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author:("holman, Peter")
1.  A pathway-based analysis provides additional support for an immune-related genetic susceptibility to Parkinson's disease 
Holmans, Peter | Moskvina, Valentina | Jones, Lesley | Sharma, Manu | Vedernikov, Alexey | Buchel, Finja | Sadd, Mohamad | Bras, Jose M. | Bettella, Francesco | Nicolaou, Nayia | Simón-Sánchez, Javier | Mittag, Florian | Gibbs, J. Raphael | Schulte, Claudia | Durr, Alexandra | Guerreiro, Rita | Hernandez, Dena | Brice, Alexis | Stefánsson, Hreinn | Majamaa, Kari | Gasser, Thomas | Heutink, Peter | Wood, Nicholas W. | Martinez, Maria | Singleton, Andrew B. | Nalls, Michael A. | Hardy, John | Morris, Huw R. | Williams, Nigel M. | Arepalli, Sampath | Barker, Roger | Barrett, Jeffrey | Ben-Shlomo, Yoav | Berendse, Henk W. | Berg, Daniela | Bhatia, Kailash | de Bie, Rob M.A. | Biffi, Alessandro | Bloem, Bas | Brice, Alexis | Bochdanovits, Zoltan | Bonin, Michael | Bras, Jose M. | Brockmann, Kathrin | Brooks, Janet | Burn, David J. | Charlesworth, Gavin | Chen, Honglei | Chinnery, Patrick F. | Chong, Sean | Clarke, Carl E. | Cookson, Mark R. | Cooper, Jonathan M. | Corvol, Jen-Christophe | Counsell, Carl | Damier, Philippe | Dartigues, Jean Francois | Deloukas, Panagiotis | Deuschl, Günther | Dexter, David T. | van Dijk, Karin D. | Dillman, Allissa | Durif, Frank | Durr, Alexandra | Edkins, Sarah | Evans, Jonathan R. | Foltynie, Thomas | Gao, Jianjun | Gardner, Michelle | Gasser, Thomas | Gibbs, J. Raphael | Goate, Alison | Gray, Emma | Guerreiro, Rita | Gústafsson, Ómar | Hardy, John | Harris, Clare | Hernandez, Dena G. | Heutink, Peter | van Hilten, Jacobus J. | Hofman, Albert | Hollenbeck, Albert | Holmans, Peter | Holton, Janice | Hu, Michele | Huber, Heiko | Hudson, Gavin | Hunt, Sarah E. | Huttenlocher, Johanna | Illig, Thomas | Langford, Cordelia | Lees, Andrew | Lesage, Suzanne | Lichtner, Peter | Limousin, Patricia | Lopez, Grisel | Lorenz, Delia | Martinez, Maria | McNeill, Alisdair | Moorby, Catriona | Moore, Matthew | Morris, Huw | Morrison, Karen E. | Moskvina, Valentina | Mudanohwo, Ese | Nalls, Michael A. | Pearson, Justin | Perlmutter, Joel S. | Pétursson, Hjörvar | Plagnol, Vincent | Pollak, Pierre | Post, Bart | Potter, Simon | Ravina, Bernard | Revesz, Tamas | Riess, Olaf | Rivadeneira, Fernando | Rizzu, Patrizia | Ryten, Mina | Saad, Mohamad | Sawcer, Stephen | Schapira, Anthony | Scheffer, Hans | Sharma, Manu | Shaw, Karen | Sheerin, Una-Marie | Shoulson, Ira | Schulte, Claudia | Sidransky, Ellen | Simón-Sánchez, Javier | Singleton, Andrew B. | Smith, Colin | Stefánsson, Hreinn | Stefánsson, Kári | Steinberg, Stacy | Stockton, Joanna D. | Sveinbjornsdottir, Sigurlaug | Talbot, Kevin | Tanner, Carlie M. | Tashakkori-Ghanbaria, Avazeh | Tison, François | Trabzuni, Daniah | Traynor, Bryan J. | Uitterlinden, André G. | Velseboer, Daan | Vidailhet, Marie | Walker, Robert | van de Warrenburg, Bart | Wickremaratchi, Mirdhu | Williams, Nigel | Williams-Gray, Caroline H. | Winder-Rhodes, Sophie | Wood, Nicholas
Human Molecular Genetics  2012;22(5):1039-1049.
Parkinson's disease (PD) is the second most common neurodegenerative disease affecting 1–2% in people >60 and 3–4% in people >80. Genome-wide association (GWA) studies have now implicated significant evidence for association in at least 18 genomic regions. We have studied a large PD-meta analysis and identified a significant excess of SNPs (P < 1 × 10−16) that are associated with PD but fall short of the genome-wide significance threshold. This result was independent of variants at the 18 previously implicated regions and implies the presence of additional polygenic risk alleles. To understand how these loci increase risk of PD, we applied a pathway-based analysis, testing for biological functions that were significantly enriched for genes containing variants associated with PD. Analysing two independent GWA studies, we identified that both had a significant excess in the number of functional categories enriched for PD-associated genes (minimum P = 0.014 and P = 0.006, respectively). Moreover, 58 categories were significantly enriched for associated genes in both GWA studies (P < 0.001), implicating genes involved in the ‘regulation of leucocyte/lymphocyte activity’ and also ‘cytokine-mediated signalling’ as conferring an increased susceptibility to PD. These results were unaltered by the exclusion of all 178 genes that were present at the 18 genomic regions previously reported to be strongly associated with PD (including the HLA locus). Our findings, therefore, provide independent support to the strong association signal at the HLA locus and imply that the immune-related genetic susceptibility to PD is likely to be more widespread in the genome than previously appreciated.
doi:10.1093/hmg/dds492
PMCID: PMC3561909  PMID: 23223016
2.  Biological Insights From 108 Schizophrenia-Associated Genetic Loci 
Ripke, Stephan | Neale, Benjamin M | Corvin, Aiden | 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 | Chan, Ronald YL | Chen, Eric YH | Cheng, Wei | Cheung, Eric FC | Chong, Siow Ann | Cloninger, C Robert | Cohen, David | Cohen, Nadine | Cormican, Paul | Craddock, Nick | Crowley, James J | Curtis, David | Davidson, Michael | Davis, Kenneth L | Degenhardt, Franziska | Del Favero, Jurgen | Demontis, Ditte | Dikeos, Dimitris | Dinan, Timothy | Djurovic, Srdjan | Donohoe, Gary | Drapeau, Elodie | Duan, Jubao | Dudbridge, Frank | Durmishi, Naser | Eichhammer, Peter | Eriksson, Johan | Escott-Price, Valentina | Essioux, Laurent | Fanous, Ayman H | Farrell, Martilias S | Frank, Josef | Franke, Lude | Freedman, Robert | Freimer, Nelson B | Friedl, Marion | Friedman, Joseph I | Fromer, Menachem | Genovese, Giulio | Georgieva, Lyudmila | Giegling, Ina | Giusti-Rodríguez, Paola | Godard, Stephanie | Goldstein, Jacqueline I | Golimbet, Vera | Gopal, Srihari | Gratten, Jacob | de Haan, Lieuwe | Hammer, Christian | Hamshere, Marian L | Hansen, Mark | Hansen, Thomas | Haroutunian, Vahram | Hartmann, Annette M | Henskens, Frans A | Herms, Stefan | Hirschhorn, Joel N | Hoffmann, Per | Hofman, Andrea | Hollegaard, Mads V | Hougaard, David M | Ikeda, Masashi | Joa, Inge | Julià, Antonio | Kahn, René S | Kalaydjieva, Luba | Karachanak-Yankova, Sena | Karjalainen, Juha | Kavanagh, David | Keller, Matthew C | Kennedy, James L | Khrunin, Andrey | Kim, Yunjung | Klovins, Janis | Knowles, James A | Konte, Bettina | Kucinskas, Vaidutis | Kucinskiene, Zita Ausrele | Kuzelova-Ptackova, Hana | Kähler, Anna K | Laurent, Claudine | Lee, Jimmy | Lee, S Hong | Legge, Sophie E | Lerer, Bernard | Li, Miaoxin | Li, Tao | Liang, Kung-Yee | Lieberman, Jeffrey | Limborska, Svetlana | Loughland, Carmel M | Lubinski, Jan | Lönnqvist, Jouko | Macek, Milan | Magnusson, Patrik KE | Maher, Brion S | Maier, Wolfgang | Mallet, Jacques | Marsal, Sara | Mattheisen, Manuel | Mattingsdal, Morten | McCarley, Robert W | McDonald, Colm | McIntosh, Andrew M | Meier, Sandra | Meijer, Carin J | Melegh, Bela | Melle, Ingrid | Mesholam-Gately, Raquelle I | Metspalu, Andres | Michie, Patricia T | Milani, Lili | Milanova, Vihra | Mokrab, Younes | Morris, Derek W | Mors, Ole | Murphy, Kieran C | Murray, Robin M | Myin-Germeys, Inez | Müller-Myhsok, Bertram | Nelis, Mari | Nenadic, Igor | Nertney, Deborah A | Nestadt, Gerald | Nicodemus, Kristin K | Nikitina-Zake, Liene | Nisenbaum, Laura | Nordin, Annelie | O’Callaghan, Eadbhard | O’Dushlaine, Colm | O’Neill, F Anthony | Oh, Sang-Yun | Olincy, Ann | Olsen, Line | Van Os, Jim | Pantelis, Christos | Papadimitriou, George N | Papiol, Sergi | Parkhomenko, Elena | Pato, Michele T | Paunio, Tiina | Pejovic-Milovancevic, Milica | Perkins, Diana O | Pietiläinen, Olli | Pimm, Jonathan | Pocklington, Andrew J | Powell, John | Price, Alkes | Pulver, Ann E | Purcell, Shaun M | Quested, Digby | Rasmussen, Henrik B | Reichenberg, Abraham | Reimers, Mark A | Richards, Alexander L | Roffman, Joshua L | Roussos, Panos | Ruderfer, Douglas M | Salomaa, Veikko | Sanders, Alan R | Schall, Ulrich | Schubert, Christian R | Schulze, Thomas G | Schwab, Sibylle G | Scolnick, Edward M | Scott, Rodney J | Seidman, Larry J | Shi, Jianxin | Sigurdsson, Engilbert | Silagadze, Teimuraz | Silverman, Jeremy M | Sim, Kang | Slominsky, Petr | Smoller, Jordan W | So, Hon-Cheong | Spencer, Chris C A | Stahl, Eli A | Stefansson, Hreinn | Steinberg, Stacy | Stogmann, Elisabeth | Straub, Richard E | Strengman, Eric | Strohmaier, Jana | Stroup, T Scott | Subramaniam, Mythily | Suvisaari, Jaana | Svrakic, Dragan M | Szatkiewicz, Jin P | Söderman, Erik | Thirumalai, Srinivas | Toncheva, Draga | Tosato, Sarah | Veijola, Juha | Waddington, John | Walsh, Dermot | Wang, Dai | Wang, Qiang | Webb, Bradley T | Weiser, Mark | Wildenauer, Dieter B | Williams, Nigel M | Williams, Stephanie | Witt, Stephanie H | Wolen, Aaron R | Wong, Emily HM | Wormley, Brandon K | Xi, Hualin Simon | Zai, Clement C | Zheng, Xuebin | Zimprich, Fritz | Wray, Naomi R | Stefansson, Kari | Visscher, Peter M | Adolfsson, Rolf | Andreassen, Ole A | Blackwood, Douglas HR | Bramon, Elvira | Buxbaum, Joseph D | Børglum, Anders D | Cichon, Sven | Darvasi, Ariel | Domenici, Enrico | Ehrenreich, Hannelore | Esko, Tõnu | Gejman, Pablo V | Gill, Michael | Gurling, Hugh | Hultman, Christina M | Iwata, Nakao | Jablensky, Assen V | Jönsson, Erik G | Kendler, Kenneth S | Kirov, George | Knight, Jo | Lencz, Todd | Levinson, Douglas F | Li, Qingqin S | Liu, Jianjun | Malhotra, Anil K | McCarroll, Steven A | McQuillin, Andrew | Moran, Jennifer L | Mortensen, Preben B | Mowry, Bryan J | Nöthen, Markus M | Ophoff, Roel A | Owen, Michael J | Palotie, Aarno | Pato, Carlos N | Petryshen, Tracey L | Posthuma, Danielle | Rietschel, Marcella | Riley, Brien P | Rujescu, Dan | Sham, Pak C | Sklar, Pamela | St Clair, David | Weinberger, Daniel R | Wendland, Jens R | Werge, Thomas | Daly, Mark J | Sullivan, Patrick F | O’Donovan, Michael C
Nature  2014;511(7510):421-427.
Summary
Schizophrenia is a highly heritable disorder. Genetic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here, we report a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain providing biological plausibility for the findings. Many findings have the potential to provide entirely novel insights into aetiology, but associations at DRD2 and multiple genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that play important roles in immunity, providing support for the hypothesized link between the immune system and schizophrenia.
doi:10.1038/nature13595
PMCID: PMC4112379  PMID: 25056061
4.  De novo mutations in schizophrenia implicate synaptic networks 
Nature  2014;506(7487):179-184.
Summary
Inherited alleles account for most of the genetic risk for schizophrenia. However, new (de novo) mutations, in the form of large chromosomal copy number changes, occur in a small fraction of cases and disproportionally disrupt genes encoding postsynaptic proteins. Here, we show that small de novo mutations, affecting one or a few nucleotides, are overrepresented among glutamatergic postsynaptic proteins comprising activity-regulated cytoskeleton-associated protein (ARC) and N-methyl-D-aspartate receptor (NMDAR) complexes. Mutations are additionally enriched in proteins that interact with these complexes to modulate synaptic strength, namely proteins regulating actin filament dynamics and those whose mRNAs are targets of fragile X mental retardation protein (FMRP). Genes affected by mutations in schizophrenia overlap those mutated in autism and intellectual disability, as do mutation-enriched synaptic pathways. Aligning our findings with a parallel case-control study, we demonstrate reproducible insights into aetiological mechanisms for schizophrenia and reveal pathophysiology shared with other neurodevelopmental disorders.
doi:10.1038/nature12929
PMCID: PMC4237002  PMID: 24463507
5.  The Role of Variation at AβPP, PSEN1, PSEN2, and MAPT in Late Onset Alzheimer’s Disease 
Gerrish, Amy | Russo, Giancarlo | Richards, Alexander | Moskvina, Valentina | Ivanov, Dobril | Harold, Denise | Sims, Rebecca | Abraham, Richard | Hollingworth, Paul | Chapman, Jade | Hamshere, Marian | Pahwa, Jaspreet Singh | Dowzell, Kimberley | Williams, Amy | Jones, Nicola | Thomas, Charlene | Stretton, Alexandra | Morgan, Angharad R. | 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 | McGuinness, Bernadette | Todd, Stephen | Johnston, Janet A. | Holmes, Clive | Mann, David | Smith, A. David | Love, Seth | Kehoe, Patrick G. | Hardy, John | Mead, Simon | Fox, Nick | Rossor, Martin | Collinge, John | Maier, Wolfgang | Jessen, Frank | Kölsch, Heike | Heun, Reinhard | Schürmann, Britta | van den Bussche, Hendrik | Heuser, Isabella | Kornhuber, Johannes | Wiltfang, Jens | Dichgans, Martin | Frölich, Lutz | Hampel, Harald | Hüll, Michael | Rujescu, Dan | Goate, Alison M. | Kauwe, John S. K. | Cruchaga, Carlos | Nowotny, Petra | Morris, John C. | Mayo, Kevin | Livingston, Gill | Bass, Nicholas J. | Gurling, Hugh | McQuillin, Andrew | Gwilliam, Rhian | Deloukas, Panagiotis | Davies, Gail | Harris, Sarah E. | Starr, John M. | Deary, Ian J. | Al-Chalabi, Ammar | Shaw, Christopher E. | Tsolaki, Magda | Singleton, Andrew B. | Guerreiro, Rita | Mühleisen, Thomas W. | Nöthen, Markus M. | Moebus, Susanne | Jöckel, Karl-Heinz | Klopp, Norman | Wichmann, H-Erich | Carrasquillo, Minerva M | Pankratz, V Shane | Younkin, Steven G. | Jones, Lesley | Holmans, Peter A. | O’Donovan, Michael C. | Owen, Michael J. | Williams, Julie
Rare mutations in AβPP, PSEN1, and PSEN2 cause uncommon early onset forms of Alzheimer’s disease (AD), and common variants in MAPT are associated with risk of other neurodegenerative disorders. We sought to establish whether common genetic variation in these genes confer risk to the common form of AD which occurs later in life (>65 years). We therefore tested single-nucleotide polymorphisms at these loci for association with late-onset AD (LOAD) in a large case-control sample consisting of 3,940 cases and 13,373 controls. Single-marker analysis did not identify any variants that reached genome-wide significance, a result which is supported by other recent genome-wide association studies. However, we did observe a significant association at the MAPT locus using a gene-wide approach (p = 0.009). We also observed suggestive association between AD and the marker rs9468, which defines the H1 haplotype, an extended haplotype that spans the MAPT gene and has previously been implicated in other neurodegenerative disorders including Parkinson’s disease, progressive supranuclear palsy, and corticobasal degeneration. In summary common variants at AβPP, PSEN1, and PSEN2 and MAPT are unlikely to make strong contributions to susceptibility for LOAD. However, the gene-wide effect observed at MAPT indicates a possible contribution to disease risk which requires further study.
doi:10.3233/JAD-2011-110824
PMCID: PMC4118466  PMID: 22027014
Alzheimer’s disease; amyloid-β protein precursor; genetics; human; MAPT protein; PSEN1 protein; PSEN2 protein
6.  De novo CNVs in bipolar affective disorder and schizophrenia 
Human Molecular Genetics  2014;23(24):6677-6683.
An increased rate of de novo copy number variants (CNVs) has been found in schizophrenia (SZ), autism and developmental delay. An increased rate has also been reported in bipolar affective disorder (BD). Here, in a larger BD sample, we aimed to replicate these findings and compare de novo CNVs between SZ and BD. We used Illumina microarrays to genotype 368 BD probands, 76 SZ probands and all their parents. Copy number variants were called by PennCNV and filtered for frequency (<1%) and size (>10 kb). Putative de novo CNVs were validated with the z-score algorithm, manual inspection of log R ratios (LRR) and qPCR probes. We found 15 de novo CNVs in BD (4.1% rate) and 6 in SZ (7.9% rate). Combining results with previous studies and using a cut-off of >100 kb, the rate of de novo CNVs in BD was intermediate between controls and SZ: 1.5% in controls, 2.2% in BD and 4.3% in SZ. Only the differences between SZ and BD and SZ and controls were significant. The median size of de novo CNVs in BD (448 kb) was also intermediate between SZ (613 kb) and controls (338 kb), but only the comparison between SZ and controls was significant. Only one de novo CNV in BD was in a confirmed SZ locus (16p11.2). Sporadic or early onset cases were not more likely to have de novo CNVs. We conclude that de novo CNVs play a smaller role in BD compared with SZ. Patients with a positive family history can also harbour de novo mutations.
doi:10.1093/hmg/ddu379
PMCID: PMC4240207  PMID: 25055870
7.  Biological Overlap of Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder: Evidence From Copy Number Variants 
Objective
Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) often co-occur and share genetic risks. The aim of this analysis was to determine more broadly whether ADHD and ASD share biological underpinnings.
Method
We compared copy number variant (CNV) data from 727 children with ADHD and 5,081 population controls to data from 996 individuals with ASD and an independent set of 1,287 controls. Using pathway analyses, we investigated whether CNVs observed in individuals with ADHD have an impact on genes in the same biological pathways as on those observed in individuals with ASD.
Results
The results suggest that the biological pathways affected by CNVs in ADHD overlap with those affected by CNVs in ASD more than would be expected by chance. Moreover, this was true even when specific CNV regions common to both disorders were excluded from the analysis. After correction for multiple testing, genes involved in 3 biological processes (nicotinic acetylcholine receptor signalling pathway, cell division, and response to drug) showed significant enrichment for case CNV hits in the combined ADHD and ASD sample.
Conclusion
The results of this study indicate the presence of significant overlap of shared biological processes disrupted by large rare CNVs in children with these 2 neurodevelopmental conditions.
doi:10.1016/j.jaac.2014.03.004
PMCID: PMC4074351  PMID: 24954825
ADHD; ASD; pathway analysis; CNVs; comorbidity
8.  Gene-Wide Analysis Detects Two New Susceptibility Genes for Alzheimer's Disease 
Escott-Price, Valentina | Bellenguez, Céline | Wang, Li-San | Choi, Seung-Hoan | Harold, Denise | Jones, Lesley | Holmans, Peter | Gerrish, Amy | Vedernikov, Alexey | Richards, Alexander | DeStefano, Anita L. | Lambert, Jean-Charles | Ibrahim-Verbaas, Carla A. | Naj, Adam C. | Sims, Rebecca | Jun, Gyungah | Bis, Joshua C. | Beecham, Gary W. | Grenier-Boley, Benjamin | Russo, Giancarlo | Thornton-Wells, Tricia A. | Denning, Nicola | Smith, Albert V. | Chouraki, Vincent | Thomas, Charlene | Ikram, M. Arfan | Zelenika, Diana | Vardarajan, Badri N. | Kamatani, Yoichiro | Lin, Chiao-Feng | Schmidt, Helena | Kunkle, Brian | Dunstan, Melanie L. | Vronskaya, Maria | Johnson, Andrew D. | Ruiz, Agustin | Bihoreau, Marie-Thérèse | Reitz, Christiane | Pasquier, Florence | Hollingworth, Paul | Hanon, Olivier | Fitzpatrick, Annette L. | Buxbaum, Joseph D. | Campion, Dominique | Crane, Paul K. | Baldwin, Clinton | Becker, Tim | Gudnason, Vilmundur | Cruchaga, Carlos | Craig, David | Amin, Najaf | Berr, Claudine | Lopez, Oscar L. | De Jager, Philip L. | Deramecourt, Vincent | Johnston, Janet A. | Evans, Denis | Lovestone, Simon | Letenneur, Luc | Hernández, Isabel | Rubinsztein, David C. | Eiriksdottir, Gudny | Sleegers, Kristel | Goate, Alison M. | Fiévet, Nathalie | Huentelman, Matthew J. | Gill, Michael | Brown, Kristelle | Kamboh, M. Ilyas | Keller, Lina | Barberger-Gateau, Pascale | McGuinness, Bernadette | Larson, Eric B. | Myers, Amanda J. | Dufouil, Carole | Todd, Stephen | Wallon, David | Love, Seth | Rogaeva, Ekaterina | Gallacher, John | George-Hyslop, Peter St | Clarimon, Jordi | Lleo, Alberto | Bayer, Anthony | Tsuang, Debby W. | Yu, Lei | Tsolaki, Magda | Bossù, Paola | Spalletta, Gianfranco | Proitsi, Petra | Collinge, John | Sorbi, Sandro | Garcia, Florentino Sanchez | Fox, Nick C. | Hardy, John | Naranjo, Maria Candida Deniz | Bosco, Paolo | Clarke, Robert | Brayne, Carol | Galimberti, Daniela | Scarpini, Elio | Bonuccelli, Ubaldo | Mancuso, Michelangelo | Siciliano, Gabriele | Moebus, Susanne | Mecocci, Patrizia | Zompo, Maria Del | Maier, Wolfgang | Hampel, Harald | Pilotto, Alberto | Frank-García, Ana | Panza, Francesco | Solfrizzi, Vincenzo | Caffarra, Paolo | Nacmias, Benedetta | Perry, William | Mayhaus, Manuel | Lannfelt, Lars | Hakonarson, Hakon | Pichler, Sabrina | Carrasquillo, Minerva M. | Ingelsson, Martin | Beekly, Duane | Alvarez, Victoria | Zou, Fanggeng | Valladares, Otto | Younkin, Steven G. | Coto, Eliecer | Hamilton-Nelson, Kara L. | Gu, Wei | Razquin, Cristina | Pastor, Pau | Mateo, Ignacio | Owen, Michael J. | Faber, Kelley M. | Jonsson, Palmi V. | Combarros, Onofre | O'Donovan, Michael C. | Cantwell, Laura B. | Soininen, Hilkka | Blacker, Deborah | Mead, Simon | Mosley, Thomas H. | Bennett, David A. | Harris, Tamara B. | Fratiglioni, Laura | Holmes, Clive | de Bruijn, Renee F. A. G. | Passmore, Peter | Montine, Thomas J. | Bettens, Karolien | Rotter, Jerome I. | Brice, Alexis | Morgan, Kevin | Foroud, Tatiana M. | Kukull, Walter A. | Hannequin, Didier | Powell, John F. | Nalls, Michael A. | Ritchie, Karen | Lunetta, Kathryn L. | Kauwe, John S. K. | Boerwinkle, Eric | Riemenschneider, Matthias | Boada, Mercè | Hiltunen, Mikko | Martin, Eden R. | Schmidt, Reinhold | Rujescu, Dan | Dartigues, Jean-François | Mayeux, Richard | Tzourio, Christophe | Hofman, Albert | Nöthen, Markus M. | Graff, Caroline | Psaty, Bruce M. | Haines, Jonathan L. | Lathrop, Mark | Pericak-Vance, Margaret A. | Launer, Lenore J. | Van Broeckhoven, Christine | Farrer, Lindsay A. | van Duijn, Cornelia M. | Ramirez, Alfredo | Seshadri, Sudha | Schellenberg, Gerard D. | Amouyel, Philippe | Williams, Julie
PLoS ONE  2014;9(6):e94661.
Background
Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 m genotypes from 25,580 Alzheimer's cases and 48,466 controls.
Principal Findings
In addition to earlier reported genes, we detected genome-wide significant loci on chromosomes 8 (TP53INP1, p = 1.4×10−6) and 14 (IGHV1-67 p = 7.9×10−8) which indexed novel susceptibility loci.
Significance
The additional genes identified in this study, have an array of functions previously implicated in Alzheimer's disease, including aspects of energy metabolism, protein degradation and the immune system and add further weight to these pathways as potential therapeutic targets in Alzheimer's disease.
doi:10.1371/journal.pone.0094661
PMCID: PMC4055488  PMID: 24922517
9.  Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer’s disease 
Lambert, Jean-Charles | Ibrahim-Verbaas, Carla A | Harold, Denise | Naj, Adam C | Sims, Rebecca | Bellenguez, Céline | Jun, Gyungah | DeStefano, Anita L | Bis, Joshua C | Beecham, Gary W | Grenier-Boley, Benjamin | Russo, Giancarlo | Thornton-Wells, Tricia A | Jones, Nicola | Smith, Albert V | Chouraki, Vincent | Thomas, Charlene | Ikram, M Arfan | Zelenika, Diana | Vardarajan, Badri N | Kamatani, Yoichiro | Lin, Chiao-Feng | Gerrish, Amy | Schmidt, Helena | Kunkle, Brian | Dunstan, Melanie L | Ruiz, Agustin | Bihoreau, Marie-Thérèse | Choi, Seung-Hoan | Reitz, Christiane | Pasquier, Florence | Hollingworth, Paul | Ramirez, Alfredo | Hanon, Olivier | Fitzpatrick, Annette L | Buxbaum, Joseph D | Campion, Dominique | Crane, Paul K | Baldwin, Clinton | Becker, Tim | Gudnason, Vilmundur | Cruchaga, Carlos | Craig, David | Amin, Najaf | Berr, Claudine | Lopez, Oscar L | De Jager, Philip L | Deramecourt, Vincent | Johnston, Janet A | Evans, Denis | Lovestone, Simon | Letenneur, Luc | Morón, Francisco J | Rubinsztein, David C | Eiriksdottir, Gudny | Sleegers, Kristel | Goate, Alison M | Fiévet, Nathalie | Huentelman, Matthew J | Gill, Michael | Brown, Kristelle | Kamboh, M Ilyas | Keller, Lina | Barberger-Gateau, Pascale | McGuinness, Bernadette | Larson, Eric B | Green, Robert | Myers, Amanda J | Dufouil, Carole | Todd, Stephen | Wallon, David | Love, Seth | Rogaeva, Ekaterina | Gallacher, John | St George-Hyslop, Peter | Clarimon, Jordi | Lleo, Alberto | Bayer, Anthony | Tsuang, Debby W | Yu, Lei | Tsolaki, Magda | Bossù, Paola | Spalletta, Gianfranco | Proitsi, Petroula | Collinge, John | Sorbi, Sandro | Sanchez-Garcia, Florentino | Fox, Nick C | Hardy, John | Deniz Naranjo, Maria Candida | Bosco, Paolo | Clarke, Robert | Brayne, Carol | Galimberti, Daniela | Mancuso, Michelangelo | Matthews, Fiona | Moebus, Susanne | Mecocci, Patrizia | Zompo, Maria Del | Maier, Wolfgang | Hampel, Harald | Pilotto, Alberto | Bullido, Maria | Panza, Francesco | Caffarra, Paolo | Nacmias, Benedetta | Gilbert, John R | Mayhaus, Manuel | Lannfelt, Lars | Hakonarson, Hakon | Pichler, Sabrina | Carrasquillo, Minerva M | Ingelsson, Martin | Beekly, Duane | Alvarez, Victoria | Zou, Fanggeng | Valladares, Otto | Younkin, Steven G | Coto, Eliecer | Hamilton-Nelson, Kara L | Gu, Wei | Razquin, Cristina | Pastor, Pau | Mateo, Ignacio | Owen, Michael J | Faber, Kelley M | Jonsson, Palmi V | Combarros, Onofre | O’Donovan, Michael C | Cantwell, Laura B | Soininen, Hilkka | Blacker, Deborah | Mead, Simon | Mosley, Thomas H | Bennett, David A | Harris, Tamara B | Fratiglioni, Laura | Holmes, Clive | de Bruijn, Renee F A G | Passmore, Peter | Montine, Thomas J | Bettens, Karolien | Rotter, Jerome I | Brice, Alexis | Morgan, Kevin | Foroud, Tatiana M | Kukull, Walter A | Hannequin, Didier | Powell, John F | Nalls, Michael A | Ritchie, Karen | Lunetta, Kathryn L | Kauwe, John S K | Boerwinkle, Eric | Riemenschneider, Matthias | Boada, Mercè | Hiltunen, Mikko | Martin, Eden R | Schmidt, Reinhold | Rujescu, Dan | Wang, Li-san | Dartigues, Jean-François | Mayeux, Richard | Tzourio, Christophe | Hofman, Albert | Nöthen, Markus M | Graff, Caroline | Psaty, Bruce M | Jones, Lesley | Haines, Jonathan L | Holmans, Peter A | Lathrop, Mark | Pericak-Vance, Margaret A | Launer, Lenore J | Farrer, Lindsay A | van Duijn, Cornelia M | Van Broeckhoven, Christine | Moskvina, Valentina | Seshadri, Sudha | Williams, Julie | Schellenberg, Gerard D | Amouyel, Philippe
Nature genetics  2013;45(12):1452-1458.
Eleven susceptibility loci for late-onset Alzheimer’s disease (LOAD) were identified by previous studies; however, a large portion of the genetic risk for this disease remains unexplained. We conducted a large, two-stage meta-analysis of genome-wide association studies (GWAS) in individuals of European ancestry. In stage 1, we used genotyped and imputed data (7,055,881 SNPs) to perform meta-analysis on 4 previously published GWAS data sets consisting of 17,008 Alzheimer’s disease cases and 37,154 controls. In stage 2,11,632 SNPs were genotyped and tested for association in an independent set of 8,572 Alzheimer’s disease cases and 11,312 controls. In addition to the APOE locus (encoding apolipoprotein E), 19 loci reached genome-wide significance (P < 5 × 10−8) in the combined stage 1 and stage 2 analysis, of which 11 are newly associated with Alzheimer’s disease.
doi:10.1038/ng.2802
PMCID: PMC3896259  PMID: 24162737
10.  Replication of bipolar disorder susceptibility alleles and identification of 2 novel genome-wide significant associations in a new bipolar disorder case-control sample 
Molecular psychiatry  2012;18(12):1302-1307.
We have conducted a genotyping study using a custom Illumina Infinium HD genotyping array, the ImmunoChip, in a new UK sample of 1,218 bipolar disorder cases and 2,913 controls that have not been used in any studies previously reported independently or in meta-analyses. The ImmunoChip was designed prior to the publication of the Psychiatric GWAS Consortium Bipolar Disorder Working Group (PGC-BD) meta-analysis data. As such 3106 SNPs with a P value less than 1×10−3 from the bipolar disorder meta-analysis by Ferreira et al., 2008 were genotyped. We report support for two of the three most strongly associated chromosomal regions in the Ferreira study, CACNA1C (rs1006737, p=4.09×10−4) and 15q14 (rs2172835, p=0.043) but not ANK3 (rs10994336, p=0.912). We have combined our ImmunoChip data (569 quasi-independent SNPs from the 3016 SNPs genotyped) with the recently published PGC-BD meta-analysis data, using either the PGC-BD combined discovery and replication data where available or just the discovery data where the SNP was not typed in a replication sample in PGC-BD. Our data provide support for two regions, at ODZ4 and CACNA1C, with prior evidence for genome-wide significant association in PGC-BD meta-analysis. In addition, the combined analysis shows two novel genome-wide significant associations. First, rs7296288 (P = 8.97 × 10−9, OR = 0.9), an intergenic polymorphism on chromosome 12 located between RHEBL1 and DHH. Secondly, rs3818253 (P = 3.88 × 10−8, OR = 1.16), an intronic SNP on chromosome 20q11.2 in the gene TRPC4AP which lies in a high linkage disequilibrium region along with the genes GSS and MYH7B.
doi:10.1038/mp.2012.142
PMCID: PMC3971368  PMID: 23070075
Bipolar disorder; genome-wide significant association; ImmunoChip; PGC-BD; rs7296288; rs3818253
12.  Genome-wide Association Analysis Identifies 14 New Risk Loci for Schizophrenia 
Nature genetics  2013;45(10):10.1038/ng.2742.
Schizophrenia is a heritable disorder with substantial public health impact. We conducted a multi-stage genome-wide association study (GWAS) for schizophrenia beginning with a Swedish national sample (5,001 cases, 6,243 controls) followed by meta-analysis with prior schizophrenia GWAS (8,832 cases, 12,067 controls) and finally by replication of SNPs in 168 genomic regions in independent samples (7,413 cases, 19,762 controls, and 581 trios). In total, 22 regions met genome-wide significance (14 novel and one previously implicated in bipolar disorder). The results strongly implicate calcium signaling in the etiology of schizophrenia, and include genome-wide significant results for CACNA1C and CACNB2 whose protein products interact. We estimate that ∼8,300 independent and predominantly common SNPs contribute to risk for schizophrenia and that these collectively account for most of its heritability. Common genetic variation plays an important role in the etiology of schizophrenia, and larger studies will allow more detailed understanding of this devastating disorder.
doi:10.1038/ng.2742
PMCID: PMC3827979  PMID: 23974872
schizophrenia; genetics; genome-wide association; meta-analysis
13.  Strong genetic evidence for a selective influence of GABAA receptors on a component of the bipolar disorder phenotype 
Molecular psychiatry  2008;15(2):146-153.
Despite compelling evidence for a major genetic contribution to risk of bipolar mood disorder, conclusive evidence implicating specific genes or pathophysiological systems has proved elusive. In part this is likely to be related to the unknown validity of current phenotype definitions and consequent aetiological heterogeneity of samples. In the recent Wellcome Trust Case Control Consortium (WTCCC) genome-wide association analysis of bipolar disorder (1868 cases, 2938 controls) one of the most strongly associated polymorphisms lay within the gene encoding the GABAA receptor β1 subunit, GABRB1. Aiming to increase biological homogeneity, we sought the diagnostic subset that showed the strongest signal at this polymorphism and used this to test for independent evidence of association with other members of the GABAA receptor gene family. The index signal was significantly enriched in the 279 cases meeting Research Diagnostic Criteria for schizoaffective disorder, bipolar type (p=3.8×10−6). Independently, these cases showed strong evidence that variation in GABAA receptor genes influences risk for this phenotype (independent system-wide p=6.6×10−5) with association signals also at GABRA4, GABRB3, GABRA5 and GABRR1. Our findings have the potential to inform understanding of presentation, pathogenesis and nosology of bipolar disorders. Our method of phenotype refinement may be useful in studies of other complex psychiatric and non-psychiatric disorders.
doi:10.1038/mp.2008.66
PMCID: PMC3967096  PMID: 19078961
14.  Pathway Analyses Implicate Glial Cells in Schizophrenia 
PLoS ONE  2014;9(2):e89441.
Background
The quest to understand the neurobiology of schizophrenia and bipolar disorder is ongoing with multiple lines of evidence indicating abnormalities of glia, mitochondria, and glutamate in both disorders. Despite high heritability estimates of 81% for schizophrenia and 75% for bipolar disorder, compelling links between findings from neurobiological studies, and findings from large-scale genetic analyses, are only beginning to emerge.
Method
Ten publically available gene sets (pathways) related to glia, mitochondria, and glutamate were tested for association to schizophrenia and bipolar disorder using MAGENTA as the primary analysis method. To determine the robustness of associations, secondary analyses were performed with: ALIGATOR, INRICH, and Set Screen. Data from the Psychiatric Genomics Consortium (PGC) were used for all analyses. There were 1,068,286 SNP-level p-values for schizophrenia (9,394 cases/12,462 controls), and 2,088,878 SNP-level p-values for bipolar disorder (7,481 cases/9,250 controls).
Results
The Glia-Oligodendrocyte pathway was associated with schizophrenia, after correction for multiple tests, according to primary analysis (MAGENTA p = 0.0005, 75% requirement for individual gene significance) and also achieved nominal levels of significance with INRICH (p = 0.0057) and ALIGATOR (p = 0.022). For bipolar disorder, Set Screen yielded nominally and method-wide significant associations to all three glial pathways, with strongest association to the Glia-Astrocyte pathway (p = 0.002).
Conclusions
Consistent with findings of white matter abnormalities in schizophrenia by other methods of study, the Glia-Oligodendrocyte pathway was associated with schizophrenia in our genomic study. These findings suggest that the abnormalities of myelination observed in schizophrenia are at least in part due to inherited factors, contrasted with the alternative of purely environmental causes (e.g. medication effects or lifestyle). While not the primary purpose of our study, our results also highlight the consequential nature of alternative choices regarding pathway analysis, in that results varied somewhat across methods, despite application to identical datasets and pathways.
doi:10.1371/journal.pone.0089441
PMCID: PMC3933626  PMID: 24586781
15.  Fine mapping of ZNF804A and genome wide significant evidence for its involvement in schizophrenia and bipolar disorder 
Molecular psychiatry  2010;16(4):429-441.
A recent genome wide association study reported evidence for association between rs1344706 within ZNF804A (encoding zinc finger protein 804A) and schizophrenia (P=1.61 ×10−7), and stronger evidence when the phenotype was broadened to include bipolar disorder (P=9.96 ×10−9). Here we provide additional evidence for association through meta-analysis of a larger dataset (schizophrenia/schizoaffective disorder N = 18945, schizophrenia plus bipolar disorder N =21274, controls N =38675). We also sought to better localize the association signal using a combination of de novo polymorphism discovery in exons, pooled de novo polymorphism discovery spanning the genomic sequence of the locus and high density LD mapping. Meta-analysis provided evidence for association between rs1344706 that surpasses widely accepted benchmarks of significance by several orders of magnitude for both schizophrenia (P=2.5 ×10−11, OR=1.10, 95% CI 1.07–1.14) and schizophrenia and bipolar disorder combined (P=4.1 ×10−13, OR=1.11, 95% CI 1.07–1.14). After de novo polymorphism discovery and detailed association analysis, rs1344706 remained the most strongly associated marker in the gene. The allelic association at the ZNF804A locus is now one of the most compelling in schizophrenia to date, and supports the accumulating data suggesting overlapping genetic risk between schizophrenia and bipolar disorder.
doi:10.1038/mp.2010.36
PMCID: PMC3918934  PMID: 20368704
17.  Genome-Wide Association Study of Clinical Dimensions of Schizophrenia: Polygenic Effect on Disorganized Symptoms 
The American journal of psychiatry  2012;169(12):1309-1317.
Objective
Multiple sources of evidence suggest that genetic factors influence variation in clinical features of schizophrenia. The authors present the first genome-wide association study (GWAS) of dimensional symptom scores among individuals with schizophrenia.
Method
Based on the Lifetime Dimensions of Psychosis Scale ratings of 2,454 case subjects of European ancestry from the Molecular Genetics of Schizophrenia (MGS) sample, three symptom factors (positive, negative/disorganized, and mood) were identified with exploratory factor analysis. Quantitative scores for each factor from a confirmatory factor analysis were analyzed for association with 696,491 single-nucleotide polymorphisms (SNPs) using linear regression, with correction for age, sex, clinical site, and ancestry. Polygenic score analysis was carried out to determine whether case and comparison subjects in 16 Psychiatric GWAS Consortium (PGC) schizophrenia samples (excluding MGS samples) differed in scores computed by weighting their genotypes by MGS association test results for each symptom factor.
Results
No genome-wide significant associations were observed between SNPs and factor scores. Most of the SNPs producing the strongest evidence for association were in or near genes involved in neurodevelopment, neuroprotection, or neurotransmission, including genes playing a role in Mendelian CNS diseases, but no statistically significant effect was observed for any defined gene pathway. Finally, polygenic scores based on MGS GWAS results for the negative/disorganized factor were significantly different between case and comparison subjects in the PGC data set; for MGS subjects, negative/ disorganized factor scores were correlated with polygenic scores generated using case-control GWAS results from the other PGC samples.
Conclusions
The polygenic signal that has been observed in cross-sample analyses of schizophrenia GWAS data sets could be in part related to genetic effects on negative and disorganized symptoms (i.e., core features of chronic schizophrenia).
doi:10.1176/appi.ajp.2012.12020218
PMCID: PMC3646712  PMID: 23212062
18.  Using genome-wide complex trait analysis to quantify ‘missing heritability’ in Parkinson's disease 
Human Molecular Genetics  2012;21(22):4996-5009.
Genome-wide association studies (GWASs) have been successful at identifying single-nucleotide polymorphisms (SNPs) highly associated with common traits; however, a great deal of the heritable variation associated with common traits remains unaccounted for within the genome. Genome-wide complex trait analysis (GCTA) is a statistical method that applies a linear mixed model to estimate phenotypic variance of complex traits explained by genome-wide SNPs, including those not associated with the trait in a GWAS. We applied GCTA to 8 cohorts containing 7096 case and 19 455 control individuals of European ancestry in order to examine the missing heritability present in Parkinson's disease (PD). We meta-analyzed our initial results to produce robust heritability estimates for PD types across cohorts. Our results identify 27% (95% CI 17–38, P = 8.08E − 08) phenotypic variance associated with all types of PD, 15% (95% CI −0.2 to 33, P = 0.09) phenotypic variance associated with early-onset PD and 31% (95% CI 17–44, P = 1.34E − 05) phenotypic variance associated with late-onset PD. This is a substantial increase from the genetic variance identified by top GWAS hits alone (between 3 and 5%) and indicates there are substantially more risk loci to be identified. Our results suggest that although GWASs are a useful tool in identifying the most common variants associated with complex disease, a great deal of common variants of small effect remain to be discovered.
doi:10.1093/hmg/dds335
PMCID: PMC3576713  PMID: 22892372
19.  Permutation-based approaches do not adequately allow for linkage disequilibrium in gene-wide multi-locus association analysis 
Additional information about risk genes or risk pathways for diseases can be extracted from genome-wide association studies through analyses of groups of markers. The most commonly employed approaches involve combining individual marker data by adding the test statistics, or summing the logarithms of their P-values, and then using permutation testing to derive empirical P-values that allow for the statistical dependence of single-marker tests arising from linkage disequilibrium (LD). In the present study, we use simulated data to show that these approaches fail to reflect the structure of the sampling error, and the effect of this is to give undue weight to correlated markers. We show that the results obtained are internally inconsistent in the presence of strong LD, and are externally inconsistent with the results derived from multi-locus analysis. We also show that the results obtained from regression and multivariate Hotelling T2 (H-T2) testing, but not those obtained from permutations, are consistent with the theoretically expected distributions, and that the H-T2 test has greater power to detect gene-wide associations in real datasets. Finally, we show that while the results from permutation testing can be made to approximate those from regression and multivariate Hotelling T2 testing through aggressive LD pruning of markers, this comes at the cost of loss of information. We conclude that when conducting multi-locus analyses of sets of single-nucleotide polymorphisms, regression or multivariate Hotelling T2 testing, which give equivalent results, are preferable to the other more commonly applied approaches.
doi:10.1038/ejhg.2012.8
PMCID: PMC3400741  PMID: 22317971
gene-wide analysis; correlated tests; GWAS
20.  Shared polygenic contribution between childhood attention-deficit hyperactivity disorder and adult schizophrenia† 
The British Journal of Psychiatry  2013;203(2):107-111.
Background
There is recent evidence of some degree of shared genetic susceptibility between adult schizophrenia and childhood attention-deficit hyperactivity disorder (ADHD) for rare chromosomal variants.
Aims
To determine whether there is overlap between common alleles conferring risk of schizophrenia in adults with those that do so for ADHD in children.
Method
We used recently published Psychiatric Genome-wide Association Study (GWAS) Consortium (PGC) adult schizophrenia data to define alleles over-represented in people with schizophrenia and tested whether those alleles were more common in 727 children with ADHD than in 2067 controls.
Results
Schizophrenia risk alleles discriminated ADHD cases from controls (P = 1.04×10–4, R2 = 0.45%); stronger discrimination was given by alleles that were risk alleles for both adult schizophrenia and adult bipolar disorder (also derived from a PGC data-set) (P = 9.98×10–6, R2 = 0.59%).
Conclusions
This increasing evidence for a small, but significant, shared genetic susceptibility between adult schizophrenia and childhood ADHD highlights the importance of research work across traditional diagnostic boundaries.
doi:10.1192/bjp.bp.112.117432
PMCID: PMC3730114  PMID: 23703318
21.  Genome-wide Association Study of Alzheimer’s disease with Psychotic Symptoms 
Molecular psychiatry  2011;17(12):1316-1327.
Psychotic symptoms occur in approximately 40% of subjects with Alzheimer’s disease (AD) and are associated with more rapid cognitive decline and increased functional deficits. They show heritability up to 61% and have been proposed as a marker for a disease subtype suitable for gene mapping efforts. We undertook a combined analysis of three genome-wide association studies (GWAS) to identify loci that a) increase susceptibility to an AD and subsequent psychotic symptoms; or b) modify risk of psychotic symptoms in the presence of neurodegeneration caused by AD. 1299 AD cases with psychosis (AD+P), 735 AD cases without psychosis (AD-P) and 5659 controls were drawn from GERAD1, the NIA-LOAD family study and the University of Pittsburgh ADRC GWAS. Unobserved genotypes were imputed to provide data on > 1.8 million SNPs. Analyses in each dataset were completed comparing a) AD+P to AD-P cases, and b) AD+P cases with controls (GERAD1, ADRC only). Aside from the APOE locus, the strongest evidence for association was observed in an intergenic region on chromosome 4 (rs753129; ‘AD+PvAD-P’ P=2.85 × 10−7; ‘AD+PvControls’ P=1.11 × 10−4). SNPs upstream of SLC2A9 (rs6834555, P=3.0×10−7) and within VSNL1 (rs4038131, P=5.9×10−7) showed strongest evidence for association with AD+P when compared to controls. These findings warrant further investigation in larger, appropriately powered samples in which the presence of psychotic symptoms in AD has been well characterised.
doi:10.1038/mp.2011.125
PMCID: PMC3272435  PMID: 22005930
Alzheimer’s disease; psychosis; behavioural symptoms; genome-wide association study; genetic
22.  Evaluation of an approximation method for assessment of overall significance of multiple dependent tests in a genome wide association study 
Genetic Epidemiology  2011;35(8):861-866.
We describe implementation of a set-based method to assess the significance of findings from genome-wide association study data. Our method, implemented in PLINK, is based on theoretical approximation of Fisher’s statistics such that the combination of p-vales at a gene or across a pathway are done in a manner that accounts for the correlation structure, or linkage disequilibrium, between SNPs. We compare our method to a permutation based product of p-values approach and show a typical correlation in excess of 0.98 for a number of comparisons. The method gives Type I error rates that are less than or equal to the corresponding nominal significance levels, making it robust to the effects of false positives. We show that in broadly similar populations, reference datasets of markers are an appropriate substrate for deriving marker-marker LD, negating the need to access individual level genotypes, greatly facilitating its generic applicability. We show that the method is thus robust to LD-associated bias and has equivalent performance to permutation-based methods, with a significantly shorter runtime. This is particularly relevant at a time of increasing public availability of significantly larger genetic datasets and should go a long way to assist in the rapid analysis of these datasets.
doi:10.1002/gepi.20636
PMCID: PMC3268180  PMID: 22006681
GWAS; set-based analysis; multiple dependent tests
23.  Genome-wide Association Study of Alzheimer’s disease with Psychotic Symptoms 
Molecular psychiatry  2011;17(12):1316-1327.
Psychotic symptoms occur in approximately 40% of subjects with Alzheimer’s disease (AD) and are associated with more rapid cognitive decline and increased functional deficits. They show heritability up to 61% and have been proposed as a marker for a disease subtype suitable for gene mapping efforts. We undertook a combined analysis of three genome-wide association studies (GWAS) to identify loci that a) increase susceptibility to an AD and subsequent psychotic symptoms; or b) modify risk of psychotic symptoms in the presence of neurodegeneration caused by AD. 1299 AD cases with psychosis (AD+P), 735 AD cases without psychosis (AD−P) and 5659 controls were drawn from GERAD1, the NIA-LOAD family study and the University of Pittsburgh ADRC GWAS. Unobserved genotypes were imputed to provide data on > 1.8 million SNPs. Analyses in each dataset were completed comparing a) AD+P to AD−P cases, and b) AD+P cases with controls (GERAD1, ADRC only). Aside from the APOE locus, the strongest evidence for association was observed in an intergenic region on chromosome 4 (rs753129; ‘AD+PvAD−P’ P=2.85 × 10−7; ‘AD+PvControls’ P=1.11 × 10−4). SNPs upstream of SLC2A9 (rs6834555, P=3.0×10−7) and within VSNL1 (rs4038131, P=5.9×10−7) showed strongest evidence for association with AD+P when compared to controls. These findings warrant further investigation in larger, appropriately powered samples in which the presence of psychotic symptoms in AD has been well characterised.
doi:10.1038/mp.2011.125
PMCID: PMC3272435  PMID: 22005930
Alzheimer’s disease; psychosis; behavioural symptoms; genome-wide association study; genetic
24.  A genome-wide study shows a limited contribution of rare copy number variants to Alzheimer's disease risk 
Human Molecular Genetics  2012;22(4):816-824.
We assessed the role of rare copy number variants (CNVs) in Alzheimer's disease (AD) using intensity data from 3260 AD cases and 1290 age-matched controls from the genome-wide association study (GWAS) conducted by the Genetic and Environmental Risk for Alzheimer's disease Consortium (GERAD). We did not observe a significant excess of rare CNVs in cases, although we did identify duplications overlapping APP and CR1 which may be pathogenic. We looked for an excess of CNVs in loci which have been highlighted in previous AD CNV studies, but did not replicate previous findings. Through pathway analyses, we observed suggestive evidence for biological overlap between single nucleotide polymorphisms and CNVs in AD susceptibility. We also identified that our sample of elderly controls harbours significantly fewer deletions >1 Mb than younger control sets in previous CNV studies on schizophrenia and bipolar disorder (P = 8.9 × 10−4 and 0.024, respectively), raising the possibility that healthy elderly individuals have a reduced rate of large deletions. Thus, in contrast to diseases such as schizophrenia, autism and attention deficit/hyperactivity disorder, CNVs do not appear to make a significant contribution to the development of AD.
doi:10.1093/hmg/dds476
PMCID: PMC3554198  PMID: 23148125
25.  Genetic Predictors of Response to Serotonergic and Noradrenergic Antidepressants in Major Depressive Disorder: A Genome-Wide Analysis of Individual-Level Data and a Meta-Analysis 
PLoS Medicine  2012;9(10):e1001326.
Testing whether genetic information could inform the selection of the best drug for patients with depression, Rudolf Uher and colleagues searched for genetic variants that could predict clinically meaningful responses to two major groups of antidepressants.
Background
It has been suggested that outcomes of antidepressant treatment for major depressive disorder could be significantly improved if treatment choice is informed by genetic data. This study aims to test the hypothesis that common genetic variants can predict response to antidepressants in a clinically meaningful way.
Methods and Findings
The NEWMEDS consortium, an academia–industry partnership, assembled a database of over 2,000 European-ancestry individuals with major depressive disorder, prospectively measured treatment outcomes with serotonin reuptake inhibiting or noradrenaline reuptake inhibiting antidepressants and available genetic samples from five studies (three randomized controlled trials, one part-randomized controlled trial, and one treatment cohort study). After quality control, a dataset of 1,790 individuals with high-quality genome-wide genotyping provided adequate power to test the hypotheses that antidepressant response or a clinically significant differential response to the two classes of antidepressants could be predicted from a single common genetic polymorphism. None of the more than half million genetic markers significantly predicted response to antidepressants overall, serotonin reuptake inhibitors, or noradrenaline reuptake inhibitors, or differential response to the two types of antidepressants (genome-wide significance p<5×10−8). No biological pathways were significantly overrepresented in the results. No significant associations (genome-wide significance p<5×10−8) were detected in a meta-analysis of NEWMEDS and another large sample (STAR*D), with 2,897 individuals in total. Polygenic scoring found no convergence among multiple associations in NEWMEDS and STAR*D.
Conclusions
No single common genetic variant was associated with antidepressant response at a clinically relevant level in a European-ancestry cohort. Effects specific to particular antidepressant drugs could not be investigated in the current study.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Genetic and environmental factors can influence a person's response to medications. Taking advantage of the recent advancements in genetics, scientists are working to match specific gene variations with responses to particular medications. Knowing whether a patient is likely to respond to a drug or have serious side effects would allow doctors to select the best treatment up front. Right now, there are only a handful of examples where a patient's version of a particular gene predicts their response to a particular drug. Some scientists believe that there will be many more such matches between genetic variants and treatment responses. Others think that because the action of most drugs is influenced by many different genes, a variant in one of those genes is unlikely to have measurable effect in most cases.
Why Was This Study Done?
One of the areas where patients' responses to available drugs vary widely is severe depression (or major depressive disorder). Prescription of an antidepressant is often the first step in treating the disease. However, less than half of patients get well taking the first antidepressant prescribed. Those who don't respond to the first drug need to, together with their doctors, try multiple courses of treatment to find the right drug and the right dose for them. For some patients none of the existing drugs work well.
To see whether genetic information could help improve the choice of antidepressant, researchers from universities and the pharmaceutical industry joined forces in this large study. They examined two ways to use genetic information to improve the treatment of depression. First, they searched all genes for common genetic variants that could predict which patients would not respond to the two major groups of antidepressants (serotonin reuptake inhibitors, or SRIs, and noradrenaline reuptake inhibitors, or NRIs). They hoped that this would help with the development of new drugs that could help these patients. Second, they looked for common genetic variants in all genes that could identify patients who responded to one of the two major groups of antidepressants. Such predictors would make it possible to know which drug to prescribe for which patient.
What Did the Researchers Do and Find?
The researchers selected 1,790 patients with severe depression who had participated in one of several research studies; 1,222 of the patients had been treated with an SRI, the remaining 568 with an NRI, and it was recorded how well the drugs worked for each patient. The researchers also had a detailed picture of the genetic make-up of each patient, with information for over half a million genetic variants. They then looked for an association between genetic variants and responses to drugs.
They found not a single genetic variant that could predict clearly whether a person would respond to antidepressants in general, to one of the two main groups (SRIs and NRIs), or much better to one than the other. They also didn't find any combination of variants in groups of genes that work together that could predict responses. Combining their data with those from another large study did not yield any robust predictors either.
What Do These Findings Mean?
This study was large enough that it should have been possible to find common genetic variants that by themselves could predict a clinically meaningful response to SRIs and/or NRIs, had such variants existed. The fact that the study failed to find such variants suggests that such variants do not exist. It is still possible, however, that variants that are less common could predict response, or that combinations of variants could. To find those, if they do exist, even larger studies will need to be done.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001326
The National Institute of General Medical Sciences at the US National Institutes of Health has a fact sheet on personalized medicine
PubMed Health at the US National Library of Medicine has a page on major depressive disorder
Wikipedia has pages on major depressive disorder and pharmacogenetics, the study of how genetic variation affects response to certain drugs (note that Wikipedia is a free online encyclopedia that anyone can edit)
The UK National Health Service has comprehensive information pages on depression
doi:10.1371/journal.pmed.1001326
PMCID: PMC3472989  PMID: 23091423

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