General cognitive function is a prominent and relatively stable human trait that is associated with many important life outcomes. We combine cognitive and genetic data from the CHARGE and COGENT consortia, and UK Biobank (total N = 300,486; age 16–102) and find 148 genome-wide significant independent loci (P < 5 × 10−8) associated with general cognitive function. Within the novel genetic loci are variants associated with neurodegenerative and neurodevelopmental disorders, physical and psychiatric illnesses, and brain structure. Gene-based analyses find 709 genes associated with general cognitive function. Expression levels across the cortex are associated with general cognitive function. Using polygenic scores, up to 4.3% of variance in general cognitive function is predicted in independent samples. We detect significant genetic overlap between general cognitive function, reaction time, and many health variables including eyesight, hypertension, and longevity. In conclusion we identify novel genetic loci and pathways contributing to the heritability of general cognitive function.

Background: The coronavirus disease 2019 (COVID-19) pandemic and mitigation measures are likely to have a marked effect on mental health. It is important to use longitudinal data to improve inferences. Aims: To quantify the prevalence of depression, anxiety and mental wellbeing before and during the COVID-19 pandemic. To identify groups at risk of depression and/or anxiety during the pandemic. Methods: Data were from two generations of the Avon Longitudinal Study of Parents and Children (ALSPAC): the index generation (ALSPAC-young, n=2850, mean age=28), parent's generation (ALSPAC-parents, n=3720, mean age=59), and Generation Scotland (GS, n=4233, mean age=59). Depression was measured using the Short Mood and Feelings Questionnaire (SMFQ) in ALSPAC and the Patient Health Questionnaire (PHQ-9) in GS. Anxiety and mental wellbeing were measured using the Generalised Anxiety Disorder Assessment (GAD-7) and the Short Warwick Edinburgh Mental Wellbeing Scale. Results: Depression during COVID-19 was similar to pre-pandemic levels in ALSPAC-young, but those experiencing anxiety almost doubled during COVID-19: 24% (95% CI: 23%, 26%) compared to pre-pandemic levels of 13% (95% CI: 12%, 14%). In both ALSPAC and Generation Scotland, anxiety and depression during COVID-19 was greater in younger members, in women, in those with preexisting mental/physical health conditions, and in individuals in socioeconomic adversity, even when controlling for pre-pandemic anxiety and depression. Conclusions: These results provide evidence for increased anxiety in young people that is coincident with the pandemic. Specific groups are at elevated risk of depression and anxiety during COVID-19. This is important for planning mental health provisions now and for long-term impact beyond this pandemic.

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.

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.

Table 2). The Manhattan plot is shown in Figure 1 and Table 94 6). 95INSERT FIGURE 1 ABOUT HERE 97Of the 116 independent associated SNPs, 111 were present in the replication cohort, 98