Evening chronotype, disordered eating behavior, and poor dietary habits in bipolar disorder.

OBJECTIVE: Our aim was to evaluate the relationship between evening chronotype, a proxy marker of circadian system dysfunction, and disordered eating behavior and poor dietary habits in individuals with bipolar disorder (BD). METHODS: In this cross-sectional study, we evaluated 783 adults with BD. Chronotype was determined using item 5 from the reduced Morningness-Eveningness Questionnaire. The Eating Disorder Diagnostic Scale (EDDS) and the Rapid Eating Assessment for Participants-Shortened Version (REAP-S) were used to assess disordered eating behavior and dietary habits respectively. General linear models and logistic regression models were utilized to evaluate differences between chronotype groups. RESULTS: Two hundred and eight (27%) BD participants self-identified as having evening chronotypes. Compared to non-evening types, evening types were younger (P < 0.01) and, after controlling for age, had higher mean EDDS composite z-scores (P < 0.01); higher rates of binge-eating (BE) behavior (P = 0.04), bulimia nervosa (P < 0.01), and nocturnal eating binges (P < 0.01); and a higher body mass index (P = 0.04). Compared to non-evening types, evening chronotypes had a lower REAP-S overall score (P < 0.01) and scored lower on the 'healthy foods' and 'avoidance of unhealthy food' factors. Evening types also skipped breakfast more often (P < 0.01), ate less fruit (P = 0.02) and vegetables (P = 0.04), and consumed more fried foods (P < 0.01), unhealthy snacks (P = 0.02), and soft drinks (P = 0.01). CONCLUSIONS: Our findings suggest that the circadian system plays a role in the disordered eating and unhealthy dietary behaviors observed in BD patients. The circadian system may therefore represent a therapeutic target in BD-associated morbidity that warrants further investigation.

New insights into the pharmacogenomics of antidepressant response from the GENDEP and STAR*D studies: rare variant analysis and high-density imputation.

Genome-wide association studies have generally failed to identify polymorphisms associated with antidepressant response. Possible reasons include limited coverage of genetic variants that this study tried to address by exome genotyping and dense imputation. A meta-analysis of Genome-Based Therapeutic Drugs for Depression (GENDEP) and Sequenced Treatment Alternatives to Relieve Depression (STAR*D) studies was performed at the single-nucleotide polymorphism (SNP), gene and pathway levels. Coverage of genetic variants was increased compared with previous studies by adding exome genotypes to previously available genome-wide data and using the Haplotype Reference Consortium panel for imputation. Standard quality control was applied. Phenotypes were symptom improvement and remission after 12 weeks of antidepressant treatment. Significant findings were investigated in NEWMEDS consortium samples and Pharmacogenomic Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) for replication. A total of 7062 950 SNPs were analyzed in GENDEP (n=738) and STAR*D (n=1409). rs116692768 (P=1.80e-08, ITGA9 (integrin α9)) and rs76191705 (P=2.59e-08, NRXN3 (neurexin 3)) were significantly associated with symptom improvement during citalopram/escitalopram treatment. At the gene level, no consistent effect was found. At the pathway level, the Gene Ontology (GO) terms GO: 0005694 (chromosome) and GO: 0044427 (chromosomal part) were associated with improvement (corrected P=0.007 and 0.045, respectively). The association between rs116692768 and symptom improvement was replicated in PGRN-AMPS (P=0.047), whereas rs76191705 was not. The two SNPs did not replicate in NEWMEDS. ITGA9 codes for a membrane receptor for neurotrophins and NRXN3 is a transmembrane neuronal adhesion receptor involved in synaptic differentiation. Despite their meaningful biological rationale for being involved in antidepressant effect, replication was partial. Further studies may help in clarifying their role.

Genome-wide association study of bipolar disorder accounting for effect of body mass index identifies a new risk allele in TCF7L2.

Bipolar disorder (BD) is associated with higher body mass index (BMI) and increased metabolic comorbidity. Considering the associated phenotypic traits in genetic studies of complex diseases, either by adjusting for covariates or by investigating interactions between genetic variants and covariates, may help to uncover the missing heritability. However, obesity-related traits have not been incorporated in prior genome-wide analyses of BD as covariates or potential interacting factors. To investigate the genetic factors underlying BD while considering BMI, we conducted genome-wide analyses using data from the Genetic Association Information Network BD study. We analyzed 729,454 genotyped single-nucleotide polymorphism (SNP) markers on 388 European-American BD cases and 1020 healthy controls with available data for maximum BMI. We performed genome-wide association analyses of the genetic effects while accounting for the effect of maximum BMI, and also evaluated SNP-BMI interactions. A joint test of main and interaction effects demonstrated significant evidence of association at the genome-wide level with rs12772424 in an intron of TCF7L2 (P=2.85E-8). This SNP exhibited interaction effects, indicating that the bipolar susceptibility risk of this SNP is dependent on BMI. TCF7L2 codes for the transcription factor TCF/LF, part of the Wnt canonical pathway, and is one of the strongest genetic risk variants for type 2 diabetes (T2D). This is consistent with BD pathophysiology, as the Wnt pathway has crucial implications in neurodevelopment, neurogenesis and neuroplasticity, and is involved in the mechanisms of action of BD and depression treatments. We hypothesize that genetic risk for BD is BMI dependent, possibly related to common genetic risk with T2D.

Pharmacogenomics of selective serotonin reuptake inhibitor treatment for major depressive disorder: genome-wide associations and functional genomics.

A genome-wide association (GWA) study of treatment outcomes (response and remission) of selective serotonin reuptake inhibitors (SSRIs) was conducted using 529 subjects with major depressive disorder. While no SNP associations reached the genome-wide level of significance, 14 SNPs of interest were identified for functional analysis. The rs11144870 SNP in the riboflavin kinase (RFK) gene on chromosome 9 was associated with 8-week treatment response (odds ratio (OR)=0.42, P=1.04 × 10⁻6). The rs915120 SNP in the G protein-coupled receptor kinase 5 (GRK5) gene on chromosome 10 was associated with 8-week remission (OR=0.50, P=1.15 × 10⁻5). Both SNPs were shown to influence transcription by a reporter gene assay and to alter nuclear protein binding using an electrophoretic mobility shift assay. This report represents an example of joining functional genomics with traditional GWA study results derived from a GWA analysis of SSRI treatment outcomes. The goal of this analytical strategy is to provide insights into the potential relevance of biologically plausible observed associations.

SLC6A4 variation and citalopram response.

The influence of genetic variations in SLC6A4 (serotonin transporter gene) on citalopram treatment of depression using the Sequenced Treatment to Relieve Depression (STAR*D) sample was assessed. Of primary interest were three previously studied polymorphisms: 1) the VNTR variation of the second intron, 2) the indel promoter polymorphism (5HTTLPR or SERT), and 3) a single nucleotide polymorphism (SNP) rs25531. Additionally, SLC6A4 was resequenced to identify new SNPs for exploratory analyses. DNA from 1914 subjects in the STAR*D study were genotyped for the intron 2 VNTR region, the indel promoter polymorphism, and rs25531. Associations of these variants with remission of depressive symptoms were evaluated following citalopram treatment. In white non-Hispanic subjects, variations in the intron 2 VNTR (point-wise P = 0.041) and the indel promoter polymorphism (point-wise P = 0.039) were associated with remission following treatment with citalopram. The haplotype composed of the three candidate loci was also associated with remission, with a global p-value of 0.040 and a maximum statistic simulation p-value of 0.0031 for the S-a-12 haplotype, under a dominant model. One SNP identified through re-sequencing the SLC6A4 gene, Intron7-83-TC, showed point-wise evidence of association, which did not remain significant after correction for the number of SNPs evaluated in this exploratory analysis. No associations between these SLC6A4 variations and remission were found in the white Hispanic or black subjects. These findings suggest that multiple variations in the SLC6A4 gene are associated with remission in white non-Hispanic depressed adults treated with citalopram. The mechanism of action of these variants remains to be determined.

Association of the serotonin transporter-linked polymorphic region genotype with lower bone mineral density.

The serotonin transporter-linked polymorphic region (5-HTTLPR) of the serotonin transporter gene (SLC6A4) S allele is linked to pathogenesis of depression and slower response to selective serotonin reuptake inhibitors (SSRIs); depression and SSRIs are independently associated with bone loss. We aimed to determine whether 5-HTTLPR was associated with bone loss. This cross-sectional study included psychiatric patients with both 5-HTTLPR analysis and bone mineral density (BMD) assessment (hip and spine Z-scores if age <50 years and T-scores if ⩾50 years). BMD association with 5-HTTLPR was evaluated under models with additive allele effects and dominant S allele effects using linear regression models. Patients were stratified by age (<50 and ⩾50 years) and sex. Of 3016 patients with 5-HTTLPR genotyping, 239 had BMD assessments. Among the younger patients, the S allele was associated with lower Z-scores at the hip (P=0.002, dominant S allele effects; P=0.004, additive allele effects) and spine (P=0.0006, dominant S allele effects; P=0.01, additive allele effects). In sex-stratified analyses, the association of the S allele with lower BMD in the younger patients was also significant in the subset of women (P⩽0.003 for both hip and spine BMD under the additive allele effect model). In the small group of men younger than 50 years, the S allele was marginally associated with higher spine BMD (P=0.05). BMD T-scores were not associated with 5-HTTLPR genotypes in patients 50 years or older. The 5-HTTLPR variants may modify serotonin effects on bone with sex-specific effects.

Genome-wide association study of borderline personality disorder reveals genetic overlap with bipolar disorder, major depression and schizophrenia.

Borderline personality disorder (BOR) is determined by environmental and genetic factors, and characterized by affective instability and impulsivity, diagnostic symptoms also observed in manic phases of bipolar disorder (BIP). Up to 20% of BIP patients show comorbidity with BOR. This report describes the first case-control genome-wide association study (GWAS) of BOR, performed in one of the largest BOR patient samples worldwide. The focus of our analysis was (i) to detect genes and gene sets involved in BOR and (ii) to investigate the genetic overlap with BIP. As there is considerable genetic overlap between BIP, major depression (MDD) and schizophrenia (SCZ) and a high comorbidity of BOR and MDD, we also analyzed the genetic overlap of BOR with SCZ and MDD. GWAS, gene-based tests and gene-set analyses were performed in 998 BOR patients and 1545 controls. Linkage disequilibrium score regression was used to detect the genetic overlap between BOR and these disorders. Single marker analysis revealed no significant association after correction for multiple testing. Gene-based analysis yielded two significant genes: DPYD (P=4.42 × 10-7) and PKP4 (P=8.67 × 10-7); and gene-set analysis yielded a significant finding for exocytosis (GO:0006887, PFDR=0.019; FDR, false discovery rate). Prior studies have implicated DPYD, PKP4 and exocytosis in BIP and SCZ. The most notable finding of the present study was the genetic overlap of BOR with BIP (rg=0.28 [P=2.99 × 10-3]), SCZ (rg=0.34 [P=4.37 × 10-5]) and MDD (rg=0.57 [P=1.04 × 10-3]). We believe our study is the first to demonstrate that BOR overlaps with BIP, MDD and SCZ on the genetic level. Whether this is confined to transdiagnostic clinical symptoms should be examined in future studies.

Leveraging electronic health records to study pleiotropic effects on bipolar disorder and medical comorbidities.

Patients with bipolar disorder (BD) have a high prevalence of comorbid medical illness. However, the mechanisms underlying these comorbidities with BD are not well known. Certain genetic variants may have pleiotropic effects, increasing the risk of BD and other medical illnesses simultaneously. In this study, we evaluated the association of BD-susceptibility genetic variants with various medical conditions that tend to co-exist with BD, using electronic health records (EHR) data linked to genome-wide single-nucleotide polymorphism (SNP) data. Data from 7316 Caucasian subjects were used to test the association of 19 EHR-derived phenotypes with 34 SNPs that were previously reported to be associated with BD. After Bonferroni multiple testing correction, P<7.7 × 10(-5) was considered statistically significant. The top association findings suggested that the BD risk alleles at SNP rs4765913 in CACNA1C gene and rs7042161 in SVEP1 may be associated with increased risk of 'cardiac dysrhythmias' (odds ratio (OR)=1.1, P=3.4 × 10(-3)) and 'essential hypertension' (OR=1.1, P=3.5 × 10(-3)), respectively. Although these associations are not statistically significant after multiple testing correction, both genes have been previously implicated with cardiovascular phenotypes. Moreover, we present additional evidence supporting these associations, particularly the association of the SVEP1 SNP with hypertension. This study shows the potential for EHR-based analyses of large cohorts to discover pleiotropic effects contributing to complex psychiatric traits and commonly co-occurring medical conditions.

Feasibility of investigating differential proteomic expression in depression: implications for biomarker development in mood disorders.

The objective of this study was to determine whether proteomic profiling in serum samples can be utilized in identifying and differentiating mood disorders. A consecutive sample of patients with a confirmed diagnosis of unipolar (UP n=52) or bipolar depression (BP-I n=46, BP-II n=49) and controls (n=141) were recruited. A 7.5-ml blood sample was drawn for proteomic multiplex profiling of 320 proteins utilizing the Myriad RBM Discovery Multi-Analyte Profiling platform. After correcting for multiple testing and adjusting for covariates, growth differentiation factor 15 (GDF-15), hemopexin (HPX), hepsin (HPN), matrix metalloproteinase-7 (MMP-7), retinol-binding protein 4 (RBP-4) and transthyretin (TTR) all showed statistically significant differences among groups. In a series of three post hoc analyses correcting for multiple testing, MMP-7 was significantly different in mood disorder (BP-I+BP-II+UP) vs controls, MMP-7, GDF-15, HPN were significantly different in bipolar cases (BP-I+BP-II) vs controls, and GDF-15, HPX, HPN, RBP-4 and TTR proteins were all significantly different in BP-I vs controls. Good diagnostic accuracy (ROC-AUC⩾0.8) was obtained most notably for GDF-15, RBP-4 and TTR when comparing BP-I vs controls. While based on a small sample not adjusted for medication state, this discovery sample with a conservative method of correction suggests feasibility in using proteomic panels to assist in identifying and distinguishing mood disorders, in particular bipolar I disorder. Replication studies for confirmation, consideration of state vs trait serial assays to delineate proteomic expression of bipolar depression vs previous mania, and utility studies to assess proteomic expression profiling as an advanced decision making tool or companion diagnostic are encouraged.

Elevated baseline serum glutamate as a pharmacometabolomic biomarker for acamprosate treatment outcome in alcohol-dependent subjects.

Acamprosate has been widely used since the Food and Drug Administration approved the medication for treatment of alcohol use disorders (AUDs) in 2004. Although the detailed molecular mechanism of acamprosate remains unclear, it has been largely known that acamprosate inhibits glutamate action in the brain. However, AUD is a complex and heterogeneous disorder. Thus, biomarkers are required to prescribe this medication to patients who will have the highest likelihood of responding positively. To identify pharmacometabolomic biomarkers of acamprosate response, we utilized serum samples from 120 alcohol-dependent subjects, including 71 responders (maintained continuous abstinence) and 49 non-responders (any alcohol use) during 12 weeks of acamprosate treatment. Notably, baseline serum glutamate levels were significantly higher in responders compared with non-responders. Importantly, serum glutamate levels of responders are normalized after acamprosate treatment, whereas there was no significant glutamate change in non-responders. Subsequent functional studies in animal models revealed that, in the absence of alcohol, acamprosate activates glutamine synthetase, which synthesizes glutamine from glutamate and ammonia. These results suggest that acamprosate reduces serum glutamate levels for those who have elevated baseline serum glutamate levels among responders. Taken together, our findings demonstrate that elevated baseline serum glutamate levels are a potential biomarker associated with positive acamprosate response, which is an important step towards development of a personalized approach to treatment for AUD.

The International SSRI Pharmacogenomics Consortium (ISPC): a genome-wide association study of antidepressant treatment response.

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. The top association result in the meta-analysis of response represents 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.

Genetic markers associated with abstinence length in alcohol-dependent subjects treated with acamprosate.

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 × 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.

Using a pharmacogenomic algorithm to guide the treatment of depression.

The objective of this study was to evaluate the potential benefit of utilizing a pharmacogenomic testing report to guide the selection and dosing of psychotropic medications in an outpatient psychiatric practice. The non-randomized, open label, prospective cohort study was conducted from September 2009 to July 2010. In the first cohort, depressed patients were treated without the benefit of pharmacogenomic testing (the unguided group). A DNA sample was obtained from patients in the unguided group, but the results were not shared with either the physicians or patients until the end of the 8-week study period. In the second cohort (the guided group), testing results were provided at the beginning of the 8-week treatment period. Depression ratings were collected at baseline and after 2 weeks, 4 weeks and 8 weeks of treatment using the Quick Inventory of Depressive Symptomatology, Clinician Rated (QIDS-C16) and the 17-item Hamilton Rating Scale for Depression (HAM-D17). Clinician and patient satisfaction was also assessed. The reduction in depressive symptoms achieved within the guided treatment group was greater than the reduction of depressive symptoms in the unguided treatment group using either the QIDS-C16 (P=0.002) or HAM-D17 (P=0.04). We concluded that a rapidly available pharmacogenomic interpretive report provided clinical guidance that was associated with improved clinical outcomes for depressed patients treated in an outpatient psychiatric clinic setting.