Publications by authors named "Miguel L Prieto"

19 Publications

  • Page 1 of 1

Pharmacogenetics in Psychiatry: Perceived Value and Opinions in a Chilean Sample of Practitioners.

Front Pharmacol 2021 15;12:657985. Epub 2021 Apr 15.

Center for Genetics and Genomics, Instituto de Ciencias e Innovación en Medicina, Facultad de Medicina, Clínica Alemana Universidad Del Desarrollo, Santiago, Chile.

Use of pharmacogenetics (PGx) testing to guide clinical decisions is growing in developed countries. Published guidelines for gene-drug pair analysis are available for prescriptions in psychiatry, but information on their utilization, barriers, and health outcomes in Latin America is limited. As a result, this work aimed at exploring current use, opinions, and perceived obstacles on PGx testing among psychiatrists in Chile, via an online, anonymous survey. Among 123 respondents (5.9% of registered psychiatrists in the country), 16.3% reported ever requesting a PGx test. The vast majority (95%) of tests were ordered by clinicians practicing in the Metropolitan Region of Santiago. Having more than 20 years in practice was positively associated with prior use of PGx (p 0.02, OR 3.74 (1.19-11.80)), while working in the public health system was negatively associated (OR 0.30 (0.10-0.83)). Perceived barriers to local implementation included insufficient evidence of clinical utility, limited clinicians' knowledge on PGx and on test availability, and health systems' issues, such as costs and reimbursement. Despite the recognition of these barriers, 80% of respondents asserted that it is likely that they will incorporate PGx tests in their practice in the next five years. Given these results, we propose next steps to facilitate implementation such as further research in health outcomes and clinical utility of known and novel clinically actionable variants, growth in local sequencing capabilities, education of clinicians, incorporation of clinical decision support tools, and economic evaluations, all in local context.
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http://dx.doi.org/10.3389/fphar.2021.657985DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8082421PMC
April 2021

Body mass index and blood pressure in bipolar patients: Target cardiometabolic markers for clinical practice.

J Affect Disord 2021 03 29;282:637-643. Epub 2020 Dec 29.

Department of Psychiatry & Psychology, Mayo Clinic, Rochester, Minnesota. Electronic address:

Objective: To evaluate the association between cardiometabolic markers and bipolar disorder (BD), examining the impact of sex and cardiometabolic medication use, from a large case-control biorepository of more than 1300 participants.

Patients And Methods: Recruited from July 2009 through September 2017, cardiometabolic markers were harvested from electronic health records (EHR) of participants (n=661) from the Mayo Clinic Individualized Medicine Biobank for Bipolar Disorder and Mayo Clinic Biobank age-sex-matched controls (n=706). Markers were compared between cases and controls using logistic regression, stratified by sex, adjusting for cardiometabolic medications and current smoking status. We studied the effect of psychotropics in case-only analyses.

Results: The mean age of the sample was 52.5 ± 11.6 years and 55% were female. BD patients had higher rates of smoking, but lower utilization of lipid-lowering medication compared with controls. After adjustment, BD was associated with obesity [Odds ratio (CI) 1.62 (1.22-2.15)], elevated systolic blood pressure (SBP) [2.18 (1.55-3.06)] and elevated triglycerides [1.58 (1.13-2.2)]. When stratified by sex, obesity [1.8 (1.23-2.66)] and systolic blood pressure [2.32 (1.46-3.7)] were associated with BD females compared to female controls; however, only systolic blood pressure [2.04 (1.23-3.42)] was associated with male bipolars compared to male controls. Psychotropics were marginally associated with mean BMI, abnormal triglycerides, and HbA1c.

Limitations: EHR cross-sectional data CONCLUSION: To our knowledge, this is the largest case controlled study to date to explore the association between cardiometabolic markers and bipolar disorder adjusting for utilization of cardiometabolic medication. Identification of significant, non-laboratory based cardiometabolic markers that are associated with increased risk of major cardiovascular adverse events in patients with bipolar disorder, underscores, both the utility and importance of risk monitoring that can be easily done in community mental health centers.
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http://dx.doi.org/10.1016/j.jad.2020.12.121DOI Listing
March 2021

Genome-wide Association Studies in Ancestrally Diverse Populations: Opportunities, Methods, Pitfalls, and Recommendations.

Cell 2019 10 10;179(3):589-603. Epub 2019 Oct 10.

Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA.

Genome-wide association studies (GWASs) have focused primarily on populations of European descent, but it is essential that diverse populations become better represented. Increasing diversity among study participants will advance our understanding of genetic architecture in all populations and ensure that genetic research is broadly applicable. To facilitate and promote research in multi-ancestry and admixed cohorts, we outline key methodological considerations and highlight opportunities, challenges, solutions, and areas in need of development. Despite the perception that analyzing genetic data from diverse populations is difficult, it is scientifically and ethically imperative, and there is an expanding analytical toolbox to do it well.
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http://dx.doi.org/10.1016/j.cell.2019.08.051DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6939869PMC
October 2019

Cytochrome P450 2C19 Poor Metabolizer Phenotype in Treatment Resistant Depression: Treatment and Diagnostic Implications.

Front Pharmacol 2019 19;10:83. Epub 2019 Feb 19.

Department of Psychiatry and Psychology, Mayo Clinic Depression Center, Mayo Clinic College of Medicine and Science, Rochester, MN, United States.

Pharmacogenomic testing, specifically for pharmacokinetic (PK) and pharmacodynamic (PD) genetic variation, may contribute to a better understanding of baseline genetic differences in patients seeking treatment for depression, which may further impact clinical antidepressant treatment recommendations. This study evaluated PK and PD genetic variation and the clinical use of such testing in treatment seeking patients with bipolar disorder (BP) and major depressive disorder (MDD) and history of multiple drug failures/treatment resistance. Consecutive depressed patients evaluated at the Mayo Clinic Depression Center over a 10-year study time frame (2003-2013) were included in this retrospective analysis. Diagnoses of BP or MDD were confirmed using a semi-structured diagnostic interview. Clinical rating scales included the Hamilton Rating Scale for Depression (HRSD), Generalized Anxiety Disorder 7-item scale (GAD-7), Patient Health Questionnaire-9 (PHQ-9), and Adverse Childhood Experiences (ACE) Questionnaire. Clinically selected patients underwent genotyping of cytochrome P450 / and the serotonin transporter . PK and PD differences and whether clinicians incorporated test results in providing recommendations were compared between the two patient groups. Of the 1795 patients, 167/523 (31.9%) with BP and 446/1272 (35.1%) with MDD were genotyped. Genotyped patients had significantly higher self-report measures of depression and anxiety compared to non-genotyped patients. There were significantly more poor metabolizer (PM) phenotypes in BP (9.3%) vs. MDD patients (1.7%, = 0.003); among participants with an S-allele, the rate of PM phenotype was even higher in the BP (9.8%) vs. MDD (0.6%, = 0.003). There was a significant difference in the distribution of genotypes between BP ( = 28.1%, = 59.3%, = 12.6%) and MDD ( = 31.4%, = 46.1%, = 22.7%) patients ( < 0.01). There may be underlying pharmacogenomic differences in treatment seeking depressed patients that potentially have impact on serum levels of metabolized antidepressants (i.e., citalopram / escitalopram) contributing to rates of efficacy vs. side effect burden with additional potential risk of antidepressant response vs. induced mania. The evidence for utilizing pharmacogenomics-guided therapy in MDD and BP is still developing with a much needed focus on drug safety, side effect burden, and treatment adherence.
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http://dx.doi.org/10.3389/fphar.2019.00083DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6389687PMC
February 2019

Association of schizophrenia polygenic risk score with manic and depressive psychosis in bipolar disorder.

Transl Psychiatry 2018 09 10;8(1):188. Epub 2018 Sep 10.

Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA.

Bipolar disorder (BD) is highly heterogeneous in symptomatology. Narrowing the clinical phenotype may increase the power to identify risk genes that contribute to particular BD subtypes. This study was designed to test the hypothesis that genetic overlap between schizophrenia (SZ) and BD is higher for BD with a history of manic psychosis. Analyses were conducted using a Mayo Clinic Bipolar Biobank cohort of 957 bipolar cases (including 333 with history of psychosis during mania, 64 with history of psychosis only during depression, 547 with no history of psychosis, and 13 with unknown history of psychosis) and 778 controls. Polygenic risk score (PRS) analysis was performed by calculating a SZ-PRS for the BD cases and controls, and comparing the calculated SZ risk between different psychosis subgroups and bipolar types. The SZ-PRS was significantly higher for BD-I cases with manic psychosis than BD-I cases with depressive psychosis (Nagelkerke's R = 0.021; p = 0.045), BD-I cases without psychosis (R = 0.015; p = 0.007), BD-II cases without psychosis (R = 0.014; p = 0.017), and controls (R = 0.065; p = 2 × 10). No other significant differences were found. Our results show that BD-I with manic psychosis is genetically more similar to SZ than any other tested BD subgroup. Further investigations on genetics of distinct clinical phenotypes composing major psychoses may help refine the current diagnostic classification system.
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http://dx.doi.org/10.1038/s41398-018-0242-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6131184PMC
September 2018

Clinical features of bipolar spectrum with binge eating behaviour.

J Affect Disord 2016 Sep 6;201:95-8. Epub 2016 May 6.

Department of Psychiatry and Psychology, Mayo Clinic College of Medicine, Rochester, MN, USA.

Objective: To determine whether bipolar spectrum disorder with binge eating behavior (BE) is an important clinical sub-phenotype.

Methods: Prevalence rates and correlates of different levels of BE were assessed in 1114 bipolar spectrum patients participating in a genetic biobank. BE and eating disorders (EDs) were assessed with the Eating Disorder Diagnostic Scale (EDDS). Psychiatric illness burden was evaluated with measures of suicidality, psychosis, mood instability, anxiety disorder comorbidity, and substance abuse comorbidity. Medical illness burden was evaluated with body mass index (BMI) and the Cumulative Index Rating Scale (CIRS).

Results: Thirty percent of patients had any BE and 27% had BE plus an ED diagnosis. Compared with bipolar spectrum patients without BE, bipolar spectrum patients with BE were younger and more likely to be female; had significantly higher levels of eating psychopathology, suicidality, mood instability, and anxiety disorder comorbidity; had a significantly higher mean BMI and a significantly higher rate of obesity; and had a significantly higher medical illness burden. Bipolar spectrum patients with BE but no ED diagnosis were more similar to bipolar spectrum patients without BE than to those with an ED. Nonetheless, the positive predictive value and specificity of BE predicting an ED was 0.90 and 0.96, respectively.

Limitations: As only two patients had co-occurring anorexia nervosa, these results may not generalize to bipolar spectrum patients with restricting EDs.

Conclusion: Bipolar spectrum disorder with broadly-defined BE may not be as clinically relevant a sub-phenotype as bipolar spectrum disorder with an ED but may be an adequate proxy for the latter when phenotyping large samples of individuals.
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http://dx.doi.org/10.1016/j.jad.2016.05.003DOI Listing
September 2016

Accumulating evidence for a role of TCF7L2 variants in bipolar disorder with elevated body mass index.

Bipolar Disord 2016 Mar 2;18(2):124-35. Epub 2016 Mar 2.

Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA.

Objectives: Bipolar disorder (BD) is a complex disease associated with various hereditary traits, including a higher body mass index (BMI). In a prior genome-wide association study, we found that BMI modified the association of rs12772424 - a common variant in the gene encoding transcription factor 7-like 2 (TCF7L2) - with risk for BD. TCF7L2 is a transcription factor in the canonical Wnt pathway, involved in multiple disorders, including diabetes, cancer and psychiatric conditions. Here, using an independent sample, we evaluated 26 TCF7L2 single nucleotide polymorphisms (SNPs) to explore further the association of BD with the TCF7L2-BMI interaction.

Methods: Using a sample of 662 BD cases and 616 controls, we conducted SNP-level and gene-level tests to assess the evidence for an association between BD and the interaction of BMI and genetic variation in TCF7L2. We also explored the potential mechanism behind the detected associations using human brain expression quantitative trait loci (eQTL) analysis.

Results: The analysis provided independent evidence of an rs12772424-BMI interaction (p = 0.011). Furthermore, while overall there was no evidence for SNP marginal effects on BD, the TCF7L2-BMI interaction was significant at the gene level (p = 0.042), with seven of the 26 SNPs showing SNP-BMI interaction effects with p < 0.05. The strongest evidence of interaction was observed for rs7895307 (p = 0.006). TCF7L2 expression showed a significant enrichment of association with the expression of other genes in the Wnt canonical pathway.

Conclusions: The current study provides further evidence suggesting that TCF7L2 involvement in BD risk may be regulated by BMI. Detailed, prospective assessment of BMI, comorbidity, and other possible contributing factors is necessary to explain fully the mechanisms underlying this association.
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http://dx.doi.org/10.1111/bdi.12368DOI Listing
March 2016

Long-term risk of myocardial infarction and stroke in bipolar I disorder: A population-based Cohort Study.

J Affect Disord 2016 Apr 13;194:120-7. Epub 2016 Jan 13.

Department of Psychiatry and Psychology, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA. Electronic address:

Objectives: To estimate the risk of fatal and non-fatal myocardial infarction (MI) and stroke in patients with bipolar I disorder compared to people without bipolar I disorder.

Method: Utilizing a records-linkage system spanning 30 years (1966-1996), a population-based cohort of 334 subjects with bipolar I disorder and 334 age and sex-matched referents from Olmsted County, Minnesota, U.S. was identified. Longitudinal follow-up continued until incident MI or stroke (confirmed by board-certified cardiologist/neurologist), death, or study end date (December 31, 2013). Cox proportional hazards models assessed the hazard ratio (HR) for MI or stroke, adjusting for potential confounders.

Results: There was an increased risk of fatal or non-fatal MI or stroke (as a composite outcome) in patients with bipolar I disorder [HR 1.54, 95% confidence interval (CI) 1.02, 2.33; p=0.04]. However, after adjusting for baseline cardiovascular risk factors (alcoholism, hypertension, diabetes, and smoking), the risk was no longer significantly increased (HR 1.19, 95% CI 0.76, 1.86; p=0.46).

Limitations: Small sample size for the study design. Findings were not retained after adjustment for cardiovascular disease risk factors. Psychotropic medication use during the follow-up was not ascertained and was not included in the analyses.

Conclusion: This study in a geographically defined region in the U.S. demonstrated a significant increased risk of MI or stroke in bipolar I disorder, which was no longer significant after adjustment for cardiovascular risk factors.
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http://dx.doi.org/10.1016/j.jad.2016.01.015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4909505PMC
April 2016

Prevalence and correlates of DSM-5 eating disorders in patients with bipolar disorder.

J Affect Disord 2016 Feb 19;191:216-21. Epub 2015 Nov 19.

Department of Psychiatry and Psychology, Mayo Clinic College of Medicine, Rochester, MN, USA.

Objective: To determine prevalence rates and clinical correlates of current DSM-5 eating disorders in patients with bipolar disorder (BP).

Methods: Prevalence rates of current DSM-5- and DSM-IV-defined binge eating disorder (BED), bulimia nervosa (BN), and anorexia nervosa (AN) were assessed with the Eating Disorder Diagnostic Scale (EDDS) in 1092 patients with BP. Psychiatric illness burden was evaluated with five proxy measures of BP illness severity. Medical illness burden was evaluated with the Cumulative Index Rating Scale (CIRS).

Results: Twenty-seven percent of patients had a current DSM-5 eating disorder: 12% had BED, 15% had BN, and 0.2% had AN. Rates of DSM-5-defined BED and BN were higher than clinical diagnosis rates and rates of DSM-IV-defined BED and BN. Compared with BP patients without an eating disorder, BP patients with a DSM-5 eating disorder were younger and more likely to be women; had an earlier age of onset of BP; had higher EDDS composite scores and higher degrees of suicidality, mood instability, and anxiety disorder comorbidity; and had a higher mean BMI, higher rate of obesity, and higher CIRS total scores. In a logistic regression model controlling for previously identified correlates of an eating disorder, younger age, female gender, and higher BMI remained significantly associated with an eating disorder.

Limitations: The EDDS has not been validated in BP patients.

Conclusion: DSM-5-defined BED and BN are common in BP patients, possibly more common than DSM-IV-defined BED and BN, and associated with greater psychiatric and general medical illness burden. Further studies assessing DSM-5 eating disorders in people with BP are greatly needed.
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http://dx.doi.org/10.1016/j.jad.2015.11.010DOI Listing
February 2016

Sex differences in the risk of rapid cycling and other indicators of adverse illness course in patients with bipolar I and II disorder.

Bipolar Disord 2015 Sep;17(6):670-6

Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA.

Objectives: To examine the independent effects of sex on the risk of rapid cycling and other indicators of adverse illness course in patients with bipolar I disorder (BP-I) or bipolar II disorder (BP-II).

Methods: We analyzed data from the first 1,225 patients enrolled in the Mayo Clinic Individualized Medicine Biobank for Bipolar Disorder. Demographic and clinical variables were ascertained using standardized questionnaires; height and weight were assessed to determine body mass index (BMI). Rates of rapid cycling, cycle acceleration, and increased severity of mood episodes over time were compared between women and men overall and within subgroups defined by bipolar disorder subtype (BP-I or BP-II). Multiple logistic regression analysis was used to assess the independent effect of sex on the risk of these indicators of adverse illness course.

Results: Women had significantly higher rates of rapid cycling than men. Overall rates of rapid cycling were higher in patients with BP-II than BP-I; and sex differences in the rate of rapid cycling were more pronounced in patients with BP-II than BP-I, although the power to detect statistically significant differences was reduced due to the lower sample size of subjects with BP-II. Female sex was a significant predictor of rapid cycling, cycle acceleration, and increased severity of mood episodes over time after adjusting for age, bipolar disorder subtype, BMI, having any comorbid psychiatric disorder, and current antidepressant use.

Conclusions: Female sex was associated with significantly higher risk of rapid cycling, cycle acceleration, and increased severity of mood episodes over time in a sample of 1,225 patients with bipolar disorders.
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http://dx.doi.org/10.1111/bdi.12329DOI Listing
September 2015

Development of a bipolar disorder biobank: differential phenotyping for subsequent biomarker analyses.

Int J Bipolar Disord 2015 Dec 24;3(1):30. Epub 2015 Jun 24.

Department of Psychiatry and Psychology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA,

Background: We aimed to establish a bipolar disorder biobank to serve as a resource for clinical and biomarker studies of disease risk and treatment response. Here, we describe the aims, design, infrastructure, and research uses of the biobank, along with demographics and clinical features of the first participants enrolled.

Methods: Patients were recruited for the Mayo Clinic Bipolar Biobank beginning in July 2009. The Structured Clinical Interview for DSM-IV was used to confirm bipolar diagnosis. The Bipolar Biobank Clinical Questionnaire and Participant Questionnaire were designed to collect detailed demographic and clinical data, including clinical course of illness measures that would delineate differential phenotypes for subsequent analyses. Blood specimens were obtained from participants, and various aliquots were stored for future research.

Results: As of September 2014, 1363 participants have been enrolled in the bipolar biobank. Among these first participants, 69.0 % had a diagnosis of bipolar disorder type I. The group was 60.2 % women and predominantly white (90.6 %), with a mean (SD) age of 42.6 (14.9) years. Clinical phenotypes of the group included history of psychosis (42.3 %), suicide attempt (32.5 %), addiction to alcohol (39.1 %), addiction to nicotine (39.8 %), obesity (42.9 %), antidepressant-induced mania (31.7 %), tardive dyskinesia (3.2 %), and history of drug-related serious rash (5.7 %).

Conclusions: Quantifying phenotypic patterns of illness beyond bipolar subtype can provide more detailed clinical disease characteristics for biomarker research, including genomic-risk studies. Future research can harness clinically useful biomarkers using state-of-the-art research technology to help stage disease burden and better individualize treatment selection for patients with bipolar disorder.
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http://dx.doi.org/10.1186/s40345-015-0030-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4478187PMC
December 2015

Association between history of psychosis and cardiovascular disease in bipolar disorder.

Bipolar Disord 2015 Aug 9;17(5):518-27. Epub 2015 Jun 9.

Mayo Clinic Depression Center, Department of Psychiatry and Psychology, Rochester, MN, USA.

Objectives: To determine whether clinical features of bipolar disorder, such as history of psychosis, and cardiovascular disease (CVD) risk factors contribute to a higher risk of CVD among patients with bipolar disorder.

Methods: This cross-sectional study included a sample of 988 patients with bipolar I or bipolar II disorder or schizoaffective bipolar type confirmed by the Structured Clinical Interview for DSM-IV-TR disorders (SCID). Medical comorbidity burden was quantified utilizing the Cumulative Illness Severity Rating Scale (CIRS). This 13-item organ-based scale includes cardiac disease severity quantification. Confirmed by medical record review, patients who scored 1 (current mild or past significant problem) or higher in the cardiac item were compared by logistic regression to patients who scored 0 (no impairment), adjusting for CVD risk factors that were selected using a backwards stepwise approach or were obtained from the literature.

Results: In a multivariate model, age [odds ratio (OR) = 3.03, 95% confidence interval (CI): 1.66-5.54, p < 0.0001], hypertension (OR = 2.43, 95% CI: 1.69-3.55, p < 0.0001), and history of psychosis (OR = 1.48, 95% CI: 1.03-2.13, p = 0.03) were associated with CVD. When CVD risk factors from the literature were added to the analysis, age (OR = 3.19, 95% CI: 1.67-6.10, p = 0.0005) and hypertension (OR = 2.46, 95% CI: 1.61-3.76, p < 0.01) remained significant, with psychosis being at the trend level (OR = 1.43, 95% CI: 0.96-2.13, p = 0.08).

Conclusions: The phenotype of psychotic bipolar disorder may reflect higher illness severity with associated cardiac comorbidity. Further studies are encouraged to clarify the effect of the disease burden (i.e., depression), lifestyle, and treatment interventions (i.e., atypical antipsychotics) on this risk association.
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http://dx.doi.org/10.1111/bdi.12302DOI Listing
August 2015

Clinical risk factors and serotonin transporter gene variants associated with antidepressant-induced mania.

J Clin Psychiatry 2015 Feb;76(2):174-80

200 First St SW, Rochester, MN 55905

Introduction: Identifying clinical and genetic risk factors associated with antidepressant-induced mania (AIM) may improve individualized treatment strategies for bipolar depression.

Method: From 2009 to 2012, bipolar depressed patients, confirmed by DSM-IV-TR-structured interview, were screened for AIM. An AIM+ case was defined as a manic/hypomanic episode within 60 days of starting or changing dose of antidepressant, while an AIM- control was defined as an adequate (≥ 60 days) exposure to an antidepressant with no associated manic/hypomanic episode. 591 subjects (205 AIM+ and 386 AIM-) exposed to an antidepressant and a subset of 545 subjects (191 AIM+ and 354 AIM-) treated with a selective serotonin reuptake inhibitor (SSRI) or serotonin-norepinephrine reuptake inhibitor (SNRI) were used to evaluate the association of AIM with phenotypic clinical risk factors previously published. 295 white subjects (113 AIM+ cases, 182 AIM-controls) were genotyped for 3 SLC6A4 variants: the 5-HTTLPR, single nucleotide polymorphism (SNP) rs25531, and the intron 2 variable number of tandem repeats (VNTR). Tests of association with AIM were performed for each polymorphism and the haplotype.

Results: The only clinical risk factors associated with AIM in the overall and the SSRI + SNRI analysis was bipolar I subtype. The S allele of 5-HTTLPR was not significantly associated with AIM; however, a meta-analysis combining this sample with 5 prior studies provided marginal evidence of association (P = .059). The L-A-10 haplotype was associated with a reduced risk of AIM (P = .012).

Discussion: Narrowly defined, AIM appears to be at greatest risk for bipolar I patients. Our haplotype analysis of SLC6A4 suggests that future pharmacogenetic studies should not only focus on the SLC6A4 promotor variation but also investigate the role of other variants in the gene.
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http://dx.doi.org/10.4088/JCP.14m09127DOI Listing
February 2015

Current landscape, unmet needs, and future directions for treatment of bipolar depression.

J Affect Disord 2014 Dec;169 Suppl 1:S17-23

Mayo Clinic Depression Center, Department of Psychiatry & Psychology, Mayo Clinic College of Medicine, Rochester, MN, USA.

Background: Depression is the predominant pole of illness disability in bipolar disorder and, compared with acute mania, has less systematic research guiding treatment development. The aim of this review is to present the therapeutic options currently available for managing bipolar depression and to highlight areas of unmet need and future research.

Methods: Literature search of PubMed, PsycINFO, and Cochrane databases and bibliographies from 2000 to August 2013 for treatments that have regulatory approval for bipolar depression or early controlled preliminary data on efficacy.

Results: Treatment options for bipolar depression have increased over the last decade, most notably with regulatory approval for olanzapine/fluoxetine combination, quetiapine, and lurasidone. Conventional mood stabilizers lamotrigine and divalproex have meta-analyses suggesting acute antidepressant response. Manual-based psychotherapies also appear to be effective in treating bipolar depression. The therapeutic utility of unimodal antidepressants, as a class, for the treatment of patients with bipolar depression, as a group, remains to be confirmed. There is a substantially unmet need to develop new interventions that are efficacious, effective, and have low side effect burden.

Limitations: Additional compounds are currently being developed that may ultimately be applicable to the treatment of bipolar depression and early open-trial data encourage further studies, but both of these topics are beyond the scope of this review.

Conclusion: Future registrational trials will need to establish initial efficacy, but increasing interest for personalized or individualized medicine will encourage further studies on individual predictors or biomarkers of response.
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http://dx.doi.org/10.1016/S0165-0327(14)70005-9DOI Listing
December 2014

Different patterns of manic/hypomanic symptoms in depression: A pilot modification of the hypomania checklist-32 to assess mixed depression.

J Affect Disord 2015 Feb 13;172:355-60. Epub 2014 Oct 13.

Mayo Clinic Depression Center, Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA. Electronic address:

Background: There are no self-report scales that assess manic/hypomanic symptoms in patients with depression. The aim of this study was to explore the use of a modified screening instrument for bipolar disorder to assess current manic/hypomanic symptoms in patients with a depressive episode.

Methods: The study sample consisted of 188 patients with Structured Clinical Interview for DSM-IV-TR disorders (SCID) confirmed bipolar or major depressive disorder. We modified the Hypomania Checklist-32 (mHCL-32) to assess current instead of lifetime symptoms. An Exploratory Factor Analysis (EFA) was conducted to identify clusters of mHCL-32 items that were endorsed concurrently. A Latent Class Analysis (LCA) was carried out to identify groups of patients with similar mHCL-32 item endorsement patterns.

Results: The EFA identified 3 factors: factor #1 ("elation-disinhibition-increased goal directed activity"), factor #2 ("risk-taking-impulsivity-substance use") and factor #3 (distractibility-irritability). The LCA yielded 3 classes (2 showing manic/hypomanic features). While class #1 patients endorsed more items related to disinhibition and racing thoughts, class #2 patients recognized more items associated with irritability and substance use.

Limitations: Lack of an adequate gold standard measure of mixed depression to compare to, the cross-sectional design and the lack of a validation sample.

Conclusions: The mHCL-32 scale allowed a comprehensive and convergent delineation of hypomanic/manic symptoms in depression. Further validation of these findings is needed.
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http://dx.doi.org/10.1016/j.jad.2014.09.047DOI Listing
February 2015

Change in consumption patterns for treatment-seeking patients with alcohol use disorder post-bariatric surgery.

J Psychosom Res 2015 Mar 7;78(3):199-204. Epub 2014 Sep 7.

Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States. Electronic address:

Objective: The aim of this study is to describe the clinical phenotype of alcohol use disorder (AUD) treatment-seeking patients with Roux-en-Y Gastric Bypass Surgery (RYGB) history; and to compare it to AUD obese non-RYGB controls.

Methods: Retrospective study of electronic medical records for all patients 30-60years treated at the Mayo Clinic Addiction Treatment Program, between June, 2004 and July, 2012. Comparisons were performed with consumption patterns pre-RYGB and at time of treatment; excluding patients with AUD treatments pre-RYGB.

Results: Forty-one out of 823 patients had a RYGB history (4.9%); 122 controls were selected. Compared to controls, the RYGB group had significantly more females [n=29 (70.7%) vs. n=35 (28.7%) p<0.0001]; and met AUD criteria at a significantly earlier age (19.1±0.4 vs. 25.0±1years old, p=0.002). On average, RYGB patients reported resuming alcohol consumption 1.4±0.2years post-surgery, meeting criteria for AUD at 3.1±0.5years and seeking treatment at 5.4±0.3years postoperatively. Pre-surgical drinks per day were significantly fewer compared to post-surgical consumption [2.5±0.4 vs. 8.1±1.3, p=0.009]. Prior to admission, RYGB patients reported fewer drinking days per week vs. controls (4.7±0.3 vs. 5.5±1.8days, p=0.02). Neither RYGB, gender, age nor BMI was associated with differential drinking patterns.

Conclusion: The results of this study suggest that some patients develop progressive AUD several years following RYGB. This observation has important clinical implications, calling for AUD-preventive measures following RYGB. Further large-scale longitudinal studies are needed to clarify the association between RYGB and AUD onset.
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http://dx.doi.org/10.1016/j.jpsychores.2014.06.019DOI Listing
March 2015

Activation of neurotensin receptor type 1 attenuates locomotor activity.

Neuropharmacology 2014 Oct 11;85:482-92. Epub 2014 Jun 11.

Neurobiology of Disease Program, Mayo Clinic College of Medicine, Rochester, MN 55905, USA; Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic College of Medicine, Rochester, MN 55905, USA; Department of Psychiatry and Psychology, Mayo Clinic College of Medicine, Rochester, MN 55905, USA. Electronic address:

Intracerebroventricular administration of neurotensin (NT) suppresses locomotor activity. However, the brain regions that mediate the locomotor depressant effect of NT and receptor subtype-specific mechanisms involved are unclear. Using a brain-penetrating, selective NT receptor type 1 (NTS1) agonist PD149163, we investigated the effect of systemic and brain region-specific NTS1 activation on locomotor activity. Systemic administration of PD149163 attenuated the locomotor activity of C57BL/6J mice both in a novel environment and in their homecage. However, mice developed tolerance to the hypolocomotor effect of PD149163 (0.1 mg/kg, i.p.). Since NTS1 is known to modulate dopaminergic signaling, we examined whether PD149163 blocks dopamine receptor-mediated hyperactivity. Pretreatment with PD149163 (0.1 or 0.05 mg/kg, i.p.) inhibited D2R agonist bromocriptine (8 mg/kg, i.p.)-mediated hyperactivity. D1R agonist SKF-81297 (8 mg/kg, i.p.)-induced hyperlocomotion was only inhibited by 0.1 mg/kg of PD149163. Since the nucleus accumbens (NAc) and medial prefrontal cortex (mPFC) have been implicated in the behavioral effects of NT, we examined whether microinjection of PD149163 into these regions reduces locomotion. Microinjection of PD149163 (2 pmol) into the NAc, but not the mPFC suppressed locomotor activity. In summary, our results indicate that systemic and intra-NAc activation of NTS1 is sufficient to reduce locomotion and NTS1 activation inhibits D2R-mediated hyperactivity. Our study will be helpful to identify pharmacological factors and a possible therapeutic window for NTS1-targeted therapies for movement disorders.
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http://dx.doi.org/10.1016/j.neuropharm.2014.05.046DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4107019PMC
October 2014

A multinational study to pilot the modified Hypomania Checklist (mHCL) in the assessment of mixed depression.

J Affect Disord 2014 Jan 23;152-154:478-82. Epub 2013 Aug 23.

Department of Psychiatry, Canakkale Onsekiz Mart University, Canakkale, Turkey.

Background: Mixed depression is a common, dimensional phenomenon that is increasingly recognized in unipolar and bipolar disorders. We piloted a modified version of the Hypomania Checklist (mHCL-32) to assess the prevalence and clinical correlates of concurrent manic (hypo) symptoms in depressed patients.

Methods: The mHCL-32, Young Mania Rating Scale (YMRS) and Hamilton Rating Scale for Depression (HAMD-24) were utilized in the assessment of unipolar (UP=61) and bipolar (BP=44) patients with an index major depressive episode confirmed by the Structured Clinical Interview for DSM-IV (SCID). Differential mHLC-32 item endorsement was compared between UP and BP. Correlation analyses assessed the association of symptom dimensions measured by mHCL-32, YMRS and HAMD-24.

Results: There was no significant difference between mood groups in the mean mHCL-32 and YMRS scores. Individual mHLC-32 items of increased libido, quarrels, and caffeine intake were endorsed more in BP vs. UP patients. The mHCL-32 active-elevated subscale score was positively correlated with the YMRS in BP patients and negatively correlated with HAMD-24 in UP patients. Conversely, the mHCL-32 irritable-risk taking subscale score was positively correlated with HAMD-24 in BP and with YMRS in UP patients.

Limitations: Small sample size and cross-sectional design.

Conclusion: Modifying the HCL to screen for (hypo) manic symptoms in major depression may have utility in identifying mixed symptoms in both bipolar vs. unipolar depression. Further research is encouraged to quantify mixed symptoms with standardized assessments.
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http://dx.doi.org/10.1016/j.jad.2013.07.032DOI Listing
January 2014

Clinical phenotype of bipolar disorder with comorbid binge eating disorder.

J Affect Disord 2013 Sep 3;150(3):981-6. Epub 2013 Jun 3.

Lindner Center of HOPE, 4075 Old Western Road, Mason, OH 45040, USA.

Background: To explore the relationship between binge eating disorder (BED) and obesity in patients with bipolar disorder (BP).

Methods: 717 patients participating in the Mayo Clinic Bipolar Biobank completed structured diagnostic interviews and questionnaires for demographic and illness-related variables. They also had weight and height measured to determine body mass index (BMI). The effects of BED and obesity (BMI≥30 kg/m(2)), as well as their interaction, were assessed on one measure of general medical burden and six proxies of psychiatric illness burden.

Results: 9.5% of patients received a clinical diagnosis of BED and 42.8% were obese. BED was associated with a significantly elevated BMI. Both BED and obesity were associated with greater psychiatric and general illness burden, but illness burden profiles differed. After controlling for obesity, BED was associated with suicidality, psychosis, mood instability, anxiety disorder comorbidity, and substance abuse comorbidity. After controlling for BED status, obesity was associated with greater general medical comorbidity, but lower substance abuse comorbidity. There were no significant interaction effects between obesity and BED, or BMI and BED, on any illness burden outcome.

Limitations: There may have been insufficient power to detect interactions between BED and obesity.

Conclusions: Among patients with BP, BED and obesity are highly prevalent and correlated, but associated with different profiles of enhanced illness burden. As the association of BED with greater psychiatric illness burden remained significant even after accounting for the effect of obesity, BP with BED may represent a clinically important sub-phenotype.
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http://dx.doi.org/10.1016/j.jad.2013.05.024DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5551039PMC
September 2013