14 research outputs found
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.The present work has been performed as part of the doctoral program of I. de Rojas at the
Universitat de Barcelona (Barcelona, Spain) supported by national grant from the
Instituto de Salud Carlos III FI20/00215. The Genome Research @ FundaciĂł ACE project
(GR@ACE) is supported by Grifols SA, Fundación bancaria “La Caixa”, Fundació ACE,
and CIBERNED. A.R. and M.B. receive support from the European Union/EFPIA
Innovative Medicines Initiative Joint undertaking ADAPTED and MOPEAD projects
(grant numbers 115975 and 115985, respectively). M.B. and A.R. are also supported by
national grants PI13/02434, PI16/01861, PI17/01474, PI19/01240 and PI19/01301.
Acción Estratégica en Salud is integrated into the Spanish National R + D + I Plan and
funded by ISCIII (Instituto de Salud Carlos III)—Subdirección General de Evaluación
and the Fondo Europeo de Desarrollo Regional (FEDER—“Una manera de hacer
Europa”). The Alzheimer Center Amsterdam is supported by Stichting
Alzheimer Nederland and Stichting VUmc fonds. The clinical database structure was
developed with funding from Stichting Dioraphte. Genotyping of the Dutch case-control
samples was performed in the context of EADB (European Alzheimer DNA biobank)
funded by the JPco-fuND FP-829-029 (ZonMW project number 733051061). 100-Plus
study. This work was supported by Stichting Alzheimer
Nederland (WE09.2014-03), Stichting Diorapthe, horstingstuit foundation, Memorabel
(ZonMW project number 733050814, 733050512) and Stichting VUmc Fonds. Genotyping of the 100-Plus Study was performed in the context of EADB (European Alzheimer DNA biobank) funded by the JPco-fuND FP-829-029 (ZonMW project numb 733051061). Longitudinal Aging Study Amsterdam (LASA) is largely supported by a
grant from the Netherlands Ministry of Health, Welfare and Sports, Directorate of LongTerm Care. This work was supported by a
grant (European Alzheimer DNA BioBank, EADB) from the EU Joint Program—Neurodegenerative Disease Research (JPND) and also funded by Inserm, Institut Pasteur de
Lille, the Lille Métropole Communauté Urbaine, the French government’s LABEX
DISTALZ program (development of innovative strategies for a transdisciplinary
approach to AD). Genotyping of the German case-control samples was performed in the
context of EADB (European Alzheimer DNA biobank) funded by the JPco-fuND
(German Federal Ministry of Education and Research, BMBF: 01ED1619A). The i–Select chips was funded by the French National Foundation on AD and
related disorders. EADI was supported by the LABEX (laboratory of excellence program
investment for the future) DISTALZ grant, Inserm, Institut Pasteur de Lille, Université
de Lille 2 and the Lille University Hospital. GERAD was supported by the Medical
Research Council (Grant n° 503480), Alzheimer’s Research UK (Grant n° 503176), the
Wellcome Trust (Grant n° 082604/2/07/Z) and German Federal Ministry of Education
and Research (BMBF): Competence Network Dementia (CND) grant n° 01GI0102,
01GI0711, 01GI0420. CHARGE was partly supported by the NIA/NHLBI grants
AG049505, AG058589, HL105756 and AGES contract N01–AG–12100, the Icelandic
Heart Association, and the Erasmus Medical Center and Erasmus University. ADGC was
supported by the NIH/NIA grants: U01 AG032984, U24 AG021886, U01 AG016976, and
the Alzheimer’s Association grant ADGC–10–19672
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.Peer reviewe
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Gene-Based Analysis in HRC Imputed Genome Wide Association Data Identifies Three Novel Genes For Alzheimer’s Disease
A novel POLARIS gene-based analysis approach was employed to compute gene-based polygenic risk score (PRS) for all individuals in the latest HRC imputed GERAD (N cases=3,332 and N controls=9,832) data using the International Genomics of Alzheimer’s Project summary statistics (N cases=13,676 and N controls=27,322, excluding GERAD subjects) to identify the SNPs and weight their risk alleles for the PRS score. SNPs were assigned to known, protein coding genes using GENCODE (v19). SNPs are assigned using both 1) no window around the gene and 2) a window of 35kb upstream and 10kb downstream to include transcriptional regulatory elements. The overall association of a gene is determined using a logistic regression model, adjusting for population covariates. Three novel gene-wide significant genes were determined from the POLARIS gene-based analysis using a gene window; PPARGC1A, RORA and ZNF423 . The ZNF423 gene resides in an Alzheimer’s disease (AD)-specific protein network which also includes other AD-related genes. The PPARGC1A gene has been linked to energy metabolism and the generation of amyloid beta plaques and the RORA has strong links with genes which are differentially expressed in the hippocampus. We also demonstrate no enrichment for genes in either loss of function intolerant or conserved noncoding sequence regions
Body Mass Index and Risk of Alzheimer’s Disease: A Mendelian Randomization Study of 399,536 Individuals
Molecular Basis for Increased Risk for Late-onset Alzheimer Disease Due to the Naturally Occurring L28P Mutation in Apolipoprotein E4
Replicative association analysis of genetic markers of cognitive traits with Alzheimer’s disease in the Russian population
Genome-wide haplotype association study identifies the FRMD4A gene as a risk locus for Alzheimer’s disease.
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.</p
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