Saskia P. Hagenaars

Genome-wide association study of cognitive functions and educational attainment in UK Biobank (N=112 151)

People’s differences in cognitive functions are partly heritable and are associated with important life outcomes. Previous genome-wide association (GWA) studies of cognitive functions have found evidence for polygenic effects yet, to date, there are few replicated genetic associations. Here we use data from the UK Biobank sample to investigate the genetic contributions to variation in tests of three cognitive functions and in educational attainment. GWA analyses were performed for verbal–numerical reasoning (N=36 035), memory (N=112 067), reaction time (N=111 483) and for the attainment of a college or a university degree (N=111 114). We report genome-wide significant single-nucleotide polymorphism (SNP)-based associations in 20 genomic regions, and significant gene-based findings in 46 regions. These include findings in the ATXN2, CYP2DG, APBA1 and CADM2 genes. We report replication of these hits in published GWA studies of cognitive function, educational attainment and childhood intelligence. There is also replication, in UK Biobank, of SNP hits reported previously in GWA studies of educational attainment and cognitive function. GCTA-GREML analyses, using common SNPs (minor allele frequency>0.01), indicated significant SNP-based heritabilities of 31% (s.e.m.=1.8%) for verbal–numerical reasoning, 5% (s.e.m.=0.6%) for memory, 11% (s.e.m.=0.6%) for reaction time and 21% (s.e.m.=0.6%) for educational attainment. Polygenic score analyses indicate that up to 5% of the variance in cognitive test scores can be predicted in an independent cohort. The genomic regions identified include several novel loci, some of which have been associated with intracranial volume, neurodegeneration, Alzheimer’s disease and schizophrenia.

Shared genetic aetiology between cognitive functions and physical and mental health in UK Biobank ( N =112 151) and 24 GWAS consortia

Causes of the well-documented association between low levels of cognitive functioning and many adverse neuropsychiatric outcomes, poorer physical health and earlier death remain unknown. We used linkage disequilibrium regression and polygenic profile scoring to test for shared genetic aetiology between cognitive functions and neuropsychiatric disorders and physical health. Using information provided by many published genome-wide association study consortia, we created polygenic profile scores for 24 vascular–metabolic, neuropsychiatric, physiological–anthropometric and cognitive traits in the participants of UK Biobank, a very large population-based sample (N=112 151). Pleiotropy between cognitive and health traits was quantified by deriving genetic correlations using summary genome-wide association study statistics and to the method of linkage disequilibrium score regression. Substantial and significant genetic correlations were observed between cognitive test scores in the UK Biobank sample and many of the mental and physical health-related traits and disorders assessed here. In addition, highly significant associations were observed between the cognitive test scores in the UK Biobank sample and many polygenic profile scores, including coronary artery disease, stroke, Alzheimer’s disease, schizophrenia, autism, major depressive disorder, body mass index, intracranial volume, infant head circumference and childhood cognitive ability. Where disease diagnosis was available for UK Biobank participants, we were able to show that these results were not confounded by those who had the relevant disease. These findings indicate that a substantial level of pleiotropy exists between cognitive abilities and many human mental and physical health disorders and traits and that it can be used to predict phenotypic variance across samples.

Subcortical volumetric abnormalities in bipolar disorder.

Considerable uncertainty exists about the defining brain changes associated with bipolar disorder (BD). Understanding and quantifying the sources of uncertainty can help generate novel clinical hypotheses about etiology and assist in the development of biomarkers for indexing disease progression and prognosis. Here we were interested in quantifying case–control differences in intracranial volume (ICV) and each of eight subcortical brain measures: nucleus accumbens, amygdala, caudate, hippocampus, globus pallidus, putamen, thalamus, lateral ventricles. In a large study of 1710 BD patients and 2594 healthy controls, we found consistent volumetric reductions in BD patients for mean hippocampus (Cohen’s d=−0.232; P=3.50 × 10−7) and thalamus (d=−0.148; P=4.27 × 10−3) and enlarged lateral ventricles (d=−0.260; P=3.93 × 10−5) in patients. No significant effect of age at illness onset was detected. Stratifying patients based on clinical subtype (BD type I or type II) revealed that BDI patients had significantly larger lateral ventricles and smaller hippocampus and amygdala than controls. However, when comparing BDI and BDII patients directly, we did not detect any significant differences in brain volume. This likely represents similar etiology between BD subtype classifications. Exploratory analyses revealed significantly larger thalamic volumes in patients taking lithium compared with patients not taking lithium. We detected no significant differences between BDII patients and controls in the largest such comparison to date. Findings in this study should be interpreted with caution and with careful consideration of the limitations inherent to meta-analyzed neuroimaging comparisons.

Genome-wide analysis of over 106 000 individuals identifies 9 neuroticism-associated loci

Neuroticism is a personality trait of fundamental importance for psychological well-being and public health. It is strongly associated with major depressive disorder (MDD) and several other psychiatric conditions. Although neuroticism is heritable, attempts to identify the alleles involved in previous studies have been limited by relatively small sample sizes. Here we report a combined meta-analysis of genome-wide association study (GWAS) of neuroticism that includes 91 370 participants from the UK Biobank cohort, 6659 participants from the Generation Scotland: Scottish Family Health Study (GS:SFHS) and 8687 participants from a QIMR (Queensland Institute of Medical Research) Berghofer Medical Research Institute (QIMR) cohort. All participants were assessed using the same neuroticism instrument, the Eysenck Personality Questionnaire-Revised (EPQ-R-S) Short Form’s Neuroticism scale. We found a single-nucleotide polymorphism-based heritability estimate for neuroticism of ∼15% (s.e.=0.7%). Meta-analysis identified nine novel loci associated with neuroticism. The strongest evidence for association was at a locus on chromosome 8 (P=1.5 × 10−15) spanning 4 Mb and containing at least 36 genes. Other associated loci included interesting candidate genes on chromosome 1 (GRIK3 (glutamate receptor ionotropic kainate 3)), chromosome 4 (KLHL2 (Kelch-like protein 2)), chromosome 17 (CRHR1 (corticotropin-releasing hormone receptor 1) and MAPT (microtubule-associated protein Tau)) and on chromosome 18 (CELF4 (CUGBP elav-like family member 4)). We found no evidence for genetic differences in the common allelic architecture of neuroticism by sex. By comparing our findings with those of the Psychiatric Genetics Consortia, we identified a strong genetic correlation between neuroticism and MDD and a less strong but significant genetic correlation with schizophrenia, although not with bipolar disorder. Polygenic risk scores derived from the primary UK Biobank sample captured ∼1% of the variance in neuroticism in the GS:SFHS and QIMR samples, although most of the genome-wide significant alleles identified within a UK Biobank-only GWAS of neuroticism were not independently replicated within these cohorts. The identification of nine novel neuroticism-associated loci will drive forward future work on the neurobiology of neuroticism and related phenotypes.

Pleiotropy between neuroticism and physical and mental health: findings from 108 038 men and women in UK Biobank.

People with higher levels of neuroticism have an increased risk of several types of mental disorder. Higher neuroticism has also been associated, less consistently, with increased risk of various physical health outcomes. We hypothesised that these associations may, in part, be due to shared genetic influences. We tested for pleiotropy between neuroticism and 17 mental and physical diseases or health traits using linkage disequilibrium regression and polygenic profile scoring. Genetic correlations were derived between neuroticism scores in 108 038 people in the UK Biobank and health-related measures from 14 large genome-wide association studies (GWASs). Summary information for the 17 GWASs was used to create polygenic risk scores for the health-related measures in the UK Biobank participants. Associations between the health-related polygenic scores and neuroticism were examined using regression, adjusting for age, sex, genotyping batch, genotyping array, assessment centre and population stratification. Genetic correlations were identified between neuroticism and anorexia nervosa (rg=0.17), major depressive disorder (rg=0.66) and schizophrenia (rg=0.21). Polygenic risk for several health-related measures were associated with neuroticism, in a positive direction in the case of bipolar disorder, borderline personality, major depressive disorder, negative affect, neuroticism (Genetics of Personality Consortium), schizophrenia, coronary artery disease, and smoking (β between 0.009–0.043), and in a negative direction in the case of body mass index (β=−0.0095). A high level of pleiotropy exists between neuroticism and some measures of mental and physical health, particularly major depressive disorder and schizophrenia.

Ageing and brain white matter structure in 3,513 UK Biobank participants

Quantifying the microstructural properties of the human brains connections is necessary for understanding normal ageing and disease. Here we examine brain white matter magnetic resonance imaging (MRI) data in 3,513 generally healthy people aged 44.64–77.12 years from the UK Biobank. Using conventional water diffusion measures and newer, rarely studied indices from neurite orientation dispersion and density imaging, we document large age associations with white matter microstructure. Mean diffusivity is the most age-sensitive measure, with negative age associations strongest in the thalamic radiation and association fibres. White matter microstructure across brain tracts becomes increasingly correlated in older age. This may reflect an age-related aggregation of systemic detrimental effects. We report several other novel results, including age associations with hemisphere and sex, and comparative volumetric MRI analyses. Results from this unusually large, single-scanner sample provide one of the most extensive characterizations of age associations with major white matter tracts in the human brain.

Molecular genetic contributions to social deprivation and household income in UK biobank

Summary Individuals with lower socio-economic status (SES) are at increased risk of physical and mental illnesses and tend to die at an earlier age [1, 2, 3]. Explanations for the association between SES and health typically focus on factors that are environmental in origin [4]. However, common SNPs have been found collectively to explain around 18% of the phenotypic variance of an area-based social deprivation measure of SES [5]. Molecular genetic studies have also shown that common physical and psychiatric diseases are partly heritable [6]. It is possible that phenotypic associations between SES and health arise partly due to a shared genetic etiology. We conducted a genome-wide association study (GWAS) on social deprivation and on household income using 112,151 participants of UK Biobank. We find that common SNPs explain 21% of the variation in social deprivation and 11% of household income. Two independent loci attained genome-wide significance for household income, with the most significant SNP in each of these loci being rs187848990 on chromosome 2 and rs8100891 on chromosome 19. Genes in the regions of these SNPs have been associated with intellectual disabilities, schizophrenia, and synaptic plasticity. Extensive genetic correlations were found between both measures of SES and illnesses, anthropometric variables, psychiatric disorders, and cognitive ability. These findings suggest that some SNPs associated with SES are involved in the brain and central nervous system. The genetic associations with SES obviously do not reflect direct causal effects and are probably mediated via other partly heritable variables, including cognitive ability, personality, and health.

Genetic variants linked to education predict longevity

Significance Individuals with more education tend to live longer. Genetic variants have been discovered that predict educational attainment. We tested whether a “polygenic score” based on these genetic variants could make predictions about people’s lifespan. We used data from three cohort studies (including >130,000 participants) to examine the link between offspring polygenic score for education and parental longevity. Across the studies, we found that participants with more education-linked genetic variants had longer-living parents; compared with those with the lowest genetic education scores, those with the highest scores had parents who lived on average 6 months longer. This finding suggests the hypothesis that part of the ultimate explanation for the extended longevity of better-educated people is an underlying, quantifiable, genetic propensity. Educational attainment is associated with many health outcomes, including longevity. It is also known to be substantially heritable. Here, we used data from three large genetic epidemiology cohort studies (Generation Scotland, n = ∼17,000; UK Biobank, n = ∼115,000; and the Estonian Biobank, n = ∼6,000) to test whether education-linked genetic variants can predict lifespan length. We did so by using cohort members’ polygenic profile score for education to predict their parents’ longevity. Across the three cohorts, meta-analysis showed that a 1 SD higher polygenic education score was associated with ∼2.7% lower mortality risk for both mothers (total ndeaths = 79,702) and ∼2.4% lower risk for fathers (total ndeaths = 97,630). On average, the parents of offspring in the upper third of the polygenic score distribution lived 0.55 y longer compared with those of offspring in the lower third. Overall, these results indicate that the genetic contributions to educational attainment are useful in the prediction of human longevity.

Association analysis in over 329,000 individuals identifies 116 independent variants influencing neuroticism

Neuroticism is a relatively stable personality trait characterized by negative emotionality (for example, worry and guilt)1; heritability estimated from twin studies ranges from 30 to 50%2, and SNP-based heritability ranges from 6 to 15%3–6. Increased neuroticism is associated with poorer mental and physical health7,8, translating to high economic burden9. Genome-wide association studies (GWAS) of neuroticism have identified up to 11 associated genetic loci3,4. Here we report 116 significant independent loci from a GWAS of neuroticism in 329,821 UK Biobank participants; 15 of these loci replicated at P < 0.00045 in an unrelated cohort (N = 122,867). Genetic signals were enriched in neuronal genesis and differentiation pathways, and substantial genetic correlations were found between neuroticism and depressive symptoms (rg = 0.82, standard error (s.e.) = 0.03), major depressive disorder (MDD; rg = 0.69, s.e. = 0.07) and subjective well-being (rg = –0.68, s.e. = 0.03) alongside other mental health traits. These discoveries significantly advance understanding of neuroticism and its association with MDD.Analysis of 329,000 individuals in the UK Biobank identifies 116 loci associated with neuroticism. Genes implicated are enriched in neuronal differentiation pathways, and genetic correlations between neuroticism and other mental health traits are elucidated.

Molecular genetic contributions to self-rated health.

Abstract Background: Poorer self-rated health (SRH) predicts worse health outcomes, even when adjusted for objective measures of disease at time of rating. Twin studies indicate SRH has a heritability of up to 60% and that its genetic architecture may overlap with that of personality and cognition. Methods: We carried out a genome-wide association study (GWAS) of SRH on 111 749 members of the UK Biobank sample. Univariate genome-wide complex trait analysis (GCTA)-GREML analyses were used to estimate the proportion of variance explained by all common autosomal single nucleotide polymorphisms (SNPs) for SRH. Linkage disequilibrium (LD) score regression and polygenic risk scoring, two complementary methods, were used to investigate pleiotropy between SRH in the UK Biobank and up to 21 health-related and personality and cognitive traits from published GWAS consortia. Results: The GWAS identified 13 independent signals associated with SRH, including several in regions previously associated with diseases or disease-related traits. The strongest signal was on chromosome 2 (rs2360675, P = 1.77 x 10-10) close to KLF7. A second strong peak was identified on chromosome 6 in the major histocompatibility region (rs76380179, P = 6.15 x 10-10). The proportion of variance in SRH that was explained by all common genetic variants was 13%. Polygenic scores for the following traits and disorders were associated with SRH: cognitive ability, education, neuroticism, body mass index (BMI), longevity, attention-deficit hyperactivity disorder (ADHD), major depressive disorder, schizophrenia, lung function, blood pressure, coronary artery disease, large vessel disease stroke and type 2 diabetes. Conclusions: Individual differences in how people respond to a single item on SRH are partly explained by their genetic propensity to many common psychiatric and physical disorders and psychological traits.