Identifying genetic differences between bipolar disorder and major depression through multiple GWAS.

Background: Accurate diagnosis of bipolar disorder (BD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A key reason is that the first manic episode is often preceded by a depressive one, making it difficult to distinguish BD from unipolar major depressive disorder (MDD). Aims: Here, we use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores that may aid early differential diagnosis. Methods: Based on individual genotypes from case-control cohorts of BD and MDD shared through the Psychiatric Genomics Consortium, we compile case-case-control cohorts, applying a careful merging and quality control procedure. In a resulting cohort of 51,149 individuals (15,532 BD cases, 12,920 MDD cases and 22,697 controls), we perform a variety of GWAS and polygenic risk scores (PRS) analyses. Results: While our GWAS is not well-powered to identify genome-wide significant loci, we find significant SNP-heritability and demonstrate the ability of the resulting PRS to distinguish BD from MDD, including BD cases with depressive onset. We replicate our PRS findings, but not signals of individual loci in an independent Danish cohort (iPSYCH 2015 case-cohort study, N=25,966). We observe strong genetic correlation between our case-case GWAS and that of case-control BD. Conclusions: We find that MDD and BD, including BD with a depressive onset, are genetically distinct. Further, our findings support the hypothesis that Controls - MDD - BD primarily lie on a continuum of genetic risk. Future studies with larger and richer samples will likely yield a better understanding of these findings and enable the development of better genetic predictors distinguishing BD and, importantly, BD with depressive onset from MDD.

Focal adhesion is associated with lithium response in bipolar disorder: evidence from a network-based multi-omics analysis.

Lithium (Li) is one of the most effective drugs for treating bipolar disorder (BD), however, there is presently no way to predict response to guide treatment. The aim of this study is to identify functional genes and pathways that distinguish BD Li responders (LR) from BD Li non-responders (NR). An initial Pharmacogenomics of Bipolar Disorder study (PGBD) GWAS of lithium response did not provide any significant results. As a result, we then employed network-based integrative analysis of transcriptomic and genomic data. In transcriptomic study of iPSC-derived neurons, 41 significantly differentially expressed (DE) genes were identified in LR vs NR regardless of lithium exposure. In the PGBD, post-GWAS gene prioritization using the GWA-boosting (GWAB) approach identified 1119 candidate genes. Following DE-derived network propagation, there was a highly significant overlap of genes between the top 500- and top 2000-proximal gene networks and the GWAB gene list (Phypergeometric = 1.28E-09 and 4.10E-18, respectively). Functional enrichment analyses of the top 500 proximal network genes identified focal adhesion and the extracellular matrix (ECM) as the most significant functions. Our findings suggest that the difference between LR and NR was a much greater effect than that of lithium. The direct impact of dysregulation of focal adhesion on axon guidance and neuronal circuits could underpin mechanisms of response to lithium, as well as underlying BD. It also highlights the power of integrative multi-omics analysis of transcriptomic and genomic profiling to gain molecular insights into lithium response in BD.

Correction of depression-associated circadian rhythm abnormalities is associated with lithium response in bipolar disorder.

BACKGROUND: Bipolar disorder (BD) is characterized by episodes of depression and mania and disrupted circadian rhythms. Lithium is an effective therapy for BD, but only 30%-40% of patients are fully responsive. Preclinical models show that lithium alters circadian rhythms. However, it is unknown if the circadian rhythm effects of lithium are essential to its therapeutic properties. METHODS: In secondary analyses of a multi-center, prospective, trial of lithium for BD, we examined the relationship between circadian rhythms and therapeutic response to lithium. Using standardized instruments, we measured morningness, diurnal changes in mood, sleep, and energy (circadian rhythm disturbances) in a cross-sectional study of 386 BD subjects with varying lithium exposure histories. Next, we tracked symptoms of depression and mania prospectively over 12 weeks in a subset of 88 BD patients initiating treatment with lithium. Total, circadian, and affective mood symptoms were scored separately and analyzed. RESULTS: Subjects with no prior lithium exposure had the most circadian disruption, while patients stable on lithium monotherapy had the least. Patients who were stable on lithium with another drug or unstable on lithium showed intermediate levels of disruption. Treatment with lithium for 12 weeks yielded significant reductions in total and affective depression symptoms. Lithium responders (Li-Rs) showed improvement in circadian symptoms of depression, but non-responders did not. There was no difference between Li-Rs and nonresponders in affective, circadian, or total symptoms of mania. CONCLUSIONS: Exposure to lithium is associated with reduced circadian disruption. Lithium response at 12 weeks was selectively associated with the reduction of circadian depressive symptoms. We conclude that stabilization of circadian rhythms may be an important feature of lithium's therapeutic effects. CLINICAL TRIALS REGISTRY: NCT0127253.

Clinical predictors of non-response to lithium treatment in the Pharmacogenomics of Bipolar Disorder (PGBD) study.

BACKGROUND: Lithium is regarded as a first-line treatment for bipolar disorder (BD), but partial response and non-response commonly occurs. There exists a need to identify lithium non-responders prior to initiating treatment. The Pharmacogenomics of Bipolar Disorder (PGBD) Study was designed to identify predictors of lithium response. METHODS: The PGBD Study was an eleven site prospective trial of lithium treatment in bipolar I disorder. Subjects were stabilized on lithium monotherapy over 4 months and gradually discontinued from all other psychotropic medications. After ensuring a sustained clinical remission (defined by a score of ≤3 on the CGI for 4 weeks) had been achieved, subjects were followed for up to 2 years to monitor clinical response. Cox proportional hazard models were used to examine the relationship between clinical measures and time until failure to remit or relapse. RESULTS: A total of 345 individuals were enrolled into the study and included in the analysis. Of these, 101 subjects failed to remit or relapsed, 88 achieved remission and continued to study completion, and 156 were terminated from the study for other reasons. Significant clinical predictors of treatment failure (p < 0.05) included baseline anxiety symptoms, functional impairments, negative life events and lifetime clinical features such as a history of migraine, suicidal ideation/attempts, and mixed episodes, as well as a chronic course of illness. CONCLUSIONS: In this PGBD Study of lithium response, several clinical features were found to be associated with failure to respond to lithium. Future validation is needed to confirm these clinical predictors of treatment failure and their use clinically to distinguish who will do well on lithium before starting pharmacotherapy.

A 7 Tesla Amygdalar-Hippocampal Shape Analysis of Lithium Response in Bipolar Disorder.

Research to discover clinically useful predictors of lithium response in patients with bipolar disorder has largely found them to be elusive. We demonstrate here that detailed neuroimaging may have the potential to fill this important gap in mood disorder therapeutics. Lithium treatment and bipolar disorder have both been shown to affect anatomy of the hippocampi and amygdalae but there is no consensus on the nature of their effects. We aimed to investigate structural surface anatomy changes in amygdala and hippocampus correlated with treatment response in bipolar disorder. Patients with bipolar disorder (N = 14) underwent lithium treatment, were classified by response status at acute and long-term time points, and scanned with 7 Tesla structural MRI. Large Deformation Diffeomorphic Metric Mapping was applied to detect local differences in hippocampal and amygdalar anatomy between lithium responders and non-responders. Anatomy was also compared to 21 healthy comparison participants. A patch of the ventral surface of the left hippocampus was found to be significantly atrophied in non-responders as compared to responders at the acute time point and was associated at a trend-level with long-term response status. We did not detect an association between response status and surface anatomy of the right hippocampus or amygdala. To the best of our knowledge, this is the first shape analysis of hippocampus and amygdala in bipolar disorder using 7 Tesla MRI. These results can inform future work investigating possible neuroimaging predictors of lithium response in bipolar disorder.

The utility of PHQ-9 and CGI-S in measurement-based care for predicting suicidal ideation and behaviors.

BACKGROUND: Measurement-based care (MBC) has emerged as an effective strategy for improving outcomes in patients with mood disorders. Suicide is a particularly devastating outcome of mood disorders. Using data from a new MBC program from the National Network of Depression Centers (NNDC), we examined whether capturing a patient-rated symptom measure, the patient health questionnaire (PHQ-9), along with a provider-rated global functioning measure, the clinical global impression scale (CGI-S), improves identification of patients at risk of suicide over using either measure alone. METHODS: A total of 126 adults with mood disorders from nine sites in the NNDC completed the PHQ-9 and CGI-S and had at least one subsequent visit where they completed the Columbia-suicide severity rating scale (C-SSRS). The PHQ-9 (≥10) and CGI-S (≥4) were dichotomized at commonly accepted severity thresholds. Associations of the PHQ-9 and CGI-S with suicidal ideation or behavior were examined using Firth's logistic regression to accommodate small samples while controlling for age, sex, race, and diagnosis. RESULTS: Patients who scored higher on only the PHQ-9 or CGI-S were not significantly more likely to experience subsequent suicidal ideation or behaviors. However, patients who scored higher on both the PHQ-9 and CGI-S were significantly more likely to experience suicidal ideation (OR = 4.70, p = 0.0005) and suicidal behaviors (OR = 25.38, p = 0.0003). DISCUSSION: Information from both patient and clinician-rated measures was better able to identify patients with mood disorders at risk for suicidal ideation and behaviors. Using both together may help reduce the risk of suicide by identifying those patients at greatest risk and allowing for more targeted interventions.

Comparing sensitivity to change using the 6-item versus the 17-item Hamilton depression rating scale in the GUIDED randomized controlled trial.

BACKGROUND: Previous research suggests that the 17-item Hamilton Depression Rating Scale (HAM-D17) is less sensitive in detecting differences between active treatment and placebo for major depressive disorder (MDD) than is the HAM-D6 scale, which focuses on six core depression symptoms. Whether HAM-D6 shows greater sensitivity when comparing two active MDD treatment arms is unknown. METHODS: This post hoc analysis used data from the intent-to-treat (ITT) cohort (N = 1541) of the Genomics Used to Improve DEpression Decisions (GUIDED) trial, a rater- and patient-blinded randomized controlled trial. GUIDED compared combinatorial pharmacogenomics-guided care with treatment as usual (TAU) in patients with MDD. Percent of symptom improvement, response rate and remission rate from baseline to week 8 were evaluated using both scales. Analyses were performed for the full cohort and for the subset of patients who at baseline were taking medications predicted by the test to have moderate or significant gene-drug interactions. A Mokken scale analysis was conducted to compare the homogeneity of HAM-D17 with that of HAM-D6. RESULTS: At week 8, the guided-care arm demonstrated statistically significant benefit over TAU when the HAM-D6 (∆ = 4.4%, p = 0.023) was used as the continuous measure of symptom improvement, but not when using the HAM-D17 (∆ = 3.2%, p = 0.069). Response rates increased significantly for guided-care compared with TAU when evaluated using both HAM-D6 (∆ = 7.0%, p = 0.004) and HAM-D17 (∆ = 6.3%, p = 0.007). Remission rates also were significantly greater for guided-care versus TAU using both measures (HAM-D6 ∆ = 4.6%, p = 0.031; HAM-D17 ∆ = 5.5%, p = 0.005). Patients in the guided-care arm who at baseline were taking medications predicted to have gene-drug interactions showed further increased benefit over TAU at week 8 for symptom improvement (∆ = 7.3%, p = 0.004) response (∆ = 10.0%, p = 0.001) and remission (∆ = 7.9%, p = 0.005) using HAM-D6. All outcomes showed continued improvement through week 24. Mokken scale analysis demonstrated the homogeneity and unidimensionality of HAM-D6, but not of HAM-D17, across treatment arms. CONCLUSIONS: The HAM-D6 scale identified a statistically significant difference in symptom improvement between combinatorial pharmacogenomics-guided care and TAU, whereas the HAM-D17 did not. The demonstrated utility of pharmacogenomics-guided treatment over TAU as detected by the HAM-D6 highlights its value for future biomarker-guided trials comparing active treatment arms. TRIAL REGISTRATION: Clinicaltrials.gov: NCT02109939. Registered 10 April 2014.

Impact of Pharmacogenomics on Clinical Outcomes for Patients Taking Medications With Gene-Drug Interactions in a Randomized Controlled Trial.

OBJECTIVE: The objective of the Genomics Used to Improve DEpression Decisions (GUIDED) trial was to evaluate the utility of pharmacogenomic testing to improve outcomes among patients with major depressive disorder (MDD) who had not responded to at least 1 prior medication trial. The objective of the present analysis was to assess outcomes for the subset of patients expected to benefit from combinatorial pharmacogenomic testing because they were taking medications with predicted gene-drug interactions. METHODS: Participants (enrolled from April 14, 2014, to February 10, 2017) had an inadequate response to at least 1 psychotropic medication in the current episode of MDD. Patients were randomized to treatment as usual (TAU) or the guided-care arm, in which clinicians had access to a combinatorial pharmacogenomic test report to inform medication selection. Patients and raters were blinded to study arm through week 8. The following outcomes were assessed using the 17-item Hamilton Depre​ssion Rating Scale (HDRS-17): symptom improvement (percent change in HDRS-17 score), response (≥ 50% decrease in HDRS-17 score), and remission (HDRS-17 score ≤ 7). In the GUIDED trial, the primary endpoint of symptom improvement did not reach significance in the intent-to-treat cohort (P = .069). Here, a post hoc analysis of patients who were taking medications subject to gene-drug interactions at baseline as predicted by combinatorial pharmacogenomic testing (N = 912) is presented. RESULTS: Among participants taking medications subject to gene-drug interactions at baseline, outcomes at week 8 were significantly improved for those in the guided-care arm compared to TAU (symptom improvement: 27.1% versus 22.1%, P = .029; response: 27.0% versus 19.0%, P = .008; remission: 18.2% versus 10.7%, P = .003). When patients who switched medications were assessed, all outcomes were significantly improved in the guided-care arm compared to TAU (P = .011 for symptom improvement, P = .011 for response, P = .008 for remission). CONCLUSIONS: By identifying and focusing on the patients with predicted gene-drug interactions, use of a combinatorial pharmacogenomic test significantly improved outcomes among patients with MDD who had at least 1 prior medication failure. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT02109939​.

Impact of pharmacogenomics on clinical outcomes in major depressive disorder in the GUIDED trial: A large, patient- and rater-blinded, randomized, controlled study.

Current prescribing practices for major depressive disorder (MDD) produce limited treatment success. Although pharmacogenomics may improve outcomes by identifying genetically inappropriate medications, studies to date were limited in scope. Outpatients (N = 1167) diagnosed with MDD and with a patient- or clinician-reported inadequate response to at least one antidepressant were enrolled in the Genomics Used to Improve DEpression Decisions (GUIDED) trial - a rater- and patient-blind randomized controlled trial. Patients were randomized to treatment as usual (TAU) or a pharmacogenomics-guided intervention arm in which clinicians had access to a pharmacogenomic test report to inform medication selections (guided-care). Medications were considered congruent ('use as directed' or 'use with caution' test categories) or incongruent ('use with increased caution and with more frequent monitoring' test category) with test results. Unblinding occurred after week 8. Primary outcome was symptom improvement [change in 17-item Hamilton Depression Rating Scale (HAM-D17)] at week 8; secondary outcomes were response (≥50% decrease in HAM-D17) and remission (HAM-D17 ≤ 7) at week 8. At week 8, symptom improvement for guided-care was not significantly different than TAU (27.2% versus 24.4%, p = 0.107); however, improvements in response (26.0% versus 19.9%, p = 0.013) and remission (15.3% versus 10.1%, p = 0.007) were statistically significant. Patients taking incongruent medications prior to baseline who switched to congruent medications by week 8 experienced greater symptom improvement (33.5% versus 21.1%, p = 0.002), response (28.5% versus 16.7%, p = 0.036), and remission (21.5% versus 8.5%, p = 0.007) compared to those remaining incongruent. Pharmacogenomic testing did not significantly improve mean symptoms but did significantly improve response and remission rates for difficult-to-treat depression patients over standard of care (ClinicalTrials.gov NCT02109939).

Chronotype and cellular circadian rhythms predict the clinical response to lithium maintenance treatment in patients with bipolar disorder.

Bipolar disorder (BD) is a serious mood disorder associated with circadian rhythm abnormalities. Risk for BD is genetically encoded and overlaps with systems that maintain circadian rhythms. Lithium is an effective mood stabilizer treatment for BD, but only a minority of patients fully respond to monotherapy. Presently, we hypothesized that lithium-responsive BD patients (Li-R) would show characteristic differences in chronotype and cellular circadian rhythms compared to lithium non-responders (Li-NR). Selecting patients from a prospective, multi-center, clinical trial of lithium monotherapy, we examined morning vs. evening preference (chronotype) as a dimension of circadian rhythm function in 193 Li-R and Li-NR BD patients. From a subset of 59 patient donors, we measured circadian rhythms in skin fibroblasts longitudinally over 5 days using a bioluminescent reporter (Per2-luc). We then estimated circadian rhythm parameters (amplitude, period, phase) and the pharmacological effects of lithium on rhythms in cells from Li-R and Li-NR donors. Compared to Li-NRs, Li-Rs showed a difference in chronotype, with higher levels of morningness. Evening chronotype was associated with increased mood symptoms at baseline, including depression, mania, and insomnia. Cells from Li-Rs were more likely to exhibit a short circadian period, a linear relationship between period and phase, and period shortening effects of lithium. Common genetic variation in the IP3 signaling pathway may account for some of the individual differences in the effects of lithium on cellular rhythms. We conclude that circadian rhythms may influence response to lithium in maintenance treatment of BD.

Mobile technology for medication adherence in people with mood disorders: A systematic review.

BACKGROUND: Medication non-adherence is a critical challenge for many patients diagnosed with mood disorders (Goodwin and Jamison, 1990). There is a need for alternative strategies that improve adherence among patients with mood disorders that are cost-effective, able to reach large patient populations, easy to implement, and that allow for communication with patients outside of in-person visits. Technology-based approaches to promote medication adherence are increasingly being explored to address this need. The aim of this paper is to provide a systematic review of the use of mobile technologies to improve medication adherence in patients with mood disorders. METHODS: A total of nine articles were identified as describing mobile technology targeting medication adherence in mood disorder populations. RESULTS: Results showed overall satisfaction and feasibility of mobile technology, and reduction in mood symptoms; however, few examined effectiveness of mobile technology improving medication adherence through randomized control trials. LIMITATIONS: Given the limited number of studies, further research is needed to determine long term effectiveness. CONCLUSIONS: Mobile technologies has the potential to improve medication adherence and can be further utilized for symptom tracking, side effects tracking, direct links to prescription refills, and provide patients with greater ownership over their treatment progress.

Test-retest reliability of a new questionnaire for the retrospective assessment of long-term lithium use in bipolar disorder.

BACKGROUND: The identification of predictors of treatment response holds tremendous potential for the improvement of clinical outcomes in bipolar disorder (BP). The goal of this project is to evaluate the test-retest reliability of a new clinical tool, the Lithium Questionnaire (LQ), for the retrospective assessment of long-term lithium use in research participants with BP. METHODS: Twenty-nine individuals with BP-I (n=27), major depression (n=1), or schizoaffective disorder (n=1) were recruited for participation. The LQ was administered to all participants at two time-points, spaced 17 months apart on average, and used to determine each subject׳s score on the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder Scale, or the Alda Scale. Scores were confirmed through a best-estimate procedure, and test-retest reliability (intra-class correlation coefficient [ICC]) of the LQ was calculated. RESULTS: The correlation between the total Alda Scale scores at the two time-points was in the moderate range (ICC=0.60). Relevant clinical factors such as age or presence of Axis I psychiatric comorbidity did not influence the reliability. LIMITATIONS: The validity of the LQ was not examined. Inclusion of two participants with non-BP diagnoses may have affected the LQ׳s reliability, but re-analysis of our data after exclusion of these participants did not influence the reliability. The absence of measures of mood and cognition at time of LQ may be a limitation of this work. CONCLUSIONS: The LQ holds promise for the standardization of the retrospective assessment of long-term treatment in BP.

Posttraumatic stress disorder increases risk for suicide attempt in adults with recurrent major depression.

BACKGROUND: Genetics of Recurrent Early-Onset Depression study (GenRED II) data were used to examine the relationship between posttraumatic stress disorder (PTSD) and attempted suicide in a population of 1,433 individuals with recurrent early-onset major depressive disorder (MDD). We tested the hypothesis that PTSD resulting from assaultive trauma increases risk for attempted suicide among individuals with recurrent MDD. METHODS: Data on lifetime trauma exposures and clinical symptoms were collected using the Diagnostic Interview for Genetic Studies version 3.0 and best estimate diagnoses of MDD, PTSD, and other DSM-IV Axis I disorders were reported with best estimated age of onset. RESULTS: The lifetime prevalence of suicide attempt in this sample was 28%. Lifetime PTSD was diagnosed in 205 (14.3%) participants. We used discrete time-survival analyses to take into account timing in the PTSD-suicide attempt relationship while adjusting for demographic variables (gender, race, age, and education level) and comorbid diagnoses prior to trauma exposure. PTSD was an independent predictor of subsequent suicide attempt (HR = 2.5, 95% CI: 1.6, 3.8; P < .0001). Neither assaultive nor nonassaultive trauma without PTSD significantly predicted subsequent suicide attempt after Bonferroni correction. The association between PTSD and subsequent suicide attempt was driven by traumatic events involving assaultive violence (HR = 1.7, 95% CI: 1.3, 2.2; P< .0001). CONCLUSIONS: Among those with recurrent MDD, PTSD appears to be a vulnerability marker of maladaptive responses to traumatic events and an independent risk factor for attempted suicide. Additional studies examining differences between those with and without PTSD on biological measures might shed light on this potential vulnerability.

Association study of serotonin pathway genes in attempted suicide.

Epidemiological studies, such as family, twin, and adoption studies, demonstrate the presence of a heritable component to both attempted and completed suicide. Some of this heritability is accounted for by the presence of comorbid psychiatric disorders, but the evidence also indicates that a portion of this heritability is specific to suicidality. The serotonergic system has been studied extensively in this phenotype, but findings have been inconsistent, possibly due to the presence of multiple susceptibility variants and/or gene-gene interactions. In this study, we genotyped 174 tag and coding single nucleotide polymorphisms (SNPs) from 17 genes within the serotonin pathway on 516 subjects with a major mood disorder and a history of a suicide attempt (cases) and 515 healthy controls, with the goal of capturing the common genetic variation across each of these candidate genes. We tested the 174 markers in single-SNP, haplotype, gene-based, and epistasis analyses. While these association analyses identified multiple marginally significant SNPs, haplotypes, genes, and interactions, none of them survived correction for multiple testing. Additional studies, including assessment in larger sample sets and deep resequencing to identify rare causal variants, may be required to fully understand the role that the serotonin pathway plays in suicidal behavior.

Genome-wide linkage and follow-up association study of postpartum mood symptoms.

OBJECTIVE: Family studies have suggested that postpartum mood symptoms might have a partly genetic etiology. The authors used a genome-wide linkage analysis to search for chromosomal regions that harbor genetic variants conferring susceptibility for such symptoms. The authors then fine-mapped their best linkage regions, assessing single nucleotide polymorphisms (SNPs) for genetic association with postpartum symptoms. METHOD: Subjects were ascertained from two studies: the NIMH Genetics Initiative Bipolar Disorder project and the Genetics of Recurrent Early-Onset Depression. Subjects included women with a history of pregnancy, any mood disorder, and information about postpartum symptoms. In the linkage study, 1,210 women met criteria (23% with postpartum symptoms), and 417 microsatellite markers were analyzed in multipoint allele sharing analyses. For the association study, 759 women met criteria (25% with postpartum symptoms), and 16,916 SNPs in the regions of the best linkage peaks were assessed for association with postpartum symptoms. RESULTS: The maximum linkage peak for postpartum symptoms occurred on chromosome 1q21.3-q32.1, with a chromosome-wide significant likelihood ratio Z score (Z(LR)) of 2.93 (permutation p=0.02). This was a significant increase over the baseline Z(LR) of 0.32 observed at this locus among all women with a mood disorder (permutation p=0.004). Suggestive linkage was also found on 9p24.3-p22.3 (Z(LR)=2.91). In the fine-mapping study, the strongest implicated gene was HMCN1 (nominal p=0.00017), containing four estrogen receptor binding sites, although this was not region-wide significant. CONCLUSIONS: This is the first study to examine the genetic etiology of postpartum mood symptoms using genome-wide data. The results suggest that genetic variations on chromosomes 1q21.3-q32.1 and 9p24.3-p22.3 may increase susceptibility to postpartum mood symptoms.

The Intensive Treatment Unit: A brief inpatient detoxification facility demonstrating good postdetoxification treatment entry.

Inpatient detoxification is frequently used to treat substance use disorders, despite consistent findings that drug use soon after detoxification is the norm. A number of lines of evidence suggest the most rational means of improving outcomes after detoxification is to improve postdetoxification treatment entry. This report presents outcomes from the Intensive Treatment Unit (ITU), a brief inpatient detoxification unit in Baltimore, MD, found to have good postdischarge treatment entry outcomes. The patients followed were predominantly male African Americans in early middle age who were sequentially admitted to the unit (N = 134) and demonstrated severe social disruption and psychiatric comorbidity. More than 80% of the patients discharged from the ITU were admitted to treatment postdetoxification, with most going to long-term residential settings or recovery houses. Success was associated with seeking residential treatment, and failure was concentrated among the minority discharged with no plan for aftercare and those seeking outpatient treatments. The report explores patient and process factors associated with these outcomes and discusses the possibility that the ITU may be a model system for improving outcomes postdetoxification.

Premenstrual mood symptoms: study of familiality and personality correlates in mood disorder pedigrees.

We sought to determine whether premenstrual mood symptoms exhibit familial aggregation in bipolar disorder or major depression pedigrees. Two thousand eight hundred seventy-six women were interviewed with the Diagnostic Interview for Genetic Studies as part of either the NIMH Genetics Initiative Bipolar Disorder Collaborative study or the Genetics of Early Onset Major Depression (GenRED) study and asked whether they had experienced severe mood symptoms premenstrually. In families with two or more female siblings with bipolar disorder (BP) or major depressive disorder (MDD), we examined the odds of having premenstrual mood symptoms given one or more siblings with these symptoms. For the GenRED MDD sample we also assessed the impact of personality as measured by the NEO-FFI. Premenstrual mood symptoms did not exhibit familial aggregation in families with BP or MDD. We unexpectedly found an association between high NEO openness scores and premenstrual mood symptoms, but neither this factor, nor NEO neuroticism influenced evidence for familial aggregation of symptoms. Limitations include the retrospective interview, the lack of data on premenstrual dysphoric disorder, and the inability to control for factors such as medication use.

Family-based association study of Neuregulin 1 with psychotic bipolar disorder.

The Neuregulin 1 gene (NRG1) has been associated with schizophrenia, and, to a lesser extent, with bipolar disorder (BP). We investigated the association of NRG1 with BP in a large family sample, and then performed analyses according to the presence of psychotic features or mood-incongruent psychotic features. We genotyped 116 tagSNPs and four Icelandic "core" SNPs in 1,199 subjects from 314 nuclear families. Of 515 BP offspring, 341 had psychotic features, and 103 had mood-incongruent psychotic features. In single-marker and sliding window haplotype analyses using FBAT, there was little association using the standard BP or mood-incongruent psychotic BP phenotypes, but stronger signals were seen in the psychotic BP phenotype. The most significant associations with psychotic BP were in haplotypes within the 5' "core" region. The strongest global P-value was across three SNPs: NRG241930-NRG243177-rs7819063 (P = 0.0016), with an undertransmitted haplotype showing an individual P = 0.0007. The most significant individual haplotype was an undertransmitted two-allele subset of the above (NRG243177-rs7819063, P = 0.0004). Additional associations with psychotic BP were found across six SNPs in a 270 kb central region of the gene. The most 3' of these, rs7005606 (P = 0.0029), is located approximately 4 kb from the type I NRG1 isoform promoter. In sum, our study suggests that NRG1 may be specifically associated with the psychotic subset of BP; however, our results should be interpreted cautiously since they do not meet correction for multiple testing and await independent replication.