Publications by authors named "Saskia P Hagenaars"

52 Publications

Transcriptome-wide association study of treatment-resistant depression and depression subtypes for drug repurposing.

Neuropsychopharmacology 2021 09 22;46(10):1821-1829. Epub 2021 Jun 22.

Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy.

Major depressive disorder (MDD) is the single largest contributor to global disability and up to 20-30% of patients do not respond to at least two antidepressants (treatment-resistant depression, TRD). This study leveraged imputed gene expression in TRD to perform a drug repurposing analysis. Among those with MDD, we defined TRD as having at least two antidepressant switches according to primary care records in UK Biobank (UKB). We performed a transcriptome-wide association study (TWAS) of TRD (n = 2165) vs healthy controls (n = 11,188) using FUSION and gene expression levels from 21 tissues. We identified compounds with opposite gene expression signatures (ConnectivityMap data) compared to our TWAS results using the Kolmogorov-Smirnov test, Spearman and Pearson correlation. As symptom patterns are routinely assessed in clinical practice and could be used to provide targeted treatments, we identified MDD subtypes associated with TRD in UKB and analysed them using the same pipeline described for TRD. Anxious MDD (n = 14,954) and MDD with weight gain (n = 4697) were associated with TRD. In the TWAS, two genes were significantly dysregulated (TMEM106B and ATP2A1 for anxious and weight gain MDD, respectively). A muscarinic receptor antagonist was identified as top candidate for repurposing in TRD; inhibition of heat shock protein 90 was the main mechanism of action identified for anxious MDD, while modulators of metabolism such as troglitazone showed promising results for MDD with weight gain. This was the first TWAS of TRD and associated MDD subtypes. Our results shed light on possible pharmacological approaches in individuals with difficult-to-treat depression.
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http://dx.doi.org/10.1038/s41386-021-01059-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8357803PMC
September 2021

Using Mendelian Randomisation methods to understand whether diurnal preference is causally related to mental health.

Mol Psychiatry 2021 Jun 8. Epub 2021 Jun 8.

Genetics of Complex Traits, The College of Medicine and Health, University of Exeter, The RILD Building, RD&E Hospital, Exeter, UK.

Late diurnal preference has been linked to poorer mental health outcomes, but the understanding of the causal role of diurnal preference on mental health and wellbeing is currently limited. Late diurnal preference is often associated with circadian misalignment (a mismatch between the timing of the endogenous circadian system and behavioural rhythms), so that evening people live more frequently against their internal clock. This study aims to quantify the causal contribution of diurnal preference on mental health outcomes, including anxiety, depression and general wellbeing and test the hypothesis that more misaligned individuals have poorer mental health and wellbeing using an actigraphy-based measure of circadian misalignment. Multiple Mendelian Randomisation (MR) approaches were used to test causal pathways between diurnal preference and seven well-validated mental health and wellbeing outcomes in up to 451,025 individuals. In addition, observational analyses tested the association between a novel, objective measure of behavioural misalignment (Composite Phase Deviation, CPD) and seven mental health and wellbeing outcomes. Using genetic instruments identified in the largest GWAS for diurnal preference, we provide robust evidence that early diurnal preference is protective for depression and improves wellbeing. For example, using one-sample MR, a twofold higher genetic liability of morningness was associated with lower odds of depressive symptoms (OR: 0.92, 95% CI: 0.88, 0.97). It is possible that behavioural factors including circadian misalignment may contribute in the chronotype depression relationship, but further work is needed to confirm these findings.
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http://dx.doi.org/10.1038/s41380-021-01157-3DOI Listing
June 2021

Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology.

Nat Genet 2021 06 17;53(6):817-829. Epub 2021 May 17.

Department of Neuroscience, Istituto Di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.

Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.
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http://dx.doi.org/10.1038/s41588-021-00857-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8192451PMC
June 2021

Elevated C-Reactive Protein in Patients With Depression, Independent of Genetic, Health, and Psychosocial Factors: Results From the UK Biobank.

Am J Psychiatry 2021 06 14;178(6):522-529. Epub 2021 May 14.

Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience (Pitharouli, Hotopf, Pariante), and Social, Genetic and Developmental Psychiatry Centre (Pitharouli, Hagenaars, Glanville, Coleman, Lewis), King's College London, London; National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service Foundation Trust, London (Hotopf, Lewis, Pariante).

Objective: The authors investigated the pathways (genetic, environmental, lifestyle, medical) leading to inflammation in major depressive disorder using C-reactive protein (CRP), genetic, and phenotypic data from the UK Biobank.

Methods: This was a case-control study of 26,894 participants with a lifetime diagnosis of major depressive disorder from the Composite International Diagnostic Interview and 59,001 control subjects who reported no mental disorder and had not reported taking any antidepressant medication. Linear regression models of log CRP level were fitted to regress out the effects of age, sex, body mass index (BMI), and smoking and to test whether the polygenic risk score (PRS) for major depression was associated with log CRP level and whether the association between log CRP level and major depression remained after adjusting for early-life trauma, socioeconomic status, and self-reported health status.

Results: CRP levels were significantly higher in patients with depression relative to control subjects (2.4 mg/L compared with 2.1 mg/L, respectively), and more case than control subjects had CRP levels >3 mg/L (21.2% compared with 16.8%, respectively), indicating low-grade inflammation. The PRS for depression was positively and significantly associated with log CRP levels, but this association was no longer significant after adjustment for BMI and smoking. The association between depression and increased log CRP level was substantially reduced, but still remained significant, after adjustment for the aforementioned clinical and sociodemographic factors.

Conclusions: The data indicate that the "genetic" contribution to increased inflammation in depression is due to regulation of eating and smoking habits rather than an "autoimmune" genetic predisposition. Moreover, the association between depression and increased inflammation even after full adjustment indicates either the presence of yet unknown or unmeasured psychosocial and clinical confounding factors or that a core biological association between depression and increased inflammation exists independently from confounders.
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http://dx.doi.org/10.1176/appi.ajp.2020.20060947DOI Listing
June 2021

Evaluation of polygenic prediction methodology within a reference-standardized framework.

PLoS Genet 2021 05 4;17(5):e1009021. Epub 2021 May 4.

Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.

The predictive utility of polygenic scores is increasing, and many polygenic scoring methods are available, but it is unclear which method performs best. This study evaluates the predictive utility of polygenic scoring methods within a reference-standardized framework, which uses a common set of variants and reference-based estimates of linkage disequilibrium and allele frequencies to construct scores. Eight polygenic score methods were tested: p-value thresholding and clumping (pT+clump), SBLUP, lassosum, LDpred1, LDpred2, PRScs, DBSLMM and SBayesR, evaluating their performance to predict outcomes in UK Biobank and the Twins Early Development Study (TEDS). Strategies to identify optimal p-value thresholds and shrinkage parameters were compared, including 10-fold cross validation, pseudovalidation and infinitesimal models (with no validation sample), and multi-polygenic score elastic net models. LDpred2, lassosum and PRScs performed strongly using 10-fold cross-validation to identify the most predictive p-value threshold or shrinkage parameter, giving a relative improvement of 16-18% over pT+clump in the correlation between observed and predicted outcome values. Using pseudovalidation, the best methods were PRScs, DBSLMM and SBayesR. PRScs pseudovalidation was only 3% worse than the best polygenic score identified by 10-fold cross validation. Elastic net models containing polygenic scores based on a range of parameters consistently improved prediction over any single polygenic score. Within a reference-standardized framework, the best polygenic prediction was achieved using LDpred2, lassosum and PRScs, modeling multiple polygenic scores derived using multiple parameters. This study will help researchers performing polygenic score studies to select the most powerful and predictive analysis methods.
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http://dx.doi.org/10.1371/journal.pgen.1009021DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8121285PMC
May 2021

Associations and limited shared genetic aetiology between bipolar disorder and cardiometabolic traits in the UK Biobank.

Psychol Med 2021 Mar 26:1-10. Epub 2021 Mar 26.

Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.

Background: People with bipolar disorder (BPD) are more likely to die prematurely, which is partly attributed to comorbid cardiometabolic traits. Previous studies report cardiometabolic abnormalities in BPD, but their shared aetiology remains poorly understood. This study examined the phenotypic associations and shared genetic aetiology between BPD and various cardiometabolic traits.

Methods: In a subset of the UK Biobank sample (N = 61 508) we investigated phenotypic associations between BPD (ncases = 4186) and cardiometabolic traits, represented by biomarkers, anthropometric traits and cardiometabolic diseases. To determine shared genetic aetiology in European ancestry, polygenic risk scores (PRS) and genetic correlations were calculated between BPD and cardiometabolic traits.

Results: Several traits were significantly associated with increased risk for BPD, namely low total cholesterol, low high-density lipoprotein cholesterol, high triglycerides, high glycated haemoglobin, low systolic blood pressure, high body mass index, high waist-to-hip ratio; and stroke, coronary artery disease and type 2 diabetes diagnosis. BPD was associated with higher polygenic risk for triglycerides, waist-to-hip ratio, coronary artery disease and type 2 diabetes. Shared genetic aetiology persisted for coronary artery disease, when correcting PRS associations for cardiometabolic base phenotypes. Associations were not replicated using genetic correlations.

Conclusions: This large study identified increased phenotypic cardiometabolic abnormalities in BPD participants. It is found that the comorbidity of coronary artery disease may be based on shared genetic aetiology. These results motivate hypothesis-driven research to consider individual cardiometabolic traits rather than a composite metabolic syndrome when attempting to disentangle driving mechanisms of cardiometabolic abnormalities in BPD.
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http://dx.doi.org/10.1017/S0033291721000945DOI Listing
March 2021

Genetic and clinical characteristics of treatment-resistant depression using primary care records in two UK cohorts.

Mol Psychiatry 2021 Mar 22. Epub 2021 Mar 22.

Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.

Treatment-resistant depression (TRD) is a major contributor to the disability caused by major depressive disorder (MDD). Primary care electronic health records provide an easily accessible approach to investigate TRD clinical and genetic characteristics. MDD defined from primary care records in UK Biobank (UKB) and EXCEED studies was compared with other measures of depression and tested for association with MDD polygenic risk score (PRS). Using prescribing records, TRD was defined from at least two switches between antidepressant drugs, each prescribed for at least 6 weeks. Clinical-demographic characteristics, SNP-based heritability (h) and genetic overlap with psychiatric and non-psychiatric traits were compared in TRD and non-TRD MDD cases. In 230,096 and 8926 UKB and EXCEED participants with primary care data, respectively, the prevalence of MDD was 8.7% and 14.2%, of which 13.2% and 13.5% was TRD, respectively. In both cohorts, MDD defined from primary care records was strongly associated with MDD PRS, and in UKB it showed overlap of 71-88% with other MDD definitions. In UKB, TRD vs healthy controls and non-TRD vs healthy controls h was comparable (0.25 [SE = 0.04] and 0.19 [SE = 0.02], respectively). TRD vs non-TRD was positively associated with the PRS of attention deficit hyperactivity disorder, with lower socio-economic status, obesity, higher neuroticism and other unfavourable clinical characteristics. This study demonstrated that MDD and TRD can be reliably defined using primary care records and provides the first large scale population assessment of the genetic, clinical and demographic characteristics of TRD.
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http://dx.doi.org/10.1038/s41380-021-01062-9DOI Listing
March 2021

Cerebral small vessel disease genomics and its implications across the lifespan.

Nat Commun 2020 12 8;11(1):6285. Epub 2020 Dec 8.

University of Alabama at Birmingham School of Medicine, Birmingham, AL, 35233, USA.

White matter hyperintensities (WMH) are the most common brain-imaging feature of cerebral small vessel disease (SVD), hypertension being the main known risk factor. Here, we identify 27 genome-wide loci for WMH-volume in a cohort of 50,970 older individuals, accounting for modification/confounding by hypertension. Aggregated WMH risk variants were associated with altered white matter integrity (p = 2.5×10-7) in brain images from 1,738 young healthy adults, providing insight into the lifetime impact of SVD genetic risk. Mendelian randomization suggested causal association of increasing WMH-volume with stroke, Alzheimer-type dementia, and of increasing blood pressure (BP) with larger WMH-volume, notably also in persons without clinical hypertension. Transcriptome-wide colocalization analyses showed association of WMH-volume with expression of 39 genes, of which four encode known drug targets. Finally, we provide insight into BP-independent biological pathways underlying SVD and suggest potential for genetic stratification of high-risk individuals and for genetically-informed prioritization of drug targets for prevention trials.
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http://dx.doi.org/10.1038/s41467-020-19111-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7722866PMC
December 2020

Examining the association between family status and depression in the UK Biobank.

J Affect Disord 2021 01 10;279:585-598. Epub 2020 Oct 10.

Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom. Electronic address:

Background: We examined associations between family status (living with a spouse or partner and number of children) and lifetime depression.

Methods: We used data from the UK Biobank, a large prospective study of middle-aged and older adults. Lifetime depression was assessed as part of a follow-up mental health questionnaire. Logistic regression was used to estimate associations between family status and depression. We included extensive adjustment for social, demographic and other potential confounders, including depression polygenic risk scores.

Results: 52,078 participants (mean age = 63.6, SD = 7.6; 52% female) were included in our analyses. Living with a spouse or partner was associated with substantially lower odds of lifetime depression (OR = 0.67, 95% CI 0.62-0.74). Compared to individuals without children, we found higher odds of lifetime depression for parents of one child (OR = 1.17, 95% CI 1.07-1.27) and parents of three (OR = 1.11, 95% CI 1.03-1.20) or four or more children (OR = 1.27, 95% CI 1.14-1.42). Amongst those not cohabiting, having any number of children was associated with higher odds of lifetime depression. Our results were consistent across age groups, the sexes, neighbourhood deprivation and genetic risk for depression. Exploratory Mendelian randomisation analyses suggested a causal effect of number of children on lifetime depression.

Limitations: Our data did not allow distinguishing between non-marital and marital cohabitation. Results may not generalise to all ages or populations.

Conclusions: Living with a spouse or partner was strongly associated with reduced odds of depression. Having one or three or more children was associated with increased odds of depression, especially in individuals not living with a spouse or partner.
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http://dx.doi.org/10.1016/j.jad.2020.10.017DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7780845PMC
January 2021

Genetic comorbidity between major depression and cardio-metabolic traits, stratified by age at onset of major depression.

Am J Med Genet B Neuropsychiatr Genet 2020 09 18;183(6):309-330. Epub 2020 Jul 18.

Max Planck Institute of Psychiatry, Munich, Germany.

It is imperative to understand the specific and shared etiologies of major depression and cardio-metabolic disease, as both traits are frequently comorbid and each represents a major burden to society. This study examined whether there is a genetic association between major depression and cardio-metabolic traits and if this association is stratified by age at onset for major depression. Polygenic risk scores analysis and linkage disequilibrium score regression was performed to examine whether differences in shared genetic etiology exist between depression case control status (N cases = 40,940, N controls = 67,532), earlier (N = 15,844), and later onset depression (N = 15,800) with body mass index, coronary artery disease, stroke, and type 2 diabetes in 11 data sets from the Psychiatric Genomics Consortium, Generation Scotland, and UK Biobank. All cardio-metabolic polygenic risk scores were associated with depression status. Significant genetic correlations were found between depression and body mass index, coronary artery disease, and type 2 diabetes. Higher polygenic risk for body mass index, coronary artery disease, and type 2 diabetes was associated with both early and later onset depression, while higher polygenic risk for stroke was associated with later onset depression only. Significant genetic correlations were found between body mass index and later onset depression, and between coronary artery disease and both early and late onset depression. The phenotypic associations between major depression and cardio-metabolic traits may partly reflect their overlapping genetic etiology irrespective of the age depression first presents.
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http://dx.doi.org/10.1002/ajmg.b.32807DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7991693PMC
September 2020

Depression with atypical neurovegetative symptoms shares genetic predisposition with immuno-metabolic traits and alcohol consumption.

Psychol Med 2020 Jul 6:1-11. Epub 2020 Jul 6.

Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.

Background: Depression is a highly prevalent and heterogeneous disorder. This study aims to determine whether depression with atypical features shows different heritability and different degree of overlap with polygenic risk for psychiatric and immuno-metabolic traits than other depression subgroups.

Methods: Data included 30 069 European ancestry individuals from the UK Biobank who met criteria for lifetime major depression. Participants reporting both weight gain and hypersomnia were classified as ↑WS depression (N = 1854) and the others as non-↑WS depression (N = 28 215). Cases with non-↑WS depression were further classified as ↓WS depression (i.e. weight loss and insomnia; N = 10 142). Polygenic risk scores (PRS) for 22 traits were generated using genome-wide summary statistics (Bonferroni corrected p = 2.1 × 10-4). Single-nucleotide polymorphism (SNP)-based heritability of depression subgroups was estimated.

Results: ↑WS depression had a higher polygenic risk for BMI [OR = 1.20 (1.15-1.26), p = 2.37 × 10-14] and C-reactive protein [OR = 1.11 (1.06-1.17), p = 8.86 × 10-06] v. non-↑WS depression and ↓WS depression. Leptin PRS was close to the significance threshold (p = 2.99 × 10-04), but the effect disappeared when considering GWAS summary statistics of leptin adjusted for BMI. PRS for daily alcohol use was inversely associated with ↑WS depression [OR = 0.88 (0.83-0.93), p = 1.04 × 10-05] v. non-↑WS depression. SNP-based heritability was not significantly different between ↑WS depression and ↓WS depression (14.3% and 12.2%, respectively).

Conclusions: ↑WS depression shows evidence of distinct genetic predisposition to immune-metabolic traits and alcohol consumption. These genetic signals suggest that biological targets including immune-cardio-metabolic pathways may be relevant to therapies in individuals with ↑WS depression.
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http://dx.doi.org/10.1017/S0033291720002342DOI Listing
July 2020

Using major depression polygenic risk scores to explore the depressive symptom continuum.

Psychol Med 2021 Jul 19:1-10. Epub 2021 Jul 19.

Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.

Background: Major depression (MD) is often characterised as a categorical disorder; however, observational studies comparing sub-threshold and clinical depression suggest MD is continuous. Many of these studies do not explore the full continuum and are yet to consider genetics as a risk factor. This study sought to understand if polygenic risk for MD could provide insight into the continuous nature of depression.

Methods: Factor analysis on symptom-level data from the UK Biobank (N = 148 957) was used to derive continuous depression phenotypes which were tested for association with polygenic risk scores (PRS) for a categorical definition of MD (N = 119 692).

Results: Confirmatory factor analysis showed a five-factor hierarchical model, incorporating 15 of the original 18 items taken from the PHQ-9, GAD-7 and subjective well-being questionnaires, produced good fit to the observed covariance matrix (CFI = 0.992, TLI = 0.99, RMSEA = 0.038, SRMR = 0.031). MD PRS associated with each factor score (standardised β range: 0.057-0.064) and the association remained when the sample was stratified into case- and control-only subsets. The case-only subset had an increased association compared to controls for all factors, shown via a significant interaction between lifetime MD diagnosis and MD PRS (p value range: 2.23 × 10-3-3.94 × 10-7).

Conclusions: An association between MD PRS and a continuous phenotype of depressive symptoms in case- and control-only subsets provides support against a purely categorical phenotype; indicating further insights into MD can be obtained when this within-group variation is considered. The stronger association within cases suggests this variation may be of particular importance.
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http://dx.doi.org/10.1017/S0033291720001828DOI Listing
July 2021

Studying individual risk factors for self-harm in the UK Biobank: A polygenic scoring and Mendelian randomisation study.

PLoS Med 2020 06 1;17(6):e1003137. Epub 2020 Jun 1.

Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.

Background: Identifying causal risk factors for self-harm is essential to inform preventive interventions. Epidemiological studies have identified risk factors associated with self-harm, but these associations can be subject to confounding. By implementing genetically informed methods to better account for confounding, this study aimed to better identify plausible causal risk factors for self-harm.

Methods And Findings: Using summary statistics from 24 genome-wide association studies (GWASs) comprising 16,067 to 322,154 individuals, polygenic scores (PSs) were generated to index 24 possible individual risk factors for self-harm (i.e., mental health vulnerabilities, substance use, cognitive traits, personality traits, and physical traits) among a subset of UK Biobank participants (N = 125,925, 56.2% female) who completed an online mental health questionnaire in the period from 13 July 2016 to 27 July 2017. In total, 5,520 (4.4%) of these participants reported having self-harmed in their lifetime. In binomial regression models, PSs indexing 6 risk factors (major depressive disorder [MDD], attention deficit/hyperactivity disorder [ADHD], bipolar disorder, schizophrenia, alcohol dependence disorder, and lifetime cannabis use) predicted self-harm, with effect sizes ranging from odds ratio (OR) = 1.05 (95% CI 1.02 to 1.07, q = 0.008) for lifetime cannabis use to OR = 1.20 (95% CI 1.16 to 1.23, q = 1.33 × 10-35) for MDD. No systematic differences emerged between suicidal and non-suicidal self-harm. To further probe causal relationships, two-sample Mendelian randomisation (MR) analyses were conducted, with MDD, ADHD, and schizophrenia emerging as the most plausible causal risk factors for self-harm. The genetic liabilities for MDD and schizophrenia were associated with self-harm independently of diagnosis and medication. Main limitations include the lack of representativeness of the UK Biobank sample, that self-harm was self-reported, and the limited power of some of the included GWASs, potentially leading to possible type II error.

Conclusions: In addition to confirming the role of MDD, we demonstrate that ADHD and schizophrenia likely play a role in the aetiology of self-harm using multivariate genetic designs for causal inference. Among the many individual risk factors we simultaneously considered, our findings suggest that systematic detection and treatment of core psychiatric symptoms, including psychotic and impulsivity symptoms, may be beneficial among people at risk for self-harm.
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http://dx.doi.org/10.1371/journal.pmed.1003137DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7263593PMC
June 2020

Genetic stratification of depression in UK Biobank.

Transl Psychiatry 2020 05 24;10(1):163. Epub 2020 May 24.

Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK.

Depression is a common and clinically heterogeneous mental health disorder that is frequently comorbid with other diseases and conditions. Stratification of depression may align sub-diagnoses more closely with their underling aetiology and provide more tractable targets for research and effective treatment. In the current study, we investigated whether genetic data could be used to identify subgroups within people with depression using the UK Biobank. Examination of cross-locus correlations were used to test for evidence of subgroups using genetic data from seven other complex traits and disorders that were genetically correlated with depression and had sufficient power (>0.6) for detection. We found no evidence for subgroups within depression for schizophrenia, bipolar disorder, attention deficit/hyperactivity disorder, autism spectrum disorder, anorexia nervosa, inflammatory bowel disease or obesity. This suggests that for these traits, genetic correlations with depression were driven by pleiotropic genetic variants carried by everyone rather than by a specific subgroup.
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http://dx.doi.org/10.1038/s41398-020-0848-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7246256PMC
May 2020

Cannabis use, depression and self-harm: phenotypic and genetic relationships.

Addiction 2020 03 12;115(3):482-492. Epub 2019 Dec 12.

Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.

Background And Aims: The use of cannabis has previously been linked to both depression and self-harm; however, the role of genetics in this relationship is unclear. This study aimed to estimate the phenotypic and genetic associations between cannabis use and depression and self-harm.

Design: Cross-sectional data collected through UK Biobank were used to test the phenotypic association between cannabis use, depression and self-harm. UK Biobank genetic data were then combined with consortia genome-wide association study summary statistics to further test the genetic relationships between these traits using LD score regression, polygenic risk scoring and Mendelian randomization methods.

Setting: United Kingdom, with additional international consortia data.

Participants: A total of 126 291 British adults aged between 40 and 70 years, recruited into UK Biobank.

Measurements: Phenotypic outcomes were life-time history of cannabis use (including initial and continued cannabis use), depression (including single-episode and recurrent depression) and self-harm. Genome-wide genetic data were used and assessment centre, batch and the first six principal components were included as key covariates when handling genetic data.

Findings: In UK Biobank, cannabis use is associated with an increased likelihood of depression [odds ratio (OR) = 1.64, 95% confidence interval (CI) = 1.59-1.70] and self-harm (OR = 2.85, 95% CI = 2.69-3.01). The strength of this phenotypic association is stronger when more severe trait definitions of cannabis use and depression are considered. Using consortia genome-wide summary statistics, significant genetic correlations are seen between cannabis use and depression [rg = 0.289, standard error (SE) = 0.036]. Polygenic risk scores for cannabis use and depression explain a small but significant proportion of variance in cannabis use, depression and self-harm within a UK Biobank target sample. However, two-sample Mendelian randomization analyses were not significant.

Conclusions: Cannabis use appeared to be both phenotypically and genetically associated with depression and self-harm. Limitations in statistical power mean that conclusions could not be made on the direction of causality between these traits.
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http://dx.doi.org/10.1111/add.14845DOI Listing
March 2020

Associations of autozygosity with a broad range of human phenotypes.

Nat Commun 2019 10 31;10(1):4957. Epub 2019 Oct 31.

Department of Neurology, Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht University, Utrecht, 3584 CX, The Netherlands.

In many species, the offspring of related parents suffer reduced reproductive success, a phenomenon known as inbreeding depression. In humans, the importance of this effect has remained unclear, partly because reproduction between close relatives is both rare and frequently associated with confounding social factors. Here, using genomic inbreeding coefficients (F) for >1.4 million individuals, we show that F is significantly associated (p < 0.0005) with apparently deleterious changes in 32 out of 100 traits analysed. These changes are associated with runs of homozygosity (ROH), but not with common variant homozygosity, suggesting that genetic variants associated with inbreeding depression are predominantly rare. The effect on fertility is striking: F equivalent to the offspring of first cousins is associated with a 55% decrease [95% CI 44-66%] in the odds of having children. Finally, the effects of F are confirmed within full-sibling pairs, where the variation in F is independent of all environmental confounding.
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http://dx.doi.org/10.1038/s41467-019-12283-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6823371PMC
October 2019

Genetic architecture of subcortical brain structures in 38,851 individuals.

Nat Genet 2019 11 21;51(11):1624-1636. Epub 2019 Oct 21.

Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.
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http://dx.doi.org/10.1038/s41588-019-0511-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7055269PMC
November 2019

Predicting incident dementia 3-8 years after brief cognitive tests in the UK Biobank prospective study of 500,000 people.

Alzheimers Dement 2019 12 13;15(12):1546-1557. Epub 2019 Oct 13.

Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), Department of Psychology, University of Edinburgh, Edinburgh, UK.

Introduction: Prospective studies reporting associations between cognitive performance and subsequent incident dementia have been subject to attrition bias. Furthermore, the extent to which established risk factors account for such associations requires further elucidation.

Methods: We used UK Biobank baseline cognitive data (n ≤ 488,130) and electronically linked hospital inpatient and death records during three- to eight-year follow-up, to estimate risk of total dementia (n = 1051), Alzheimer's disease (n = 352), and vascular dementia (n = 169) according to four brief cognitive tasks, with/without adjustment for constitutional and modifiable risk factors.

Results: We found associations of cognitive task performance with all-cause and cause-specific dementia (P <  .01); these were not accounted for by established risk factors. Cognitive data added up to 5% to the discriminative accuracy of receiver operating characteristic curve models; areas under the curve ranged from 82% to 86%.

Discussion: This study offers robust evidence that brief cognitive testing could be a valuable addition to dementia prediction models.
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http://dx.doi.org/10.1016/j.jalz.2019.07.014DOI Listing
December 2019

Genetic Contributions to Health Literacy.

Twin Res Hum Genet 2019 06;22(3):131-139

Centre for Cognitive Ageing and Cognitive Epidemiology,University of Edinburgh,Edinburgh, UK.

Higher health literacy is associated with higher cognitive function and better health. Despite its wide use in medical research, no study has investigated the genetic contributions to health literacy. Using 5783 English Longitudinal Study of Ageing (ELSA) participants (mean age = 65.49, SD = 9.55) who had genotyping data and had completed a health literacy test at wave 2 (2004-2005), we carried out a genome-wide association study (GWAS) of health literacy. We estimated the proportion of variance in health literacy explained by all common single nucleotide polymorphisms (SNPs). Polygenic profile scores were calculated using summary statistics from GWAS of 21 cognitive and health measures. Logistic regression was used to test whether polygenic scores for cognitive and health-related traits were associated with having adequate, compared to limited, health literacy. No SNPs achieved genome-wide significance for association with health literacy. The proportion of variance in health literacy accounted for by common SNPs was 8.5% (SE = 7.2%). Greater odds of having adequate health literacy were associated with a 1 standard deviation higher polygenic score for general cognitive ability [OR = 1.34, 95% CI (1.26, 1.42)], verbal-numerical reasoning [OR = 1.30, 95% CI (1.23, 1.39)], and years of schooling [OR = 1.29, 95% CI (1.21, 1.36)]. Reduced odds of having adequate health literacy were associated with higher polygenic profiles for poorer self-rated health [OR = 0.92, 95% CI (0.87, 0.98)] and schizophrenia [OR = 0.91, 95% CI (0.85, 0.96)). The well-documented associations between health literacy, cognitive function and health may partly be due to shared genetic etiology. Larger studies are required to obtain accurate estimates of SNP-based heritability and to discover specific health literacy-associated genetic variants.
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http://dx.doi.org/10.1017/thg.2019.28DOI Listing
June 2019

Correction: GWAS on family history of Alzheimer's disease.

Transl Psychiatry 2019 Jun 6;9(1):161. Epub 2019 Jun 6.

Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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http://dx.doi.org/10.1038/s41398-019-0498-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6554304PMC
June 2019

A multi-ancestry genome-wide study incorporating gene-smoking interactions identifies multiple new loci for pulse pressure and mean arterial pressure.

Hum Mol Genet 2019 08;28(15):2615-2633

Icelandic Heart Association, Kopavogur, Iceland.

Elevated blood pressure (BP), a leading cause of global morbidity and mortality, is influenced by both genetic and lifestyle factors. Cigarette smoking is one such lifestyle factor. Across five ancestries, we performed a genome-wide gene-smoking interaction study of mean arterial pressure (MAP) and pulse pressure (PP) in 129 913 individuals in stage 1 and follow-up analysis in 480 178 additional individuals in stage 2. We report here 136 loci significantly associated with MAP and/or PP. Of these, 61 were previously published through main-effect analysis of BP traits, 37 were recently reported by us for systolic BP and/or diastolic BP through gene-smoking interaction analysis and 38 were newly identified (P < 5 × 10-8, false discovery rate < 0.05). We also identified nine new signals near known loci. Of the 136 loci, 8 showed significant interaction with smoking status. They include CSMD1 previously reported for insulin resistance and BP in the spontaneously hypertensive rats. Many of the 38 new loci show biologic plausibility for a role in BP regulation. SLC26A7 encodes a chloride/bicarbonate exchanger expressed in the renal outer medullary collecting duct. AVPR1A is widely expressed, including in vascular smooth muscle cells, kidney, myocardium and brain. FHAD1 is a long non-coding RNA overexpressed in heart failure. TMEM51 was associated with contractile function in cardiomyocytes. CASP9 plays a central role in cardiomyocyte apoptosis. Identified only in African ancestry were 30 novel loci. Our findings highlight the value of multi-ancestry investigations, particularly in studies of interaction with lifestyle factors, where genomic and lifestyle differences may contribute to novel findings.
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http://dx.doi.org/10.1093/hmg/ddz070DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6644157PMC
August 2019

Author Correction: Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function.

Nat Commun 2019 May 1;10(1):2068. Epub 2019 May 1.

Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, 00014, Finland.

Christina M. Lill, who contributed to analysis of data, was inadvertently omitted from the author list in the originally published version of this article. This has now been corrected in both the PDF and HTML versions of the article.
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http://dx.doi.org/10.1038/s41467-019-10160-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6494826PMC
May 2019

Polygenic predictors of age-related decline in cognitive ability.

Mol Psychiatry 2020 10 13;25(10):2584-2598. Epub 2019 Feb 13.

Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK.

Polygenic scores can be used to distil the knowledge gained in genome-wide association studies for prediction of health, lifestyle, and psychological factors in independent samples. In this preregistered study, we used fourteen polygenic scores to predict variation in cognitive ability level at age 70, and cognitive change from age 70 to age 79, in the longitudinal Lothian Birth Cohort 1936 study. The polygenic scores were created for phenotypes that have been suggested as risk or protective factors for cognitive ageing. Cognitive abilities within older age were indexed using a latent general factor estimated from thirteen varied cognitive tests taken at four waves, each three years apart (initial n = 1091 age 70; final n = 550 age 79). The general factor indexed over two-thirds of the variance in longitudinal cognitive change. We ran additional analyses using an age-11 intelligence test to index cognitive change from age 11 to age 70. Several polygenic scores were associated with the level of cognitive ability at age-70 baseline (range of standardized β-values = -0.178 to 0.302), and the polygenic score for education was associated with cognitive change from childhood to age 70 (standardized β = 0.100). No polygenic scores were statistically significantly associated with variation in cognitive change between ages 70 and 79, and effect sizes were small. However, APOE e4 status made a significant prediction of the rate of cognitive decline from age 70 to 79 (standardized β = -0.319 for carriers vs. non-carriers). The results suggest that the predictive validity for cognitive ageing of polygenic scores derived from genome-wide association study summary statistics is not yet on a par with APOE e4, a better-established predictor.
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http://dx.doi.org/10.1038/s41380-019-0372-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515838PMC
October 2020

Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions.

Nat Neurosci 2019 03 4;22(3):343-352. Epub 2019 Feb 4.

23andMe, Inc, Mountain View, CA, USA.

Major depression is a debilitating psychiatric illness that is typically associated with low mood and anhedonia. Depression has a heritable component that has remained difficult to elucidate with current sample sizes due to the polygenic nature of the disorder. To maximize sample size, we meta-analyzed data on 807,553 individuals (246,363 cases and 561,190 controls) from the three largest genome-wide association studies of depression. We identified 102 independent variants, 269 genes, and 15 genesets associated with depression, including both genes and gene pathways associated with synaptic structure and neurotransmission. An enrichment analysis provided further evidence of the importance of prefrontal brain regions. In an independent replication sample of 1,306,354 individuals (414,055 cases and 892,299 controls), 87 of the 102 associated variants were significant after multiple testing correction. These findings advance our understanding of the complex genetic architecture of depression and provide several future avenues for understanding etiology and developing new treatment approaches.
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http://dx.doi.org/10.1038/s41593-018-0326-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6522363PMC
March 2019

Progressing Polygenic Medicine in Psychiatry Through Electronic Health Records.

JAMA Psychiatry 2019 05;76(5):470-472

Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England.

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http://dx.doi.org/10.1001/jamapsychiatry.2018.3975DOI Listing
May 2019

Author Correction: Association analysis in over 329,000 individuals identifies 116 independent variants influencing neuroticism.

Nat Genet 2019 03;51(3):577

Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, UK.

In the version of this article initially published, in Table 2, the descriptions of pathways and definitions in the first and last columns did not correctly correspond to the values in the other columns. The error has been corrected in the HTML and PDF versions of the article.
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http://dx.doi.org/10.1038/s41588-019-0357-3DOI Listing
March 2019

Sex-specific moderation by lifestyle and psychosocial factors on the genetic contributions to adiposity in 112,151 individuals from UK Biobank.

Sci Rep 2019 01 23;9(1):363. Epub 2019 Jan 23.

Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), Department of Psychology, University of Edinburgh, Edinburgh, UK.

Evidence suggests that lifestyle factors, e.g. physical activity, moderate the manifestation of genetic susceptibility to obesity. The present study uses UK Biobank data to investigate interaction between polygenic scores (PGS) for two obesity indicators, and lifestyle and psychosocial factors in the prediction of the two indicators, with attention to sex-specific effects. Analyses were of 112 151 participants (58 914 females; 40 to 73 years) whose genetic data passed quality control. Moderation effects were analysed in linear regression models predicting body mass index (BMI) and waist-to-hip ratio (WHR), including interaction terms for PGS and each exposure. Greater physical activity, more education, higher income, moderate vs low alcohol consumption, and low material deprivation were each associated with a relatively lower risk for manifestation of genetic susceptibility to obesity (p < 0.001); the moderating effects of physical activity and alcohol consumption were greater in women than men (three-way interaction: p = 0.009 and p = 0.008, respectively). More income and less neuroticism were related to reduced manifestation of genetic susceptibility to high WHR (p = 0.007; p = 0.003); the effect of income was greater in women (three-way interaction: p = 0.001). Lifestyle and psychosocial factors appear to offset genetic risk for adiposity in mid to late adulthood, with some sex-specific associations.
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http://dx.doi.org/10.1038/s41598-018-36629-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6344557PMC
January 2019

Sleep and cognitive aging in the eighth decade of life.

Sleep 2019 04;42(4)

Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.

We examined associations between self-reported sleep measures and cognitive level and change (age 70-76 years) in a longitudinal, same-year-of-birth cohort study (baseline N = 1091; longitudinal N = 664). We also leveraged GWAS summary data to ascertain whether polygenic scores (PGS) of chronotype and sleep duration related to self-reported sleep, and to cognitive level and change. Shorter sleep latency was associated with significantly higher levels of visuospatial ability, processing speed, and verbal memory (β ≥ |0.184|, SE ≤ 0.075, p ≤ 0.003). Longer daytime sleep duration was significantly associated slower processing speed (β = -0.085, SE = 0.027, p = 0.001), and with steeper 6-year decline in visuospatial reasoning (β = -0.009, SE = 0.003, p = 0.008), and processing speed (β = -0.009, SE = 0.002, p < 0.001). Only longitudinal associations between longer daytime sleeping and steeper cognitive declines survived correction for important health covariates and false discovery rate (FDR). PGS of chronotype and sleep duration were nominally associated with specific self-reported sleep characteristics for most SNP thresholds (standardized β range = |0.123 to 0.082|, p range = 0.003 to 0.046), but neither PGS predicted cognitive level or change following FDR. Daytime sleep duration is a potentially important correlate of cognitive decline in visuospatial reasoning and processing speed in older age, whereas cross-sectional associations are partially confounded by important health factors. A genetic propensity toward morningness and sleep duration were weakly, but consistently, related to self-reported sleep characteristics, and did not relate to cognitive level or change.
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http://dx.doi.org/10.1093/sleep/zsz019DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6448287PMC
April 2019
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