Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Ancient Plasmodium genomes shed light on the history of human malaria

Malaria-causing protozoa of the genus Plasmodium have exerted one of the strongest selective pressures on the human genome, and resistance alleles provide biomolecular footprints that outline the historical reach of these species1. Nevertheless, debate persists over when and how malaria parasites emerged as human pathogens and spread around the globe1,2. To address these questions, we generated high-coverage ancient mitochondrial and nuclear genome-wide data from P. falciparum, P. vivax and P. malariae from 16 countries spanning around 5,500 years of human history. We identified P. vivax and P. falciparum across geographically disparate regions of Eurasia from as early as the fourth and first millennia bce, respectively; for P. vivax, this evidence pre-dates textual references by several millennia3. Genomic analysis supports distinct disease histories for P. falciparum and P. vivax in the Americas: similarities between now-eliminated European and peri-contact South American strains indicate that European colonizers were the source of American P. vivax, whereas the trans-Atlantic slave trade probably introduced P. falciparum into the Americas. Our data underscore the role of cross-cultural contacts in the dissemination of malaria, laying the biomolecular foundation for future palaeo-epidemiological research into the impact of Plasmodium parasites on human history. Finally, our unexpected discovery of P. falciparum in the high-altitude Himalayas provides a rare case study in which individual mobility can be inferred from infection status, adding to our knowledge of cross-cultural connectivity in the region nearly three millennia ago.This project was funded by the National Science Foundation, grants BCS-2141896 and BCS-1528698; the European Research Council (ERC) under the European Union’s Horizon 2020 programme, grants 851511-MICROSCOPE (to S. Schiffels), 771234-PALEoRIDER (to W.H.) and starting grant 805268-CoDisEASe (to K.I.B.); and the ERC starting grant Waves ERC758967 (supporting K. Nägele and S.C.). We thank the Max Planck-Harvard Research Center for the Archaeoscience of the Ancient Mediterranean for supporting M. Michel, E. Skourtanioti, A.M., R.A.B., L.C.B., G.U.N., N.S., V.V.-M., M. McCormick, P.W.S., C.W. and J.K.; the Kone Foundation for supporting E.K.G. and A.S.; and the Faculty of Medicine and the Faculty of Biological and Environmental Sciences at the University of Helsinki for grants to E.K.G. A.S. thanks the Magnus Ehrnrooth Foundation, the Sigrid Jusélius Foundation, the Finnish Cultural Foundation, the Academy of Finland, the Life and Health Medical Foundation and the Finnish Society of Sciences and Letters. M.C.B. acknowledges funding from: research project PID2020-116196GB-I00 funded by MCIN/AEI/10.13039/501100011033; the Spanish Ministry of Culture; the Chiang Ching Kuo Foundation; Fundación Palarq; the EU FP7 Marie Curie Zukunftskolleg Incoming Fellowship Programme, University of Konstanz (grant 291784); STAR2-Santander Universidades and Ministry of Education, Culture and Sports; and CEI 2015 project Cantabria Campus Internacional. M.E. received support from the Czech Academy of Sciences award Praemium Academiae and project RVO 67985912 of the Institute of Archaeology of the Czech Academy of Sciences, Prague. This work has been funded within project PID2020-115956GB-I00 ‘Origen y conformación del Bronce Valenciano’, granted by the Ministry of Science and Innovation of the Government of Spain, and grants from the Canadian Institutes for Health Research (MZI187236), Research Nova Scotia (RNS 2023-2565) and The Center for Health Research in Developing Countries. D.K. is the Canada research chair in translational vaccinology and inflammation. R.L.K. acknowledges support from a 2019 University of Otago research grant (Human health and adaptation along Silk Roads, a bioarchaeological investigation of a medieval Uzbek cemetery). P.O. thanks the Jane and Aatos Erkko Foundation, the Finnish Cultural Foundation and the Academy of Finland. S. Peltola received support from the Emil Aaltonen Foundation and the Ella and Georg Ehrnrooth Foundation. D.C.S.-G. thanks the Generalitat Valenciana (CIDEGENT/2019/061). E.W.K. acknowledges support from the DEEPDEAD project, HERA-UP, CRP (15.055) and the Horizon 2020 programme (grant 649307). M. Spyrou thanks the Elite program for postdocs of the Baden-Württemberg Stiftung. Open access funding provided by Max Planck Society

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies