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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 health 7 , 8 , translating to high economic burden 9 . Genome-wide association studies (GWAS) of neuroticism have identified up to 11 associated genetic loci 3 , 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 ( r g  = 0.82, standard error (s.e.) = 0.03), major depressive disorder (MDD; r g  = 0.69, s.e. = 0.07) and subjective well-being ( r g  = –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.

ADHD and internalising problems commonly co-occur with up to 50% of children diagnosed with ADHD also suffering from anxiety or depression. However, their developmental relations are currently not well understood. Longitudinal symptom level analyses can provide valuable insights into how difficulties in these areas of psychosocial functioning affect each other. Using Gaussian Graphical Models and Graphical Vector Autoregression Models, this study estimated cross-sectional and longitudinal networks of ADHD and internalising symptoms in 1387 children using parent- and teacher-reported Social Behaviour Questionnaires (SBQ) when children were aged 7, 9 and 11. Cross-sectional and longitudinal networks suggested that ADHD shares reciprocal relations with internalising symptoms through a number of potential bridge symptoms that are primarily connected to anxiety symptoms. High scores on child cannot sit still, is restless, or hyperactive were found to be the strongest bridge symptom acting as an antecedent to higher internalising symptoms whereas child is worried was the strongest antecedent for higher ADHD symptoms. Findings of this study highlight several potential bridge symptoms that may serve as key intervention targets and further emphasise the need for clinicians to assess children presenting with ADHD symptoms for internalising problems and vice versa.

Pedigree-based analyses of intelligence have reported that genetic differences account for 50–80% of the phenotypic variation. For personality traits these effects are smaller, with 34–48% of the variance being explained by genetic differences. However, molecular genetic studies using unrelated individuals typically report a heritability estimate of around 30% for intelligence and between 0 and 15% for personality variables. Pedigree-based estimates and molecular genetic estimates may differ because current genotyping platforms are poor at tagging causal variants, variants with low minor allele frequency, copy number variants, and structural variants. Using ~20,000 individuals in the Generation Scotland family cohort genotyped for ~700,000 single-nucleotide polymorphisms (SNPs), we exploit the high levels of linkage disequilibrium (LD) found in members of the same family to quantify the total effect of genetic variants that are not tagged in GWAS of unrelated individuals. In our models, genetic variants in low LD with genotyped SNPs explain over half of the genetic variance in intelligence, education, and neuroticism. By capturing these additional genetic effects our models closely approximate the heritability estimates from twin studies for intelligence and education, but not for neuroticism and extraversion. We then replicated our finding using imputed molecular genetic data from unrelated individuals to show that ~50% of differences in intelligence, and ~40% of the differences in education, can be explained by genetic effects when a larger number of rare SNPs are included. From an evolutionary genetic perspective, a substantial contribution of rare genetic variants to individual differences in intelligence, and education is consistent with mutation-selection balance.

Using a unique and rich data set of lifetime cognitive measures, the contribution of genetics to differences in cognitive ageing is explored. Influence of ageing and genetics on cognitive function The ageing world population adds urgency to studying the causes of mental deterioration with age. The Scottish Mental Surveys of 1932 and 1947 subjected 11-year-old children to a well-validated test of general intelligence. Almost 2,000 of these individuals have been tested in subsequent years — and genome-wide single nucleotide polymorphism data collected — to provide a unique data set of lifetime cognitive measures. The data suggest that genetic factors underlie the differences in intelligence stability across the human lifespan. Estimates of the genetic contributions to cognitive stability and change in this cohort imply that a search for the genetic causes of lifetime cognitive change is worthwhile. Understanding the determinants of healthy mental ageing is a priority for society today 1 , 2 . So far, we know that intelligence differences show high stability from childhood to old age 3 , 4 and there are estimates of the genetic contribution to intelligence at different ages 5 , 6 . However, attempts to discover whether genetic causes contribute to differences in cognitive ageing have been relatively uninformative 7 , 8 , 9 , 10 . Here we provide an estimate of the genetic and environmental contributions to stability and change in intelligence across most of the human lifetime. We used genome-wide single nucleotide polymorphism (SNP) data from 1,940 unrelated individuals whose intelligence was measured in childhood (age 11 years) and again in old age (age 65, 70 or 79 years) 11 , 12 . We use a statistical method that allows genetic (co)variance to be estimated from SNP data on unrelated individuals 13 , 14 , 15 , 16 , 17 . We estimate that causal genetic variants in linkage disequilibrium with common SNPs account for 0.24 of the variation in cognitive ability change from childhood to old age. Using bivariate analysis, we estimate a genetic correlation between intelligence at age 11 years and in old age of 0.62. These estimates, derived from rarely available data on lifetime cognitive measures, warrant the search for genetic causes of cognitive stability and change.

As a cardinal marker of brain ageing, lifetime brain atrophy obtained from a cross-sectional magnetic resonance image promises to boost statistical power to uncover novel genetic mechanisms of neurodegeneration. By analysing five young and old adult cohorts, we perform the most definitive study on lifetime brain atrophy’s measurement and correlates. It is simply calculated from the relationship between total brain volume and intracranial volume, using the difference, ratio, or regression-residual method. Lifetime brain atrophy is correlated with well-validated neuroradiological atrophy ratings ( r  = 0.37–0.44), cognitive decline ( r  = 0.36), frailty ( r  = 0.24), and longitudinally-measured atrophic changes ( r  = 0.36). Lifetime brain atrophy computed with the difference method yields phenotypic and genetic signal similar to baseline intracranial volume ( r g  = 0.75), in contrast to the residual method, which also best captures brain shrinkage. Lifetime brain atrophy is highly heritable ( h 2 SNP  = 41%[95%CI = 38–43%]), and the strongest genome-wide association ( N  = 43,110) implicates WNT16 , a gene linked with neurodegenerative diseases. A single MRI scan can provide reliable estimates of human lifetime brain atrophy, helping overcome lifespan data collection challenges. This may enhance genetic studies of late-life neurodegeneration and reveal new insights into its underlying mechanisms.

Autosomal variants have successfully been associated with trait neuroticism in genome-wide analysis of adequately powered samples. But such studies have so far excluded the X chromosome from analysis. Here, we report genetic association analyses of X chromosome and XY pseudoautosomal single nucleotide polymorphisms (SNPs) and trait neuroticism using UK Biobank samples (N = 405,274). Significant association was found with neuroticism on the X chromosome for 204 markers found within three independent loci (a further 783 were suggestive). Most of the lead neuroticism-related X chromosome variants were located in intergenic regions (n = 397). Involvement of HS6ST2, which has been previously associated with sociability behaviour in the dog, was supported by single SNP and gene-based tests. We found that the amino acid and nucleotide sequences are highly conserved between dogs and humans. From the suggestive X chromosome variants, there were 19 nearby genes which could be linked to gene ontology information. Molecular function was primarily related to binding and catalytic activity; notable biological processes were cellular and metabolic, and nucleic acid binding and transcription factor protein classes were most commonly involved. X-variant heritability of neuroticism was estimated at 0.22% (SE = 0.05) from a full dosage compensation model. A polygenic X-variant score created in an independent sample (maximum N ≈ 7,300) did not predict significant variance in neuroticism, psychological distress, or depressive disorder. We conclude that the X chromosome harbours significant variants influencing neuroticism, and might prove important for other quantitative traits and complex disorders.

IntroductionSuccessful acquisition of language and literacy skills is essential to child development and is associated with positive socioeconomic and well-being outcomes later in life. Research into communication skills has primarily focused on early development and childhood. This is particularly the case for studies of genetic variation in reading and language skills, which rarely include older adults; the largest genome-wide association study to date includes participants only up to 26 years of age. We argue that reading-related traits remain stable across the adult lifespan and that including older adults offers a way to increase statistical power for gene discovery. Here, we describe newly available reading, spelling and oral-language-related measures in the Generation Scotland: Scottish Family Health Study (GS:SFHS).MethodsPhenotypic data in GS:SFHS were extended to include quantitative measures of reading, spelling and language-related measures as well as self-reported neurodevelopmental and psychiatric conditions. Participants also reported frequency of book reading in both childhood and adulthood. Multiple regression analyses were conducted to examine associations between reading-related measures and age and characterise their stability across the adult lifespan.ResultsReading-related data were collected for N=1595 GS:SFHS participants aged 29.5–76.9 years. Regression analyses indicated that reading and spelling performance were stable across the adult lifespan. In contrast, negative curvilinear effects of age2 were observed with phonological verbal-memory, auditory short-term memory and working memory, indicating decreasing performance with increasing age.ConclusionsThese data provide a novel resource for investigating reading, spelling and language skills in adults. The opportunity to link these measures with the existing and future biomarker, cognitive and health record data within GS:SFHS offers a deeply phenotyped dataset with substantial potential for replication studies, meta-analyses and future genetic discovery.

Visual acuity significantly contributes to quality of life. Deficits in childhood are associated with reading difficulties, which can have detrimental effects on education outcomes. In adults, it has been observed that vision defects such as myopia are associated with higher educational attainment (EA). Understanding genetic factors contributing to visual acuity could help to dissect its links with cognitive skills, neurodevelopmental conditions, and education. We examined associations between distance visual acuity, cognitive measures including school grades, and neurodevelopmental conditions in a longitudinal cohort of British children (ALSPAC, n = 6807, M age = 11.8). We performed a genome-wide association study (GWAS, n = 5571) on visual acuity and tested for genetic associations with relevant phenotypes using polygenic scores (PGS) and genetic correlation analyses. Visual acuity was associated with better cognitive performance and school grades, and reduced in individuals with reading difficulties compared to controls. GWAS revealed genetic associations at the NPLOC4 locus and highlighted other genes involved in sensory function. In line with positive genetic correlations between visual acuity and cognitive measures, EA PGS were positively associated with visual acuity, while there was a less robust negative association with myopia PGS. In conclusion, increased visual acuity is associated with a range of positive outcomes, including better school grades. Our results suggest an association between a higher EA PGS and slightly increased visual acuity in childhood. This could indicate gene-environment correlation, in which environmental exposures linked to higher EA might have detrimental effects on vision offsetting the initial positive effect.

The ability to read is an important life skill and a major route to education. Dyslexia, characterized by difficulties with accurate/ fluent word reading, and poor spelling is influenced by genetic variation, with a twin study heritability estimate of 0.4–0.6. Until recently, genomic investigations were limited by modest sample size. We used a multivariate genome-wide association study (GWAS) method, MTAG, to leverage summary statistics from two independent GWAS efforts, boosting power for analyses of dyslexia; the GenLang meta-analysis of word reading ( N  = 27,180) and the 23andMe, Inc., study of dyslexia (N cases  = 51,800, N controls  = 1,087,070). We increased the effective sample size to 1,228,832 participants, representing the largest genetic study of reading-related phenotypes to date. Our analyses identified 80 independent genome-wide significant loci, including 36 regions which were not previously reported as significant. Of these 36 loci, 13 were novel regions with no prior association with dyslexia. We observed clear genetic correlations with cognitive and educational measures. Gene-set analyses revealed significant enrichment of dyslexia-associated genes in four neuronal biological process pathways, and findings were further supported by enrichment of neuronally expressed genes in the developing embryonic brain. Polygenic index analysis of our multivariate results predicted between 2.34–4.73% of variance in reading traits in an independent sample, the National Child Development Study cohort ( N  = 6410). Polygenic adaptation was examined using a large panel of ancient genomes spanning the last ~15 k years. We did not find evidence of selection, suggesting that dyslexia has not been subject to recent selection pressure in Europeans. By combining existing datasets to improve statistical power, these results provide novel insights into the biology of dyslexia.

Subjective wellbeing (SWB) has been widely accepted as one of the most important elements of successful ageing. The present study explores the impact of two well-established correlates of SWB: physical activity and personality. Physical activity and each of the Big Five personality traits are consistent predictors of SWB, but there has been little research on whether certain personality traits enhance or hinder the psychological benefits of physical activity in older adults. This study examines the interactions of leisure-time physical activity and personality traits on SWB, and whether such interactions vary between older adults in Hong Kong (HK) and older adults in the United Kingdom (UK). Altogether, 349 participants (178 HK, 171 UK; 157 males, 192 female) aged 50 years or above (mean age = 61.84 ± 8.46 years old) completed an online assessment of: (1) leisure-time physical activity (Godin–Shephard Leisure-Time Physical Activity Questionnaire); (2) personality traits (Big Five Inventory); and (3) SWB (Satisfaction with Life Scale, Positive and Negative Affect Schedule). Results showed that agreeableness, conscientiousness, extraversion, neuroticism, openness to experience, and physical activity were all significantly related to SWB in the expected direction. The relationship between physical activity and SWB was moderated by extraversion and by openness to experience: higher levels of these two traits significantly enhanced the relationship. None of the interactions varied between the HK and UK samples. The expected negative relationship between neuroticism and SWB, however, was significantly stronger in the UK sample than in the HK sample. The findings of the present study indicate that personality needs to be considered when promoting and providing physical activity for older adults, although more research is needed to further explore how this can work effectively.