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In this largest whole-exome sequencing study of epilepsies to date, the Epi25 Collaborative identified extremely rare variants that confer risk for diverse epilepsy subtypes, highlighting roles in synaptic transmission and neuronal excitability.

Data from over 700,000 individuals reveal the identity of 83 sequence variants that affect human height, implicating new candidate genes and pathways as being involved in growth.

Genome-wide analysis identifies 30 loci associated with bipolar disorder, allowing for comparisons of shared genes and pathways with other psychiatric disorders, including schizophrenia and depression.

Meta-analysis of genome-wide association studies for cognitive ability identifies 190 new loci and implicates 939 new genes related to neurogenesis, neuron differentiation and synaptic structure.

A cross-scale analysis of paired-stressor effects on biological variables of European freshwater ecosystems shows that in 39% of cases, significant effects were limited to single stressors, with nutrient enrichment being the most important of these in lakes. Additive and interactive effects were similarly frequent (ca. 30% each), this frequency being independent of the spatial scale of analysis for lakes but increasing with scale for rivers.

The MAGIC investigators report results of a large genome-wide association study meta-analysis to identify common variants influencing fasting glucose homeostasis. They further show that several of the newly discovered loci influencing glycemic traits are also associated with risk of type 2 diabetes.

At zero magnetic field, the triangular-lattice antiferromagnet NaYbO₂ shows the absence of long-range magnetic order down to 50 mK, consistent with quantum spin liquid behaviour. An external field renders the system a collinear ordered phase.

Using transcriptomic data from human brain cells, the authors show that the expression patterns of the genes implicated in human cognition and brain evolution overlap in specific neuron types, and relate to cellular function and structure.

A genome-wide association study in ~3 million individuals identifies 3,952 independent variants associated with educational attainment. A polygenic index explains 12–16% of variance for this trait and contributes to risk prediction for ten diseases.

Common polygenic variation at chromosome 16p and rare recurrent deletions of 16p11.2 influencing autism risk are associated with reduced expression of genes throughout the 16p region, suggesting functional convergence of rare and common variant effects.

The CNV analysis group of the Psychiatric Genomic Consortium analyzes a large schizophrenia cohort to examine genomic copy number variants (CNVs) and disease risk. They find an enrichment of CNV burden in cases versus controls and identify 8 genome-wide significant loci as well as novel suggestive loci conferring either risk or protection to schizophrenia.

Sexual dimorphism in genetic vulnerability to schizophrenia, systemic lupus erythematosus and Sjögren’s syndrome is linked to differential protein abundance from alleles of complement component 4.

Patrick Sullivan and colleagues report a multi-stage genome-wide association study for schizophrenia in a Swedish population. They identify 13 loci newly associated with schizophrenia.

This study uses gene expression predictors for the dorsolateral prefrontal cortex and other brain regions to perform a transcriptomic imputation analysis of schizophrenia, identifying 413 genic associations across 13 brain regions and 36 significantly enriched pathways.

Cortex morphology varies with age, cognitive function, and in neurological and psychiatric diseases. Here the authors report 160 genome-wide significant associations with thickness, surface area and volume of the total cortex and 34 cortical regions from a GWAS meta-analysis in 22,824 adults.

Integration of GWAS and single-cell transcriptomic data from the entire nervous system systematically identifies cell types underlying brain complex traits and provides insights into the etiology of Parkinson’s disease.

Environmental influences during prenatal development may have implications for health and disease later in life. Here, Czamara et al. assess DNA methylation in cord blood from new-born under various models including environmental and genetic effects individually and their additive or interaction effects.

The authors defined a roadmap for investigating the genetic covariance between structural or functional brain phenotypes and risk for psychiatric disorders. Their proof-of-concept study using the largest available common variant data sets for schizophrenia and volumes of several (mainly subcortical) brain structures did not find evidence of genetic overlap.

Frequencies of rare variants fluctuate over populations, hampering gene discovery. Here the authors use a population-specific reference panel, the Genome of the Netherlands, to discover four novel loci involved in lipid metabolism, including an exonic variant in ABCA6.

Schizophrenia is a highly heritable genetic disorder, however, identification of specific genetic risk variants has proven difficult because of its complex polygenic nature—a large multi-stage genome-wide association study identifies 128 independent associations in over 100 loci (83 of which are new); key findings include identification of genes involved in glutamergic neurotransmission and support for a link between the immune system and schizophrenia.

Relatives of patients with amyotrophic lateral sclerosis have an unexpectedly high incidence of schizophrenia. Here, the authors show a genetic link between the two conditions, suggesting shared neurobiological mechanisms.

Depression is correlated with many brain-related traits. Here, Shen et al. perform phenome-wide association studies of a depression polygenic risk score (PRS) and find associations with 51 behavioural and 26 neuroimaging traits which are further followed up on using Mendelian randomization and mediation analyses.

In genome-wide association meta-analysis, it is often difficult to find an independent dataset of sufficient size to replicate associations. Here, the authors have developed MAMBA to calculate the probability of replicability based on consistency between datasets within the meta-analysis.

A genome-wide-association meta-analysis of 18,381 austim spectrum disorder (ASD) cases and 27,969 controls identifies five risk loci. The authors find quantitative and qualitative polygenic heterogeneity across ASD subtypes.

Cross-trait meta-analysis on 12 psychiatric disorders identifies the genetic overlap between pairs of disorders and highlights the challenges of cross-trait genetic research.

Better analytical methods are needed to extract biological meaning from genome-wide association studies (GWAS) of psychiatric disorders. Here the authors take GWAS data from over 60,000 subjects, including patients with schizophrenia, bipolar disorder and major depression, and identify common etiological pathways shared amongst them.

Aarno Palotie and colleagues present results of a large genome-wide association study of migraine. They identified significant associations at 38 distinct loci and found enrichment for genes expressed in vascular and smooth muscle tissues.

Gene discovery and polygenic predictions from a genome-wide association study of educational attainment in 1.1 million individuals.

Heritability is one of the oldest parameters in genetics, but also one of the most misunderstood. The authors explore exactly what heritability means, the pitfalls to avoid when using it, and its continued relevance in the genomics era.

Association studies of up to 1.2 million individuals identify 566 genetic variants in 406 loci associated with tobacco use and addiction (initiation, cessation, and heaviness) as well as alcohol use, with 150 loci showing pleiotropic association.

A genome-wide association study in 293,723 individuals identifies 74 genetic variants associated with educational attainment, which, although only explaining a small proportion of the variation in educational attainment, highlights candidate genes and pathways for further study.

Uffelmann et al. describe the key considerations and best practices for conducting genome-wide association studies (GWAS), techniques for deriving functional inferences from the results and applications of GWAS in understanding disease risk and trait architecture. The Primer also provides information on the best practices for data sharing and discusses important ethical considerations when considering GWAS populations and data.

The Tobacco and Genetics Consortium report meta-analyses of several smoking phenotypes across 16 cohorts including 74,053 individuals. They identify three loci associated with cigarettes smoked per day.

Naomi Wray and colleagues report an analysis of genome-wide association data sets from the Psychiatric Genomics Consortium for five psychiatric disorders. They find that common variation explains 17–29% of the variance in liability and provide further support for a shared genetic etiology for these related psychiatric disorders.