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Genome-wide association analysis of gout and urate identifies 148 new loci, implicating biological pathways and prioritizing candidate genes involved in inflammatory processes.

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.

Different functional variants in ADH1B (and elsewhere) in Europeans and Africans strongly affect risk for alcohol dependence. Dependence only partly genetically correlates with consumption, with strong correlations to other psychiatric disorders.

Transancestral GWAS meta-analysis in 160,420 individuals identifies 139 loci associated with refractive error, including myopia. Newly identified genes implicate pathways involved in eye growth and light signaling cascades.

This bi-ancestral genome-wide association study of major depressive disorder (MDD) identified 178 risk variants. The results advance understanding of the biology of MDD and hint at new treatment possibilities.

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.

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.

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 genetic basis of atopic dermatitis is not fully understood. Here, the authors find 91 genetic loci associated with atopic dermatitis in a GWAS of >1million individuals, which highlight the importance of systemic immune regulation.

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.

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.

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.

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.

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.

Genome-wide analyses in over one million self-reported cases and controls identify genetic variants associated with stuttering and find genetic correlations with autism, depression and impaired musical rhythm, supporting a potential neurological basis for stuttering.

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 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-ancestry meta-regression study analyses diverse genome-wide association studies and genome loci associated with tobacco and alcohol use.

Submarine fans play an important role in routing sediment in continental and deep water settings. Here the authors develop a framework is to explain the shape of submarine fans using a numerical model framework which can either predict seafloor topography from turbidity current flow properties or infer these flow properties from seafloor topography.

Thorp et al. use symptom-level genetic modelling to identify 61 and 73 genomic loci associated with depression and anxiety, respectively, and reveal that they possess highly similar genetic architectures.

Genome-wide association analysis of irritable bowel syndrome identifies genetic susceptibility loci and highlights shared pathways with mood and anxiety disorders.

The Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA) aims to better understand population genetics of the African diaspora. Here, it uses deeply sequenced whole-genomes to describe the impact of admixture and potential disease burden of deleterious variants.

This study investigates the underlying physical mechanisms of turbidity currents travelling thousands of miles in confined submarine settings, rather than diffusing after short distance. Using high resolution simulations with up to a billion grid points helps to understand the evolving layered structure of a current.

Using a battery of statistical tools, Alagöz et al. examine the genetic overlap between dyslexia and rhythm impairment and shed light on how the genome influences the neural bases of human language and musicality.

A genome-wide association study in ~3 million individuals identifies 3,952 independent variants associated with educational attainment. A polygenic index explains 12–16% of variance for this trait and contributes to risk prediction for ten diseases.

A genome-wide association study identifies 17 genetic loci that are associated with the risk of myeloproliferative neoplasms (MPNs), and shows that the modulation of haematopoietic stem cell function drives MPN risk.

MTAG is a new method for joint analysis of summary statistics from genome-wide association studies of different traits. Applying MTAG to summary statistics for depressive symptoms, neuroticism and subjective well-being increased discovery of associated loci as compared to single-trait analyses.

Incorporating functional information has shown promise for improving polygenic risk prediction of complex traits. Here, the authors describe polygenic prediction method LDpred-funct, and demonstrate its utility across 21 heritable traits in the UK Biobank.

Multi-ancestry genome-wide association analyses identify new risk loci for Parkinson’s disease, and fine-mapping and co-localization analyses implicate candidate genes whose expression is associated with disease susceptibility.

A genetic study identifies hundreds of loci associated with risk tolerance and risky behaviors, finds evidence of substantial shared genetic influences across these phenotypes, and implicates genes involved in neurotransmission.

Genome-wide analyses in >1 million individuals identify new loci and pathways associated with insomnia. The findings implicate key brain areas and cell types in the neurobiology of insomnia and highlight potential targets for developing new treatments.

Basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) are the most common skin cancers and have genetic overlap. Here, the authors use a multi-trait genetic and phenotypic analysis to reveal susceptibility loci for BCC and SCC, and report an optimised polygenic risk score for risk stratification.

A genome-wide association study for attention deficit/hyperactivity disorder (ADHD) identifies 12 loci and implicates neurodevelopmental pathways and conserved regions of the genome as being involved in underlying ADHD biology.

Predicting who will develop skin cancer is difficult. Here, the authors from 23andMe developed a polygenic risk score for skin cancer based on a questionnaire and genetic data from more than 210,000 individuals and suggest that the score could be used in early screening programmes.

Integration of GWAS and single-cell transcriptomic data from the entire nervous system systematically identifies cell types underlying brain complex traits and provides insights into the etiology of Parkinson’s disease.

REM-sleep behavior disorder often precedes Parkinson’s disease or dementia. Here, the authors perform a genome-wide association study for REM-sleep behavior disorder, and discover how it potentially affects gene expression in the brain.

Primary open-angle glaucoma (POAG) is highly heritable, yet not well understood from a genetic perspective. Here, the authors perform a meta-analysis of genome-wide association studies in 34,179 POAG cases, identifying 44 previously unreported risk loci and mapping effects across multiple ethnicities.

Genetic analyses identify widespread sex-differential participation bias in population-based studies and show how this bias can lead to incorrect inferences. These findings highlight new challenges for association studies as sample sizes continue to grow.

Uterine leiomyomata (UL) or fibroids are neoplasms of the uterine smooth muscle associated with heavy menstrual bleeding and other female reproductive tract morbidity. Here, the authors identify eight previously undescribed genetic loci for UL and further look into genetic overlap with heavy menstrual bleeding and endometriosis.