scholarly journals A cross-disorder MR-pheWAS of 5 major psychiatric disorders in UK Biobank

2019 ◽  
Author(s):  
Beate Leppert ◽  
Louise AC Millard ◽  
Lucy Riglin ◽  
George Davey Smith ◽  
Anita Thapar ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Computer Games ◽  
Genetic Risk ◽  
Autism Spectrum ◽  
Uk Biobank ◽  
First Sexual Intercourse ◽  
Hyperactivity Disorder ◽  
Socio Demographic Factors ◽  
The Uk

ABSTRACTPsychiatric disorders are highly heritable and associated with a wide variety of social adversity and physical health problems. Using genetic liability (rather than phenotypic measures of disease) as a proxy for psychiatric disease risk can be a useful alternative for research questions that would traditionally require large cohort studies with long-term follow up.Here we conducted a hypothesis-free phenome-wide association study in about 300,000 participants from the UK Biobank to examine associations of polygenic risk scores (PRS) for five psychiatric disorders (major depression (MDD), bipolar disorder (BP), schizophrenia (SCZ), attention-deficit/ hyperactivity disorder (ADHD) and autism spectrum disorder (ASD)) with 23,004 outcomes in UK Biobank, using the open-source PHESANT software package.There was evidence after multiple testing (p<2.55×10−06) for associations of PRSs with 226 outcomes, most of them attributed to associations of PRSMDD (n=120) with mental health factors and PRSADHD (n=77) with socio-demographic factors. Among others, we found strong evidence of associations between a 1 standard deviation increase in PRSADHD with 1.1 months younger age at first sexual intercourse [95% confidence interval [CI]: −1.26,−0.94]; PRSASD with 0.01% reduced lower erythrocyte distribution width [95%CI: −0.013,-0.007]; PRSSCZ with 0.98 odds of playing computer games [95%CI:0.976,0.989]; PRSMDD with a 0.11 points higher neuroticism score [95%CI:0.094,0.118] and PRSBP with 1.04 higher odds of having a university degree [95%CI:1.033,1.048].We were able to show that genetic liabilities for five major psychiatric disorders associate with long-term aspects of adult life, including socio-demographic factors, mental and physical health. This is evident even in individuals from the general population who do not necessarily present with a psychiatric disorder diagnosis.AUTHOR SUMMARYPsychiatric disorders are associated with a wide range of adverse health, social and economic problems. Our study investigates the association of genetic risk for five common psychiatric disorders with socio-demographics, lifestyle and health of about 330,000 participants in the UK Biobank using a systematic, hypothesis-free approach. We found that genetic risk for attention deficit/hyperactivity disorder (ADHD) and bipolar disorder were most strongly associated with lifestyle factors, such as time of first sexual intercourse and educational attainment. Genetic risks for autism spectrum disorder and schizophrenia were associated with altered blood cell counts and time playing computer games, respectively. Increased genetic risk for depression was associated with other mental health outcomes such as neuroticism and irritability. In general, our results suggest that genetic risk for psychiatric disorders associates with a range of health and lifestyle traits that were measured in adulthood, in individuals from the general population who do not necessarily present with a psychiatric disorder diagnosis. However, it is important to note that these associations aren’t necessary causal but can themselves be influenced by other factors, like socio-economic factors and selection into the cohort. The findings inform future hypotheses to be tested using causally informative designs.

scholarly journals Genetic underpinnings of sociability in the UK Biobank

2019 ◽  
Author(s):  
J Bralten ◽  
CJHM Klemann ◽  
NR Mota ◽  
W De Witte ◽  
C Arango ◽  
...  
Keyword(s):  
Social Anxiety ◽  
Psychiatric Disorders ◽  
Genetic Correlation ◽  
Genome Wide Association Study ◽  
Autism Spectrum ◽  
Self Report ◽  
Uk Biobank ◽  
Genome Wide ◽  
A Genome ◽  
The Uk

ABSTRACTDifficulties with sociability include a tendency to avoid social contacts and activities, and to prefer being alone rather than being with others. While sociability is a continuously distributed trait in the population, decreased sociability represent a common early manifestation of multiple neuropsychiatric disorders such as Schizophrenia (SCZ), Bipolar Disorder (BP), Major Depressive Disorder (MDD), Autism Spectrum Disorders (ASDs), and Alzheimer’s disease (AD). We aimed to investigate the genetic underpinnings of sociability as a continuous trait in the general population. In this respect, we performed a genome-wide association study (GWAS) using a sociability score based on 4 social functioning-related self-report questions in the UK Biobank sample (n=342,461) to test the effect of individual genetic variants. This was followed by LD score analyses to investigate the genetic correlation with psychiatric disorders (SCZ, BP, MDD, ASDs) and a neurological disorder (AD) as well as related phenotypes (Loneliness and Social Anxiety). The phenotypic data indeed showed that the sociability score was decreased in individuals with ASD, (probable) MDD, BP and SCZ, but not in individuals with AD. Our GWAS showed 604 genome-wide significant SNPs, coming from 18 independent loci (SNP-based h2=0.06). Genetic correlation analyses showed significant correlations with SCZ (rg=0.15, p=9.8e-23), MDD (rg=0.68, p=6.6e-248) and ASDs (rg=0.27, p=4.5e-28), but no correlation with BP (rg=0.01, p=0.45) or AD (rg=0.04, p=0.55). Our sociability trait was also genetically correlated with Loneliness (rg=0.45, p=2.4e-8) and Social Anxiety (rg=0.48, p=0.002). Our study shows that there is a significant genetic component to variation in population levels of sociability, which is relevant to some psychiatric disorders (SCZ, MDD, ASDs), but not to BP and AD.

scholarly journals Genetic predisposition to psychiatric disorders and risk of COVID-19

2021 ◽  
Author(s):  
Wenwen Chen ◽  
Yu Zeng ◽  
Chen Suo ◽  
Huazhen Yang ◽  
Yilong Chen ◽  
...  
Keyword(s):  
Psychiatric Disorder ◽  
Psychiatric Disorders ◽  
Genetic Predisposition ◽  
Genetic Risk ◽  
Substance Misuse ◽  
Hospital Inpatient ◽  
Summary Statistics ◽  
Uk Biobank ◽  
Increased Risk ◽  
The Uk

AbstractBackgroundPre-pandemic psychiatric disorders have been associated with an increased risk of COVID-19. However, the underlying mechanisms remain unknown, e.g. to what extent genetic predisposition to psychiatric disorders contributes to the observed association.MethodsThe analytic sample consisted of white British participants of UK Biobank registered in England, with available genetic data, and alive on Jan 31, 2020 (i.e., the start of the COVID-19 outbreak in the UK) (n=346,554). We assessed individuals’ genetic predisposition to different psychiatric disorders, including substance misuse, depression, anxiety, and psychotic disorder, using polygenic risk score (PRS). Diagnoses of psychiatric disorders were identified through the UK Biobank hospital inpatient data. We performed a GWAS analysis for each psychiatric disorder in a randomly selected half of the study population who were free of COVID-19 (i.e., the base dataset). For the other half (i.e., the target dataset), PRS was calculated for each psychiatric disorder using the discovered genetic variants from the base dataset. We then examined the association between PRS of each psychiatric disorder and risk of COVID-19, or severe COVID-19 (i.e., hospitalization and death), using logistic regression models. The ascertainment of COVID-19 was through the Public Health England dataset, the UK Biobank hospital inpatient data and death registers, updated until July 26, 2020. For validation, we repeated the PRS analyses based on publicly available GWAS summary statistics.Results155,988 participants (including 1,451 COVID-19 cases), with a mean age of 68.50 years at COVID-19 outbreak, were included for PRS analysis. Higher genetic liability forwards psychiatric disorders was associated with increased risk of both any COVID-19 and severe COVID-19, especially genetic risk for substance misuse and depression. The adjusted odds ratios (ORs) for any COVID-19 were 1.15 (95% confidence interval [CI] 1.02-1.31) and 1.26 (1.11-1.42) among individuals with a high genetic risk (above the upper tertile of PRS) for substance misuse and depression, respectively, compared with individuals with a low genetic risk (below the lower tertile). Largely similar ORs were noted for severe COVID-19 and similar albeit slightly lower estimates using PRSs generated from GWAS summary statistics from independent samples.ConclusionIn the UK Biobank, genetic predisposition to psychiatric disorders was associated with an increased risk of COVID-19, including severe course of the disease. These findings suggest the potential role of genetic factors in the observed phenotypic association between psychiatric disorders and COVID-19, underscoring the need of increased medical surveillance of for this vulnerable population during the pandemic.

scholarly journals Genetic overlap between multivariate measures of human functional brain connectivity and psychiatric disorders

2021 ◽  
Author(s):  
Daniel Roelfs ◽  
Dennis van der Meer ◽  
Dag Alnæs ◽  
Oleksandr Frei ◽  
Robert Loughnan ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Brain Connectivity ◽  
Autism Spectrum ◽  
Genetic Determinants ◽  
Functional Brain ◽  
Hyperactivity Disorder ◽  
Genome Wide ◽  
Genetic Overlap ◽  
The Uk ◽  
Shared Genetic

Psychiatric disorders are complex, heritable, and highly polygenic. Supported by findings of abnormalities in functional magnetic resonance imaging (fMRI) based measures of brain connectivity, current theoretical and empirical accounts have conceptualized them as disorders of brain connectivity and dysfunctional integration of brain signaling, however, the extent to which these findings reflect common genetic factors remains unclear. Here, we performed a multivariate genome-wide association analysis of fMRI-based functional brain connectivity in a sample of 30,701 individuals from the UK Biobank and investigated the shared genetic determinants with seven major psychiatric disorders. The analysis revealed significant genetic overlap between functional brain connectivity and schizophrenia, bipolar disorder, attention-deficit hyperactivity disorder, autism spectrum disorder, anxiety, and major depression, adding further genetic support for the dysconnectivity hypothesis of psychiatric disorders and identifying potential genetic and functional targets for future studies.

scholarly journals Dietary Behaviors and Incident COVID-19 in the UK Biobank

Nutrients ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 2114
Author(s):  
Thanh-Huyen T. Vu ◽  
Kelsey J. Rydland ◽  
Chad J. Achenbach ◽  
Linda Van Horn ◽  
Marilyn C. Cornelis
Keyword(s):  
Dietary Behaviors ◽  
Processed Meat ◽  
Uk Biobank ◽  
Processed Meats ◽  
Additional Tool ◽  
Oily Fish ◽  
Case Rate ◽  
Specific Association ◽  
Socio Demographic Factors ◽  
The Uk

Background: Nutritional status influences immunity but its specific association with susceptibility to COVID-19 remains unclear. We examined the association of specific dietary data and incident COVID-19 in the UK Biobank (UKB). Methods: We considered UKB participants in England with self-reported baseline (2006–2010) data and linked them to Public Health England COVID-19 test results—performed on samples from combined nose/throat swabs, using real time polymerase chain reaction (RT-PCR)—between March and November 2020. Baseline diet factors included breastfed as baby and specific consumption of coffee, tea, oily fish, processed meat, red meat, fruit, and vegetables. Individual COVID-19 exposure was estimated using the UK’s average monthly positive case rate per specific geo-populations. Logistic regression estimated the odds of COVID-19 positivity by diet status adjusting for baseline socio-demographic factors, medical history, and other lifestyle factors. Another model was further adjusted for COVID-19 exposure. Results: Eligible UKB participants (n = 37,988) were 40 to 70 years of age at baseline; 17% tested positive for COVID-19 by SAR-CoV-2 PCR. After multivariable adjustment, the odds (95% CI) of COVID-19 positivity was 0.90 (0.83, 0.96) when consuming 2–3 cups of coffee/day (vs. <1 cup/day), 0.88 (0.80, 0.98) when consuming vegetables in the third quartile of servings/day (vs. lowest quartile), 1.14 (1.01, 1.29) when consuming fourth quartile servings of processed meats (vs. lowest quartile), and 0.91 (0.85, 0.98) when having been breastfed (vs not breastfed). Associations were attenuated when further adjusted for COVID-19 exposure, but patterns of associations remained. Conclusions: In the UK Biobank, consumption of coffee, vegetables, and being breastfed as a baby were favorably associated with incident COVID-19; intake of processed meat was adversely associated. Although these findings warrant independent confirmation, adherence to certain dietary behaviors may be an additional tool to existing COVID-19 protection guidelines to limit the spread of this virus.

scholarly journals What families in the UK use to manage attention-deficit/hyperactivity disorder (ADHD): a survey of resource use

2020 ◽  
Vol 4 (1) ◽  
pp. e000771
Author(s):  
Philippa Fibert ◽  
Clare Relton
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Support Groups ◽  
Attention Deficit ◽  
Service Use ◽  
Behavioural Change ◽  
Behavioural Therapy ◽  
Autism Spectrum ◽  
Convenience Sample ◽  
Hyperactivity Disorder ◽  
The Uk

ObjectiveTo identify interventions being used to manage attention-deficit/hyperactivity disorder (ADHD) in the UK.DesignA survey within the Sheffield Treatments for ADHD Research project. A convenience sample of participants in the UK who consented to join an observational cohort were asked closed questions about medication, behavioural change programmes and service use, and an open-ended question about what else they used.SettingA broad variety of non-National Health Service, non-treatment seeking settings throughout the UK, including local authority organisations, schools, ADHD and autism spectrum condition support groups and social media.ParticipantsFamilies of children aged 5–18 with carer reported ADHD and Conners Global Index (CGI) T scores of 55+.ResultsResponses from 175 families were analysed. The mean age of the children was 10.21 (2.44), and two-thirds (n=114) had additional diagnoses. The majority used medications to manage ADHD (n=120) and had participated in a parenting class (n=130). Just over a quarter (28%, n=49) did not use ADHD medications, and used sleep medications. Just under half had consulted psychologists (n=83), and 32 had participated in other talking therapies such as psychotherapy, counselling and cognitive–behavioural therapy. A few used aids such as reward charts or fiddle toys (n=17) and participated in activities (mostly physical) (n=14). A substantial minority (78/175) had used non-mainstream treatments, the most popular being homoeopathy (n=32), nutritional interventions (n=21) and bodywork such as massage or cranial osteopathy (n=9).ConclusionsFamilies reported use of a wide variety of treatments to help with management of their children with ADHD in addition to their use of mainstream treatments.

scholarly journals Psychiatric comorbid disorders of cognition: a machine learning approach using 1175 UK Biobank participants

2020 ◽  
Vol 23 (4) ◽  
pp. 140-145
Author(s):  
Chenlu Li ◽  
Delia A Gheorghe ◽  
John E Gallacher ◽  
Sarah Bauermeister
Keyword(s):  
Machine Learning ◽  
Cognitive Decline ◽  
Psychiatric Disorders ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Imaging Study ◽  
Cognitive Change ◽  
Poor Mental Health ◽  
Uk Biobank

BackgroundConceptualising comorbidity is complex and the term is used variously. Here, it is the coexistence of two or more diagnoses which might be defined as ‘chronic’ and, although they may be pathologically related, they may also act independently. Of interest here is the comorbidity of common psychiatric disorders and impaired cognition.ObjectivesTo examine whether anxiety and/or depression are/is important longitudinal predictors of cognitive change.MethodsUK Biobank participants used at three time points (n=502 664): baseline, first follow-up (n=20 257) and first imaging study (n=40 199). Participants with no missing data were 1175 participants aged 40–70 years, 41% women. Machine learning was applied and the main outcome measure of reaction time intraindividual variability (cognition) was used.FindingsUsing the area under the receiver operating characteristic curve, the anxiety model achieves the best performance with an area under the curve (AUC) of 0.68, followed by the depression model with an AUC of 0.63. The cardiovascular and diabetes model, and the covariates model have weaker performance in predicting cognition, with an AUC of 0.60 and 0.56, respectively.ConclusionsOutcomes suggest that psychiatric disorders are more important comorbidities of long-term cognitive change than diabetes and cardiovascular disease, and demographic factors. Findings suggest that psychiatric disorders (anxiety and depression) may have a deleterious effect on long-term cognition and should be considered as an important comorbid disorder of cognitive decline.Clinical implicationsImportant predictive effects of poor mental health on longitudinal cognitive decline should be considered in secondary and also primary care.

scholarly journals Night Shift Work, Genetic Risk, and Type 2 Diabetes in the UK Biobank

Diabetes Care ◽  
2018 ◽  
Vol 41 (4) ◽  
pp. 762-769 ◽  
Author(s):  
Céline Vetter ◽  
Hassan S. Dashti ◽  
Jacqueline M. Lane ◽  
Simon G. Anderson ◽  
Eva S. Schernhammer ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Shift Work ◽  
Genetic Risk ◽  
Night Shift ◽  
Uk Biobank ◽  
Night Shift Work ◽  
The Uk

scholarly journals Identifying cross-disease components of genetic risk across hospital data in the UK Biobank

2019 ◽  
Vol 52 (1) ◽  
pp. 126-134 ◽  
Author(s):  
Adrian Cortes ◽  
Patrick K. Albers ◽  
Calliope A. Dendrou ◽  
Lars Fugger ◽  
Gil McVean
Keyword(s):  
Genetic Risk ◽  
Uk Biobank ◽  
Hospital Data ◽  
The Uk
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