Familial Influences on Neuroticism and Education in the UK Biobank

Sibling similarity can reveal key insights into genetic architecture

The use of siblings to infer the factors influencing complex traits has been a cornerstone of quantitative genetics. Here, we utilise siblings for a novel application: the inference of genetic architecture, specifically that relating to individuals with extreme trait values (e.g. in the top 1%). Inferring the genetic architecture most relevant to this group of individuals is important because they are at the greatest risk of disease and may be more likely to harbour rare variants of large effect due to natural selection. We develop a theoretical framework that derives expected distributions of sibling trait values based on an index sibling's trait value, estimated trait heritability, and null assumptions that include infinitesimal genetic effects and environmental factors that are either controlled for or have combined Gaussian effects. This framework is then used to develop statistical tests powered to distinguish between trait tails characterised by common polygenic architecture from those that include substantial enrichments of de novo or rare variant (Mendelian) architecture. We apply our tests to UK Biobank data here, although we note that they can be used to infer genetic architecture in any cohort or health registry that includes siblings and their trait values, since these tests do not use genetic data. We describe how our approach has the potential to help disentangle the genetic and environmental causes of extreme trait values, and to improve the design and power of future sequencing studies to detect rare variants.

Striking Departures from Polygenic Architecture in the Tails of Complex Traits

Understanding the genetic architecture of human traits is of key biological, medical and evolutionary importance[1]. Despite much progress, little is known about how genetic architecture varies across the trait continuum and, in particular, if it differs in the tails of complex traits, where disease often occurs. Here, applying a novel approach based on polygenic scores, we reveal striking departures from polygenic architecture across 148 quantitative trait tails, consistent with distinct concentrations of high-impact rare alleles in one or both tails of most of the traits. We demonstrate replication of these results across ancestries, cohorts, repeat measures, and using an orthogonal family-based approach[2]. Furthermore, trait tails with inferred enrichment of rare alleles are associated with more exome study hits, reduced fecundity, advanced paternal age, and lower predictive accuracy of polygenic scores. Finally, we find evidence of ongoing selection consistent with the observed departures in polygenicity and demonstrate, via simulation, that traits under stabilising selection are expected to have tails enriched for rare, large-effect alleles. Overall, our findings suggest that while common variants of small effect likely account for most of the heritability in complex traits[3], rare variants of large effect are often more important in the trait tails, particularly among individuals at highest risk of disease. Our study has implications for rare variant discovery, the utility of polygenic scores, the study of selection in humans, and for the relative importance of common and rare variants to complex traits and diseases.

Causal association between Neuroticism and risk of aortic aneurysm: A bidirectional two-sample Mendelian randomization study

BACKGROUND

The objective of this study was to analyze the causal relationship between Neuroticism and aortic aneurysm using Mendelian randomization (MR). The study aimed to establish a foundation for the development of effective prevention and treatment strategies.

METHODS

Genetic association data for Neuroticism were obtained from the UK Biobank, which included 393,411 individuals and 11,968,760 single nucleotide polymorphisms (SNPs). Genetic association data for aortic aneurysm were obtained from a genome-wide association study (GWAS), which included 479,194 individuals and 24,191,825 SNPs. Heterogeneity was assessed using the Cochran's Q statistic test. The study also utilized the MR Pleiotropy RESidual Sum and Outlier (Mr-PRESSO) test, as well as the MR-Egger regression method, to examine horizontal pleiotropy and determine the reliability of the findings through the leave-one-out method.

RESULTS

Forward MR analysis showed that the risk of aortic aneurysm was elevated in individuals with genetically predicted Neuroticism compared to those without Neuroticism (OR = 1.1315, 95 % CI: 1.0269-1.2468; P = 0.0126). The Cochran's Q test showed no heterogeneity (P > 0.05), and the MR-PRESSO test did not identify instrumental variables of horizontal pleiotropy (P > 0.05). The MR analysis remained robust after removing SNPs one by one. Inverse MR analysis did not observe an association between aortic aneurysm and having Neuroticism OR = 1.030, 95 % CI: 0.9459-1.118, P = 0.488).

CONCLUSION

Our study has established a clear causal relationship between genetically determined Neuroticism and the development of aortic aneurysms. It is therefore important to intensify screening and prevention efforts for aortic aneurysms in neurotic patients. It also opens new avenues for exploring the disease's pathogenesis.

A Two-Sample Mendelian Randomization Study of Neuroticism and Sleep Bruxism

Sleep bruxism (SB) affects a considerable part of the population and is associated with neuroticism, stress, and anxiety in various studies. However, the causal mechanisms between neuroticism and SB have not been examined. Understanding the reasons for SB is important as understanding bruxism may allow improved comprehensive management of the disorders and comorbidities related to it. Previous studies on the association of risk factors to SB have provided important symptomatic insight but were mainly questionnaire based or limited in sample size and could not adequately assess causal relationships. The aim of this study was to elaborate the possible causal relationship of neuroticism as a risk factor for SB through a Mendelian randomization (MR) approach by combining questionnaires, registry data, and genetic information in large scale. We performed a two-sample MR study using instrumental genetic variants of neuroticism, including neuroticism subcategories, in the UK Biobank (n = 380,506) and outcome data of probable SB using FinnGen (n [cases/controls] = 12,297/364,980). We discovered a causal effect from neuroticism to SB (odds ratio [OR] = 1.38 [1.10-1.74], P = 0.0057). A phenotype sensitive to stress and adversity had the strongest effect (OR = 1.59 [1.17-2.15], P = 0.0028). Sensitivity analyses across MR methods supported a causal relationship, and we did not observe pleiotropy between neuroticism and SB (MR-Egger intercept, P = 0.87). Our findings are in line with earlier observational studies that connect stress and SB. Furthermore, our results provide evidence that neurotic traits increase the risk of probable SB.

Comparing findings from the random-intercept cross-lagged panel model and the monozygotic twin difference cross-lagged panel model: Maladaptive parenting and offspring emotional and behavioural problems

Background

In this study we compare results obtained when applying the monozygotic twin difference cross-lagged panel model (MZD-CLPM) and a random intercept cross-lagged panel model (RI-CLPM) to the same data. Each of these models is designed to strengthen researchers' ability to draw causal inference from cross-lagged associations. We explore differences and similarities in how each model does this, and in the results each model produces. Specifically, we examine associations between maladaptive parenting and child emotional and behavioural problems in identical twins aged 9, 12 and 16.

Method

Child reports of 5698 identical twins from the Twins Early Development Study (TEDS) were analysed. We ran a regular CLPM to anchor our findings within the current literature, then applied the MZD-CLPM and the RI-CLPM.

Results

The RI-CLPM and MZD-CLPM each enable researchers to evaluate the direction of effects between correlated variables, after accounting for unmeasured sources of potential confounding. Our interpretation of these models therefore focusses primarily on the magnitude and significance of cross-lagged associations. In both the MZD-CLPM and the RI-CLPM behavioural problems at age 9 resulted in higher levels of maladaptive parenting at age 12. Other effects were not consistently significant across the two models, although the majority of estimates pointed in the same direction.

Conclusion

In light of the triangulated methods, differences in the results obtained using the MZD-CLPM and the RI-CLPM underline the importance of careful consideration of what sources of unmeasured confounding different models control for and that nuance is required when interpreting findings using such models. We provide an overview of what the CLPM, RI-CLPM and MZD-CLPM can and cannot control for in this respect and the conclusions that can be drawn from each model.

Genetic basis of STEM occupational choice and regional economic performance: a UK biobank genome-wide association study

BACKGROUND

Science, technology, engineering, and mathematics (STEM) professionals are regarded as the highly skilled labor force that fosters economic productivity, enterprise innovation, and international competitiveness of a country. This study aims to understand the genetic predisposition to STEM occupations and investigate its associations with regional economic performance. We conducted a genome-wide association study on the occupational choice of STEM jobs based on a sample of 178,976 participants from the UK Biobank database.

RESULTS

We identified two genetic loci significantly associated with participants' STEM job choices: rs10048736 on chromosome 2 and rs12903858 on chromosome 15. The SNP heritability of STEM occupations was estimated to be 4.2%. We also found phenotypic and genetic evidence of assortative mating in STEM occupations. At the local authority level, we found that the average polygenic score of STEM is significantly and robustly associated with several metrics of regional economic performance.

CONCLUSIONS

The current study expands our knowledge of the genetic basis of occupational choice and potential regional disparities in socioeconomic developments.

Association of circadian rhythms with brain disorder incidents: a prospective cohort study of 72242 participants

Circadian rhythm disruption (CRD) is a shared characteristic of various brain disorders, such as Alzheimer's disease (AD), Parkinson's disease (PD), and major depression disorder (MDD). Disruption of circadian rhythm might be a risk factor for brain disorder incidents. From 7-day accelerometry data of 72,242 participants in UK Biobank, we derived a circadian relative amplitude variable, which to some extent reflected the degree of circadian rhythm disruption. Records of brain disorder incidents were obtained from a wide range of health outcomes across self-report, primary care, hospital inpatient data, and death data. Using multivariate Cox proportional hazard ratio regression, we created two models adjusting for different covariates. Then, linear correlations between relative amplitude and several brain morphometric measures were examined in participants with brain MRI data. After a median follow-up of around 6.1 years, 72,242 participants were included in the current study (female 54.9%; mean age 62.1 years). Individuals with reduced relative amplitude had increasing risk of all-cause dementia (Hazard ratio 1.23 [95% CI 1.15 to 1.31]), PD (1.33 [1.25 to 1.41]), stroke (1.13 [1.06 to 1.22]), MDD (1.18 [1.13 to 1.23]), and anxiety disorder (1.14 [1.09 to 1.20]) in fully adjusted models. Additionally, significant correlations were found between several cortical regions and white matter tracts and relative amplitude that have been linked to dementia and psychiatric disorders. We confirm CRD to be a risk factor for various brain disorders. Interventions for regulating circadian rhythm may have clinical relevance to reducing the risk of various brain disorders.

A Moderated Mediation Model of the Relationship between Family Dynamics and Sleep Quality in College Students: The Role of Big Five Personality and Only-Child Status

Sleep quality among college students is affected by numerous factors. Previous studies have linked sleep quality to family dynamics as well as personality. However, little is known about the mechanisms underlying this relationship. The aim of this study is to incorporate a moderated mediation model to explore the big five personality traits in mediating the relationship between family dynamics and sleep quality and whether this indirect relationship is modified by only-child status among Chinese undergraduate students. Survey data were collected from a cross-sectional study conducted in Shandong, China and 1022 undergraduate students aged 18–24 were recruited. The mediation and moderated mediation modeling analyses were carried out with the software SPSS PROCESS macro. After controlling for gender and grade, mediation analysis indicated that conscientiousness and agreeableness of the big five personality traits partially mediated the link between family dynamics and sleep quality (β = −0.0093, CI: −0.0178, −0.0018; β = −0.0047, CI: −0.0084, −0.0013), and moderation analysis found only-child status acted as a moderator in the relationship between family dynamics and the agreeableness of the big five personality traits (only child, β = −0.0129, CI: −0.0196, −0.0072; non-only-child, β = −0.0040, CI: −0.0078, −0.0002). Results showed that family dynamics positively predicted sleep quality both directly and indirectly via the conscientiousness and agreeableness of big five personality traits. Only-child status moderated the indirect association between family dynamics and agreeableness of big five personality traits. The current study advanced our understanding of the mechanism underlying the connection between family dynamics and sleep quality and helped to develop intervention measures to improve sleep quality of college students.

Association Between Medication-Taking and Refractive Error in a Large General Population-Based Cohort

Purpose

Refractive errors, particularly myopia, are common and a leading cause of blindness. This study aimed to explore associations between medications and refractive error in an aging adult cohort and to determine whether childhood-onset refractive errors predict future medication use to provide novel insights into disease mechanisms.

Methods

The study compared the spherical equivalent values measured in 102,318 UK Biobank participants taking the 960 most commonly used medications. The strengths of associations were evaluated against the self-reported age of spectacle wear. The causality of refractive error changes was inferred using sensitivity and Mendelian randomization analyses.

Results

Anti-glaucoma drugs were associated with 1 to 2 diopters greater myopic refraction, particularly in subjects who started wearing correction in the first two decades of life, potentially due to the association of higher intraocular pressure since early years with both myopia and, later in life, glaucoma. All classes of pain-control medications, including paracetamol, opiates, non-steroidal antiinflammatory drugs, and gabapentinoids, were associated with greater hyperopia (+0.68-1.15 diopters), after correction for deprivation, education, and polypharmacy and sensitivity analyses for common diagnoses. Oral hypoglycemics (metformin, gliburonide) were associated with myopia, as was allopurinol, and participants using bronchodilators (ipratropium and salbutamol) were more hyperopic.

Conclusions

This study finds for the first time, to our knowledge, that medication use is associated with refractive error in adults. The novel finding that analgesics are associated with hyperopic refraction, and the possibility that multisite chronic pain predisposes to hyperopia, deserves further research. Some drugs, such as antihyperglycemic or bronchodilators, may directly alter refractive error. Intraocular pressure appears causative for myopia.

Spatial distribution and cognitive impact of cerebrovascular risk-related white matter hyperintensities

OBJECTIVES

White matter hyperintensities (WMHs) are considered macroscale markers of cerebrovascular burden and are associated with increased risk of vascular cognitive impairment and dementia. However, the spatial location of WMHs has typically been considered in broad categories of periventricular versus deep white matter. The spatial distribution of WHMs associated with individual cerebrovascular risk factors (CVR), controlling for frequently comorbid risk factors, has not been systematically investigated at the population level in a healthy ageing cohort. Furthermore, there is an inconsistent relationship between total white matter hyperintensity load and cognition, which may be due to the confounding of several simultaneous risk factors in models based on smaller cohorts.

METHODS

We examined trends in individual CVR factors on total WMH burden in 13,680 individuals (aged 45-80) using data from the UK Biobank. We estimated the spatial distribution of white matter hyperintensities associated with each risk factor and their contribution to explaining total WMH load using voxel-wise probit regression and univariate linear regression. Finally, we explored the impact of CVR-related WMHs on speed of processing using regression and mediation analysis.

RESULTS

Contrary to the assumed dominance of hypertension as the biggest predictor of WMH burden, we show associations with a number of risk factors including diabetes, heavy smoking, APOE ε4/ε4 status and high waist-to-hip ratio of similar, or greater magnitude to hypertension. The spatial distribution of WMHs varied considerably with individual cerebrovascular risk factors. There were independent effects of visceral adiposity, as measured by waist-to-hip ratio, and carriage of the APOE ε4 allele in terms of the unique spatial distribution of CVR-related WMHs. Importantly, the relationship between total WMH load and speed of processing was mediated by waist-to-hip ratio suggesting cognitive consequences to WMHs associated with excessive visceral fat deposition.

CONCLUSION

Waist-to-hip ratio, diabetes, heavy smoking, hypercholesterolemia and homozygous APOE ε4 status are important risk factors, beyond hypertension, associated with WMH total burden and warrant careful control across ageing. The spatial distribution associated with different risk factors may provide important clues as to the pathogenesis and cognitive consequences of WMHs. High waist-to-hip ratio is a key risk factor associated with slowing in speed of processing. With global obesity levels rising, focused management of visceral adiposity may present a useful strategy for the mitigation of cognitive decline in ageing.