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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.

Systematic comparison of genome-wide association results for disease risk and disease-specific mortality for nine common diseases across seven biobanks finds limited overlap between genetic effects on disease susceptibility and survival.

Mutational signature analysis of blood cells isolated from 23 chemotherapy-exposed samples and 9 nonexposed controls characterizes the effects of various drugs on mutational burden, signature exposure and cell types.

This study explores the relationship between telomere length and clonal hematopoiesis. Splicing factor and PPM1D gene mutations are more frequent in people with genetically predicted shorter telomere lengths, suggesting that these mutations protect against the consequences of telomere attrition.

A study reports whole-genome sequences for 490,640 participants from the UK Biobank and combines these data with phenotypic data to provide new insights into the relationship between human variation and sequence variation.

This study maps the connections of layer 5 pyramidal neurons in the mouse cortex, revealing distinct local and intercortical wiring patterns, and provides an open framework for exploring the connectivity of cell types.

Using well-calibrated statistical methods the authors jointly analyze Undiagnosed Diseases Network genomes, identifying known and novel disease genes. Software is publicly available to support future cross-cohort rare disease discovery efforts.

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.

MultiSTAAR provides a general and flexible statistical framework for functionally informed multi-trait rare variant analysis of biobank-scale sequencing studies by jointly analyzing multiple traits and incorporating annotation information.

Reduced glomerular filtration rate (eGFR) is a hallmark of chronic kidney disease. Here, Pattaro et al. conduct a meta-analysis to discover several new loci associated with variation in eGFR and find that genes associated with eGFR loci often encode proteins potentially related to kidney development.

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.

Analyses of genome and exome sequencing data identify rare coding and structural variants associated with atrial fibrillation and highlight genetic links between atrial fibrillation and cardiomyopathies.

Here, using neural activity patterns in the inferior frontal gyrus and large language modeling embeddings, the authors provide evidence for a common neural code for language processing.

Thompson et al. report clinical outcomes and immunological correlates of a phase 1 trial of a peptide vaccine targeting the CMV antigen pp65 in children and young adults with recurrent high-grade glioma and medulloblastoma.

Two complementary studies used whole-genome sequencing of single cell-derived hematopoietic colonies to show that chemotherapy results in a marked decrease in hematopoietic stem and progenitor cell (HSPC) diversity, with the parallel evolution of multiple independent HSPCs harboring mutations in DNA damage response genes.

A genome-wide study by the Long COVID Host Genetics Initiative identifies an association between the FOXP4 locus and long COVID, implicating altered lung function in its pathophysiology.

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.

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

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 genome-wide association meta-analysis study of blood lipid levels in roughly 1.6 million individuals demonstrates the gain of power attained when diverse ancestries are included to improve fine-mapping and polygenic score generation, with gains in locus discovery related to sample size.

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.

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.

Metabolic and alcohol-related liver disease presents challenges in clinical trials due to complex pathophysiology. This Review discusses noninvasive imaging, serum biomarkers and adaptive designs as modalities to enhance patient-centric end points, aiming to refine diagnostics and improve drug development.

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.

Using multi-ancestry genome-wide association study and fine-mapping, 298 loci and 36 credible genes are identified in the aetiology of bipolar disorder.

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.

A study reports the development of a method to trace intercellular transfer of mitochondria, and demonstrates that cancer cells that receive mitochondria from neurons have enhanced metastatic capabilities.

In the Tumor Profiler proof-of-concept observational study, a multiomics approach for profiling tumors from patients with melanoma was feasible, returning data within 4 weeks and informing treatment recommendations in 75% of cases.

Dense calcium imaging combined with co-registered high-resolution electron microscopy reconstruction of the brain of the same mouse provide a functional connectomics map of tens of thousands of neurons of a region of the primary cortex and higher visual areas.

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.

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 Connectome Annotation Versioning Engine (CAVE) is a platform for proofreading, annotating and analyzing datasets reaching the petascale. Currently, CAVE is used for electron microscopy datasets, but it can potentially be used for other large-scale datasets.

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.

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).

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.

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.

Anti-NMDA receptor encephalitis is a severe brain disorder caused by autoantibodies that trigger NMDA receptor loss. Here, the authors show that ART5803, a monovalent antibody, blocks this process and restores function in cell and primate models.

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.

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.

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.