Search

Understanding collective behaviour is an important aspect of managing the pandemic response. Here the authors show in a large global study that participants that reported identifying more strongly with their nation reported greater engagement in public health behaviours and support for public health policies in the context of the pandemic.

In the CheckMate 142 study, nivolumab (anti-PD-1) alone and in combination with ipilimumab (anti-CTLA-4) was shown to induce durable clinical benefit in patients with previously treated microsatellite instability-high/mismatch repair-deficient metastatic colorectal cancer. Here, the authors perform exploratory biomarker analysis of the CheckMate 142 study.

Analysis combining multiple global tree databases reveals that whether a location is invaded by non-native tree species depends on anthropogenic factors, but the severity of the invasion depends on the native species diversity.

The Zika viral protease NS2B-NS3 is a crucial target for antiviral drug development due to its role in processing viral polyproteins. Here, the authors utilize crystallographic fragment screening and deep mutational scanning to identify binding sites for resistance-resilient inhibitors.

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.

Head and neck squamous cell carcinoma (HNSCC) frequency and risk factors vary considerably across regions and ancestries. Here, the authors conduct a multi-ancestry genome-wide association study and fine mapping study of HNSCC subsites in cohorts from multiple continents, finding susceptibility and protective loci, gene-environment interactions, and gene variants related to immune response.

Nature Biotechnology’s annual survey highlights academic startups that are, among other things, designing circular RNA therapeutics, tackling cancer with arenaviruses, creating psychedelics without the trip, editing genes and cells in vivo, harnessing the power of autoantibodies and editing the epigenome.

Genome-wide association meta-analyses of attention-deficit/hyperactivity disorder symptom measures and clinical diagnoses identify new risk loci, highlight putative effector genes and yield improved polygenic risk scores.

Analysis of human Robertsonian chromosomes originating from 13, 14 and 21 reveal that they result from breaks at the SST1 macrosatellite DNA array and recombination between homologous sequences surrounding SST1.

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.

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.

Species’ traits and environmental conditions determine the abundance of tree species across the globe. Here, the authors find that dominant tree species are taller and have softer wood compared to rare species and that these trait differences are more strongly associated with temperature than water availability.

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.

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.

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).

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.

A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants.

Psoriasis is a partially heritable skin disorder, the genetic basis of which is not fully understood. Here, the authors use genome-wide association meta-analysis to discover psoriasis susceptibility loci and genes, which encode existing and potential new drug targets.

HistoPlexer, a deep learning model, generates multiplexed protein expression maps from H&E images, capturing tumour–immune cell interactions. It outperforms baselines, enhances immune subtyping and survival prediction and offers a cost-effective tool for precision oncology.

An expert recommendation is presented for the design and evaluation of research studies using transcranial electrical stimulation, resulting in the selection of a 66-point checklist aimed at improving the quality of transcranial electrical stimulation studies.

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.

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.

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.

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.

The advantage of living in cities compared with rural areas with respect to height and BMI in children and adolescents has generally become smaller globally from 1990 to 2020, except in sub-Saharan Africa.

In atrial fibrillation patients, circulating biomarkers reflecting inflammation, myocardial injury, and coagulation improve prediction of stroke, heart failure, and bleeding, outperforming clinical scores and enhance risk stratification.”.

Small CRISPR Cas9 proteins have potential in gene therapies but generally have poor editing efficiency or specificity and often recognize sub-optimal PAM sequences. Here the authors characterise four small nucleases and use protein engineering to create effective in vivo editors.

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.

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.

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.

Certain antimetabolites used to treat cancer are more neurotoxic than others, and it is now shown that this is due to their greater tendency to generate DNA double-stranded breaks, whereas less neurotoxic agents induce single-stranded breaks.

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.

Timothy Frayling, Joel Hirschhorn, Peter Visscher and colleagues report a meta-analysis of genome-wide association studies for adult height in 253,288 individuals. They identify 697 variants in 423 loci significantly associated with adult height and find that these variants cluster in pathways involved in growth and together explain one-fifth of the heritability for this trait.

A high-resolution, global atlas of mortality of children under five years of age between 2000 and 2017 highlights subnational geographical inequalities in the distribution, rates and absolute counts of child deaths by age.

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.

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.

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.

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.

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.

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.

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.

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

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.

Here the authors apply machine learning approaches to Alzheimer’s genetics, confirm known associations and suggest novel risk loci. These methods demonstrate predictive power comparable to traditional approaches, while also offering potential new insights beyond standard genetic analyses.