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A multi-ancestry transcriptome-wide association study using an optimal linear combination of association statistics provides insights into tobacco use biology and suggests opportunities for drug repurposing.

Single-nucleus RNA-sequencing analysis supports the presence of immature dentate granule cells throughout the human lifespan and shows that these cells are reduced in number and dysregulated in Alzheimer's disease.

Cell-type-specific chromatin accessibility QTL during neurogenesis allow fine mapping of causal variants and more complete underlying of regulatory mechanisms underlying noncoding loci associated with gene expression and neuropsychiatric disorders.

Human mobility plays a central role in the spread of infectious diseases and can help in forecasting incidence. Here the authors show a comparison of multiple mobility benchmarks in forecasting influenza, and demonstrate the value of a machine-learned mobility map with global coverage at multiple spatial scales.

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.

The growing availability of human mobility data can help assess the structure and dynamics of urban environments and their relation to the performance of cities. Here the authors introduce a metric of hierarchy in urban travel and find correlations between levels of hierarchy and other urban indicators.

Genome-wide analysis identifies variants associated with the volume of seven different subcortical brain regions defined by magnetic resonance imaging. Implicated genes are involved in neurodevelopmental and synaptic signaling 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.

The hippocampus in mammalian brain varies in size across individuals. Here, Hibar and colleagues perform a genome-wide association meta-analysis to find six genetic loci with significant association to hippocampus volume.

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.

In a GWAS study of 32,438 adults, the authors discovered five novel loci for intracranial volume and confirmed two known signals. Variants for intracranial volume were also related to childhood and adult cognitive function and to Parkinson's disease, and enriched near genes involved in growth pathways, including PI3K-AKT signaling.

The cellular heterogeneity in brain obscures the identification of robust cellular regulatory networks. Here the authors integrate genome-wide chromosome conformation data from sorted neurons and glia, with transcriptomic and enhancer profiles, to characterize cell-type-specific gene regulatory landscapes in the human brain, and provide insights into cell-type-specific gene regulatory networks in brain disorders.

Genome-wide association studies are used to identify common genetic variants that affect the structure of selected subcortical regions of the human brain; their identification provides insight into the causes of variability in brain development and may help to determine mechanisms of neuropsychiatric dysfunction.

Recent research on disparate psychiatric disorders has implicated rare variants in genes involved in global gene regulation and chromatin modification, as well as many common variants located primarily in regulatory regions of the genome. Understanding precisely how these variants contribute to disease will require a deeper appreciation for the mechanisms of gene regulation in the developing and adult human brain. The PsychENCODE project aims to produce a public resource of multidimensional genomic data using tissue- and cell type–specific samples from approximately 1,000 phenotypically well-characterized, high-quality healthy and disease-affected human post-mortem brains, as well as functionally characterize disease-associated regulatory elements and variants in model systems. We are beginning with a focus on autism spectrum disorder, bipolar disorder and schizophrenia, and expect that this knowledge will apply to a wide variety of psychiatric disorders. This paper outlines the motivation and design of PsychENCODE.