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The Taiwan Precision Medicine Initiative (TPMI) has built a cohort of more than half a million individuals with Han Chinese ancestry, providing a rich resource of genetic and medical data for this group.

The Taiwan Precision Medicine Initiative recruited and genotyped more than half a million Taiwanese participants, almost all of Han Chinese ancestry, and performed comprehensive genomic analyses and developed polygenic risk score prediction models for numerous health conditions.

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.

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.

Here the authors reveal a study of 486,956 Han Chinese individuals showing that most people with genetic variants affecting drug response do not have the predicted adverse events, highlighting the challenges of implementing pharmacogenetics in clinical practice.

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.

Combination of epidemiology, preclinical models and ultradeep DNA profiling of clinical cohorts unpicks the inflammatory mechanism by which air pollution promotes lung cancer

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

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.

Whole-genome and transcriptome analysis of 1,364 cases of breast cancer from South Korea broadens our understanding of breast cancer biology and reveals genomic features that connect tumour biology with treatment responses and clinical outcomes.

With rich, multi-layered baseline data and long-term follow-up through linkage, the HELIOS Study provides a resource to investigate the behavioural, environmental, genomic, and molecular factors impacting health in Asian populations.

The CMS Collaboration reports the measurement of the spin, parity, and charge conjugation properties of all-charm tetraquarks, exotic fleeting particles formed in proton–proton collisions at the Large Hadron Collider.

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.

A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants.

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.

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.

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.

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.

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.

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.

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.

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.

A meta-analysis of genome-wide association studies of type 2 diabetes (T2D) identifies more than 600 T2D-associated loci; integrating physiological trait and single-cell chromatin accessibility data at these loci sheds light on heterogeneity within the T2D phenotype.

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.

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.

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 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.

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.

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.

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.

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, 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.

A genome-wide association meta-analysis study of blood lipid levels in roughly 1.6 million individuals demonstrates the gain of power attained when diverse ancestries are included to improve fine-mapping and polygenic score generation, with gains in locus discovery related to sample size.

Dengue early warning systems integrating climate information are an important tool for epidemic preparedness and response. Here, the authors develop a prediction model that incorporates climate and serotype data to forecast dengue outbreaks in Singapore up to two months ahead.

As immune checkpoint therapy is more frequently used for cancer, side effects such as Stevens-Johson syndrome / toxic epidermal necrolysis (SJS/TEN) are becoming more common. Here the authors use single cell transcriptomics to implicate TNF and CXCL10 in recruitment of CXCR3⁺ cytotoxic T cell in SJS/TEN skin lesions.

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.

The influence of X chromosome genetic variation on blood lipids and coronary heart disease (CHD) is not well understood. Here, the authors analyse X chromosome sequencing data across 65,322 multi-ancestry individuals, identifying associations of the Xq23 locus with lipid changes and reduced risk of CHD and diabetes mellitus.

Post-acute sequelae of SARS-CoV-2 (PASC) have been linked to brain alterations, but association with cognitive problems are not well understood. Here, the authors analyze blood proteins and brain MRI data one year after mild COVID-19, revealing distinct neurodegenerative processes in PASC patients with cognitive problems, such as cortical thinning, brain iron deposition, enlarged choroid plexus, and increased blood neuronal/glial injury markers, compared to other-PASC.

Here, the authors perform a genome-wide association study to identify 157 significant testosterone genetic variants in male veterans, of which 8 are ancestry-specific. Men with higher testosterone genetic scores have lower odds of diabetes, hyperlipidemia, gout, and cardiac disorders.

The quark structure of the f₀(980) hadron is still unknown after 50 years of its discovery. Here, the CMS Collaboration reports a measurement of the elliptic flow of the f₀(980) state in proton-lead collisions at a nucleon-nucleon centre-of-mass energy of 8.16 TeV, providing strong evidence that the state is an ordinary meson.