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Key Points Psychiatric disorders cause enormous morbidity, mortality and personal and societal costs. Despite considerable investigation, little is known for certain about aetiologies. Genetic approaches are a major avenue of investigation. In the past 5 years, a considerable number of new findings have been discovered that meet community standards for robustness and replication. Where sample sizes are sufficiently large, genome-wide association has yielded several dozen findings that suggest novel biological mechanisms. Studies of rare variation (generally using genome-wide association study chips) have yielded over ten copy number variants that confer markedly increased risk. However, these tend to be nonspecific and increase risk for multiple different neuropsychiatric conditions. Studies of exonic variation have yielded new findings for autism. However, for autism and schizophrenia, these findings are not abundant, and their genetic architectures do not appear to consist of a series of Mendelian traits, making the 'many Mendelian model' very unlikely. Looking at the psychiatric disorders for which there are sufficient genetics data, it seems that these disorders are fairly typical complex traits with genetic variation scattered across the allelic spectrum. For the first time, a fairly complete enumeration of the 'parts list' for these disorders is attainable using established methods. Further study using a balanced portfolio of methods to assess multiple forms of genetic variation is likely to yield many additional new findings. This Review considers recent findings — from genome-wide association studies, structural variant studies and exome sequencing — about the genetics of nine psychiatric disorders. The authors evaluate the implications of our current picture of the genetic architectures of these conditions for future research strategies. Psychiatric disorders are among the most intractable enigmas in medicine. In the past 5 years, there has been unprecedented progress on the genetics of many of these conditions. In this Review, we discuss the genetics of nine cardinal psychiatric disorders (namely, Alzheimer's disease, attention-deficit hyperactivity disorder, alcohol dependence, anorexia nervosa, autism spectrum disorder, bipolar disorder, major depressive disorder, nicotine dependence and schizophrenia). Empirical approaches have yielded new hypotheses about aetiology and now provide data on the often debated genetic architectures of these conditions, which have implications for future research strategies. Further study using a balanced portfolio of methods to assess multiple forms of genetic variation is likely to yield many additional new findings.

The search for the genetic factors underlying complex neuropsychiatric disorders has proceeded apace in the past decade. Despite some advances in identifying genetic variants associated with psychiatric disorders, most variants have small individual contributions to risk. By contrast, disease risk increase appears to be less subtle for disease-predisposing environmental insults. In this study, we sought to identify associations between environmental pollution and risk of neuropsychiatric disorders. We present exploratory analyses of 2 independent, very large datasets: 151 million unique individuals, represented in a United States insurance claims dataset, and 1.4 million unique individuals documented in Danish national treatment registers. Environmental Protection Agency (EPA) county-level environmental quality indices (EQIs) in the US and individual-level exposure to air pollution in Denmark were used to assess the association between pollution exposure and the risk of neuropsychiatric disorders. These results show that air pollution is significantly associated with increased risk of psychiatric disorders. We hypothesize that pollutants affect the human brain via neuroinflammatory pathways that have also been shown to cause depression-like phenotypes in animal studies.

Danielle Posthuma, Peter Visscher and colleagues report a meta-analysis of 17,804 traits based on virtually all twin studies from the last 50 years. For a majority of traits, twin resemblance seems solely due to additive genetic variation and lacks evidence for a substantial influence of shared environment or non-additive genetic variation. Despite a century of research on complex traits in humans, the relative importance and specific nature of the influences of genes and environment on human traits remain controversial. We report a meta-analysis of twin correlations and reported variance components for 17,804 traits from 2,748 publications including 14,558,903 partly dependent twin pairs, virtually all published twin studies of complex traits. Estimates of heritability cluster strongly within functional domains, and across all traits the reported heritability is 49%. For a majority (69%) of traits, the observed twin correlations are consistent with a simple and parsimonious model where twin resemblance is solely due to additive genetic variation. The data are inconsistent with substantial influences from shared environment or non-additive genetic variation. This study provides the most comprehensive analysis of the causes of individual differences in human traits thus far and will guide future gene-mapping efforts. All the results can be visualized using the MaTCH webtool.

Whether schizophrenia and bipolar disorder are the clinical outcomes of discrete or shared causative processes is much debated in psychiatry. We aimed to assess genetic and environmental contributions to liability for schizophrenia, bipolar disorder, and their comorbidity. We linked the multi-generation register, which contains information about all children and their parents in Sweden, and the hospital discharge register, which includes all public psychiatric inpatient admissions in Sweden. We identified 9 009 202 unique individuals in more than 2 million nuclear families between 1973 and 2004. Risks for schizophrenia, bipolar disorder, and their comorbidity were assessed for biological and adoptive parents, offspring, full-siblings and half-siblings of probands with one of the diseases. We used a multivariate generalised linear mixed model for analysis of genetic and environmental contributions to liability for schizophrenia, bipolar disorder, and the comorbidity. First-degree relatives of probands with either schizophrenia (n=35 985) or bipolar disorder (n=40 487) were at increased risk of these disorders. Half-siblings had a significantly increased risk (schizophrenia: relative risk [RR] 3·6, 95% CI 2·3–5·5 for maternal half-siblings, and 2·7, 1·9–3·8 for paternal half-siblings; bipolar disorder: 4·5, 2·7–7·4 for maternal half-siblings, and 2·4, 1·4–4·1 for paternal half-siblings), but substantially lower than that of the full-siblings (schizophrenia: 9·0, 8·5–11·6; bipolar disorder: 7·9, 7·1–8·8). When relatives of probands with bipolar disorder were analysed, increased risks for schizophrenia existed for all relationships, including adopted children to biological parents with bipolar disorder. Heritability for schizophrenia and bipolar disorder was 64% and 59%, respectively. Shared environmental effects were small but substantial (schizophrenia: 4·5%, 4·4%–7·4%; bipolar disorder: 3·4%, 2·3%–6·2%) for both disorders. The comorbidity between disorders was mainly (63%) due to additive genetic effects common to both disorders. Similar to molecular genetic studies, we showed evidence that schizophrenia and bipolar disorder partly share a common genetic cause. These results challenge the current nosological dichotomy between schizophrenia and bipolar disorder, and are consistent with a reappraisal of these disorders as distinct diagnostic entities. Swedish Council for Working Life and Social Research, and the Swedish Research Council.

Genome-wide association studies (GWAS) have identified over 100 risk loci for schizophrenia, but the causal mechanisms remain largely unknown. We performed a transcriptome-wide association study (TWAS) integrating a schizophrenia GWAS of 79,845 individuals from the Psychiatric Genomics Consortium with expression data from brain, blood, and adipose tissues across 3,693 primarily control individuals. We identified 157 TWAS-significant genes, of which 35 did not overlap a known GWAS locus. Of these 157 genes, 42 were associated with specific chromatin features measured in independent samples, thus highlighting potential regulatory targets for follow-up. Suppression of one identified susceptibility gene, mapk3 , in zebrafish showed a significant effect on neurodevelopmental phenotypes. Expression and splicing from the brain captured most of the TWAS effect across all genes. This large-scale connection of associations to target genes, tissues, and regulatory features is an essential step in moving toward a mechanistic understanding of GWAS. A transcriptome-wide association study integrating genome-wide association data with expression data from brain, blood and adipose tissues identifies new candidate susceptibility genes for schizophrenia, providing a step toward understanding the underlying biology.

Post-traumatic stress disorder (PTSD) is a major problem among military veterans and civilians alike, yet its pathophysiology remains poorly understood. We performed a genome-wide association study and bioinformatic analyses, which included 146,660 European Americans and 19,983 African Americans in the US Million Veteran Program, to identify genetic risk factors relevant to intrusive reexperiencing of trauma, which is the most characteristic symptom cluster of PTSD. In European Americans, eight distinct significant regions were identified. Three regions had values of P < 5 × 10−10: CAMKV; chromosome 17 closest to KANSL1, but within a large high linkage disequilibrium region that also includes CRHR1; and TCF4. Associations were enriched with respect to the transcriptomic profiles of striatal medium spiny neurons. No significant associations were observed in the African American cohort of the sample. Results in European Americans were replicated in the UK Biobank data. These results provide new insights into the biology of PTSD in a well-powered genome-wide association study.

A genome-wide association analysis using data from Chinese individuals combined with a transethnic meta-analysis of Psychiatry Genomics Consortium data identifies 30 new loci for schizophrenia. These analyses improve the fine-mapping of susceptibility loci and implicate multiple pathways in schizophrenia biology. We conducted a genome-wide association study (GWAS) with replication in 36,180 Chinese individuals and performed further transancestry meta-analyses with data from the Psychiatry Genomics Consortium (PGC2). Approximately 95% of the genome-wide significant (GWS) index alleles (or their proxies) from the PGC2 study were overrepresented in Chinese schizophrenia cases, including ∼50% that achieved nominal significance and ∼75% that continued to be GWS in the transancestry analysis. The Chinese-only analysis identified seven GWS loci; three of these also were GWS in the transancestry analyses, which identified 109 GWS loci, thus yielding a total of 113 GWS loci (30 novel) in at least one of these analyses. We observed improvements in the fine-mapping resolution at many susceptibility loci. Our results provide several lines of evidence supporting candidate genes at many loci and highlight some pathways for further research. Together, our findings provide novel insight into the genetic architecture and biological etiology of schizophrenia.

Schizophrenia is strongly familial yet rarely (if ever) exhibits classical Mendelian inheritance patterns. The advent of large-scale genotyping and sequencing projects has yielded large data sets with higher statistical power in an effort to uncover new associations with schizophrenia. Here, we review the challenges in dissecting the genetics of schizophrenia and provide an update of the current understanding of the underlying genomics. We discuss the breadth of susceptibility alleles, including those that may occur with low frequency and high disease risk, such as the 22q11.2 hemideletion, as well as alleles that may occur with greater frequency but convey a lower risk of schizophrenia, such as variants in genes encoding subunits of the voltage-gated L-type calcium channel. Finally, we provide an overview of the clinical implications for the diagnosis and treatment of schizophrenia based on progress in understanding the underlying genetic basis.

Soil microbial communities remain active during much of the Arctic winter, despite deeply frozen soils. Overwinter microbial activity affects the global carbon (C) budget, nutrient cycling, and vegetation composition. Microbial respiration is highly temperature sensitive in frozen soils, as liquid water and solute availability decrease rapidly with declining temperature. Climate warming and changes in snowpack are leading to warmer Arctic winter soils. Warmer winter soils are thought to yield greater microbial respiration of available C, greater overwinter CO 2 efflux and greater nutrient availability to plants at thaw. Using field and laboratory observations and experiments, we demonstrate that persistently warm winter soils can lead to labile C starvation and reduced microbial respiration, despite the high C content of most Arctic soils. If winter soils continue to warm, microbial C limitation will reduce expected CO 2 emissions and alter soil nutrient cycling, if not countered by greater labile C inputs. Soil microbial communities remain active throughout much of the Arctic winter, and Arctic winters are warming dramatically. Here, the authors show that persistently warm winter soils can lead to labile carbon starvation and reduced microbial respiration, despite the high carbon content of most Arctic soils.