Dataset Information

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

ABSTRACT: 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.

SUBMITTER: de Rojas I

PROVIDER: S-EPMC8184987 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

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

de Rojas Itziar I Moreno-Grau Sonia S Tesi Niccolo N Grenier-Boley Benjamin B Andrade Victor V Jansen Iris E IE Pedersen Nancy L NL Stringa Najada N Zettergren Anna A Hernández Isabel I Montrreal Laura L Antúnez Carmen C Antonell Anna A Tankard Rick M RM Bis Joshua C JC Sims Rebecca R Bellenguez Céline C Quintela Inés I González-Perez Antonio A Calero Miguel M Franco-Macías Emilio E Macías Juan J Blesa Rafael R Cervera-Carles Laura L Menéndez-González Manuel M Frank-García Ana A Royo Jose Luís JL Moreno Fermin F Huerto Vilas Raquel R Baquero Miquel M Diez-Fairen Mónica M Lage Carmen C García-Madrona Sebastián S García-González Pablo P Alarcón-Martín Emilio E Valero Sergi S Sotolongo-Grau Oscar O Ullgren Abbe A Naj Adam C AC Lemstra Afina W AW Benaque Alba A Pérez-Cordón Alba A Benussi Alberto A Rábano Alberto A Padovani Alessandro A Squassina Alessio A de Mendonça Alexandre A Arias Pastor Alfonso A Kok Almar A L AAL Meggy Alun A Pastor Ana Belén AB Espinosa Ana A Corma-Gómez Anaïs A Martín Montes Angel A Sanabria Ángela Á DeStefano Anita L AL Schneider Anja A Haapasalo Annakaisa A Kinhult Ståhlbom Anne A Tybjærg-Hansen Anne A Hartmann Annette M AM Spottke Annika A Corbatón-Anchuelo Arturo A Rongve Arvid A Borroni Barbara B Arosio Beatrice B Nacmias Benedetta B Nordestgaard Børge G BG Kunkle Brian W BW Charbonnier Camille C Abdelnour Carla C Masullo Carlo C Martínez Rodríguez Carmen C Muñoz-Fernandez Carmen C Dufouil Carole C Graff Caroline C Ferreira Catarina B CB Chillotti Caterina C Reynolds Chandra A CA Fenoglio Chiara C Van Broeckhoven Christine C Clark Christopher C Pisanu Claudia C Satizabal Claudia L CL Holmes Clive C Buiza-Rueda Dolores D Aarsland Dag D Rujescu Dan D Alcolea Daniel D Galimberti Daniela D Wallon David D Seripa Davide D Grünblatt Edna E Dardiotis Efthimios E Düzel Emrah E Scarpini Elio E Conti Elisa E Rubino Elisa E Gelpi Ellen E Rodriguez-Rodriguez Eloy E Duron Emmanuelle E Boerwinkle Eric E Ferri Evelyn E Tagliavini Fabrizio F Küçükali Fahri F Pasquier Florence F Sanchez-Garcia Florentino F Mangialasche Francesca F Jessen Frank F Nicolas Gaël G Selbæk Geir G Ortega Gemma G Chêne Geneviève G Hadjigeorgiou Georgios G Rossi Giacomina G Rossi Giacomina G Spalletta Gianfranco G Giaccone Giorgio G Grande Giulia G Binetti Giuliano G Papenberg Goran G Hampel Harald H Bailly Henri H Zetterberg Henrik H Soininen Hilkka H Karlsson Ida K IK Alvarez Ignacio I Appollonio Ildebrando I Giegling Ina I Skoog Ingmar I Saltvedt Ingvild I Rainero Innocenzo I Rosas Allende Irene I Hort Jakub J Diehl-Schmid Janine J Van Dongen Jasper J Vidal Jean-Sebastien JS Lehtisalo Jenni J Wiltfang Jens J Thomassen Jesper Qvist JQ Kornhuber Johannes J Haines Jonathan L JL Vogelgsang Jonathan J Pineda Juan A JA Fortea Juan J Popp Julius J Deckert Jürgen J Buerger Katharina K Morgan Kevin K Fließbach Klaus K Sleegers Kristel K Molina-Porcel Laura L Kilander Lena L Weinhold Leonie L Farrer Lindsay A LA Wang Li-San LS Kleineidam Luca L Farotti Lucia L Parnetti Lucilla L Tremolizzo Lucio L Hausner Lucrezia L Benussi Luisa L Froelich Lutz L Ikram M Arfan MA Deniz-Naranjo M Candida MC Tsolaki Magda M Rosende-Roca Maitée M Löwenmark Malin M Hulsman Marc M Spallazzi Marco M Pericak-Vance Margaret A MA Esiri Margaret M Bernal Sánchez-Arjona María M Dalmasso Maria Carolina MC Martínez-Larrad María Teresa MT Arcaro Marina M Nöthen Markus M MM Fernández-Fuertes Marta M Dichgans Martin M Ingelsson Martin M Herrmann Martin J MJ Scherer Martin M Vyhnalek Martin M Kosmidis Mary H MH Yannakoulia Mary M Schmid Matthias M Ewers Michael M Heneka Michael T MT Wagner Michael M Scamosci Michela M Kivipelto Miia M Hiltunen Mikko M Zulaica Miren M Alegret Montserrat M Fornage Myriam M Roberto Natalia N van Schoor Natasja M NM Seidu Nazib M NM Banaj Nerisa N Armstrong Nicola J NJ Scarmeas Nikolaos N Scherbaum Norbert N Goldhardt Oliver O Hanon Oliver O Peters Oliver O Skrobot Olivia Anna OA Quenez Olivier O Lerch Ondrej O Bossù Paola P Caffarra Paolo P Dionigi Rossi Paolo P Sakka Paraskevi P Mecocci Patrizia P Hoffmann Per P Holmans Peter A PA Fischer Peter P Riederer Peter P Yang Qiong Q Marshall Rachel R Kalaria Rajesh N RN Mayeux Richard R Vandenberghe Rik R Cecchetti Roberta R Ghidoni Roberta R Frikke-Schmidt Ruth R Sorbi Sandro S Hägg Sara S Engelborghs Sebastiaan S Helisalmi Seppo S Botne Sando Sigrid S Kern Silke S Archetti Silvana S Boschi Silvia S Fostinelli Silvia S Gil Silvia S Mendoza Silvia S Mead Simon S Ciccone Simona S Djurovic Srdjan S Heilmann-Heimbach Stefanie S Riedel-Heller Steffi S Kuulasmaa Teemu T Del Ser Teodoro T Lebouvier Thibaud T Polak Thomas T Ngandu Tiia T Grimmer Timo T Bessi Valentina V Escott-Price Valentina V Giedraitis Vilmantas V Deramecourt Vincent V Maier Wolfgang W Jian Xueqiu X Pijnenburg Yolande A L YAL Kehoe Patrick Gavin PG Garcia-Ribas Guillermo G Sánchez-Juan Pascual P Pastor Pau P Pérez-Tur Jordi J Piñol-Ripoll Gerard G Lopez de Munain Adolfo A García-Alberca Jose María JM Bullido María J MJ Álvarez Victoria V Lleó Alberto A Real Luis M LM Mir Pablo P Medina Miguel M Medina Miguel M Scheltens Philip P Holstege Henne H Marquié Marta M Sáez María Eugenia ME Carracedo Ángel Á Amouyel Philippe P Schellenberg Gerard D GD Williams Julie J Seshadri Sudha S van Duijn Cornelia M CM Mather Karen A KA Mather Karen A KA Sánchez-Valle Raquel R Serrano-Ríos Manuel M Orellana Adelina A Tárraga Lluís L Blennow Kaj K Huisman Martijn M Andreassen Ole A OA Andreassen Ole A OA Posthuma Danielle D Clarimón Jordi J Boada Mercè M van der Flier Wiesje M WM Ramirez Alfredo A Lambert Jean-Charles JC van der Lee Sven J SJ Ruiz Agustín A

Nature communications 20210607 1

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, PRKD ...[more]

PMID: 34099642

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Project description:ObjectiveGenome-wide association studies (GWAS) have identified over 30 susceptibility loci associated with Alzheimer's disease (AD). Using AD GWAS data from the International Genomics of Alzheimer's Project (IGAP), Polygenic Risk Score (PRS) was successfully applied to predict life time risk of AD development. A recently introduced Polygenic Hazard Score (PHS) is able to quantify individuals with age-specific genetic risk for AD. The aim of this study was to quantify the age-specific genetic risk for AD with PRS and compare the results generated by PRS with those from PHS.MethodsQuantification of individual differences in age-specific genetic risk for AD identified by the PRS, was performed with Cox Regression on 9903 (2626 cases and 7277 controls) individuals from the Genetic and Environmental Risk in Alzheimer's Disease consortium (GERAD). Polygenic Hazard Scores were generated for the same individuals. The age-specific genetic risk for AD identified by the PRS was compared with that generated by the PHS. This was repeated using varying SNPs P-value thresholds for disease association.ResultsPolygenic Risk Score significantly predicted the risk associated with age at AD onset when SNPs were preselected for association to AD at P ≤ 0.001. The strongest effect (B = 0.28, SE = 0.04, P = 2.5 × 10-12) was observed for PRS based upon genome-wide significant SNPs (P ≤ 5 × 10-8). The strength of association was weaker with less stringent SNP selection thresholds.InterpretationBoth PRS and PHS can be used to predict an age-specific risk for developing AD. The PHS approach uses SNP effect sizes derived with the Cox Proportional Hazard Regression model. When SNPs were selected based upon AD GWAS case/control P ≤ 10-3, we found no advantage of using SNP effects sizes calculated with the Cox Proportional Hazard Regression model in our study. When SNPs are selected for association with AD risk at P > 10-3, the age-specific risk prediction results are not significant for either PRS or PHS. However PHS could be more advantageous than PRS of age specific AD risk predictions when SNPs are prioritized for association with AD age at onset (i.e., powerful Cox Regression GWAS study).

Project description:The treatment of complex and multifactorial diseases constitutes a big challenge in day-to-day clinical practice. As many parameters influence clinical phenotypes, accurate diagnosis and prompt therapeutic management is often difficult. Significant research and investment focuses on state-of-the-art genomic and metagenomic analyses in the burgeoning field of Precision (or Personalized) Medicine with genome-wide-association-studies (GWAS) helping in this direction by linking patient genotypes at specific polymorphic sites (single-nucleotide polymorphisms, SNPs) to the specific phenotype. The generation of polygenic risk scores (PRSs) is a relatively novel statistical method that associates the collective genotypes at many of a person's SNPs to a trait or disease. As GWAS sample sizes increase, PRSs may become a powerful tool for prevention, early diagnosis and treatment. However, the complexity and multidimensionality of genetic and environmental contributions to phenotypes continue to pose significant challenges for the clinical, broad-scale use of PRSs. To improve the value of PRS measures, we propose a novel pipeline which might better utilize GWAS results and improve the utility of PRS when applied to Alzheimer's Disease (AD), as a paradigm of multifactorial disease with existing large GWAS datasets that have not yet achieved significant clinical impact. We propose a refined approach for the construction of AD PRS improved by (1), taking into consideration the genetic loci where the SNPs are located, (2) evaluating the post-translational impact of SNPs on coding and non-coding regions by focusing on overlap with open chromatin data and SNPs that are expression quantitative trait loci (QTLs), and (3) scoring and annotating the severity of the associated clinical phenotype into the PRS. Open chromatin and eQTL data need to be carefully selected based on tissue/cell type of origin (e.g., brain, excitatory neurons). Applying such filters to traditional PRS on GWAS studies of complex diseases like AD, can produce a set of SNPs weighted according to our algorithm and a more useful PRS. Our proposed methodology may pave the way for new applications of genomic machine and deep learning pipelines to GWAS datasets in an effort to identify novel clinically useful genetic biomarkers for complex diseases like AD.

Dataset Information

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

Publications

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

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