scholarly journals Multidimensional assessment of impulsivity in schizophrenia, bipolar disorder, and major depressive disorder: testing for shared endophenotypes

2016 ◽  
Vol 46 (7) ◽  
pp. 1497-1507 ◽  
Author(s):  
R. G. Fortgang ◽  
C. M. Hultman ◽  
T. G. M. van Erp ◽  
T. D. Cannon
Keyword(s):  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Sensation Seeking ◽  
Behavioral Measure ◽  
Clinical Feature ◽  
Major Depressive ◽  
Genetic Overlap ◽  
Stop Signal Reaction Time ◽  
Genetic Loading

BackgroundImpulsivity is associated with bipolar disorder as a clinical feature during and between manic episodes and is considered a potential endophenotype for the disorder. Schizophrenia and major depressive disorder share substantial genetic overlap with bipolar disorder, and these two disorders have also been associated with elevations in impulsivity. However, little is known about the degree of overlap among these disorders in discrete subfacets of impulsivity and whether any overlap is purely phenotypic or due to shared genetic diathesis.MethodWe focused on five subfacets of impulsivity: self-reported attentional, motor, and non-planning impulsivity, self-reported sensation seeking, and a behavioral measure of motor inhibition (stop signal reaction time; SSRT). We examined these facets within and across disorder proband and co-twin groups, modeled heritability, and tested for endophenotypic patterning in a sample of twin pairs recruited from the Swedish Twin Registry (N = 420).ResultsWe found evidence of moderate to high levels of heritability for all five subfacets. All three proband groups and their unaffected co-twins showed elevations on attentional, motor, and non-planning impulsivity. Schizophrenia probands (but not their co-twins) showed significantly lower sensation seeking, and schizophrenia and bipolar disorder probands (but not in their co-twins) had significantly longer SSRTs, compared with healthy controls and the other groups.ConclusionsAttentional, motor, and non-planning impulsivity emerged as potential shared endophenotypes for the three disorders, whereas sensation seeking and SSRT were associated with phenotypic affection but not genetic loading for these disorders.

scholarly journals Psychological trauma and the genetic overlap between posttraumatic stress disorder and major depressive disorder

2021 ◽  
pp. 1-10
Author(s):  
Jessica Mundy ◽  
Christopher Hübel ◽  
Joel Gelernter ◽  
Daniel Levey ◽  
Robin M. Murray ◽  
...  
Keyword(s):  
Posttraumatic Stress Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Stress Disorder ◽  
Genetic Correlations ◽  
Psychological Trauma ◽  
Major Depressive ◽  
Single Episode ◽  
Genetic Overlap ◽  
Genetic Loading

Abstract Background Posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) are commonly reported co-occurring mental health consequences of psychological trauma exposure. The disorders have high genetic overlap. Trauma is a complex phenotype but research suggests that trauma sensitivity has a heritable basis. We investigated whether sensitivity to trauma in those with MDD reflects a similar genetic component in those with PTSD. Methods Genetic correlations between PTSD and MDD in individuals reporting trauma and MDD in individuals not reporting trauma were estimated, as well as with recurrent MDD and single-episode MDD, using genome-wide association study (GWAS) summary statistics. Genetic correlations were replicated using PTSD data from the Psychiatric Genomics Consortium and the Million Veteran Program. Polygenic risk scores were generated in UK Biobank participants who met the criteria for lifetime MDD (N = 29 471). We investigated whether genetic loading for PTSD was associated with reporting trauma in these individuals. Results Genetic loading for PTSD was significantly associated with reporting trauma in individuals with MDD [OR 1.04 (95% CI 1.01–1.07), Empirical-p = 0.02]. PTSD was significantly more genetically correlated with recurrent MDD than with MDD in individuals not reporting trauma (rg differences = ~0.2, p < 0.008). Participants who had experienced recurrent MDD reported significantly higher rates of trauma than participants who had experienced single-episode MDD (χ2 > 166, p < 0.001) Conclusions Our findings point towards the existence of genetic variants associated with trauma sensitivity that might be shared between PTSD and MDD, although replication with better powered GWAS is needed. Our findings corroborate previous research highlighting trauma exposure as a key risk factor for recurrent MDD.

scholarly journals Molecular genetic overlap in bipolar disorder, schizophrenia, and major depressive disorder

2012 ◽  
Vol 15 (3) ◽  
pp. 200-208 ◽  
Author(s):  
Thomas G. Schulze ◽  
Nirmala Akula ◽  
René Breuer ◽  
Jo Steele ◽  
Michael A. Nalls ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Molecular Genetic ◽  
Major Depressive ◽  
Genetic Overlap

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.

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.

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