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In this study, authors explore cortical morphology using Mendelian randomization to identify positive causal effects of total brain cortical surface on neuropsychiatric phenotypes.

Circulating metabolites reflect complex disease risk and are shaped by diverse genetic factors. Here, the authors show widespread pleiotropy across 249 metabolic traits, identify rare variant and sex-specific effects, and implicate lipid-related pathways in metabolism.

Genome-wide association analyses of intracranial and nine subcortical brain volumes in 74,898 participants of European ancestry identify 254 independent loci and yield polygenic scores accounting for brain variation across ancestries.

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.

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.

Using a multivariate approach in a sample from the UK Biobank, the authors examine the genetic relationships between measures of functional connectivity and psychiatric disorders.

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.

Human brain structure changes throughout the lifespan. Brouwer et al. identified genetic variants that affect rates of brain growth and atrophy. The genes are linked to early brain development and neurodegeneration and suggest involvement of metabolic processes.

The hippocampus has been associated with memory traits and a variety of neurodegenerative and psychiatric disorders. Here, the authors have done a multivariate GWAS revealing 177 genetic loci, and overlap with various brain disorders may suggest partly age- and disorder-independent mechanisms underlying hippocampal pathology.

Meta-analyses in up to 1.3 million individuals identify 87 rare-variant associations with blood pressure traits. On average, rare variants exhibit effects ~8 times larger than the mean effects of common variants and implicate candidate causal genes at associated regions.

Regional brain morphology has a complex genetic architecture. Here the authors present MOSTest, a multivariate statistical framework, apply it to UK Biobank data, and discover hundreds of loci associated with regional brain morphology.

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.

In a prespecified secondary analysis of the STEP-HFpEF trial, semagludtide treatment was associated with improvements in KCCQ-CSS and body weight, as well as trial secondary endpoints, across the spectrum of obesity classes, with the magnitude of beneficial effects being proportional to the extent of weight loss.

This Perspective discusses the need for standards that allow for comparisons of quantitative physiological features in microphysiological systems and humans.

How the tissue composition of the human brain is determined remains unclear. Here, the authors apply advanced analyses to two large imaging genetic datasets to identify and validate genetic loci that simultaneously influence multiple brain regions.

The genetic architecture underlying brainstem regions and how this links to common brain disorders is not well understood. Here, the authors use MRI and GWAS data from 27,034 individuals to identify genetic and morphological brainstem features that influence common brain disorders.

Hindley et al. used multivariate statistical genetics tools to examine the genetic underpinnings of cognitive and personality traits and find they are shared across higher order domains of mental functioning.

Differences in thalamic structure have been observed in several psychiatric disorders, but the genetic overlap has not been explored. Here, the authors perform a genome-wide association study on thalamic nuclei volume and find genetic loci in common between thalamic volumes and brain disorders.

The human brain is highly asymmetrical and increasingly so with age. Here the authors examine hemispheric brain age estimates, which provide additional insights into brain asymmetries.

Oxytocin is a hormone and neurotransmitter involved in reproductive and social behavior, but the role of oxytocin-related genes in the human brain remains unclear. Here, the authors map oxytocin pathway gene expression and show that it overlaps with brain regions involved in reward and emotional states.

GSA-MiXeR models gene heritability and variant linkage disequilibrium for improved gene set enrichment testing. GSA-MiXeR implicates relevant sets of fewer than ten genes in schizophrenia, providing more nuanced insights into trait biology.

Analyses of data from the UK Biobank reveal different urban living environments that are associated with affective, anxiety and emotional instability symptom groups and mediated by distinct neurological and genetic pathways in adults.

Using structural MRI data from 45,615 individuals aged 3–96 years, Kaufmann and colleagues reveal that common brain disorders are associated with heritable patterns of apparent aging of the brain.

A GWAS study of European individuals uncovers genetic associations between whole-body MRI derived measures and cardiometabolic diseases and highlights the key role of liver fat in cardiometabolic health.

In this Perspective, the authors present a model of assessing urban environmental factors’ impact on mental health by using UrbanSat measures and data from adolescents in the ABCD Study.

This Comment explores new approaches to enrich large-scale population data, including incorporating macro-environmental and digital health measures.

A study on the evolution of the oxytocin system illustrates the varied role of this neuropeptide in physiology and behavior

Integrative analyses that incorporate different levels of ‘-omics’ data represent a powerful tool for deciphering the biological mechanisms that underlie environmental influences on mental health and disease. This Comment highlights various aspects of such multi-omics approaches, using the example of the EU-funded environMENTAL project.

This Comment presents a high-level protocol for data harmonization within large cohorts, in which it postulates four main steps including (1) expert review, (2) pre-statistical harmonization, (3) statistical harmonization, and (4) validation.

The focus of much of contemporary research ethics is on compliance with established protocols. However, large data-driven neuroscience research raises new ethical concerns that have no agreed-upon solution. Here we reflect on these challenges and propose better integration of public and patient involvement in this evolving landscape.