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Creative experiences such as dance, music, drawing, and strategy video games might preserve brain health. The authors show that regular practice or short training in these activities is linked to brains that look younger and work more efficiently.

Polygenic risk scores can help identify individuals at higher risk of type 2 diabetes. Here, the authors characterise a multi-ancestry score across nearly 900,000 people, showing that its predictive value depends on demographic and clinical context and extends to related traits and complications.

A study of several longitudinal birth cohorts and cross-sectional cohorts finds only moderate overlap in genetic variants between autism that is diagnosed earlier and that diagnosed later, so they may represent aetiologically different conditions.

People living in rural areas of the United States have poorer outcomes from acute COVID-19. Here, the authors show that higher mortality rates among rural dwellers persist for up to two years after the initial infection, even after accounting for baseline risk factors.

In this Stage 2 Registered Report, Buchanan et al. show evidence confirming the phenomenon of semantic priming across speakers of 19 diverse languages.

BioID detection of Ebola virus–host interactions when computationally integrated with existing host protein-protein networks, revealed functional cell protein complexes supporting infection, including the RNA decapping complex.

A global network of researchers was formed to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity; this paper reports 13 genome-wide significant loci and potentially actionable mechanisms in response to infection.

Polygenic scores for body mass index and obesity constructed using data from 5 million people with different ancestries were associated with distinct weight gain trajectories from early childhood to adulthood.

An analysis of 24,202 critical cases of COVID-19 identifies potentially druggable targets in inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).

Rising seafood demand strains fish stocks, risking ecosystem collapse. Using a dynamic food-web model, we compare fishing strategies. Targeting mid-trophic species yields sustainable returns with minimal biodiversity loss, guiding ecosystem-based management.

ParABS systems partition chromosomal DNA and low-copy plasmids in bacteria. Here, the authors elucidate the mode of interaction between ParA and ParB and clarify how ParB stimulates the ATPase activity of ParA to drive the segregation process.

Chronic care manages long-term, progressive conditions, while acute care handles short-term ones. Here, authors show chronic conditions account for most of the global health burden, with 68% of DALYs and 93% of YLDs attributed to chronic care needs.

The authors highlight inconsistencies and divergencies in the literature reporting data on indirect calorimetry for studies on whole-body energy homeostasis, and propose harmonization of standards to facilitate data comparison and interpretation across different datasets.

Federated learning (FL) algorithms have emerged as a promising solution to train models for healthcare imaging across institutions while preserving privacy. Here, the authors describe the Federated Tumor Segmentation (FeTS) challenge for the decentralised benchmarking of FL algorithms and evaluation of Healthcare AI algorithm generalizability in real-world cancer imaging datasets.

The flagship paper of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium describes the generation of the integrative analyses of 2,658 cancer whole genomes and their matching normal tissues across 38 tumour types, the structures for international data sharing and standardized analyses, and the main scientific findings from across the consortium studies.

A Telluride Science Workshop on electrochemical separations was convened in early 2025. In this Feature, 17 of the workshop participants share their perspectives and future outlooks on this rapidly growing research area.

CLEM-Reg automates the three-dimensional alignment of volume correlative light and electron microscopy datasets by leveraging probabilistic point cloud registration techniques for fast and accurate results across diverse datasets.

An analysis of 2,954 genomes from 38 cancer subtypes identified 19,166 retrotransposition events in 35% of samples. Aberrant LINE-1 retrotranspositions can lead to the deletion of tumor-suppressor genes as well as the amplification of oncogenes.

With the generation of large pan-cancer whole-exome and whole-genome sequencing projects, a question remains about how comparable these datasets are. Here, using The Cancer Genome Atlas samples analysed as part of the Pan-Cancer Analysis of Whole Genomes project, the authors explore the concordance of mutations called by whole exome sequencing and whole genome sequencing techniques.

Body size and composition are complex traits that are challenging to characterize due to environmental and genetic influences. Here, Arehart et al. disentangle shared and distinct genetic signals underlying body size and composition.

A combination of mouse model data and data from a randomized phase 2 trial in patients with breast cancer in remission demonstrates feasibility, safety and a reduction in residual tumor cells following treatment with hydroxychloroquine and/or everolimus.

EchoNext, a deep learning model for electrocardiograms trained and validated in diverse health systems, successfully detects many forms of structural heart disease, supporting the potential of artificial intelligence to expand access to heart disease screening at scale.

The authors present SVclone, a computational method for inferring the cancer cell fraction of structural variants from whole-genome sequencing data.

This study used multiplex serology to monitor multiple diseases simultaneously from a single serosurvey. Seroprevalence estimates were performed for five disease categories in Zambezia Province, Mozambique.

Whole-genome sequencing data for 2,778 cancer samples from 2,658 unique donors across 38 cancer types is used to reconstruct the evolutionary history of cancer, revealing that driver mutations can precede diagnosis by several years to decades.

Whole-genome sequencing, transcriptome-wide association and fine-mapping analyses in over 7,000 individuals with critical COVID-19 are used to identify 16 independent variants that are associated with severe illness in COVID-19.

There’s an emerging body of evidence to show how biological sex impacts cancer incidence, treatment and underlying biology. Here, using a large pan-cancer dataset, the authors further highlight how sex differences shape the cancer genome.

An expert-elicitation process identifies current methodological barriers for monitoring terrestrial biodiversity, and how technological and procedural development of robotic and autonomous systems may contribute to overcoming these challenges.

Analysing camera-trap data of 163 mammal species before and after the onset of COVID-19 lockdowns, the authors show that responses to human activity are dependent on the degree to which the landscape is modified by humans, with carnivores being especially sensitive.

Understanding deregulation of biological pathways in cancer can provide insight into disease etiology and potential therapies. Here, as part of the PanCancer Analysis of Whole Genomes (PCAWG) consortium, the authors present pathway and network analysis of 2583 whole cancer genomes from 27 tumour types.

Analyses of 2,658 whole genomes across 38 types of cancer identify the contribution of non-coding point mutations and structural variants to driving cancer.

In somatic cells the mechanisms maintaining the chromosome ends are normally inactivated; however, cancer cells can re-activate these pathways to support continuous growth. Here, the authors characterize the telomeric landscapes across tumour types and identify genomic alterations associated with different telomere maintenance mechanisms.

Integrative analyses of transcriptome and whole-genome sequencing data for 1,188 tumours across 27 types of cancer are used to provide a comprehensive catalogue of RNA-level alterations in cancer.

Whole-genome sequencing data from more than 2,500 cancers of 38 tumour types reveal 16 signatures that can be used to classify somatic structural variants, highlighting the diversity of genomic rearrangements in cancer.

Viral pathogen load in cancer genomes is estimated through analysis of sequencing data from 2,656 tumors across 35 cancer types using multiple pathogen-detection pipelines, identifying viruses in 382 genomic and 68 transcriptome datasets.

Analysis of cancer genome sequencing data has enabled the discovery of driver mutations. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium the authors present DriverPower, a software package that identifies coding and non-coding driver mutations within cancer whole genomes via consideration of mutational burden and functional impact evidence.

A pan-cancer genomic analysis reports the effects of structural variations on chromatin domains (TADs). Most TAD disruptions do not result in appreciable changes in expression of nearby genes.

Some cancer patients first present with metastases where the location of the primary is unidentified; these are difficult to treat. In this study, using machine learning, the authors develop a method to determine the tissue of origin of a cancer based on whole sequencing data.

Many tumours exhibit hypoxia (low oxygen) and hypoxic tumours often respond poorly to therapy. Here, the authors quantify hypoxia in 1188 tumours from 27 cancer types, showing elevated hypoxia links to increased mutational load, directing evolutionary trajectories.

Multi-omics datasets pose major challenges to data interpretation and hypothesis generation owing to their high-dimensional molecular profiles. Here, the authors develop ActivePathways method, which uses data fusion techniques for integrative pathway analysis of multi-omics data and candidate gene discovery.

The characterization of 4,645 whole-genome and 19,184 exome sequences, covering most types of cancer, identifies 81 single-base substitution, doublet-base substitution and small-insertion-and-deletion mutational signatures, providing a systematic overview of the mutational processes that contribute to cancer development.

In this study the authors consider the structural variants (SVs) present within cancer cases of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. They report hundreds of genes, including known cancer-associated genes for which the nearby presence of a SV breakpoint is associated with altered expression.

Cancers evolve as they progress under differing selective pressures. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, the authors present the method TrackSig the estimates evolutionary trajectories of somatic mutational processes from single bulk tumour data.

Genome-wide analyses identify 30 independent loci associated with obsessive–compulsive disorder, highlighting genetic overlap with other psychiatric disorders and implicating putative effector genes and cell types contributing to its etiology.