6 research outputs found

    Adipocyte mesenchymal transition contributes to mammary tumor progression

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    Obesity is associated with increased cancer incidence and progression. However, the relationship between adiposity and cancer remains poorly understood at the mechanistic level. Here, we report that adipocytes from tumor-invasive mammary fat undergo de-differentiation to fibroblast-like precursor cells during tumor progression and integrate into the tumor microenvironment. Single-cell sequencing reveals that these de-differentiated adipocytes lose their original identities and transform into multiple cell types, including myofibroblast- and macrophage-like cells, with their characteristic features involved in immune response, inflammation, and extracellular matrix remodeling. The de-differentiated cells are metabolically distinct from tumor-associated fibroblasts but exhibit comparable effects on tumor cell proliferation. Inducing de-differentiation by Xbp1s overexpression promotes tumor progression despite lower adiposity. In contrast, promoting lipid-storage capacity in adipocytes through MitoNEET overexpression curbs tumor growth despite greater adiposity. Collectively, the metabolic interplay between tumor cells and adipocytes induces adipocyte mesenchymal transition and contributes to reconfigure the stroma into a more tumor-friendly microenvironment

    Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals

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    We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57

    Genome-wide association study identifies 74 loci associated with educational attainment

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    Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals1. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample1,2 of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases

    Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences

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    Humans vary substantially in their willingness to take risks. In a combined sample of over 1 million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. Across all GWAS, we identified hundreds of associated loci, including 99 loci associated with general risk tolerance. We report evidence of substantial shared genetic influences across risk tolerance and the risky behaviors: 46 of the 99 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is genetically correlated (|r^g| ~ 0.25 to 0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near SNPs associated with general risk tolerance are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We found no evidence of enrichment for genes previously hypothesized to relate to risk tolerance

    Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals.

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    Here we conducted a large-scale genetic association analysis of educational attainment in a sample of approximately 1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of around 0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11-13% of the variance in educational attainment and 7-10% of the variance in cognitive performance. This prediction accuracy substantially increases the utility of polygenic scores as tools in research.Medical Research Council (MC_UU_12015/1), Department of Health (via National Institute for Health Research (NIHR)) (NF-SI-0512-10135), MRC (MC_PC_13048), Department of Health (via National Institute for Health Research (NIHR)) (NF-SI-0617-10149
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