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A Two-Stage Meta-Analysis Identifies Several New Loci for Parkinson's Disease
International Parkinson's Disease Genomics Consortium (IPDGC),Wellcome Trust Case Control Consortium 2 (WTCCC2)
PLOS Genetics , 2011, DOI: 10.1371/journal.pgen.1002142
Abstract: A previous genome-wide association (GWA) meta-analysis of 12,386 PD cases and 21,026 controls conducted by the International Parkinson's Disease Genomics Consortium (IPDGC) discovered or confirmed 11 Parkinson's disease (PD) loci. This first analysis of the two-stage IPDGC study focused on the set of loci that passed genome-wide significance in the first stage GWA scan. However, the second stage genotyping array, the ImmunoChip, included a larger set of 1,920 SNPs selected on the basis of the GWA analysis. Here, we analyzed this set of 1,920 SNPs, and we identified five additional PD risk loci (combined p<5×10?10, PARK16/1q32, STX1B/16p11, FGF20/8p22, STBD1/4q21, and GPNMB/7p15). Two of these five loci have been suggested by previous association studies (PARK16/1q32, FGF20/8p22), and this study provides further support for these findings. Using a dataset of post-mortem brain samples assayed for gene expression (n = 399) and methylation (n = 292), we identified methylation and expression changes associated with PD risk variants in PARK16/1q32, GPNMB/7p15, and STX1B/16p11 loci, hence suggesting potential molecular mechanisms and candidate genes at these risk loci.
Comparison of Methods to Account for Relatedness in Genome-Wide Association Studies with Family-Based Data
Jakris Eu-ahsunthornwattana,E. Nancy Miller,Michaela Fakiola,Wellcome Trust Case Control Consortium 2,Selma M. B. Jeronimo,Jenefer M. Blackwell,Heather J. Cordell
PLOS Genetics , 2014, DOI: doi/10.1371/journal.pgen.1004445
Abstract: Approaches based on linear mixed models (LMMs) have recently gained popularity for modelling population substructure and relatedness in genome-wide association studies. In the last few years, a bewildering variety of different LMM methods/software packages have been developed, but it is not always clear how (or indeed whether) any newly-proposed method differs from previously-proposed implementations. Here we compare the performance of several LMM approaches (and software implementations, including EMMAX, GenABEL, FaST-LMM, Mendel, GEMMA and MMM) via their application to a genome-wide association study of visceral leishmaniasis in 348 Brazilian families comprising 3626 individuals (1972 genotyped). The implementations differ in precise details of methodology implemented and through various user-chosen options such as the method and number of SNPs used to estimate the kinship (relatedness) matrix. We investigate sensitivity to these choices and the success (or otherwise) of the approaches in controlling the overall genome-wide error-rate for both real and simulated phenotypes. We compare the LMM results to those obtained using traditional family-based association tests (based on transmission of alleles within pedigrees) and to alternative approaches implemented in the software packages MQLS, ROADTRIPS and MASTOR. We find strong concordance between the results from different LMM approaches, and all are successful in controlling the genome-wide error rate (except for some approaches when applied naively to longitudinal data with many repeated measures). We also find high correlation between LMMs and alternative approaches (apart from transmission-based approaches when applied to SNPs with small or non-existent effects). We conclude that LMM approaches perform well in comparison to competing approaches. Given their strong concordance, in most applications, the choice of precise LMM implementation cannot be based on power/type I error considerations but must instead be based on considerations such as speed and ease-of-use.
A “Candidate-Interactome” Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis
Rosella Mechelli, Renato Umeton, Claudia Policano, Viviana Annibali, Giulia Coarelli, Vito A. G. Ricigliano, Danila Vittori, Arianna Fornasiero, Maria Chiara Buscarinu, International Multiple Sclerosis Genetics Consortium , Wellcome Trust Case Control Consortium,2 , Silvia Romano, Marco Salvetti, Giovanni Ristori
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0063300
Abstract: Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a “candidate interactome” (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms.
Serum Iron Levels and the Risk of Parkinson Disease: A Mendelian Randomization Study
Irene Pichler equal contributor ,Fabiola Del Greco M. equal contributor,Martin G?gele,Christina M. Lill,Lars Bertram,Chuong B. Do,Nicholas Eriksson,Tatiana Foroud,Richard H. Myers,PD GWAS Consortium,Michael Nalls,Margaux F. Keller,International Parkinson's Disease Genomics Consortium,Wellcome Trust Case Control Consortium 2,Beben Benyamin,John B. Whitfield,Genetics of Iron Status Consortium,Peter P. Pramstaller,Andrew A. Hicks,John R. Thompson,Cosetta Minelli
PLOS Medicine , 2013, DOI: 10.1371/journal.pmed.1001462
Abstract: Background Although levels of iron are known to be increased in the brains of patients with Parkinson disease (PD), epidemiological evidence on a possible effect of iron blood levels on PD risk is inconclusive, with effects reported in opposite directions. Epidemiological studies suffer from problems of confounding and reverse causation, and mendelian randomization (MR) represents an alternative approach to provide unconfounded estimates of the effects of biomarkers on disease. We performed a MR study where genes known to modify iron levels were used as instruments to estimate the effect of iron on PD risk, based on estimates of the genetic effects on both iron and PD obtained from the largest sample meta-analyzed to date. Methods and Findings We used as instrumental variables three genetic variants influencing iron levels, HFE rs1800562, HFE rs1799945, and TMPRSS6 rs855791. Estimates of their effect on serum iron were based on a recent genome-wide meta-analysis of 21,567 individuals, while estimates of their effect on PD risk were obtained through meta-analysis of genome-wide and candidate gene studies with 20,809 PD cases and 88,892 controls. Separate MR estimates of the effect of iron on PD were obtained for each variant and pooled by meta-analysis. We investigated heterogeneity across the three estimates as an indication of possible pleiotropy and found no evidence of it. The combined MR estimate showed a statistically significant protective effect of iron, with a relative risk reduction for PD of 3% (95% CI 1%–6%; p = 0.001) per 10 μg/dl increase in serum iron. Conclusions Our study suggests that increased iron levels are causally associated with a decreased risk of developing PD. Further studies are needed to understand the pathophysiological mechanism of action of serum iron on PD risk before recommendations can be made. Please see later in the article for the Editors' Summary
Association of Genetic Markers with CSF Oligoclonal Bands in Multiple Sclerosis Patients
Maurizio A. Leone, Nadia Barizzone, Federica Esposito, Ausiliatrice Lucenti, Hanne F. Harbo, An Goris, Ingrid Kockum, Annette Bang Oturai, Elisabeth Gulowsen Celius, Inger L. Mero, Bénédicte Dubois, Tomas Olsson, Helle Bach S?ndergaard, Daniele Cusi, Sara Lupoli, Bettina Kulle Andreassen, the International Multiple Sclerosis Genetics Consortium , the Wellcome Trust Case Control Consortium 2 , Kjell-Morten Myhr, Franca R. Guerini, the PROGEMUS Group , the PROGRESSO Group , Giancarlo Comi, Filippo Martinelli-Boneschi, Sandra D'Alfonso
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0064408
Abstract: Objective to explore the association between genetic markers and Oligoclonal Bands (OCB) in the Cerebro Spinal Fluid (CSF) of Italian Multiple Sclerosis patients. Methods We genotyped 1115 Italian patients for HLA-DRB1*15 and HLA-A*02. In a subset of 925 patients we tested association with 52 non-HLA SNPs associated with MS susceptibility and we calculated a weighted Genetic Risk Score. Finally, we performed a Genome Wide Association Study (GWAS) with OCB status on a subset of 562 patients. The best associated SNPs of the Italian GWAS were replicated in silico in Scandinavian and Belgian populations, and meta-analyzed. Results HLA-DRB1*15 is associated with OCB+: p = 0.03, Odds Ratio (OR) = 1.6, 95% Confidence Limits (CL) = 1.1–2.4. None of the 52 non-HLA MS susceptibility loci was associated with OCB, except one SNP (rs2546890) near IL12B gene (OR: 1.45; 1.09–1.92). The weighted Genetic Risk Score mean was significantly (p = 0.0008) higher in OCB+ (7.668) than in OCB? (7.412) patients. After meta-analysis on the three datasets (Italian, Scandinavian and Belgian) for the best associated signals resulted from the Italian GWAS, the strongest signal was a SNP (rs9320598) on chromosome 6q (p = 9.4×10?7) outside the HLA region (65 Mb). Discussion genetic factors predispose to the development of OCB.
A Bayesian Method for Detecting and Characterizing Allelic Heterogeneity and Boosting Signals in Genome-Wide Association Studies
Zhan Su,Niall Cardin,the Wellcome Trust Case Control Consortium,Peter Donnelly,Jonathan Marchini
Quantitative Biology , 2010, DOI: 10.1214/09-STS311
Abstract: The standard paradigm for the analysis of genome-wide association studies involves carrying out association tests at both typed and imputed SNPs. These methods will not be optimal for detecting the signal of association at SNPs that are not currently known or in regions where allelic heterogeneity occurs. We propose a novel association test, complementary to the SNP-based approaches, that attempts to extract further signals of association by explicitly modeling and estimating both unknown SNPs and allelic heterogeneity at a locus. At each site we estimate the genealogy of the case-control sample by taking advantage of the HapMap haplotypes across the genome. Allelic heterogeneity is modeled by allowing more than one mutation on the branches of the genealogy. Our use of Bayesian methods allows us to assess directly the evidence for a causative SNP not well correlated with known SNPs and for allelic heterogeneity at each locus. Using simulated data and real data from the WTCCC project, we show that our method (i) produces a significant boost in signal and accurately identifies the form of the allelic heterogeneity in regions where it is known to exist, (ii) can suggest new signals that are not found by testing typed or imputed SNPs and (iii) can provide more accurate estimates of effect sizes in regions of association.
Genetic Loci for Retinal Arteriolar Microcirculation
Xueling Sim, Richard A. Jensen, M. Kamran Ikram, Mary Frances Cotch, Xiaohui Li, Stuart MacGregor, Jing Xie, Albert Vernon Smith, Eric Boerwinkle, Paul Mitchell, Ronald Klein, Barbara E. K. Klein, Nicole L. Glazer, Thomas Lumley, Barbara McKnight, Bruce M. Psaty, Paulus T. V. M. de Jong, Albert Hofman, Fernando Rivadeneira, Andre G. Uitterlinden, Cornelia M. van Duijn, Thor Aspelund, Gudny Eiriksdottir, Tamara B. Harris, Fridbert Jonasson, Lenore J. Launer, The Wellcome Trust Case Control Consortium 2 , John Attia, Paul N. Baird, Stephen Harrap, Elizabeth G. Holliday, Michael Inouye, Elena Rochtchina, Rodney J. Scott, Ananth Viswanathan, Global BPGen Consortium , Guo Li, Nicholas L. Smith, Kerri L. Wiggins, Jane Z. Kuo, Kent D. Taylor, Alex W. Hewitt, Nicholas G. Martin, Grant W. Montgomery, Cong Sun, Terri L. Young, David A. Mackey, Natalie R. van Zuydam, Alex S. F. Doney, Colin N. A. Palmer, Andrew D. Morris, Jerome I. Rotter, E. Shyong Tai, Vilmundur Gudnason, Johannes R. Vingerling, David S. Siscovick, Jie Jin Wang, Tien Y. Wong
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0065804
Abstract: Narrow arterioles in the retina have been shown to predict hypertension as well as other vascular diseases, likely through an increase in the peripheral resistance of the microcirculatory flow. In this study, we performed a genome-wide association study in 18,722 unrelated individuals of European ancestry from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium and the Blue Mountain Eye Study, to identify genetic determinants associated with variations in retinal arteriolar caliber. Retinal vascular calibers were measured on digitized retinal photographs using a standardized protocol. One variant (rs2194025 on chromosome 5q14 near the myocyte enhancer factor 2C MEF2C gene) was associated with retinal arteriolar caliber in the meta-analysis of the discovery cohorts at genome-wide significance of P-value <5×10?8. This variant was replicated in an additional 3,939 individuals of European ancestry from the Australian Twins Study and Multi-Ethnic Study of Atherosclerosis (rs2194025, P-value = 2.11×10?12 in combined meta-analysis of discovery and replication cohorts). In independent studies of modest sample sizes, no significant association was found between this variant and clinical outcomes including coronary artery disease, stroke, myocardial infarction or hypertension. In conclusion, we found one novel loci which underlie genetic variation in microvasculature which may be relevant to vascular disease. The relevance of these findings to clinical outcomes remains to be determined.
Common Genetic Determinants of Intraocular Pressure and Primary Open-Angle Glaucoma
Leonieke M. E. van Koolwijk equal contributor,Wishal D. Ramdas equal contributor,M. Kamran Ikram,Nomdo M. Jansonius,Francesca Pasutto,Pirro G. Hysi,Stuart Macgregor,Sarah F. Janssen,Alex W. Hewitt,Ananth C. Viswanathan,Jacoline B. ten Brink,S. Mohsen Hosseini,Najaf Amin,Dominiek D. G. Despriet,Jacqueline J. M. Willemse-Assink,Rogier Kramer,Fernando Rivadeneira,Maksim Struchalin,Yurii S. Aulchenko,Nicole Weisschuh,Matthias Zenkel,Christian Y. Mardin,Eugen Gramer,Ulrich Welge-Lüssen,Grant W. Montgomery,Francis Carbonaro,Terri L. Young,The DCCT/EDIC Research Group,Céline Bellenguez,Peter McGuffin,Paul J. Foster,Fotis Topouzis,Paul Mitchell,Jie Jin Wang,Tien Y. Wong,Monika A. Czudowska,Albert Hofman,Andre G. Uitterlinden,Roger C. W. Wolfs,Paulus T. V. M. de Jong,Ben A. Oostra,Andrew D. Paterson,Wellcome Trust Case Control Consortium 2,David A. Mackey,Arthur A. B. Bergen,André Reis,Christopher J. Hammond,Johannes R. Vingerling,Hans G. Lemij,Caroline C. W. Klaver,Cornelia M. van Duijn
PLOS Genetics , 2012, DOI: 10.1371/journal.pgen.1002611
Abstract: Intraocular pressure (IOP) is a highly heritable risk factor for primary open-angle glaucoma and is the only target for current glaucoma therapy. The genetic factors which determine IOP are largely unknown. We performed a genome-wide association study for IOP in 11,972 participants from 4 independent population-based studies in The Netherlands. We replicated our findings in 7,482 participants from 4 additional cohorts from the UK, Australia, Canada, and the Wellcome Trust Case-Control Consortium 2/Blue Mountains Eye Study. IOP was significantly associated with rs11656696, located in GAS7 at 17p13.1 (p = 1.4×10?8), and with rs7555523, located in TMCO1 at 1q24.1 (p = 1.6×10?8). In a meta-analysis of 4 case-control studies (total N = 1,432 glaucoma cases), both variants also showed evidence for association with glaucoma (p = 2.4×10?2 for rs11656696 and p = 9.1×10?4 for rs7555523). GAS7 and TMCO1 are highly expressed in the ciliary body and trabecular meshwork as well as in the lamina cribrosa, optic nerve, and retina. Both genes functionally interact with known glaucoma disease genes. These data suggest that we have identified two clinically relevant genes involved in IOP regulation.
Comprehensive Research Synopsis and Systematic Meta-Analyses in Parkinson's Disease Genetics: The PDGene Database
Christina M. Lill,Johannes T. Roehr,Matthew B. McQueen,Fotini K. Kavvoura,Sachin Bagade,Brit-Maren M. Schjeide,Leif M. Schjeide,Esther Meissner,Ute Zauft,Nicole C. Allen,Tian Liu,Marcel Schilling,Kari J. Anderson,Gary Beecham,Daniela Berg,Joanna M. Biernacka,Alexis Brice,Anita L. DeStefano,Chuong B. Do,Nicholas Eriksson,Stewart A. Factor,Matthew J. Farrer,Tatiana Foroud,Thomas Gasser,Taye Hamza,John A. Hardy,Peter Heutink,Erin M. Hill-Burns,Christine Klein,Jeanne C. Latourelle,Demetrius M. Maraganore,Eden R. Martin,Maria Martinez,Richard H. Myers,Michael A. Nalls,Nathan Pankratz,Haydeh Payami,Wataru Satake,William K. Scott,Manu Sharma,Andrew B. Singleton,Kari Stefansson,Tatsushi Toda,Joyce Y. Tung,Jeffery Vance,Nick W. Wood,Cyrus P. Zabetian,23andMe The Genetic Epidemiology of Parkinson's Disease (GEO-PD) Consortium,The International Parkinson's Disease Genomics Consortium (IPDGC) ?,The Parkinson's Disease GWAS Consortium,The Wellcome Trust Case Control Consortium 2 (WTCCC2) ?,Peter Young,Rudolph E. Tanzi,Muin J. Khoury,Frauke Zipp,Hans Lehrach,John P. A. Ioannidis,Lars Bertram
PLOS Genetics , 2012, DOI: 10.1371/journal.pgen.1002548
Abstract: More than 800 published genetic association studies have implicated dozens of potential risk loci in Parkinson's disease (PD). To facilitate the interpretation of these findings, we have created a dedicated online resource, PDGene, that comprehensively collects and meta-analyzes all published studies in the field. A systematic literature screen of ~27,000 articles yielded 828 eligible articles from which relevant data were extracted. In addition, individual-level data from three publicly available genome-wide association studies (GWAS) were obtained and subjected to genotype imputation and analysis. Overall, we performed meta-analyses on more than seven million polymorphisms originating either from GWAS datasets and/or from smaller scale PD association studies. Meta-analyses on 147 SNPs were supplemented by unpublished GWAS data from up to 16,452 PD cases and 48,810 controls. Eleven loci showed genome-wide significant (P<5×10?8) association with disease risk: BST1, CCDC62/HIP1R, DGKQ/GAK, GBA, LRRK2, MAPT, MCCC1/LAMP3, PARK16, SNCA, STK39, and SYT11/RAB25. In addition, we identified novel evidence for genome-wide significant association with a polymorphism in ITGA8 (rs7077361, OR 0.88, P = 1.3×10?8). All meta-analysis results are freely available on a dedicated online database (www.pdgene.org), which is cross-linked with a customized track on the UCSC Genome Browser. Our study provides an exhaustive and up-to-date summary of the status of PD genetics research that can be readily scaled to include the results of future large-scale genetics projects, including next-generation sequencing studies.
Genome-Wide Association and Functional Follow-Up Reveals New Loci for Kidney Function
Cristian Pattaro equal contributor,Anna K?ttgen equal contributor,Alexander Teumer equal contributor,Maija Garnaas equal contributor,Carsten A. B?ger equal contributor,Christian Fuchsberger,Matthias Olden,Ming-Huei Chen,Adrienne Tin,Daniel Taliun,Man Li,Xiaoyi Gao,Mathias Gorski,Qiong Yang,Claudia Hundertmark,Meredith C. Foster,Conall M. O'Seaghdha,Nicole Glazer,Aaron Isaacs,Ching-Ti Liu,Albert V. Smith,Jeffrey R. O'Connell,Maksim Struchalin,Toshiko Tanaka,Guo Li,Andrew D. Johnson,Hinco J. Gierman,Mary Feitosa,Shih-Jen Hwang,Elizabeth J. Atkinson,Kurt Lohman,Marilyn C. Cornelis,?sa Johansson,Anke T?njes,Abbas Dehghan,Vincent Chouraki,Elizabeth G. Holliday,Rossella Sorice,Zoltan Kutalik,Terho Lehtim?ki,T?nu Esko,Harshal Deshmukh,Sheila Ulivi,Audrey Y. Chu,Federico Murgia,Stella Trompet,Medea Imboden,Barbara Kollerits,Giorgio Pistis,CARDIoGRAM Consortium,ICBP Consortium,CARe Consortium,Wellcome Trust Case Control Consortium 2 (WTCCC2),Tamara B. Harris,Lenore J. Launer,Thor Aspelund,Gudny Eiriksdottir,Braxton D. Mitchell,Eric Boerwinkle,Helena Schmidt,Margherita Cavalieri,Madhumathi Rao,Frank B. Hu,Ayse Demirkan,Ben A. Oostra,Mariza de Andrade,Stephen T. Turner,Jingzhong Ding,Jeanette S. Andrews,Barry I. Freedman,Wolfgang Koenig,Thomas Illig,Angela D?ring,H.-Erich Wichmann,Ivana Kolcic,Tatijana Zemunik,Mladen Boban,Cosetta Minelli,Heather E. Wheeler,Wilmar Igl,Ghazal Zaboli,Sarah H. Wild,Alan F. Wright,Harry Campbell,David Ellinghaus,Ute N?thlings,Gunnar Jacobs,Reiner Biffar
PLOS Genetics , 2012, DOI: 10.1371/journal.pgen.1002584
Abstract: Chronic kidney disease (CKD) is an important public health problem with a genetic component. We performed genome-wide association studies in up to 130,600 European ancestry participants overall, and stratified for key CKD risk factors. We uncovered 6 new loci in association with estimated glomerular filtration rate (eGFR), the primary clinical measure of CKD, in or near MPPED2, DDX1, SLC47A1, CDK12, CASP9, and INO80. Morpholino knockdown of mpped2 and casp9 in zebrafish embryos revealed podocyte and tubular abnormalities with altered dextran clearance, suggesting a role for these genes in renal function. By providing new insights into genes that regulate renal function, these results could further our understanding of the pathogenesis of CKD.
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