Genotype imputation is a key component of genetic association studies, where it increases power, facilitates meta-analysis, and aids interpretation of signals. Genotype imputation is computationally demanding and, with current tools, typically requires access to a high-performance computing cluster and to a reference panel of sequenced genomes. Here we describe improvements to imputation machinery that reduce computational requirements by more than an order of magnitude with no loss of accuracy in comparison to standard imputation tools. We also describe a new web-based service for imputation that facilitates access to new reference panels and greatly improves user experience and productivity.

Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders 1 . They are heritable 2 , 3 and etiologically related 4 , 5 behaviors that have been resistant to gene discovery efforts 6 – 11 . In sample sizes up to 1.2 million individuals, we discovered 566 genetic variants in 406 loci associated with multiple stages of tobacco use (initiation, cessation, and heaviness) as well as alcohol use, with 150 loci evidencing pleiotropic association. Smoking phenotypes were positively genetically correlated with many health conditions, whereas alcohol use was negatively correlated with these conditions, such that increased genetic risk for alcohol use is associated with lower disease risk. We report evidence for the involvement of many systems in tobacco and alcohol use, including genes involved in nicotinic, dopaminergic, and glutamatergic neurotransmission. The results provide a solid starting point to evaluate the effects of these loci in model organisms and more precise substance use measures.

SummaryEducational attainment (EA) is strongly influenced by social and other environmental factors, but genetic factors are also estimated to account for at least 20% of the variation across individuals1. We report the results of a genome-wide association study (GWAS) for EA that extends our earlier discovery sample1,2 of 101,069 individuals to 293,723 individuals, and a replication in an independent sample of 111,349 individuals from the UK Biobank. We now identify 74 genome-wide significant loci associated with number of years of schooling completed. Single-nucleotide polymorphisms (SNPs) associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioral phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because EA is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric disease.

A hierarchical biometric model is presented of the origins of comorbidity among substance dependence, antisocial behavior, and a disinhibited personality style. The model posits a spectrum of personality and psychopathology, united by an externalizing factor linked to each phenotype within the spectrum, as well as specific factors that account for distinctions among phenotypes within the spectrum. This model fit self-report and mother-report data from 1,048 male and female 17-year-old twins. The variance of the externalizing factor was mostly genetic, but both genetic and environmental factors accounted for distinctions among phenotypes within the spectrum. These results reconcile evidence for general and specific causal factors within the externalizing spectrum and offer the externalizing factor as a novel target for future research.

We describe a reference panel of 64,976 human haplotypes at 39,235,157 SNPs constructed using whole genome sequence data from 20 studies of predominantly European ancestry. Using this resource leads to accurate genotype imputation at minor allele frequencies as low as 0.1%, a large increase in the number of SNPs tested in association studies and can help to discover and refine causal loci. We describe remote server resources that allow researchers to carry out imputation and phasing consistently and efficiently.

We conducted genome-wide association studies of three phenotypes: subjective well-being (N = 298,420), depressive symptoms (N = 161,460), and neuroticism (N = 170,910). We identified three variants associated with subjective well-being, two with depressive symptoms, and eleven with neuroticism, including two inversion polymorphisms. The two depressive symptoms loci replicate in an independent depression sample. Joint analyses that exploit the high genetic correlations between the phenotypes (|ρ̂| ≈ 0.8) strengthen the overall credibility of the findings, and allow us to identify additional variants. Across our phenotypes, loci regulating expression in central nervous system and adrenal/pancreas tissues are strongly enriched for association.

A genome-wide association study of educational attainment was conducted in a discovery sample of 101,069 individuals and a replication sample of 25,490. Three independent SNPs are genome-wide significant (rs9320913, rs11584700, rs4851266), and all three replicate. Estimated effects sizes are small (R2 ≈ 0.02%), approximately 1 month of schooling per allele. A linear polygenic score from all measured SNPs accounts for ≈ 2% of the variance in both educational attainment and cognitive function. Genes in the region of the loci have previously been associated with health, cognitive, and central nervous system phenotypes, and bioinformatics analyses suggest the involvement of the anterior caudate nucleus. These findings provide promising candidate SNPs for follow-up work, and our effect size estimates can anchor power analyses in social-science genetics.

Depression is a highly recurrent disorder with significant personal and public health consequences. Prevention of recurrence would be extremely desirable, and thus researchers have begun to identify risk factors that are specific to recurrence, which may be different from risk factors for first-onset of depression. Methodological issues in this area of research are briefly reviewed (e.g., the various definitions of "recurrence" and "depression"), followed by a review of studies on specific risk factors, including demographic variables (gender, socio-economic status, marital status), clinical variables (age at first onset, number of prior episodes, severity of first/index episode, comorbid psychopathology), family history of psychopathology, and psychosocial and psychological variables (level of psychosocial functioning, cognitions, personality, social support, and stressful life events). In addition, scar theories are evaluated for their potential to explain how these variables and recurrent depression are linked. Our review suggests that recurrent depression reflects an underlying vulnerability that is largely genetic in nature and that may predispose those high in the vulnerability not only to recurrent depressive episodes, but also to the significant psychosocial risk factors that often accompany recurrent depression.Major depressive disorder is one of the most common forms of psychopathology, one that will affect approximately one in six men and one in four women in their lifetimes . It is also usually highly recurrent, with at least 50% of those who recover from a first episode of depression having one or more additional episodes in their lifetime, and approximately 80% of those with a history of two episodes having another recurrence (American Psychiatric Association, 2000;Kupfer, Frank, & Wamhoff, 1996;Post, 1992). Once a first episode has occurred, recurrent episodes will usually begin within five years of the initial episode (Belsher & Costello, 1988;Lewinsohn, Clarke, Seeley, & Rohde, 1994), and, on average, individuals with a history of depression will have five (Kessler & Walters, 1998) to nine (Kessler, Zhao, Blazer, & Swartz, 1997) separate depressive episodes in their lifetime.Due to the fact that depression can be so recurrent, it can have significant personal and public health consequences. For example, one meta-analysis found that the suicide rate among those with depression is approximately twenty times higher than the rate for the general population (Harris & Barraclough, 1997). In addition, a study of over 3000 adolescents and young adults found that 90% of those with recurrent depression reported "very much" impairment, limiting work productivity and social interactions, and 40% sought professional help as a result (Wittchen, Nelson, & Lachner, 1998). Depression can also have a significant economic impact due to decreased productivity in affected individuals (Klerman & Weissman, 1992); in 1996 the annual direct (e.g., visits to doctors, pharmaceutical costs) and indirect (e.g., time...