Dysfunctional Cognitions among Offspring of Individuals with Bipolar Disorder

2013 ◽  
Vol 43 (4) ◽  
pp. 449-464 ◽  
Author(s):  
Camilo J. Ruggero ◽  
Kathleen M. Bain ◽  
Patrick M. Smith ◽  
Jared N. Kilmer
Keyword(s):  
Bipolar Disorder ◽  
Young Adult ◽  
Depressive Disorder ◽  
Mood Disorder ◽  
Cognitive Models ◽  
Mood States ◽  
Dysfunctional Beliefs ◽  
Structured Interviews ◽  
Major Depressive ◽  
Dysfunctional Cognitions

Background: Individuals with bipolar disorder often endorse dysfunctional beliefs consistent with cognitive models of bipolar disorder (Beck, 1976; Mansell, 2007). Aims: The present study sought to assess whether young adult offspring of those with bipolar disorder would also endorse these beliefs, independent of their own mood episode history. Method: Participants (N = 89) were young adult college students with a parent with bipolar disorder (n = 27), major depressive disorder (MDD; n = 30), or no mood disorder (n = 32). Semi-structured interviews of the offspring were used to assess diagnoses. Dysfunctional beliefs related to Beck and colleagues’ (2006) and Mansell's (2007) cognitive models were assessed. Results: Unlike offspring of parents with MDD or no mood disorder, those with a parent with bipolar disorder endorsed significantly more dysfunctional cognitions associated with extreme appraisal of mood states, even after controlling for their own mood diagnosis. Once affected by a bipolar or depressive disorder, offspring endorsed dysfunctional cognitions across measures. Conclusions: Dysfunctional cognitions, particularly those related to appraisals of mood states and their potential consequences, are evident in young adults with a parent who has bipolar disorder and may represent targets for psychotherapeutic intervention.

Attention-deficit/hyperactivity disorder and other neurodevelopmental disorders in offspring of parents with depression and bipolar disorder

2021 ◽  
pp. 1-8
Author(s):  
L. Propper ◽  
A. Sandstrom ◽  
S. Rempel ◽  
E. Howes Vallis ◽  
S. Abidi ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Attention Deficit Hyperactivity Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Mood Disorder ◽  
Attention Deficit ◽  
Neurodevelopmental Disorders ◽  
Autism Spectrum ◽  
Major Depressive ◽  
Hyperactivity Disorder

Abstract Background Offspring of parents with major mood disorders (MDDs) are at increased risk for early psychopathology. We aim to compare the rates of neurodevelopmental disorders in offspring of parents with bipolar disorder, major depressive disorder, and controls. Method We established a lifetime diagnosis of neurodevelopmental disorders [attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, communication disorders, intellectual disabilities, specific learning disorders, and motor disorders] using the Kiddie Schedule for Affective Disorders and Schizophrenia, Present and Lifetime Version in 400 participants (mean age 11.3 + s.d. 3.9 years), including 93 offspring of parents with bipolar disorder, 182 offspring of parents with major depressive disorder, and 125 control offspring of parents with no mood disorder. Results Neurodevelopmental disorders were elevated in offspring of parents with bipolar disorder [odds ratio (OR) 2.34, 95% confidence interval (CI) 1.23–4.47, p = 0.010] and major depressive disorder (OR 1.87, 95% CI 1.03–3.39, p = 0.035) compared to controls. This difference was driven by the rates of ADHD, which were highest among offspring of parents with bipolar disorder (30.1%), intermediate in offspring of parents with major depressive disorder (24.2%), and lowest in controls (14.4%). There were no significant differences in frequencies of other neurodevelopmental disorders between the three groups. Chronic course of mood disorder in parents was associated with higher rates of any neurodevelopmental disorder and higher rates of ADHD in offspring. Conclusions Our findings suggest monitoring for ADHD and other neurodevelopmental disorders in offspring of parents with MDDs may be indicated to improve early diagnosis and treatment.

scholarly journals Reliability and validity of a Brazilian version of the Hypomania Checklist (HCL-32) compared to the Mood Disorder Questionnaire (MDQ)

2010 ◽  
Vol 32 (4) ◽  
pp. 416-423 ◽  
Author(s):  
Odeilton Tadeu Soares ◽  
Doris Hupfeld Moreno ◽  
Eduardo Calmon de Moura ◽  
Jules Angst ◽  
Ricardo Alberto Moreno
Keyword(s):  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Mood Disorder ◽  
Psychometric Properties ◽  
Internal Consistency ◽  
Major Depressive ◽  
Brazilian Version ◽  
Diagnostic Certainty ◽  
Mood Disorder Questionnaire

OBJECTIVE: Bipolar disorders are often not recognized and undertreated. The diagnosis of current or past episodes of hypomania is of importance in order to increase diagnostic certainty. The Hypomania Checklist-32 is a self-applied questionnaire aimed at recognizing these episodes. As part of the international collaborative effort to develop multi-lingual versions of the Hypomania Checklist-32, we aimed to validate the Brazilian version and to compare its psychometric properties with those of the Mood Disorder Questionnaire. METHOD: Adult outpatients with bipolar disorder I (n = 37), bipolar disorder II (n = 44) and major depressive disorder (n = 42) of a specialized mood disorder unit were diagnosed according to DSM-IV-TR using a modified version of the SCID. We analyzed the internal consistency and discriminative ability of the Hypomania Checklist-32 Brazilian version in relation to the Mood Disorder Questionnaire. RESULTS: The internal consistency of the Brazilian Hypomania Checklist-32, analyzed using Cronbach's alpha coefficient, was 0.86. A score of 18 or higher in the Hypomania Checklist-32 Brazilian version distinguished between bipolar disorder and major depressive disorder, with a sensitivity of 0.75 and a specificity of 0.58, compared to 0.70 and 0.58, respectively, for the Mood Disorder Questionnaire (score > 7). The Hypomania Checklist-32 Brazilian version showed a dual factor structure characterized by "active/elated" and "risk-taking/irritable" items. Hence, the Hypomania Checklist-32 Brazilian version was found to have a higher sensitivity but the same specificity as the Mood Disorder Questionnaire. CONCLUSION: The Brazilian version of the Hypomania Checklist-32 has adequate psychometric properties and helps discriminating bipolar disorder from major depressive disorder (but not bipolar disorder I from bipolar disorder II) with good sensitivity and specificity indices, similar to those of the Mood Disorder Questionnaire.

scholarly journals The overlap of genetic susceptibility to schizophrenia and cardiometabolic disease can be used to identify metabolically different groups of individuals

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rona J. Strawbridge ◽  
Keira J. A. Johnston ◽  
Mark E. S. Bailey ◽  
Damiano Baldassarre ◽  
Breda Cullen ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
European Ancestry ◽  
Cardiometabolic Disease ◽  
Metabolic Profiles ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Major Depressive ◽  
Increased Risk

AbstractUnderstanding why individuals with severe mental illness (Schizophrenia, Bipolar Disorder and Major Depressive Disorder) have increased risk of cardiometabolic disease (including obesity, type 2 diabetes and cardiovascular disease), and identifying those at highest risk of cardiometabolic disease are important priority areas for researchers. For individuals with European ancestry we explored whether genetic variation could identify sub-groups with different metabolic profiles. Loci associated with schizophrenia, bipolar disorder and major depressive disorder from previous genome-wide association studies and loci that were also implicated in cardiometabolic processes and diseases were selected. In the IMPROVE study (a high cardiovascular risk sample) and UK Biobank (general population sample) multidimensional scaling was applied to genetic variants implicated in both psychiatric and cardiometabolic disorders. Visual inspection of the resulting plots used to identify distinct clusters. Differences between these clusters were assessed using chi-squared and Kruskall-Wallis tests. In IMPROVE, genetic loci associated with both schizophrenia and cardiometabolic disease (but not bipolar disorder or major depressive disorder) identified three groups of individuals with distinct metabolic profiles. This grouping was replicated within UK Biobank, with somewhat less distinction between metabolic profiles. This work focused on individuals of European ancestry and is unlikely to apply to more genetically diverse populations. Overall, this study provides proof of concept that common biology underlying mental and physical illness may help to stratify subsets of individuals with different cardiometabolic profiles.

Predictors of conversion of major depressive disorder to bipolar disorder

2021 ◽  
pp. 113939
Author(s):  
Satish Suhas ◽  
Abha Thakurdesai ◽  
Amal Jolly Joseph ◽  
Chittaranjan Andrade
Keyword(s):  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Major Depressive

scholarly journals A machine learning algorithm to differentiate bipolar disorder from major depressive disorder using an online mental health questionnaire and blood biomarker data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jakub Tomasik ◽  
Sung Yeon Sarah Han ◽  
Giles Barton-Owen ◽  
Dan-Mircea Mirea ◽  
Nayra A. Martin-Key ◽  
...  
Keyword(s):  
Mental Health ◽  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Diagnostic Algorithm ◽  
Health Questionnaire ◽  
Major Depressive ◽  
Blood Biomarker ◽  
Mental Health Questionnaire ◽  
Biomarker Data

AbstractThe vast personal and economic burden of mood disorders is largely caused by their under- and misdiagnosis, which is associated with ineffective treatment and worsening of outcomes. Here, we aimed to develop a diagnostic algorithm, based on an online questionnaire and blood biomarker data, to reduce the misdiagnosis of bipolar disorder (BD) as major depressive disorder (MDD). Individuals with depressive symptoms (Patient Health Questionnaire-9 score ≥5) aged 18–45 years were recruited online. After completing a purpose-built online mental health questionnaire, eligible participants provided dried blood spot samples for biomarker analysis and underwent the World Health Organization World Mental Health Composite International Diagnostic Interview via telephone, to establish their mental health diagnosis. Extreme Gradient Boosting and nested cross-validation were used to train and validate diagnostic models differentiating BD from MDD in participants who self-reported a current MDD diagnosis. Mean test area under the receiver operating characteristic curve (AUROC) for separating participants with BD diagnosed as MDD (N = 126) from those with correct MDD diagnosis (N = 187) was 0.92 (95% CI: 0.86–0.97). Core predictors included elevated mood, grandiosity, talkativeness, recklessness and risky behaviour. Additional validation in participants with no previous mood disorder diagnosis showed AUROCs of 0.89 (0.86–0.91) and 0.90 (0.87–0.91) for separating newly diagnosed BD (N = 98) from MDD (N = 112) and subclinical low mood (N = 120), respectively. Validation in participants with a previous diagnosis of BD (N = 45) demonstrated sensitivity of 0.86 (0.57–0.96). The diagnostic algorithm accurately identified patients with BD in various clinical scenarios, and could help expedite accurate clinical diagnosis and treatment of BD.

BDgene: A Genetic Database for Bipolar Disorder and Its Overlap With Schizophrenia and Major Depressive Disorder

2013 ◽  
Vol 74 (10) ◽  
pp. 727-733 ◽  
Author(s):  
Su-Hua Chang ◽  
Lei Gao ◽  
Zhao Li ◽  
Wei-Na Zhang ◽  
Yang Du ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Major Depressive ◽  
Genetic Database
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