles is unknown. Given that VPA confers a pro-inflammatory effect (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e) and that plasma vesicles are capable of inducing and amplifying inflammation (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e), we sought to ascertain whether VPA affects counts of apoptotic bodies or microparticles in AUD/BD cohort. First, we isolated apoptotic bodies using centrifugation and determined RNA distribution using Nanodrop 2000. In contrast to previous reports (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e), RNA profile in apoptotic bodies was strikingly different from that in nucleated cells (Fig.\u0026nbsp;3). To ensure RNA integrity, we measured expression of several genes by quantitative real-time PCR. While we observed that all measured genes were robustly expressed indicating high quality of RNA (Fig.\u0026nbsp;4A), we unexpectedly found that expression of genes tended to be much less in patients with detectable plasma levels of VPA compared to those with undetectable VPA levels (collected from a small additional cohort of patients who were likely non-compliant with the treatment protocol, P\u0026thinsp;=\u0026thinsp;0.1, Fig.\u0026nbsp;4B). We reasoned that two scenarios could be responsible for such a trend. First, VPA could lower the levels of apoptotic bodies in plasma which would be in line with previous report describing anti-apoptotic effect of VPA (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) and with the observed anti-inflammatory action of VPA (Fig.\u0026nbsp;1). Second, VPA could decrease levels of RNA cargo in apoptotic bodies. To differentiate between two scenarios, we counted apoptotic bodies and microparticles in plasma using flow cytometry with size beads and found that counts of plasma vesicles did not differ in patients prior to and after the treatment with VPA (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Fig.\u0026nbsp;5).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eApoptotic bodies and microparticles as predictors of therapeutic response to VPA in patients with AUD/BD\u003c/h2\u003e \u003cp\u003eNext, we aimed to address if plasma levels of apoptotic bodies and/or microparticles can predict therapeutic response to VPA in patients with AUD/BD. No difference in counts of apoptotic bodies or microparticles was detected between responders and non-responders to VPA (Fig.\u0026nbsp;6) indicating that plasma vesicles are unlikely to serve as prognosticators of therapeutic response to VPA.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe salient findings of the current study are: 1) Altered plasma levels of CRP but not altered counts of plasma vesicles predict response to VPA in patients with AUD/BD, 2) Treatment with VPA alters plasma levels of inflammatory cytokines but does not affect counts of plasma vesicles.\u003c/p\u003e \u003cp\u003eTreatment of AUD in a personalized manner is yet to be achieved. AUD rarely presents as an isolated disease and is commonly associated with other psychiatric illnesses, most often \u0026ndash; with BD (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). We previously reported that patients with AUD/BD treated with VPA had a lower proportion of heavy drinking days and fewer drinks per heavy drinking day (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). We could not determine, however, why certain patients respond to VPA while others remain refractory. Difficulty in finding predictors for AUD/BD may result from the complexity of the intertwined pathogenetic mechanisms, as these psychiatric conditions co-occur. As almost all psychiatric illnesses, AUD and BD are polygenic diseases which develop and progress as a result of numerous interactions between various genetic and environmental factors. Even in a non-comorbid AUD, there are currently no predictors of clinical response to such commonly used medications as naltrexone or acamprosate. Likewise, no algorithms have been developed to address which subpopulations of patients with BD would respond to a particular mood stabilizer or atypical antipsychotic.\u003c/p\u003e \u003cp\u003eIn the current study, we found that pro-inflammatory cytokines may serve as a marker of clinical response to VPA. Specifically, we determined that responders to VPA have increased baseline plasma levels of CRP. We also observed that VPA decreases CRP and increases the metalloproteinase MMP-10. Mechanisms by which VPA imparts an anti-inflammatory effect are not elucidated but are likely related to an ability of VPA to function as an inhibitor of histone deacetylases thereby orchestrating the expression of multiple genes. These epigenetic properties of VPA recently again came under scrutiny, as clinical benefits were discerned in repurposing VPA for the treatment of systemic inflammation in patients with COVID-2019 (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe also addressed if patients with AUD/BD have altered counts of plasma vesicles. It has been known that various classes of extracellular vesicles including apoptotic bodies and microparticles are closely linked to the progression of a pro-inflammatory state. Treatment of endothelial cells with CRP causes the release of extracellular vesicles (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). Likewise, production of extracellular vesicles is triggered by the staphylococcal superantigen-like protein 5 (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). Reversely, extracellular vesicles induced expression of cyclooxygenase-2 and production of prostacyclins in endothelial cells (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). In our study, although responders to VPA had elevated levels of inflammatory indices, we did not observe the difference in counts of plasma vesicles between responders and non-responders suggesting that both apoptotic bodies and microparticles are unlikely to be reliable predictors of clinical response to VPA.\u003c/p\u003e \u003cp\u003eThat inflammation is a marker of clinical response to VPA may be related to the involvement of inflammation in both AUD and BD. Increased levels of CRP were reported in men who consume excessive amounts of alcohol (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). Furthermore, patients with AUD were demonstrated to have altered systemic concentrations of multiple cytokines (reviewed in (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e)). Several studies established the association between BD and increased pro-inflammatory cytokines including CRP, IL-2, IL-6, and TNF (\u003cspan additionalcitationids=\"CR21 CR22 CR23 CR24\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). One may speculate that elevated levels of pro-inflammatory markers in AUD/BD are not mere bystanders but rather a pathogenetic link, and VPA is effective in these patients due to its anti-inflammatory action.\u003c/p\u003e \u003cp\u003eWe suggest that identified set of pro- and anti-inflammatory cytokines may represent only a part of putative prognostic panel, and further search for other predictors of response to VPA in patients with AUD/BD is warranted. RNA sequencing studies of brain from patients with BD showed that only a handful of genes were differentially expressed (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e). AUD, on the contrary, is accompanied by genome-wide changes in brain transcriptome (\u003cspan additionalcitationids=\"CR51 CR52\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e); VPA also induces broad changes in gene expression (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e). Potential predictors may be represented by perturbed expression of non-coding RNAs, altered DNA methylation profiles, and chromatin remodeling (latter may be particularly attractive given that VPA is a histone deacetylase inhibitor). Development of a comprehensive prognostic panel will allow to find patients with co-occurring AUD/BD who will likely benefit from VPA.\u003c/p\u003e \u003cp\u003eOur study has few limitations. Sample size is relatively small, and more patients should be recruited for a replication cohort as well as for search of novel prognosticators. Furthermore, data from our cohort may not be highly generalizable. Recent study demonstrated that Han Chinese population has a much lower prevalence of low-grade inflammation in BD (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e), so that other ethnic groups may have to be studied separately.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eAuthors thank Drs. James Potash, Eric Hollander, and Helen Lavretsky for valuable suggestions regarding the manuscript. Authors also thank Patricia Guevara from the Flow Cytometry Shared Resource of the Sylvester Comprehensive Cancer Center at the University of Miami Miller School of Medicine for skilled assistance with the\u0026nbsp;provision of sophisticated fluorescence analysis and cell sorting services.\u003c/p\u003e\n\u003cp\u003eSources of funding\u003c/p\u003e\n\u003cp\u003eThis study was supported by R01 AA015385, in part by R01 DA019992 and R01 AA024933 (to IMS), and R01 AA029924 (to CW).\u003c/p\u003e\n\u003cp\u003eDisclosures\u003c/p\u003e\n\u003cp\u003eAuthors declare no conflict of interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAnderson BO, Berdzuli N, Ilbawi A, Kestel D, Kluge HP, Krech R, et al. Health and cancer risks associated with low levels of alcohol consumption. 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PLoS One. 2013;8(3):e58822.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"","lastPublishedDoi":"10.21203/rs.3.rs-5903730/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5903730/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAlcohol use disorder (AUD) is a chronic condition commonly associated with bipolar disorder (BD). We previously reported that valproate (VPA) can decrease drinking in some patients with comorbid AUD/BD. Predictors of treatment response to VPA, however, are yet to be elucidated, and it is not possible to prospectively identify patients who may benefit from the course of VPA. Both pathogenesis of AUD/BD and mechanism of action of VPA are related to inflammation (AUD/BD confers a pro-inflammatory state, while VPA has anti-inflammatory properties) which is associated with an altered counts of plasma vesicles.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eApproach:\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePatients with co-occurring AUD/BD were recruited and treated with VPA for 3 months at an average dose of 1,000 mg a day. Clinical response was defined as a decrease in proportion of weekly heavy drinking days (defined as ³ 5 drinks per day for men and ³ 4 drinks per day for women). Levels of inflammatory cytokines in plasma were measured using MAGPIX Luminex. Counts of apoptotic bodies and microparticles were determined using flow cytometry with size beads.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe found that plasma levels of C-reactive protein (CRP) at baseline were significantly increased in patients who responded to VPA. We did not find the difference in counts of microparticles or apoptotic bodies between responders and non-responders. In line, we observed that treatment with VPA conferred an anti-inflammatory effect but did not alter counts of plasma vesicles.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePatients with AUD/BD who have increased levels of CRP are more likely to benefit from the treatment with VPA.\u003c/p\u003e","manuscriptTitle":"Inflammatory cytokines as predictors of therapeutic response to valproate in patients with comorbid alcohol use disorder and bipolar disorder","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-31 11:07:39","doi":"10.21203/rs.3.rs-5903730/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":"51f3bc79-06e0-41a7-8c14-c66175d61bc0","owner":[],"postedDate":"March 31st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":45919693,"name":"Health sciences/Biomarkers/Predictive markers"},{"id":45919694,"name":"Biological sciences/Molecular biology"}],"tags":[],"updatedAt":"2025-08-28T09:32:20+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-31 11:07:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5903730","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5903730","identity":"rs-5903730","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}