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1.  Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis 
Sawcer, Stephen | Hellenthal, Garrett | Pirinen, Matti | Spencer, Chris C.A. | Patsopoulos, Nikolaos A. | Moutsianas, Loukas | Dilthey, Alexander | Su, Zhan | Freeman, Colin | Hunt, Sarah E. | Edkins, Sarah | Gray, Emma | Booth, David R. | Potter, Simon C. | Goris, An | Band, Gavin | Oturai, Annette Bang | Strange, Amy | Saarela, Janna | Bellenguez, Céline | Fontaine, Bertrand | Gillman, Matthew | Hemmer, Bernhard | Gwilliam, Rhian | Zipp, Frauke | Jayakumar, Alagurevathi | Martin, Roland | Leslie, Stephen | Hawkins, Stanley | Giannoulatou, Eleni | D’alfonso, Sandra | Blackburn, Hannah | Boneschi, Filippo Martinelli | Liddle, Jennifer | Harbo, Hanne F. | Perez, Marc L. | Spurkland, Anne | Waller, Matthew J | Mycko, Marcin P. | Ricketts, Michelle | Comabella, Manuel | Hammond, Naomi | Kockum, Ingrid | McCann, Owen T. | Ban, Maria | Whittaker, Pamela | Kemppinen, Anu | Weston, Paul | Hawkins, Clive | Widaa, Sara | Zajicek, John | Dronov, Serge | Robertson, Neil | Bumpstead, Suzannah J. | Barcellos, Lisa F. | Ravindrarajah, Rathi | Abraham, Roby | Alfredsson, Lars | Ardlie, Kristin | Aubin, Cristin | Baker, Amie | Baker, Katharine | Baranzini, Sergio E. | Bergamaschi, Laura | Bergamaschi, Roberto | Bernstein, Allan | Berthele, Achim | Boggild, Mike | Bradfield, Jonathan P. | Brassat, David | Broadley, Simon A. | Buck, Dorothea | Butzkueven, Helmut | Capra, Ruggero | Carroll, William M. | Cavalla, Paola | Celius, Elisabeth G. | Cepok, Sabine | Chiavacci, Rosetta | Clerget-Darpoux, Françoise | Clysters, Katleen | Comi, Giancarlo | Cossburn, Mark | Cournu-Rebeix, Isabelle | Cox, Mathew B. | Cozen, Wendy | Cree, Bruce A.C. | Cross, Anne H. | Cusi, Daniele | Daly, Mark J. | Davis, Emma | de Bakker, Paul I.W. | Debouverie, Marc | D’hooghe, Marie Beatrice | Dixon, Katherine | Dobosi, Rita | Dubois, Bénédicte | Ellinghaus, David | Elovaara, Irina | Esposito, Federica | Fontenille, Claire | Foote, Simon | Franke, Andre | Galimberti, Daniela | Ghezzi, Angelo | Glessner, Joseph | Gomez, Refujia | Gout, Olivier | Graham, Colin | Grant, Struan F.A. | Guerini, Franca Rosa | Hakonarson, Hakon | Hall, Per | Hamsten, Anders | Hartung, Hans-Peter | Heard, Rob N. | Heath, Simon | Hobart, Jeremy | Hoshi, Muna | Infante-Duarte, Carmen | Ingram, Gillian | Ingram, Wendy | Islam, Talat | Jagodic, Maja | Kabesch, Michael | Kermode, Allan G. | Kilpatrick, Trevor J. | Kim, Cecilia | Klopp, Norman | Koivisto, Keijo | Larsson, Malin | Lathrop, Mark | Lechner-Scott, Jeannette S. | Leone, Maurizio A. | Leppä, Virpi | Liljedahl, Ulrika | Bomfim, Izaura Lima | Lincoln, Robin R. | Link, Jenny | Liu, Jianjun | Lorentzen, Åslaug R. | Lupoli, Sara | Macciardi, Fabio | Mack, Thomas | Marriott, Mark | Martinelli, Vittorio | Mason, Deborah | McCauley, Jacob L. | Mentch, Frank | Mero, Inger-Lise | Mihalova, Tania | Montalban, Xavier | Mottershead, John | Myhr, Kjell-Morten | Naldi, Paola | Ollier, William | Page, Alison | Palotie, Aarno | Pelletier, Jean | Piccio, Laura | Pickersgill, Trevor | Piehl, Fredrik | Pobywajlo, Susan | Quach, Hong L. | Ramsay, Patricia P. | Reunanen, Mauri | Reynolds, Richard | Rioux, John D. | Rodegher, Mariaemma | Roesner, Sabine | Rubio, Justin P. | Rückert, Ina-Maria | Salvetti, Marco | Salvi, Erika | Santaniello, Adam | Schaefer, Catherine A. | Schreiber, Stefan | Schulze, Christian | Scott, Rodney J. | Sellebjerg, Finn | Selmaj, Krzysztof W. | Sexton, David | Shen, Ling | Simms-Acuna, Brigid | Skidmore, Sheila | Sleiman, Patrick M.A. | Smestad, Cathrine | Sørensen, Per Soelberg | Søndergaard, Helle Bach | Stankovich, Jim | Strange, Richard C. | Sulonen, Anna-Maija | Sundqvist, Emilie | Syvänen, Ann-Christine | Taddeo, Francesca | Taylor, Bruce | Blackwell, Jenefer M. | Tienari, Pentti | Bramon, Elvira | Tourbah, Ayman | Brown, Matthew A. | Tronczynska, Ewa | Casas, Juan P. | Tubridy, Niall | Corvin, Aiden | Vickery, Jane | Jankowski, Janusz | Villoslada, Pablo | Markus, Hugh S. | Wang, Kai | Mathew, Christopher G. | Wason, James | Palmer, Colin N.A. | Wichmann, H-Erich | Plomin, Robert | Willoughby, Ernest | Rautanen, Anna | Winkelmann, Juliane | Wittig, Michael | Trembath, Richard C. | Yaouanq, Jacqueline | Viswanathan, Ananth C. | Zhang, Haitao | Wood, Nicholas W. | Zuvich, Rebecca | Deloukas, Panos | Langford, Cordelia | Duncanson, Audrey | Oksenberg, Jorge R. | Pericak-Vance, Margaret A. | Haines, Jonathan L. | Olsson, Tomas | Hillert, Jan | Ivinson, Adrian J. | De Jager, Philip L. | Peltonen, Leena | Stewart, Graeme J. | Hafler, David A. | Hauser, Stephen L. | McVean, Gil | Donnelly, Peter | Compston, Alastair
Nature  2011;476(7359):214-219.
Multiple sclerosis (OMIM 126200) is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability.1 Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals;2,3 and systematic attempts to identify linkage in multiplex families have confirmed that variation within the Major Histocompatibility Complex (MHC) exerts the greatest individual effect on risk.4 Modestly powered Genome-Wide Association Studies (GWAS)5-10 have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects play a key role in disease susceptibility.11 Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the Class I region. Immunologically relevant genes are significantly over-represented amongst those mapping close to the identified loci and particularly implicate T helper cell differentiation in the pathogenesis of multiple sclerosis.
doi:10.1038/nature10251
PMCID: PMC3182531  PMID: 21833088
multiple sclerosis; GWAS; genetics
2.  Genome-wide association study of ankylosing spondylitis identifies non-MHC susceptibility loci 
Nature genetics  2010;42(2):123-127.
To identify susceptibility loci for ankylosing spondylitis, we undertook a genome-wide association study in 2,053 unrelated ankylosing spondylitis cases among people of European descent and 5,140 ethnically matched controls, with replication in an independent cohort of 898 ankylosing spondylitis cases and 1,518 controls. Cases were genotyped with Illumina HumHap370 genotyping chips. In addition to strong association with the major histocompatibility complex (MHC; P < 10−800), we found association with SNPs in two gene deserts at 2p15 (rs10865331; combined P = 1.9 × 10−19) and 21q22 (rs2242944; P = 8.3 × 10−20), as well as in the genes ANTXR2 (rs4333130; P = 9.3 × 10−8) and IL1R2 (rs2310173; P = 4.8 × 10−7). We also replicated previously reported associations at IL23R (rs11209026; P = 9.1 × 10−14) and ERAP1 (rs27434; P = 5.3 × 10−12). This study reports four genetic loci associated with ankylosing spondylitis risk and identifies a major role for the interleukin (IL)-23 and IL-1 cytokine pathways in disease susceptibility.
doi:10.1038/ng.513
PMCID: PMC3224997  PMID: 20062062
3.  Genome-wide and fine-resolution association analysis of malaria in West Africa 
Jallow, Muminatou | Teo, Yik Ying | Small, Kerrin S | Rockett, Kirk A | Deloukas, Panos | Clark, Taane G | Kivinen, Katja | Bojang, Kalifa A | Conway, David J | Pinder, Margaret | Sirugo, Giorgio | Sisay-Joof, Fatou | Usen, Stanley | Auburn, Sarah | Bumpstead, Suzannah J | Campino, Susana | Coffey, Alison | Dunham, Andrew | Fry, Andrew E | Green, Angela | Gwilliam, Rhian | Hunt, Sarah E | Inouye, Michael | Jeffreys, Anna E | Mendy, Alieu | Palotie, Aarno | Potter, Simon | Ragoussis, Jiannis | Rogers, Jane | Rowlands, Kate | Somaskantharajah, Elilan | Whittaker, Pamela | Widden, Claire | Donnelly, Peter | Howie, Bryan | Marchini, Jonathan | Morris, Andrew | SanJoaquin, Miguel | Achidi, Eric Akum | Agbenyega, Tsiri | Allen, Angela | Amodu, Olukemi | Corran, Patrick | Djimde, Abdoulaye | Dolo, Amagana | Doumbo, Ogobara K | Drakeley, Chris | Dunstan, Sarah | Evans, Jennifer | Farrar, Jeremy | Fernando, Deepika | Hien, Tran Tinh | Horstmann, Rolf D | Ibrahim, Muntaser | Karunaweera, Nadira | Kokwaro, Gilbert | Koram, Kwadwo A | Lemnge, Martha | Makani, Julie | Marsh, Kevin | Michon, Pascal | Modiano, David | Molyneux, Malcolm E | Mueller, Ivo | Parker, Michael | Peshu, Norbert | Plowe, Christopher V | Puijalon, Odile | Reeder, John | Reyburn, Hugh | Riley, Eleanor M | Sakuntabhai, Anavaj | Singhasivanon, Pratap | Sirima, Sodiomon | Tall, Adama | Taylor, Terrie E | Thera, Mahamadou | Troye-Blomberg, Marita | Williams, Thomas N | Wilson, Michael | Kwiatkowski, Dominic P
Nature genetics  2009;41(6):657-665.
We report a genome-wide association (GWA) study of severe malaria in The Gambia. The initial GWA scan included 2,500 children genotyped on the Affymetrix 500K GeneChip, and a replication study included 3,400 children. We used this to examine the performance of GWA methods in Africa. We found considerable population stratification, and also that signals of association at known malaria resistance loci were greatly attenuated owing to weak linkage disequilibrium (LD). To investigate possible solutions to the problem of low LD, we focused on the HbS locus, sequencing this region of the genome in 62 Gambian individuals and then using these data to conduct multipoint imputation in the GWA samples. This increased the signal of association, from P = 4 × 10−7 to P = 4 × 10−14, with the peak of the signal located precisely at the HbS causal variant. Our findings provide proof of principle that fine-resolution multipoint imputation, based on population-specific sequencing data, can substantially boost authentic GWA signals and enable fine mapping of causal variants in African populations.
doi:10.1038/ng.388
PMCID: PMC2889040  PMID: 19465909
4.  Population-Specific Risk of Type 2 Diabetes Conferred by HNF4A P2 Promoter Variants 
Diabetes  2008;57(11):3161-3165.
OBJECTIVE—Single nucleotide polymorphisms (SNPs) in the P2 promoter region of HNF4A were originally shown to be associated with predisposition for type 2 diabetes in Finnish, Ashkenazi, and, more recently, Scandinavian populations, but they generated conflicting results in additional populations. We aimed to investigate whether data from a large-scale mapping approach would replicate this association in novel Ashkenazi samples and in U.K. populations and whether these data would allow us to refine the association signal.
RESEARCH DESIGN AND METHODS—Using a dense linkage disequilibrium map of 20q, we selected SNPs from a 10-Mb interval centered on HNF4A. In a staged approach, we first typed 4,608 SNPs in case-control populations from four U.K. populations and an Ashkenazi population (n = 2,516). In phase 2, a subset of 763 SNPs was genotyped in 2,513 additional samples from the same populations.
RESULTS—Combined analysis of both phases demonstrated association between HNF4A P2 SNPs (rs1884613 and rs2144908) and type 2 diabetes in the Ashkenazim (n = 991; P < 1.6 × 10−6). Importantly, these associations are significant in a subset of Ashkenazi samples (n = 531) not previously tested for association with P2 SNPs (odds ratio [OR] ∼1.7; P < 0.002), thus providing replication within the Ashkenazim. In the U.K. populations, this association was not significant (n = 4,022; P > 0.5), and the estimate for the OR was much smaller (OR 1.04; [95%CI 0.91–1.19]).
CONCLUSIONS—These data indicate that the risk conferred by HNF4A P2 is significantly different between U.K. and Ashkenazi populations (P < 0.00007), suggesting that the underlying causal variant remains unidentified. Interactions with other genetic or environmental factors may also contribute to this difference in risk between populations.
doi:10.2337/db08-0719
PMCID: PMC2570416  PMID: 18728231
5.  The brain-derived neurotrophic factor rs6265 (Val66Met) polymorphism and depression in Mexican-Americans 
Neuroreport  2007;18(12):1291-1293.
The hypothesis that brain-derived neurotrophic factor (BDNF) is involved in the pathogenesis of major depression is supported by several research findings; however, genetic studies assessing the relationship between BDNF and psychiatric disorders have produced conflicting results.We examined the effect of a BDNF polymorphism on depression susceptibility in Mexican-Americans.The single nucleotide polymorphism (Val66Met), which has been shown to have functional and behavioral effects, was genotyped in 284 depressed participants and 331 controls, showing association with depression (P=0.005). Individuals homozygous for the major allele (GG) had an increased chance of being depressed (OR=1.7 95% CI 1.17-2.47).Our findings support the association of BDNF single nucleotide polymorphism rs6265 and depression, suggesting that this polymorphism may increase susceptibility to major depression in Mexican-Americans.
doi:10.1097/WNR.0b013e328273bcb0
PMCID: PMC2686836  PMID: 17632285
BDNF (brain derived neurotrophic factor); major depressive disorder; Mexican-Americans; pharmacogenetics; polymorphism; psychiatry; single nucleotide polymorphism; rs6265; Val66Met
6.  Population-Specific Risk of Type 2 Diabetes Conferred by HNF4A P2 Promoter Variants 
Diabetes  2008;57(11):3161-3165.
OBJECTIVE
Single nucleotide polymorphisms (SNPs) in the P2 promoter region of HNF4A were originally shown to be associated with predisposition for type 2 diabetes in Finnish, Ashkenazi, and, more recently, Scandinavian populations, but they generated conflicting results in additional populations. We aimed to investigate whether data from a large-scale mapping approach would replicate this association in novel Ashkenazi samples and in U.K. populations and whether these data would allow us to refine the association signal.
RESEARCH DESIGN AND METHODS
Using a dense linkage disequilibrium map of 20q, we selected SNPs from a 10-Mb interval centered on HNF4A. In a staged approach, we first typed 4,608 SNPs in case-control populations from four U.K. populations and an Ashkenazi population (n = 2,516). In phase 2, a subset of 763 SNPs was genotyped in 2,513 additional samples from the same populations.
RESULTS
Combined analysis of both phases demonstrated association between HNF4A P2 SNPs (rs1884613 and rs2144908) and type 2 diabetes in the Ashkenazim (n = 991; P < 1.6 × 10−6). Importantly, these associations are significant in a subset of Ashkenazi samples (n = 531) not previously tested for association with P2 SNPs (odds ratio [OR] ~1.7; P < 0.002), thus providing replication within the Ashkenazim. In the U.K. populations, this association was not significant (n = 4,022; P > 0.5), and the estimate for the OR was much smaller (OR 1.04; [95%CI 0.91-1.19]).
CONCLUSIONS
These data indicate that the risk conferred by HNF4A P2 is significantly different between U.K. and Ashkenazi populations (P < 0.00007), suggesting that the underlying causal variant remains unidentified. Interactions with other genetic or environmental factors may also contribute to this difference in risk between populations.
doi:10.2337/db08-0719
PMCID: PMC2570416  PMID: 18728231
7.  A high resolution HLA and SNP haplotype map for disease association studies in the extended human MHC 
Nature genetics  2006;38(10):1166-1172.
The proteins encoded by the classical HLA class I and class II genes in the major histocompatibility complex (MHC) are highly polymorphic and play an essential role in self/non-self immune recognition. HLA variation is a crucial determinant of transplant rejection and susceptibility to a large number of infectious and autoimmune disease1. Yet identification of causal variants is problematic due to linkage disequilibrium (LD) that extends across multiple HLA and non-HLA genes in the MHC2,3. We therefore set out to characterize the LD patterns between the highly polymorphic HLA genes and background variation by typing the classical HLA genes and >7,500 common single nucleotide polymorphisms (SNPs) and deletion/insertion polymorphisms (DIPs) across four population samples. The analysis provides informative tag SNPs that capture some of the variation in the MHC region and that could be used in initial disease association studies, and provides new insight into the evolutionary dynamics and ancestral origins of the HLA loci and their haplotypes.
doi:10.1038/ng1885
PMCID: PMC2670196  PMID: 16998491
8.  A Genome-Wide Association Study Confirms VKORC1, CYP2C9, and CYP4F2 as Principal Genetic Determinants of Warfarin Dose 
PLoS Genetics  2009;5(3):e1000433.
We report the first genome-wide association study (GWAS) whose sample size (1,053 Swedish subjects) is sufficiently powered to detect genome-wide significance (p<1.5×10−7) for polymorphisms that modestly alter therapeutic warfarin dose. The anticoagulant drug warfarin is widely prescribed for reducing the risk of stroke, thrombosis, pulmonary embolism, and coronary malfunction. However, Caucasians vary widely (20-fold) in the dose needed for therapeutic anticoagulation, and hence prescribed doses may be too low (risking serious illness) or too high (risking severe bleeding). Prior work established that ∼30% of the dose variance is explained by single nucleotide polymorphisms (SNPs) in the warfarin drug target VKORC1 and another ∼12% by two non-synonymous SNPs (*2, *3) in the cytochrome P450 warfarin-metabolizing gene CYP2C9. We initially tested each of 325,997 GWAS SNPs for association with warfarin dose by univariate regression and found the strongest statistical signals (p<10−78) at SNPs clustering near VKORC1 and the second lowest p-values (p<10−31) emanating from CYP2C9. No other SNPs approached genome-wide significance. To enhance detection of weaker effects, we conducted multiple regression adjusting for known influences on warfarin dose (VKORC1, CYP2C9, age, gender) and identified a single SNP (rs2108622) with genome-wide significance (p = 8.3×10−10) that alters protein coding of the CYP4F2 gene. We confirmed this result in 588 additional Swedish patients (p<0.0029) and, during our investigation, a second group provided independent confirmation from a scan of warfarin-metabolizing genes. We also thoroughly investigated copy number variations, haplotypes, and imputed SNPs, but found no additional highly significant warfarin associations. We present power analysis of our GWAS that is generalizable to other studies, and conclude we had 80% power to detect genome-wide significance for common causative variants or markers explaining at least 1.5% of dose variance. These GWAS results provide further impetus for conducting large-scale trials assessing patient benefit from genotype-based forecasting of warfarin dose.
Author Summary
Recently, geneticists have begun assaying hundreds of thousands of genetic markers covering the entire human genome to systematically search for and identify genes that cause disease. We have extended this “genome-wide association study” (GWAS) method by assaying ∼326,000 markers in 1,053 Swedish patients in order to identify genes that alter response to the anticoagulant drug warfarin. Warfarin is widely prescribed to reduce blood clotting in order to protect high-risk patients from stroke, thrombosis, and heart attack. But patients vary widely (20-fold) in the warfarin dose needed for proper blood thinning, which means that initial doses in some patients are too high (risking severe bleeding) or too low (risking serious illness). Our GWAS detected two genes (VKORC1, CYP2C9) already known to cause ∼40% of the variability in warfarin dose and discovered a new gene (CYP4F2) contributing 1%–2% of the variability. Since our GWAS searched the entire genome, additional genes having a major influence on warfarin dose might not exist or be found in the near-term. Hence, clinical trials assessing patient benefit from individualized dose forecasting based on a patient's genetic makeup at VKORC1, CYP2C9 and possibly CYP4F2 could provide state-of-the-art clinical benchmarks for warfarin use during the foreseeable future.
doi:10.1371/journal.pgen.1000433
PMCID: PMC2652833  PMID: 19300499
9.  Common variants in the region around Osterix are associated with bone mineral density and growth in childhood 
Human Molecular Genetics  2009;18(8):1510-1517.
Peak bone mass achieved in adolescence is a determinant of bone mass in later life. In order to identify genetic variants affecting bone mineral density (BMD), we performed a genome-wide association study of BMD and related traits in 1518 children from the Avon Longitudinal Study of Parents and Children (ALSPAC). We compared results with a scan of 134 adults with high or low hip BMD. We identified associations with BMD in an area of chromosome 12 containing the Osterix (SP7) locus, a transcription factor responsible for regulating osteoblast differentiation (ALSPAC: P = 5.8 × 10−4; Australia: P = 3.7 × 10−4). This region has previously shown evidence of association with adult hip and lumbar spine BMD in an Icelandic population, as well as nominal association in a UK population. A meta-analysis of these existing studies revealed strong association between SNPs in the Osterix region and adult lumbar spine BMD (P = 9.9 × 10−11). In light of these findings, we genotyped a further 3692 individuals from ALSPAC who had whole body BMD and confirmed the association in children as well (P = 5.4 × 10−5). Moreover, all SNPs were related to height in ALSPAC children, but not weight or body mass index, and when height was included as a covariate in the regression equation, the association with total body BMD was attenuated. We conclude that genetic variants in the region of Osterix are associated with BMD in children and adults probably through primary effects on growth.
doi:10.1093/hmg/ddp052
PMCID: PMC2664147  PMID: 19181680

Results 1-9 (9)