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Acamprosate is an anti-craving drug used for the pharmacotherapy of alcohol use disorder (AUD). However, only some patients achieve optimal therapeutic outcomes. This study was designed to explore differences in metabolomic profiles between patients who maintained sobriety and those who relapsed, to determine whether those differences provide insight into variation in acamprosate treatment response phenotypes.We previously conducted an acamprosate trial involving 442 AUD patients, and 267 of these subjects presented themselves for a 3-month follow-up. The primary outcome was abstinence. Clinical information, genomic data and metabolomics data were collected. Baseline plasma samples were assayed using targeted metabolomics.Baseline plasma arginine, threonine, α-aminoadipic acid and ethanolamine concentrations were associated with acamprosate treatment outcomes and baseline craving intensity, a measure that has been associated with acamprosate treatment response. We next applied a pharmacometabolomics-informed genome-wide association study (GWAS) strategy to identify genetic variants that might contribute to variations in plasma metabolomic profiles that were associated with craving and/or acamprosate treatment outcome. Gene expression data for induced pluripotent stem cell-derived forebrain astrocytes showed that a series of genes identified during the metabolomics-informed GWAS were ethanol responsive. Furthermore, a large number of those genes could be regulated by acamprosate. Finally, we identified a series of single nucleotide polymorphisms that were associated with acamprosate treatment outcomes.These results serve as an important step towards advancing our understanding of disease pathophysiology and drug action responsible for variation in acamprosate response and alcohol craving in AUD patients.

Major depressive disorder (MDD) is a prevalent psychiatric disorder, and exposure to stress is a robust risk factor for MDD. Clinical data and rodent models have indicated the negative impact of chronic exposure to stress-induced hormones like cortisol on brain volume, memory, and cell metabolism. However, the cellular and transcriptomic changes that occur in the brain after prolonged exposure to cortisol are less understood. Furthermore, the astrocyte-specific contribution to cortisol-induced neuropathology remains understudied. Here, we have developed an in vitro model of “chronic stress” using human induced pluripotent stem cell (iPSC)-derived astrocytes treated with cortisol for 7 days. Whole transcriptome sequencing reveals differentially expressed genes (DEGs) uniquely regulated in chronic cortisol compared to acute cortisol treatment. Utilizing this paradigm, we examined the stress response transcriptome of astrocytes generated from MDD patient iPSCs. The MDD-specific DEGs are related to GPCR ligand binding, synaptic signaling, and ion homeostasis. Together, these data highlight the unique role astrocytes play in the central nervous system and present interesting genes for future study into the relationship between chronic stress and MDD.

Naltrexone can aid in reducing alcohol consumption, while acamprosate supports abstinence; however, not all patients with alcohol use disorder (AUD) benefit from these treatments. Here we present the first genome-wide association study of AUD treatment outcomes based on data from the COMBINE and PREDICT studies of acamprosate and naltrexone, and the Mayo Clinic CITA study of acamprosate. Primary analyses focused on treatment outcomes regardless of pharmacological intervention and were followed by drug-stratified analyses to identify treatment-specific pharmacogenomic predictors of acamprosate and naltrexone response. Treatment outcomes were defined as: (1) time until relapse to any drinking (TR) and (2) time until relapse to heavy drinking (THR; ≥ 5 drinks for men, ≥4 drinks for women in a day), during the first 3 months of treatment. Analyses were performed within each dataset, followed by meta-analysis across the studies (N = 1083 European ancestry participants). Single nucleotide polymorphisms (SNPs) in the BRE gene were associated with THR (min p = 1.6E−8) in the entire sample, while two intergenic SNPs were associated with medication-specific outcomes (naltrexone THR: rs12749274, p = 3.9E−8; acamprosate TR: rs77583603, p = 3.1E−9). The top association signal for TR (p = 7.7E−8) and second strongest signal in the THR (p = 6.1E−8) analysis of naltrexone-treated patients maps to PTPRD, a gene previously implicated in addiction phenotypes in human and animal studies. Leave-one-out polygenic risk score analyses showed significant associations with TR (p = 3.7E−4) and THR (p = 2.6E−4). This study provides the first evidence of a polygenic effect on AUD treatment response, and identifies genetic variants associated with potentially medication-specific effects on AUD treatment response.

Heterogeneity in the clinical presentation of major depressive disorder and response to antidepressants limits clinicians’ ability to accurately predict a specific patient’s eventual response to therapy. Validated depressive symptom profiles may be an important tool for identifying poor outcomes early in the course of treatment. To derive these symptom profiles, we first examined data from 947 depressed subjects treated with selective serotonin reuptake inhibitors (SSRIs) to delineate the heterogeneity of antidepressant response using probabilistic graphical models (PGMs). We then used unsupervised machine learning to identify specific depressive symptoms and thresholds of improvement that were predictive of antidepressant response by 4 weeks for a patient to achieve remission, response, or nonresponse by 8 weeks. Four depressive symptoms (depressed mood, guilt feelings and delusion, work and activities and psychic anxiety) and specific thresholds of change in each at 4 weeks predicted eventual outcome at 8 weeks to SSRI therapy with an average accuracy of 77% (p = 5.5E-08). The same four symptoms and prognostic thresholds derived from patients treated with SSRIs correctly predicted outcomes in 72% (p = 1.25E-05) of 1996 patients treated with other antidepressants in both inpatient and outpatient settings in independent publicly-available datasets. These predictive accuracies were higher than the accuracy of 53% for predicting SSRI response achieved using approaches that (i) incorporated only baseline clinical and sociodemographic factors, or (ii) used 4-week nonresponse status to predict likely outcomes at 8 weeks. The present findings suggest that PGMs providing interpretable predictions have the potential to enhance clinical treatment of depression and reduce the time burden associated with trials of ineffective antidepressants. Prospective trials examining this approach are forthcoming.

Lifetime history of major depressive disorder (MDD) has a sex-specific association with pretreatment alcohol consumption in patients with alcohol dependence. Here, we investigated the association of genetic load for MDD estimated using a polygenic risk score (PRS) with pretreatment alcohol consumption assessed with Timeline Follow Back in a sample of 287 men and 156 women meeting DSM-IV-TR criteria for alcohol dependence. Preferred drinking situations were assessed using the Inventory of Drug Taking Situations (IDTS). Linear models were used to test for association of normalized alcohol consumption measures with the MDD-PRS, adjusting for ancestry, age, sex, and number of days sober at baseline. We fit models both with and without adjustment for MDD history and alcohol-use-related PRSs as covariates. Higher MDD-PRS was associated with lower 90-day total alcohol consumption in men (β = -0.16, p = 0.0012) but not in women (β = 0.11, p = 0.18). The association of MDD-PRS with IDTS measures was also sex-specific: higher MDD-PRS was associated with higher propensity to drink in temptation-related situations in women, while the opposite (negative association)was found in men. MDD-PRS was not associated with lifetime MDD history in our sample, and adjustment for lifetime MDD and alcohol-related PRSs did not impact the results. Our results suggest that genetic load for MDD impacts pretreatment alcohol consumption in a sex-specific manner, which is similar to, but independent from, the effect of history of MDD. The clinical implications of these findings and contributing biological and psychological factors should be investigated in future studies.

Combination antidepressant pharmacotherapies are frequently used to treat major depressive disorder (MDD). However, there is no evidence that machine learning approaches combining multi-omics measures (e.g., genomics and plasma metabolomics) can achieve clinically meaningful predictions of outcomes to combination pharmacotherapy. This study examined data from 264 MDD outpatients treated with citalopram or escitalopram in the Mayo Clinic Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) and 111 MDD outpatients treated with combination pharmacotherapies in the Combined Medications to Enhance Outcomes of Antidepressant Therapy (CO-MED) study to predict response to combination antidepressant therapies. To assess whether metabolomics with functionally validated single-nucleotide polymorphisms (SNPs) improves predictability over metabolomics alone, models were trained/tested with and without SNPs. Models trained with PGRN-AMPS’ and CO-MED’s escitalopram/citalopram patients predicted response in CO-MED’s combination pharmacotherapy patients with accuracies of 76.6% (p p p p

We set out to determine whether machine learning–based algorithms that included functionally validated pharmacogenomic biomarkers joined with clinical measures could predict selective serotonin reuptake inhibitor (SSRI) remission/response in patients with major depressive disorder (MDD). We studied 1,030 white outpatients with MDD treated with citalopram/escitalopram in the Mayo Clinic Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN‐AMPS; n = 398), Sequenced Treatment Alternatives to Relieve Depression (STAR*D; n = 467), and International SSRI Pharmacogenomics Consortium (ISPC; n = 165) trials. A genomewide association study for PGRN‐AMPS plasma metabolites associated with SSRI response (serotonin) and baseline MDD severity (kynurenine) identified single nucleotide polymorphisms (SNPs) in DEFB1,ERICH3,AHR, and TSPAN5 that we tested as predictors. Supervised machine‐learning methods trained using SNPs and total baseline depression scores predicted remission and response at 8 weeks with area under the receiver operating curve (AUC) > 0.7 (P 69% (P ≤ 0.07) in STAR*D and ISPC. These results demonstrate that machine learning can achieve accurate and, importantly, replicable prediction of SSRI therapy response using total baseline depression severity combined with pharmacogenomic biomarkers.

Disrupted serotonergic neurotransmission has long been implicated in major depressive disorder (MDD), for which selective serotonin reuptake inhibitors (SSRIs) are the first line of treatment. However, a significant percentage of patients remain SSRI-resistant and it is unclear whether and how alterations in serotonergic neurons contribute to SSRI resistance in these patients. Induced pluripotent stem cells (iPSCs) facilitate the study of patient-specific neural subtypes that are typically inaccessible in living patients, enabling the discovery of disease-related phenotypes. In our study of a well-characterized cohort of over 800 MDD patients, we generated iPSCs and serotonergic neurons from three extreme SSRI-remitters (R) and SSRI-nonremitters (NR). We studied serotonin (5-HT) biochemistry and observed no significant differences in 5-HT release and reuptake or in genes related to 5-HT biochemistry. NR patient-derived serotonergic neurons exhibited altered neurite growth and morphology downstream of lowered expression of key Protocadherin alpha genes as compared to healthy controls and Rs. Furthermore, knockdown of Protocadherin alpha genes directly regulated iPSC-derived neurite length and morphology. Our results suggest that intrinsic differences in serotonergic neuron morphology and the resulting circuitry may contribute to SSRI resistance in MDD patients.

Selective serotonin reuptake inhibitors (SSRIs) are first-line antidepressants for the treatment of major depressive disorder (MDD). However, treatment response during an initial therapeutic trial is often poor and is difficult to predict. Heterogeneity of response to SSRIs in depressed patients is partly driven by co-occurring somatic disorders such as coronary artery disease (CAD) and obesity. CAD and obesity may also be associated with metabolic side effects of SSRIs. In this study, we assessed the association of CAD and obesity with treatment response to SSRIs in patients with MDD using a polygenic score (PGS) approach. Additionally, we performed cross-trait meta-analyses to pinpoint genetic variants underpinnings the relationship of CAD and obesity with SSRIs treatment response. First, PGSs were calculated at different p value thresholds (PT) for obesity and CAD. Next, binary logistic regression was applied to evaluate the association of the PGSs to SSRIs treatment response in a discovery sample (ISPC, N = 865), and in a replication cohort (STAR*D, N = 1,878). Finally, a cross-trait GWAS meta-analysis was performed by combining summary statistics. We show that the PGSs for CAD and obesity were inversely associated with SSRIs treatment response. At the most significant thresholds, the PGS for CAD and body mass index accounted 1.3%, and 0.8% of the observed variability in treatment response to SSRIs, respectively. In the cross-trait meta-analyses, we identified (1) 14 genetic loci (including NEGR1, CADM2, PMAIP1, PARK2) that are associated with both obesity and SSRIs treatment response; (2) five genetic loci (LINC01412, PHACTR1, CDKN2B, ATXN2, KCNE2) with effects on CAD and SSRIs treatment response. Our findings implicate that the genetic variants of CAD and obesity are linked to SSRIs treatment response in MDD. A better SSRIs treatment response might be achieved through a stratified allocation of treatment for MDD patients with a genetic risk for obesity or CAD.

BACKGROUND Although group-based intensive outpatient programs (IOPs) are a level of care commonly utilized by adults with serious mental illness, few studies have examined the acceptability of group-based IOPs that required rapid transition to a telemental health (TMH) format during the COVID-19 pandemic. OBJECTIVE The aim of this study was to evaluate patient satisfaction and future recommendations for a group-based IOP that was transitioned to a TMH format during the COVID-19 pandemic. METHODS A 17-item patient satisfaction questionnaire was completed by patients at discharge and covered 3 areas: IOP TMH satisfaction, future recommendations, and video technology challenges. Descriptive and content analyses were conducted for the quantitative and open-ended questions, respectively. RESULTS A total of 76 patients completed the program in 2020. A subset of patients (n=40, 53%) responded to the survey at program discharge. The results indicated that the patients were satisfied overall with the TMH program format; 50% (n=20) of the patients preferred the program continue offering the TMH format, and the rest preferred returning to in-person formats after the pandemic. The patients indicated the elements of the program that they found most valuable and provided recommendations for future program improvement. CONCLUSIONS Overall, adults with serious mental illness reported high satisfaction with the group-based IOP delivered via TMH. Health care systems may want to consider offering both TMH and in-person formats regardless of the state of the pandemic. Patients’ feedback on future improvements should be considered to help ensure long-term success.

Selective serotonin reuptake inhibitors (SSRIs) are the first-line treatment for major depressive disorder (MDD), yet their mechanisms of action are not fully understood and their therapeutic benefit varies among individuals. We used a targeted metabolomics approach utilizing a panel of 180 metabolites to gain insights into mechanisms of action and response to citalopram/escitalopram. Plasma samples from 136 participants with MDD enrolled into the Mayo Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) were profiled at baseline and after 8 weeks of treatment. After treatment, we saw increased levels of short-chain acylcarnitines and decreased levels of medium-chain and long-chain acylcarnitines, suggesting an SSRI effect on β-oxidation and mitochondrial function. Amines—including arginine, proline, and methionine sulfoxide—were upregulated while serotonin and sarcosine were downregulated, suggesting an SSRI effect on urea cycle, one-carbon metabolism, and serotonin uptake. Eighteen lipids within the phosphatidylcholine (PC aa and ae) classes were upregulated. Changes in several lipid and amine levels correlated with changes in 17-item Hamilton Rating Scale for Depression scores (HRSD17). Differences in metabolic profiles at baseline and post-treatment were noted between participants who remitted (HRSD17 ≤ 7) and those who gained no meaningful benefits (17). Remitters exhibited (a) higher baseline levels of C3, C5, alpha-aminoadipic acid, sarcosine, and serotonin; and (b) higher week-8 levels of PC aa C34:1, PC aa C34:2, PC aa C36:2, and PC aa C36:4. These findings suggest that mitochondrial energetics—including acylcarnitine metabolism, transport, and its link to β-oxidation—and lipid membrane remodeling may play roles in SSRI treatment response.

Selective serotonin reuptake inhibitors (SSRIs) are the first-line treatment for major depressive disorder (MDD), yet their mechanisms of action are not fully understood and their therapeutic benefit varies among individuals. We used a targeted metabolomics approach utilizing a panel of 180 metabolites to gain insights into mechanisms of action and response to citalopram/escitalopram. Plasma samples from 136 participants with MDD enrolled into the Mayo Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) were profiled at baseline and after 8 weeks of treatment. After treatment, we saw increased levels of short-chain acylcarnitines and decreased levels of medium- and long-chain acylcarnitines, suggesting an SSRI effect on β-oxidation and mitochondrial function. Amines – including arginine, proline, and methionine-sulfoxide – were upregulated while serotonin and sarcosine were downregulated, suggesting an SSRI effect on urea cycle, one-carbon metabolism and serotonin uptake. Eighteen lipids within the phosphatidylcholine (PC aa and ae) classes were upregulated. Changes in several lipid and amine levels correlated with changes in 17-item Hamilton Rating Scale for Depression scores (HRSD17). Differences in metabolic profiles at baseline and post-treatment were noted between participants who remitted (HRSD17≤7) and those who gained no meaningful benefits (17). Remitters exhibited a) higher baseline levels of C3, C5, alpha-aminoadipic acid, sarcosine and serotonin; and b) higher week-8 levels of PC aa C34:1, PC aa C34:2, PC aa C36:2 and PC aa C36:4. These findings suggest that mitochondrial energetics – including acylcarnitine metabolism, transport and its link to β-oxidation – and lipid membrane remodeling may play roles in SSRI treatment response.

Glutamatergic dysregulation is implicated in the neurobiology of mood disorders. This study investigated the relationship between the anterior cingulate cortex (AC) glutamate, as measured by proton magnetic resonance spectroscopy (1H-MRS), and single-nucleotide polymorphisms (SNPs) from four genes (GLUL, SLC1A3, SLC1A2, and SLC1A7) that regulate the extracellular glutamate in 26 depressed patients with major depressive disorder (MDD; n = 15) and bipolar disorder (BD; n = 11). Two SNPs (rs3812778 and rs3829280), in perfect linkage disequilibrium, in the 3′ untranslated region of the EAAT2 gene SLC1A2, were associated with AC glutamate, with minor allele carriers having significantly higher glutamate levels (p CD44 localized downstream of SLC1A2 on chromosome 11. Finally, we tested the disease relevance of these SNPs in a large group of depressed patients [MDD (n = 458); BD (n = 1473)] and found that minor allele carriers had a significantly higher risk for rapid cycling (p = 0.006). Further work is encouraged to delineate the functional impact of excitatory amino acid transporter genetic variation on CD44 associated physiology and glutamatergic neurotransmission, specifically glutamate–glutamine cycling, and its contribution to subphenotypes of mood disorders.

BackgroundAcylcarnitines have important functions in mitochondrial energetics and β-oxidation, and have been implicated to play a significant role in metabolic functions of the brain. This retrospective study examined whether plasma acylcarnitine profiles can help biochemically distinguish the three phenotypic subtypes of major depressive disorder (MDD)—(core depression (CD+), anxious depression (ANX+), and neurovegetative symptoms of melancholia (NVSM+))—following treatment with a selective serotonin reuptake inhibitor (SSRI).MethodsDepressed outpatients (n=240) from the Mayo Clinic Pharmacogenomics Research Network were treated with citalopram or escitalopram for eight weeks. Plasma samples collected at baseline and eight weeks post-treatment were profiled for multiple-, short-, medium- and long-chain acylcarnitine levels using AbsoluteIDQ®p180-Kit and LC-MS. Linear mixed effects models were used to examine whether acylcarnitine levels discriminate the clinical phenotypes at baseline or eight weeks post-treatment, and whether temporal changes in acylcarnitine profiles differ between groups.ResultsAt baseline, significantly lower concentrations of short- and long-chain acylcarnitines were found in CD+ and NVSM+ compared to ANX+, and the short-chain acylcarnitines remained lower after eight weeks. At eight weeks, the medium- and long-chain acylcarnitines were significantly lower in NVSM+ compared to ANX+. Regarding changes baseline to week eight, short-chain acylcarnitine levels significantly increased in CD+ and ANX+, and medium- and long-chain acylcarnitines significantly decreased in NVSM+ and CD+.ConclusionsIn depressed patients treated with SSRIs, β-oxidation and mitochondrial energetics as evaluated by levels and changes in acylcarnitines may provide the biochemical basis of the clinical heterogeneity of MDD, especially when combined with clinical characteristics.

Millions of patients suffer from major depressive disorder (MDD), but many do not respond to selective serotonin reuptake inhibitor (SSRI) therapy. We used a pharmacometabolomics-informed pharmacogenomics research strategy to identify genes associated with metabolites that were related to SSRI response. Specifically, 306 MDD patients were treated with citalopram or escitalopram and blood was drawn at baseline, 4 and 8 weeks for blood drug levels, genome-wide single nucleotide polymorphism (SNP) genotyping and metabolomic analyses. SSRI treatment decreased plasma serotonin concentrations (P

IMPORTANCE: Infection-associated immune activation and inflammation are increasingly recognized in the pathophysiology of bipolar disorder. OBJECTIVE: To determine whether antibodies to common infectious agents, including cytomegalovirus (CMV), Toxoplasma gondii, and measles, as well as the inflammatory marker C-reactive protein, in serum samples differ between patients with bipolar disorder and control individuals without bipolar disorder. DESIGN, SETTING, AND PARTICIPANTS: In this case-control study, antibody titers were measured in serum samples from 1207 patients with bipolar disorder and 745 controls that were obtained from biobanks with participating sites in Rochester and Minneapolis, Minnesota (n = 1537), and Cincinnati, Ohio (n = 415), from January 5, 2009, through May 12, 2014. A subset of case patients and controls from Minnesota were matched by age, sex, and educational level. Bipolar type, age at onset, and history of psychosis were assessed for case patients as well as current drug treatment at the time of blood sample obtainment from the biobank. Data were analyzed from February 5, 2018, to January 4, 2019. EXPOSURES: The CMV and T gondii antibodies with IgM titers were expressed as z scores and IgG titers dichotomized into seropositive and seronegative based on expected prevalence in the US population and further classified based on the joint CMV-positive/T gondii–negative IgG status, C-reactive protein z score, and drug treatments with antitoxoplasma activity. MAIN OUTCOMES AND MEASURES: Patients were stratified by bipolar disorder type I or type II, nonearly (>19 years of age) and early (≤19 years of age) onset, and history of psychosis during mania or no psychosis. RESULTS: Of 1207 patients with bipolar disorder (mean [SD] age, 43.2 [15.1] years; 742 [61.5%] female), the CMV-positive/T gondii–negative IgG status was significantly higher (odds ratio [OR], 1.33; 95% CI, 1.09-1.62; P = .004) compared with that in the 745 controls (mean [SD] age, 44.5 [15.5] years; 444 [59.6%] female). The CMV-positive/T gondii–negative IgG status was associated with bipolar cases type I (OR, 1.41; 95% CI, 1.14-1.75; P = .001), nonearly age at onset (OR, 1.41; 95% CI, 1.16-1.72; P = .001), and history of manic psychosis (OR, 1.46; 95% CI, 1.13-1.88; P = .004). Patients with bipolar disorder who received drug treatment with antitoxoplasma activity (n = 272) had significantly lower T gondii IgM titers (median, 1.59; interquartile range, 1.30-2.07) compared with those (n = 900) who did not receive this treatment (median, 1.69; interquartile range, 1.35-2.25) (P = .03). CONCLUSIONS AND RELEVANCE: In this sample, increased long-term antibody response to CMV and decreased long-term antibody response to T gondii were associated with bipolar disorder and the subphenotypes of bipolar type I, nonearly disease onset, and manic psychosis. Further work appears to be needed to better understand genetic vs environmental disease risk and infection or immune activation contribution to overall disease pathogenesis with particular reference to disease onset.

Selective serotonin reuptake inhibitors (SSRIs) are the most prescribed antidepressants. They regulate serotonergic neurotransmission, but it remains unclear how altered serotonergic neurotransmission may contribute to the SSRI resistance observed in approximately 30% of major depressive disorder (MDD) patients. Patient stratification based on pharmacological responsiveness and the use of patient-derived neurons may make possible the discovery of disease-relevant neural phenotypes. In our study from a large cohort of well-characterized MDD patients, we have generated induced pluripotent stem cells (iPSCs) from SSRI-remitters and SSRI-nonremitters. We studied serotonergic neurotransmission in patient forebrain neurons in vitro and observed that nonremitter patient-derived neurons displayed serotonin-induced hyperactivity downstream of upregulated excitatory serotonergic receptors, in contrast to what is seen in healthy and remitter patient-derived neurons. Our data suggest that postsynaptic forebrain hyperactivity downstream of SSRI treatment may play a role in SSRI resistance in MDD.

We assessed the impact of comorbid depression and anxiety disorders as well as positive and negative emotional states on alcohol consumption in alcohol dependent men and women.Per day alcohol consumption during 90 days before enrolment was assessed by the Time Line Follow Back (TLFB) in 287 men and 156 women meeting DSM-IV-TR criteria for alcohol dependence. Propensity to drink in negative/positive emotional states was assessed using the Inventory of Drug Taking Situations (IDTS). Psychiatric comorbidities, including major depressive disorder (MDD), substance-induced depression (SID), anxiety disorders (AnxD), or substance-induced anxiety (SIA) were identified by Psychiatric Research Interview of Substance and Mood Disorders (PRISM).In the combined group, increased number of drinks per day and number of heavy drinking days correlated with increased IDTS scores (all p 0.0001), while the lifetime history of MDD was associated with fewer drinking days (p = 0.045) but not average number of drinks per day. Male sex was associated with higher alcohol consumption per day (p 0.0001), but not with the number of drinking days (p 0.05). Lifetime MDD history was associated with less drinking days (p = 0.0084) and less heavy drinking days (p = 0.021) in alcohol dependent men, while current MDD was associated with higher alcohol use per day in alcohol dependent women (p = 0.044).Our findings suggest that emotional states and lifetime MDD history have sex-specific impact on alcohol use in alcohol dependent men and women. The mechanisms underlying these findings and their relevance to treatment outcomes need to be examined in future studies.

Background Substantial research progress can be achieved if available clinical datasets can be mapped to the National Institute of Mental Health Research-Domain-Criteria (RDoC) constructs. This mapping would allow investigators to both explore more narrowly defined clinical phenotypes and the relationship of these phenotypes to biological markers and clinical outcomes approximating RDoC criteria. Methods Using expert review and consensus, we defined four major depression phenotypes based on specific RDoC constructs. Having matched these constructs to individual items from the Hamilton Depression Rating Scale and Quick Inventory of Depressive Symptomatology, we identified subjects meeting criteria for each of these phenotypes from two large clinical trials of patients treated for major depression. In a post hoc analysis, we evaluated the overall treatment response based on the phenotypes: Core Depression (CD), Anxiety (ANX), and Neurovegetative Symptoms of Melancholia (NVSM) and Atypical Depression (NVSAD). Results The phenotypes were prevalent (range 10.5–52.4%, 50% reduction range 51.9–82.9%) and tracked with overall treatment response. Although the CD phenotype was associated with lower rates of remission in both cohorts, this was mainly driven by baseline symptom severity. However, when controlling for baseline severity, patients with the ANX phenotype had a significantly lower rate of remission. Limitations The lack of replication between the studies of the phenotypes’ treatment prediction value reflects important variability across studies that may limit generalizability. Conclusion Further work evaluating biological markers associated with these phenotypes is needed for further RDoC concept development.

Major depressive disorder (MDD) is a heterogeneous disease. Efforts to identify biomarkers for sub-classifying MDD and antidepressant therapy by genome-wide association studies (GWAS) alone have generally yielded disappointing results. We applied a metabolomics-informed genomic research strategy to study the contribution of genetic variation to MDD pathophysiology by assaying 31 metabolites, including compounds from the tryptophan, tyrosine, and purine pathways, in plasma samples from 290 MDD patients. Associations of metabolite concentrations with depressive symptoms were determined, followed by GWAS for selected metabolites and functional validation studies of the genes identified. Kynurenine (KYN), the baseline plasma metabolite that was most highly associated with depressive symptoms, was negatively correlated with severity of those symptoms. GWAS for baseline plasma KYN concentrations identified SNPs across the beta-defensin 1 (DEFB1) and aryl hydrocarbon receptor (AHR) genes that were cis-expression quantitative trait loci (eQTLs) for DEFB1 and AHR mRNA expression, respectively. Furthermore, the DEFB1 locus was associated with severity of MDD symptoms in a larger cohort of 803 MDD patients. Functional studies demonstrated that DEFB1 could neutralize lipopolysaccharide-stimulated expression of KYN-biosynthesizing enzymes in monocytic cells, resulting in altered KYN concentrations in the culture media. In addition, we demonstrated that AHR was involved in regulating the expression of enzymes in the KYN pathway and altered KYN biosynthesis in cell lines of hepatocyte and astrocyte origin. In conclusion, these studies identified SNPs that were cis-eQTLs for DEFB1 and AHR and, which were associated with variation in plasma KYN concentrations that were related to severity of MDD symptoms.

Background and Aims Depression and anxiety are often comorbid with alcoholism and contribute to craving and relapse. We aimed to estimate the prevalence of life-time diagnoses of major depressive disorder (MDD), substance-induced depression (SID), anxiety disorder (AnxD) and substance-induced anxiety (SIA), the effects of these comorbidities on the propensity to drink in negative emotional states (negative craving), and test whether these effects differ by sex. Design Secondary analyses of baseline data collected in a single-arm study of pharmacogenetic predictors of acamprosate response. Setting Academic medical center and affiliated community-based treatment programs in the American upper mid-west. Participants A total of 287 males and 156 females aged 18–80 years, meeting DSM-IV criteria for alcohol dependence. Measurements The primary outcome measure was ‘propensity to drink in negative emotional situations’ (determined by the Inventory of Drug Taking Situations) and the key predictors/covariates were sex and psychiatric comorbidities, including MDD, SID, AnxD and SIA (determined by Psychiatric Research Interview of Substance and Mood Disorders). Findings The prevalence of the MDD, SID and AnxD was higher in females compared with males (33.1 versus 18.4%, 44.8 versus 26.4% and 42.2 versus 27.4%, respectively; P

BackgroundPsychiatric comorbidities and alcohol craving are known contributors to differences in alcohol consumption patterns.MethodsUnivariate and multivariable linear regression models were used to examine the association and interactions between the Inventory of Drug Taking Situations (IDTS) negative, positive and temptation sub-scale scores, sex, as well as co-morbid depression and anxiety determined by Psychiatric Research Interview of Substance and Mood Disorders (PRISM) with alcohol consumption measured by Time Line Follow Back (TLFB) during preceding 90 days in 287 males and 156 females meeting DSM-IV criteria for alcohol dependence.ResultsIDTS positive, negative and temptation scores were strongly associated with increased alcohol consumption measures including the number of drinks per day and number of drinking days per week (P < 0.0001). Male sex was associated with higher amount of alcohol consumption per drinking day (P < 0.001), but not with the number of drinking days per week (P > 0.05). In men, lifetime history of depression was associated with fewer drinking days (P = 0.0084) and fewer hazardous drinking days (P = 0.0214) but not with differences in daily alcohol consumption. In women, depression history was not significantly associated with alcohol consumption measures. Post-hoc sex-stratified analyses suggested that the association of the negative IDTS score with total amount of alcohol consumed by men may be modified (decreased) by lifetime depression history. We found no associations of alcohol consumption measures with anxiety or substance-induced depression.DiscussionDecreased frequency of drinking in male alcoholics with lifetime depression history is unexpected. This finding emphasizes the complex relationships between alcoholism and depression, which require further investigation.Disclosure of interestThe authors have not supplied their declaration of competing interest.

Background Heavy alcohol use is causally associated with liver dysfunction. Prior genome wide association studies (GWAS) identified single nucleotide polymorphisms (SNPs) associated with liver cirrhosis or elevation of liver enzymes (including aspartate aminotransferase or AST and alanine aminotransferase or ALT) in alcohol dependent subjects. Yet, it is possible that effects of SNPs on liver function may depend on the extent of recent alcohol exposure, which was not investigated in these studies. To address this gap in our knowledge, we investigated SNP-by-consumption interaction effects on the levels of three liver enzymes (AST, ALT and gamma-glutamyl transferase or GGT) commonly used in clinical practice to assess liver function in alcohol dependent subjects Methods Self-reported alcohol consumption during previous 30 days (measured by Timeline Follow back), DNA and plasma samples for measurement of AST, ALT and GGT levels were collected from 480 alcohol dependent subjects treated in community-based treatment programs. Genotyping was conducted using Illumina HumanCore array. Multivariable linear regression models were used to assess the effects of SNP-by-consumption interaction on ALT, AST and GGT levels. Results Genome-wide significant evidence of consumption-interaction effects on AST (p Discussion Genomic location of our top association findings indicates their potential involvement in the essential cellular function, which may also be relevant for alcohol-related liver damage. Specifically, EXOSC10 gene is a putative catalytic component of the RNA exosome complex involved in proper maturation of stable RNA species such as rRNA, snRNA and snoRNA as well as elimination of RNA processing by-products. Moreover, the top SNP in ALT analysis (EXOSC10 rs2258621) might be a blood eQTL for MTOR, which is a serine/threonine protein kinase, belonging to a family of kinases mediating cellular responses to stresses such as DNA damage and nutrient deprivation. Similarly, GALNT2 encodes protein involved in metabolism and O-linked glycosylation pathways, while PDE9A encodes protein involved in signal transduction by regulating the intracellular concentration of cAMP and cGMP. Replication in the independent sample as well as investigation of the functional mechanisms behind these associations needs to follow.

The decision regarding whether to initiate treatment with an SSRI for patients with depression is a common and important question for both patients and clinicians. Multiple clinical efficacy trials have demonstrated superiority of antidepressants to placebo.[1] Recently there has been increased debate about the effectiveness of antidepressants especially among patients with mild to moderate depression.[2–4] Parker in “Antidepressants on trial: how valid is the evidence?” discusses the concerns about using pharmaceutical registration efficacy trials to answer this question.[5] He underscores the exclusion of patients with documented medical and psychiatric co-morbidity, and the method of recruiting patients as important limitations in the generalizability of these studies. He also discusses the potential impact of heterogeneity within depressed populations which include patients with more classic biologic forms of depression such as melancholia and patients with more acute and situationally related depressive symptoms. Identification of subgroups more likely to reach remission or otherwise benefit from treatment is a critical clinical question. The aim of the Pharmacogenomic Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) is to identify subgroups of patients most likely to benefit from SSRIs. The PGRN-AMPS was designed to assess clinical outcomes of patients with major depressive disorder (MDD) treated with either citalopram or escitalopram, and to investigate genetic factors associated with these outcomes. This report describes the clinical outcomes following treatment in 529 subjects and compares these treatment outcomes with those achieved in the first phase of the Sequence Treatment Alternatives to Relieve Depression Study (STAR*D). As in the STAR*D study,[6] the primary outcome measures in the PGRN-AMPS were remission defined as a Quick Inventory of Depressive Symptomatology Clinician Rated (QIDS-C16)[7] score of 5 or less and response defined as at least a 50% reduction in the QIDS-C16 score from baseline. However, unlike the STAR*D study, DNA and plasma were collected for all subjects and drug serum levels were monitored over the course of treatment. Blood drug levels were examined to assess medication adherence. The availability of DNA samples made it possible to verify self-reported gender and ethnicity which has rarely been done in depression efficacy and effectiveness studies. While STAR*D was designed to be an effectiveness trial, data from this study have been used to address pharmacogenomic questions.[8, 9] In contrast, the PGRN-AMPS was designed to be a pharmacogenomic study and was conducted by a single research team within an integrated health care system.

Acamprosate supports abstinence in some alcohol-dependent subjects, yet predictors of response are unknown. To identify response biomarkers, we investigated associations of abstinence length with polymorphisms in candidate genes in glycine and glutamate neurotransmission pathways and genes previously implicated in acamprosate response. Association analyses were conducted in the discovery sample of 225 alcohol-dependent subjects treated with acamprosate for 3 months in community-based treatment programs in the United States. Data from 110 alcohol-dependent males treated with acamprosate in the study PREDICT were used for replication of the top association findings. Statistical models were adjusted for relevant covariates, including recruitment site and baseline clinical variables associated with response. In the discovery sample, shorter abstinence was associated with increased intensity of alcohol craving and lower number of days between the last drink and initiation of acamprosate treatment. After adjustment for covariates, length of abstinence was associated with the GRIN2B rs2058878 (P = 4.6 x 10(-5)). In the replication sample, shorter abstinence was associated with increased craving, increased depressive mood score and higher alcohol consumption. Association of abstinence length with GRIN2B rs2058878 was marginally significant (P = 0.0675); as in the discovery sample, the minor A allele was associated with longer abstinence. Furthermore, rs2300272, which is in strong linkage disequilibrium with rs2058878, was also associated with abstinence length (P = 0.049). This is the first report of a replicated association of genetic markers with the length of abstinence in acamprosate-treated alcoholics. Investigation of the underlying mechanisms of this association and its usefulness for individualized treatment selection should follow.

To investigate the attitudes among mental health professionals regarding the use of genetic testing. Psychiatrists and other mental health professionals (N=41) who were enrolled in a week-long course in psychiatric genomics completed questionnaires before and after the course designed to assess how diagnostic genetic tests should be used and the value of pharmacogenomic testing for clinical practice. Only 5% of the course participants knew their genotype for the CYP 2D6 and CYP 2C19 genes at the time they participated in the course. However, after completing the course, 95% of the participants who had not been tested responded that they would be tested if genotyping was provided at no cost. Most of the participants reported that adults have the right to know their genotypes. Specifically, a majority of participants also reported that adults should have access to information regarding their genetic predispositions to both Huntington’s disease and Alzheimer’s disease. A majority of participants believed that parents had the right to know the genotypes of their children and that adolescents should have access to their genotypes if they had parental permission or were emancipated minors. However, only 29% of participants reported that children ages 6 to 12 should have access to the results of their genotyping. Continuing medical educational programs can provide an effective and informative opportunity to develop a better understanding of contemporary perspectives of practicing clinicians. Despite some variability in beliefs regarding the implications of age and diagnosis for making genetic testing decisions, a majority of course participants reported that they would choose to be genotyped for two drug metabolizing enzyme genes. Furthermore, they felt that, in most circumstances, adults should be permitted to know their genotype.

Response to treatment with selective serotonin reuptake inhibitors (SSRIs) varies considerably between patients. The International SSRI Pharmacogenomics Consortium (ISPC) was formed with the primary goal of identifying genetic variation that may contribute to response to SSRI treatment of major depressive disorder. A genome-wide association study of 4-week treatment outcomes, measured using the 17-item Hamilton Rating Scale for Depression (HRSD-17), was performed using data from 865 subjects from seven sites. The primary outcomes were percent change in HRSD-17 score and response, defined as at least 50% reduction in HRSD-17. Data from two prior studies, the Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomics Study (PGRN-AMPS) and the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study, were used for replication, and a meta-analysis of the three studies was performed (N=2394). Although many top association signals in the ISPC analysis map to interesting candidate genes, none were significant at the genome-wide level and the associations were not replicated using PGRN-AMPS and STAR*D data. Top association results in the meta-analysis of response included single-nucleotide polymorphisms (SNPs) in the HPRTP4 (hypoxanthine phosphoribosyltransferase pseudogene 4)/VSTM5 (V-set and transmembrane domain containing 5) region, which approached genome-wide significance (P=5.03E−08) and SNPs 5’ upstream of the neuregulin-1 gene, NRG1 (P=1.20E−06). NRG1 is involved in many aspects of brain development, including neuronal maturation and variations in this gene have been shown to be associated with increased risk for mental disorders, particularly schizophrenia. Replication and functional studies of these findings are warranted.

Background We recently identified association between GRIN2B rs2058878 variant and abstinence length in acamprosate-treated alcoholics (Karpyak et al. 2014). Here we present results of additional analyses exploring associations in the same sample (225 alcoholics treated with acamprosate for three months) at the gene and gene-set levels, for 12 genes involved in glycine signaling, 4 genes involved in glutamate reuptake, synthesis and degradation and 7 genes encoding NMDA receptor subunits. Methods After adjustment for relevant covariates, gene-level tests were performed using principal components (PC) analysis. Gene-set analyses were performed using the PC-Gamma approach with varying soft truncation threshold (STT) for the Gamma method for combining gene-level p-values. Results Shorter abstinence was associated with increased intensity of alcohol craving and lower number of days between last drink and initiation of acamprosate treatment. After adjustment for covariates, we observed nominally significant association of abstinence length with variation in the AMT (p=0.024), GRIN3A (p=0.016) and SHMT2 (p=0.039) genes, and marginally significant evidence for association with the GRIN2B (p=0.067) and GLRB (p=0.060) genes. At the gene-set level, association of abstinence length with variation in the glycine pathway was nominally significant (p=0.042 with STT=0.37). Marginal evidence of association with abstinence length was also observed for variation in the NMDA-receptor subunits (p Discussion Our findings suggest association of abstinence length in acamprosate-treated alcoholics with variation in the glycine signaling pathway and genes encoding NMDA receptor subunits. Investigation of the mechanisms underlying these associations and their usefulness for individualized treatment selection should follow.