Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association (GWA) meta-analysis based in 135,458 cases and 344,901 control, We identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression, and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relations of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine and define the basis of major depression and imply a continuous measure of risk underlies the clinical phenotype.

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.

Determination of recombination rates across the human genome has been constrained by the limited resolution and accuracy of existing genetic maps and the draft genome sequence. We have genotyped 5,136 microsatellite markers for 146 families, with a total of 1,257 meiotic events, to build a high-resolution genetic map meant to: (i) improve the genetic order of polymorphic markers; (ii) improve the precision of estimates of genetic distances; (iii) correct portions of the sequence assembly and SNP map of the human genome; and (iv) build a map of recombination rates. Recombination rates are significantly correlated with both cytogenetic structures (staining intensity of G bands) and sequence (GC content, CpG motifs and poly(A)/poly(T) stretches). Maternal and paternal chromosomes show many differences in locations of recombination maxima. We detected systematic differences in recombination rates between mothers and between gametes from the same mother, suggesting that there is some underlying component determined by both genetic and environmental factors that affects maternal recombination rates.

Reduced fecundity, associated with severe mental disorders1, places negative selection pressure on risk alleles and may explain, in part, why common variants have not been found that confer risk of disorders such as autism2 schizophrenia3 and mental retardation4. Thus, rare variants may account for a larger fraction of the overall genetic risk than previously assumed. In contrast to rare single nucleotide mutations, rare copy number variations (CNVs) can be detected using genome-wide single nucleotide polymorphism arrays. This has led to the identification of CNVs associated with mental retardation4,5 and autism2. In a genome-wide search for CNVs associating with schizophrenia, we used a population-based sample to identify de novo CNVs by analysing 9,878 transmissions from parents to offspring. The 66 de novo CNVs identified were tested for association in a sample of 1,433 schizophrenia cases and 33,250 controls. Three deletions at 1q21.1, 15q11.2 and 15q13.3 showing nominal association with schizophrenia in the first sample (phase I) were followed up in a second sample of 3,285 cases and 7,951 controls (phase II). All three deletions significantly associate with schizophrenia and related psychoses in the combined sample. The identification of these rare, recurrent risk variants, having occurred independently in multiple founders and being subject to negative selection, is important in itself. CNV analysis may also point the way to the identification of additional and more prevalent risk variants in genes and pathways involved in schizophrenia.

Smoking is a leading cause of preventable death, causing approximately five million premature deaths world-wide each year 1, 2 . Evidence for genetic influence on smoking behaviour and nicotine dependence (ND) 3-8 has prompted a search for susceptibility genes. Furthermore, assessing the impact of sequence variants on smoking-related diseases is important for public health reasons 9, 10 . Smoking is the major risk factor for lung cancer (LC) [11][12][13][14] , and one of the main risk factors for peripheral arterial disease (PAD) [15][16][17] . We have identified a common variant in the nicotinic acetylcholine receptor gene cluster on chromosome 15q24 with an effect on smoking quantity, ND and the risk of two smoking-related diseases in populations of European descent. The variant has an effect on the number of cigarettes smoked per day in 15,771 smokers (P=6×10 −20 ). The same variant associated with ND in a previous genome-wide association study using low quantity smokers as controls (OR=1.3, P=1×10 −3 ) 18,19 , and with a similar approach we observe a highly significant association with ND (OR =1.40, P=7×10 −15 ). Comparison of LC (N=1,024) and PAD (N= 2,738) cases with about 30,000 population controls each showed that the variant confers risk of LC (OR=1.31, P=1.5×10 −8 ) and PAD (OR=1.19, P=1.4×10 −7 ). The findings highlight the role of nicotine addiction in the pathogenesis of other serious diseases and provide a case study of the role of active gene-environment correlation 20 in the pathogenesis of disease.To perform a genome-wide association (GWA) study of smoking quantity (SQ), we utilised questionnaire data limited to basic questions on smoking behaviour that were available for a large number of lifetime smokers. The GWA scan comprises 10,995 Icelandic smokers who Reprints and permissions information is available at www.nature.com/reprints.