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As Nature Aging celebrates its fifth anniversary, the journal asks some of the researchers who contributed to the journal early on to reflect on the past and the future of aging and age-related disease research, the impact of the field on human health now and in the future, and what challenges need to be addressed to ensure sustained progress.

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.

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

Estimates from the Global Burden of Disease study reveal declines in chronic respiratory disease mortality between 1990 and 2023—especially during the COVID-19 pandemic—but the burdens on people affected remain substantial.

Global Burden of Disease estimates show that between 1990 and 2023, the prevalence and burden of drug use disorders, inclusive of amphetamine, cannabis, cocaine and opioid use, have been increasing in high-income countries, particularly in the USA.

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.

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.

Mesothelioma is a highly lethal cancer that remains challenging to diagnose. Here, the authors curate a histomorphological atlas of resected mesothelioma and map it using self-supervised AI endorsed by human pathological assessment, revealing patterns that generate highly interpretable predictions.

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.

Genomic analyses applied to 14 childhood- and adult-onset psychiatric disorders identifies five underlying genomic factors that explain the majority of the genetic variance of the individual disorders.

Natural products inspire the development of pseudo-natural products through combinations of fragments of compound classes that are chemically and biologically distinct. Here, the authors report a library of 244 pseudo-natural products, evaluate them in the cell painting essays and identify the phenotypic role of individual fragments.

Basal cells, rather than neuroendocrine cells, have been identified as the probable origin of small cell lung cancer and other neuroendocrine–tuft cancers, explaining neuroendocrine–tuft heterogeneity and offering new perspectives for targeting lineage plasticity.

Saito et al. identify sphingosine kinase 1 as a critical regulator of physiological ductus arteriosus closure and pathological supravalvular aortic stenosis through its role in smooth muscle cell proliferation and propose potential therapeutics.

Multi-ancestry genome-wide and transcriptome-wide association studies of aortic stenosis identify more than 200 independent risk loci and provide insights into its genetic architecture.

Analysis of a placebo-controlled trial of a BCMA-targeting CAR-T cell therapy in patients with myasthenia gravis shows that CAR-T cell infusion selectively remodels the systemic immune environment, with elimination of BCMA-high plasma cells and activated plasmacytoid dendritic cells and changes in the autoreactive B cell repertoire.

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).

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.

Kang, Lazo de la Vega et al. introduce iCatalog, a precision oncology reporting tool developed to address the needs of a large multi-institutional pediatric study. iCatalog combines a database for patient, sample, and genomic data to enable clinical interpretation of patient-level tumor profiling results.

Here the authors provide an explanation for 95% of examined predicted loss of function variants found in disease-associated haploinsufficient genes in the Genome Aggregation Database (gnomAD), underscoring the power of the presented analysis to minimize false assignments of disease risk.

Understanding the mechanisms underlying the survival of drug tolerant persister cells following chemotherapy remains elusive. Here, multi-omics analysis and experimental approaches show that the germ-cell-specific H3K4 methyltransferase PRDM9 promotes metabolic rewiring in glioblastoma stem cells.

The extent to which in-vitro cellular experiments are effective models for complex biology underlying human phenotypes is often unclear. Here the authors propose and implement a framework using gene perturbation data to evaluate in-vitro models.

Roer et al. analyze genomes of Escherichia coli clonal complex 38 from humans, animals, and food to investigate its spread and host associations. They find distinct human and poultry lineages and identify plasmid markers linked to animal adaptation and zoonotic transmission.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

In this work, authors present an AI framework to detect pediatric tuberculosis by using both frontal and lateral chest X-rays, showing robust performance across several age groups and settings.