Ho, Ada Man‐Choi

Abstract Background Anxiety disorders (ANX) affect 30–60% of individuals with bipolar disorder (BD), yet limited research has systematically examined clinical characteristics and treatment patterns in this comorbid population. This study investigated demographic, clinical, and pharmacotherapeutic differences between individuals with BD with and without comorbid ANX. Methods Cross-sectional data from 2,225 adults with BD enrolled in the Mayo Clinic Bipolar Disorder Biobank were analyzed. Participants were assessed for comorbid ANX, demographics, clinical characteristics, medication use, and treatment response using the Alda-A scale. Results Overall, 61% (n = 1,366) had comorbid ANX. Individuals with BD + ANX were younger (40.4 vs. 43.6 years, p < 0.001), more likely female (66.6% vs. 54.8%, p < 0.001), and exhibited higher rates of rapid cycling (64.2% vs. 45.2%, p < 0.001), suicide attempts (40.4% vs. 24.8%, p < 0.001), substance use disorders (63.5% vs. 54.8%, p < 0.001), and somatic comorbidities (MCIRS: 6.68 vs. 5.42, p < 0.001). Pharmacotherapeutically, BD + ANX individuals were less likely to receive lithium (37.1% vs. 47.8%, p = 0.005) and valproic acid (21.7% vs. 29.6%, p = 0.047), but more likely to receive antidepressants (53.8% vs. 39.5%, p < 0.001), benzodiazepines (39.9% vs. 26.6%, p < 0.001), and gabapentinoids (8.5% vs. 4.5%, p < 0.001). Notably, 17.3% of BD + ANX individuals received antidepressants without mood stabilizer coverage. Treatment response (Alda-A) scores were significantly lower in BD + ANX for lithium (4.91 vs. 6.05, p < 0.001), mood-stabilizing anticonvulsants (5.09 vs. 6.22, p < 0.001), and second-generation antipsychotics (4.67 vs. 5.73, p < 0.001). Similar patterns were observed in both BD-I and BD-II subtypes. Conclusions Individuals with BD + ANX represent a more severely affected subgroup with distinct prescribing patterns favoring antidepressants over mood stabilizers and attenuated mood stabilizers response. These findings highlight the need for anxiety-informed treatment algorithms recognizing anxiety comorbidity as a negative prognostic factor.

IntroductionAlcohol withdrawal syndrome (AWS) is among the most severe components of alcohol dependence (AD). Severe AWS, especially complicated with seizures and delirium, was a common reason for medical complications and death. The introduction of benzodiazepines decreased but did not eliminate those risks. The definition of AWS evolved in different versions of Diagnostic and Statistical Manual for Mental Disorders (DSM) from having hand tremor plus one or more other symptoms in DSM-III-R to any two or more symptoms in DSM-IV, which was retained in the current version of DSM-5.ObjectivesComparing subgroups of individuals with AUD based on AWS symptoms profile to define phenotypes for investigation of biological underpinnings of AWS phenomenology and treatment response.MethodsTreatment-seeking individuals diagnosed with DSM-IV alcohol dependence (AD; n=473; 35.5% females) were assessed with Psychiatric Research Interview for Substance and Mental Disorders (PRISM), Timeline Follow back (past 90 days) alcohol consumption, Penn Alcohol Craving Scale (PACS), Pittsburgh Sleep Quality Index (PSQI), Patient Health Questionnaire-9 (PHQ9), and General Anxiety Disorder-7 (GAD-7). Latent class analysis was used to classify subjects according to lifetime prevalence of AWS symptoms according to DSM-III-R or DSM-IV/5. Demographic and other clinical variables were compared among clusters by linear model ANOVA and chi-squared test.ResultsFour clusters were identified: subjects with (1) no history of meeting any AWS criteria (n=50); (4) with complete number of AWS symptoms, meeting both DSM definitions (n=259); and two clusters of subjects with smaller number of AWS symptoms: (3) those meeting only DSM-IV/5 criteria (n=94) and (2) those also meeting DSM-III-R criteria (n=70). Compared to cluster 2, the Cluster 3 members had higher frequency of anxiety, insomnia, and restlessness during withdrawal. The clusters also differed in the total number of drinks (p=0.021), average drinks per drinking days (p=0.013), history of anxiety disorder (p=0.006), substance-induced depression (p=0.019), and higher scores of PSQI (p<0.001), PHQ9 (p<0.001), and GAD-7 (p<0.001) with a relative increase in frequency between clusters as follows 1<2<3<4. Group 4 also had the highest percentages of subjects with history of seizure, delirium or hallucinations.ConclusionsDifferent definitions of AWS capture clusters of AD patients with different symptomatology, comorbidity and consumption patterns. Understanding of biological underpinnings behind those differences may guide improvement in personalized treatment selection.Disclosure of InterestNone Declared

Abstract Background: Responsiveness to mood-stabilizing pharmacotherapy varies in bipolar disorder (BD). We investigated clinical correlates of second-generation antipsychotic (SGA) treatment response and conducted the first genome-wide association study (GWAS), including exploratory polygenic scores (PGS), of SGA pharmacogenomic treatment response in BD. Methods: Treatment response was quantified using the Alda scale, and GWAS was performed using Alda-A score, controlling for sex, genotyping batch, and the genomic principal components. Results: The cohort included 2,159 adults with BD (1,416 BD-I, 691 BD-II, 51 schizoaffective BD), mean age 41.8 years, 62% female, 84% white, and 14% Hispanic. Nearly half (48%) were treated with SGAs. Current SGA users were younger (41.2±14.7 vs. 42.5±15.3 years, p =0.040), more likely to be Hispanic (14% vs. 11%, p =0.047), had a higher body mass index (BMI; 30.4±7.6 vs. 29.5±7.1 kg/m 2 , p =0.005). Lifetime comorbidity patterns for current SGA users include higher rates of manic psychosis (29% vs. 17%, p <0.001) and eating disorders — Anorexia Nervosa (7% vs. 4%, p =0.003), Bulimia Nervosa (7% vs. 4%, p =0.003), and Binge Eating Disorder (14% vs. 11%, p =0.030). We detected a genome-wide significant association between SGA Alda-A scores and GAS7 variants (top variant: rs202127418, β =-2.998, p =4.96E-08). However, SGA response was not significantly associated with PGS for schizophrenia, BD, and major depression (FDR>0.05). Conclusions: SGAs are frequently utilized as mood stabilizers in patients with BD and are associated with manic psychosis and eating disorders. GAS7 variants may predict SGA response, but larger, more diverse cohorts are needed for validation.

AbstractBackground and AimsSex‐related hormones and proteins may underlie sex differences in alcohol use disorder characteristics and consequences. Previous reports suggest steroid sex hormones may influence alcohol consumption behaviors while proteins that regulate their circulation levels are rarely investigated. Following up on our earlier study of individual sex‐related hormones' associations with alcohol dependence (AD), this study measured the associations between the combinations of sex‐related hormones and proteins and AD in a larger sample.DesignSex‐stratified case‐control comparison and clustering of plasma sex‐related hormone and protein levels, plus a genome‐wide association study on the AD‐associated hormone and protein combinations.SettingAddiction treatment programs in the United States.ParticipantsFour hundred treatment‐seeking recently abstained AD patients (median = 24.5 days) and 388 age‐and‐sex‐matched controls from a community biobank (male:female ≈ 2:1).MeasurementsPlasma levels of total testosterone, estrone (E1), estradiol (E2), follicle‐stimulating hormone (FSH), luteinizing hormone (LH), sex hormone binding globulin (SHBG) and albumin.FindingsIn males, we found higher E2 [β = 0.13, Punadjusted < 0.001, false discovery rate (FDR) = 0.005], progesterone (β = 0.01, Punadjusted = 0.025, FDR = 0.054), LH (β = 0.12, Punadjusted = 0.017, FDR = 0.044) and albumin (β = 0.09, Punadjusted < 0.001, FDR = 0.005) in AD patients than controls; in females, we observed lower E1 (β = −0.24, Punadjusted = 0.024, FDR = 0.113) and progesterone (β = −1.86, Punadjusted = 0.026, FDR = 0.113) and higher albumin (β = 0.18, Punadjusted < 0.001, FDR = 0.001) in AD patients than controls. Three principal components (PCs), reflecting hormone signatures, were statistically significantly associated with AD in each sex: PC1 (TT, E2 and SHBG; β = −0.15, P = 0.016), PC3 (E1, progesterone and albumin; β = 0.28, P = 0.007) and PC4 (SHBG and albumin; β = 0.34, P = 0.001) in males; PC3 (progesterone and albumin; β = −0.38, P = 0.009), PC4 (TT and albumin; β = −0.49, P = 0.001) and PC5 (TT and progesterone; β = 0.54, P = 0.004) in females. Statistically significant SNP × group associations were found in females between PC4 and polymorphisms in RP51004I9.1 (top SNP: rs6082693; P = 5.41E‐12) and in males between PC3 and a genomic locus that contained SLC35E4, DUSP18 and OSBP2 (top SNP: rs13053277; P = 1.77E‐07).ConclusionsThree sex‐related hormone and protein signatures appear to be associated with alcohol dependence in each sex. Peripheral levels of sex‐related hormones and proteins, as well as their combinations, could be altered in people with alcohol dependence who have abstained for a few weeks compared with controls, and such differences may be sex‐specific.

Abstract Objective Sex-specific differences impact vulnerability to alcohol effects, dependence (AD) and related phenotypes. Previous studies demonstrated that sex-related hormone and protein levels may contribute to those differences in sex-specific manner. However, previous studies were limited by sample size, the depths of phenotyping assessments and/or the number of hormones and proteins measured at the same time. Here, we investigated the association of the sex-related hormone (testosterone, estrogens, and progesterone) and protein (FSH, LH, SHBG, and albumin) levels with AD in males and females treated in community-based programs compared to age and sex-matched controls. We also investigated the associations of AD with the combined plasma sex-related hormone/protein “signatures” in the same groups of study subjects. Methods Sex-related hormone and protein levels were measured in plasma samples collected from 401 male and female subjects meeting DSM-IV-TR criteria for AD and 401 age and sex matched controls. Psychiatric Research Interview for Substance and Mental Disorder (PRISM) was used to capture DSM-IV diagnoses of substance use and other psychiatric disorders. All analyses were stratified by sex. Associations between each plasma sex-related hormone/protein level and AD was assessed with multivariable linear regression adjusted for age and BMI for males and age, BMI, and menopause status for females. Progesterone was defined as a continuous variable and a binary variable based on a lower laboratory detection limit of 0.1 ng/mL. We used principal component analysis to define hormone/protein signatures. Hormones and proteins with factor loadings =/&gt; |0.4| were considered important drivers for the corresponding principal components (PCs). Resulting PCs were entered into a sex-stratified logistic regression model with adjustment of age and BMI to determine which PCs were associated with AD. Results Male AD subjects had higher estradiol and albumin levels (p &lt;0.00625) as well as progesterone and LH levels (p &lt;0.05) compared to controls. Progesterone was detected in a larger proportion of AD subjects than in the controls (62.6% vs. 47.7%; p = 0.017). In females, albumin levels were significantly higher (p &lt;0.00385) while estrone and progesterone levels were lower (p &lt;0.05) in AD subjects than the controls. Total testosterone (TT) levels were relatively higher in AD subjects but differences between groups were not significant (p &gt;0.05). In males, the first PC (PC1) that accounted for the majority of data variance was significantly associated with AD (p=0.016) and was mostly driven by TT, estrone, estradiol and SHBG. PC3 (driven by albumin, progesterone and estradiol) and PC4 (driven by albumin and SHBG) were also associated with AD (p=0.007 and p&lt;0.001, respectively). In females, PC1 (driven by estrone, estradiol, SHBG) was not significantly associated with AD. However, PC3 (driven by Albumin and progesterone), PC4 (driven by TT and Albumin) and PC5 (driven by progesterone and TT), were significantly associated with AD (p=0.009, p=0.001, p=0.004, respectively). Conclusion Our findings indicate that individual hormone/protein levels as well as hormone/protein combination signatures associated with AD are different in male and female alcoholics. Future studies should investigate physiological mechanisms reflected in hormone/protein signatures captured by PC analyses.

Abstract Background Alcohol consumption behaviors and alcohol use disorder risk and presentation differ by sex, and these complex traits are associated with blood concentrations of the steroid sex hormones, testosterone and estradiol, and their regulatory binding proteins, sex hormone binding globulin (SHBG) and albumin. Genetic variation is associated with alcohol consumption and alcohol use disorder, as well as levels of steroid sex hormones and their binding proteins. Methods To assess the contribution of genetic factors to previously described phenotypic associations between alcohol-use traits and sex-hormone levels, we estimated genetic correlations (rg) using summary statistics from prior published, large sample size genome-wide association studies (GWAS) of alcohol consumption, alcohol dependence, testosterone, estradiol, SHBG, and albumin. Results For alcohol consumption, we observed positive genetic correlation (i.e. genetic effects in the same direction) with total testosterone in males (rg = 0.084, p = 0.007) and trends toward positive genetic correlation with bioavailable testosterone (rg = 0.060, p = 0.084) and SHBG in males (rg = 0.056, p = 0.086) and with albumin in a sex-combined cohort (rg = 0.082, p = 0.015); however in females, we observed positive genetic correlation with SHBG (rg = 0.089, p = 0.004) and a trend toward negative genetic correlation (i.e. genetic effects in opposite directions) with bioavailable testosterone (rg = -0.064, p = 0.032). For alcohol dependence, we observed a trend toward negative genetic correlation with total testosterone in females (rg = -0.106, p = 0.024) and positive genetic correlation with BMI-adjusted SHBG in males (rg = 0.119, p = 0.017). Several of these genetic correlations differed between females and males and were not in the same direction as the corresponding phenotypic associations. Conclusions Findings suggest that shared genetic effects may contribute to positive associations of alcohol consumption with albumin in both sexes, as well as positive associations between alcohol consumption and bioavailable testosterone and between alcohol dependence and SHBG in males. However, relative contributions of heritable and environmental factors to associations between alcohol-use traits and sex-hormone levels may differ by sex, with genetic factors contributing more in males and environmental factors contributing more in females.

AbstractAimsBrain-derived neurotrophic factor (BDNF) levels may be associated with alcohol use disorders (AUD) and alcohol consumption, correlate with sleep disturbance and be influenced by sex differences and sex hormones. These associations have not been examined in a single sample accounting for all these factors.MethodsData from 190 participants (29.4% female) with AUD were utilized. Sleep quality, craving intensity, depression, anxiety and alcohol consumption were assessed using the Pittsburgh Sleep Quality Index (PSQI), Penn Alcohol Craving Scale (PACS), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7) and Timeline Follow Back for 90 days(TLFB 90). Inventory of Drug Taking Situations (IDTS) assessed the tendency to drink in positive/negative emotional states. Serum BDNF (sBDNF) and plasma sex hormones (estrogen, progesterone, testosterone, FSH and SHBG) were measured. Pearson correlation analyses were used to examine the association between sBDNF and these measures in the entire sample and in men and women separately. Higher order interaction effects between these factors were evaluated for their association with sBDNF using a backward selection model.ResultsNo significant correlations between sBDNF levels and sex hormones, PSQI, PHQ-9, PACS, IDTS scores and alcohol consumption were found (all P-values &gt; 0.05). sBDNF levels were negatively correlated with GAD-7 scores in men (r = −0.1841; P = 0.03). When considering all quadratic and two-way interactions among PSQI, PHQ-9, GAD-7, mean and max drinks/day, number of drinking days, heavy drinking days, and sex no higher order moderating effects of sBDNF levels were found.ConclusionOur study revealed no significant associations between sBDNF and alcohol measures, sleep, depression and sex hormones suggesting limited utility as a biomarker.

AbstractMale and female human subjects show contrasting propensities to misuse drugs of addiction, including alcohol. These differences lead to different psychological and neurological consequences, such as the likelihood of developing dependence. The pattern and extent of brain damage in alcohol‐use disorder cases also varies with comorbid disease. To explore mechanisms that might underlie these outcomes, we used autopsy tissue to determine mRNA transcript expression in relation to genotype for two GABAA receptor subunit genes. We used quantitative Real‐Time PCR to measure GABRA6 and GABRA2 mRNA concentrations in dorsolateral prefrontal and primary motor cortices of alcohol‐use disorder subjects and controls of both sexes with and without liver disease who had been genotyped for these GABAA receptor subunit genes. Cirrhotic alcohol‐use disorder cases had significantly higher expression of GABRA6 and GABRA2 transcripts than either controls or non‐cirrhotic alcohol‐use disorder cases. Differences were observed between sexes, genotypes and brain regions. We show that sex differences in subjects with GABRA6 and GABRA2 variants may contribute to differences in susceptibility to alcohol‐use disorder and alcohol‐induced cirrhosis.