Common variants in Alzheimer’s disease and risk stratification by polygenic risk scores

Genetic discoveries of Alzheimer’s disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer’s disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer’s disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer’s disease.Fil: Dalmasso, Maria Carolina. Gobierno de la Provincia de la Pampa. Ministerio Publico. Laboratorio de Genetica Forense.; Argentina. Universitat zu Köln; Alemania. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Confluencia; ArgentinaFil: de Rojas, Itziar. Universitat Internacional de Catalunya; España. Instituto de Salud Carlos Iii (isciii); EspañaFil: Moreno Grau, Sonia. Universitat Internacional de Catalunya; España. Instituto de Salud Carlos Iii (isciii); EspañaFil: Tesi, Niccolo. Vrije Universiteit Amsterdam; Países Bajos. Delft University of Technology; Países BajosFil: Grenier Boley, Benjamin. Universite Lille; FranciaFil: Andrade, Victor. Universitat zu Köln; Alemania. Universitat Bonn; AlemaniaFil: Pedersen, Nancy L.. Karolinska Huddinge Hospital. Karolinska Institutet; SueciaFil: Stringa, Najada. University of Amsterdam; Países BajosFil: Zettergren, Anna. University of Gothenburg; SueciaFil: Hernández, Isabel. Universitat Internacional de Catalunya; España. Instituto de Salud Carlos Iii (isciii); EspañaFil: Montrreal, Laura. Universitat Internacional de Catalunya; EspañaFil: Antúnez, Carmen. Hospital Clínico Universitario Virgen de la Arrixaca; EspañaFil: Antonell, Anna. Universidad de Barcelona; EspañaFil: Tankard, Rick M.. Murdoch University; AustraliaFil: Bis, Joshua C.. University of Washington; Estados UnidosFil: Sims, Rebecca. Cardiff University; Reino UnidoFil: Bellenguez, Céline. Universite Lille; FranciaFil: Quintela, Inés. Universidad de Santiago de Compostela; EspañaFil: González Perez, Antonio. Centro Andaluz de Estudios Bioinformáticos; EspañaFil: Calero, Miguel. Instituto de Salud Carlos Iii (isciii); España. Fundación Reina Sofia; EspañaFil: Franco Macías, Emilio. Universidad de Sevilla; EspañaFil: Macías, Juan. Hospital Universitario de Valme; EspañaFil: Blesa, Rafael. Instituto de Salud Carlos Iii (isciii); España. Universitat Autònoma de Barcelona; EspañaFil: Cervera Carles, Laura. Instituto de Salud Carlos Iii (isciii); España. Universitat Autònoma de Barcelona; EspañaFil: Menéndez González, Manuel. Universidad de Oviedo; EspañaFil: Frank García, Ana. Instituto de Salud Carlos Iii (isciii); España. Universidad Autónoma de Madrid; España. Instituto de Investigacion del Hospital de la Paz.; España. Hospital Universitario La Paz; EspañaFil: Royo, Jose Luís. Universidad de Málaga; EspañaFil: Moreno, Fermin. Instituto de Salud Carlos Iii (isciii); España. Hospital Universitario Donostia; España. Instituto Biodonostia; EspañaFil: Huerto Vilas, Raquel. Hospital Universitari Santa Maria de Lleida; España. Institut de Recerca Biomedica de Lleida; EspañaFil: Baquero, Miquel. Hospital Universitari i Politècnic La Fe; Españ

Common variants in Alzheimer’s disease and risk stratification by polygenic risk scores

Genetic discoveries of Alzheimer’s disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer’s disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer’s disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer’s disease.Additional co-authors: Joshua C. Bis, Rebecca Sims, Céline Bellenguez, Inés Quintela, Antonio González-Perez, Miguel Calero, Emilio Franco-Macías, Juan Macías, Rafael Blesa, Laura Cervera-Carles, Manuel Menéndez-González, Ana Frank-García, Jose Luís Royo, Fermin Moreno, Raquel Huerto Vilas, Miquel Baquero, Mónica Diez-Fairen, Carmen Lage, Sebastián García-Madrona, Pablo García-González, Emilio Alarcón-Martín, Sergi Valero, Oscar Sotolongo-Grau, Abbe Ullgren, Adam C. Naj, Afina W. Lemstra, Alba Benaque, Alba Pérez-Cordón, Alberto Benussi, Alberto Rábano, Alessandro Padovani, Alessio Squassina, Alexandre de Mendonça, Alfonso Arias Pastor, Almar A. L. Kok, Alun Meggy, Ana Belén Pastor, Ana Espinosa, Anaïs Corma-Gómez, Angel Martín Montes, Ángela Sanabria, Anita L. DeStefano, Anja Schneider, Annakaisa Haapasalo, Anne Kinhult Ståhlbom, Anne Tybjærg-Hansen, Annette M. Hartmann, Annika Spottke, Arturo Corbatón-Anchuelo, Arvid Rongve, Barbara Borroni, Beatrice Arosio, Benedetta Nacmias, Børge G. Nordestgaard, Brian W. Kunkle, Camille Charbonnier, Carla Abdelnour, Carlo Masullo, Carmen Martínez Rodríguez, Carmen Muñoz-Fernandez, Carole Dufouil, Caroline Graff, Catarina B. Ferreira, Caterina Chillotti, Chandra A. Reynolds, Chiara Fenoglio, Christine Van Broeckhoven, Christopher Clark, Claudia Pisanu, Claudia L. Satizabal, Clive Holmes, Dolores Buiza-Rueda, Dag Aarsland, Dan Rujescu, Daniel Alcolea, Daniela Galimberti, David Wallon, Davide Seripa, Edna Grünblatt, Efthimios Dardiotis, Emrah Düzel, Elio Scarpini, Elisa Conti, Elisa Rubino, Ellen Gelpi, Eloy Rodriguez-Rodriguez, Emmanuelle Duron, Eric Boerwinkle, Evelyn Ferri, Fabrizio Tagliavini, Fahri Küçükali, Florence Pasquier, Florentino Sanchez-Garcia, Francesca Mangialasche, Frank Jessen, Gaël Nicolas, Geir Selbæk, Gemma Ortega, Geneviève Chêne, Georgios Hadjigeorgiou, Giacomina Rossi, Gianfranco Spalletta, Giorgio Giaccone, Giulia Grande, Giuliano Binetti, Goran Papenberg, Harald Hampel, Henri Bailly, Henrik Zetterberg, Hilkka Soininen, Ida K. Karlsson, Ignacio Alvarez, Ildebrando Appollonio, Ina Giegling, Ingmar Skoog, Ingvild Saltvedt, Innocenzo Rainero, Irene Rosas Allende, Jakub Hort, Janine Diehl-Schmid, Jasper Van Dongen, Jean-Sebastien Vidal, Jenni Lehtisalo, Jens Wiltfang, Jesper Qvist Thomassen, Johannes Kornhuber, Jonathan L. Haines, Jonathan Vogelgsang, Juan A. Pineda, Juan Fortea, Julius Popp, Jürgen Deckert, Katharina Buerger, Kevin Morgan, Klaus Fließbach, Kristel Sleegers, Laura Molina-Porcel, Lena Kilander, Leonie Weinhold, Lindsay A. Farrer, Li-San Wang, Luca Kleineidam, Lucia Farotti, Lucilla Parnetti, Lucio Tremolizzo, Lucrezia Hausner, Luisa Benussi, Lutz Froelich, M. Arfan Ikram, M. Candida Deniz-Naranjo, Magda Tsolaki, Maitée Rosende-Roca, Malin Löwenmark, Marc Hulsman, Marco Spallazzi, Margaret A. Pericak-Vance, Margaret Esiri, María Bernal Sánchez-Arjona, Maria Carolina Dalmasso, María Teresa Martínez-Larrad, Marina Arcaro, Markus M. Nöthen, Marta Fernández-Fuertes, Martin Dichgans, Martin Ingelsson, Martin J. Herrmann, Martin Scherer, Martin Vyhnalek, Mary H. Kosmidis, Mary Yannakoulia, Matthias Schmid, Michael Ewers, Michael T. Heneka, Michael Wagner, Michela Scamosci, Miia Kivipelto, Mikko Hiltunen, Miren Zulaica, Montserrat Alegret, Myriam Fornage, Natalia Roberto, Natasja M. van Schoor, Nazib M. Seidu, Nerisa Banaj, Nicola J. Armstrong, Nikolaos Scarmeas, Norbert Scherbaum, Oliver Goldhardt, Oliver Hanon, Oliver Peters, Olivia Anna Skrobot, Olivier Quenez, Ondrej Lerch, Paola Bossù, Paolo Caffarra, Paolo Dionigi Rossi, Paraskevi Sakka, Per Hoffmann, Peter A. Holmans, Peter Fischer, Peter Riederer, Qiong Yang, Rachel Marshall, Rajesh N. Kalaria, Richard Mayeux, Rik Vandenberghe, Roberta Cecchetti, Roberta Ghidoni, Ruth Frikke-Schmidt, Sandro Sorbi, Sara Hägg, Sebastiaan Engelborghs, Seppo Helisalmi, Sigrid Botne Sando, Silke Kern, Silvana Archetti, Silvia Boschi, Silvia Fostinelli, Silvia Gil, Silvia Mendoza, Simon Mead, Simona Ciccone, Srdjan Djurovic, Stefanie Heilmann-Heimbach, Steffi Riedel-Heller, Teemu Kuulasmaa, Teodoro del Ser, Thibaud Lebouvier, Thomas Polak, Tiia Ngandu, Timo Grimmer, Valentina Bessi, Valentina Escott-Price, Vilmantas Giedraitis, Vincent Deramecourt, Wolfgang Maier, Xueqiu Jian, Yolande A. L. Pijnenburg, EADB contributors, The GR@ACE study group, DEGESCO consortium, IGAP (ADGC, CHARGE, EADI, GERAD), PGC-ALZ consortia, Patrick Gavin Kehoe, Guillermo Garcia-Ribas, Pascual Sánchez-Juan, Pau Pastor, Jordi Pérez-Tur, Gerard Piñol-Ripoll, Adolfo Lopez de Munain, Jose María García-Alberca, María J. Bullido, Victoria Álvarez, Alberto Lleó, Luis M. Real, Pablo Mir, Miguel Medina, Philip Scheltens, Henne Holstege, Marta Marquié, María Eugenia Sáez, Ángel Carracedo, Philippe Amouyel, Gerard D. Schellenberg, Julie Williams, Sudha Seshadri, Cornelia M. van Duijn, Karen A. Mather, Raquel Sánchez-Valle, Manuel Serrano-Ríos, Adelina Orellana, Lluís Tárraga, Kaj Blennow, Martijn Huisman, Ole A. Andreassen, Danielle Posthuma, Jordi Clarimón, Mercè Boada, Wiesje M. van der Flier, Alfredo Ramirez, Jean-Charles Lambert, Sven J. van der Lee & Agustín Rui

Polygenic resilience scores capture protective genetic effects for Alzheimer’s disease

Polygenic risk scores (PRSs) can boost risk prediction in late-onset Alzheimer’s disease (LOAD) beyond apolipoprotein E (APOE) but have not been leveraged to identify genetic resilience factors. Here, we sought to identify resilience-conferring common genetic variants in (1) unaffected individuals having high PRSs for LOAD, and (2) unaffected APOE-ε4 carriers also having high PRSs for LOAD. We used genome-wide association study (GWAS) to contrast “resilient” unaffected individuals at the highest genetic risk for LOAD with LOAD cases at comparable risk. From GWAS results, we constructed polygenic resilience scores to aggregate the addictive contributions of risk-orthogonal common variants that promote resilience to LOAD. Replication of resilience scores was undertaken in eight independent studies. We successfully replicated two polygenic resilience scores that reduce genetic risk penetrance for LOAD. We also showed that polygenic resilience scores positively correlate with polygenic risk scores in unaffected individuals, perhaps aiding in staving off disease. Our findings align with the hypothesis that a combination of risk-independent common variants mediates resilience to LOAD by moderating genetic disease risk

The genome of the yellow potato cyst nematode, Globodera rostochiensis, reveals insights into the basis of parasitism and virulence

BACKGROUND: The yellow potato cyst nematode, Globodera rostochiensis, is a devastating plant pathogen of global economic importance. This biotrophic parasite secretes effectors from pharyngeal glands, some of which were acquired by horizontal gene transfer, to manipulate host processes and promote parasitism. G. rostochiensis is classified into pathotypes with different plant resistance-breaking phenotypes. RESULTS: We generate a high quality genome assembly for G. rostochiensis pathotype Ro1, identify putative effectors and horizontal gene transfer events, map gene expression through the life cycle focusing on key parasitic transitions and sequence the genomes of eight populations including four additional pathotypes to identify variation. Horizontal gene transfer contributes 3.5 % of the predicted genes, of which approximately 8.5 % are deployed as effectors. Over one-third of all effector genes are clustered in 21 putative ‘effector islands’ in the genome. We identify a dorsal gland promoter element motif (termed DOG Box) present upstream in representatives from 26 out of 28 dorsal gland effector families, and predict a putative effector superset associated with this motif. We validate gland cell expression in two novel genes by in situ hybridisation and catalogue dorsal gland promoter element-containing effectors from available cyst nematode genomes. Comparison of effector diversity between pathotypes highlights correlation with plant resistance-breaking. CONCLUSIONS: These G. rostochiensis genome resources will facilitate major advances in understanding nematode plant-parasitism. Dorsal gland promoter element-containing effectors are at the front line of the evolutionary arms race between plant and parasite and the ability to predict gland cell expression a priori promises rapid advances in understanding their roles and mechanisms of action.SE-vdA is supported by BBSRC grant BB/M014207/1. Sequencing was funded by BBSRC grant BB/F000642/1 to the University of Leeds and grant BB/F00334X/1 to the Wellcome Trust Sanger Institute). DRL was supported by a fellowship from The James Hutton Institute and the School of Biological Sciences, University of Edinburgh. GK was supported by a BBSRC PhD studentship. The James Hutton Institute receives funding from the Scottish Government. JAC and NEH are supported by the Wellcome Trust through its core funding of the Wellcome Trust Sanger Institute (grant 098051). This work was also supported by funding from the Canadian Safety and Security Program, project number CRTI09_462RD

学会抄録

Genome annotation. (XLSX 9 kb

Common variants in Alzheimer’s disease and risk stratification by polygenic risk scores

Funder: Funder: Fundación bancaria ‘La Caixa’ Number: LCF/PR/PR16/51110003 Funder: Grifols SA Number: LCF/PR/PR16/51110003 Funder: European Union/EFPIA Innovative Medicines Initiative Joint Number: 115975 Funder: JPco-fuND FP-829-029 Number: 733051061Genetic discoveries of Alzheimer's disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer's disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer's disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer's disease

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Supplement: "Localization and broadband follow-up of the gravitational-wave transient GW150914" (2016, ApJL, 826, L13)

This Supplement provides supporting material for Abbott et al. (2016a). We briefly summarize past electromagnetic (EM) follow-up efforts as well as the organization and policy of the current EM follow-up program. We compare the four probability sky maps produced for the gravitational-wave transient GW150914, and provide additional details of the EM follow-up observations that were performed in the different bands

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Search for supersymmetry in events with one lepton and multiple jets in proton-proton collisions at root s=13 TeV

Peer reviewe