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

2020 ◽  
Author(s):  
Rona J. Strawbridge ◽  
Keira J. A. Johnston ◽  
Mark E. S. Bailey ◽  
Damiano Baldasarre ◽  
Breda Cullen ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Depressive Disorders ◽  
Cardiometabolic Disease ◽  
Metabolic Profiles ◽  
Uk Biobank ◽  
Major Depressive ◽  
Increased Risk ◽  
Chi Squared

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 researcher. We explored whether genetic variation could identify individuals with different metabolic profiles. Loci previously associated with schizophrenia, bipolar disorder and major depressive disorder were identified from literature and those overlapping loci genotyped on the Illumina CardioMetabo and Immuno chips (representing cardiometabolic processes and diseases) were selected. In the IMPROVE study (high cardiovascular risk) and UK Biobank (general population) multidimensional scaling was applied to genetic variants implicated in both mental and cardiometabolic illness. Visual inspection of the resulting plots used to identify distinct clusters. Differences between clusters were assessed using chi-squared and Kruskall-Wallis tests. In IMPROVE, genetic loci associated with both cardiometabolic disease and schizophrenia (but not bipolar or major depressive disorders) identified three groups of individuals with distinct metabolic profiles. The grouping was replicated in UK Biobank, albeit with less distinction between metabolic profiles. This study provides proof of concept that common biology underlying mental and physical illness can identify subsets of individuals with different cardiometabolic profiles.

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.

scholarly journals Disruptive mood dysregulation disorder in offspring of parents with depression and bipolar disorder

2017 ◽  
Vol 210 (6) ◽  
pp. 408-412 ◽  
Author(s):  
Lukas Propper ◽  
Jill Cumby ◽  
Victoria C. Patterson ◽  
Vladislav Drobinin ◽  
Jacqueline M. Glover ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Family History ◽  
Depressive Disorder ◽  
Control Group ◽  
Major Depressive ◽  
Disruptive Mood Dysregulation Disorder ◽  
Increased Risk ◽  
History Of ◽  
Mood Dysregulation

BackgroundIt has been suggested that offspring of parents with bipolar disorder are at increased risk for disruptive mood dysregulation disorder (DMDD), but the specificity of this association has not been established.AimsWe examined the specificity of DMDD to family history by comparing offspring of parents with (a) bipolar disorder, (b) major depressive disorder and (c) a control group with no mood disorders.MethodWe established lifetime diagnosis of DMDD using the Schedule for Affective Disorders and Schizophrenia for School Aged Children for DSM-5 in 180 youth aged 6–18 years, including 58 offspring of parents with bipolar disorder, 82 offspring of parents with major depressive disorder and 40 control offspring.ResultsDiagnostic criteria for DMDD were met in none of the offspring of parents with bipolar disorder, 6 of the offspring of parents with major depressive disorder and none of the control offspring. DMDD diagnosis was significantly associated with family history of major depressive disorder.ConclusionsOur results suggest that DMDD is not specifically associated with a family history of bipolar disorder and may be associated with parental depression.

scholarly journals Genetic association study of psychotic experiences in UK Biobank

2019 ◽  
Author(s):  
Sophie E. Legge ◽  
Hannah J. Jones ◽  
Kimberley M. Kendall ◽  
Antonio F. Pardiñas ◽  
Georgina Menzies ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Neurodevelopmental Disorders ◽  
Population Based ◽  
Uk Biobank ◽  
Psychotic Experiences ◽  
Psychotic Experience ◽  
Major Depressive ◽  
Genome Wide

AbstractPsychotic experiences, such as hallucinations and delusions, are reported by approximately 5%-10% of the general population, though only a small proportion of individuals develop psychotic disorders such as schizophrenia or bipolar disorder. Studying the genetic aetiology of psychotic experiences in the general population, and its relationship with the genetic aetiology of other disorders, may increase our understanding of their pathological significance. Using the population-based UK Biobank sample, we performed the largest genetic association study of psychotic experiences in individuals without a psychotic disorder. We conducted three genome-wide association studies (GWAS) for (i) any psychotic experience (6123 cases vs. 121,843 controls), (ii) distressing psychotic experiences (2143 cases vs. 121,843 controls), and (iii) multiple occurrence psychotic experiences (3337 cases vs. 121,843 controls). Analyses of polygenic risk scores (PRS), genetic correlation, and copy number variation (CNV) were conducted to assess whether genetic liability to psychotic experiences is shared with schizophrenia and/or other neuropsychiatric disorders and traits. GWAS analyses identified four loci associated with psychotic experiences including a locus in Ankyrin-3 (ANK3, OR=1.16,p=3.06 × 10−8) with any psychotic experience and a locus in cannabinoid receptor 2 gene (CNR2,OR=0.66,p=3.78×10−8) with distressing psychotic experiences. PRS analyses identified associations between psychotic experiences and genetic liability for schizophrenia, major depressive disorder, and bipolar disorder, and these associations were stronger for distressing psychotic experiences. Genetic correlation analysis identified significant genetic correlations between psychotic experiences and major depressive disorder, schizophrenia, autism spectrum disorder and a cross-disorder GWAS. Individuals reporting psychotic experiences had an increased burden of CNVs previously associated with schizophrenia (OR=2.04,p=2.49×10−4) and of those associated with neurodevelopmental disorders more widely (OR=1.75,p=1.41×10−3). In conclusion, we identified four genome-wide significant loci in the largest GWAS of psychotic experiences from the population-based UK Biobank sample and found support for a shared genetic aetiology between psychotic experiences and schizophrenia, but also major depressive disorder, bipolar disorder and neurodevelopmental disorders.

scholarly journals Disparities in COVID-19 infection, hospitalisation and death in people with schizophrenia, bipolar disorder, and major depressive disorder: a cohort study of the UK Biobank

2021 ◽  
Author(s):  
Lamiece Hassan ◽  
Niels Peek ◽  
Karina Lovell ◽  
Andre F. Carvalho ◽  
Marco Solmi ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Cohort Study ◽  
Depressive Disorder ◽  
Sociodemographic Factors ◽  
Vulnerable Groups ◽  
Multivariable Logistic Regression Analysis ◽  
Uk Biobank ◽  
Major Depressive ◽  
The Uk

AbstractPeople with severe mental illness (SMI; including schizophrenia/psychosis, bipolar disorder (BD), major depressive disorder (MDD)) experience large disparities in physical health. Emerging evidence suggests this group experiences higher risks of infection and death from COVID-19, although the full extent of these disparities are not yet established. We investigated COVID-19 related infection, hospitalisation and mortality among people with SMI in the UK Biobank (UKB) cohort study. Overall, 447,296 participants from UKB (schizophrenia/psychosis = 1925, BD = 1483 and MDD = 41,448, non-SMI = 402,440) were linked with healthcare and death records. Multivariable logistic regression analysis was used to examine differences in COVID-19 outcomes by diagnosis, controlling for sociodemographic factors and comorbidities. In unadjusted analyses, higher odds of COVID-19 mortality were seen among people with schizophrenia/psychosis (odds ratio [OR] 4.84, 95% confidence interval [CI] 3.00–7.34), BD (OR 3.76, 95% CI 2.00–6.35), and MDD (OR 1.99, 95% CI 1.69–2.33) compared to people with no SMI. Higher odds of infection and hospitalisation were also seen across all SMI groups, particularly among people with schizophrenia/psychosis (OR 1.61, 95% CI 1.32–1.96; OR 3.47, 95% CI 2.47–4.72) and BD (OR 1.48, 95% CI 1.16–1.85; OR 3.31, 95% CI 2.22–4.73). In fully adjusted models, mortality and hospitalisation odds remained significantly higher among all SMI groups, though infection odds remained significantly higher only for MDD. People with schizophrenia/psychosis, BD and MDD have higher risks of COVID-19 infection, hospitalisation and mortality. Only a proportion of these disparities were accounted for by pre-existing demographic characteristics or comorbidities. Vaccination and preventive measures should be prioritised in these particularly vulnerable groups.

scholarly journals Predictors of diagnostic transition from major depressive disorder to bipolar disorder: a retrospective observational network study

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Anastasiya Nestsiarovich ◽  
Jenna M. Reps ◽  
Michael E. Matheny ◽  
Scott L. DuVall ◽  
Kristine E. Lynch ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
External Validation ◽  
Severe Depression ◽  
Common Data Model ◽  
Major Depressive ◽  
National Network ◽  
Increased Risk ◽  
One Year

AbstractMany patients with bipolar disorder (BD) are initially misdiagnosed with major depressive disorder (MDD) and are treated with antidepressants, whose potential iatrogenic effects are widely discussed. It is unknown whether MDD is a comorbidity of BD or its earlier stage, and no consensus exists on individual conversion predictors, delaying BD’s timely recognition and treatment. We aimed to build a predictive model of MDD to BD conversion and to validate it across a multi-national network of patient databases using the standardization afforded by the Observational Medical Outcomes Partnership (OMOP) common data model. Five “training” US databases were retrospectively analyzed: IBM MarketScan CCAE, MDCR, MDCD, Optum EHR, and Optum Claims. Cyclops regularized logistic regression models were developed on one-year MDD-BD conversion with all standard covariates from the HADES PatientLevelPrediction package. Time-to-conversion Kaplan-Meier analysis was performed up to a decade after MDD, stratified by model-estimated risk. External validation of the final prediction model was performed across 9 patient record databases within the Observational Health Data Sciences and Informatics (OHDSI) network internationally. The model’s area under the curve (AUC) varied 0.633–0.745 (µ = 0.689) across the five US training databases. Nine variables predicted one-year MDD-BD transition. Factors that increased risk were: younger age, severe depression, psychosis, anxiety, substance misuse, self-harm thoughts/actions, and prior mental disorder. AUCs of the validation datasets ranged 0.570–0.785 (µ = 0.664). An assessment algorithm was built for MDD to BD conversion that allows distinguishing as much as 100-fold risk differences among patients and validates well across multiple international data sources.

scholarly journals 117 Impact of Antipsychotic Treatment Switching in Patients with Schizophrenia, Bipolar Disorder, and Major Depressive Disorder

CNS Spectrums ◽  
2020 ◽  
Vol 25 (2) ◽  
pp. 276-276
Author(s):  
Rajeev Ayyagari ◽  
Darren Thomason ◽  
Fan Mu ◽  
Michael Philbin ◽  
Benjamin Carroll
Keyword(s):  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Side Effects ◽  
Depressive Disorder ◽  
Antipsychotic Treatment ◽  
Disease Relapse ◽  
Major Depressive ◽  
Study Objective ◽  
Increased Risk ◽  
Risk Of Relapse

Abstract:Study Objective:To evaluate the risk of relapse for patients with schizophrenia (SZ), bipolar disorder (BP), and major depressive disorder (MDD) who switched antipsychotics compared with those who did not switch.Background:Antipsychotics are commonly used for maintenance treatment of SZ, BP, and MDD but can have significant side effects, such as extrapyramidal symptoms (EPS). Adherence to treatment is important for reducing the risk of relapse, but fear of side effects may prompt medication switching.Methods:Medicaid claims from 6 US states spanning 6 years were retrospectively analyzed for antipsychotic switching versus non-switching. For all patients with SZ, BD or MDD and for the subset of patients who also had ≥1 EPS diagnosis during the baseline period, times to the following outcomes, during a 2-year study period were analyzed: underlying disease relapse, psychiatric relapse, all-cause emergency room (ER) visit, all-cause inpatient (IP) admission and EPS diagnosis.Results:Switchers (N=10,548) had a shorter time to disease relapse, other psychiatric relapse, IP admissions, ER visits, and EPS diagnosis (all, log-rank P<0.001) than non-switchers (N=31,644). Switchers reached the median for IP admission (21.50 months) vs non-switchers (not reached) and for ER visits (switchers, 9.07 months; non-switchers, 13.35 months). For disease relapse, other psychiatric relapse, and EPS diagnosis, <50% of patients had an event during the 2-year study period. Comparisons in a subgroup of patients with ≥1 EPS diagnosis revealed similar outcomes.Conclusions:These results show that disease and other psychiatric relapse, all-cause ER visits, IP admissions, and EPS diagnosis occurred earlier for switchers than for non-switchers, suggesting that switching is associated with an increased risk of relapse in patients with SZ, BP and MDD.Funding Acknowledgements:This study was supported by Teva Pharmaceuticals, Petach Tikva, Israel.

scholarly journals Pleiotropy between neuroticism and physical and mental health: findings from 108 038 men and women in UK Biobank

2015 ◽  
Author(s):  
Catharine Gale ◽  
Saskia P Hagenaars ◽  
Gail Davies ◽  
W David Hill ◽  
David CM Liewald ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Physical Health ◽  
Genetic Correlations ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Major Depressive ◽  
Polygenic Risk ◽  
Increased Risk ◽  
Health Related

There is considerable evidence that people with higher levels of the personality trait neuroticism have an increased risk of several types of mental disorder. Higher neuroticism has also been associated, less consistently, with increased risk of various physical health outcomes. We hypothesised that these associations may, in part, be due to shared genetic influences. We tested for pleiotropy between neuroticism and 12 mental and physical diseases or health traits using linkage disequilibrium regression and polygenic profile scoring. Genetic correlations were derived between neuroticism scores in 108 038 people in UK Biobank and health-related measures from 12 large genome-wide association studies(GWAS). Summary information for the 12 GWAS was used to create polygenic risk scores for the health-related measures in the UK Biobank participants. Associations between the health-related polygenic scores and neuroticism were examined using regression, adjusting for age, sex, genotyping batch, genotyping array, assessment centre, and population stratification. Genetic correlations were identified between neuroticism and anorexia nervosa(rg = 0.17), major depressive disorder (rg = 0.66) and schizophrenia (rg = 0.21). Polygenic risk for several health-related measures were associated with neuroticism, in a positive direction in the case of bipolar disorder (β = 0.017), major depressive disorder (β = 0.036), schizophrenia (β = 0.036), and coronary artery disease (β = 0.011), and in a negative direction in the case of BMI (β = -0.0095). These findings indicate that a high level of pleiotropy exists between neuroticism and some measures of mental and physical health, particularly major depressive disorder and schizophrenia.

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