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Showing 1–50 of 263 results
Advanced filters: Author: Mark Donovan Clear advanced filters
  • 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.

    • Andrew D. Grotzinger
    • Josefin Werme
    • Jordan W. Smoller
    ResearchOpen Access
    Nature
    Volume: 649, P: 406-415
  • 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.

    • Sanna Gudmundsson
    • Moriel Singer-Berk
    • Anne O’Donnell-Luria
    ResearchOpen Access
    Nature Communications
    Volume: 16, P: 1-14
  • This study used fine-mapping to analyze genetic regions associated with bipolar disorder, identifying specific risk genes and providing new insights into the biology of the condition that may guide future research and treatment approaches.

    • Maria Koromina
    • Ashvin Ravi
    • Niamh Mullins
    ResearchOpen Access
    Nature Neuroscience
    Volume: 28, P: 1393-1403
  • A genome-wide association study including over 76,000 individuals with schizophrenia and over 243,000 control individuals identifies common variant associations at 287 genomic loci, and further fine-mapping analyses highlight the importance of genes involved in synaptic processes.

    • Vassily Trubetskoy
    • Antonio F. Pardiñas
    • Jim van Os
    Research
    Nature
    Volume: 604, P: 502-508
  • The authors defined a roadmap for investigating the genetic covariance between structural or functional brain phenotypes and risk for psychiatric disorders. Their proof-of-concept study using the largest available common variant data sets for schizophrenia and volumes of several (mainly subcortical) brain structures did not find evidence of genetic overlap.

    • Barbara Franke
    • Jason L Stein
    • Patrick F Sullivan
    Research
    Nature Neuroscience
    Volume: 19, P: 420-431
  • 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.

    • Esther Rheinbay
    • Morten Muhlig Nielsen
    • Christian von Mering
    ResearchOpen Access
    Nature
    Volume: 578, P: 102-111
  • 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.

    • Matthew A. Reyna
    • David Haan
    • Christian von Mering
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-17
  • 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.

    • Lauri A. Aaltonen
    • Federico Abascal
    • Christian von Mering
    ResearchOpen Access
    Nature
    Volume: 578, P: 82-93
  • 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.

    • Shimin Shuai
    • Federico Abascal
    • Christian von Mering
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-12
  • 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.

    • Athanasios Kousathanas
    • Erola Pairo-Castineira
    • J. Kenneth Baillie
    ResearchOpen Access
    Nature
    Volume: 607, P: 97-103
  • In the second of three papers on the genetics of schizophrenia, a large genome-wide association study looking at common genetic variants underlying the risk of schizophrenia implicates the major histocompatibility complex — and thus, immunity — and provides molecular genetic evidence for a substantial polygenic component to the risk of schizophrenia. The latter involves thousands of common alleles of very small effect that also contribute to the risk of bipolar disorder.

    • Shaun M. Purcell
    • Naomi R. Wray
    • Pamela Sklar
    Research
    Nature
    Volume: 460, P: 748-752
  • CAR T cell therapies have been developed to treat paediatric diffuse intrinsic pontine glioma (DIPG), however, clinical efficacy remains limited. Here, the authors report that engineering B7-H3-targeting CAR T cells to express the chemokine receptor CXCR3-A enhances their trafficking and efficacy in DIPG preclinical models.

    • Edward Z. Song
    • Andrea Timpanaro
    • Nicholas A. Vitanza
    ResearchOpen Access
    Nature Communications
    Volume: 16, P: 1-18
  • Over one hundred loci have been identified to be associated with the familial risk of prostate cancer but the functional effects are poorly understood. Here the authors use single-nucleotide variant and epigentic data to show an underlying genetic architecture marked by histone modification.

    • Alexander Gusev
    • Huwenbo Shi
    • Bogdan Pasaniuc
    ResearchOpen Access
    Nature Communications
    Volume: 7, P: 1-13
  • 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.

    • Matthew H. Bailey
    • William U. Meyerson
    • Christian von Mering
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-27
  • 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.

    • Wei Jiao
    • Gurnit Atwal
    • Christian von Mering
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-12
  • 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.

    • Marta Paczkowska
    • Jonathan Barenboim
    • Christian von Mering
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-16
  • 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.

    • Yulia Rubanova
    • Ruian Shi
    • Christian von Mering
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-12
  • Similarities in cancers can be studied to interrogate their etiology. Here, the authors use genome-wide association study summary statistics from six cancer types based on 296,215 cases and 301,319 controls of European ancestry, showing that solid tumours arising from different tissues share a degree of common germline genetic basis.

    • Xia Jiang
    • Hilary K. Finucane
    • Sara Lindström
    ResearchOpen Access
    Nature Communications
    Volume: 10, P: 1-23
  • 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.

    • Constance H. Li
    • Stephenie D. Prokopec
    • Christian von Mering
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-24
  • 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.

    • Lina Sieverling
    • Chen Hong
    • Christian von Mering
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-13
  • 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.

    • Claudia Calabrese
    • Natalie R. Davidson
    • Christian von Mering
    ResearchOpen Access
    Nature
    Volume: 578, P: 129-136
  • 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.

    • Yilong Li
    • Nicola D. Roberts
    • Christian von Mering
    ResearchOpen Access
    Nature
    Volume: 578, P: 112-121
  • 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.

    • Marc Zapatka
    • Ivan Borozan
    • Christian von Mering
    ResearchOpen Access
    Nature Genetics
    Volume: 52, P: 320-330
  • 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.

    • Moritz Gerstung
    • Clemency Jolly
    • Christian von Mering
    ResearchOpen Access
    Nature
    Volume: 578, P: 122-128
  • The authors present SVclone, a computational method for inferring the cancer cell fraction of structural variants from whole-genome sequencing data.

    • Marek Cmero
    • Ke Yuan
    • Christian von Mering
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-15
  • 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.

    • Vinayak Bhandari
    • Constance H. Li
    • Christian von Mering
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-10
  • 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.

    • Ludmil B. Alexandrov
    • Jaegil Kim
    • Christian von Mering
    ResearchOpen Access
    Nature
    Volume: 578, P: 94-101
  • 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.

    • Yiqun Zhang
    • Fengju Chen
    • Christian von Mering
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-14
  • Phylogenomic analysis of 7,923 angiosperm species using a standardized set of 353 nuclear genes produced an angiosperm tree of life dated with 200 fossil calibrations, providing key insights into evolutionary relationships and diversification.

    • Alexandre R. Zuntini
    • Tom Carruthers
    • William J. Baker
    ResearchOpen Access
    Nature
    Volume: 629, P: 843-850
  • The CNV analysis group of the Psychiatric Genomic Consortium analyzes a large schizophrenia cohort to examine genomic copy number variants (CNVs) and disease risk. They find an enrichment of CNV burden in cases versus controls and identify 8 genome-wide significant loci as well as novel suggestive loci conferring either risk or protection to schizophrenia.

    • Christian R Marshall
    • Daniel P Howrigan
    • Jonathan Sebat
    Research
    Nature Genetics
    Volume: 49, P: 27-35
  • Missense variants in RNA-binding proteins underlie many diseases. Here the authors report an oculopharyngeal muscular dystrophy caused by heterozygous frameshift mutations in HNRNPA2B1 that alter its nucleocytoplasmic transport dynamics and result in cytoplasmic accumulation of hnRNPA2 protein.

    • Hong Joo Kim
    • Payam Mohassel
    • J. Paul Taylor
    ResearchOpen Access
    Nature Communications
    Volume: 13, P: 1-18
  • The authors analyzed the whole-exome sequences of over 16,000 individuals and found that very rare variants predicted to disrupt the SETD1A gene confer substantial risk for schizophrenia. Damaging variants in SETD1A were also associated with diverse, severe developmental disorders, providing an important genetic link between schizophrenia and other neurodevelopmental disorders.

    • Tarjinder Singh
    • Mitja I Kurki
    • Jeffrey C Barrett
    Research
    Nature Neuroscience
    Volume: 19, P: 571-577
  • Analysis of mitochondrial genomes (mtDNA) by using whole-genome sequencing data from 2,658 cancer samples across 38 cancer types identifies hypermutated mtDNA cases, frequent somatic nuclear transfer of mtDNA and high variability of mtDNA copy number in many cancers.

    • Yuan Yuan
    • Young Seok Ju
    • Christian von Mering
    ResearchOpen Access
    Nature Genetics
    Volume: 52, P: 342-352