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Here the authors compare genetic testing strategies in rare movement disorders, improve diagnostic yield with genome analysis, and establish CD99L2 as an X-linked spastic ataxia gene, showing that CD99L2–CAPN1 signaling disruption likely drives neurodegeneration.

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.

Identifying jets originating from heavy quarks plays a fundamental role in hadronic collider experiments. In this work, the ATLAS Collaboration describes and tests a transformer-based neural network architecture for jet flavour tagging based on low-level input and physics-inspired constraints.

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.

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.

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.

From 1980 to 2018, the levels of total and non-high-density lipoprotein cholesterol increased in low- and middle-income countries, especially in east and southeast Asia, and decreased in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe.

Analysis of HbA1c and FPG levels across 117 population-based studies demonstrates regional variation in prevalence of previously undiagnosed screen-detected diabetes using one or both measures and suggests that use of elevated FPG alone could underestimate diabetes prevalence in low- and middle-income countries.

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

Contrary to the view that urbanization is a major driver of the global rise in obesity, the global increase in body-mass index is shown to be mostly due to increases in the body-mass indexes of rural populations.

Geospatial estimates of the prevalence of anemia in women of reproductive age across 82 low-income and middle-income countries reveals considerable heterogeneity and inequality at national and subnational levels, with few countries on track to meet the WHO Global Nutrition Targets by 2030.

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.

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.

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.

An analysis of viral genomes and epidemiological data from the 2022 mpox outbreak in Portugal sheds light on the heterogeneity of early transmission events, with national and international linkages.

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.

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.

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 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.

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.

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.

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.

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.

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.

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.

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.

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.

Coccidioidomycosis, a WHO-listed mycosis, is neglected in South America. Analysis of 292 cases in Brazil, often tied to armadillo hunting, unveils unique disease patterns, environmental factors and pathogen genetics causing the disease.

Chronic lymphocytic leukemia is a highly inheritable cancer. Here the authors conduct a metaanalysis of four genome-wide association studies and identify three novel loci located near EOMES, SERPINB6 and LPPassociated with risk of this disease.

Deubiquitylases (DUBs) remove ubiquitin chains from proteins. Here the authors develop a mass spectrometry-based DUB activity screen using unmodified diubiquitin isomers to characterize substrate specificity for 42 human DUBs, and assess the potency and selectivity of 11 DUB inhibitors.

Here, the authors present results of the ZiBRA-2 project (https://www.zibra2project.org) which is an arbovirus surveillance project, across the Midwest of Brazil using a mobile genomics laboratory, combined with a genomic surveillance training program that targeted post-graduate students, laboratory technicians, and health practitioners in universities and laboratories.

The bacterium Helicobacter pylori, often found in the human stomach, can be classified into distinct subpopulations associated with the geographic origin of the host. Here, the authors provide insights into H. pylori population structure by collecting over 1,000 clinical strains from 50 countries and generating and analyzing high-quality bacterial genome sequences.

The COVID-19 pandemic in Brazil is assessed using phylogenetic and phylogeographic analysis.

Efficient, large-scale genomic analysis is facilitated on the cloud by a computational tool with error-diagnosing and self-healing capabilities.