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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 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 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.

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.

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.

Lipid particles loaded with RNA coding for tumour-unspecific antigens can enhance early responses of type-I interferons, mediating the success of immune checkpoint inhibitors as well as epitope spreading.

Analysis of whole-genome sequencing data from hematopoietic stem and progenitor cells taken from patients with myeloma shows how treatment shapes clonal architecture and sheds light on the evolution of treatment-related myeloid neoplasms.

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.

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.

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.

Systematic analysis from the Global Burden of Disease study reported that, despite global improvements from 1990 to 2021, dietary iron deficiency-associated disease burden remains high in women, children and residents in low socio-demographic index countries.

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.

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.

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

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.

Multiancestry genome-wide association analyses identify new risk loci for stroke and stroke subtypes. Fine mapping and bioinformatics analyses of these risk loci point to mechanisms not previously implicated in stroke pathophysiology.

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.

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.

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.

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.

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.

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.

A genome-wide association study including over 76,000 individuals with schizophrenia and over 243,000 control individuals identifies common variant associations at 287 genomic loci, and further fine-mapping analyses highlight the importance of genes involved in synaptic processes.

A cross-ancestry meta-analysis of genome-wide association studies identifies association signals for stroke and its subtypes at 89 (61 new) independent loci, reveals putative causal genes, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as potential drug targets, and provides cross-ancestry integrative risk prediction.

Whole-genome sequencing analysis of individuals with primary immunodeficiency identifies new candidate disease-associated genes and shows how the interplay between genetic variants can explain the variable penetrance and complexity of the disease.

Genome-wide association studies (GWAS) have improved our understanding of the genetic basis of lung adenocarcinoma but known susceptibility variants explain only a small fraction of the familial risk. Here, the authors perform a two-stage GWAS and report 12 novel genetic loci associated with lung adenocarcinoma in East Asians.

Stratified medicine promises to tailor treatment for individual patients, however it remains a major challenge to leverage genetic risk data to aid patient stratification. Here the authors introduce an approach to stratify individuals based on the aggregated impact of their genetic risk factor profiles on tissue-specific gene expression levels, and highlight its ability to identify biologically meaningful and clinically actionable patient subgroups, supporting the notion of different patient ‘biotypes’ characterized by partially distinct disease mechanisms.

Nationwide genomic biobank in Mexico unravels demographic history and complex trait architecture from 6,057 individuals.

Openshaw and colleagues find myeloid inflammation and complement activation signatures in patients with long COVID who were previously hospitalized.

Analysis of mitochondrial genomes (mtDNA) by using whole-genome sequencing data from 2,658 cancer samples across 38 cancer types identifies hypermutated mtDNA cases, frequent somatic nuclear transfer of mtDNA and high variability of mtDNA copy number in many cancers.

Variation in antibody levels elicited by the COVID-19 vaccine ChAdOx1 nCov-19 is linked to specific major histocompatibility complex class II alleles, providing insight into the breadth of immune response among vaccinated individuals.

Studies with patient derived xenografts are hampered by factors such as genetic variability and sample availability. Here, the authors generate a leukemia mouse model by lentiviral transduction of normal human cord blood and show an oncogenic role of HOXB genes.

Analysis of whole-genome sequencing data across 2,658 tumors spanning 38 cancer types shows that chromothripsis is pervasive, with a frequency of more than 50% in several cancer types, contributing to oncogene amplification, gene inactivation and cancer genome evolution.

CellAssign uses a probabilistic model to assign single cells to a given cell type defined by known marker genes, enabling automated annotation of cell types present in a tumor microenvironment.

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

Eye contact is a key social behavior and its measurement could facilitate the diagnosis and treatment of autism. Here the authors show that a deep neural network model can detect eye contact as accurately has human experts.

Higher milk intake is associated with lower type 2 diabetes risk in lactase non-persistent individuals, partly through gut microbiome and blood metabolites.

A multi-omic analysis of pancreatic cancer identifies spatially resolved, heterogeneous cell populations including transitional cell types. Analysis of primary samples identifies treatment-related changes in cross-talk between tumor and stromal cells.

Relatives of patients with amyotrophic lateral sclerosis have an unexpectedly high incidence of schizophrenia. Here, the authors show a genetic link between the two conditions, suggesting shared neurobiological mechanisms.

Sexual dimorphism in genetic vulnerability to schizophrenia, systemic lupus erythematosus and Sjögren’s syndrome is linked to differential protein abundance from alleles of complement component 4.

The Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA) aims to better understand population genetics of the African diaspora. Here, it uses deeply sequenced whole-genomes to describe the impact of admixture and potential disease burden of deleterious variants.

Personalized medicine requires accurate and ethnicity-optimized reference genome panels. Here, the Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA) evaluates typical variant filters and existing genome databases against newly sequenced African-ancestry populations.