Current genome-wide association studies do not yet capture sufficient diversity in populations and scope of phenotypes. To expand an atlas of genetic associations in non-European populations, we ...conducted 220 deep-phenotype genome-wide association studies (diseases, biomarkers and medication usage) in BioBank Japan (n = 179,000), by incorporating past medical history and text-mining of electronic medical records. Meta-analyses with the UK Biobank and FinnGen (n
= 628,000) identified ~5,000 new loci, which improved the resolution of the genomic map of human traits. This atlas elucidated the landscape of pleiotropy as represented by the major histocompatibility complex locus, where we conducted HLA fine-mapping. Finally, we performed statistical decomposition of matrices of phenome-wide summary statistics, and identified latent genetic components, which pinpointed responsible variants and biological mechanisms underlying current disease classifications across populations. The decomposed components enabled genetically informed subtyping of similar diseases (for example, allergic diseases). Our study suggests a potential avenue for hypothesis-free re-investigation of human diseases through genetics.
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IJS, NUK, SBMB, UL, UM, UPUK
PhenoScanner is a curated database of publicly available results from large-scale genetic association studies. This tool aims to facilitate 'phenome scans', the cross-referencing of genetic variants ...with many phenotypes, to help aid understanding of disease pathways and biology. The database currently contains over 350 million association results and over 10 million unique genetic variants, mostly single nucleotide polymorphisms. It is accompanied by a web-based tool that queries the database for associations with user-specified variants, providing results according to the same effect and non-effect alleles for each input variant. The tool provides the option of searching for trait associations with proxies of the input variants, calculated using the European samples from 1000 Genomes and Hapmap.
PhenoScanner is available at www.phenoscanner.medschl.cam.ac.uk CONTACT: jrs95@medschl.cam.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online.
Epidermal growth factor receptor (EGFR) mutations are the second most common oncogenic driver event in non-small cell lung cancer (NSCLC). Classical activating mutations (exon 19 deletions and the ...L858R point mutation) comprise the vast majority of EGFR mutations and are well defined as strong predictors for good clinical response to EGFR tyrosine kinase inhibitors (EGFRi). However, low frequency mutations including point mutations, deletions, insertions and duplications occur within exons 18–25 of the EGFR gene in NSCLC and are associated with poorer responses to EGFRi. Despite an increased uptake of more sensitive detection methods to identify rare EGFR mutations in patients, our understanding of the biology of these rare EGFR mutations is poor compared to classical mutations. In particular, clinical data focused on these mutations is lacking due to their rarity and challenges in trial recruitment, resulting in an absence of effective treatment strategies for many low frequency EGFR mutations. In this review, we describe the structural and mechanistic features of rare EGFR mutations in NSCLC and discuss the preclinical and clinical evidence for EGFRi response for individual rare EGFR mutations. We also discuss EGFRi sensitivity for complex EGFR mutations, and conclude by offering a perspective on the outstanding questions and future steps required to make advances in the treatment of NSCLC patients that harbour rare EGFR mutations.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Micro-electrode arrays (MEAs) are increasingly used to characterize neuronal network activity of human induced pluripotent stem cell (hiPSC)-derived neurons. Despite their gain in popularity, MEA ...recordings from hiPSC-derived neuronal networks are not always used to their full potential in respect to experimental design, execution, and data analysis. Therefore, we benchmarked the robustness of MEA-derived neuronal activity patterns from ten healthy individual control lines, and uncover comparable network phenotypes. To achieve standardization, we provide recommendations on experimental design and analysis. With such standardization, MEAs can be used as a reliable platform to distinguish (disease-specific) network phenotypes. In conclusion, we show that MEAs are a powerful and robust tool to uncover functional neuronal network phenotypes from hiPSC-derived neuronal networks, and provide an important resource to advance the hiPSC field toward the use of MEAs for disease phenotyping and drug discovery.
•MEAs are a robust tool to model neuronal network functioning•Neuronal networks from different healthy donors show comparable network activity•MEAs are able to distinguish disease-specific neuronal network phenotypes•We provide recommendations to standardize neuronal network recordings on MEA
In this article, Mossink and colleagues demonstrate that micro-electrode arrays (MEAs) are a highly robust tool to uncover genotype/phenotype interactions in hiPSC-derived excitatory neuronal networks, and provide an important resource for the design, execution, and analysis of hiPSC-derived neuronal networks studies on MEA.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Clonal hematopoiesis (CH), as evidenced by recurrent somatic mutations in leukemia-associated genes, commonly occurs among aging human hematopoietic stem cells. We analyzed deep-coverage, targeted, ...next-generation sequencing (NGS) data of paired tumor and blood samples from 8,810 individuals to assess the frequency and clinical relevance of CH in patients with non-hematologic malignancies. We identified CH in 25% of cancer patients, with 4.5% harboring presumptive leukemia driver mutations (CH-PD). CH was associated with increased age, prior radiation therapy, and tobacco use. PPM1D and TP53 mutations were associated with prior exposure to chemotherapy. CH and CH-PD led to an increased incidence of subsequent hematologic cancers, and CH-PD was associated with shorter patient survival. These data suggest that CH occurs in an age-dependent manner and that specific perturbations can enhance fitness of clonal hematopoietic stem cells, which can impact outcome through progression to hematologic malignancies and through cell-non-autonomous effects on solid tumor biology.
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•Deep sequencing shows clonal hematopoiesis (CH) is common in solid tumor patients•CH is associated with increasing age, tobacco use, and prior radiation therapy•CH is associated with an increased risk of hematologic cancers•The presence of CH adversely impacts survival from non-hematologic cancers
Coombs et al. examined a large cohort of solid tumor patients who underwent deep-coverage, paired tumor/blood sequencing and demonstrated that clonal hematopoiesis is common and associated with increasing age, tobacco use, and prior radiation therapy and that it predicts an increased risk of hematologic cancers and shorter survival.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Despite a century of research on complex traits in humans, the relative importance and specific nature of the influences of genes and environment on human traits remain controversial. We report a ...meta-analysis of twin correlations and reported variance components for 17,804 traits from 2,748 publications including 14,558,903 partly dependent twin pairs, virtually all published twin studies of complex traits. Estimates of heritability cluster strongly within functional domains, and across all traits the reported heritability is 49%. For a majority (69%) of traits, the observed twin correlations are consistent with a simple and parsimonious model where twin resemblance is solely due to additive genetic variation. The data are inconsistent with substantial influences from shared environment or non-additive genetic variation. This study provides the most comprehensive analysis of the causes of individual differences in human traits thus far and will guide future gene-mapping efforts. All the results can be visualized using the MaTCH webtool.
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DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SBMB, UILJ, UKNU, UL, UM, UPUK
The application of massively parallel sequencing technology to the field of skeletal disorders has boosted the discovery of the underlying genetic defect for many of these diseases. It has also ...resulted in the delineation of new clinical entities and the identification of genes and pathways that had not previously been associated with skeletal disorders. These rapid advances have prompted the Nosology Committee of the International Skeletal Dysplasia Society to revise and update the last (2015) version of the Nosology and Classification of Genetic Skeletal Disorders. This newest and tenth version of the Nosology comprises 461 different diseases that are classified into 42 groups based on their clinical, radiographic, and/or molecular phenotypes. Remarkably, pathogenic variants affecting 437 different genes have been found in 425/461 (92%) of these disorders. By providing a reference list of recognized entities and their causal genes, the Nosology should help clinicians achieve accurate diagnoses for their patients and help scientists advance research in skeletal biology.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Amyotrophic lateral sclerosis is a fatal neurodegenerative disease. The discovery of genes associated with amyotrophic lateral sclerosis, commencing with SOD1 in 1993, started fairly gradually. ...Recent advances in genetic technology have led to the rapid identification of multiple new genes associated with the disease, and to a new understanding of oligogenic and polygenic disease risk. The overlap of genes associated with amyotrophic lateral sclerosis with those of other neurodegenerative diseases is shedding light on the phenotypic spectrum of neurodegeneration, leading to a better understanding of genotype–phenotype correlations. A deepening knowledge of the genetic architecture is allowing the characterisation of the molecular steps caused by various mutations that converge on recurrent dysregulated pathways. Of crucial relevance, mutations associated with amyotrophic lateral sclerosis are amenable to novel gene-based therapeutic options, an approach in use for other neurological illnesses. Lastly, the exposome—the summation of lifetime environmental exposures—has emerged as an influential component for amyotrophic lateral sclerosis through the gene–time–environment hypothesis. Our improved understanding of all these aspects will lead to long-awaited therapies and the identification of modifiable risks factors.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Biological networks are powerful resources for the discovery of genes and genetic modules that drive disease. Fundamental to network analysis is the concept that genes underlying the same phenotype ...tend to interact; this principle can be used to combine and to amplify signals from individual genes. Recently, numerous bioinformatic techniques have been proposed for genetic analysis using networks, based on random walks, information diffusion and electrical resistance. These approaches have been applied successfully to identify disease genes, genetic modules and drug targets. In fact, all these approaches are variations of a unifying mathematical machinery - network propagation - suggesting that it is a powerful data transformation method of broad utility in genetic research.
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IJS, NUK, SBMB, UL, UM, UPUK
Abstract
Epigenome-Wide Association Study (EWAS) has become increasingly significant in identifying the associations between epigenetic variations and different biological traits. In this study, we ...develop EWAS Atlas (http://bigd.big.ac.cn/ewas), a curated knowledgebase of EWAS that provides a comprehensive collection of EWAS knowledge. Unlike extant data-oriented epigenetic resources, EWAS Atlas features manual curation of EWAS knowledge from extensive publications. In the current implementation, EWAS Atlas focuses on DNA methylation—one of the key epigenetic marks; it integrates a large number of 329 172 high-quality EWAS associations, involving 112 tissues/cell lines and covering 305 traits, 1830 cohorts and 390 ontology entities, which are completely based on manual curation from 649 studies reported in 401 publications. In addition, it is equipped with a powerful trait enrichment analysis tool, which is capable of profiling trait-trait and trait-epigenome relationships. Future developments include regular curation of recent EWAS publications, incorporation of more epigenetic marks and possible integration of EWAS with GWAS. Collectively, EWAS Atlas is dedicated to the curation, integration and standardization of EWAS knowledge and has the great potential to help researchers dissect molecular mechanisms of epigenetic modifications associated with biological traits.
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