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The ratio between the levels of two synaptic proteins in cerebrospinal fluid predicts future cognitive resilience versus decline among presymptomatic individuals and individuals with early Alzheimer’s disease harboring amyloid and tau pathology.

Blood plasma protein data was combined with machine learning models for a simple method to determine differences in organ-specific aging; the study provides a basis for the prediction of diseases and aging effects using plasma proteomics.

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.

Here the authors perform a trans expression quantitative trait locus meta-analysis study of over 3,700 people and link a USP18 variant to expression of 50 inflammation genes and lupus risk, highlighting how genetic regulation of immune responses drives autoimmune disease and informs new therapies.

As we age, our brains don’t just shrink, their entire geometry changes. This study links specific patterns of brain expansion and compression to cognitive impairment, revealing a new way to understand age-related decline.

The detection of topological states is restricted to limited experimental tools. Here, the authors apply broadband solid-state ¹²⁵Te nuclear magnetic resonance on Bi₂Te₃ nanoplatelets uncovering signals distinguishing edge Dirac electrons and bulk electrons.

The largest harmonized proteomic dataset of plasma, serum and cerebrospinal fluid samples across major neurodegenerative diseases reveals both disease-specific and transdiagnostic proteomic signatures, including a robust plasma profile associated with the APOEε4 genotype.

Structural and morphological control of crystalline nanoparticles is crucial in heterogeneous catalysis. Applying DFT-assisted solid-state NMR spectroscopy, we determine the surface crystal and electronic structure of Ni₂P nanoparticles, unveiling NMR nanocrystallography as an emerging tool in facet-engineered nanocatalysts.

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.

The heterogeneity of whole-exome sequencing (WES) data generation methods presents a challenge to joint analysis. Here, the authors present a bioinformatics strategy to generate high-quality data from processing diversely generated WES samples, as applied in the Alzheimer’s Disease Sequencing Project.

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).

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

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.

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.

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.

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.

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.

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 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.

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.

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.

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.

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.

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.

A multi-cohort genome-wide association study of tau PET, a brain imaging-based marker of Alzheimer’s disease, identifies a CYP1B1-RMDN2 locus as associated with higher tau and faster cognitive decline. These results suggest a new genetic contribution to cerebral tau and target for Alzheimer’s disease research.

Quantum Hall phases in two-dimensional systems have chiral edges, along which electrons propagate in one direction without backscattering. Here, the authors use nuclear magnetic resonance to demonstrate how chiral modes establish dynamical nuclear polarization in a quantum Hall ferromagnet.

Whole-genome sequencing, transcriptome-wide association and fine-mapping analyses in over 7,000 individuals with critical COVID-19 are used to identify 16 independent variants that are associated with severe illness in COVID-19.

Mandal and colleagues report how the chromatin modulator BRWD1 mediates extensive changes in 3D chromatin topology during B cell development by converting static to dynamic cohesin.

In a large-scale proteomic study of biological aging of 11 organs from 44,498 individuals in the UK Biobank, the biological ages of the brain and immune system emerged as strong predictors of healthspan and longevity.

Hosseinzadeh et al. demonstrate use of a publicly accessible automated machine learning platform to differentiate between a common benign tumor and malignant transformation of it within the paranasal sinuses. This AI algorithm beat prior human prediction, and showed that physicians with no coding background can effectively utilize this tool.

Comparison of paired primary and recurrent glioblastomas at the single-cell transcriptomic level describes molecular and cellular trajectories associated with tumor recurrence, highlighting extensive heterogeneity and microenvironmental co-evolution.

Integrated single-cell transcriptomic and genetic characterization of 121 adult glioblastomas identifies heterogeneity at cell type, cell state and baseline expression program levels associated with specific mutations that form three stereotypical ecosystems.

The nature of quantum criticality in intermetallic f-electron compounds exhibiting valence fluctuations is not well understood. Here, using a combination of experimental techniques, the authors attribute quantum criticality in YbAlB₄ to the anisotropic hybridization between the conduction and f-electrons.

A newly discovered hybrid protein modification of mono(ADP-ribose) and ubiquitin is recognized by dedicated effectors that promote processing of the modified proteins.