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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).

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.

Khawaja et al. show sex-specific differences in neuronal-activity regulation by chaperone-mediated autophagy and that loss of chaperone-mediated autophagy leads to defective neuronal physiology and increased seizure susceptibility, linking chaperone-mediated autophagy to neuronal excitability.

Infant KMT2A-rearranged acute lymphoblastic leukemia is associated with poor overall survival rates. Here, the authors use WGS and WES of 36 relapsed KMT2A-rearranged ALL and AML patients and find alterations in drug response genes in ALL, which may correspond with relapse time. Longitudinal analyses of >250 samples could track residual leukemia cells, clonal drug responses, and the upcoming relapse.

Here, the authors find that BMAL1, best known for controlling the body clock, partners with TRIM28 in naïve pluripotent stem cells to repress retrotransposons.

Heo, Xu et al. used comprehensive plasma proteomics to identify 416 plasma proteins (294 new) associated with Alzheimer’s disease and applied machine learning to select 7 proteins that were highly predictive of Alzheimer’s disease across multiple cohorts.

Olfactomedin-2 is a pleiotropic glycoprotein emerging as a regulator of energy homeostasis via the hypothalamus. The present findings functionally connect adipose-specific OLFM2 to obesity, and highlight its significance in maintaining adipocyte commitment to avoid metabolic disease.

The genetic architecture underlying rapid adaptive responses to novel environments are poorly understood. A study of great tits from nine European cities finds that urban adaptation in a widespread songbird occurred through unique and shared selective sweeps in a core-set of behaviour-linked genes.

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.

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.

Altered pre-mRNA splicing frequently causes disease, yet how sequence variants alter splicing remains enigmatic. Here the authors use deep indel mutagenesis and deep learning tools to reveal the regulatory architecture of human exons and identify splicing-modulating antisense oligonucleotides.

Polygenic risk scores for Alzheimer’s disease derived from individuals of European ancestry can show improved performance in multiancestry settings after incorporating genome-wide association summary statistics from diverse populations.

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.

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.

Known genetic loci account for only a fraction of the genetic contribution to Alzheimer’s disease. Here, the authors have performed a large genome-wide meta-analysis comprising 409,435 individuals to discover 6 new loci and demonstrate the efficacy of an Alzheimer’s disease polygenic risk score.

A comparison of alpha diversity (number of plant species) and dark diversity (species that are currently absent from a site despite being ecologically suitable) demonstrates the negative effects of regional-scale anthropogenic activity on plant diversity.

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.

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

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.

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.

The authors present Modeling immuno-OligoSTORM (MiOS), a super-resolution imaging and computational strategy to model 3D gene folding at multiple genomic scales, reaching nucleosome resolution at the single-gene level.

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.

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 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.

Horses have lived in Iberia since the Ice Age. Using ancient genomes to study their history, Lira Garrido et al. reveal a local wild lineage lasting until Late Iron Age, and highlight the far-reaching influence of Iberian bloodlines across Europe and north Africa during the Iron Age and beyond.

Patritumab deruxtecan (HER3-DXd) is a promising therapy for breast cancer, targeting HER3. Here, the authors analyse the genomic factors that affect the response to HER3-DXd in patients with early-stage HER2-negative breast cancer as part of the SOLTI-1805 TOT-HER3 clinical trial and report outcomes for Part B of the trial using lower HER3-DXd dose in patients with HER2-negative breast 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.

Accumulation of lipid-laden macrophages in the arterial wall is a critical step in atherosclerosis. Here, the authors show that downregulation of Zeb1 in macrophages promotes lipid accumulation and atherosclerotic plaque formation while its restoration with macrophage-targeted nanoparticles reverses these effects.

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.

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.

Senolytic compounds have the ability to eliminate senescent cells from tissues and have been shown to be beneficial in various animal models of age-related diseases. Here the authors show that cardiac glycosides commonly used for heart diseases have senolytic properties in humanized mouse models of tumorigenesis and lung fibrosis.

Long-term characterisation of SARS-CoV-2 antibody kinetics is needed to understand the protective role of the immune response. Here the authors describe antibody levels and neutralisation activity in healthcare workers over seven months and investigate the role of immunity to endemic human coronaviruses.

In Myeloiddysplastic syndromes, CEBPA mutations are linked to disease progression and AML. Here, the authors use somatic reprogramming and genome editing to generate isogenic cell lines from an MDS patient, identifying CEBPA bZIP domain disruption as causative for disease progression.

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.

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.

Meta-analysis of genome-wide association studies on Alzheimer’s disease and related dementias identifies new loci and enables generation of a new genetic risk score associated with the risk of future Alzheimer’s disease and dementia.

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.

Brain age gaps (BAGs) highlight deviations from healthy brain aging, yet their biophysical underpinnings in aging and dementia are not well understood. Here, the authors use EEG connectivity and generative modeling across diverse populations to reveal that BAGs are influenced by geography, income, sex and education, with implications for understanding accelerated aging and dementia.

Proteogenomic analysis of human cerebrospinal fluid by measuring 6,361 proteins in 3,506 individuals identifies new protein QTLs and highlights genetic regulation involved in neurological processes.

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

Genetic and Structural analysis of COVID patients cohort reveals a correlation between mitochondrial haplogroup and SARS-CoV-2 severity.

Genome-wide association study of cerebrospinal fluid and brain metabolites highlights the unique genetic architecture of metabolite levels and metabolite–trait associations with brain-related phenotypes.

Dendritic cells (DCs) induce infection-protective immune memory, which has yet to be exploited for cancer therapy. Here we show that type 1 DC vaccines quantitatively and qualitatively favors anti-tumor T cell memory that prevents cancer relapse.