Search

In the second of three papers on the genetics of schizophrenia, a large genome-wide association study looking at common genetic variants underlying the risk of schizophrenia implicates the major histocompatibility complex — and thus, immunity — and provides molecular genetic evidence for a substantial polygenic component to the risk of schizophrenia. The latter involves thousands of common alleles of very small effect that also contribute to the risk of bipolar disorder.

The authors analyzed the whole-exome sequences of over 16,000 individuals and found that very rare variants predicted to disrupt the SETD1A gene confer substantial risk for schizophrenia. Damaging variants in SETD1A were also associated with diverse, severe developmental disorders, providing an important genetic link between schizophrenia and other neurodevelopmental disorders.

Douglas Ruderfer, Shaun Purcell and colleagues characterized the rates and properties of rare genic copy number variants in exome sequencing data from nearly 60,000 individuals in the Exome Aggregation Consortium. These data are available through an integrated database that spans the spectrum of human genetic variation, aiding in the interpretation of personal genomes and population-based disease studies.

Pamela Sklar and colleagues report a genome-wide association study of bipolar disorder and identify variants in the genes encoding ankyrin-3 and the alpha-1C subunit of the L-type voltage-gated calcium channel as increasing risk.

The genetics of schizophrenia and other mental disorders are complex and poorly understood, and made even harder to study due to reduced reproduction resulting in negative selection pressure on risk alleles. Two independent large-scale genome wide studies of thousands of patients and controls by two international consortia confirm a previously identified locus, but also reveal novel associations. In this study, deletions were reported on chromosomes 1 and 15, as well as a greater overall frequency of copy number variation in the genome.

Sequencing data from two large-scale studies show that most of the genetic variation influencing the risk of type 2 diabetes involves common alleles and is found in regions previously identified by genome-wide association studies, clarifying the genetic architecture of this disease.

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.

ADAR1 is an interferon-induced enzyme that catalyzes editing of adenine to inosine across the transcriptome as part of the immune response. Here the authors establish how ADAR1 recognizes non-CpG RNA sequences to facilitate the formation of A-Z junctions.

Exome sequence analysis of more than 5,000 schizophrenia cases and controls identifies a polygenic burden primarily arising from rare, disruptive mutations distributed across many genes, among which are those encoding voltage-gated calcium ion channels and the signalling complex formed by the ARC protein of the postsynaptic density; as in autism, mutations were also found in homologues of known targets of the fragile X mental retardation protein.

A genome-wide association meta-analysis of individuals with clinically assessed or self-reported depression identifies 44 independent risk loci. Comparisons with other psychiatric disorders and candidate gene analyses provide new insights into major depressive disorder.

Ruth Loos and colleagues report results of a large genome-wide association study for body mass index. They identify 18 new loci associated with this trait, some of which map near key hypothalamic regulators of energy balance.

Stratified medicine promises to tailor treatment for individual patients, however it remains a major challenge to leverage genetic risk data to aid patient stratification. Here the authors introduce an approach to stratify individuals based on the aggregated impact of their genetic risk factor profiles on tissue-specific gene expression levels, and highlight its ability to identify biologically meaningful and clinically actionable patient subgroups, supporting the notion of different patient ‘biotypes’ characterized by partially distinct disease mechanisms.

Joint analysis of multiple traits can increase power and provide insights into shared genetic architecture. Here, Nguyen et al. develop multi-trait TADA (mTADA), an extension of TADA (transmission and de novo association test) that jointly analyses de novo mutations of traits for improved risk-gene identification power.

David Altshuler and colleagues describe analysis for integrating genotype calling of SNPs, common copy number polymorphisms and rare CNVs, implemented in a suite of software programs collectively named Birdsuite.

Leonard van den Berg, Roel Ophoff and colleagues present a genome-wide association study of sporadic amyotrophic lateral sclerosis. The work uncovers associated SNPs at 9p21.2 and an associated locus at 19p13.3 mapping to the UNC13A gene.

The authors report the largest family-trio exome sequencing study of schizophrenia to date; mutations are overrepresented in genes for glutamatergic synaptic proteins and also genes mutated in autism and intellectual disability, providing insights into aetiological mechanisms and pathopshyisology shared with other neurodevelopmental disorders.

Cecilia Lindgren and colleagues report results of a large-scale genome-wide association study for waist-to-hip ratio, a measure of body fat distribution. They identify 13 new loci associated with this trait, several of which show stronger effects in women than in men.

Whole-exome sequencing in a large autism study identifies over 100 autosomal genes that are likely to affect risk for the disorder; these genes, which show unusual evolutionary constraint against mutations, carry de novo loss-of-function mutations in over 5% of autistic subjects and many function in synaptic, transcriptional and chromatin-remodelling pathways.

This Review discusses the principles and applications of significance testing and power calculation, including recently proposed gene-based tests for rare variants.

Modern genomic studies are revealing widespread associations between single genetic variants and multiple distinct traits, including diseases. This Review discusses the biological underpinnings of such pleiotropy and the available bioinformatic tools for the detection and characterization of these effects, as well as the implications for understanding human disease.

In their analysis of two datasets, Djonlagic et al. identify 23 objective sleep metrics that predict cognitive performance and processing speed in older adults.

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.

A main symptom of chronic insufficient sleep is excessive daytime sleepiness. Here, Wang et al. report 42 genome-wide significant loci for self-reported daytime sleepiness in 452,071 individuals from the UK Biobank that cluster into two biological subtypes of either sleep propensity or sleep fragmentation.

A genome-wide association study including over 76,000 individuals with schizophrenia and over 243,000 control individuals identifies common variant associations at 287 genomic loci, and further fine-mapping analyses highlight the importance of genes involved in synaptic processes.

Exome sequencing data from 60,706 people of diverse geographic ancestry is presented, providing insight into genetic variation across populations, and illuminating the relationship between DNA variants and human disease.

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.

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.

The Myocardial Infarction Genetics Consortium reports results of a genome-wide association study of early-onset myocardial infarction. The study analyzed common SNPs, common CNVs and rare CNVs and identified SNP alleles at three new loci associated with disease risk.

Sleep is essential for homeostasis and insufficient or excessive sleep are associated with adverse outcomes. Here, the authors perform GWAS for self-reported habitual sleep duration in adults, supported by accelerometer-derived measures, and identify genetic correlation with psychiatric and metabolic traits

Mark Daly and colleagues present a statistical framework to evaluate the role of de novo mutations in human disease by calibrating a model of de novo mutation rates at the individual gene level. The mutation probabilities defined by their model and list of constrained genes can be used to help identify genetic variants that have a significant role in disease.

The CommonMind Consortium sequenced RNA from dorsolateral prefrontal cortex of subjects with schizophrenia (N = 258) and control subjects (N = 279), creating a resource of gene expression and its genetic regulation. Using this resource, they found that ∼20% of schizophrenia loci have variants that may contribute to altered gene expression and liability.

Using whole-exome sequencing, the authors identified 244,246 coding-sequence and splice-site ultra-rare variants (URVs) and found that gene-disruptive and putatively protein-damaging URVs were significantly more abundant in schizophrenia cases than in controls. The excess of protein-compromising URVs was concentrated in brain-specific genes, particularly in neuronally expressed genes whose proteins are located at the synapse.

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.

This very large genome-wide association study identifies hundreds of new genetic variants influencing adult height in at least 180 loci enriched for genes involved in skeletal growth defects. The results show that the likely causal gene is often located near the most strongly associated variant, that many loci have multiple independently associated variants and that associated variants are enriched for likely functional effects on genes.

Shamil Sunyaev and colleagues present exome sequencing methods and their applications in studies to identify the genetic basis of human complex traits. They include analyses of the whole-exome sequences of 438 individuals from across several studies.

Data-driven composite sleep health scores, combining self-reported sleep duration, snoring, chronotype, insomnia, and sleepiness, provide heritable, interpretable phenotypes and novel GWAS discoveries elucidating regulatory pathways.

The Schizophrenia Psychiatric Genome-Wide Association Study Consortium reports five genetic loci newly associated with risk of schizophrenia, involving 17,836 cases of schizophrenia and 33,859 healthy controls. The new locus with the strongest support of association was located within an intron for microRNA 137, a known regulator of neuronal development. Four other genome-wide significant loci for schizophrenia contain predicted targets of MIR137, suggesting that disruption to pathways involving MIR137 may be an etiologic mechanism in 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.

The effect of sequence variants on phenotypes may depend on parental origin. Here, a method is developed that takes parental origin — the impact of which, to date, has largely been ignored — into account in genome-wide association studies. For 38,167 Icelanders genotyped, the parental origin of most alleles is determined; furthermore, a number of variants are found that show associations specific to parental origin, including three with type 2 diabetes.