Large-scale meta-analysis of genome-wide association data identifies six new risk loci for Parkinson's disease

Mike A Nalls, Nathan Pankratz, Christina M Lill, Chuong B Do, Dena G Hernandez, Mohamad Saad, Anita L DeStefano, Eleanna Kara, Jose Bras, Manu Sharma, Claudia Schulte, Margaux F Keller, Sampath Arepalli, Christopher Letson, Connor Edsall, Hreinn Stefansson, Xinmin Liu, Hannah Pliner, Joseph H Lee, Rong Cheng, International Parkinson's Disease Genomics Consortium (IPDGC), Parkinson's Study Group (PSG) Parkinson's Research: The Organized GENetics Initiative (PROGENI), 23andMe, GenePD, NeuroGenetics Research Consortium (NGRC), Hussman Institute of Human Genomics (HIHG), Ashkenazi Jewish Dataset Investigator, Cohorts for Health and Aging Research in Genetic Epidemiology (CHARGE), North American Brain Expression Consortium (NABEC), United Kingdom Brain Expression Consortium (UKBEC), Greek Parkinson's Disease Consortium, Alzheimer Genetic Analysis Group, M Arfan Ikram, John P A Ioannidis, Georgios M Hadjigeorgiou, Joshua C Bis, Maria Martinez, Joel S Perlmutter, Alison Goate, Karen Marder, Brian Fiske, Margaret Sutherland, Georgia Xiromerisiou, Richard H Myers, Lorraine N Clark, Kari Stefansson, John A Hardy, Peter Heutink, Honglei Chen, Nicholas W Wood, Henry Houlden, Haydeh Payami, Alexis Brice, William K Scott, Thomas Gasser, Lars Bertram, Nicholas Eriksson, Tatiana Foroud, Andrew B Singleton

Abstract

We conducted a meta-analysis of Parkinson's disease genome-wide association studies using a common set of 7,893,274 variants across 13,708 cases and 95,282 controls. Twenty-six loci were identified as having genome-wide significant association; these and 6 additional previously reported loci were then tested in an independent set of 5,353 cases and 5,551 controls. Of the 32 tested SNPs, 24 replicated, including 6 newly identified loci. Conditional analyses within loci showed that four loci, including GBA, GAK-DGKQ, SNCA and the HLA region, contain a secondary independent risk variant. In total, we identified and replicated 28 independent risk variants for Parkinson's disease across 24 loci. Although the effect of each individual locus was small, risk profile analysis showed substantial cumulative risk in a comparison of the highest and lowest quintiles of genetic risk (odds ratio (OR) = 3.31, 95% confidence interval (CI) = 2.55-4.30; P = 2 × 10(-16)). We also show six risk loci associated with proximal gene expression or DNA methylation.

Conflict of interest statement

COMPETING FINANCIAL INTERESTS

The authors declare no competing financial interests.

Figures

Figure 1
Figure 1
Manhattan plot of discovery phase meta-analyses.
Figure 2
Figure 2
Forest plots describing cohort level and summary effects of risk profile analyses.

References

    1. Lill CM, et al. Comprehensive research synopsis and systematic meta-analyses in Parkinson’s disease genetics: The PDGene database. PLoS Genet. 2012;8:e1002548.
    1. Do CB, et al. Web-based genome-wide association study identifies two novel loci and a substantial genetic component for Parkinson’s disease. PLoS Genet. 2011;7:e1002141.
    1. International Parkinson Disease Genomics Consortium et al. Imputation of sequence variants for identification of genetic risks for Parkinson’s disease: a meta-analysis of genome-wide association studies. Lancet. 2011;377:641–9.
    1. International Parkinson’s Disease Genomics Consortium (IPDGC) & Wellcome Trust Case Control Consortium 2 (WTCCC2) A two-stage meta-analysis identifies several new loci for Parkinson’s disease. PLoS Genet. 2011;7:e1002142.
    1. Edwards TL, et al. Genome-wide association study confirms SNPs in SNCA and the MAPT region as common risk factors for Parkinson disease. Ann Hum Genet. 2010;74:97–109.
    1. Pankratz N, et al. Genomewide association study for susceptibility genes contributing to familial Parkinson disease. Hum Genet. 2009;124:593–605.
    1. Pankratz N, et al. Meta-analysis of Parkinson’s Disease: Identification of a novel locus, RIT2. Ann Neurol. 2012;71:370–384.
    1. Simón-Sánchez J, et al. Genome-wide association study confirms extant PD risk loci among the Dutch. Eur J Hum Genet EJHG. 2011;19:655–661.
    1. Hamza TH, et al. Common genetic variation in the HLA region is associated with late-onset sporadic Parkinson’s disease. Nat Genet. 2010;42:781–785.
    1. Liu X, et al. Genome-wide association study identifies candidate genes for Parkinson’s disease in an Ashkenazi Jewish population. BMC Med Genet. 2011;12:104.
    1. Hernandez DG, et al. Genome wide assessment of young onset Parkinson’s disease from Finland. PloS One. 2012;7:e41859.
    1. Pihlstrøm L, et al. Supportive evidence for 11 loci from genome-wide association studies in Parkinson’s disease. Neurobiol Aging. 2013;34:1708. e7–13.
    1. Sharma M, et al. Large-scale replication and heterogeneity in Parkinson disease genetic loci. Neurology. 2012;79:659–667.
    1. Saad M, et al. Genome-wide association study confirms BST1 and suggests a locus on 12q24 as the risk loci for Parkinson’s disease in the European population. Hum Mol Genet. 2011;20:615–627.
    1. Satake W, et al. Genome-wide association study identifies common variants at four loci as genetic risk factors for Parkinson’s disease. Nat Genet. 2009;41:1303–1307.
    1. Elbaz A, et al. Independent and joint effects of the MAPT and SNCA genes in Parkinson disease. Ann Neurol. 2011;69:778–792.
    1. Psaty BM, et al. Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium: Design of prospective meta-analyses of genome-wide association studies from 5 cohorts. Circ Cardiovasc Genet. 2009;2:73–80.
    1. Macleod DA, et al. RAB7L1 Interacts with LRRK2 to Modify Intraneuronal Protein Sorting and Parkinson’s Disease Risk. Neuron. 2013;77:425–439.
    1. Keller MF, et al. Using genome-wide complex trait analysis to quantify ‘missing heritability’ in Parkinson’s disease. Hum Mol Genet. 2012;21:4996–5009.
    1. Wei Z, et al. Large Sample Size, Wide Variant Spectrum, and Advanced Machine-Learning Technique Boost Risk Prediction for Inflammatory Bowel Disease. Am J Hum Genet. 2013;92:1008–1012.
    1. Willems SM, Mihaescu R, Sijbrands EJG, van Duijn CM, Janssens ACJW. A Methodological Perspective on Genetic Risk Prediction Studies in Type 2 Diabetes: Recommendations for Future Research. Curr Diab Rep. 2011;11:511–518.
    1. The Cohorts for Heart and Aging Research in Genetic Epidemiology (CHARGE) Consortium et al. Whole-genome sequence-based analysis of high-density lipoprotein cholesterol. Nat Genet. 2013 doi: 10.1038/ng.2671.
    1. 1000 Genomes Project Consortium et al. A map of human genome variation from population-scale sequencing. Nature. 2010;467:1061–1073.
    1. De Bakker PIW, et al. Practical aspects of imputation-driven meta-analysis of genome-wide association studies. Hum Mol Genet. 2008;17:R122–128.
    1. Van der Walt JM, et al. Fibroblast growth factor 20 polymorphisms and haplotypes strongly influence risk of Parkinson disease. Am J Hum Genet. 2004;74:1121–1127.
    1. Gibbs JR, et al. Abundant Quantitative Trait Loci Exist for DNA Methylation and Gene Expression in Human Brain. PLoS Genet. 2010;6:e1000952.
    1. Hofman A, et al. The Rotterdam Study: 2012 objectives and design update. Eur J Epidemiol. 2011;26:657–686.
    1. Ton TG, et al. Post hoc Parkinson’s disease: identifying an uncommon disease in the Cardiovascular Health Study. Neuroepidemiology. 2010;35:241–249.
    1. Ikram MA, et al. Genomewide association studies of stroke. N Engl J Med. 2009;360:1718–1728.
    1. Eriksson N, et al. Genetic variants associated with breast size also influence breast cancer risk. BMC Med Genet. 2012;13:53.
    1. Howie B, Fuchsberger C, Stephens M, Marchini J, Abecasis GR. Fast and accurate genotype imputation in genome-wide association studies through pre-phasing. Nat Genet. 2012;44:955–959.
    1. Willer CJ, Li Y, Abecasis GR. METAL: fast and efficient meta- analysis of genomewide association scans. Bioinforma Oxf Engl. 2010;26:2190– 2191.
    1. Han B, Eskin E. Random-effects model aimed at discovering associations in meta-analysis of genome-wide association studies. Am J Hum Genet. 2011;88:586–598.
    1. Grove ML, et al. Best Practices and Joint Calling of the HumanExome BeadChip: The CHARGE Consortium. PloS One. 2013;8:e68095.
    1. Ripatti S, et al. A multilocus genetic risk score for coronary heart disease: case-control and prospective cohort analyses. Lancet. 2010;376:1393–1400.
    1. Hernandez DG, et al. Distinct DNA methylation changes highly correlated with chronological age in the human brain. Hum Mol Genet. 2011;20:1164–1172.

Source: PubMed

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