scholarly journals Understanding Cognitive Impairment in Mood Disorders: Mediation Analyses in the UK Biobank Cohort

2019 ◽  
Author(s):  
Breda Cullen ◽  
Daniel J. Smith ◽  
Ian J. Deary ◽  
Jill P. Pell ◽  
Katherine M. Keyes ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Major Depression ◽  
Mood Disorders ◽  
Psychotropic Medication ◽  
Estimation Methods ◽  
Cardiometabolic Disease ◽  
Visuospatial Memory ◽  
Uk Biobank ◽  
Small Magnitude ◽  
The Uk

AbstractBackgroundCognitive impairment is strongly linked with persistent disability in people with mood disorders, but the factors that explain cognitive impairment in this population are unclear.AimsWe aimed to estimate the total effect of (i) bipolar disorder (BD) and (ii) major depression on cognitive function, and the magnitude of the effect that was explained by potentially modifiable intermediate factors.MethodCross-sectional study using baseline data from the UK Biobank cohort. Participants were categorised as BD (N=2,709), major depression (N=50,975), or no mood disorder (N=102,931 to 105,284). The outcomes were computerised tests of reasoning, reaction time and memory. The potential mediators were cardiometabolic disease and psychotropic medication. Analyses were informed by graphical methods, and controlled for confounding using regression, propensity score-based methods, and G-computation.ResultsGroup differences of small magnitude were found on a visuospatial memory test. Z-score differences for BD were in the range −0.23 to −0.17 (95% CI range −0.39 to −0.03) across different estimation methods, and approximately −0.07 (95% CI −0.10 to −0.03) for major depression. One-quarter of the effect was mediated via psychotropic medication in the BD group (−0.05; 95% CI −0.09 to −0.01). No evidence was found for mediation via cardiometabolic disease.ConclusionsIn a large community-based sample in middle to early old age, BD and depression were associated with lower visuospatial memory performance, in part potentially due to psychotropic medication use. Mood disorders and their treatments will have increasing importance for population cognitive health as the proportion of older adults continues to grow.

scholarly journals Understanding cognitive impairment in mood disorders: mediation analyses in the UK Biobank cohort

2019 ◽  
Vol 215 (5) ◽  
pp. 683-690 ◽  
Author(s):  
Breda Cullen ◽  
Daniel J. Smith ◽  
Ian J. Deary ◽  
Jill P. Pell ◽  
Katherine M. Keyes ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Cognitive Impairment ◽  
Major Depression ◽  
Mood Disorders ◽  
Psychotropic Medication ◽  
Estimation Methods ◽  
Cardiometabolic Disease ◽  
Visuospatial Memory ◽  
Uk Biobank ◽  
The Uk

BackgroundCognitive impairment is strongly linked with persistent disability in people with mood disorders, but the factors that explain cognitive impairment in this population are unclear.AimsTo estimate the total effect of (a) bipolar disorder and (b) major depression on cognitive function, and the magnitude of the effect that is explained by potentially modifiable intermediate factors.MethodCross-sectional study using baseline data from the UK Biobank cohort. Participants were categorised as having bipolar disorder (n = 2709), major depression (n = 50 975) or no mood disorder (n = 102 931 and n = 105 284). The outcomes were computerised tests of reasoning, reaction time and memory. The potential mediators were cardiometabolic disease and psychotropic medication. Analyses were informed by graphical methods and controlled for confounding using regression, propensity score-based methods and G-computation.ResultsGroup differences of small magnitude were found on a visuospatial memory test. Z-score differences for the bipolar disorder group were in the range −0.23 to −0.17 (95% CI −0.39 to −0.03) across different estimation methods, and for the major depression group they were approximately −0.07 (95% CI −0.10 to −0.03). One-quarter of the effect was mediated via psychotropic medication in the bipolar disorder group (−0.05; 95% CI −0.09 to −0.01). No evidence was found for mediation via cardiometabolic disease.ConclusionsIn a large community-based sample in middle to early old age, bipolar disorder and depression were associated with lower visuospatial memory performance, in part potentially due to psychotropic medication use. Mood disorders and their treatments will have increasing importance for population cognitive health as the proportion of older adults continues to grow.Declaration of interestI.J.D. is a UK Biobank participant. J.P.P. is a member of the UK Biobank Steering Committee.

scholarly journals Accurate, scalable and integrative haplotype estimation

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Olivier Delaneau ◽  
Jean-François Zagury ◽  
Matthew R. Robinson ◽  
Jonathan L. Marchini ◽  
Emmanouil T. Dermitzakis
Keyword(s):  
Sample Size ◽  
Open Source ◽  
Gold Standard ◽  
Estimation Methods ◽  
Uk Biobank ◽  
Haplotype Estimation ◽  
High Coverage ◽  
Human Genomes ◽  
The Uk

AbstractThe number of human genomes being genotyped or sequenced increases exponentially and efficient haplotype estimation methods able to handle this amount of data are now required. Here we present a method, SHAPEIT4, which substantially improves upon other methods to process large genotype and high coverage sequencing datasets. It notably exhibits sub-linear running times with sample size, provides highly accurate haplotypes and allows integrating external phasing information such as large reference panels of haplotypes, collections of pre-phased variants and long sequencing reads. We provide SHAPEIT4 in an open source format and demonstrate its performance in terms of accuracy and running times on two gold standard datasets: the UK Biobank data and the Genome In A Bottle.

scholarly journals Association of Body Mass Index With Cardiometabolic Disease in the UK Biobank

2017 ◽  
Vol 2 (8) ◽  
pp. 882 ◽  
Author(s):  
Donald M. Lyall ◽  
Carlos Celis-Morales ◽  
Joey Ward ◽  
Stamatina Iliodromiti ◽  
Jana J. Anderson ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Cardiometabolic Disease ◽  
Uk Biobank ◽  
The Uk

Abstract 16105: Depression Modulates Polygenic Risk of Cardiovascular and Cardiometabolic Disease

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Michael C Honigberg ◽  
Amy Sarma ◽  
Nandita Scott ◽  
Malissa J Wood ◽  
Pradeep Natarajan
Keyword(s):  
Atrial Fibrillation ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Health Behaviors ◽  
Genetic Risk ◽  
Cardiometabolic Disease ◽  
Uk Biobank ◽  
Polygenic Risk ◽  
Artery Disease ◽  
The Uk

Introduction: Depression is associated with an increased risk of coronary artery disease (CAD). Whether depression modifies genetic risk of cardiovascular and cardiometabolic disease is unknown. Methods: We included genotyped, unrelated European ancestry individuals in the UK Biobank. Using genome-wide significant single nucleotide polymorphisms (SNPs) from studies external to the UK Biobank, we generated polygenic risk scores (PRS) for coronary artery disease (CAD, 74 SNPs), hypertension (75 SNPs), type 2 diabetes (T2D, 64 SNPs), atrial fibrillation (25 SNPs), and ischemic stroke (11 SNPs). Participants were stratified by PRS for each condition as low (quintile 1), intermediate (quintiles 2-4), and high (quintile 5) genetic risk. Cox models tested the association of depression frequency with each incident condition among individuals with high PRS, with adjustment for age, sex, the first 20 principal components, genotyping array, and Townsend deprivation index. Additional models further adjusted for health behaviors (exercise, tobacco and alcohol use, vegetable and fresh fruit intake) and tested associations across the PRS spectrum. Results: Among 348,083 individuals, 78,664 (22.6%) reported depression in the past 2 weeks, including 14,776 (4.2%) with depression more than half of days. Depression burden modified the risk of incident CAD across the spectrum of CAD polygenic risk (Figure 1A). Among individuals with high PRS, lack of depression was associated with lower risk of incident CAD (HR 0.70, 95% 0.58-0.86), hypertension (HR 0.58, 95% CI 0.50-0.67), T2D (HR 0.48, 95% CI 0.41-0.55), and atrial fibrillation (HR 0.74, 95% CI 0.62-0.89) compared to those with a high burden of depression. These risk reductions were minimally attenuated after further adjustment for health behaviors (Figure 1B). Conclusions: Lower burden of depression was associated was decreased risks of cardiovascular disease among individuals at high genetic cardiovascular risk.

scholarly journals Cognitive functioning and lifetime major depressive disorder in UK Biobank

2020 ◽  
Vol 63 (1) ◽  
Author(s):  
Laura de Nooij ◽  
Mathew A. Harris ◽  
Mark J. Adams ◽  
Toni-Kim Clarke ◽  
Xueyi Shen ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Cognitive Impairment ◽  
Depressive Disorder ◽  
Cognitive Functioning ◽  
Psychotropic Medication ◽  
Clinical Characteristics ◽  
Population Based ◽  
Uk Biobank ◽  
Major Depressive ◽  
Psychosocial Impairment

Abstract Background. Cognitive impairment associated with lifetime major depressive disorder (MDD) is well-supported by meta-analytic studies, but population-based estimates remain scarce. Previous UK Biobank studies have only shown limited evidence of cognitive differences related to probable MDD. Using updated cognitive and clinical assessments in UK Biobank, this study investigated population-level differences in cognitive functioning associated with lifetime MDD. Methods. Associations between lifetime MDD and cognition (performance on six tasks and general cognitive functioning [g-factor]) were investigated in UK Biobank (N-range 7,457–14,836, age 45–81 years, 52% female), adjusting for demographics, education, and lifestyle. Lifetime MDD classifications were based on the Composite International Diagnostic Interview. Within the lifetime MDD group, we additionally investigated relationships between cognition and (a) recurrence, (b) current symptoms, (c) severity of psychosocial impairment (while symptomatic), and (d) concurrent psychotropic medication use. Results. Lifetime MDD was robustly associated with a lower g-factor (β = −0.10, PFDR = 4.7 × 10−5), with impairments in attention, processing speed, and executive functioning (β ≥ 0.06). Clinical characteristics revealed differential profiles of cognitive impairment among case individuals; those who reported severe psychosocial impairment and use of psychotropic medication performed worse on cognitive tests. Severe psychosocial impairment and reasoning showed the strongest association (β = −0.18, PFDR = 7.5 × 10−5). Conclusions. Findings describe small but robust associations between lifetime MDD and lower cognitive performance within a population-based sample. Overall effects were of modest effect size, suggesting limited clinical relevance. However, deficits within specific cognitive domains were more pronounced in relation to clinical characteristics, particularly severe psychosocial impairment.

scholarly journals Polygenic risk for immuno-metabolic markers and specific depressive symptoms: A multi-sample network analysis study

2021 ◽  
Author(s):  
Nils Kappelmann ◽  
Darina Czamara ◽  
Nicolas Rost ◽  
Sylvain Moser ◽  
Vanessa Schmoll ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Network Analysis ◽  
Inflammatory Markers ◽  
Quality Criteria ◽  
Estimation Methods ◽  
Uk Biobank ◽  
Metabolic Markers ◽  
Model Search ◽  
Tnf Α ◽  
The Uk

ABSTRACTBackgroundAbout every fourth patient with major depressive disorder (MDD) shows evidence of systemic inflammation. Previous studies have shown inflammation-depression associations of multiple serum inflammatory markers and multiple specific depressive symptoms. It remains unclear, however, if these associations extend to genetic/lifetime predisposition to higher inflammatory marker levels and what role metabolic factors such as Body Mass Index (BMI) play. It is also unclear whether inflammation-symptom associations reflect direct or indirect associations, which can be disentangled using network analysis.MethodsThis study examined associations of polygenic risk scores (PRSs) for immuno-metabolic markers (C-reactive protein [CRP], interleukin [IL]-6, IL-10, tumour necrosis factor [TNF]-α, BMI) with seven depressive symptoms in one general population sample, the UK Biobank study (n=110,010), and two patient samples, the Munich Antidepressant Response Signature (MARS, n=1,058) and Sequenced Treatment Alternatives to Relieve Depression (STAR*D, n=1,143) studies. Network analysis was applied jointly for these samples using fused graphical least absolute shrinkage and selection operator (FGL) estimation as primary analysis and, individually, using unregularized model search estimation. Stability of results was assessed using bootstrapping and three quality criteria were defined to appraise consistency of results across estimation methods, network bootstrapping, and samples.ResultsNetwork analysis results displayed to-be-expected PRS-PRS and symptom-symptom associations (termed edges), respectively, that were mostly positive. Using FGL estimation, results further suggested 28, 29, and six PRS-symptom edges in MARS, STAR*D, and UK Biobank samples, respectively. Unregularized model search estimation suggested three PRS-symptom edges in the UK Biobank sample. Applying our quality criteria to these associations indicated that only the association of higher CRP PRS with greater changes in appetite fulfilled all three criteria. Four additional associations fulfilled at least two quality criteria; specifically, higher CRP PRS was associated with greater fatigue and reduced anhedonia, higher TNF-α PRS was associated with greater fatigue, and higher BMI PRS with greater changes in appetite and anhedonia. Associations of the BMI PRS with anhedonia, however, showed an inconsistent valence across estimation methods.ConclusionsOur findings align with previous studies suggesting that systemic inflammatory markers are primarily associated with somatic/neurovegetative symptoms of depression such as changes in appetite and fatigue. We extend these findings by providing evidence that associations are direct (using network analysis) and extend to genetic predisposition to immuno-metabolic markers (using PRSs). Our findings can inform selection of patients with inflammation-related symptoms into clinical trials of immune-modulating drugs for MDD.

scholarly journals Obesity impairs cognitive function via metabolic syndrome and cerebrovascular disease: an SEM analysis in 15,000 adults from the UK Biobank

2020 ◽  
Author(s):  
Filip Morys ◽  
Mahsa Dadar ◽  
Alain Dagher
Keyword(s):  
Metabolic Syndrome ◽  
Cognitive Impairment ◽  
White Matter ◽  
Cerebrovascular Disease ◽  
Cortical Thickness ◽  
White Matter Hyperintensities ◽  
Uk Biobank ◽  
Central Nervous System Damage ◽  
The Uk ◽  
The Relationship

AbstractChronic obesity is associated with several complications, including cognitive impairment and dementia. However, we have piecemeal knowledge of the mechanisms linking obesity to central nervous system damage. Adiposity leads to the metabolic syndrome, consisting of inflammation, hypertension, dyslipidemia and insulin resistance. In turn, these metabolic abnormalities cause cerebrovascular dysfunction, which may cause white and grey matter tissue loss and consequent cognitive impairment. While there have been several neuroimaging studies linking adiposity to changes in brain morphometry, a comprehensive investigation of the relationship has so far not been done. Here we use structural equation modelling applied to over 15,000 individuals from the UK Biobank to identify the causal chain that links adiposity to cognitive dysfunction. We found that body mass index and waist-to-hip ratio were positively related to higher plasma C-reactive protein, dyslipidemia, occurrence of hypertension and diabetes, all of which were in turn related to cerebrovascular disease as measured by volume of white matter hyperintensities on magnetic resonance imaging. White mater hyperintensities were associated with lower cortical thickness and volume and higher subcortical volumes, which were associated with cognitive deficits on tests of visuospatial memory, fluid intelligence, and working memory among others. In follow-up analyses we found that inflammation, hypertension and diabetes mediated 20% of the relationship between obesity and cerebrovascular disease and that cerebrovascular disease mediated a significant proportion of the relationship between obesity and cortical thickness and volume. We also showed that volume of white matter hyperintensities was related to decreased fractional anisotropy and increased mean diffusivity in the majority of white matter tracts, pointing to white matter dysconnectivity as a major cause of impaired cognition. Our results have clinical implications, supporting a role for the management of adiposity in the prevention of late-life dementia and cognitive decline.

scholarly journals Integrative haplotype estimation with sub-linear complexity

2018 ◽  
Author(s):  
Olivier Delaneau ◽  
Jean-Francois Zagury ◽  
Matthew R Robinson ◽  
Jonathan Marchini ◽  
Emmanouil Dermitzakis
Keyword(s):  
Sample Size ◽  
Gold Standard ◽  
Linear Complexity ◽  
Estimation Methods ◽  
Linear Scaling ◽  
Uk Biobank ◽  
Haplotype Estimation ◽  
High Coverage ◽  
Human Genomes ◽  
The Uk

The number of human genomes being genotyped or sequenced increases exponentially and efficient haplotype estimation methods able to handle this amount of data are now required. Here, we present a new method, SHAPEIT4, which substantially improves upon other methods to process large genotype and high coverage sequencing datasets. It notably exhibits sub-linear scaling with sample size, provides highly accurate haplotypes and allows integrating external phasing information such as large reference panels of haplotypes, collections of pre-phased variants and long sequencing reads. We provide SHAPET4 in an open source format on https://odelaneau.github.io/shapeit4/ and demonstrate its performance in terms of accuracy and running times on two gold standard datasets: the UK Biobank data and the Genome In A Bottle.

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