scholarly journals The effect of schizophrenia-associated CNVs on other psychiatric disorders

BJPsych Open ◽  
2021 ◽  
Vol 7 (S1) ◽  
pp. S248-S249
Author(s):  
Lily Farakish
Keyword(s):  
Psychiatric Disorders ◽  
Copy Number Variants ◽  
Clinical Importance ◽  
Carrier Status ◽  
Uk Biobank ◽  
Online Resource ◽  
Icd 10 ◽  
Heritable Disorder ◽  
Rare Genetic Variants ◽  
The Uk

AimsSchizophrenia is a highly heritable disorder, sharing genetic roots with other psychiatric disorders from both common and rare genetic variants. Copy number variants (CNVs) are one of the rare causes which increase the risk of a variety of psychiatric, medical and physical phenotypes. The role of schizophrenia-associated CNVs is becoming of increasingly scientific and clinical importance in the field of psychiatry, with new CNV-phenotype relationships opening perspectives for understanding the aetiology of psychiatric disorders. This paper aims to investigate whether 13 schizophrenia (SZ)-associated CNVs or any SZ-CNV-carrier status increase the risk for 9 psychiatric phenotypes, reduce levels of happiness, change duration of sleep, and increase the index of multiple deprivation.MethodThe study includes 421,268 participants of British or Irish descent (aged 40–69 years), containing 418,036 controls and 3232 schizophrenia-associated CNV carriers. The data are secondary from the UK Biobank, an online resource containing data on array-genotyped participants with their specific phenotypic information. Prior to analysis, CNV selection led to the exclusion of any CNV with less than 5 hits in the UK Biobank population. Incidence of each phenotype was based on self-reported diagnoses, questionnaires or hospital ICD-10 diagnoses, with a minimum of 500 cases. Both binary logistic and linear regression were used to assess the incidence of these phenotypes in relation to the CNVs, adjusted for age, sex, and ethnicity as potential cofounders.ResultOverall, 12/13 CNVs were nominally associated with at least one phenotype, including 114/168 possible associations and 54 undetectable associations as not every CNV carrier displayed one of the chosen phenotypes. 41 associations were statistically significant (p < 0.05) and 13 survived Bonferroni Correction (p < 2.98 × 10-4). All significant associations met the expected change except 15q11.2 deletion and any CNV carrier status which showed a decrease in likelihood of addiction.ConclusionThese findings suggest schizophrenia-associated CNV can affect range of psychiatric phenotypes. By building on existing reports, understanding the widespread effects of CNVs in the aetiology and pathogenicty of psychiatric disorders may overtime aid in strengthening our search for more targetted, effective treatments.Many thanks to Professor George Kirov for supervising and supporting this project.

scholarly journals Cognitive performance and functional outcomes of carriers of pathogenic copy number variants: analysis of the UK Biobank

2019 ◽  
Vol 214 (5) ◽  
pp. 297-304 ◽  
Author(s):  
Kimberley M. Kendall ◽  
Matthew Bracher-Smith ◽  
Harry Fitzpatrick ◽  
Amy Lynham ◽  
Elliott Rees ◽  
...  
Keyword(s):  
Cognitive Performance ◽  
Neurodevelopmental Disorders ◽  
Copy Number ◽  
Copy Number Variants ◽  
Autism Spectrum ◽  
Cognitive Test ◽  
Carrier Status ◽  
Cognitive Tests ◽  
Uk Biobank ◽  
The Uk

BackgroundRare copy number variants (CNVs) are associated with risk of neurodevelopmental disorders characterised by varying degrees of cognitive impairment, including schizophrenia, autism spectrum disorder and intellectual disability. However, the effects of many individual CNVs in carriers without neurodevelopmental disorders are not yet fully understood, and little is known about the effects of reciprocal copy number changes of known pathogenic loci.AimsWe aimed to analyse the effect of CNV carrier status on cognitive performance and measures of occupational and social outcomes in unaffected individuals from the UK Biobank.MethodWe called CNVs in the full UK Biobank sample and analysed data from 420 247 individuals who passed CNV quality control, reported White British or Irish ancestry and were not diagnosed with neurodevelopmental disorders. We analysed 33 pathogenic CNVs, including their reciprocal deletions/duplications, for association with seven cognitive tests and four general measures of functioning: academic qualifications, occupation, household income and Townsend Deprivation Index.ResultsMost CNVs (24 out of 33) were associated with reduced performance on at least one cognitive test or measure of functioning. The changes on the cognitive tests were modest (average reduction of 0.13 s.d.) but varied markedly between CNVs. All 12 schizophrenia-associated CNVs were associated with significant impairments on measures of functioning.ConclusionsCNVs implicated in neurodevelopmental disorders, including schizophrenia, are associated with cognitive deficits, even among unaffected individuals. These deficits may be subtle but CNV carriers have significant disadvantages in educational attainment and ability to earn income in adult life.Declaration of interestNone.

scholarly journals Schizophrenia-associated genomic copy number variants and subcortical brain volumes in the UK Biobank

2018 ◽  
Author(s):  
Anthony Warland ◽  
Kimberley M Kendall ◽  
Elliott Rees ◽  
George Kirov ◽  
Xavier Caseras
Keyword(s):  
Copy Number ◽  
Copy Number Variants ◽  
Risk Groups ◽  
Clinical Samples ◽  
Uk Biobank ◽  
Subcortical Structures ◽  
Brain Volumes ◽  
Subcortical Brain ◽  
Heritable Disorder ◽  
The Uk

AbstractSchizophrenia is a highly heritable disorder for which anatomical brain alterations have been repeatedly reported in clinical samples. Unaffected at-risk groups have also been studied in an attempt to identify brain changes that do not reflect reverse causation or treatment effects. However, no robust associations have been observed between neuroanatomical phenotypes and known genetic risk factors for schizophrenia. We tested subcortical brain volume differences between 49 unaffected participants carrying at least one of the 12 copy number variants associated with schizophrenia in UK Biobank and 9,063 individuals who did not carry any of the 93 copy number variants reported to be pathogenic. Our results show that CNV carriers have reduced volume in some of the subcortical structures previously shown to be reduced in schizophrenia. Moreover, these associations were partially accounted for by the association between pathogenic copy number variants and cognitive impairment, which is one of the features of schizophrenia.

scholarly journals Effects of genomic copy number variants penetrant for schizophrenia on cortical thickness and surface area in healthy individuals: analysis of the UK Biobank

2020 ◽  
pp. 1-8
Author(s):  
Xavier Caseras ◽  
George Kirov ◽  
Kimberley M. Kendall ◽  
Elliott Rees ◽  
Sophie E. Legge ◽  
...  
Keyword(s):  
Surface Area ◽  
Cortical Thickness ◽  
Copy Number ◽  
Copy Number Variants ◽  
Brain Anatomy ◽  
Carrier Status ◽  
Uk Biobank ◽  
Risk Alleles ◽  
The Uk ◽  
The Impact

Background Schizophrenia is a highly heritable disorder with undetermined neurobiological causes. Understanding the impact on brain anatomy of carrying genetic risk for the disorder will contribute to uncovering its neurobiological underpinnings. Aims To examine the effect of rare copy number variants (CNVs) associated with schizophrenia on brain cortical anatomy in a sample of unaffected participants from the UK Biobank. Method We used regression analyses to compare cortical thickness and surface area (total and across gyri) between 120 unaffected carriers of rare CNVs associated with schizophrenia and 16 670 participants without any pathogenic CNV. A measure of cortical thickness and surface area covariance across gyri was also compared between groups. Results Carrier status was associated with reduced surface area (β = −0.020 mm2, P < 0.001) and less robustly with increased cortical thickness (β = 0.015 mm, P = 0.035), and with increased covariance in thickness (carriers z = 0.31 v. non-carriers z = 0.22, P < 0.0005). Associations were mainly present in frontal and parietal areas and driven by a limited number of rare risk alleles included in our analyses (mainly 15q11.2 deletion for surface area and 16p13.11 duplication for thickness covariance). Conclusions Results for surface area conformed with previous clinical findings, supporting surface area reductions as an indicator of genetic liability for schizophrenia. Results for cortical thickness, though, argued against its validity as a potential risk marker. Increased structural thickness covariance across gyri also appears related to risk for schizophrenia. The heterogeneity found across the effects of rare risk alleles suggests potential different neurobiological gateways into schizophrenia's phenotype.

scholarly journals Polygenic risk for schizophrenia and season of birth within the UK Biobank cohort

2018 ◽  
Vol 49 (15) ◽  
pp. 2499-2504 ◽  
Author(s):  
Valentina Escott-Price ◽  
Daniel J. Smith ◽  
Kimberley Kendall ◽  
Joey Ward ◽  
George Kirov ◽  
...  
Keyword(s):  
Environmental Exposure ◽  
Copy Number Variants ◽  
Season Of Birth ◽  
Uk Biobank ◽  
Month Of Birth ◽  
Risk Alleles ◽  
Gene Environment ◽  
Increased Risk ◽  
The Uk ◽  
Pathogenic Process

AbstractBackgroundThere is strong evidence that people born in winter and in spring have a small increased risk of schizophrenia. As this ‘season of birth’ effect underpins some of the most influential hypotheses concerning potentially modifiable risk exposures, it is important to exclude other possible explanations for the phenomenon.MethodsHere we sought to determine whether the season of birth effect reflects gene-environment confounding rather than a pathogenic process indexing environmental exposure. We directly measured, in 136 538 participants from the UK Biobank (UKBB), the burdens of common schizophrenia risk alleles and of copy number variants known to increase the risk for the disorder, and tested whether these were correlated with a season of birth.ResultsNeither genetic measure was associated with season or month of birth within the UKBB sample.ConclusionsAs our study was highly powered to detect small effects, we conclude that the season of birth effect in schizophrenia reflects a true pathogenic effect of environmental exposure.

scholarly journals Analysis of exome-sequenced UK Biobank subjects implicates genes affecting risk of hyperlipidaemia

2020 ◽  
Author(s):  
David Curtis
Keyword(s):  
Rare Variants ◽  
Sequence Data ◽  
Lipid Lowering ◽  
P Value ◽  
Data Sets ◽  
Uk Biobank ◽  
Functional Studies ◽  
Exome Sequence Data ◽  
Rare Genetic Variants ◽  
The Uk

Rare genetic variants in LDLR, APOB and PCSK9 are known causes of familial hypercholesterolaemia and it is expected that rare variants in other genes will also have effects on hyperlipidaemia risk although such genes remain to be identified. The UK Biobank consists of a sample of 500,000 volunteers and exome sequence data is available for 50,000 of them. 11,490 of these were classified as hyperlipidaemia cases on the basis of having a relevant diagnosis recorded and/or taking lipid-lowering medication while the remaining 38,463 were treated as controls. Variants in each gene were assigned weights according to rarity and predicted impact and overall weighted burden scores were compared between cases and controls, including population principal components as covariates. One biologically plausible gene, HUWE1, produced statistically significant evidence for association after correction for testing 22,028 genes with a signed log10 p value (SLP) of -6.15, suggesting a protective effect of variants in this gene. Other genes with uncorrected p<0.001 are arguably also of interest, including LDLR (SLP=3.67), RBP2 (SLP=3.14), NPFFR1 (SLP=3.02) and ACOT9 (SLP=-3.19). Gene set analysis indicated that rare variants in genes involved in metabolism and energy can influence hyperlipidaemia risk. Overall, the results provide some leads which might be followed up with functional studies and which could be tested in additional data sets as these become available. This research has been conducted using the UK Biobank Resource.

scholarly journals Pre-pandemic psychiatric disorders and risk of COVID-19: a cohort analysis in the UK Biobank

2020 ◽  
Author(s):  
Huazhen Yang ◽  
Wenwen Chen ◽  
Yao Hu ◽  
Yilong Chen ◽  
Yu Zeng ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Cohort Analysis ◽  
Uk Biobank ◽  
Hospital Data ◽  
Logistic Regression Models ◽  
Inpatient Hospital ◽  
Increased Risk ◽  
Somatic Comorbidities ◽  
The Uk ◽  
Study Participants

Objective To determine the association between pre-pandemic psychiatric disorders and the risk of COVID-19. Design Community-based prospective cohort study. Setting UK Biobank population. Participants 421,048 participants who were recruited in England and alive by January 31st 2020, i.e., the start of COVID-19 outbreak in the UK. 50,815 individuals with psychiatric disorders recorded in the UK Biobank inpatient hospital data before the outbreak were included in the exposed group, while 370,233 participants without such conditions were in the unexposed group. Measurements We obtained information on positive results of COVID-19 test as registered in the Public Health England, COVID-19 related hospitalizations in the UK Biobank inpatient hospital data, and COIVD-19 related deaths from the death registers. We also identified individuals who was hospitalized for infections other than COVID-19 during the follow-up. Logistic regression models were used to estimate odds ratios (ORs) with 95% confidence intervals (CIs), controlling for multiple confounders. Results The mean age at outbreak was 67.8 years and around 43% of the study participants were male. We observed an elevated risk of COVID-19 among individuals with pre-pandemic psychiatric disorder, compared with those without such diagnoses. The fully adjusted ORs were 1.44 (95%CI 1.27 to 1.64), 1.67 (1.42 to 1.98), and 2.03 (1.56 to 2.63) for any COVID-19, inpatient COVID-19, COVID-19 related death, respectively. The excess risk was observed across all levels of somatic comorbidities and subtypes of pre-pandemic psychiatric disorders, while further increased with greater number of pre-pandemic psychiatric disorders. We also observed an association between pre-pandemic psychiatric disorders and increased risk of hospitalization for other infections (1.85 [1.65 to 2.07]). Conclusions Pre-pandemic psychiatric disorders are associated with increased risk of COVID-19, especially severe and fatal COVID-19. The similar association observed for hospitalization for other infections suggests a shared pathway between psychiatric disorders and different infections, including altered immune responses.

scholarly journals Modelling the distribution of white matter hyperintensities due to ageing on MRI images using Bayesian inference

2018 ◽  
Author(s):  
Vaanathi Sundaresan ◽  
Ludovica Griffanti ◽  
Petya Kindalova ◽  
Fidel Alfaro-Almagro ◽  
Giovanna Zamboni ◽  
...  
Keyword(s):  
White Matter ◽  
Vascular Disease ◽  
White Matter Hyperintensities ◽  
Age Groups ◽  
Clinical Importance ◽  
Population Level ◽  
Distribution Model ◽  
Ageing Population ◽  
Uk Biobank ◽  
The Uk

AbstractWhite matter hyperintensities (WMH), also known as white matter lesions, are localised white matter areas that appear hyperintense on MRI scans. WMH commonly occur in the ageing population, and are often associated with several factors such as cognitive disorders, cardiovascular risk factors, cerebrovascular and neurodegenerative diseases. Despite the fact that some links between lesion location and parametric factors such as age have already been established, the relationship between voxel-wise spatial distribution of lesions and these factors is not yet well understood. Hence, it would be of clinical importance to model the distribution of lesions at the population-level and quantitatively analyse the effect of various factors on the lesion distribution model.In this work we compare various methods, including our proposed method, to generate voxel-wise distributions of WMH within a population with respect to various factors. Our proposed Bayesian spline method models the spatio-temporal distribution of WMH with respect to a parametric factor of interest, in this case age, within a population. Our probabilistic model takes as input the lesion segmentation binary maps of subjects belonging to various age groups and provides a population-level parametric lesion probability map as output. We used a spline representation to ensure a degree of smoothness in space and the dimension associated with the parameter, and formulated our model using a Bayesian framework.We tested our algorithm output on simulated data and compared our results with those obtained using various existing methods with different levels of algorithmic and computational complexity. We then compared the better performing methods on a real dataset, consisting of 1000 subjects of the UK Biobank, divided in two groups based on hypertension diagnosis. Finally, we applied our method on a clinical dataset of patients with vascular disease.On simulated dataset, the results from our algorithm showed a mean square error (MSE) value of 7.27 × 10−5, which was lower than the MSE value reported in the literature, with the advantage of being robust and computationally efficient. In the UK Biobank data, we found that the lesion probabilities are higher for the hypertension group compared to the non-hypertension group and further verified this finding using a statistical t-test. Finally, when applying our method on patients with vascular disease, we observed that the overall probability of lesions is significantly higher in later age groups, which is in line with the current literature.

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 Weighted burden analysis in 200 000 exome-sequenced UK Biobank subjects characterises effects of rare genetic variants on BMI

2021 ◽  
Author(s):  
David Curtis
Keyword(s):  
Multiple Testing ◽  
Rare Variants ◽  
Sequence Data ◽  
Statistical Significance ◽  
Positive Sign ◽  
P Value ◽  
Uk Biobank ◽  
Functional Variants ◽  
Rare Genetic Variants ◽  
The Uk

AbstractIntroductionA number of genes have been identified in which rare variants can cause obesity. Here we analyse a sample of exome sequenced subjects from UK Biobank using BMI as a phenotype.MethodsThere were 199,807 exome sequenced subjects for whom BMI was recorded. Weighted burden analysis of rare, functional variants was carried out, incorporating population principal components and sex as covariates. For selected genes, additional analyses were carried out to clarify the contribution of different categories of variant. Statistical significance was summarised as the signed log 10 of the p value (SLP), given a positive sign if the weighted burden score was positively correlated with BMI.ResultsTwo genes were exome-wide significant, MC4R (SLP = 15.79) and PCSK1 (SLP = 6.61). In MC4R, disruptive variants were associated with an increase in BMI of 2.72 units and probably damaging nonsynonymous variants with an increase of 2.02 units. In PCSK1, disruptive variants were associated with a BMI increase of 2.29 and protein-altering variants with an increase of 0.34. Results for other genes were not formally significant after correction for multiple testing, although SIRT1, ZBED6 and NPC2 were noted to be of potential interest.ConclusionBecause the UK Biobank consists of a self-selected sample of relatively healthy volunteers, the effect sizes noted may be underestimates. The results demonstrate the effects of very rare variants on BMI and suggest that other genes and variants will be definitively implicated when the sequence data for additional subjects becomes available.This research has been conducted using the UK Biobank Resource.

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