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The APOE-ε4 allele is the strongest genetic risk factor for late-onset Alzheimer’s disease, but it is not deterministic. Here, the authors show that common genetic variation changes how APOE-ε4 influences cognition.

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.

cellSTAAR advances noncoding rare variant association analysis by integrating single-cell genomics data.

Humanity’s Last Exam, a multi-modal benchmark at the frontier of human knowledge, is designed to be an expert-level closed-ended academic benchmark with broad subject coverage.

Genome-wide association analyses using data from 19 biobanks identify variants influencing risk of thyroid diseases and yield polygenic risk scores associated with features of aggressive thyroid cancer.

The authors show that plasma AT(N) biomarkers can distinguish Alzheimer’s disease and frontotemporal lobar degeneration in diverse Latin American populations. Using machine learning and integrating neuroimaging, significant diagnostic accuracy was achieved, enhancing clinical assessments of these conditions in Latin America.

Here, the authors examine the mechanisms behind cheatgrass’s successful invasion of North American ecosystems. Their genetic analyses and common garden experiments demonstrate that multiple introductions and migrations facilitated cheatgrass local adaptation.

This study finds that native tree extinctions and alien naturalizations are pushing forests towards fast-growing, resource-demanding species. This global shift could affect carbon storage and ecosystem stability, highlighting the need to protect slow-growing trees.

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.

Large-effect variants in autism remain elusive. Here, the authors use long-read sequencing to assemble phased genomes for 189 individuals, identifying pathogenic variants in TBL1XR1, MECP2, and SYNGAP1, plus nine candidate structural variants missed by short-read methods.

PhenoMol integrates graph theory and biological knowledge to reduce multi-omic dimensionality, predict phenotypes, and reveal causal patterns. It outperforms conventional models that lack biological constraints and is openly available for health, performance, and disease research.

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.

Vassy, Dornisch and colleagues developed a genomics-based prostate cancer risk model to support a randomized clinical trial of precision screening in a national healthcare system.

Typical quantum error correcting codes assign fixed roles to the underlying physical qubits. Now the performance benefits of alternative, dynamic error correction schemes have been demonstrated on a superconducting quantum processor.

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).

A multiancestry phenome-wide analysis of copy number variants in the UK Biobank genomes increases power to detect genetic associations with complex traits across human populations.

This study demonstrates the capability of deep learning protein design models in generating functionally validated β-strand pairing interfaces, expanding the structural diversity of de novo binding proteins and accessible target surfaces.

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.

The affected cellular populations during Alzheimer’s disease progression remain understudied. Here the authors use a cohort of 84 donors, quantitative neuropathology and multimodal datasets from the BRAIN Initiative. Their pseudoprogression analysis revealed two disease phases.

Experimental measurements of high-order out-of-time-order correlators on a superconducting quantum processor show that these correlators remain highly sensitive to the quantum many-body dynamics in quantum computers at long timescales.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Observations from the Lucy spacecraft of the small main-belt asteroid (152830) Dinkinesh reveals unexpected complexity, with a longitudinal trough and equatorial ridge, as well as the discovery of the first contact binary satellite.

Creative experiences such as dance, music, drawing, and strategy video games might preserve brain health. The authors show that regular practice or short training in these activities is linked to brains that look younger and work more efficiently.

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.

Kozai, Fernandez-Martinez et al. use high-speed atomic force microscopy to study the permeability barrier of yeast nuclear pore complexes. They show that karyopherins remodel a central plug that shapes barrier dynamics and disorder within the pore.

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.

Large genome-wide meta-analysis of clinically diagnosed late-onset Alzheimer’s disease (LOAD) from 94,437 individuals identifies new LOAD risk loci and implicates Aβ formation, tau protein binding, immune response and lipid metabolism.

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.

Redox-driven sulfur speciation and incremental magma recharge modulate the sulfur emissions and climate impacts of large explosive eruptions, according to investigation of 1257 CE Mount Samalas eruption’s sulfur budget.

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.

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.

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.

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.