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1. Author Correction: Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing

Author

Kunkle, Brian W, Grenier-Boley, Benjamin, Sims, Rebecca, Bis, Joshua C, Damotte, Vincent, Naj, Adam C, Boland, Anne, Vronskaya, Maria, van der Lee, Sven J, Amlie-Wolf, Alexandre, Bellenguez, Céline, Frizatti, Aura, Chouraki, Vincent, Martin, Eden R, Sleegers, Kristel, Badarinarayan, Nandini, Jakobsdottir, Johanna, Hamilton-Nelson, Kara L, Moreno-Grau, Sonia, Olaso, Robert, Raybould, Rachel, Chen, Yuning, Kuzma, Amanda B, Hiltunen, Mikko, Morgan, Taniesha, Ahmad, Shahzad, Vardarajan, Badri N, Epelbaum, Jacques, Hoffmann, Per, Boada, Merce, Beecham, Gary W, Garnier, Jean-Guillaume, Harold, Denise, Fitzpatrick, Annette L, Valladares, Otto, Moutet, Marie-Laure, Gerrish, Amy, Smith, Albert V, Qu, Liming, Bacq, Delphine, Denning, Nicola, Jian, Xueqiu, Zhao, Yi, Del Zompo, Maria, Fox, Nick C, Choi, Seung-Hoan, Mateo, Ignacio, Hughes, Joseph T, Adams, Hieab H, Malamon, John, Sanchez-Garcia, Florentino, Patel, Yogen, Brody, Jennifer A, Dombroski, Beth A, Naranjo, Maria Candida Deniz, Daniilidou, Makrina, Eiriksdottir, Gudny, Mukherjee, Shubhabrata, Wallon, David, Uphill, James, Aspelund, Thor, Cantwell, Laura B, Garzia, Fabienne, Galimberti, Daniela, Hofer, Edith, Butkiewicz, Mariusz, Fin, Bertrand, Scarpini, Elio, Sarnowski, Chloe, Bush, Will S, Meslage, Stéphane, Kornhuber, Johannes, White, Charles C, Song, Yuenjoo, Barber, Robert C, Engelborghs, Sebastiaan, Sordon, Sabrina, Voijnovic, Dina, Adams, Perrie M, Vandenberghe, Rik, Mayhaus, Manuel, Cupples, L Adrienne, Albert, Marilyn S, De Deyn, Peter P, Gu, Wei, Himali, Jayanadra J, Beekly, Duane, Squassina, Alessio, Hartmann, Annette M, Orellana, Adelina, Blacker, Deborah, Rodriguez-Rodriguez, Eloy, Lovestone, Simon, Garcia, Melissa E, Doody, Rachelle S, Munoz-Fernadez, Carmen, Sussams, Rebecca, Lin, Honghuang, Fairchild, Thomas J, and Benito, Yolanda A

Subjects
Biochemistry and Cell Biology, Biological Sciences, Alzheimer Disease Genetics Consortium, European Alzheimer’s Disease Initiative, Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium, Genetic and Environmental Risk in AD/Defining Genetic, Polygenic and Environmental Risk for Alzheimer’s Disease Consortium, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology, Genetics
Abstract

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Published
2019

4. Population‐based identity‐by‐descent mapping combined with exome sequencing to detect rare risk variants for schizophrenia

Author

Harold, Denise, Connolly, Siobhan, Riley, Brien P, Kendler, Kenneth S, McCarthy, Shane E, McCombie, William R, Richards, Alex, Owen, Michael J, O'Donovan, Michael C, Walters, James, Donnelly, Peter, Bates, Lesley, Barroso, Ines, Blackwell, Jenefer M, Bramon, Elvira, Brown, Matthew A, Casas, Juan P, Corvin, Aiden, Deloukas, Panos, Duncanson, Audrey, Jankowski, Janusz, Markus, Hugh S, Mathew, Christopher G, Palmer, Colin NA, Plomin, Robert, Rautanen, Anna, Sawcer, Stephen J, Trembath, Richard C, Viswanathan, Ananth C, Wood, Nicholas W, Spencer, Chris CA, Band, Gavin, Bellenguez, Céline, Freeman, Colin, Hellenthal, Garrett, Giannoulatou, Eleni, Hopkins, Lucinda, Pirinen, Matti, Pearson, Richard, Strange, Amy, Su, Zhan, Vukcevic, Damjan, Langford, Cordelia, Hunt, Sarah E, Edkins, Sarah, Gwilliam, Rhian, Blackburn, Hannah, Bumpstead, Suzannah J, Dronov, Serge, Gillman, Matthew, Gray, Emma, Hammond, Naomi, Jayakumar, Alagurevathi, McCann, Owen T, Liddle, Jennifer, Potter, Simon C, Ravindrarajah, Radhi, Ricketts, Michelle, Waller, Matthew, Weston, Paul, Widaa, Sara, Whittaker, Pamela, Ripke, Stephan, Neale, Benjamin M, Walters, James TR, Farh, Kai‐How, Holmans, Peter A, Lee, Phil, Bulik‐Sullivan, Brendan, Collier, David A, Huang, Hailiang, Pers, Tune H, Agartz, Ingrid, Agerbo, Esben, Albus, Margot, Alexander, Madeline, Amin, Farooq, Bacanu, Silviu A, Begemann, Martin, Belliveau, Richard A, Bene, Judit, Bergen, Sarah E, Bevilacqua, Elizabeth, Bigdeli, Tim B, Black, Donald W, Bruggeman, Richard, Buccola, Nancy G, Buckner, Randy L, Byerley, William, Cahn, Wiepke, Cai, Guiqing, Campion, Dominique, Cantor, Rita M, Carr, Vaughan J, Carrera, Noa, Catts, Stanley V, Chambert, Kimberley D, Chan, Raymond CK, and Chan, Ronald YL

Subjects
Biological Sciences, Genetics, Clinical Research, Schizophrenia, Brain Disorders, Human Genome, Prevention, Serious Mental Illness, Mental Health, Aetiology, 2.1 Biological and endogenous factors, Adult, Case-Control Studies, Chromosome Mapping, DNA Copy Number Variations, Databases, Genetic, Exome, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Haplotypes, Humans, Male, Middle Aged, Risk Factors, Sequence Analysis, DNA, Exome Sequencing, GWAS, IBD mapping, rare variants, Wellcome Trust Case Control Consortium 2, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Clinical Sciences, Neurosciences, Clinical sciences
Abstract

Genome-wide association studies (GWASs) are highly effective at identifying common risk variants for schizophrenia. Rare risk variants are also important contributors to schizophrenia etiology but, with the exception of large copy number variants, are difficult to detect with GWAS. Exome and genome sequencing, which have accelerated the study of rare variants, are expensive so alternative methods are needed to aid detection of rare variants. Here we re-analyze an Irish schizophrenia GWAS dataset (n = 3,473) by performing identity-by-descent (IBD) mapping followed by exome sequencing of individuals identified as sharing risk haplotypes to search for rare risk variants in coding regions. We identified 45 rare haplotypes (>1 cM) that were significantly more common in cases than controls. By exome sequencing 105 haplotype carriers, we investigated these haplotypes for functional coding variants that could be tested for association in independent GWAS samples. We identified one rare missense variant in PCNT but did not find statistical support for an association with schizophrenia in a replication analysis. However, IBD mapping can prioritize both individual samples and genomic regions for follow-up analysis but genome rather than exome sequencing may be more effective at detecting risk variants on rare haplotypes.

Published
2019

5. Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing

Author

Kunkle, Brian W, Grenier-Boley, Benjamin, Sims, Rebecca, Bis, Joshua C, Damotte, Vincent, Naj, Adam C, Boland, Anne, Vronskaya, Maria, van der Lee, Sven J, Amlie-Wolf, Alexandre, Bellenguez, Céline, Frizatti, Aura, Chouraki, Vincent, Martin, Eden R, Sleegers, Kristel, Badarinarayan, Nandini, Jakobsdottir, Johanna, Hamilton-Nelson, Kara L, Moreno-Grau, Sonia, Olaso, Robert, Raybould, Rachel, Chen, Yuning, Kuzma, Amanda B, Hiltunen, Mikko, Morgan, Taniesha, Ahmad, Shahzad, Vardarajan, Badri N, Epelbaum, Jacques, Hoffmann, Per, Boada, Merce, Beecham, Gary W, Garnier, Jean-Guillaume, Harold, Denise, Fitzpatrick, Annette L, Valladares, Otto, Moutet, Marie-Laure, Gerrish, Amy, Smith, Albert V, Qu, Liming, Bacq, Delphine, Denning, Nicola, Jian, Xueqiu, Zhao, Yi, Del Zompo, Maria, Fox, Nick C, Choi, Seung-Hoan, Mateo, Ignacio, Hughes, Joseph T, Adams, Hieab H, Malamon, John, Sanchez-Garcia, Florentino, Patel, Yogen, Brody, Jennifer A, Dombroski, Beth A, Naranjo, Maria Candida Deniz, Daniilidou, Makrina, Eiriksdottir, Gudny, Mukherjee, Shubhabrata, Wallon, David, Uphill, James, Aspelund, Thor, Cantwell, Laura B, Garzia, Fabienne, Galimberti, Daniela, Hofer, Edith, Butkiewicz, Mariusz, Fin, Bertrand, Scarpini, Elio, Sarnowski, Chloe, Bush, Will S, Meslage, Stéphane, Kornhuber, Johannes, White, Charles C, Song, Yuenjoo, Barber, Robert C, Engelborghs, Sebastiaan, Sordon, Sabrina, Voijnovic, Dina, Adams, Perrie M, Vandenberghe, Rik, Mayhaus, Manuel, Cupples, L Adrienne, Albert, Marilyn S, De Deyn, Peter P, Gu, Wei, Himali, Jayanadra J, Beekly, Duane, Squassina, Alessio, Hartmann, Annette M, Orellana, Adelina, Blacker, Deborah, Rodriguez-Rodriguez, Eloy, Lovestone, Simon, Garcia, Melissa E, Doody, Rachelle S, Munoz-Fernadez, Carmen, Sussams, Rebecca, Lin, Honghuang, Fairchild, Thomas J, and Benito, Yolanda A

Subjects
Biochemistry and Cell Biology, Genetics, Biological Sciences, Neurodegenerative, Dementia, Alzheimer's Disease, Aging, Prevention, Brain Disorders, Neurosciences, Clinical Research, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Human Genome, Acquired Cognitive Impairment, 2.1 Biological and endogenous factors, Aetiology, Inflammatory and immune system, Neurological, Aged, Alzheimer Disease, Amyloid beta-Peptides, Case-Control Studies, Female, Genetic Loci, Genetic Predisposition to Disease, Genetic Testing, Genome-Wide Association Study, Haplotypes, Humans, Immunity, Lipid Metabolism, Lipids, Male, tau Proteins, Alzheimer Disease Genetics Consortium (ADGC), European Alzheimer’s Disease Initiative (EADI), Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (CHARGE), Genetic and Environmental Risk in AD/Defining Genetic, Polygenic and Environmental Risk for Alzheimer’s Disease Consortium (GERAD/PERADES), Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Risk for late-onset Alzheimer's disease (LOAD), the most prevalent dementia, is partially driven by genetics. To identify LOAD risk loci, we performed a large genome-wide association meta-analysis of clinically diagnosed LOAD (94,437 individuals). We confirm 20 previous LOAD risk loci and identify five new genome-wide loci (IQCK, ACE, ADAM10, ADAMTS1, and WWOX), two of which (ADAM10, ACE) were identified in a recent genome-wide association (GWAS)-by-familial-proxy of Alzheimer's or dementia. Fine-mapping of the human leukocyte antigen (HLA) region confirms the neurological and immune-mediated disease haplotype HLA-DR15 as a risk factor for LOAD. Pathway analysis implicates immunity, lipid metabolism, tau binding proteins, and amyloid precursor protein (APP) metabolism, showing that genetic variants affecting APP and Aβ processing are associated not only with early-onset autosomal dominant Alzheimer's disease but also with LOAD. Analyses of risk genes and pathways show enrichment for rare variants (P = 1.32 × 10-7), indicating that additional rare variants remain to be identified. We also identify important genetic correlations between LOAD and traits such as family history of dementia and education.

Published
2019

6. Analysis of shared heritability in common disorders of the brain

Author

Consortium, The Brainstorm, Anttila, Verneri, Bulik-Sullivan, Brendan, Finucane, Hilary K, Walters, Raymond K, Bras, Jose, Duncan, Laramie, Escott-Price, Valentina, Falcone, Guido J, Gormley, Padhraig, Malik, Rainer, Patsopoulos, Nikolaos A, Ripke, Stephan, Wei, Zhi, Yu, Dongmei, Lee, Phil H, Turley, Patrick, Grenier-Boley, Benjamin, Chouraki, Vincent, Kamatani, Yoichiro, Berr, Claudine, Letenneur, Luc, Hannequin, Didier, Amouyel, Philippe, Boland, Anne, Deleuze, Jean-François, Duron, Emmanuelle, Vardarajan, Badri N, Reitz, Christiane, Goate, Alison M, Huentelman, Matthew J, Kamboh, M Ilyas, Larson, Eric B, Rogaeva, Ekaterina, St George-Hyslop, Peter, Hakonarson, Hakon, Kukull, Walter A, Farrer, Lindsay A, Barnes, Lisa L, Beach, Thomas G, Demirci, F Yesim, Head, Elizabeth, Hulette, Christine M, Jicha, Gregory A, Kauwe, John SK, Kaye, Jeffrey A, Leverenz, James B, Levey, Allan I, Lieberman, Andrew P, Pankratz, Vernon S, Poon, Wayne W, Quinn, Joseph F, Saykin, Andrew J, Schneider, Lon S, Smith, Amanda G, Sonnen, Joshua A, Stern, Robert A, Van Deerlin, Vivianna M, Van Eldik, Linda J, Harold, Denise, Russo, Giancarlo, Rubinsztein, David C, Bayer, Anthony, Tsolaki, Magda, Proitsi, Petra, Fox, Nick C, Hampel, Harald, Owen, Michael J, Mead, Simon, Passmore, Peter, Morgan, Kevin, Nöthen, Markus M, Schott, Jonathan M, Rossor, Martin, Lupton, Michelle K, Hoffmann, Per, Kornhuber, Johannes, Lawlor, Brian, McQuillin, Andrew, Al-Chalabi, Ammar, Bis, Joshua C, Ruiz, Agustin, Boada, Mercè, Seshadri, Sudha, Beiser, Alexa, Rice, Kenneth, van der Lee, Sven J, De Jager, Philip L, Geschwind, Daniel H, Riemenschneider, Matthias, Riedel-Heller, Steffi, Rotter, Jerome I, Ransmayr, Gerhard, Hyman, Bradley T, Cruchaga, Carlos, Alegret, Montserrat, Winsvold, Bendik, Palta, Priit, Farh, Kai-How, and Cuenca-Leon, Ester

Subjects
Biological Sciences, Genetics, Biological Psychology, Health Sciences, Psychology, Mental Illness, Brain Disorders, Clinical Research, Human Genome, Neurosciences, Mental Health, 2.1 Biological and endogenous factors, Mental health, Neurological, Brain Diseases, Genetic Variation, Genome-Wide Association Study, Humans, Mental Disorders, Phenotype, Quantitative Trait, Heritable, Risk Factors, Brainstorm Consortium, General Science & Technology
Abstract

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

Published
2018

7. Analysis of shared heritability in common disorders of the brain.

Author

Brainstorm Consortium, Anttila, Verneri, Bulik-Sullivan, Brendan, Finucane, Hilary K, Walters, Raymond K, Bras, Jose, Duncan, Laramie, Escott-Price, Valentina, Falcone, Guido J, Gormley, Padhraig, Malik, Rainer, Patsopoulos, Nikolaos A, Ripke, Stephan, Wei, Zhi, Yu, Dongmei, Lee, Phil H, Turley, Patrick, Grenier-Boley, Benjamin, Chouraki, Vincent, Kamatani, Yoichiro, Berr, Claudine, Letenneur, Luc, Hannequin, Didier, Amouyel, Philippe, Boland, Anne, Deleuze, Jean-François, Duron, Emmanuelle, Vardarajan, Badri N, Reitz, Christiane, Goate, Alison M, Huentelman, Matthew J, Kamboh, M Ilyas, Larson, Eric B, Rogaeva, Ekaterina, St George-Hyslop, Peter, Hakonarson, Hakon, Kukull, Walter A, Farrer, Lindsay A, Barnes, Lisa L, Beach, Thomas G, Demirci, F Yesim, Head, Elizabeth, Hulette, Christine M, Jicha, Gregory A, Kauwe, John SK, Kaye, Jeffrey A, Leverenz, James B, Levey, Allan I, Lieberman, Andrew P, Pankratz, Vernon S, Poon, Wayne W, Quinn, Joseph F, Saykin, Andrew J, Schneider, Lon S, Smith, Amanda G, Sonnen, Joshua A, Stern, Robert A, Van Deerlin, Vivianna M, Van Eldik, Linda J, Harold, Denise, Russo, Giancarlo, Rubinsztein, David C, Bayer, Anthony, Tsolaki, Magda, Proitsi, Petra, Fox, Nick C, Hampel, Harald, Owen, Michael J, Mead, Simon, Passmore, Peter, Morgan, Kevin, Nöthen, Markus M, Rossor, Martin, Lupton, Michelle K, Hoffmann, Per, Kornhuber, Johannes, Lawlor, Brian, McQuillin, Andrew, Al-Chalabi, Ammar, Bis, Joshua C, Ruiz, Agustin, Boada, Mercè, Seshadri, Sudha, Beiser, Alexa, Rice, Kenneth, van der Lee, Sven J, De Jager, Philip L, Geschwind, Daniel H, Riemenschneider, Matthias, Riedel-Heller, Steffi, Rotter, Jerome I, Ransmayr, Gerhard, Hyman, Bradley T, Cruchaga, Carlos, Alegret, Montserrat, Winsvold, Bendik, Palta, Priit, Farh, Kai-How, Cuenca-Leon, Ester, and Furlotte, Nicholas

Subjects
Brainstorm Consortium, Humans, Brain Diseases, Risk Factors, Mental Disorders, Quantitative Trait, Heritable, Phenotype, Genetic Variation, Genome-Wide Association Study, Clinical Research, Neurosciences, Rare Diseases, Human Genome, Brain Disorders, Genetics, Mental Health, 2.1 Biological and endogenous factors, Mental health, Neurological, General Science & Technology
Abstract

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

Published
2018

8. Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease.

Author

Sims, Rebecca, van der Lee, Sven J, Naj, Adam C, Bellenguez, Céline, Badarinarayan, Nandini, Jakobsdottir, Johanna, Kunkle, Brian W, Boland, Anne, Raybould, Rachel, Bis, Joshua C, Martin, Eden R, Grenier-Boley, Benjamin, Heilmann-Heimbach, Stefanie, Chouraki, Vincent, Kuzma, Amanda B, Sleegers, Kristel, Vronskaya, Maria, Ruiz, Agustin, Graham, Robert R, Olaso, Robert, Hoffmann, Per, Grove, Megan L, Vardarajan, Badri N, Hiltunen, Mikko, Nöthen, Markus M, White, Charles C, Hamilton-Nelson, Kara L, Epelbaum, Jacques, Maier, Wolfgang, Choi, Seung-Hoan, Beecham, Gary W, Dulary, Cécile, Herms, Stefan, Smith, Albert V, Funk, Cory C, Derbois, Céline, Forstner, Andreas J, Ahmad, Shahzad, Li, Hongdong, Bacq, Delphine, Harold, Denise, Satizabal, Claudia L, Valladares, Otto, Squassina, Alessio, Thomas, Rhodri, Brody, Jennifer A, Qu, Liming, Sánchez-Juan, Pascual, Morgan, Taniesha, Wolters, Frank J, Zhao, Yi, Garcia, Florentino Sanchez, Denning, Nicola, Fornage, Myriam, Malamon, John, Naranjo, Maria Candida Deniz, Majounie, Elisa, Mosley, Thomas H, Dombroski, Beth, Wallon, David, Lupton, Michelle K, Dupuis, Josée, Whitehead, Patrice, Fratiglioni, Laura, Medway, Christopher, Jian, Xueqiu, Mukherjee, Shubhabrata, Keller, Lina, Brown, Kristelle, Lin, Honghuang, Cantwell, Laura B, Panza, Francesco, McGuinness, Bernadette, Moreno-Grau, Sonia, Burgess, Jeremy D, Solfrizzi, Vincenzo, Proitsi, Petra, Adams, Hieab H, Allen, Mariet, Seripa, Davide, Pastor, Pau, Cupples, L Adrienne, Price, Nathan D, Hannequin, Didier, Frank-García, Ana, Levy, Daniel, Chakrabarty, Paramita, Caffarra, Paolo, Giegling, Ina, Beiser, Alexa S, Giedraitis, Vilmantas, Hampel, Harald, Garcia, Melissa E, Wang, Xue, Lannfelt, Lars, Mecocci, Patrizia, Eiriksdottir, Gudny, Crane, Paul K, Pasquier, Florence, and Boccardi, Virginia

Subjects
ARUK Consortium, GERAD/PERADES, CHARGE, ADGC, EADI, Microglia, Humans, Alzheimer Disease, Genetic Predisposition to Disease, Adaptor Proteins, Signal Transducing, Membrane Glycoproteins, Receptors, Immunologic, Odds Ratio, Case-Control Studies, Gene Expression Profiling, Amino Acid Sequence, Sequence Homology, Amino Acid, Gene Frequency, Genotype, Linkage Disequilibrium, Polymorphism, Single Nucleotide, Phospholipase C gamma, Immunity, Innate, Protein Interaction Maps, Exome, Neurodegenerative, Brain Disorders, Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Dementia, Alzheimer's Disease, Aging, Acquired Cognitive Impairment, 2.1 Biological and endogenous factors, Developmental Biology, Biological Sciences, Medical and Health Sciences
Abstract

We identified rare coding variants associated with Alzheimer's disease in a three-stage case-control study of 85,133 subjects. In stage 1, we genotyped 34,174 samples using a whole-exome microarray. In stage 2, we tested associated variants (P < 1 × 10-4) in 35,962 independent samples using de novo genotyping and imputed genotypes. In stage 3, we used an additional 14,997 samples to test the most significant stage 2 associations (P < 5 × 10-8) using imputed genotypes. We observed three new genome-wide significant nonsynonymous variants associated with Alzheimer's disease: a protective variant in PLCG2 (rs72824905: p.Pro522Arg, P = 5.38 × 10-10, odds ratio (OR) = 0.68, minor allele frequency (MAF)cases = 0.0059, MAFcontrols = 0.0093), a risk variant in ABI3 (rs616338: p.Ser209Phe, P = 4.56 × 10-10, OR = 1.43, MAFcases = 0.011, MAFcontrols = 0.008), and a new genome-wide significant variant in TREM2 (rs143332484: p.Arg62His, P = 1.55 × 10-14, OR = 1.67, MAFcases = 0.0143, MAFcontrols = 0.0089), a known susceptibility gene for Alzheimer's disease. These protein-altering changes are in genes highly expressed in microglia and highlight an immune-related protein-protein interaction network enriched for previously identified risk genes in Alzheimer's disease. These genetic findings provide additional evidence that the microglia-mediated innate immune response contributes directly to the development of Alzheimer's disease.

Published
2017

9. Functional and positional candidate gene studies of late-onset Alzheimer's disease

Author

Harold, Denise

Subjects
616.8, QH426 Genetics, RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
Abstract

Alzheimer's disease is a neurodegenerative disorder characterised by progressive memory impairment, a decline in language function and a variety of behavioural symptoms. The majority of AD cases have an age at onset above 65 years and exhibit no clear pattern of inheritance. The only known genetic risk factor this late onset AD, LOAD, is the [Special character omitted]4 allele of the apolipoprotein E gene on chromosome 19. There is significant evidence of linkage to LOAD on chromosome 10q21-23. Therefore, nine candidate genes that map to this region were examined as susceptibility loci for the disease. In addition, a purely functional candidate, ADAM12, was examined on the basis of its homology to α-secretase enzymes, 58,752 basepairs of genomic sequence were screened by DHPLC, covering all exons, intron-exon boundaries and putative promoter regions, and 89 polymorphisms were detected. An additional 25 SNPs were identified from a SNP database. A two-stage strategy was employed. Variants were initially tested for association with AD by genotyping them in a small case-control sample, either in DNA pools or individually. Polymorphism showing a significant  difference between cases and controls were carried forward to the second stage and individually genotyped in a larger sample. A number of SNPs initially gave a positive result but after individual genotyping in a larger sample only 2 SNPs in the ADAM12 gene showed evidence for association with LOAD. As a large number of polymorphisms were examined, this may be a false positive finding, but this gene certainly warrants further investigation.

Published
2004

11. Genome-wide association interaction analysis for Alzheimer's disease

Author

Gusareva, Elena S., Carrasquillo, Minerva M., Bellenguez, Céline, Cuyvers, Elise, Colon, Samuel, Graff-Radford, Neill R., Petersen, Ronald C., Dickson, Dennis W., Mahachie John, Jestinah M., Bessonov, Kyrylo, Van Broeckhoven, Christine, Harold, Denise, Williams, Julie, Amouyel, Philippe, Sleegers, Kristel, Ertekin-Taner, Nilüfer, Lambert, Jean-Charles, and Van Steen, Kristel

Published
2014
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15. Monitoring of emerging contaminants of concern in the aquatic environment: a review of studies showing the application of effect-based measures

Author

Yusuf, Azeez, O'Flynn, Dylan, White, Blanaid, Holland, Linda, Parle-McDermott, Anne, Lawler, Jenny, McCloughlin, Thomas, Harold, Denise, Huerta, Belinda, and Regan, Fiona

Subjects
Chemical detectors, Analytical chemistry
Abstract

Water scarcity is increasingly a global cause of concern mainly due to widespread changes in climate conditions and increased consumptive water use driven by the exponential increase in population growth. In addition, increased pollution of fresh water sources due to rising production and consumption of pharmaceuticals and organic chemicals will further exacerbate this concern. Although surface water contamination by individual chemicals is often at very low concentration, pharmaceuticals for instance are designed to be efficacious at low concentrations, creating genuine concern for their presence in freshwater sources. Furthermore, the additive impact of multiple compounds may result in toxic or other biological effects that otherwise will not be induced by individual chemicals. Globally, different legislative frameworks have led to pre-emptive efforts which aim to ensure good water ecological status. Reports detailing the use and types of effect-based measures covering specific bioassay batteries that can identify specific mode of actions of chemical pollutants in the aquatic ecosystem to evaluate the real threat of pollutants to aquatic lives and ultimately human lives have recently emerged from monitoring networks such as the NORMAN network. In this review, we critically evaluate some studies within the last decade that have implemented effect-based monitoring of pharmaceuticals and organic chemicals in aquatic fauna, evaluating the occurrence of different chemical pollutants and the impact of these pollutants on aquatic fauna with special focus on pollutants that are contaminants of emerging concern (CEC) in urban wastewater. A critical discussion on studies that have used effect-based measures to assess biological impact of pharmaceutical/organic compound in the aquatic ecosystem and the endpoints measurements employed is presented. The application of effect-based monitoring of chemicals other than assessment of water quality status is also discussed.

Published
2021

17. Common polygenic variation enhances risk prediction for Alzheimer’s disease

Author

Escott-Price, Valentina, Sims, Rebecca, Bannister, Christian, Harold, Denise, Vronskaya, Maria, Majounie, Elisa, Badarinarayan, Nandini, Morgan, Kevin, Passmore, Peter, Holmes, Clive, Powell, John, Brayne, Carol, Gill, Michael, Mead, Simon, Goate, Alison, Cruchaga, Carlos, Lambert, Jean-Charles, van Duijn, Cornelia, Maier, Wolfgang, Ramirez, Alfredo, Holmans, Peter, Jones, Lesley, Hardy, John, Seshadri, Sudha, Schellenberg, Gerard D., Amouyel, Philippe, and Williams, Julie

Published
2015
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18. Rare Copy Number Variants Are Associated With Poorer Cognition in Schizophrenia

Author

Hubbard, Leon, primary, Rees, Elliott, additional, Morris, Derek W., additional, Lynham, Amy J., additional, Richards, Alex L., additional, Pardiñas, Antonio F., additional, Legge, Sophie E., additional, Harold, Denise, additional, Zammit, Stanley, additional, Corvin, Aiden C., additional, Gill, Michael G., additional, Hall, Jeremy, additional, Holmans, Peter, additional, O’Donovan, Michael C., additional, Owen, Michael J., additional, Donohoe, Gary, additional, Kirov, George, additional, Pocklington, Andrew, additional, and Walters, James T.R., additional

Published
2021
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20. Genome-wide analysis of genetic loci associated with Alzheimer disease

Author

Seshadri, Sudha, Fitzpatrick, Annette L., Ikram, M. Arfan, DeStefano, Anita L., Gudnason, Vilmundur, Boada, Merce, Bis, Joshua C., Smith, Albert V., Carrasquillo, Minerva M, Lambert, Jean Charles, Harold, Denise, Schrijvers, Elisabeth M. C., Ramirez-Lorca, Reposo, Debette, Stephanie, Longstreth, W.T. Jr., Janssens, A. Cecile J.W., Pankratz, V. Shane, Dartigues, Jean Francois, Hollingworth, Paul, Aspelund, Thor, Hernandez, Isabel, Beiser, Alexa, Kuller, Lewis H., Koudstaal, Peter J., Dickson, Dennis W., Tzourio, Christophe, Abraham, Richard, Antunez, Carmen, Yangchun Du, Rotter, Jerome I., Aulchenko, Yurii S., Harris, Tamara B., Petersen, Ronald C., Berr, Claudine, Owen, Michael J., Lopez-Arrieta, Jesus, Vardarajan, Badri N., Becker, James T., Rivadeneira, Fernando, and Nalls, Michael A

Subjects
Alzheimer's disease -- Genetic aspects, Alzheimer's disease -- Risk factors, Genetic variation -- Research
Abstract

Several genome-wide association studies are conducted to explain the additional genetic loci that are related to the Alzheimer disease (AD). The loci are shown to have no significant impact on the AD risk prediction.

Published
2010

24. Analysis of Genome-Wide Association Studies of Alzheimer Disease and of Parkinson Disease to Determine If These 2 Diseases Share a Common Genetic Risk

Author

Moskvina, Valentina, Harold, Denise, Russo, GianCarlo, Vedernikov, Alexey, Sharma, Manu, Saad, Mohamad, Holmans, Peter, Bras, Jose M., Bettella, Francesco, Keller, Margaux F., Nicolaou, Nayia, Simón-Sánchez, Javier, Gibbs, Raphael J., Schulte, Claudia, Durr, Alexandra, Guerreiro, Rita, Hernandez, Dena, Brice, Alexis, Stefánsson, Hreinn, Majamaa, Kari, Gasser, Thomas, Heutink, Peter, Wood, Nick, Martinez, Maria, Singleton, Andrew B., Nalls, Michael A., Hardy, John, Owen, Michael J., O’Donovan, Michael C., Williams, Julie, Morris, Huw R., and Williams, Nigel M.

Published
2013
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25. α-T-catenin is expressed in human brain and interacts with the Wnt signaling pathway but is not responsible for linkage to chromosome 10 in Alzheimer’s disease

Author

Busby, Victoria, Goossens, Steven, Nowotny, Petra, Hamilton, Gillian, Smemo, Scott, Harold, Denise, Turic, Dragana, Jehu, Luke, Myers, Amanda, Womick, Meredith, Woo, Daniel, Compton, Danielle, Doil, Lisa M., Tacey, Kristina M., Lau, Kit F., Al-Saraj, Safa, Killick, Richard, Pickering-Brown, Stuart, Moore, Pamela, Hollingworth, Paul, Archer, Nicola, Foy, Catherine, Walter, Sarah, Lendon, Corrine, Iwatsubo, Takeshi, Morris, John C., Norton, Joanne, Mann, David, Janssens, Barbara, Hardy, John, O’Donovan, Michael, Jones, Lesley, Williams, Julie, Holmans, Peter, Owen, Michael J., Grupe, Andrew, Powell, John, van Hengel, Jolanda, Goate, Alison, Van Roy, Frans, and Lovestone, Simon

Published
2004
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28. Sequence variation in the CHAT locus shows no association with late-onset Alzheimer's disease

Author

Harold, Denise, Peirce, Timothy, Moskvina, Valentina, Myers, Amanda, Jones, Susan, Hollingworth, Paul, Moore, Pamela, Lovestone, Simon, Powell, John, Foy, Catherine, Archer, Nicola, Walter, Sarah, Edmonson, Amanda, McIlroy, Stephen, Craig, David, Passmore, Peter A., Goate, Alison, Hardy, John, O'Donovan, Michael, Williams, Julie, Liddell, Malcolm, Owen, Michael J., and Jones, Lesley

Published
2003
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31. Missense variant in TREML2 protects against Alzheimer's disease

Author

Benitez, Bruno A., Jin, Sheng Chih, Guerreiro, Rita, Graham, Rob, Lord, Jenny, Harold, Denise, Sims, Rebecca, Lambert, Jean-Charles, Gibbs, J. Raphael, Bras, Jose, Sassi, Celeste, Harari, Oscar, Bertelsen, Sarah, Lupton, Michelle K., Powell, John, Bellenguez, Celine, Brown, Kristelle, Medway, Christopher, Haddick, Patrick CG., van der Brug, Marcel P., Bhangale, Tushar, Ortmann, Ward, Behrens, Tim, Mayeux, Richard, Pericak-Vance, Margaret A., Farrer, Lindsay A., Schellenberg, Gerard D., Haines, Jonathan L., Turton, Jim, Braae, Anne, Barber, Imelda, Fagan, Anne M., Holtzman, David M., Morris, John C., Williams, Julie, Kauwe, John S.K., Amouyel, Philippe, Morgan, Kevin, Singleton, Andy, Hardy, John, Goate, Alison M., and Cruchaga, Carlos

Published
2014
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32. No evidence that extended tracts of homozygosity are associated with Alzheimerʼs disease

Author

Sims, Rebecca, Dwyer, Sarah, Harold, Denise, Gerrish, Amy, Hollingworth, Paul, Chapman, Jade, Jones, Nicola, Abraham, Richard, Ivanov, Dobril, Pahwa, Jaspreet Singh, Moskvina, Valentina, Dowzell, Kimberley, Thomas, Charlene, Stretton, Alexandra, Lovestone, Simon, Powell, John, Proitsi, Petroula, Lupton, Michelle K., Brayne, Carol, Rubinsztein, David C., Gill, Michael, Lawlor, Brian, Lynch, Aoibhinn, Morgan, Kevin, Brown, Kristelle S., Passmore, Peter A., Craig, David, McGuiness, Bernadette, Todd, Stephen, Johnston, Janet A., Holmes, Clive, Mann, David, Smith, David A., Love, Seth, Kehoe, Patrick G., Hardy, John, Mead, Simon, Fox, Nick, Rossor, Martin, Collinge, John, Livingston, Gill, Bass, Nicholas J., Gurling, Hugh, McQuillin, Andrew, Jones, Lesley, Holmans, Peter A., OʼDonovan, Michael, Owen, Michael J., and Williams, Julie

Published
2011
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33. Meta-analysis of the Association Between Variants in SORL1 and Alzheimer Disease

Author

Reitz, Christiane, Cheng, Rong, Rogaeva, Ekaterina, Lee, Joseph H., Tokuhiro, Shinya, Zou, Fanggeng, Bettens, Karolien, Sleegers, Kristel, Tan, Eng King, Kimura, Ryo, Shibata, Nobuto, Arai, Heii, Kamboh, M. Ilyas, Prince, Jonathan A., Maier, Wolfgang, Riemenschneider, Matthias, Owen, Michael, Harold, Denise, Hollingworth, Paul, Cellini, Elena, Sorbi, Sandro, Nacmias, Benedetta, Takeda, Masatoshi, Pericak-Vance, Margaret A., Haines, Jonathan L., Younkin, Steven, Williams, Julie, van Broeckhoven, Christine, Farrer, Lindsay A., St George–Hyslop, Peter H., and Mayeux, Richard

Published
2011
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34. Identifying schizophrenia patients who carry pathogenic genetic copy number variants using standard clinical assessment: retrospective cohort study

Author

Foley, Claire, primary, Heron, Elizabeth A., additional, Harold, Denise, additional, Walters, James, additional, Owen, Michael, additional, O'Donovan, Michael, additional, Sebat, Jonathan, additional, Kelleher, Eric, additional, Mooney, Christina, additional, Durand, Amy, additional, Pinto, Carlos, additional, Cormican, Paul, additional, Morris, Derek, additional, Donohoe, Gary, additional, Gill, Michael, additional, Gallagher, Louise, additional, and Corvin, Aiden, additional

Published
2020
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36. Remapping the Insulin Gene/IDDM2 Locus in Type 1 Diabetes

Author

Barratt, Bryan J., Payne, Felicity, Lowe, Chris E., Hermann, Robert, Healy, Barry C., Harold, Denise, Concannon, Patrick, Gharani, Neda, McCarthy, Mark I., Olavesen, Mark G., McCormack, Rose, Guja, Cristian, Ionescu-Tîrgovişte, Constantin, Undlien, Dag E., Rønningen, Kjersti S., Gillespie, Kathleen M., Tuomilehto-Wolf, Eva, Tuomilehto, Jaakko, Bennett, Simon T., Clayton, David G., Cordell, Heather J., and Todd, John A.

Published
2004

37. Alzheimer's disease and age-related macular degeneration have different genetic models for complement gene variation

Author

Proitsi, Petroula, Lupton, Michelle K., Dudbridge, Frank, Tsolaki, Magda, Hamilton, Gillian, Daniilidou, Makrina, Pritchard, Megan, Lord, Kathryn, Martin, Belinda M., Craig, David, Todd, Stephen, McGuinness, Bernadette, Hollingworth, Paul, Harold, Denise, Kloszewska, Iwona, Soininen, Hilkka, Mecocci, Patrizia, Velas, Bruno, Gill, Michael, Lawlor, Brian, Rubinsztein, David C., Brayne, Carol, Passmore, Peter A., Williams, Julie, Lovestone, Simon, and Powell, John F.

Published
2012
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38. Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection

Author

Pardiñas, Antonio F, Holmans, Peter, Han, Jun, Nothen, Markus, Goate, Alison, Cruchaga, Carlos, Nowotny, Petra, Morris, John C, Mayo, Kevin, O'Donovan, Michael, Owen, Michael, Williams, Julie, Hubbard, Leon, Achilla, Evanthia, Agerbo, Esben, Barr, Cathy L, Böttger, Theresa Wimberly, Breen, Gerome, Cohen, Dan, Collier, David A, Curran, Sarah, Dempster, Emma, Dima, Danai, Lynham, Amy, Sabes-Figuera, Ramon, Flanagan, Robert J, Frangou, Sophia, Frank, Josef, Gasse, Christiane, Gaughran, Fiona, Giegling, Ina, Grove, Jakob, Hannon, Eilis, Hartmann, Annette M, Mantripragada, Kiran, Heißerer, Barbara, Helthuis, Marinka, Horsdal, Henriette Thisted, Ingimarsson, Oddur, Jollie, Karel, Kennedy, James L, Köhler, Ole, Konte, Bettina, Lang, Maren, Legge, Sophie E, Rees, Elliott, Lewis, Cathryn, MacCabe, James, Malhotra, Anil K, McCrone, Paul, Meier, Sandra M, Mill, Jonathan, Mors, Ole, Mortensen, Preben Bo, Nöthen, Markus M, O'Donovan, Michael C, MacCabe, James H, Owen, Michael J, Pedersen, Carsten B, Rietschel, Marcella, Rujescu, Dan, Schwalber, Ameli, Sigurdsson, Engilbert, Sørensen, Holger J, Spencer, Benjamin, Stefansson, Hreinn, McCarroll, Steven A, Støvring, Henrik, Strohmaier, Jana, Sullivan, Patrick, Vassos, Evangelos, Verbelen, Moira, Walters, James T R, Werge, Thomas, Baune, Bernhard T, Byrne, Enda M, Pocklington, Andrew J, Dannlowski, Udo, Eley, Thalia C, Hayward, Caroline, Martin, Nicholas G, McIntosh, Andrew M, Plomin, Robert, Porteous, David J, Wray, Naomi R, Caballero, Armando, Geschwind, Daniel H, Escott-Price, Valentina, Huckins, Laura M, Ruderfer, Douglas M, Santiago, Enrique, Sklar, Pamela, Stahl, Eli A, Won, Hyejung, Als, Thomas D, Andreassen, Ole A, Bækvad-Hansen, Marie, Ripke, Stephan, Pedersen, Carsten Bøcker, Børglum, Anders D, Bybjerg-Grauholm, Jonas, Djurovic, Srdjan, Durmishi, Naser, Pedersen, Marianne Giørtz, Golimbet, Vera, Hougaard, David M, Carrera, Noa, Mattheisen, Manuel, Molden, Espen, Nordentoft, Merete, Pejovic-Milovancevic, Milica, Silagadze, Teimuraz, Hansen, Christine Søholm, Stefansson, Kari, Steinberg, Stacy, Tosato, Sarah, Consortium, GERAD1, Consortium, CRESTAR, Kirov, George, Bishop, Sophie, Harold, Denise, Sims, Rebecca, Gerrish, Amy, Chapman, Jade, Abraham, Richard, Hollingworth, Paul, Pahwa, Jaspreet, Denning, Nicola, Cameron, Darren, Thomas, Charlene, Taylor, Sarah, Powell, John, Proitsi, Petroula, Lupton, Michelle, Lovestone, Simon, Passmore, Peter, Craig, David, McGuinness, Bernadette, Johnston, Janet, Hamshere, Marian L, Todd, Stephen, Maier, Wolfgang, Jessen, Frank, Heun, Reiner, Schurmann, Britta, Ramirez, Alfredo, Becker, Tim, Herold, Christine, Lacour, André, and Drichel, Dmitriy

Subjects
0301 basic medicine, POSITIVE SELECTION, REGULATORY ELEMENTS, LD SCORE REGRESSION, Schizophrenia (object-oriented programming), Population, LOCI, Inheritance Patterns, Genome-wide association study, VARIANTS, Biology, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, 0302 clinical medicine, Gene Frequency, ddc:570, Genetics, Journal Article, Humans, Genetic Predisposition to Disease, genetics [Schizophrenia], GENOME-WIDE ASSOCIATION, Selection, Genetic, MENTAL-ILLNESS, education, Allele frequency, Alleles, education.field_of_study, HUMAN ADAPTATION, Mechanism (biology), Background selection, Genetic architecture, genome-wide association studies, schizophrenia, genetics [Genes, Lethal], NATURAL-SELECTION, 030104 developmental biology, DE-NOVO MUTATIONS, Genetic Loci, Case-Control Studies, Schizophrenia, Genes, Lethal, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Schizophrenia is a debilitating psychiatric condition often associated with poor quality of life and decreased life expectancy. Lack of progress in improving treatment outcomes has been attributed to limited knowledge of the underlying biology, although large-scale genomic studies have begun to provide insights. We report a new genome-wide association study of schizophrenia (11,260 cases and 24,542 controls), and through meta-analysis with existing data we identify 50 novel associated loci and 145 loci in total. Through integrating genomic fine-mapping with brain expression and chromosome conformation data, we identify candidate causal genes within 33 loci. We also show for the first time that the common variant association signal is highly enriched among genes that are under strong selective pressures. These findings provide new insights into the biology and genetic architecture of schizophrenia, highlight the importance of mutation-intolerant genes and suggest a mechanism by which common risk variants persist in the population.

Published
2018

42. 43RARE COPY NUMBER VARIATIONS ARE ASSOCIATED WITH POORER COGNITION IN SCHIZOPHRENIA

Author

Hubbard, Leon, primary, Rees, Elliott, additional, Morris, Derek, additional, Lynham, Amy, additional, Legge, Sophie, additional, Harold, Denise, additional, Zammit, Stanley, additional, Corvin, Aiden, additional, Gill, Michael, additional, O'Donovan, Michael, additional, Owen, Michael, additional, Donohoe, Gary, additional, Kirov, George, additional, Pocklington, Andrew, additional, and Walters, James T.R., additional

Published
2019
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45. Quantitative Interaction Proteomics of Neurodegenerative Disease Proteins

Author

Hosp, Fabian, Vossfeldt, Hannes, Lannfelt, Lars, Holmans, Peter, O'Donovan, Michael, Owen, Michael J., Williams, Julie, Ingelsson, Martin, Lalowski, Maciej, Voigt, Aaron, Selbach, Matthias, Harold, Denise, Abraham, Richard, Hollingworth, Paul, Sims, Rebecca, Gerrish, Amy, Heinig, Matthias, Chapman, Jade, Russo, Giancarlo, Hamshere, Marian, Pahwa, Jaspreet Singh, Escott-Price, Valentina, Dowzell, Kimberley, Williams, Amy, Jones, Nicola, Thomas, Charlene, Stretton, Alexandra, Vasiljevic, Djordje, Morgan, Angharad, Lovestone, Simon, Powell, John, Proitsi, Petroula, Lupton, Michelle K., Brayne, Carol, Rubinsztein, David C., Gill, Michael, Lawlor, Brian, Lynch, Aoibhinn, Arumughan, Anup, Morgan, Kevin, Brown, Kristelle, Passmore, Peter, Craig, David, McGuinness, Bernadette, Todd, Stephen, Johnston, Janet, Holmes, Clive, Mann, David, Smith, A. David, Wyler, Emanuel, Love, Seth, Kehoe, Patrick G., Hardy, John, Mead, Simon, Fox, Nick, Rossor, Martin, Collinge, John, Maier, Wolfgang, Jessen, Frank, Heun, Reiner, Genetic and Environmental Risk for Alzheimer's Disease GERAD1 Consortium, Schürmann, Britta, Ramirez, Alfredo, Becker, Tim, Herold, Christine, Lacour, André, Drichel, Dmitriy, van den Bussche, Hendrik, Heuser, Isabella, Kornhuber, Johannes, Wiltfang, Jens, Landthaler, Markus, Dichgans, Martin, Frölich, Lutz, Hampel, Harald, Hüll, Michael, Rujescu, Dan, Goate, Alison, Kauwe, John S. K., Cruchaga, Carlos, Nowotny, Petra, Morris, John C., Hubner, Norbert, Mayo, Kevin, Livingston, Gill, Bass, Nicholas J., Gurling, Hugh, McQuillin, Andrew, Gwilliam, Rhian, Deloukas, Panagiotis, Al-Chalabi, Ammar, Shaw, Christopher E., Singleton, Andrew B., Wanker, Erich E., Guerreiro, Rita, Mühleisen, Thomas W., Nöthen, Markus M., Moebus, Susanne, Jöckel, Karl-Heinz, Klopp, Norman, Wichmann, H-Erich, Carrasquillo, Minerva M., Pankratz, V. Shane, and Younkin, Steven G.

Subjects
Proteomics, Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy), Neurodegenerative Diseases, nervous system diseases, Phenotype, lcsh:Biology (General), Cardiovascular and Metabolic Diseases, Tandem Mass Spectrometry, mental disorders, Animals, Humans, Immunoprecipitation, Function and Dysfunction of the Nervous System, lcsh:QH301-705.5, Medicinsk bioteknologi (med inriktning mot cellbiologi (inklusive stamcellsbiologi), molekylärbiologi, mikrobiologi, biokemi eller biofarmaci), Chromatography, Liquid, Genome-Wide Association Study
Abstract

SummarySeveral proteins have been linked to neurodegenerative disorders (NDDs), but their molecular function is not completely understood. Here, we used quantitative interaction proteomics to identify binding partners of Amyloid beta precursor protein (APP) and Presenilin-1 (PSEN1) for Alzheimer’s disease (AD), Huntingtin (HTT) for Huntington’s disease, Parkin (PARK2) for Parkinson’s disease, and Ataxin-1 (ATXN1) for spinocerebellar ataxia type 1. Our network reveals common signatures of protein degradation and misfolding and recapitulates known biology. Toxicity modifier screens and comparison to genome-wide association studies show that interaction partners are significantly linked to disease phenotypes in vivo. Direct comparison of wild-type proteins and disease-associated variants identified binders involved in pathogenesis, highlighting the value of differential interactome mapping. Finally, we show that the mitochondrial protein LRPPRC interacts preferentially with an early-onset AD variant of APP. This interaction appears to induce mitochondrial dysfunction, which is an early phenotype of AD.

Published
2015
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46. The Differential Influence of Immune, Endocytotic, and Lipid Metabolism Genes on Amyloid Deposition and Neurodegeneration in Subjects at Risk of Alzheimer's Disease.

Author

Femminella, Grazia Daniela, Harold, Denise, Scott, James, Williams, Julie, Edison, Paul, and Alzheimer’s Disease Neuroimaging Initiative

Subjects
*LIPID metabolism, *ALZHEIMER'S disease, *AMYLOID plaque, *AMYLOID, *MULTIPLE regression analysis, *MILD cognitive impairment
Abstract

Background: Over 20 single-nucleotide polymorphisms (SNPs) are associated with increased risk of Alzheimer's disease (AD). We categorized these loci into immunity, lipid metabolism, and endocytosis pathways, and associated the polygenic risk scores (PRS) calculated, with AD biomarkers in mild cognitive impairment (MCI) subjects.Objective: The aim of this study was to identify associations between pathway-specific PRS and AD biomarkers in patients with MCI and healthy controls.Methods: AD biomarkers ([18F]Florbetapir-PET SUVR, FDG-PET SUVR, hippocampal volume, CSF tau and amyloid-β levels) and neurocognitive tests scores were obtained in 258 healthy controls and 451 MCI subjects from the ADNI dataset at baseline and at 24-month follow up. Pathway-related (immunity, lipid metabolism, and endocytosis) and total polygenic risk scores were calculated from 20 SNPs. Multiple linear regression analysis was used to test predictive value of the polygenic risk scores over longitudinal biomarker and cognitive changes.Results: Higher immune risk score was associated with worse cognitive measures and reduced glucose metabolism. Higher lipid risk score was associated with increased amyloid deposition and cortical hypometabolism. Total, immune, and lipid scores were associated with significant changes in cognitive measures, amyloid deposition, and brain metabolism.Conclusion: Polygenic risk scores highlights the influence of specific genes on amyloid-dependent and independent pathways; and these pathways could be differentially influenced by lipid and immune scores respectively. [ABSTRACT FROM AUTHOR]

Published
2021
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47. Publisher Correction: Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection

Author

Pardiñas, Antonio F, Holmans, Peter, Han, Jun, Nothen, Markus, Goate, Alison, Cruchaga, Carlos, Nowotny, Petra, Morris, John C, Mayo, Kevin, Williams, Julie, Achilla, Evanthia, Agerbo, Esben, Hubbard, Leon, Barr, Cathy L, Böttger, Theresa Wimberly, Breen, Gerome, Cohen, Dan, Collier, David A, Curran, Sarah, Dempster, Emma, Dima, Danai, Sabes-Figuera, Ramon, Flanagan, Robert J, Lynham, Amy, Frangou, Sophia, Frank, Josef, Gasse, Christiane, Gaughran, Fiona, Giegling, Ina, Grove, Jakob, Hannon, Eilis, Hartmann, Annette M, Heißerer, Barbara, Helthuis, Marinka, Mantripragada, Kiran, Horsdal, Henriette Thisted, Ingimarsson, Oddur, Jollie, Karel, Kennedy, James L, Köhler, Ole, Konte, Bettina, Lang, Maren, Legge, Sophie E, Lewis, Cathryn, MacCabe, James, Rees, Elliott, Malhotra, Anil K, McCrone, Paul, Meier, Sandra M, Mill, Jonathan, Mors, Ole, Mortensen, Preben Bo, O'Donovan, Michael C, Owen, Michael J, Pedersen, Carsten B, MacCabe, James H, Rietschel, Marcella, Rujescu, Dan, Schwalber, Ameli, Sigurdsson, Engilbert, Sørensen, Holger J, Spencer, Benjamin, Stefansson, Hreinn, Støvring, Henrik, Strohmaier, Jana, Sullivan, Patrick, McCarroll, Steven A, Vassos, Evangelos, Verbelen, Moira, Walters, James T R, Werge, Thomas, Baune, Bernhard T, Byrne, Enda M, Pocklington, Andrew J, Dannlowski, Udo, Eley, Thalia C, Hayward, Caroline, Martin, Nicholas G, McIntosh, Andrew M, Plomin, Robert, Porteous, David J, Wray, Naomi R, Caballero, Armando, Geschwind, Daniel H, Escott-Price, Valentina, Huckins, Laura M, Ruderfer, Douglas M, Santiago, Enrique, Sklar, Pamela, Stahl, Eli A, Won, Hyejung, Als, Thomas D, Andreassen, Ole A, Bækvad-Hansen, Marie, Ripke, Stephan, Pedersen, Carsten Bøcker, Børglum, Anders D, Bybjerg-Grauholm, Jonas, Djurovic, Srdjan, Durmishi, Naser, Pedersen, Marianne Giørtz, Golimbet, Vera, Hougaard, David M, Carrera, Noa, Mattheisen, Manuel, Molden, Espen, Nordentoft, Merete, Pejovic-Milovancevic, Milica, Silagadze, Teimuraz, Hansen, Christine Søholm, Stefansson, Kari, Steinberg, Stacy, Tosato, Sarah, Consortium, GERAD1, Consortium, CRESTAR, Kirov, George, Bishop, Sophie, Harold, Denise, Sims, Rebecca, Gerrish, Amy, Chapman, Jade, Abraham, Richard, Hollingworth, Paul, Pahwa, Jaspreet, Denning, Nicola, Cameron, Darren, Thomas, Charlene, Taylor, Sarah, Powell, John, Proitsi, Petroula, Lupton, Michelle, Lovestone, Simon, Passmore, Peter, Craig, David, McGuinness, Bernadette, Johnston, Janet, Hamshere, Marian L, Todd, Stephen, Maier, Wolfgang, Jessen, Frank, Heun, Reiner, Schurmann, Britta, Ramirez, Alfredo, Becker, Tim, Herold, Christine, Lacour, Andre, and Drichel, Dmitriy

Subjects
0303 health sciences, 03 medical and health sciences, 0302 clinical medicine, ddc:570, Genetics, Biology, Humanities, 030217 neurology & neurosurgery, 030304 developmental biology
Abstract

Author(s): Pardinas, Antonio F; Holmans, Peter; Pocklington, Andrew J; Escott-Price, Valentina; Ripke, Stephan; Carrera, Noa; Legge, Sophie E; Bishop, Sophie; Cameron, Darren; Hamshere, Marian L; Han, Jun; Hubbard, Leon; Lynham, Amy; Mantripragada, Kiran; Rees, Elliott; MacCabe, James H; McCarroll, Steven A; Baune, Bernhard T; Breen, Gerome; Byrne, Enda M; Dannlowski, Udo; Eley, Thalia C; Hayward, Caroline; Martin, Nicholas G; McIntosh, Andrew M; Plomin, Robert; Porteous, David J; Wray, Naomi R; Caballero, Armando; Geschwind, Daniel H; Huckins, Laura M; Ruderfer, Douglas M; Santiago, Enrique; Sklar, Pamela; Stahl, Eli A; Won, Hyejung; Agerbo, Esben; Als, Thomas D; Andreassen, Ole A; Baekvad-Hansen, Marie; Mortensen, Preben Bo; Pedersen, Carsten Bocker; Borglum, Anders D; Bybjerg-Grauholm, Jonas; Djurovic, Srdjan; Durmishi, Naser; Pedersen, Marianne Giortz; Golimbet, Vera; Grove, Jakob; Hougaard, David M; Mattheisen, Manuel; Molden, Espen; Mors, Ole; Nordentoft, Merete; Pejovic-Milovancevic, Milica; Sigurdsson, Engilbert; Silagadze, Teimuraz; Hansen, Christine Soholm; Stefansson, Kari; Stefansson, Hreinn; Steinberg, Stacy; Tosato, Sarah; Werge, Thomas; GERAD1 Consortium; CRESTAR Consortium; Collier, David A; Rujescu, Dan; Kirov, George; Owen, Michael J; O'Donovan, Michael C; Walters, James TR | Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Published
2019

49. Shared genetic contribution to ischemic stroke and Alzheimer's disease:Ischemic Stroke and Alzheimer's Disease

Author

Traylor, Matthew, Adib-samii, Poneh, Harold, Denise, Dichgans, Martin, Williams, Julie, Lewis, Cathryn M., Markus, Hugh S., Lovestone, Simon H, and Proitsi, Petroula

Abstract

ObjectiveIncreasing evidence suggests epidemiological and pathological links between Alzheimer's disease (AD) and ischemic stroke (IS). We investigated the evidence that shared genetic factors underpin the two diseases.MethodsUsing genome-wide association study (GWAS) data from METASTROKE + (15,916 IS cases and 68,826 controls) and the International Genomics of Alzheimer's Project (IGAP; 17,008 AD cases and 37,154 controls), we evaluated known associations with AD and IS. On the subset of data for which we could obtain compatible genotype-level data (4,610 IS cases, 1,281 AD cases, and 14,320 controls), we estimated the genome-wide genetic correlation (rG) between AD and IS, and the three subtypes (cardioembolic, small vessel, and large vessel), using genome-wide single-nucleotide polymorphism (SNP) data. We then performed a meta-analysis and pathway analysis in the combined AD and small vessel stroke data sets to identify the SNPs and molecular pathways through which disease risk may be conferred.ResultsWe found evidence of a shared genetic contribution between AD and small vessel stroke (rG [standard error] = 0.37 [0.17]; p = 0.011). Conversely, there was no evidence to support shared genetic factors in AD and IS overall or with the other stroke subtypes. Of the known GWAS associations with IS or AD, none reached significance for association with the other trait (or stroke subtypes). A meta-analysis of AD IGAP and METASTROKE + small vessel stroke GWAS data highlighted a region (ATP5H/KCTD2/ICT1) associated with both diseases (p = 1.8 × 10−8). A pathway analysis identified four associated pathways involving cholesterol transport and immune response.InterpretationOur findings indicate shared genetic susceptibility to AD and small vessel stroke and highlight potential causal pathways and loci.

Published
2016

50. Common polygenic variation can predict risk of Alzheimer’s disease

Author

Escott-Price, Valentina, Sims, Rebecca, Bannister, Christian, Harold, Denise, Vronskaya, Maria, Majounie, Elisa, Badarinarayan, Nandini, Morgan, Kevin, Passmore, Peter, Holmes, Clive, Powell, John, Lovestone, Simon, Brayne, Carol, Gill, Michael, Mead, Simon, Goate, Alison, Cruchaga, Carlos, Lambert, Jean-Charles, van Duijn, Cornelia, Maier, Wolfgang, Ramirez, Alfredo, Holmans, Peter, Jones, Lesley, Hardy, John, Seshadri, Sudha, Schellenberg, Gerard D., Amouyel, Philippe, and Williams, Julie

Subjects
Alzheimer’s disease, polygenic score, predictive model
Abstract

Background: The identification of subjects at high risk for Alzheimer’s disease is important for prognosis and early intervention. We investigated the polygenic architecture of Alzheimer’s disease (AD) and the accuracy of AD prediction models, including and excluding the polygenic component in the model. Methods: This study used genotype data from the powerful dataset comprising 17,008 cases and 37,154 controls obtained from the International Genomics of Alzheimer’s Project (IGAP). Polygenic score analysis tested whether the alleles identified to associate with disease in one sample set were significantly enriched in the cases relative to the controls in an independent sample. The disease prediction accuracy was investigated by means of sensitivity, specificity, Area Under the receiver operating characteristic Curve (AUC) and positive predictive value (PPV). Results: We observed significant evidence for a polygenic component enriched in Alzheimer’s disease (p=4.9x10-26). This enrichment remained significant after APOE and other genome-wide associated regions were excluded (p=3.4x10 19). The best prediction accuracy AUC=78% was achieved by a logistic regression model with APOE, the polygenic score as predictors and age. When looking at the genetic component only, the PPV was 81%, increasing to 82% when age was added as a predictor. Setting the total normalised polygenic score of greater than 0.91, the positive predictive value has reached 90%. Conclusion: Polygenic score has strong predictive utility of Alzheimer’s disease risk and is a valuable research tool in experimental designs, e.g. for selecting Alzheimer’s disease patients into clinical trials.

Published
2015

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